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[{"path":"https://pkgdown.jrwb.de/pfm/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Johannes Ranke. Author, maintainer.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Johannes Ranke (2023). pfm: Utilities Pesticide Fate Modelling. R package version 0.6.0, https://github.com/jranke/pfm, https://pkgdown.jrwb.de/pfm.","code":"@Manual{, title = {pfm: Utilities for Pesticide Fate Modelling}, author = {{Johannes Ranke}}, year = {2023}, note = {R package version 0.6.0, https://github.com/jranke/pfm}, url = {https://pkgdown.jrwb.de/pfm}, }"},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"pfm","dir":"","previous_headings":"","what":"Utilities for Pesticide Fate Modelling","title":"Utilities for Pesticide Fate Modelling","text":"R package pfm provides utilities fate modelling, including dealing FOCUS pesticide fate modelling tools, (currently TOXSWA cwa files), made available GNU public license.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Utilities for Pesticide Fate Modelling","text":"easiest way install package probably use drat: Alternatively can install package using devtools package. Using quick = TRUE skips docs, multiple-architecture builds, demos, vignettes.","code":"install.packages(\"drat\") drat::addRepo(\"jranke\") install.packages(\"pfm\") library(devtools) install_github(\"jranke/pfm\", quick = TRUE)"},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"use","dir":"","previous_headings":"","what":"Use","title":"Utilities for Pesticide Fate Modelling","text":"Please refer reference.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Utilities for Pesticide Fate Modelling","text":"One recent nice example usage package visualisation time weighted average sawtooth curve obtained several overlays mkinfit predictions shown .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"Subset EFSA crop interception default values groundwater modelling","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"Subset EFSA crop washoff default values","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":null,"dir":"Reference","previous_headings":"","what":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"Currently, scenario names acronyms small subset soil definitions provided. soil definitions page 46ff. FOCUS (2012).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":null,"dir":"Reference","previous_headings":"","what":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"data extracted scenario.txt file using R code shown . text file included package licence clear.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"Actual maximum moving window time average concentrations FOMC kinetics","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"","code":"FOMC_actual_twa( alpha = 1.0001, beta = 10, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":null,"dir":"Reference","previous_headings":"","what":"Groundwater ubiquity score based on Gustafson (1989) — GUS","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"groundwater ubiquity score GUS calculated according following equation $$GUS = \\log_{10} DT50_{soil} (4 - \\log_{10} K_{oc})$$","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"","code":"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)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"... Included generic allow arguments later. Therefore also added specific methods. DT50 Half-life chemical soil. field half-life according Gustafson (1989). However, leaching sub-soil can completely excluded field dissipation experiments Gustafson refer normalisation procedure, says field study conducted use conditions. Koc sorption constant normalised organic carbon. Gustafson mention nonlinearity sorption constant commonly found usually described Freundlich sorption, therefore unclear reference concentration Koc observed (reference concentration soil porewater). chent chent given appropriate information present chyaml field, information used, defaults specified . degradation_value available degradation values ======= available degradation values >>>>>>> refs/remotes/origin/main used? lab_field laboratory field half-lives used? defaults lab implementation, order avoid double-accounting mobility. comparability original GUS values given Gustafson (1989) desired, non-normalised first-order field half-lives obtained actual use conditions used. redox Aerobic anaerobic degradation data sorption_value available sorption values used? Defaults Kfoc generally available European pesticide peer review process. values generally use reference concentration 1 mg/L porewater, means expected Koc values concentration 1 mg/L water phase. degradation_aggregator Function aggregating half-lives sorption_aggregator Function aggregation Koc values x object class GUS_result printed digits number digits used print method","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"Get relative accumulation FOMC model multiples interval","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"","code":"PEC_FOMC_accu_rel(n, interval, FOMC)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"n number applications interval Time applications FOMC Named numeric vector containing FOMC parameters alpha beta","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"numeric vector containing n accumulation factors n applications","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in soil — PEC_soil","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"basic calculation contaminant concentration bulk soil based complete, instantaneous mixing. interval given, attempt made calculating long term maximum concentration using concepts layed PPR panel opinion (EFSA PPR panel 2012 EFSA guidance PEC soil calculations (EFSA, 2015, 2017).