Articles | Volume 25, issue 12
https://doi.org/10.5194/acp-25-6161-2025
© Author(s) 2025. 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-25-6161-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jun 2025
Research article |
| 24 Jun 2025
| 24 Jun 2025
Sources and trends of black carbon aerosol in the megacity of Nanjing, eastern China, after the China Clean Action Plan and Three-Year Action Plan
Abudurexiati Abulimiti
State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yanlin Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Mingyuan Yu
State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yihang Hong
State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Yu-Chi Lin
State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Chaman Gul
Reading Academy, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China
Fang Cao
State Key Laboratory of Climate System Prediction and Risk Management, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Yan-Lin Zhang, Imad El-Haddad, Ru-Jin Huang, Kin-Fai Ho, Jun-Ji Cao, Yongming Han, Peter Zotter, Carlo Bozzetti, Kaspar R. Daellenbach, Jay G. Slowik, Gary Salazar, André S. H. Prévôt, and Sönke Szidat
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Here we present a quantitative source apportionment of WSOC, isolated from aerosols in China using radiocarbon (14C) and offline high-resolution time of flight aerosol mass spectrometer measurements. We demonstrate a dominant contribution of non-fossil emissions to WSOC aerosols in the Northern Hemisphere. However, the fossil fraction is substantially larger in aerosols from East Asia and the east Asian pollution outflow, especially during winter, due to increasing coal combustion.
Yunhua Chang, Congrui Deng, Fang Cao, Chang Cao, Zhong Zou, Shoudong Liu, Xuhui Lee, Jun Li, Gan Zhang, and Yanlin Zhang
Atmos. Chem. Phys., 17, 9945–9964, https://doi.org/10.5194/acp-17-9945-2017, https://doi.org/10.5194/acp-17-9945-2017, 2017
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This paper presents the results from a 5-year and near-real-time measurement study of carbonaceous aerosols in PM2.5 conducted at an urban site in Shanghai. Moreover, we integrated the results from historical field measurements and satellite observations, concluding that carbonaceous aerosol pollution in Shanghai has gradually reduced since 2006. This can be largely explained by the introduction of air-cleaning measures such as controlling vehicular emissions.
Peter Zotter, Hanna Herich, Martin Gysel, Imad El-Haddad, Yanlin Zhang, Griša Močnik, Christoph Hüglin, Urs Baltensperger, Sönke Szidat, and André S. H. Prévôt
Atmos. Chem. Phys., 17, 4229–4249, https://doi.org/10.5194/acp-17-4229-2017, https://doi.org/10.5194/acp-17-4229-2017, 2017
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Yan-Lin Zhang, Kimitaka Kawamura, Ping Qing Fu, Suresh K. R. Boreddy, Tomomi Watanabe, Shiro Hatakeyama, Akinori Takami, and Wei Wang
Atmos. Chem. Phys., 16, 6407–6419, https://doi.org/10.5194/acp-16-6407-2016, https://doi.org/10.5194/acp-16-6407-2016, 2016
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Here, based on three aircraft measurements over East Asia, we demonstrate an aqueous-phase mechanism for enhanced SOA production in the troposphere following correlation analysis of oxalic acid in tropospheric aerosols with other measured chemical variables including its precursors and its intermediate as well as biogenic-derived SOA from isoprene, monoterpenes and β-caryophyllene.
Junwen Liu, Jun Li, Di Liu, Ping Ding, Chengde Shen, Yangzhi Mo, Xinming Wang, Chunling Luo, Zhineng Cheng, Sönke Szidat, Yanlin Zhang, Yingjun Chen, and Gan Zhang
Atmos. Chem. Phys., 16, 2985–2996, https://doi.org/10.5194/acp-16-2985-2016, https://doi.org/10.5194/acp-16-2985-2016, 2016
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Many Chinese cities now are suffering the high loadings of fine particular matters, which can bring a lot of negative impacts on air quality, human health, and the climate system. The Chinese government generally focuses on the control of the emissions from vehicles and industry. Our results evidently show that the burning of biomass materials such as wood and agricultural residues can lead to the urban air pollution in China. The characteristic of haze covering China is distinct from regions.
K. R. Daellenbach, C. Bozzetti, A. Křepelová, F. Canonaco, R. Wolf, P. Zotter, P. Fermo, M. Crippa, J. G. Slowik, Y. Sosedova, Y. Zhang, R.-J. Huang, L. Poulain, S. Szidat, U. Baltensperger, I. El Haddad, and A. S. H. Prévôt
Atmos. Meas. Tech., 9, 23–39, https://doi.org/10.5194/amt-9-23-2016, https://doi.org/10.5194/amt-9-23-2016, 2016
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In this study, we developed an offline technique using the AMS for the characterization of the chemical fingerprints of aerosols collected on quartz filters, and evaluated the suitability of the organic mass spectral data for source apportionment. This technique may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved long-term data sets.
G. O. Mouteva, S. M. Fahrni, G. M. Santos, J. T. Randerson, Y.-L. Zhang, S. Szidat, and C. I. Czimczik
Atmos. Meas. Tech., 8, 3729–3743, https://doi.org/10.5194/amt-8-3729-2015, https://doi.org/10.5194/amt-8-3729-2015, 2015
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We describe a stepwise uncertainty analysis of 14C measurements of organic (OC) and elemental (EC) carbon fractions of aerosols. Using the Swiss_4S thermal-optical protocol with a newly established trapping setup, we show that we can efficiently isolate and trap each carbon fraction and perform 14C analysis of ultra-small OC and EC samples with high accuracy and low 14C blanks. Our study presents a first step towards the development of a common protocol for OC and EC 14C measurements.
