Articles | Volume 16, issue 20
https://doi.org/10.5194/acp-16-13271-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-13271-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Properties of aerosols and formation mechanisms over southern China during the monsoon season
Weihua Chen
School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China
Xuemei Wang
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
Jason Blake Cohen
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
Shengzhen Zhou
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
Zhisheng Zhang
South China Institute of Environmental Sciences, Guangzhou, China
Ming Chang
School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China
Chuen-Yu Chan
Key Laboratory of Aerosol, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
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Yunfei Wu, Jiwei Li, Zhisheng Zhang, Jun Tao, Yunjie Xia, Liang Ran, and Zhaoze Deng
EGUsphere, https://doi.org/10.5194/egusphere-2026-4178, https://doi.org/10.5194/egusphere-2026-4178, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Atmospheric particles affect climate by absorbing water and forming clouds, but how organic aerosols uptake water remains unclear. Our field measurements in rural eastern China show their hygroscopicity depends more on emission sources – especially biomass burning – than oxidation. Aging increases water uptake from biomass burning, but not from other sources. These results urge models to include source information for better climate predictions.
Pravash Tiwari, Jason Blake Cohen, Hongrui Gao, Lingxiao Lu, Jun Wang, Oleg Dubovik, and Kai Qin
Atmos. Chem. Phys., 26, 9149–9180, https://doi.org/10.5194/acp-26-9149-2026, https://doi.org/10.5194/acp-26-9149-2026, 2026
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Black carbon's climate impact is highly uncertain because its radiative effect depends on particle size, mixing state, and column loading. This study combines satellite data, physics-based simulations, and machine learning to estimate black carbon forcing across contrasting regions. The same black carbon amount can warm or cool the atmosphere depending on local aerosol properties. The machine learning framework provides a fast, transferable tool for regional climate assessment.
Hongrui Gao, Qin He, Kai Qin, Jhoon Kim, Diego Loyola, Pravash Tiwari, Lingxiao Lu, and Jason Blake Cohen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-443, https://doi.org/10.5194/essd-2026-443, 2026
Revised manuscript under review for ESSD
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There are always gaps in satellite records of air pollution because of factors such as clouds and operating conditions. We used a physics-aware deep learning method, producing a gapless 0.05° hourly dataset of tropospheric nitrogen dioxide over Asian pollution hotspots from 2019 to 2024. The dataset can capture sub-daily changes, revealing how traffic, industry, and clean-air policies shaped pollution, supporting health and environment studies.
Jinglan Lin, Liqing Wu, Chujun Chen, Yongkang Wu, Rui Lin, Xuemei Wang, and Weihua Chen
Atmos. Chem. Phys., 26, 7081–7103, https://doi.org/10.5194/acp-26-7081-2026, https://doi.org/10.5194/acp-26-7081-2026, 2026
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By integrating satellite data from 2005–2023 (warm seasons), we analyzed the spatiotemporal evolution of ozone formation sensitivity across China. Results show a shift toward NOx-limited and transitional regimes under policy measures. Explainable machine learning suggests this evolution is mainly associated with emission changes, while meteorological factors become increasingly important under cleaner conditions. These findings support more precise, region-specific ozone control strategies.
Luoyao Guan, Jason Blake Cohen, Shuo Wang, Pravash Tiwari, Zhewen Liu, Zhengqiang Li, and Kai Qin
Atmos. Chem. Phys., 26, 3107–3123, https://doi.org/10.5194/acp-26-3107-2026, https://doi.org/10.5194/acp-26-3107-2026, 2026
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This study examines how black carbon particles from the coal industry influence regional climate by absorbing sunlight. Based on ground measurements and modeling, we find that conventional approaches, which oversimplify particle size and structure, which could leading a bias in terms of their warming effect. Our results highlight that more realistic particle characterizations are crucial for improving climate predictions in industrial regions.