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"","code":"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 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"rate Application rate units specified rate_units Defaults g/ha interception fraction application rate reach soil mixing_depth Mixing depth cm PEC_units Requested units calculated PEC. mg/kg currently supported PEC_pw_units mg/L currently supported interval Period deeper mixing. default NA, .e. deeper mixing. annual deeper mixing, set 365 degradation units days n_periods Number periods considered long term PEC calculations tillage_depth Periodic (see interval) deeper mixing cm leaching_depth EFSA (2017) uses mixing depth (ecotoxicological evaluation depth) calculate leaching annual crops tillage takes place. default, losses layer tillage depth taken account implementation. crop Ignored scenarios EFSA_2017. annual crops supported scenarios used. crops single cropping cycle per year currently supported. cultivation mechanical cultivation sense EFSA (2017) take place, .e. twice year depth 5 cm? Ignored scenarios EFSA_2017 chent optional chent object holding substance specific information. Can also name substance character string DT50 specified, overrides soil DT50 endpoints chent object DT50 specified available chent object, zero degradation assumed FOMC specified, named numeric vector containing FOMC parameters alpha beta. overrides degradation endpoints, degradation interval maximum PEC calculated using parameters without temperature correction Koc specified, overrides Koc endpoints chent object Kom Calculated Koc default, can explicitly specified Kom t_avg Averaging times time weighted average concentrations t_act Time series actual concentrations scenarios 'default', DT50 used without correction soil properties specified REACH guidance (R.16, Table R.16-9) used porewater PEC calculations. \"EFSA_2015\", DT50 taken modelling half-life 20°C pF2 ('chent' specified, DegT50 destination 'PECgw' used), corrected using Arrhenius activation energy 65.4 kJ/mol. Also model scenario adjustment factors EFSA guidance used. leaching leaching taken account? default FALSE, except EFSA_2017 scenarios used. porewater equilibrium porewater concentrations estimated based Kom organic carbon fraction soil instead total soil concentrations? Based equation (7) given PPR panel opinion (EFSA 2012, p. 24) scenarios specified EFSA guidance (2015, p. 13).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"predicted concentration soil","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"assumes complete load soil time specified 'interval' (typically 365 days) dosed . PPR panel opinion cited (EFSA PPR panel 2012), temperature correction using Arrhenius equation performed. Total soil porewater PEC values scenarios defined EFSA guidance (2017, p. 14/15) can easily calculated.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"time weighted average (TWA) concentrations given examples EFSA guidance 2015 (p. 80) reproduced, true TWA concentrations given example EFSA guidance 2017 (p. 92). According EFSA guidance (EFSA, 2017, p. 43), leaching taken account EFSA 2017 scenarios, using evaluation depth (mixing depth) depth layer leaching takes place. However, amount leaching evaluation depth (often 5 cm) partly mixed back tillage, default function use tillage depth calculation leaching rate. temperature information available selected scenarios, ","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"EFSA Panel Plant Protection Products Residues (2012) Scientific Opinion science behind guidance scenario selection scenario parameterisation predicting environmental concentrations plant protection products soil. EFSA Journal 10(2) 2562, doi:10.2903/j.efsa.2012.2562 EFSA (European Food Safety Authority) 2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982 EFSA (European Food Safety Authority) (2015) EFSA guidance document EFSA Journal 13(4) 4093 doi:10.2903/j.efsa.2015.4093","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"","code":"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)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"Calculate initial accumulation PEC soil set metabolites","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"","code":"PEC_soil_mets(rate, mw_parent, mets, interval = 365, ...)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"rate Application rate units specified mw_parent molecular weight parent compound mets dataframe metabolite identifiers rownames columns \"mw\", \"occ\" \"DT50\" holding molecular weight, maximum occurrence soil soil DT50 interval accumulation calculations ... arguments passed PEC_soil","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"implements method specified UK data requirements handbook checked spreadsheet published CRC website","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"","code":"PEC_sw_drainage_UK( rate, interception = 0, Koc, latest_application = NULL, soil_DT50 = NULL, model = NULL, model_parms = NULL )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"rate Application rate g/ha interception fraction application rate reach soil Koc sorption coefficient normalised organic carbon L/kg latest_application Latest application date, formatted e.g. \"01 July\" soil_DT50 Soil degradation half-life, SFO kinetics used model soil degradation model used. Either one \"FOMC\", \"DFOP\", \"HS\", \"IORE\", mkinmod object model_parms named numeric vector containing model parameters","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"predicted concentration surface water µg/L","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"basic, vectorised form simple calculation contaminant concentration surface water based complete, instantaneous mixing input via spray drift.