Articles | Volume 24, issue 7
https://doi.org/10.5194/acp-24-4177-2024
© Author(s) 2024. 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-24-4177-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Apr 2024
Research article |
| 08 Apr 2024
| 08 Apr 2024
Diagnosing ozone–NOx–VOC–aerosol sensitivity and uncovering causes of urban–nonurban discrepancies in Shandong, China, using transformer-based estimations
Chenliang Tao
Big Data Research Center for Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao 266237, PR China
Yanbo Peng
CORRESPONDING AUTHOR
Big Data Research Center for Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao 266237, PR China
Shandong Academy for Environmental Planning, Jinan 250101, PR China
Qingzhu Zhang
CORRESPONDING AUTHOR
Big Data Research Center for Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao 266237, PR China
Yuqiang Zhang
Big Data Research Center for Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao 266237, PR China
Bing Gong
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Qiao Wang
Big Data Research Center for Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao 266237, PR China
Wenxing Wang
Big Data Research Center for Ecology and Environment, Environmental Research Institute, Shandong University, Qingdao 266237, PR China
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3702, https://doi.org/10.5194/egusphere-2024-3702, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study analyzes summertime ozone trends in East and Southeast Asia derived from a comprehensive observational database spanning from 1995 to 2019, incorporating aircraft observations, ozonesonde data, and measurements from 2500 surface sites. Multiple models are applied to attribute to changes in anthropogenic emissions and climate. The results highlight increases in anthropogenic emission are the primary driver of ozone increases both in the free troposphere and at the surface.
Zizhen Han, Yuqiang Zhang, Zhou Liu, Kexin Zhang, Zhuyi Wang, Bin Luo, Likun Xue, and Xinfeng Wang
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During the COVID-19 lockdown, changes in air pollutants offered a real-world test of emission reductions. JPL’s chemical reanalysis data showed a general decrease in CO, NO2, O3, and nitrate aerosols across most African countries, but an increase in SO2, sulfate aerosols, and O3 in Southern Africa during winter. We concluded that air quality changes are influenced by both natural and anthropogenic factors, emphasizing the need for stricter emission standards and clean energy promotion in Africa.
Yujia Wang, Hongbin Wang, Bo Zhang, Peng Liu, Xinfeng Wang, Shuchun Si, Likun Xue, Qingzhu Zhang, and Qiao Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2791, https://doi.org/10.5194/egusphere-2024-2791, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study established a bottom-up approach that employs real-time traffic flows and interpolation to obtain a spatially continuous on-road vehicle emission mapping for the main urban area of Jinan. The diurnal variation, spatial distribution, and emission hotspots were analyzed with clustering and hotspot analysis, showing unique fine-scale variation characteristics of on-road vehicle emissions. Future scenario analysis demonstrates remarkable benefits of electrification on emission reduction.
Bin Luo, Yuqiang Zhang, Tao Tang, Hongliang Zhang, Jianlin Hu, Jiangshan Mu, Wenxing Wang, and Likun Xue
EGUsphere, https://doi.org/10.5194/egusphere-2024-974, https://doi.org/10.5194/egusphere-2024-974, 2024
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Yue Sun, Yujiao Zhu, Yanbin Qi, Lanxiadi Chen, Jiangshan Mu, Ye Shan, Yu Yang, Yanqiu Nie, Ping Liu, Can Cui, Ji Zhang, Mingxuan Liu, Lingli Zhang, Yufei Wang, Xinfeng Wang, Mingjin Tang, Wenxing Wang, and Likun Xue
Atmos. Chem. Phys., 24, 3241–3256, https://doi.org/10.5194/acp-24-3241-2024, https://doi.org/10.5194/acp-24-3241-2024, 2024
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Field observations were conducted at the summit of Changbai Mountain in northeast Asia. The cumulative number concentration of ice-nucleating particles (INPs) varied from 1.6 × 10−3 to 78.3 L−1 over the temperature range of −5.5 to −29.0 ℃. Biological INPs (bio-INPs) accounted for the majority of INPs, and the proportion exceeded 90% above −13.0 ℃. Planetary boundary layer height, valley breezes, and long-distance transport of air mass influence the abundance of bio-INPs.
