Articles | Volume 22, issue 8
https://doi.org/10.5194/acp-22-5265-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-5265-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Apr 2022
Research article |
| 22 Apr 2022
| 22 Apr 2022
Two-way coupled meteorology and air quality models in Asia: a systematic review and meta-analysis of impacts of aerosol feedbacks on meteorology and air quality
Chao Gao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
Aijun Xiu
CORRESPONDING AUTHOR
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
Xuelei Zhang
CORRESPONDING AUTHOR
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
Qingqing Tong
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
Hongmei Zhao
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
Shichun Zhang
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
Guangyi Yang
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
Mengduo Zhang
Key Laboratory of Wetland Ecology and Environment, Northeast Institute
of Geography and Agroecology, Chinese Academy of Sciences, Changchun,
130102, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
Related authors
Chao Gao, Xuelei Zhang, Aijun Xiu, Qingqing Tong, Hongmei Zhao, Shichun Zhang, Guangyi Yang, Mengduo Zhang, and Shengjin Xie
Geosci. Model Dev., 17, 2471–2492, https://doi.org/10.5194/gmd-17-2471-2024, https://doi.org/10.5194/gmd-17-2471-2024, 2024
Short summary
Short summary
A comprehensive comparison study is conducted targeting the performances of three two-way coupled meteorology and air quality models (WRF-CMAQ, WRF-Chem, and WRF-CHIMERE) for eastern China during 2017. The impacts of aerosol–radiation–cloud interactions on these models’ results are evaluated against satellite and surface observations. Further improvements to the calculation of aerosol–cloud interactions in these models are crucial to ensure more accurate and timely air quality forecasts.
Kun Wang, Chao Gao, Kai Wu, Kaiyun Liu, Haofan Wang, Mo Dan, Xiaohui Ji, and Qingqing Tong
Geosci. Model Dev., 16, 1961–1973, https://doi.org/10.5194/gmd-16-1961-2023, https://doi.org/10.5194/gmd-16-1961-2023, 2023
Short summary
Short summary
This study establishes an easy-to-use and integrated framework for a model-ready emission inventory for the Weather Research and Forecasting (WRF)–Air Quality Numerical Model (AQM). A free tool called the ISAT (Inventory Spatial Allocation Tool) was developed based on this framework. ISAT helps users complete the workflow from the WRF nested-domain configuration to a model-ready emission inventory for AQM with a regional emission inventory and a shapefile for the target region.
Chao Gao, Xuelei Zhang, Aijun Xiu, Qingqing Tong, Hongmei Zhao, Shichun Zhang, Guangyi Yang, Mengduo Zhang, and Shengjin Xie
Geosci. Model Dev., 17, 2471–2492, https://doi.org/10.5194/gmd-17-2471-2024, https://doi.org/10.5194/gmd-17-2471-2024, 2024
Short summary
Short summary
A comprehensive comparison study is conducted targeting the performances of three two-way coupled meteorology and air quality models (WRF-CMAQ, WRF-Chem, and WRF-CHIMERE) for eastern China during 2017. The impacts of aerosol–radiation–cloud interactions on these models’ results are evaluated against satellite and surface observations. Further improvements to the calculation of aerosol–cloud interactions in these models are crucial to ensure more accurate and timely air quality forecasts.
Kun Wang, Chao Gao, Kai Wu, Kaiyun Liu, Haofan Wang, Mo Dan, Xiaohui Ji, and Qingqing Tong
Geosci. Model Dev., 16, 1961–1973, https://doi.org/10.5194/gmd-16-1961-2023, https://doi.org/10.5194/gmd-16-1961-2023, 2023
Short summary
Short summary
This study establishes an easy-to-use and integrated framework for a model-ready emission inventory for the Weather Research and Forecasting (WRF)–Air Quality Numerical Model (AQM). A free tool called the ISAT (Inventory Spatial Allocation Tool) was developed based on this framework. ISAT helps users complete the workflow from the WRF nested-domain configuration to a model-ready emission inventory for AQM with a regional emission inventory and a shapefile for the target region.
Siqi Ma, Daniel Tong, Lok Lamsal, Julian Wang, Xuelei Zhang, Youhua Tang, Rick Saylor, Tianfeng Chai, Pius Lee, Patrick Campbell, Barry Baker, Shobha Kondragunta, Laura Judd, Timothy A. Berkoff, Scott J. Janz, and Ivanka Stajner
Atmos. Chem. Phys., 21, 16531–16553, https://doi.org/10.5194/acp-21-16531-2021, https://doi.org/10.5194/acp-21-16531-2021, 2021
Short summary
Short summary
Predicting high ozone gets more challenging as urban emissions decrease. How can different techniques be used to foretell the quality of air to better protect human health? We tested four techniques with the CMAQ model against observations during a field campaign over New York City. The new system proves to better predict the magnitude and timing of high ozone. These approaches can be extended to other regions to improve the predictability of high-O3 episodes in contemporary urban environments.
Tenglong Shi, Jiecan Cui, Yang Chen, Yue Zhou, Wei Pu, Xuanye Xu, Quanliang Chen, Xuelei Zhang, and Xin Wang
Atmos. Chem. Phys., 21, 6035–6051, https://doi.org/10.5194/acp-21-6035-2021, https://doi.org/10.5194/acp-21-6035-2021, 2021
Short summary
Short summary
We assess the effect of dust external and internal mixing with snow grains on the absorption coefficient and albedo of snowpack. The results suggest that dust–snow internal mixing strongly enhances snow absorption coefficient and albedo reduction relative to external mixing. Meanwhile, the possible non-uniform distribution of dust in snow grains may lead to significantly different values of absorption coefficient and albedo of snowpack in the visible spectral range.
Wei Pu, Jiecan Cui, Tenglong Shi, Xuelei Zhang, Cenlin He, and Xin Wang
Atmos. Chem. Phys., 19, 9949–9968, https://doi.org/10.5194/acp-19-9949-2019, https://doi.org/10.5194/acp-19-9949-2019, 2019
Short summary
Short summary
LAPs (light-absorbing particles) deposited on snow can decrease snow albedo and increase the absorption of solar radiation. Radiative forcing by LAPs will affect the regional hydrological cycle and climate. We use MODIS observations to retrieve the radiative forcing by LAPs in snow across northeastern China (NEC). The results of radiative forcing present distinct spatial variability. We find that the biases are negatively correlated with LAP concentrations and range from
~ 5 % to ~ 350 %.
