Combined Burden of Heat and Particulate Matter Air Quality in WA Agriculture. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Austin, Elena; Kasner, Edward; Seto, Edmund; Spector, June
• Is Part Of: Journal of agromedicine. Volume 26:Issue 1(2021)
• Page Start: 18
• Page End: 27
• Publication Date: 2021-01-02
• Subjects: Rural air pollution -- heat index -- wildfire smoke -- agriculture -- heat stress; Agriculture -- Health aspects -- Periodicals; Agricultural laborers -- Health and hygiene -- Periodicals; 616.9803
• DOI: 10.1080/1059924X.2020.1795032
• Languages: English
• ISSNs: 1059-924X

Abstract

ABSTRACT: Objectives : To evaluate the combined burden of heat and air quality exposure in Washington State agriculture by (1) characterizing the spatiotemporal pattern of heat and PM2.5 exposures during wildfire seasons; (2) describing the potential impact of these combined exposures on agricultural worker populations; and (3) identifying data gaps for addressing this burden in rural areas. Methods: We combined county-level data to explore data availability and estimate the burden of heat and PM2.5 co-exposures for Washington agricultural workers from 2010 to 2018. Quarterly agricultural worker population estimates were linked with data from a weather station network and ambient air pollution monitoring sites. A geographical information system displayed counties, air monitoring sites, agricultural crops, and images from a smoke dispersion model during recent wildfire events. Results: We found substantial spatial and temporal variability in high heat and PM2.5 exposures. The largest peaks in PM2.5 exposures tended to occur when the heat index was around 85°F and during summers when there were wildfires. Counties with the largest agricultural populations tended to have the greatest concurrent high heat and PM2.5 exposures, and these exposures tended to be highest during the third quarter (July–September), when population counts were also highest. Additionally, we observed limited access to local air quality information in certain rural areas. Conclusion: Our findings inform efforts about highest risk areas, times of year, and data availability in rural areas. Understanding the spatiotemporal pattern of exposures is consistent with the precision agriculture framework and is foundational to addressing equity in rural agricultural settings.