Xuelian Zhong, Hengqing Shen, Min Zhao, Ji Zhang, Yue Sun, Yuhong Liu, Yingnan Zhang, Ye Shan, Hongyong Li, Jiangshan Mu, Yu Yang, Yanqiu Nie, Jinghao Tang, Can Dong, Xinfeng Wang, Yujiao Zhu, Mingzhi Guo, Wenxing Wang, and Likun Xue
Atmos. Chem. Phys., 23, 14761–14778, https://doi.org/10.5194/acp-23-14761-2023, https://doi.org/10.5194/acp-23-14761-2023, 2023
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Nitrous acid (HONO) is vital for atmospheric oxidation. In research at Mount Lao, China, models revealed a significant unidentified marine HONO source. Overlooking this could skew our understanding of air quality and climate change. This finding emphasizes HONO’s importance in the coastal atmosphere, uncovering previously unnoticed interactions.
Yan Ji, Bing Gong, Michael Langguth, Amirpasha Mozaffari, and Xiefei Zhi
Geosci. Model Dev., 16, 2737–2752, https://doi.org/10.5194/gmd-16-2737-2023, https://doi.org/10.5194/gmd-16-2737-2023, 2023
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Formulating short-term precipitation forecasting as a video prediction task, a novel deep learning architecture (convolutional long short-term memory generative adversarial network, CLGAN) is proposed. A benchmark dataset is built on minute-level precipitation measurements. Results show that with the GAN component the model generates predictions sharing statistical properties with observations, resulting in it outperforming the baseline in dichotomous and spatial scores for heavy precipitation.
Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Geosci. Model Dev., 15, 8931–8956, https://doi.org/10.5194/gmd-15-8931-2022, https://doi.org/10.5194/gmd-15-8931-2022, 2022
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Inspired by the success of deep learning in various domains, we test the applicability of video prediction methods by generative adversarial network (GAN)-based deep learning to predict the 2 m temperature over Europe. Our video prediction models have skill in predicting the diurnal cycle of 2 m temperature up to 12 h ahead. Complemented by probing the relevance of several model parameters, this study confirms the potential of deep learning in meteorological forecasting applications.
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.
Dianyi Li, Drew Shindell, Dian Ding, Xiao Lu, Lin Zhang, and Yuqiang Zhang
Atmos. Chem. Phys., 22, 2625–2638, https://doi.org/10.5194/acp-22-2625-2022, https://doi.org/10.5194/acp-22-2625-2022, 2022
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In this study, we applied chemical transport model simulation with the latest annual anthropogenic emission inventory to study the long-term trend of ozone-induced crop production losses from 2010 to 2017 in China. We find that overall the ozone-induced crop production loss in China is significant and the annual average economic losses for wheat, rice, maize, and soybean in China are USD 9.55 billion, USD 8.53 billion, USD 2.23 billion, and USD 1.16 billion respectively, over the 8 years.
Yuqiang Zhang, Drew Shindell, Karl Seltzer, Lu Shen, Jean-Francois Lamarque, Qiang Zhang, Bo Zheng, Jia Xing, Zhe Jiang, and Lei Zhang
Atmos. Chem. Phys., 21, 16051–16065, https://doi.org/10.5194/acp-21-16051-2021, https://doi.org/10.5194/acp-21-16051-2021, 2021
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In this study, we use a global chemical transport model to simulate the effects on global air quality and human health due to emission changes in China from 2010 to 2017. By performing sensitivity analysis, we found that the air pollution control policies not only decrease the air pollutant concentration but also bring significant co-benefits in air quality to downwind regions. The benefits for the improved air pollution are dominated by PM2.5.
Tao Tang, Drew Shindell, Yuqiang Zhang, Apostolos Voulgarakis, Jean-Francois Lamarque, Gunnar Myhre, Gregory Faluvegi, Bjørn H. Samset, Timothy Andrews, Dirk Olivié, Toshihiko Takemura, and Xuhui Lee
Atmos. Chem. Phys., 21, 13797–13809, https://doi.org/10.5194/acp-21-13797-2021, https://doi.org/10.5194/acp-21-13797-2021, 2021
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Previous studies showed that black carbon (BC) could warm the surface with decreased incoming radiation. With climate models, we found that the surface energy redistribution plays a more crucial role in surface temperature compared with other forcing agents. Though BC could reduce the surface heating, the energy dissipates less efficiently, which is manifested by reduced convective and evaporative cooling, thereby warming the surface.