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"","code":"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\" )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"rate Application rate units specified applications Number applications selection drift percentile water_depth Depth water body cm drift_percentages Percentage drift values calculate PECsw. 'drift_data' 'distances' NULL. drift_data Source drift percentage data. 'JKI', [drift_data_JKI] ======= Source drift percentage data. 'JKI', drift_data_JKI >>>>>>> refs/remotes/origin/main included package used. 'RF', Rautmann formula used, implemented crop type number applications crop Crop name (use German names JKI data), defaults \"Ackerbau\" distances distances m get PEC values rate_units Defaults g/ha PEC_units Requested units calculated PEC. µg/L currently supported","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"predicted concentration surface water","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"reimplementation calculation described Exposit 3.02 spreadsheet file, worksheet \"Konzept Drainage\". Although four groups compounds (\"Gefährdungsgruppen\"), one distinction made calculations, compounds low mobility (group 1) compounds modest high mobility (groups 2, 3 4). implementation, group derived Koc, given explicitly. details, see discussion function arguments .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"","code":"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 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"reimplementation calculation described Exposit 3.02 spreadsheet file, worksheet \"Konzept Runoff\".","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"","code":"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 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"reimplementation FOCUS Step 1 2 calculator version 3.2, authored Michael Klein, R. Note results multiple applications compared corresponding results single application. current, done automatically implementation. Step 1 PECs calculated. However, input files can generated suitable input FOCUS calculator.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"","code":"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 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in sediment from surface\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","title":"Calculate predicted environmental concentrations in sediment from surface\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"method 'percentage' equivalent used CRD spreadsheet PEC calculator","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in sediment from surface\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"","code":"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\") )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in sediment from surface\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"PEC_sw Numeric vector matrix surface water concentrations µg/L corresponding sediment concentration estimated percentage percentage sediment, used percentage method method method used calculation sediment_depth Depth sediment layer water_depth Depth water body cm sediment_density density sediment L/kg (equivalent g/cm3) PEC_sed_units units estimated sediment PEC value","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in sediment from surface\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"predicted concentration sediment","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"Actual maximum moving window time average concentrations SFO kinetics","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"implements method specified UK data requirements handbook checked spreadsheet published CRC website","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"R6 class holding TOXSWA water concentration (cwa) data associated statistics. like maximum moving window average concentrations, dataframes holding events exceeding specified thresholds. Usually, instance class generated read.TOXSWA_cwa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimation of the transpiration stream concentration factor — TSCF","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"FOCUS groundwater guidance (FOCUS 2014, p. 41) states reliable measured log Kow neutral pH must available order apply Briggs equation. clarified can regarded reliable, equation stated produced non-ionic compounds, suggesting compound ionogenic (weak acid/base) ionic.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"Create chemical compound object FOCUS Step 1 calculations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"","code":"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 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"name Length one character vector containing name Koc Partition coefficient organic carbon water L/kg. Half-life water/sediment systems days DT50_soil Half-life soil days DT50_water Half-life water days (Step 2) DT50_sediment Half-life sediment days (Step 2) cwsat Water solubility mg/L mw Molar weight g/mol. max_soil Maximum observed fraction (dimensionless) soil max_ws Maximum observed fraction (dimensionless) water/sediment systems","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":null,"dir":"Reference","previous_headings":"","what":"Deposition from spray drift expressed as percent of the applied dose as\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","title":"Deposition from spray drift expressed as percent of the applied dose as\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"Deposition spray drift expressed percent applied dose published German Julius-Kühn Institute (JKI).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Deposition from spray drift expressed as percent of the applied dose as\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"list currently containing matrices spray drift percentage data field crops (Ackerbau), Pome/stone fruit, early late (Obstbau frueh, spaet).