Xuelei Zhang, Daniel Q. Tong, Guangjian Wu, Xin Wang, Aijun Xiu, Yongxiang Han, Tianli Xu, Shichun Zhang, and Hongmei Zhao
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-681, https://doi.org/10.5194/acp-2016-681, 2016
Revised manuscript has not been submitted
Short summary
Short summary
More detailed knowledge regarding recent variations in the characteristics of East Asian dust events and dust sources can effectively improve regional dust modeling and forecasts. Here we reassess the accuracy of previous predictions of trends in dust variations in East Asia, and establish a relatively detailed inventory of dust events based on satellite observations from 2000 to 2015.
Related subject area
Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Cluster-dynamics-based parameterization for sulfuric acid–dimethylamine nucleation: comparison and selection through box and three-dimensional modeling
Observed and CMIP6-model-simulated organic aerosol response to drought in the contiguous United States during summertime
Cooling radiative forcing effect enhancement of atmospheric amines and mineral particles caused by heterogeneous uptake and oxidation
Source-resolved atmospheric metal emissions, concentrations, and deposition fluxes into the East Asian seas
Analysis of secondary inorganic aerosols over the greater Athens area using the EPISODE–CityChem source dispersion and photochemistry model
Global estimates of ambient reactive nitrogen components during 2000–2100 based on the multi-stage model
The role of naphthalene and its derivatives in the formation of secondary organic aerosol in the Yangtze River Delta region, China
Unveiling the optimal regression model for source apportionment of the oxidative potential of PM10
Investigating the contribution of grown new particles to cloud condensation nuclei with largely varying preexisting particles – Part 2: Modeling chemical drivers and 3-D new particle formation occurrence
Technical note: Influence of different averaging metrics and temporal resolutions on the aerosol pH calculated by thermodynamic modeling
Dual roles of the inorganic aqueous phase on secondary organic aerosol growth from benzene and phenol
Global source apportionment of aerosols into major emission regions and sectors over 1850–2017
Modeling atmospheric brown carbon in the GISS ModelE Earth system model
Observation-constrained kinetic modeling of isoprene SOA formation in the atmosphere
Significant impact of urban tree biogenic emissions on air quality estimated by a bottom-up inventory and chemistry transport modeling
Secondary organic aerosols derived from intermediate-volatility n-alkanes adopt low-viscous phase state
Modeling the contribution of leads to sea spray aerosol in the high Arctic
Assessing the Effectiveness of SO2, NOx, and NH3 Emission Reductions in Mitigating Winter PM2.5 in Taiwan Using CMAQ Model
Modelling of atmospheric concentrations of fungal spores: a two-year simulation over France using CHIMERE
Modeling the drivers of fine PM pollution over Central Europe: impacts and contributions of emissions from different sources
Global Spatial Variation in the PM2.5 to AOD Relationship Strongly Influenced by Aerosol Composition
Reaction of SO3 with H2SO4 and its implications for aerosol particle formation in the gas phase and at the air–water interface
Weakened aerosol–radiation interaction exacerbating ozone pollution in eastern China since China's clean air actions
Uncertainties from biomass burning aerosols in air quality models obscure public health impacts in Southeast Asia
The Co-benefits of a Low-Carbon Future on Air Quality in Europe
Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique
Aqueous-phase chemistry of glyoxal with multifunctional reduced nitrogen compounds: a potential missing route for secondary brown carbon
An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment
Frequent haze events associated with transport and stagnation over the corridor between the North China Plain and Yangtze River Delta
Evaluation of WRF-Chem-simulated meteorology and aerosols over northern India during the severe pollution episode of 2016
How well are aerosol–cloud interactions represented in climate models? – Part 1: Understanding the sulfate aerosol production from the 2014–15 Holuhraun eruption
pH regulates the formation of organosulfates and inorganic sulfate from organic peroxide reaction with dissolved SO2 in aquatic media
Technical note: Accurate, reliable, and high-resolution air quality predictions by improving the Copernicus Atmosphere Monitoring Service using a novel statistical post-processing method
Measurement report: Rapid oxidation of phenolic compounds by O3 and HO•: effects of air-water interface and mineral dust in tropospheric chemical processes
Contribution of intermediate-volatility organic compounds from on-road transport to secondary organic aerosol levels in Europe
Development of an integrated model framework for multi-air-pollutant exposure assessments in high-density cities
CAMx–UNIPAR simulation of secondary organic aerosol mass formed from multiphase reactions of hydrocarbons under the Central Valley urban atmospheres of California
Impact of urbanization on fine particulate matter concentrations over central Europe
Measurement report: Assessing the impacts of emission uncertainty on aerosol optical properties and radiative forcing from biomass burning in peninsular Southeast Asia
The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics
Dynamics-based estimates of decline trend with fine temporal variations in China's PM2.5 emissions
Effects of simulated secondary organic aerosol water on PM1 levels and composition over the US
Reactive organic carbon air emissions from mobile sources in the United States
Development and evaluation of processes affecting simulation of diel fine particulate matter variation in the GEOS-Chem model
Substantially positive contributions of new particle formation to cloud condensation nuclei under low supersaturation in China based on numerical model improvements
Evolution of atmospheric age of particles and its implications for the formation of a severe haze event in eastern China
A multimodel evaluation of the potential impact of shipping on particle species in the Mediterranean Sea
How does tropospheric VOC chemistry affect climate? An investigation of preindustrial control simulations using the Community Earth System Model version 2
Anthropogenic amplification of biogenic secondary organic aerosol production
A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling
Jiewen Shen, Bin Zhao, Shuxiao Wang, An Ning, Yuyang Li, Runlong Cai, Da Gao, Biwu Chu, Yang Gao, Manish Shrivastava, Jingkun Jiang, Xiuhui Zhang, and Hong He
Atmos. Chem. Phys., 24, 10261–10278, https://doi.org/10.5194/acp-24-10261-2024, https://doi.org/10.5194/acp-24-10261-2024, 2024
Short summary
Short summary
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 being the most reliable one. This study offers a valuable reference for developing parameterizations of other nucleation systems and is meaningful for the accurate quantification of the environmental and climate impacts of new particle formation.
Wei Li and Yuxuan Wang
Atmos. Chem. Phys., 24, 9339–9353, https://doi.org/10.5194/acp-24-9339-2024, https://doi.org/10.5194/acp-24-9339-2024, 2024
Short summary
Short summary
Droughts immensely increased organic aerosol (OA) in the contiguous United States in summer (1998–2019), notably in the Pacific Northwest (PNW) and Southeast (SEUS). The OA rise in the SEUS is driven by the enhanced formation of epoxydiol-derived secondary organic aerosol due to the increase in biogenic volatile organic compounds and sulfate, while in the PNW, it is caused by wildfires. A total of 10 climate models captured the OA increase in the PNW yet greatly underestimated it in the SEUS.
