Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4641-2021
© 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-14-4641-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
28 Jul 2021
Model description paper |
| 28 Jul 2021
| 28 Jul 2021
Exploring deep learning for air pollutant emission estimation
Lin Huang
Microsoft Research Lab – Asia, Beijing, China
Song Liu
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
Zeyuan Yang
School of Economics and Management, Tsinghua University, Beijing,
China
Jia Xing
CORRESPONDING AUTHOR
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
Jia Zhang
CORRESPONDING AUTHOR
Microsoft Research Lab – Asia, Beijing, China
Jiang Bian
Microsoft Research Lab – Asia, Beijing, China
Siwei Li
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan, China
State Key Laboratory of Information Engineering in Surveying, Mapping
and Remote Sensing, Wuhan University, Wuhan, China
Shovan Kumar Sahu
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
Shuxiao Wang
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
Tie-Yan Liu
Microsoft Research Lab – Asia, Beijing, China
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EGUsphere, https://doi.org/10.5194/egusphere-2024-642, https://doi.org/10.5194/egusphere-2024-642, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We extensively compare various cluster-dynamics based parameterizations for sulfuric acid-dimethylamine nucleation and identify a newly developed parameterization derived from Atmospheric Cluster Dynamic Code (ACDC) simulations as the most reliable one. This study offers valuable reference for developing parameterizations of other nucleation system and is meaningful for the accurate quantification of the environmental and climate impacts of NPF.
Da Gao, Bin Zhao, Shuxiao Wang, Yuan Wang, Brian Gaudet, Yun Zhu, Xiaochun Wang, Jiewen Shen, Shengyue Li, Yicong He, Dejia Yin, and Zhaoxin Dong
Atmos. Chem. Phys., 23, 14359–14373, https://doi.org/10.5194/acp-23-14359-2023, https://doi.org/10.5194/acp-23-14359-2023, 2023
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Surface PM2.5 concentrations can be enhanced by aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs). In this study, we found PM2.5 enhancement induced by ACIs shows a significantly smaller decrease ratio than that induced by ARIs in China with anthropogenic emission reduction from 2013 to 2021, making ACIs more important for enhancing PM2.5 concentrations. ACI-induced PM2.5 enhancement needs to be emphatically considered to meet the national PM2.5 air quality standard.
Zeqi Li, Shuxiao Wang, Shengyue Li, Xiaochun Wang, Guanghan Huang, Xing Chang, Lyuyin Huang, Chengrui Liang, Yun Zhu, Haotian Zheng, Qian Song, Qingru Wu, Fenfen Zhang, and Bin Zhao
Earth Syst. Sci. Data, 15, 5017–5037, https://doi.org/10.5194/essd-15-5017-2023, https://doi.org/10.5194/essd-15-5017-2023, 2023
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This study developed the first full-volatility organic emission inventory for cooking sources in China, presenting high-resolution cooking emissions during 2015–2021. It identified the key subsectors and hotspots of cooking emissions, analyzed emission trends and drivers, and proposed future control strategies. The dataset is valuable for accurately simulating organic aerosol formation and evolution and for understanding the impact of organic emissions on air pollution and climate change.
Chupeng Zhang, Shangfei Hai, Yang Gao, Yuhang Wang, Shaoqing Zhang, Lifang Sheng, Bin Zhao, Shuxiao Wang, Jingkun Jiang, Xin Huang, Xiaojing Shen, Junying Sun, Aura Lupascu, Manish Shrivastava, Jerome D. Fast, Wenxuan Cheng, Xiuwen Guo, Ming Chu, Nan Ma, Juan Hong, Qiaoqiao Wang, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 23, 10713–10730, https://doi.org/10.5194/acp-23-10713-2023, https://doi.org/10.5194/acp-23-10713-2023, 2023
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New particle formation is an important source of atmospheric particles, exerting critical influences on global climate. Numerical models are vital tools to understanding atmospheric particle evolution, which, however, suffer from large biases in simulating particle numbers. Here we improve the model chemical processes governing particle sizes and compositions. The improved model reveals substantial contributions of newly formed particles to climate through effects on cloud condensation nuclei.
Yuyang Li, Jiewen Shen, Bin Zhao, Runlong Cai, Shuxiao Wang, Yang Gao, Manish Shrivastava, Da Gao, Jun Zheng, Markku Kulmala, and Jingkun Jiang
Atmos. Chem. Phys., 23, 8789–8804, https://doi.org/10.5194/acp-23-8789-2023, https://doi.org/10.5194/acp-23-8789-2023, 2023
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We set up a new parameterization for 1.4 nm particle formation rates from sulfuric acid–dimethylamine (SA–DMA) nucleation, fully including the effects of coagulation scavenging and cluster stability. Incorporating the new parameterization into 3-D chemical transport models, we achieved better consistencies between simulation results and observation data. This new parameterization provides new insights into atmospheric nucleation simulations and its effects on atmospheric pollution or health.
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, https://doi.org/10.5194/essd-15-2279-2023, 2023
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This study compiled China's emission inventory of air pollutants and CO2 during 2005–2021 (ABaCAS-EI v2.0) based on unified emission-source framework. The emission trends and its drivers are analyzed. Key sectors and regions with higher synergistic reduction potential of air pollutants and CO2 are identified. Future control measures are suggested. The dataset and analyses provide insights into the synergistic reduction of air pollutants and CO2 emissions for China and other developing countries.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
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Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Xiao He, Xuan Zheng, Shaojun Zhang, Xuan Wang, Ting Chen, Xiao Zhang, Guanghan Huang, Yihuan Cao, Liqiang He, Xubing Cao, Yuan Cheng, Shuxiao Wang, and Ye Wu
Atmos. Chem. Phys., 22, 13935–13947, https://doi.org/10.5194/acp-22-13935-2022, https://doi.org/10.5194/acp-22-13935-2022, 2022
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With the use of two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC ToF-MS), we successfully give a comprehensive characterization of particulate intermediate-volatility and semi-volatile organic compounds (I/SVOCs) emitted from heavy-duty diesel vehicles. I/SVOCs are speciated, identified, and quantified based on the patterns of the mass spectrum, and the gas–particle partitioning is fully addressed.
Yi Cheng, Shaofei Kong, Liquan Yao, Huang Zheng, Jian Wu, Qin Yan, Shurui Zheng, Yao Hu, Zhenzhen Niu, Yingying Yan, Zhenxing Shen, Guofeng Shen, Dantong Liu, Shuxiao Wang, and Shihua Qi
Earth Syst. Sci. Data, 14, 4757–4775, https://doi.org/10.5194/essd-14-4757-2022, https://doi.org/10.5194/essd-14-4757-2022, 2022
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This work establishes the first emission inventory of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue, using multi-source datasets and tested emission factors. These emissions were concentrated in specific periods and areas. Positive and negative correlations between income and emissions were revealed in urban and rural regions. The dataset will be helpful for improving modeling studies and modifying corresponding emission control policies.
