Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7573-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7573-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
15 Dec 2021
Model evaluation paper |
| 15 Dec 2021
| 15 Dec 2021
High-resolution modeling of the distribution of surface air pollutants and their intercontinental transport by a global tropospheric atmospheric chemistry source–receptor model (GNAQPMS-SM)
Qian Ye
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy
of Sciences, Beijing 100049, China
Jie Li
CORRESPONDING AUTHOR
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy
of Sciences, Beijing 100049, China
Center for Excellence in Regional Atmospheric Environment, Institute
of Urban Environment, Chinese Academy of Science, Xiamen 361021, China
Xueshun Chen
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute
of Urban Environment, Chinese Academy of Science, Xiamen 361021, China
Huansheng Chen
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Wenyi Yang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute
of Urban Environment, Chinese Academy of Science, Xiamen 361021, China
Huiyun Du
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Xiaole Pan
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute
of Urban Environment, Chinese Academy of Science, Xiamen 361021, China
Xiao Tang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Center for Excellence in Regional Atmospheric Environment, Institute
of Urban Environment, Chinese Academy of Science, Xiamen 361021, China
Wei Wang
CORRESPONDING AUTHOR
China National Environmental Monitoring Center, Beijing 100012, China
Lili Zhu
China National Environmental Monitoring Center, Beijing 100012, China
Jianjun Li
CORRESPONDING AUTHOR
China National Environmental Monitoring Center, Beijing 100012, China
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Zifa Wang
CORRESPONDING AUTHOR
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy
of Sciences, Beijing 100049, China
Center for Excellence in Regional Atmospheric Environment, Institute
of Urban Environment, Chinese Academy of Science, Xiamen 361021, China
Related authors
No articles found.
Yali Jin, Hao Luo, Siqi Tang, Shuhui Xue, Chengyu Nie, Xiaocong Peng, Yan Zheng, Weiqi Xu, Guohua Zhang, Xiaole Pan, Yele Sun, Qi Chen, Lanzhong Liu, and Defeng Zhao
Atmos. Chem. Phys., 26, 2813–2830, https://doi.org/10.5194/acp-26-2813-2026, https://doi.org/10.5194/acp-26-2813-2026, 2026
Short summary
Short summary
Cloud substantially changes the compositions organic aerosol. How cloud processing of organics occur on molecular level remains unclear. We found that compared with cloud free particles, organics in cloud contains more large molecules likely due to accretion reactions and has more nitrogen-containing compounds. We identify some new compounds formed in cloud. Such modifications of the organics in cloud can further change its physicochemical properties, and impact on climate and human health.
Wei Zhou, Liu Yang, Siqi Zeng, Yunping Kan, Lirong Yang, Weihong Zhang, Weijie Wang, Zijun Zhang, Yan Li, Weiqi Xu, Yucheng Gu, Yaozong Wang, Zhengyan Zuo, Jie Li, Zifa Wang, and Yele Sun
Atmos. Chem. Phys., 26, 2425–2441, https://doi.org/10.5194/acp-26-2425-2026, https://doi.org/10.5194/acp-26-2425-2026, 2026
Short summary
Short summary
Northwest China, situated in an arid and semi-arid climate region; air quality issues in this area have received less attention compared to other Chinese metropolitan clusters. This research identify a significant shift towards the coupling PM2.5 and O3 relationships over the past decade in northwest China, highlighting the great importance of urban terpenes and aromatic oxidation in secondary organic aerosol formation.
Shengxuan Ji, Yawei Qu, Cheng Yuan, Tijian Wang, Bing Liu, Lili Zhu, Huihui Zheng, Zhenfeng Qiu, and Pulong Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-5589, https://doi.org/10.5194/egusphere-2025-5589, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This study introduces BiXiao, an artificial intelligence model that forecasts air pollution by combining weather data and observations from monitoring stations. Tested in northern China, BiXiao can produce city-scale air-quality forecasts within seconds and is more accurate than traditional numerical models. The work shows how artificial intelligence can enhance environmental forecasting and support cleaner air and public health.
Weibin Zhu, Sai Shang, Jieqi Wang, Yunfei Wu, Zhaoze Deng, Liang Ran, Ye Kuang, Guiqian Tang, Xiangpeng Huang, Xiaole Pan, Lanzhong Liu, Weiqi Xu, Yele Sun, Bo Hu, Zifa Wang, and Zirui Liu
Atmos. Chem. Phys., 26, 1947–1965, https://doi.org/10.5194/acp-26-1947-2026, https://doi.org/10.5194/acp-26-1947-2026, 2026
Short summary
Short summary
NPF (new particle formation) is a key global CCN (cloud condensation nuclei) source, but its contribution at the polluted boundary-layer top remains unclear. Based on mountaintop observations in the Yangtze River Delta, we show that under polluted conditions, NPF at the boundary-layer top is enhanced and accelerates its conversion to CCN. Ammonia plays a key role, and a newly defined "Time Window" metric highlights the importance of oxidation-driven growth and regional transport in this process.
Yi Zhang, Weiqi Xu, Yan Li, Guohua Zhang, Dantong Liu, Ye Kuang, Yu Zhang, Wei Zhou, Xiaocong Peng, Bojiang Su, Weihong Huang, Zijun Zhang, Liu Yang, Yangzhou Wu, Siyuan Li, Shitong Zhao, Lanzhong Liu, Xiaole Pan, Zifa Wang, Xinhui Bi, Mikael Ehn, Douglas R. Worsnop, and Yele Sun
EGUsphere, https://doi.org/10.5194/egusphere-2025-5835, https://doi.org/10.5194/egusphere-2025-5835, 2025
Short summary
Short summary
This study explores how clouds influence the chemical composition of air particles through field research at a high-altitude station in southeastern China across different seasons. We found that different cloud types cause varying degrees of chemical changes in these particles. These findings enhance our understanding of the impact of clouds on air quality and contribute to improving climate models.
Yutong Tian, Ting Yang, Hongyi Li, Ping Tian, Yifan Song, Jiancun He, Yining Tan, Yele Sun, and Zifa Wang
Atmos. Chem. Phys., 25, 17581–17594, https://doi.org/10.5194/acp-25-17581-2025, https://doi.org/10.5194/acp-25-17581-2025, 2025
Short summary
Short summary
This study examines how nitrate pollution varies with height and season to combat urban haze. Nitrate levels peak near the ground in spring/winter due to humidity and temperature, while wind and sunlight drive high-altitude pollution in late autumn. Winter shows unique daytime peaks linked to sunlight and nighttime chemistry. Findings help cities design targeted strategies, like timing emissions cuts, to improve air quality by addressing pollution at specific heights and times.
Mengjie Lou, Qizhong Wu, Wending Wang, Huansheng Chen, Kai Cao, Xiaohan Fan, Dingyue Liang, Fenfen Yu, Jiating Zhang, Wei Wang, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4441, https://doi.org/10.5194/egusphere-2025-4441, 2025
Short summary
Short summary
This study compares the performance of the independently developed EPICC-Model with CAMx and CMAQ in simulating PM2.5 and O3 in China. It finds that EPICC-Model excels in simulating summer ozone peaks, accurately captures pollution characteristics in highly polluted areas, and better reproduces persistent compound pollution processes. Furthermore, this study reveals common issues among the models and directions for improvement, providing a basis for optimizing global air quality models.
Fei Zhang, Xingcai Li, Zifa Wang, Yunyun Wen, Xuyang Zhou, Zichen Wu, Zhuoran Wang, Huansheng Chen, Zhe Wang, and Xueshun Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-4439, https://doi.org/10.5194/egusphere-2025-4439, 2025
Short summary
Short summary
Solar power generation depends on weather conditions and photovoltaic modules, making accurate forecasts crucial for reliable grid operation. We combined weather prediction and artificial intelligence to improve the solar power prediction at different time scales for a plant. By improving sunlight predictions and incorporating physical constraints into the model, our approach reduced errors significantly. This can help integrate clean energy into power grids safely and efficiently.
Kai Cao, Qizhong Wu, Xiao Tang, Jinxi Li, Xueshun Chen, Huansheng Chen, Wending Wang, Huangjian Wu, Lei Kong, Jie Li, Jiang Zhu, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-2918, https://doi.org/10.5194/egusphere-2025-2918, 2025
Short summary
Short summary
This study achieves significant acceleration by developing an optimized advection module for Emission and atmospheric Processes Integrated and Coupled Community Model on GPU-like accelerators. Through implementing thread-block coordinated indexing, minimizing CPU-GPU communication, and an hybrid parallelization framework, we demonstrate prominent speedups: 556.5× faster offline performance for the Heterogeneous Interface PPM solver and 20.5× acceleration in coupled simulations.
Hongyi Li, Ting Yang, Yele Sun, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4237, https://doi.org/10.5194/egusphere-2025-4237, 2025
Short summary
Short summary
To precisely obtain the vertical profiles of PM2.5 chemical components, we developed a physics-constrained deep-learning retrieval framework through a long-term lidar data training, which extends the component types identified by traditional remote-sensing retrieval algorithms. Observational verifications at varying altitudes indicate that our retrieval framework can accurately interpret the evolutions and vertical distributions of components with robust spatiotemporal expandability.
Hongyi Li, Ting Yang, Lei Kong, Di Zhang, Guigang Tang, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3960, https://doi.org/10.5194/egusphere-2025-3960, 2025
Short summary
Short summary
Chemical transport model-based data assimilation is computationally inefficient for large ensemble sizes and offers limited improvements in forecasting PM2.5 chemical components. This paper introduces a machine learning-based data assimilation system that facilitates rapid iterations for forecasting, assimilation, and incremental learning. Results show that our system achieves superior efficiency and accuracy in forecasting and assimilation compared to traditional data assimilation.