Weina Zhang, Jianhua Mai, Zhichao Fan, Yongpeng Ji, Yuemeng Ji, Guiying Li, Yanpeng Gao, and Taicheng An
Atmos. Chem. Phys., 24, 9019–9030, https://doi.org/10.5194/acp-24-9019-2024, https://doi.org/10.5194/acp-24-9019-2024, 2024
Short summary
Short summary
This study reveals heterogeneous oxidation causes further radiative forcing effect (RFE) enhancement of amine–mineral mixed particles. Note that RFE increment is higher under clean conditions than that under polluted conditions, which is contributed to high-oxygen-content products. The enhanced RFE of amine–mineral particles caused by heterogenous oxidation is expected to alleviate warming effects.
Shenglan Jiang, Yan Zhang, Guangyuan Yu, Zimin Han, Junri Zhao, Tianle Zhang, and Mei Zheng
Atmos. Chem. Phys., 24, 8363–8381, https://doi.org/10.5194/acp-24-8363-2024, https://doi.org/10.5194/acp-24-8363-2024, 2024
Short summary
Short summary
This study aims to provide gridded data on sea-wide concentrations, deposition fluxes, and soluble deposition fluxes with detailed source categories of metals using the modified CMAQ model. We developed a monthly emission inventory of six metals – Fe, Al, V, Ni, Zn, and Cu – from terrestrial anthropogenic, ship, and dust sources in East Asia in 2017. Our results reveal the contribution of each source to the emissions, concentrations, and deposition fluxes of metals in the East Asian seas.
Stelios Myriokefalitakis, Matthias Karl, Kim A. Weiss, Dimitris Karagiannis, Eleni Athanasopoulou, Anastasia Kakouri, Aikaterini Bougiatioti, Eleni Liakakou, Iasonas Stavroulas, Georgios Papangelis, Georgios Grivas, Despina Paraskevopoulou, Orestis Speyer, Nikolaos Mihalopoulos, and Evangelos Gerasopoulos
Atmos. Chem. Phys., 24, 7815–7835, https://doi.org/10.5194/acp-24-7815-2024, https://doi.org/10.5194/acp-24-7815-2024, 2024
Short summary
Short summary
A state-of-the-art thermodynamic model has been coupled with the city-scale chemistry transport model EPISODE–CityChem to investigate the equilibrium between the inorganic gas and aerosol phases over the greater Athens area, Greece. The simulations indicate that the formation of nitrates in an urban environment is significantly affected by local nitrogen oxide emissions, as well as ambient temperature, relative humidity, photochemical activity, and the presence of non-volatile cations.
Rui Li, Yining Gao, Lijia Zhang, Yubing Shen, Tianzhao Xu, Wenwen Sun, and Gehui Wang
Atmos. Chem. Phys., 24, 7623–7636, https://doi.org/10.5194/acp-24-7623-2024, https://doi.org/10.5194/acp-24-7623-2024, 2024
Short summary
Short summary
A three-stage model was developed to obtain the global maps of reactive nitrogen components during 2000–2100. The results implied that cross-validation R2 values of four species showed satisfactory performance (R2 > 0.55). Most reactive nitrogen components, except NH3, in China showed increases during 2000–2013. In the future scenarios, SSP3-7.0 (traditional-energy scenario) and SSP1-2.6 (carbon neutrality scenario) showed the highest and lowest reactive nitrogen component concentrations.
Fei Ye, Jingyi Li, Yaqin Gao, Hongli Wang, Jingyu An, Cheng Huang, Song Guo, Keding Lu, Kangjia Gong, Haowen Zhang, Momei Qin, and Jianlin Hu
Atmos. Chem. Phys., 24, 7467–7479, https://doi.org/10.5194/acp-24-7467-2024, https://doi.org/10.5194/acp-24-7467-2024, 2024
Short summary
Short summary
Naphthalene (Nap) and methylnaphthalene (MN) are key precursors of secondary organic aerosol (SOA), yet their sources and sinks are often inadequately represented in air quality models. In this study, we incorporated detailed emissions, gas-phase chemistry, and SOA parameterization of Nap and MN into CMAQ to address this issue. The findings revealed remarkably high SOA formation potentials for these compounds despite their low emissions in the Yangtze River Delta region during summer.
Vy Dinh Ngoc Thuy, Jean-Luc Jaffrezo, Ian Hough, Pamela A. Dominutti, Guillaume Salque Moreton, Grégory Gille, Florie Francony, Arabelle Patron-Anquez, Olivier Favez, and Gaëlle Uzu
Atmos. Chem. Phys., 24, 7261–7282, https://doi.org/10.5194/acp-24-7261-2024, https://doi.org/10.5194/acp-24-7261-2024, 2024
Short summary
Short summary
The capacity of particulate matter (PM) to generate reactive oxygen species in vivo is represented by oxidative potential (OP). This study focuses on finding the appropriate model to evaluate the oxidative character of PM sources in six sites using the PM sources and OP. Eight regression techniques are introduced to assess the OP of PM. The study highlights the importance of selecting a model according to the input data characteristics and establishes some recommendations for the procedure.
Ming Chu, Xing Wei, Shangfei Hai, Yang Gao, Huiwang Gao, Yujiao Zhu, Biwu Chu, Nan Ma, Juan Hong, Yele Sun, and Xiaohong Yao
Atmos. Chem. Phys., 24, 6769–6786, https://doi.org/10.5194/acp-24-6769-2024, https://doi.org/10.5194/acp-24-6769-2024, 2024
Short summary
Short summary
We used a 20-bin WRF-Chem model to simulate NPF events in the NCP during a three-week observational period in the summer of 2019. The model was able to reproduce the observations during June 29–July 6, which was characterized by a high frequency of NPF occurrence.
Haoqi Wang, Xiao Tian, Wanting Zhao, Jiacheng Li, Haoyu Yu, Yinchang Feng, and Shaojie Song
Atmos. Chem. Phys., 24, 6583–6592, https://doi.org/10.5194/acp-24-6583-2024, https://doi.org/10.5194/acp-24-6583-2024, 2024
Short summary
Short summary
pH is a key property of ambient aerosols, which affect many atmospheric processes. As aerosol pH is a non-conservative parameter, diverse averaging metrics and temporal resolutions may influence the pH values calculated by thermodynamic models. This technical note seeks to quantitatively evaluate the average pH using varied metrics and resolutions. The ultimate goal is to establish standardized reporting practices in future research endeavors.