Lulu Cui, Di Wu, Shuxiao Wang, Qingcheng Xu, Ruolan Hu, and Jiming Hao
Atmos. Chem. Phys., 22, 11931–11944, https://doi.org/10.5194/acp-22-11931-2022, https://doi.org/10.5194/acp-22-11931-2022, 2022
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A 1-year campaign was conducted to characterize VOCs at a Beijing urban site during different episodes. VOCs from fuel evaporation and diesel exhaust, particularly toluene, xylenes, trans-2-butene, acrolein, methyl methacrylate, vinyl acetate, 1-butene, and 1-hexene, were the main contributors. VOCs from diesel exhaust as well as coal and biomass combustion were found to be the dominant contributors for SOAFP, particularly the VOC species toluene, 1-hexene, xylenes, ethylbenzene, and styrene.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Shansi Wang, Siwei Li, Jia Xing, Yu Ding, Senlin Hu, Shuchang Liu, Yu Qin, Zhaoxin Dong, Jiaxin Dong, Ge Song, and Lechao Dong
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-368, https://doi.org/10.5194/acp-2022-368, 2022
Preprint withdrawn
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Future warming meteorological conditions may enhance the influence of regional transport on PM2.5 pollution. Our results prove that climate-friendly policy could lead to considerable co-benefits in mitigating the regional transport of PM2.5 in future. Meanwhile, climate change will exert larger impacts on across-regional (long-distance) transport than inner (neighboring provinces) regional transport, highlighting the significance of multi-regional cooperation in the future.
Jiandong Wang, Jia Xing, Shuxiao Wang, Rohit Mathur, Jiaping Wang, Yuqiang Zhang, Chao Liu, Jonathan Pleim, Dian Ding, Xing Chang, Jingkun Jiang, Peng Zhao, Shovan Kumar Sahu, Yuzhi Jin, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 22, 5147–5156, https://doi.org/10.5194/acp-22-5147-2022, https://doi.org/10.5194/acp-22-5147-2022, 2022
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Aerosols reduce surface solar radiation and change the photolysis rate and planetary boundary layer stability. In this study, the online coupled meteorological and chemistry model was used to explore the detailed pathway of how aerosol direct effects affect secondary inorganic aerosol. The effects through the dynamics pathway act as an equally or even more important route compared with the photolysis pathway in affecting secondary aerosol concentration in both summer and winter.
Yuqiang Zhang, Drew Shindell, Karl Seltzer, Lu Shen, Jean-Francois Lamarque, Qiang Zhang, Bo Zheng, Jia Xing, Zhe Jiang, and Lei Zhang
Atmos. Chem. Phys., 21, 16051–16065, https://doi.org/10.5194/acp-21-16051-2021, https://doi.org/10.5194/acp-21-16051-2021, 2021
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In this study, we use a global chemical transport model to simulate the effects on global air quality and human health due to emission changes in China from 2010 to 2017. By performing sensitivity analysis, we found that the air pollution control policies not only decrease the air pollutant concentration but also bring significant co-benefits in air quality to downwind regions. The benefits for the improved air pollution are dominated by PM2.5.
Shuping Zhang, Golam Sarwar, Jia Xing, Biwu Chu, Chaoyang Xue, Arunachalam Sarav, Dian Ding, Haotian Zheng, Yujing Mu, Fengkui Duan, Tao Ma, and Hong He
Atmos. Chem. Phys., 21, 15809–15826, https://doi.org/10.5194/acp-21-15809-2021, https://doi.org/10.5194/acp-21-15809-2021, 2021
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Six heterogeneous HONO chemistry updates in CMAQ significantly improve HONO concentration. HONO production is primarily controlled by the heterogeneous reactions on ground and aerosol surfaces during haze. Additional HONO chemistry updates increase OH and production of secondary aerosols: sulfate, nitrate, and SOA.
Sunling Gong, Hongli Liu, Bihui Zhang, Jianjun He, Hengde Zhang, Yaqiang Wang, Shuxiao Wang, Lei Zhang, and Jie Wang
Atmos. Chem. Phys., 21, 2999–3013, https://doi.org/10.5194/acp-21-2999-2021, https://doi.org/10.5194/acp-21-2999-2021, 2021
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Surface concentrations of PM2.5 in China have had a declining trend since 2013 across the country. This research found that the control measures of emission reduction are the dominant factors in the PM2.5 declining trends in various regions. The contribution by the meteorology to the surface PM2.5 concentrations from 2013 to 2019 was not found to show a consistent trend, fluctuating positively or negatively by about 5% on the annual average and 10–20% for the fall–winter heavy-pollution seasons.
Xiaodan Ma, Jianping Huang, Tianliang Zhao, Cheng Liu, Kaihui Zhao, Jia Xing, and Wei Xiao
Atmos. Chem. Phys., 21, 1–16, https://doi.org/10.5194/acp-21-1-2021, https://doi.org/10.5194/acp-21-1-2021, 2021
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The present work aims at identifying and quantifying the relative contributions of the key factors in driving a rapid increase in summertime surface O3 over the North China Plain during 2013–2019. In addition to anthropogenic emission reduction and meteorological variabilities, our study highlights the importance of inclusion of aerosol absorption and scattering properties rather than aerosol abundance only in accurate assessment of aerosol radiative effect on surface O3 formation and change.
Jia Xing, Siwei Li, Yueqi Jiang, Shuxiao Wang, Dian Ding, Zhaoxin Dong, Yun Zhu, and Jiming Hao
Atmos. Chem. Phys., 20, 14347–14359, https://doi.org/10.5194/acp-20-14347-2020, https://doi.org/10.5194/acp-20-14347-2020, 2020
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Quantifying emission changes is a prerequisite for assessment of control effectiveness in improving air quality. However, traditional bottom-up methods usually take months to perform and limit timely assessments. A novel method was developed by using a response model that provides real-time estimation of emission changes based on air quality observations. It was successfully applied to quantify emission changes on the North China Plain due to the COVID-19 pandemic shutdown.
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
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Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
Meng Gao, Zirui Liu, Bo Zheng, Dongsheng Ji, Peter Sherman, Shaojie Song, Jinyuan Xin, Cheng Liu, Yuesi Wang, Qiang Zhang, Jia Xing, Jingkun Jiang, Zifa Wang, Gregory R. Carmichael, and Michael B. McElroy
Atmos. Chem. Phys., 20, 1497–1505, https://doi.org/10.5194/acp-20-1497-2020, https://doi.org/10.5194/acp-20-1497-2020, 2020
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We quantified the relative influences of anthropogenic emissions and meteorological conditions on PM2.5 concentrations in Beijing over the winters of 2002–2016. Meteorological conditions over the study period would have led to an increase of haze in Beijing, but the strict emission control measures have suppressed the unfavorable influences of the recent climate.
