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Characterization and source apportionment for light absorption amplification of black carbon at an urban site in eastern China.
Chen, Dong; Zhao, Wenxin; Zhang, Lei; Zhao, Qiuyue; Zhang, Jie; Chen, Feng; Li, Huipeng; Guan, Miao; Zhao, Yu.
Afiliação
  • Chen D; Jiangsu Provincial Academy of Environmental Science, 176 North Jiangdong Rd., Nanjing, Jiangsu 210036, China; State Key Laboratory of Pollution Control and Resource Reuse, and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu 210023, China.
  • Zhao W; State Key Laboratory of Pollution Control and Resource Reuse, and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu 210023, China.
  • Zhang L; State Key Laboratory of Pollution Control and Resource Reuse, and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu 210023, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information
  • Zhao Q; Jiangsu Provincial Academy of Environmental Science, 176 North Jiangdong Rd., Nanjing, Jiangsu 210036, China. Electronic address: qiuyue.zhao@163.com.
  • Zhang J; Jiangsu Environmental Engineering and Technology Co., Ltd., Jiangsu Environmental Protection Group Co., Ltd., 8 East Jialingjiang St., Nanjing, Jiangsu 210019, China.
  • Chen F; Jiangsu Environmental Engineering and Technology Co., Ltd., Jiangsu Environmental Protection Group Co., Ltd., 8 East Jialingjiang St., Nanjing, Jiangsu 210019, China.
  • Li H; Jiangsu Provincial Academy of Environmental Science, 176 North Jiangdong Rd., Nanjing, Jiangsu 210036, China.
  • Guan M; Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd., Nanjing, Jiangsu 210023, China.
  • Zhao Y; State Key Laboratory of Pollution Control and Resource Reuse, and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu 210023, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information
Sci Total Environ ; 865: 161180, 2023 Mar 20.
Article em En | MEDLINE | ID: mdl-36581288
ABSTRACT
The mass absorption efficiency (MAE) of black carbon (BC) could be amplified by both internal mixing and the lensing effect from non-absorbing coating, which could intensify the global warming effect of BC. In this study, a two-year-long continuous campaign with measurements of aerosol optical properties and chemical composition were conducted in Nanjing, a typical polluted city in the Yangtze River Delta (YRD) region. Relatively large MAE values were observed in 2016, and the high BC internal mixing level could be the main cause. The strong positive correlation between the ratio of non-absorbing particulate matter (NAPM) over elemental carbon (EC) and the MAE value indicated that the coating thickness of BC largely promotes its light absorption ability. The impacts of chemical component coating on MAE amplification in autumn and winter were greater than in other seasons. Multiple linear regression was performed to estimate the MAE amplification effect by internal mixing and the coating of different chemical components. Nitrate coating had the strongest impact on MAE amplification, followed by organic matter. The effects of organic matter and nitrate coatings on MAE amplification increased with the internal mixing index (IMI). Based on the positive matrix factorization (PMF) model, it was found that large decrease in the contribution of industrial emissions and coal combustion to PM2.5 from 2016 to 2017 was the main cause for MAE reduction. The novel statistical model developed in this study could be a useful tool to separate the impacts of internal mixing and non-absorbing coating.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Total Environ Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Total Environ Ano de publicação: 2023 Tipo de documento: Article