Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.
Department of Physics and Astronomy, Università degli Studi di Firenze, Via Sansone 1, 50019 Florence, Italy; INFN-Firenze, Via Sansone 1, 50019 Florence, Italy.
Sci Total Environ. 2014 Aug 15;490:488-500. doi: 10.1016/j.scitotenv.2014.04.118. Epub 2014 May 27.
In this study, the Multilinear Engine (ME-2) receptor model was applied to speciated particulate matter concentration data collected with two different measuring instruments upwind and downwind of a steelworks complex in Port Talbot, South Wales, United Kingdom. Hourly and daily PM samples were collected with Streaker and Partisol samplers, respectively, during a one month sampling campaign between April 18 and May 16, 2012. Daily samples (PM10, PM2.5, PM2.5-10) were analysed for trace metals and water-soluble ions using standard procedures. Hourly samples (PM2.5 and PM2.5-10) were assayed for 22 elements by Particle Induced X-ray Emission (PIXE). PM10 data analysis using ME-2 resolved 6 factors from both datasets identifying different steel processing units including emissions from the blast furnaces (BF), the basic oxygen furnace steelmaking plant (BOS), the coke-making plant, and the sinter plant. Steelworks emissions were the main contributors to PM10 accounting for 45% of the mass when including also secondary aerosol. The blast furnaces were the largest emitter of primary PM10 in the study area, explaining about one-fifth of the mass. Other source contributions to PM10 were from marine aerosol (28%), traffic (16%), and background aerosol (11%). ME-2 analysis was also performed on daily PM2.5 and PM2.5-10 data resolving 7 and 6 factors, respectively. The largest contributions to PM2.5-10 were from marine aerosol (30%) and blast furnace emissions (28%). Secondary components explained one-half of PM2.5 mass. The influence of steelworks sources on ambient particulate matter at Port Talbot was distinguishable for several separate processing sections within the steelworks in all PM fractions.
在这项研究中,多线性引擎 (ME-2) 受体模型应用于在英国南威尔士塔尔博特港的一家钢铁厂综合体上风和下风处使用两种不同测量仪器收集的特定颗粒物质浓度数据。在 2012 年 4 月 18 日至 5 月 16 日的一个月采样活动中,使用 Streaker 和 Partisol 采样器分别采集了每小时和每日的 PM 样本。使用标准程序对每日样本(PM10、PM2.5、PM2.5-10)进行痕量金属和水溶性离子分析。使用粒子感生 X 射线发射(PIXE)对每小时样本(PM2.5 和 PM2.5-10)进行 22 种元素的分析。使用 ME-2 对 PM10 数据进行分析,从两个数据集解析了 6 个因素,确定了不同的钢铁加工单元,包括来自高炉(BF)、碱性氧气炉炼钢厂(BOS)、焦炉和烧结厂的排放物。钢铁厂排放物是 PM10 的主要贡献者,当包括二次气溶胶时,占质量的 45%。在研究区域内,高炉是 PM10 的最大一次排放源,占质量的五分之一。PM10 的其他来源贡献来自海洋气溶胶(28%)、交通(16%)和背景气溶胶(11%)。还对每日 PM2.5 和 PM2.5-10 数据进行了 ME-2 分析,分别解析了 7 个和 6 个因素。PM2.5-10 的最大贡献来自海洋气溶胶(30%)和高炉排放物(28%)。二次成分解释了 PM2.5 质量的一半。在塔尔博特港,钢铁厂内的几个单独加工段对环境颗粒物中钢铁厂源的影响在所有 PM 分数中都可区分。