Yingnan Zhang, Likun Xue, William P. L. Carter, Chenglei Pei, Tianshu Chen, Jiangshan Mu, Yujun Wang, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 21, 11053–11068, https://doi.org/10.5194/acp-21-11053-2021, https://doi.org/10.5194/acp-21-11053-2021, 2021
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We developed the localized incremental reactivity (IR) for VOCs in a Chinese megacity and elucidated their applications in calculating the ozone formation potential (OFP). The IR scales showed a strong dependence on chemical mechanisms. Both emission- and observation-based inputs are suitable for the MIR calculation but not the case under mixed-limited or NOx-limited O3 formation regimes. We provide suggestions for the application of IR and OFP scales to aid in VOC control in China.
Zhe Jiang, Hongrong Shi, Bin Zhao, Yu Gu, Yifang Zhu, Kazuyuki Miyazaki, Xin Lu, Yuqiang Zhang, Kevin W. Bowman, Takashi Sekiya, and Kuo-Nan Liou
Atmos. Chem. Phys., 21, 8693–8708, https://doi.org/10.5194/acp-21-8693-2021, https://doi.org/10.5194/acp-21-8693-2021, 2021
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We use the COVID-19 pandemic as a unique natural experiment to obtain a more robust understanding of the effectiveness of emission reductions toward air quality improvement by combining chemical transport simulations and observations. Our findings imply a shift from current control policies in California: a strengthened control on primary PM2.5 emissions and a well-balanced control on NOx and volatile organic compounds are needed to effectively and sustainably alleviate PM2.5 and O3 pollution.
Yujiao Zhu, Likun Xue, Jian Gao, Jianmin Chen, Hongyong Li, Yong Zhao, Zhaoxin Guo, Tianshu Chen, Liang Wen, Penggang Zheng, Ye Shan, Xinfeng Wang, Tao Wang, Xiaohong Yao, and Wenxing Wang
Atmos. Chem. Phys., 21, 1305–1323, https://doi.org/10.5194/acp-21-1305-2021, https://doi.org/10.5194/acp-21-1305-2021, 2021
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This work investigates the long-term changes in new particle formation (NPF) events under reduced SO2 emissions at the summit of Mt. Tai during seven campaigns from 2007 to 2018. We found the NPF intensity increased 2- to 3-fold in 2018 compared to 2007. In contrast, the probability of new particles growing to CCN size largely decreased. Changes to biogenic VOCs and anthropogenic emissions are proposed to explain the distinct NPF characteristics.
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.
Ling Zou, Sabine Griessbach, Lars Hoffmann, Bing Gong, and Lunche Wang
Atmos. Chem. Phys., 20, 9939–9959, https://doi.org/10.5194/acp-20-9939-2020, https://doi.org/10.5194/acp-20-9939-2020, 2020
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Cirrus clouds appearing in the upper troposphere and lower stratosphere have important impacts on the radiation budget and climate change. We revisited global stratospheric cirrus clouds with CALIPSO and for the first time with MIPAS satellite observations. Stratospheric cirrus clouds related to deep convection are frequently detected in the tropics. At middle latitudes, MIPAS detects more than twice as many stratospheric cirrus clouds due to higher detection sensitivity.
Tao Tang, Drew Shindell, Yuqiang Zhang, Apostolos Voulgarakis, Jean-Francois Lamarque, Gunnar Myhre, Camilla W. Stjern, Gregory Faluvegi, and Bjørn H. Samset
Atmos. Chem. Phys., 20, 8251–8266, https://doi.org/10.5194/acp-20-8251-2020, https://doi.org/10.5194/acp-20-8251-2020, 2020
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By using climate simulations, we found that both CO2 and black carbon aerosols could reduce low-level cloud cover, which is mainly due to changes in relative humidity, cloud water, dynamics, and stability. Because the impact of cloud on solar radiation is in effect only during daytime, such cloud reduction could enhance solar heating, thereby raising the daily maximum temperature by 10–50 %, varying by region, which has great implications for extreme climate events and socioeconomic activity.