Bo Zheng, Jason Blake Cohen, Lingxiao Lu, Wei Hu, Pravash Tiwari, Simone Lolli, Andrea Garzelli, Hui Su, and Kai Qin
Atmos. Chem. Phys., 26, 1931–1946, https://doi.org/10.5194/acp-26-1931-2026, https://doi.org/10.5194/acp-26-1931-2026, 2026
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This study provides TROPOMI (TROPOspheric Monitoring Instrument) with a new methane emission estimation method that can accurately identify emission sources. Our results generate non-negative emission datasets using objective selection and filtering methods. The results include lower minimum emission thresholds for all power grids and fewer false positives. The new method provides more robust emission quantification in the face of data uncertainty, going beyond traditional plume identification and background subtraction.
Zhewen Liu, Jason B. Cohen, Pravash Tiwari, Luoyao Guan, Shuo Wang, Zhengqiang Li, and Kai Qin
Earth Syst. Sci. Data, 18, 507–533, https://doi.org/10.5194/essd-18-507-2026, https://doi.org/10.5194/essd-18-507-2026, 2026
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Black carbon (BC), emitted from fires, industry, and fossil fuels, warms the climate and worsens air quality. Due to complex physical and optical properties, BC remains poorly constrained. We combined satellite observations with physical models to build a daily, high-resolution, decadal global dataset of BC mass, number, size, and mixing details. The data contains both known sources and new hotspots. These results can support climate models, satellite products, and pollution mitigation.
Xi Chen, Xiaoyang Chen, Long Wang, Shucheng Chang, Minhui Li, Chong Shen, Chenghao Liao, Yongbo Zhang, Mei Li, and Xuemei Wang
Atmos. Chem. Phys., 26, 879–897, https://doi.org/10.5194/acp-26-879-2026, https://doi.org/10.5194/acp-26-879-2026, 2026
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Typhoons moving north near China create ozone pollution in Guangdong by combining strong sunlight with stagnant air. These tyhoons also push ozone-rich air from high altitudes down to ground level. When multiple north-moving typhoons occur back-to-back, they cause widespread and long-lasting ozone pollution. Vertical air currents during these events can contribute up to 16 % of boundary layer ozone.
Ye Feng, Jason Blake Cohen, Xiaolu Li, Lingxiao Lu, Zhewen Liu, Lei Wang, Jian Liu, and Kai Qin
EGUsphere, https://doi.org/10.5194/egusphere-2025-5890, https://doi.org/10.5194/egusphere-2025-5890, 2026
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Carbon monoxide emissions in Central Asia's coal-heavy regions, like Xinjiang Province and Kazakhstan, are poorly tracked. Using satellite data and a new approach, this study maps daily emissions (2019–2024) while addressing measurement errors. About 69 % of estimates were unreliable. Underground coal fires, often ignored, emit as much CO as power plants. Emissions peaked in 2019, dropped until 2022, then rose again, linking to policy changes and economic shifts.
Jingnan Shi, Zhisheng Zhang, Li Li, Li Liu, Yaqing Zhou, Shuang Han, Shaobin Zhang, Minghua Liang, Linhong Xie, Weikang Ran, Shaowen Zhu, Hanbing Xu, Jiangchuan Tao, Alfred Wiedensohler, Qiaoqiao Wang, Qiyuan Wang, Nan Ma, and Juan Hong
Atmos. Chem. Phys., 26, 1–13, https://doi.org/10.5194/acp-26-1-2026, https://doi.org/10.5194/acp-26-1-2026, 2026
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This study examines the aerosol hygroscopicity and mixing state at Huashan (2060 m), a key free tropospheric site in central China. We find that hygroscopicity depends on particle size, source-related changes, and moisture-driven processing, which distinguishes this region from other high-altitude regions and may provide key constraints for aerosol-cloud and regional climate models.
