Articles | Volume 18, issue 5
https://doi.org/10.5194/amt-18-1149-2025
© 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/amt-18-1149-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Mar 2025
Research article |
| 06 Mar 2025
| 06 Mar 2025
Inversion algorithm of black carbon mixing state based on machine learning
Zeyuan Tian
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Jiaping Wang
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, 210023, China
Chao Liu
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Jia Xing
Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996, USA
Jinbo Wang
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, 210023, China
Zhouyang Zhang
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Yuzhi Jin
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Sunan Shen
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Bin Wang
State Key Laboratory of Climate System Prediction and Risk Management/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory, Nanjing University of Information Science and Technology, Nanjing, 210044, China
School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, 210023, China
Xin Huang
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, 210023, China
Aijun Ding
Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
National Observation and Research Station for Atmospheric Processes and Environmental Change in Yangtze River Delta, Nanjing, 210023, China
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Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
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Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
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Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Yishuo Guo, Chao Yan, Yuliang Liu, Xiaohui Qiao, Feixue Zheng, Ying Zhang, Ying Zhou, Chang Li, Xiaolong Fan, Zhuohui Lin, Zemin Feng, Yusheng Zhang, Penggang Zheng, Linhui Tian, Wei Nie, Zhe Wang, Dandan Huang, Kaspar R. Daellenbach, Lei Yao, Lubna Dada, Federico Bianchi, Jingkun Jiang, Yongchun Liu, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 10077–10097, https://doi.org/10.5194/acp-22-10077-2022, https://doi.org/10.5194/acp-22-10077-2022, 2022
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Gaseous oxygenated organic molecules (OOMs) are able to form atmospheric aerosols, which will impact on human health and climate change. Here, we find that OOMs in urban Beijing are dominated by anthropogenic sources, i.e. aromatic (29 %–41 %) and aliphatic (26 %–41 %) OOMs. They are also the main contributors to the condensational growth of secondary organic aerosols (SOAs). Therefore, the restriction on anthropogenic VOCs is crucial for the reduction of SOAs and haze formation.
You Zhao, Chao Liu, Di Di, Ziqiang Ma, and Shihao Tang
Atmos. Meas. Tech., 15, 2791–2805, https://doi.org/10.5194/amt-15-2791-2022, https://doi.org/10.5194/amt-15-2791-2022, 2022
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A typhoon is a high-impact atmospheric phenomenon that causes most significant socioeconomic damage, and its precipitation observation is always needed for typhoon characteristics and disaster prevention. This study developed a typhoon precipitation fusion method to combine observations from satellite radiometers, rain gauges and reanalysis to provide much improved typhoon precipitation datasets.
Jiandong Wang, Jia Xing, Shuxiao Wang, Rohit Mathur, Jiaping Wang, Yuqiang Zhang, Chao Liu, Jonathan Pleim, Dian Ding, Xing Chang, Jingkun Jiang, Peng Zhao, Shovan Kumar Sahu, Yuzhi Jin, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 22, 5147–5156, https://doi.org/10.5194/acp-22-5147-2022, https://doi.org/10.5194/acp-22-5147-2022, 2022
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Aerosols reduce surface solar radiation and change the photolysis rate and planetary boundary layer stability. In this study, the online coupled meteorological and chemistry model was used to explore the detailed pathway of how aerosol direct effects affect secondary inorganic aerosol. The effects through the dynamics pathway act as an equally or even more important route compared with the photolysis pathway in affecting secondary aerosol concentration in both summer and winter.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, https://doi.org/10.5194/amt-15-735-2022, 2022
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Jing Cai, Cheng Wu, Jiandong Wang, Wei Du, Feixue Zheng, Simo Hakala, Xiaolong Fan, Biwu Chu, Lei Yao, Zemin Feng, Yongchun Liu, Yele Sun, Jun Zheng, Chao Yan, Federico Bianchi, Markku Kulmala, Claudia Mohr, and Kaspar R. Daellenbach
Atmos. Chem. Phys., 22, 1251–1269, https://doi.org/10.5194/acp-22-1251-2022, https://doi.org/10.5194/acp-22-1251-2022, 2022
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This study investigates the connection between organic aerosol (OA) molecular composition and particle absorptive properties in autumn in Beijing. We find that the molecular properties of OA compounds in different episodes influence particle light absorption properties differently: the light absorption enhancement of black carbon and light absorption coefficient of brown carbon were mostly related to more oxygenated OA (low C number and four O atoms) and aromatics/nitro-aromatics, respectively.