Jiwon Choi, Myoseon Jang, and Spencer Blau
Atmos. Chem. Phys., 24, 6567–6582, https://doi.org/10.5194/acp-24-6567-2024, https://doi.org/10.5194/acp-24-6567-2024, 2024
Short summary
Short summary
Persistent phenoxy radical (PPR), formed by phenol gas oxidation and its aqueous reaction, catalytically destroys O3 and retards secondary organic aerosol (SOA) growth. Explicit gas mechanisms including the formation of PPR and low-volatility products from the oxidation of phenol or benzene are applied to the UNIPAR model to predict SOA mass via multiphase reactions of precursors. Aqueous reactions of reactive organics increase SOA mass but retard SOA growth via heterogeneously formed PPR.
Yang Yang, Shaoxuan Mou, Hailong Wang, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 24, 6509–6523, https://doi.org/10.5194/acp-24-6509-2024, https://doi.org/10.5194/acp-24-6509-2024, 2024
Short summary
Short summary
The variations in anthropogenic aerosol concentrations and source contributions and their subsequent radiative impact in major emission regions during historical periods are quantified based on an aerosol-tagging system in E3SMv1. Due to the industrial development and implementation of economic policies, sources of anthropogenic aerosols show different variations, which has important implications for pollution prevention and control measures and decision-making for global collaboration.
Maegan A. DeLessio, Kostas Tsigaridis, Susanne E. Bauer, Jacek Chowdhary, and Gregory L. Schuster
Atmos. Chem. Phys., 24, 6275–6304, https://doi.org/10.5194/acp-24-6275-2024, https://doi.org/10.5194/acp-24-6275-2024, 2024
Short summary
Short summary
This study presents the first explicit representation of brown carbon aerosols in the GISS ModelE Earth system model (ESM). Model sensitivity to a range of brown carbon parameters and model performance compared to AERONET and MODIS retrievals of total aerosol properties were assessed. A summary of best practices for incorporating brown carbon into ModelE is also included.
Chuanyang Shen, Xiaoyan Yang, Joel Thornton, John Shilling, Chenyang Bi, Gabriel Isaacman-VanWertz, and Haofei Zhang
Atmos. Chem. Phys., 24, 6153–6175, https://doi.org/10.5194/acp-24-6153-2024, https://doi.org/10.5194/acp-24-6153-2024, 2024
Short summary
Short summary
In this work, a condensed multiphase isoprene oxidation mechanism was developed to simulate isoprene SOA formation from chamber and field studies. Our results show that the measured isoprene SOA mass concentrations can be reasonably reproduced. The simulation results indicate that multifunctional low-volatility products contribute significantly to total isoprene SOA. Our findings emphasize that the pathways to produce these low-volatility species should be considered in models.
Alice Maison, Lya Lugon, Soo-Jin Park, Alexia Baudic, Christopher Cantrell, Florian Couvidat, Barbara D'Anna, Claudia Di Biagio, Aline Gratien, Valérie Gros, Carmen Kalalian, Julien Kammer, Vincent Michoud, Jean-Eudes Petit, Marwa Shahin, Leila Simon, Myrto Valari, Jérémy Vigneron, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, https://doi.org/10.5194/acp-24-6011-2024, 2024
Short summary
Short summary
This study presents the development of a bottom-up inventory of urban tree biogenic emissions. Emissions are computed for each tree based on their location and characteristics and are integrated in the regional air quality model WRF-CHIMERE. The impact of these biogenic emissions on air quality is quantified for June–July 2022. Over Paris city, urban trees increase the concentrations of particulate organic matter by 4.6 %, of PM2.5 by 0.6 %, and of ozone by 1.0 % on average over 2 months.
Tommaso Galeazzo, Bernard Aumont, Marie Camredon, Richard Valorso, Yong B. Lim, Paul J. Ziemann, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 5549–5565, https://doi.org/10.5194/acp-24-5549-2024, https://doi.org/10.5194/acp-24-5549-2024, 2024
Short summary
Short summary
Secondary organic aerosol (SOA) derived from n-alkanes is a major component of anthropogenic particulate matter. We provide an analysis of n-alkane SOA by chemistry modeling, machine learning, and laboratory experiments, showing that n-alkane SOA adopts low-viscous semi-solid or liquid states. Our results indicate few kinetic limitations of mass accommodation in SOA formation, supporting the application of equilibrium partitioning for simulating n-alkane SOA in large-scale atmospheric models.
Rémy Lapere, Louis Marelle, Pierre Rampal, Laurent Brodeau, Christian Melsheimer, Gunnar Spreen, and Jennie L. Thomas
EGUsphere, https://doi.org/10.5194/egusphere-2024-1271, https://doi.org/10.5194/egusphere-2024-1271, 2024
Short summary
Short summary
Elongated open water areas in sea ice, called leads, can release marine aerosols into the atmosphere. In the Arctic, this source of atmospheric particles could play an important role for climate. However, the amount, seasonality and spatial distribution of such emissions are mostly unknown. Here, we propose a first parameterization for sea spray aerosols emitted through leads in sea ice and quantify their impact on aerosol populations in the high Arctic.
Ping-Chieh Huang, Hui-Ming Hung, Hsin-Chih Lai, and Charles C.-K. Chou
EGUsphere, https://doi.org/10.5194/egusphere-2024-343, https://doi.org/10.5194/egusphere-2024-343, 2024
Short summary
Short summary
Models were used to study ways to reduce PM pollution in Taiwan during winter. After considering various factors, such as physical processes and chemical reactions, we found that reducing NOx or NH3 emissions is more effective in mitigating PM2.5 than reducing SO2 emissions. When considering both efficiency and cost, reducing NH3 emissions seems to be a more suitable policy for the studied Taiwan's environment.
Matthieu Vida, Gilles Foret, Guillaume Siour, Florian Couvidat, Olivier Favez, Gaelle Uzu, Arineh Cholakian, Sébastien Conil, Matthias Beekmann, and Jean-Luc Jaffrezo
EGUsphere, https://doi.org/10.5194/egusphere-2024-698, https://doi.org/10.5194/egusphere-2024-698, 2024
Short summary
Short summary
We simulate 2 years of atmospheric fungal spores over France and use observations of polyols and primary biogenic factor from a PMF for the evaluation. The representation of emissions taking into account a proxy for vegetation surface and specific humidity enables us to reproduce very accurately the seasonal cycle of fungal spore. Furthermore, we estimate that fungal spores can can account for 20 % of PM10 and 40 % of the organic fraction of PM10 over vegetated areas in summer.
Lukáš Bartík, Peter Huszár, Jan Karlický, Ondřej Vlček, and Kryštof Eben
Atmos. Chem. Phys., 24, 4347–4387, https://doi.org/10.5194/acp-24-4347-2024, https://doi.org/10.5194/acp-24-4347-2024, 2024
Short summary
Short summary
The presented study deals with the attribution of fine particulate matter (PM2.5) concentrations to anthropogenic emissions over Central Europe using regional-scale models. It calculates the present-day contributions of different emissions sectors to concentrations of PM2.5 and its secondary components. Moreover, the study investigates the effect of chemical nonlinearities by using multiple source attribution methods and secondary organic aerosol calculation methods.