Chujun Chen, Weihua Chen, Linhao Guo, Yongkang Wu, Xianzhong Duan, Xuemei Wang, and Min Shao
Atmos. Chem. Phys., 25, 15145–15169, https://doi.org/10.5194/acp-25-15145-2025, https://doi.org/10.5194/acp-25-15145-2025, 2025
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Background O3 forms the baseline level of O3 pollution, even without local human activities. This review examines how background O3 is defined and estimated, revealing significant variations across China, with higher level in the Northwest and lower in the Northeast region. Globally, China’s background O3 levels are medium-to-high and rising. The study calls for integrated estimation methods, international collaboration, and research on climate-ozone links to improve air quality strategies.
Fan Lu, Kai Qin, Jason Blake Cohen, Qin He, Pravash Tiwari, Wei Hu, Chang Ye, Yanan Shan, Qing Xu, Shuo Wang, and Qiansi Tu
Atmos. Chem. Phys., 25, 5837–5856, https://doi.org/10.5194/acp-25-5837-2025, https://doi.org/10.5194/acp-25-5837-2025, 2025
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This work describes a field campaign and new fast emissions estimation approach to attribute methane from a large known and previously unknown coal mine in Shanxi, China. The emissions computed are shown to be larger than known oil and gas sources, indicating that methane from coal mines may play a larger role in the global methane budget. The results are found to be slightly larger than or similar to satellite observational campaigns over the same region.
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He
Atmos. Chem. Phys., 25, 2291–2309, https://doi.org/10.5194/acp-25-2291-2025, https://doi.org/10.5194/acp-25-2291-2025, 2025
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This study applies an approach that assimilates NO2 vertical column densities from TROPOMI in a mass-conserving manner and inverts daily NOx emissions, presented over rapidly changing regions in China. Source attribution is quantified by the local thermodynamics of the combustion temperature (NOx/NO2). Emission results identify sources which do not exist in the a priori datasets, especially medium industrial sources located next to the Yangtze River.
Kai Qin, Hongrui Gao, Xuancen Liu, Qin He, Pravash Tiwari, and Jason Blake Cohen
Earth Syst. Sci. Data, 16, 5287–5310, https://doi.org/10.5194/essd-16-5287-2024, https://doi.org/10.5194/essd-16-5287-2024, 2024
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Satellites have brought new opportunities for monitoring atmospheric NO2, although the results are limited by clouds and other factors, resulting in missing data. This work proposes a new process to obtain reliable data products with high coverage by reconstructing the raw data from multiple satellites. The results are validated in terms of traditional methods as well as variance maximization and demonstrate a good ability to reproduce known polluted and clean areas around the world.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
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Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Qiansi Tu, Frank Hase, Kai Qin, Jason Blake Cohen, Farahnaz Khosrawi, Xinrui Zou, Matthias Schneider, and Fan Lu
Atmos. Chem. Phys., 24, 4875–4894, https://doi.org/10.5194/acp-24-4875-2024, https://doi.org/10.5194/acp-24-4875-2024, 2024
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Four-year satellite observations of XCH4 are used to derive CH4 emissions in three regions of China’s coal-rich Shanxi province. The wind-assigned anomalies for two opposite wind directions are calculated, and the estimated emission rates are comparable to the current bottom-up inventory but lower than the CAMS and EDGAR inventories. This research enhances the understanding of emissions in Shanxi and supports climate mitigation strategies by validating emission inventories.
Kai Qin, Wei Hu, Qin He, Fan Lu, and Jason Blake Cohen
Atmos. Chem. Phys., 24, 3009–3028, https://doi.org/10.5194/acp-24-3009-2024, https://doi.org/10.5194/acp-24-3009-2024, 2024
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We compute CH4 emissions and uncertainty on a mine-by-mine basis, including underground, overground, and abandoned mines. Mine-by-mine gas and flux data and 30 min observations from a flux tower located next to a mine shaft are integrated. The observed variability and bias correction are propagated over the emissions dataset, demonstrating that daily observations may not cover the range of variability. Comparisons show both an emissions magnitude and spatial mismatch with current inventories.