Qi En Zhong, Chunlei Cheng, Zaihua Wang, Lei Li, Mei Li, Dafeng Ge, Lei Wang, Yuanyuan Li, Wei Nie, Xuguang Chi, Aijun Ding, Suxia Yang, Duohong Chen, and Zhen Zhou
Atmos. Chem. Phys., 21, 17953–17967, https://doi.org/10.5194/acp-21-17953-2021, https://doi.org/10.5194/acp-21-17953-2021, 2021
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Particulate amines play important roles in new particle formation, aerosol acidity, and hygroscopicity. Most of the field observations did not distinguish the different behavior of each type amine under the same ambient influencing factors. In this study, two amine-containing single particles exhibited different mixing states and disparate enrichment of secondary organics, which provide insight into the discriminated fates of organics during the formation and evolution processes.
Xinyan Li, Yuanjian Yang, Jiaqin Mi, Xueyan Bi, You Zhao, Zehao Huang, Chao Liu, Lian Zong, and Wanju Li
Atmos. Meas. Tech., 14, 7007–7023, https://doi.org/10.5194/amt-14-7007-2021, https://doi.org/10.5194/amt-14-7007-2021, 2021
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A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
Yuliang Liu, Wei Nie, Yuanyuan Li, Dafeng Ge, Chong Liu, Zhengning Xu, Liangduo Chen, Tianyi Wang, Lei Wang, Peng Sun, Ximeng Qi, Jiaping Wang, Zheng Xu, Jian Yuan, Chao Yan, Yanjun Zhang, Dandan Huang, Zhe Wang, Neil M. Donahue, Douglas Worsnop, Xuguang Chi, Mikael Ehn, and Aijun Ding
Atmos. Chem. Phys., 21, 14789–14814, https://doi.org/10.5194/acp-21-14789-2021, https://doi.org/10.5194/acp-21-14789-2021, 2021
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Oxygenated organic molecules (OOMs) are crucial intermediates linking volatile organic compounds to secondary organic aerosols. Using nitrate time-of-flight chemical ionization mass spectrometry in eastern China, we performed positive matrix factorization (PMF) on binned OOM mass spectra. We reconstructed over 1000 molecules from 14 derived PMF factors and identified about 72 % of the observed OOMs as organic nitrates, highlighting the decisive role of NOx in OOM formation in populated areas.
Mao Xiao, Christopher R. Hoyle, Lubna Dada, Dominik Stolzenburg, Andreas Kürten, Mingyi Wang, Houssni Lamkaddam, Olga Garmash, Bernhard Mentler, Ugo Molteni, Andrea Baccarini, Mario Simon, Xu-Cheng He, Katrianne Lehtipalo, Lauri R. Ahonen, Rima Baalbaki, Paulus S. Bauer, Lisa Beck, David Bell, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, António Dias, Jonathan Duplissy, Henning Finkenzeller, Hamish Gordon, Victoria Hofbauer, Changhyuk Kim, Theodore K. Koenig, Janne Lampilahti, Chuan Ping Lee, Zijun Li, Huajun Mai, Vladimir Makhmutov, Hanna E. Manninen, Ruby Marten, Serge Mathot, Roy L. Mauldin, Wei Nie, Antti Onnela, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Simone Schuchmann, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Robert Wagner, Yonghong Wang, Lena Weitz, Daniela Wimmer, Yusheng Wu, Chao Yan, Penglin Ye, Qing Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Ken Carslaw, Joachim Curtius, Armin Hansel, Rainer Volkamer, Paul M. Winkler, Richard C. Flagan, Markku Kulmala, Douglas R. Worsnop, Jasper Kirkby, Neil M. Donahue, Urs Baltensperger, Imad El Haddad, and Josef Dommen
Atmos. Chem. Phys., 21, 14275–14291, https://doi.org/10.5194/acp-21-14275-2021, https://doi.org/10.5194/acp-21-14275-2021, 2021
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Experiments at CLOUD show that in polluted environments new particle formation (NPF) is largely driven by the formation of sulfuric acid–base clusters, stabilized by amines, high ammonia concentrations or lower temperatures. While oxidation products of aromatics can nucleate, they play a minor role in urban NPF. Our experiments span 4 orders of magnitude variation of observed NPF rates in ambient conditions. We provide a framework based on NPF and growth rates to interpret ambient observations.