Tianshu Chen, Likun Xue, Penggang Zheng, Yingnan Zhang, Yuhong Liu, Jingjing Sun, Guangxuan Han, Hongyong Li, Xin Zhang, Yunfeng Li, Hong Li, Can Dong, Fei Xu, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 20, 7069–7086, https://doi.org/10.5194/acp-20-7069-2020, https://doi.org/10.5194/acp-20-7069-2020, 2020
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Oil production is a significant source of ambient VOCs, but its impact on air quality has long been overlooked in China. We addressed this gap by conducting field campaigns in an oil field region followed by chemical modeling analyses. The VOC speciation profiles from the oil field emissions were directly measured for the first time in China. This study emphasizes the importance of oil extraction to photochemical pollution and atmospheric chemistry in the oil production regions of China.
Yanhong Zhu, Andreas Tilgner, Erik Hans Hoffmann, Hartmut Herrmann, Kimitaka Kawamura, Lingxiao Yang, Likun Xue, and Wenxing Wang
Atmos. Chem. Phys., 20, 6725–6747, https://doi.org/10.5194/acp-20-6725-2020, https://doi.org/10.5194/acp-20-6725-2020, 2020
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The formation and processing of secondary inorganic and organic compounds at Mt. Tai, the highest mountain on the North China Plain, are modeled using a multiphase chemical model. The concentrations of key radical and non-radical oxidations in the formation processes are investigated. Sensitivity tests assess the impacts of emission data and glyoxal partitioning constants on modeled results. The key precursors of secondary organic compounds are also identified.
Jun Zhang, Xinfeng Wang, Rui Li, Shuwei Dong, Yingnan Zhang, Penggang Zheng, Min Li, Tianshu Chen, Yuhong Liu, Likun Xue, Wei Nie, Aijun Ding, Mingjin Tang, Xuehua Zhou, Lin Du, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-757, https://doi.org/10.5194/acp-2019-757, 2019
Preprint withdrawn
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This study presents the concentrations, variation characteristics, and key influencing factors of particulate organic nitrates at four urban and rural sites in eastern China. The effects of anthropogenic activities (i.e. biomass burning and coal combustion) and meteorological conditions (in particular the humidity) on the secondary formation of organic nitrates have been investigated. The results highlight the greater role of SO2 in organic nitrate chemistry than previously assumed.
Siyang Li, Xiaotong Jiang, Marie Roveretto, Christian George, Ling Liu, Wei Jiang, Qingzhu Zhang, Wenxing Wang, Maofa Ge, and Lin Du
Atmos. Chem. Phys., 19, 9887–9902, https://doi.org/10.5194/acp-19-9887-2019, https://doi.org/10.5194/acp-19-9887-2019, 2019
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We stimulated the photochemical aging of organic film coated on aqueous aerosol in the presence of imidazole-2-carboxaldehyde, humic acid, an atmospheric PM2.5 sample, and a secondary organic aerosol sample from the lab. The unsaturated lipid mixed with photosensitizer under UV irradiation produced hydroperoxides, leading to surface area increase in organic film. Our results reveal the modification of organic film on aqueous aerosol has potential influence on the hygroscopic growth of droplets.
Lei Sun, Likun Xue, Yuhang Wang, Longlei Li, Jintai Lin, Ruijing Ni, Yingying Yan, Lulu Chen, Juan Li, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 19, 1455–1469, https://doi.org/10.5194/acp-19-1455-2019, https://doi.org/10.5194/acp-19-1455-2019, 2019
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We quantified the detailed impacts of meteorology and anthropogenic emissions on surface O3 increase in central eastern China between 2003 and 2015 using GEOS-Chem. The emission change plays a more important role than the meteorological change, while the regions with a larger O3 increase are more sensitive to meteorology. NMVOC emission change dominated the O3 increase in eastern CEC, while NOx emission change led to an O3 increase in western and central CEC and O3 decrease in urban areas.
Yuqiang Zhang, J. Jason West, Rohit Mathur, Jia Xing, Christian Hogrefe, Shawn J. Roselle, Jesse O. Bash, Jonathan E. Pleim, Chuen-Meei Gan, and David C. Wong
Atmos. Chem. Phys., 18, 15003–15016, https://doi.org/10.5194/acp-18-15003-2018, https://doi.org/10.5194/acp-18-15003-2018, 2018
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Here we use a fine-resolution (36 km) self-consistent 21-year air quality simulation from 1990 to 2010, a health impact function, and annual county-level population and baseline mortality rate estimates to estimate annual mortality burdens from PM2.5 and O3 in the US, and also the contributions to the trends. We found that the PM2.5-related mortality burden has steadily decreased by 53 %, while the O3-related mortality burden has increased by 13 %, with larger inter-annual variabilities.
