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
Data sets
Highly time-resolved characterization of carbonaceous aerosols using a two-wavelength Sunset thermal-optical carbon analyzer M. Bao https://doi.org/10.17605/OSF.IO/MA8CU
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...