Jia Xing, Dian Ding, Shuxiao Wang, Zhaoxin Dong, James T. Kelly, Carey Jang, Yun Zhu, and Jiming Hao
Atmos. Chem. Phys., 19, 13627–13646, https://doi.org/10.5194/acp-19-13627-2019, https://doi.org/10.5194/acp-19-13627-2019, 2019
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The study aims at addressing the challenge in efficient quantification of the nonlinear response of air pollution to precursor emission perturbations. The newly developed observable response indicators can be easily calculated by a combination of ambient concentrations of certain species. Their capability in representing the spatial and temporal variation in PM2.5 and O3 chemistry has also been well evaluated and applied in China.
Mingchen Ma, Yang Gao, Yuhang Wang, Shaoqing Zhang, L. Ruby Leung, Cheng Liu, Shuxiao Wang, Bin Zhao, Xing Chang, Hang Su, Tianqi Zhang, Lifang Sheng, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 12195–12207, https://doi.org/10.5194/acp-19-12195-2019, https://doi.org/10.5194/acp-19-12195-2019, 2019
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Ozone pollution has become severe in China, and extremely high ozone episodes occurred in summer 2017 over the North China Plain. While meteorology impacts are clear, we find that enhanced biogenic emissions, previously ignored by the community, driven by high vapor pressure deficit, land cover change and urban landscape contribute substantially to ozone formation. This study has significant implications for ozone pollution control with more frequent heat waves and urbanization growth in future.
Ling Qi and Shuxiao Wang
Atmos. Chem. Phys., 19, 11545–11557, https://doi.org/10.5194/acp-19-11545-2019, https://doi.org/10.5194/acp-19-11545-2019, 2019
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Black carbon (BC) contributes two-thirds of the climate impact of carbon dioxide, pushing methane into third place of the human contributors to global warming. This study shows that contributions from biomass burning (producing marginal lensing effect) have a strong spatial variation, from 20 % in Europe to 60 % in Africa. Thus, the inclusion of strong lensing-related absorption enhancement to all BC particles in previous estimates may lead to overestimating their positive radiative forcing.
Tuan V. Vu, Zongbo Shi, Jing Cheng, Qiang Zhang, Kebin He, Shuxiao Wang, and Roy M. Harrison
Atmos. Chem. Phys., 19, 11303–11314, https://doi.org/10.5194/acp-19-11303-2019, https://doi.org/10.5194/acp-19-11303-2019, 2019
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A 5-year Clean Air Action Plan was implemented in 2013 to improve ambient air quality in Beijing. Here, we applied a novel machine-learning-based model to determine the real trend in air quality from 2013 to 2017 in Beijing to assess the efficacy of the plan. We showed that the action plan led to a major reduction in primary emissions and significant improvement in air quality. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal combustion.
Xionghui Qiu, Qi Ying, Shuxiao Wang, Lei Duan, Jian Zhao, Jia Xing, Dian Ding, Yele Sun, Baoxian Liu, Aijun Shi, Xiao Yan, Qingcheng Xu, and Jiming Hao
Atmos. Chem. Phys., 19, 6737–6747, https://doi.org/10.5194/acp-19-6737-2019, https://doi.org/10.5194/acp-19-6737-2019, 2019
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Current chemical transport models cannot capture the diurnal and nocturnal variation in atmospheric nitrate, which may be relative to the missing atmospheric chlorine chemistry. In this work, the Community Multiscale Air Quality (CMAQ) model with improved chlorine heterogeneous chemistry is applied to simulate the impact of chlorine chemistry on summer nitrate concentrations in Beijing. The results of this work can improve our understanding of nitrate formation.
Junlan Feng, Yan Zhang, Shanshan Li, Jingbo Mao, Allison P. Patton, Yuyan Zhou, Weichun Ma, Cong Liu, Haidong Kan, Cheng Huang, Jingyu An, Li Li, Yin Shen, Qingyan Fu, Xinning Wang, Juan Liu, Shuxiao Wang, Dian Ding, Jie Cheng, Wangqi Ge, Hong Zhu, and Katherine Walker
Atmos. Chem. Phys., 19, 6167–6183, https://doi.org/10.5194/acp-19-6167-2019, https://doi.org/10.5194/acp-19-6167-2019, 2019
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This study aims to estimate the emissions, air quality and population exposure impacts of shipping in 2015, prior to the implementation of the DECAs. It shows that ship emissions within 12 NM of the shore could account for over 55 % of the shipping impact on air pollution in the YRD in summer. Ships entering the Yangtze River and other inland waterways of Shanghai contribute 40–80 % of the ship-related air pollution and population exposure，which both have important implications regarding policy.
Zhenying Xu, Mingxu Liu, Minsi Zhang, Yu Song, Shuxiao Wang, Lin Zhang, Tingting Xu, Tiantian Wang, Caiqing Yan, Tian Zhou, Yele Sun, Yuepeng Pan, Min Hu, Mei Zheng, and Tong Zhu
Atmos. Chem. Phys., 19, 5605–5613, https://doi.org/10.5194/acp-19-5605-2019, https://doi.org/10.5194/acp-19-5605-2019, 2019
Haotian Zheng, Siyi Cai, Shuxiao Wang, Bin Zhao, Xing Chang, and Jiming Hao
Atmos. Chem. Phys., 19, 3447–3462, https://doi.org/10.5194/acp-19-3447-2019, https://doi.org/10.5194/acp-19-3447-2019, 2019
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The heavy air pollution in the Beijing-Tianjin-Hebei (BTH) region is a global hot topic. We established a unit-based industrial emission inventory for the BTH region. The inventory significantly improved air quality modeling results; this improvement subsequently contributes to an accurate source apportionment of haze pollution and more precisely targeted decision making.
Shaojie Song, Meng Gao, Weiqi Xu, Yele Sun, Douglas R. Worsnop, John T. Jayne, Yuzhong Zhang, Lei Zhu, Mei Li, Zhen Zhou, Chunlei Cheng, Yibing Lv, Ying Wang, Wei Peng, Xiaobin Xu, Nan Lin, Yuxuan Wang, Shuxiao Wang, J. William Munger, Daniel J. Jacob, and Michael B. McElroy
Atmos. Chem. Phys., 19, 1357–1371, https://doi.org/10.5194/acp-19-1357-2019, https://doi.org/10.5194/acp-19-1357-2019, 2019
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Chemistry responsible for sulfate production in northern China winter haze remains mysterious. We propose a potentially key pathway through the reaction of formaldehyde and sulfur dioxide that has not been accounted for in previous studies. The special atmospheric conditions favor the formation and existence of their complex, hydroxymethanesulfonate (HMS).
