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Performance of a Low-Cost Sensor Community Air Monitoring Network in Imperial County, CA. | LitMetric

AI Article Synopsis

  • Community-developed air monitoring networks can lower exposure to pollutants and influence environmental policies, but there haven't been many evaluations of them in real-world settings.
  • A network with over 40 low-cost air sensors was set up in Imperial County, CA, providing communities with real-time data on particulate matter levels and was compared to regulatory monitors from 2015 to 2018.
  • The results showed that while annual mean levels of PM were similar to regulatory monitors, these networks detected more pollution episodes and improved community involvement and understanding of air quality issues.

Article Abstract

Air monitoring networks developed by communities have potential to reduce exposures and affect environmental health policy, yet there have been few performance evaluations of networks of these sensors in the field. We developed a network of over 40 air sensors in Imperial County, CA, which is delivering real-time data to local communities on levels of particulate matter. We report here on the performance of the Network to date by comparing the low-cost sensor readings to regulatory monitors for 4 years of operation (2015-2018) on a network-wide basis. Annual mean levels of PM did not differ statistically from regulatory annual means, but did for PM for two out of the 4 years. Rs from ordinary least square regression results ranged from 0.16 to 0.67 for PM, and increased each year of operation. Sensor variability was higher among the Network monitors than the regulatory monitors. The Network identified a larger number of pollution episodes and identified under-reporting by the regulatory monitors. The participatory approach of the project resulted in increased engagement from local and state agencies and increased local knowledge about air quality, data interpretation, and health impacts. Community air monitoring networks have the potential to provide real-time reliable data to local populations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309036PMC
http://dx.doi.org/10.3390/s20113031DOI Listing

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