{"title":"Two different approaches for source apportionment of ambient black carbon in highly polluted environments","authors":"Ajit Kumar , Vikas Goel , Mohd Faisal , Umer Ali , Rakesh Maity , Dilip Ganguly , Vikram Singh , Mayank Kumar","doi":"10.1016/j.atmosenv.2024.120863","DOIUrl":null,"url":null,"abstract":"<div><div>The aethalometer model (AM) is widely used for source apportionment (SA) of black carbon (BC) in regions with mixed BC sources despite being initially developed for a relatively simplistic and low-pollution environments. The present study interrogates the applicability of AM in highly polluted metropolitan environments by comparing its results with the more nuanced Positive Matrix Factorization (PMF) model. The measurements were conducted in Delhi during the winter and summer season. PMF apportions the BC into diverse sources by taking help from complementary trace elemental measurements, thereby acknowledging the complex pollution landscape of the Delhi region. The AM estimates BC<sub>bb</sub> (BC from biomass burning) and BC<sub>ff</sub> (BC from fossil fuel combustion) contributions as 48.3% and 51.7% during the winter and 16.6% and 83.4% during the summer, respectively.</div><div>In contrast, the PMF model-derived biomass burning factor is the dominant source of BC during both winter and summer seasons, contributing 53.9% and 44% of the total BC, respectively. The decrease in light absorption at UV wavelengths of biomass-burning aerosols owing to escalated ambient aging is posited to be the reason for BC<sub>bb</sub> underprediction by the AM model during summers. Furthermore, while the AM model identifies fossil fuel combustion as the only other BC source apart from biomass burning, the PMF model apportions BC to five additional sources during winter, including vehicle emissions (22.9%), Pb-rich factor (10%), power plant (5.7%), waste incineration (4%) and industrial emission (3.6%). The contribution of these BC sources during summer is vehicular emission (16.5%), power plant (14.5%), waste incineration (11.5%), Pb-rich factor (9.5%), and industrial emission (4%). Additionally, the spectral variation of the light absorption properties of black carbon (b<sub>BCabs</sub>) and brown carbon (b<sub>BrCabs</sub>), delta-C effect, and sensitivity of the AM are reported for the study period. The present study cautions that BC source apportionment can be complex in highly polluted metropolitan environments, and complementary tracer measurements are recommended for reliable results.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"338 ","pages":"Article 120863"},"PeriodicalIF":4.2000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Environment","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1352231024005387","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The aethalometer model (AM) is widely used for source apportionment (SA) of black carbon (BC) in regions with mixed BC sources despite being initially developed for a relatively simplistic and low-pollution environments. The present study interrogates the applicability of AM in highly polluted metropolitan environments by comparing its results with the more nuanced Positive Matrix Factorization (PMF) model. The measurements were conducted in Delhi during the winter and summer season. PMF apportions the BC into diverse sources by taking help from complementary trace elemental measurements, thereby acknowledging the complex pollution landscape of the Delhi region. The AM estimates BCbb (BC from biomass burning) and BCff (BC from fossil fuel combustion) contributions as 48.3% and 51.7% during the winter and 16.6% and 83.4% during the summer, respectively.
In contrast, the PMF model-derived biomass burning factor is the dominant source of BC during both winter and summer seasons, contributing 53.9% and 44% of the total BC, respectively. The decrease in light absorption at UV wavelengths of biomass-burning aerosols owing to escalated ambient aging is posited to be the reason for BCbb underprediction by the AM model during summers. Furthermore, while the AM model identifies fossil fuel combustion as the only other BC source apart from biomass burning, the PMF model apportions BC to five additional sources during winter, including vehicle emissions (22.9%), Pb-rich factor (10%), power plant (5.7%), waste incineration (4%) and industrial emission (3.6%). The contribution of these BC sources during summer is vehicular emission (16.5%), power plant (14.5%), waste incineration (11.5%), Pb-rich factor (9.5%), and industrial emission (4%). Additionally, the spectral variation of the light absorption properties of black carbon (bBCabs) and brown carbon (bBrCabs), delta-C effect, and sensitivity of the AM are reported for the study period. The present study cautions that BC source apportionment can be complex in highly polluted metropolitan environments, and complementary tracer measurements are recommended for reliable results.
尽管乙硫计模型(AM)最初是针对相对简单和低污染的环境而开发的,但它被广泛用于混合碳源地区的黑碳(BC)源分配(SA)。本研究通过将 AM 的结果与更精细的正矩阵因式分解(PMF)模型进行比较,对 AM 在高污染大都市环境中的适用性进行了探讨。测量是在德里的冬季和夏季进行的。正矩阵因式分解模型通过补充痕量元素测量结果,将 BC 分解为不同的来源,从而反映了德里地区复杂的污染状况。根据 AM 估计,BCbb(生物质燃烧产生的 BC)和 BCff(化石燃料燃烧产生的 BC)在冬季分别占 48.3% 和 51.7%,在夏季分别占 16.6% 和 83.4%。由于环境老化加剧,生物质燃烧气溶胶对紫外线波长的光吸收减少,这被认为是夏季 AM 模式对 BCbb 预测不足的原因。此外,调幅模式认为化石燃料燃烧是除生物质燃烧之外唯一的其他 BC 来源,而 PMF 模式则将冬季的 BC 分配给另外五个来源,包括汽车尾气排放(22.9%)、富铅因子(10%)、发电厂(5.7%)、垃圾焚烧(4%)和工业排放(3.6%)。这些 BC 源在夏季的贡献是车辆排放(16.5%)、发电厂(14.5%)、垃圾焚烧(11.5%)、富铅因子(9.5%)和工业排放(4%)。此外,还报告了研究期间黑碳(bBCabs)和褐碳(bBrCabs)光吸收特性的光谱变化、delta-C 效应以及 AM 的灵敏度。本研究提醒说,在高度污染的大都市环境中,BC 源分配可能很复杂,建议进行补充示踪测量以获得可靠的结果。
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.