The Power of Data from Urban Air Quality Monitoring Networks
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Air pollution is recognized as the leading environmental risk to human health. It affects young and old, rich and poor, and unlike the food we eat and the water we drink, our air cannot be replaced with an “organic” or “bottled” alternative. Air pollution contributes to respiratory, cardiovascular, and neurological disease. A recent study found that air pollution in the United States was linked to over 100,000 premature deaths in a year at an annual cost to society of $866 billion.
Communities that already experience numerous social, economic, and environmental burdens feel these environmental health costs especially acutely. However, pinpointing the specific sources of air pollution at the local level and estimating the associated public health impacts on the community scale is notoriously difficult. Since the advent of air monitoring, use of the technology has been limited by its high cost, resulting in a lack of extensive and meaningful data, especially at the local level. But recent technological innovations have enabled reliable, low-cost air quality monitoring that can support targeted, community-level policies to improve air quality.
Challenging the Status-Quo of Air Quality Monitoring
Historically, data collected from air quality monitoring has often lacked the spatial resolution; that is, the density of monitors on the ground, necessary to identify pollution hot spots and inform subsequent policy efforts. Many different sources emit the most commonly monitored air pollutants, such as particulate matter, ozone, nitrogen oxides, sulfur oxides, and carbon monoxide. Some of these sources include traffic (heavy- and light-duty vehicles); home-heating using oil, gas, and biomass; home cooking; electricity generation from coal- and gas-fired power plants; refinery operations; prescribed fires and wildfires; and various other industrial and chemical processes. Literally every fossil fuel-burning activity pollutes the air. Consequently, attributing air pollution to specific sources on the ground is a notoriously complicated task.
Federal air quality standards in the United States, established and enforced under the Clean Air Act, are evaluated using air quality monitors sited at the regional scale. These monitors are large, expensive, and few and far between. As a result, regional air monitoring is often unable to identify local air pollution hotspots, address community-level air quality concerns, and influence effective local policies to mitigate air pollution.
Recently, low-cost air-quality sensor technology has emerged as a viable option to support denser monitor networks and provide significantly higher spatial resolution data to inform emission reduction strategies. Low-cost air-quality sensor technology has made incredible strides in both measurement accuracy and affordability. Increasingly accessible low-cost sensor technology offers ample opportunities for community-led projects that can improve public understanding of local air quality and support targeted policy efforts to improve local air quality.
As in other fields, California has led the pack in supporting community-led air monitoring efforts using low-cost air quality sensor technology through the implementation of Assembly Bill 617 (AB 617). This landmark 2017 legislation directed the California Air Resources Board (CARB) to support air quality efforts at the local level and include communities in the process.
Local Air Quality Monitoring Efforts in California
In California, local air-quality monitoring projects have flourished in recent years. In West Oakland, researchers deployed Google Street View vehicles equipped with mobile air quality monitors on roadways and found significant block-by-block differences in average air pollution concentrations. Hyperlocal air quality data, such as those collected in West Oakland, can also be used to evaluate elevated health risks associated with localized air pollution. Combining the air quality data collected with mobile monitors in West Oakland with local health outcome data, another study found elevated risks for cardiovascular events, such as heart attacks and strokes, among elderly populations living near roadways with higher concentrations of traffic-related air pollutants (nitric oxide, nitrogen dioxide, and black carbon).
While mobile monitoring data can offer extremely high spatial resolution with block-by-block pollution information, one drawback is that these data are time-averaged over the course of an entire year or season and lack the frequent and consistent measurements needed to observe air quality variations and pollution peaks on an hourly or daily time-scales. Dense networks of stationary low-cost air monitors enable both high spatial resolution and continuous real-time observations, while simultaneously providing an opportunity to engage citizens in the monitoring process. High-density stationary monitoring is currently underway in several places in California. In Los Angeles, the South Coast Air Quality Management District deployed 100 low-cost monitors that have been evaluated for precision as compared to federal standard monitors for particulate matter, ozone, and nitrogen dioxide. In Imperial County, real-time measurements of particulate matter are available online through an air monitoring program established by community groups, academics, and state agencies.
Our Project: The Richmond Air Monitoring Network
Through an AB 617 Community Air Grant, our organization, Physicians, Scientists, and Engineers for Healthy Energy (PSE), will be conducting local air-quality monitoring in the Richmond-San Pablo corridor in San Francisco East Bay (CA) over the next two years. This region is subject to numerous sources of air pollution, including three major highways with heavy commuter traffic, intensive industrial activities (e.g. the Chevron refinery), coal transport via train and the port terminal, and others. It is also located downwind from San Francisco, which provides another source of emissions contributing to ozone formation. Demographically, the area is composed of some of the most disadvantaged communities in California, according to the State’s environmental justice screening tool CalEnviroScreen 3.0.
Currently, only three Air District monitors are located in Richmond-San Pablo, which has numerous stationary emissions sources throughout the region.
Along with our community-based partner, Asian Pacific Environmental Network (APEN), PSE is launching a dense network of 50+ air quality monitors to measure concentrations of pollutants (particulate matter, ozone, and nitrogen dioxide) that are known to be associated with various adverse health outcomes. The monitors will collect measurements every minute, providing us with the ability to capture episodic spikes in pollutant concentrations, triangulate the sources, and better characterize local exposure to air pollution. Direct community feedback will influence where monitors are deployed throughout the community at homes, workplaces, and community centers and near known and suspected sources of air pollutant emissions.
This is Only the Beginning
Low-cost air monitoring technology is becoming increasingly precise, affordable, and accessible to communities in the United States and across the globe. Greater access to air quality data can improve public awareness about the relationship between air pollution and human health. Air quality data collection efforts deeply rooted in the places where people live, work, study, and play can also support increased community engagement in local policy making.
Improved understanding about local air quality can support significant policy changes and targeted incentives, including electric fleet conversions for particular transit routes, the provision of emission-control technologies or alternative routes for heavy duty trucks, targeted fuel-switching efforts for home heating in heavily impacted communities, or the enactment of new regulations for specific industrial operations. We can also use data about localized air pollution exposures to study health outcomes under specific environmental conditions. With the wealth of these new, localized data on air quality, supported by low-cost sensor technology, we can design the policies and deploy clean energy strategies that truly empower local communities and protect public health.
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I’m looking forward to seeing the results of this work and to having it replicated globally.
This paper might be helpful in terms of choosing the monitors. Its important that the data is sufficiently robust in order to get buy in from the scientists and public health professionals:
It will be helpful to name and guide to the low cost monitoring systems manufacturers and vendors. Very interesting idea to get communities involved