Liang Wen, Likun Xue, Xinfeng Wang, Caihong Xu, Tianshu Chen, Lingxiao Yang, Tao Wang, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 18, 11261–11275, https://doi.org/10.5194/acp-18-11261-2018, https://doi.org/10.5194/acp-18-11261-2018, 2018
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We present the first piece of observational evidence of the increasing trend of fine nitrate aerosol in the North China Plain (NCP) during 2005–2015. The summertime nitrate formation mechanism is dissected with a multiphase chemical box model based on observations at three different sites. The nitrate formation is most sensitive to NO2 and to a lesser extent to O3. NH3 plays a significant role in prompting the nitrate formation, but it is usually in excess in summer in the NCP region.
Yanhong Zhu, Lingxiao Yang, Jianmin Chen, Kimitaka Kawamura, Mamiko Sato, Andreas Tilgner, Dominik van Pinxteren, Ying Chen, Likun Xue, Xinfeng Wang, Isobel J. Simpson, Hartmut Herrmann, Donald R. Blake, and Wenxing Wang
Atmos. Chem. Phys., 18, 10741–10758, https://doi.org/10.5194/acp-18-10741-2018, https://doi.org/10.5194/acp-18-10741-2018, 2018
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Molecular distributions of dicarboxylic acids, oxocarboxylic acids and α-dicarbonyls in the free troposphere are identified, and their concentration variations between 2014 and 2006 are presented. High nighttime concentrations were probably due to precursor emissions and aqueous-phase oxidation. Biomass burning was significant, but its tracer levoglucosan in 2014 was 5 times lower than 2006 concentrations. Finally, regional emission from anthropogenic activities was identified as a major source.
Yuqiang Zhang, Rohit Mathur, Jesse O. Bash, Christian Hogrefe, Jia Xing, and Shawn J. Roselle
Atmos. Chem. Phys., 18, 9091–9106, https://doi.org/10.5194/acp-18-9091-2018, https://doi.org/10.5194/acp-18-9091-2018, 2018
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For this study, we evaluated the WRF–CMAQ coupled model's ability to simulate the long-term trends of wet deposition of nitrogen and sulfur from 1990 to 2010 by comparing the model results with long-term observation datasets in the US. The model generally underestimates the wet deposition of both nitrogen and sulfur but captured well the decreasing trends for the deposition. Then we estimated the deposition budget in the US, including wet deposition and dry deposition from model simulations.
Liwei Wang, Xinfeng Wang, Rongrong Gu, Hao Wang, Lan Yao, Liang Wen, Fanping Zhu, Weihao Wang, Likun Xue, Lingxiao Yang, Keding Lu, Jianmin Chen, Tao Wang, Yuanghang Zhang, and Wenxing Wang
Atmos. Chem. Phys., 18, 4349–4359, https://doi.org/10.5194/acp-18-4349-2018, https://doi.org/10.5194/acp-18-4349-2018, 2018
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This study presents concentrations, variation characteristics, sources and secondary formations of nitrated phenols, a major component of brown carbon, in typical seasons at four sites in northern China. The results highlight the strong influences and contributions of anthropogenic activities, in particular coal combustion and the aging processes, to the atmospheric nitrated phenols in this region.
Caihong Xu, Min Wei, Jianmin Chen, Chao Zhu, Jiarong Li, Ganglin Lv, Xianmang Xu, Lulu Zheng, Guodong Sui, Weijun Li, Bing Chen, Wenxing Wang, Qingzhu Zhang, Aijun Ding, and Abdelwahid Mellouki
Atmos. Chem. Phys., 17, 11247–11260, https://doi.org/10.5194/acp-17-11247-2017, https://doi.org/10.5194/acp-17-11247-2017, 2017
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Fungi are ubiquitous throughout the near-surface atmosphere, where they represent an important component of primary biological aerosol particles. The diversity and composition of the fungal communities varied over the different seasons between the fine (PM2.5) and submicron (PM1) particles at the summit of Mt. Tai located in the North China Plain, China. This work may serve as an important reference for the fungal contribution to primary biological aerosol particles.
