R/emissions.R

In JGCRI/iamrpt: Convert GCAM results to the format required by various IAM experiment databases

#### Data modules for the emissions group

#' CO2 emissions Data Module
#'
#' Produce CO2 emissions
#'
#' The raw table used by this module has columns:
#' \itemize{
#'   \item{scenario}
#'   \item{region}
#'   \item{year}
#'   \item{value}
#'   \item{Units}
#' }
#'
#' @keywords internal

module.co2_emissions <- function(mode, allqueries, aggkeys, aggfn, years,
                                  filters, ounit)
{
    if(mode == GETQ) {
        # Return titles of necessary queries
        # For more complex variables, will return multiple query titles in vector
        'CO2 Emissions'
    }
    else {
        ## silence notes on package check
        Units <- scenario <- region <- year <- service <- submode <- value <-
            NULL
        warning('The CO2 emissions module appears not to have been tested.')
        message('Function for processing variable: CO2 emissions')
        co2 <- allqueries$'CO2 emissions'
        co2 <- trans_standardize(co2) %>% # function stored in transp modules group
            dplyr::group_by(Units, scenario, region, year, service, mode, submode) %>%
            dplyr::summarise(value=sum(value)) %>%
            dplyr::ungroup()
        co2 <- filter(co2, years, filters)
        co2 <- aggregate(co2, aggfn, aggkeys)
        co2 <- unitconv_co2(co2, ounit)
        co2
    }
}

#' CO2 emissions by end-use sector Data Module
#'
#' Produce service output by technology and vintage
#'
#' The raw table used by this module has columns:
#' \itemize{
#'   \item{scenario}
#'   \item{region}
#'   \item{year}
#'   \item{value}
#'   \item{Units}
#' }
#'
#' @keywords internal

module.co2_emissions_end_use <- function(mode, allqueries, aggkeys, aggfn, years,
                                 filters, ounit)
{
    if(mode == GETQ) {
        # Return titles of necessary queries
        # For more complex variables, will return multiple query titles in vector
        'CO2 Emissions by enduse'
    }
    else {
        message('Function for processing variable: CO2 Emissions by enduse')
        co2 <- allqueries$'CO2 Emissions by enduse'
        co2 <- filter(co2, years, filters)
        co2 <- aggregate(co2, aggfn, aggkeys)

        if(!is.na(ounit)) {
            cfac <- unitconv_co2(co2$Units[1], ounit)
            if(!is.na(cfac)) {
                co2$value <- co2$value * cfac
                co2$Units <- ounit
            }
        }
        co2
    }
}

#' GHG Emissions Data Module
#'
#' Produce ghg emissions by subsector, converted to MTCO2e with AR4 GWPs
#'
#' The raw table used by this module has columns:
#' \itemize{
#'   \item{scenario}
#'   \item{region}
#'   \item{year}
#'   \item{value}
#'   \item{Units}
#' }
#'
#' @keywords internal

module.ghg_emissions_ar4 <- function(mode, allqueries, aggkeys, aggfn, years,
                                     filters, ounit)
{
    if(mode == GETQ) {
        # Return titles of necessary queries
        # For more complex variables, will return multiple query titles in vector
        'GHG emissions by subsector'
    }
    else {
        ghg_emissions_by_gwp(gwp_ar4, allqueries, aggkeys, aggfn, years,
                             filters, ounit)
    }
}

#' GHG Emissions Data Module
#'
#' Produce ghg emissions by technology, converted to MTCO2e with AR5 GWPs
#'
#' The raw table used by this module has columns:
#' \itemize{
#'   \item{scenario}
#'   \item{region}
#'   \item{year}
#'   \item{value}
#'   \item{Units}
#' }
#'
#' @keywords internal

module.ghg_emissions_ar5 <- function(mode, allqueries, aggkeys, aggfn, years,
                                     filters, ounit)
{
    if(mode == GETQ) {
        # Return titles of necessary queries
        # For more complex variables, will return multiple query titles in vector
        'GHG emissions by subsector'
    }
    else {
        ghg_emissions_by_gwp(gwp_ar5, allqueries, aggkeys, aggfn, years,
                             filters, ounit)
    }
}


#' Helper for GHG Emissions Data Module
#'
#' Produce ghg emissions by technology, converted to MTCO2e with given gwp
#'
#' @param gwp Lookup table of ghg to GWP (with units)
#' @keywords internal
ghg_emissions_by_gwp <- function(gwp, allqueries, aggkeys, aggfn, years,
                                 filters, ounit) {
    ## silence notes on package checks
    GWP <- value <- NULL

    message('Function for processing variable: GHG emissions by subsector')

    # 1. Add in GWP, and remove gases without GWP
    # 2. Convert to MTCO2e
    # 3. Add in gas type
    ghg <- allqueries$'GHG emissions by subsector' %>%
        dplyr::right_join(gwp, by = c('ghg', 'Units')) %>%
        dplyr::mutate(value = value * GWP, Units = 'MTCO2e') %>%
        dplyr::select(-GWP) %>%
        dplyr::left_join(ghg_gas_type, by = 'ghg')

    ghg <- filter(ghg, years, filters)
    ghg <- aggregate(ghg, aggfn, aggkeys)

    if(!is.na(ounit)) {
        cfac <- unitconv_counts(ghg$Units[1], ounit)
        if(!is.na(cfac)) {
            ghg$value <- ghg$value * cfac
            ghg$Units <- ounit
        }
    }
    ghg
}