compute_pesticide_load_indicator {PesticideLoadIndicator}

Compute Pesticide Load Indicator with user supplied information on pesticide properties

Description

Compute Pesticide Load Indicator with user supplied information on pesticide properties

Usage

compute_pesticide_load_indicator(substances, products)

Arguments

substances

Dataframe describing active ingredients of the applied pesticide products, including their ecotoxicity, fate and human health properties.

products

Dataframe with raw pesticide application data.

Value

Dataframe with pesticide indicators for each pesticide application indicated in the products dataframe. Computes Pesticide Load Indicator (L) and its subindicators: The Human Health Load (HL), Ecotoxicity Load (TL) and Fate Load (FL). If standard dosages are provided the Standard Treatment Index (STI) and the Pesticide Load Index (LI=STI*L) are also computed.

Examples

## Not run: 
# A) Compute Pesticide Load indicator for a complete database

# load the dataframe containing the pesticide use data.
products_user <- products.load()
# load the (user-supplied) dataframe with detailed information on used pesticides.
substances_user <- substances.load()

# Compute the Pesticide Load Indicator and its sub-indicators using the user supplied data.
indicators_user <- compute_pesticide_load_indicator(substances = substances_user,
products= products_user)

# B) Compute Pesticide Load Indicator starting from basic data on products used
# Add properties of pesticides with match_ppdb()

# Step1: load the dataframe containing the basic pesticide use data.
products_basic <- products.load()[,c("product","crop","standard.dosage","formula")]
# Step2: Add information on the year in which the product is used.
# (not neccessary if all data is before 2013 - then just insert a dummy year > 2013)
products_basic$Year <- c(2009,2010,2011,2012)

# Step3: load the (user-supplied) dataframe with basic information on used pesticides
substances_basic <- substances.load()[,c("substance","product","concentration")]

# Step4: Add the CAS number of each active ingredient to link to the Pesticide Properties database.
substances_basic$CAS.number <- c("94361-06-5","141517-21-7","111988-49-9","467-69-6",
                                "1918-00-9","94-74-6","21087-64-9","142459-58-3")

# Step5: Add the Load factors as defined in the Danish Pesticide Load indicator.
# These values are supplied in the package.
# Alternatively supply own values for the Load factor.
Load.factors <- c("Load.Factor.SCI","Load.Factor.BCF","Load.Factor.SoilDT50",
       "Load.Factor.Birds","Load.Factor.Mammals","Load.Factor.Fish",
       "Load.Factor.Aquatic.Invertebrates","Load.Factor.Algae","Load.Factor.Aquatic.Plants",
       "Load.Factor.Earthworms","Load.Factor.Bees","Load.Factor.Fish.Chronic",
       "Load.Factor.Aquatic.Invertebrates.Chronic","Load.Factor.Earthworms.Chronic")
for (i in 1:length(Load.factors)){
  substances_basic[,Load.factors[i]]<- rep(times=dim(substances_basic)[[1]],
                                          substances.load()[1,Load.factors[i]])
}

# Step6: Add pesticide properties from the PPDB using the match_ppdb() function
# Indicate the folder containing the "General","Fate", "Human" and "Ecotox" tables of the PPPDB.
# Excel files (under the exact same name, e.g. Human.xlsx) are required.
# Attention, a licensed access to the PPPDB (Lewis et al., 2016) is required.
# Note that the "Fate" table should include a column indicating the "SCI.GROW" values.
folder <- "path"
matched_data <- match.ppdb (substances=substances_basic, products=products_basic, 
                            folder=folder, healthrisk_off=TRUE)
                            
products_complete<- matched_data[[1]]
substances_complete<- matched_data[[2]]

# Step7(optional): change reference values in the substances_complete data_frame if required.

# Step8: Supply the sum of risk scores based on the product label to compute the Human Health Load.
# Add the reference value for the Human Health Load 
products_complete$sum.risk.score <- c(150,25,20,130)
products_complete$reference.sum.risk.scores <- 350                                                        

# Step9: Compute the Pesticide Load Indicator and its sub-indicators 
indicators_user <- compute_pesticide_load_indicator(substances = substances_complete,
products= products_complete)
# Note that from version 1.3.1 on, the optional Pesticide Load Index
# is computed by first standardizing the Pesticide Load with the standard dosage. 

## End(Not run)