Air pollutants produce some of the most deleterious effects for our planet and personal health. The World Health Organization (WHO) attributes ambient and indoor air pollution to the premature death of about 6.7 million people each year. In the United States, it is estimated by the Environmental Protection Agency that about a third of the population lives in areas that don’t meet air quality levels set by the National Ambient Air Quality Standards (NAAQS). Understanding the number of individuals exposed to low-quality air requires that models precisely cover the areas impacted by various pollutants.
Anthropogenic emissions from exhaust and other pollutants have significant impacts on health and the environment, but until recently these emissions were not well tracked or mapped across most of the United States. In fact, we only had a general understanding of what counties or regions produced the most air pollution.
Mapping hourly air pollution across the contiguous United States
Researchers from George Mason University developed the Neighborhood Emission Mapping Operation (NEMO). This project produced the first hourly maps of air pollutants at 1 -kilometer spatial resolution in the contiguous United States. This helps to produce and understand where unhealthy levels of emissions are present at finer temporal scales that enable a better understanding in shifting air quality.
What air pollutants are mapped by NEMO?
The new mapping produced by NEMO includes monitoring for volatile organic compounds (VOCs), nitrous oxide/dioxide (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ammonia (NH3), and fine particulate matter (PM2.5). This is the first effort to map all these pollutants at relatively fine scales (1 KM spatial resolution) across the contiguous United States.
Creating an air pollutant map of the contiguous United States
To create such a data set for NEMO, several steps are needed. First, a base emission set is generated using the National Emission Inventory (NEI2017), which is compiled by the Environmental Protection Agency (EPA). This provides annual emissions at the county level for the relevant emissions. The Motor Vehicle Emissions Simulator (MOVES) 2014b generates motor vehicle and non-road emission estimates also at the county level. To differentiate chemicals, a chemical speciation is used which enables chemical profiles allocating pollutants to be modeled and deployed. The EPA’s speciation profiles from the SPECIATE database can be used; the MOVES database can be deployed for speciation of motor vehicle emissions.
To make a model that predict air quality at specific times, the researchers needed to break down data that is collected over longer periods, like a year or a month, into smaller time frames. This means using detailed schedules that divide yearly data into months, monthly data into days, and daily data into hours. These schedules can include information from important organizations, like the Federal Aviation Administration or the Association American Railroads, to understand pollution from planes and trains better.
For certain types of pollution, the researchers looked at weather patterns to estimate pollution movement. One of the challenges was determining where exactly in a larger area, like a county, the pollution is coming from. To solve this, the researchers used a tool called spatial surrogates using GIS. This tool was used to estimate how much pollution each small area within the county is responsible for, based on a number of factors like the number of roads, factories, and other structures that are known to affect pollution levels.
A spatial allocator (SA) tool incorporated with a PostgreSQL was used for the generation of spatial data. The SA was developed by the University of North Carolina Community Modeling and Analysis System. In total, 108 spatial surrogates were deployed across the contiguous United States. Finally, the application of the Sparse Matrix Operator Kernel Emissions (SMOKE) model produced the overall map from the developed input data.
The overall model and map enable both 1 km resolution and hourly emissions to be estimated. Model validation was conducted using the NEI and NEMO generated data. In areas compared, generally emissions varied no greater than 0.02%, demonstrating a highly accurate model.
How to find NEMO air pollutant mapping data
The NEMO air pollution data can be accessed in the NetCDF format with updates every hour, as well as in monthly and yearly summaries. Data is available in shapefile format only as a yearly summary of emissions. Data is available via the emission data portal for NEMO.
TEMPO: NASA’s high-resolution air quality satellite instrument
On April 7, 2023, NASA launched TEMPO, or Tropospheric Emissions: Monitoring of Pollution. This satellite-based spectrometer measures air pollution across North America at a resolution of four-square miles (about 10 square kilometers). TEMPO takes hourly scans of the lower atmosphere during the day across North America, stretching from the Atlantic to the Pacific coasts and from around Mexico City up to central Canada. TEMPO will take measurements of ozone, nitrogen dioxide, formaldehyde, aerosols, water vapor, and several trace gases as it passed over North America.
Benefits of more detailed pollution maps of the United States
Increasingly, it is becoming clear that more finer scale maps of pollution are needed to determine not only where the worst polluters are but also look at temporal variation for given areas. Projects, for instance, are looking at building-level emissions for CO2 as this allows more specific intervention and knowing where the largest emitters are. By producing fine-scale approaches, then it may be easier to also achieve pollution targets, such as carbon neutrality, by focusing efforts to individual areas or even buildings.
Controlling air pollution has been a difficult problem in many cities and even some rural areas. However, by creating more finer scale maps that enable even hourly tracking of such pollution, policy makers and scientists may be better able to focus efforts and create mitigation measures that can save resources and be better targeted.
Current models and maps may need to expand to other forms of air pollution to cover other health hazards, but by covering some of the most prominent emissions we now have a better way to pinpoint some of our biggest threats to health and environmental air quality. Expanding such mapping efforts to other countries may also be crucial in coming years if we are to achieve reduced pollution levels.
 For more on the methods, data, and code used to generate 1-km spatial resolution maps of emissions across the contiguous United States at 1 hour intervals, see: Ma, S., Tong, D.Q. Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States. Sci Data 9, 680 (2022). https://doi.org/10.1038/s41597-022-01790-9.
 See also Ma and Tong 2022.
 For more on fine-scale building level CO2 mapping, see: Zheng Y, Ou J, Chen G, et al. (2022) Mapping Building-Based Spatiotemporal Distributions of Carbon Dioxide Emission: A Case Study in England. International Journal of Environmental Research and Public Health 19(10): 5986. DOI: 10.3390/ijerph19105986.