Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1279-2023
© Author(s) 2023. 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-16-1279-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Mar 2023
Research article |
| 10 Mar 2023
| 10 Mar 2023
Typhoon-associated air quality over the Guangdong–Hong Kong–Macao Greater Bay Area, China: machine-learning-based prediction and assessment
Yilin Chen
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
Yuanjian Yang
CORRESPONDING AUTHOR
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
Related authors
No articles found.
Wanju Li, Lifang Sheng, Xueyan Bi, Zehao Huang, Yali Luo, Shiqi Xiao, Chao Liu, Yang Yang, Jiandong Wang, Yuanjian Yang, and Simone Lolli
EGUsphere, https://doi.org/10.5194/egusphere-2025-2955, https://doi.org/10.5194/egusphere-2025-2955, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study investigated the precursor factors of Warm-Sector Heavy Rainfall (WSHR) events in South China, which existed challenges in nowcasting and hazard warning. Four dynamical and thermodynamical indices were explored and tracked as precursor signals of WSHR, showing anomalous values in precursor signals are detected 1–4 hours preceding WSHR onset with regional heterogeneity. This research provides fundamental insights to enhance nowcasting and hazard warning for WSHR in South China.
Zhiheng Liao, Jinqiang Zhang, Meng Gao, and Zhiqiang Ma
Atmos. Chem. Phys., 25, 14865–14877, https://doi.org/10.5194/acp-25-14865-2025, https://doi.org/10.5194/acp-25-14865-2025, 2025
Short summary
Short summary
We present evidence for widespread stratospheric intrusion influence on surface ozone pollution from western plateaus to eastern plains over China in a deep trough event based on multi-site ozonesondes and validated ozone reanalysis. The findings refine the fundamental understanding of stratospheric ozone intrusion and its contribution to surface ozone pollution in China.
Yuanjian Yang, Chenjie Qian, Minxuan Zhang, Chenchao Zhan, Zhenxin Liu, Pak Wai Chan, Xueyan Bi, Meng Gao, and Simone Lolli
EGUsphere, https://doi.org/10.5194/egusphere-2025-4668, https://doi.org/10.5194/egusphere-2025-4668, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Up to ~ 40 % of ozone pollution in the Greater Bay Area of China is related to tropical cyclones. The O3 pollution was found to be transported from inland areas to coastal areas. The transport process can be roughly divided into three phases: downdraft control, horizontal transport, and vertical mixing.
Yunhua Chang, Tianhao Ding, Haifeng Yu, Yuanjian Yang, Liang Zhu, Xiaozheng Liu, and Wen Tan
EGUsphere, https://doi.org/10.5194/egusphere-2025-4515, https://doi.org/10.5194/egusphere-2025-4515, 2025
Short summary
Short summary
We validate a novel chemical ionization mass spectrometer for simultaneous measurements of volatile organic and inorganic compounds. A field comparison with a Cavity Ring-Down Spectroscopy analyzer for NH3 validated its accuracy and superior time resolution for capturing transient pollution peaks. Versatility is demonstrated across three key applications: stationary urban monitoring, mobile source mapping, and industrial process control.
Tao Shi, Yuanjian Yang, Gaopeng Lu, Zuofang Zheng, Yucheng Zi, Ye Tian, Lei Liu, and Simone Lolli
Atmos. Chem. Phys., 25, 9219–9234, https://doi.org/10.5194/acp-25-9219-2025, https://doi.org/10.5194/acp-25-9219-2025, 2025
Short summary
Short summary
The city significantly influences thunderstorm and lightning activity, yet the potential mechanisms remain largely unexplored. Our study has revealed that both city size and building density play pivotal roles in modulating thunderstorm and lightning activity. This research not only deepens our understanding of urban meteorology but also lays an important foundation for developing accurate and targeted urban thunderstorm risk prediction models.
Jialu Xu, Yingjie Zhang, Yuying Wang, Xing Yan, Bin Zhu, Chunsong Lu, Yuanjian Yang, Yele Sun, Junhui Zhang, Xiaofan Zuo, Zhanghanshu Han, and Rui Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3184, https://doi.org/10.5194/egusphere-2025-3184, 2025
Short summary
Short summary
We conducted a year-long study in Nanjing to explore how the height of the atmospheric boundary layer affects fine particle pollution. We found that low boundary layers in winter trap pollutants like nitrate and primary particles, while higher layers in summer help form secondary pollutants like sulfate and organic aerosols. These findings show that boundary layer dynamics are key to understanding and managing seasonal air pollution.
Junhui Zhang, Yuying Wang, Jialu Xu, Xiaofan Zuo, Chunsong Lu, Bin Zhu, Yuanjian Yang, Xing Yan, and Yele Sun
EGUsphere, https://doi.org/10.5194/egusphere-2025-3186, https://doi.org/10.5194/egusphere-2025-3186, 2025
Short summary
Short summary
We conducted a year-long study in Nanjing to understand how tiny airborne particles take up water, which affects air quality and climate. We found that particle water uptake varies by season and size, with lower values in summer due to more organic materials. Local pollution mainly influences smaller particles, while larger ones are shaped by air mass transport. These findings help improve climate models and support better air pollution control in fast-growing cities.
