GEPA
Emission maps
Provides annual methane emission maps for the contiguous US with 0.1° spatial and monthly temporal resolution
This repository contains the code for the EPA U.S. gridded methane greenhouse gas inventory (gridded GHGI)
3 stars
2 watching
2 forks
Language: Python
last commit: almost 2 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
 iclimate/ghgpy | A Python library for calculating greenhouse gas emissions from industrial processes and facilities | 4 |
| usepa/epa_alpha_model | A model to simulate and evaluate emissions from vehicles | 8 |
| usepa/epa_moves_model | An emission modeling system for mobile sources | 86 |
 sb-ai-lab/eco2ai | A Python library for monitoring and estimating CO2 emissions from energy consumption during code execution. | 237 |
 sede-open/pyelq | Develops software to analyze and quantify methane emissions from environmental data | 13 |
 emissions-api/emissions-api | Provides access to satellite-based emission data | 75 |
 tum-esm/pyra | Automates the operation of greenhouse gas measurement setups using sensor data | 14 |
 ipeagit/gtfs2emis | An R package for estimating public transport emissions based on GTFS data | 28 |
 singularity-energy/open-grid-emissions | Provides tools and data for high-quality hourly grid emissions analysis | 79 |
 ncpp/ocgis | A Python package for geospatial manipulation and analysis of climate datasets stored in various formats | 70 |
 icos-carbon-portal/pylib | A Python library providing direct access to European greenhouse gas research data from the ICOS Carbon Portal | 12 |
 geoschem/hemco | Computes atmospheric emissions from various sources and regions on a user-defined grid | 17 |
| usepa/flowsa | A Python library for attributing resource use and environmental impacts to economic sectors. | 24 |
| geoschem/integrated_methane_inversion | A Python-based workflow for inferring methane emissions from satellite observations | 32 |
 jdechalendar/gridemissions | Provides tools and data to track power sector emissions by reconciling grid data and computing consumption-based emissions. | 38 |