Ge Zhang, Yang Gao, Wenju Cai, L. Ruby Leung, Shuxiao Wang, Bin Zhao, Minghuai Wang, Huayao Shan, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 565–576, https://doi.org/10.5194/acp-19-565-2019, https://doi.org/10.5194/acp-19-565-2019, 2019
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Based on observed data, this study reveals a distinct seesaw feature of abnormally high and low PM2.5 concentrations in December 2015 and January 2016 over North China. The mechanism of the seesaw pattern was found to be linked to a super El Niño and the Arctic Oscillation (AO). During the mature phase of El Niño in December 2015, the weakened East Asian winter monsoon favors strong haze formation; however, the circulation pattern was reversed in the next month due to the phase change of the AO.
Mingxu Liu, Xin Huang, Yu Song, Tingting Xu, Shuxiao Wang, Zhijun Wu, Min Hu, Lin Zhang, Qiang Zhang, Yuepeng Pan, Xuejun Liu, and Tong Zhu
Atmos. Chem. Phys., 18, 17933–17943, https://doi.org/10.5194/acp-18-17933-2018, https://doi.org/10.5194/acp-18-17933-2018, 2018
Yuqiang Zhang, J. Jason West, Rohit Mathur, Jia Xing, Christian Hogrefe, Shawn J. Roselle, Jesse O. Bash, Jonathan E. Pleim, Chuen-Meei Gan, and David C. Wong
Atmos. Chem. Phys., 18, 15003–15016, https://doi.org/10.5194/acp-18-15003-2018, https://doi.org/10.5194/acp-18-15003-2018, 2018
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Here we use a fine-resolution (36 km) self-consistent 21-year air quality simulation from 1990 to 2010, a health impact function, and annual county-level population and baseline mortality rate estimates to estimate annual mortality burdens from PM2.5 and O3 in the US, and also the contributions to the trends. We found that the PM2.5-related mortality burden has steadily decreased by 53 %, while the O3-related mortality burden has increased by 13 %, with larger inter-annual variabilities.
Yuqiang Zhang, Rohit Mathur, Jesse O. Bash, Christian Hogrefe, Jia Xing, and Shawn J. Roselle
Atmos. Chem. Phys., 18, 9091–9106, https://doi.org/10.5194/acp-18-9091-2018, https://doi.org/10.5194/acp-18-9091-2018, 2018
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For this study, we evaluated the WRF–CMAQ coupled model's ability to simulate the long-term trends of wet deposition of nitrogen and sulfur from 1990 to 2010 by comparing the model results with long-term observation datasets in the US. The model generally underestimates the wet deposition of both nitrogen and sulfur but captured well the decreasing trends for the deposition. Then we estimated the deposition budget in the US, including wet deposition and dry deposition from model simulations.
Yi Tang, Shuxiao Wang, Qingru Wu, Kaiyun Liu, Long Wang, Shu Li, Wei Gao, Lei Zhang, Haotian Zheng, Zhijian Li, and Jiming Hao
Atmos. Chem. Phys., 18, 8279–8291, https://doi.org/10.5194/acp-18-8279-2018, https://doi.org/10.5194/acp-18-8279-2018, 2018
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In this study, 3-year measurements of atmospheric Hg were carried out at a rural site in East China. A significant downward trend was observed during the sampling period. This study used a new approach that considers both cluster frequency and the Hg concentration associated with each cluster, and we calculated that atmospheric Hg from the whole region of China has caused a 70 % decline of GEM concentration at the Chongming monitoring site due to strict air pollution control policies in China.
Chandra Venkataraman, Michael Brauer, Kushal Tibrewal, Pankaj Sadavarte, Qiao Ma, Aaron Cohen, Sreelekha Chaliyakunnel, Joseph Frostad, Zbigniew Klimont, Randall V. Martin, Dylan B. Millet, Sajeev Philip, Katherine Walker, and Shuxiao Wang
Atmos. Chem. Phys., 18, 8017–8039, https://doi.org/10.5194/acp-18-8017-2018, https://doi.org/10.5194/acp-18-8017-2018, 2018
Jia Xing, Dian Ding, Shuxiao Wang, Bin Zhao, Carey Jang, Wenjing Wu, Fenfen Zhang, Yun Zhu, and Jiming Hao
Atmos. Chem. Phys., 18, 7799–7814, https://doi.org/10.5194/acp-18-7799-2018, https://doi.org/10.5194/acp-18-7799-2018, 2018
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NOx is the common precursor for both PM2.5 and O3 pollution, while the effectiveness of NOx controls for reducing PM2.5 and O3 are largely influenced by the ambient levels of NH3 and VOCs. This study developed a new method to quantify the nonlinear effectiveness of emission controls for reducing PM2.5 and O3. The new method not only substantially reduces the computational burden but also provides a series of quantitative indicators to quantify the nonlinear control effectiveness.
Shaojie Song, Meng Gao, Weiqi Xu, Jingyuan Shao, Guoliang Shi, Shuxiao Wang, Yuxuan Wang, Yele Sun, and Michael B. McElroy
Atmos. Chem. Phys., 18, 7423–7438, https://doi.org/10.5194/acp-18-7423-2018, https://doi.org/10.5194/acp-18-7423-2018, 2018
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Severe haze events occur frequently over northern China, especially in winter. Acidity plays a critical role in the formation of secondary PM2.5 and its toxicity. Using field measurements of gases and particles to critically evaluate two thermodynamic models routinely employed to determine particle acidity, we found that China's winter haze particles are generally within a moderately acidic range (pH 4–5) and not highly acidic (0) or neutral (7) as has been previously reported in the literature.
Xing Chang, Shuxiao Wang, Bin Zhao, Siyi Cai, and Jiming Hao
Atmos. Chem. Phys., 18, 4843–4858, https://doi.org/10.5194/acp-18-4843-2018, https://doi.org/10.5194/acp-18-4843-2018, 2018
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The Beijing–Tianjin–Hebei region in China has been suffering from a severe particulate matter pollution, and the inter-city transport of the pollutant plays an important role. The current research quantitatively assesses the transport process. We identify three transport pathways. The southwest–northwest one happens in both winter and summer. The transport is stronger at 300–1000 m, or 1–2 days before a pollution peak. The result may guide the joint emission control along the transport pathway.
Qian Yu, Yao Luo, Shuxiao Wang, Zhiqi Wang, Jiming Hao, and Lei Duan
Atmos. Chem. Phys., 18, 495–509, https://doi.org/10.5194/acp-18-495-2018, https://doi.org/10.5194/acp-18-495-2018, 2018
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This study provides high-quality direct observation data of a clean and a contaminated site in subtropical south China and quantifies the natural forest Hg emission. We find that clean and contaminated forests present a net GEM source with annual average values of 6.67 and 0.30 ng m-2 h-1, respectively; daily variations of GEM fluxes showed a source in the daytime with a peak at 13:00, and as a sink or balance at night; and higher atmospheric GEM concentration restricted the forest GEM emission.