Tenglong Shi, Jiayao Wang, Daizhou Zhang, Jiecan Cui, Zihang Wang, Yue Zhou, Wei Pu, Yang Bai, Zhigang Han, Meng Liu, Yanbiao Liu, Hongbin Xie, Minghui Yang, Ying Li, Meng Gao, and Xin Wang
The Cryosphere, 19, 2821–2835, https://doi.org/10.5194/tc-19-2821-2025, https://doi.org/10.5194/tc-19-2821-2025, 2025
Short summary
Short summary
This study examines the properties of dust in snow in Changchun, China, using advanced technology to analyze its size, shape, and light absorption. We found that dust composition affects how much heat is absorbed by snow, with certain minerals, such as hematite, making snowmelt faster. Our research highlights the importance of creating clear standards for classifying dust, which could improve climate models and field observations. This work helps better understand dust's role in climate change.
Xiao Lu, Yiming Liu, Jiayin Su, Xiang Weng, Tabish Ansari, Yuqiang Zhang, Guowen He, Yuqi Zhu, Haolin Wang, Ganquan Zeng, Jingyu Li, Cheng He, Shuai Li, Teerachai Amnuaylojaroen, Tim Butler, Qi Fan, Shaojia Fan, Grant L. Forster, Meng Gao, Jianlin Hu, Yugo Kanaya, Mohd Talib Latif, Keding Lu, Philippe Nédélec, Peer Nowack, Bastien Sauvage, Xiaobin Xu, Lin Zhang, Ke Li, Ja-Ho Koo, and Tatsuya Nagashima
Atmos. Chem. Phys., 25, 7991–8028, https://doi.org/10.5194/acp-25-7991-2025, https://doi.org/10.5194/acp-25-7991-2025, 2025
Short summary
Short summary
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 that increases in anthropogenic emissions are the primary driver of ozone increases both in the free troposphere and at the surface.
Tao Shi, Yuanjian Yang, Ping Qi, and Simone Lolli
EGUsphere, https://doi.org/10.5194/egusphere-2025-2785, https://doi.org/10.5194/egusphere-2025-2785, 2025
Short summary
Short summary
Using Beijing’s Fifth Ring Road, the team combined data and models. Heatwave results: canopy heat island was 91.3 % stronger day/52.7 % night. Day heat relied on building coverage, night on sky visibility. Tall buildings block sun by day, trap heat at night. Night ventilation cools, day winds spread heat. Urban design must consider day-night cycles to fight extreme heat, guiding risk reduction.
Tao Shi, Yuanjian Yang, Lian Zong, Min Guo, Ping Qi, and Simone Lolli
Atmos. Chem. Phys., 25, 4989–5007, https://doi.org/10.5194/acp-25-4989-2025, https://doi.org/10.5194/acp-25-4989-2025, 2025
Short summary
Short summary
Our study explored the daily temperature patterns in urban areas of the Yangtze River Delta, focusing on how weather and human activities impact these patterns. We found that temperatures were higher at night, and weather patterns had a bigger impact during the day, while human activities mattered more at night. This helps us understand and address urban overheating.
Fengjiao Chen, Yuanjian Yang, Lu Yu, Yang Li, Weiguang Liu, Yan Liu, and Simone Lolli
Atmos. Chem. Phys., 25, 1587–1601, https://doi.org/10.5194/acp-25-1587-2025, https://doi.org/10.5194/acp-25-1587-2025, 2025
Short summary
Short summary
The microphysical mechanisms of precipitation responsible for the varied impacts of aerosol particles on shallow precipitation remain unclear. This study reveals that coarse aerosol particles invigorate shallow rainfall through enhanced coalescence processes, whereas fine aerosol particles suppress shallow rainfall through intensified microphysical breaks. These impacts are independent of thermodynamic environments but are more significant in low-humidity conditions.
Tao Shi, Yuanjian Yang, Ping Qi, and Simone Lolli
Atmos. Chem. Phys., 24, 12807–12822, https://doi.org/10.5194/acp-24-12807-2024, https://doi.org/10.5194/acp-24-12807-2024, 2024
Short summary
Short summary
This paper explored the formation mechanisms of the amplified canopy urban heat island intensity (ΔCUHII) during heat wave (HW) periods in the megacity of Beijing from the perspectives of mountain–valley breeze and urban morphology. During the mountain breeze phase, high-rise buildings with lower sky view factors (SVFs) had a pronounced effect on the ΔCUHII. During the valley breeze phase, high-rise buildings exerted a dual influence on the ΔCUHII.
