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Data for: Leveraging scientific community knowledge for air quality model chemistry parameterizations
Files contain values from Figures 1, 2, and 3 of the article by Pye et al., "Leveraging scientific community knowledge for air quality model chemistry parameterizations," scheduled for publication in EM in January 2024. Figures 2 and 3 are available in csv and excel spreadsheet format. Figure 1 is only available in spreadsheet format. Figure 1 shows gas and aerosol-phase chemistry representations in CMAQ since 2010. Figure 2 shows ozone and SOA formation potential (in g/g) for CRACMM species. Figure 3 shows the size (number of species and reactions) for various chemical mechanisms.
This dataset is associated with the following publication:
Pye, H., R. Schwantes, K. Barsanti, V.F. McNeill, and G. Wolfe. Leveraging scientific community knowledge for air quality model chemistry parameterizations. EM Magazine. Air and Waste Management Association, Pittsburgh, PA, USA, 24-31, (2024).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"020:00"
]
|
| contactPoint |
{
"fn": "Havala Pye",
"hasEmail": "mailto:pye.havala@epa.gov"
}
|
| description | Files contain values from Figures 1, 2, and 3 of the article by Pye et al., "Leveraging scientific community knowledge for air quality model chemistry parameterizations," scheduled for publication in EM in January 2024. Figures 2 and 3 are available in csv and excel spreadsheet format. Figure 1 is only available in spreadsheet format. Figure 1 shows gas and aerosol-phase chemistry representations in CMAQ since 2010. Figure 2 shows ozone and SOA formation potential (in g/g) for CRACMM species. Figure 3 shows the size (number of species and reactions) for various chemical mechanisms. This dataset is associated with the following publication: Pye, H., R. Schwantes, K. Barsanti, V.F. McNeill, and G. Wolfe. Leveraging scientific community knowledge for air quality model chemistry parameterizations. EM Magazine. Air and Waste Management Association, Pittsburgh, PA, USA, 24-31, (2024). |
| distribution |
[
{
"title": "https://doi.org/10.5281/zenodo.7218076",
"accessURL": "https://doi.org/10.5281/zenodo.7218076"
},
{
"title": "https://www.github.com/USEPA/CMAQ",
"accessURL": "https://www.github.com/USEPA/CMAQ"
},
{
"title": "20231120_pye_em_figuredata.xlsx",
"mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1529808/20231120_pye_em_figuredata.xlsx"
},
{
"title": "Fig2.csv",
"mediaType": "text/plain",
"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1529808/Fig2.csv"
},
{
"title": "Fig3.csv",
"mediaType": "text/plain",
"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1529808/Fig3.csv"
}
]
|
| identifier | https://doi.org/10.23719/1529808 |
| keyword |
[
"CMAQ",
"CRACMM",
"Chemical Mechanism",
"HAP",
"Nitrogen and Co-pollutants",
"Ozone",
"secondary organic aerosol (SOA)"
]
|
| license | https://pasteur.epa.gov/license/sciencehub-license.html |
| modified | 2023-11-20 |
| programCode |
[
"020:000"
]
|
| publisher |
{
"name": "U.S. EPA Office of Research and Development (ORD)",
"subOrganizationOf": {
"name": "U.S. Environmental Protection Agency",
"subOrganizationOf": {
"name": "U.S. Government"
}
}
}
|
| references |
[
"https://www.awma.org/emcurrentissue"
]
|
| rights |
null
|
| title | Data for: Leveraging scientific community knowledge for air quality model chemistry parameterizations |