Jianlin Hu, Xun Li, Lin Huang, Qi Ying, Qiang Zhang, Bin Zhao, Shuxiao Wang, and Hongliang Zhang
Atmos. Chem. Phys., 17, 13103–13118, https://doi.org/10.5194/acp-17-13103-2017, https://doi.org/10.5194/acp-17-13103-2017, 2017
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The model performance of CMAQ with WRF using four different emission inventories in China was validated and compared to obtain the best air pollutants prediction for health effect studies of severe air pollution. The differences in performance of chemical transport model were analyzed for different months and regions in the vast part of China and ensemble predictions were firstly obtained from different inventories for health analysis with minimized errors for pollutants including PM2.5 and O3.
Rohit Mathur, Jia Xing, Robert Gilliam, Golam Sarwar, Christian Hogrefe, Jonathan Pleim, George Pouliot, Shawn Roselle, Tanya L. Spero, David C. Wong, and Jeffrey Young
Atmos. Chem. Phys., 17, 12449–12474, https://doi.org/10.5194/acp-17-12449-2017, https://doi.org/10.5194/acp-17-12449-2017, 2017
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We extend CMAQ's applicability to the entire Northern Hemisphere to enable consistent examination of interactions between atmospheric processes occurring on various spatial and temporal scales. Improvements were made in model process representation, structure, and input data sets that enable a range of model applications including episodic intercontinental pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution–climate interactions.
Bin Zhao, Wenjing Wu, Shuxiao Wang, Jia Xing, Xing Chang, Kuo-Nan Liou, Jonathan H. Jiang, Yu Gu, Carey Jang, Joshua S. Fu, Yun Zhu, Jiandong Wang, Yan Lin, and Jiming Hao
Atmos. Chem. Phys., 17, 12031–12050, https://doi.org/10.5194/acp-17-12031-2017, https://doi.org/10.5194/acp-17-12031-2017, 2017
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Using over 1000 chemical transport model simulations in the Beijing–Tianjin–Hebei region, we find that the emissions of primary inorganic PM2.5 make the largest contribution to PM2.5 concentrations and thus should be prioritized in PM2.5 control strategies. Among the precursors, PM2.5 concentrations are primarily sensitive to the emissions of NH3, NMVOC+IVOC, and POA, and the sensitivities increase substantially for NH3 and NHx with the increase in emission reduction ratio.
Qingru Wu, Wei Gao, Shuxiao Wang, and Jiming Hao
Atmos. Chem. Phys., 17, 10423–10433, https://doi.org/10.5194/acp-17-10423-2017, https://doi.org/10.5194/acp-17-10423-2017, 2017
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Iron and steel production (ISP) is one of the most significant atmospheric Hg emission sources in China. Atmospheric Hg emissions from ISP increased from 11.5 t in 2000 to 32.75 t in 2015 with a peak of 35.65 t in 2013. In the coming years, emissions from ISP are expected to decrease. Although sinter/pellet plants and blast furnaces were the largest two emission processes, emissions from roasting plants and coke ovens accounted for 22 %–34 % of ISP’s emissions.
Jia Xing, Jiandong Wang, Rohit Mathur, Shuxiao Wang, Golam Sarwar, Jonathan Pleim, Christian Hogrefe, Yuqiang Zhang, Jingkun Jiang, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 17, 9869–9883, https://doi.org/10.5194/acp-17-9869-2017, https://doi.org/10.5194/acp-17-9869-2017, 2017
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The assessment of the impacts of aerosol direct effects (ADE) is important for understanding emission reduction strategies that seek co-benefits associated with reductions in both particulate matter and ozone. This study quantifies the ADE impacts on tropospheric ozone by using a two-way coupled meteorology and atmospheric chemistry model. Results suggest that reducing ADE may have the potential risk of increasing ozone in winter, but it will benefit the reduction of maxima ozone in summer.
Leiming Zhang, Seth Lyman, Huiting Mao, Che-Jen Lin, David A. Gay, Shuxiao Wang, Mae Sexauer Gustin, Xinbin Feng, and Frank Wania
Atmos. Chem. Phys., 17, 9133–9144, https://doi.org/10.5194/acp-17-9133-2017, https://doi.org/10.5194/acp-17-9133-2017, 2017
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Future research needs are proposed for improving the understanding of atmospheric mercury cycling. These include refinement of mercury emission estimations, quantification of dry deposition and air–surface exchange, improvement of the treatment of chemical mechanisms in chemical transport models, increase in the accuracy of oxidized mercury measurements, better interpretation of atmospheric mercury chemistry data, and harmonization of network operation.
Qiao Ma, Siyi Cai, Shuxiao Wang, Bin Zhao, Randall V. Martin, Michael Brauer, Aaron Cohen, Jingkun Jiang, Wei Zhou, Jiming Hao, Joseph Frostad, Mohammad H. Forouzanfar, and Richard T. Burnett
Atmos. Chem. Phys., 17, 4477–4491, https://doi.org/10.5194/acp-17-4477-2017, https://doi.org/10.5194/acp-17-4477-2017, 2017
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In order to quantitatively identify the contributions of coal combustion to airborne fine particles, we developed an emission inventory using up-to-date information and conducted simulations using an atmospheric model. Results show that coal combustion contributes 40 % of the airborne fine-particle concentration on national average in China. Among the subsectors of coal combustion, industrial coal burning is the dominant contributor, which should be prioritized when policies are applied.
Jianlin Hu, Peng Wang, Qi Ying, Hongliang Zhang, Jianjun Chen, Xinlei Ge, Xinghua Li, Jingkun Jiang, Shuxiao Wang, Jie Zhang, Yu Zhao, and Yingyi Zhang
Atmos. Chem. Phys., 17, 77–92, https://doi.org/10.5194/acp-17-77-2017, https://doi.org/10.5194/acp-17-77-2017, 2017
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An annual simulation of secondary organic aerosol (SOA) concentrations in China with updated SOA formation pathways reveals that SOA can be a significant contributor to PM2.5 in major urban areas. Summer SOA is dominated by emissions from biogenic sources, while winter SOA is dominated by anthropogenic emissions such as alkanes and aromatic compounds. Reactive surface uptake of dicarbonyls throughout the year and isoprene epoxides in summer is the most important contributor.
Yang Hua, Shuxiao Wang, Jiandong Wang, Jingkun Jiang, Tianshu Zhang, Yu Song, Ling Kang, Wei Zhou, Runlong Cai, Di Wu, Siwei Fan, Tong Wang, Xiaoqing Tang, Qiang Wei, Feng Sun, and Zhimei Xiao
Atmos. Chem. Phys., 16, 15451–15460, https://doi.org/10.5194/acp-16-15451-2016, https://doi.org/10.5194/acp-16-15451-2016, 2016
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The characteristics of three PM2.5 pollution episodes were analyzed during the APEC Summit at a rural site outside of Beijing. It was found that meteorological conditions on the ground could not explain the pollution process, while vertical parameters helped improve the understanding of heavy pollution processes. Our research suggests that regional transport of air pollutants contributes significantly to severe secondary particle pollution, even when local emission is controlled effectively.
