Merge pull request #92 from Metropolitan-Council/nrel-slope-emissions

NREL SLOPE emissions and scenario data import

.gitignore

@@ -326,3 +326,13 @@ _nature/data-raw/land_cover_stock.csv
 
 site_libs/
 _nature/_natural_systems_files/*
+
+_meta/data-raw/nrel_slope_emissions/scenario_planner/
+
+_meta/data-raw/nrel_slope_emissions/
+
+_meta/data-raw/nrel_slope/scenario_planner/
+
+_meta/data-raw/nrel_slope/emissions/
+
+_meta/data-raw/nrel_slope/scenario_planner.zip

_energy/data-raw/_run_energy.R

@@ -22,7 +22,7 @@ source("_energy/data-raw/wisconsin_natGas_ActivityAndEmissions.R")
 source("_energy/data-raw/processed_mn_electricUtil_activityData.R")
 source("_energy/data-raw/processed_wi_electricUtil_activityData.R")
 
-source("_energy/data-raw/nrel_slope.R")
+source("_energy/data-raw/nrel_slope_energy.R")
 
 # Done!
 

_energy/data-raw/nrel_slope.R → _energy/data-raw/nrel_slope_energy.R

@@ -2,7 +2,7 @@ source("R/_load_pkgs.R")
 source("_energy/data-raw/_energy_emissions_factors.R")
 source("R/plot_county_emissions.R")
 cprg_county <- readRDS("_meta/data/cprg_county.RDS")
-# NREL SLOPE data download, cleaning, and light viz
+# NREL SLOPE energy consumption and expenditure data download, cleaning, and viz
 
 # 1 Mmbtu is 0.293071 MWH
 mmbtu_to_mwh <- 0.293071

_meta/data-raw/nrel_slope_emissions.R

@@ -0,0 +1,46 @@
+# Read in 2020 city-level emissions data from NREL SLOPE tool
+source("R/_load_pkgs.R")
+cprg_county <- readRDS("_meta/data/cprg_county.RDS")
+cprg_city <- readRDS("_meta/data/cprg_ctu.RDS")
+# https://maps.nrel.gov/slope/
+# Zotero key @murphyStateLocalPlanning2024
+
+# City-level GHG emissions for the year 2020 are estimated by sector and energy
+# type and reported in units of carbon dioxide equivalent (CO₂e) based on the
+# 100-year time horizon global warming potential of other gases relative to (CO₂).
+
+# Estimates leveraged multiple detailed, open-source, sector-specific models and
+# datasets, which estimate current (and recent) energy consumption at county-level
+# resolution, including ResStock, ComStock, the 2018 Industrial Energy Databook,
+# the 2020 National Emissions Inventory, and the City and County Energy Profiles.
+
+
+# download city level emissions -----
+download.file("https://gds-files.nrel.gov/slope/ghg_emissions_baseline.zip",
+  destfile = "_meta/data-raw/nrel_slope/emissions/ghg_emissions_baseline.zip"
+)
+# unzip
+unzip("_meta/data-raw/nrel_slope/emissions/ghg_emissions_baseline.zip",
+  exdir = "_meta/data-raw/nrel_slope/emissions/"
+)
+
+# read in CSV
+raw_city_emissions <- read.csv("_meta/data-raw/nrel_slope/emissions/ghg_emissions_baseline_us_places_2020.csv") %>%
+  clean_names()
+
+# filtering and cleaning -----
+city_emissions <- raw_city_emissions %>%
+  mutate(
+    # extract state name
+    state_name = stringr::str_sub(city_name, start = -2, end = -1),
+    # clean city name
+    city = stringr::str_remove_all(city_name, " city, MN") %>%
+      stringr::str_remove(" city, WI") %>%
+      stringr::str_remove(" village, WI")
+  ) %>%
+  # filter to our states, our cities
+  filter(state_name %in% c("MN", "WI"),
+         city %in% cprg_city$CTU_NAME)
+
+
+city_emissions

