ComDef: forestry production and demand

R/functions.R

@@ -833,6 +833,77 @@ get_food_intake <- function(GCAM_version = "v7.0") {
 }
 
 
+#' get_forestry
+#'
+#' Computes Forestry production and demand
+#'
+#' @param GCAM_version Main GCAM compatible version: 'v7.0' (default), 'v7.1', or 'v6.0'.
+#' @return `forestry_demand` and `forestry_production` global variables.
+#' @keywords internal forestry
+#' @importFrom magrittr %>%
+#' @export
+get_forestry <- function(GCAM_version = "v7.0") {
+  value <- forestry_demand <- forestry_production <- NULL
+
+  # demand = domestic + imports
+  forestry_demand <-
+    rgcam::getQuery(prj, "inputs by tech") %>%
+    dplyr::filter(grepl('regional industrial_roundwood', sector)) %>%
+    dplyr::group_by(scenario, region, year) %>%
+    # billion m3 to million m3
+    dplyr::summarise(value = sum(value) /
+                       get(paste('convert',GCAM_version,sep='_'), envir = asNamespace("gcamreport"))[['conv_million_billion']]) %>%
+    dplyr::ungroup() %>%
+    dplyr::mutate(var = 'Forestry Demand|Roundwood') %>%
+    dplyr::select(dplyr::all_of(gcamreport::long_columns))
+
+  forestry_demand <- rbind(
+    forestry_demand,
+    forestry_demand %>%
+      dplyr::mutate(var = 'Forestry Demand|Roundwood|Industrial Roundwood')
+  )
+
+  # production = domestic + exports
+  forestry_exports <-
+    rgcam::getQuery(prj, "inputs by tech") %>%
+    dplyr::filter(stringr::str_detect(technology, stringr::regex("traded industrial_roundwood", ignore_case = TRUE))) %>%
+    dplyr::select(-sector,-technology,-input) %>%
+    dplyr::mutate(
+      region = stringr::str_split_fixed(subsector, " traded industrial_roundwood", 2)[, 1],
+      subsector = 'traded industrial_roundwood'
+    )
+
+  forestry_domestic <-
+    rgcam::getQuery(prj, "inputs by tech") %>%
+    dplyr::filter(grepl('domestic industrial_roundwood', subsector)) %>%
+    dplyr::select(-sector,-technology,-input)
+
+
+  forestry_production <- rbind(
+    forestry_domestic,
+    forestry_exports
+  ) %>%
+    dplyr::group_by(scenario, region, year) %>%
+    # billion m3 to million m3
+    dplyr::summarise(value = sum(value) /
+                       get(paste('convert',GCAM_version,sep='_'), envir = asNamespace("gcamreport"))[['conv_million_billion']]) %>%
+    dplyr::ungroup() %>%
+    dplyr::mutate(var = 'Forestry Production|Roundwood') %>%
+    dplyr::select(dplyr::all_of(gcamreport::long_columns))
+
+  forestry_production <- rbind(
+    forestry_production,
+    forestry_production %>%
+      dplyr::mutate(var = 'Forestry Demand|Roundwood|Industrial Roundwood')
+  )
+
+
+  forestry_demand <<- forestry_demand
+  forestry_production <<- forestry_production
+
+}
+
+
 #' get_ag_trade
 #'
 #' Computes Agricultural trade

inst/extdata/mappings/GCAM7.1/variables_functions_mapping.csv

@@ -82,3 +82,5 @@ fert_consumption_clean;get_fert_consumption;;;fertilizer consumption by region
 fert_price_clean;get_fert_price;;;ammonia and N fertilizer prices
 food_availability_clean;get_food_availability;food_intake_clean;;
 food_intake_clean;get_food_intake;population_clean;;food consumption by type (specific)
+forestry_demand;get_forestry;;;inputs by tech
+forestry_production;get_forestry;;;inputs by tech

inst/extdata/queries/GCAM7.1/queries_gcamreport_general.xml

@@ -1189,6 +1189,15 @@ A user can adjust the query to search for any of:
          <comments />
       </supplyDemandQuery>
    </aQuery>
+   <aQuery>
+      <all-regions />
+      <supplyDemandQuery title="inputs by tech">
+         <axis1 name="input">input</axis1>
+         <axis2 name="Year">demand-physical[@vintage]</axis2>
+         <xPath buildList="true" dataName="input" group="false" sumAll="false">*[@type='sector']/*[@type='subsector']/*[@type='technology']/*[@type='input']/demand-physical/node()</xPath>
+         <comments/>
+     </supplyDemandQuery>
+   </aQuery>
    <aQuery>
       <all-regions />
       <supplyDemandQuery title="transport service output by mode">