Xi Chen, Ke Li, Ting Yang, Xipeng Jin, Lei Chen, Yang Yang, Shuman Zhao, Bo Hu, Bin Zhu, Zifa Wang, and Hong Liao
Atmos. Chem. Phys., 25, 9151–9168, https://doi.org/10.5194/acp-25-9151-2025, https://doi.org/10.5194/acp-25-9151-2025, 2025
Short summary
Short summary
Aerosol vertical distribution that plays a crucial role in aerosol–photolysis interaction (API) remains underrepresented in chemical models. We integrated lidar and radiosonde observations to constrain the simulated aerosol profiles over North China and quantified the photochemical responses. The increased photolysis rates in the lower layers led to increased ozone and accounted for a 36 %–56 % reduction in API effects, resulting in enhanced atmospheric oxidizing capacity and aerosol formation.
Huiyun Du, Jie Li, Xueshun Chen, Gabriele Curci, Fangqun Yu, Yele Sun, Xu Dao, Song Guo, Zhe Wang, Wenyi Yang, Lianfang Wei, and Zifa Wang
Atmos. Chem. Phys., 25, 5665–5681, https://doi.org/10.5194/acp-25-5665-2025, https://doi.org/10.5194/acp-25-5665-2025, 2025
Short summary
Short summary
Inadequate consideration of mixing states and coatings on black carbon (BC) hinders aerosol radiation forcing quantification. Core–shell mixing aligns well with observations, but partial internal mixing is a more realistic representation. We used a microphysics module to determine the fraction of embedded BC and coating aerosols, constraining the mixing state. This reduced absorption enhancement by 30 %–43 % in northern China, offering insights into BC's radiative effects.
Dylan Jones, Lucas Prates, Zhen Qu, William Cheng, Kazuyuki Miyazaki, Takashi Sekiya, Antje Inness, Rajesh Kumar, Xiao Tang, Helen Worden, Gerbrand Koren, and Vincent Huijen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3759, https://doi.org/10.5194/egusphere-2024-3759, 2025
Short summary
Short summary
We evaluate five chemical reanalysis products to assess their potential to provide useful information on tropospheric ozone variability. We find that the reanalyses produce consistent information on ozone variations in the free troposphere, but have large discrepancies at the surface. The results suggests that improvements in the reanalyses are needed to better exploit the assimilated observations to enhance the utility of the reanalysis products at the surface.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
Lei Kong, Xiao Tang, Zifa Wang, Jiang Zhu, Jianjun Li, Huangjian Wu, Qizhong Wu, Huansheng Chen, Lili Zhu, Wei Wang, Bing Liu, Qian Wang, Duohong Chen, Yuepeng Pan, Jie Li, Lin Wu, and Gregory R. Carmichael
Earth Syst. Sci. Data, 16, 4351–4387, https://doi.org/10.5194/essd-16-4351-2024, https://doi.org/10.5194/essd-16-4351-2024, 2024
Short summary
Short summary
A new long-term inversed emission inventory for Chinese air quality (CAQIEI) is developed in this study, which contains constrained monthly emissions of NOx, SO2, CO, PM2.5, PM10, and NMVOCs in China from 2013 to 2020 with a horizontal resolution of 15 km. Emissions of different air pollutants and their changes during 2013–2020 were investigated and compared with previous emission inventories, which sheds new light on the complex variations of air pollutant emissions in China.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
Short summary
Short summary
AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Zijun Zhang, Weiqi Xu, Yi Zhang, Wei Zhou, Xiangyu Xu, Aodong Du, Yinzhou Zhang, Hongqin Qiao, Ye Kuang, Xiaole Pan, Zifa Wang, Xueling Cheng, Lanzhong Liu, Qingyan Fu, Douglas R. Worsnop, Jie Li, and Yele Sun
Atmos. Chem. Phys., 24, 8473–8488, https://doi.org/10.5194/acp-24-8473-2024, https://doi.org/10.5194/acp-24-8473-2024, 2024
Short summary
Short summary
We investigated aerosol composition and sources and the interaction between secondary organic aerosol (SOA) and clouds at a regional mountain site in southeastern China. Clouds efficiently scavenge more oxidized SOA; however, cloud evaporation leads to the production of less oxidized SOA. The unexpectedly high presence of nitrate in aerosol particles indicates that nitrate formed in polluted areas has undergone interactions with clouds, significantly influencing the regional background site.
Zhiqiang Zhang, Ying Li, Haiyan Ran, Junling An, Yu Qu, Wei Zhou, Weiqi Xu, Weiwei Hu, Hongbin Xie, Zifa Wang, Yele Sun, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 4809–4826, https://doi.org/10.5194/acp-24-4809-2024, https://doi.org/10.5194/acp-24-4809-2024, 2024
Short summary
Short summary
Secondary organic aerosols (SOAs) can exist in liquid, semi-solid, or amorphous solid states, which are rarely accounted for in current chemical transport models. We predict the phase state of SOA particles over China and find that in northwestern China SOA particles are mostly highly viscous or glassy solid. Our results indicate that the particle phase state should be considered in SOA formation in chemical transport models for more accurate prediction of SOA mass concentrations.
Aodong Du, Jiaxing Sun, Hang Liu, Weiqi Xu, Wei Zhou, Yuting Zhang, Lei Li, Xubing Du, Yan Li, Xiaole Pan, Zifa Wang, and Yele Sun
Atmos. Chem. Phys., 23, 13597–13611, https://doi.org/10.5194/acp-23-13597-2023, https://doi.org/10.5194/acp-23-13597-2023, 2023
Short summary
Short summary
We characterized the impacts of emission controls on particle mixing state and density during the Beijing Olympic Winter Games using a SPAMS in tandem with a DMA and an AAC. OC and sulfate-containing particles increased, while those from primary emissions decreased. The effective particle densities increased and varied largely for different particles, highlighting the impacts of aging and formation processes on the changes of particle density and mixing state.
Tao Wang, Hang Liu, Jie Li, Shuai Wang, Youngseob Kim, Yele Sun, Wenyi Yang, Huiyun Du, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, https://doi.org/10.5194/gmd-16-5585-2023, 2023
Short summary
Short summary
This paper developed a two-way coupled module in a new version of a regional urban–street network model, IAQMS-street v2.0, in which the mass flux from streets to background is considered. Test cases are defined to evaluate the performance of IAQMS-street v2.0 in Beijing by comparing it with that simulated by IAQMS-street v1.0 and a regional model. The contribution of local emissions and the influence of on-road vehicle control measures on air quality are evaluated by using IAQMS-street v2.0.
Xi Chen, Ting Yang, Zifa Wang, Futing Wang, and Haibo Wang
Atmos. Meas. Tech., 16, 4289–4302, https://doi.org/10.5194/amt-16-4289-2023, https://doi.org/10.5194/amt-16-4289-2023, 2023
Short summary
Short summary
Uncertainties remain great in the planetary boundary layer height (PBLH) determination from radiosonde, especially during the transition period of different PBL regimes. We combine seven existing methods along with statistical modification on gradient-based methods. We find that the ensemble method can eliminate the overestimation of PBLH and reduce the inconsistency between individual methods. The ensemble method improves the effectiveness of PBLH determination to 62.6 %.
Kai Cao, Qizhong Wu, Lingling Wang, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongqing Li, and Lanning Wang
Geosci. Model Dev., 16, 4367–4383, https://doi.org/10.5194/gmd-16-4367-2023, https://doi.org/10.5194/gmd-16-4367-2023, 2023
Short summary
Short summary
Offline performance experiment results show that the GPU-HADVPPM on a V100 GPU can achieve up to 1113.6 × speedups to its original version on an E5-2682 v4 CPU. A series of optimization measures are taken, and the CAMx-CUDA model improves the computing efficiency by 128.4 × on a single V100 GPU card. A parallel architecture with an MPI plus CUDA hybrid paradigm is presented, and it can achieve up to 4.5 × speedup when launching eight CPU cores and eight GPU cards.
Lichao Yang, Wansuo Duan, and Zifa Wang
Geosci. Model Dev., 16, 3827–3848, https://doi.org/10.5194/gmd-16-3827-2023, https://doi.org/10.5194/gmd-16-3827-2023, 2023
Short summary
Short summary
An approach is proposed to refine a ground meteorological observation network to improve the PM2.5 forecasts in the Beijing–Tianjin–Hebei region. A cost-effective observation network is obtained and makes the relevant PM2.5 forecasts assimilate fewer observations but achieve the forecasting skill comparable to or higher than that obtained by assimilating all ground station observations, suggesting that many of the current ground stations can be greatly scattered to avoid much unnecessary work.
Hang Liu, Xiaole Pan, Shandong Lei, Yuting Zhang, Aodong Du, Weijie Yao, Guiqian Tang, Tao Wang, Jinyuan Xin, Jie Li, Yele Sun, Junji Cao, and Zifa Wang
Atmos. Chem. Phys., 23, 7225–7239, https://doi.org/10.5194/acp-23-7225-2023, https://doi.org/10.5194/acp-23-7225-2023, 2023
Short summary
Short summary
We provide the average vertical profiles of black carbon (BC) concentration, size distribution and coating thickness at different times of the day in an urban area based on 112 vertical profiles. In addition, it is found that BC in the residual layer generally has a thicker coating, higher absorption enhancement and hygroscopicity than on the surface. Such aged BC could enter into the boundary layer and influence the BC properties in the early morning.