Lian Zong, Yuanjian Yang, Meng Gao, Hong Wang, Peng Wang, Hongliang Zhang, Linlin Wang, Guicai Ning, Chao Liu, Yubin Li, and Zhiqiu Gao
Atmos. Chem. Phys., 21, 9105–9124, https://doi.org/10.5194/acp-21-9105-2021, https://doi.org/10.5194/acp-21-9105-2021, 2021
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In recent years, summer O3 pollution over eastern China has become more serious, and it is even the case that surface O3 and PM2.5 pollution can co-occur. However, the synoptic weather pattern (SWP) related to this compound pollution remains unclear. Regional PM2.5 and O3 compound pollution is characterized by various SWPs with different dominant factors. Our findings provide insights into the regional co-occurring high PM2.5 and O3 levels via the effects of certain meteorological factors.
Markku Kulmala, Tom V. Kokkonen, Juha Pekkanen, Sami Paatero, Tuukka Petäjä, Veli-Matti Kerminen, and Aijun Ding
Atmos. Chem. Phys., 21, 8313–8322, https://doi.org/10.5194/acp-21-8313-2021, https://doi.org/10.5194/acp-21-8313-2021, 2021
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The eastern part of China as a whole is practically a gigacity with 650 million inhabitants. The gigacity, with its emissions, processes in the pollution cocktail and numerous feedbacks and interactions, has a crucial and big impact on regional air quality and on global climate. A large-scale research and innovation program is needed to meet the interlinked grand challenges in this gigacity and to serve as a platform for finding pathways for sustainable development of the globe.
Shibao Wang, Yun Ma, Zhongrui Wang, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Mengxian Wu, Ling Zhang, Yongle Xiao, and Yanxu Zhang
Atmos. Chem. Phys., 21, 7199–7215, https://doi.org/10.5194/acp-21-7199-2021, https://doi.org/10.5194/acp-21-7199-2021, 2021
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Mobile monitoring with low-cost sensors is a promising approach to garner high-spatial-resolution observations representative of the community scale. We develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3) based on GIS technology. Our results demonstrate the sensing power of mobile monitoring for urban air pollution, which provides detailed information for source attribution and accurate traceability at the urban micro-scale.
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, https://doi.org/10.5194/acp-21-2917-2021, 2021
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Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Yang Yang, Yu Zhao, Lei Zhang, Jie Zhang, Xin Huang, Xuefen Zhao, Yan Zhang, Mengxiao Xi, and Yi Lu
Atmos. Chem. Phys., 21, 1191–1209, https://doi.org/10.5194/acp-21-1191-2021, https://doi.org/10.5194/acp-21-1191-2021, 2021
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We conducted new NOx emission estimation based on the satellite-derived NO2 column constraint and found reduced emissions compared to previous estimates for a developed region in east China. The subsequent improvement in air quality modeling was demonstrated based on available ground observations. With multiple emission reduction cases for various pollutants, we explored the effective control approaches for ozone and inorganic aerosol pollution.
Ying Jiang, Likun Xue, Rongrong Gu, Mengwei Jia, Yingnan Zhang, Liang Wen, Penggang Zheng, Tianshu Chen, Hongyong Li, Ye Shan, Yong Zhao, Zhaoxin Guo, Yujian Bi, Hengde Liu, Aijun Ding, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 20, 12115–12131, https://doi.org/10.5194/acp-20-12115-2020, https://doi.org/10.5194/acp-20-12115-2020, 2020
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We analyzed the characteristics and sources of HONO in the upper boundary layer and lower free troposphere in the North China Plain, based on the field measurements at Mount Tai. Higher-than-expected levels and broad daytime peaks of HONO were observed. Without presence of ground surfaces, aerosol surface plays a key role in the heterogeneous HONO formation at high altitudes. Models without additional HONO sources largely
underestimatedthe oxidation processes in the elevation atmospheres.
