From aed160d7f0eaf5865e2bd9bf6c4b1c9d7b13d911 Mon Sep 17 00:00:00 2001 From: Ranke Johannes Date: Wed, 31 Jan 2024 13:16:17 +0100 Subject: Reorganise data generation - Use inst/data_generation for R code generating data as in some of my other packages - data/*.RData files were checked using https://github.com/jranke/dotfiles/blob/main/bin/rda_diff contents were not changed - Remove ChangeLog, the history is in the git logs - Update docs and some links contained therein - use \doi{} markup - Move logs to log directory --- .Rbuildignore | 6 +- ChangeLog | 1561 --------------------- DESCRIPTION | 13 +- GNUmakefile | 75 +- NAMESPACE | 2 - R/EFSA_GW_interception_2014.R | 30 +- R/EFSA_washoff_2017.R | 30 +- R/PEC_sw_exposit_runoff.R | 52 +- R/drift_data_JKI.R | 49 +- R/soil_scenario_data_EFSA_2015.R | 24 +- R/soil_scenario_data_EFSA_2017.R | 6 +- build.log | 15 - data/EFSA_GW_interception_2014.RData | Bin 352 -> 343 bytes data/EFSA_washoff_2017.RData | Bin 356 -> 356 bytes data/FOCUS_GW_scenarios_2012.RData | Bin 0 -> 957 bytes data/perc_runoff.RData | Bin 0 -> 623 bytes data/soil_scenario_data_EFSA_2015.RData | Bin 522 -> 530 bytes data/soil_scenario_data_EFSA_2017.RData | Bin 582 -> 590 bytes docs/404.html | 117 +- docs/authors.html | 136 +- docs/index.html | 82 +- docs/pkgdown.css | 83 +- docs/pkgdown.js | 4 +- docs/pkgdown.yml | 6 +- docs/reference/EFSA_GW_interception_2014.html | 171 +-- docs/reference/EFSA_washoff_2017.html | 171 +-- docs/reference/FOCUS_GW_scenarios_2012.html | 248 ++-- docs/reference/FOCUS_Step_12_scenarios.html | 327 +---- docs/reference/FOMC_actual_twa.html | 186 +-- docs/reference/GUS.html | 287 ++-- docs/reference/PEC_FOMC_accu_rel.html | 149 +- docs/reference/PEC_soil.html | 477 +++---- docs/reference/PEC_soil_mets.html | 159 +-- docs/reference/PEC_sw_drainage_UK.html | 226 ++- docs/reference/PEC_sw_drift.html | 271 ++-- docs/reference/PEC_sw_exposit_drainage.html | 289 ++-- docs/reference/PEC_sw_exposit_runoff.html | 341 ++--- docs/reference/PEC_sw_focus.html | 528 +++---- docs/reference/PEC_sw_sed.html | 224 ++- docs/reference/Rplot002.png | Bin 0 -> 16733 bytes docs/reference/Rplot003.png | Bin 0 -> 16733 bytes docs/reference/Rplot004.png | Bin 0 -> 12802 bytes docs/reference/Rplot005.png | Bin 0 -> 7538 bytes docs/reference/SFO_actual_twa.html | 170 +-- docs/reference/SSLRC_mobility_classification.html | 185 +-- docs/reference/TOXSWA_cwa.html | 412 +++--- docs/reference/TSCF-1.png | Bin 24506 -> 39919 bytes docs/reference/TSCF.html | 154 +- docs/reference/chent_focus_sw.html | 233 ++- docs/reference/drift_data_JKI.html | 566 +++----- docs/reference/endpoint.html | 295 ++-- docs/reference/geomean.html | 156 +- docs/reference/get_vertex.html | 135 +- docs/reference/index.html | 365 +---- docs/reference/max_twa.html | 213 +-- docs/reference/one_box-1.png | Bin 15801 -> 24719 bytes docs/reference/one_box-2.png | Bin 15228 -> 21981 bytes docs/reference/one_box-3.png | Bin 30063 -> 34076 bytes docs/reference/one_box.html | 236 ++-- docs/reference/perc_runoff_exposit.html | 170 +-- docs/reference/perc_runoff_reduction_exposit.html | 190 +-- docs/reference/pesticide.txt | 3 - docs/reference/pfm_degradation.html | 210 +-- docs/reference/plot.TOXSWA_cwa-1.png | Bin 21821 -> 34458 bytes docs/reference/plot.TOXSWA_cwa-2.png | Bin 21005 -> 33311 bytes docs/reference/plot.TOXSWA_cwa-3.png | Bin 22278 -> 35208 bytes docs/reference/plot.TOXSWA_cwa-4.png | Bin 22682 -> 35650 bytes docs/reference/plot.TOXSWA_cwa-5.png | Bin 16209 -> 23109 bytes docs/reference/plot.TOXSWA_cwa.html | 258 ++-- docs/reference/plot.one_box-1.png | Bin 16135 -> 24259 bytes docs/reference/plot.one_box-2.png | Bin 32593 -> 29965 bytes docs/reference/plot.one_box-3.png | Bin 37285 -> 41819 bytes docs/reference/plot.one_box.html | 242 ++-- docs/reference/read.TOXSWA_cwa.html | 243 ++-- docs/reference/reexports.html | 83 ++ docs/reference/sawtooth-1.png | Bin 16202 -> 24497 bytes docs/reference/sawtooth-2.png | Bin 42340 -> 41819 bytes docs/reference/sawtooth.html | 218 +-- docs/reference/soil_scenario_data_EFSA_2015.html | 179 +-- docs/reference/soil_scenario_data_EFSA_2017.html | 192 ++- docs/reference/twa.html | 183 +-- docs/sitemap.xml | 12 + inst/data_generation/EFSA_GW_interception.R | 29 + inst/data_generation/EFSA_washoff_2017.R | 29 + inst/data_generation/FOCUS_GW_scenarios_2012.R | 63 + inst/data_generation/PEC_sw_exposit.R | 34 + inst/data_generation/drift_data_JKI.R | 47 + inst/data_generation/drift_parameters_Rautmann.R | 5 + inst/data_generation/soil_scenario_data_EFSA.R | 40 + inst/extdata/FOCUS_GW_scenarios_2012.R | 59 - log/build.log | 7 + log/check.log | 80 ++ man/EFSA_GW_interception_2014.Rd | 32 +- man/EFSA_washoff_2017.Rd | 32 +- man/PEC_sw_exposit_drainage.Rd | 2 +- man/PEC_sw_exposit_runoff.Rd | 2 +- man/PEC_sw_focus.Rd | 10 +- man/drift_data_JKI.Rd | 49 +- man/perc_runoff_exposit.Rd | 7 +- man/perc_runoff_reduction_exposit.Rd | 2 +- man/soil_scenario_data_EFSA_2015.Rd | 25 +- man/soil_scenario_data_EFSA_2017.Rd | 7 +- test.log | 18 - 103 files changed, 3944 insertions(+), 8283 deletions(-) delete mode 100644 ChangeLog delete mode 100644 build.log create mode 100644 data/FOCUS_GW_scenarios_2012.RData create mode 100644 data/perc_runoff.RData create mode 100644 docs/reference/Rplot002.png create mode 100644 docs/reference/Rplot003.png create mode 100644 docs/reference/Rplot004.png create mode 100644 docs/reference/Rplot005.png delete mode 100644 docs/reference/pesticide.txt create mode 100644 docs/reference/reexports.html create mode 100644 inst/data_generation/EFSA_GW_interception.R create mode 100644 inst/data_generation/EFSA_washoff_2017.R create mode 100644 inst/data_generation/FOCUS_GW_scenarios_2012.R create mode 100644 inst/data_generation/PEC_sw_exposit.R create mode 100644 inst/data_generation/drift_data_JKI.R create mode 100644 inst/data_generation/drift_parameters_Rautmann.R create mode 100644 inst/data_generation/soil_scenario_data_EFSA.R delete mode 100644 inst/extdata/FOCUS_GW_scenarios_2012.R create mode 100644 log/build.log create mode 100644 log/check.log delete mode 100644 test.log diff --git a/.Rbuildignore b/.Rbuildignore index 4159cc9..99c6d74 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,12 +1,12 @@ ^pfm_.*.tar.gz ^pfm_.*.zip +^pfm.Rcheck$ ^GNUmakefile$ ^README.html$ -^build.log$ -^test.log$ +^log ^test.R$ +^pesticide.txt$ ^inst/extdata/Tabelle\ der\ Abdrifteckwerte.xls$ -^inst/extdata/FOCUS_Step_12_scenarios.txt$ ^_pkgdown.yml$ ^\.travis\.yml$ ^docs$ diff --git a/ChangeLog b/ChangeLog deleted file mode 100644 index 0ad0374..0000000 --- a/ChangeLog +++ /dev/null @@ -1,1561 +0,0 @@ -commit df4034c64aa3590c3911dca88b066332dc8e4df1 -Author: Johannes Ranke -Date: 2022-11-11 14:35:37 +0100 - - Simplify travis config - -commit f4e22fc28fa0b05b05c8a1277333777635802e86 -Author: Johannes Ranke -Date: 2022-11-11 13:46:24 +0100 - - Try to simplify drat configuration - -commit 6bc40dbd4e7c76179009a501ae168f0fa73f2be2 -Author: Johannes Ranke -Date: 2022-11-11 12:12:09 +0100 - - Disable bspm to make install from drat work - -commit 96b6f8954d4eb9ec5b8ee9209074d21fdd67f966 -Author: Johannes Ranke -Date: 2022-11-11 12:04:15 +0100 - - Fix last commit - -commit c9e9f1312e7b73c8596d2d01324fcb67c000f3e9 -Author: Johannes Ranke -Date: 2022-11-11 12:00:39 +0100 - - Install drat to use it... - -commit b0a7a94ac0a7070e8612e443b4aa485beb07b85d -Author: Johannes Ranke -Date: 2022-11-11 11:57:20 +0100 - - Another attempt to make drat work on travis - -commit 854cc695a1f64a9b37957fdcd81c1ce23a6a2d69 -Author: Johannes Ranke -Date: 2022-11-11 11:52:53 +0100 - - Try to make drat work - -commit c463f9fb197f70f97831b3648bc398be8ff9ae7d -Author: Johannes Ranke -Date: 2022-11-11 11:41:40 +0100 - - mkin was not pulled from the drat repo - -commit f3ba961b6be63d3995cccea2968d7b2fb907ca16 -Author: Johannes Ranke -Date: 2022-11-11 11:35:27 +0100 - - Use drat instead of install_github - -commit 510416bc07eb7b3197c20d687f6c51a032cfbfec -Author: Johannes Ranke -Date: 2022-11-11 11:12:59 +0100 - - Forgot to commit .travis.yml ... - -commit f21a53421dc481604c681c2be8438c8a8b5db23d -Author: Johannes Ranke -Date: 2022-11-11 10:58:46 +0100 - - mkin and chents from github for check on travis - -commit e63dbdf1fdae0abc7246f721357504798309033d -Author: Johannes Ranke -Date: 2022-11-11 10:52:07 +0100 - - Don't force suggested packages - -commit 60a217ecc9a035ab956bd4229da6ad4c654e7d6e -Author: Johannes Ranke -Date: 2022-11-11 10:37:13 +0100 - - Remove Remotes: field from DESCRIPTION - - It causes trouble with remotes::install_deps() on travis, see the - various previous build logs. - -commit 3ef243d18b7972eb8cb4a561ac07d93b46df13a5 -Author: Johannes Ranke -Date: 2022-11-11 10:06:39 +0100 - - Fix call to download.file for debugging - -commit 9f977cb5d9657d0066598cda38908282dadae0c4 -Author: Johannes Ranke -Date: 2022-11-11 10:02:57 +0100 - - Try to debug the failure in remotes::install_deps - -commit 6681356b8abab27f0735341ed6d3a44e1374e2e5 -Author: Johannes Ranke -Date: 2022-11-11 09:00:41 +0100 - - Typo, remove PELMO related suggestions - - PELMO related functions are not used in pfm, so apart from advertising, - these suggestions did not do anything. - -commit 3e82035d2753d031401f80833de8939740491bd0 -Author: Johannes Ranke -Date: 2022-11-10 17:17:03 +0100 - - Revert standalone option for remotes on travis - -commit 9f28f36b00c156ff9c78790302c6fc74e0195651 -Author: Johannes Ranke -Date: 2022-11-10 16:48:27 +0100 - - Yet another attempt on remotes on travis - -commit 4f315619d56a191a80d2223913ee976d96ae5f97 -Author: Johannes Ranke -Date: 2022-11-10 16:43:39 +0100 - - Another attempt to make remotes work on travis - -commit 8d03f6ae52e6c45e3da93e41b15eb5f853ab6d17 -Author: Johannes Ranke -Date: 2022-11-10 16:35:33 +0100 - - Try to make remotes work - -commit e46ee27b218dde8ebb948e8b3b28e9cd8250bc70 -Author: Johannes Ranke -Date: 2022-11-10 16:27:12 +0100 - - Skip BSPM, it's the default - -commit f41d1759b890613895879f36e69e9928dd517f0e -Author: Johannes Ranke -Date: 2022-11-10 15:49:36 +0100 - - Only install dependencies, as chents fails to install - -commit 7a54d9b65fc55e28411126b97c542fb4c180c0a7 -Author: Johannes Ranke -Date: 2022-11-10 15:43:43 +0100 - - Use Dirks run.sh on travis - -commit a0364c2561dda4c4b67e7e3b6830719b4ed60916 -Author: Johannes Ranke -Date: 2022-11-10 12:17:34 +0100 - - set_nd_nq is now in mkin, fix Steps12 bug - - If a scenario with a slash "/" was selected in PEC_sw_focus(), - the Step 2 file generated giving an error (path not found) in the - Steps12 calculator, because the scenario name is part of the "compound" - name in this implementation, in order to show it in the list that the - calculator presents. - -commit aa0c59c7a3ede267730fe85f9e27b1814f9e897a -Author: Johannes Ranke -Date: 2021-11-19 00:18:41 +0100 - - Update static docs - -commit f4e35b0bf9c4de0b5c6235f5cf9e284faf40569f -Author: Johannes Ranke -Date: 2021-11-19 00:17:33 +0100 - - Update docs and logs - -commit 6e3917d814500d5af43702b4d4be1e44cefc00d4 -Author: Johannes Ranke -Date: 2021-11-18 11:22:44 +0100 - - Update README after changing default branch to main - -commit e0029129aec8b92d58aea8552006002c5fe409f5 -Author: Johannes Ranke -Date: 2021-02-10 09:29:33 +0100 - - Treat Kfoc = 0 like Exposit in runoff calcs - -commit c97a4f5a9fe30ffc3321681a97eea167cfc427b5 -Author: Johannes Ranke -Date: 2020-07-23 12:22:25 +0200 - - PEC_sw_drift: Rautmann formula (1 app, Ackerbau) - - This makes it possible to calculate drift PECsw for other distances than - present in the JKI data or the Rautmann paper. - -commit 90fa42c86596c85168931148bf8d5fa014fa7794 -Author: Johannes Ranke -Date: 2020-07-23 10:51:39 +0200 - - Update docs, use R6 support of roxygen - -commit df70d80d9ef13b69e58de6f47b9041b6a021025e -Author: Johannes Ranke -Date: 2020-07-21 15:50:21 +0200 - - Clean test.log after testing - -commit 512cd50874b060d50a14d28df88018ac144cf6d3 -Author: Johannes Ranke -Date: 2020-07-07 12:36:56 +0200 - - Remove copyright headers, update TOXSWA_cwa test - - - The window column of the windows component of a TOXSWA_cwa object is not - a factor any more, but a character vector. - - testthat::expect_equal_to_reference is replaced by - testthat::expect_known_output, so we can have git diff show what has - changed - -commit 58c6214f459b28b899794f32a60836aef97ac01b -Author: Johannes Ranke -Date: 2020-07-07 11:27:44 +0200 - - Adapt pfm_degradation to current mkin - - use_of_ff = "max" is now the default - -commit e3bc264df69f892e9ad990be22d3ec1b22041daa -Author: Johannes Ranke -Date: 2020-06-17 13:37:59 +0200 - - TSCF estimation equations, update docs - - Briggs et al. (1982) and Dettenmaier et al. (2009) - -commit e505ecc4aba0f6719fd772faa2655dd824a6930d -Author: Johannes Ranke -Date: 2020-04-17 09:51:33 +0200 - - Skip testing on R-devel - - it currently fails with - - ✖ | 6 1 | Read and analyse TOXSWA cwa files [6.4 s] - ──────────────────────────────────────────────────────────────────────────────────────────────────── - test_TOXSWA.R:68: failure: Getting events and moving window analysis works - H_sw_R1_stream$windows has changed from known value recorded in 'H_sw_R1_stream_windows.rds'. - Component "window": Modes: character, numeric - Component "window": Attributes: < target is NULL, current is list > - Component "window": target is character, current is factor - -commit d81550d0cccae824cc748de48e7fd50ea8d8033a -Author: Johannes Ranke -Date: 2020-04-16 18:02:18 +0200 - - Make na.rm = FALSE the default for geomean() - - This makes more sense and is in line with mean() from base R. Adapt - tests and update docs. - -commit 4bc95b3e4aae22e4052e0a4c905a9227c909e2cd -Author: Johannes Ranke -Date: 2020-02-19 07:49:08 +0100 - - Check in last build log - -commit 00e177fdf6929058fd26c3086ae159462ae0a456 -Author: Johannes Ranke -Date: 2019-10-23 16:18:24 +0200 - - Fix static docs for set_nd_nq - -commit a23fdf1152744341bd73f22f9b86951987125e6d -Author: Johannes Ranke -Date: 2019-10-23 16:15:38 +0200 - - Updated ChangeLog and DESCRIPTION - -commit 020bce41dd821b5949f824eaa3a2998584a14585 -Author: Johannes Ranke -Date: 2019-10-15 11:27:59 +0200 - - Residue processing for depth profiles over time - -commit a2ca8be6f5593f0afd833ea73b62149055ee84f9 -Author: Johannes Ranke -Date: 2019-10-10 14:56:35 +0200 - - Do not mess with zero values at time zero - -commit a071d46f698397a6c8247e19eceb0fcd5f139056 -Author: Johannes Ranke -Date: 2019-10-10 12:25:42 +0200 - - Fix set_nd for metabolites, handle zero at time zero - -commit a5503d3e26408f7308a7bf4da617205b93d17422 -Author: Johannes Ranke -Date: 2019-10-10 09:21:46 +0200 - - Fix documentation for set_nd - -commit a5e458ecb33ae87e46b2237174a194f6252a97cf -Author: Johannes Ranke -Date: 2019-10-10 08:53:30 +0200 - - Finish documentation of set_nd and test it - -commit 63df3871a442de4bf47e4d9de1449e7f6ed65b2f -Author: Johannes Ranke -Date: 2019-10-09 19:17:07 +0200 - - Function to set non-detects in residue series - -commit 9f848a9518aabf162723271bafba244221ee83ed -Author: Johannes Ranke -Date: 2019-09-27 12:55:03 +0200 - - Built windows binary for drat - -commit 435e07a6f7fd2599d783fd306ee6d9e08acc0c6b -Author: Johannes Ranke -Date: 2019-09-27 10:00:15 +0200 - - Fix for UK drainage, some EFSA interception and washoff - - - PEC_sw_drainage_UK() gave results that were a little bit too high - for the substances with the highest Koc (>4000), as I used 0.01% instead - of 0.008% for them. This must have come from an old vesion of the UK - data requirements handbook, at least I do not have another explanation - - - Add EFSA interception (from 2014 DegT50 guidance) and tier 1 - crop wash-off factors (from 2017 PEC soil guidance) for some major - arable crops - - - Update docs - -commit 803fe13e505960fddccdbd4dcb524715f5eb068d -Author: Johannes Ranke -Date: 2019-09-18 18:18:40 +0200 - - Add url: tag to _pkgdown.yml, typo, update docs - -commit 8deaa29a659630a40e8b11df1fa3ebbbd9ca9e68 -Author: Johannes Ranke -Date: 2019-07-01 08:04:40 +0200 - - Typo - -commit 37a1513d73201dbacc71af3c33a2a2a4e798583c -Author: Johannes Ranke -Date: 2019-06-12 18:15:46 +0200 - - Update of static docs - -commit 5c9dd5c269acc4a6e6e32a7e599afb8f98d8ca36 -Author: Johannes Ranke -Date: 2019-06-12 18:14:46 +0200 - - Documentation fix - -commit 069824057caf8e57507852b858a7ecfd8e13e49a -Author: Johannes Ranke -Date: 2019-05-14 12:41:16 +0200 - - Version bump and doc update - -commit 41f3c867008c24b69a9bb0e5c7c084969d46bebd -Author: Johannes Ranke -Date: 2019-05-14 12:33:21 +0200 - - Add Exposit version 3.01a2 for runoff calculations - - At the request of Muris Korkaric (Agroscope). This is for 3 m buffer - only and provides consistency with earlier calculations - -commit 7b11b5d0da29447df026002af3ae5283510fdae9 -Author: Johannes Ranke -Date: 2019-04-29 13:03:00 +0200 - - Additional runoff data used by Agroscope - -commit 67cd9e04caaf18a40231262c9033fb24e8bb2a66 -Author: Johannes Ranke -Date: 2019-04-26 13:45:44 +0200 - - Formatting improvement for the online docs - -commit 45f540ef19fd2a2a80e3f3f72950933ed6396f0c -Author: Johannes Ranke -Date: 2019-04-26 13:33:27 +0200 - - Another take on completing the drift data - - The R script I used yesterday got lost because I used the .Rd file - that got overwritten by roxygen later. - -commit 451b332c8888bac8279340b086abb3b714ac3ae1 -Author: Johannes Ranke -Date: 2019-04-25 11:50:35 +0200 - - Add more drift data, especially 3 m field crop data - - To support Agroscope in doing lots of PEC calculations for Switzerland - -commit 3bb842b93107dd6207610de1fe5b44be66779e4d -Author: Johannes Ranke -Date: 2019-04-25 10:25:56 +0200 - - Remove leftover docs from earlier version - - Docs now live in docs/ - -commit 77f63efa62b6530fbe2accdacc866e34626fe4e3 -Author: Johannes Ranke -Date: 2019-02-21 16:01:38 +0100 - - Update docs - -commit 5086e2b87eaec90a02b4744d1321c6949d0b8982 -Author: Johannes Ranke -Date: 2019-02-21 15:59:22 +0100 - - Use codecov - -commit e21ec96873bf60072414369bc96e4c076a450235 -Author: Johannes Ranke -Date: 2019-02-19 17:13:55 +0100 - - Add grImport to Suggests: - - Because chent which in turn suggests grImport is loaded from github - which obviously does not pull grImport - -commit 4e99ae029638a3720eba97b28bd7de3129a727ce -Author: Johannes Ranke -Date: 2019-02-19 15:22:26 +0100 - - Update README.html - -commit 31eca93dadf58d47b3f3dd7aa485f89023090440 -Author: Johannes Ranke -Date: 2019-02-19 14:54:26 +0100 - - Add Remotes: field for travis - -commit 70b85fd2a11da1e20cd4978c717540021af34be8 -Author: Johannes Ranke -Date: 2019-02-19 14:35:15 +0100 - - Test on Travis - -commit 17755babc3a517f4c7cec1c04e3e1f32b7ffb5d9 -Author: Johannes Ranke -Date: 2019-02-19 14:27:03 +0100 - - Add another test for Exposit drainage - - to test overriding the mobility group derived from Koc - -commit 138638976f792684483520fe7837ded0a27938e4 -Author: Johannes Ranke -Date: 2019-02-19 12:35:19 +0100 - - Stop endless appending to pesticide.txt example - -commit 72c56f4246966c1bea627f601cf3cc457734f023 -Author: Johannes Ranke -Date: 2019-02-19 12:27:00 +0100 - - Add German drainage calculations using Exposit 3.02 - -commit e5a077e28153f6494c99d6945b8b1bd239464609 -Author: Johannes Ranke -Date: 2019-02-08 15:25:19 +0100 - - Make SSLRC and PEC drainage UK accept NA for Koc - -commit b935273d651301b271e0cb66bf36c2bbc1d15b32 -Author: Johannes Ranke -Date: 2019-01-31 01:40:24 +0100 - - Separate out PELMO utilities into rPELMO - -commit 1611dd58df6b2b2e6ad01af6573664da8ce8b6b9 -Author: Johannes Ranke -Date: 2019-01-30 23:58:55 +0100 - - Convenience function for metabolite PEC soil - -commit eab95c62479d732cbd531ad67ea458d2744af420 -Author: Johannes Ranke -Date: 2018-09-27 18:58:32 +0200 - - Create valid Step 1 files with fewer arguments - -commit 8452daa2015aa645dcc1eca3ec2bba5726603e4e -Author: Johannes Ranke -Date: 2018-09-22 09:54:59 +0200 - - Add test and update docs - -commit ff7e67a4d3415419dd3f712ef1af7467ebf65508 -Author: Johannes Ranke -Date: 2018-09-21 19:39:44 +0200 - - Support FOMC in PEC_soil - -commit 03c3035ca01c66b6a1352f7e509753fe2d057af2 -Author: Johannes Ranke -Date: 2018-07-11 03:41:43 +0200 - - Improve PELMO tests - -commit 22b36c824fe5e1561868a649216fe079c6fbfb85 -Author: Johannes Ranke -Date: 2018-07-10 18:06:29 +0200 - - Update static docs - -commit cb3695dd434b3a3273217fb22c5ffb86065ae96d -Author: Johannes Ranke -Date: 2018-07-10 17:57:33 +0200 - - EFSA PEC soil guidance from 2017 - - - Implement the new guidance as well as possible - - Maintenance work addressing CRAN checks - -commit c4c3ca282c6aadca82e392692ae4100fec1dd834 -Author: Johannes Ranke -Date: 2018-07-10 16:46:47 +0200 - - .out file from TOXSWA 5.5.3 for testing - -commit a736ecc357889107b6e93f14cdf0c1ea4587817f -Author: Johannes Ranke -Date: 2018-07-10 16:08:52 +0200 - - Adapt path to package on windows - -commit 8989a484b9b2d23463c95e0a3927e307ec0a5e64 -Author: Johannes Ranke -Date: 2018-07-04 10:59:47 +0200 - - Some documentation updates - - Document that TOXSWA 5.5.3 is supported in the help files - -commit 6ca8bdb8636141fac592688a6794ae092f0bc85a -Author: Johannes Ranke -Date: 2018-06-20 14:58:44 +0200 - - Advertise drat repo - -commit 6acfd0dfb2670e3eeab6144c90586f28105583a8 -Author: Johannes Ranke -Date: 2018-06-20 14:53:02 +0200 - - Update static docs - -commit cac29c8c1cc0f6004ef0cd63229cfb993a24496c -Author: Johannes Ranke -Date: 2018-06-11 16:27:22 +0200 - - Adapt to TOXSWA 5.5.3 - -commit bd15236d5dedb4067bd29e58e655c5352aca1db4 -Author: Johannes Ranke -Date: 2018-06-08 16:20:40 +0200 - - Enable PEC porewater for the default scenario - - The default scenario uses soil parameters from the REACH guidance R.16, - Table R.16-9. - -commit ec2052d68950745380c2724757b3ba8b116605fc -Author: Johannes Ranke -Date: 2018-06-08 14:54:40 +0200 - - Add actual/twa calcs for FOMC, typo - -commit edc3462fb4fa9f0eb604fc18ec62bb48997b5627 -Author: Johannes Ranke -Date: 2018-06-08 14:53:58 +0200 - - Pending stuff from the doc update - -commit 197606de234a936751ac3c1db2e4feb3fa117a92 -Author: Johannes Ranke -Date: 2018-06-06 02:48:44 +0200 - - Rebuild docs with pkgdown 1.1.0 - -commit 282820693c62b958e12104f4bb6229c04803f098 -Author: Johannes Ranke -Date: 2018-03-01 10:32:08 +0100 - - Add a README.html for cgit.jrwb.de - -commit 6d8de73e68f2c0349e618af35ce4a8f095ca0ed5 -Author: Johannes Ranke -Date: 2018-03-01 10:10:08 +0100 - - Rebuild static docs using current pkdown - - Process PELMO runs in example using 15 (hyperthreading) cores and show - processor info. - -commit ffeec05d913f2e987da362c05df2afc2a8a23965 -Author: Johannes Ranke -Date: 2018-01-29 10:11:27 +0100 - - Documentation fixes and updates - -commit 8423df9693c5cd2f2d36ee3131c7b6fcefa4d0ca -Author: Johannes Ranke -Date: 2018-01-29 10:11:27 +0100 - - Documentation fixes and updates - -commit b9ce44748f2795ae1f35fe5a510e88635f247a7f -Author: Johannes Ranke -Date: 2018-01-29 09:22:42 +0100 - - Correction of return value documentation for PEC_sw_exposit_runoff - - Rebuild pkgdown documentation - -commit 87d63e649da5e12409c50cb06d3d2a01e9880759 -Author: Johannes Ranke -Date: 2017-12-15 17:25:21 +0100 - - Improve handling of µ in y axis for plot.TOXSWA_cwa - -commit 4944d7ade227f1dd54c94b6a02c3c849dc1fb8ab -Author: Johannes Ranke -Date: 2017-12-14 10:19:43 +0100 - - Update copyright date - -commit 0e1d517d4d6351f2d43ab8636363e73d8b8cf677 -Author: Johannes Ranke -Date: 2017-11-04 11:48:08 +0100 - - Option to thin low TOXSWA PECsw data for plotting - - to reduce the file size of plots e.g. as PDF files - -commit eb4465035dd44907eae3ea0340221316b7cfca12 -Author: Johannes Ranke -Date: 2017-11-03 11:18:10 +0100 - - Also return runoff percentages - -commit 06b528f0c19ca9f7a311612c0e9ae80c0d0c1d3f -Author: Johannes Ranke -Date: 2017-10-27 18:15:29 +0200 - - Exposit runoff calculations for surface water - -commit 2cd464455a22791c0450ada45a0e0128c637fade -Author: Johannes Ranke -Date: 2017-10-23 15:19:03 +0200 - - Typos, rebuild static docs - -commit 6f6575701d9b028af4b3b1b4b61c36d4989e2812 -Author: Johannes Ranke -Date: 2017-10-10 14:03:20 +0200 - - Add ORCID - -commit a33f1bbbf6f6121e8ad40284690a463733a00bc2 -Author: Johannes Ranke -Date: 2017-10-09 08:48:39 +0200 - - Write Step 2 input files on windows - -commit 311c4fbcc51ad727551da41569d64e6bc290c2b2 -Author: Johannes Ranke -Date: 2017-10-06 09:30:21 +0200 - - Update docs, small bugfix - -commit 72d7358581bca88af8c507b6c80791100aaafafc -Author: Johannes Ranke -Date: 2017-08-24 10:30:11 +0200 - - Build for windows using roxygen from master - - Now that roxygen can handle UTF8 characters in function - arguments thanks to Hadley Wickham and Jim Hester - -commit a8a2a9d57f40ec7a4fc70df3dc470d88cd10c525 -Author: Johannes Ranke -Date: 2017-07-24 16:31:07 +0200 - - Improve Makefile - -commit 89fc0926722fbfd6420297194c8b18f5b8a9447d -Author: Johannes Ranke -Date: 2017-07-24 16:26:51 +0200 - - Version bump as I had 0.4.3 in my drat already - -commit 762880a78620e50814351248c02d012a7b030fb8 -Author: Johannes Ranke -Date: 2017-07-24 16:23:22 +0200 - - Avoid warning about possibly mis-spelled word - -commit a2e24495c01f837474b69263a9861a89050cbfd1 -Author: Johannes Ranke -Date: 2017-07-21 11:15:41 +0200 - - New Option for Step 1, fix example, update docs - - Also add the reference file for testing Step12 input file generation - -commit dffa31a5ad5026d4d67327da622f45c00be40584 -Author: Johannes Ranke -Date: 2017-06-22 08:23:13 +0200 - - Add scenario, region and season to run name - -commit 0607a619d92d582ba40f9c0c3b32a1d0a8791655 -Author: Johannes Ranke -Date: 2017-06-20 16:40:21 +0200 - - Possibility to turn off formation in water - - This makes it possible to compare the Step 1 output with earlier - versions of the Steps 12 tool. - -commit 0d60c88ba7e0693a832056ea3db5cc0eaf3b0819 -Author: Johannes Ranke -Date: 2017-06-20 14:16:14 +0200 - - Fix line endings and allow all interception classes - -commit dc1e49c8bb27cac81268719055bc4336843c0506 -Author: Johannes Ranke -Date: 2017-06-20 06:16:19 +0200 - - Keep dos format for pesticide.txt test data - -commit fd40f74907e89077bd81af5d779ae93e1434d8c6 -Author: Johannes Ranke -Date: 2017-06-20 06:11:12 +0200 - - Now the errors in PELMO output are gone - not reproducible - -commit 88044fd98c5b95d3f3f9bbef7416af66552189c1 -Author: Johannes Ranke -Date: 2017-06-20 06:04:14 +0200 - - Tests for Step 1 and 2 (input file only) pass, PELMO fails - - There are spurious errors in the output PELMO generates. Two examples - are in the test.log - -commit 34d4915297faf6236479f0e6474f8aa6b8d4b416 -Author: Johannes Ranke -Date: 2017-06-20 04:30:52 +0200 - - Fix generation of input files - - - Write header only if not appending - - Write max_soil and max_ws for metabolites - - Formatting - -commit 7233eed00b799e08c31ae971f997b4b3c14eaea2 -Author: Johannes Ranke -Date: 2017-06-19 20:10:21 +0200 - - Single line of generated Step12 input file partially validated - -commit c9bcd8e68db61515080ff377c6a04fa807337258 -Author: Johannes Ranke -Date: 2017-06-17 16:36:13 +0200 - - Start with the generation of an input file - -commit e6f968cf97ed6ca9268e6098d86ba63ff2c6d2b0 -Author: Johannes Ranke -Date: 2017-05-24 16:07:35 +0200 - - Fix for the sawtooth function for repeated applications - - For n > 2, the second application was made at 2 * i instead of i. - -commit 4835e20d1d08203657ab616600286ad9dfd71344 -Author: Johannes Ranke -Date: 2017-05-24 15:46:44 +0200 - - Re-enable PELMO examples and tests - - - Add .gitattributes to make sure CRLF line endings are kept for PELMO - .psm files - - Update static docs - -commit 539ea37b45ddc41b36dd199f06ffe5936ab13f21 -Author: Johannes Ranke -Date: 2017-05-17 12:23:38 +0200 - - Documentation fix - -commit 62bffd4873bc53fa9cd81336efa716b220c83e0a -Author: Johannes Ranke -Date: 2017-05-17 09:36:22 +0200 - - Simplify tests where possible - -commit d60bb9c0b52c8e0452bfbe507e60d5f651589cc8 -Author: Johannes Ranke -Date: 2017-05-16 18:57:16 +0200 - - Update static documentation - -commit 14fa47b1ea1651fc2cb7bbf0086741a8004d35ee -Author: Johannes Ranke -Date: 2017-05-16 18:54:34 +0200 - - Remove external data also from git as their licence is unclear - -commit 608c4f89a2656f67ba915aab17633d41acc789a7 -Author: Johannes Ranke -Date: 2017-05-16 18:44:22 +0200 - - Add build and test logs to the git repo - -commit 3e26a8ab76a434c3465ea1db1b4a2a2ff3ea8ec8 -Author: Johannes Ranke -Date: 2017-05-16 18:40:25 +0200 - - Add TWA concentrations for days > 1, fix link - - Now we have seven test calculations for the Step 1 calculator, all - perfectly passing. This provides confidence that this is a - correct reimplementation of the Step 1 part of the Step 1/2 calculator. - -commit 36036b5901223591e7e21e8b73d8cd1fb034f4cb -Author: Johannes Ranke -Date: 2017-05-16 15:43:50 +0200 - - Finish the Step 1 calculator including tests - - Some cleaning up. PELMO facilities do not currently work at my end, - as I have no working wine installation on this computer - -commit d042f8f06b313e8595087587455daac73d84f17b -Author: Johannes Ranke -Date: 2017-05-15 20:01:28 +0200 - - Start of an Steps 1/2 calculator in R - -commit b052bf8d1e090e07bf0853f0aa8b895db8f41a2a -Author: Johannes Ranke -Date: 2017-03-29 19:24:37 +0200 - - Make it possible to use expressions in axis labels - -commit d69fda8d8f854b735394ecdaec9d59fb18c42b00 -Author: Johannes Ranke -Date: 2017-03-28 10:09:45 +0200 - - Update Changelog - -commit 90e5ff0a9fdadd65e179c04c7d43b4db6e301984 -Author: Johannes Ranke -Date: 2017-03-06 17:59:16 +0100 - - Move static docs to pkdown.jrwb.de, update them - -commit 68e36eb0a5f1b611588d47f77e0ef7c3d9ba0beb -Author: Johannes Ranke -Date: 2017-03-01 11:37:31 +0100 - - The package is not in subdir `pkg` any more - -commit f67ea0c4aeb68631e9f93c95e86c14364718477a -Author: Johannes Ranke -Date: 2017-01-31 07:33:21 +0100 - - Small documentation fix - -commit 4e696997516543e29119e94d67283f513be4484d -Author: Johannes Ranke -Date: 2017-01-30 18:08:50 +0100 - - Regenerate static documentation - -commit 03bda75d343402dad99df2aad55611e11279b833 -Author: Johannes Ranke -Date: 2017-01-30 18:04:53 +0100 - - Correct psm file in the example with metabolites - -commit 39d202b0a0f833c756bc98fb4961483de1b15353 -Author: Johannes Ranke -Date: 2017-01-30 16:14:15 +0100 - - Ignore windows binary builds in git and in R package - -commit e6bb9654679f43af6958d6e28cb5206abb91d574 -Author: Johannes Ranke -Date: 2017-01-30 16:10:30 +0100 - - Test reproducing the FOCUS Summary information - - generated from the FOCUS PELMO GUI, as copied into the text files - in the testdata directory. - -commit 80b451ddb4e749041c2b216603274a012dc83d59 -Author: Johannes Ranke -Date: 2017-01-30 14:28:23 +0100 - - PELMO summary files for testing - -commit 826cf9a2687ff1d7ca5b568882f5686f76f82074 -Author: Johannes Ranke -Date: 2017-01-30 14:11:34 +0100 - - Use relative tolerance of 1e-6 for flux test - - to pass test also for more extreme situations as in the current test data. - -commit eea72720956dc8358fac98b29c9a627a9363cbd2 -Author: Johannes Ranke -Date: 2017-01-30 13:12:24 +0100 - - Better documentation of PELMO_runs(). - -commit d78d2effd517ab3c27412ae6f4ae701c456ae590 -Author: Johannes Ranke -Date: 2017-01-30 12:46:57 +0100 - - pfm for windows in my drat - -commit eaf3b558747ff8228e87ded727a6c0e91a6579f8 -Author: Johannes Ranke -Date: 2017-01-30 12:01:14 +0100 - - More extreme parameters for metabolites for testing - -commit a6c13f70f6c6669a8088827a602ac475fdf9b624 -Author: Johannes Ranke -Date: 2017-01-29 16:58:53 +0100 - - Setting up PELMO runs, execution and evaluation - - It all works! - -commit bc97a35a32c4f47e29364488a3601f94c6e68d45 -Author: Johannes Ranke -Date: 2017-01-27 18:33:45 +0100 - - Really use all scenarios in test data - - Maize, that was used in the last commit, is not parameterised for - Jokioinen - -commit a4081ddfea726283874968c0b62a7f46e4fd1232 -Author: Johannes Ranke -Date: 2017-01-27 18:23:35 +0100 - - Use all scenarios in the test data - -commit 3c82d26206e2f2e74600acd71a49c70eaed555c4 -Author: Johannes Ranke -Date: 2017-01-27 08:17:08 +0100 - - Also test run with metabolites - -commit 8fd050e57b7babfbdb1ccfabb468a0398396d466 -Author: Johannes Ranke -Date: 2017-01-27 07:54:53 +0100 - - Include a run with metabolites in PELMO test data - -commit b38055278d4a801598ece9d2c93716a9bf67134a -Author: Johannes Ranke -Date: 2017-01-27 01:00:07 +0100 - - Set up FOCUS PELMO runs and run them in parallel - - - This works on Linux using wine - - PELMO runs (including pelmo.inp files) are correctly generated - - The PLM files for FOCUS Pesticide_D in the test data archive are - correctly reproduced - - The data files (including FOCUS groundwater scenario data) are now - created and documented in R files - -commit 40c2f387775a168df1be699813807586cf098648 -Author: Johannes Ranke -Date: 2017-01-26 10:30:32 +0100 - - Improved test data with 'irrigation' - -commit 228ab628b407af4812a48f20693a9a3a6bba8af4 -Author: Johannes Ranke -Date: 2017-01-25 16:45:24 +0100 - - More variable selection of test data - -commit bf6634b7d9a5033a217f04060f77e0c7d5b3046a -Author: Johannes Ranke -Date: 2017-01-25 15:27:05 +0100 - - Use tar.bz2 to correctly transfer file names - -commit 476d556cb6a490b138e47d487dd732f298aa6c3d -Author: Johannes Ranke -Date: 2017-01-25 14:29:41 +0100 - - Add FOCUS PELMO 5.5.3 output for dummy pesticide D - -commit 9f16be247e851c948edb30ac756550d89ba0af52 -Author: Johannes Ranke -Date: 2017-01-19 11:44:22 +0100 - - Another correction of the docs - -commit 2ab822d51c4c7e29d62076336d7a3f02a46e41a5 -Author: Johannes Ranke -Date: 2017-01-19 11:41:19 +0100 - - Corrections in the documentation - -commit 46883a0c3a3c00127a563a7befa0af440573baaa -Author: Johannes Ranke -Date: 2017-01-19 11:22:08 +0100 - - Correct default y axis label for plot.one_box - -commit 3947731a5a8c3598271b26f5201dea4bcb13ef6d -Author: Johannes Ranke -Date: 2017-01-19 10:47:09 +0100 - - Fix one_box for ini = 1, use in sawtooth examples - -commit dd30f0d0ff1d8d0cc46aaef6e0917c51fe798f52 -Author: Johannes Ranke -Date: 2017-01-19 10:36:19 +0100 - - Move mkin::twa to pfm::max_twa.mkinfit - - - Add max_twa.mkinfit() recently introduced to mkin as mkin::twa() but - never released with it - - Add a test to check max_twa.one_box() against analytical solutions in - max_twa.mkinfit(). - - Clean up R CMD check - - Update docs - -commit 