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• W4366438861 abstract "Since compliance air monitoring networks have limited spatial coverage, low-cost air quality sensors (LCAQS) are being used to facilitate exposure assessment for environmental justice communities and investigating the effects from nearby emitters. This study illustrates an application of LCAQS at the Spring Valley High School (SVHS), located at the southern fenceline of an asphalt plant in Las Vegas, Nevada, from March through August 2019 to assess the plant's contributions to schoolchildrens' PM2.5 and PM10 exposure. A computational fluid dynamics (CFD)-based dispersion modeling found that the plant's emissions affected SVHS only for wind directions ranging from 270° to 112.5°. Within the wind sector, the plant's contributions at a 5-min resolution were estimated by the incremental PM concentrations between downwind and upwind senor measurements made at SVHS and a northern fenceline site, respectively. The method was able to attribute 3.7% of the PM2.5 and 11.8% of the PM10 at SVHS to the asphalt plant over the measurement period and estimate the plant's daily contributions that were up to 28% and 50% for PM2.5 and PM10, respectively. The contributions depended on wind speed, time of day, and day of week (weekday vs. weekend), consistent with emission activities from aggregate handling in such a facility. By coupling LCAQS and CFD results, an average PM10 emission rate of 0.58 g s−1 and PM10/PM2.5 emission ratio of 11 were derived for a 10 miles per hour (4.5 m s−1) wind speed. The emission rate and ratio agree, within 20%, with estimates from the U.S. National Emission Inventory. This study design may be applicable for environmental justice-centered monitoring projects with resource constraints, providing information for stakeholders to take necessary actions to address air quality concerns." @default.
• W4366438861 created "2023-04-21" @default.
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• W4366438861 date "2023-07-01" @default.
• W4366438861 modified "2023-10-14" @default.
• W4366438861 title "High time-resolution fenceline air quality sensing and dispersion modeling for environmental justice-centered source attribution" @default.
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• W4366438861 doi "https://doi.org/10.1016/j.atmosenv.2023.119778" @default.
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