Socioeconomic Disparities of Low-Cost Air Quality Sensors in California, 2017-2020

Am J Public Health. 2022 Mar;112(3):434-442. doi: 10.2105/AJPH.2021.306603.

Abstract

Objectives. To (1) examine the disparity in availability of PurpleAir low-cost air quality sensors in California based on neighborhood socioeconomic status (SES) and exposure to fine particulate matter smaller than 2.5 micrometers (PM2.5), (2) investigate the temporal trend of sensor distribution and operation, and (3) identify priority communities for future sensor distribution. Methods. We obtained census tract-level SES variables and PM2.5 concentrations from the CalEnviroScreen4.0 data set. We obtained real-time PurpleAir sensor data (July 2017-September 2020) to examine sensor distribution and operation. We conducted spatial and temporal analyses at the census tract level to investigate neighborhood SES and PM2.5 concentrations in relation to sensor distribution and operation. Results. The spatial coverage and the number of PurpleAir sensors increased significantly in California. Fewer sensors were distributed in census tracts with lower SES, higher PM2.5, and higher proportions of racial/ethnic minority populations. Furthermore, a large proportion of existing sensors were not in operation at a given time, especially in disadvantaged communities. Conclusions. Disadvantaged communities should be given access to low-cost sensors to fill in spatial gaps of air quality monitoring and address environmental justice concerns. Sensor purchasing and deployment must be paired with regular maintenance to ensure their reliable performance. (Am J Public Health. 2022;112(3):434-442. https://doi.org/10.2105/AJPH.2021.306603).

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Air Pollutants / analysis*
  • Air Pollution / analysis*
  • California / epidemiology
  • Cardiovascular Diseases / epidemiology
  • Environmental Exposure / analysis*
  • Ethnic and Racial Minorities / statistics & numerical data*
  • Humans
  • Particulate Matter / analysis*
  • Residence Characteristics / statistics & numerical data
  • Sociodemographic Factors
  • Vehicle Emissions / analysis

Substances

  • Air Pollutants
  • Particulate Matter
  • Vehicle Emissions