Combined-phase source apportionment of ambient PM2.5, PAHs and VOCs from an industrialized environment: Consequences of photochemical initial concentrations

IF 4.2 2区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Atmospheric Environment Pub Date : 2024-10-26 DOI:10.1016/j.atmosenv.2024.120894
Uwayemi M. Sofowote , Ewa Dabek-Zlotorzynska , Mahmoud M. Yassine , Dennis Mooibroek , May Siu , Valbona Celo , Philip K. Hopke
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Abstract

Air pollutants in the particulate (PM2.5 species, PAHs) and gaseous phases (VOCs) collected between 2013 and 2019 once every three or six days for a period of 24 hours in an industrialized city in Ontario were analyzed to apportion their common sources. The consequences of using these species jointly for receptor modelling were assessed via combined-phase source apportionment that used the data as is, and in a protocol that factored in the potential for photochemical losses of gas-phase species. Thus, photochemically corrected initial concentrations (PIC) were calculated. Analyses of the inputs followed either with positive matrix factorization or its dispersion-normalized variant (DN-PMF). Comparisons of applying PMF to the originally observed input data (BASE) and DN-PMF on data with PIC corrections were made. When the inputs consisted only of VOCs, three factors were resolved with BASE PMF: natural gas, vehicular emissions, and industrial emissions co-emitted with summertime gasoline evaporation. A fourth factor was obtained, representing reactive VOCs when DN-PIC PMF was used. When the combined phase input data were analyzed, nine factors were resolved for both BASE and DN-PIC PMF. These factors in order of diminishing average PM mass contributions were: particulate sulphate, secondary organic aerosol (SOA), particulate nitrate (pNO3), biomass burning with natural gas, crustal matter, winter blend of gasoline, coking/coal combustion, steelmaking, and summer blend/light duty vehicular emissions. When BASE and DN-PIC PMF results are compared, the average PM mass contribution of the summer gasoline fuel factor increased from 2% in BASE case to 5%, suggesting severe underestimation of this source's contributions without DN-PIC. Also, substantial increases of reactive VOCs in the SOA factor, and PAHs with ≥four rings in the pNO3 and steelmaking factors were observed with DN-PIC PMF compared to the BASE PMF case, indicating that for SOA, reactive VOCs at this location contributed to SOA sources.

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来自工业化环境的环境 PM2.5、多环芳烃和挥发性有机化合物的综合阶段源分配:光化学初始浓度的后果
分析了2013年至2019年期间在安大略省的一个工业化城市每隔3天或6天收集一次、持续24小时的颗粒物(PM2.5物种、多环芳烃)和气相(挥发性有机化合物)中的空气污染物,以分摊其共同来源。通过使用原数据的综合相源分配,以及考虑到气相物种光化学损失可能性的协议,评估了将这些物种联合用于受体建模的后果。因此,计算出了光化学校正初始浓度(PIC)。输入分析采用正矩阵因式分解法或其分散归一化变体(DN-PMF)。对最初观测到的输入数据(BASE)进行了正矩阵因式分解,并对经过 PIC 修正的数据进行了 DN-PMF 分析。当输入数据仅包括挥发性有机化合物时,BASE PMF 解决了三个因子:天然气、车辆排放和与夏季汽油蒸发共同排放的工业排放。使用 DN-PIC PMF 时,第四个因子代表反应性挥发性有机化合物。在分析综合阶段输入数据时,BASE 和 DN-PIC PMF 都解决了九个因子。这些因子按可吸入颗粒物平均质量贡献递减的顺序排列为:颗粒硫酸盐、二次有机气溶胶(SOA)、颗粒硝酸盐(pNO3)、生物质燃烧与天然气、地壳物质、冬季混合汽油、炼焦/燃煤、炼钢和夏季混合/轻型车辆排放。当比较基准和 DN-PIC PMF 结果时,夏季汽油燃料因子的平均 PM 质量贡献从基准情况下的 2% 增加到 5%,这表明在没有 DN-PIC 的情况下严重低估了这一来源的贡献。此外,与 BASE PMF 案例相比,DN-PIC PMF 观察到 SOA 因子中的活性 VOCs 以及 pNO3 和炼钢因子中≥四环的 PAHs 显著增加,表明对于 SOA 而言,该地点的活性 VOCs 是 SOA 的贡献源。
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来源期刊
Atmospheric Environment
Atmospheric Environment 环境科学-环境科学
CiteScore
9.40
自引率
8.00%
发文量
458
审稿时长
53 days
期刊介绍: Atmospheric Environment has an open access mirror journal Atmospheric Environment: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. Atmospheric Environment is the international journal for scientists in different disciplines related to atmospheric composition and its impacts. The journal publishes scientific articles with atmospheric relevance of emissions and depositions of gaseous and particulate compounds, chemical processes and physical effects in the atmosphere, as well as impacts of the changing atmospheric composition on human health, air quality, climate change, and ecosystems.
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