Martin Heinritzi, Lubna Dada, Mario Simon, Dominik Stolzenburg, Andrea C. Wagner, Lukas Fischer, Lauri R. Ahonen, Stavros Amanatidis, Rima Baalbaki, Andrea Baccarini, Paulus S. Bauer, Bernhard Baumgartner, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, Antonio Dias, Josef Dommen, Jonathan Duplissy, Henning Finkenzeller, Carla Frege, Claudia Fuchs, Olga Garmash, Hamish Gordon, Manuel Granzin, Imad El Haddad, Xucheng He, Johanna Helm, Victoria Hofbauer, Christopher R. Hoyle, Juha Kangasluoma, Timo Keber, Changhyuk Kim, Andreas Kürten, Houssni Lamkaddam, Tiia M. Laurila, Janne Lampilahti, Chuan Ping Lee, Katrianne Lehtipalo, Markus Leiminger, Huajun Mai, Vladimir Makhmutov, Hanna Elina Manninen, Ruby Marten, Serge Mathot, Roy Lee Mauldin, Bernhard Mentler, Ugo Molteni, Tatjana Müller, Wei Nie, Tuomo Nieminen, Antti Onnela, Eva Partoll, Monica Passananti, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti P. Rissanen, Clémence Rose, Siegfried Schobesberger, Wiebke Scholz, Kay Scholze, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, Miguel Vazquez-Pufleau, Annele Virtanen, Alexander L. Vogel, Rainer Volkamer, Robert Wagner, Mingyi Wang, Lena Weitz, Daniela Wimmer, Mao Xiao, Chao Yan, Penglin Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Urs Baltensperger, Armin Hansel, Markku Kulmala, António Tomé, Paul M. Winkler, Douglas R. Worsnop, Neil M. Donahue, Jasper Kirkby, and Joachim Curtius
Atmos. Chem. Phys., 20, 11809–11821, https://doi.org/10.5194/acp-20-11809-2020, https://doi.org/10.5194/acp-20-11809-2020, 2020
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With experiments performed at CLOUD, we show how isoprene interferes in monoterpene oxidation via RO2 termination at atmospherically relevant concentrations. This interference shifts the distribution of highly oxygenated organic molecules (HOMs) away from C20 class dimers towards C15 class dimers, which subsequently reduces both biogenic nucleation and early growth rates. Our results may help to understand the absence of new-particle formation in isoprene-rich environments.
Wei Tao, Hang Su, Guangjie Zheng, Jiandong Wang, Chao Wei, Lixia Liu, Nan Ma, Meng Li, Qiang Zhang, Ulrich Pöschl, and Yafang Cheng
Atmos. Chem. Phys., 20, 11729–11746, https://doi.org/10.5194/acp-20-11729-2020, https://doi.org/10.5194/acp-20-11729-2020, 2020
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We simulated the thermodynamic and multiphase reactions in aerosol water during a wintertime haze event over the North China Plain. It was found that aerosol pH exhibited a strong spatiotemporal variability, and multiple oxidation pathways were predominant for particulate sulfate formation in different locations. Sensitivity tests further showed that ammonia, crustal particles, and dissolved transition metal ions were important factors for multiphase chemistry during haze episodes.
Cited articles
Ahmad, G. N., Fatima, H., Ullah, S., and Saidi, A. S.: Efficient medical diagnosis of human heart diseases using machine learning techniques with and without GridSearchCV, IEEE Access, 10, 80151–80173, https://doi.org/10.1109/ACCESS.2022.3165792, 2022.
Bond, T. C. and Bergstrom, R. W.: Light Absorption by Carbonaceous Particles: An Investigative Review, Aerosol Sci. Tech., 40, 27–67, https://doi.org/10.1080/02786820500421521, 2006.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K., Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U., Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C. S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, https://doi.org/10.1002/jgrd.50171, 2013.
