Measurement of ambient particulate matter concentrations and particle types near agricultural burns using electron microscopy and passive samplers

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• 作者：Jeff Wagner^a ; ^{Jeff.Wagner@cdph.ca.gov} ; Kinnery Naik-Patel^b ; ^c ; ^{kinnery@gmail.com} ; Stephen Wall^a ; ^{Stephen.Wall@cdph.ca.gov} ; Martha Harnly^c ; ^{Martha.Harnly@cdph.ca.gov}
• 关键词：PM2.5 ; PM10 ; Agricultural burning ; Passive samplers ; Electron microscopy ; Exposure assessment
• 刊名：Atmospheric Environment
• 出版年：2012
• 期刊代码：11_13522310
• 类别：env
• 出版时间：July, 2012
• 卷：54
• 期：Complete
• 页码：260-271
• 文件大小：1426 K

摘要

Computer-controlled scanning electron microscopy and energy-dispersive X-ray spectroscopy were used to obtain ambient PM mass concentrations, elemental size distributions, morphologies, and particle types during four Bermuda grass burn events in Imperial Valley, California. Passive PM samplers were deployed to three to six locations surrounding each burn for durations of 24-120聽h. Average PM_2.5 and PM₁₀ levels were modestly but significantly higher at locations less than 3.2聽km (two miles) from the nearest burn (n聽=聽37). During one monitored burn, higher winds caused an intense ground-level plume to envelop two samplers mounted on telephone poles very close to the field. For this event, 24-h PM_2.5 exposures downwind were up to 17 times higher than that measured upwind. Particles were classified into five distinct chemical types consistent with local area sources. Burn-related particle types, primarily submicron carbonaceous particles, contributed 95%of the PM_2.5 in the location directly impacted by the ground-level plume, compared to only 12%in the upwind location. Downwind PM_10-2.5 particles were enriched in potassium, phosphorus, chlorine, calcium, silicon, and sulfur, consistent with analyses of bulk and partially-burned Bermuda grass. The accuracy and precision of passive sampler PM measurements were all within 4聽渭g聽m^鈭?, though low median values caused high percent differences for PM_2.5. The use of electron microscopy and passive sampling in this study enabled detailed PM characterizations, spatial comparisons, and rapid deployment in often dynamic sampling scenarios.