Wen Lu, Bin Zhu, Shuqi Yan, Jie Li, and Zifa Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1089, https://doi.org/10.5194/egusphere-2023-1089, 2023
Preprint archived
Short summary
Short summary
Parameterized the minimum turbulent diffusivity (Kzmin) by sensible heat flux and latent heat flux and embedded it into the WRF-Chem model. New scheme improved the underestimation of turbulence diffusion underestimation and overestimation of surface PM2.5 under stable boundary layer simulation over eastern China. The physical relationship between Kzmin and two factors was discussed. Process analysis showed that vertical mixing is the key process to improve surface PM2.5 simulations.
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.
Junhua Wang, Baozhu Ge, Xueshun Chen, Jie Li, Keding Lu, Yayuan Dong, Lei Kong, Zifa Wang, and Yuanhang Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-22, https://doi.org/10.5194/gmd-2023-22, 2023
Revised manuscript not accepted
Short summary
Short summary
We developed a quantitative decoupling analysis (QDA) method to quantify the contributions of emissions, meteorology, chemical reactions, and their nonlinear interactions on PM2.5. We found the effects of adverse meteorological conditions and the importance of nonlinear interactions. This method can provide valuable information for understanding of key factors to heavy pollution, but also help the modelers to find out the sources of uncertainties in numerical models.
Shujun Zhong, Shuang Chen, Junjun Deng, Yanbing Fan, Qiang Zhang, Qiaorong Xie, Yulin Qi, Wei Hu, Libin Wu, Xiaodong Li, Chandra Mouli Pavuluri, Jialei Zhu, Xin Wang, Di Liu, Xiaole Pan, Yele Sun, Zifa Wang, Yisheng Xu, Haijie Tong, Hang Su, Yafang Cheng, Kimitaka Kawamura, and Pingqing Fu
Atmos. Chem. Phys., 23, 2061–2077, https://doi.org/10.5194/acp-23-2061-2023, https://doi.org/10.5194/acp-23-2061-2023, 2023
Short summary
Short summary
This study investigated the role of the secondary organic aerosol (SOA) loading on the molecular composition of wintertime urban aerosols by ultrahigh-resolution mass spectrometry. Results demonstrate that the SOA loading is an important factor associated with the oxidation degree, nitrate group content, and chemodiversity of nitrooxy–organosulfates. Our study also found that the hydrolysis of nitrooxy–organosulfates is a possible pathway for the formation of organosulfates.
Futing Wang, Ting Yang, Zifa Wang, Haibo Wang, Xi Chen, Yele Sun, Jianjun Li, Guigang Tang, and Wenxuan Chai
Atmos. Meas. Tech., 15, 6127–6144, https://doi.org/10.5194/amt-15-6127-2022, https://doi.org/10.5194/amt-15-6127-2022, 2022
Short summary
Short summary
We develop a new algorithm to get the vertical mass concentration profiles of fine aerosol components based on the synergy of ground-based remote sensing for the first time. The comparisons with in situ observations and chemistry transport models validate the performance of the algorithm. Uncertainties caused by input parameters are also assessed in this paper. We expected that the algorithm can provide a new idea for lidar inversion and promote the development of aerosol component profiles.
Lichao Yang, Wansuo Duan, Zifa Wang, and Wenyi Yang
Atmos. Chem. Phys., 22, 11429–11453, https://doi.org/10.5194/acp-22-11429-2022, https://doi.org/10.5194/acp-22-11429-2022, 2022
Short summary
Short summary
The initial meteorological state has a great impact on PM2.5 forecasts. Assimilating additional observations is an effective way to improve the accuracy of the initial meteorological state. Here we used an advanced optimization approach to identify where we should preferentially place the meteorological observations associated with PM2.5 forecasts in the Beijing–Tianjin–Hebei region of China. We provide evidence that the target observation strategy is effective for improving PM2.5 forecasts.
Zhiqiang Zhang, Yele Sun, Chun Chen, Bo You, Aodong Du, Weiqi Xu, Yan Li, Zhijie Li, Lu Lei, Wei Zhou, Jiaxing Sun, Yanmei Qiu, Lianfang Wei, Pingqing Fu, and Zifa Wang
Atmos. Chem. Phys., 22, 10409–10423, https://doi.org/10.5194/acp-22-10409-2022, https://doi.org/10.5194/acp-22-10409-2022, 2022
Short summary
Short summary
We present a comprehensive characterization of water-soluble organic aerosol and the first mass spectral characterization of water-insoluble organic aerosol in the cold season in Beijing by integrating online and offline aerosol mass spectrometer measurements. WSOA comprised dominantly secondary OA and showed large changes during the transition season from autumn to winter. WIOA was characterized by prominent hydrocarbon ions series, low oxidation states, and significant day–night differences.
Jiaxing Sun, Yele Sun, Conghui Xie, Weiqi Xu, Chun Chen, Zhe Wang, Lei Li, Xubing Du, Fugui Huang, Yan Li, Zhijie Li, Xiaole Pan, Nan Ma, Wanyun Xu, Pingqing Fu, and Zifa Wang
Atmos. Chem. Phys., 22, 7619–7630, https://doi.org/10.5194/acp-22-7619-2022, https://doi.org/10.5194/acp-22-7619-2022, 2022
Short summary
Short summary
We analyzed the chemical composition and mixing state of BC-containing particles at urban and rural sites in winter in the North China Plain and evaluated their impact on light absorption enhancement. BC was dominantly mixed with organic carbon, nitrate, and sulfate, and the mixing state evolved significantly as a function of relative humidity (RH) at both sites. The absorption enhancement depended strongly on coated secondary inorganic aerosol and was up to ~1.3–1.4 during aging processes.
Zixuan Jia, Ruth M. Doherty, Carlos Ordóñez, Chaofan Li, Oliver Wild, Shipra Jain, and Xiao Tang
Atmos. Chem. Phys., 22, 6471–6487, https://doi.org/10.5194/acp-22-6471-2022, https://doi.org/10.5194/acp-22-6471-2022, 2022
Short summary
Short summary
This study investigates the modulation of daily PM2.5 over three major populated regions in China by regional meteorology and large-scale circulation during winter. These results demonstrate the benefits of considering the large-scale circulation for air quality studies. The novel circulation indices proposed here can explain a considerable fraction of the day-to-day variability of PM2.5 and can be combined with regional meteorology to improve our capability to predict the variability of PM2.5.
Junjun Deng, Hao Ma, Xinfeng Wang, Shujun Zhong, Zhimin Zhang, Jialei Zhu, Yanbing Fan, Wei Hu, Libin Wu, Xiaodong Li, Lujie Ren, Chandra Mouli Pavuluri, Xiaole Pan, Yele Sun, Zifa Wang, Kimitaka Kawamura, and Pingqing Fu
Atmos. Chem. Phys., 22, 6449–6470, https://doi.org/10.5194/acp-22-6449-2022, https://doi.org/10.5194/acp-22-6449-2022, 2022
Short summary
Short summary
Light-absorbing brown carbon (BrC) plays an important role in climate change and atmospheric chemistry. Here we investigated the seasonal and diurnal variations in water-soluble BrC in PM2.5 in the megacity Tianjin in coastal China. Results of the source apportionments from the combination with organic molecular compositions and optical properties of water-soluble BrC reveal a large contribution from primary bioaerosol particles to BrC in the urban atmosphere.
Haibo Wang, Ting Yang, Zifa Wang, Jianjun Li, Wenxuan Chai, Guigang Tang, Lei Kong, and Xueshun Chen
Geosci. Model Dev., 15, 3555–3585, https://doi.org/10.5194/gmd-15-3555-2022, https://doi.org/10.5194/gmd-15-3555-2022, 2022
Short summary
Short summary
In this paper, we develop an online data coupled assimilation system (NAQPMS-PDAF) with the Eulerian atmospheric chemistry-transport model. NAQPMS-PDAF allows efficient use of large computational resources. The application and performance of the system are investigated by assimilating 1 month of vertical aerosol observations. The results show that NAQPMS-PDAF can significantly improve the performance of aerosol vertical structure simulation and reduce the uncertainty to a large extent.
Jiaxing Sun, Zhe Wang, Wei Zhou, Conghui Xie, Cheng Wu, Chun Chen, Tingting Han, Qingqing Wang, Zhijie Li, Jie Li, Pingqing Fu, Zifa Wang, and Yele Sun
Atmos. Chem. Phys., 22, 561–575, https://doi.org/10.5194/acp-22-561-2022, https://doi.org/10.5194/acp-22-561-2022, 2022
Short summary
Short summary
We analyzed 9-year measurements of BC and aerosol optical properties from 2012 to 2020 in Beijing, China. Our results showed large reductions in BC and light extinction coefficient due to the Clean Air Action Plan. As a response, both SSA and mass extinction efficiency (MEE) showed considerable increases, demonstrating a future challenge in visibility improvement. The primary and secondary BrC was also separated and quantified, and the changes in radiative forcing of BC and BrC were estimated.
Yuting Zhang, Hang Liu, Shandong Lei, Wanyun Xu, Yu Tian, Weijie Yao, Xiaoyong Liu, Qi Liao, Jie Li, Chun Chen, Yele Sun, Pingqing Fu, Jinyuan Xin, Junji Cao, Xiaole Pan, and Zifa Wang
Atmos. Chem. Phys., 21, 17631–17648, https://doi.org/10.5194/acp-21-17631-2021, https://doi.org/10.5194/acp-21-17631-2021, 2021
Short summary
Short summary
In this study, the authors used a single-particle soot photometer (SP2) to characterize the particle size, mixing state, and optical properties of black carbon aerosols in rural areas of the North China Plain in winter. Relatively warm and high-RH environments (RH > 50 %, −4° < T < 4 °) were more favorable to rBC aging than dry and cold environments (RH < 60 %, T < −8°). The paper emphasizes the importance of meteorological parameters in the mixing state of black carbon.
