Articles | Volume 23, issue 11
https://doi.org/10.5194/acp-23-6545-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-6545-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Black carbon content of traffic emissions significantly impacts black carbon mass size distributions and mixing states
School of Atmospheric Sciences, Guangdong Province Key Laboratory for
Climate Change and Natural Disaster Studies, and Southern Marine Science and
Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai,
519082, China
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510640, China
Xiamen Key Laboratory of Straits Meteorology, Xiamen Meteorological
Bureau, Xiamen, 361012, China
Biao Luo
Institute for Environmental and Climate Research, Jinan University,
Guangzhou, 511443, China
Guangdong–Hong Kong–Macau Joint Laboratory of Collaborative
Innovation for Environmental Quality, Guangzhou, 511443, China
Miaomiao Zhai
Institute for Environmental and Climate Research, Jinan University,
Guangzhou, 511443, China
Guangdong–Hong Kong–Macau Joint Laboratory of Collaborative
Innovation for Environmental Quality, Guangzhou, 511443, China
Li Liu
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510640, China
Gang Zhao
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, International Joint Laboratory for Regional Pollution Control,
Ministry of Education, College of Environmental Sciences and Engineering,
Peking University, Beijing, 100871, China
Hanbing Xu
Experimental Teaching Center, Sun Yat-Sen University, Guangzhou
510275, China
Tao Deng
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510640, China
Xuejiao Deng
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510640, China
Haobo Tan
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510640, China
Institute for Environmental and Climate Research, Jinan University,
Guangzhou, 511443, China
Guangdong–Hong Kong–Macau Joint Laboratory of Collaborative
Innovation for Environmental Quality, Guangzhou, 511443, China
School of Atmospheric Sciences, Guangdong Province Key Laboratory for
Climate Change and Natural Disaster Studies, and Southern Marine Science and
Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai,
519082, China
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Cited
6 citations as recorded by crossref.
- The Contribution of Black Carbon-Containing Particles to PM2.5: Variability, Drivers, and Impacts Y. Zhang et al. 10.1021/acs.est.5c00675
- Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley – an integrated approach combining high-resolution dispersion modelling and micro-aethalometers G. Veratti et al. 10.5194/acp-24-10475-2024
- Model simulation of carbonaceous fine particulate matter using SAFAR emission inventory and comparison with EDGAR-HTAP simulations P. Kumar et al. 10.1016/j.atmosenv.2023.120147
- Black carbon in urban Jinan: variations, health risks, and driving factors analyzed with machine learning J. Chen et al. 10.1016/j.jes.2025.04.049
- Evolution of refractory black carbon mixing state in an urban environment S. Kasparoglu et al. 10.1016/j.atmosenv.2024.120651
- Population exposure to outdoor NO2, black carbon, and ultrafine and fine particles over Paris with multi-scale modelling down to the street scale S. Park et al. 10.5194/acp-25-3363-2025
6 citations as recorded by crossref.
- The Contribution of Black Carbon-Containing Particles to PM2.5: Variability, Drivers, and Impacts Y. Zhang et al. 10.1021/acs.est.5c00675
- Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley – an integrated approach combining high-resolution dispersion modelling and micro-aethalometers G. Veratti et al. 10.5194/acp-24-10475-2024
- Model simulation of carbonaceous fine particulate matter using SAFAR emission inventory and comparison with EDGAR-HTAP simulations P. Kumar et al. 10.1016/j.atmosenv.2023.120147
- Black carbon in urban Jinan: variations, health risks, and driving factors analyzed with machine learning J. Chen et al. 10.1016/j.jes.2025.04.049
- Evolution of refractory black carbon mixing state in an urban environment S. Kasparoglu et al. 10.1016/j.atmosenv.2024.120651
- Population exposure to outdoor NO2, black carbon, and ultrafine and fine particles over Paris with multi-scale modelling down to the street scale S. Park et al. 10.5194/acp-25-3363-2025
Latest update: 06 May 2025
Short summary
A field campaign was conducted to study black carbon (BC) mass size distributions and mixing states connected to traffic emissions using a system that combines a differential mobility analyzer and single-particle soot photometer. Results showed that the black carbon content of traffic emissions has a considerable influence on both BC mass size distributions and mixing states, which has crucial implications for accurately representing BC from various sources in regional and climate models.
A field campaign was conducted to study black carbon (BC) mass size distributions and mixing...
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