Chaman Gul, Shichang Kang, Yuanjian Yang, Xinlei Ge, and Dong Guo
EGUsphere, https://doi.org/10.5194/egusphere-2024-1144, https://doi.org/10.5194/egusphere-2024-1144, 2024
Preprint archived
Short summary
Short summary
Long-term variations in upper atmospheric temperature and water vapor in the selected domains of time and space are presented. The temperature during the past two decades showed a cooling trend and water vapor showed an increasing trend and had an inverse relation with temperature in selected domains of space and time. Seasonal temperature variations are distinct, with a summer minimum and a winter maximum. Our results can be an early warning indication for future climate change.
Zhiheng Liao, Meng Gao, Jinqiang Zhang, Jiaren Sun, Jiannong Quan, Xingcan Jia, Yubing Pan, and Shaojia Fan
Atmos. Chem. Phys., 24, 3541–3557, https://doi.org/10.5194/acp-24-3541-2024, https://doi.org/10.5194/acp-24-3541-2024, 2024
Short summary
Short summary
This study collected 1897 ozonesondes from two Chinese megacities (Beijing and Hong Kong) in 2000–2022 to investigate the climatological vertical heterogeneity of lower-tropospheric ozone distribution with a mixing-layer-height-referenced (h-referenced) vertical coordinate system. This vertical coordinate system highlighted O3 stratification features existing at the mixing layer–free troposphere interface and provided a better understanding of O3 pollution in urban regions.
Yuan Wang, Qiangqiang Yuan, Tongwen Li, Yuanjian Yang, Siqin Zhou, and Liangpei Zhang
Earth Syst. Sci. Data, 15, 3597–3622, https://doi.org/10.5194/essd-15-3597-2023, https://doi.org/10.5194/essd-15-3597-2023, 2023
Short summary
Short summary
We propose a novel spatiotemporally self-supervised fusion method to establish long-term daily seamless global XCO2 and XCH4 products. Results show that the proposed method achieves a satisfactory accuracy that distinctly exceeds that of CAMS-EGG4 and is superior or close to those of GOSAT and OCO-2. In particular, our fusion method can effectively correct the large biases in CAMS-EGG4 due to the issues from assimilation data, such as the unadjusted anthropogenic emission for COVID-19.
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Yele Sun, Pingqing Fu, Meng Gao, Huangjian Wu, Miaomiao Lu, Qian Wu, Shuyuan Huang, Wenxuan Sui, Jie Li, Xiaole Pan, Lin Wu, Hajime Akimoto, and Gregory R. Carmichael
Atmos. Chem. Phys., 23, 6217–6240, https://doi.org/10.5194/acp-23-6217-2023, https://doi.org/10.5194/acp-23-6217-2023, 2023
Short summary
Short summary
A multi-air-pollutant inversion system has been developed in this study to estimate emission changes in China during COVID-19 lockdown. The results demonstrate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing by ~40 %. Emissions of other species only decreased by ~10 % due to smaller effects of lockdown on other sectors. Assessment results further indicate that the lockdown only had limited effects on the control of PM2.5 and O3 in China.
Peng Wang, Ruhan Zhang, Shida Sun, Meng Gao, Bo Zheng, Dan Zhang, Yanli Zhang, Gregory R. Carmichael, and Hongliang Zhang
Atmos. Chem. Phys., 23, 2983–2996, https://doi.org/10.5194/acp-23-2983-2023, https://doi.org/10.5194/acp-23-2983-2023, 2023
Short summary
Short summary
In China, the number of vehicles has jumped significantly in the last decade. This caused severe traffic congestion and aggravated air pollution. In this study, we developed a new temporal allocation approach to quantify the impacts of traffic congestion. We found that traffic congestion worsens air quality and the health burden across China, especially in the urban clusters. More effective and comprehensive vehicle emission control policies should be implemented to improve air quality in China.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
Short summary
Short summary
We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, https://doi.org/10.5194/acp-22-13753-2022, 2022
Short summary
Short summary
We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Fan Wang, Gregory R. Carmichael, Jing Wang, Bin Chen, Bo Huang, Yuguo Li, Yuanjian Yang, and Meng Gao
Atmos. Chem. Phys., 22, 13341–13353, https://doi.org/10.5194/acp-22-13341-2022, https://doi.org/10.5194/acp-22-13341-2022, 2022
Short summary
Short summary
Unprecedented urbanization in China has led to serious urban heat island (UHI) issues, exerting intense heat stress on urban residents. We find diverse influences of aerosol pollution on urban heat island intensity (UHII) under different circulations. Our results also highlight the role of black carbon in aggravating UHI, especially during nighttime. It could thus be targeted for cooperative management of heat islands and aerosol pollution.