Liting Yang, Ming Chang, Shuping Situ, Weiwen Wang, and Xuemei Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-28, https://doi.org/10.5194/egusphere-2024-28, 2024
Preprint archived
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The study aims to develop and apply the WRF-uEMEP model to simulate air quality at the city scale, with a focus on Foshan, the city with the highest industrial density. The research process included model development, calibration, and validation using existing air quality data in Foshan. Research shows that WRF-uEMEP model effectively captures the impact of urban structure on air pollutant processes and reveals the spatial and temporal distribution of air pollutants in Foshan.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
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A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Xiaolu Li, Jason Blake Cohen, Kai Qin, Hong Geng, Xiaohui Wu, Liling Wu, Chengli Yang, Rui Zhang, and Liqin Zhang
Atmos. Chem. Phys., 23, 8001–8019, https://doi.org/10.5194/acp-23-8001-2023, https://doi.org/10.5194/acp-23-8001-2023, 2023
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Remotely sensed NO2 and surface NOx are combined with a mathematical method to estimate daily NOx emissions. The results identify new sources and improve existing estimates. The estimation is driven by three flexible factors: thermodynamics of combustion, chemical loss, and atmospheric transport. The thermodynamic term separates power, iron, and cement from coking, boilers, and aluminum. This work finds three causes for the extremes: emissions, UV radiation, and transport.
Yanqin Ren, Gehui Wang, Jie Wei, Jun Tao, Zhisheng Zhang, and Hong Li
Atmos. Chem. Phys., 23, 6835–6848, https://doi.org/10.5194/acp-23-6835-2023, https://doi.org/10.5194/acp-23-6835-2023, 2023
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Nine quantified nitrated aromatic compounds (NACs) in PM2.5 were examined at the peak of Mt. Wuyi. They manifested a significant rise in overall abundance in the winter and autumn. The transport of contaminants had a significant impact on NACs. Under low-NOx conditions, the formation of NACs was comparatively sensitive to NO2, suggesting that NACs would become significant in the aerosol characteristics when nitrate concentrations decreased as a result of emission reduction measures.
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
Yongkang Wu, Weihua Chen, Yingchang You, Qianqian Xie, Shiguo Jia, and Xuemei Wang
Atmos. Chem. Phys., 23, 453–469, https://doi.org/10.5194/acp-23-453-2023, https://doi.org/10.5194/acp-23-453-2023, 2023
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Relying on observed and simulated data, we determine the spatiotemporal characteristics of nocturnal O3 increase (NOI) events in the Pearl River Delta region during 2006–2019. Low-level jets and convective storms are the main meteorological processes causing NOI. Daytime O3 is another essential influencing factor. More importantly, a more prominent role of meteorological processes in NOI has been demonstrated. Our study highlights the important role of meteorology in nocturnal O3 pollution.
Haichao Wang, Bin Yuan, E Zheng, Xiaoxiao Zhang, Jie Wang, Keding Lu, Chenshuo Ye, Lei Yang, Shan Huang, Weiwei Hu, Suxia Yang, Yuwen Peng, Jipeng Qi, Sihang Wang, Xianjun He, Yubin Chen, Tiange Li, Wenjie Wang, Yibo Huangfu, Xiaobing Li, Mingfu Cai, Xuemei Wang, and Min Shao
Atmos. Chem. Phys., 22, 14837–14858, https://doi.org/10.5194/acp-22-14837-2022, https://doi.org/10.5194/acp-22-14837-2022, 2022
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We present intensive field measurement of ClNO2 in the Pearl River Delta in 2019. Large variation in the level, formation, and atmospheric impacts of ClNO2 was found in different air masses. ClNO2 formation was limited by the particulate chloride (Cl−) and aerosol surface area. Our results reveal that Cl− originated from various anthropogenic emissions rather than sea sources and show minor contribution to the O3 pollution and photochemistry.