3ead7acba845b4f2552f555dfb29da889ed0cda8 -Author: Johannes Ranke -Date: 2017-01-19 09:42:21 +0100 - - Make max_twa() a bit safer - -commit 74ed85b07f09ea99476208749cd274a476ba4536 -Author: Johannes Ranke -Date: 2017-01-19 09:27:36 +0100 - - Documentation updates - -commit a6d61c06d573574cf574ed893cc13808a9e8b785 -Author: Johannes Ranke -Date: 2017-01-19 09:20:22 +0100 - - Fix order of arguments to one_box, correct docs - -commit b8ac1393b9e1bef8c48b26b790cf5759ccd69fed -Author: Johannes Ranke -Date: 2017-01-19 09:10:37 +0100 - - Predict parent decline without fitting for non-SFO models - -commit 3d4f6f8c582c19c38587ead305a1229ff069da63 -Author: Johannes Ranke -Date: 2017-01-19 08:24:44 +0100 - - Switch sawtooth plotting example to FOMC - - as this it is claimed in the README that an mkinfit prediction is used. - - Add another seealso link - - Delete trailing whitespace - -commit 9b5faa8b8475bdd7624c58b07d45d28d42a47a2e -Author: Johannes Ranke -Date: 2017-01-18 23:02:14 +0100 - - Point to the github.io documentation site - -commit cff68edc1ac113ac9e159dfdf7cfcbb6721ff2a7 -Author: Johannes Ranke -Date: 2017-01-18 22:58:51 +0100 - - Make README.md simple, and point to the reference - -commit a76221d87485029444c8e684022ca606a0c7e68d -Author: Johannes Ranke -Date: 2017-01-18 22:41:01 +0100 - - Update static docs using pkgdown - - - Add _pkgdown.yml for a structured function/data reference - - Make seealso links active - - Make mkinfit calls quiet - - Use pkgdown branch from pull request hadley/pkgdown#229 to have topics - ordered - -commit a1d9f93138c2cfed92a683e37e72c737d52b7ad7 -Author: Johannes Ranke -Date: 2017-01-18 19:58:13 +0100 - - One box time series and twa values - - - one_box() creates decline time series from mkinfit objects or simply - from a half-life - - sawtooth() generates sawtooth curves for arbitrary application - patterns and decline models - - twa() calculates moving window averages - - max_twa() gives their maxima and - - plot.one_box() can plot series generated by one_box() or sawtooth(), - optionally adding a greay rectangle to illustrate the maximum moving - window time weighted average - -commit bba2cf3a70849ba86f37520d3e909cf1c706f416 -Author: Johannes Ranke -Date: 2016-12-22 11:06:57 +0100 - - Fix reading in times from .out files - - The code from the previous commit was broken. Also, the time - zone for the times that are read is now wet to 'UTC', in order to - avoid setting different time zones due to daylight savings, which - introduces artificial one-hour offsets on changeover days. - -commit 0af7c7b8c34067fc4756929925239c329b28ed32 -Author: Johannes Ranke -Date: 2016-12-14 18:26:14 +0100 - - Changelog update and roxygen run - -commit 5a04ad3061c1484b45703e44149f49ec97cfbf15 -Author: Johannes Ranke -Date: 2016-12-14 16:52:14 +0100 - - Set time correctly for 00:00 hours in .out file - - For ConLiqWatLayCur_xxxxx entries which are output at 00:00 (midnight), - no time is listed in the .out file for this time. This commit introduces - a workaround, setting the time to 00:00 when there is no time - information. - -commit e51e063564bffcb75dbb6ab7a364704c8d8e992e -Author: Johannes Ranke -Date: 2016-12-12 21:24:24 +0100 - - Fix reading .out for acronyms containing numbers - -commit 9124e0f7d673c65584c1b2f838a3b944ea89c31d -Author: Johannes Ranke -Date: 2016-10-13 17:49:18 +0200 - - Add drat target, remove unmaintained usage hints - -commit 12a31f4c130c551f82232d9ef7dfb608bd52c53f -Author: Johannes Ranke -Date: 2016-09-27 23:00:48 +0200 - - Reorganise repository using standard package layout - -commit 0d958ab6f84b569b5437f231c56004890c4ae23b -Author: Johannes Ranke -Date: 2016-09-27 17:50:34 +0200 - - Make the chents package optional - -commit 399383adcdb37c4a3e32f1a2133a2fa3663618d0 -Author: Johannes Ranke -Date: 2016-09-23 18:23:00 +0200 - - Keep the graph for the markdown file - - The markdown file is not self-contained as the html file... - -commit 9fb69b042924045df90119e47ad4dc666dbc8b4d -Author: Johannes Ranke -Date: 2016-09-23 18:16:51 +0200 - - Slightly update the README - -commit 2f618da8cfbeb0379f4d38af6f608a69c6d54bd5 -Author: Johannes Ranke -Date: 2016-07-30 11:29:09 +0200 - - Update static documentation - -commit 3b8730a58f7846b5261922ec90e582e0158a54c7 -Author: Johannes Ranke -Date: 2016-07-30 11:09:47 +0200 - - Add 'methods' to dependecies - -commit 3260b0e875b7af24f2aef7bc2464418525a192df -Author: Johannes Ranke -Date: 2016-07-30 11:08:05 +0200 - - Fix the TOXSWA reading test - - Since a recent commit we are reading the concentrations at the end - of each hour, so the test needed to be updated accordingly - -commit b8f953d04e4094c79b4f860d99f3c1466ed3ad6a -Author: Johannes Ranke -Date: 2016-07-30 11:06:53 +0200 - - Import 'is' from methods - -commit 1ceb226d999d56276c9e361f359368287a0749c4 -Author: Johannes Ranke -Date: 2016-07-30 10:42:48 +0200 - - Read cwas from .out files with metabolites - - TOXSWA 4 stores the detailed output for SWASH runs with metabolites - in its .out files. With this commit it is possible to read in - .out files from such runs with metabolites. Default is to read in - the concentrations for the parent, a newly gained "substance" argument - makes it possible to specify the metabolite for which the data should - be read. - -commit d6b230cd1b415a112009227bc9e0ff50316c42f7 -Author: Johannes Ranke -Date: 2016-07-15 15:05:22 +0200 - - Fix calculation of t_firstjan - - There is an inconsistency in (some?) output files, so the first - datetime needs to be fixed before reading it into a data frame - -commit b45c9bfae9e5578dd455ed417363b4996cffd46a -Author: Johannes Ranke -Date: 2016-06-08 08:36:48 +0200 - - Clean up remainders of NL drift calculation function - -commit 234a20018fe9fe9824bcfaae2c391e59d09f9871 -Author: Johannes Ranke -Date: 2016-06-08 08:29:39 +0200 - - Use the concentration at the end of the hour - - This is also what TOXSWA presents in the summary files - -commit 4284c57c7d53a9aef0c917a050ccf2ab779cfce3 -Author: Johannes Ranke -Date: 2016-06-08 08:29:39 +0200 - - Use the concentration at the end of the hour - - This is also what TOXSWA presents in the summary files - -commit 057d53d0faed7b297bbb99de8cd4bf3e3e448538 -Author: Johannes Ranke -Date: 2016-03-10 05:28:03 +0100 - - Merge the NL drift calculations based on percentages into PEC_sw_drift - -commit 527d927371083e784ad583a6b3c7465c49a53cdc -Author: Johannes Ranke -Date: 2016-03-10 05:17:45 +0100 - - Add NL specific drift calculations - -commit 1ab6d4c9f186fb7ea9bb8b968e47a9f1eab64583 -Author: Johannes Ranke -Date: 2016-03-02 17:51:21 +0100 - - Fix the name of the Chateadun scenario - -commit d14923ae1ac023c8f8f5ae8b5c0884f4247f764b -Author: Johannes Ranke -Date: 2016-02-04 18:06:15 +0100 - - Test reading .out files and close connections - -commit 98a706373107188496a1df295697e739e51d6b06 -Author: Johannes Ranke -Date: 2016-02-04 17:45:02 +0100 - - Improve reading spead for new TOXSWA format - -commit 057ba40426d49e09c06db26fb7d4072741b4cb8d -Author: Johannes Ranke -Date: 2016-02-04 12:21:02 +0100 - - Read cwa data from TOXSWA 4.4.2 .out files - -commit e7f8a0e82b24d28b74681dafc97f1cf8a4662b51 -Author: Johannes Ranke -Date: 2015-12-27 12:30:20 +0100 - - Fix rounding of endpoint retrieval functions - -commit f9373e361dde232b08fe7431e85bf367a1cfc269 -Author: Johannes Ranke -Date: 2015-12-27 12:29:37 +0100 - - Another useless variant to avoid warnings in staticdoc plots - -commit 3a579d87820ccbec514f1be5eb090e874fd87eec -Author: Johannes Ranke -Date: 2015-12-22 19:32:54 +0100 - - EFSA 2015 tier 1 PEC soil, clean up, add static docs - -commit 9851a97ec915ddbfc8357f1a7e2cabae56c89f7d -Author: Johannes Ranke -Date: 2015-12-18 14:45:24 +0100 - - Documentation fixes, chents is currently a hard dependency - -commit 6b4e342b240baaf18150360986d15895fc80a937 -Author: Johannes Ranke -Date: 2015-10-15 14:41:26 +0200 - - Add endpoint and GUS functions, roxygenize - -commit c43b4947007b3c26bc56260499af51c41b8cd702 -Author: Johannes Ranke -Date: 2015-10-01 14:42:14 +0200 - - Add some soil data for FOCUS groundwater scenarios - -commit 697e0554bf89a63f23b9ab5548e31f218bc483e9 -Author: Johannes Ranke -Date: 2015-09-11 10:07:53 +0200 - - Added PEC soil for products as defined in chents v0.1-2 - -commit 634d4a0a93882a3b2d3961abbdd33694fd93dcc6 -Author: Johannes Ranke -Date: 2015-09-10 16:18:17 +0200 - - Add PEC soil for product with serveral ais - -commit 1ec3ee4a03d4e47fdd3be1bcbe754e478353410b -Author: Johannes Ranke -Date: 2015-08-22 12:10:06 +0200 - - Updates of DESCRIPTION and NAMESPACE - -commit 51aa1a77c9b9b9a6becdb2a5a85213946719b051 -Author: Johannes Ranke -Date: 2015-08-22 12:06:37 +0200 - - Add README.html for cgit on jrwb.de - -commit 83c8575e2abde12208584b9c80935d4a873689fd -Author: Johannes Ranke -Date: 2015-08-22 12:01:57 +0200 - - Small documentation updates - -commit 5038ba57fef6cc386566ec30f3d5dd67e62decff -Author: Johannes Ranke -Date: 2015-08-21 15:10:42 +0200 - - Adapt the description to R CMD check requirements - -commit 4477e69b46e88c196f354463190753650157ea0d -Author: Johannes Ranke -Date: 2015-08-21 15:01:10 +0200 - - Updates to pass checks and tests - -commit ad4cd5d9a1f8c3976d08048a441129b1fb49a62b -Author: Johannes Ranke -Date: 2015-07-02 16:05:59 +0200 - - Changes to pass R CMD check --as-cran, roxygen run - -commit fef0bb7fe916f91dcff089c17aa3290c0ea1ab1f -Author: Johannes Ranke -Date: 2015-06-12 02:19:38 +0200 - - Add sediment PEC calculations using the percentage method - -commit 5b32c30549bfa3cb42ffde7e13f75608b98c79c2 -Author: Johannes Ranke -Date: 2015-06-12 02:19:01 +0200 - - Make UK drainage with non-SFO soil degradation work - -commit 9b8e5cb80ba4a89578d979bee134f8342ca0a527 -Author: Johannes Ranke -Date: 2015-06-11 17:38:01 +0200 - - Now we pass R CMD check - -commit dd803b191062925eda830543236836e7822fd884 -Author: Johannes Ranke -Date: 2015-06-11 16:57:43 +0200 - - Add UK tier 1 drainage PEC calculations - -commit 09cf970942706cfab43753d298b42e8d85216d80 -Author: Johannes Ranke -Date: 2015-06-11 15:25:22 +0200 - - Now there is enough content to warrant 0.2-x - -commit 3aa5fb86772c28402047c7ebd07841061dbcdbba -Author: Johannes Ranke -Date: 2015-06-11 15:23:22 +0200 - - Add facilities to calculate decline curves - -commit d3daa7b73fa5d0508ff51a843247d126c2a11691 -Author: Johannes Ranke -Date: 2015-06-11 13:17:13 +0200 - - Generate README.md with current pfm version - -commit cb0d72e2c2d431bd32ffb129b62ea1a522cbdfeb -Author: Johannes Ranke -Date: 2015-06-11 13:09:10 +0200 - - Rename PEC_sw_drift() to PEC_sw_drift_ini() - -commit ea9b75183bcf41fcdd6f61ec6060e94c4bc321a2 -Author: Johannes Ranke -Date: 2015-06-11 12:13:47 +0200 - - Add simple drift PEC ini calculations - - These are tested for field crops with the CRD spreadsheet - -commit cbba81d73faa83c63a33afc61be5efc1964925bb -Author: Johannes Ranke -Date: 2015-06-11 12:12:40 +0200 - - Use devtools for roxygenizing, improve logging - -commit 6e4a152925011528c21937f12bc53042a53f72de -Author: Johannes Ranke -Date: 2015-06-11 10:13:18 +0200 - - JKI drift percentage data for field crops and pome/stone fruit - -commit 53099978c971ee8e5c94e67bf972f51629d67fd3 -Author: Johannes Ranke -Date: 2015-06-11 10:04:22 +0200 - - and the incomplete documentation - -commit 372ab2f2f59f0baaee759ce966a705f9f754cf6d -Author: Johannes Ranke -Date: 2015-06-11 10:03:32 +0200 - - Intermediate stage for pfm_chent - -commit 586b248f5d249f4ebaad2175c9f78fcae8646636 -Author: Johannes Ranke -Date: 2015-06-11 09:54:57 +0200 - - Formatting - -commit fd1609aafd2f40266c1e29d8dfdf5e08e8838d35 -Author: Johannes Ranke -Date: 2015-05-24 03:52:28 +0200 - - Start of a pfm_chent data object - -commit e2b1d510e921f7721647b0df6602c2618937c1da -Author: Johannes Ranke -Date: 2015-05-08 08:47:11 +0200 - - Update the Figure in the README - -commit 8021c7cb9aac06e961227a3c0e0b013ec2d2d501 -Author: Johannes Ranke -Date: 2015-05-07 16:15:23 +0200 - - Bugfix: Reset maximum event concentration for each event - -commit 508d883f7689d617d15915dbd26a27f1613bb857 -Author: Johannes Ranke -Date: 2015-05-07 12:04:28 +0200 - - Make quarterly labels for plot.TOXSWA_cwa - -commit c6e57ab29170266b3038b01c54bf161ab361d440 -Author: Johannes Ranke -Date: 2015-04-24 02:22:21 +0200 - - Do not test the path to the zip file - -commit 7d2096855edcc196629c1c7a9983a56ec6addd1e -Author: Johannes Ranke -Date: 2015-04-24 02:21:04 +0200 - - Add a geometric mean function - -commit bcfe0af7970efe36c3aa661e89953fbe3689c310 -Author: Johannes Ranke -Date: 2015-04-24 02:20:21 +0200 - - Clean the Makefile a bit - -commit 768a043848dd84b9e699916657d0a23b2f3b9e83 -Author: Johannes Ranke -Date: 2015-04-22 13:48:42 +0200 - - Fix header formatting - -commit 04502ca0c658a6c929debd61aee87be8c7eceb04 -Author: Johannes Ranke -Date: 2015-04-22 13:46:32 +0200 - - Update markdown version of README - -commit ec79637749d300ab4ca170805c673905e52d67dd -Author: Johannes Ranke -Date: 2015-04-22 13:42:10 +0200 - - Add simplest PEC soil calcs, use testthat - -commit 8ffbc49b3f01deac6f9e83aaa6d318d4e2f8552b -Author: Johannes Ranke -Date: 2015-01-23 16:44:04 +0100 - - Add option to plot relative to maximum - -commit 8975dc148d0a6f222174980eb60314054be9b6cf -Author: Johannes Ranke -Date: 2015-01-13 14:54:58 +0100 - - Fix warning in README - -commit 891af5d0f1ee8d45cd4403af43293463d23ba96b -Author: Johannes Ranke -Date: 2015-01-13 14:05:31 +0100 - - README.rmd with example, fix reading unzipped files - -commit 4d74570f1ca4a94d894c6c5169684a8246d0a51c -Author: Johannes Ranke -Date: 2015-01-13 12:58:26 +0100 - - Correctly initialize R6 fields, read from zip files - -commit ee070c11f7c7faff2f573d27cf32aafab78971a8 -Author: Johannes Ranke -Date: 2015-01-07 23:56:54 +0100 - - Pass ... parameters to added cwa lines - -commit 92d97ba99d7b90d95a67796cb5e68f28f752b70b -Author: Johannes Ranke -Date: 2014-12-17 21:39:42 +0100 - - Initial commit: R6 class for TOXSWA cwa files diff --git a/DESCRIPTION b/DESCRIPTION index 8d11e33..ab6d2ce 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,8 +1,8 @@ Package: pfm Type: Package Title: Utilities for Pesticide Fate Modelling -Version: 0.6.0 -Date: 2023-11-11 +Version: 0.6.1 +Date: 2024-01-31 Authors@R: person("Johannes Ranke", email = "johannes.ranke@agroscope.admin.ch", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4371-6538")) @@ -10,6 +10,7 @@ Description: Utilities for simple calculations of predicted environmental concentrations ('PEC' values) and for dealing with data from some FOCUS pesticide fate modelling software packages. Depends: + R (>= 3.5.0), R6, mkin (>= 1.2) Imports: @@ -21,10 +22,12 @@ Suggests: chents, grImport, magrittr, - covr + covr, + here, + waldo License: GPL -LazyLoad: yes -LazyData: yes +LazyLoad: true +LazyData: true Encoding: UTF-8 URL: https://pkgdown.jrwb.de/pfm RoxygenNote: 7.2.3 diff --git a/GNUmakefile b/GNUmakefile index fae80e3..b987f41 100644 --- a/GNUmakefile +++ b/GNUmakefile @@ -2,80 +2,51 @@ PKGNAME := $(shell sed -n "s/Package: *\([^ ]*\)/\1/p" DESCRIPTION) PKGVERS := $(shell sed -n "s/Version: *\([^ ]*\)/\1/p" DESCRIPTION) TGZ := $(PKGNAME)_$(PKGVERS).tar.gz WINBIN := $(PKGNAME)_$(PKGVERS).zip -R_HOME ?= $(shell R RHOME) -DATE := $(shell date +%Y-%m-%d) +RBIN ?= $(shell dirname "`which R`") -.PHONEY: usage check clean +.PHONEY: check pkgfiles = \ .Rbuildignore \ - ChangeLog \ DESCRIPTION \ data/* \ - docs/* \ - docs/reference/* \ + GNUmakefile \ + inst/data_generation/* \ inst/testdata/* \ README.html \ R/* \ tests/testthat.R \ tests/testthat/* -clean: - @echo "Cleaning up..." - rm -fR pfm.Rcheck - @echo "DONE." +all: build -roxygen: - @echo "Roxygenizing package..." - "$(R_HOME)/bin/Rscript" -e 'devtools::document()' - @echo "DONE." +roxy: + Rscript -e "roxygen2::roxygenize(roclets = c('rd', 'collate', 'namespace'))" README.html: README.md - "$(R_HOME)/bin/Rscript" -e "rmarkdown::render('README.md', output_format = 'html_document', output_options = list(mathjax = NULL))" - -pd: roxygen - @echo "Building static documentation..." - # suppressWarnings to get rid of mbcsToSbcs warnings when plotting the 'µ' character - "$(R_HOME)/bin/Rscript" -e 'suppressWarnings(pkgdown::build_site(lazy=TRUE))' - @echo "DONE." + "$(RBIN)/Rscript" -e "rmarkdown::render('README.md', output_format = 'html_document', output_options = list(mathjax = NULL))" $(TGZ): $(pkgfiles) - sed -i -e "s/Date:.*/Date: $(DATE)/" DESCRIPTION - @echo "Roxygenizing package..." - "$(R_HOME)/bin/Rscript" -e 'devtools::document()' - @echo "Building package..." - "$(R_HOME)/bin/R" CMD build . > build.log 2>&1 - @echo "DONE." + "$(RBIN)/R" CMD build . 2>&1 | tee log/build.log + +build: roxy $(TGZ) -build: $(TGZ) +install: build + "$(RBIN)/R" CMD INSTALL $(TGZ) $(WINBIN): build @echo "Building windows binary package..." - "$(R_HOME)/bin/R" CMD INSTALL $(TGZ) --build + "$(RBIN)/R" CMD INSTALL $(TGZ) --build @echo "DONE." winbin: $(WINBIN) -test: build - @echo "Running testthat tests..." - NOT_CRAN=true "$(R_HOME)/bin/Rscript" -e 'options(cli.dynamic = TRUE); devtools::test()' 2>&1 | tee test.log - sed -i -e "s/\r.*\r//" test.log - @echo "DONE." - -quickcheck: build - @echo "Running check..." - "$(R_HOME)/bin/R" CMD check $(TGZ) - @echo "DONE." - -check: build - @echo "Running CRAN check..." - _R_CHECK_CRAN_INCOMING_REMOTE_=false "$(R_HOME)/bin/R" CMD check --as-cran $(TGZ) - @echo "DONE." +check: roxy build + _R_CHECK_CRAN_INCOMING_REMOTE_=false "$(RBIN)/R" CMD check --as-cran --no-tests $(TGZ) 2>&1 | tee log/check.log -install: build - @echo "Installing package..." - "$(R_HOME)/bin/R" CMD INSTALL --no-multiarch $(TGZ) - @echo "DONE." +test: install + "$(RBIN)/Rscript" -e 'options(cli.dynamic = TRUE); devtools::test()' 2>&1 | tee log/test.log + sed -i -e "s/.*\r.*\r//" log/test.log drat: build "$(R_HOME)/bin/Rscript" -e "drat::insertPackage('$(TGZ)', commit = TRUE)" @@ -89,3 +60,11 @@ winbuilder: build curl -T $(TGZ) ftp://anonymous@win-builder.r-project.org/R-release/ @echo "Uploading to R-devel on win-builder" curl -T $(TGZ) ftp://anonymous@win-builder.r-project.org/R-devel/ + +pd: roxy + # In earlier versions, we used suppressWarnings to get + # rid of mbcsToSbcs warnings when plotting the 'µ' character + Rscript -e 'pkgdown::build_site(lazy = TRUE, run_dont_run = TRUE)' + +pd_all: roxy + Rscript -e 'pkgdown::build_site(lazy = FALSE, run_dont_run = TRUE)' diff --git a/NAMESPACE b/NAMESPACE index e24d712..3b23c45 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -32,8 +32,6 @@ export(endpoint) export(geomean) export(max_twa) export(one_box) -export(perc_runoff_exposit) -export(perc_runoff_reduction_exposit) export(pfm_degradation) export(read.TOXSWA_cwa) export(sawtooth) diff --git a/R/EFSA_GW_interception_2014.R b/R/EFSA_GW_interception_2014.R index 15d7835..386fddf 100644 --- a/R/EFSA_GW_interception_2014.R +++ b/R/EFSA_GW_interception_2014.R @@ -9,33 +9,5 @@ #' \bold{12}(5):3662, 37 pp., doi:10.2903/j.efsa.2014.3662 #' @format A matrix containing interception values, currently only for some selected crops #' @examples -#' \dontrun{ -#' # This is the code that was used to define the data -#' bbch <- paste0(0:9, "x") -#' crops <- c( -#' "Beans (field + vegetable)", -#' "Peas", -#' "Summer oilseed rape", "Winter oilseed rape", -#' "Tomatoes", -#' "Spring cereals", "Winter cereals") -#' EFSA_GW_interception_2014 <- matrix(NA, length(crops), length(bbch), -#' dimnames = list(Crop = crops, BBCH = bbch)) -#' EFSA_GW_interception_2014["Beans (field + vegetable)", ] <- -#' c(0, 0.25, rep(0.4, 2), rep(0.7, 5), 0.8) -#' EFSA_GW_interception_2014["Peas", ] <- -#' c(0, 0.35, rep(0.55, 2), rep(0.85, 5), 0.85) -#' EFSA_GW_interception_2014["Summer oilseed rape", ] <- -#' c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9) -#' EFSA_GW_interception_2014["Winter oilseed rape", ] <- -#' c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9) -#' EFSA_GW_interception_2014["Tomatoes", ] <- -#' c(0, 0.5, rep(0.7, 2), rep(0.8, 5), 0.5) -#' EFSA_GW_interception_2014["Spring cereals", ] <- -#' c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8) -#' EFSA_GW_interception_2014["Winter cereals", ] <- -#' c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8) -#' save(EFSA_GW_interception_2014, -#' file = "../data/EFSA_GW_interception_2014.RData") -#' } #' EFSA_GW_interception_2014 -NULL +"EFSA_GW_interception_2014" diff --git a/R/EFSA_washoff_2017.R b/R/EFSA_washoff_2017.R index 450c12e..59e299c 100644 --- a/R/EFSA_washoff_2017.R +++ b/R/EFSA_washoff_2017.R @@ -10,33 +10,5 @@ #' doi:10.2903/j.efsa.2017.4982 #' @format A matrix containing wash-off factors, currently only for some selected crops #' @examples -#' \dontrun{ -#' # This is the code that was used to define the data -#' bbch <- paste0(0:9, "x") -#' crops <- c( -#' "Beans (field + vegetable)", -#' "Peas", -#' "Summer oilseed rape", "Winter oilseed rape", -#' "Tomatoes", -#' "Spring cereals", "Winter cereals") -#' EFSA_washoff_2017 <- matrix(NA, length(crops), length(bbch), -#' dimnames = list(Crop = crops, BBCH = bbch)) -#' EFSA_washoff_2017["Beans (field + vegetable)", ] <- -#' c(NA, 0.6, rep(0.75, 2), rep(0.8, 5), 0.35) -#' EFSA_washoff_2017["Peas", ] <- -#' c(NA, 0.4, rep(0.6, 2), rep(0.65, 5), 0.35) -#' EFSA_washoff_2017["Summer oilseed rape", ] <- -#' c(NA, 0.4, rep(0.5, 2), rep(0.6, 5), 0.5) -#' EFSA_washoff_2017["Winter oilseed rape", ] <- -#' c(NA, 0.1, rep(0.4, 2), rep(0.55, 5), 0.3) -#' EFSA_washoff_2017["Tomatoes", ] <- -#' c(NA, 0.55, rep(0.75, 2), rep(0.7, 5), 0.35) -#' EFSA_washoff_2017["Spring cereals", ] <- -#' c(NA, 0.4, 0.5, 0.5, rep(0.65, 3), rep(0.65, 2), 0.55) -#' EFSA_washoff_2017["Winter cereals", ] <- -#' c(NA, 0.1, 0.4, 0.6, rep(0.55, 3), rep(0.6, 2), 0.4) -#' save(EFSA_washoff_2017, -#' file = "../data/EFSA_washoff_2017.RData") -#' } #' EFSA_washoff_2017 -NULL +"EFSA_washoff_2017" diff --git a/R/PEC_sw_exposit_runoff.R b/R/PEC_sw_exposit_runoff.R index d68a521..8b89cd9 100644 --- a/R/PEC_sw_exposit_runoff.R +++ b/R/PEC_sw_exposit_runoff.R @@ -13,18 +13,11 @@ #' adjacent water body bound to eroding particles} #' } #' @source Excel 3.02 spreadsheet available from -#' \url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} -#' @export perc_runoff_exposit +#' \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} +#' @docType data #' @examples #' print(perc_runoff_exposit) -{Koc_breaks <- c(0, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, Inf) -tmp <- paste(Koc_breaks[1:11], Koc_breaks[2:12], sep = "-") -Koc_classes <- c(tmp[1], paste0(">", tmp[2:11]), ">50000")} -perc_runoff_exposit <- data.frame( - Koc_lower_bound = Koc_breaks[1:12], - dissolved = c(0.11, 0.151, 0.197, 0.248, 0.224, 0.184, 0.133, 0.084, 0.037, 0.031, 0.014, 0.001), - bound = c(0, 0, 0, 0.001, 0.004, 0.020, 0.042, 0.091, 0.159, 0.192, 0.291, 0.451)) -rownames(perc_runoff_exposit) <- Koc_classes +"perc_runoff_exposit" #' Runoff reduction percentages as used in Exposit #' @@ -40,31 +33,14 @@ rownames(perc_runoff_exposit) <- Koc_classes #' \item{bound}{The reduction percentage for the particulate phase} #' } #' @source Excel 3.02 spreadsheet available from -#' \url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} +#' \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} #' #' Agroscope version 3.01a with additional runoff factors for 3 m and 6 m buffer zones received from Muris Korkaric (not published). #' The variant 3.01a2 was introduced for consistency with previous calculations performed by Agroscope for a 3 m buffer zone. -#' @export +#' @docType data #' @examples #' print(perc_runoff_reduction_exposit) -perc_runoff_reduction_exposit <- list( - "3.02" = data.frame( - dissolved = c(0, 40, 60, 80), - bound = c(0, 40, 85, 95), - row.names = c("No buffer", paste(c(5, 10, 20), "m"))), - "3.01a" = data.frame( - dissolved = c(0, 25, 40, 45, 60, 80), - bound = c(0, 30, 40, 55, 85, 95), - row.names = c("No buffer", paste(c(3, 5, 6, 10, 20), "m"))), - "3.01a2" = data.frame( - dissolved = c(0, 25), - bound = c(0, 25), - row.names = c("No buffer", paste(c(3), "m"))), - "2.0" = data.frame( - dissolved = c(0, 97.5), - bound = c(0, 97.5), - row.names = c("No buffer", "20 m")) -) +"perc_runoff_reduction_exposit" #' Calculate PEC surface water due to runoff and erosion as in Exposit 3 #' @@ -93,7 +69,7 @@ perc_runoff_reduction_exposit <- list( #' } #' @export #' @source Excel 3.02 spreadsheet available from -#' \url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} +#' \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} #' @seealso \code{\link{perc_runoff_exposit}} for runoff loss percentages and \code{\link{perc_runoff_reduction_exposit}} for runoff reduction percentages used #' @examples #' PEC_sw_exposit_runoff(500, Koc = 150) @@ -108,18 +84,18 @@ PEC_sw_exposit_runoff <- function(rate, interception = 0, Koc, DT50 = Inf, t_run if (length(Koc) > 1) stop("Only one compound at a time supported") exposit_reduction_version <- match.arg(exposit_reduction_version) - red_water <- perc_runoff_reduction_exposit[[exposit_reduction_version]]["dissolved"] / 100 - red_bound <- perc_runoff_reduction_exposit[[exposit_reduction_version]]["bound"] / 100 - reduction_runoff <- perc_runoff_reduction_exposit[[exposit_reduction_version]] / 100 + red_water <- pfm::perc_runoff_reduction_exposit[[exposit_reduction_version]]["dissolved"] / 100 + red_bound <- pfm::perc_runoff_reduction_exposit[[exposit_reduction_version]]["bound"] / 100 + reduction_runoff <- pfm::perc_runoff_reduction_exposit[[exposit_reduction_version]] / 100 transfer_runoff <- 1 - reduction_runoff V_runoff <- V_event * (1 - reduction_runoff[["dissolved"]]) # m3 V_flowing_ditch_runoff <- dilution * (V_ditch + V_runoff) f_runoff_exposit <- function(Koc) { - Koc_breaks <- c(perc_runoff_exposit$Koc_lower_bound, Inf) - Koc_classes <- as.character(cut(Koc, Koc_breaks, labels = rownames(perc_runoff_exposit))) - perc_runoff <- perc_runoff_exposit[Koc_classes, c("dissolved", "bound")] + Koc_breaks <- c(pfm::perc_runoff_exposit$Koc_lower_bound, Inf) + Koc_classes <- as.character(cut(Koc, Koc_breaks, labels = rownames(pfm::perc_runoff_exposit))) + perc_runoff <- pfm::perc_runoff_exposit[Koc_classes, c("dissolved", "bound")] if (identical(Koc, 0)) perc_runoff <- c(dissolved = 0, bound = 0) return(unlist(perc_runoff) / 100) } @@ -168,7 +144,7 @@ PEC_sw_exposit_runoff <- function(rate, interception = 0, Koc, DT50 = Inf, t_run #' } #' @export #' @source Excel 3.02 spreadsheet available from -#' \url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} +#' \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} #' @seealso \code{\link{perc_runoff_exposit}} for runoff loss percentages and \code{\link{perc_runoff_reduction_exposit}} for runoff reduction percentages used #' @examples #' PEC_sw_exposit_drainage(500, Koc = 150) diff --git a/R/drift_data_JKI.R b/R/drift_data_JKI.R index 3b02f43..8f78e4d 100644 --- a/R/drift_data_JKI.R +++ b/R/drift_data_JKI.R @@ -29,59 +29,12 @@ #' @source JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved #' from #' http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html -#' on 2015-06-11 +#' on 2015-06-11, not present any more 2024-01-31 #' #' Rautmann, D., Streloke, M and Winkler, R (2001) New basic drift values in #' the authorization procedure for plant protection products Mitt. Biol. #' Bundesanst. Land- Forstwirtsch. 383, 133-141 #' @keywords datasets #' @examples -#' -#' \dontrun{ -#' # This is the code that was used to extract the data -#' library(readxl) -#' abdrift_path <- "inst/extdata/Tabelle der Abdrifteckwerte.xls" -#' JKI_crops <- c("Ackerbau", "Obstbau frueh", "Obstbau spaet", "Weinbau frueh", "Weinbau spaet", -#' "Hopfenbau", "Flaechenkulturen > 900 l/ha", "Gleisanlagen") -#' names(JKI_crops) <- c("Field crops", "Pome/stone fruit, early", "Pome/stone fruit, late", -#' "Vines early", "Vines late", "Hops", "Areic cultures > 900 L/ha", "Railroad tracks") -#' drift_data_JKI <- list() -#' -#' for (n in 1:8) { -#' drift_data_raw <- read_excel(abdrift_path, sheet = n + 1, skip = 2) -#' drift_data <- matrix(NA, nrow = 9, ncol = length(JKI_crops)) -#' dimnames(drift_data) <- list(distance = drift_data_raw[[1]][1:9], -#' crop = JKI_crops) -#' if (n == 1) { # Values for railroad tracks only present for one application -#' drift_data[, c(1:3, 5:8)] <- as.matrix(drift_data_raw[c(2:7, 11)][1:9, ]) -#' } else { -#' drift_data[, c(1:3, 5:7)] <- as.matrix(drift_data_raw[c(2:7)][1:9, ]) -#' } -#' drift_data_JKI[[n]] <- drift_data -#' } -#' -#' # Manual data entry from the Rautmann paper -#' drift_data_JKI[[1]]["3", "Ackerbau"] <- 0.95 -#' drift_data_JKI[[1]][, "Weinbau frueh"] <- c(NA, 2.7, 1.18, 0.39, 0.2, 0.13, 0.07, 0.04, 0.03) -#' drift_data_JKI[[2]]["3", "Ackerbau"] <- 0.79 -#' drift_data_JKI[[2]][, "Weinbau frueh"] <- c(NA, 2.53, 1.09, 0.35, 0.18, 0.11, 0.06, 0.03, 0.02) -#' drift_data_JKI[[3]]["3", "Ackerbau"] <- 0.68 -#' drift_data_JKI[[3]][, "Weinbau frueh"] <- c(NA, 2.49, 1.04, 0.32, 0.16, 0.10, 0.05, 0.03, 0.02) -#' drift_data_JKI[[4]]["3", "Ackerbau"] <- 0.62 -#' drift_data_JKI[[4]][, "Weinbau frueh"] <- c(NA, 2.44, 1.02, 0.31, 0.16, 0.10, 0.05, 0.03, 0.02) -#' drift_data_JKI[[5]]["3", "Ackerbau"] <- 0.59 -#' drift_data_JKI[[5]][, "Weinbau frueh"] <- c(NA, 2.37, 1.00, 0.31, 0.15, 0.09, 0.05, 0.03, 0.02) -#' drift_data_JKI[[6]]["3", "Ackerbau"] <- 0.56 -#' drift_data_JKI[[6]][, "Weinbau frueh"] <- c(NA, 2.29, 0.97, 0.30, 0.15, 0.09, 0.05, 0.03, 0.02) -#' drift_data_JKI[[7]]["3", "Ackerbau"] <- 0.55 -#' drift_data_JKI[[7]][, "Weinbau frueh"] <- c(NA, 2.24, 0.94, 0.29, 0.15, 0.09, 0.05, 0.03, 0.02) -#' drift_data_JKI[[8]]["3", "Ackerbau"] <- 0.52 -#' drift_data_JKI[[8]][, "Weinbau frueh"] <- c(NA, 2.16, 0.91, 0.28, 0.14, 0.09, 0.04, 0.03, 0.02) -#' -#' # Save the data -#' save(drift_data_JKI, file = "data/drift_data_JKI.RData") -#' } -#' -#' # And these are the resulting data #' drift_data_JKI NULL diff --git a/R/soil_scenario_data_EFSA_2015.R b/R/soil_scenario_data_EFSA_2015.R index 660cafe..0660d40 100644 --- a/R/soil_scenario_data_EFSA_2015.R +++ b/R/soil_scenario_data_EFSA_2015.R @@ -13,28 +13,8 @@ #' EFSA guidance document for predicting environmental concentrations #' of active substances of plant protection products and transformation products of these #' active substances in soil. \emph{EFSA Journal} \bold{13}(4) 4093 -#' doi:10.2903/j.efsa.2015.4093 +#' \doi{10.2903/j.efsa.2015.4093} #' @keywords datasets #' @examples -#' \dontrun{ -#' # This is the code that was used to define the data -#' soil_scenario_data_EFSA_2015 <- data.frame( -#' Zone = rep(c("North", "Central", "South"), 2), -#' Country = c("Estonia", "Germany", "France", "Denmark", "Czech Republik", "Spain"), -#' T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8), -#' T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7), -#' Texture = c("Coarse", "Coarse", "Medium fine", "Medium", "Medium", "Medium"), -#' f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011), -#' theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347), -#' rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51), -#' f_sce = c(3, 2, 2, 2, 1.5, 1.5), -#' f_mod = c(2, 2, 2, 4, 4, 4), -#' stringsAsFactors = FALSE, -#' row.names = c("CTN", "CTC", "CTS", "CLN", "CLC", "CLS") -#' ) -#' save(soil_scenario_data_EFSA_2015, file = '../data/soil_scenario_data_EFSA_2015.RData') -#' } -#' -#' # And this is the resulting dataframe #' soil_scenario_data_EFSA_2015 -NULL +"soil_scenario_data_EFSA_2015" diff --git a/R/soil_scenario_data_EFSA_2017.R b/R/soil_scenario_data_EFSA_2017.R index 79ee15f..f7cbea0 100644 --- a/R/soil_scenario_data_EFSA_2017.R +++ b/R/soil_scenario_data_EFSA_2017.R @@ -13,8 +13,10 @@ #' EFSA guidance document for predicting environmental concentrations #' of active substances of plant protection products and transformation products of these #' active substances in soil. \emph{EFSA Journal} \bold{15}(10) 4982 -#' doi:10.2903/j.efsa.2017.4982 +#' \doi{10.2903/j.efsa.2017.4982} #' @keywords datasets #' @examples #' soil_scenario_data_EFSA_2017 -NULL +#' +#' waldo::compare(soil_scenario_data_EFSA_2017, soil_scenario_data_EFSA_2015) +"soil_scenario_data_EFSA_2017" diff --git a/build.log b/build.log deleted file mode 100644 index b1447b2..0000000 --- a/build.log +++ /dev/null @@ -1,15 +0,0 @@ -* checking for file ‘./DESCRIPTION’ ... OK -* preparing ‘pfm’: -* checking DESCRIPTION meta-information ... OK -* checking for LF line-endings in source and make files and shell scripts -* checking for empty or unneeded directories - NB: this package now depends on R (>= 3.5.0) - WARNING: Added dependency on R >= 3.5.0 because serialized objects in - serialize/load version 3 cannot be read in older versions of R. - File(s) containing such objects: - ‘pfm/data/EFSA_GW_interception_2014.RData’ - ‘pfm/data/EFSA_washoff_2017.RData’ -* building ‘pfm_0.6.0.tar.gz’ -Warning: invalid uid value replaced by that for user 'nobody' -Warning: invalid gid value replaced by that for user 'nobody' - diff --git a/data/EFSA_GW_interception_2014.RData b/data/EFSA_GW_interception_2014.RData index 14fded6..d533b53 100644 Binary files a/data/EFSA_GW_interception_2014.RData and b/data/EFSA_GW_interception_2014.RData differ diff --git a/data/EFSA_washoff_2017.RData b/data/EFSA_washoff_2017.RData index 699c0c0..18d043f 100644 Binary files a/data/EFSA_washoff_2017.RData and b/data/EFSA_washoff_2017.RData differ diff --git a/data/FOCUS_GW_scenarios_2012.RData b/data/FOCUS_GW_scenarios_2012.RData new file mode 100644 index 0000000..c8367fa Binary files /dev/null and b/data/FOCUS_GW_scenarios_2012.RData differ diff --git a/data/perc_runoff.RData b/data/perc_runoff.RData new file mode 100644 index 0000000..249820e Binary files /dev/null and b/data/perc_runoff.RData differ diff --git a/data/soil_scenario_data_EFSA_2015.RData b/data/soil_scenario_data_EFSA_2015.RData index b30076f..f2caeca 100644 Binary files a/data/soil_scenario_data_EFSA_2015.RData and b/data/soil_scenario_data_EFSA_2015.RData differ diff --git a/data/soil_scenario_data_EFSA_2017.RData b/data/soil_scenario_data_EFSA_2017.RData index ff8f045..56b0a8f 100644 Binary files a/data/soil_scenario_data_EFSA_2017.RData and b/data/soil_scenario_data_EFSA_2017.RData differ diff --git a/docs/404.html b/docs/404.html index acdca31..bc1b5ff 100644 --- a/docs/404.html +++ b/docs/404.html @@ -1,66 +1,27 @@ - - - - + + + + - Page not found (404) • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + - - - - -
-
- + +
+ + + - - -
+