Zexia Duan, Zhiqiu Gao, Qing Xu, Shaohui Zhou, Kai Qin, and Yuanjian Yang
Earth Syst. Sci. Data, 14, 4153–4169, https://doi.org/10.5194/essd-14-4153-2022, https://doi.org/10.5194/essd-14-4153-2022, 2022
Short summary
Short summary
Land–atmosphere interactions over the Yangtze River Delta (YRD) in China are becoming more varied and complex, as the area is experiencing rapid land use changes. In this paper, we describe a dataset of microclimate and eddy covariance variables at four sites in the YRD. This dataset has potential use cases in multiple research fields, such as boundary layer parametrization schemes, evaluation of remote sensing algorithms, and development of climate models in typical East Asian monsoon regions.
Bo Li, Cheng Liu, Qihou Hu, Mingzhai Sun, Chengxin Zhang, Shulin Zhang, Yizhi Zhu, Ting Liu, Yike Guo, Gregory R. Carmichael, and Meng Gao
EGUsphere, https://doi.org/10.5194/egusphere-2022-578, https://doi.org/10.5194/egusphere-2022-578, 2022
Preprint archived
Short summary
Short summary
Ambient particles have an important impact on human health, meteorology and climate change. By building a deep spatiotemporal neural network model we have overcome the long-standing limitations and get the full time and space coverage ground PM2.5 concentrations. We open the neural network black box data model by using sensitivity analysis and visualization techniques. This research will help improve health effects studies, climate effects of aerosols, and air quality prediction.
Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-187, https://doi.org/10.5194/essd-2022-187, 2022
Manuscript not accepted for further review
Short summary
Short summary
We develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O3 over 2005–2021 in China. It can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).
Lian Zong, Yuanjian Yang, Haiyun Xia, Meng Gao, Zhaobin Sun, Zuofang Zheng, Xianxiang Li, Guicai Ning, Yubin Li, and Simone Lolli
Atmos. Chem. Phys., 22, 6523–6538, https://doi.org/10.5194/acp-22-6523-2022, https://doi.org/10.5194/acp-22-6523-2022, 2022
Short summary
Short summary
Heatwaves (HWs) paired with higher ozone (O3) concentration at surface level pose a serious threat to human health. Taking Beijing as an example, three unfavorable synoptic weather patterns were identified to dominate the compound HW and O3 pollution events. Under the synergistic stress of HWs and O3 pollution, public mortality risk increased, and synoptic patterns and urbanization enhanced the compound risk of events in Beijing by 33.09 % and 18.95 %, respectively.
Shaohui Zhou, Yuanjian Yang, Zhiqiu Gao, Xingya Xi, Zexia Duan, and Yubin Li
Atmos. Meas. Tech., 15, 757–773, https://doi.org/10.5194/amt-15-757-2022, https://doi.org/10.5194/amt-15-757-2022, 2022
Short summary
Short summary
Our research has determined the possible relationship between Weibull natural wind mesoscale parameter c and shape factor k with height under the conditions of a desert steppe terrain in northern China, which has great potential in wind power generation. We have gained an enhanced understanding of the seasonal changes in the surface roughness of the desert grassland and the changes in the incoming wind direction.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Chengzhi Xing, Cheng Liu, Hongyu Wu, Jinan Lin, Fan Wang, Shuntian Wang, and Meng Gao
Earth Syst. Sci. Data, 13, 4897–4912, https://doi.org/10.5194/essd-13-4897-2021, https://doi.org/10.5194/essd-13-4897-2021, 2021
Short summary
Short summary
Observations of atmospheric composition, especially vertical profile observations, remain sparse and rare on the Tibetan Plateau (TP), due to extremely high altitude, topographical heterogeneity and the grinding environment. This paper introduces a high-time-resolution (~ 15 min) vertical profile observational dataset of atmospheric composition (aerosols, NO2, HCHO and HONO) on the TP for more than 1 year (2017–2019) using a passive remote sensing technique.
Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
Atmos. Chem. Phys., 21, 11405–11421, https://doi.org/10.5194/acp-21-11405-2021, https://doi.org/10.5194/acp-21-11405-2021, 2021
Short summary
Short summary
Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asian-Pacific Economic Cooperation (APEC) conference affect the mixing state and light absorption of BC and the associated implications for BC-PBL interactions.
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
Short summary
Short summary
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.
Yan Zhang, Yu Zhao, Meng Gao, Xin Bo, and Chris P. Nielsen
Atmos. Chem. Phys., 21, 6411–6430, https://doi.org/10.5194/acp-21-6411-2021, https://doi.org/10.5194/acp-21-6411-2021, 2021
Short summary
Short summary
We combined air quality and exposure response models to analyze the benefits for air quality and human health of China’s ultra-low emission policy in one of its most developed regions. Atmospheric observations and the air quality model were also used to demonstrate improvement of emission inventories incorporating online emission monitoring data. With implementation of the policy in both power and industrial sectors, the attributable deaths due to PM2.5 exposure are estimated to decrease 5.5 %.