Xiao-Bing Li, Bin Yuan, Sihang Wang, Chunlin Wang, Jing Lan, Zhijie Liu, Yongxin Song, Xianjun He, Yibo Huangfu, Chenglei Pei, Peng Cheng, Suxia Yang, Jipeng Qi, Caihong Wu, Shan Huang, Yingchang You, Ming Chang, Huadan Zheng, Wenda Yang, Xuemei Wang, and Min Shao
Atmos. Chem. Phys., 22, 10567–10587, https://doi.org/10.5194/acp-22-10567-2022, https://doi.org/10.5194/acp-22-10567-2022, 2022
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High-time-resolution measurements of volatile organic compounds (VOCs) were made using an online mass spectrometer at a 600 m tall tower in urban region. Compositions, temporal variations, and sources of VOCs were quantitatively investigated in this study. We find that VOC measurements in urban regions aloft could better characterize source characteristics of anthropogenic emissions. Our results could provide important implications in making future strategies for control of VOCs.
Qi Zhang, Shiguo Jia, Weihua Chen, Jingying Mao, Liming Yang, Padmaja Krishnan, Sayantan Sarkar, Min Shao, and Xuemei Wang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-394, https://doi.org/10.5194/acp-2022-394, 2022
Revised manuscript not accepted
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We use satellite data in the establishment of methylamines marine biological emission (MBE) inventory for the first time, which considers effects of actual marine environment on methylamines emission fluxes. MBE fluxes of monomethylamine and trimethylamines can be comparable with or even higher than that of terrestrial anthropogenic emissions , while for dimethylamines, the ocean acts as a sink. Wind and Chlorophyll-a were potentially the most important factors affecting MBE fluxes.
Suxia Yang, Bin Yuan, Yuwen Peng, Shan Huang, Wei Chen, Weiwei Hu, Chenglei Pei, Jun Zhou, David D. Parrish, Wenjie Wang, Xianjun He, Chunlei Cheng, Xiao-Bing Li, Xiaoyun Yang, Yu Song, Haichao Wang, Jipeng Qi, Baolin Wang, Chen Wang, Chaomin Wang, Zelong Wang, Tiange Li, E Zheng, Sihang Wang, Caihong Wu, Mingfu Cai, Chenshuo Ye, Wei Song, Peng Cheng, Duohong Chen, Xinming Wang, Zhanyi Zhang, Xuemei Wang, Junyu Zheng, and Min Shao
Atmos. Chem. Phys., 22, 4539–4556, https://doi.org/10.5194/acp-22-4539-2022, https://doi.org/10.5194/acp-22-4539-2022, 2022
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We use a model constrained using observations to study the formation of nitrate aerosol in and downwind of a representative megacity. We found different contributions of various chemical reactions to ground-level nitrate concentrations between urban and suburban regions. We also show that controlling VOC emissions are effective for decreasing nitrate formation in both urban and regional environments, although VOCs are not direct precursors of nitrate aerosol.
Ming Chang, Jiachen Cao, Qi Zhang, Weihua Chen, Guotong Wu, Liping Wu, Weiwen Wang, and Xuemei Wang
Geosci. Model Dev., 15, 787–801, https://doi.org/10.5194/gmd-15-787-2022, https://doi.org/10.5194/gmd-15-787-2022, 2022
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Despite the importance of nitrogen deposition, its simulation is still insufficiently represented in current atmospheric chemistry models. In this study, the improvement of the canopy stomatal resistance mechanism and the nitrogen-limiting schemes in Noah-MP-WDDM v1.42 give new options for simulating nitrogen dry deposition velocity. This study finds that the combined BN-23 mechanism agrees better with the observed NO2 dry deposition velocity, with the mean bias reduced by 50.1 %.
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Short summary
Measurements of size-resolved aerosols (0.25–18 μm) were conducted at three sites (urban, suburban and background sites) in southern China during monsoon season (May–June) in 2010 aqueous-phase reaction was the main formation pathway of droplet mode sulfate. New particle formation, chemical aging, and long-range transport from upwind urban or biomass burning regions were also found to be important in at least some of the sights on some of the sampling days.
Measurements of size-resolved aerosols (0.25–18 μm) were conducted at three sites (urban,...
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