Identifying PM sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM from 515 EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO); (6) Secondary nitrate (NO) and (7) Sea salt (Mg, Na, Cl and SO). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.

中文翻译：

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使用多线性引擎模型对美国本土（2000-2019 年）PM2.5 的长期来源解析


识别 PM 来源对于有效的空气质量管理和公共卫生至关重要。本研究使用多线性引擎 (ME-2) 模型分析 2000 年至 2019 年间美国 515 个 EPA 化学形态网络 (CSN) 和受保护视觉环境机构间监测 (IMPROVE) 站点的 PM。美国分为九个区域进行详细分析。全国范围内总共解决了七种源类型（示踪剂）：（1）土壤/灰尘（Si、Al、Ca 和 Fe）； (2) 车辆排放（EC、OC、Cu 和 Zn）； (3) 生物质/木材燃烧（K）； (4) 重油/煤燃烧（Ni、V、Cl、As）； (5)仲硫酸盐(SO)； (6) 仲硝酸盐 (NO) 和 (7) 海盐（Mg、Na、Cl 和 SO）。此外，我们根据二次硫酸盐和硝酸盐因子提取并计算了二次有机气溶胶（SOA）。值得注意的是，二次硫酸盐、硝酸盐和重油/煤炭燃烧排放量的大幅减少反映了近期化石燃料电力部门排放量的减少。 SOA 的下降表明可以有效缓解其形成条件或前兆。尽管有这些改进，但车辆排放和生物质燃烧并没有显着减少，这凸显了未来空气质量管理需要集中控制这些持久性污染源。