Peter Sherman, Meng Gao, Shaojie Song, Alex T. Archibald, Nathan Luke Abraham, Jean-François Lamarque, Drew Shindell, Gregory Faluvegi, and Michael B. McElroy
Atmos. Chem. Phys., 21, 3593–3605, https://doi.org/10.5194/acp-21-3593-2021, https://doi.org/10.5194/acp-21-3593-2021, 2021
Short summary
Short summary
The aims here are to assess the role of aerosols in India's monsoon precipitation and to determine the relative contributions from Chinese and Indian emissions using CMIP6 models. We find that increased sulfur emissions reduce precipitation, which is primarily dynamically driven due to spatial shifts in convection over the region. A significant increase in precipitation (up to ~ 20 %) is found only when both Indian and Chinese sulfate emissions are regulated.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy
Atmos. Chem. Phys., 21, 457–481, https://doi.org/10.5194/acp-21-457-2021, https://doi.org/10.5194/acp-21-457-2021, 2021
Short summary
Short summary
We simulate the atmospheric chemical processes of an important sulfur-containing organic aerosol species, which is produced by the reaction between sulfur dioxide and formaldehyde. We can predict its distribution on a global scale. We find it is particularly rich in East Asia. This aerosol species is more abundant in the colder season partly because of weaker sunlight.
Cited articles
Arnold, J. R., Dennis, R. L., and Tonnesen, G. S.: Diagnostic evaluation of
numerical air quality models with specialized ambient observations: testing
the Community Multiscale Air Quality modeling system (CMAQ) at selected SOS
95 ground sites, Atmos. Environ., 37, 1185–1198,
https://doi.org/10.1016/S1352-2310(02)01008-7, 2003.
Bai, K., Li, K., Chang, N.-B., and Gao, W.: Advancing the prediction
accuracy of satellite-based PM2.5 concentration mapping: A perspective of data mining through in situ PM2.5 measurements, Environ. Pollut., 254, 113047, https://doi.org/10.1016/j.envpol.2019.113047, 2019.
Bochenek, B. and Ustrnul, Z.: Machine Learning in Weather Prediction and
Climate Analyses–Applications and Perspectives, Atmosphere, 13, 180,
https://doi.org/10.3390/atmos13020180, 2022.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Che, H., Xia, X., Zhu, J., Li, Z., Dubovik, O., Holben, B., Goloub, P., Chen, H., Estelles, V., Cuevas-Agulló, E., Blarel, L., Wang, H., Zhao, H., Zhang, X., Wang, Y., Sun, J., Tao, R., Zhang, X., and Shi, G.: Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements, Atmos. Chem. Phys., 14, 2125–2138, https://doi.org/10.5194/acp-14-2125-2014, 2014.
Che, H. Z., Shi, G. Y., Zhang, X. Y., Arimoto, R., Zhao, J. Q., Xu, L., Wang, B., and Chen, Z. H.: Analysis of 40 years of solar radiation data from
China, 1961–2000, Geophys. Res. Lett., 32, L06803, https://doi.org/10.1029/2004GL022322, 2005.
Chen, S., Yang, Y., Deng, F., Zhang, Y., Liu, D., Liu, C., and Gao, Z.: A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations, Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, 2022.
Chen, W., Wang, X., Cohen, J. B., Zhou, S., Zhang, Z., Chang, M., and Chan, C.-Y.: Properties of aerosols and formation mechanisms over southern China during the monsoon season, Atmos. Chem. Phys., 16, 13271–13289, https://doi.org/10.5194/acp-16-13271-2016, 2016.
Chen, Y.: Air quality data from the article “Typhoon associated air quality over the Guangdong-Hong Kong-Macao Greater Bay Area, China: machine-learning-based prediction and assessment”, Version 2, Zenodo [data set], https://doi.org/10.5281/zenodo.7451539, 2022.
Chow, E. C. H., Li, R. C. Y., and Zhou, W.: Influence of Tropical Cyclones
on Hong Kong Air Quality, Adv. Atmos. Sci., 35, 1177–1188,
https://doi.org/10.1007/s00376-018-7225-4, 2018.
Deng, T., Wang, T., Wang, S., Zou, Y., Yin, C., Li, F., Liu, L., Wang, N.,
Song, L., Wu, C., and Wu, D.: Impact of typhoon periphery on high ozone and
high aerosol pollution in the Pearl River Delta region, Sci. Total Environ.,
668, 617–630, https://doi.org/10.1016/j.scitotenv.2019.02.450, 2019.
Deng, X., Tie, X., Wu, D., Zhou, X., Bi, X., Tan, H., Li, F., and Jiang, C.:
Long-term trend of visibility and its characterizations in the Pearl River
Delta (PRD) region, China, Atmos. Environ., 42, 1424–1435,
https://doi.org/10.1016/j.atmosenv.2007.11.025, 2008.
Deng, X., Zhou, X., Wu, D., Tie, X., Tan, H., Li, F., Bi, X., Deng, T., and
Jiang, D.: Effect of atmospheric aerosol on surface ozone variation over the
Pearl River Delta region, Sci. China Earth Sci., 54, 744–752,
https://doi.org/10.1007/s11430-011-4172-7, 2011.
