CalculateEmissionFactors.Rmd

---
title: "Supply Chain GHG Emission Factors for Commodities by NAICS-6"
output:
  md_document:
    variant: gfm
params:
  dollaryear: 2022
---

Generate supply chain GHG emission factors for NAICS-6 Commodities using 2022 GHG data in CO2-equivalent and by gas.

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
source("R/Functions.R")
source("R/utils.R")
SEFversion <- get_latest_SEF_version()
install_useeior(SEFversion)
library(useeior)
library(kableExtra)
price_adjust_matrices <- c("B", "D", "M", "N", "M_margin", "N_margin")
MajorGHGs <- c("Carbon dioxide", "Methane", "Nitrous oxide")
dollaryear <- params$dollaryear
modelname <- "USEEIOv2.2.22-GHG"
checkModelIOYear(modelname)
```

```{r build-model, include=FALSE}
# Build model
modelconfigfile <- c(paste0("model-specs/", modelname, ".yml"))
model <- buildModel(modelname, configpaths=modelconfigfile)
# Calculate margin impacts for M and N matrices
model <- c(model, calculateMarginSectorImpacts(model))
# Adjust price of multipliers in model
price_adjusted_model <- list()
for (matrix in price_adjust_matrices) {
  price_adjusted_model[[paste0(matrix, "_pro_", dollaryear)]] <- adjustResultMatrixPrice(matrix, dollaryear, purchaser_price = FALSE, model)
  price_adjusted_model[[paste0(matrix, "_pur_", dollaryear)]] <- adjustResultMatrixPrice(matrix, dollaryear, purchaser_price = TRUE, model)
}
```

```{r}

prepareSEFtable <- function(table, factorform="Scientific Notation") {
  table[, 1:3] <- table[, c("Sector", "Name", "Flowable")]
  # Rename columns in table
  useeiocodefield <- paste(model$specs$CommodityorIndustryType, "Code")
  useeionamefield <- paste(model$specs$CommodityorIndustryType, "Name")
  seffields <-  c("Supply Chain Emission Factors without Margins","Margins of Supply Chain Emission Factors",
  "Supply Chain Emission Factors with Margins")
  colnames(table) <- c(useeiocodefield,
                       useeionamefield,
                       "GHG",
                       "Unit",
                       seffields) 
  # Remove records of all gov, Rest of World adjustment and electricity
  #table <- table[!substr(table[, paste(params$modeltype, "Code")], 1, 1)%in%c("S", "G"), ]
  table <- table[!substr(table[, useeiocodefield], 1, 1)%in%c("S", "G"), ]
  table <- table[!substr(table[, useeiocodefield], 1, 4) == "2211", ]
  
  # Drop 0s
  table <- table[table[,seffields[1]] != 0,]
  
  # Associate SEFs with 2017 NAICS-6
  table <- mapto2017NAICS(table,model,useeiocodefield,useeionamefield,seffields)
  
  if (factorform=="Decimal Form") {
    # Round table values to 3 digits
    table[, sapply(table, is.numeric)] <- round(table[, sapply(table, is.numeric)], 3)  
  } else {
    table[, seffields] <- lapply(table[, seffields],
                           function(x) scales::scientific(x, 3))
  }
  
  
  return(table)
}

```



Prepare table with 1 factor for All GHGs per commodity in kg CO2e/USD
```{r}
SEF_df <- generateEmissionFactorTable(model, price_adjusted_model, margin = FALSE, characterized=TRUE)
MEF_df <- generateEmissionFactorTable(model, price_adjusted_model, margin = TRUE, characterized=TRUE)
# Combine SEF and MEF tables
df <- cbind(SEF_df, MEF_df[, "FlowAmount"], SEF_df[, "FlowAmount"] + MEF_df[, "FlowAmount"])

# Filter only to include records which used the GWP-AR4-100 indicator
table_characterized <- df[df$Flowable == "All GHGs", ]

table_characterized <- prepareSEFtable(table_characterized,factorform="Decimal Form")

write_to_filename <- paste0("SupplyChainGHGEmissionFactors_",SEFversion,"_NAICS_CO2e_USD", dollaryear, ".csv")
write.csv(table_characterized, write_to_filename, row.names = FALSE, fileEncoding = "UTF-8")
```
Saved `r write_to_filename`.

Prepare table with factors for each GHG in kg gas/USD
```{r create-table-to-CSV}
SEF_df <- generateEmissionFactorTable(model, price_adjusted_model, margin = FALSE, characterized=FALSE)
MEF_df <- generateEmissionFactorTable(model, price_adjusted_model, margin = TRUE, characterized=FALSE)

df_un <- cbind(SEF_df, MEF_df[, "FlowAmount"], SEF_df[, "FlowAmount"] + MEF_df[, "FlowAmount"])

df <- rbind(df,df_un)

table_by_gas <- df_un
table_by_gas <- prepareSEFtable(table_by_gas)

write_to_filename <- paste0("SupplyChainGHGEmissionFactors_",SEFversion,"_NAICS_byGHG_USD", dollaryear,".csv")
write.csv(table_by_gas, write_to_filename, row.names = FALSE, fileEncoding = "UTF-8")


```
Saved `r write_to_filename`.