esta

Emissions Spatial and Temporal Allocator model

https://github.com/mmb-carb/esta

Science Score: 26.0%

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  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
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  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.7%) to scientific vocabulary

Keywords

air-pollution automobiles emissions inventory modeling on-road
Last synced: 6 months ago · JSON representation

Repository

Emissions Spatial and Temporal Allocator model

Basic Info
  • Host: GitHub
  • Owner: mmb-carb
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 77.6 MB
Statistics
  • Stars: 13
  • Watchers: 2
  • Forks: 4
  • Open Issues: 4
  • Releases: 0
Topics
air-pollution automobiles emissions inventory modeling on-road
Created over 8 years ago · Last pushed 8 months ago
Metadata Files
Readme License

README.md

ESTA

Emissions Spatial and Temporal Allocator

ESTA is a command-line tool for processing raw emissions data into spatially and temporally-allocated emissions inventories, suitable for photochemicaly modeling or other analysis. ESTA is an open-source, Python-based tool designed by the AQPSD branch of the California EPA's Air Resources Board. Though it is a general-purpose model, it is currently only used for processing on-road inventories.

Recent Updates

The source code is updated to read EMFAC2017 emissions, and has the option to output diesel PM emissions. The directory NH3dataEF17MPO010 contains the NH3 emissions files for several years and user can append the specific year of the NH3 emissions files to the EMFAC2017 emissions files. The scripts that append the NH3 emissions files to the EMFAC2017 emissions files are provided at EF17formatld and EF17formathd directories. The current version of the NH3 inventory is MPO010. Day of week fraction file 'calvadgaidowfactors2012.csv' has been replaced with 'pemsdowfactors2018.csv'.

There is another version of ESTA that uses EMFAC2021 emissions (branch EMFAC2021). The source code can be downloaded by using the following command. git clone -b EMFAC2021 https://github.com/mmb-carb/ESTA.git

ESTA Documentation

The ESTA documentation is provided as its own repository:

Open-Source Licence

As ESTA was developed by the California State government, the model and its documenation are part of the public domain. They are openly licensed under the GNU GPLv3 license, and free for all.

Owner

  • Name: Modeling and Meteorology Branch of the California Air Resources Board
  • Login: mmb-carb
  • Kind: organization
  • Location: Sacramento, California

GitHub Events

Total
  • Watch event: 2
  • Delete event: 5
  • Push event: 2
  • Create event: 3
Last Year
  • Watch event: 2
  • Delete event: 5
  • Push event: 2
  • Create event: 3

Committers

Last synced: 6 months ago

All Time
  • Total Commits: 551
  • Total Committers: 5
  • Avg Commits per committer: 110.2
  • Development Distribution Score (DDS): 0.541
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
theJollySin t****n@g****m 253
John Stilley j****y@a****v 147
dchau20 5****0@u****m 122
John Stilley j****y@a****v 26
Maybelline Disuanco m****n@u****m 3
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 20
  • Total pull requests: 0
  • Average time to close issues: 2 months
  • Average time to close pull requests: N/A
  • Total issue authors: 3
  • Total pull request authors: 0
  • Average comments per issue: 1.3
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • john-science (16)
  • leoand23 (3)
  • maybuhleen (1)
Pull Request Authors
Top Labels
Issue Labels
enhancement (14) question (7) update (1)
Pull Request Labels

Dependencies

requirements.txt pypi
  • h5py >=2.5.0
  • netCDF4 >=1.2.0
  • numpy >=1.10.0
  • pandas >0.17.0
  • pyproj >=1.9.0
  • scipy >=0.12.0