Hong Ren, Wei Hu, Lianfang Wei, Siyao Yue, Jian Zhao, Linjie Li, Libin Wu, Wanyu Zhao, Lujie Ren, Mingjie Kang, Qiaorong Xie, Sihui Su, Xiaole Pan, Zifa Wang, Yele Sun, Kimitaka Kawamura, and Pingqing Fu
Atmos. Chem. Phys., 21, 12949–12963, https://doi.org/10.5194/acp-21-12949-2021, https://doi.org/10.5194/acp-21-12949-2021, 2021
Short summary
Short summary
This study presents vertical profiles of biogenic and anthropogenic secondary organic aerosols (SOAs) in the urban boundary layer based on a 325 m tower in Beijing in late summer. The increases in the isoprene and toluene SOAs with height were found to be more related to regional transport, whereas the decrease in those from monoterpenes and sesquiterpene were more subject to local emissions. Such complicated vertical distributions of SOA should be considered in future modeling work.
Junhua Wang, Baozhu Ge, Xueshun Chen, Jie Li, Keding Lu, Yayuan Dong, Lei Kong, Zifa Wang, and Yuanhang Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-259, https://doi.org/10.5194/gmd-2021-259, 2021
Revised manuscript not accepted
Short summary
Short summary
This paper developed a novel quantitative decoupling analysis (QDA) method to quantify the contributions of emission, meteorology, chemical reaction, and their nonlinear interactions on PM2.5 and applied it to a pollution episode in Beijing. This method can provides the researchers and policy makers with valuable information for understanding of key factors to heavy pollution, but also help the modelers to find out the sources of uncertainties among numerical models.
Qiaorong Xie, Sihui Su, Jing Chen, Yuqing Dai, Siyao Yue, Hang Su, Haijie Tong, Wanyu Zhao, Lujie Ren, Yisheng Xu, Dong Cao, Ying Li, Yele Sun, Zifa Wang, Cong-Qiang Liu, Kimitaka Kawamura, Guibin Jiang, Yafang Cheng, and Pingqing Fu
Atmos. Chem. Phys., 21, 11453–11465, https://doi.org/10.5194/acp-21-11453-2021, https://doi.org/10.5194/acp-21-11453-2021, 2021
Short summary
Short summary
This study investigated the role of nighttime chemistry during Chinese New Year's Eve that enhances the formation of nitrooxy organosulfates in the aerosol phase. Results show that anthropogenic precursors, together with biogenic ones, considerably contribute to the formation of low-volatility nitrooxy OSs. Our study provides detailed molecular composition of firework-related aerosols, which gives new insights into the physicochemical properties and potential health effects of urban aerosols.
Ying Wei, Xueshun Chen, Huansheng Chen, Yele Sun, Wenyi Yang, Huiyun Du, Qizhong Wu, Dan Chen, Xiujuan Zhao, Jie Li, and Zifa Wang
Geosci. Model Dev., 14, 4411–4428, https://doi.org/10.5194/gmd-14-4411-2021, https://doi.org/10.5194/gmd-14-4411-2021, 2021
Short summary
Short summary
The sub-grid particle formation (SGPF) in plumes plays an important role in air pollution and climate. We coupled an SGPF scheme to a chemical transport model with an aerosol microphysics module and applied it to investigate the SGPF impact over China. The scheme clearly improved the model performance in simulating aerosol components and particle number at typical sites influenced by point sources. The results indicate the significant effects of SGPF on aerosol particles in industrial areas.
Baozhu Ge, Danhui Xu, Oliver Wild, Xuefeng Yao, Junhua Wang, Xueshun Chen, Qixin Tan, Xiaole Pan, and Zifa Wang
Atmos. Chem. Phys., 21, 9441–9454, https://doi.org/10.5194/acp-21-9441-2021, https://doi.org/10.5194/acp-21-9441-2021, 2021
Short summary
Short summary
In this study, an improved sequential sampling method is developed and implemented to estimate the contribution of below-cloud and in-cloud wet deposition over four years of measurements in Beijing. We find that the contribution of below-cloud scavenging for Ca2+, SO4 2–, and NH4+ decreases from above 50 % in 2014 to below 40 % in 2017. This suggests that the Action Plan has mitigated particulate matter pollution in the surface layer and hence decreased scavenging due to the washout process.
Xueshun Chen, Fangqun Yu, Wenyi Yang, Yele Sun, Huansheng Chen, Wei Du, Jian Zhao, Ying Wei, Lianfang Wei, Huiyun Du, Zhe Wang, Qizhong Wu, Jie Li, Junling An, and Zifa Wang
Atmos. Chem. Phys., 21, 9343–9366, https://doi.org/10.5194/acp-21-9343-2021, https://doi.org/10.5194/acp-21-9343-2021, 2021
Short summary
Short summary
Atmospheric aerosol particles have significant climate and health effects that depend on aerosol size, composition, and mixing state. A new global-regional nested aerosol model with an advanced particle microphysics module and a volatility basis set organic aerosol module was developed to simulate aerosol microphysical processes. Simulations strongly suggest the important role of anthropogenic organic species in particle formation over the areas influenced by anthropogenic sources.
Syuichi Itahashi, Baozhu Ge, Keiichi Sato, Zhe Wang, Junichi Kurokawa, Jiani Tan, Kan Huang, Joshua S. Fu, Xuemei Wang, Kazuyo Yamaji, Tatsuya Nagashima, Jie Li, Mizuo Kajino, Gregory R. Carmichael, and Zifa Wang
Atmos. Chem. Phys., 21, 8709–8734, https://doi.org/10.5194/acp-21-8709-2021, https://doi.org/10.5194/acp-21-8709-2021, 2021
Short summary
Short summary
This study presents the detailed analysis of acid deposition over southeast Asia based on the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. Simulated wet deposition is evaluated with observation data from the Acid Deposition Monitoring Network in East Asia (EANET). The difficulties of models to capture observations are related to the model performance on precipitation. The precipitation-adjusted approach was applied, and the distribution of wet deposition was successfully revised.
Weiqi Xu, Chun Chen, Yanmei Qiu, Ying Li, Zhiqiang Zhang, Eleni Karnezi, Spyros N. Pandis, Conghui Xie, Zhijie Li, Jiaxing Sun, Nan Ma, Wanyun Xu, Pingqing Fu, Zifa Wang, Jiang Zhu, Douglas R. Worsnop, Nga Lee Ng, and Yele Sun
Atmos. Chem. Phys., 21, 5463–5476, https://doi.org/10.5194/acp-21-5463-2021, https://doi.org/10.5194/acp-21-5463-2021, 2021
Short summary
Short summary
Here aerosol volatility and viscosity at a rural site (Gucheng) and an urban site (Beijing) in the North China Plain (NCP) were investigated in summer and winter. Our results showed that organic aerosol (OA) in winter in the NCP is more volatile than that in summer due to enhanced primary emissions from coal combustion and biomass burning. We also found that OA existed mainly as a solid in winter in Beijing but as semisolids in Beijing in summer and Gucheng in winter.
Santosh Kumar Verma, Kimitaka Kawamura, Fei Yang, Pingqing Fu, Yugo Kanaya, and Zifa Wang
Atmos. Chem. Phys., 21, 4959–4978, https://doi.org/10.5194/acp-21-4959-2021, https://doi.org/10.5194/acp-21-4959-2021, 2021
Short summary
Short summary
We studied aerosol samples collected in autumn 2007 with day and night intervals in a rural site of Mangshan, north of Beijing, for sugar compounds (SCs) that are abundant organic aerosol components and can influence the air quality and climate. We found higher concentrations of biomass burning (BB) products at nighttime than daytime, whereas pollen tracers and other SCs showed an opposite diurnal trend, because this site is meteorologically characterized by a mountain/valley breeze.
Hui Wang, Qizhong Wu, Alex B. Guenther, Xiaochun Yang, Lanning Wang, Tang Xiao, Jie Li, Jinming Feng, Qi Xu, and Huaqiong Cheng
Atmos. Chem. Phys., 21, 4825–4848, https://doi.org/10.5194/acp-21-4825-2021, https://doi.org/10.5194/acp-21-4825-2021, 2021
Short summary
Short summary
We assessed the influence of the greening trend on BVOC emission in China. The comparison among different scenarios showed that vegetation changes resulting from land cover management are the main driver of BVOC emission change in China. Climate variability contributed significantly to interannual variations but not much to the long-term trend during the study period.
Tabish Umar Ansari, Oliver Wild, Edmund Ryan, Ying Chen, Jie Li, and Zifa Wang
Atmos. Chem. Phys., 21, 4471–4485, https://doi.org/10.5194/acp-21-4471-2021, https://doi.org/10.5194/acp-21-4471-2021, 2021
Short summary
Short summary
We use novel modelling approaches to quantify the lingering effects of 1 d local and regional emission controls on subsequent days, the effects of longer continuous emission controls of individual sectors over different regions, and the effects of combined emission controls of multiple sectors and regions on air quality in Beijing under varying weather conditions to inform precise short-term emission control policies for avoiding heavy haze pollution in Beijing.