Cappa, C. D., Onasch, T. B., Massoli, P., Worsnop, D. R., Bates, T. S., Cross, E. S., Davidovits, P., Hakala, J., Hayden, K. L., Jobson, B. T., Kolesar, K. R., Lack, D. A., Lerner, B. M., Li, S.-M., Mellon, D., Nuaaman, I., Olfert, J. S., Petäjä, T., Quinn, P. K., Song, C., Subramanian, R., Williams, E. J., and Zaveri, R. A.: Radiative Absorption Enhancements Due to the Mixing State of Atmospheric Black Carbon, Science, 337, 1078–1081, https://doi.org/10.1126/science.1223447, 2012.
Carleo, G., Cirac, I., Cranmer, K., Daudet, L., Schuld, M., Tishby, N., Vogt-Maranto, L., and Zdeborová, L.: Machine learning and the physical sciences, Rev. Mod. Phys., 91, 045002, https://doi.org/10.1103/RevModPhys.91.045002, 2019.
Fan, J., Ma, X., Wu, L., Zhang, F., Yu, X., and Zeng, W.: Light Gradient Boosting Machine: An efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data, Agr. Water Manage., 225, 105758, https://doi.org/10.1016/j.agwat.2019.105758, 2019.
Fierce, L., Onasch, T. B., Cappa, C. D., Mazzoleni, C., China, S., Bhandari, J., Davidovits, P., Fischer, D. A., Helgestad, T., Lambe, A. T., Sedlacek, A. J., Smith, G. D., and Wolff, L.: Radiative absorption enhancements by black carbon controlled by particle-to-particle heterogeneity in composition, P. Natl. Acad. Sci. USA, 117, 5196–5203, https://doi.org/10.1073/pnas.1919723117, 2020.
Fuller, K. A., Malm, W. C., and Kreidenweis, S. M.: Effects of mixing on extinction by carbonaceous particles, J. Geophys. Res., 104, 15941–15954, https://doi.org/10.1029/1998JD100069, 1999.
Gan, M., Pan, S., Chen, Y., Cheng, C., Pan, H., and Zhu, X.: Application of the Machine Learning LightGBM Model to the Prediction of the Water Levels of the Lower Columbia River, Journal of Marine Science and Engineering, 9, 496, https://doi.org/10.3390/jmse9050496, 2021.
Gao, R. S., Schwarz, J. P., Kelly, K. K., Fahey, D. W., Watts, L. A., Thompson, T. L., Spackman, J. R., Slowik, J. G., Cross, E. S., Han, J.-H., Davidovits, P., Onasch, T. B., and Worsnop, D. R.: A Novel Method for Estimating Light-Scattering Properties of Soot Aerosols Using a Modified Single-Particle Soot Photometer, Aerosol Sci. Tech., 41, 125–135, https://doi.org/10.1080/02786820601118398, 2007.
Jacobson, M. Z.: Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols, Nature, 409, 695–697, 2001.
Jordan, M. I. and Mitchell, T. M.: Machine learning: Trends, perspectives, and prospects, Science, 349, 255–260, https://doi.org/10.1126/science.aaa8415, 2015.
Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., and Liu, T.-Y.: LightGBM: a highly efficient gradient boosting decision tree, in: NIPS'17: Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, California, USA, 4–9 December 2017, Curran Associates Inc., Red Hook, NY, USA, 3149–3157, 2017.
Keller, C. A. and Evans, M. J.: Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10, Geosci. Model Dev., 12, 1209–1225, https://doi.org/10.5194/gmd-12-1209-2019, 2019.
Laborde, M., Mertes, P., Zieger, P., Dommen, J., Baltensperger, U., and Gysel, M.: Sensitivity of the Single Particle Soot Photometer to different black carbon types, Atmos. Meas. Tech., 5, 1031–1043, https://doi.org/10.5194/amt-5-1031-2012, 2012.
Li, J., An, X., Li, Q., Wang, C., Yu, H., Zhou, X., and Geng, Y.: Application of XGBoost algorithm in the optimization of pollutant concentration, Atmos. Res., 276, 106238, https://doi.org/10.1016/j.atmosres.2022.106238, 2022.
Liakos, K., Busato, P., Moshou, D., Pearson, S., and Bochtis, D.: Machine Learning in Agriculture: A Review, Sensors, 18, 2674, https://doi.org/10.3390/s18082674, 2018.
