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High-time-resolution source apportionment of PMsub2.5/sub in Beijing with multiple models

机译:多种模式对北京PM 2.5 的高分辨率源分配

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Beijing has suffered from heavy local emissions as well as regional transport of air pollutants, resulting in severe atmospheric fine-particle (PM sub2.5/sub ) pollution. This study developed a combined method to investigate source types of PM sub2.5/sub and its source regions during winter 2016 in Beijing, which include the receptor model (positive matrix factorization, PMF), footprint and an air quality model. The PMF model was performed with high-time-resolution measurements of trace elements, water soluble ions, organic carbon and elemental carbon using online instruments during the wintertime campaign of the Air Pollution and Human Health in a Chinese Megacity – Beijing (APHH-Beijing) program in 2016. Source types and their contributions estimated by PMF model using online measurements were linked with source regions identified by the footprint model, and the regional transport contribution was estimated by an air quality model (the Nested Air Quality Prediction Model System, NAQPMS) to analyze the specific sources and source regions during haze episodes. Our results show that secondary and biomass-burning sources were dominated by regional transport, while the coal combustion source increased with local contribution, suggesting that strict control strategies for local coal combustion in Beijing and a reduction of biomass-burning and gaseous precursor emissions in surrounding areas were essential to improve air quality in Beijing. The combination of PMF with footprint results revealed that secondary sources were mainly associated with southern footprints (53?%). The northern footprint was characterized by a high dust source contribution (11?%), while industrial sources increased with the eastern footprint (10?%). The results demonstrated the power of combining receptor model-based source apportionment with other models in understanding the formation of haze episodes and identifying specific sources from different source regions affecting air quality in Beijing.
机译:北京遭受了严重的局部排放以及空气污染物的区域运输,导致了严重的大气微粒(PM 2.5 )污染。本研究开发了一种组合方法来研究北京地区2016年冬季PM 2.5 的污染源类型及其污染源区域,包括受体模型(正矩阵分解,PMF),足迹和空气质量模型。在冬季大气污染与人类健康活动期间,通过在线仪器对PMF模型进行了高分辨率的痕量元素,水溶性离子,有机碳和元素碳测量,北京(APHH-北京)计划在2016年实施。通过PMF模型使用在线测量方法估算的源类型及其贡献与通过足迹模型确定的源区域相关联,并通过空气质量模型(嵌套空气质量预测模型系统,NAQPMS)估算区域运输贡献。分析烟雾事件中的特定来源和来源区域。我们的结果表明,次生和生物质燃烧源主要受区域运输的影响,而煤炭燃烧源随地方贡献的增加而增加,这表明北京对本地煤炭燃烧采取严格的控制策略,并减少了周围生物质燃烧和气态前体排放这些地区对于改善北京的空气质量至关重要。 PMF与足迹结果的结合表明,次要来源主要与南部足迹有关(53%)。北部足迹的特点是粉尘源贡献高(11%),而工业来源则随着东部足迹的增加而增加(10%)。结果表明,将基于受体模型的源分配与其他模型相结合,可以有效地了解霾事件的发生,并从影响北京空气质量的不同源区域中识别出特定的源。

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