This study proposes the use of spatially resolved data to identify local sources contributing to PM10 mass concentration and OP in urban-industrial contexts. Over a 18-month monitoring campaign spanning from October 2020 to May 2022, a low-volume PM10 sampling device was employed at 12 sites in the Sacco River Valley, Italy. PM10 samples were analyzed for OP by applying the DTT, AA, and DCFH assays, and for 77 chemical parameters: the main chemical components (major elements, inorganic ions, EC, OC, levoglucosan) and the water-soluble and insoluble fractions of 28 elements. Source apportionment via PMF analysis on spatially resolved data revealed seven PM10 source contributions, notably biomass burning and soil dust. Biomass burning predominated in winter, while soil dust prevailed in summer. Spatial variability in source contributions was observed due to diverse biomass types, domestic heating, and proximity to the cement plant and transportation networks. Bubble maps and FPCA represented OP and PM10 source relationships, highlighting biomass burning as the main contributor to OPDTT and OPDCFH, while non-exhaust traffic contributed significantly to OPAA. Findings from this study provide valuable insights into planning effective air pollution mitigation policies aimed at enhancing air quality in urban-industrial contexts.

中文翻译：

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城市工业环境中 PM10 和氧化潜在源解析的空间解析化学数据


本研究建议使用空间分辨数据来识别城市工业环境中导致 PM10 质量浓度和有机污染物的本地来源。在从 2020 年 10 月到 2022 年 5 月为期 18 个月的监测活动中，意大利萨科河谷的 12 个地点使用了小量 PM10 采样装置。通过应用 DTT、AA 和 DCFH 测定法对 PM10 样品进行 OP 分析，并分析 77 种化学参数：主要化学成分（主要元素、无机离子、EC、OC、左旋葡聚糖）以及 28 种物质的水溶性和不溶性部分。元素。通过对空间分辨数据进行 PMF 分析进行的源解析揭示了 PM10 的七个来源，特别是生物质燃烧和土壤灰尘。冬季以生物质燃烧为主，夏季以土壤扬尘为主。由于不同的生物质类型、家庭供暖以及靠近水泥厂和运输网络，观察到源贡献的空间变异性。气泡图和 FPCA 代表了 OP 和 PM10 来源关系，强调生物质燃烧是 OPDTT 和 OPDCFH 的主要贡献者，而非废气交通对 OPAA 贡献很大。这项研究的结果为规划旨在提高城市工业环境空气质量的有效空气污染缓解政策提供了宝贵的见解。