Istituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Str. Prv. Lecce-Monteroni km 1.2, 73100 Lecce, Italy.
Istituto di Scienze dell'Atmosfera e del Clima, ISAC-CNR, Str. Prv. Lecce-Monteroni km 1.2, 73100 Lecce, Italy.
Sci Total Environ. 2016 Aug 1;560-561:131-40. doi: 10.1016/j.scitotenv.2016.04.031. Epub 2016 Apr 19.
The evaluation of the contribution of coal-fired thermo-electrical power plants to particulate matter (PM) is important for environmental management, for evaluation of health risks, and for its potential influence on climate. The application of receptor models, based on chemical composition of PM, is not straightforward because the chemical profile of this source is loaded with Si and Al and it is collinear with the profile of crustal particles. In this work, a new methodology, based on Positive Matrix Factorization (PMF) receptor model and Si/Al diagnostic ratio, specifically developed to discriminate the coal-fired power plant contribution from the crustal contribution is discussed. The methodology was applied to daily PM10 samples collected in central Italy in proximity of a large coal-fired power plant. Samples were simultaneously collected at three sites between 2.8 and 5.8km from the power plant: an urban site, an urban background site, and a rural site. Chemical characterization included OC/EC concentrations, by thermo-optical method, ions concentrations (NH4(+), Ca(2+), Mg(2+), Na(+), K(+), Mg(2+), SO4(2-), NO3(-), Cl(-)), by high performances ion chromatography, and metals concentrations (Si, Al, Ti, V, Mn, Fe, Ni, Cu, Zn, Br), by Energy dispersive X-ray Fluorescence (ED-XRF). Results showed an average primary contribution of the power plant of 2% (±1%) in the area studied, with limited differences between the sites. Robustness of the methodology was tested inter-comparing the results with two independent evaluations: the first obtained using the Chemical Mass Balance (CMB) receptor model and the second correlating the Si-Al factor/source contribution of PMF with wind directions and Calpuff/Calmet dispersion model results. The contribution of the power plant to secondary ammonium sulphate was investigated using an approach that integrates dispersion model results and the receptor models (PMF and CMB), a sulphate contribution of 1.5% of PM10 (±0.3%) as average of the three sites was observed.
评估燃煤热电厂对颗粒物（PM）的贡献对于环境管理、健康风险评估以及其对气候的潜在影响都很重要。应用基于 PM 化学成分的受体模型并不简单，因为该源的化学成分特征富含 Si 和 Al，并且与地壳颗粒的特征呈线性相关。在这项工作中，讨论了一种新的方法，该方法基于正矩阵因子分解（PMF）受体模型和 Si/Al 诊断比，专门用于区分燃煤电厂的贡献和地壳的贡献。该方法应用于意大利中部一个大型燃煤电厂附近采集的每日 PM10 样本。在距离电厂 2.8 至 5.8 公里的三个地点同时采集了样本：一个城市地点、一个城市背景地点和一个农村地点。化学特征包括 OC/EC 浓度（通过热光法）、离子浓度（NH4(+)、Ca(2+)、Mg(2+)、Na(+)、K(+)、Mg(2+)、SO4(2-)、NO3(-)、Cl(-)）（通过高性能离子色谱法）和金属浓度（Si、Al、Ti、V、Mn、Fe、Ni、Cu、Zn、Br）（通过能量色散 X 射线荧光法（ED-XRF））。结果表明，在研究区域内，电厂的平均一次贡献为 2%（±1%），各站点之间的差异有限。该方法的稳健性通过与两种独立评估进行比较来测试：第一种是使用化学质量平衡（CMB）受体模型获得的结果，第二种是将 PMF 的 Si-Al 因子/源贡献与风向以及 Calpuff/Calmet 分散模型的结果进行关联。使用一种将分散模型结果与受体模型（PMF 和 CMB）相结合的方法来研究电厂对二次硫酸铵的贡献，在三个站点的平均值为 PM10 的 1.5%（±0.3%）。