Ding, A., Wang, T., Zhao, M., Wang, T., and Li, Z.: Simulation of sea-land
breezes and a discussion of their implications on the transport of air
pollution during a multi-day ozone episode in the Pearl River Delta of
China, Atmos. Environ., 38, 6737–6750,
https://doi.org/10.1016/j.atmosenv.2004.09.017, 2004.
Ding, J., Dai, Q., Fan, W., Lu, M., Zhang, Y., Han, S., and Feng, Y.: Impact
of meteorology and precursor emission changes on O3 variation in Tianjin,
China from 2015 to 2021, J. Environ. Sci., S1001074222001267,
https://doi.org/10.1016/j.jes.2022.03.010, 2022.
Feng, Y., Wang, A., Wu, D., and Xu, X.: The influence of tropical cyclone
Melor on PM10 concentrations during an aerosol episode over the Pearl River Delta region of China: Numerical modeling versus observational analysis, Atmos. Environ., 41, 4349–4365,
https://doi.org/10.1016/j.atmosenv.2007.01.055, 2007.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2018a.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1959 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018b.
Hou, X., Chan, C. K., Dong, G. H., and Yim, S. H. L.: Impacts of
transboundary air pollution and local emissions on PM2.5 pollution in the Pearl River Delta region of China and the public health, and the policy
implications, Environ. Res. Lett., 14, 034005,
https://doi.org/10.1088/1748-9326/aaf493, 2019.
Hu, J., Pan, Y., He, Y., Chi, X., Zhang, Q., Song, T., and Shen, W.: Changes
in air pollutants during the COVID-19 lockdown in Beijing: Insights from a
machine-learning technique and implications for future control policy,
Atmospheric and Oceanic Science Letters, 14, 100060,
https://doi.org/10.1016/j.aosl.2021.100060, 2021.
Huang, J.-P., Fung, J. C. H., Lau, A. K. H., and Qin, Y.: Numerical
simulation and process analysis of typhoon-related ozone episodes in Hong
Kong, J. Geophys. Res.-Atmos., 110, D05301, https://doi.org/10.1029/2004JD004914, 2005.
Kamińska, J. A.: The use of random forests in modelling short-term air
pollution effects based on traffic and meteorological conditions: A case
study in Wrocław, J. Environ. Manage., 217, 164–174,
https://doi.org/10.1016/j.jenvman.2018.03.094, 2018.
Lam, K., Wang, T., Wu, C., and Li, Y.: Study on an ozone episode in hot
season in Hong Kong and transboundary air pollution over Pearl River Delta
region of China, Atmos. Environ., 39, 1967–1977,
https://doi.org/10.1016/j.atmosenv.2004.11.023, 2005.
Lam, Y. F., Cheung, H. M., and Ying, C. C.: Impact of tropical cyclone track
change on regional air quality, Sci. Total Environ., 610–611, 1347–1355,
https://doi.org/10.1016/j.scitotenv.2017.08.100, 2018.
Li, J., Wang, Z., Wang, X., Yamaji, K., Takigawa, M., Kanaya, Y., Pochanart,
P., Liu, Y., Irie, H., Hu, B., Tanimoto, H., and Akimoto, H.: Impacts of
aerosols on summertime tropospheric photolysis frequencies and
photochemistry over Central Eastern China, Atmos. Environ., 45, 1817–1829,
https://doi.org/10.1016/j.atmosenv.2011.01.016, 2011.
Li, X., Yang, Y., Mi, J., Bi, X., Zhao, Y., Huang, Z., Liu, C., Zong, L., and Li, W.: Leveraging machine learning for quantitative precipitation estimation from Fengyun-4 geostationary observations and ground meteorological measurements, Atmos. Meas. Tech., 14, 7007–7023, https://doi.org/10.5194/amt-14-7007-2021, 2021.
Liu, H., Yue, F., and Xie, Z.: Quantify the role of anthropogenic emission
and meteorology on air pollution using machine learning approach: A case
study of PM2.5 during the COVID-19 outbreak in Hubei Province, China,
Environ. Pollut., 300, 118932, https://doi.org/10.1016/j.envpol.2022.118932, 2022.
Lolli, S.: Is the Air Too Polluted for Outdoor Activities? Check by Using
Your Photovoltaic System as an Air-Quality Monitoring Device, Sensors, 21,
6342, https://doi.org/10.3390/s21196342, 2021.
Lolli, S., Madonna, F., Rosoldi, M., Campbell, J. R., Welton, E. J., Lewis, J. R., Gu, Y., and Pappalardo, G.: Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects, Atmos. Meas. Tech., 11, 1639–1651, https://doi.org/10.5194/amt-11-1639-2018, 2018.
Lu, R., Turco, R. P., and Jacobson, M. Z.: An integrated air pollution
modeling system for urban and regional scales: 2. Simulations for SCAQS
1987, J. Geophys. Res.-Atmos., 102, 6081–6098,
https://doi.org/10.1029/96JD03502, 1997.