Page not found (404)

@@ -110,31 +63,31 @@ Content not found. Please use links in the navbar.
+
-
-
-

Developed by Johannes Ranke.

+
+

+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown 2.0.7.

-
+
+ + - - diff --git a/docs/authors.html b/docs/authors.html index e4155eb..c65d25e 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -1,66 +1,12 @@ - - - - - - - -Authors • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Authors and Citation • pfm - + + - - - - -
-
-
- -
+
-
-

Authors

+
+
+

Authors

+
+ + +
  • +

    Johannes Ranke. Author, maintainer. +

    +
    • +
+
+
+

Citation

+
+
+ -
    -
  • -

    Johannes Ranke. Author, maintainer, copyright holder. -

    -
    • -
+

Johannes Ranke (2024). +pfm: Utilities for Pesticide Fate Modelling. +R package version 0.6.1, https://pkgdown.jrwb.de/pfm. +

+ 
@Manual{,
+  title = {pfm: Utilities for Pesticide Fate Modelling},
+  author = {{Johannes Ranke}},
+  year = {2024},
+  note = {R package version 0.6.1},
+  url = {https://pkgdown.jrwb.de/pfm},
+}
@@ -118,22 +70,20 @@ -
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/index.html b/docs/index.html index fd7cfd1..7658961 100644 --- a/docs/index.html +++ b/docs/index.html @@ -21,6 +21,8 @@ + +
-
-

-pfm

- +
+

pfm +

+

Build Status codecov

The R package pfm provides some utilities for fate modelling, including dealing with FOCUS pesticide fate modelling tools, (currently only TOXSWA cwa and out files), made available under the GNU public license.

-
-

-Installation

-

The easiest way to install the package is probably to use drat:

+
+

Installation +

+

The easiest way to install the package is probably to use drat:

-install.packages("drat")
-drat::addRepo("jranke")
-install.packages("pfm")
+install.packages("drat") +drat::addRepo("jranke") +install.packages("pfm")

Alternatively you can install the package using the devtools package. Using quick = TRUE skips docs, multiple-architecture builds, demos, and vignettes.

-library(devtools)
-install_github("jranke/pfm", quick = TRUE)
+library(devtools) +install_github("jranke/pfm", quick = TRUE)
-
-

-Use

-

Please refer to the reference.

+
+

Use +

+

Please refer to the reference.

-
-

-Examples

-

One recent nice example of the usage of this package is the visualisation of a time weighted average for a sawtooth curve obtained from several overlays of mkinfit predictions as shown here.

+
+

Examples +

+

One recent nice example of the usage of this package is the visualisation of a time weighted average for a sawtooth curve obtained from several overlays of mkinfit predictions as shown here.

-

Developed by Johannes Ranke.

+

+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown 2.0.7.

@@ -131,5 +133,7 @@ + + diff --git a/docs/pkgdown.css b/docs/pkgdown.css index 1273238..80ea5b8 100644 --- a/docs/pkgdown.css +++ b/docs/pkgdown.css @@ -56,8 +56,10 @@ img.icon { float: right; } -img { +/* Ensure in-page images don't run outside their container */ +.contents img { max-width: 100%; + height: auto; } /* Fix bug in bootstrap (only seen in firefox) */ @@ -78,11 +80,10 @@ dd { /* Section anchors ---------------------------------*/ a.anchor { - margin-left: -30px; - display:inline-block; - width: 30px; - height: 30px; - visibility: hidden; + display: none; + margin-left: 5px; + width: 20px; + height: 20px; background-image: url(./link.svg); background-repeat: no-repeat; @@ -90,17 +91,15 @@ a.anchor { background-position: center center; } -.hasAnchor:hover a.anchor { - visibility: visible; -} - -@media (max-width: 767px) { - .hasAnchor:hover a.anchor { - visibility: hidden; - } +h1:hover .anchor, +h2:hover .anchor, +h3:hover .anchor, +h4:hover .anchor, +h5:hover .anchor, +h6:hover .anchor { + display: inline-block; } - /* Fixes for fixed navbar --------------------------*/ .contents h1, .contents h2, .contents h3, .contents h4 { @@ -264,31 +263,26 @@ table { /* Syntax highlighting ---------------------------------------------------- */ -pre { - word-wrap: normal; - word-break: normal; - border: 1px solid #eee; -} - -pre, code { +pre, code, pre code { background-color: #f8f8f8; color: #333; } +pre, pre code { + white-space: pre-wrap; + word-break: break-all; + overflow-wrap: break-word; +} -pre code { - overflow: auto; - word-wrap: normal; - white-space: pre; +pre { + border: 1px solid #eee; } -pre .img { +pre .img, pre .r-plt { margin: 5px 0; } -pre .img img { +pre .img img, pre .r-plt img { background-color: #fff; - display: block; - height: auto; } code a, pre a { @@ -305,9 +299,8 @@ a.sourceLine:hover { .kw {color: #264D66;} /* keyword */ .co {color: #888888;} /* comment */ -.message { color: black; font-weight: bolder;} -.error { color: orange; font-weight: bolder;} -.warning { color: #6A0366; font-weight: bolder;} +.error {font-weight: bolder;} +.warning {font-weight: bolder;} /* Clipboard --------------------------*/ @@ -365,3 +358,27 @@ mark { content: ""; } } + +/* Section anchors --------------------------------- + Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71 +*/ + +div.csl-bib-body { } +div.csl-entry { + clear: both; +} +.hanging-indent div.csl-entry { + margin-left:2em; + text-indent:-2em; +} +div.csl-left-margin { + min-width:2em; + float:left; +} +div.csl-right-inline { + margin-left:2em; + padding-left:1em; +} +div.csl-indent { + margin-left: 2em; +} diff --git a/docs/pkgdown.js b/docs/pkgdown.js index 7e7048f..6f0eee4 100644 --- a/docs/pkgdown.js +++ b/docs/pkgdown.js @@ -80,7 +80,7 @@ $(document).ready(function() { var copyButton = ""; - $(".examples, div.sourceCode").addClass("hasCopyButton"); + $("div.sourceCode").addClass("hasCopyButton"); // Insert copy buttons: $(copyButton).prependTo(".hasCopyButton"); @@ -91,7 +91,7 @@ // Initialize clipboard: var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', { text: function(trigger) { - return trigger.parentNode.textContent; + return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, ""); } }); diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index cc57584..62c4837 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -1,8 +1,8 @@ -pandoc: 2.9.2.1 -pkgdown: 1.6.1 +pandoc: 3.1.1 +pkgdown: 2.0.7 pkgdown_sha: ~ articles: {} -last_built: 2021-11-18T23:17Z +last_built: 2024-01-31T12:15Z urls: reference: https://pkgdown.jrwb.de/pfm/reference article: https://pkgdown.jrwb.de/pfm/articles diff --git a/docs/reference/EFSA_GW_interception_2014.html b/docs/reference/EFSA_GW_interception_2014.html index d7ec108..8bc0b51 100644 --- a/docs/reference/EFSA_GW_interception_2014.html +++ b/docs/reference/EFSA_GW_interception_2014.html @@ -1,67 +1,12 @@ - - - - - - - -Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014 • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014 • pfm - - - - + + -
-
- -
- -
+

Subset of EFSA crop interception default values for groundwater modelling

@@ -112,82 +43,58 @@

Subset of EFSA crop interception default values for groundwater modelling

+
+ 
EFSA_GW_interception_2014
+
- -

Format

- +
+

Format

A matrix containing interception values, currently only for some selected crops

-

Source

- +
+
+

Source

European Food Safety Authority (2014) EFSA Guidance Document for evaluating laboratory and field dissipation studies to obtain DegT50 values of active substances of plant protection products and transformation products of these active substances in soil. EFSA Journal 12(5):3662, 37 pp., doi:10.2903/j.efsa.2014.3662

+
-

Examples

- 
if (FALSE) {
-  # This is the code that was used to define the data
-  bbch <- paste0(0:9, "x")
-  crops <- c(
-    "Beans (field + vegetable)",
-    "Peas",
-    "Summer oilseed rape", "Winter oilseed rape",
-    "Tomatoes",
-    "Spring cereals", "Winter cereals")
-  EFSA_GW_interception_2014 <- matrix(NA, length(crops), length(bbch),
-    dimnames = list(Crop = crops, BBCH = bbch))
-  EFSA_GW_interception_2014["Beans (field + vegetable)", ] <-
-    c(0, 0.25, rep(0.4, 2), rep(0.7, 5), 0.8)
-  EFSA_GW_interception_2014["Peas", ] <-
-    c(0, 0.35, rep(0.55, 2), rep(0.85, 5), 0.85)
-  EFSA_GW_interception_2014["Summer oilseed rape", ] <-
-    c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9)
-  EFSA_GW_interception_2014["Winter oilseed rape", ] <-
-    c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9)
-  EFSA_GW_interception_2014["Tomatoes", ] <-
-    c(0, 0.5, rep(0.7, 2), rep(0.8, 5), 0.5)
-  EFSA_GW_interception_2014["Spring cereals", ] <-
-    c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8)
-  EFSA_GW_interception_2014["Winter cereals", ] <-
-    c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8)
-  save(EFSA_GW_interception_2014,
-    file = "../data/EFSA_GW_interception_2014.RData")
-}
-EFSA_GW_interception_2014
#>                            BBCH
-#> Crop                        0x   1x   2x   3x   4x   5x   6x   7x   8x   9x
-#>   Beans (field + vegetable)  0 0.25 0.40 0.40 0.70 0.70 0.70 0.70 0.70 0.80
-#>   Peas                       0 0.35 0.55 0.55 0.85 0.85 0.85 0.85 0.85 0.85
-#>   Summer oilseed rape        0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90
-#>   Winter oilseed rape        0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90
-#>   Tomatoes                   0 0.50 0.70 0.70 0.80 0.80 0.80 0.80 0.80 0.50
-#>   Spring cereals             0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80
-#>   Winter cereals             0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80
+
+

Examples

+ 
EFSA_GW_interception_2014
+#>                            BBCH
+#> Crop                        0x   1x   2x   3x   4x   5x   6x   7x   8x   9x
+#>   Beans (field + vegetable)  0 0.25 0.40 0.40 0.70 0.70 0.70 0.70 0.70 0.80
+#>   Peas                       0 0.35 0.55 0.55 0.85 0.85 0.85 0.85 0.85 0.85
+#>   Summer oilseed rape        0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90
+#>   Winter oilseed rape        0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90
+#>   Tomatoes                   0 0.50 0.70 0.70 0.80 0.80 0.80 0.80 0.80 0.50
+#>   Spring cereals             0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80
+#>   Winter cereals             0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/EFSA_washoff_2017.html b/docs/reference/EFSA_washoff_2017.html index abe0b24..8c95681 100644 --- a/docs/reference/EFSA_washoff_2017.html +++ b/docs/reference/EFSA_washoff_2017.html @@ -1,67 +1,12 @@ - - - - - - - -Subset of EFSA crop washoff default values — EFSA_washoff_2017 • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Subset of EFSA crop washoff default values — EFSA_washoff_2017 • pfm - - - - + + -
-
- -
- -
+

Subset of EFSA crop washoff default values

@@ -112,82 +43,58 @@

Subset of EFSA crop washoff default values

+
+ 
EFSA_washoff_2017
+
- -

Format

- +
+

Format

A matrix containing wash-off factors, currently only for some selected crops

-

Source

- +
+
+

Source

European Food Safety Authority (2017) EFSA guidance document for predicting environmental concentrations of active substances of plant protection products and transformation products of these active substances in soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982

+
-

Examples

- 
if (FALSE) {
-  # This is the code that was used to define the data
-  bbch <- paste0(0:9, "x")
-  crops <- c(
-    "Beans (field + vegetable)",
-    "Peas",
-    "Summer oilseed rape", "Winter oilseed rape",
-    "Tomatoes",
-    "Spring cereals", "Winter cereals")
-  EFSA_washoff_2017 <- matrix(NA, length(crops), length(bbch),
-    dimnames = list(Crop = crops, BBCH = bbch))
-  EFSA_washoff_2017["Beans (field + vegetable)", ] <-
-    c(NA, 0.6, rep(0.75, 2), rep(0.8, 5), 0.35)
-  EFSA_washoff_2017["Peas", ] <-
-    c(NA, 0.4, rep(0.6, 2), rep(0.65, 5), 0.35)
-  EFSA_washoff_2017["Summer oilseed rape", ] <-
-    c(NA, 0.4, rep(0.5, 2), rep(0.6, 5), 0.5)
-  EFSA_washoff_2017["Winter oilseed rape", ] <-
-    c(NA, 0.1, rep(0.4, 2), rep(0.55, 5), 0.3)
-  EFSA_washoff_2017["Tomatoes", ] <-
-    c(NA, 0.55, rep(0.75, 2), rep(0.7, 5), 0.35)
-  EFSA_washoff_2017["Spring cereals", ] <-
-    c(NA, 0.4, 0.5, 0.5, rep(0.65, 3), rep(0.65, 2), 0.55)
-  EFSA_washoff_2017["Winter cereals", ] <-
-    c(NA, 0.1, 0.4, 0.6, rep(0.55, 3), rep(0.6, 2), 0.4)
-  save(EFSA_washoff_2017,
-    file = "../data/EFSA_washoff_2017.RData")
-}
-EFSA_washoff_2017
#>                            BBCH
-#> Crop                        0x   1x   2x   3x   4x   5x   6x   7x   8x   9x
-#>   Beans (field + vegetable) NA 0.60 0.75 0.75 0.80 0.80 0.80 0.80 0.80 0.35
-#>   Peas                      NA 0.40 0.60 0.60 0.65 0.65 0.65 0.65 0.65 0.35
-#>   Summer oilseed rape       NA 0.40 0.50 0.50 0.60 0.60 0.60 0.60 0.60 0.50
-#>   Winter oilseed rape       NA 0.10 0.40 0.40 0.55 0.55 0.55 0.55 0.55 0.30
-#>   Tomatoes                  NA 0.55 0.75 0.75 0.70 0.70 0.70 0.70 0.70 0.35
-#>   Spring cereals            NA 0.40 0.50 0.50 0.65 0.65 0.65 0.65 0.65 0.55
-#>   Winter cereals            NA 0.10 0.40 0.60 0.55 0.55 0.55 0.60 0.60 0.40
+
+

Examples

+ 
EFSA_washoff_2017
+#>                            BBCH
+#> Crop                        0x   1x   2x   3x   4x   5x   6x   7x   8x   9x
+#>   Beans (field + vegetable) NA 0.60 0.75 0.75 0.80 0.80 0.80 0.80 0.80 0.35
+#>   Peas                      NA 0.40 0.60 0.60 0.65 0.65 0.65 0.65 0.65 0.35
+#>   Summer oilseed rape       NA 0.40 0.50 0.50 0.60 0.60 0.60 0.60 0.60 0.50
+#>   Winter oilseed rape       NA 0.10 0.40 0.40 0.55 0.55 0.55 0.55 0.55 0.30
+#>   Tomatoes                  NA 0.55 0.75 0.75 0.70 0.70 0.70 0.70 0.70 0.35
+#>   Spring cereals            NA 0.40 0.50 0.50 0.65 0.65 0.65 0.65 0.65 0.55
+#>   Winter cereals            NA 0.10 0.40 0.60 0.55 0.55 0.55 0.60 0.60 0.40
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/FOCUS_GW_scenarios_2012.html b/docs/reference/FOCUS_GW_scenarios_2012.html index 8b55d14..75c3ff4 100644 --- a/docs/reference/FOCUS_GW_scenarios_2012.html +++ b/docs/reference/FOCUS_GW_scenarios_2012.html @@ -1,68 +1,13 @@ - - - - - - - -A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfm - - - - + + -
-
- -
- -
+

A very small subset of the FOCUS Groundwater scenario definitions

@@ -114,104 +45,107 @@ soil definitions are from page 46ff. from FOCUS (2012)." /> soil definitions are from page 46ff. from FOCUS (2012).

- 
FOCUS_GW_scenarios_2012
- - -

Format

+
+ 
FOCUS_GW_scenarios_2012
+
+
+

Format

An object of class list of length 2.

-

References

- +
+
+

References

FOCUS (2012) Generic guidance for Tier 1 FOCUS ground water assessments. Version 2.1. FOrum for the Co-ordination of pesticde fate models and their USe. http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf

+
-

Examples

- 
FOCUS_GW_scenarios_2012
#> $names
-#>            Cha            Ham            Jok            Kre            Oke 
-#>   "Châteaudun"      "Hamburg"    "Jokioinen" "Kremsmünster"   "Okehampton" 
-#>            Pia            Por            Sev            Thi 
-#>     "Piacenza"        "Porto"      "Sevilla"        "Thiva" 
-#> 
-#> $soils
-#>    location horizon number pH_H2O perc_clay perc_oc rel_deg
-#> 1       Cha      Ap      1    8.0      30.0    1.39     1.0
-#> 2       Cha      B1      2    8.1      31.0    0.93     0.5
-#> 3       Cha      B2      3    8.2      25.0    0.70     0.5
-#> 4       Cha   II C1      4    8.5      26.0    0.30     0.3
-#> 5       Cha   II C1      5    8.5      26.0    0.30     0.0
-#> 6       Cha   II C2      6    8.5      24.0    0.27     0.0
-#> 7       Cha       M      7    8.3      31.0    0.21     0.0
-#> 8       Ham      Ap      1    6.4       7.2    1.50     1.0
-#> 9       Ham     BvI      2    5.6       6.7    1.00     0.5
-#> 10      Ham    BvII      3    5.6       0.9    0.20     0.3
-#> 11      Ham   Bv/Cv      4    5.7       0.0    0.00     0.3
-#> 12      Ham      Cv      5    5.5       0.0    0.00     0.3
-#> 13      Ham      Cv      6    5.5       0.0    0.00     0.0
-#> 14      Jok      Ap      1    6.2       3.6    4.06     1.0
-#> 15      Jok      Bs      2    5.6       1.8    0.84     0.5
-#> 16      Jok     BC1      3    5.4       1.2    0.36     0.3
-#> 17      Jok     BC2      4    5.4       1.7    0.29     0.3
-#> 18      Jok     BC2      5    5.4       1.7    0.29     0.0
-#> 19      Jok      Cg      6    5.3       1.9    0.21     0.0
-#> 20      Kre    <NA>      1    7.7      14.0    3.60     1.0
-#> 21      Kre    <NA>      2    7.0      25.0    1.00     0.5
-#> 22      Kre    <NA>      3    7.1      27.0    0.50     0.5
-#> 23      Kre    <NA>      4    7.1      27.0    0.50     0.3
-#> 24      Kre    <NA>      5    7.1      27.0    0.50     0.0
-#> 25      Oke       A      1    5.8      18.0    2.20     1.0
-#> 26      Oke     Bw1      2    6.3      17.0    0.70     0.5
-#> 27      Oke      BC      3    6.5      14.0    0.40     0.3
-#> 28      Oke       C      4    6.6       9.0    0.10     0.3
-#> 29      Oke       C      5    6.6       9.0    0.10     0.0
-#> 30      Pia      Ap      1    7.0      15.0    1.26     1.0
-#> 31      Pia      Ap      2    7.0      15.0    1.26     0.5
-#> 32      Pia      Bw      3    6.3       7.0    0.47     0.5
-#> 33      Pia      Bw      4    6.3       7.0    0.47     0.3
-#> 34      Pia      2C      5    6.4       0.0    0.00     0.3
-#> 35      Pia      2C      6    6.4       0.0    0.00     0.0
-#> 36      Por    <NA>      1    4.9      10.0    1.42     1.0
-#> 37      Por    <NA>      2    4.8       8.0    0.78     0.5
-#> 38      Por    <NA>      3    4.8       8.0    0.78     0.3
-#> 39      Por    <NA>      4    4.8       8.0    0.78     0.0
-#> 40      Sev    <NA>      1    7.3      14.0    0.93     1.0
-#> 41      Sev    <NA>      2    7.3      13.0    0.93     1.0
-#> 42      Sev    <NA>      3    7.8      15.0    0.70     0.5
-#> 43      Sev    <NA>      4    8.1      16.0    0.58     0.3
-#> 44      Sev    <NA>      5    8.1      16.0    0.58     0.0
-#> 45      Sev    <NA>      6    8.2      22.0    0.49     0.0
-#> 46      Thi     Ap1      1    7.7      25.3    0.74     1.0
-#> 47      Thi     Ap2      2    7.7      25.3    0.74     0.5
-#> 48      Thi      Bw      3    7.8      29.6    0.57     0.5
-#> 49      Thi      Bw      4    7.8      31.9    0.31     0.3
-#> 50      Thi     Ck1      5    7.8      32.9    0.18     0.3
-#> 51      Thi     Ck1      6    7.8      32.9    0.18     0.0
-#>
+
+

Examples

+ 
FOCUS_GW_scenarios_2012
+#> $names
+#>            Cha            Ham            Jok            Kre            Oke 
+#>   "Châteaudun"      "Hamburg"    "Jokioinen" "Kremsmünster"   "Okehampton" 
+#>            Pia            Por            Sev            Thi 
+#>     "Piacenza"        "Porto"      "Sevilla"        "Thiva" 
+#> 
+#> $soils
+#>    location horizon number pH_H2O perc_clay perc_oc rel_deg
+#> 1       Cha      Ap      1    8.0      30.0    1.39     1.0
+#> 2       Cha      B1      2    8.1      31.0    0.93     0.5
+#> 3       Cha      B2      3    8.2      25.0    0.70     0.5
+#> 4       Cha   II C1      4    8.5      26.0    0.30     0.3
+#> 5       Cha   II C1      5    8.5      26.0    0.30     0.0
+#> 6       Cha   II C2      6    8.5      24.0    0.27     0.0
+#> 7       Cha       M      7    8.3      31.0    0.21     0.0
+#> 8       Ham      Ap      1    6.4       7.2    1.50     1.0
+#> 9       Ham     BvI      2    5.6       6.7    1.00     0.5
+#> 10      Ham    BvII      3    5.6       0.9    0.20     0.3
+#> 11      Ham   Bv/Cv      4    5.7       0.0    0.00     0.3
+#> 12      Ham      Cv      5    5.5       0.0    0.00     0.3
+#> 13      Ham      Cv      6    5.5       0.0    0.00     0.0
+#> 14      Jok      Ap      1    6.2       3.6    4.06     1.0
+#> 15      Jok      Bs      2    5.6       1.8    0.84     0.5
+#> 16      Jok     BC1      3    5.4       1.2    0.36     0.3
+#> 17      Jok     BC2      4    5.4       1.7    0.29     0.3
+#> 18      Jok     BC2      5    5.4       1.7    0.29     0.0
+#> 19      Jok      Cg      6    5.3       1.9    0.21     0.0
+#> 20      Kre    <NA>      1    7.7      14.0    3.60     1.0
+#> 21      Kre    <NA>      2    7.0      25.0    1.00     0.5
+#> 22      Kre    <NA>      3    7.1      27.0    0.50     0.5
+#> 23      Kre    <NA>      4    7.1      27.0    0.50     0.3
+#> 24      Kre    <NA>      5    7.1      27.0    0.50     0.0
+#> 25      Oke       A      1    5.8      18.0    2.20     1.0
+#> 26      Oke     Bw1      2    6.3      17.0    0.70     0.5
+#> 27      Oke      BC      3    6.5      14.0    0.40     0.3
+#> 28      Oke       C      4    6.6       9.0    0.10     0.3
+#> 29      Oke       C      5    6.6       9.0    0.10     0.0
+#> 30      Pia      Ap      1    7.0      15.0    1.26     1.0
+#> 31      Pia      Ap      2    7.0      15.0    1.26     0.5
+#> 32      Pia      Bw      3    6.3       7.0    0.47     0.5
+#> 33      Pia      Bw      4    6.3       7.0    0.47     0.3
+#> 34      Pia      2C      5    6.4       0.0    0.00     0.3
+#> 35      Pia      2C      6    6.4       0.0    0.00     0.0
+#> 36      Por    <NA>      1    4.9      10.0    1.42     1.0
+#> 37      Por    <NA>      2    4.8       8.0    0.78     0.5
+#> 38      Por    <NA>      3    4.8       8.0    0.78     0.3
+#> 39      Por    <NA>      4    4.8       8.0    0.78     0.0
+#> 40      Sev    <NA>      1    7.3      14.0    0.93     1.0
+#> 41      Sev    <NA>      2    7.3      13.0    0.93     1.0
+#> 42      Sev    <NA>      3    7.8      15.0    0.70     0.5
+#> 43      Sev    <NA>      4    8.1      16.0    0.58     0.3
+#> 44      Sev    <NA>      5    8.1      16.0    0.58     0.0
+#> 45      Sev    <NA>      6    8.2      22.0    0.49     0.0
+#> 46      Thi     Ap1      1    7.7      25.3    0.74     1.0
+#> 47      Thi     Ap2      2    7.7      25.3    0.74     0.5
+#> 48      Thi      Bw      3    7.8      29.6    0.57     0.5
+#> 49      Thi      Bw      4    7.8      31.9    0.31     0.3
+#> 50      Thi     Ck1      5    7.8      32.9    0.18     0.3
+#> 51      Thi     Ck1      6    7.8      32.9    0.18     0.0
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/FOCUS_Step_12_scenarios.html b/docs/reference/FOCUS_Step_12_scenarios.html index bbfb592..0216e4e 100644 --- a/docs/reference/FOCUS_Step_12_scenarios.html +++ b/docs/reference/FOCUS_Step_12_scenarios.html @@ -1,68 +1,13 @@ - - - - - - - -Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios • pfm - - - - + + -
-
- -
- -
+

Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator

@@ -115,210 +46,78 @@ The text file is not included in the package as its licence is not clear.

- -

Format

- +
+

Format

A list containing the scenario names in a character vector called 'names', the drift percentiles in a matrix called 'drift', interception percentages in a matrix called 'interception' and the runoff/drainage percentages for Step 2 calculations in a matrix called 'rd'.