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Deposition from spray drift expressed as percent of the applied dose as\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html 2015-06-11, present 2024-01-31 Rautmann, D., Streloke, M Winkler, R (2001) New basic drift values authorization procedure plant protection products Mitt. Biol. Bundesanst. Land- Forstwirtsch. 383, 133-141","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Deposition from spray drift expressed as percent of the applied dose as\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"data extracted spreadsheet cited using R code given example section. spreadsheet included package licence clear. Additional spray drift values taken publication Rautmann et al. (2001). Specifically, values early vines, values 3 m buffer incomplete spreadsheet. Note vegetables, ornamentals small fruit, values field crops used crops < 50 cm, vales late vines used crops > 50 cm. JKI spreadsheet, indicated values used spray applications handheld/knapsack equipment (tragbare Spritz- und Sprühgerate). Values non-professional use listed JKI spreadsheet included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deposition from spray drift expressed as percent of the applied dose as\n=======\n<!-- Generated by pkgdown: do not edit by hand --><html lang=","text":"","code":"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 >>>>>>> refs/remotes/origin/main #> [[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 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"R6 class objects class chent represent chemical entities can hold list information loaded chemical yaml file chyaml field. information extracted optionally aggregated function.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"","code":"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 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"chent chent object get information medium medium information sought type information type lab_field NA, want laboratory field endpoints redox NA, looking aerobic anaerobic data value name value want. list given ======= name value want. list given >>>>>>> refs/remotes/origin/main usage section exclusive aggregator aggregator function. Can mean, ======= aggregator function. Can mean, >>>>>>> refs/remotes/origin/main geomean, identity, example. raw number(s) returned stored chent object (character value) retain original information precision? signif many significant digits want values values returned aggregators named vector aggregator functions used","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the geometric mean — geomean","title":"Calculate the geometric mean — geomean","text":"Based posts thread Stackoverflow http://stackoverflow.com/questions/2602583/geometric-mean----built-function returns NA NA values present na.rm = FALSE (default). negative values present, gives error message. least one element vector 0, returns 0.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit a parabola through three points — get_vertex","title":"Fit a parabola through three points — get_vertex","text":"inspired answer stackoverflow https://stackoverflow.com//717791","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"The maximum time weighted average concentration for a moving window — max_twa","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"generate time series using sawtooth, need make sure length time series allows finding maximum. therefore recommended check using plot.one_box using window size argument max_twa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a time series of decline data — one_box","title":"Create a time series of decline data — one_box","text":"Create time series decline data","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a time series of decline data — one_box","text":"","code":"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)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a time series of decline data — one_box","text":"x numeric, half-life used exponential decline. character string specifying parent decline model given e.g. FOMC, parms must contain corresponding parameters. x mkinfit object, decline calculated object. ini initial amount. x mkinfit object, ini 'model', fitted initial concentrations used. Otherwise, ini must numeric. length one, used parent initial values metabolites zero, otherwise, must give values observed variables. ... arguments passed methods t_end End time series res Resolution time series parms named numeric vector containing model parameters","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a time series of decline data — one_box","text":"object class one_box, inheriting ts.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a time series of decline data — one_box","text":"","code":"# 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)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":null,"dir":"Reference","previous_headings":"","what":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"table loss percentages used Exposit 3 twelve different Koc classes","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":null,"dir":"Reference","previous_headings":"","what":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"table runoff reduction percentages used Exposit 3 different vegetated buffer widths","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"Calculate time course relative concentrations based mkinmod model","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"","code":"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) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"model degradation model used. Either parent model like 'SFO' 'FOMC', mkinmod object DT50 half-life. used simple exponential decline calculated (SFO model). parms parameters used degradation model years many years degradation predicted? step_days step size days output ? times output times","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"Plot TOXSWA hourly concentrations chemical substance specific segment TOXSWA surface water body.