Haihui Zhu, Randall Martin, Aaron van Donkelaar, Melanie Hammer, Chi Li, Jun Meng, Christopher Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
EGUsphere, https://doi.org/10.5194/egusphere-2024-950, https://doi.org/10.5194/egusphere-2024-950, 2024
Short summary
Short summary
Ambient fine particulate matter (PM2.5) contributes to 4 million deaths every year globally. Satellite remote sensing of aerosol optical depth (AOD) coupled with a simulated PM2.5 to AOD relationship (η) can provide global PM2.5 estimation. This study aims to understand the spatial pattern and driving factors of η to guide future measurement and model efforts. We quantified η globally and regionally and found its spatial variation is strongly influenced by the aerosol composition.
Rui Wang, Yang Cheng, Shasha Chen, Rongrong Li, Yue Hu, Xiaokai Guo, Tianlei Zhang, Fengmin Song, and Hao Li
Atmos. Chem. Phys., 24, 4029–4046, https://doi.org/10.5194/acp-24-4029-2024, https://doi.org/10.5194/acp-24-4029-2024, 2024
Short summary
Short summary
We used quantum chemical calculations, Born–Oppenheimer molecular dynamics simulations, and the ACDC kinetic model to characterize SO3–H2SO4 interaction in the gas phase and at the air–water interface and to study the effect of H2S2O7 on H2SO4–NH3-based clusters. The work expands our understanding of new pathways for the loss of SO3 in acidic polluted areas and helps reveal some missing sources of NPF in metropolitan industrial regions and understand the atmospheric organic–sulfur cycle better.
Hao Yang, Lei Chen, Hong Liao, Jia Zhu, Wenjie Wang, and Xin Li
Atmos. Chem. Phys., 24, 4001–4015, https://doi.org/10.5194/acp-24-4001-2024, https://doi.org/10.5194/acp-24-4001-2024, 2024
Short summary
Short summary
The present study quantifies the response of aerosol–radiation interaction (ARI) to anthropogenic emission reduction from 2013 to 2017, with the main focus on the contribution to changed O3 concentrations over eastern China both in summer and winter using the WRF-Chem model. The weakened ARI due to decreased anthropogenic emission aggravates the summer (winter) O3 pollution by +0.81 ppb (+0.63 ppb), averaged over eastern China.
Margaret R. Marvin, Paul I. Palmer, Fei Yao, Mohd Talib Latif, and Md Firoz Khan
Atmos. Chem. Phys., 24, 3699–3715, https://doi.org/10.5194/acp-24-3699-2024, https://doi.org/10.5194/acp-24-3699-2024, 2024
Short summary
Short summary
We use an atmospheric chemistry model to investigate aerosols emitted from fire activity across Southeast Asia. We find that the limited nature of measurements in this region leads to large uncertainties that significantly hinder the model representation of these aerosols and their impacts on air quality. As a result, the number of monthly attributable deaths is underestimated by as many as 4500, particularly in March at the peak of the mainland burning season.
Connor J. Clayton, Daniel R. Marsh, Steven T. Turnock, Ailish M. Graham, Kirsty J. Pringle, Carly L. Reddington, Rajesh Kumar, and James B. McQuaid
EGUsphere, https://doi.org/10.5194/egusphere-2024-755, https://doi.org/10.5194/egusphere-2024-755, 2024
Short summary
Short summary
We demonstrate that strong climate mitigation could lead to vastly improved air quality in Europe, however, only minimal benefits are seen following the current trajectory of climate mitigation. We use a model that allows us to see where the improvements are greatest (Central Europe) and analyse what sectors are most important for achieving these co-benefits (agriculture/power).
Julie Camman, Benjamin Chazeau, Nicolas Marchand, Amandine Durand, Grégory Gille, Ludovic Lanzi, Jean-Luc Jaffrezo, Henri Wortham, and Gaëlle Uzu
Atmos. Chem. Phys., 24, 3257–3278, https://doi.org/10.5194/acp-24-3257-2024, https://doi.org/10.5194/acp-24-3257-2024, 2024
Short summary
Short summary
Fine particle (PM1) pollution is a major health issue in the city of Marseille, which is subject to numerous pollution sources. Sampling carried out during the summer enabled a fine characterization of the PM1 sources and their oxidative potential, a promising new metric as a proxy for health impact. PM1 came mainly from combustion sources, secondary ammonium sulfate, and organic nitrate, while the oxidative potential of PM1 came from these sources and from resuspended dust in the atmosphere.
Yuemeng Ji, Zhang Shi, Wenjian Li, Jiaxin Wang, Qiuju Shi, Yixin Li, Lei Gao, Ruize Ma, Weijun Lu, Lulu Xu, Yanpeng Gao, Guiying Li, and Taicheng An
Atmos. Chem. Phys., 24, 3079–3091, https://doi.org/10.5194/acp-24-3079-2024, https://doi.org/10.5194/acp-24-3079-2024, 2024
Short summary
Short summary
The formation mechanisms for secondary brown carbon (SBrC) contributed by multifunctional reduced nitrogen compounds (RNCs) remain unclear. Hence, from combined laboratory experiments and quantum chemical calculations, we investigated the heterogeneous reactions of glyoxal (GL) with multifunctional RNCs, which are driven by four-step indirect nucleophilic addition reactions. Our results show a possible missing source for SBrC formation on urban, regional, and global scales.
Elyse A. Pennington, Yuan Wang, Benjamin C. Schulze, Karl M. Seltzer, Jiani Yang, Bin Zhao, Zhe Jiang, Hongru Shi, Melissa Venecek, Daniel Chau, Benjamin N. Murphy, Christopher M. Kenseth, Ryan X. Ward, Havala O. T. Pye, and John H. Seinfeld
Atmos. Chem. Phys., 24, 2345–2363, https://doi.org/10.5194/acp-24-2345-2024, https://doi.org/10.5194/acp-24-2345-2024, 2024
Short summary
Short summary
To assess the air quality in Los Angeles (LA), we improved the CMAQ model by using dynamic traffic emissions and new secondary organic aerosol schemes to represent volatile chemical products. Source apportionment demonstrates that the urban areas of the LA Basin and vicinity are NOx-saturated, with the largest sensitivity of O3 to changes in volatile organic compounds in the urban core. The improvement and remaining issues shed light on the future direction of the model development.