_meta/data-raw/nrel_slope_scenario.R

@@ -0,0 +1,99 @@
+# data from NREL SLOPE emissions scenario planner
+# Reference scenario downloaded only - no interventions
+# CO2 emissions only.
+# https://maps.nrel.gov/slope/
+# Zotero key @schleiferSLOPEScenarioPlanner2023
+
+# This scenario evaluates the effects of business-as-usual projections for the
+# evolution of electricity supply and energy demand sectors, incorporating the
+# potential impacts of the Inflation Reduction Act. The electricity generation
+# mix evolves over time based on existing policies and default market and
+# technology assumptions. In this scenario, customer adoption of electric vehicles
+# and heat pumps expands significantly over time due to a combination of technology
+# cost and performance improvements, as well as incentives from the Inflation Reduction Act.
+# The electrification of buildings modeling includes new construction and
+# beneficial retrofit applications, while the electrification of vehicles
+# modeling assumes that vehicles are replaced at the end of their useful lives.
+
+# The scenario planning tool is interactive, so we can't download directly
+# from a single link
+# I downloaded each state and county manually and added each to our MS Team site
+# 
+source("R/_load_pkgs.R")
+if (!file.exists("_meta/data-raw/nrel_slope/scenario_planner/anoka_reference/c03e2f7f40cf72b29fdb11fe595cc6851bf4ed23c592b02d0014c6db-CO2-emissions-county.csv")) {
+  cli::cli_abort("You need to download the raw data from MS Teams. Contact a project lead if you need help")
+}
+
+# read in state level data -----
+nrel_reference_state <-
+  bind_rows(
+    read.csv("_meta/data-raw/nrel_slope/scenario_planner/minnesota_reference/a53f3fe1e47c31850239f7b18130bb2b10d6fcbfa78789cc3f04d391-CO2-emissions-state.csv") %>%
+      clean_names() %>%
+      mutate(state = "MN"),
+    read.csv("_meta/data-raw/nrel_slope/scenario_planner/wisconsin_reference/3613af67df1f93b92f59917564f5ac243295e4305ffc066fe88a492c-CO2-emissions-state.csv") %>%
+      clean_names() %>%
+      mutate(state = "WI")
+  )
+
+# function to read in and standard cleaning for county level data -----
+# the tables within each county folder do not have a county name column
+# so we need to add it manually
+read_nrel_scenario <- function(file_path, state, county) {
+  read.csv(file_path) %>%
+    clean_names() %>%
+    mutate(
+      state = state,
+      county = county
+    )
+}
+
+# read in and bind together all county tables
+nrel_reference_county <- bind_rows(
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/anoka_reference/c03e2f7f40cf72b29fdb11fe595cc6851bf4ed23c592b02d0014c6db-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Anoka"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/carver_reference/bec31af0df88e9aee2dc23c8c2824bcafc0853354ff2ff47d3d4c543-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Carver"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/chisago_reference/39b909e572184b8a8531342c8a5315589d75204019182c61b0dcc745-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Chisago"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/dakota_reference/8a5f4c944361f69342e894c13702c1b743f6e3fc9946dd0f36c9d2b4-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Dakota"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/hennepin_reference/d037c812b9dd6dc0d9b42c6bbb97213172391853a9ac4e83ec5c3628_county.csv",
+                     state = "MN",
+                     county = "Hennepin"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/ramsey_reference/4e0b8987e8d3b66893a4e348f049eed5af27c7d000b4e7c1f28cb2eb-CO2-emissions-county.csv",
+                     state = "MN",
+                     county = "Ramsey"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/pierce_reference/a4794ae3e72bcab0cd614f877d587092b9f5944e137d9574704875b4-CO2-emissions-county.csv",
+    state = "WI",
+    county = "Pierce"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/scott_reference/14e98aa5e7ac6c0c9914193b44c825c680a042941e86ac4697c5b183-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Scott"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/sherburne_reference/3fac4bb99b09007be8365f62fb7853db53487c6d8ada61287368e059-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Sherburne"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/st_croix_reference/335ef3b33af8dbcd9d62044979ca32a959ebca1d7965689de8ac3edc-CO2-emissions-county.csv",
+    state = "WI",
+    county = "St. Croix"
+  ),
+  read_nrel_scenario("_meta/data-raw/nrel_slope/scenario_planner/washington_reference/00ce19fbf4747a8696d1bc68b7590a9a702c270364883d01901ed16b-CO2-emissions-county.csv",
+    state = "MN",
+    county = "Washington"
+  ),
+)
+
+
+length(unique(nrel_reference_county$county))