Chemistry Division, Atomic Energy Centre, Dhaka, Bangladesh.
J Air Waste Manag Assoc. 2013 Sep;63(9):1046-57. doi: 10.1080/10962247.2013.784716.
Fine particulate matter (PM2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 microg/m3 and 6.0 microg/m3 of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter.
2010 年 2 月至 2011 年 2 月,在孟加拉国达卡的一个城市监测点(CAMS2),使用 AirMetrics MiniVol 采样器同时在特氟龙和石英滤膜上收集细颗粒物(PM2.5)样本。使用 PIXE 和 PESA 分析特氟龙滤膜上的样品元素组成。使用 IMPROVE 热光反射(TOR)法分析石英滤膜上的颗粒碳,该方法将碳分为四个有机碳(OC)、热解有机碳(OP)和三个元素碳(EC)部分。使用 PMF2 程序通过正定矩阵因子分解分析数据。最初,仅包括总 OC 和总 EC 进行分析,并获得了五个来源,包括道路灰尘、海盐和 Zn、土壤灰尘、机动车和砖窑。在第二次分析中,包括八个碳部分(OC1、OC2、OC3、OC4、OP、EC1、EC2、EC3),以确定是否可以从数据中提取额外的源信息。在这种情况下,可以识别出比仅使用总 OC 和 EC 更多的来源。机动车源分为汽油和柴油排放,确定了一个逃逸 Pb 源。根据这两个结果,砖窑分别向细颗粒物贡献 7.9μg/m3 和 6.0μg/m3 的 OC 和 EC。从估计的质量消光系数和分配的源贡献来看,土壤灰尘、砖窑、柴油、汽油和 Pb 源对能见度下降的贡献最大,特别是在冬季。