Science Inventory

Spatial and Temporal Trends of Air Pollutants in the South Coast Basin Using Low Cost Sensors


Williams, R., D. Vallano, A. Polidori, AND S. Garvey. Spatial and Temporal Trends of Air Pollutants in the South Coast Basin Using Low Cost Sensors. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-17/463, 2018.


The Office of Research and Development (ORD) at EPA has been conducting a variety of both laboratory and field based evaluations/deployments of air quality sensors and other Next Generation Air Monitors (NGAM). These efforts have included laboratory and/or field evaluations of numerous NGAM devices for measuring nitrogen dioxide (NO2), ozone (O3), particulate matter (PM), volatile organic compounds (VOC), and sulfur dioxide (SO2) (Williams 2015a, Williams 2015b, Williams 2014a, Williams 2014b). ORD has published findings from some of these efforts through its Air Sensor Toolbox for Citizen Scientists, Researchers and Developers website ( During recent years, there have been significant advances in air pollution sensor technology. Specifically, sensors are now being developed that are much smaller, lightweight, and lower in cost than traditional ambient air monitoring systems. These types of sensors present an opportunity to advance EPA’s strategic goals, including community monitoring and environmental justice. One of the potential benefits of this type of technology is the ability to deploy a larger number of sensors across a small geographic area (e.g., a neighborhood) and collect data with a level of spatial and temporal resolution that would be cost-prohibitive using traditional monitoring methods. Prime examples of such efforts include the Citizen Science Air Monitor (CSAM; Barzyk 2016, Williams 2015c) and the AirMapper (U.S. EPA, 2016) devices. All of the aforementioned examples involved ORD collaboration with Regional offices and local communities and/or state air quality agencies. To the greatest extent possible, technology insights from such recent projects were leveraged in this study to reduce sensor pod development costs as well as provide for project timeline savings. This project supports the development of low cost sensor technologies that can be used for community monitoring.


The emergence of small, portable, low-cost air sensors has encouraged a shift from traditional monitoring approaches for air quality. The U.S. Environmental Protection Agency (U.S. EPA), in collaboration with the South Coast Air Quality Management District’s (SCAQMD) Air Quality Sensor Performance Evaluation Center (AQ-SPEC), deployed custom-built sensor devices (pods) measuring fine particulate matter (PM2.5), ozone (O3), relative humidity, and temperature at nine locations throughout southern California from January 2017 to April 2017 to evaluate their performance under “real-life” conditions. Prior to the deployment, these pods were evaluated within the AQ-SPEC program both in the field and in the laboratory. Southern California is ideal as a testing location for air quality sensor technology, as it often experiences elevated air pollutant levels resulting from gasoline and diesel engines, marine ports, and various other industries. The peculiar meteorology (frequent sunny days and little precipitation) and geography of the South Coast Air Basin also contribute to the elevated pollution levels in the region. The goal of this project was to characterize the performance of these newly developed pods and better understand their potential applications for community monitoring. This report provides a summary of the AQ-SPEC field and laboratory performance evaluations of the Citizen Science Air Monitor (CSAM) sensor pods designed and developed by EPA. In addition, this document summarizes the spatial and temporal variability of PM2.5 and O3 measurements collected during the field deployment of the CSAM pods at nine monitoring locations covering approximately a 200 km2 area in southern California.

Record Details:

Product Published Date: 01/04/2018
Record Last Revised: 01/08/2018
OMB Category: Other
Record ID: 339291