Lu, X., Yu, H., Ying, M., Zhao, B., Zhang, S., Lin, L., Bai, L., and Wan,
R.: Western North Pacific Tropical Cyclone Database Created by the China
Meteorological Administration, Adv. Atmos. Sci., 38, 690–699,
https://doi.org/10.1007/s00376-020-0211-7, 2021 (data available at: https://tcdata.typhoon.org.cn/en/zjljsjj_zlhq.html, last access: 23 May 2022).
Luo, M., Hou, X., Gu, Y., Lau, N.-C., and Yim, S. H.-L.: Trans-boundary air
pollution in a city under various atmospheric conditions, Sci. Total
Environ., 618, 132–141, https://doi.org/10.1016/j.scitotenv.2017.11.001,
2018.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, É.: Scikit-learn: Machine learning in python, J. Mach. Learn. Res., 12, 2825–2830, 2011.
Ross, Z., Jerrett, M., Ito, K., Tempalski, B., and Thurston, G.: A land use
regression for predicting fine particulate matter concentrations in the New
York City region, Atmos. Environ., 41, 2255–2269,
https://doi.org/10.1016/j.atmosenv.2006.11.012, 2007.
Singh, K. P., Gupta, S., Kumar, A., and Shukla, S. P.: Linear and nonlinear
modeling approaches for urban air quality prediction, Sci. Total Environ.,
426, 244–255, https://doi.org/10.1016/j.scitotenv.2012.03.076, 2012.
Su, J. G., Jerrett, M., Beckerman, B., Wilhelm, M., Ghosh, J. K., and Ritz,
B.: Predicting traffic-related air pollution in Los Angeles using a distance
decay regression selection strategy, Environ. Res., 109, 657–670,
https://doi.org/10.1016/j.envres.2009.06.001, 2009.
Tong, C. H. M., Yim, S. H. L., Rothenberg, D., Wang, C., Lin, C.-Y., Chen,
Y. D., and Lau, N. C.: Assessing the impacts of seasonal and vertical
atmospheric conditions on air quality over the Pearl River Delta region,
Atmos. Environ., 180, 69–78, https://doi.org/10.1016/j.atmosenv.2018.02.039, 2018a.
Tong, C. H. M., Yim, S. H. L., Rothenberg, D., Wang, C., Lin, C.-Y., Chen,
Y. D., and Lau, N. C.: Projecting the impacts of atmospheric conditions
under climate change on air quality over the Pearl River Delta region,
Atmos. Environ., 193, 79–87, https://doi.org/10.1016/j.atmosenv.2018.08.053, 2018b.
Venter, Z. S., Chakraborty, T., and Lee, X.: Crowdsourced air temperatures
contrast satellite measures of the urban heat island and its mechanisms,
Sci. Adv., 7, eabb9569, https://doi.org/10.1126/sciadv.abb9569, 2021.
Wang, H., Li, J., Gao, Z., Yim, S. H. L., Shen, H., Ho, H. C., Li, Z., Zeng,
Z., Liu, C., Li, Y., Ning, G., and Yang, Y.: High-Spatial-Resolution
Population Exposure to PM2.5 Pollution Based on Multi-Satellite Retrievals: A Case Study of Seasonal Variation in the Yangtze River Delta, China in 2013, Remote Sens., 11, 2724, https://doi.org/10.3390/rs11232724, 2019.
Wang, N., Huang, X., Xu, J., Wang, T., Tan, Z., and Ding, A.:
Typhoon-boosted biogenic emission aggravates cross-regional ozone pollution
in China, Sci. Adv., 8, eabl6166, https://doi.org/10.1126/sciadv.abl6166, 2022.
Wei, X., Lam, K., Cao, C., Li, H., and He, J.: Dynamics of the Typhoon
Haitang Related High Ozone Episode over Hong Kong, Adv. Meteorol., 2016,
1–12, https://doi.org/10.1155/2016/6089154, 2016.
Wei, X. L., Li, Y. S., Lam, K. S., Wang, A. Y., and Wang, T. J.: Impact of
biogenic VOC emissions on a tropical cyclone-related ozone episode in the
Pearl River Delta region, China, Atmos. Environ., 41, 7851–7864,
https://doi.org/10.1016/j.atmosenv.2007.06.012, 2007.
Yang, J. X., Lau, A. K. H., Fung, J. C. H., Zhou, W., and Wenig, M.: An air
pollution episode and its formation mechanism during the tropical cyclone
Nuri's landfall in a coastal city of south China, Atmos. Environ., 54,
746–753, https://doi.org/10.1016/j.atmosenv.2011.12.023, 2012.
