Air Pollution: Particulate Matter
The University of Wisconsin Population Health Institute Model of Health
Use the model to explore the measures of how long and how well we live and what shapes these trends. Select a measure in the diagram or browse the list of all measures.
Measures marked with an asterisk (*) are not included in summary calculations for Population Health and Well-being or Community Conditions.
About
Average daily density of fine particulate matter in micrograms per cubic meter (PM2.5). The 2025 Annual Data Release used data from 2020 for this measure.
The relationship between elevated air pollution (especially fine particulate matter and ozone) and compromised health has been well documented.1-3 Negative consequences of ambient air pollution include decreased lung function, chronic bronchitis, asthma, and other adverse pulmonary effects.1 Long-term exposure to fine particulate matter increases premature death risk among people age 65 and older, even when exposure is at levels below the National Ambient Air Quality Standards.2,3
Minority populations and those living in poverty are more likely to be exposed because of historic practices like redlining, which segregated neighborhoods and limited housing choices for these groups. Formerly redlined neighborhoods are more likely to include environmental health hazards such as coal-fired power plants.4 In 2010, approximately 164,000 premature U.S. deaths were related to fine particulate matter (PM 2.5) exposure and immigrants experienced 2.11 more deaths per 100,000 population than the U.S.-born.5
Find strategies to address Air Pollution: Particulate Matter
The University of Wisconsin Population Health Institute Model of Health
Use the model to explore the measures of how long and how well we live and what shapes these trends. Select a measure in the diagram or browse the list of all measures.
Measures marked with an asterisk (*) are not included in summary calculations for Population Health and Well-being or Community Conditions.
Data and methods
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Data Source
Environmental Public Health Tracking Network
From CDC:
CDC's National Environmental Public Health Tracking Network is a website that brings together data concerning health and environmental problems. The goal of this network is to provide information to help improve where we live, work, and play.
The Tracking Network is part of CDC's National Environmental Public Health Tracking Program. The Tracking Program includes not only the Tracking Network but the people, resources, and program management involved in building this network. The Tracking Network is a discrete product of the Tracking Program.
Website to download data
For more detailed methodological information
Key Measure Methods
Air Pollution: Particulate Matter is a density
Air Pollution: Particulate Matter is a measure of the fine particulate matter in the air. It is reported as the average daily density of fine particulate matter in micrograms per cubic meter. Fine particulate matter is defined as particles of air pollutants with an aerodynamic diameter less than 2.5 micrometers (PM2.5).
Air Pollution: Particulate Matter has changed over time
Several government agencies track air pollution. Since 2017, this measure has used data provided by the Environmental Public Health Tracking (EPHT) Network. From 2013 to 2016 this measure used data provided by the NASA Applied Sciences Program, which uses a similar methodology but also incorporates satellite data. This measure of air pollution was introduced to the Health Snapshots in 2013; prior to 2013, the Health Snapshots included two different measures: Air Pollution-Particulate Matter Days and Air Pollution-Ozone Days.
Air Pollution: Particulate Matter is created using statistical modeling
The Air Pollution: Particulate Matter measure is created based on air pollution data from monitors and modeled estimates. From EPHT: The monitoring data comes from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS). When AQS data are available from multiple monitors at one site, the maximum daily concentration of PM2.5 is retained. The site-level daily monitoring data is used to create the annual average measures of PM2.5. Only monitors that have at least 11 observations for each of the four calendar quarters are considered complete and annual averages are computed only for monitors that satisfy the completeness criteria. Many U.S. counties do not have sufficient air quality monitoring to derive PM2.5 concentration estimates from monitor data alone. The monitor data are supplemented with modeled estimates of PM2.5 concentrations derived from the Downscaler (DS) model, which uses a statistical approach to fuse monitoring data with Community Multiscale Air Quality (CMAQ) modeled outputs. DS modeled estimates are available by census tract centroid—the geographic center of the census tract. Daily county level modeled estimates are obtained by selecting the maximum value among all the census tracts within each county.
Measure limitations
This measure provides a general indication of the overall patterns and trends in annual PM2.5 concentrations and does not directly reflect individual exposure. Air monitoring data provides information regarding concentrations around the location of the monitor and doesn't capture potential inter-county variation (high concentrations near roads and other major sources) or other pollutants (such as ozone, etc.). Additionally, many monitors do not measure PM2.5 concentrations every day and can miss important short-term fluctuations in air quality (such as stagnation events). Even counties with low average fine particulate matter concentrations can experience days of dangerously elevated levels. Further, for counties without monitoring data, temporal (seasonal) and spatial (regional) biases in the modeled estimate can influence the accuracy of the PM2.5 concentration estimate.
It should be noted that these data are derived from only one air quality model among several. Like all models, this air quality model has errors. There is also a large time lag (up to five years) between when these data are collected and when the modeled results become available.
Can This Measure Be Used to Track Progress
This measure could be used to measure progress, but only after considering its substantial limitations. The measure data sources and modeling methods have frequently changed. Current estimates are produced using sophisticated modeling techniques which make them difficult to use for tracking progress in small geographic areas. However, trend data is available by county at AirData overtime.
Finding More Data
The CDC Wonder Environmental Data uses a different modeling approach than EPHT to estimate air quality. It may be useful to compare these estimates to the EPHT estimates. In addition, it may be useful to contact air quality experts in your state who may have more detailed information regarding differences in air quality within counties. For communities with air monitors located in them, the EPA maintains an AirData website that provides more current information on fine particulate matter and other types of air pollution.
References
- Pope CA, Dockery DW, Schwartz J. Review of epidemiological evidence of health-effects of particulate air-pollution. Inhalation Toxicology. 1995;7(1):1-18.
- Di Q, Wang Y, Zanobetti A, et al. Air pollution and mortality in the Medicare population. The New England Journal of Medicine. 2017;376(26).
- Harvard T.H. Chan School of Public Health. More evidence of causal link between air pollution and early death. Boston. 2020. Accessed February 2, 2023. https://www.hsph.harvard.edu/news/press-releases/more-evidence-of-causal-link-between-air-pollution-and-early-death/
- Braveman PA, Arkin E, Proctor D, Kauh T, Holm N. Systemic and structural racism: Definitions, examples, health damages, and approaches to dismantling. Health Affairs. 2022;41(2):171-178.
- Fong KC, Bell ML. Do fine particulate air pollution (PM2.5) exposure and its attributable premature mortality differ for immigrants compared to those born in the United States?. Environmental Research. 2021;196:110387.