Jiarong Li, Xinfeng Wang, Jianmin Chen, Chao Zhu, Weijun Li, Chengbao Li, Lu Liu, Caihong Xu, Liang Wen, Likun Xue, Wenxing Wang, Aijun Ding, and Hartmut Herrmann
Atmos. Chem. Phys., 17, 9885–9896, https://doi.org/10.5194/acp-17-9885-2017, https://doi.org/10.5194/acp-17-9885-2017, 2017
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Cloud events at Mt. Tai were investigated for the chemical composition and size distribution of cloud droplets. An obvious rise in pH was found for elevated NH+4 during the last decade. Higher PM2.5 levels resulted in higher concentrations of water-soluble ions, smaller sizes and higher numbers of cloud droplets. The mechanism of cloud-droplet formation and the mass transfer between aerosol–gas–cloud phases were summarized to enrich the knowledge of cloud chemical and microphysical properties.
Jia Xing, Jiandong Wang, Rohit Mathur, Shuxiao Wang, Golam Sarwar, Jonathan Pleim, Christian Hogrefe, Yuqiang Zhang, Jingkun Jiang, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 17, 9869–9883, https://doi.org/10.5194/acp-17-9869-2017, https://doi.org/10.5194/acp-17-9869-2017, 2017
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The assessment of the impacts of aerosol direct effects (ADE) is important for understanding emission reduction strategies that seek co-benefits associated with reductions in both particulate matter and ozone. This study quantifies the ADE impacts on tropospheric ozone by using a two-way coupled meteorology and atmospheric chemistry model. Results suggest that reducing ADE may have the potential risk of increasing ozone in winter, but it will benefit the reduction of maxima ozone in summer.
Shurui Chen, Liang Xu, Yinxiao Zhang, Bing Chen, Xinfeng Wang, Xiaoye Zhang, Mei Zheng, Jianmin Chen, Wenxing Wang, Yele Sun, Pingqing Fu, Zifa Wang, and Weijun Li
Atmos. Chem. Phys., 17, 1259–1270, https://doi.org/10.5194/acp-17-1259-2017, https://doi.org/10.5194/acp-17-1259-2017, 2017
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Many studies have focused on the unusually severe hazes instead of the more frequent light and moderate hazes (22–63 %) in winter in the North China Plain (NCP). The morphology, mixing state, and size of organic aerosols in the L & M hazes were characterized. We conclude that the direct emissions from residential coal stoves without any pollution controls in rural and urban outskirts contribute large amounts of primary OM particles to the regional L & M hazes in winter in the NCP.
Lei Sun, Likun Xue, Tao Wang, Jian Gao, Aijun Ding, Owen R. Cooper, Meiyun Lin, Pengju Xu, Zhe Wang, Xinfeng Wang, Liang Wen, Yanhong Zhu, Tianshu Chen, Lingxiao Yang, Yan Wang, Jianmin Chen, and Wenxing Wang
Atmos. Chem. Phys., 16, 10637–10650, https://doi.org/10.5194/acp-16-10637-2016, https://doi.org/10.5194/acp-16-10637-2016, 2016
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We compiled the available observations of surface O3 at Mt. Tai – the highest mountain in the North China Plain, and found a significant increase of O3 concenrations from 2003 to 2015. The observed O3 increase was mainly due to the increase of O3 precursors, especially VOCs. Our analysis shows that controlling NOx alone, in the absence of VOC controls, is not sufficient to reduce regional O3 levels in North China in a short period.
Yuqiang Zhang, Jared H. Bowden, Zachariah Adelman, Vaishali Naik, Larry W. Horowitz, Steven J. Smith, and J. Jason West
Atmos. Chem. Phys., 16, 9533–9548, https://doi.org/10.5194/acp-16-9533-2016, https://doi.org/10.5194/acp-16-9533-2016, 2016
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Reducing greenhouse gas (GHG) emissions can also improve air quality. We estimate the co-benefits of global GHG mitigation for US air quality in 2050 at fine resolution by downscaling from a previous global study. Foreign GHG mitigation under RCP4.5 contributes more to the US O3 reduction (76 % of the total) than domestic mitigation and contributes 26 % of the PM2.5 reduction. Therefore, the US gains significantly greater air quality co-benefits by coordinating GHG controls internationally.
