Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4053-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-4053-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jun 2021
Research article |
| 03 Jun 2021
| 03 Jun 2021
Highly time-resolved characterization of carbonaceous aerosols using a two-wavelength Sunset thermal–optical carbon analyzer
Mengying Bao
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Fang Cao
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yu-Chi Lin
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yuhang Wang
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
Xiaoyan Liu
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Wenqi Zhang
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Meiyi Fan
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Feng Xie
Yale–NUIST Center on Atmospheric Environment, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Meteorological Disaster Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Robert Cary
Sunset Laboratory, 1080 SW Nimbus Avenue, Suite J/5, Tigard, OR 97223, USA
Joshua Dixon
Sunset Laboratory, 1080 SW Nimbus Avenue, Suite J/5, Tigard, OR 97223, USA
Lihua Zhou
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
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Jianfeng Li, Yuhang Wang, Ruixiong Zhang, Charles Smeltzer, Andrew Weinheimer, Jay Herman, K. Folkert Boersma, Edward A. Celarier, Russell W. Long, James J. Szykman, Ruben Delgado, Anne M. Thompson, Travis N. Knepp, Lok N. Lamsal, Scott J. Janz, Matthew G. Kowalewski, Xiong Liu, and Caroline R. Nowlan
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Yunhua Chang, Yan-Lin Zhang, Sawaeng Kawichai, Qian Wang, Martin Van Damme, Lieven Clarisse, Tippawan Prapamontol, and Moritz F. Lehmann
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In this study, we integrated satellite constraints on atmospheric NH3 levels and fire intensity, discrete NH3 concentration measurement, and N isotopic analysis of NH3 in order to assess the regional-scale contribution of biomass burning to ambient atmospheric NH3 in the heartland of Southeast Asia. The combined approach provides a valuable cross-validation framework for source apportioning of NH3 in the lower atmosphere and will thus help to ameliorate predictions of biomass burning emissions.
Kun Zhang, Ling Huang, Qing Li, Juntao Huo, Yusen Duan, Yuhang Wang, Elly Yaluk, Yangjun Wang, Qingyan Fu, and Li Li
Atmos. Chem. Phys., 21, 5905–5917, https://doi.org/10.5194/acp-21-5905-2021, https://doi.org/10.5194/acp-21-5905-2021, 2021
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Recently, high O3 concentrations were frequently observed in rural areas of the Yangtze River Delta (YRD) region under stagnant conditions. Using an online measurement and observation-based model, we investigated the budget of ROx radicals and the influence of isoprene chemistry on O3 formation. Our results underline that isoprene chemistry in the rural atmosphere becomes important with the participation of anthropogenic NOx.
Qingcai Chen, Haoyao Sun, Wenhuai Song, Fang Cao, Chongguo Tian, and Yan-Lin Zhang
Atmos. Chem. Phys., 20, 14407–14417, https://doi.org/10.5194/acp-20-14407-2020, https://doi.org/10.5194/acp-20-14407-2020, 2020
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This study found environmentally persistent free radicals (EPFRs) are widely present in atmospheric particles of different particle sizes and exhibit significant particle size distribution characteristics. EPFR concentrations are higher in coarse particles than in fine particles in summer and vice versa in winter. The potential toxicity caused by EPFRs may also vary with particle size and season. Combustion is the most important source of EPFRs (>70 %).
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Short summary
We introduce a two-wavelength method for brown C measurements with a modified Sunset carbon analyzer. We defined the enhanced concentrations and gave the possibility of providing an indicator of brown C. Compared with the strong local sources of organic and elemental C, we found that differences in EC mainly originated from regional transport. Biomass burning emissions significantly contributed to high differences in EC concentrations during the heavy biomass burning periods.
We introduce a two-wavelength method for brown C measurements with a modified Sunset carbon...