+
-

Examples

- 

-if (FALSE) {
-  # This is the code that was used to extract the data
-  scenario_path <- "inst/extdata/FOCUS_Step_12_scenarios.txt"
-  scenarios <- readLines(scenario_path)[9:38]
-  FOCUS_Step_12_scenarios <- list()
-  sce <- read.table(text = scenarios, sep = "\t", header = TRUE, check.names = FALSE,
-    stringsAsFactors = FALSE)
-  FOCUS_Step_12_scenarios$names = sce$Crop
-  rownames(sce) <- sce$Crop
-  FOCUS_Step_12_scenarios$drift = sce[, 3:11]
-  FOCUS_Step_12_scenarios$interception = sce[, 12:15]
-  sce_2 <- readLines(scenario_path)[41:46]
-  rd <- read.table(text = sce_2, sep = "\t")[1:2]
-  rd_mat <- matrix(rd$V2, nrow = 3, byrow = FALSE)
-  dimnames(rd_mat) = list(Time = c("Oct-Feb", "Mar-May", "Jun-Sep"),
-                          Region = c("North", "South"))
-  FOCUS_Step_12_scenarios$rd = rd_mat
-  save(FOCUS_Step_12_scenarios, file = "data/FOCUS_Step_12_scenarios.RData")
-}
-
-# And this is the resulting data
-FOCUS_Step_12_scenarios
#> $names
-#>  [1] "cereals, spring"                  "cereals, winter"                 
-#>  [3] "citrus"                           "cotton"                          
-#>  [5] "field beans"                      "grass / alfalfa"                 
-#>  [7] "hops"                             "legumes"                         
-#>  [9] "maize"                            "oil seed rape, spring"           
-#> [11] "oil seed rape, winter"            "olives"                          
-#> [13] "pome / stone fruit, early applns" "pome / stone fruit, late applns" 
-#> [15] "potatoes"                         "soybeans"                        
-#> [17] "sugar beets"                      "sunflowers"                      
-#> [19] "tobacco"                          "vegetables, bulb"                
-#> [21] "vegetables, fruiting"             "vegetables, leafy"               
-#> [23] "vegetables, root"                 "vines, early applns"             
-#> [25] "vines, late applns"               "appln, aerial"                   
-#> [27] "appln, hand (crop < 50 cm)"       "appln, hand (crop > 50 cm)"      
-#> [29] "no drift (incorp or seed trtmt)" 
-#> 
-#> $drift
-#>                                       1      2      3      4      5      6
-#> cereals, spring                   2.759  2.438  2.024  1.862  1.794  1.631
-#> cereals, winter                   2.759  2.438  2.024  1.862  1.794  1.631
-#> citrus                           15.725 12.129 11.011 10.124  9.743  9.204
-#> cotton                            2.759  2.438  2.024  1.862  1.794  1.631
-#> field beans                       2.759  2.438  2.024  1.862  1.794  1.631
-#> grass / alfalfa                   2.759  2.438  2.024  1.862  1.794  1.631
-#> hops                             19.326 17.723 15.928 15.378 15.114 14.902
-#> legumes                           2.759  2.438  2.024  1.862  1.794  1.631
-#> maize                             2.759  2.438  2.024  1.862  1.794  1.631
-#> oil seed rape, spring             2.759  2.438  2.024  1.862  1.794  1.631
-#> oil seed rape, winter             2.759  2.438  2.024  1.862  1.794  1.631
-#> olives                           15.725 12.129 11.011 10.124  9.743  9.204
-#> pome / stone fruit, early applns 29.197 25.531 23.960 23.603 23.116 22.760
-#> pome / stone fruit, late applns  15.725 12.129 11.011 10.124  9.743  9.204
-#> potatoes                          2.759  2.438  2.024  1.862  1.794  1.631
-#> soybeans                          2.759  2.438  2.024  1.862  1.794  1.631
-#> sugar beets                       2.759  2.438  2.024  1.862  1.794  1.631
-#> sunflowers                        2.759  2.438  2.024  1.862  1.794  1.631
-#> tobacco                           2.759  2.438  2.024  1.862  1.794  1.631
-#> vegetables, bulb                  2.759  2.438  2.024  1.862  1.794  1.631
-#> vegetables, fruiting              2.759  2.438  2.024  1.862  1.794  1.631
-#> vegetables, leafy                 2.759  2.438  2.024  1.862  1.794  1.631
-#> vegetables, root                  2.759  2.438  2.024  1.862  1.794  1.631
-#> vines, early applns               2.699  2.496  2.546  2.499  2.398  2.336
-#> vines, late applns                8.028  7.119  6.898  6.631  6.636  6.431
-#> appln, aerial                    33.200 33.200 33.200 33.200 33.200 33.200
-#> appln, hand (crop < 50 cm)        2.759  2.438  2.024  1.862  1.794  1.631
-#> appln, hand (crop > 50 cm)        8.028  7.119  6.898  6.631  6.636  6.431
-#> no drift (incorp or seed trtmt)   0.000  0.000  0.000  0.000  0.000  0.000
-#>                                       7      8     >8
-#> cereals, spring                   1.578  1.512  1.512
-#> cereals, winter                   1.578  1.512  1.512
-#> citrus                            9.102  8.656  8.656
-#> cotton                            1.578  1.512  1.512
-#> field beans                       1.578  1.512  1.512
-#> grass / alfalfa                   1.578  1.512  1.512
-#> hops                             14.628 13.520 13.520
-#> legumes                           1.578  1.512  1.512
-#> maize                             1.578  1.512  1.512
-#> oil seed rape, spring             1.578  1.512  1.512
-#> oil seed rape, winter             1.578  1.512  1.512
-#> olives                            9.102  8.656  8.656
-#> pome / stone fruit, early applns 22.690 22.241 22.241
-#> pome / stone fruit, late applns   9.102  8.656  8.656
-#> potatoes                          1.578  1.512  1.512
-#> soybeans                          1.578  1.512  1.512
-#> sugar beets                       1.578  1.512  1.512
-#> sunflowers                        1.578  1.512  1.512
-#> tobacco                           1.578  1.512  1.512
-#> vegetables, bulb                  1.578  1.512  1.512
-#> vegetables, fruiting              1.578  1.512  1.512
-#> vegetables, leafy                 1.578  1.512  1.512
-#> vegetables, root                  1.578  1.512  1.512
-#> vines, early applns               2.283  2.265  2.265
-#> vines, late applns                6.227  6.173  6.173
-#> appln, aerial                    33.200 33.200 33.200
-#> appln, hand (crop < 50 cm)        1.578  1.512  1.512
-#> appln, hand (crop > 50 cm)        6.227  6.173  6.173
-#> no drift (incorp or seed trtmt)   0.000  0.000  0.000
-#> 
-#> $interception
-#>                                  no interception minimal crop cover
-#> cereals, spring                                0               0.00
-#> cereals, winter                                0               0.00
-#> citrus                                         0               0.80
-#> cotton                                         0               0.30
-#> field beans                                    0               0.25
-#> grass / alfalfa                                0               0.40
-#> hops                                           0               0.20
-#> legumes                                        0               0.25
-#> maize                                          0               0.25
-#> oil seed rape, spring                          0               0.40
-#> oil seed rape, winter                          0               0.40
-#> olives                                         0               0.70
-#> pome / stone fruit, early applns               0               0.20
-#> pome / stone fruit, late applns                0               0.20
-#> potatoes                                       0               0.15
-#> soybeans                                       0               0.20
-#> sugar beets                                    0               0.20
-#> sunflowers                                     0               0.20
-#> tobacco                                        0               0.20
-#> vegetables, bulb                               0               0.10
-#> vegetables, fruiting                           0               0.25
-#> vegetables, leafy                              0               0.25
-#> vegetables, root                               0               0.25
-#> vines, early applns                            0               0.40
-#> vines, late applns                             0               0.40
-#> appln, aerial                                  0               0.20
-#> appln, hand (crop < 50 cm)                     0               0.20
-#> appln, hand (crop > 50 cm)                     0               0.20
-#> no drift (incorp or seed trtmt)                0               0.00
-#>                                  average crop cover full canopy
-#> cereals, spring                                0.20        0.70
-#> cereals, winter                                0.20        0.70
-#> citrus                                         0.80        0.80
-#> cotton                                         0.60        0.75
-#> field beans                                    0.40        0.70
-#> grass / alfalfa                                0.60        0.75
-#> hops                                           0.50        0.70
-#> legumes                                        0.50        0.70
-#> maize                                          0.50        0.75
-#> oil seed rape, spring                          0.70        0.75
-#> oil seed rape, winter                          0.70        0.75
-#> olives                                         0.70        0.70
-#> pome / stone fruit, early applns               0.40        0.65
-#> pome / stone fruit, late applns                0.40        0.65
-#> potatoes                                       0.50        0.70
-#> soybeans                                       0.50        0.75
-#> sugar beets                                    0.70        0.75
-#> sunflowers                                     0.50        0.75
-#> tobacco                                        0.70        0.75
-#> vegetables, bulb                               0.25        0.40
-#> vegetables, fruiting                           0.50        0.70
-#> vegetables, leafy                              0.40        0.70
-#> vegetables, root                               0.50        0.70
-#> vines, early applns                            0.50        0.60
-#> vines, late applns                             0.50        0.60
-#> appln, aerial                                  0.50        0.70
-#> appln, hand (crop < 50 cm)                     0.50        0.70
-#> appln, hand (crop > 50 cm)                     0.50        0.70
-#> no drift (incorp or seed trtmt)                0.00        0.00
-#> 
-#> $rd
-#>          Region
-#> Time      North South
-#>   Oct-Feb     5     4
-#>   Mar-May     2     4
-#>   Jun-Sep     2     3
-#>
+
+

Examples

+ 

+# \dontrun{
+  # This is the code that was used to extract the data
+  scenario_path <- "inst/extdata/FOCUS_Step_12_scenarios.txt"
+  scenarios <- readLines(scenario_path)[9:38]
+#> Warning: cannot open file 'inst/extdata/FOCUS_Step_12_scenarios.txt': No such file or directory
+#> Error in file(con, "r"): cannot open the connection
+  FOCUS_Step_12_scenarios <- list()
+  sce <- read.table(text = scenarios, sep = "\t", header = TRUE, check.names = FALSE,
+    stringsAsFactors = FALSE)
+#> Error in eval(expr, envir, enclos): object 'scenarios' not found
+  FOCUS_Step_12_scenarios$names = sce$Crop
+#> Error in eval(expr, envir, enclos): object 'sce' not found
+  rownames(sce) <- sce$Crop
+#> Error in eval(expr, envir, enclos): object 'sce' not found
+  FOCUS_Step_12_scenarios$drift = sce[, 3:11]
+#> Error in eval(expr, envir, enclos): object 'sce' not found
+  FOCUS_Step_12_scenarios$interception = sce[, 12:15]
+#> Error in eval(expr, envir, enclos): object 'sce' not found
+  sce_2 <- readLines(scenario_path)[41:46]
+#> Warning: cannot open file 'inst/extdata/FOCUS_Step_12_scenarios.txt': No such file or directory
+#> Error in file(con, "r"): cannot open the connection
+  rd <- read.table(text = sce_2, sep = "\t")[1:2]
+#> Error in eval(expr, envir, enclos): object 'sce_2' not found
+  rd_mat <- matrix(rd$V2, nrow = 3, byrow = FALSE)
+#> Error in eval(expr, envir, enclos): object 'rd' not found
+  dimnames(rd_mat) = list(Time = c("Oct-Feb", "Mar-May", "Jun-Sep"),
+                          Region = c("North", "South"))
+#> Error: object 'rd_mat' not found
+  FOCUS_Step_12_scenarios$rd = rd_mat
+#> Error in eval(expr, envir, enclos): object 'rd_mat' not found
+  save(FOCUS_Step_12_scenarios, file = "data/FOCUS_Step_12_scenarios.RData")
+#> Warning: cannot open compressed file 'data/FOCUS_Step_12_scenarios.RData', probable reason 'No such file or directory'
+#> Error in gzfile(file, "wb"): cannot open the connection
+# }
+
+# And this is the resulting data
+FOCUS_Step_12_scenarios
+#> list()
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/FOMC_actual_twa.html b/docs/reference/FOMC_actual_twa.html index a365556..1fa9b97 100644 --- a/docs/reference/FOMC_actual_twa.html +++ b/docs/reference/FOMC_actual_twa.html @@ -1,64 +1,12 @@ - - - - - - - -Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa • pfm - - - - + + -
-
- -
- -
+

Actual and maximum moving window time average concentrations for FOMC kinetics

@@ -109,79 +43,77 @@

Actual and maximum moving window time average concentrations for FOMC kinetics

- 
FOMC_actual_twa(
-  alpha = 1.0001,
-  beta = 10,
-  times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100)
-)
- -

Arguments

- - - - - - - - - - - - - - -
alpha

Parameter of the FOMC model

beta

Parameter of the FOMC model

times

The output times, and window sizes for time weighted average concentrations

- -

Source

+
+ 
FOMC_actual_twa(
+  alpha = 1.0001,
+  beta = 10,
+  times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100)
+)
+
+
+

Source

FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, 18 December 2014, p. 251

+
+
+

Arguments

+
alpha
+

Parameter of the FOMC model

-

Examples

- 
FOMC_actual_twa(alpha = 1.0001, beta = 10)
#>         actual       twa
-#> 0   1.00000000       NaN
-#> 1   0.90908224 0.9530973
-#> 2   0.83331814 0.9115995
-#> 4   0.71426168 0.8411664
-#> 7   0.58820408 0.7580202
-#> 14  0.41663019 0.6253074
-#> 21  0.32254415 0.5387324
-#> 28  0.26312277 0.4767543
-#> 42  0.19227599 0.3925054
-#> 50  0.16663681 0.3583198
-#> 100 0.09088729 0.2397608
-
- +

Author

Johannes Ranke

+
+ +
+

Examples

+ 
FOMC_actual_twa(alpha = 1.0001, beta = 10)
+#>         actual       twa
+#> 0   1.00000000       NaN
+#> 1   0.90908224 0.9530973
+#> 2   0.83331814 0.9115995
+#> 4   0.71426168 0.8411664
+#> 7   0.58820408 0.7580202
+#> 14  0.41663019 0.6253074
+#> 21  0.32254415 0.5387324
+#> 28  0.26312277 0.4767543
+#> 42  0.19227599 0.3925054
+#> 50  0.16663681 0.3583198
+#> 100 0.09088729 0.2397608
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/GUS.html b/docs/reference/GUS.html index e371c1a..dfe3b80 100644 --- a/docs/reference/GUS.html +++ b/docs/reference/GUS.html @@ -1,66 +1,14 @@ - - - - - - - -Groundwater ubiquity score based on Gustafson (1989) — GUS • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Groundwater ubiquity score based on Gustafson (1989) — GUS • pfm - - - - - - - - - - - - - - + + -
-
- -
- -
+

Groundwater ubiquity score based on Gustafson (1989)

@@ -113,139 +47,136 @@ the following equation $$GUS = \log_{10} DT50_{soil} (4 - \log_{10} K_{oc})$$

- 
GUS(...)
-
-# S3 method for numeric
-GUS(DT50, Koc, ...)
-
-# S3 method for chent
-GUS(
-  chent,
-  degradation_value = "DT50ref",
-  lab_field = "laboratory",
-  redox = "aerobic",
-  sorption_value = "Kfoc",
-  degradation_aggregator = geomean,
-  sorption_aggregator = geomean,
-  ...
-)
-
-# S3 method for GUS_result
-print(x, ..., digits = 1)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
...

Included in the generic to allow for further arguments later. Therefore -this also had to be added to the specific methods.

DT50

Half-life of the chemical in soil. Should be a field +

+ 
GUS(...)
+
+# S3 method for numeric
+GUS(DT50, Koc, ...)
+
+# S3 method for chent
+GUS(
+  chent,
+  degradation_value = "DT50ref",
+  lab_field = "laboratory",
+  redox = "aerobic",
+  sorption_value = "Kfoc",
+  degradation_aggregator = geomean,
+  sorption_aggregator = geomean,
+  ...
+)
+
+# S3 method for GUS_result
+print(x, ..., digits = 1)
+
+ +
+

Arguments

+
...
+

Included in the generic to allow for further arguments later. Therefore +this also had to be added to the specific methods.

+ + +
DT50
+

Half-life of the chemical in soil. Should be a field half-life according to Gustafson (1989). However, leaching to the sub-soil can not completely be excluded in field dissipation experiments and Gustafson did not refer to any normalisation procedure, but says the field study should -be conducted under use conditions.

Koc

The sorption constant normalised to organic carbon. Gustafson +be conducted under use conditions.

+ + +
Koc
+

The sorption constant normalised to organic carbon. Gustafson does not mention the nonlinearity of the sorption constant commonly found and usually described by Freundlich sorption, therefore it is unclear at which reference concentration the Koc should be observed -(and if the reference concentration would be in soil or in porewater).

chent

If a chent is given with appropriate information present in its -chyaml field, this information is used, with defaults specified below.

degradation_value

Which of the available degradation values should -be used?

lab_field

Should laboratory or field half-lives be used? This +(and if the reference concentration would be in soil or in porewater).

+ + +
chent
+

If a chent is given with appropriate information present in its +chyaml field, this information is used, with defaults specified below.

+ + +
degradation_value
+

Which of the available degradation values should +be used?

+ + +
lab_field
+

Should laboratory or field half-lives be used? This defaults to lab in this implementation, in order to avoid double-accounting for mobility. If comparability with the original GUS values given by Gustafson (1989) is desired, non-normalised first-order -field half-lives obtained under actual use conditions should be used.

redox

Aerobic or anaerobic degradation data

sorption_value

Which of the available sorption values should be used? +field half-lives obtained under actual use conditions should be used.

+ + +
redox
+

Aerobic or anaerobic degradation data

+ + +
sorption_value
+

Which of the available sorption values should be used? Defaults to Kfoc as this is what is generally available from the European pesticide peer review process. These values generally use a reference concentration of 1 mg/L in porewater, that means they would be expected to -be Koc values at a concentration of 1 mg/L in the water phase.

degradation_aggregator

Function for aggregating half-lives

sorption_aggregator

Function for aggregation Koc values

x

An object of class GUS_result to be printed

digits

The number of digits used in the print method

- -

Value

- -

A list with the DT50 and Koc used as well as the resulting score - of class GUS_result

-

References

+be Koc values at a concentration of 1 mg/L in the water phase.

+ + +
degradation_aggregator
+

Function for aggregating half-lives

+ + +
sorption_aggregator
+

Function for aggregation Koc values

+ +
x
+

An object of class GUS_result to be printed

+ + +
digits
+

The number of digits used in the print method

+ +
+
+

Value

+ + +

A list with the DT50 and Koc used as well as the resulting score + of class GUS_result

+
+
+

References

Gustafson, David I. (1989) Groundwater ubiquity score: a simple method for assessing pesticide leachability. Environmental toxicology and chemistry 8(4) 339–57.

- -
- +

Author

Johannes Ranke

+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_FOMC_accu_rel.html b/docs/reference/PEC_FOMC_accu_rel.html index e4d9bf4..ebe531f 100644 --- a/docs/reference/PEC_FOMC_accu_rel.html +++ b/docs/reference/PEC_FOMC_accu_rel.html @@ -1,61 +1,12 @@ - - - - - - - -Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel • pfm - - - - + + -
-
- -
- -
+

Get the relative accumulation of an FOMC model over multiples of an interval

@@ -104,64 +40,55 @@
-

Get the relative accumulation of an FOMC model over multiples of an interval

-
- 
PEC_FOMC_accu_rel(n, interval, FOMC)
- -

Arguments

- - - - - - - - - - - - - - -
n

number of applications

interval

Time between applications

FOMC

Named numeric vector containing the FOMC parameters alpha and beta

- -

Value

+
+ 
PEC_FOMC_accu_rel(n, interval, FOMC)
+
-

A numeric vector containing all n accumulation factors for the n applications

+
+

Arguments

+
n
+

number of applications

+ + +
interval
+

Time between applications

+ + +
FOMC
+

Named numeric vector containing the FOMC parameters alpha and beta

+ +
+
+

Value

-
-
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_soil.html b/docs/reference/PEC_soil.html index 3e405a5..f7e1da5 100644 --- a/docs/reference/PEC_soil.html +++ b/docs/reference/PEC_soil.html @@ -1,68 +1,16 @@ - - - - - - - -Calculate predicted environmental concentrations in soil — PEC_soil • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate predicted environmental concentrations in soil — PEC_soil • pfm - - - - - - - - - - - - - - + + -
-
- -
- -
+

Calculate predicted environmental concentrations in soil

@@ -117,164 +51,167 @@ the concepts layed out in the PPR panel opinion (EFSA PPR panel 2012 and in the EFSA guidance on PEC soil calculations (EFSA, 2015, 2017).

- 
PEC_soil(
-  rate,
-  rate_units = "g/ha",
-  interception = 0,
-  mixing_depth = 5,
-  PEC_units = "mg/kg",
-  PEC_pw_units = "mg/L",
-  interval = NA,
-  n_periods = Inf,
-  tillage_depth = 20,
-  leaching_depth = tillage_depth,
-  crop = "annual",
-  cultivation = FALSE,
-  chent = NA,
-  DT50 = NA,
-  FOMC = NA,
-  Koc = NA,
-  Kom = Koc/1.724,
-  t_avg = 0,
-  t_act = NULL,
-  scenarios = c("default", "EFSA_2017", "EFSA_2015"),
-  leaching = scenarios == "EFSA_2017",
-  porewater = FALSE
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
rate

Application rate in units specified below

rate_units

Defaults to g/ha

interception

The fraction of the application rate that does not reach the soil

mixing_depth

Mixing depth in cm

PEC_units

Requested units for the calculated PEC. Only mg/kg currently supported

PEC_pw_units

Only mg/L currently supported

interval

Period of the deeper mixing. The default is NA, i.e. no +

+ 
PEC_soil(
+  rate,
+  rate_units = "g/ha",
+  interception = 0,
+  mixing_depth = 5,
+  PEC_units = "mg/kg",
+  PEC_pw_units = "mg/L",
+  interval = NA,
+  n_periods = Inf,
+  tillage_depth = 20,
+  leaching_depth = tillage_depth,
+  crop = "annual",
+  cultivation = FALSE,
+  chent = NA,
+  DT50 = NA,
+  FOMC = NA,
+  Koc = NA,
+  Kom = Koc/1.724,
+  t_avg = 0,
+  t_act = NULL,
+  scenarios = c("default", "EFSA_2017", "EFSA_2015"),
+  leaching = scenarios == "EFSA_2017",
+  porewater = FALSE
+)
+
+ +
+

Arguments

+
rate
+

Application rate in units specified below

+ + +
rate_units
+

Defaults to g/ha

+ + +
interception
+

The fraction of the application rate that does not reach the soil

+ + +
mixing_depth
+

Mixing depth in cm

+ + +
PEC_units
+

Requested units for the calculated PEC. Only mg/kg currently supported

+ + +
PEC_pw_units
+

Only mg/L currently supported

+ + +
interval
+

Period of the deeper mixing. The default is NA, i.e. no deeper mixing. For annual deeper mixing, set this to 365 when degradation -units are in days

n_periods

Number of periods to be considered for long term PEC calculations

tillage_depth

Periodic (see interval) deeper mixing in cm

leaching_depth

EFSA (2017) uses the mixing depth (ecotoxicological +units are in days

+ + +
n_periods
+

Number of periods to be considered for long term PEC calculations

+ + +
tillage_depth
+

Periodic (see interval) deeper mixing in cm

+ + +
leaching_depth
+

EFSA (2017) uses the mixing depth (ecotoxicological evaluation depth) to calculate leaching for annual crops where tillage takes place. By default, losses from the layer down to the tillage -depth are taken into account in this implementation.

crop

Ignored for scenarios other than EFSA_2017. Only annual crops +depth are taken into account in this implementation.

+ + +
crop
+

Ignored for scenarios other than EFSA_2017. Only annual crops are supported when these scenarios are used. Only crops with a single cropping -cycle per year are currently supported.

cultivation

Does mechanical cultivation in the sense of EFSA (2017) +cycle per year are currently supported.

+ + +
cultivation
+

Does mechanical cultivation in the sense of EFSA (2017) take place, i.e. twice a year to a depth of 5 cm? Ignored for scenarios -other than EFSA_2017

chent

An optional chent object holding substance specific information. Can -also be a name for the substance as a character string

DT50

If specified, overrides soil DT50 endpoints from a chent object +other than EFSA_2017

+ + +
chent
+

An optional chent object holding substance specific information. Can +also be a name for the substance as a character string

+ + +
DT50
+

If specified, overrides soil DT50 endpoints from a chent object If DT50 is not specified here and not available from the chent object, zero -degradation is assumed

FOMC

If specified, it should be a named numeric vector containing +degradation is assumed

+ + +
FOMC
+

If specified, it should be a named numeric vector containing the FOMC parameters alpha and beta. This overrides any other degradation endpoints, and the degradation during the interval and after the maximum PEC -is calculated using these parameters without temperature correction

Koc

If specified, overrides Koc endpoints from a chent object

Kom

Calculated from Koc by default, but can explicitly be specified -as Kom here

t_avg

Averaging times for time weighted average concentrations

t_act

Time series for actual concentrations

scenarios

If this is 'default', the DT50 will be used without correction +is calculated using these parameters without temperature correction

+ + +
Koc
+

If specified, overrides Koc endpoints from a chent object

+ + +
Kom
+

Calculated from Koc by default, but can explicitly be specified +as Kom here

+ + +
t_avg
+

Averaging times for time weighted average concentrations

+ + +
t_act
+

Time series for actual concentrations

+ + +
scenarios
+

If this is 'default', the DT50 will be used without correction and soil properties as specified in the REACH guidance (R.16, Table R.16-9) are used for porewater PEC calculations. If this is "EFSA_2015", the DT50 is taken to be a modelling half-life at 20°C and pF2 (for when -'chents' is specified, the DegT50 with destination 'PECgw' will be used), +'chent' is specified, the DegT50 with destination 'PECgw' will be used), and corrected using an Arrhenius activation energy of 65.4 kJ/mol. Also -model and scenario adjustment factors from the EFSA guidance are used.

leaching

Should leaching be taken into account? The default is FALSE, -except when the EFSA_2017 scenarios are used.

porewater

Should equilibrium porewater concentrations be estimated +model and scenario adjustment factors from the EFSA guidance are used.

+ + +
leaching
+

Should leaching be taken into account? The default is FALSE, +except when the EFSA_2017 scenarios are used.

+ + +
porewater
+

Should equilibrium porewater concentrations be estimated based on Kom and the organic carbon fraction of the soil instead of total soil concentrations? Based on equation (7) given in the PPR panel opinion (EFSA 2012, p. 24) and the scenarios specified in the EFSA guidance (2015, -p. 13).

+p. 13).

-

Value

- -

The predicted concentration in soil

-

Details

+
+
+

Value

+ +

The predicted concentration in soil

+
+
+

Details

This assumes that the complete load to soil during the time specified by 'interval' (typically 365 days) is dosed at once. As in the PPR panel opinion cited below (EFSA PPR panel 2012), only temperature correction using the Arrhenius equation is performed.

Total soil and porewater PEC values for the scenarios as defined in the EFSA guidance (2017, p. 14/15) can easily be calculated.

-

Note

- +
+
+

Note

While time weighted average (TWA) concentrations given in the examples from the EFSA guidance from 2015 (p. 80) are be reproduced, this is not true for the TWA concentrations given for the same example in the EFSA guidance @@ -289,8 +226,9 @@ from 2017 (p. 92).

e.g. in the EFSA scenarios, the DT50 for groundwater modelling (destination 'PECgw') is taken from the chent object, otherwise the DT50 with destination 'PECsoil'.

-

References

- +
+
+

References

EFSA Panel on Plant Protection Products and their Residues (2012) Scientific Opinion on the science behind the guidance for scenario selection and scenario parameterisation for predicting environmental @@ -306,75 +244,80 @@ from 2017 (p. 92).

protection products and transformation products of these active substances in soil. EFSA Journal 13(4) 4093 doi:10.2903/j.efsa.2015.4093

- -

Examples

- 
PEC_soil(100, interception = 0.25)
#>      scenario
-#> t_avg default
-#>     0     0.1

-# This is example 1 starting at p. 92 of the EFSA guidance (2017)
-# Note that TWA concentrations differ from the ones given in the guidance
-# for an unknown reason (the values from EFSA (2015) can be reproduced).
-PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21),
-               Kom = 1000, scenarios = "EFSA_2017")
#>      scenario
-#> t_avg      CTN     CTC      CTS
-#>    0  19.76834 13.8619 10.53795
-#>    21 19.59345 13.7169 10.39882
PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21),
-               Kom = 1000, scenarios = "EFSA_2017", porewater = TRUE)
#>      scenario
-#> t_avg       CLN       CLC       CLS
-#>    0  0.5541984 0.6779249 0.9816693
-#>    21 0.5484576 0.6693125 0.9609119

-# This is example 1 starting at p. 79 of the EFSA guidance (2015)
-PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21),
-               scenarios = "EFSA_2015")
#>      scenario
-#> t_avg      CTN      CTC      CTS
-#>    0  21.96827 11.53750 9.145259
-#>    21 21.78517 11.40701 9.017370
PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21),
-               Kom = 1000, scenarios = "EFSA_2015", porewater = TRUE)
#>      scenario
-#> t_avg       CLN       CLC       CLS
-#>    0  0.7589401 0.6674322 0.9147861
-#>    21 0.7506036 0.6590345 0.8987279

-# The following is from example 4 starting at p. 85 of the EFSA guidance (2015)
-# Metabolite M2
-# Calculate total and porewater soil concentrations for tier 1 scenarios
-# Relative molar mass is 100/300, formation fraction is 0.7 * 1
-results_pfm <- PEC_soil(100/300 * 0.7 * 1 * 1000, interval = 365, DT50 = 250, t_avg = c(0, 21),
-                        scenarios = "EFSA_2015")
-results_pfm_pw <- PEC_soil(100/300 * 0.7 * 1000, interval = 365, DT50 = 250, t_av = c(0, 21),
-                           Kom = 100, scenarios = "EFSA_2015", porewater = TRUE)
-
- +

Author

Johannes Ranke

+
+ +
+

Examples

+ 
PEC_soil(100, interception = 0.25)
+#>      scenario
+#> t_avg default
+#>     0     0.1
+
+# This is example 1 starting at p. 92 of the EFSA guidance (2017)
+# Note that TWA concentrations differ from the ones given in the guidance
+# for an unknown reason (the values from EFSA (2015) can be reproduced).
+PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21),
+               Kom = 1000, scenarios = "EFSA_2017")
+#>      scenario
+#> t_avg      CTN     CTC      CTS
+#>    0  19.76834 13.8619 10.53795
+#>    21 19.59345 13.7169 10.39882
+PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21),
+               Kom = 1000, scenarios = "EFSA_2017", porewater = TRUE)
+#>      scenario
+#> t_avg       CLN       CLC       CLS
+#>    0  0.5541984 0.6779249 0.9816693
+#>    21 0.5484576 0.6693125 0.9609119
+
+# This is example 1 starting at p. 79 of the EFSA guidance (2015)
+PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21),
+               scenarios = "EFSA_2015")
+#>      scenario
+#> t_avg      CTN      CTC      CTS
+#>    0  21.96827 11.53750 9.145259
+#>    21 21.78517 11.40701 9.017370
+PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21),
+               Kom = 1000, scenarios = "EFSA_2015", porewater = TRUE)
+#>      scenario
+#> t_avg       CLN       CLC       CLS
+#>    0  0.7589401 0.6674322 0.9147861
+#>    21 0.7506036 0.6590345 0.8987279
+
+# The following is from example 4 starting at p. 85 of the EFSA guidance (2015)
+# Metabolite M2
+# Calculate total and porewater soil concentrations for tier 1 scenarios
+# Relative molar mass is 100/300, formation fraction is 0.7 * 1
+results_pfm <- PEC_soil(100/300 * 0.7 * 1 * 1000, interval = 365, DT50 = 250, t_avg = c(0, 21),
+                        scenarios = "EFSA_2015")
+results_pfm_pw <- PEC_soil(100/300 * 0.7 * 1000, interval = 365, DT50 = 250, t_av = c(0, 21),
+                           Kom = 100, scenarios = "EFSA_2015", porewater = TRUE)
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_soil_mets.html b/docs/reference/PEC_soil_mets.html index c3b09f4..0864211 100644 --- a/docs/reference/PEC_soil_mets.html +++ b/docs/reference/PEC_soil_mets.html @@ -1,61 +1,12 @@ - - - - - - - -Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets • pfm - - - - + + -
-
- -
- -
+

Calculate initial and accumulation PEC soil for a set of metabolites

@@ -104,68 +40,59 @@
-

Calculate initial and accumulation PEC soil for a set of metabolites

-
- 
PEC_soil_mets(rate, mw_parent, mets, interval = 365, ...)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - -
rate

Application rate in units specified below

mw_parent

The molecular weight of the parent compound

mets

A dataframe with metabolite identifiers as rownames +

+ 
PEC_soil_mets(rate, mw_parent, mets, interval = 365, ...)
+
+ +
+

Arguments

+
rate
+

Application rate in units specified below

+ + +
mw_parent
+

The molecular weight of the parent compound

+ + +
mets
+

A dataframe with metabolite identifiers as rownames and columns "mw", "occ" and "DT50" holding their molecular weight, -maximum occurrence in soil and their soil DT50

interval

The interval for accumulation calculations

...

Further arguments are passed to PEC_soil

- +maximum occurrence in soil and their soil DT50

-
-
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_sw_drainage_UK.html b/docs/reference/PEC_sw_drainage_UK.html index bdcf5af..b0be7f3 100644 --- a/docs/reference/PEC_sw_drainage_UK.html +++ b/docs/reference/PEC_sw_drainage_UK.html @@ -1,65 +1,13 @@ - - - - - - - -Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK • pfm - - - - + + -
-
- -
- -
+

Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method

@@ -111,97 +45,97 @@ published on the CRC website" /> published on the CRC website

- 
PEC_sw_drainage_UK(
-  rate,
-  interception = 0,
-  Koc,
-  latest_application = NULL,
-  soil_DT50 = NULL,
-  model = NULL,
-  model_parms = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
rate

Application rate in g/ha

interception

The fraction of the application rate that does not reach the soil

Koc

The sorption coefficient normalised to organic carbon in L/kg

latest_application

Latest application date, formatted as e.g. "01 July"

soil_DT50

Soil degradation half-life, if SFO kinetics are to be used

model

The soil degradation model to be used. Either one of "FOMC", -"DFOP", "HS", or "IORE", or an mkinmod object

model_parms

A named numeric vector containing the model parameters

- -

Value

- -

The predicted concentration in surface water in µg/L

-

References

+
+ 
PEC_sw_drainage_UK(
+  rate,
+  interception = 0,
+  Koc,
+  latest_application = NULL,
+  soil_DT50 = NULL,
+  model = NULL,
+  model_parms = NULL
+)
+
+ +
+

Arguments

+
rate
+

Application rate in g/ha

+ + +
interception
+

The fraction of the application rate that does not reach the soil

+ + +
Koc
+

The sorption coefficient normalised to organic carbon in L/kg

+ + +
latest_application
+

Latest application date, formatted as e.g. "01 July"

+ + +
soil_DT50
+

Soil degradation half-life, if SFO kinetics are to be used

+ + +
model
+

The soil degradation model to be used. Either one of "FOMC", +"DFOP", "HS", or "IORE", or an mkinmod object

+ +
model_parms
+

A named numeric vector containing the model parameters

+ +
+
+

Value

+ + +

The predicted concentration in surface water in µg/L

+
+ - +

Author

Johannes Ranke

+
+ +
+

Examples

+ 
PEC_sw_drainage_UK(150, Koc = 100)
+#> [1] 8.076923
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_sw_drift.html b/docs/reference/PEC_sw_drift.html index e2c325b..c017454 100644 --- a/docs/reference/PEC_sw_drift.html +++ b/docs/reference/PEC_sw_drift.html @@ -1,69 +1,14 @@ - - - - - - - -Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

Calculate predicted environmental concentrations in surface water due to drift

@@ -116,106 +47,118 @@ concentration in surface water based on complete, instantaneous mixing with input via spray drift.

- 
PEC_sw_drift(
-  rate,
-  applications = 1,
-  water_depth = 30,
-  drift_percentages = NULL,
-  drift_data = c("JKI", "RF"),
-  crop = "Ackerbau",
-  distances = c(1, 5, 10, 20),
-  rate_units = "g/ha",
-  PEC_units = "µg/L"
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
rate

Application rate in units specified below

applications

Number of applications for selection of drift percentile

water_depth

Depth of the water body in cm

drift_percentages

Percentage drift values for which to calculate PECsw. -'drift_data' and 'distances' if not NULL.

drift_data

Source of drift percentage data. If 'JKI', the [drift_data_JKI] +

+ 
PEC_sw_drift(
+  rate,
+  applications = 1,
+  water_depth = 30,
+  drift_percentages = NULL,
+  drift_data = c("JKI", "RF"),
+  crop = "Ackerbau",
+  distances = c(1, 5, 10, 20),
+  rate_units = "g/ha",
+  PEC_units = "µg/L"
+)
+
+ +
+

Arguments

+
rate
+

Application rate in units specified below

+ + +
applications
+

Number of applications for selection of drift percentile

+ + +
water_depth
+

Depth of the water body in cm

+ + +
drift_percentages
+

Percentage drift values for which to calculate PECsw. +'drift_data' and 'distances' if not NULL.

+ + +
drift_data
+

Source of drift percentage data. If 'JKI', the [drift_data_JKI] included in the package is used. If 'RF', the Rautmann formula is used, if -implemented for the crop type and number of applications

crop

Crop name (use German names for JKI data), defaults to "Ackerbau"

distances

The distances in m for which to get PEC values

rate_units

Defaults to g/ha

PEC_units

Requested units for the calculated PEC. Only µg/L currently supported

- -

Value

- -

The predicted concentration in surface water

- -

Examples

- 
PEC_sw_drift(100)
#>        1 m        5 m       10 m       20 m 
-#> 0.92333333 0.19000000 0.09666667 0.05000000 
# Alternatively, we can use the formula for a single application to "Ackerbau" from the paper
-PEC_sw_drift(100, drift_data = "RF")
#>        1 m        5 m       10 m       20 m 
-#> 0.92350000 0.19114149 0.09699222 0.04921742 

-# This makes it possible to also use different substances
-PEC_sw_drift(100, distances = c(1, 3, 5, 6, 10, 20, 50, 100), drift_data = "RF")
#>        1 m        3 m        5 m        6 m       10 m       20 m       50 m 
-#> 0.92350000 0.31512171 0.19114149 0.15990435 0.09699222 0.04921742 0.02007497 
-#>      100 m 
-#> 0.01018678 

-# Using custom drift percentages is also supported
-PEC_sw_drift(100, drift_percentages = c(2.77, 0.95, 0.57, 0.48, 0.29, 0.15, 0.06, 0.03))
#>     2.77 %     0.95 %     0.57 %     0.48 %     0.29 %     0.15 %     0.06 % 
-#> 0.92333333 0.31666667 0.19000000 0.16000000 0.09666667 0.05000000 0.02000000 
-#>     0.03 % 
-#> 0.01000000
+implemented for the crop type and number of applications

+ + +
crop
+

Crop name (use German names for JKI data), defaults to "Ackerbau"

+ + +
distances
+

The distances in m for which to get PEC values

+ + +
rate_units
+

Defaults to g/ha

+ + +
PEC_units
+

Requested units for the calculated PEC. Only µg/L currently supported

+ +
+
+

Value

+ + +

The predicted concentration in surface water

+
+
+

Author

+

Johannes Ranke

+
+ +
+

Examples

+ 
PEC_sw_drift(100)
+#>        1 m        5 m       10 m       20 m 
+#> 0.92333333 0.19000000 0.09666667 0.05000000 
+# Alternatively, we can use the formula for a single application to "Ackerbau" from the paper
+PEC_sw_drift(100, drift_data = "RF")
+#>        1 m        5 m       10 m       20 m 
+#> 0.92350000 0.19114149 0.09699222 0.04921742 
+
+# This makes it possible to also use different substances
+PEC_sw_drift(100, distances = c(1, 3, 5, 6, 10, 20, 50, 100), drift_data = "RF")
+#>        1 m        3 m        5 m        6 m       10 m       20 m       50 m 
+#> 0.92350000 0.31512171 0.19114149 0.15990435 0.09699222 0.04921742 0.02007497 
+#>      100 m 
+#> 0.01018678 
+
+# Using custom drift percentages is also supported
+PEC_sw_drift(100, drift_percentages = c(2.77, 0.95, 0.57, 0.48, 0.29, 0.15, 0.06, 0.03))
+#>     2.77 %     0.95 %     0.57 %     0.48 %     0.29 %     0.15 %     0.06 % 
+#> 0.92333333 0.31666667 0.19000000 0.16000000 0.09666667 0.05000000 0.02000000 
+#>     0.03 % 
+#> 0.01000000 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_sw_exposit_drainage.html b/docs/reference/PEC_sw_exposit_drainage.html index 5bd1d80..becfa0c 100644 --- a/docs/reference/PEC_sw_exposit_drainage.html +++ b/docs/reference/PEC_sw_exposit_drainage.html @@ -1,70 +1,18 @@ - - - - - - - -Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage • pfm - - - - + + -
-
- -
- -
+

Calculate PEC surface water due to drainage as in Exposit 3

@@ -121,123 +55,126 @@ the group is derived only from the Koc, if not given explicitly. For details, see the discussion of the function arguments below.

- 
PEC_sw_exposit_drainage(
-  rate,
-  interception = 0,
-  Koc = NA,
-  mobility = c(NA, "low", "high"),
-  DT50 = Inf,
-  t_drainage = 3,
-  V_ditch = 30,
-  V_drainage = c(spring = 10, autumn = 100),
-  dilution = 2
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
rate

The application rate in g/ha

interception

The fraction intercepted by the crop

Koc

The sorption coefficient to soil organic carbon used to determine the mobility. A trigger -value of 550 L/kg is used in order to decide if Koc >> 500.

mobility

Overrides what is determined from the Koc.

DT50

The soil half-life in days

t_drainage

The time between application and the drainage event, where degradation occurs, in days

V_ditch

The volume of the ditch is assumed to be 1 m * 100 m * 30 cm = 30 m3

V_drainage

The drainage volume, equivalent to 1 mm precipitation on 1 ha for spring/summer or 10 mm for -autumn/winter/early spring.

dilution

The dilution factor

- -

Source

+
+ 
PEC_sw_exposit_drainage(
+  rate,
+  interception = 0,
+  Koc = NA,
+  mobility = c(NA, "low", "high"),
+  DT50 = Inf,
+  t_drainage = 3,
+  V_ditch = 30,
+  V_drainage = c(spring = 10, autumn = 100),
+  dilution = 2
+)
+
+ +
+

Arguments

+
rate
+

The application rate in g/ha

+ + +
interception
+

The fraction intercepted by the crop

+ + +
Koc
+

The sorption coefficient to soil organic carbon used to determine the mobility. A trigger +value of 550 L/kg is used in order to decide if Koc >> 500.