Jia Xing, Rohit Mathur, Jonathan Pleim, Christian Hogrefe, Jiandong Wang, Chuen-Meei Gan, Golam Sarwar, David C. Wong, and Stuart McKeen
Atmos. Chem. Phys., 16, 10865–10877, https://doi.org/10.5194/acp-16-10865-2016, https://doi.org/10.5194/acp-16-10865-2016, 2016
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Downward transport of ozone from the stratosphere has large impacts on surface concentration and needs to be properly represented in regional models. This study developed a seasonally and spatially varying PV-based function from an investigation of the relationship between PV and O3. The implementation of the new function significantly improves the model's performance in O3 simulation, which enables a more accurate simulation of the vertical distribution of O3 across the Northern Hemisphere.
Bin Zhao, Kuo-Nan Liou, Yu Gu, Cenlin He, Wee-Liang Lee, Xing Chang, Qinbin Li, Shuxiao Wang, Hsien-Liang R. Tseng, Lai-Yung R. Leung, and Jiming Hao
Atmos. Chem. Phys., 16, 5841–5852, https://doi.org/10.5194/acp-16-5841-2016, https://doi.org/10.5194/acp-16-5841-2016, 2016
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We examine the impact of buildings on surface solar fluxes in Beijing by accounting for their 3-D structures. We find that inclusion of buildings changes surface solar fluxes by within ±1 W m−2, ±1–10 W m−2, and up to ±100 W m−2 at grid resolutions of 4 km, 800 m, and 90 m, respectively. We can resolve pairs of positive-negative flux deviations on different sides of buildings at ≤ 800 m resolutions. We should treat building-effect on solar fluxes differently in models with different resolutions.
Lei Zhang, Shuxiao Wang, Qingru Wu, Fengyang Wang, Che-Jen Lin, Leiming Zhang, Mulin Hui, Mei Yang, Haitao Su, and Jiming Hao
Atmos. Chem. Phys., 16, 2417–2433, https://doi.org/10.5194/acp-16-2417-2016, https://doi.org/10.5194/acp-16-2417-2016, 2016
C.-M. Gan, J. Pleim, R. Mathur, C. Hogrefe, C. N. Long, J. Xing, D. Wong, R. Gilliam, and C. Wei
Atmos. Chem. Phys., 15, 12193–12209, https://doi.org/10.5194/acp-15-12193-2015, https://doi.org/10.5194/acp-15-12193-2015, 2015
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This study attempts to determine the consequences of the changes in tropospheric aerosol burden arising from substantial reductions in emissions of SO2 and NOx associated with control measures under the Clean Air Act especially on trends in solar radiation. Comparisons of model results with observations of aerosol optical depth, aerosol concentration, and radiation demonstrate that the coupled WRF-CMAQ model is capable of replicating the trends well even though it tends to underestimate the AOD.
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
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This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
J. Xing, R. Mathur, J. Pleim, C. Hogrefe, C.-M. Gan, D. C. Wong, and C. Wei
Atmos. Chem. Phys., 15, 9997–10018, https://doi.org/10.5194/acp-15-9997-2015, https://doi.org/10.5194/acp-15-9997-2015, 2015
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The ability of a coupled meteorology-chemistry model (WRF-CMAQ) to reproduce the historical trend in AOD and clear-sky SWR over the N. Hemisphere has been evaluated through a comparison of 21-year simulated results with observation-derived records from 1990 to 2010. Questions of how well the model represents the regional and temporal variability of aerosol burden and DRE, and whether the model is able to capture past trends in aerosol loading and associated radiation effects, will be addressed.
J. Xing, R. Mathur, J. Pleim, C. Hogrefe, C.-M. Gan, D. C. Wong, C. Wei, R. Gilliam, and G. Pouliot
Atmos. Chem. Phys., 15, 2723–2747, https://doi.org/10.5194/acp-15-2723-2015, https://doi.org/10.5194/acp-15-2723-2015, 2015
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Model-simulated air quality trends over the past 2 decades largely agree with those derived from observations. In the relative amounts of VOC and NOx emission controls in different regions across the northern hemisphere have led to significantly different trends in tropospheric O3. Differences in the historical changes in the relative amounts of NH3, NOx and SO2 emissions also impact the trends in inorganic particulate matter amounts and composition in China, the U.S. and Europe.
B. Zhao, S. X. Wang, J. Xing, K. Fu, J. S. Fu, C. Jang, Y. Zhu, X. Y. Dong, Y. Gao, W. J. Wu, J. D. Wang, and J. M. Hao
Geosci. Model Dev., 8, 115–128, https://doi.org/10.5194/gmd-8-115-2015, https://doi.org/10.5194/gmd-8-115-2015, 2015
S. X. Wang, B. Zhao, S. Y. Cai, Z. Klimont, C. P. Nielsen, T. Morikawa, J. H. Woo, Y. Kim, X. Fu, J. Y. Xu, J. M. Hao, and K. B. He
Atmos. Chem. Phys., 14, 6571–6603, https://doi.org/10.5194/acp-14-6571-2014, https://doi.org/10.5194/acp-14-6571-2014, 2014
Z. Cheng, S. Wang, X. Fu, J. G. Watson, J. Jiang, Q. Fu, C. Chen, B. Xu, J. Yu, J. C. Chow, and J. Hao
Atmos. Chem. Phys., 14, 4573–4585, https://doi.org/10.5194/acp-14-4573-2014, https://doi.org/10.5194/acp-14-4573-2014, 2014
C.-M. Gan, J. Pleim, R. Mathur, C. Hogrefe, C. N. Long, J. Xing, S. Roselle, and C. Wei
Atmos. Chem. Phys., 14, 1701–1715, https://doi.org/10.5194/acp-14-1701-2014, https://doi.org/10.5194/acp-14-1701-2014, 2014
X. Fu, S. X. Wang, Z. Cheng, J. Xing, B. Zhao, J. D. Wang, and J. M. Hao
Atmos. Chem. Phys., 14, 1239–1254, https://doi.org/10.5194/acp-14-1239-2014, https://doi.org/10.5194/acp-14-1239-2014, 2014
L. Zhang, S. X. Wang, L. Wang, and J. M. Hao
Atmos. Chem. Phys., 13, 10505–10516, https://doi.org/10.5194/acp-13-10505-2013, https://doi.org/10.5194/acp-13-10505-2013, 2013
J. Xing, J. Pleim, R. Mathur, G. Pouliot, C. Hogrefe, C.-M. Gan, and C. Wei
Atmos. Chem. Phys., 13, 7531–7549, https://doi.org/10.5194/acp-13-7531-2013, https://doi.org/10.5194/acp-13-7531-2013, 2013
Related subject area
Atmospheric sciences
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Balloon drift estimation and improved position estimates for radiosondes
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-201, https://doi.org/10.5194/gmd-2023-201, 2023
Revised manuscript accepted for GMD
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In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-215, https://doi.org/10.5194/gmd-2023-215, 2023
Revised manuscript accepted for GMD
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The paper presents a method for calculating balloon drift from historical radiosonde ascent data. This drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes, but would also work for drop sondes, ozone sondes, or any other in-situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Jelena Radovic, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-197, https://doi.org/10.5194/gmd-2023-197, 2023
Revised manuscript accepted for GMD
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The initial and boundary conditions are of crucial importance for numerical model (e.g., PALM model) validation studies and have a large influence on the model results especially in the case of studying the atmosphere of a real, complex, and densely built urban environments. Our experiments with different driving conditions for the LES model PALM show its strong dependency on them which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-214, https://doi.org/10.5194/gmd-2023-214, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS), is well suited for calculating transport, as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Cited articles
Aardenne, J. V. and Pulles, T.: Uncertainty in emission inventories: What
do we mean and how could we assess it?, Thesis Wageningen University, 2002.
