Neighborhood Emission Mapping Operation (NEMO): A 1-km Anthropogenic Emission Dataset in the United States

Overview

Journal Sci Data

Specialty Science

Date 2022 Nov 9

PMID 36351966

Authors

Siqi Ma

Daniel Q Tong

Affiliations

Soon will be listed here.

Abstract

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

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