Yang, Y., Zheng, X., Gao, Z., Wang, H., Wang, T., Li, Y., Lau, G. N. C., and
Yim, S. H. L.: Long-Term Trends of Persistent Synoptic Circulation Events in
Planetary Boundary Layer and Their Relationships With Haze Pollution in
Winter Half Year Over Eastern China, J. Geophys. Res.-Atmos., 123,
10991–11007, https://doi.org/10.1029/2018JD028982, 2018.
Yang, Y., Yim, S. H. L., Haywood, J., Osborne, M., Chan, J. C. S., Zeng, Z.,
and Cheng, J. C. H.: Characteristics of Heavy Particulate Matter Pollution
Events Over Hong Kong and Their Relationships With Vertical Wind Profiles
Using High-Time-Resolution Doppler Lidar Measurements, J. Geophys. Res.-Atmos., 124, 9609–9623, https://doi.org/10.1029/2019JD031140, 2019.
Yang, Y., Fan, S., Wang, L., Gao, Z., Zhang, Y., Zou, H., Miao, S., Li, Y.,
Huang, M., Yim, S. H. L., and Lolli, S.: Diurnal Evolution of the Wintertime
Boundary Layer in Urban Beijing, China: Insights from Doppler Lidar and a
325-m Meteorological Tower, Remote Sensing, 12, 3935,
https://doi.org/10.3390/rs12233935, 2020a.
Yang, Y., Zhang, M., Li, Q., Chen, B., Gao, Z., Ning, G., Liu, C., Li, Y.,
and Luo, M.: Modulations of surface thermal environment and agricultural
activity on intraseasonal variations of summer diurnal temperature range in
the Yangtze River Delta of China, Sci. Total Environ., 736, 139445,
https://doi.org/10.1016/j.scitotenv.2020.139445, 2020b.
Yim, S. H. L., Wang, M., Gu, Y., Yang, Y., Dong, G., and Li, Q.: Effect of
Urbanization on Ozone and Resultant Health Effects in the Pearl River Delta
Region of China, J. Geophys. Res.-Atmos., 124, 11568–11579,
https://doi.org/10.1029/2019JD030562, 2019.
Ying, M., Zhang, W., Yu, H., Lu, X., Feng, J., Fan, Y., Zhu, Y., and Chen,
D.: An Overview of the China Meteorological Administration Tropical Cyclone
Database, J. Atmos. Ocean. Tech., 31, 287–301, https://doi.org/10.1175/JTECH-D-12-00119.1, 2014 (data available at: https://tcdata.typhoon.org.cn/en/zjljsjj_zlhq.html, last access: 23 May 2022).
Zeng, Z., Wang, Z., Gui, K., Yan, X., Gao, M., Luo, M., Geng, H., Liao, T.,
Li, X., An, J., Liu, H., He, C., Ning, G., and Yang, Y.: Daily Global Solar
Radiation in China Estimated From High-Density Meteorological Observations:
A Random Forest Model Framework, Earth. Space. Sci., 7, e2019EA001058,
https://doi.org/10.1029/2019EA001058, 2020.
Zhang, Y., Mao, H., Ding, A., Zhou, D., and Fu, C.: Impact of synoptic
weather patterns on spatio-temporal variation in surface O3 levels in Hong
Kong during 1999–2011, Atmos. Environ., 73, 41–50,
https://doi.org/10.1016/j.atmosenv.2013.02.047, 2013.
Zheng, L., Lin, R., Wang, X., and Chen, W.: The Development and Application
of Machine Learning in Atmospheric Environment Studies, Remote Sens., 13,
4839, https://doi.org/10.3390/rs13234839, 2021.
Zheng, Z., Zhao, C., Lolli, S., Wang, X., Wang, Y., Ma, X., Li, Q., and
Yang, Y.: Diurnal variation of summer precipitation modulated by air
pollution: observational evidences in the beijing metropolitan area,
Environ. Res. Lett., 15, 094053, https://doi.org/10.1088/1748-9326/ab99fc, 2020.
Zhu, C., Maharajan, K., Liu, K., and Zhang, Y.: Role of atmospheric
particulate matter exposure in COVID-19 and other health risks in human: A
review, Environ. Res., 198, 111281, https://doi.org/10.1016/j.envres.2021.111281, 2021.
Zong, L., Yang, Y., Gao, M., Wang, H., Wang, P., Zhang, H., Wang, L., Ning, G., Liu, C., Li, Y., and Gao, Z.: Large-scale synoptic drivers of co-occurring summertime ozone and PM2.5 pollution in eastern China, Atmos. Chem. Phys., 21, 9105–9124, https://doi.org/10.5194/acp-21-9105-2021, 2021.
Short summary
The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events related to typhoons. The present study leverages machine learning to predict typhoon-associated air quality over the area. The model evaluation shows that the model performs excellently. Moreover, the change in meteorological drivers of air quality on typhoon days and non-typhoon days suggests that air pollution control strategies should have different focuses on typhoon days and non-typhoon days.
The Guangdong–Hong Kong–Macao Greater Bay Area suffers from summertime air pollution events...