Tie Dai, Yueming Cheng, Daisuke Goto, Yingruo Li, Xiao Tang, Guangyu Shi, and Teruyuki Nakajima
Atmos. Chem. Phys., 21, 4357–4379, https://doi.org/10.5194/acp-21-4357-2021, https://doi.org/10.5194/acp-21-4357-2021, 2021
Short summary
Short summary
The anthropogenic emission of sulfur dioxide (SO2) over China has significantly declined as a consequence of the clean air actions. We have developed a new emission inversion system to dynamically update the SO2 emission grid by grid over China by assimilating ground-based SO2 observations. The inverted SO2 emission over China in November 2016 on average had declined by 49.4 % since 2010, which is well in agreement with the bottom-up estimation of 48.0 %.
Cited articles
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C.,
Hoglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., Rafaj, P.,
Sandler, R., Schopp, W., Wagner, F., and Winiwarter, W.: Cost-effective
control of air quality and greenhouse gases in Europe: Modeling and policy
applications, Environ. Modell. Softw., 26, 1489–1501, https://doi.org/10.1016/j.envsoft.2011.07.012, 2011.
Andreae, M. O. and Crutzen, P. J.: Atmospheric aerosols: Biogeochemical
sources and role in atmospheric chemistry, Science, 276, 1052–1058, https://doi.org/10.1126/science.276.5315.1052, 1997.
Badia, A., Jorba, O., Voulgarakis, A., Dabdub, D., Pérez García-Pando, C., Hilboll, A., Gonçalves, M., and Janjic, Z.: Description and evaluation of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH) version 1.0: gas-phase chemistry at global scale, Geosci. Model Dev., 10, 609–638, https://doi.org/10.5194/gmd-10-609-2017, 2017.
Bauer, S. E. and Koch, D.: Impact of heterogeneous sulfate formation at
mineral dust surfaces on aerosol loads and radiative forcing in the Goddard
Institute for Space Studies general circulation model, J.
Geophys. Res.-Atmos., 110, D17202, https://doi.org/10.1029/2005jd005870, 2005.
Byun, D. W. and Dennis, R.: Design artifacts in eulerian air-quality models
– evaluation of the effects of layer thickness and vertical profile
correction on surface ozone concentrations, Atmos. Environ., 29,
105–126, https://doi.org/10.1016/1352-2310(94)00225-a, 1995.
Carmichael, G. R., Tang, Y., Kurata, G., Uno, I., Streets, D., Woo, J. H.,
Huang, H., Yienger, J., Lefer, B., Shetter, R., Blake, D., Atlas, E., Fried,
A., Apel, E., Eisele, F., Cantrell, C., Avery, M., Barrick, J., Sachse, G.,
Brune, W., Sandholm, S., Kondo, Y., Singh, H., Talbot, R., Bandy, A.,
Thorton, D., Clarke, A., and Heikes, B.: Regional-scale chemical transport
modeling in support of the analysis of observations obtained during the
TRACE-P experiment, J. Geophys. Res.-Atmos., 108, 8823, https://doi.org/10.1029/2002jd003117, 2003.
Carn, S. A., Yang, K., Prata, A. J., and Krotkov, N. A.: Extending the
long-term record of volcanic SO2 emissions with the Ozone Mapping and
Profiler Suite nadir mapper, Geophys. Res. Lett., 42, 925–932, https://doi.org/10.1002/2014gl062437, 2015.
Carter, T. S., Heald, C. L., Jimenez, J. L., Campuzano-Jost, P., Kondo, Y., Moteki, N., Schwarz, J. P., Wiedinmyer, C., Darmenov, A. S., da Silva, A. M., and Kaiser, J. W.: How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, 2020.
Chen, H. S., Wang, Z. F., Li, J., Tang, X., Ge, B. Z., Wu, X. L., Wild, O., and Carmichael, G. R.: GNAQPMS-Hg v1.0, a global nested atmospheric mercury transport model: model description, evaluation and application to trans-boundary transport of Chinese anthropogenic emissions, Geosci. Model Dev., 8, 2857–2876, https://doi.org/10.5194/gmd-8-2857-2015, 2015.
Chen, X. S., Yang, W. Y., Wang, Z. F., Li, J., Hu, M., An, J. L., Wu, Q. Z.,
Wang, Z., Chen, H. S., Wei, Y., Du, H. Y., and Wang, D. W.: Improving new
particle formation simulation by coupling a volatility-basis set (VBS)
organic aerosol module in NAQPMS plus APM, Atmos. Environ., 204,
1–11, https://doi.org/10.1016/j.atmosenv.2019.01.053, 2019.
Cooper, O. R., Forster, C., Parrish, D., Trainer, M., Dunlea, E., Ryerson,
T., Hubler, G., Fehsenfeld, F., Nicks, D., Holloway, J., de Gouw, J.,
Warneke, C., Roberts, J. M., Flocke, F., and Moody, J.: A case study of
transpacific warm conveyor belt transport: Influence of merging airstreams
on trace gas import to North America, J. Geophys. Res.-Atmos., 109, D23S08, https://doi.org/10.1029/2003jd003624, 2004.
Crippa, M., Janssens-Maenhout, G., Guizzardi, D., Van Dingenen, R., and Dentener, F.: Contribution and uncertainty of sectorial and regional emissions to regional and global PM2.5 health impacts, Atmos. Chem. Phys., 19, 5165–5186, https://doi.org/10.5194/acp-19-5165-2019, 2019.
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M.,
Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution
temporal profiles in the Emissions Database for Global Atmospheric Research,
Sci. Data, 7, 121, https://doi.org/10.1038/s41597-020-0462-2, 2020.
Dentener, F., Keating, T., and Akimoto, H.: Hemispheric Transport of Air Pollution 2010: Part A – Ozone and Particulate Matter, Air Pollut. Stud., 17, 305, https://doi.org/10.18356/2c908168-en, 2010.
Derwent, R. G., Stevenson, D. S., Collins, W. J., and Johnson, C. E.:
Intercontinental transport and the origins of the ozone observed at surface
sites in Europe, Atmos. Environ., 38, 1891–1901, https://doi.org/10.1016/j.atmosenv.2004.01.008, 2004.
Eastham, S. D. and Jacob, D. J.: Limits on the ability of global Eulerian models to resolve intercontinental transport of chemical plumes, Atmos. Chem. Phys., 17, 2543–2553, https://doi.org/10.5194/acp-17-2543-2017, 2017.
Emanuel, K. A.: A scheme for representing cumulus convection in large-scale
models, J. Atmos. Sci., 48, 2313–2335, https://doi.org/10.1175/1520-0469(1991)048<2313:Asfrcc>2.0.Co;2, 1991.
Fan, J. W., Wang, Y., Rosenfeld, D., and Liu, X. H.: Review of Aerosol-Cloud
Interactions: Mechanisms, Significance, and Challenges, J. Atmos. Sci., 73,
4221–4252, https://doi.org/10.1175/jas-d-16-0037.1, 2016.
Fenech, S., Doherty, R. M., Heaviside, C., Vardoulakis, S., Macintyre, H. L., and O'Connor, F. M.: The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments, Atmos. Chem. Phys., 18, 5765–5784, https://doi.org/10.5194/acp-18-5765-2018, 2018.
Fiore, A. M., Jacob, D. J., Bey, I., Yantosca, R. M., Field, B. D., Fusco,
A. C., and Wilkinson, J. G.: Background ozone over the United States in
summer: Origin, trend, and contribution to pollution episodes, J. Geophys. Res.-Atmos., 107, 4275, https://doi.org/10.1029/2001jd000982, 2002.
Fiore, A. M., Dentener, F. J., Wild, O., Cuvelier, C., Schultz, M. G., Hess,
P., Textor, C., Schulz, M., Doherty, R. M., Horowitz, L. W., MacKenzie, I.
A., Sanderson, M. G., Shindell, D. T., Stevenson, D. S., Szopa, S., Van
Dingenen, R., Zeng, G., Atherton, C., Bergmann, D., Bey, I., Carmichael, G.,
Collins, W. J., Duncan, B. N., Faluvegi, G., Folberth, G., Gauss, M., Gong,
S., Hauglustaine, D., Holloway, T., Isaksen, I. S. A., Jacob, D. J., Jonson,
J. E., Kaminski, J. W., Keating, T. J., Lupu, A., Marmer, E., Montanaro, V.,
Park, R. J., Pitari, G., Pringle, K. J., Pyle, J. A., Schroeder, S.,
Vivanco, M. G., Wind, P., Wojcik, G., Wu, S., and Zuber, A.: Multimodel
estimates of intercontinental source-receptor relationships for ozone
pollution, J. Geophys. Res.-Atmos., 114, D04301, https://doi.org/10.1029/2008jd010816, 2009.
Granier, C., Darras, S., van der Gon, H. D., Jana, D., and Elguindi, N.: The
Copernicus Atmosphere Monitoring Service global and regional emissions
(April 2019 version), [Research Report] Copernicus Atmosphere Monitoring
Service, https://doi.org/10.24380/d0bn-kx16, 2019.
Grewe, V.: Technical Note: A diagnostic for ozone contributions of various NOx emissions in multi-decadal chemistry-climate model simulations, Atmos. Chem. Phys., 4, 729–736, https://doi.org/10.5194/acp-4-729-2004, 2004.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Guo, J. J., Fiore, A. M., Murray, L. T., Jaffe, D. A., Schnell, J. L., Moore, C. T., and Milly, G. P.: Average versus high surface ozone levels over the continental USA: model bias, background influences, and interannual variability, Atmos. Chem. Phys., 18, 12123–12140, https://doi.org/10.5194/acp-18-12123-2018, 2018.