Feifan Yan, Hang Su, Yafang Cheng, Rujin Huang, Hong Liao, Ting Yang, Yuanyuan Zhu, Shaoqing Zhang, Lifang Sheng, Wenbin Kou, Xinran Zeng, Shengnan Xiang, Xiaohong Yao, Huiwang Gao, and Yang Gao
Atmos. Chem. Phys., 24, 2365–2376, https://doi.org/10.5194/acp-24-2365-2024, https://doi.org/10.5194/acp-24-2365-2024, 2024
Short summary
Short summary
PM2.5 pollution is a major air quality issue deteriorating human health, and previous studies mostly focus on regions like the North China Plain and Yangtze River Delta. However, the characteristics of PM2.5 concentrations between these two regions are studied less often. Focusing on the transport corridor region, we identify an interesting seesaw transport phenomenon with stagnant weather conditions, conducive to PM2.5 accumulation over this region, resulting in large health effects.
Prerita Agarwal, David S. Stevenson, and Mathew R. Heal
Atmos. Chem. Phys., 24, 2239–2266, https://doi.org/10.5194/acp-24-2239-2024, https://doi.org/10.5194/acp-24-2239-2024, 2024
Short summary
Short summary
Air pollution levels across northern India are amongst some of the worst in the world, with episodic and hazardous haze events. Here, the ability of the WRF-Chem model to predict air quality over northern India is assessed against several datasets. Whilst surface wind speed and particle pollution peaks are over- and underestimated, respectively, meteorology and aerosol trends are adequately captured, and we conclude it is suitable for investigating severe particle pollution events.
George Jordan, Florent Malavelle, Ying Chen, Amy Peace, Eliza Duncan, Daniel G. Partridge, Paul Kim, Duncan Watson-Parris, Toshihiko Takemura, David Neubauer, Gunnar Myhre, Ragnhild Skeie, Anton Laakso, and James Haywood
Atmos. Chem. Phys., 24, 1939–1960, https://doi.org/10.5194/acp-24-1939-2024, https://doi.org/10.5194/acp-24-1939-2024, 2024
Short summary
Short summary
The 2014–15 Holuhraun eruption caused a huge aerosol plume in an otherwise unpolluted region, providing a chance to study how aerosol alters cloud properties. This two-part study uses observations and models to quantify this relationship’s impact on the Earth’s energy budget. Part 1 suggests the models capture the observed spatial and chemical evolution of the plume, yet no model plume is exact. Understanding these differences is key for Part 2, where changes to cloud properties are explored.
Lin Du, Xiaofan Lv, Makroni Lily, Kun Li, and Narcisse Tsona Tchinda
Atmos. Chem. Phys., 24, 1841–1853, https://doi.org/10.5194/acp-24-1841-2024, https://doi.org/10.5194/acp-24-1841-2024, 2024
Short summary
Short summary
This study explores the pH effect on the reaction of dissolved SO2 with selected organic peroxides. Results show that the formation of organic and/or inorganic sulfate from these peroxides strongly depends on their electronic structures, and these processes are likely to alter the chemical composition of dissolved organic matter in different ways. The rate constants of these reactions exhibit positive pH and temperature dependencies within pH 1–10 and 240–340 K ranges.
Angelo Riccio and Elena Chianese
Atmos. Chem. Phys., 24, 1673–1689, https://doi.org/10.5194/acp-24-1673-2024, https://doi.org/10.5194/acp-24-1673-2024, 2024
Short summary
Short summary
Starting from the Copernicus Atmosphere Monitoring Service (CAMS), we provided a novel ensemble statistical post-processing approach to improve their air quality predictions. Our approach is able to provide reliable short-term forecasts of pollutant concentrations, which is a key challenge in supporting national authorities in their tasks related to EU Air Quality Directives, such as planning and reporting the state of air quality to the citizens.
Yanru Huo, Mingxue Li, Xueyu Wang, Jianfei Sun, Yuxin Zhou, Yuhui Ma, and Maoxia He
EGUsphere, https://doi.org/10.5194/egusphere-2023-2856, https://doi.org/10.5194/egusphere-2023-2856, 2024
Short summary
Short summary
This work found that the A-W interface and TiO2 clusters promote the oxidation of phenolic compounds (PhCs) to varying degrees comparing with gas phase, and bulk water. Some by-products are more harmful than their parent compounds. This work provides important evidence for the rapid oxidation observed in the O3/HO• + PhCs experiments at the A-W interface and in the mineral dust.
Stella E. I. Manavi and Spyros N. Pandis
Atmos. Chem. Phys., 24, 891–909, https://doi.org/10.5194/acp-24-891-2024, https://doi.org/10.5194/acp-24-891-2024, 2024
Short summary
Short summary
Organic vapors of intermediate volatility have often been neglected as sources of atmospheric organic aerosol. In this work we use a new approach for their simulation and quantify the contribution of these compounds emitted by transportation sources (gasoline and diesel vehicles) to particulate matter over Europe. The estimated secondary organic aerosol levels are on average 60 % higher than predicted by previous approaches. However, these estimates are probably lower limits.
Zhiyuan Li, Kin-Fai Ho, Harry Fung Lee, and Steve Hung Lam Yim
Atmos. Chem. Phys., 24, 649–661, https://doi.org/10.5194/acp-24-649-2024, https://doi.org/10.5194/acp-24-649-2024, 2024
Short summary
Short summary
This study developed an integrated model framework for accurate multi-air-pollutant exposure assessments in high-density and high-rise cities. Following the proposed integrated model framework, we established multi-air-pollutant exposure models for four major PM10 chemical species as well as four criteria air pollutants with R2 values ranging from 0.73 to 0.93. The proposed framework serves as an important tool for combined exposure assessment in epidemiological studies.
Yujin Jo, Myoseon Jang, Sanghee Han, Azad Madhu, Bonyoung Koo, Yiqin Jia, Zechen Yu, Soontae Kim, and Jinsoo Park
Atmos. Chem. Phys., 24, 487–508, https://doi.org/10.5194/acp-24-487-2024, https://doi.org/10.5194/acp-24-487-2024, 2024
Short summary
Short summary
The CAMx–UNIPAR model simulated the SOA budget formed via multiphase reactions of hydrocarbons and the impact of emissions and climate on SOA characteristics under California’s urban environments during winter 2018. SOA growth was dominated by daytime oxidation of long-chain alkanes and nighttime terpene oxidation with O3 and NO−3 radicals. The spatial distributions of anthropogenic SOA were affected by the northwesterly wind, whereas those of biogenic SOA were insensitive to wind directions.
