Potential impacts of Washington State's wildfire worker protection rule on construction workers

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 μg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Wildfire Smoke Monitoring for Agricultural Safety and Health in Rural Washington

OBJECTIVES

This study aimed to evaluate the performance of a low-cost smoke sampling platform relative to environmental and occupational exposure monitoring methods in a rural agricultural region in central Washington state.

METHODS

We co-located the Thingy AQ sampling platform alongside cyclone-based gravimetric samplers, a nephelometer, and an environmental beta attenuation mass (E-BAM) monitor during August and September of 2020. Ambient particulate matter concentrations were collected during a smoke and non-smoke period and measurements were compared across sampling methods.

RESULTS

We found reasonable agreement between observations from two particle sensors within the Thingy AQ platform and the nephelometer and E-BAM measurements throughout the study period, though the measurement range of the sensors was greater during the smoke period compared to the non-smoke period. Occupational gravimetric sampling methods did not correlate with PM2.5 data collected during smoke periods, likely due to their capture of larger particle sizes than those typically measured by PM2.5 ambient air quality instruments during wildfire events.

CONCLUSION

Data collected before and during an intense wildfire smoke episode in September 2020 indicated that the low-cost smoke sampling platform provides a strategy to increase access to real-time air quality information in rural areas where regulatory monitoring networks are sparse if sensor performance characteristics under wildfire smoke conditions are understood. Improving access to spatially resolved air quality information could help agricultural employers protect both worker and crop health as wildfire smoke exposure increases due to the impacts of climate change. Such information can also assist employers with meeting new workplace wildfire smoke health and safety rules.

Potential Impacts of Different Occupational Outdoor Heat Exposure Thresholds among Washington State Crop and Construction Workers and Implications for Other Jurisdictions

Occupational heat exposure is associated with substantial morbidity and mortality among outdoor workers. We sought to descriptively evaluate spatiotemporal variability in heat threshold exceedances and describe potential impacts of these exposures for crop and construction workers. We also present general considerations for approaching heat policy-relevant analyses. We analyzed county-level 2011-2020 monthly employment (Bureau of Labor Statistics Quarterly Census of Employment and Wages) and environmental exposure (Parameter-elevation Relationships on Independent Slopes Model (PRISM)) data for Washington State (WA), USA, crop (North American Industry Classification System (NAICS) 111 and 1151) and construction (NAICS 23) sectors. Days exceeding maximum daily temperature thresholds, averaged per county, were linked with employment estimates to generate employment days of exceedances. We found spatiotemporal variability in WA temperature threshold exceedances and crop and construction employment. Maximum temperature exceedances peaked in July and August and were most numerous in Central WA counties. Counties with high employment and/or high numbers of threshold exceedance days, led by Yakima and King Counties, experienced the greatest total employment days of exceedances. Crop employment contributed to the largest proportion of total state-wide employment days of exceedances with Central WA counties experiencing the greatest potential workforce burden of exposure. Considerations from this analysis can help inform decision-making regarding thresholds, timing of provisions for heat rules, and tailoring of best practices in different industries and areas.