Abstract. Fine particulate matter (PM2.5) is among the air pollutants representing the most critical threat to human health in Europe. For designing strategies to mitigate this kind of air pollution, it is essential to identify and quantify the sources of its components. Here, we utilized the regional chemistry transport model CAMx (Comprehensive Air Quality Model with Extensions) to investigate the relationships between emissions from different categories and the concentrations of PM2.5 and its secondary components over Central Europe during the period 2018–2019, both in terms of the contributions of emission categories calculated by the particle source apportionment technology (PSAT) and the impacts of the complete removal of emissions from individual categories (i.e., the zero-out method). During the winter seasons, emissions from other stationary combustion (including residential combustion) were the main contributor to the domain-wide average PM2.5 concentration (3.2 µg m−3), and their removal also had the most considerable impact on it (3.4 µg m−3). During the summer seasons, the domain-wide average PM2.5 concentration was contributed the most by biogenic emissions (0.57 µg m−3), while removing emissions from agriculture–livestock had the most substantial impact on it (0.46 µg m−3). The most notable differences between the contributions and impacts for PM2.5 were associated with emissions from agriculture–livestock, mainly due to the differences in nitrate concentrations, which reached up to 4.5 and 1.25 µg m−3 in the winter and summer seasons, respectively. We also performed a sensitivity test of the mentioned impacts on PM2.5 on two different modules for secondary organic aerosol formation (SOAP and VBS), which showed the most considerable differences for emissions from other stationary combustion (in winter) and road transport (in summer).

中文翻译：

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对中欧细颗粒物污染的驱动因素进行建模：不同来源排放的影响和贡献

摘要。细颗粒物 (PM2.5) 是对欧洲人类健康构成最严重威胁的空气污染物之一。为了设计减轻此类空气污染的策略，必须识别和量化其成分的来源。在这里，我们利用区域化学传输模型 CAMx（带有扩展的综合空气质量模型）来研究 2018 年至 2019 年期间中欧不同类别的排放与 PM2.5 及其次要成分浓度之间的关系。粒子源解析技术（PSAT）计算的排放类别的贡献以及完全消除个别类别排放（即归零法）的影响。在冬季，其他固定燃烧（包括住宅燃烧）的排放是全域平均 PM2.5 浓度（3.2 µg m−3）的主要贡献者，其去除对其影响也最为显着（3.4 µg m−3)。夏季，全域平均 PM2.5 浓度由生物排放贡献最大（0.57 µg m−3），而消除农牧业排放对其影响最大（0.46 µg m−3） 。 PM2.5 的贡献和影响之间最显着的差异与农牧业排放有关，主要是由于硝酸盐浓度的差异，冬季和夏季分别达到 4.5 和 1.25 µg m−3 。我们还在二次有机气溶胶形成的两个不同模块（SOAP 和 VBS）上对上述对 PM2.5 的影响进行了敏感性测试，结果表明，其他固定燃烧（冬季）和道路运输（冬季）的排放存在最大差异。夏天）。