Appel, K. W., Pouliot, G. A., Simon, H., Sarwar, G., Pye, H. O. T., Napelenok, S. L., Akhtar, F., and Roselle, S. J.: Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0, Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, 2013.
Appel, K. W., Napelenok, S., Hogrefe, C., Pouliot, G., Foley, K. M.,
Roselle, S. J., Pleim, J. E., Bash, J., Pye, H. O. T., and Heath, N.:
Overview and Evaluation of the Community Multiscale Air Quality (CMAQ)
Modeling System Version 5.2, in: Air Pollution
Modeling and its Application XXV, edited by: Mensink, C. and Kallos, G., ITM 2016, Springer Proceedings in Complexity, Springer, Cham, 69–73, https://doi.org/10.1007/978-3-319-57645-9_11,
2018.
Bottou, L.: Large-Scale Machine Learning with Stochastic Gradient Descent,
Physica-Verlag HD, 2010.
Brioude, J., Angevine, W. M., Ahmadov, R., Kim, S.-W., Evan, S., McKeen, S. A., Hsie, E.-Y., Frost, G. J., Neuman, J. A., Pollack, I. B., Peischl, J., Ryerson, T. B., Holloway, J., Brown, S. S., Nowak, J. B., Roberts, J. M., Wofsy, S. C., Santoni, G. W., Oda, T., and Trainer, M.: Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO, NOx and CO2 and their impacts, Atmos. Chem. Phys., 13, 3661–3677, https://doi.org/10.5194/acp-13-3661-2013, 2013.
Byun, D.: Science algorithms of the EPA Models-3 community multiscale air
quality (CMAQ) modeling system, U.S. Environmental Protection Agency, EPA/600/R-99/030, 1999.
Cho, K., Merrienboer, B. V., Bahdanau, D., and Bengio, Y.: On the Properties
of Neural Machine Translation: Encoder-Decoder Approaches, arXiv [preprint],
arXiv:1409.1259, 2014.
Chung, J., Gulcehre, C., Cho, K., and Bengio, Y.: Empirical Evaluation of
Gated Recurrent Neural Networks on Sequence Modeling, arXiv [preprint],
arXiv:1412.3555, 2014.
Ding, D., Xing, J., Wang, S., Liu, K., and Hao, J.: Estimated contributions
of emissions controls, meteorological factors, population growth, and
changes in baseline mortality to reductions in ambient PM2.5 and
PM2.5-related mortality in China, 2013–2017, Environ. Health
Persp., 127, 067009, https://doi.org/10.1289/EHP4157, 2019.
Ding, D., Yun, Z., Jang, C., Lin, C. J., Wang, S., Fu, J., and Jian, G.:
Evaluation of health benefit using BenMAP-CE with an integrated scheme of
model and monitor data during Guangzhou Asian Games, J. Environ., 42, 9–18,
2016.
Fan, J., Li, Q., Hou, J., Feng, X., Karimian, H., and Lin, S.: A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W2, 15–22, https://doi.org/10.5194/isprs-annals-IV-4-W2-15-2017, 2017.
Friedl, M. A., Mciver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D.,
Strahler, A. H., Woodcock, C. E., Gopal, S., Schneider, A., and Cooper, A.:
Global land cover mapping from MODIS: algorithms and early results, Remote
Sens. Environ., 83, 287–302, 2002.
Ghil, M. and Malanotte-Rizzoli, P.: Data Assimilation in Meteorology and
Oceanography, Adv. Geophys., 33, 141–266, 1991.
Guo, S., Hu, M., Zamora, M. L., Peng, J., and Zhang, R.: Elucidating severe
urban haze formation in China, P. Natl. Acad.
Sci. USA, 111, 17373, https://doi.org/10.1073/pnas.1419604111, 2014.
He, D., Xia, Y., Qin, T., Wang, L., Yu, N., Liu, T.-Y., and Ma, W.-Y.: Dual
learning for machine translation, Proceedings of the 30th International
Conference on Neural Information Processing Systems, Barcelona, Spain,
820–828, 2016.
He, K.: Multi-resolution Emission Inventory for China (MEIC): model
framework and 1990–2010 anthropogenic emissions, American Geophysical Union, Fall Meeting, A32B-05, 2012.
He, K., Zhang, X., Ren, S., and Sun, J.: Deep Residual Learning for Image
Recognition, arXiv [preprint], arXiv:1512.03385, 2015a.
He, K., Zhang, X., Ren, S., and Sun, J.: Delving Deep into Rectifiers:
Surpassing Human-Level Performance on ImageNet Classification, arXiv [preprint], arXiv:1502.01852, 2015b.
Hochreiter, S. and Schmidhuber, J.: Long Short-Term Memory, Neural
Comput., 9, 1735–1780, 1997.
Huang, G., Liu, Z., Laurens, V. D. M., and Weinberger, K. Q.: Densely
Connected Convolutional Networks, arXiv [preprint], arXiv:1608.06993, 2016.
Huang, L., Liu, S., Yang, Z., Xing, J., Zhang, J., Bian, J., Li, S., Sahu,
S. K., Wang, S., and Liu, T.-Y.: The Inventory Optimization Code for
Exploring Deep Learning in Air Pollutant Emission Estimation Scale, Zenodo, https://doi.org/10.5281/zenodo.4607127, 2021.
Health Effects Institute: State of global air 2019, Health Effects Institute, Boston, 2019.
Ioffe, S. and Szegedy, C.: Batch Normalization: Accelerating Deep Network
Training by Reducing Internal Covariate Shift, arXiv [preprint], arXiv:1502.03167, 2015.
Kain, J. S.: The Kain–Fritsch convective parameterization: an update,
J. Appl. Meteorol., 43, 170–181, 2004.
Kingma, D. and Ba, J.: Adam: A Method for Stochastic Optimization, arXiv [preprint], arXiv:1412.6980, 2014.
