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Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States

We present an unprecedented effort to map anthropogenic emissions of air pollutants at 1 km spatial resolution in the contiguous United States (CONUS). This new dataset, Neighborhood Emission Mapping Operation (NEMO), is produced at hourly intervals based on the United States Environmental Protectio...

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Autores principales: Ma, Siqi, Tong, Daniel Q.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646775/
https://www.ncbi.nlm.nih.gov/pubmed/36351966
http://dx.doi.org/10.1038/s41597-022-01790-9
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author Ma, Siqi
Tong, Daniel Q.
author_facet Ma, Siqi
Tong, Daniel Q.
author_sort Ma, Siqi
collection PubMed
description We present an unprecedented effort to map anthropogenic emissions of air pollutants at 1 km spatial resolution in the contiguous United States (CONUS). This new dataset, Neighborhood Emission Mapping Operation (NEMO), is produced at hourly intervals based on the United States Environmental Protection Agency (US EPA) National Emission Inventories 2017. Fine-scale spatial allocation was achieved through distributing the emission sources using 108 spatial surrogates, factors representing the portion of a source in each 1 km grid. Gaseous and particulate pollutants are speciated into model species for the Carbon Bond 6 chemical mechanism. All sources are grouped in 9 sectors and stored in NetCDF format for air quality models, and in shapefile format for GIS users and air quality managers. This dataset shows good consistency with the USEPA benchmark dataset, with a monthly difference in emissions less than 0.03% for any sector. NEMO provides the first 1 km mapping of air pollution over the CONUS, enabling new applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies.
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spelling pubmed-96467752022-11-15 Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States Ma, Siqi Tong, Daniel Q. Sci Data Data Descriptor We present an unprecedented effort to map anthropogenic emissions of air pollutants at 1 km spatial resolution in the contiguous United States (CONUS). This new dataset, Neighborhood Emission Mapping Operation (NEMO), is produced at hourly intervals based on the United States Environmental Protection Agency (US EPA) National Emission Inventories 2017. Fine-scale spatial allocation was achieved through distributing the emission sources using 108 spatial surrogates, factors representing the portion of a source in each 1 km grid. Gaseous and particulate pollutants are speciated into model species for the Carbon Bond 6 chemical mechanism. All sources are grouped in 9 sectors and stored in NetCDF format for air quality models, and in shapefile format for GIS users and air quality managers. This dataset shows good consistency with the USEPA benchmark dataset, with a monthly difference in emissions less than 0.03% for any sector. NEMO provides the first 1 km mapping of air pollution over the CONUS, enabling new applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies. Nature Publishing Group UK 2022-11-09 /pmc/articles/PMC9646775/ /pubmed/36351966 http://dx.doi.org/10.1038/s41597-022-01790-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Ma, Siqi
Tong, Daniel Q.
Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States
title Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States
title_full Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States
title_fullStr Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States
title_full_unstemmed Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States
title_short Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States
title_sort neighborhood emission mapping operation (nemo): a 1-km anthropogenic emission dataset in the united states
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9646775/
https://www.ncbi.nlm.nih.gov/pubmed/36351966
http://dx.doi.org/10.1038/s41597-022-01790-9
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