+ + +
mobility
+

Overrides what is determined from the Koc.

+ + +
DT50
+

The soil half-life in days

+ + +
t_drainage
+

The time between application and the drainage event, where degradation occurs, in days

+ + +
V_ditch
+

The volume of the ditch is assumed to be 1 m * 100 m * 30 cm = 30 m3

-

A list containing the following components

-
perc_runoff

The runoff percentages for dissolved and bound substance

-
runoff

A matrix containing dissolved and bound input for the different distances

-
PEC_sw_runoff

A matrix containing PEC values for dissolved and bound substance + +

V_drainage
+

The drainage volume, equivalent to 1 mm precipitation on 1 ha for spring/summer or 10 mm for +autumn/winter/early spring.

+ + +
dilution
+

The dilution factor

+ +
+
+

Value

+ + +

A list containing the following components

+

+
perc_runoff
+

The runoff percentages for dissolved and bound substance

+ +
runoff
+

A matrix containing dissolved and bound input for the different distances

+ +
PEC_sw_runoff
+

A matrix containing PEC values for dissolved and bound substance for the different distances. If the rate was given in g/ha, the PECsw are in microg/L.

+ -
- -

See also

- -

perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used

- -

Examples

- 
  PEC_sw_exposit_drainage(500, Koc = 150)
#> $perc_drainage_total
-#> spring autumn 
-#>    0.2    1.0 
-#> 
-#> $perc_peak
-#> spring autumn 
-#>   12.5   25.0 
-#> 
-#> $PEC_sw_drainage
-#>   spring   autumn 
-#> 1.562500 4.807692 
-#>
-
- +
+

See also

+

perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used

+
+
+

Examples

+ 
  PEC_sw_exposit_drainage(500, Koc = 150)
+#> $perc_drainage_total
+#> spring autumn 
+#>    0.2    1.0 
+#> 
+#> $perc_peak
+#> spring autumn 
+#>   12.5   25.0 
+#> 
+#> $PEC_sw_drainage
+#>   spring   autumn 
+#> 1.562500 4.807692 
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_sw_exposit_runoff.html b/docs/reference/PEC_sw_exposit_runoff.html index 81549e0..101274c 100644 --- a/docs/reference/PEC_sw_exposit_runoff.html +++ b/docs/reference/PEC_sw_exposit_runoff.html @@ -1,65 +1,13 @@ - - - - - - - -Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff • pfm - - - - + + -
-
- -
- -
+

Calculate PEC surface water due to runoff and erosion as in Exposit 3

@@ -111,152 +45,157 @@ in the worksheet "Konzept Runoff"." /> in the worksheet "Konzept Runoff".

- 
PEC_sw_exposit_runoff(
-  rate,
-  interception = 0,
-  Koc,
-  DT50 = Inf,
-  t_runoff = 3,
-  exposit_reduction_version = c("3.02", "3.01a", "3.01a2", "2.0"),
-  V_ditch = 30,
-  V_event = 100,
-  dilution = 2
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
rate

The application rate in g/ha

interception

The fraction intercepted by the crop

Koc

The sorption coefficient to soil organic carbon

DT50

The soil half-life in days

t_runoff

The time between application and the runoff event, where degradation occurs, in days

exposit_reduction_version

The version of the reduction factors to be used. "3.02" is the current +

+ 
PEC_sw_exposit_runoff(
+  rate,
+  interception = 0,
+  Koc,
+  DT50 = Inf,
+  t_runoff = 3,
+  exposit_reduction_version = c("3.02", "3.01a", "3.01a2", "2.0"),
+  V_ditch = 30,
+  V_event = 100,
+  dilution = 2
+)
+
+ + +
+

Arguments

+
rate
+

The application rate in g/ha

+ + +
interception
+

The fraction intercepted by the crop

+ + +
Koc
+

The sorption coefficient to soil organic carbon

+ + +
DT50
+

The soil half-life in days

+ + +
t_runoff
+

The time between application and the runoff event, where degradation occurs, in days

+ + +
exposit_reduction_version
+

The version of the reduction factors to be used. "3.02" is the current version used in Germany, "3.01a" is the version with additional percentages for 3 m and 6 m buffer zones used in Switzerland. "3.01a2" is a version introduced for consistency with previous calculations performed for a 3 m buffer zone in Switzerland, with the same reduction being applied to the dissolved -and the bound fraction.

V_ditch

The volume of the ditch is assumed to be 1 m * 100 m * 30 cm = 30 m3

V_event

The unreduced runoff volume, equivalent to 10 mm precipitation on 1 ha

dilution

The dilution factor

- -

Source

+and the bound fraction.

-

Excel 3.02 spreadsheet available from - https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3

-

Value

-

A list containing the following components

-
perc_runoff

The runoff percentages for dissolved and bound substance

-
runoff

A matrix containing dissolved and bound input for the different distances

-
PEC_sw_runoff

A matrix containing PEC values for dissolved and bound substance +

V_ditch
+

The volume of the ditch is assumed to be 1 m * 100 m * 30 cm = 30 m3

+ + +
V_event
+

The unreduced runoff volume, equivalent to 10 mm precipitation on 1 ha

+ + +
dilution
+

The dilution factor

+ +
+
+

Value

+ + +

A list containing the following components

+

+
perc_runoff
+

The runoff percentages for dissolved and bound substance

+ +
runoff
+

A matrix containing dissolved and bound input for the different distances

+ +
PEC_sw_runoff
+

A matrix containing PEC values for dissolved and bound substance for the different distances. If the rate was given in g/ha, the PECsw are in microg/L.

+ -
- -

See also

- -

perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used

- -

Examples

- 
  PEC_sw_exposit_runoff(500, Koc = 150)
#> $perc_runoff
-#> dissolved     bound 
-#>     0.248     0.001 
-#> 
-#> $runoff
-#>           dissolved   bound   total
-#> No buffer     1.240 0.00500 1.24500
-#> 5 m           0.744 0.00300 0.74700
-#> 10 m          0.496 0.00075 0.49675
-#> 20 m          0.248 0.00025 0.24825
-#> 
-#> $PEC_sw_runoff
-#>           dissolved       bound    total
-#> No buffer  4.769231 0.019230769 4.788462
-#> 5 m        4.133333 0.016666667 4.150000
-#> 10 m       3.542857 0.005357143 3.548214
-#> 20 m       2.480000 0.002500000 2.482500
-#> 
  PEC_sw_exposit_runoff(600, Koc = 10000, DT50 = 195, exposit = "3.01a")
#> $perc_runoff
-#> dissolved     bound 
-#>     0.037     0.159 
-#> 
-#> $runoff
-#>            dissolved      bound      total
-#> No buffer 0.21964521 0.94388078 1.16352600
-#> 3 m       0.16473391 0.66071655 0.82545046
-#> 5 m       0.13178713 0.56632847 0.69811560
-#> 6 m       0.12080487 0.42474635 0.54555122
-#> 10 m      0.08785809 0.14158212 0.22944020
-#> 20 m      0.04392904 0.04719404 0.09112308
-#> 
-#> $PEC_sw_runoff
-#>           dissolved     bound     total
-#> No buffer 0.8447893 3.6303107 4.4751000
-#> 3 m       0.7844472 3.1462693 3.9307165
-#> 5 m       0.7321507 3.1462693 3.8784200
-#> 6 m       0.7106169 2.4985080 3.2091248
-#> 10 m      0.6275578 1.0113008 1.6388586
-#> 20 m      0.4392904 0.4719404 0.9112308
-#>
-
- +
+

See also

+

perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used

+
+
+

Examples

+ 
  PEC_sw_exposit_runoff(500, Koc = 150)
+#> $perc_runoff
+#> dissolved     bound 
+#>     0.248     0.001 
+#> 
+#> $runoff
+#>           dissolved   bound   total
+#> No buffer     1.240 0.00500 1.24500
+#> 5 m           0.744 0.00300 0.74700
+#> 10 m          0.496 0.00075 0.49675
+#> 20 m          0.248 0.00025 0.24825
+#> 
+#> $PEC_sw_runoff
+#>           dissolved       bound    total
+#> No buffer  4.769231 0.019230769 4.788462
+#> 5 m        4.133333 0.016666667 4.150000
+#> 10 m       3.542857 0.005357143 3.548214
+#> 20 m       2.480000 0.002500000 2.482500
+#> 
+  PEC_sw_exposit_runoff(600, Koc = 10000, DT50 = 195, exposit = "3.01a")
+#> $perc_runoff
+#> dissolved     bound 
+#>     0.037     0.159 
+#> 
+#> $runoff
+#>            dissolved      bound      total
+#> No buffer 0.21964521 0.94388078 1.16352600
+#> 3 m       0.16473391 0.66071655 0.82545046
+#> 5 m       0.13178713 0.56632847 0.69811560
+#> 6 m       0.12080487 0.42474635 0.54555122
+#> 10 m      0.08785809 0.14158212 0.22944020
+#> 20 m      0.04392904 0.04719404 0.09112308
+#> 
+#> $PEC_sw_runoff
+#>           dissolved     bound     total
+#> No buffer 0.8447893 3.6303107 4.4751000
+#> 3 m       0.7844472 3.1462693 3.9307165
+#> 5 m       0.7321507 3.1462693 3.8784200
+#> 6 m       0.7106169 2.4985080 3.2091248
+#> 10 m      0.6275578 1.0113008 1.6388586
+#> 20 m      0.4392904 0.4719404 0.9112308
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_sw_focus.html b/docs/reference/PEC_sw_focus.html index 8242f6a..605d2cc 100644 --- a/docs/reference/PEC_sw_focus.html +++ b/docs/reference/PEC_sw_focus.html @@ -1,70 +1,18 @@ - - - - - - - -Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus • pfm - - - - - - - - - - - - - - + + -
-
- -
- -
+

Calculate PEC surface water at FOCUS Step 1

@@ -117,119 +51,118 @@ authored by Michael Klein, in R. Note that results for multiple applications should be compared to the corresponding results for a single application. At current, this is not done automatically in this implementation. Only Step 1 PECs are calculated. However, -input files are generated that are suitable as input also for Step 2 -to be used with the FOCUS calculator.

+input files can be generated that are suitable as input for +the FOCUS calculator.

+
+ +
+ 
PEC_sw_focus(
+  parent,
+  rate,
+  n = 1,
+  i = NA,
+  comment = "",
+  met = NULL,
+  f_drift = NA,
+  f_rd = 0.1,
+  scenario = FOCUS_Step_12_scenarios$names,
+  region = c("n", "s"),
+  season = c(NA, "of", "mm", "js"),
+  interception = c("no interception", "minimal crop cover", "average crop cover",
+    "full canopy"),
+  met_form_water = TRUE,
+  txt_file = "pesticide.txt",
+  overwrite = FALSE,
+  append = FALSE
+)
- 
PEC_sw_focus(
-  parent,
-  rate,
-  n = 1,
-  i = NA,
-  comment = "",
-  met = NULL,
-  f_drift = NA,
-  f_rd = 0.1,
-  scenario = FOCUS_Step_12_scenarios$names,
-  region = c("n", "s"),
-  season = c(NA, "of", "mm", "js"),
-  interception = c("no interception", "minimal crop cover", "average crop cover",
-    "full canopy"),
-  met_form_water = TRUE,
-  txt_file = "pesticide.txt",
-  overwrite = FALSE,
-  append = TRUE
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
parent

A list containing substance specific parameters, e.g. -conveniently generated by chent_focus_sw.

rate

The application rate in g/ha. Overriden when -applications are given explicitly

n

The number of applications

i

The application interval

comment

A comment for the input file

met

A list containing metabolite specific parameters. e.g. -conveniently generated by chent_focus_sw. If not NULL, -the PEC is calculated for this compound, not the parent.

f_drift

The fraction of the application rate reaching the waterbody +

+

Arguments

+
parent
+

A list containing substance specific parameters, e.g. +conveniently generated by [chent_focus_sw].

+ + +
rate
+

The application rate in g/ha. Overriden when +applications are given explicitly

+ + +
n
+

The number of applications

+ + +
i
+

The application interval

+ + +
comment
+

A comment for the input file

+ + +
met
+

A list containing metabolite specific parameters. e.g. +conveniently generated by [chent_focus_sw]. If not NULL, +the PEC is calculated for this compound, not the parent.

+ + +
f_drift
+

The fraction of the application rate reaching the waterbody via drift. If NA, this is derived from the scenario name and the number of applications via the drift data defined by the -FOCUS_Step_12_scenarios

f_rd

The fraction of the amount applied reaching the waterbody via +[FOCUS_Step_12_scenarios]

+ + +
f_rd
+

The fraction of the amount applied reaching the waterbody via runoff/drainage. At Step 1, it is assumed to be 10 -parent or a metabolite

scenario

The name of the scenario. Must be one of the scenario -names given in FOCUS_Step_12_scenarios

region

'n' for Northern Europe or 's' for Southern Europe. If NA, only -Step 1 PECsw are calculated

season

'of' for October to February, 'mm' for March to May, and 'js' -for June to September. If NA, only step 1 PECsw are calculated

interception

One of 'no interception' (default), 'minimal crop cover', -'average crop cover' or 'full canopy'

met_form_water

Should the metabolite formation in water be taken into +parent or a metabolite

+ + +
scenario
+

The name of the scenario. Must be one of the scenario +names given in [FOCUS_Step_12_scenarios]

+ + +
region
+

'n' for Northern Europe or 's' for Southern Europe. If NA, only +Step 1 PECsw are calculated

+ + +
season
+

'of' for October to February, 'mm' for March to May, and 'js' +for June to September. If NA, only step 1 PECsw are calculated

+ + +
interception
+

One of 'no interception' (default), 'minimal crop cover', +'average crop cover' or 'full canopy'

+ + +
met_form_water
+

Should the metabolite formation in water be taken into account? This can be switched off to check the influence and to compare -with previous versions of the Steps 12 calculator

txt_file

the name, and potentially the full path to the +with previous versions of the Steps 12 calculator

+ + +
txt_file
+

the name, and potentially the full path to the Steps.12 input text file to which the specification of the run(s) -should be written

overwrite

Should an existing file a the location specified in -txt_file be overwritten? Only takes effect if append is FALSE.

append

Should the input text file be appended?

- -

Note

+should be written

+ + +
overwrite
+

Should an existing file a the location specified in +txt_file be overwritten? Only takes effect if append is FALSE.

+ +
append
+

Should the input text file be appended, if it exists?

+ +
+
+

Note

The formulas for input to the waterbody via runoff/drainage of the parent and subsequent formation of the metabolite in water is not documented in the model description coming with the calculator. As one would @@ -237,142 +170,141 @@ should be written

multiplying the application rate with the molar weight correction and the formation fraction in water/sediment systems.

Step 2 is not implemented.

-

References

- +
+
+

References

FOCUS (2014) Generic guidance for Surface Water Scenarios (version 1.4). FOrum for the Co-ordination of pesticde fate models and their USe. http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic

Website of the Steps 1 and 2 calculator at the Joint Research Center of the European Union: http://esdac.jrc.ec.europa.eu/projects/stepsonetwo

+
-

Examples

- 
# Parent only
-dummy_1 <- chent_focus_sw("Dummy 1", cwsat = 6000, DT50_ws = 6, Koc = 344.8)
-PEC_sw_focus(dummy_1, 3000, f_drift = 0, overwrite = TRUE, append = FALSE)
#> $f_drift
-#> [1] 0
-#> 
-#> $eq_rate_drift_s
-#> [1] 3000
-#> 
-#> $eq_rate_rd_s
-#> [1] 3000
-#> 
-#> $eq_rate_rd_parent_s
-#> [1] NA
-#> 
-#> $input_drift_s
-#> [1] 0
-#> 
-#> $input_rd_s
-#> [1] 300
-#> 
-#> $f_rd_sw
-#> [1] 0.6850566
-#> 
-#> $f_rd_sed
-#> [1] 0.3149434
-#> 
-#> $PEC
-#>      type
-#> Time         PECsw   TWAECsw       PECsed  TWAECsed
-#>   0   6.850566e+02        NA 2.362075e+03        NA
-#>   1   6.103161e+02 647.68635 2.104370e+03 2233.2225
-#>   2   5.437298e+02 612.03420 1.874780e+03 2110.2939
-#>   4   4.315586e+02 548.76030 1.488014e+03 1892.1255
-#>   7   3.051580e+02 469.88375 1.052185e+03 1620.1592
-#>   14  1.359325e+02 339.57370 4.686951e+02 1170.8501
-#>   21  6.055102e+01 257.45458 2.087799e+02  887.7034
-#>   28  2.697241e+01 203.47173 9.300089e+01  701.5705
-#>   42  5.352005e+00 140.10377 1.845371e+01  483.0778
-#>   50  2.123945e+00 118.24602 7.323361e+00  407.7123
-#>   100 6.585062e-03  59.30629 2.270529e-02  204.4881
-#> 
-#> $PEC_sw_max
-#> [1] 685.0566
-#> 
-#> $PEC_sed_max
-#> [1] 2362.075
-#> 

-# Metabolite
-new_dummy <- chent_focus_sw("New Dummy", mw = 250, Koc = 100)
-M1 <- chent_focus_sw("M1", mw = 100, cwsat = 100, DT50_ws = 100, Koc = 50,
-  max_ws = 0, max_soil = 0.5)
-PEC_sw_focus(new_dummy, 1000, scenario = "cereals, winter", met = M1)
#> $f_drift
-#> [1] 0.02759
-#> 
-#> $eq_rate_drift_s
-#> [1] 0
-#> 
-#> $eq_rate_rd_s
-#> [1] 200
-#> 
-#> $eq_rate_rd_parent_s
-#> [1] 0
-#> 
-#> $input_drift_s
-#> [1] 0
-#> 
-#> $input_rd_s
-#> [1] 20
-#> 
-#> $f_rd_sw
-#> [1] 0.9375
-#> 
-#> $f_rd_sed
-#> [1] 0.0625
-#> 
-#> $PEC
-#>      type
-#> Time     PECsw  TWAECsw   PECsed TWAECsed
-#>   0   62.50000       NA 31.25000       NA
-#>   1   62.06828 62.28414 31.03414 31.14207
-#>   2   61.63954 62.06890 30.81977 31.03445
-#>   4   60.79093 61.64158 30.39547 30.82079
-#>   7   59.53987 61.00800 29.76994 30.50400
-#>   14  56.71995 59.56326 28.35997 29.78163
-#>   21  54.03358 58.16414 27.01679 29.08207
-#>   28  51.47444 56.80902 25.73722 28.40451
-#>   42  46.71404 54.22460 23.35702 27.11230
-#>   50  44.19417 52.81945 22.09709 26.40973
-#>   100 31.25000 45.08422 15.62500 22.54211
-#> 
-#> $PEC_sw_max
-#> [1] 62.5
-#> 
-#> $PEC_sed_max
-#> [1] 31.25
-#>
-
- +
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/PEC_sw_sed.html b/docs/reference/PEC_sw_sed.html index 458eeb7..247c8d7 100644 --- a/docs/reference/PEC_sw_sed.html +++ b/docs/reference/PEC_sw_sed.html @@ -1,67 +1,15 @@ - - - - - - - -Calculate predicted environmental concentrations in sediment from surface -water concentrations — PEC_sw_sed • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate predicted environmental concentrations in sediment from surface +water concentrations — PEC_sw_sed • pfm - - - - + + -
-
- -
- -
+

Calculate predicted environmental concentrations in sediment from surface @@ -114,89 +48,89 @@ water concentrations

PEC calculator

- 
PEC_sw_sed(
-  PEC_sw,
-  percentage = 100,
-  method = "percentage",
-  sediment_depth = 5,
-  water_depth = 30,
-  sediment_density = 1.3,
-  PEC_sed_units = c("µg/kg", "mg/kg")
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
PEC_sw

Numeric vector or matrix of surface water concentrations in µg/L for -which the corresponding sediment concentration is to be estimated

percentage

The percentage in sediment, used for the percentage method

method

The method used for the calculation

sediment_depth

Depth of the sediment layer

water_depth

Depth of the water body in cm

sediment_density

The density of the sediment in L/kg (equivalent to -g/cm3)

PEC_sed_units

The units of the estimated sediment PEC value

- -

Value

- -

The predicted concentration in sediment

- -

Examples

- 
PEC_sw_sed(PEC_sw_drift(100, distances = 1), percentage = 50)
#>      1 m 
-#> 2.130769
-
- +
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/Rplot002.png b/docs/reference/Rplot002.png new file mode 100644 index 0000000..8269e66 Binary files /dev/null and b/docs/reference/Rplot002.png differ diff --git a/docs/reference/Rplot003.png b/docs/reference/Rplot003.png new file mode 100644 index 0000000..8269e66 Binary files /dev/null and b/docs/reference/Rplot003.png differ diff --git a/docs/reference/Rplot004.png b/docs/reference/Rplot004.png new file mode 100644 index 0000000..9ec61d5 Binary files /dev/null and b/docs/reference/Rplot004.png differ diff --git a/docs/reference/Rplot005.png b/docs/reference/Rplot005.png new file mode 100644 index 0000000..02941cf Binary files /dev/null and b/docs/reference/Rplot005.png differ diff --git a/docs/reference/SFO_actual_twa.html b/docs/reference/SFO_actual_twa.html index b5fa5da..855ca3c 100644 --- a/docs/reference/SFO_actual_twa.html +++ b/docs/reference/SFO_actual_twa.html @@ -1,64 +1,12 @@ - - - - - - - -Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa • pfm - - - - + + -
-
- -
- -
+

Actual and maximum moving window time average concentrations for SFO kinetics

@@ -109,71 +43,69 @@

Actual and maximum moving window time average concentrations for SFO kinetics

- 
SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))
- -

Arguments

- - - - - - - - - - -
DT50

The half-life.

times

The output times, and window sizes for time weighted average concentrations

- -

Source

+
+ 
SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))
+
+
+

Source

FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, 18 December 2014, p. 251

+
+
+

Arguments

+
DT50
+

The half-life.

-

Examples

- 
SFO_actual_twa(10)
#>           actual       twa
-#> 0   1.0000000000       NaN
-#> 1   0.9330329915 0.9661297
-#> 2   0.8705505633 0.9337803
-#> 4   0.7578582833 0.8733416
-#> 7   0.6155722067 0.7923030
-#> 14  0.3789291416 0.6400113
-#> 21  0.2332582479 0.5267498
-#> 28  0.1435872944 0.4412651
-#> 42  0.0544094102 0.3248093
-#> 50  0.0312500000 0.2795222
-#> 100 0.0009765625 0.1441286
-
- +

Author

Johannes Ranke

+
+ +
+

Examples

+ 
SFO_actual_twa(10)
+#>           actual       twa
+#> 0   1.0000000000       NaN
+#> 1   0.9330329915 0.9661297
+#> 2   0.8705505633 0.9337803
+#> 4   0.7578582833 0.8733416
+#> 7   0.6155722067 0.7923030
+#> 14  0.3789291416 0.6400113
+#> 21  0.2332582479 0.5267498
+#> 28  0.1435872944 0.4412651
+#> 42  0.0544094102 0.3248093
+#> 50  0.0312500000 0.2795222
+#> 100 0.0009765625 0.1441286
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/SSLRC_mobility_classification.html b/docs/reference/SSLRC_mobility_classification.html index b0ae939..a50d906 100644 --- a/docs/reference/SSLRC_mobility_classification.html +++ b/docs/reference/SSLRC_mobility_classification.html @@ -1,62 +1,13 @@ - - - - - - - -Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification • pfm - - - - + + -
-
- -
- -
+

Determine the SSLRC mobility classification for a chemical substance from its Koc

@@ -105,86 +41,81 @@ checked against the spreadsheet published on the CRC website" />
-

This implements the method specified in the UK data requirements handbook and was checked against the spreadsheet published on the CRC website

-
- 
SSLRC_mobility_classification(Koc)
- -

Arguments

- - - - - - -
Koc

The sorption coefficient normalised to organic carbon in L/kg

- -

Value

+
+ 
SSLRC_mobility_classification(Koc)
+
-

A list containing the classification and the percentage of the - compound transported per 10 mm drain water

+
+

Arguments

+
Koc
+

The sorption coefficient normalised to organic carbon in L/kg

+ +
+
+

Value

-

References

+

A list containing the classification and the percentage of the + compound transported per 10 mm drain water

+
+
+

References

HSE's Chemicals Regulation Division (CRD) Active substance PECsw calculations (for UK specific authorisation requests) - https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm + https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm accessed 2019-09-27

Drainage PECs Version 1.0 (2015) Spreadsheet published at - https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx + https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx accessed 2019-09-27

- - -

Examples

- 
SSLRC_mobility_classification(100)
#> $`Mobility classification`
-#> [1] "Moderately mobile"
-#> 
-#> $`Percentage drained per mm of drain water`
-#> [1] 0.7
-#> 
SSLRC_mobility_classification(10000)
#> $`Mobility classification`
-#> [1] "Non mobile"
-#> 
-#> $`Percentage drained per mm of drain water`
-#> [1] 0.008
-#>
-
- +

Author

Johannes Ranke

+
+ +
+

Examples

+ 
SSLRC_mobility_classification(100)
+#> $`Mobility classification`
+#> [1] "Moderately mobile"
+#> 
+#> $`Percentage drained per mm of drain water`
+#> [1] 0.7
+#> 
+SSLRC_mobility_classification(10000)
+#> $`Mobility classification`
+#> [1] "Non mobile"
+#> 
+#> $`Percentage drained per mm of drain water`
+#> [1] 0.008
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/TOXSWA_cwa.html b/docs/reference/TOXSWA_cwa.html index 16dc5db..a64ad40 100644 --- a/docs/reference/TOXSWA_cwa.html +++ b/docs/reference/TOXSWA_cwa.html @@ -1,71 +1,16 @@ - - - - - - - -R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

R6 class for holding TOXSWA water concentration data and associated statistics

@@ -117,179 +48,236 @@ by read.TOXSWA_cwa." /> and some associated statistics. like maximum moving window average concentrations, and dataframes holding the events exceeding specified thresholds. Usually, an instance of this class will be generated -by read.TOXSWA_cwa.

+by read.TOXSWA_cwa.

+
+

Format

+

An R6Class generator object.

+
+
+

Public fields

+

filename
+

Length one character vector holding the filename.

-

Format

-

An R6Class generator object.

-

Public fields

+
basedir
+

Length one character vector holding the directory where the file came from.

+ -

-
filename

Length one character vector holding the filename.

+
zipfile
+

If not null, giving the path to the zip file from which the file was read.

-
basedir

Length one character vector holding the directory where the file came from.

-
zipfile

If not null, giving the path to the zip file from which the file was read.

+
segment
+

Length one integer, specifying for which segment the cwa data were read.

-
segment

Length one integer, specifying for which segment the cwa data were read.

-
substance

The TOXSWA name of the substance.

+
substance
+

The TOXSWA name of the substance.

-
cwas

Dataframe holding the concentrations.

-
events

List of dataframes holding the event statistics for each threshold.

+
cwas
+

Dataframe holding the concentrations.

-
windows

Matrix of maximum time weighted average concentrations (TWAC_max) + +

events
+

List of dataframes holding the event statistics for each threshold.

+ + +
windows
+

Matrix of maximum time weighted average concentrations (TWAC_max) and areas under the curve in µg/day * h (AUC_max_h) or µg/day * d (AUC_max_d) for the requested moving window sizes in days.

-

-

Methods

+

+
+
+

Methods

-

Public methods

- - -

-

Method new()

-

Create a TOXSWA_cwa object from a file

Usage

-

TOXSWA_cwa$new(
-  filename,
-  basedir,
-  zipfile = NULL,
-  segment = "last",
-  substance = "parent",
-  total = FALSE
-)

- -

Arguments

-

-
filename

The filename

- -
basedir

The directory to look in

- -
zipfile

Optional path to a zipfile holding the file

- -
segment

Either "last" or the number of the segment for which to read the data

- -
substance

The TOXSWA substance name (for TOXSWA 4 or higher)

- -
total

Should total concentrations be read in? If FALSE, free concentrations are read

- -

-

-

Method moving_windows()

-

Add to the `windows` field described above.

Usage

-

TOXSWA_cwa$moving_windows(windows, total = FALSE)

- -

Arguments

-

-
windows

Window sizes in days

- -
total

If TRUE, the total concentration including the amount adsorbed to +

+

Public methods

+ +

+

Method new()

+

Create a TOXSWA_cwa object from a file

+

Usage

+

TOXSWA_cwa$new(
+  filename,
+  basedir,
+  zipfile = NULL,
+  segment = "last",
+  substance = "parent",
+  total = FALSE
+)

+
+ +
+

Arguments

+

filename
+

The filename

+ + +
basedir
+

The directory to look in

+ + +
zipfile
+

Optional path to a zipfile holding the file

+ + +
segment
+

Either "last" or the number of the segment for which to read the data

+ + +
substance
+

The TOXSWA substance name (for TOXSWA 4 or higher)

+ + +
total
+

Should total concentrations be read in? If FALSE, free concentrations are read

+ + +

+
+ +

+

Method moving_windows()

+

Add to the `windows` field described above.

+

Usage

+

TOXSWA_cwa$moving_windows(windows, total = FALSE)

+
+ +
+

Arguments

+

windows
+

Window sizes in days

+ + +
total
+

If TRUE, the total concentration including the amount adsorbed to suspended matter will be used.

-

-

-

Method get_events()

+ +

+
+ +

+

Method get_events()

Populate a datataframe with event information for the specified threshold value. The resulting dataframe is stored in the `events` -field of the object.

Usage

-

TOXSWA_cwa$get_events(thresholds, total = FALSE)

+field of the object.

+

Usage

+

TOXSWA_cwa$get_events(thresholds, total = FALSE)

+
+ +
+

Arguments

+

thresholds
+

Threshold values in µg/L.

-

Arguments

-

-
thresholds

Threshold values in µg/L.

-
total

If TRUE, the total concentration including the amount adsorbed to +

total
+

If TRUE, the total concentration including the amount adsorbed to suspended matter will be used.

-

-

-

Method print()

-

Print a `TOXSWA_cwa` object

Usage

-

TOXSWA_cwa$print()

- -

-

Method clone()

-

The objects of this class are cloneable with this method.

Usage

-

TOXSWA_cwa$clone(deep = FALSE)

- -

Arguments

-

-
deep

Whether to make a deep clone.

- -

- - - -

Examples

- 
H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
-                                 basedir = "SwashProjects/project_H_sw/TOXSWA",
-                                 zipfile = system.file("testdata/SwashProjects.zip",
-                                             package = "pfm"))
-H_sw_R1_stream$get_events(c(2, 10))
-H_sw_R1_stream$moving_windows(c(7, 21))
-print(H_sw_R1_stream)
#> <TOXSWA_cwa> data from file 00003s_pa.cwa segment 20 
-#>                datetime     t t_firstjan t_rel_to_max cwa_mug_per_L
-#> 20  1978-10-01 00:00:00 0.000   273.0000      -55.333             0
-#> 40  1978-10-01 01:00:00 0.042   273.0417      -55.291             0
-#> 60  1978-10-01 02:00:00 0.083   273.0833      -55.250             0
-#> 80  1978-10-01 03:00:00 0.125   273.1250      -55.208             0
-#> 100 1978-10-01 04:00:00 0.167   273.1667      -55.166             0
-#> 120 1978-10-01 05:00:00 0.208   273.2083      -55.125             0
-#>     cwa_tot_mug_per_L
-#> 20                  0
-#> 40                  0
-#> 60                  0
-#> 80                  0
-#> 100                 0
-#> 120                 0
-#> Moving window analysis
-#>    window  max_TWAC max_AUC_h max_AUC_d
-#> 1  7 days 2.3926551  401.9660  16.74859
-#> 2 21 days 0.8369248  421.8101  17.57542
-#> Event statistics for threshold 2 
-#>   t_start   cwa_max duration pre_interval     AUC_h     AUC_d
-#> 1  44.375  4.167238    0.208       44.375  17.77202  0.740501
-#> 2  55.042 40.584010    0.583       10.459 398.21189 16.592162
-#> Event statistics for threshold 10 
-#>   t_start  cwa_max duration pre_interval   AUC_h    AUC_d
-#> 1  55.083 40.58401    0.459       55.083 379.433 15.80971
+ +

+
+ +

+

Method print()

+

Print a `TOXSWA_cwa` object

+

Usage

+

TOXSWA_cwa$print()

+
+ + +

+

Method clone()

+

The objects of this class are cloneable with this method.

+

Usage

+

TOXSWA_cwa$clone(deep = FALSE)

+
+ +
+

Arguments

+

deep
+

Whether to make a deep clone.

+ + +

+
+ +
+ +
+ +
+

Examples

+ 
H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
+                                 basedir = "SwashProjects/project_H_sw/TOXSWA",
+                                 zipfile = system.file("testdata/SwashProjects.zip",
+                                             package = "pfm"))
+H_sw_R1_stream$get_events(c(2, 10))
+H_sw_R1_stream$moving_windows(c(7, 21))
+print(H_sw_R1_stream)
+#> <TOXSWA_cwa> data from file 00003s_pa.cwa segment 20 
+#>                datetime     t t_firstjan t_rel_to_max cwa_mug_per_L
+#> 20  1978-10-01 00:00:00 0.000   273.0000      -55.333             0
+#> 40  1978-10-01 01:00:00 0.042   273.0417      -55.291             0
+#> 60  1978-10-01 02:00:00 0.083   273.0833      -55.250             0
+#> 80  1978-10-01 03:00:00 0.125   273.1250      -55.208             0
+#> 100 1978-10-01 04:00:00 0.167   273.1667      -55.166             0
+#> 120 1978-10-01 05:00:00 0.208   273.2083      -55.125             0
+#>     cwa_tot_mug_per_L
+#> 20                  0
+#> 40                  0
+#> 60                  0
+#> 80                  0
+#> 100                 0
+#> 120                 0
+#> Moving window analysis
+#>    window  max_TWAC max_AUC_h max_AUC_d
+#> 1  7 days 2.3926551  401.9660  16.74859
+#> 2 21 days 0.8369248  421.8101  17.57542
+#> Event statistics for threshold 2 
+#>   t_start   cwa_max duration pre_interval     AUC_h     AUC_d
+#> 1  44.375  4.167238    0.208       44.375  17.77202  0.740501
+#> 2  55.042 40.584010    0.583       10.459 398.21189 16.592162
+#> Event statistics for threshold 10 
+#>   t_start  cwa_max duration pre_interval   AUC_h    AUC_d
+#> 1  55.083 40.58401    0.459       55.083 379.433 15.80971
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/TSCF-1.png b/docs/reference/TSCF-1.png index efa9e0a..82c0ea8 100644 Binary files a/docs/reference/TSCF-1.png and b/docs/reference/TSCF-1.png differ diff --git a/docs/reference/TSCF.html b/docs/reference/TSCF.html index b635ba2..62ad5a0 100644 --- a/docs/reference/TSCF.html +++ b/docs/reference/TSCF.html @@ -1,72 +1,17 @@ - - - - - - - -Estimation of the transpiration stream concentration factor — TSCF • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Estimation of the transpiration stream concentration factor — TSCF • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

Estimation of the transpiration stream concentration factor

@@ -122,60 +53,63 @@ the compound should not be ionogenic (weak acid/base) or ionic.

- 
TSCF(log_Kow, method = c("briggs82", "dettenmaier09"))
+
+ 
TSCF(log_Kow, method = c("briggs82", "dettenmaier09"))
+
-

Arguments

- - - - - - - - - - -
log_Kow

The decadic logarithm of the octanol-water partition constant

method

Short name of the estimation method.

+
+

Arguments

+
log_Kow
+

The decadic logarithm of the octanol-water partition constant

-

Details

-

The Dettenmaier equation is given to show that other views on the subject exist.

-

References

+
method
+

Short name of the estimation method.

+
+
+

Details

+

The Dettenmaier equation is given to show that other views on the subject exist.

+
+
+

References

FOCUS (2014) Generic Guidance for Tier 1 FOCUS Ground Water Assessments. Version 2.2, May 2014 Dettenmaier EM, Doucette WJ and Bugbee B (2009) Chemical hydrophobicity and uptake by plant roots. Environ. Sci. Technol 43, 324 - 329

+
-

Examples

- 
plot(TSCF, -1, 5, xlab = "log Kow", ylab = "TSCF", ylim = c(0, 1.1))
TSCF_2 <- function(x) TSCF(x, method = "dettenmaier09")
-curve(TSCF_2, -1, 5, add = TRUE, lty = 2)
legend("topright", lty = 1:2, bty = "n",
-  legend = c("Briggs et al. (1982)", "Dettenmaier et al. (2009)"))
+
+

Examples

+ 
plot(TSCF, -1, 5, xlab = "log Kow", ylab = "TSCF", ylim = c(0, 1.1))
+TSCF_2 <- function(x) TSCF(x, method = "dettenmaier09")
+curve(TSCF_2, -1, 5, add = TRUE, lty = 2)
+legend("topright", lty = 1:2, bty = "n",
+  legend = c("Briggs et al. (1982)", "Dettenmaier et al. (2009)"))
+
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/chent_focus_sw.html b/docs/reference/chent_focus_sw.html index 70fd16d..13129b8 100644 --- a/docs/reference/chent_focus_sw.html +++ b/docs/reference/chent_focus_sw.html @@ -1,64 +1,12 @@ - - - - - - - -Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw • pfm - - - - + + -
-
- -
- -
+

Create a chemical compound object for FOCUS Step 1 calculations

@@ -109,98 +43,93 @@

Create a chemical compound object for FOCUS Step 1 calculations

- 
chent_focus_sw(
-  name,
-  Koc,
-  DT50_ws = NA,
-  DT50_soil = NA,
-  DT50_water = NA,
-  DT50_sediment = NA,
-  cwsat = 1000,
-  mw = NA,
-  max_soil = 1,
-  max_ws = 1
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
name

Length one character vector containing the name

Koc

Partition coefficient between organic carbon and water -in L/kg.

