ArticleScientific data2022
Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed.
- Neighborhood-Scale OACS ES&T air · 2026Article
- Can Electric Vehicles Reduce Summertime Air Pollution Exposure Inequalities in Metro Atlanta? A High-Resolution Analysis.GeoHealth · 2026Article
- Application and Evaluation of a NOAA GFS-Driven Air Quality Model Using CMAQv5.4 and High-Resolution Emissions: FIREX-AQ 2019.Journal of geophysical research. Atmospheres : JGR · 2026Article
- Article
- Intercomparison of Modeled Urban-Scale Vehicle NOEnvironmental science & technology · 2025Article
- PMScience advances · 2024Article
- Air pollution impacts from warehousing in the United States uncovered with satellite data.Nature communications · 2024Article
- State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity.Environmental health perspectives · 2023Article
- Healthy Cities, A comprehensive dataset for environmental determinants of health in England cities.Scientific data · 2023Article
- Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States.Scientific data · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.