def get_upstream_process_df(eia_gen_year):
"""
Automatically load all of the upstream emissions data from the various
modules. Will return a dataframe with upstream emissions from
coal, natural gas, petroleum, nuclear, and plant construction.
"""
import electricitylci.coal_upstream as coal
import electricitylci.natural_gas_upstream as ng
import electricitylci.petroleum_upstream as petro
import electricitylci.nuclear_upstream as nuke
import electricitylci.power_plant_construction as const
from electricitylci.combinator import concat_map_upstream_databases
print("Generating upstream inventories...")
coal_df = coal.generate_upstream_coal(eia_gen_year)
ng_df = ng.generate_upstream_ng(eia_gen_year)
petro_df = petro.generate_petroleum_upstream(eia_gen_year)
nuke_df = nuke.generate_upstream_nuc(eia_gen_year)
const = const.generate_power_plant_construction(eia_gen_year)
#coal and ng already conform to mapping so no mapping needed
upstream_df = concat_map_upstream_databases(eia_gen_year, petro_df,
nuke_df, const)
upstream_df = pd.concat([upstream_df, coal_df, ng_df],
sort=False,
ignore_index=True)
return upstream_df
def get_upstream_process_df():
"""
Automatically load all of the upstream emissions data from the various
modules. Will return a dataframe with upstream emissions from
coal, natural gas, petroleum, and nuclear.
"""
import electricitylci.coal_upstream as coal
import electricitylci.natural_gas_upstream as ng
import electricitylci.petroleum_upstream as petro
import electricitylci.nuclear_upstream as nuke
import electricitylci.power_plant_construction as const
from electricitylci.combinator import concat_map_upstream_databases
from electricitylci.model_config import eia_gen_year
print("Generating upstream inventories...")
coal_df = coal.generate_upstream_coal(eia_gen_year)
ng_df = ng.generate_upstream_ng(eia_gen_year)
petro_df = petro.generate_petroleum_upstream(eia_gen_year)
nuke_df = nuke.generate_upstream_nuc(eia_gen_year)
const = const.generate_power_plant_construction(eia_gen_year)
upstream_df = concat_map_upstream_databases(coal_df, ng_df, petro_df,
nuke_df, const)
return upstream_df
"""
Integration of emissions from data sources that were not included in stewi
"""
import pandas as pd
from electricitylci.coal_upstream import generate_upstream_coal
from electricitylci.model_config import eia_gen_year
# Import functions for other upstream fuels and include them in this list
# with the appropriate input parameters.
UPSTREAM_EMISSION_GENERATORS = [
generate_upstream_coal(eia_gen_year),
]
def integrate_replace_emissions(new_emissions, stewi_emissions):
"""
Replace and/or add emissions to those compiled in stewi. This is done by
concatenating the two dataframe and dropping duplicates (keep the new values).
For reference, the following FlowNames are used in stewi and should be used
in the new_emissions dataframe:
- Sulfur dioxide
- Carbon dioxide
- Methane
- Nitrogen oxides
- Nitrous oxide
Parameters
----------
new_emissions : dataframe
)
gen_plus_up_df = pd.concat([gen_df, fuel_df], ignore_index=True)
gen_plus_up_df = fill_nans(gen_plus_up_df)
return gen_plus_up_df
if __name__ == "__main__":
import electricitylci.coal_upstream as coal
import electricitylci.natural_gas_upstream as ng
import electricitylci.petroleum_upstream as petro
import electricitylci.geothermal as geo
import electricitylci.solar_upstream as solar
import electricitylci.wind_upstream as wind
import electricitylci.nuclear_upstream as nuke
coal_df = coal.generate_upstream_coal(2016)
ng_df = ng.generate_upstream_ng(2016)
petro_df = petro.generate_petroleum_upstream(2016)
geo_df = geo.generate_upstream_geo(2016)
solar_df = solar.generate_upstream_solar(2016)
wind_df = wind.generate_upstream_wind(2016)
nuke_df = nuke.generate_upstream_nuc(2016)
upstream_df = concat_map_upstream_databases(
coal_df, ng_df, petro_df, geo_df, nuke_df, solar_df, wind_df
)
plant_df = altg.create_generation_process_df()
plant_df["stage_code"] = "Power plant"
print(plant_df.columns)
print(upstream_df.columns)
combined_df = concat_clean_upstream_and_plant(plant_df, upstream_df)
canadian_inventory = import_impacts.generate_canadian_mixes(combined_df)
# ar["dataDocumentor"] = metadata["DataDocumentor"]
# ar["dataGenerator"] = metadata["DataGenerator"]
# ar["dataSetOwner"] = metadata["DatasetOwner"]
# ar["intendedApplication"] = metadata["IntendedApplication"]
# ar["projectDescription"] = metadata["ProjectDescription"]
# ar["publication"] = ""
# ar["geographyDescription"] = ""
# ar["exchangeDqSystem"] = exchangeDqsystem()
# ar["dqSystem"] = processDqsystem()
# # Temp place holder for process DQ scores
# ar["dqEntry"] = "(5;5)"
# return ar
if __name__ == "__main__":
import electricitylci.coal_upstream as coal
import electricitylci.natural_gas_upstream as ng
import electricitylci.petroleum_upstream as petro
import electricitylci.nuclear_upstream as nuke
from combinator import concat_map_upstream_databases
year = 2016
coal_df = coal.generate_upstream_coal(year)
ng_df = ng.generate_upstream_ng(year)
petro_df = petro.generate_petroleum_upstream(year)
nuke_df = nuke.generate_upstream_nuc(year)
merged = concat_map_upstream_databases(coal_df, ng_df, petro_df, nuke_df)
merged.to_csv(f"{output_dir}/total_upstream_{year}.csv")
upstream_process_dict = olcaschema_genupstream_processes(merged)
upstream_olca_processes = write_process_dicts_to_jsonld(
upstream_process_dict)