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"","code":"# 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\", ... )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"x TOXSWA_cwa object plotted. time_column used time axis. \"t_firstjan\" chosen, time given days relative first January first year. xlab, ylab Labels x y axis. add add existing plot? threshold_factor factor data lower maximum order get thinned plotting (see next argument). thin_low integer greater 1, data close zero (smaller 1/threshold_factor maximum) series thinned factor order decrease amount data included plots total total concentration water plotted, including substance sorbed suspended matter? LC_TIME Specification locale used format dates ... arguments passed plot adding existing plot","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot time series of decline data — plot.one_box","title":"Plot time series of decline data — plot.one_box","text":"Plot time series decline data","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot time series of decline data — plot.one_box","text":"","code":"# 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], ... )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot time series of decline data — plot.one_box","text":"x object type one_box plotted xlim Limits x axis ylim Limits y axis xlab Label x axis ylab Label y axis max_twa numeric value given, maximum time weighted average concentration(s) /shown graph. max_twa_var Variable maximum time weighted average shown max_twa NULL. ... arguments passed methods","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"Read TOXSWA hourly concentrations chemical substance specific segment TOXSWA surface water body. Per default, data last segment imported. TOXSWA 4 reports values end hour (ConLiqWatLayCur) summary file, use value well instead hourly averages (ConLiqWatLay). TOXSWA 5.5.3 variable renamed ConLiqWatLay file.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"","code":"read.TOXSWA_cwa( filename, basedir = \".\", zipfile = NULL, segment = \"last\", substance = \"parent\", total = FALSE, windows = NULL, thresholds = NULL )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"filename filename cwa file (TOXSWA 2.x.y similar) file using FOCUS TOXSWA 4 (.e. TOXSWA 4.4.2) higher. basedir path directory cwa file resides. zipfile Optional path zip file containing cwa file. segment segment data read. Either \"last\", segment number. substance .files, default value \"parent\" leads reading concentrations parent compound. Alternatively, substance interested can selected code name. total Set TRUE order read total concentrations well. necessary .files generated TOXSWA 4.4.2 similar, .cwa files. .cwa files, total concentration always read well. windows Numeric vector width moving windows days, calculating maximum time weighted average concentrations areas curve. thresholds Numeric vector threshold concentrations µg/L generating event statistics.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"instance R6 object class TOXSWA_cwa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. mkin set_nd_nq, set_nd_nq_focus","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Create decline time series for multiple applications — sawtooth","title":"Create decline time series for multiple applications — sawtooth","text":"application pattern specified applications, n disregarded.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create decline time series for multiple applications — sawtooth","text":"","code":"sawtooth( x, n = 1, i = 365, applications = data.frame(time = seq(0, (n - 1) * i, length.out = n), amount = 1) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create decline time series for multiple applications — sawtooth","text":"x one_box object n number applications. applications specified, n ignored interval applications. applications specified, ignored applications data frame holding application times first column corresponding amounts applied second column.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create decline time series for multiple applications — sawtooth","text":"","code":"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 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":null,"dir":"Reference","previous_headings":"","what":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"Properties predefined scenarios used Tier 1, Tier 2A Tier 3A concentration soil given EFSA guidance (2015, p. 13/14). Also, scenario model adjustment factors p. 15 p. 17 included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":null,"dir":"Reference","previous_headings":"","what":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"Properties predefined scenarios used Tier 1, Tier 2A Tier 3A concentration soil given EFSA guidance (2017, p. 14/15). Also, scenario model adjustment factors p. 16 p. 18 included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate a time weighted average concentration — twa","title":"Calculate a time weighted average concentration — twa","text":"moving average built using values past, earliest possible time maximum time series returned one window passed.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate a time weighted average concentration — twa","text":"","code":"twa(x, window = 21) # S3 method for one_box twa(x, window = 21)"}]
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