The Clean Air Act first became law in 1970 and legislators could not have envisioned the capability of measuring air quality on a spatially precise basis from satellites.

By Daniel Sullivan and Alan Krupnick

New satellite data suggest that 24.4 million more Americans than previously thought live in counties that do not meet the annual health standard for fine particulate matter (PM2.5) set under the Clean Air Act. These areas were wrongly classified as meeting the standard because of the limited coverage by ground-based pollution monitors.

We used satellite-based data on fine particulate concentrations for the United States at a one-kilometer resolution to show that 54 US counties are incorrectly classified as complying with the PM2.5 standards. The satellite data show that a total of 47.6 million people live in areas that fail to meet the standard rather than 23.3 million as currently thought. The affected counties are spread across Arizona, California, Illinois, Indiana, Kentucky, Missouri, Ohio, Pennsylvania, Tennessee, Texas, and West Virginia. .

Our analysis helps to quantify the consequences of misclassification in tangible terms. If misclassified areas sped up PM2.5 reductions to match that of properly designated nonattainment areas, 5,000 deaths would be avoided.

Compliance with the PM2.5 standards is assessed primarily using ground-based monitors. However, many Americans do not live near a monitor; 79 percent of US counties do not have a PM2.5 monitor.

The National Ambient Air Quality Standards (NAAQS) and the attainment designations depend on EPA’s network of pollution monitors to provide an accurate measure of how much pollution people are exposed to. However, there are several problems with using a limited network of air pollution monitors to measure exposure of a spatially dispersed population. The fundamental issues are that air pollution varies significantly over short distances, with spikes around every factory, every road, and every refinery; pollution can travel long distances from its source; and accurate monitors are expensive to buy and operate. In 2015, 79 percent of counties did not have a PM2.5 monitor, 10 percent had one monitor, 5 percent had two monitors, and 6 percent had three or more. Even if a county has a monitor, it may not operate very often.

In addition to physical problems of measuring pollution, there are two problems with regulatory air pollution monitors that arise because air pollution is generated by economic activity. The first problem is Goodhart’s law: once a metric of economic activity becomes a regulatory target, it is no longer a good metric of the underlying activity. This is because economic actors may adapt their behavior to affect the metric, like when a teacher changes his curriculum to better fit standardized tests used to evaluate his performance. For air pollution, this “teaching to the test” could happen in a number of ways: strategic placement of monitors in less-polluted parts of the county, strategic timing of abatement by polluters when monitors are in operation, or the gradual relocation of polluters over time from locations upwind of monitors to locations downwind.

None of these distributions are static. As polluters in different locations change their polluting behavior, as establishments relocate or open for the first time, the spatial distribution of emissions changes, and in turn the overall exposure to nearby residents changes. As neighborhoods grow in some parts of a city and shrink in others, overall exposure changes. As the local climate becomes hotter, airborne pollutants react in different ways and total exposure changes. Meanwhile, the monitor observes the air at the same physical location and is blind to all these changes. If a monitor initially corresponds to the median concentration in a county, a year later it may correspond to the 40th percentile, the 60th percentile, or some other order statistic from the population exposure distribution. These problems together motivate a closer look at how well the monitors in the United States measure resident exposure to air pollution and, in turn, at whether the process of designating areas can be improved through the use of remote sensing data.

The data are primarily gathered by satellite-based instruments that measure aerosol optical depth (AOD). The best known of these instruments among economists are the MODIS instruments aboard the Terra and Aqua satellites. As these satellites orbit Earth, the MODIS instruments on board capture data on the density of airborne particles. It does this by comparing the intensity of solar radiation at the top of the atmosphere with how much radiation is reflected by Earth’s surface. The more airborne particles there are to scatter and absorb this radiation, the less radiation is reflected to the satellite. Both satellites follow a polar orbit, going from the North Pole to the South Pole and back to the North Pole every 100 minutes or so. As the satellites orbit pole to pole, Earth continues to rotate, giving the satellites a new swath of ground to scan. The satellites’ orbits are calculated so that they pass over and scan any given point on Earth at approximately the same time every day. On the sun-facing side of Earth, Terra crosses the equator at approximately 10:30 a.m. local time with each orbital pass, while Aqua crosses the equator at approximately 1:30 p.m. Thus, every location is scanned by each satellite approximately once per day at roughly the same time every day. These once-a-day readings are temporally sparser than hourly readings available from ground monitors. However, as discussed in the previous section, few monitors report hourly data, and most do not collect data every day.

The Clean Air Act establishes NAAQS that set protective limits based on science for several harmful air pollutants, like particulate matter, whose smaller particles pose the greatest health risks. According to the US Environmental Protection Agency (EPA), numerous scientific studies have linked particle pollution exposure to a variety of problems including nonfatal heart attacks, aggravated asthma, and premature death in people with heart or lung disease. Fine particles are also the main cause of reduced visibility (haze) in parts of the US, including many treasured national parks and wilderness areas.

While state and local compliance with federal air standards is determined at the county level using ground-level air pollution monitors but the network of terrestrial monitors may give a poor representation of actual levels of concentrations and population exposure.

Our recent report notes that if pollution levels in an area exceed the standard but this fact is not known, the area is unlikely to exercise mitigation actions to reduce its pollution.

We state in our paper:

“The Clean Air Act first became law in 1970 and legislators could not have envisioned the capability of measuring air quality on a spatially precise basis from satellites. Our results suggest that EPA should examine the scope for reclassifying areas according to satellite information, or at least the use of satellite data as one of several factors that enter into the designation decision.”

We are entering a new era of environmental innovation that is driving better alignment between technology and environmental goals — and results. #FourthWave

The Fourth Wave

Environmental progress doesn't just happen. It's been propelled by successive waves of innovation, each unleashing powerful new tools: Land conservation. Force of Law. Power of Market-Based Solutions. Today we are seeing the emergence of a Fourth Wave of environmental innovation.

Environmental Defense Fund

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We work with businesses, governments and communities to create lasting solutions to the most serious environmental problems. We’re EDF.

The Fourth Wave

Environmental progress doesn't just happen. It's been propelled by successive waves of innovation, each unleashing powerful new tools: Land conservation. Force of Law. Power of Market-Based Solutions. Today we are seeing the emergence of a Fourth Wave of environmental innovation.

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