Liu, D., Allan, J. D., Young, D. E., Coe, H., Beddows, D., Fleming, Z. L., Flynn, M. J., Gallagher, M. W., Harrison, R. M., Lee, J., Prevot, A. S. H., Taylor, J. W., Yin, J., Williams, P. I., and Zotter, P.: Size distribution, mixing state and source apportionment of black carbon aerosol in London during wintertime, Atmos. Chem. Phys., 14, 10061–10084, https://doi.org/10.5194/acp-14-10061-2014, 2014.
Liu, D., Whitehead, J., Alfarra, M. R., Reyes-Villegas, E., Spracklen, D. V., Reddington, C. L., Kong, S., Williams, P. I., Ting, Y.-C., and Haslett, S.: Black-carbon absorption enhancement in the atmosphere determined by particle mixing state, Nat. Geosci., 10, 184–188, 2017.
Liu, Z.-H., Weng, S.-S., Zeng, Z.-L., Ding, M.-H., Wang, Y.-Q., and Liang, Z.: Hourly land surface temperature retrieval over the Tibetan Plateau using Geo-LightGBM framework: Fusion of Himawari-8 satellite, ERA5 and site observations, Advances in Climate Change Research, 15, 623–635, https://doi.org/10.1016/j.accre.2024.06.007, 2024.
Lundberg, S. M. and Lee, S.-I.: A unified approach to interpreting model predictions, in: NIPS'17: Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, California, USA, 4–9 December 2017, Curran Associates Inc., Red Hook, NY, USA, 4768–4777, 2017.
Lundberg, S. M., Erion, G. G., and Lee, S.-I.: Consistent Individualized Feature Attribution for Tree Ensembles, arXiv [preprint], https://doi.org/10.48550/arXiv.1802.03888, 7 March 2019.
Matsui, H., Hamilton, D. S., and Mahowald, N. M.: Black carbon radiative effects highly sensitive to emitted particle size when resolving mixing-state diversity, Nat. Commun., 9, 3446, https://doi.org/10.1038/s41467-018-05635-1, 2018.
Moteki, N. and Kondo, Y.: Effects of Mixing State on Black Carbon Measurements by Laser-Induced Incandescence, Aerosol Sci. Tech., 41, 398–417, https://doi.org/10.1080/02786820701199728, 2007.
Moteki, N. and Kondo, Y.: Method to measure time-dependent scattering cross sections of particles evaporating in a laser beam, J. Aerosol Sci., 39, 348–364, https://doi.org/10.1016/j.jaerosci.2007.12.002, 2008.
Moteki, N. and Kondo, Y.: Dependence of Laser-Induced Incandescence on Physical Properties of Black Carbon Aerosols: Measurements and Theoretical Interpretation, Aerosol Sci. Tech., 44, 663–675, https://doi.org/10.1080/02786826.2010.484450, 2010.
Moteki, N., Ohata, S., Yoshida, A., and Adachi, K.: Constraining the complex refractive index of black carbon particles using the complex forward-scattering amplitude, Aerosol Sci. Tech., 57, 678–699, https://doi.org/10.1080/02786826.2023.2202243, 2023.
Oshima, N., Koike, M., Zhang, Y., Kondo, Y., Moteki, N., Takegawa, N., and Miyazaki, Y.: Aging of black carbon in outflow from anthropogenic sources using a mixing state resolved model: Model development and evaluation, J. Geophys. Res., 114, 2008JD010680, https://doi.org/10.1029/2008JD010680, 2009.
Pang, Y., Wang, Y., Wang, Z., Zhang, Y., Liu, L., Kong, S., Liu, F., Shi, Z., and Li, W.: Quantifying the Fractal Dimension and Morphology of Individual Atmospheric Soot Aggregates, J. Geophys. Res.-Atmos., 127, e2021JD036055, https://doi.org/10.1029/2021JD036055, 2022.
Ramanathan, V. and Carmichael, G.: Global and regional climate changes due to black carbon, Nat. Geosci., 1, 221–227, 2008.
Schnaiter, M., Linke, C., Möhler, O., Naumann, K. -H., Saathoff, H., Wagner, R., Schurath, U., and Wehner, B.: Absorption amplification of black carbon internally mixed with secondary organic aerosol, J. Geophys. Res., 110, 2005JD006046, https://doi.org/10.1029/2005JD006046, 2005.