Peter Huszar, Alvaro Patricio Prieto Perez, Lukáš Bartík, Jan Karlický, and Anahi Villalba-Pradas
Atmos. Chem. Phys., 24, 397–425, https://doi.org/10.5194/acp-24-397-2024, https://doi.org/10.5194/acp-24-397-2024, 2024
Short summary
Short summary
Urbanization transforms rural land into artificial land, while due to human activities, it also introduces a great quantity of emissions. We quantify the impact of urbanization on the final particulate matter pollutant levels by looking not only at these emissions, but also at the way urban land cover influences meteorological conditions, how the removal of pollutants changes due to urban land cover, and how biogenic emissions from vegetation change due to less vegetation in urban areas.
Yinbao Jin, Yiming Liu, Xiao Lu, Xiaoyang Chen, Ao Shen, Haofan Wang, Yinping Cui, Yifei Xu, Siting Li, Jian Liu, Ming Zhang, Yingying Ma, and Qi Fan
Atmos. Chem. Phys., 24, 367–395, https://doi.org/10.5194/acp-24-367-2024, https://doi.org/10.5194/acp-24-367-2024, 2024
Short summary
Short summary
This study aims to address these issues by evaluating eight independent biomass burning (BB) emission inventories (GFED, FINN1.5, FINN2.5 MOS, FINN2.5 MOSVIS, GFAS, FEER, QFED, and IS4FIRES) using the WRF-Chem model and analyzing their impact on aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in peninsular Southeast Asia (PSEA) that occurred in March 2019.
Hamza Ahsan, Hailong Wang, Jingbo Wu, Mingxuan Wu, Steven J. Smith, Susanne Bauer, Harrison Suchyta, Dirk Olivié, Gunnar Myhre, Hitoshi Matsui, Huisheng Bian, Jean-François Lamarque, Ken Carslaw, Larry Horowitz, Leighton Regayre, Mian Chin, Michael Schulz, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Vaishali Naik
Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023, https://doi.org/10.5194/acp-23-14779-2023, 2023
Short summary
Short summary
We examine the impact of the assumed effective height of SO2 injection, SO2 and BC emission seasonality, and the assumed fraction of SO2 emissions injected as SO4 on climate and chemistry model results. We find that the SO2 injection height has a large impact on surface SO2 concentrations and, in some models, radiative flux. These assumptions are a
hiddensource of inter-model variability and may be leading to bias in some climate model results.
Zhen Peng, Lili Lei, Zhe-Min Tan, Meigen Zhang, Aijun Ding, and Xingxia Kou
Atmos. Chem. Phys., 23, 14505–14520, https://doi.org/10.5194/acp-23-14505-2023, https://doi.org/10.5194/acp-23-14505-2023, 2023
Short summary
Short summary
Annual PM2.5 emissions in China consistently decreased by about 3% to 5% from 2017 to 2020 with spatial variations and seasonal dependencies. High-temporal-resolution and dynamics-based PM2.5 emission estimates provide quantitative diurnal variations for each season. Significant reductions in PM2.5 emissions in the North China Plain and northeast of China in 2020 were caused by COVID-19.
Stylianos Kakavas, Spyros N. Pandis, and Athanasios Nenes
Atmos. Chem. Phys., 23, 13555–13564, https://doi.org/10.5194/acp-23-13555-2023, https://doi.org/10.5194/acp-23-13555-2023, 2023
Short summary
Short summary
Water uptake from organic species in aerosol can affect the partitioning of semi-volatile inorganic compounds but are not considered in global and chemical transport models. We address this with a version of the PM-CAMx model that considers such organic water effects and use it to carry out 1-year aerosol simulations over the continental US. We show that such organic water impacts can increase dry PM1 levels by up to 2 μg m-3 when RH levels and PM1 concentrations are high.
Benjamin N. Murphy, Darrell Sonntag, Karl M. Seltzer, Havala O. T. Pye, Christine Allen, Evan Murray, Claudia Toro, Drew R. Gentner, Cheng Huang, Shantanu Jathar, Li Li, Andrew A. May, and Allen L. Robinson
Atmos. Chem. Phys., 23, 13469–13483, https://doi.org/10.5194/acp-23-13469-2023, https://doi.org/10.5194/acp-23-13469-2023, 2023
Short summary
Short summary
We update methods for calculating organic particle and vapor emissions from mobile sources in the USA. Conventionally, particulate matter (PM) and volatile organic carbon (VOC) are speciated without consideration of primary semivolatile emissions. Our methods integrate state-of-the-science speciation profiles and correct for common artifacts when sampling emissions in a laboratory. We quantify impacts of the emission updates on ambient pollution with the Community Multiscale Air Quality model.
Yanshun Li, Randall V. Martin, Chi Li, Brian L. Boys, Aaron van Donkelaar, Jun Meng, and Jeffrey R. Pierce
Atmos. Chem. Phys., 23, 12525–12543, https://doi.org/10.5194/acp-23-12525-2023, https://doi.org/10.5194/acp-23-12525-2023, 2023
Short summary
Short summary
We developed and evaluated processes affecting within-day (diel) variability in PM2.5 concentrations in a chemical transport model over the contiguous US. Diel variability in PM2.5 for the contiguous US is driven by early-morning accumulation into a shallow mixed layer, decreases from mid-morning through afternoon with mixed-layer growth, increases from mid-afternoon through evening as the mixed-layer collapses, and decreases overnight as emissions decrease.
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
Short summary
Short summary
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.
Xiaodong Xie, Jianlin Hu, Momei Qin, Song Guo, Min Hu, Dongsheng Ji, Hongli Wang, Shengrong Lou, Cheng Huang, Chong Liu, Hongliang Zhang, Qi Ying, Hong Liao, and Yuanhang Zhang
Atmos. Chem. Phys., 23, 10563–10578, https://doi.org/10.5194/acp-23-10563-2023, https://doi.org/10.5194/acp-23-10563-2023, 2023
Short summary
Short summary
The atmospheric age of particles reflects how long particles have been formed and suspended in the atmosphere, which is closely associated with the evolution processes of particles. An analysis of the atmospheric age of PM2.5 provides a unique perspective on the evolution processes of different PM2.5 components. The results also shed lights on how to design effective emission control actions under unfavorable meteorological conditions.
Lea Fink, Matthias Karl, Volker Matthias, Sonia Oppo, Richard Kranenburg, Jeroen Kuenen, Sara Jutterström, Jana Moldanova, Elisa Majamäki, and Jukka-Pekka Jalkanen
Atmos. Chem. Phys., 23, 10163–10189, https://doi.org/10.5194/acp-23-10163-2023, https://doi.org/10.5194/acp-23-10163-2023, 2023
Short summary
Short summary
The Mediterranean Sea is a heavily trafficked shipping area, and air quality monitoring stations in numerous cities along the Mediterranean coast have detected high levels of air pollutants originating from shipping emissions. The current study investigates how existing restrictions on shipping-related emissions to the atmosphere ensure compliance with legislation. Focus was laid on fine particles and particle species, which were simulated with five different chemical transport models.
