Data Source

Environmental Public Health Tracking Network: CDC's National Environmental Public Health Tracking Network is a website that brings together data concerning health and environmental problems. This network aims to provide information to help improve where we live, work, and play. The Tracking Network is part of the CDC's National Environmental Public Health Tracking Program. The Tracking Program includes the Tracking Network and the people, resources, and program management involved in building this network. 

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 of less than 2.5 micrometers (PM_2.5)."

• "Air Pollution - Particulate Matter has changed over time: Several government agencies track air pollution. Since 2017, County Health Rankings have used data from the Environmental Public Health Tracking (EPHT) Network. From 2013 to 2016, the County Health Rankings used data provided by the NASA Applied Sciences Program, which uses a similar methodology but also incorporates satellite data. Before 2013, the data source for this measure and the definition differed."

• "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 PM_2.5 is retained. The site-level daily monitoring data is used to create the annual average measures of PM_2.5. Only monitors with 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 PM_2.5 concentration estimates from monitor data alone. The monitor data are supplemented with modeled estimates of PM_2.5 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 PM_2.5 concentrations and does not directly reflect individual exposure. Air monitoring data provides information regarding concentrations around the monitor's location 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 PM_2.5 concentrations daily 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 PM_2.5 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 5 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 only measure progress after considering its substantial limitations. The measure data sources and modeling methods have frequently changed. Current estimates are produced using sophisticated modeling techniques, making them difficult to track progress in small geographic areas. However, trend data is available by county at AirData over time." 

Source: Air Pollution - Particulate Matter | County Health Rankings & Roadmaps

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.

• Harvard T.H. Chan School of Public Health. Nationwide study of U.S. seniors strengthens link between air pollution and premature death. https://www.hsph.harvard.edu/news/press-releases/u-s-seniors-air-pollution-premature-death. Updated June 28, 2017. Accessed July 17, 2017.

• Harvard T.H. Chan School of Public Health. More evidence of causal link between air pollution and early death. Boston. https://www.hsph.harvard.edu/news/press-releases/more-evidence-of-causal-link-between-air-pollution-and-early-death/. June 26, 2020. Accessed February 2, 2023. 

• Watts  N, Amann  M, Arnell  N,  et al. The 2019 report of The Lancet Countdown on health and climate change: ensuring that the health of a child born today is not defined by a changing climate. The Lancet. 2019; 394(10211):1836-78.

Data unavailable for year 2017