J. Gabbi, M. Huss, A. Bauder, F. Cao, and M. Schwikowski
The Cryosphere, 9, 1385–1400, https://doi.org/10.5194/tc-9-1385-2015, https://doi.org/10.5194/tc-9-1385-2015, 2015
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Light-absorbing impurities in snow and ice increase the absorption of solar radiation and thus enhance melting. We investigated the effect of Saharan dust and black carbon on the mass balance of an Alpine glacier over 1914-2014. Snow impurities increased melt by 15-19% depending on the location on the glacier. From the accumulation area towards the equilibrium line, the effect of impurities increased as more frequent years with negative mass balance led to a re-exposure of dust-enriched layers.
Y.-L. Zhang, R.-J. Huang, I. El Haddad, K.-F. Ho, J.-J. Cao, Y. Han, P. Zotter, C. Bozzetti, K. R. Daellenbach, F. Canonaco, J. G. Slowik, G. Salazar, M. Schwikowski, J. Schnelle-Kreis, G. Abbaszade, R. Zimmermann, U. Baltensperger, A. S. H. Prévôt, and S. Szidat
Atmos. Chem. Phys., 15, 1299–1312, https://doi.org/10.5194/acp-15-1299-2015, https://doi.org/10.5194/acp-15-1299-2015, 2015
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Source apportionment of fine carbonaceous aerosols using radiocarbon and other organic markers measurements during 2013 winter haze episodes was conducted at four megacities in China. Our results demonstrate that fossil emissions predominate EC with a mean contribution of 75±8%, whereas non-fossil sources account for 55±10% of OC; and the increment of TC on heavily polluted days was mainly driven by the increase of secondary OC from both fossil-fuel and non-fossil emissions.
P. Zotter, V. G. Ciobanu, Y. L. Zhang, I. El-Haddad, M. Macchia, K. R. Daellenbach, G. A. Salazar, R.-J. Huang, L. Wacker, C. Hueglin, A. Piazzalunga, P. Fermo, M. Schwikowski, U. Baltensperger, S. Szidat, and A. S. H. Prévôt
Atmos. Chem. Phys., 14, 13551–13570, https://doi.org/10.5194/acp-14-13551-2014, https://doi.org/10.5194/acp-14-13551-2014, 2014
Related subject area
Subject: Aerosols | Research Activity: Machine Learning | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Influencing Factors of Gas-Particle Distribution of Oxygenated Organic Molecules in Urban Atmosphere and its Deviation from Equilibrium Partitioning
A satellite-based analysis of semi-direct effects of biomass burning aerosols on fog and low-cloud dissipation in the Namib Desert
Improving the predictions of black carbon (BC) optical properties at various aging stages using a machine-learning-based approach
Xinyu Wang, Nan Chen, Bo Zhu, and Huan Yu
EGUsphere, https://doi.org/10.5194/egusphere-2025-229, https://doi.org/10.5194/egusphere-2025-229, 2025
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Gas-to-particle partitioning governs the fate of organic molecules and the formation of organic aerosols in the atmosphere. Based on field measurement data, we built machine learning models to predict gas-to-particle partitioning. We also unveiled previously unrecognized interactions that lead to the deviations of partitioning from equilibrium state under real atmospheric conditions. Our study provided valuable insights for future research in atmospheric chemistry.
Alexandre Mass, Hendrik Andersen, Jan Cermak, Paola Formenti, Eva Pauli, and Julian Quinting
Atmos. Chem. Phys., 25, 491–510, https://doi.org/10.5194/acp-25-491-2025, https://doi.org/10.5194/acp-25-491-2025, 2025
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This study investigates the interaction between smoke aerosols and fog and low clouds (FLCs) in the Namib Desert between June and October. Here, a satellite-based dataset of FLCs, reanalysis data and machine learning are used to systematically analyze FLC persistence under different aerosol loadings. Aerosol plumes are shown to modify local thermodynamics, which increase FLC persistence. But fully disentangling aerosol effects from meteorological ones remains a challenge.
Baseerat Romshoo, Jaikrishna Patil, Tobias Michels, Thomas Müller, Marius Kloft, and Mira Pöhlker
Atmos. Chem. Phys., 24, 8821–8846, https://doi.org/10.5194/acp-24-8821-2024, https://doi.org/10.5194/acp-24-8821-2024, 2024
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Through the use of our machine-learning-based optical model, realistic BC morphologies can be incorporated into atmospheric science applications that require highly accurate results with minimal computational resources. The results of the study demonstrate that the predictions of single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved over the conventional Mie-based predictions when using the machine learning method.
Cited articles
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Short summary
To improve air quality, the Chinese government has implemented strict clean-air measures. We explored how black carbon (BC) responded to these measures and found that a reduction in liquid fuel use was the main factor driving a decrease in BC levels. Additionally, meteorological factors also played a significant role in the long-term trends of BC. These factors should be considered in future emission reduction policies to further enhance air quality improvements.
To improve air quality, the Chinese government has implemented strict clean-air measures. We...
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