Spatialized CO2 emissions for Paris and IDF for 2019, 2030 and 2050

This repository contains multiple datasets related to energy consumption and CO2 emissions across different activity sectors (residential, traffic, tertiary, and industry) in Ile-de-France, France. The projections are based on the implementation of the Paris Climate Action Plan 2018 mitigation actions. 

Below is a detailed description of each dataset and its columns.

1. Residential Dataset

This dataset contains information on energy consumption and CO2 emissions for the residential sector over different years.

Columns:

• nom_zone: Name of the spatial zone, IDF or Paris.

• code_iris: IRIS code identifying the zone.

• conso_kwh_2019: Energy consumption in kilowatt-hours for 2019.

• conso_kwh_2030: Projected energy consumption in kilowatt-hours for 2030.

• conso_kwh_2050: Projected energy consumption in kilowatt-hours for 2050.

• kg_co2eq_2019: CO2 equivalent emissions in kilograms for 2019.

• kg_co2eq_2030: Projected CO2 equivalent emissions in kilograms for 2030.

• kg_co2eq_2050: Projected CO2 equivalent emissions in kilograms for 2050.

• population_2019: Population in the residential zone in 2019.

• population_2030: Projected population in the residential zone in 2030.

• population_2050: Projected population in the residential zone in 2050.

• geom: Geospatial data representing the location.

2. Traffic Dataset

This dataset contains information on emissions from the traffic sector over different years.

Columns:

• date: Date of data collection.

• iris: IRIS code identifying the zone.

• annee: Year of data, 2019, 2030, 2050.

• zone: Name of the geographical zone, ZFE-75 = inside Paris administrative boundaries, hors-ZFE = in IDF no application of the Low Emissions Zone (LEZ), ZFE partielle = partial application of the LEZ, ZFE totale hors 75= full application of the LEZ outside of Paris.

• categorie: Category of traffic (VP=personal vehicles, PL=heavy-duty trucks).

• type_route: Type of road (1=highway, 2= rural roads, 3=urban roads).

• emission_kg_CO2: CO2 emissions in kilograms.

• evolution_demographique: Demographic evolution impact on emissions.

• evolution_facteurs_emission: Evolution of emission factors.

• nom_iris: Name of the IRIS zone.

• geom: Geospatial data representing the location.

3. Tertiary Dataset

This dataset provides emission data for the tertiary sector over different years.

Columns: 

• annee: Year of data, eg. 2019, 2030, 2050.

• code_iris: IRIS code identifying the zone.

• tco2_par_an: CO2 emissions in tons per year.

• kgco2_par_an: CO2 emissions in kilograms per year.

• geom: Geospatial data representing the location.

4. Industry Dataset

This dataset provides emissions data for various industrial sectors.

Columns:

• emission_kg: Carbon emissions in kilograms.

• year: Year of data collection.

• iris: IRIS code identifying the zone.

• secteur: Industry.

• polluant: Type of pollutant emitted, CO2 or CO2eq.

• geom: Geospatial data representing the location.

Usage

These datasets provide insights into energy consumption, emissions, and their evolution over time across various sectors. They can be used for environmental impact studies, urban planning, and policy-making.