Schwarz, J. P., Gao, R. S., Fahey, D. W., Thomson, D. S., Watts, L. A., Wilson, J. C., Reeves, J. M., Darbeheshti, M., Baumgardner, D. G., Kok, G. L., Chung, S. H., Schulz, M., Hendricks, J., Lauer, A., Kärcher, B., Slowik, J. G., Rosenlof, K. H., Thompson, T. L., Langford, A. O., Loewenstein, M., and Aikin, K. C.: Single-particle measurements of midlatitude black carbon and light-scattering aerosols from the boundary layer to the lower stratosphere, J. Geophys. Res., 111, 2006JD007076, https://doi.org/10.1029/2006JD007076, 2006.
Schwarz, J. P., Spackman, J. R., Fahey, D. W., Gao, R. S., Lohmann, U., Stier, P., Watts, L. A., Thomson, D. S., Lack, D. A., Pfister, L., Mahoney, M. J., Baumgardner, D., Wilson, J. C., and Reeves, J. M.: Coatings and their enhancement of black carbon light absorption in the tropical atmosphere, J. Geophys. Res., 113, 2007JD009042, https://doi.org/10.1029/2007JD009042, 2008.
Sedlacek, A. J., Lewis, E. R., Kleinman, L., Xu, J., and Zhang, Q.: Determination of and evidence for non-core-shell structure of particles containing black carbon using the Single-Particle Soot Photometer (SP2), Geophys. Res. Lett., 39, 2012GL050905, https://doi.org/10.1029/2012GL050905, 2012.
Sedlacek, A. J., Lewis, E. R., Onasch, T. B., Lambe, A. T., and Davidovits, P.: Investigation of Refractory Black Carbon-Containing Particle Morphologies Using the Single-Particle Soot Photometer (SP2), Aerosol Sci. Tech., 49, 872–885, https://doi.org/10.1080/02786826.2015.1074978, 2015.
Shiraiwa, M., Kondo, Y., Moteki, N., Takegawa, N., Sahu, L. K., Takami, A., Hatakeyama, S., Yonemura, S., and Blake, D. R.: Radiative impact of mixing state of black carbon aerosol in Asian outflow, J. Geophys. Res., 113, 2008JD010546, https://doi.org/10.1029/2008JD010546, 2008.
Slowik, J. G., Cross, E. S., Han, J.-H., Davidovits, P., Onasch, T. B., Jayne, J. T., Williams, L. R., Canagaratna, M. R., Worsnop, D. R., Chakrabarty, R. K., Moosmüller, H., Arnott, W. P., Schwarz, J. P., Gao, R.-S., Fahey, D. W., Kok, G. L., and Petzold, A.: An Inter-Comparison of Instruments Measuring Black Carbon Content of Soot Particles, Aerosol Sci. Tech., 41, 295–314, https://doi.org/10.1080/02786820701197078, 2007.
Stephens, M., Turner, N., and Sandberg, J.: Particle identification by laser-induced incandescence in a solid-state laser cavity, Appl. Optics, 42, 3726–3736, 2003.
Subramanian, R., Kok, G. L., Baumgardner, D., Clarke, A., Shinozuka, Y., Campos, T. L., Heizer, C. G., Stephens, B. B., de Foy, B., Voss, P. B., and Zaveri, R. A.: Black carbon over Mexico: the effect of atmospheric transport on mixing state, mass absorption cross-section, and BC/CO ratios, Atmos. Chem. Phys., 10, 219–237, https://doi.org/10.5194/acp-10-219-2010, 2010.
Sun, X., Liu, M., and Sima, Z.: A novel cryptocurrency price trend forecasting model based on LightGBM, Financ. Res. Lett., 32, 101084, https://doi.org/10.1016/j.frl.2018.12.032, 2020.
Tarca, A. L., Carey, V. J., Chen, X., Romero, R., and Drăghici, S.: Machine Learning and Its Applications to Biology, PLoS Comput. Biol., 3, e116, https://doi.org/10.1371/journal.pcbi.0030116, 2007.