Krizhevsky, A., Sutskever, I., and Hinton, G.: ImageNet Classification with
Deep Convolutional Neural Networks, Proceedings of the 25th International Conference on Neural Information Processing Systems, Lake Tahoe, NV, December 2012, 1097–1105, 2012.
Li, G.: Report on the completion of environmental conditions and
environmental protection targets for 2018, The National People's Congress, available at: http://wx.h2o-china.com/news/290686.html (last access: 26 June 2021), 2019 (in Chinese).
Liu, S., Xing, J., Westervelt, D. M., Liu, S., Ding, D., Fiore, A. M.,
Kinney, P. L., Zhang, Y., He, M. Z., and Zhang, H.: Role of emission
controls in reducing the 2050 climate change penalty for PM2.5 in China,
Sci. Total Environ., 765, 144338, https://doi.org/10.1016/j.scitotenv.2020.144338, 2020.
Liu, S., Xing, J., Zhang, H., Ding, D., Zhang, F., Zhao, B., Sahu, S. K.,
and Wang, S.: Climate-driven trends of biogenic volatile organic compound
emissions and their impacts on summertime ozone and secondary organic
aerosol in China in the 2050s, Atmos. Environ., 218, 117020, https://doi.org/10.1016/j.atmosenv.2019.117020, 2019.
Mlawer, E., Clough, S., and Kato, S.: Shortwave clear-sky model measurement
intercomparison using RRTM, in: Proceedings of the Eighth ARM Science Team Meeting, 23–27, 1998.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S.
A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, 1997.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics
on the development of trailing stratiform precipitation in a simulated
squall line: Comparison of one-and two-moment schemes, Mon. Weather
Rev., 137, 991–1007, 2009.
Pleim, J. E.: A combined local and nonlocal closure model for the
atmospheric boundary layer. Part I: Model description and testing, J. Appl. Meteorol. Climatol., 46, 1383–1395, 2007.
Pleim, J. E. and Xiu, A.: Development and testing of a surface flux and
planetary boundary layer model for application in mesoscale models, J. Appl. Meteorol., 34, 16–32, 1995.
Richter, A., Burrows, J. P., Nüss, H., Granier, C., and Niemeier, U.:
Increase in nitrogen dioxide over China observed from space, Nature,
437, 129–132, 2005.
Ronneberger, O., Fischer, P., and Brox, T.: U-Net: Convolutional Networks
for Biomedical Image Segmentation, arXiv [preprint], arXiv:1505.04597, 2015.
Sarwar, G., Luecken, D., Yarwood, G., Whitten, G. Z., and Carter, W. P. L.:
Impact of an Updated Carbon Bond Mechanism on Predictions from the CMAQ
Modeling System: Preliminary Assessment, J. Appl. Meteorol.
Climatol., 47, 3–14, 2008.
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., and
Salakhutdinov, R.: Dropout: A Simple Way to Prevent Neural Networks from
Overfitting, J. Mach. Learn. Res., 15, 1929–1958, 2014.
Tao, Q., Liu, F., Li, Y., and Sidorov, D.: Air Pollution Forecasting Using a
Deep Learning Model Based on 1D Convnets and Bidirectional GRU, IEEE Access,
7, 76690–76698, 2019.
US EPA Office of Research and Development: CMAQ (Version 5.2), Zenodo, https://doi.org/10.5281/zenodo.1167892, 2017.
Vallero, D.: Translating Diverse Environmental Data into Reliable
Information, Elsevier Reference Monographs, 25–41, 2017.
Vesilind, P. A., Peirce, J. J., and Weiner, R. F.: Air
Pollution, chap. 18, Elsevier Inc., 1988.
Wen, C., Liu, S., Yao, X., Peng, L., Li, X., Hu, Y., and Chi, T.: A novel
spatiotemporal convolutional long short-term neural network for air
pollution prediction, Sci. Total Environ., 654, 1091–1099,
2019.
Wikle, C. K.: Atmospheric modeling, data assimilation, and predictability,
Technometrics, 47, 521, https://doi.org/10.1198/tech.2005.s326, 2003.
Xing, J., Li, S., Ding, D., Kelly, J. T., and Hao, J.: Data Assimilation of
Ambient Concentrations of Multiple Air Pollutants Using an
Emission-Concentration Response Modeling Framework, Atmosphere, 11, 1289, https://doi.org/10.3390/atmos11121289, 2020a.
Xing, J., Li, S., Jiang, Y., Wang, S., Ding, D., Dong, Z., Zhu, Y., and Hao, J.: Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic on the North China Plain: a response modeling study, Atmos. Chem. Phys., 20, 14347–14359, https://doi.org/10.5194/acp-20-14347-2020, 2020b.
Xing, J., Zheng, S., Ding, D., Kelly, J. T., Wang, S., Li, S., Qin, T., Ma,
M., Dong, Z., Jang, C., Zhu, Y., Zheng, H., Ren, L., Liu, T.-Y., and Hao,
J.: Deep Learning for Prediction of the Air Quality Response to Emission
Changes, Environ. Sci. Technol., 54, 8589–8600, 2020c.
Xiu, A. and Pleim, J. E.: Development of a land surface model. Part I:
Application in a mesoscale meteorological model, J. Appl.
Meteorol., 40, 192–209, 2001.
Yang, X., Pang, J., Teng, F., Gong, R., and Springer, C.: The environmental
co-benefit and economic impact of China's low-carbon pathways: Evidence from
linking bottom-up and top-down models, Renew. Sustain. Energ.
Rev., 136, 110438, https://doi.org/10.1016/j.rser.2020.110438, 2021.
Zeiler, M. D., Krishnan, D., Taylor, G. W., and Fergus, R.: Deconvolutional
networks, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 13–18 June 2010.
Zhang, C., Be Ngio, S., Hardt, M., Recht, B., and Vinyals, O.: Understanding
deep learning requires rethinking generalization, arXiv [preprint], arXiv:1611.03530, 2016.
Zhao, B., Wang, S., Wang, J., Fu, J. S., Liu, T., Xu, J., Fu, X., and Hao,
J.: Impact of national NOx and SO2 control policies on particulate matter pollution in China, Atmos. Environ., 77, 453–463, 2013.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zheng, H., Zhao, B., Wang, S., Wang, T., Ding, D., Chang, X., Liu, K., Xing,
J., Dong, Z., and Aunan, K.: Transition in source contributions of PM2.5
exposure and associated premature mortality in China during 2005–2015,
Environ. Int., 132, 105111, https://doi.org/10.1016/j.envint.2019.105111, 2019.
Short summary
Accurate estimation of emissions is a prerequisite for effectively controlling air pollution, but current methods lack either sufficient data or a representation of nonlinearity. Here, we proposed a novel deep learning method to model the dual relationship between emissions and pollutant concentrations. Emissions can be updated by back-propagating the gradient of the loss function measuring the deviation between simulations and observations, resulting in better model performance.
Accurate estimation of emissions is a prerequisite for effectively controlling air pollution,...