DT50_ws

Half-life in water/sediment systems in days

DT50_soil

Half-life in soil in days

DT50_water

Half-life in water in days (Step 2)

DT50_sediment

Half-life in sediment in days (Step 2)

cwsat

Water solubility in mg/L

mw

Molar weight in g/mol.

max_soil

Maximum observed fraction (dimensionless) in soil

max_ws

Maximum observed fraction (dimensionless) in water/sediment -systems

- -

Value

- -

A list with the substance specific properties

+
+ 
chent_focus_sw(
+  name,
+  Koc,
+  DT50_ws = NA,
+  DT50_soil = NA,
+  DT50_water = NA,
+  DT50_sediment = NA,
+  cwsat = 1000,
+  mw = NA,
+  max_soil = 1,
+  max_ws = 1
+)
+
+ +
+

Arguments

+
name
+

Length one character vector containing the name

+ + +
Koc
+

Partition coefficient between organic carbon and water +in L/kg.

+ + +
DT50_ws
+

Half-life in water/sediment systems in days

+ + +
DT50_soil
+

Half-life in soil in days

+ + +
DT50_water
+

Half-life in water in days (Step 2)

+ + +
DT50_sediment
+

Half-life in sediment in days (Step 2)

-
- +
+

Value

+ + +

A list with the substance specific properties

+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/drift_data_JKI.html b/docs/reference/drift_data_JKI.html index 36472d1..b8a0907 100644 --- a/docs/reference/drift_data_JKI.html +++ b/docs/reference/drift_data_JKI.html @@ -1,70 +1,15 @@ - - - - - - - -Deposition from spray drift expressed as percent of the applied dose as -published by the JKI — drift_data_JKI • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Deposition from spray drift expressed as percent of the applied dose as +published by the JKI — drift_data_JKI • pfm - - - - + + -
-
- -
- -
+

Deposition from spray drift expressed as percent of the applied dose as @@ -118,23 +49,24 @@ published by the German Julius-Kühn Institute (JKI).

- -

Format

- +
+

Format

A list currently containing matrices with spray drift percentage data for field crops (Ackerbau), and Pome/stone fruit, early and late (Obstbau frueh, spaet).

-

Source

- +
+
+

Source

JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved from http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html -on 2015-06-11

+on 2015-06-11, not present any more 2024-01-31

Rautmann, D., Streloke, M and Winkler, R (2001) New basic drift values in the authorization procedure for plant protection products Mitt. Biol. Bundesanst. Land- Forstwirtsch. 383, 133-141

-

Details

- +
+
+

Details

The data were extracted from the spreadsheet cited below using the R code given in the example section. The spreadsheet is not included in the package as its licence is not clear.

@@ -148,272 +80,226 @@ these values are used for spray applications with handheld/knapsack equipment (tragbare Spritz- und Sprühgerate).

Values for non-professional use listed in the JKI spreadsheet were not included.

+
-

Examples

- 

-if (FALSE) {
-  # This is the code that was used to extract the data
-  library(readxl)
-  abdrift_path <- "inst/extdata/Tabelle der Abdrifteckwerte.xls"
-  JKI_crops <- c("Ackerbau", "Obstbau frueh", "Obstbau spaet", "Weinbau frueh", "Weinbau spaet",
-    "Hopfenbau", "Flaechenkulturen > 900 l/ha", "Gleisanlagen")
-  names(JKI_crops) <- c("Field crops", "Pome/stone fruit, early", "Pome/stone fruit, late",
-    "Vines early", "Vines late", "Hops", "Areic cultures > 900 L/ha", "Railroad tracks")
-  drift_data_JKI <- list()
-
-  for (n in 1:8) {
-    drift_data_raw <- read_excel(abdrift_path, sheet = n + 1, skip = 2)
-    drift_data <- matrix(NA, nrow = 9, ncol = length(JKI_crops))
-    dimnames(drift_data) <- list(distance = drift_data_raw[[1]][1:9],
-                                            crop = JKI_crops)
-    if (n == 1) { # Values for railroad tracks only present for one application
-      drift_data[, c(1:3, 5:8)] <- as.matrix(drift_data_raw[c(2:7, 11)][1:9, ])
-    } else {
-      drift_data[, c(1:3, 5:7)] <- as.matrix(drift_data_raw[c(2:7)][1:9, ])
-    }
-    drift_data_JKI[[n]] <- drift_data
-  }
-
-  # Manual data entry from the Rautmann paper
-  drift_data_JKI[[1]]["3", "Ackerbau"] <- 0.95
-  drift_data_JKI[[1]][, "Weinbau frueh"] <- c(NA, 2.7, 1.18, 0.39, 0.2, 0.13, 0.07, 0.04, 0.03)
-  drift_data_JKI[[2]]["3", "Ackerbau"] <- 0.79
-  drift_data_JKI[[2]][, "Weinbau frueh"] <- c(NA, 2.53, 1.09, 0.35, 0.18, 0.11, 0.06, 0.03, 0.02)
-  drift_data_JKI[[3]]["3", "Ackerbau"] <- 0.68
-  drift_data_JKI[[3]][, "Weinbau frueh"] <- c(NA, 2.49, 1.04, 0.32, 0.16, 0.10, 0.05, 0.03, 0.02)
-  drift_data_JKI[[4]]["3", "Ackerbau"] <- 0.62
-  drift_data_JKI[[4]][, "Weinbau frueh"] <- c(NA, 2.44, 1.02, 0.31, 0.16, 0.10, 0.05, 0.03, 0.02)
-  drift_data_JKI[[5]]["3", "Ackerbau"] <- 0.59
-  drift_data_JKI[[5]][, "Weinbau frueh"] <- c(NA, 2.37, 1.00, 0.31, 0.15, 0.09, 0.05, 0.03, 0.02)
-  drift_data_JKI[[6]]["3", "Ackerbau"] <- 0.56
-  drift_data_JKI[[6]][, "Weinbau frueh"] <- c(NA, 2.29, 0.97, 0.30, 0.15, 0.09, 0.05, 0.03, 0.02)
-  drift_data_JKI[[7]]["3", "Ackerbau"] <- 0.55
-  drift_data_JKI[[7]][, "Weinbau frueh"] <- c(NA, 2.24, 0.94, 0.29, 0.15, 0.09, 0.05, 0.03, 0.02)
-  drift_data_JKI[[8]]["3", "Ackerbau"] <- 0.52
-  drift_data_JKI[[8]][, "Weinbau frueh"] <- c(NA, 2.16, 0.91, 0.28, 0.14, 0.09, 0.04, 0.03, 0.02)
-
-  # Save the data
-  save(drift_data_JKI, file = "data/drift_data_JKI.RData")
-}
-
-# And these are the resulting data
-drift_data_JKI
#> [[1]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      2.77            NA            NA            NA            NA
-#>       3      0.95         29.20         15.73          2.70          8.02
-#>       5      0.57         19.89          8.41          1.18          3.62
-#>       10     0.29         11.81          3.60          0.39          1.23
-#>       15     0.20          5.55          1.81          0.20          0.65
-#>       20     0.15          2.77          1.09          0.13          0.42
-#>       30     0.10          1.04          0.54          0.07          0.22
-#>       40     0.07          0.52          0.32          0.04          0.14
-#>       50     0.06          0.30          0.22          0.03          0.10
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       4.440           NA
-#>       3      19.33                          NA  0.018721696
-#>       5      11.57                       0.180  0.014363896
-#>       10      5.77                       0.050  0.010026007
-#>       15      3.84                       0.020  0.008124366
-#>       20      1.79                       0.012  0.006998158
-#>       30      0.56                       0.005  0.005670811
-#>       40      0.25                       0.003           NA
-#>       50      0.13                       0.002  0.004350831
-#> 
-#> [[2]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      2.38            NA            NA            NA            NA
-#>       3      0.79         25.53         12.13          2.53          7.23
-#>       5      0.47         16.87          6.81          1.09          3.22
-#>       10     0.24          9.61          3.11          0.35          1.07
-#>       15     0.16          5.61          1.58          0.18          0.56
-#>       20     0.12          2.59          0.90          0.11          0.36
-#>       30     0.08          0.87          0.40          0.06          0.19
-#>       40     0.06          0.40          0.23          0.03          0.12
-#>       50     0.05          0.22          0.15          0.02          0.08
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       3.780           NA
-#>       3      17.73                          NA           NA
-#>       5       9.60                       0.160           NA
-#>       10      4.18                       0.040           NA
-#>       15      2.57                       0.020           NA
-#>       20      1.21                       0.011           NA
-#>       30      0.38                       0.005           NA
-#>       40      0.17                       0.003           NA
-#>       50      0.09                       0.002           NA
-#> 
-#> [[3]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      2.01            NA            NA            NA            NA
-#>       3      0.68         23.96         11.01          2.49          6.90
-#>       5      0.41         15.79          6.04          1.04          3.07
-#>       10     0.20          8.96          2.67          0.32          1.02
-#>       15     0.14          4.24          1.39          0.16          0.54
-#>       20     0.10          2.01          0.80          0.10          0.34
-#>       30     0.07          0.70          0.36          0.05          0.18
-#>       40     0.05          0.33          0.21          0.03          0.11
-#>       50     0.04          0.19          0.13          0.02          0.08
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       3.420           NA
-#>       3      15.93                          NA           NA
-#>       5       8.57                       0.150           NA
-#>       10      3.70                       0.040           NA
-#>       15      2.26                       0.020           NA
-#>       20      1.05                       0.010           NA
-#>       30      0.34                       0.004           NA
-#>       40      0.15                       0.003           NA
-#>       50      0.08                       0.002           NA
-#> 
-#> [[4]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      1.85            NA            NA            NA            NA
-#>       3      0.62         23.61         10.12          2.44          6.71
-#>       5      0.38         15.42          5.60          1.02          2.99
-#>       10     0.19          8.66          2.50          0.31          0.99
-#>       15     0.13          4.01          1.28          0.16          0.52
-#>       20     0.10          1.89          0.75          0.10          0.33
-#>       30     0.06          0.66          0.35          0.05          0.17
-#>       40     0.05          0.31          0.20          0.03          0.11
-#>       50     0.04          0.17          0.13          0.02          0.08
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       2.290           NA
-#>       3      15.38                          NA           NA
-#>       5       8.26                       0.120           NA
-#>       10      3.55                       0.030           NA
-#>       15      2.17                       0.020           NA
-#>       20      0.93                       0.009           NA
-#>       30      0.31                       0.004           NA
-#>       40      0.14                       0.002           NA
-#>       50      0.08                       0.002           NA
-#> 
-#> [[5]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      1.75            NA            NA            NA            NA
-#>       3      0.59         23.12          9.74          2.37          6.59
-#>       5      0.36         15.06          5.41          1.00          2.93
-#>       10     0.18          8.42          2.43          0.31          0.98
-#>       15     0.12          3.83          1.24          0.15          0.51
-#>       20     0.09          1.81          0.72          0.09          0.33
-#>       30     0.06          0.63          0.34          0.05          0.17
-#>       40     0.05          0.30          0.20          0.03          0.11
-#>       50     0.04          0.17          0.13          0.02          0.08
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       2.120           NA
-#>       3      15.12                          NA           NA
-#>       5       7.99                       0.110           NA
-#>       10      3.36                       0.030           NA
-#>       15      2.03                       0.010           NA
-#>       20      0.88                       0.008           NA
-#>       30      0.29                       0.004           NA
-#>       40      0.14                       0.002           NA
-#>       50      0.07                       0.002           NA
-#> 
-#> [[6]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      1.64            NA            NA            NA            NA
-#>       3      0.56         22.76          9.21          2.29          6.41
-#>       5      0.34         14.64          5.18          0.97          2.85
-#>       10     0.17          8.04          2.38          0.30          0.95
-#>       15     0.11          3.71          1.20          0.15          0.50
-#>       20     0.09          1.75          0.68          0.09          0.32
-#>       30     0.06          0.61          0.31          0.05          0.17
-#>       40     0.04          0.29          0.17          0.03          0.11
-#>       50     0.03          0.16          0.11          0.02          0.07
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       1.980           NA
-#>       3      14.90                          NA           NA
-#>       5       7.79                       0.100           NA
-#>       10      3.23                       0.030           NA
-#>       15      1.93                       0.010           NA
-#>       20      0.83                       0.008           NA
-#>       30      0.28                       0.004           NA
-#>       40      0.13                       0.002           NA
-#>       50      0.07                       0.001           NA
-#> 
-#> [[7]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      1.61            NA            NA            NA            NA
-#>       3      0.55         22.69          9.10          2.24          6.33
-#>       5      0.33         14.45          5.11          0.94          2.81
-#>       10     0.17          7.83          2.33          0.29          0.94
-#>       15     0.11          3.62          1.20          0.15          0.49
-#>       20     0.08          1.71          0.67          0.09          0.31
-#>       30     0.06          0.60          0.30          0.05          0.16
-#>       40     0.04          0.28          0.17          0.03          0.10
-#>       50     0.03          0.16          0.11          0.02          0.07
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       1.930           NA
-#>       3      14.63                          NA           NA
-#>       5       7.60                       0.100           NA
-#>       10      3.13                       0.030           NA
-#>       15      1.86                       0.010           NA
-#>       20      0.81                       0.008           NA
-#>       30      0.26                       0.004           NA
-#>       40      0.12                       0.002           NA
-#>       50      0.06                       0.001           NA
-#> 
-#> [[8]]
-#>         crop
-#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
-#>       1      1.52            NA            NA            NA            NA
-#>       3      0.52         22.24          8.66          2.16          6.26
-#>       5      0.31         14.09          4.92          0.91          2.78
-#>       10     0.16          7.58          2.29          0.28          0.93
-#>       15     0.11          3.48          1.14          0.14          0.49
-#>       20     0.08          1.65          0.65          0.09          0.31
-#>       30     0.05          0.57          0.29          0.04          0.16
-#>       40     0.04          0.27          0.16          0.03          0.10
-#>       50     0.03          0.15          0.11          0.02          0.07
-#>         crop
-#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
-#>       1         NA                       1.640           NA
-#>       3      13.53                          NA           NA
-#>       5       7.15                       0.090           NA
-#>       10      3.01                       0.020           NA
-#>       15      1.82                       0.010           NA
-#>       20      0.78                       0.007           NA
-#>       30      0.25                       0.003           NA
-#>       40      0.12                       0.002           NA
-#>       50      0.06                       0.001           NA
-#>
+
+

Examples

+ 
drift_data_JKI
+#> [[1]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      2.77            NA            NA            NA            NA
+#>       3      0.95         29.20         15.73          2.70          8.02
+#>       5      0.57         19.89          8.41          1.18          3.62
+#>       10     0.29         11.81          3.60          0.39          1.23
+#>       15     0.20          5.55          1.81          0.20          0.65
+#>       20     0.15          2.77          1.09          0.13          0.42
+#>       30     0.10          1.04          0.54          0.07          0.22
+#>       40     0.07          0.52          0.32          0.04          0.14
+#>       50     0.06          0.30          0.22          0.03          0.10
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       4.440           NA
+#>       3      19.33                          NA  0.018721696
+#>       5      11.57                       0.180  0.014363896
+#>       10      5.77                       0.050  0.010026007
+#>       15      3.84                       0.020  0.008124366
+#>       20      1.79                       0.012  0.006998158
+#>       30      0.56                       0.005  0.005670811
+#>       40      0.25                       0.003           NA
+#>       50      0.13                       0.002  0.004350831
+#> 
+#> [[2]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      2.38            NA            NA            NA            NA
+#>       3      0.79         25.53         12.13          2.53          7.23
+#>       5      0.47         16.87          6.81          1.09          3.22
+#>       10     0.24          9.61          3.11          0.35          1.07
+#>       15     0.16          5.61          1.58          0.18          0.56
+#>       20     0.12          2.59          0.90          0.11          0.36
+#>       30     0.08          0.87          0.40          0.06          0.19
+#>       40     0.06          0.40          0.23          0.03          0.12
+#>       50     0.05          0.22          0.15          0.02          0.08
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       3.780           NA
+#>       3      17.73                          NA           NA
+#>       5       9.60                       0.160           NA
+#>       10      4.18                       0.040           NA
+#>       15      2.57                       0.020           NA
+#>       20      1.21                       0.011           NA
+#>       30      0.38                       0.005           NA
+#>       40      0.17                       0.003           NA
+#>       50      0.09                       0.002           NA
+#> 
+#> [[3]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      2.01            NA            NA            NA            NA
+#>       3      0.68         23.96         11.01          2.49          6.90
+#>       5      0.41         15.79          6.04          1.04          3.07
+#>       10     0.20          8.96          2.67          0.32          1.02
+#>       15     0.14          4.24          1.39          0.16          0.54
+#>       20     0.10          2.01          0.80          0.10          0.34
+#>       30     0.07          0.70          0.36          0.05          0.18
+#>       40     0.05          0.33          0.21          0.03          0.11
+#>       50     0.04          0.19          0.13          0.02          0.08
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       3.420           NA
+#>       3      15.93                          NA           NA
+#>       5       8.57                       0.150           NA
+#>       10      3.70                       0.040           NA
+#>       15      2.26                       0.020           NA
+#>       20      1.05                       0.010           NA
+#>       30      0.34                       0.004           NA
+#>       40      0.15                       0.003           NA
+#>       50      0.08                       0.002           NA
+#> 
+#> [[4]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      1.85            NA            NA            NA            NA
+#>       3      0.62         23.61         10.12          2.44          6.71
+#>       5      0.38         15.42          5.60          1.02          2.99
+#>       10     0.19          8.66          2.50          0.31          0.99
+#>       15     0.13          4.01          1.28          0.16          0.52
+#>       20     0.10          1.89          0.75          0.10          0.33
+#>       30     0.06          0.66          0.35          0.05          0.17
+#>       40     0.05          0.31          0.20          0.03          0.11
+#>       50     0.04          0.17          0.13          0.02          0.08
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       2.290           NA
+#>       3      15.38                          NA           NA
+#>       5       8.26                       0.120           NA
+#>       10      3.55                       0.030           NA
+#>       15      2.17                       0.020           NA
+#>       20      0.93                       0.009           NA
+#>       30      0.31                       0.004           NA
+#>       40      0.14                       0.002           NA
+#>       50      0.08                       0.002           NA
+#> 
+#> [[5]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      1.75            NA            NA            NA            NA
+#>       3      0.59         23.12          9.74          2.37          6.59
+#>       5      0.36         15.06          5.41          1.00          2.93
+#>       10     0.18          8.42          2.43          0.31          0.98
+#>       15     0.12          3.83          1.24          0.15          0.51
+#>       20     0.09          1.81          0.72          0.09          0.33
+#>       30     0.06          0.63          0.34          0.05          0.17
+#>       40     0.05          0.30          0.20          0.03          0.11
+#>       50     0.04          0.17          0.13          0.02          0.08
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       2.120           NA
+#>       3      15.12                          NA           NA
+#>       5       7.99                       0.110           NA
+#>       10      3.36                       0.030           NA
+#>       15      2.03                       0.010           NA
+#>       20      0.88                       0.008           NA
+#>       30      0.29                       0.004           NA
+#>       40      0.14                       0.002           NA
+#>       50      0.07                       0.002           NA
+#> 
+#> [[6]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      1.64            NA            NA            NA            NA
+#>       3      0.56         22.76          9.21          2.29          6.41
+#>       5      0.34         14.64          5.18          0.97          2.85
+#>       10     0.17          8.04          2.38          0.30          0.95
+#>       15     0.11          3.71          1.20          0.15          0.50
+#>       20     0.09          1.75          0.68          0.09          0.32
+#>       30     0.06          0.61          0.31          0.05          0.17
+#>       40     0.04          0.29          0.17          0.03          0.11
+#>       50     0.03          0.16          0.11          0.02          0.07
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       1.980           NA
+#>       3      14.90                          NA           NA
+#>       5       7.79                       0.100           NA
+#>       10      3.23                       0.030           NA
+#>       15      1.93                       0.010           NA
+#>       20      0.83                       0.008           NA
+#>       30      0.28                       0.004           NA
+#>       40      0.13                       0.002           NA
+#>       50      0.07                       0.001           NA
+#> 
+#> [[7]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      1.61            NA            NA            NA            NA
+#>       3      0.55         22.69          9.10          2.24          6.33
+#>       5      0.33         14.45          5.11          0.94          2.81
+#>       10     0.17          7.83          2.33          0.29          0.94
+#>       15     0.11          3.62          1.20          0.15          0.49
+#>       20     0.08          1.71          0.67          0.09          0.31
+#>       30     0.06          0.60          0.30          0.05          0.16
+#>       40     0.04          0.28          0.17          0.03          0.10
+#>       50     0.03          0.16          0.11          0.02          0.07
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       1.930           NA
+#>       3      14.63                          NA           NA
+#>       5       7.60                       0.100           NA
+#>       10      3.13                       0.030           NA
+#>       15      1.86                       0.010           NA
+#>       20      0.81                       0.008           NA
+#>       30      0.26                       0.004           NA
+#>       40      0.12                       0.002           NA
+#>       50      0.06                       0.001           NA
+#> 
+#> [[8]]
+#>         crop
+#> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
+#>       1      1.52            NA            NA            NA            NA
+#>       3      0.52         22.24          8.66          2.16          6.26
+#>       5      0.31         14.09          4.92          0.91          2.78
+#>       10     0.16          7.58          2.29          0.28          0.93
+#>       15     0.11          3.48          1.14          0.14          0.49
+#>       20     0.08          1.65          0.65          0.09          0.31
+#>       30     0.05          0.57          0.29          0.04          0.16
+#>       40     0.04          0.27          0.16          0.03          0.10
+#>       50     0.03          0.15          0.11          0.02          0.07
+#>         crop
+#> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen
+#>       1         NA                       1.640           NA
+#>       3      13.53                          NA           NA
+#>       5       7.15                       0.090           NA
+#>       10      3.01                       0.020           NA
+#>       15      1.82                       0.010           NA
+#>       20      0.78                       0.007           NA
+#>       30      0.25                       0.003           NA
+#>       40      0.12                       0.002           NA
+#>       50      0.06                       0.001           NA
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/endpoint.html b/docs/reference/endpoint.html index 39071ee..8ca3467 100644 --- a/docs/reference/endpoint.html +++ b/docs/reference/endpoint.html @@ -1,67 +1,15 @@ - - - - - - - -Retrieve endpoint information from the chyaml field of a chent object — endpoint • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Retrieve endpoint information from the chyaml field of a chent object — endpoint • pfm - - - - - - - - - - - - - - + + -
-
- -
- -
+

Retrieve endpoint information from the chyaml field of a chent object

@@ -115,136 +49,131 @@ chyaml field. Such information is extracted and optionally aggregated by this function.

- 
endpoint(
-  chent,
-  medium = "soil",
-  type = c("degradation", "sorption"),
-  lab_field = c(NA, "laboratory", "field"),
-  redox = c(NA, "aerobic", "anaerobic"),
-  value = c("DT50ref", "Kfoc", "N"),
-  aggregator = geomean,
-  raw = FALSE,
-  signif = 3
-)
-
-soil_DT50(
-  chent,
-  aggregator = geomean,
-  signif = 3,
-  lab_field = "laboratory",
-  value = "DT50ref",
-  redox = "aerobic",
-  raw = FALSE
-)
-
-soil_Kfoc(chent, aggregator = geomean, signif = 3, value = "Kfoc", raw = FALSE)
-
-soil_N(chent, aggregator = mean, signif = 3, raw = FALSE)
-
-soil_sorption(
-  chent,
-  values = c("Kfoc", "N"),
-  aggregators = c(Kfoc = geomean, Koc = geomean, N = mean),
-  signif = c(Kfoc = 3, N = 3),
-  raw = FALSE
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
chent

The chent object to get the information from

medium

The medium for which information is sought

type

The information type

lab_field

If not NA, do we want laboratory or field endpoints

redox

If not NA, are we looking for aerobic or anaerobic data

value

The name of the value we want. The list given in the -usage section is not exclusive

aggregator

The aggregator function. Can be mean, -geomean, or identity, for example.

raw

Should the number(s) be returned as stored in the chent +

+ 
endpoint(
+  chent,
+  medium = "soil",
+  type = c("degradation", "sorption"),
+  lab_field = c(NA, "laboratory", "field"),
+  redox = c(NA, "aerobic", "anaerobic"),
+  value = c("DT50ref", "Kfoc", "N"),
+  aggregator = geomean,
+  raw = FALSE,
+  signif = 3
+)
+
+soil_DT50(
+  chent,
+  aggregator = geomean,
+  signif = 3,
+  lab_field = "laboratory",
+  value = "DT50ref",
+  redox = "aerobic",
+  raw = FALSE
+)
+
+soil_Kfoc(chent, aggregator = geomean, signif = 3, value = "Kfoc", raw = FALSE)
+
+soil_N(chent, aggregator = mean, signif = 3, raw = FALSE)
+
+soil_sorption(
+  chent,
+  values = c("Kfoc", "N"),
+  aggregators = c(Kfoc = geomean, Koc = geomean, N = mean),
+  signif = c(Kfoc = 3, N = 3),
+  raw = FALSE
+)
+
+ +
+

Arguments

+
chent
+

The chent object to get the information from

+ + +
medium
+

The medium for which information is sought

+ + +
type
+

The information type

+ + +
lab_field
+

If not NA, do we want laboratory or field endpoints

+ + +
redox
+

If not NA, are we looking for aerobic or anaerobic data

+ + +
value
+

The name of the value we want. The list given in the +usage section is not exclusive

+ + +
aggregator
+

The aggregator function. Can be mean, +geomean, or identity, for example.

+ + +
raw
+

Should the number(s) be returned as stored in the chent object (could be a character value) to retain original information -about precision?

signif

How many significant digits do we want

values

The values to be returned

aggregators

A named vector of aggregator functions to be used

- -

Value

- -

The result from applying the aggregator function to +about precision?

+ + +
signif
+

How many significant digits do we want

+ + +
values
+

The values to be returned

+ + +
aggregators
+

A named vector of aggregator functions to be used

+ +
+
+

Value

+ + +

The result from applying the aggregator function to the values converted to a numeric vector, rounded to the given number of significant digits, or, if raw = TRUE, the values as a character value, retaining any implicit information on precision that may be present.

-

Details

- +
+
+

Details

The functions soil_* are functions to extract soil specific endpoints. For the Freundlich exponent, the capital letter N is used in order to facilitate dealing with such data in R. In pesticide fate modelling, this exponent is often called 1/n.

+
- +
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/geomean.html b/docs/reference/geomean.html index 34befc3..540b33b 100644 --- a/docs/reference/geomean.html +++ b/docs/reference/geomean.html @@ -1,68 +1,16 @@ - - - - - - - -Calculate the geometric mean — geomean • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate the geometric mean — geomean • pfm - - - - - - - - - - - - - - + + -
-
- -
- -
+

Calculate the geometric mean

@@ -111,64 +45,68 @@ If at least one element of the vector is 0, it returns 0." />

Based on some posts in a thread on Stackoverflow -http://stackoverflow.com/questions/2602583/geometric-mean-is-there-a-built-in +http://stackoverflow.com/questions/2602583/geometric-mean-is-there-a-built-in This function returns NA if NA values are present and na.rm = FALSE (default). If negative values are present, it gives an error message. If at least one element of the vector is 0, it returns 0.

- 
geomean(x, na.rm = FALSE)
+
+ 
geomean(x, na.rm = FALSE)
+
-

Arguments

- - - - - - - - - - -
x

Vector of numbers

na.rm

Should NA values be omitted?

+
+

Arguments

+
x
+

Vector of numbers

-

Value

-

The geometric mean

+
na.rm
+

Should NA values be omitted?

-

Examples

- 
geomean(c(1, 3, 9))
#> [1] 3
geomean(c(1, 3, NA, 9))
#> [1] NA
if (FALSE) geomean(c(1, -3, 9)) # returns an error
-
- +
+

Value

+ +

The geometric mean

+
+

Author

Johannes Ranke

+
+ +
+

Examples

+ 
geomean(c(1, 3, 9))
+#> [1] 3
+geomean(c(1, 3, NA, 9))
+#> [1] NA
+geomean(c(1, -3, 9)) # returns an error
+#> Error in geomean(c(1, -3, 9)): Only defined for positive numbers
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/get_vertex.html b/docs/reference/get_vertex.html index 3d0bc2d..c6dc00c 100644 --- a/docs/reference/get_vertex.html +++ b/docs/reference/get_vertex.html @@ -1,62 +1,13 @@ - - - - - - - -Fit a parabola through three points — get_vertex • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Fit a parabola through three points — get_vertex • pfm - - - - + + -
-
- -
- -
+

Fit a parabola through three points

@@ -105,55 +41,46 @@ https://stackoverflow.com/a/717791" />
-

This was inspired by an answer on stackoverflow https://stackoverflow.com/a/717791

-
- 
get_vertex(x, y)
- -

Arguments

- - - - - - - - - - -
x

Three x coordinates

y

Three y coordinates

- +
+ 
get_vertex(x, y)
+
-
- +
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/index.html b/docs/reference/index.html index fed30cc..3d660d3 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -1,66 +1,12 @@ - - - - - - - -Function reference • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Function reference • pfm - - - - + + -
-
- -
- -
+

Reference

- - - - - - - - - - -
-

General utility functions

-

Functions that are independent of specific fate modelling areas

+ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
+

General utility functions

+

Functions that are independent of specific fate modelling areas

+

geomean()

Calculate the geometric mean

+

one_box()

Create a time series of decline data

+

plot(<one_box>)

Plot time series of decline data

+

sawtooth()

Create decline time series for multiple applications

+

twa()

Calculate a time weighted average concentration

+

max_twa()

The maximum time weighted average concentration for a moving window

+

pfm_degradation()

Calculate a time course of relative concentrations based on an mkinmod model

+

SFO_actual_twa()

Actual and maximum moving window time average concentrations for SFO kinetics

+

FOMC_actual_twa()

Actual and maximum moving window time average concentrations for FOMC kinetics

-

set_nd_nq() set_nd_nq_focus()

-

Set non-detects and unquantified values in residue series without replicates

+
+

reexports set_nd_nq set_nd_nq_focus

+

Objects exported from other packages

TSCF()

Estimation of the transpiration stream concentration factor

-

Predicted environmental concentrations in soil

+
+

Predicted environmental concentrations in soil

+

PEC_soil()

Calculate predicted environmental concentrations in soil

+

PEC_soil_mets()

Calculate initial and accumulation PEC soil for a set of metabolites

+

soil_scenario_data_EFSA_2015

Properties of the predefined scenarios from the EFSA guidance from 2015

+

soil_scenario_data_EFSA_2017

Properties of the predefined scenarios from the EFSA guidance from 2017

+

PEC_FOMC_accu_rel()

Get the relative accumulation of an FOMC model over multiples of an interval

+

EFSA_washoff_2017

Subset of EFSA crop washoff default values

-

Predicted environmental concentrations in groundwater

+
+

Predicted environmental concentrations in groundwater

+

FOCUS_GW_scenarios_2012

A very small subset of the FOCUS Groundwater scenario definitions

+

EFSA_GW_interception_2014

Subset of EFSA crop interception default values for groundwater modelling

-

Predicted environmental concentrations in surface water

+
+

Predicted environmental concentrations in surface water

+

PEC_sw_drift()

Calculate predicted environmental concentrations in surface water due to drift

+

drift_data_JKI

Deposition from spray drift expressed as percent of the applied dose as published by the JKI

+

PEC_sw_drainage_UK()

Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method

+

PEC_sw_sed()

Calculate predicted environmental concentrations in sediment from surface water concentrations

+

PEC_sw_focus()

Calculate PEC surface water at FOCUS Step 1

+

chent_focus_sw()

Create a chemical compound object for FOCUS Step 1 calculations

+

FOCUS_Step_12_scenarios

Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator

+

PEC_sw_exposit_drainage()

Calculate PEC surface water due to drainage as in Exposit 3

+

PEC_sw_exposit_runoff()

Calculate PEC surface water due to runoff and erosion as in Exposit 3

+

perc_runoff_exposit

Runoff loss percentages as used in Exposit 3

+

perc_runoff_reduction_exposit

Runoff reduction percentages as used in Exposit

+

TOXSWA_cwa

R6 class for holding TOXSWA water concentration data and associated statistics

+

read.TOXSWA_cwa()

Read TOXSWA surface water concentrations

+

plot(<TOXSWA_cwa>)

Plot TOXSWA surface water concentrations

-

Classifications and indicators

-

Evaluating environmental fate properties

+
+

Classifications and indicators

+

Evaluating environmental fate properties

+

SSLRC_mobility_classification()

Determine the SSLRC mobility classification for a chemical substance from its Koc

+

GUS() print(<GUS_result>)

Groundwater ubiquity score based on Gustafson (1989)

-

Work with chent objects containing relevant information

+
+

Work with chent objects containing relevant information

+

endpoint() soil_DT50() soil_Kfoc() soil_N() soil_sorption()

Retrieve endpoint information from the chyaml field of a chent object

-

Utilities

+
+

Utilities

+

get_vertex()

Fit a parabola through three points

- +
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/max_twa.html b/docs/reference/max_twa.html index 1d24c2a..c0387d7 100644 --- a/docs/reference/max_twa.html +++ b/docs/reference/max_twa.html @@ -1,65 +1,16 @@ - - - - - - - -The maximum time weighted average concentration for a moving window — max_twa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - -The maximum time weighted average concentration for a moving window — max_twa • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

The maximum time weighted average concentration for a moving window

@@ -108,101 +44,90 @@ max_twa." />
- -

If you generate your time series using sawtooth, +

If you generate your time series using sawtooth, you need to make sure that the length of the time series allows for finding the maximum. It is therefore recommended to check this using -plot.one_box using the window size for the argument +plot.one_box using the window size for the argument max_twa.

-
- 
max_twa(x, window = 21)
- -

Arguments

- - - - - - - - - - -
x

An object of type one_box

window

The size of the moving window

- -

Details

+
+ 
max_twa(x, window = 21)
+
+ +
+

Arguments

+
x
+

An object of type one_box

+ +
window
+

The size of the moving window

+ +
+
+

Details

The method working directly on fitted mkinfit objects uses the equations given in the PEC soil section of the FOCUS guidance and is restricted SFO, FOMC and DFOP models and to the parent compound

- -

References

- -

FOCUS (2006) “Guidance Document on Estimating Persistence and +

+
+

References

+

FOCUS (2006) “Guidance Document on Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU - Registration” Report of the FOCUS Work Group on Degradation Kinetics, + Registration” Report of the FOCUS Work Group on Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, - http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

- -

See also

- -

twa

- - -

Examples

- 
pred <- sawtooth(one_box(10),
-  applications = data.frame(time = c(0, 7), amount = c(1, 1)))
-max_twa(pred)
#> $max
-#>    parent 
-#> 0.9537545 
-#> 
-#> $window_start
-#> parent 
-#>      0 
-#> 
-#> $window_end
-#> parent 
-#>     21 
-#> 
pred_FOMC <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-max_twa(pred_FOMC)
#>       21 
-#> 18.22124
-
- +
+

See also

+

twa

+
+
+

Examples

+ 
pred <- sawtooth(one_box(10),
+  applications = data.frame(time = c(0, 7), amount = c(1, 1)))
+max_twa(pred)
+#> $max
+#>    parent 
+#> 0.9537545 
+#> 
+#> $window_start
+#> parent 
+#>      0 
+#> 
+#> $window_end
+#> parent 
+#>     21 
+#> 
+pred_FOMC <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+max_twa(pred_FOMC)
+#>       21 
+#> 18.22124 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/one_box-1.png b/docs/reference/one_box-1.png index 10bc9f7..eb4d2ee 100644 Binary files a/docs/reference/one_box-1.png and b/docs/reference/one_box-1.png differ diff --git a/docs/reference/one_box-2.png b/docs/reference/one_box-2.png index 9cbb045..1b34c2d 100644 Binary files a/docs/reference/one_box-2.png and b/docs/reference/one_box-2.png differ diff --git a/docs/reference/one_box-3.png b/docs/reference/one_box-3.png index ec1cc0c..e4e41ea 100644 Binary files a/docs/reference/one_box-3.png and b/docs/reference/one_box-3.png differ diff --git a/docs/reference/one_box.html b/docs/reference/one_box.html index cf58a58..62875b3 100644 --- a/docs/reference/one_box.html +++ b/docs/reference/one_box.html @@ -1,64 +1,12 @@ - - - - - - - -Create a time series of decline data — one_box • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create a time series of decline data — one_box • pfm - - - - + + -
-
- -
- -
+

Create a time series of decline data

@@ -109,99 +43,105 @@

Create a time series of decline data

- 
one_box(x, ini, ..., t_end = 100, res = 0.01)
-
-# S3 method for numeric
-one_box(x, ini = 1, ..., t_end = 100, res = 0.01)
-
-# S3 method for character
-one_box(x, ini = 1, parms, ..., t_end = 100, res = 0.01)
-
-# S3 method for mkinfit
-one_box(x, ini = "model", ..., t_end = 100, res = 0.01)
+
+ 
one_box(x, ini, ..., t_end = 100, res = 0.01)
+
+# S3 method for numeric
+one_box(x, ini = 1, ..., t_end = 100, res = 0.01)
+
+# S3 method for character
+one_box(x, ini = 1, parms, ..., t_end = 100, res = 0.01)
+
+# S3 method for mkinfit
+one_box(x, ini = "model", ..., t_end = 100, res = 0.01)
+
-

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - -
x

When numeric, this is the half-life to be used for an exponential +

+

Arguments

+
x
+

When numeric, this is the half-life to be used for an exponential decline. When a character string specifying a parent decline model is given e.g. FOMC, parms must contain the corresponding parameters. -If x is an mkinfit object, the decline is calculated from this -object.

ini

The initial amount. If x is an mkinfit object, and +If x is an mkinfit object, the decline is calculated from this +object.

+ + +
ini
+

The initial amount. If x is an mkinfit object, and ini is 'model', the fitted initial concentrations are used. Otherwise, ini must be numeric. If it has length one, it is used for the parent and initial values of metabolites are zero, otherwise, it must give values for -all observed variables.

...

Further arguments passed to methods

t_end

End of the time series

res

Resolution of the time series

parms

A named numeric vector containing the model parameters

- -

Value

- -

An object of class one_box, inheriting from ts.

- -

Examples

- 
# Only use a half-life
-pred_0 <- one_box(10)
-plot(pred_0)

-# Use a fitted mkinfit model
-require(mkin)
-fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-pred_1 <- one_box(fit)
-plot(pred_1)

-# Use a model with more than one observed variable
-m_2 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
pred_2 <- one_box(fit_2, ini = "model")
-plot(pred_2)
-
- +
+

Value

+ + +

An object of class one_box, inheriting from ts.