Taylor, J. W., Allan, J. D., Liu, D., Flynn, M., Weber, R., Zhang, X., Lefer, B. L., Grossberg, N., Flynn, J., and Coe, H.: Assessment of the sensitivity of core/shell parameters derived using the single-particle soot photometer to density and refractive index, Atmos. Meas. Tech., 8, 1701–1718, https://doi.org/10.5194/amt-8-1701-2015, 2015.
Wang, Y., Liu, F., He, C., Bi, L., Cheng, T., Wang, Z., Zhang, H., Zhang, X., Shi, Z., and Li, W.: Fractal Dimensions and Mixing Structures of Soot Particles during Atmospheric Processing, Environm. Sci. Tech. Let., 4, 487–493, https://doi.org/10.1021/acs.estlett.7b00418, 2017.
Wang, Y., Pang, Y., Huang, J., Bi, L., Che, H., Zhang, X., and Li, W.: Constructing Shapes and Mixing Structures of Black Carbon Particles With Applications to Optical Calculations, J. Geophys. Res.-Atmos., 126, e2021JD034620, https://doi.org/10.1029/2021JD034620, 2021a.
Wang, Y., Li, W., Huang, J., Liu, L., Pang, Y., He, C., Liu, F., Liu, D., Bi, L., Zhang, X., and Shi, Z.: Nonlinear Enhancement of Radiative Absorption by Black Carbon in Response to Particle Mixing Structure, Geophys. Res. Lett., 48, e2021GL096437, https://doi.org/10.1029/2021GL096437, 2021b.
Wei, J., Li, Z., Pinker, R. T., Wang, J., Sun, L., Xue, W., Li, R., and Cribb, M.: Himawari-8-derived diurnal variations in ground-level PM2.5 pollution across China using the fast space-time Light Gradient Boosting Machine (LightGBM), Atmos. Chem. Phys., 21, 7863–7880, https://doi.org/10.5194/acp-21-7863-2021, 2021.
Yang, L., Xu, H., and Yu, S.: Estimating PM2.5 concentrations in Yangtze River Delta region of China using random forest model and the Top-of-Atmosphere reflectance, Journal of Environmental Management, 272, 111061, https://doi.org/10.1016/j.jenvman.2020.111061, 2020.
Zhang, L., Shen, F., Gao, J., Cui, S., Yue, H., Wang, J., Chen, M., and Ge, X.: Characteristics and potential sources of black carbon particles in suburban Nanjing, China, Atmos. Pollut. Res., 11, 981–991, https://doi.org/10.1016/j.apr.2020.02.011, 2020.
Zhang, Y., Zhang, Q., Cheng, Y., Su, H., Kecorius, S., Wang, Z., Wu, Z., Hu, M., Zhu, T., Wiedensohler, A., and He, K.: Measuring the morphology and density of internally mixed black carbon with SP2 and VTDMA: new insight into the absorption enhancement of black carbon in the atmosphere, Atmos. Meas. Tech., 9, 1833–1843, https://doi.org/10.5194/amt-9-1833-2016, 2016.
Zhang, Y., Wang, Y., Gao, M., Ma, Q., Zhao, J., Zhang, R., Wang, Q., and Huang, L.: A Predictive Data Feature Exploration-Based Air Quality Prediction Approach, IEEE Access, 7, 30732–30743, https://doi.org/10.1109/ACCESS.2019.2897754, 2019.
Zhong, J., Zhang, X., Gui, K., Wang, Y., Che, H., Shen, X., Zhang, L., Zhang, Y., Sun, J., and Zhang, W.: Robust prediction of hourly PM2.5 from meteorological data using LightGBM, Natl. Sci. Rev., 8, nwaa307, https://doi.org/10.1093/nsr/nwaa307, 2021.
Short summary
The radiative effect of black carbon (BC) is substantially modulated by its mixing state, which is challenging to derive physically with a single-particle soot photometer. This study establishes a machine-learning-based inversion model which can accurately and efficiently acquire the BC mixing state. Compared to the widely used leading-edge-only method, our model utilizes a broader scattering signal coverage to more accurately capture diverse particle characteristics.
The radiative effect of black carbon (BC) is substantially modulated by its mixing state, which...