Han, H., Wu, Y., Liu, J., Zhao, T., Zhuang, B., Wang, H., Li, Y., Chen, H., Zhu, Y., Liu, H., Wang, Q., Li, S., Wang, T., Xie, M., and Li, M.: Impacts of atmospheric transport and biomass burning on the inter-annual variation in black carbon aerosols over the Tibetan Plateau, Atmos. Chem. Phys., 20, 13591–13610, https://doi.org/10.5194/acp-20-13591-2020, 2020.
Hogrefe, C., Liu, P., Pouliot, G., Mathur, R., Roselle, S., Flemming, J., Lin, M., and Park, R. J.: Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States, Atmos. Chem. Phys., 18, 3839–3864, https://doi.org/10.5194/acp-18-3839-2018, 2018.
Horowitz, L. W., Walters, S., Mauzerall, D. L., Emmons, L. K., Rasch, P. J.,
Granier, C., Tie, X. X., Lamarque, J. F., Schultz, M. G., Tyndall, G. S.,
Orlando, J. J., and Brasseur, G. P.: A global simulation of tropospheric
ozone and related tracers: Description and evaluation of MOZART, version 2,
J. Geophys. Res.-Atmos., 108, 4784, https://doi.org/10.1029/2002jd002853,
2003.
Horowitz, L. W., Naik, V., Paulot, F., Ginoux, P. A., Dunne, J. P., Mao, J.
Q., Schnell, J., Chen, X., He, J., John, J. G., Lin, M. Y., Lin, P.,
Malyshev, S., Paynter, D., Shevliakova, E., and Zhao, M.: The GFDL Global
Atmospheric Chemistry-Climate Model AM4.1: Model Description and Simulation
Characteristics, J. Adv. Model. Earth Sy., 12, e2019MS002032, https://doi.org/10.1029/2019ms002032,
2020.
Huang, K., Fu, J. S., Prikhodko, V. Y., Storey, J. M., Romanov, A., Hodson,
E. L., Cresko, J., Morozova, I., Ignatieva, Y., and Cabaniss, J.: Russian
anthropogenic black carbon: Emission reconstruction and Arctic black carbon
simulation, J. Geophys. Res.-Atmos., 120, 11306–11333, https://doi.org/10.1002/2015jd023358, 2015.
Hudman, R. C., Moore, N. E., Mebust, A. K., Martin, R. V., Russell, A. R., Valin, L. C., and Cohen, R. C.: Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints, Atmos. Chem. Phys., 12, 7779–7795, https://doi.org/10.5194/acp-12-7779-2012, 2012.
Huijnen, V., Williams, J., van Weele, M., van Noije, T., Krol, M., Dentener, F., Segers, A., Houweling, S., Peters, W., de Laat, J., Boersma, F., Bergamaschi, P., van Velthoven, P., Le Sager, P., Eskes, H., Alkemade, F., Scheele, R., Nédélec, P., and Pätz, H.-W.: The global chemistry transport model TM5: description and evaluation of the tropospheric chemistry version 3.0, Geosci. Model Dev., 3, 445–473, https://doi.org/10.5194/gmd-3-445-2010, 2010.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., Denier van der Gon, H., Kuenen, J. J. P., Klimont, Z., Frost, G., Darras, S., Koffi, B., and Li, M.: HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution, Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, 2015.
Karamchandani, P., Long, Y., Pirovano, G., Balzarini, A., and Yarwood, G.: Source-sector contributions to European ozone and fine PM in 2010 using AQMEII modeling data, Atmos. Chem. Phys., 17, 5643–5664, https://doi.org/10.5194/acp-17-5643-2017, 2017.
Kim, H. C., Kim, E., Bae, C., Cho, J. H., Kim, B.-U., and Kim, S.: Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory, Atmos. Chem. Phys., 17, 10315–10332, https://doi.org/10.5194/acp-17-10315-2017, 2017.
Kim, P. S., Jacob, D. J., Fisher, J. A., Travis, K., Yu, K., Zhu, L., Yantosca, R. M., Sulprizio, M. P., Jimenez, J. L., Campuzano-Jost, P., Froyd, K. D., Liao, J., Hair, J. W., Fenn, M. A., Butler, C. F., Wagner, N. L., Gordon, T. D., Welti, A., Wennberg, P. O., Crounse, J. D., St. Clair, J. M., Teng, A. P., Millet, D. B., Schwarz, J. P., Markovic, M. Z., and Perring, A. E.: Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model, Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, 2015.
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys., 17, 8681–8723, https://doi.org/10.5194/acp-17-8681-2017, 2017.
Koo, B., Knipping, E., and Yarwood, G.: 1.5-Dimensional volatility basis set
approach for modeling organic aerosol in CAMx and CMAQ, Atmos. Environ., 95, 158–164, https://doi.org/10.1016/j.atmosenv.2014.06.031, 2014.
Lee, H. M., Park, R. J., Henze, D. K., Lee, S., Shim, C., Shin, H. J., Moon,
K. J., and Woo, J. H.: PM2.5 source attribution for Seoul in May from 2009
to 2013 using GEOS-Chem and its adjoint model, Environ. Pollut., 221,
377–384, https://doi.org/10.1016/j.envpol.2016.11.088, 2017.
Li, J., Wang, Z., Akimoto, H., Yamaji, K., Takigawa, M., Pochanart, P., Liu, Y., Tanimoto, H., and Kanaya, Y.: Near-ground ozone source attributions and outflow in central eastern China during MTX2006, Atmos. Chem. Phys., 8, 7335–7351, https://doi.org/10.5194/acp-8-7335-2008, 2008.
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, J., Wang, Z., Zhuang, G., Luo, G., Sun, Y., and Wang, Q.: Mixing of Asian mineral dust with anthropogenic pollutants over East Asia: a model case study of a super-duststorm in March 2010, Atmos. Chem. Phys., 12, 7591–7607, https://doi.org/10.5194/acp-12-7591-2012, 2012.
Li, J., Wang, Z. F., Huang, H. L., Hu, M., Meng, F., Sun, Y. L., Wang, X.
Q., Wang, Y. S., and Wang, Q.: Assessing the effects of trans-boundary
aerosol transport between various city clusters on regional haze episodes in
spring over East China, Tellus Ser. B,
65, 20052, https://doi.org/10.3402/tellusb.v65i0.20052, 2013.
Li, J., Yang, W., Wang, Z., Chen, H., Hu, B., Li, J., Sun, Y., and Huang,
Y.: A modeling study of source-receptor relationships in atmospheric
particulate matter over Northeast Asia, Atmos. Environ., 91, 40–51, https://doi.org/10.1016/j.atmosenv.2014.03.027, 2014.
Li, J., Yang, W. Y., Wang, Z. F., Chen, H. S., Hu, B., Li, J. J., Sun, Y.
L., Fu, P. Q., and Zhang, Y. Q.: Modeling study of surface ozone
source-receptor relationships in East Asia, Atmos. Res., 167, 77–88, https://doi.org/10.1016/j.atmosres.2015.07.010, 2016.
Li, J., Nagashima, T., Kong, L., Ge, B., Yamaji, K., Fu, J. S., Wang, X., Fan, Q., Itahashi, S., Lee, H.-J., Kim, C.-H., Lin, C.-Y., Zhang, M., Tao, Z., Kajino, M., Liao, H., Li, M., Woo, J.-H., Kurokawa, J., Wang, Z., Wu, Q., Akimoto, H., Carmichael, G. R., and Wang, Z.: Model evaluation and intercomparison of surface-level ozone and relevant species in East Asia in the context of MICS-Asia Phase III – Part 1: Overview, Atmos. Chem. Phys., 19, 12993–13015, https://doi.org/10.5194/acp-19-12993-2019, 2019.
Li, X. Y., Liu, J. F., Mauzerall, D. L., Emmons, L. K., Walters, S.,
Horowitz, L. W., and Tao, S.: Effects of trans-Eurasian transport of air
pollutants on surface ozone concentrations over Western China, J. Geophys. Res.-Atmos., 119, 12338–12354, https://doi.org/10.1002/2014jd021936,
2014.
Li, Z., Zhao, X., Kahn, R., Mishchenko, M., Remer, L., Lee, K.-H., Wang, M., Laszlo, I., Nakajima, T., and Maring, H.: Uncertainties in satellite remote sensing of aerosols and impact on monitoring its long-term trend: a review and perspective, Ann. Geophys., 27, 2755–2770, https://doi.org/10.5194/angeo-27-2755-2009, 2009.
Lin, M., Holloway, T., Carmichael, G. R., and Fiore, A. M.: Quantifying pollution inflow and outflow over East Asia in spring with regional and global models, Atmos. Chem. Phys., 10, 4221–4239, https://doi.org/10.5194/acp-10-4221-2010, 2010.
Liu, Z., Omar, A., Vaughan, M., Hair, J., Kittaka, C., Hu, Y., Powell, K.,
Trepte, C., Winker, D., Hostetler, C., Ferrare, R., and Pierce, R.: CALIPSO
lidar observations of the optical properties of Saharan dust: A case study
of long-range transport, J. Geophys. Res.-Atmos., 113, D07207, https://doi.org/10.1029/2007jd008878, 2008.
Logan, J. A.: An analysis of ozonesonde data for the troposphere:
Recommendations for testing 3-D models and development of a gridded
climatology for tropospheric ozone, J. Geophys. Res.-Atmos., 104, 16115–16149, https://doi.org/10.1029/1998jd100096, 1999.
