A high-resolution dataset of anthropogenic emissions: Neighborhood Emission Mapping Operation (NEMO)

A 1-km anthropogenic emission dataset in the contiguous United States which can enable new applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies.
A high-resolution dataset of anthropogenic emissions: Neighborhood Emission Mapping Operation (NEMO)
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The release of gases and particles from the Earth’s surface into the atmosphere is the starting point of many Earth system processes responsible for some of the greatest environmental challenges today, such as air pollution, acid deposition, and climate change. In the United States, over one third of the population lives in areas not attaining the health-based National Ambient Air Quality Standards (NAAQS) for ozone (O3) and/or fine particulate matter (PM2.5). Air quality and public health managers have an important task to protect public health by alerting the population when forecasts predict the exceedance of the NAAQS, which critically depends on the accurate prediction of the timing, location, and severity of unhealthy air quality episodes. A detailed description of the spatio-temporal distributions of the human-induced air pollutants emission may not only improve the air quality modeling but also support applications in public health and environmental management. Therefore, we considered to make a high-resolution emission dataset for the contiguous United States. With the data support and help from US EPA and funding support from NOAA and NASA, the anthropogenic emission dataset, called the Neighborhood Emission Mapping Operation (NEMO), are created based on the 2017 National Emissions Inventory (NEI). The emission data are mapped at 1 km spatial gridding and at hourly intervals, including integrated species like VOCs, NOx, PM2.5, and three inorganic gases, SO2, CO, and NH3. Furthermore, the VOC species are split into chemical species consistent with the Carbon Bond 6 (CB6) chemical mechanism for air quality models. The dataset is available to researchers and policy makers for the applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies.

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