Related subject area
Subject: Gases | Research Activity: Machine Learning | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Technical note: Towards atmospheric compound identification in chemical ionization mass spectrometry with machine learning
A machine learning approach to downscale EMEP4UK: analysis of UK ozone variability and trends
Automated detection and monitoring of methane super-emitters using satellite data
Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning
Estimating nitrogen and sulfur deposition across China during 2005 to 2020 based on multiple statistical models
Technical note: Improving the European air quality forecast of the Copernicus Atmosphere Monitoring Service using machine learning techniques
Federica Bortolussi, Hilda Sandström, Fariba Partovi, Joona Mikkilä, Patrick Rinke, and Matti Rissanen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1846, https://doi.org/10.5194/egusphere-2024-1846, 2024
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Chemical ionization mass spectrometry (CIMS) is widely used in atmospheric chemistry studies. We still have a limited understanding of the complex functioning of the instrument, therefore, we applied machine learning to provide insights from CIMS analyses. We were able to predict both detection and signal intensity with a fair error and we found out the most important structural fragments for negative ionization schemes (NH and OH) and positive ones (nitrogen-containing groups).
Lily Gouldsbrough, Ryan Hossaini, Emma Eastoe, Paul J. Young, and Massimo Vieno
Atmos. Chem. Phys., 24, 3163–3196, https://doi.org/10.5194/acp-24-3163-2024, https://doi.org/10.5194/acp-24-3163-2024, 2024
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High-resolution spatial fields of surface ozone are used to understand spikes in ozone concentration and predict their impact on public health. Such fields are routinely output from complex mathematical models for atmospheric conditions. These outputs are on a coarse spatial resolution and the highest concentrations tend to be biased. Using a novel data-driven machine learning methodology, we show how such output can be corrected to produce fields with both lower bias and higher resolution.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
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Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Vigneshkumar Balamurugan, Jia Chen, Adrian Wenzel, and Frank N. Keutsch
Atmos. Chem. Phys., 23, 10267–10285, https://doi.org/10.5194/acp-23-10267-2023, https://doi.org/10.5194/acp-23-10267-2023, 2023
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In this study, machine learning models are employed to model NO2 and O3 concentrations. We employed a wide range of sources of data, including meteorological and column satellite measurements, to model NO2 and O3 concentrations. The spatial and temporal variability, and their drivers, were investigated. Notably, the machine learning model established the relationship between NOx and O3. Despite the fact that metropolitan regions are NO2 hotspots, rural areas have high O3 concentrations.
Kaiyue Zhou, Wen Xu, Lin Zhang, Mingrui Ma, Xuejun Liu, and Yu Zhao
Atmos. Chem. Phys., 23, 8531–8551, https://doi.org/10.5194/acp-23-8531-2023, https://doi.org/10.5194/acp-23-8531-2023, 2023
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We developed a dataset of the long-term (2005–2020) variabilities of China’s nitrogen and sulfur deposition, with multiple statistical models that combine available observations and chemistry transport modeling. We demonstrated the strong impact of human activities and national pollution control actions on the spatiotemporal changes in deposition and indicated a relatively small benefit of emission abatement on deposition (and thereby ecological risk) for China compared to Europe and the USA.
Jean-Maxime Bertrand, Frédérik Meleux, Anthony Ung, Gaël Descombes, and Augustin Colette
Atmos. Chem. Phys., 23, 5317–5333, https://doi.org/10.5194/acp-23-5317-2023, https://doi.org/10.5194/acp-23-5317-2023, 2023
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Post-processing methods based on machine learning algorithms were applied to refine the forecasts of four key pollutants at monitoring sites across Europe. Performances show significant improvements compared to those of the deterministic model raw outputs. Taking advantage of the large modelling domain extension, an innovative
globalapproach is proposed to drastically reduce the period necessary to train the models and thus facilitate the implementation in an operational context.
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Short summary
We developed a novel transformer framework to bridge the sparse surface monitoring for inferring ozone–NOx–VOC–aerosol sensitivity and their urban–nonurban discrepancies at a finer scale with implications for improving our understanding of ozone variations. The change in urban–rural disparities in ozone was dominated by PM2.5 from 2019 to 2020. An aerosol-inhibited regime on top of the two traditional NOx- and VOC-limited regimes was identified in Jiaodong Peninsula, Shandong, China.
We developed a novel transformer framework to bridge the sparse surface monitoring for inferring...
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