Lu, X., Zhang, L., Wu, T., Long, M. S., Wang, J., Jacob, D. J., Zhang, F., Zhang, J., Eastham, S. D., Hu, L., Zhu, L., Liu, X., and Wei, M.: Development of the global atmospheric chemistry general circulation model BCC-GEOS-Chem v1.0: model description and evaluation, Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, 2020.
Mar, K. A., Ojha, N., Pozzer, A., and Butler, T. M.: Ozone air quality simulations with WRF-Chem (v3.5.1) over Europe: model evaluation and chemical mechanism comparison, Geosci. Model Dev., 9, 3699–3728, https://doi.org/10.5194/gmd-9-3699-2016, 2016.
Miyazaki, K., Bowman, K. W., Yumimoto, K., Walker, T., and Sudo, K.: Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis, Atmos. Chem. Phys., 20, 931–967, https://doi.org/10.5194/acp-20-931-2020, 2020.
Mori, T., Kondo, Y., Ohata, S., Zhao, Y., Sinha, P. R., Oshima, N., Matsui,
H., Moteki, N., and Koike, M.: Seasonal Variation of Wet Deposition of Black
Carbon in Arctic Alaska, J. Geophys. Res.-Atmos., 125, e2019JD032240, https://doi.org/10.1029/2019jd032240, 2020.
Nagashima, T., Ohara, T., Sudo, K., and Akimoto, H.: The relative importance of various source regions on East Asian surface ozone, Atmos. Chem. Phys., 10, 11305–11322, https://doi.org/10.5194/acp-10-11305-2010, 2010.
Nagashima, T., Sudo, K., Akimoto, H., Kurokawa, J., and Ohara, T.: Long-term change in the source contribution to surface ozone over Japan, Atmos. Chem. Phys., 17, 8231–8246, https://doi.org/10.5194/acp-17-8231-2017, 2017.
Nenes, A., Pandis, S. N., and Pilinis, C.: ISORROPIA: A new thermodynamic
equilibrium model for multiphase multicomponent inorganic aerosols, Aquat.
Geochem., 4, 123–152, https://doi.org/10.1023/a:1009604003981, 1998.
Nopmongcol, U., Liu, Z., Stoeckenius, T., and Yarwood, G.: Modeling intercontinental transport of ozone in North America with CAMx for the Air Quality Model Evaluation International Initiative (AQMEII) Phase 3, Atmos. Chem. Phys., 17, 9931–9943, https://doi.org/10.5194/acp-17-9931-2017, 2017.
Pal, S., Davis, K. J., Lauvaux, T., Browell, E. V., Gaudet, B. J., Stauffer,
D. R., Obland, M. D., Choi, Y., DiGangi, J. P., Feng, S., Lin, B., Miles, N.
L., Pauly, R. M., Richardson, S. J., and Zhang, F. Q.: Observations of
Greenhouse Gas Changes Across Summer Frontal Boundaries in the Eastern
United States, J. Geophys. Res.-Atmos., 125, e2019JD030526, https://doi.org/10.1029/2019jd030526, 2020.
Petaja, T., Jarvi, L., Kerminen, V. M., Ding, A. J., Sun, J. N., Nie, W.,
Kujansuu, J., Virkkula, A., Yang, X. Q., Fu, C. B., Zilitinkevich, S., and
Kulmala, M.: Enhanced air pollution via aerosol-boundary layer feedback in
China, Sci. Rep., 6, 18998, https://doi.org/10.1038/srep18998, 2016.
Platnick, S.: MODIS Atmosphere L3 Monthly Product, NASA MODIS Adaptive
Processing System [code],
https://doi.org/10.5067/MODIS/MOD08_M3.006, 2015.
Price, C., Penner, J., and Prather, M.: NOx from lightning .1. Global
distribution based on lightning physics, J. Geophys. Res.-Atmos., 102, 5929–5941, https://doi.org/10.1029/96jd03504, 1997.
Qian, Y., Gustafson Jr., W. I., and Fast, J. D.: An investigation of the sub-grid variability of trace gases and aerosols for global climate modeling, Atmos. Chem. Phys., 10, 6917–6946, https://doi.org/10.5194/acp-10-6917-2010, 2010.
Shindell, D. T., Chin, M., Dentener, F., Doherty, R. M., Faluvegi, G., Fiore, A. M., Hess, P., Koch, D. M., MacKenzie, I. A., Sanderson, M. G., Schultz, M. G., Schulz, M., Stevenson, D. S., Teich, H., Textor, C., Wild, O., Bergmann, D. J., Bey, I., Bian, H., Cuvelier, C., Duncan, B. N., Folberth, G., Horowitz, L. W., Jonson, J., Kaminski, J. W., Marmer, E., Park, R., Pringle, K. J., Schroeder, S., Szopa, S., Takemura, T., Zeng, G., Keating, T. J., and Zuber, A.: A multi-model assessment of pollution transport to the Arctic, Atmos. Chem. Phys., 8, 5353–5372, https://doi.org/10.5194/acp-8-5353-2008, 2008.
Sobhani, N., Kulkarni, S., and Carmichael, G. R.: Source sector and region contributions to black carbon and PM2.5 in the Arctic, Atmos. Chem. Phys., 18, 18123–18148, https://doi.org/10.5194/acp-18-18123-2018, 2018.
Stockwell, W. R., Middleton, P., Chang, J. S., and Tang, X.: The 2nd
generation regional acid deposition model chemical mechanism for regional
air quality modeling, J. Geophys. Res.-Atmos., 95, 16343–16367, https://doi.org/10.1029/JD095iD10p16343,
1990.
Sudo, K. and Akimoto, H.: Global source attribution of tropospheric ozone:
Long-range transport from various source regions, J. Geophys. Res.-Atmos., 112, D12302, https://doi.org/10.1029/2006jd007992, 2007.
Sugiura, K., Ohata, T., and Yang, D.: Catch characteristics of precipitation
gauges in high-latitude regions with high winds, J.
Hydrometeorol., 7, 984–994, https://doi.org/10.1175/jhm542.1, 2006.
Tao, Z., Chin, M., Gao, M., Kucsera, T., Kim, D., Bian, H., Kurokawa, J., Wang, Y., Liu, Z., Carmichael, G. R., Wang, Z., and Akimoto, H.: Evaluation of NU-WRF model performance on air quality simulation under various model resolutions – an investigation within the framework of MICS-Asia Phase III, Atmos. Chem. Phys., 20, 2319–2339, https://doi.org/10.5194/acp-20-2319-2020, 2020.
Uno, I., Osada, K., Yumimoto, K., Wang, Z., Itahashi, S., Pan, X., Hara, Y., Kanaya, Y., Yamamoto, S., and Fairlie, T. D.: Seasonal variation of fine- and coarse-mode nitrates and related aerosols over East Asia: synergetic observations and chemical transport model analysis, Atmos. Chem. Phys., 17, 14181–14197, https://doi.org/10.5194/acp-17-14181-2017, 2017.
Van Dingenen, R., Dentener, F., Crippa, M., Leitao, J., Marmer, E., Rao, S., Solazzo, E., and Valentini, L.: TM5-FASST: a global atmospheric source–receptor model for rapid impact analysis of emission changes on air quality and short-lived climate pollutants, Atmos. Chem. Phys., 18, 16173–16211, https://doi.org/10.5194/acp-18-16173-2018, 2018.
van Geffen, J., Boersma, K. F., Eskes, H., Sneep, M., ter Linden, M., Zara, M., and Veefkind, J. P.: S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI, Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, 2020.
Venkatram, A. and Karamchandani, P.: Source-receptor relationships,
Environ. Sci. Technol., 20, 1084–1091, https://doi.org/10.1021/es00153a002,
1986.
Verhoelst, T., Compernolle, S., Pinardi, G., Lambert, J.-C., Eskes, H. J., Eichmann, K.-U., Fjæraa, A. M., Granville, J., Niemeijer, S., Cede, A., Tiefengraber, M., Hendrick, F., Pazmiño, A., Bais, A., Bazureau, A., Boersma, K. F., Bognar, K., Dehn, A., Donner, S., Elokhov, A., Gebetsberger, M., Goutail, F., Grutter de la Mora, M., Gruzdev, A., Gratsea, M., Hansen, G. H., Irie, H., Jepsen, N., Kanaya, Y., Karagkiozidis, D., Kivi, R., Kreher, K., Levelt, P. F., Liu, C., Müller, M., Navarro Comas, M., Piters, A. J. M., Pommereau, J.-P., Portafaix, T., Prados-Roman, C., Puentedura, O., Querel, R., Remmers, J., Richter, A., Rimmer, J., Rivera Cárdenas, C., Saavedra de Miguel, L., Sinyakov, V. P., Stremme, W., Strong, K., Van Roozendael, M., Veefkind, J. P., Wagner, T., Wittrock, F., Yela González, M., and Zehner, C.: Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks, Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, 2021.
Verstraeten, W. W., Boersma, K. F., Zörner, J., Allaart, M. A. F., Bowman, K. W., and Worden, J. R.: Validation of six years of TES tropospheric ozone retrievals with ozonesonde measurements: implications for spatial patterns and temporal stability in the bias, Atmos. Meas. Tech., 6, 1413–1423, https://doi.org/10.5194/amt-6-1413-2013, 2013.