+
+ +
+

Examples

+ 
# Only use a half-life
+pred_0 <- one_box(10)
+plot(pred_0)
+
+
+# Use a fitted mkinfit model
+require(mkin)
+fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+pred_1 <- one_box(fit)
+plot(pred_1)
+
+
+# Use a model with more than one observed variable
+m_2 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
+#> Temporary DLL for differentials generated and loaded
+fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE)
+#> Warning: Observations with value of zero were removed from the data
+pred_2 <- one_box(fit_2, ini = "model")
+plot(pred_2)
+
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/perc_runoff_exposit.html b/docs/reference/perc_runoff_exposit.html index 38c1f70..ca7b25d 100644 --- a/docs/reference/perc_runoff_exposit.html +++ b/docs/reference/perc_runoff_exposit.html @@ -1,67 +1,12 @@ - - - - - - - -Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit • pfm - - - - + + -
-
- -
- -
+

Runoff loss percentages as used in Exposit 3

@@ -112,64 +43,71 @@

A table of the loss percentages used in Exposit 3 for the twelve different Koc classes

+
+ 
perc_runoff_exposit
+
- -

Format

- +
+

Format

A data frame with percentage values for the dissolved fraction and the fraction - bound to eroding particles, with Koc classes used as row names

-
Koc_lower_bound

The lower bound of the Koc class

-
dissolved

The percentage of the applied substance transferred to an + bound to eroding particles, with Koc classes used as row names

Koc_lower_bound
+

The lower bound of the Koc class

+ +
dissolved
+

The percentage of the applied substance transferred to an adjacent water body in the dissolved phase

-
bound

The percentage of the applied substance transferred to an - adjacent water body bound to eroding particles

- -
-

Source

+
bound
+

The percentage of the applied substance transferred to an + adjacent water body bound to eroding particles

+ +
+
+

Source

Excel 3.02 spreadsheet available from - https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html

- -

Examples

- 
print(perc_runoff_exposit)
#>              Koc_lower_bound dissolved bound
-#> 0-20                       0     0.110 0.000
-#> >20-50                    20     0.151 0.000
-#> >50-100                   50     0.197 0.000
-#> >100-200                 100     0.248 0.001
-#> >200-500                 200     0.224 0.004
-#> >500-1000                500     0.184 0.020
-#> >1000-2000              1000     0.133 0.042
-#> >2000-5000              2000     0.084 0.091
-#> >5000-10000             5000     0.037 0.159
-#> >10000-20000           10000     0.031 0.192
-#> >20000-50000           20000     0.014 0.291
-#> >50000                 50000     0.001 0.451
+ https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html

+
+ +
+

Examples

+ 
print(perc_runoff_exposit)
+#>              Koc_lower_bound dissolved bound
+#> 0-20                       0     0.110 0.000
+#> >20-50                    20     0.151 0.000
+#> >50-100                   50     0.197 0.000
+#> >100-200                 100     0.248 0.001
+#> >200-500                 200     0.224 0.004
+#> >500-1000                500     0.184 0.020
+#> >1000-2000              1000     0.133 0.042
+#> >2000-5000              2000     0.084 0.091
+#> >5000-10000             5000     0.037 0.159
+#> >10000-20000           10000     0.031 0.192
+#> >20000-50000           20000     0.014 0.291
+#> >50000                 50000     0.001 0.451
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/perc_runoff_reduction_exposit.html b/docs/reference/perc_runoff_reduction_exposit.html index dd37f4b..6075ed0 100644 --- a/docs/reference/perc_runoff_reduction_exposit.html +++ b/docs/reference/perc_runoff_reduction_exposit.html @@ -1,67 +1,12 @@ - - - - - - - -Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit • pfm - - - - + + -
-
- -
- -
+

Runoff reduction percentages as used in Exposit

@@ -112,80 +43,83 @@

A table of the runoff reduction percentages used in Exposit 3 for different vegetated buffer widths

- 
perc_runoff_reduction_exposit
- - -

Format

+
+ 
perc_runoff_reduction_exposit
+
+
+

Format

A named list of data frames with reduction percentage values for the dissolved fraction and the fraction bound to eroding particles, with vegetated buffer widths as row names. The names of the list items are the Exposit versions -from which the values were taken.

-
dissolved

The reduction percentage for the dissolved phase

-
bound

The reduction percentage for the particulate phase

- -
+from which the values were taken.

dissolved
+

The reduction percentage for the dissolved phase

-

Source

+
bound
+

The reduction percentage for the particulate phase

+ +
+
+

Source

Excel 3.02 spreadsheet available from - https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html

+ https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html

Agroscope version 3.01a with additional runoff factors for 3 m and 6 m buffer zones received from Muris Korkaric (not published). The variant 3.01a2 was introduced for consistency with previous calculations performed by Agroscope for a 3 m buffer zone.

+
-

Examples

- 
print(perc_runoff_reduction_exposit)
-
#> $`3.02`
-#>           dissolved bound
-#> No buffer         0     0
-#> 5 m              40    40
-#> 10 m             60    85
-#> 20 m             80    95
-#> 
-#> $`3.01a`
-#>           dissolved bound
-#> No buffer         0     0
-#> 3 m              25    30
-#> 5 m              40    40
-#> 6 m              45    55
-#> 10 m             60    85
-#> 20 m             80    95
-#> 
-#> $`3.01a2`
-#>           dissolved bound
-#> No buffer         0     0
-#> 3 m              25    25
-#> 
-#> $`2.0`
-#>           dissolved bound
-#> No buffer       0.0   0.0
-#> 20 m           97.5  97.5
-#>
+
+

Examples

+ 
print(perc_runoff_reduction_exposit)
+#> $`3.02`
+#>           dissolved bound
+#> No buffer         0     0
+#> 5 m              40    40
+#> 10 m             60    85
+#> 20 m             80    95
+#> 
+#> $`3.01a`
+#>           dissolved bound
+#> No buffer         0     0
+#> 3 m              25    30
+#> 5 m              40    40
+#> 6 m              45    55
+#> 10 m             60    85
+#> 20 m             80    95
+#> 
+#> $`3.01a2`
+#>           dissolved bound
+#> No buffer         0     0
+#> 3 m              25    25
+#> 
+#> $`2.0`
+#>           dissolved bound
+#> No buffer       0.0   0.0
+#> 20 m           97.5  97.5
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/pesticide.txt b/docs/reference/pesticide.txt deleted file mode 100644 index 4618e8b..0000000 --- a/docs/reference/pesticide.txt +++ /dev/null @@ -1,3 +0,0 @@ -Active Substance Compound Comment Mol mass a.i. Mol mass met. Water solubility KOC assessed compound KOC parent compound DT50 Max. in Water Max. in Soil asessed compound App. Rate Number of App. Time between app. App. Type DT50 soil parent compound DT50 soil DT50 water DT50 sediment Region / Season Interception class -Dummy 1 cereals, spring n NA Dummy 1 cereals, spring n NA -99.00 -99.00 6000.00 344.80 0.00E+00 6.00 0.00E+00 0.00E+00 3000.00 1.00 0.00E+00 0.00E+00 0.00E+00 -99.00 -99.00 -99.00 0.00E+00 1.00 -M1 cereals, winter n NA M1 cereals, winter n NA 250.00 100.00 100.00 50.00 100.00 100.00 0.00E+00 50.00 1000.00 1.00 0.00E+00 1.00 -99.00 -99.00 -99.00 -99.00 0.00E+00 1.00 diff --git a/docs/reference/pfm_degradation.html b/docs/reference/pfm_degradation.html index 8d06107..724a1aa 100644 --- a/docs/reference/pfm_degradation.html +++ b/docs/reference/pfm_degradation.html @@ -1,67 +1,12 @@ - - - - - - - -Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation • pfm - - - - + + -
-
- -
- -
+

Calculate a time course of relative concentrations based on an mkinmod model

@@ -112,80 +43,83 @@

Calculate a time course of relative concentrations based on an mkinmod model

- 
pfm_degradation(
-  model = "SFO",
-  DT50 = 1000,
-  parms = c(k_parent = log(2)/DT50),
-  years = 1,
-  step_days = 1,
-  times = seq(0, years * 365, by = step_days)
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - -
model

The degradation model to be used. Either a parent only model like -'SFO' or 'FOMC', or an mkinmod object

DT50

The half-life. This is only used when simple exponential decline -is calculated (SFO model).

parms

The parameters used for the degradation model

years

For how many years should the degradation be predicted?

step_days

What step size in days should the output have?

times

The output times

- - -

Examples

- 
head(pfm_degradation("SFO", DT50 = 10))
#>   time    parent
-#> 0    0 1.0000000
-#> 1    1 0.9330330
-#> 2    2 0.8705506
-#> 3    3 0.8122524
-#> 4    4 0.7578583
-#> 5    5 0.7071068
+
+ 
pfm_degradation(
+  model = "SFO",
+  DT50 = 1000,
+  parms = c(k_parent = log(2)/DT50),
+  years = 1,
+  step_days = 1,
+  times = seq(0, years * 365, by = step_days)
+)
+
+ +
+

Arguments

+
model
+

The degradation model to be used. Either a parent only model like +'SFO' or 'FOMC', or an mkinmod object

+ + +
DT50
+

The half-life. This is only used when simple exponential decline +is calculated (SFO model).

+ + +
parms
+

The parameters used for the degradation model

+ + +
years
+

For how many years should the degradation be predicted?

+ + +
step_days
+

What step size in days should the output have?

+ + +
times
+

The output times

+ +
+
+

Author

+

Johannes Ranke

+
+ +
+

Examples

+ 
head(pfm_degradation("SFO", DT50 = 10))
+#>   time    parent
+#> 0    0 1.0000000
+#> 1    1 0.9330330
+#> 2    2 0.8705506
+#> 3    3 0.8122524
+#> 4    4 0.7578583
+#> 5    5 0.7071068
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/plot.TOXSWA_cwa-1.png b/docs/reference/plot.TOXSWA_cwa-1.png index c6a278a..11a34cc 100644 Binary files a/docs/reference/plot.TOXSWA_cwa-1.png and b/docs/reference/plot.TOXSWA_cwa-1.png differ diff --git a/docs/reference/plot.TOXSWA_cwa-2.png b/docs/reference/plot.TOXSWA_cwa-2.png index 869c43c..327a21b 100644 Binary files a/docs/reference/plot.TOXSWA_cwa-2.png and b/docs/reference/plot.TOXSWA_cwa-2.png differ diff --git a/docs/reference/plot.TOXSWA_cwa-3.png b/docs/reference/plot.TOXSWA_cwa-3.png index 315c741..65524b5 100644 Binary files a/docs/reference/plot.TOXSWA_cwa-3.png and b/docs/reference/plot.TOXSWA_cwa-3.png differ diff --git a/docs/reference/plot.TOXSWA_cwa-4.png b/docs/reference/plot.TOXSWA_cwa-4.png index a0a88f9..1d82cfc 100644 Binary files a/docs/reference/plot.TOXSWA_cwa-4.png and b/docs/reference/plot.TOXSWA_cwa-4.png differ diff --git a/docs/reference/plot.TOXSWA_cwa-5.png b/docs/reference/plot.TOXSWA_cwa-5.png index 3ac506d..d28c87c 100644 Binary files a/docs/reference/plot.TOXSWA_cwa-5.png and b/docs/reference/plot.TOXSWA_cwa-5.png differ diff --git a/docs/reference/plot.TOXSWA_cwa.html b/docs/reference/plot.TOXSWA_cwa.html index 1262c71..857b154 100644 --- a/docs/reference/plot.TOXSWA_cwa.html +++ b/docs/reference/plot.TOXSWA_cwa.html @@ -1,65 +1,13 @@ - - - - - - - -Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa • pfm - - - - + + -
-
- -
- -
+

Plot TOXSWA surface water concentrations

@@ -111,106 +45,112 @@ segment of a TOXSWA surface water body." /> segment of a TOXSWA surface water body.

- 
# S3 method for TOXSWA_cwa
-plot(
-  x,
-  time_column = c("datetime", "t", "t_firstjan", "t_rel_to_max"),
-  xlab = "default",
-  ylab = "default",
-  add = FALSE,
-  threshold_factor = 1000,
-  thin_low = 1,
-  total = FALSE,
-  LC_TIME = "C",
-  ...
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
x

The TOXSWA_cwa object to be plotted.

time_column

What should be used for the time axis. If "t_firstjan" is chosen, -the time is given in days relative to the first of January in the first year.

xlab, ylab

Labels for x and y axis.

add

Should we add to an existing plot?

threshold_factor

The factor by which the data have to be lower than the maximum -in order to get thinned for plotting (see next argument).

thin_low

If an integer greater than 1, the data close to zero (smaller than +

+ 
# S3 method for TOXSWA_cwa
+plot(
+  x,
+  time_column = c("datetime", "t", "t_firstjan", "t_rel_to_max"),
+  xlab = "default",
+  ylab = "default",
+  add = FALSE,
+  threshold_factor = 1000,
+  thin_low = 1,
+  total = FALSE,
+  LC_TIME = "C",
+  ...
+)
+
+ +
+

Arguments

+
x
+

The TOXSWA_cwa object to be plotted.

+ + +
time_column
+

What should be used for the time axis. If "t_firstjan" is chosen, +the time is given in days relative to the first of January in the first year.

+ + +
xlab, ylab
+

Labels for x and y axis.

+ + +
add
+

Should we add to an existing plot?

+ + +
threshold_factor
+

The factor by which the data have to be lower than the maximum +in order to get thinned for plotting (see next argument).

+ + +
thin_low
+

If an integer greater than 1, the data close to zero (smaller than 1/threshold_factor of the maximum) in the series will be thinned by this factor -in order to decrease the amount of data that is included in the plots

total

Should the total concentration in water be plotted, including substance sorbed -to suspended matter?

LC_TIME

Specification of the locale used to format dates

...

Further arguments passed to plot if we are not adding to an existing plot

- - -

Examples

- 
H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
-  basedir = "SwashProjects/project_H_sw/TOXSWA",
-  zipfile = system.file("testdata/SwashProjects.zip", package = "pfm"))
-plot(H_sw_D4_pond)
plot(H_sw_D4_pond, time_column = "t")
plot(H_sw_D4_pond, time_column = "t_firstjan")
plot(H_sw_D4_pond, time_column = "t_rel_to_max")

-H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
-  basedir = "SwashProjects/project_H_sw/TOXSWA",
-  zipfile = system.file("testdata/SwashProjects.zip", package = "pfm"))
-plot(H_sw_R1_stream, time_column = "t_rel_to_max")
-
- +

Author

Johannes Ranke

+
+ +
+

Examples

+ 
H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
+  basedir = "SwashProjects/project_H_sw/TOXSWA",
+  zipfile = system.file("testdata/SwashProjects.zip", package = "pfm"))
+plot(H_sw_D4_pond)
+
+plot(H_sw_D4_pond, time_column = "t")
+
+plot(H_sw_D4_pond, time_column = "t_firstjan")
+
+plot(H_sw_D4_pond, time_column = "t_rel_to_max")
+
+
+H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
+  basedir = "SwashProjects/project_H_sw/TOXSWA",
+  zipfile = system.file("testdata/SwashProjects.zip", package = "pfm"))
+plot(H_sw_R1_stream, time_column = "t_rel_to_max")
+
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/plot.one_box-1.png b/docs/reference/plot.one_box-1.png index cf3f132..066f466 100644 Binary files a/docs/reference/plot.one_box-1.png and b/docs/reference/plot.one_box-1.png differ diff --git a/docs/reference/plot.one_box-2.png b/docs/reference/plot.one_box-2.png index 0e152d6..307dc3c 100644 Binary files a/docs/reference/plot.one_box-2.png and b/docs/reference/plot.one_box-2.png differ diff --git a/docs/reference/plot.one_box-3.png b/docs/reference/plot.one_box-3.png index ad93165..cea8b0b 100644 Binary files a/docs/reference/plot.one_box-3.png and b/docs/reference/plot.one_box-3.png differ diff --git a/docs/reference/plot.one_box.html b/docs/reference/plot.one_box.html index 75b8fe9..2fc946e 100644 --- a/docs/reference/plot.one_box.html +++ b/docs/reference/plot.one_box.html @@ -1,64 +1,12 @@ - - - - - - - -Plot time series of decline data — plot.one_box • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Plot time series of decline data — plot.one_box • pfm - - - - + + -
-
- -
- -
+

Plot time series of decline data

@@ -109,97 +43,101 @@

Plot time series of decline data

- 
# S3 method for one_box
-plot(
-  x,
-  xlim = range(time(x)),
-  ylim = c(0, max(x)),
-  xlab = "Time",
-  ylab = "Residue",
-  max_twa = NULL,
-  max_twa_var = dimnames(x)[[2]][1],
-  ...
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
x

The object of type one_box to be plotted

xlim

Limits for the x axis

ylim

Limits for the y axis

xlab

Label for the x axis

ylab

Label for the y axis

max_twa

If a numeric value is given, the maximum time weighted -average concentration(s) is/are shown in the graph.

max_twa_var

Variable for which the maximum time weighted average should -be shown if max_twa is not NULL.

...

Further arguments passed to methods

- -

See also

- -

sawtooth

- -

Examples

- 
dfop_pred <- one_box("DFOP", parms = c(k1 = 0.2, k2 = 0.02, g = 0.7))
-plot(dfop_pred)
plot(sawtooth(dfop_pred, 3, 7), max_twa = 21)

-# Use a fitted mkinfit model
-m_2 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
pred_2 <- one_box(fit_2, ini = 1)
-pred_2_saw <- sawtooth(pred_2, 2, 7)
-plot(pred_2_saw, max_twa = 21, max_twa_var = "m1")
-
- +
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/read.TOXSWA_cwa.html b/docs/reference/read.TOXSWA_cwa.html index 9c5c2a0..2685c21 100644 --- a/docs/reference/read.TOXSWA_cwa.html +++ b/docs/reference/read.TOXSWA_cwa.html @@ -1,69 +1,17 @@ - - - - - - - -Read TOXSWA surface water concentrations — read.TOXSWA_cwa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Read TOXSWA surface water concentrations — read.TOXSWA_cwa • pfm - - - - - - - - - - - - - - + + -
-
- -
- -
+

Read TOXSWA surface water concentrations

@@ -119,103 +53,102 @@ of the hourly averages (ConLiqWatLay). In TOXSWA 5.5.3 this variable was renamed to ConLiqWatLay in the out file.

- 
read.TOXSWA_cwa(
-  filename,
-  basedir = ".",
-  zipfile = NULL,
-  segment = "last",
-  substance = "parent",
-  total = FALSE,
-  windows = NULL,
-  thresholds = NULL
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
filename

The filename of the cwa file (TOXSWA 2.x.y or similar) or the -out file when using FOCUS TOXSWA 4 (i.e. TOXSWA 4.4.2) or higher.

basedir

The path to the directory where the cwa file resides.

zipfile

Optional path to a zip file containing the cwa file.

segment

The segment for which the data should be read. Either "last", or -the segment number.

substance

For .out files, the default value "parent" leads +

+ 
read.TOXSWA_cwa(
+  filename,
+  basedir = ".",
+  zipfile = NULL,
+  segment = "last",
+  substance = "parent",
+  total = FALSE,
+  windows = NULL,
+  thresholds = NULL
+)
+
+ +
+

Arguments

+
filename
+

The filename of the cwa file (TOXSWA 2.x.y or similar) or the +out file when using FOCUS TOXSWA 4 (i.e. TOXSWA 4.4.2) or higher.

+ + +
basedir
+

The path to the directory where the cwa file resides.

+ + +
zipfile
+

Optional path to a zip file containing the cwa file.

+ + +
segment
+

The segment for which the data should be read. Either "last", or +the segment number.

+ + +
substance
+

For .out files, the default value "parent" leads to reading concentrations of the parent compound. Alternatively, the substance -of interested can be selected by its code name.

total

Set this to TRUE in order to read total concentrations as well. This is +of interested can be selected by its code name.

+ + +
total
+

Set this to TRUE in order to read total concentrations as well. This is only necessary for .out files as generated by TOXSWA 4.4.2 or similar, not for .cwa -files. For .cwa files, the total concentration is always read as well.

windows

Numeric vector of width of moving windows in days, for calculating -maximum time weighted average concentrations and areas under the curve.

thresholds

Numeric vector of threshold concentrations in µg/L for -generating event statistics.

- -

Value

- -

An instance of an R6 object of class -TOXSWA_cwa.

- -

Examples

- 
H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
-                                 basedir = "SwashProjects/project_H_sw/TOXSWA",
-                                 zipfile = system.file("testdata/SwashProjects.zip",
-                                                       package = "pfm"))
-
- +
+

Value

+ +

An instance of an R6 object of class +TOXSWA_cwa.

+
+

Author

Johannes Ranke

+
+ +
+

Examples

+ 
H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
+                                 basedir = "SwashProjects/project_H_sw/TOXSWA",
+                                 zipfile = system.file("testdata/SwashProjects.zip",
+                                                       package = "pfm"))
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/reexports.html b/docs/reference/reexports.html new file mode 100644 index 0000000..9b8cb48 --- /dev/null +++ b/docs/reference/reexports.html @@ -0,0 +1,83 @@ + +Objects exported from other packages — reexports • pfm + + +
+
+ + + +
+
+
+

Objects exported from other packages

+ + +
+ +
+

These objects are imported from other packages. Follow the links +below to see their documentation.

+
mkin
+

set_nd_nq, set_nd_nq_focus

+ + +
+ + + +
+ +
+ + +
+

Developed by Johannes Ranke.

+
+ +
+

Site built with pkgdown 2.0.7.

+
+ +
+ + + + + + + + diff --git a/docs/reference/sawtooth-1.png b/docs/reference/sawtooth-1.png index 2952433..062202c 100644 Binary files a/docs/reference/sawtooth-1.png and b/docs/reference/sawtooth-1.png differ diff --git a/docs/reference/sawtooth-2.png b/docs/reference/sawtooth-2.png index 87da954..cea8b0b 100644 Binary files a/docs/reference/sawtooth-2.png and b/docs/reference/sawtooth-2.png differ diff --git a/docs/reference/sawtooth.html b/docs/reference/sawtooth.html index fea24d4..8e29b9c 100644 --- a/docs/reference/sawtooth.html +++ b/docs/reference/sawtooth.html @@ -1,68 +1,13 @@ - - - - - - - -Create decline time series for multiple applications — sawtooth • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Create decline time series for multiple applications — sawtooth • pfm - - - - + + -
-
- -
- -
+

Create decline time series for multiple applications

@@ -114,81 +45,88 @@ n and i are disregarded." /> n and i are disregarded.

- 
sawtooth(
-  x,
-  n = 1,
-  i = 365,
-  applications = data.frame(time = seq(0, (n - 1) * i, length.out = n), amount = 1)
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - -
x

A one_box object

n

The number of applications. If applications is specified, n is ignored

i

The interval between applications. If applications is specified, i -is ignored

applications

A data frame holding the application times in the first column and -the corresponding amounts applied in the second column.

- - -

Examples

- 
applications = data.frame(time = seq(0, 14, by = 7), amount = c(1, 2, 3))
-pred <- one_box(10)
-plot(sawtooth(pred, applications = applications))

-m_2 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
#> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
pred_2 <- one_box(fit_2, ini = 1)
-pred_2_saw <- sawtooth(pred_2, 2, 7)
-plot(pred_2_saw, max_twa = 21, max_twa_var = "m1")

-max_twa(pred_2_saw)
#> $max
-#>    parent        m1 
-#> 0.7834480 0.8617048 
-#> 
-#> $window_start
-#> parent     m1 
-#>   0.00  26.85 
-#> 
-#> $window_end
-#> parent     m1 
-#>  21.00  47.85 
-#>
+
+ 
sawtooth(
+  x,
+  n = 1,
+  i = 365,
+  applications = data.frame(time = seq(0, (n - 1) * i, length.out = n), amount = 1)
+)
+
+ +
+

Arguments

+
x
+

A one_box object

+ + +
n
+

The number of applications. If applications is specified, n is ignored

+ + +
i
+

The interval between applications. If applications is specified, i +is ignored

+ + +
applications
+

A data frame holding the application times in the first column and +the corresponding amounts applied in the second column.

+ +
+ +
+

Examples

+ 
applications = data.frame(time = seq(0, 14, by = 7), amount = c(1, 2, 3))
+pred <- one_box(10)
+plot(sawtooth(pred, applications = applications))
+
+
+m_2 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
+#> Temporary DLL for differentials generated and loaded
+fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE)
+#> Warning: Observations with value of zero were removed from the data
+pred_2 <- one_box(fit_2, ini = 1)
+pred_2_saw <- sawtooth(pred_2, 2, 7)
+plot(pred_2_saw, max_twa = 21, max_twa_var = "m1")
+
+
+max_twa(pred_2_saw)
+#> $max
+#>    parent        m1 
+#> 0.7834481 0.8617049 
+#> 
+#> $window_start
+#> parent     m1 
+#>   0.00  26.85 
+#> 
+#> $window_end
+#> parent     m1 
+#>  21.00  47.85 
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/soil_scenario_data_EFSA_2015.html b/docs/reference/soil_scenario_data_EFSA_2015.html index cb3cf14..abea480 100644 --- a/docs/reference/soil_scenario_data_EFSA_2015.html +++ b/docs/reference/soil_scenario_data_EFSA_2015.html @@ -1,69 +1,14 @@ - - - - - - - -Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015 • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015 • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

Properties of the predefined scenarios from the EFSA guidance from 2015

@@ -116,81 +47,65 @@ concentration in soil as given in the EFSA guidance (2015, p. 13/14). Also, the scenario and model adjustment factors from p. 15 and p. 17 are included.

+
+ 
soil_scenario_data_EFSA_2015
+
- -

Format

- +
+

Format

A data frame with one row for each scenario. Row names are the scenario codes, e.g. CTN for the Northern scenario for the total concentration in soil. Columns are mostly self-explanatory. rho is the dry bulk density of the top soil.

-

Source

- +
+
+

Source

EFSA (European Food Safety Authority) (2015) EFSA guidance document for predicting environmental concentrations of active substances of plant protection products and transformation products of these active substances in soil. EFSA Journal 13(4) 4093 - doi:10.2903/j.efsa.2015.4093

- -

Examples

- 
if (FALSE) {
-  # This is the code that was used to define the data
-  soil_scenario_data_EFSA_2015 <- data.frame(
-    Zone = rep(c("North", "Central", "South"), 2),
-    Country = c("Estonia", "Germany", "France", "Denmark", "Czech Republik", "Spain"),
-    T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8),
-    T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7),
-    Texture = c("Coarse", "Coarse", "Medium fine", "Medium", "Medium", "Medium"),
-    f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011),
-    theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347),
-    rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51),
-    f_sce = c(3, 2, 2, 2, 1.5, 1.5),
-    f_mod = c(2, 2, 2, 4, 4, 4),
-    stringsAsFactors = FALSE,
-    row.names = c("CTN", "CTC", "CTS", "CLN", "CLC", "CLS")
-  )
-  save(soil_scenario_data_EFSA_2015, file = '../data/soil_scenario_data_EFSA_2015.RData')
-}
-
-# And this is the resulting dataframe
-soil_scenario_data_EFSA_2015
#>        Zone        Country T_arit T_arr     Texture  f_om theta_fc  rho f_sce
-#> CTN   North        Estonia    4.7   7.0      Coarse 0.118    0.244 0.95   3.0
-#> CTC Central        Germany    8.0  10.1      Coarse 0.086    0.244 1.05   2.0
-#> CTS   South         France   11.0  12.3 Medium fine 0.048    0.385 1.22   2.0
-#> CLN   North        Denmark    8.2   9.8      Medium 0.023    0.347 1.39   2.0
-#> CLC Central Czech Republik    9.1  11.2      Medium 0.018    0.347 1.43   1.5
-#> CLS   South          Spain   12.8  14.7      Medium 0.011    0.347 1.51   1.5
-#>     f_mod
-#> CTN     2
-#> CTC     2
-#> CTS     2
-#> CLN     4
-#> CLC     4
-#> CLS     4
+ doi:10.2903/j.efsa.2015.4093

+
+ +
+

Examples

+ 
soil_scenario_data_EFSA_2015
+#>        Zone        Country T_arit T_arr     Texture  f_om theta_fc  rho f_sce
+#> CTN   North        Estonia    4.7   7.0      Coarse 0.118    0.244 0.95   3.0
+#> CTC Central        Germany    8.0  10.1      Coarse 0.086    0.244 1.05   2.0
+#> CTS   South         France   11.0  12.3 Medium fine 0.048    0.385 1.22   2.0
+#> CLN   North        Denmark    8.2   9.8      Medium 0.023    0.347 1.39   2.0
+#> CLC Central Czech Republik    9.1  11.2      Medium 0.018    0.347 1.43   1.5
+#> CLS   South          Spain   12.8  14.7      Medium 0.011    0.347 1.51   1.5
+#>     f_mod
+#> CTN     2
+#> CTC     2
+#> CTS     2
+#> CLN     4
+#> CLC     4
+#> CLS     4
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/soil_scenario_data_EFSA_2017.html b/docs/reference/soil_scenario_data_EFSA_2017.html index 7e8044e..96cdd1b 100644 --- a/docs/reference/soil_scenario_data_EFSA_2017.html +++ b/docs/reference/soil_scenario_data_EFSA_2017.html @@ -1,69 +1,14 @@ - - - - - - - -Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

Properties of the predefined scenarios from the EFSA guidance from 2017

@@ -116,61 +47,98 @@ concentration in soil as given in the EFSA guidance (2017, p. 14/15). Also, the scenario and model adjustment factors from p. 16 and p. 18 are included.

+
+ 
soil_scenario_data_EFSA_2017
+
- -

Format

- +
+

Format

A data frame with one row for each scenario. Row names are the scenario codes, e.g. CTN for the Northern scenario for the total concentration in soil. Columns are mostly self-explanatory. rho is the dry bulk density of the top soil.

-

Source

- +
+
+

Source

EFSA (European Food Safety Authority) (2017) EFSA guidance document for predicting environmental concentrations of active substances of plant protection products and transformation products of these active substances in soil. EFSA Journal 15(10) 4982 - doi:10.2903/j.efsa.2017.4982

- -

Examples

- 
soil_scenario_data_EFSA_2017
#>        Zone Country T_arit T_arr Texture  f_om theta_fc   rho f_sce f_mod
-#> CTN   North Estonia    5.7   7.6  Coarse 0.220    0.244 0.707   1.4     3
-#> CTC Central  Poland    7.4   9.3  Coarse 0.122    0.244 0.934   1.4     3
-#> CTS   South  France   10.2  11.7  Medium 0.070    0.349 1.117   1.4     3
-#> CLN   North Denmark    8.0   9.2  Medium 0.025    0.349 1.371   1.6     4
-#> CLC Central Austria    9.3  11.3  Medium 0.018    0.349 1.432   1.6     4
-#> CLS   South   Spain   15.4  16.7  Medium 0.010    0.349 1.521   1.6     4
-#>     FOCUS_zone prec
-#> CTN    Hamburg  639
-#> CTC    Hamburg  617
-#> CTS    Hamburg  667
-#> CLN    Hamburg  602
-#> CLC Châteaudun  589
-#> CLS    Sevilla  526
+ doi:10.2903/j.efsa.2017.4982

+
+ +
+

Examples

+ 
soil_scenario_data_EFSA_2017
+#>        Zone Country T_arit T_arr Texture  f_om theta_fc   rho f_sce f_mod
+#> CTN   North Estonia    5.7   7.6  Coarse 0.220    0.244 0.707   1.4     3
+#> CTC Central  Poland    7.4   9.3  Coarse 0.122    0.244 0.934   1.4     3
+#> CTS   South  France   10.2  11.7  Medium 0.070    0.349 1.117   1.4     3
+#> CLN   North Denmark    8.0   9.2  Medium 0.025    0.349 1.371   1.6     4
+#> CLC Central Austria    9.3  11.3  Medium 0.018    0.349 1.432   1.6     4
+#> CLS   South   Spain   15.4  16.7  Medium 0.010    0.349 1.521   1.6     4
+#>     FOCUS_zone prec
+#> CTN    Hamburg  639
+#> CTC    Hamburg  617
+#> CTS    Hamburg  667
+#> CLN    Hamburg  602
+#> CLC Châteaudun  589
+#> CLS    Sevilla  526
+
+waldo::compare(soil_scenario_data_EFSA_2017, soil_scenario_data_EFSA_2015)
+#> `old` is length 12
+#> `new` is length 10
+#> 
+#> `names(old)[8:12]`: "rho" "f_sce" "f_mod" "FOCUS_zone" "prec"
+#> `names(new)[8:10]`: "rho" "f_sce" "f_mod"                    
+#> 
+#> `old$Country`: "Estonia" "Poland"  "France" "Denmark" "Austria"        "Spain"
+#> `new$Country`: "Estonia" "Germany" "France" "Denmark" "Czech Republik" "Spain"
+#> 
+#> `old$T_arit`: 5.7 7.4 10.2 8.0 9.3 15.4
+#> `new$T_arit`: 4.7 8.0 11.0 8.2 9.1 12.8
+#> 
+#> `old$T_arr`: 7.6  9.3 11.7 9.2 11.3 16.7
+#> `new$T_arr`: 7.0 10.1 12.3 9.8 11.2 14.7
+#> 
+#> `old$Texture`: "Coarse" "Coarse" "Medium"      "Medium" "Medium" "Medium"
+#> `new$Texture`: "Coarse" "Coarse" "Medium fine" "Medium" "Medium" "Medium"
+#> 
+#> `old$f_om`: 0.220 0.122 0.070 0.025 0.018 0.010
+#> `new$f_om`: 0.118 0.086 0.048 0.023 0.018 0.011
+#> 
+#> `old$theta_fc`: 0.244 0.244 0.349 0.349 0.349 0.349
+#> `new$theta_fc`: 0.244 0.244 0.385 0.347 0.347 0.347
+#> 
+#> `old$rho`: 0.707 0.934 1.117 1.371 1.432 1.521
+#> `new$rho`: 0.950 1.050 1.220 1.390 1.430 1.510
+#> 
+#> `old$f_sce`: 1.4 1.4 1.4 1.6 1.6 1.6
+#> `new$f_sce`: 3.0 2.0 2.0 2.0 1.5 1.5
+#> 
+#> And 3 more differences ...
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.5.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/reference/twa.html b/docs/reference/twa.html index 2c21c67..f23c6f3 100644 --- a/docs/reference/twa.html +++ b/docs/reference/twa.html @@ -1,63 +1,14 @@ - - - - - - - -Calculate a time weighted average concentration — twa • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - -Calculate a time weighted average concentration — twa • pfm - - - - - - - - - - - - - + + -
-
- -
- -
+

Calculate a time weighted average concentration

@@ -106,82 +42,73 @@ is after one window has passed." />
-

The moving average is built only using the values in the past, so the earliest possible time for the maximum in the time series returned is after one window has passed.

-
- 
twa(x, window = 21)
+    

+    
twa(x, window = 21)
+
+# S3 method for one_box
+twa(x, window = 21)

+    

 
-# S3 method for one_box
-twa(x, window = 21)
- -

Arguments

- - - - - - - - - - -
x

An object of type one_box

window

The size of the moving window

- -

See also

+
+

Arguments

+
x
+

An object of type one_box

-

max_twa

- -

Examples

- 
pred <- sawtooth(one_box(10),
-  applications = data.frame(time = c(0, 7), amount = c(1, 1)))
-max_twa(pred)
#> $max
-#>    parent 
-#> 0.9537545 
-#> 
-#> $window_start
-#> parent 
-#>      0 
-#> 
-#> $window_end
-#> parent 
-#>     21 
-#>
-
- +
+

See also

+

max_twa

+
+ +
+

Examples

+ 
pred <- sawtooth(one_box(10),
+  applications = data.frame(time = c(0, 7), amount = c(1, 1)))
+max_twa(pred)
+#> $max
+#>    parent 
+#> 0.9537545 
+#> 
+#> $window_start
+#> parent 
+#>      0 
+#> 
+#> $window_end
+#> parent 
+#>     21 
+#> 
+
+
+
-
-
-

Developed by Johannes Ranke.

+
+

Developed by Johannes Ranke.

-

Site built with pkgdown 1.4.1.

+

Site built with pkgdown 2.0.7.

