Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA. (2nd December 2017)

• Record Type: Journal Article
• Authors: Carvlin, Graeme N.; Lugo, Humberto; Olmedo, Luis; Bejarano, Ester; Wilkie, Alexa; Meltzer, Dan; Wong, Michelle; King, Galatea; Northcross, Amanda; Jerrett, Michael; English, Paul B.; Hammond, Donald; Seto, Edmund
• Is Part Of: Journal of the Air & Waste Management Association. Volume 67:Number 12(2017)
• Page Start: 1342
• Page End: 1352
• Publication Date: 2017-12-02
• Subjects: Air -- Pollution -- Periodicals; Air quality management -- Periodicals; Hazardous wastes -- Management -- Periodicals; Air Pollution -- prevention & control -- Periodicals; Hazardous Waste -- prevention & control -- Periodicals; Waste Management -- Periodicals; 628.5305
• DOI: 10.1080/10962247.2017.1369471
• Languages: English
• ISSNs: 1047-3289

Abstract

ABSTRACT: 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 PM2.5 and PM10 (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 2 for converted hourly averaged Dylos mass measurements versus a PM2.5 BAM was 0.79 and that versus a PM10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high ( R 2 = 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.