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Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA. | LitMetric

AI Article Synopsis

  • The Imperial County Community Air Monitoring Network was established to offer real-time, high-resolution air quality data, particularly for particulate matter (PM), in California, focusing on vulnerable populations.
  • The study evaluates a modified low-cost Dylos optical particle counter against federal standards, revealing a reliable conversion method to estimate particle mass from Dylos data based on humidity.
  • Findings indicate that the performance of these affordable air quality sensors is generally good, providing much higher spatial and temporal detail than traditional government monitors, which can enhance community awareness and response to air quality issues.

Article Abstract

Unlabelled: The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM and PM (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R for converted hourly averaged Dylos mass measurements versus a PM BAM was 0.79 and that versus a PM BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R = 0.35-0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6179905PMC
http://dx.doi.org/10.1080/10962247.2017.1369471DOI Listing

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