-
-
+
- - + + diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 0c507b6..6ba511d 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -1,5 +1,11 @@ + + https://pkgdown.jrwb.de/pfm/404.html + + + https://pkgdown.jrwb.de/pfm/authors.html + https://pkgdown.jrwb.de/pfm/index.html @@ -75,6 +81,9 @@ https://pkgdown.jrwb.de/pfm/reference/get_vertex.html + + https://pkgdown.jrwb.de/pfm/reference/index.html + https://pkgdown.jrwb.de/pfm/reference/max_twa.html @@ -99,6 +108,9 @@ https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html + + https://pkgdown.jrwb.de/pfm/reference/reexports.html + https://pkgdown.jrwb.de/pfm/reference/sawtooth.html diff --git a/inst/data_generation/EFSA_GW_interception.R b/inst/data_generation/EFSA_GW_interception.R new file mode 100644 index 0000000..353b676 --- /dev/null +++ b/inst/data_generation/EFSA_GW_interception.R @@ -0,0 +1,29 @@ +library(here) + +bbch <- paste0(0:9, "x") +crops <- c( + "Beans (field + vegetable)", + "Peas", + "Summer oilseed rape", "Winter oilseed rape", + "Tomatoes", + "Spring cereals", "Winter cereals") +EFSA_GW_interception_2014 <- matrix(NA, length(crops), length(bbch), + dimnames = list(Crop = crops, BBCH = bbch)) +EFSA_GW_interception_2014["Beans (field + vegetable)", ] <- + c(0, 0.25, rep(0.4, 2), rep(0.7, 5), 0.8) +EFSA_GW_interception_2014["Peas", ] <- + c(0, 0.35, rep(0.55, 2), rep(0.85, 5), 0.85) +EFSA_GW_interception_2014["Summer oilseed rape", ] <- + c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9) +EFSA_GW_interception_2014["Winter oilseed rape", ] <- + c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9) +EFSA_GW_interception_2014["Tomatoes", ] <- + c(0, 0.5, rep(0.7, 2), rep(0.8, 5), 0.5) +EFSA_GW_interception_2014["Spring cereals", ] <- + c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8) +EFSA_GW_interception_2014["Winter cereals", ] <- + c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8) + +save(EFSA_GW_interception_2014, + file = here("data/EFSA_GW_interception_2014.RData")) + diff --git a/inst/data_generation/EFSA_washoff_2017.R b/inst/data_generation/EFSA_washoff_2017.R new file mode 100644 index 0000000..cbe43c6 --- /dev/null +++ b/inst/data_generation/EFSA_washoff_2017.R @@ -0,0 +1,29 @@ +library(here) + +bbch <- paste0(0:9, "x") +crops <- c( + "Beans (field + vegetable)", + "Peas", + "Summer oilseed rape", "Winter oilseed rape", + "Tomatoes", + "Spring cereals", "Winter cereals") +EFSA_washoff_2017 <- matrix(NA, length(crops), length(bbch), + dimnames = list(Crop = crops, BBCH = bbch)) +EFSA_washoff_2017["Beans (field + vegetable)", ] <- + c(NA, 0.6, rep(0.75, 2), rep(0.8, 5), 0.35) +EFSA_washoff_2017["Peas", ] <- + c(NA, 0.4, rep(0.6, 2), rep(0.65, 5), 0.35) +EFSA_washoff_2017["Summer oilseed rape", ] <- + c(NA, 0.4, rep(0.5, 2), rep(0.6, 5), 0.5) +EFSA_washoff_2017["Winter oilseed rape", ] <- + c(NA, 0.1, rep(0.4, 2), rep(0.55, 5), 0.3) +EFSA_washoff_2017["Tomatoes", ] <- + c(NA, 0.55, rep(0.75, 2), rep(0.7, 5), 0.35) +EFSA_washoff_2017["Spring cereals", ] <- + c(NA, 0.4, 0.5, 0.5, rep(0.65, 3), rep(0.65, 2), 0.55) +EFSA_washoff_2017["Winter cereals", ] <- + c(NA, 0.1, 0.4, 0.6, rep(0.55, 3), rep(0.6, 2), 0.4) + +save(EFSA_washoff_2017, + file = here("data/EFSA_washoff_2017.RData")) + diff --git a/inst/data_generation/FOCUS_GW_scenarios_2012.R b/inst/data_generation/FOCUS_GW_scenarios_2012.R new file mode 100644 index 0000000..1358b8d --- /dev/null +++ b/inst/data_generation/FOCUS_GW_scenarios_2012.R @@ -0,0 +1,63 @@ +library(here) + +# FOCUS 2012 p. 46 ff +FOCUS_GW_scenarios_2012 = list() + +n_layers = c(7, 6, 6, 5, 5, 6, 4, 6, 6) +acronyms = c("Cha", "Ham", "Jok", "Kre", "Oke", "Pia", "Por", "Sev", "Thi") +FOCUS_GW_scenarios_2012$names = c("Ch\u00e2teadun", "Hamburg", "Jokioinen", + "Kremsm\u00fcnster", "Okehampton", + "Piacenza", "Porto", "Sevilla", "Thiva") + +names(FOCUS_GW_scenarios_2012$names) = acronyms +FOCUS_GW_scenarios_2012$soils <- data.frame( + location= rep(acronyms, times = n_layers), + horizon = c("Ap", "B1", "B2", "II C1", "II C1", "II C2", "M", + "Ap", "BvI", "BvII", "Bv/Cv", "Cv", "Cv", + "Ap", "Bs", "BC1", "BC2", "BC2", "Cg", + rep(NA, 5), + "A", "Bw1", "BC", "C", "C", + "Ap", "Ap", "Bw", "Bw", "2C", "2C", + rep(NA, 4), + rep(NA, 6), + "Ap1", "Ap2", "Bw", "Bw", "Ck1", "Ck1"), + number = unlist(sapply(n_layers, function(x) 1:x)), + pH_H2O = c(8.0, 8.1, 8.2, 8.5, 8.5, 8.5, 8.3, + 6.4, 5.6, 5.6, 5.7, 5.5, 5.5, + 6.2, 5.6, 5.4, 5.4, 5.4, 5.3, + 7.7, 7.0, 7.1, 7.1, 7.1, + 5.8, 6.3, 6.5, 6.6, 6.6, + 7, 7, 6.3, 6.3, 6.4, 6.4, + 4.9, 4.8, 4.8, 4.8, + 7.3, 7.3, 7.8, 8.1, 8.1, 8.2, + 7.7, 7.7, 7.8, 7.8, 7.8, 7.8), + perc_clay = c(30, 31, 25, 26, 26, 24, 31, + 7.2, 6.7, 0.9, 0, 0, 0, + 3.6, 1.8, 1.2, 1.7, 1.7, 1.9, + 14, 25, 27, 27, 27, + 18, 17, 14, 9, 9, + 15, 15, 7, 7, 0, 0, + 10, 8, 8, 8, + 14, 13, 15, 16, 16, 22, + 25.3, 25.3, 29.6, 31.9, 32.9, 32.9), + perc_oc = c(1.39, 0.93, 0.7, 0.3, 0.3, 0.27, 0.21, + 1.5, 1, 0.2, 0, 0, 0, + 4.06, 0.84, 0.36, 0.29, 0.29, 0.21, + 3.6, 1.0, 0.5, 0.5, 0.5, + 2.2, 0.7, 0.4, 0.1, 0.1, + 1.26, 1.26, 0.47, 0.47, 0, 0, + 1.42, 0.78, 0.78, 0.78, + 0.93, 0.93, 0.70, 0.58, 0.58, 0.49, + 0.74, 0.74, 0.57, 0.31, 0.18, 0.18), + rel_deg = c(1, 0.5, 0.5, 0.3, 0, 0, 0, + 1, 0.5, 0.3, 0.3, 0.3, 0, + 1, 0.5, 0.3, 0.3, 0, 0, + 1, 0.5, 0.5, 0.3, 0, + 1, 0.5, 0.3, 0.3, 0, + 1, 0.5, 0.5, 0.3, 0.3, 0, + 1, 0.5, 0.3, 0, + 1, 1, 0.5, 0.3, 0, 0, + 1, 0.5, 0.5, 0.3, 0.3, 0)) + +save(FOCUS_GW_scenarios_2012, + file = here("data/FOCUS_GW_scenarios_2012.RData")) diff --git a/inst/data_generation/PEC_sw_exposit.R b/inst/data_generation/PEC_sw_exposit.R new file mode 100644 index 0000000..f7d9737 --- /dev/null +++ b/inst/data_generation/PEC_sw_exposit.R @@ -0,0 +1,34 @@ +library(here) + +# Runoff percentages +Koc_breaks <- c(0, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, Inf) +tmp <- paste(Koc_breaks[1:11], Koc_breaks[2:12], sep = "-") +Koc_classes <- c(tmp[1], paste0(">", tmp[2:11]), ">50000") +perc_runoff_exposit <- data.frame( + Koc_lower_bound = Koc_breaks[1:12], + dissolved = c(0.11, 0.151, 0.197, 0.248, 0.224, 0.184, 0.133, 0.084, 0.037, 0.031, 0.014, 0.001), + bound = c(0, 0, 0, 0.001, 0.004, 0.020, 0.042, 0.091, 0.159, 0.192, 0.291, 0.451)) +rownames(perc_runoff_exposit) <- Koc_classes + +# Runoff reduction percentages +perc_runoff_reduction_exposit <- list( + "3.02" = data.frame( + dissolved = c(0, 40, 60, 80), + bound = c(0, 40, 85, 95), + row.names = c("No buffer", paste(c(5, 10, 20), "m"))), + "3.01a" = data.frame( + dissolved = c(0, 25, 40, 45, 60, 80), + bound = c(0, 30, 40, 55, 85, 95), + row.names = c("No buffer", paste(c(3, 5, 6, 10, 20), "m"))), + "3.01a2" = data.frame( + dissolved = c(0, 25), + bound = c(0, 25), + row.names = c("No buffer", paste(c(3), "m"))), + "2.0" = data.frame( + dissolved = c(0, 97.5), + bound = c(0, 97.5), + row.names = c("No buffer", "20 m")) +) + +save(perc_runoff_exposit, perc_runoff_reduction_exposit, + file = here("data/perc_runoff.RData")) diff --git a/inst/data_generation/drift_data_JKI.R b/inst/data_generation/drift_data_JKI.R new file mode 100644 index 0000000..d28409c --- /dev/null +++ b/inst/data_generation/drift_data_JKI.R @@ -0,0 +1,47 @@ +library(here) + +# The following code was in the example code of the help page of the data object up to pfm version 0.6.0 +# It was not executed after migrating it to this directory (inst/data_generation), because +# the spreadsheet is not available at the JKI website any more. +library(readxl) +abdrift_path <- here("inst/extdata/Tabelle der Abdrifteckwerte.xls") +JKI_crops <- c("Ackerbau", "Obstbau frueh", "Obstbau spaet", "Weinbau frueh", "Weinbau spaet", + "Hopfenbau", "Flaechenkulturen > 900 l/ha", "Gleisanlagen") +names(JKI_crops) <- c("Field crops", "Pome/stone fruit, early", "Pome/stone fruit, late", + "Vines early", "Vines late", "Hops", "Areic cultures > 900 L/ha", "Railroad tracks") +drift_data_JKI <- list() + +for (n in 1:8) { + drift_data_raw <- read_excel(abdrift_path, sheet = n + 1, skip = 2) + drift_data <- matrix(NA, nrow = 9, ncol = length(JKI_crops)) + dimnames(drift_data) <- list(distance = drift_data_raw[[1]][1:9], + crop = JKI_crops) + if (n == 1) { # Values for railroad tracks only present for one application + drift_data[, c(1:3, 5:8)] <- as.matrix(drift_data_raw[c(2:7, 11)][1:9, ]) + } else { + drift_data[, c(1:3, 5:7)] <- as.matrix(drift_data_raw[c(2:7)][1:9, ]) + } + drift_data_JKI[[n]] <- drift_data +} + +# Manual data entry from the Rautmann paper +drift_data_JKI[[1]]["3", "Ackerbau"] <- 0.95 +drift_data_JKI[[1]][, "Weinbau frueh"] <- c(NA, 2.7, 1.18, 0.39, 0.2, 0.13, 0.07, 0.04, 0.03) +drift_data_JKI[[2]]["3", "Ackerbau"] <- 0.79 +drift_data_JKI[[2]][, "Weinbau frueh"] <- c(NA, 2.53, 1.09, 0.35, 0.18, 0.11, 0.06, 0.03, 0.02) +drift_data_JKI[[3]]["3", "Ackerbau"] <- 0.68 +drift_data_JKI[[3]][, "Weinbau frueh"] <- c(NA, 2.49, 1.04, 0.32, 0.16, 0.10, 0.05, 0.03, 0.02) +drift_data_JKI[[4]]["3", "Ackerbau"] <- 0.62 +drift_data_JKI[[4]][, "Weinbau frueh"] <- c(NA, 2.44, 1.02, 0.31, 0.16, 0.10, 0.05, 0.03, 0.02) +drift_data_JKI[[5]]["3", "Ackerbau"] <- 0.59 +drift_data_JKI[[5]][, "Weinbau frueh"] <- c(NA, 2.37, 1.00, 0.31, 0.15, 0.09, 0.05, 0.03, 0.02) +drift_data_JKI[[6]]["3", "Ackerbau"] <- 0.56 +drift_data_JKI[[6]][, "Weinbau frueh"] <- c(NA, 2.29, 0.97, 0.30, 0.15, 0.09, 0.05, 0.03, 0.02) +drift_data_JKI[[7]]["3", "Ackerbau"] <- 0.55 +drift_data_JKI[[7]][, "Weinbau frueh"] <- c(NA, 2.24, 0.94, 0.29, 0.15, 0.09, 0.05, 0.03, 0.02) +drift_data_JKI[[8]]["3", "Ackerbau"] <- 0.52 +drift_data_JKI[[8]][, "Weinbau frueh"] <- c(NA, 2.16, 0.91, 0.28, 0.14, 0.09, 0.04, 0.03, 0.02) + +# Save the data +save(drift_data_JKI, + file = here("data/drift_data_JKI.RData")) diff --git a/inst/data_generation/drift_parameters_Rautmann.R b/inst/data_generation/drift_parameters_Rautmann.R new file mode 100644 index 0000000..2dea272 --- /dev/null +++ b/inst/data_generation/drift_parameters_Rautmann.R @@ -0,0 +1,5 @@ +library(here) + +save(drift_parameters_Rautmann, + file = "../data/drift_parameters_Rautmann.RData") + diff --git a/inst/data_generation/soil_scenario_data_EFSA.R b/inst/data_generation/soil_scenario_data_EFSA.R new file mode 100644 index 0000000..80b5ce2 --- /dev/null +++ b/inst/data_generation/soil_scenario_data_EFSA.R @@ -0,0 +1,40 @@ +library(here) + +# Data from 2015 +soil_scenario_data_EFSA_2015 <- data.frame( + Zone = rep(c("North", "Central", "South"), 2), + Country = c("Estonia", "Germany", "France", "Denmark", "Czech Republik", "Spain"), + T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8), + T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7), + Texture = c("Coarse", "Coarse", "Medium fine", "Medium", "Medium", "Medium"), + f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011), + theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347), + rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51), + f_sce = c(3, 2, 2, 2, 1.5, 1.5), + f_mod = c(2, 2, 2, 4, 4, 4), + stringsAsFactors = FALSE, + row.names = c("CTN", "CTC", "CTS", "CLN", "CLC", "CLS") +) +save(soil_scenario_data_EFSA_2015, + file = here('data/soil_scenario_data_EFSA_2015.RData')) + +# Data from 2017 +soil_scenario_data_EFSA_2017 <- data.frame( + Zone = rep(c("North", "Central", "South"), 2), + Country = c("Estonia", "Poland", "France", "Denmark", "Austria", "Spain"), + T_arit = c(5.7, 7.4, 10.2, 8.0, 9.3, 15.4), + T_arr = c(7.6, 9.3, 11.7, 9.2, 11.3, 16.7), + Texture = c("Coarse", "Coarse", "Medium", "Medium", "Medium", "Medium"), + f_om = c(0.220, 0.122, 0.070, 0.025, 0.018, 0.010), + theta_fc = c(0.244, 0.244, 0.349, 0.349, 0.349, 0.349), + rho = c(0.707, 0.934, 1.117, 1.371, 1.432, 1.521), + f_sce = rep(c(1.4, 1.6), each = 3), + f_mod = rep(c(3, 4), each = 3), + FOCUS_zone = c("Hamburg", "Hamburg", "Hamburg", "Hamburg", "Ch\u00e2teaudun", "Sevilla"), + prec = c(639, 617, 667, 602, 589, 526), + stringsAsFactors = FALSE, + row.names = c("CTN", "CTC", "CTS", "CLN", "CLC", "CLS") +) + +save(soil_scenario_data_EFSA_2017, + file = here('data/soil_scenario_data_EFSA_2017.RData')) diff --git a/inst/extdata/FOCUS_GW_scenarios_2012.R b/inst/extdata/FOCUS_GW_scenarios_2012.R deleted file mode 100644 index 3715325..0000000 --- a/inst/extdata/FOCUS_GW_scenarios_2012.R +++ /dev/null @@ -1,59 +0,0 @@ -# FOCUS 2012 p. 46 ff -FOCUS_GW_scenarios_2012 = list() - -n_layers = c(7, 6, 6, 5, 5, 6, 4, 6, 6) -acronyms = c("Cha", "Ham", "Jok", "Kre", "Oke", "Pia", "Por", "Sev", "Thi") -FOCUS_GW_scenarios_2012$names = c("Ch\u00e2teadun", "Hamburg", "Jokioinen", - "Kremsm\u00fcnster", "Okehampton", - "Piacenza", "Porto", "Sevilla", "Thiva") - -names(FOCUS_GW_scenarios_2012$names) = acronyms -FOCUS_GW_scenarios_2012$soils <- data.frame( - location= rep(acronyms, times = n_layers), - horizon = c("Ap", "B1", "B2", "II C1", "II C1", "II C2", "M", - "Ap", "BvI", "BvII", "Bv/Cv", "Cv", "Cv", - "Ap", "Bs", "BC1", "BC2", "BC2", "Cg", - rep(NA, 5), - "A", "Bw1", "BC", "C", "C", - "Ap", "Ap", "Bw", "Bw", "2C", "2C", - rep(NA, 4), - rep(NA, 6), - "Ap1", "Ap2", "Bw", "Bw", "Ck1", "Ck1"), - number = unlist(sapply(n_layers, function(x) 1:x)), - pH_H2O = c(8.0, 8.1, 8.2, 8.5, 8.5, 8.5, 8.3, - 6.4, 5.6, 5.6, 5.7, 5.5, 5.5, - 6.2, 5.6, 5.4, 5.4, 5.4, 5.3, - 7.7, 7.0, 7.1, 7.1, 7.1, - 5.8, 6.3, 6.5, 6.6, 6.6, - 7, 7, 6.3, 6.3, 6.4, 6.4, - 4.9, 4.8, 4.8, 4.8, - 7.3, 7.3, 7.8, 8.1, 8.1, 8.2, - 7.7, 7.7, 7.8, 7.8, 7.8, 7.8), - perc_clay = c(30, 31, 25, 26, 26, 24, 31, - 7.2, 6.7, 0.9, 0, 0, 0, - 3.6, 1.8, 1.2, 1.7, 1.7, 1.9, - 14, 25, 27, 27, 27, - 18, 17, 14, 9, 9, - 15, 15, 7, 7, 0, 0, - 10, 8, 8, 8, - 14, 13, 15, 16, 16, 22, - 25.3, 25.3, 29.6, 31.9, 32.9, 32.9), - perc_oc = c(1.39, 0.93, 0.7, 0.3, 0.3, 0.27, 0.21, - 1.5, 1, 0.2, 0, 0, 0, - 4.06, 0.84, 0.36, 0.29, 0.29, 0.21, - 3.6, 1.0, 0.5, 0.5, 0.5, - 2.2, 0.7, 0.4, 0.1, 0.1, - 1.26, 1.26, 0.47, 0.47, 0, 0, - 1.42, 0.78, 0.78, 0.78, - 0.93, 0.93, 0.70, 0.58, 0.58, 0.49, - 0.74, 0.74, 0.57, 0.31, 0.18, 0.18), - rel_deg = c(1, 0.5, 0.5, 0.3, 0, 0, 0, - 1, 0.5, 0.3, 0.3, 0.3, 0, - 1, 0.5, 0.3, 0.3, 0, 0, - 1, 0.5, 0.5, 0.3, 0, - 1, 0.5, 0.3, 0.3, 0, - 1, 0.5, 0.5, 0.3, 0.3, 0, - 1, 0.5, 0.3, 0, - 1, 1, 0.5, 0.3, 0, 0, - 1, 0.5, 0.5, 0.3, 0.3, 0)) -save(FOCUS_GW_scenarios_2012, file = "../../data/FOCUS_GW_scenarios_2012.RData") diff --git a/log/build.log b/log/build.log new file mode 100644 index 0000000..63a1cd1 --- /dev/null +++ b/log/build.log @@ -0,0 +1,7 @@ +* checking for file ‘./DESCRIPTION’ ... OK +* preparing ‘pfm’: +* checking DESCRIPTION meta-information ... OK +* checking for LF line-endings in source and make files and shell scripts +* checking for empty or unneeded directories +* building ‘pfm_0.6.1.tar.gz’ + diff --git a/log/check.log b/log/check.log new file mode 100644 index 0000000..b08d8dc --- /dev/null +++ b/log/check.log @@ -0,0 +1,80 @@ +* using log directory ‘/home/agsad.admin.ch/f80868656/projects/pfm/pfm.Rcheck’ +* using R version 4.3.2 (2023-10-31) +* using platform: x86_64-pc-linux-gnu (64-bit) +* R was compiled by + gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 + GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 +* running under: Ubuntu 22.04.3 LTS +* using session charset: UTF-8 +* using options ‘--no-tests --as-cran’ +* checking for file ‘pfm/DESCRIPTION’ ... OK +* checking extension type ... Package +* this is package ‘pfm’ version ‘0.6.1’ +* package encoding: UTF-8 +* checking CRAN incoming feasibility ... NOTE +Maintainer: ‘Johannes Ranke ’ + +Size of tarball: 8487405 bytes +* checking package namespace information ... OK +* checking package dependencies ... OK +* checking if this is a source package ... OK +* checking if there is a namespace ... OK +* checking for executable files ... OK +* checking for hidden files and directories ... OK +* checking for portable file names ... OK +* checking for sufficient/correct file permissions ... OK +* checking whether package ‘pfm’ can be installed ... OK +* checking installed package size ... NOTE + installed size is 10.2Mb + sub-directories of 1Mb or more: + testdata 9.9Mb +* checking package directory ... OK +* checking for future file timestamps ... OK +* checking DESCRIPTION meta-information ... OK +* checking top-level files ... OK +* checking for left-over files ... OK +* checking index information ... OK +* checking package subdirectories ... OK +* checking R files for non-ASCII characters ... OK +* checking R files for syntax errors ... OK +* checking whether the package can be loaded ... OK +* checking whether the package can be loaded with stated dependencies ... OK +* checking whether the package can be unloaded cleanly ... OK +* checking whether the namespace can be loaded with stated dependencies ... OK +* checking whether the namespace can be unloaded cleanly ... OK +* checking loading without being on the library search path ... OK +* checking use of S3 registration ... OK +* checking dependencies in R code ... OK +* checking S3 generic/method consistency ... OK +* checking replacement functions ... OK +* checking foreign function calls ... OK +* checking R code for possible problems ... OK +* checking Rd files ... OK +* checking Rd metadata ... OK +* checking Rd line widths ... OK +* checking Rd cross-references ... OK +* checking for missing documentation entries ... OK +* checking for code/documentation mismatches ... OK +* checking Rd \usage sections ... OK +* checking Rd contents ... OK +* checking for unstated dependencies in examples ... OK +* checking contents of ‘data’ directory ... OK +* checking data for non-ASCII characters ... OK +* checking LazyData ... OK +* checking data for ASCII and uncompressed saves ... OK +* checking examples ... OK +* checking for unstated dependencies in ‘tests’ ... OK +* checking tests ... SKIPPED +* checking PDF version of manual ... OK +* checking HTML version of manual ... NOTE +Skipping checking HTML validation: no command 'tidy' found +* checking for non-standard things in the check directory ... OK +* checking for detritus in the temp directory ... OK +* DONE + +Status: 3 NOTEs +See + ‘/home/agsad.admin.ch/f80868656/projects/pfm/pfm.Rcheck/00check.log’ +for details. + + diff --git a/man/EFSA_GW_interception_2014.Rd b/man/EFSA_GW_interception_2014.Rd index 2334d7f..ed29454 100644 --- a/man/EFSA_GW_interception_2014.Rd +++ b/man/EFSA_GW_interception_2014.Rd @@ -14,37 +14,13 @@ of active substances of plant protection products and transformation products of these active substances in soil. \emph{EFSA Journal} \bold{12}(5):3662, 37 pp., doi:10.2903/j.efsa.2014.3662 } +\usage{ +EFSA_GW_interception_2014 +} \description{ Subset of EFSA crop interception default values for groundwater modelling } \examples{ -\dontrun{ - # This is the code that was used to define the data - bbch <- paste0(0:9, "x") - crops <- c( - "Beans (field + vegetable)", - "Peas", - "Summer oilseed rape", "Winter oilseed rape", - "Tomatoes", - "Spring cereals", "Winter cereals") - EFSA_GW_interception_2014 <- matrix(NA, length(crops), length(bbch), - dimnames = list(Crop = crops, BBCH = bbch)) - EFSA_GW_interception_2014["Beans (field + vegetable)", ] <- - c(0, 0.25, rep(0.4, 2), rep(0.7, 5), 0.8) - EFSA_GW_interception_2014["Peas", ] <- - c(0, 0.35, rep(0.55, 2), rep(0.85, 5), 0.85) - EFSA_GW_interception_2014["Summer oilseed rape", ] <- - c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9) - EFSA_GW_interception_2014["Winter oilseed rape", ] <- - c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9) - EFSA_GW_interception_2014["Tomatoes", ] <- - c(0, 0.5, rep(0.7, 2), rep(0.8, 5), 0.5) - EFSA_GW_interception_2014["Spring cereals", ] <- - c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8) - EFSA_GW_interception_2014["Winter cereals", ] <- - c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8) - save(EFSA_GW_interception_2014, - file = "../data/EFSA_GW_interception_2014.RData") -} EFSA_GW_interception_2014 } +\keyword{datasets} diff --git a/man/EFSA_washoff_2017.Rd b/man/EFSA_washoff_2017.Rd index e153fbe..28c50df 100644 --- a/man/EFSA_washoff_2017.Rd +++ b/man/EFSA_washoff_2017.Rd @@ -14,37 +14,13 @@ European Food Safety Authority (2017) EFSA guidance document for in soil. \emph{EFSA Journal} \bold{15}(10) 4982 doi:10.2903/j.efsa.2017.4982 } +\usage{ +EFSA_washoff_2017 +} \description{ Subset of EFSA crop washoff default values } \examples{ -\dontrun{ - # This is the code that was used to define the data - bbch <- paste0(0:9, "x") - crops <- c( - "Beans (field + vegetable)", - "Peas", - "Summer oilseed rape", "Winter oilseed rape", - "Tomatoes", - "Spring cereals", "Winter cereals") - EFSA_washoff_2017 <- matrix(NA, length(crops), length(bbch), - dimnames = list(Crop = crops, BBCH = bbch)) - EFSA_washoff_2017["Beans (field + vegetable)", ] <- - c(NA, 0.6, rep(0.75, 2), rep(0.8, 5), 0.35) - EFSA_washoff_2017["Peas", ] <- - c(NA, 0.4, rep(0.6, 2), rep(0.65, 5), 0.35) - EFSA_washoff_2017["Summer oilseed rape", ] <- - c(NA, 0.4, rep(0.5, 2), rep(0.6, 5), 0.5) - EFSA_washoff_2017["Winter oilseed rape", ] <- - c(NA, 0.1, rep(0.4, 2), rep(0.55, 5), 0.3) - EFSA_washoff_2017["Tomatoes", ] <- - c(NA, 0.55, rep(0.75, 2), rep(0.7, 5), 0.35) - EFSA_washoff_2017["Spring cereals", ] <- - c(NA, 0.4, 0.5, 0.5, rep(0.65, 3), rep(0.65, 2), 0.55) - EFSA_washoff_2017["Winter cereals", ] <- - c(NA, 0.1, 0.4, 0.6, rep(0.55, 3), rep(0.6, 2), 0.4) - save(EFSA_washoff_2017, - file = "../data/EFSA_washoff_2017.RData") -} EFSA_washoff_2017 } +\keyword{datasets} diff --git a/man/PEC_sw_exposit_drainage.Rd b/man/PEC_sw_exposit_drainage.Rd index 5a543c8..6f7f41a 100644 --- a/man/PEC_sw_exposit_drainage.Rd +++ b/man/PEC_sw_exposit_drainage.Rd @@ -5,7 +5,7 @@ \title{Calculate PEC surface water due to drainage as in Exposit 3} \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} + \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} } \usage{ PEC_sw_exposit_drainage( diff --git a/man/PEC_sw_exposit_runoff.Rd b/man/PEC_sw_exposit_runoff.Rd index a415a63..4b6efba 100644 --- a/man/PEC_sw_exposit_runoff.Rd +++ b/man/PEC_sw_exposit_runoff.Rd @@ -5,7 +5,7 @@ \title{Calculate PEC surface water due to runoff and erosion as in Exposit 3} \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} + \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} } \usage{ PEC_sw_exposit_runoff( diff --git a/man/PEC_sw_focus.Rd b/man/PEC_sw_focus.Rd index f23423b..362c432 100644 --- a/man/PEC_sw_focus.Rd +++ b/man/PEC_sw_focus.Rd @@ -21,7 +21,7 @@ PEC_sw_focus( met_form_water = TRUE, txt_file = "pesticide.txt", overwrite = FALSE, - append = TRUE + append = FALSE ) } \arguments{ @@ -73,7 +73,7 @@ should be written} \item{overwrite}{Should an existing file a the location specified in \code{txt_file} be overwritten? Only takes effect if append is FALSE.} -\item{append}{Should the input text file be appended?} +\item{append}{Should the input text file be appended, if it exists?} } \description{ This is a reimplementation of the FOCUS Step 1 and 2 calculator version 3.2, @@ -81,8 +81,8 @@ authored by Michael Klein, in R. Note that results for multiple applications should be compared to the corresponding results for a single application. At current, this is not done automatically in this implementation. Only Step 1 PECs are calculated. However, -input files are generated that are suitable as input also for Step 2 -to be used with the FOCUS calculator. +input files can be generated that are suitable as input for +the FOCUS calculator. } \note{ The formulas for input to the waterbody via runoff/drainage of the @@ -97,7 +97,7 @@ Step 2 is not implemented. \examples{ # Parent only dummy_1 <- chent_focus_sw("Dummy 1", cwsat = 6000, DT50_ws = 6, Koc = 344.8) -PEC_sw_focus(dummy_1, 3000, f_drift = 0, overwrite = TRUE, append = FALSE) +PEC_sw_focus(dummy_1, 3000, f_drift = 0) # Metabolite new_dummy <- chent_focus_sw("New Dummy", mw = 250, Koc = 100) diff --git a/man/drift_data_JKI.Rd b/man/drift_data_JKI.Rd index bde9aad..49b7552 100644 --- a/man/drift_data_JKI.Rd +++ b/man/drift_data_JKI.Rd @@ -14,7 +14,7 @@ data for field crops (Ackerbau), and Pome/stone fruit, early and late JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved from http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html -on 2015-06-11 +on 2015-06-11, not present any more 2024-01-31 Rautmann, D., Streloke, M and Winkler, R (2001) New basic drift values in the authorization procedure for plant protection products Mitt. Biol. @@ -43,53 +43,6 @@ Values for non-professional use listed in the JKI spreadsheet were not included. } \examples{ - -\dontrun{ - # This is the code that was used to extract the data - library(readxl) - abdrift_path <- "inst/extdata/Tabelle der Abdrifteckwerte.xls" - JKI_crops <- c("Ackerbau", "Obstbau frueh", "Obstbau spaet", "Weinbau frueh", "Weinbau spaet", - "Hopfenbau", "Flaechenkulturen > 900 l/ha", "Gleisanlagen") - names(JKI_crops) <- c("Field crops", "Pome/stone fruit, early", "Pome/stone fruit, late", - "Vines early", "Vines late", "Hops", "Areic cultures > 900 L/ha", "Railroad tracks") - drift_data_JKI <- list() - - for (n in 1:8) { - drift_data_raw <- read_excel(abdrift_path, sheet = n + 1, skip = 2) - drift_data <- matrix(NA, nrow = 9, ncol = length(JKI_crops)) - dimnames(drift_data) <- list(distance = drift_data_raw[[1]][1:9], - crop = JKI_crops) - if (n == 1) { # Values for railroad tracks only present for one application - drift_data[, c(1:3, 5:8)] <- as.matrix(drift_data_raw[c(2:7, 11)][1:9, ]) - } else { - drift_data[, c(1:3, 5:7)] <- as.matrix(drift_data_raw[c(2:7)][1:9, ]) - } - drift_data_JKI[[n]] <- drift_data - } - - # Manual data entry from the Rautmann paper - drift_data_JKI[[1]]["3", "Ackerbau"] <- 0.95 - drift_data_JKI[[1]][, "Weinbau frueh"] <- c(NA, 2.7, 1.18, 0.39, 0.2, 0.13, 0.07, 0.04, 0.03) - drift_data_JKI[[2]]["3", "Ackerbau"] <- 0.79 - drift_data_JKI[[2]][, "Weinbau frueh"] <- c(NA, 2.53, 1.09, 0.35, 0.18, 0.11, 0.06, 0.03, 0.02) - drift_data_JKI[[3]]["3", "Ackerbau"] <- 0.68 - drift_data_JKI[[3]][, "Weinbau frueh"] <- c(NA, 2.49, 1.04, 0.32, 0.16, 0.10, 0.05, 0.03, 0.02) - drift_data_JKI[[4]]["3", "Ackerbau"] <- 0.62 - drift_data_JKI[[4]][, "Weinbau frueh"] <- c(NA, 2.44, 1.02, 0.31, 0.16, 0.10, 0.05, 0.03, 0.02) - drift_data_JKI[[5]]["3", "Ackerbau"] <- 0.59 - drift_data_JKI[[5]][, "Weinbau frueh"] <- c(NA, 2.37, 1.00, 0.31, 0.15, 0.09, 0.05, 0.03, 0.02) - drift_data_JKI[[6]]["3", "Ackerbau"] <- 0.56 - drift_data_JKI[[6]][, "Weinbau frueh"] <- c(NA, 2.29, 0.97, 0.30, 0.15, 0.09, 0.05, 0.03, 0.02) - drift_data_JKI[[7]]["3", "Ackerbau"] <- 0.55 - drift_data_JKI[[7]][, "Weinbau frueh"] <- c(NA, 2.24, 0.94, 0.29, 0.15, 0.09, 0.05, 0.03, 0.02) - drift_data_JKI[[8]]["3", "Ackerbau"] <- 0.52 - drift_data_JKI[[8]][, "Weinbau frueh"] <- c(NA, 2.16, 0.91, 0.28, 0.14, 0.09, 0.04, 0.03, 0.02) - - # Save the data - save(drift_data_JKI, file = "data/drift_data_JKI.RData") -} - -# And these are the resulting data drift_data_JKI } \keyword{datasets} diff --git a/man/perc_runoff_exposit.Rd b/man/perc_runoff_exposit.Rd index 0bd2827..5b92ab3 100644 --- a/man/perc_runoff_exposit.Rd +++ b/man/perc_runoff_exposit.Rd @@ -1,5 +1,6 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/PEC_sw_exposit_runoff.R +\docType{data} \name{perc_runoff_exposit} \alias{perc_runoff_exposit} \title{Runoff loss percentages as used in Exposit 3} @@ -16,7 +17,10 @@ A data frame with percentage values for the dissolved fraction and the fraction } \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} + \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} +} +\usage{ +perc_runoff_exposit } \description{ A table of the loss percentages used in Exposit 3 for the twelve different Koc classes @@ -24,3 +28,4 @@ A table of the loss percentages used in Exposit 3 for the twelve different Koc c \examples{ print(perc_runoff_exposit) } +\keyword{datasets} diff --git a/man/perc_runoff_reduction_exposit.Rd b/man/perc_runoff_reduction_exposit.Rd index 93016b7..0157e48 100644 --- a/man/perc_runoff_reduction_exposit.Rd +++ b/man/perc_runoff_reduction_exposit.Rd @@ -16,7 +16,7 @@ from which the values were taken. } \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} + \url{https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html} Agroscope version 3.01a with additional runoff factors for 3 m and 6 m buffer zones received from Muris Korkaric (not published). The variant 3.01a2 was introduced for consistency with previous calculations performed by Agroscope for a 3 m buffer zone. diff --git a/man/soil_scenario_data_EFSA_2015.Rd b/man/soil_scenario_data_EFSA_2015.Rd index dfad4aa..4d625f8 100644 --- a/man/soil_scenario_data_EFSA_2015.Rd +++ b/man/soil_scenario_data_EFSA_2015.Rd @@ -14,7 +14,10 @@ EFSA (European Food Safety Authority) (2015) EFSA guidance document for predicting environmental concentrations of active substances of plant protection products and transformation products of these active substances in soil. \emph{EFSA Journal} \bold{13}(4) 4093 - doi:10.2903/j.efsa.2015.4093 + \doi{10.2903/j.efsa.2015.4093} +} +\usage{ +soil_scenario_data_EFSA_2015 } \description{ Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the @@ -22,26 +25,6 @@ concentration in soil as given in the EFSA guidance (2015, p. 13/14). Also, the scenario and model adjustment factors from p. 15 and p. 17 are included. } \examples{ -\dontrun{ - # This is the code that was used to define the data - soil_scenario_data_EFSA_2015 <- data.frame( - Zone = rep(c("North", "Central", "South"), 2), - Country = c("Estonia", "Germany", "France", "Denmark", "Czech Republik", "Spain"), - T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8), - T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7), - Texture = c("Coarse", "Coarse", "Medium fine", "Medium", "Medium", "Medium"), - f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011), - theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347), - rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51), - f_sce = c(3, 2, 2, 2, 1.5, 1.5), - f_mod = c(2, 2, 2, 4, 4, 4), - stringsAsFactors = FALSE, - row.names = c("CTN", "CTC", "CTS", "CLN", "CLC", "CLS") - ) - save(soil_scenario_data_EFSA_2015, file = '../data/soil_scenario_data_EFSA_2015.RData') -} - -# And this is the resulting dataframe soil_scenario_data_EFSA_2015 } \keyword{datasets} diff --git a/man/soil_scenario_data_EFSA_2017.Rd b/man/soil_scenario_data_EFSA_2017.Rd index f6de290..c43a5b7 100644 --- a/man/soil_scenario_data_EFSA_2017.Rd +++ b/man/soil_scenario_data_EFSA_2017.Rd @@ -14,7 +14,10 @@ EFSA (European Food Safety Authority) (2017) EFSA guidance document for predicting environmental concentrations of active substances of plant protection products and transformation products of these active substances in soil. \emph{EFSA Journal} \bold{15}(10) 4982 - doi:10.2903/j.efsa.2017.4982 + \doi{10.2903/j.efsa.2017.4982} +} +\usage{ +soil_scenario_data_EFSA_2017 } \description{ Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the @@ -23,5 +26,7 @@ scenario and model adjustment factors from p. 16 and p. 18 are included. } \examples{ soil_scenario_data_EFSA_2017 + +waldo::compare(soil_scenario_data_EFSA_2017, soil_scenario_data_EFSA_2015) } \keyword{datasets} diff --git a/test.log b/test.log deleted file mode 100644 index 0938948..0000000 --- a/test.log +++ /dev/null @@ -1,18 +0,0 @@ -ℹ Testing pfm -✔ | F W S OK | Context -✔ | 7 | Exposit calculations [0.1s] -✔ | 6 | Geometric mean calculation -✔ | 1 | Check max_twa for parent mkinfit models against analytical solutions [0.9s] -✔ | 1 | Simple PEC sediment calculations -✔ | 17 | Simple PEC soil calculations [0.2s] -✔ | 6 | Simple PEC surface water calculations with drift entry -✔ | 1 | Actual and time weighted average concentrations for SFO kinetics -✔ | 9 | FOCUS Step 1 calculations [0.2s] -✔ | 8 | FOCUS Steps 12 input files -✔ | 7 | Read and analyse TOXSWA cwa files [6.1s] -✔ | 12 | UK drainage PEC calculations - -══ Results ═════════════════════════════════════════════════════════════════════════════════════════ -Duration: 7.6 s - -[ FAIL 0 | WARN 0 | SKIP 0 | PASS 75 ] -- cgit v1.2.1