Voulgarakis, A., Naik, V., Lamarque, J.-F., Shindell, D. T., Young, P. J., Prather, M. J., Wild, O., Field, R. D., Bergmann, D., Cameron-Smith, P., Cionni, I., Collins, W. J., Dalsøren, S. B., Doherty, R. M., Eyring, V., Faluvegi, G., Folberth, G. A., Horowitz, L. W., Josse, B., MacKenzie, I. A., Nagashima, T., Plummer, D. A., Righi, M., Rumbold, S. T., Stevenson, D. S., Strode, S. A., Sudo, K., Szopa, S., and Zeng, G.: Analysis of present day and future OH and methane lifetime in the ACCMIP simulations, Atmos. Chem. Phys., 13, 2563–2587, https://doi.org/10.5194/acp-13-2563-2013, 2013.
Wagstrom, K. M., Pandis, S. N., Yarwood, G., Wilson, G. M., and Morris, R.
E.: Development and application of a computationally efficient particulate
matter apportionment algorithm in a three-dimensional chemical transport
model, Atmos. Environ., 42, 5650–5659, https://doi.org/10.1016/j.atmosenv.2008.03.012, 2008.
Wai, K. M., Wu, S. L., Li, X. L., Jaffe, D. A., and Perry, K. D.: Global
Atmospheric Transport and Source-Receptor Relationships for Arsenic,
Environ. Sci. Technol., 50, 3714–3720, https://doi.org/10.1021/acs.est.5b05549, 2016.
Walcek, C. J. and Aleksic, N. M.: A simple but accurate mass conservative,
peak-preserving, mixing ratio bounded advection algorithm with Fortran code,
Atmos. Environ., 32, 3863–3880, https://doi.org/10.1016/s1352-2310(98)00099-5, 1998.
Wang, H., Chen, H., Wu, Q., Lin, J., Chen, X., Xie, X., Wang, R., Tang, X., and Wang, Z.: GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors, Geosci. Model Dev., 10, 2891–2904, https://doi.org/10.5194/gmd-10-2891-2017, 2017.
Wang, Q. Q., Jacob, D. J., Spackman, J. R., Perring, A. E., Schwarz, J. P.,
Moteki, N., Marais, E. A., Ge, C., Wang, J., and Barrett, S. R. H.: Global
budget and radiative forcing of black carbon aerosol: Constraints from
pole-to-pole (HIPPO) observations across the Pacific, J. Geophys. Res.-Atmos., 119, 195–206, https://doi.org/10.1002/2013jd020824, 2014.
Wang, Z. F., Maeda, T., Hayashi, M., Hsiao, L. F., and Liu, K. Y.: A nested
air quality prediction modeling system for urban and regional scales:
Application for high-ozone episode in Taiwan, Water Air Soil Pollut.,
130, 391–396, https://doi.org/10.1023/a:1013833217916, 2001.
Wang, Z. F., Akimoto, H., and Uno, I.: Neutralization of soil aerosol and
its impact on the distribution of acid rain over east Asia: Observations and
model results, J. Geophys. Res.-Atmos., 107, 4389, https://doi.org/10.1029/2001jd001040, 2002.
Wei, Y., Chen, X., Chen, H., Li, J., Wang, Z., Yang, W., Ge, B., Du, H., Hao, J., Wang, W., Li, J., Sun, Y., and Huang, H.: IAP-AACM v1.0: a global to regional evaluation of the atmospheric chemistry model in CAS-ESM, Atmos. Chem. Phys., 19, 8269–8296, https://doi.org/10.5194/acp-19-8269-2019, 2019.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Wu, J.-B., Wang, Z., Wang, Q., Li, J., Xu, J., Chen, H., Ge, B., Zhou, G.,
and Chang, L.: Development of an on-line source-tagged model for sulfate,
nitrate and ammonium: A modeling study for highly polluted periods in
Shanghai, China, Environ. Pollut., 221, 168–179, https://doi.org/10.1016/j.envpol.2016.11.061, 2017.
Wu, Q. Z., Wang, Z. F., Gbaguidi, A., Gao, C., Li, L. N., and Wang, W.: A numerical study of contributions to air pollution in Beijing during CAREBeijing-2006, Atmos. Chem. Phys., 11, 5997–6011, https://doi.org/10.5194/acp-11-5997-2011, 2011.
Yang, W. Y., Li, J., Wang, W. G., Li, J. L., Ge, M. F., Sun, Y. L., Chen, X.
S., Ge, B. Z., Tong, S. R., Wang, Q. Q., and Wang, Z. F.: Investigating
secondary organic aerosol formation pathways in China during 2014,
Atmos. Environ., 213, 133–147, https://doi.org/10.1016/j.atmosenv.2019.05.057, 2019.
Yang, Y., Wang, H., Smith, S. J., Easter, R., Ma, P.-L., Qian, Y., Yu, H., Li, C., and Rasch, P. J.: Global source attribution of sulfate concentration and direct and indirect radiative forcing, Atmos. Chem. Phys., 17, 8903–8922, https://doi.org/10.5194/acp-17-8903-2017, 2017a.
Yang, Y., Wang, H., Smith, S. J., Ma, P.-L., and Rasch, P. J.: Source attribution of black carbon and its direct radiative forcing in China, Atmos. Chem. Phys., 17, 4319–4336, https://doi.org/10.5194/acp-17-4319-2017, 2017b.
Ye, Q. and Li, J.: A global tropospheric atmospheric chemistry source receptor model, Zenodo [code], https://doi.org/10.5281/zenodo.4777796, 2021.
Yim, S. H. L., Gu, Y., Shapiro, M. A., and Stephens, B.: Air quality and acid deposition impacts of local emissions and transboundary air pollution in Japan and South Korea, Atmos. Chem. Phys., 19, 13309–13323, https://doi.org/10.5194/acp-19-13309-2019, 2019.
Yu, F. and Luo, G.: Simulation of particle size distribution with a global aerosol model: contribution of nucleation to aerosol and CCN number concentrations, Atmos. Chem. Phys., 9, 7691–7710, https://doi.org/10.5194/acp-9-7691-2009, 2009.
Yu, F., Luo, G., and Ma, X.: Regional and global modeling of aerosol optical properties with a size, composition, and mixing state resolved particle microphysics model, Atmos. Chem. Phys., 12, 5719–5736, https://doi.org/10.5194/acp-12-5719-2012, 2012.
Zaveri, R. A. and Peters, L. K.: A new lumped structure photochemical
mechanism for large-scale applications, J. Geophys. Res.-Atmos., 104, 30387–30415, https://doi.org/10.1029/1999jd900876, 1999.
Zhang, L., Brook, J. R., and Vet, R.: A revised parameterization for gaseous dry deposition in air-quality models, Atmos. Chem. Phys., 3, 2067–2082, https://doi.org/10.5194/acp-3-2067-2003, 2003.
Zhang, L., Jacob, D. J., Knipping, E. M., Kumar, N., Munger, J. W., Carouge, C. C., van Donkelaar, A., Wang, Y. X., and Chen, D.: Nitrogen deposition to the United States: distribution, sources, and processes, Atmos. Chem. Phys., 12, 4539–4554, https://doi.org/10.5194/acp-12-4539-2012, 2012.
Zhang, Q., Zheng, Y. X., Tong, D., Shao, M., Wang, S. X., Zhang, Y. H., Xu,
X. D., Wang, J. N., He, H., Liu, W. Q., Ding, Y. H., Lei, Y., Li, J. H.,
Wang, Z. F., Zhang, X. Y., Wang, Y. S., Cheng, J., Liu, Y., Shi, Q. R., Yan,
L., Geng, G. N., Hong, C. P., Li, M., Liu, F., Zheng, B., Cao, J. J., Ding,
A. J., Gao, J., Fu, Q. Y., Huo, J. T., Liu, B. X., Liu, Z. R., Yang, F. M.,
He, K. B., and Hao, J. M.: Drivers of improved PM2.5 air quality in China
from 2013 to 2017, P. Natl. Acad. Sci. USA, 116, 24463–24469, https://doi.org/10.1073/pnas.1907956116, 2019.
Zhang, Y., Hemperly, J., Meskhidze, N., and Skamarock, J. W. C.: The
Global Weather Research and Forecasting (GWRF) Model: Model Evaluation,
Sensitivity Study, and Future Year Simulation, Atmos. Clim.
Sci., 2, 231–253, https://doi.org/10.4236/acs.2012.23024, 2012.
Zhang, Y., Sartelet, K., Zhu, S., Wang, W., Wu, S.-Y., Zhang, X., Wang, K., Tran, P., Seigneur, C., and Wang, Z.-F.: Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 2: Evaluation of chemical concentrations and sensitivity simulations, Atmos. Chem. Phys., 13, 6845–6875, https://doi.org/10.5194/acp-13-6845-2013, 2013.
Zhu, J., Liao, H., Mao, Y., Yang, Y., and Jiang, H.: Interannual variation, decadal trend, and future change in ozone outflow from East Asia, Atmos. Chem. Phys., 17, 3729–3747, https://doi.org/10.5194/acp-17-3729-2017, 2017.
Zhu, Y., Liu, J., Wang, T. J., Zhuang, B. L., Han, H., Wang, H. M., Chang,
Y., and Ding, K.: The Impacts of Meteorology on the Seasonal and Interannual
Variabilities of Ozone Transport From North America to East Asia, J. Geophys. Res.-Atmos., 122, 10612–10636, https://doi.org/10.1002/2017jd026761,
2017.
Short summary
We developed a global tropospheric atmospheric chemistry source–receptor model. This model can quantify the contributions of multiple air pollutants from various source regions in one simulation without introducing the nonlinear error of atmospheric chemistry. The S-R relationships of PM2.5 and O3 from a global high-resolution (0.5° × 0.5°) simulation were given and compared with previous studies. This model will be useful for creating a link between the scientific community and policymakers.
We developed a global tropospheric atmospheric chemistry source–receptor model. This model can...
