Community-based air toxics monitoring during rapid environmental change in industrialized neighborhoods

2019年6月，东海岸最大的炼油厂发生大规模爆炸，震动了南卡罗来纳州的建筑物。 费城居民被告知就地避难，同时676，000磅碳氢化合物和3，271磅 致命的氟化氢（HF）冲刷他们的社区，2，3和市卫生部门保证 两年后，费城能源公司停止运营， 解决方案（PES）综合体仍然是美国第二大苯排放炼油厂。7、尽管 在退役和拆除过程中挥发性有机化合物（VOCs）的排放量，很少有数据 提供给居民;一个当地的环保署空气质量系统（AQS）监测挥发性有机化合物的运作，只有每 第6天，所需的警戒线监测在2周的平均值内消除了峰值事件。 自2020年3月起已在线更新。10 -12 我们的主要目标是与费城繁荣合作 - 一个环境正义组织 fenceline居民的选区- 设计和建立一个社区范围的空气有毒物质监测网络， 在整个退役和重建过程中捕获和报告持续的暴露， 社区炼油厂和石油化工厂附近的居民不成比例地是非洲裔美国人， 61%是 7，15社会压力和污染暴露的汇合 围绕这个网站-以及我们正在开发的基于社区的监测设计模型- 对全国各地的围栏社区具有相关性和实用性。 西班牙裔，社会经济地位较低（SEP）; 13，14在这里，超过300，000人居住在3英里内; 通过建立一个高密度、社区规模的BTEX（苯、甲苯、甲苯、二甲苯）VOC 监测网络，我们将评估暴露量升高的地方，以及源活动的变化 和气象学会增加暴露。在计划的10年退役过程中， 包括拆除950英里管道、几十个储存罐和地下苯“池”19，20-我们 监测系统将在浓度较低时为社区提供重要的保证， 在浓度高的情况下倡导改进-具有第三方学术机构的可信度 科学家与社区建立了良好的关系。我们的研究将极大地改善空间和时间 解决当前稀疏监测的问题，以减少暴露，以及 推动清洁生产的有力杠杆。 提供关键性信息 我们会寻求进一步拨款，以维持该系统 经过10年的退役和重建过程。数据和土地利用回归模型 将大大改善正在进行的和计划的流行病学的时空暴露评估 问题研究这项工作将为城市社区环境监测提供重要模式 经历快速的环境变化，21，22并直接改善对VOC和健康的研究。

In June 2019, a massive explosion at the east coast’s largest oil refinery shook buildings across South Philadelphia.1 Residents were told to shelter-in-place while 676,000 pounds of hydrocarbons and 3,271 pounds of deadly hydrogen fluoride (HF) washed over their neighborhood,2,3 and the city health department assured residents that there was no evidence of a health risk.4-6 Two years later, the non-operational Philadelphia Energy Solutions (PES) complex remains the 2nd-highest benzene-emitting refinery in the U.S..7 Despite substantial emissions of volatile organic compounds (VOCs) during decommissioning and demolition, little data has been made available to residents; the one local EPA Air Quality System (AQS) monitor for VOCs operates only every 6th day, and required fenceline monitoring washes out peak events in 2-week averages.8,9 Neither data source has been updated online since March 2020.10-12 Our key goal is to collaborate with Philly Thrive – an environmental justice organization with a primary constituency of fenceline residents - to design and establish a community-scale air toxics monitoring network, to capture and report on-going exposures throughout decommissioning and reconstruction, in this vulnerable community. Residents near refineries and petrochemical complexes are disproportionately African-American, 61% are persons of color, and 45% live in poverty.7,15 The confluence of social stressors and pollution exposures surrounding this site – and the model for community-based monitoring design that we are developing - has relevance and utility for fenceline communities nationwide. Hispanic, and of lower socioeconomic position (SEP);13,14 here, over 300,000 people live within 3 miles; By establishing a high-density, community-scale BTEX (benzene, toluene, ethylbenzene, xylene) VOC monitoring network, we will assess both where exposures are elevated, and when changes in source activity and meteorology increase exposures. Throughout the planned 10-year decommissioning process – which will include removal of 950 miles of pipe, dozens of storage tanks, and underground benzene ‘pools’19,20 - our monitoring system will provide critical reassurance to the community when concentrations are low, and a means for advocating for improvement when concentrations are high - with the credibility of third-party academic scientists with an established relationship with the community. Our study will vastly improve spatial and temporal resolution over the current sparse monitoring, towards reducing exposures, and powerful levers towards advocating for cleaner processes. providing critical information We will seek further funding to maintain the system over the 10-year decommissioning and reconstruction process. Data and land use regression (LUR) models produced will greatly improve spatio-temporal exposure assessment for on-going and planned epidemiologic studies. This work will provide an important model for environmental monitoring in urban communities undergoing rapid environmental change,21,22 and directly improve studies of VOCs and health.23