Noah A. Stanton and Neil F. Tandon
Atmos. Chem. Phys., 23, 9191–9216, https://doi.org/10.5194/acp-23-9191-2023, https://doi.org/10.5194/acp-23-9191-2023, 2023
Short summary
Short summary
Chemistry in Earth’s atmosphere has a potentially strong but very uncertain impact on climate. Past attempts to fully model chemistry in Earth’s troposphere (the lowest layer of the atmosphere) typically simplified the representation of Earth’s surface, which in turn limited the ability to simulate changes in climate. The cutting-edge model that we use in this study does not require such simplification, and we use it to examine the climate effects of chemical interactions in the troposphere.
Yiqi Zheng, Larry W. Horowitz, Raymond Menzel, David J. Paynter, Vaishali Naik, Jingyi Li, and Jingqiu Mao
Atmos. Chem. Phys., 23, 8993–9007, https://doi.org/10.5194/acp-23-8993-2023, https://doi.org/10.5194/acp-23-8993-2023, 2023
Short summary
Short summary
Biogenic secondary organic aerosols (SOAs) account for a large fraction of fine aerosol at the global scale. Using long-term measurements and a climate model, we investigate anthropogenic impacts on biogenic SOA at both decadal and centennial timescales. Results show that despite reductions in biogenic precursor emissions, SOA has been strongly amplified by anthropogenic emissions since the preindustrial era and exerts a cooling radiative forcing.
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
Short summary
Short summary
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.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 3. Sectional
representation, J. Geophys. Res.-Atmos., 107, AAC 1-1–AAC 1-6,
https://doi.org/10.1029/2001JD000483, 2002.
Ackerman, A. S., Toon, O. B., Stevens, D. E., Heymsfield, A. J., Ramanathan,
V., and Welton, E. J.: Reduction of tropical cloudiness by soot, Science, 288, 1042–1047, https://doi.org/10.1126/science.288.5468.1042,
2000.
Ahmadov, R., McKeen, S. A., Robinson, A. L., Bahreini, R., Middlebrook, A.
M., De Gouw, J. A., Meagher, J., Hsie, E., Edgerton, E., and Shaw, S.: A
volatility basis set model for summertime secondary organic aerosols over
the eastern United States in 2006, J. Geophys. Res.-Atmos., 117, D06301,
https://doi.org/10.1029/2011JD016831, 2012.
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness,
Science, 245, 1227–1230,
https://doi.org/10.1126/science.245.4923.1227, 1989.
An, Z., Huang, R.-J., Zhang, R., Tie, X., Li, G., Cao, J., Zhou, W., Shi,
Z., Han, Y., and Gu, Z.: Severe haze in northern China: A synergy of
anthropogenic emissions and atmospheric processes, P. Natl. Acad. Sci. USA,
116, 8657–8666, https://doi.org/10.1073/pnas.1900125116, 2019.
Andreae, M. O. and Rosenfeld, D.: Aerosol-cloud-precipitation interactions.
Part 1. The nature and sources of cloud-active aerosols, Earth-Science Rev.,
89, 13–41, https://doi.org/10.1016/j.earscirev.2008.03.001, 2008.
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. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., and Young, J. O.: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, 2017.
Appel, K. W., Bash, J. O., Fahey, K. M., Foley, K. M., Gilliam, R. C., Hogrefe, C., Hutzell, W. T., Kang, D., Mathur, R., Murphy, B. N., Napelenok, S. L., Nolte, C. G., Pleim, J. E., Pouliot, G. A., Pye, H. O. T., Ran, L., Roselle, S. J., Sarwar, G., Schwede, D. B., Sidi, F. I., Spero, T. L., and Wong, D. C.: The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation, Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, 2021.
Archer-Nicholls, S., Lowe, D., Lacey, F., Kumar, R., Xiao, Q., Liu, Y.,
Carter, E., Baumgartner, J., and Wiedinmyer, C.: Radiative effects of
residential sector emissions in China: sensitivity to uncertainty in black
carbon emissions, J. Geophys. Res.-Atmos., 124, 5029–5044,
https://doi.org/10.1029/2018JD030120, 2019.
Ashrafi, K., Motlagh, M. S., and Neyestani, S. E.: Dust storms modeling and
their impacts on air quality and radiation budget over Iran using WRF-Chem,
Air Qual. Atmos. Heal., 10, 1059–1076,
https://doi.org/10.1007/s11869-017-0494-8, 2017.
Bai, Y., Qi, H., Zhao, T., Zhou, Y., Liu, L., Xiong, J., Zhou, Z., and Cui,
C.: Simulation of the responses of rainstorm in the Yangtze River Middle
Reaches to changes in anthropogenic aerosol emissions, Atmos. Environ., 220,
117081, https://doi.org/10.1016/j.atmosenv.2019.117081, 2020.
Baklanov, A., Schlünzen, K., Suppan, P., Baldasano, J., Brunner, D., Aksoyoglu, S., Carmichael, G., Douros, J., Flemming, J., Forkel, R., Galmarini, S., Gauss, M., Grell, G., Hirtl, M., Joffre, S., Jorba, O., Kaas, E., Kaasik, M., Kallos, G., Kong, X., Korsholm, U., Kurganskiy, A., Kushta, J., Lohmann, U., Mahura, A., Manders-Groot, A., Maurizi, A., Moussiopoulos, N., Rao, S. T., Savage, N., Seigneur, C., Sokhi, R. S., Solazzo, E., Solomos, S., Sørensen, B., Tsegas, G., Vignati, E., Vogel, B., and Zhang, Y.: Online coupled regional meteorology chemistry models in Europe: current status and prospects, Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, 2014.
Baró, R., Jiménez-Guerrero, P., Balzarini, A., Curci, G., Forkel,
R., Grell, G., Hirtl, M., Honzak, L., Langer, M., and Pérez, J. L.:
Sensitivity analysis of the microphysics scheme in WRF-Chem contributions to
AQMEII phase 2, Atmos. Environ., 115, 620–629,
https://doi.org/10.1016/j.atmosenv.2015.01.047, 2015.
Barth, M. C., Rasch, P. J., Kiehl, J. T., Benkovitz, C. M., and Schwartz, S.
E.: Sulfur chemistry in the NCAR CCM: Description, evaluation, features and
sensitivity to aqueous chemistry, J. Geophys. Res., 105, 1387–1415,
https://doi.org/10.1029/1999JD900773, 2000.
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical
weather prediction, Nature, 525, 47–55,
https://doi.org/10.1038/nature14956, 2015.
Beard, K. V.: Terminal velocity and shape of cloud and precipitation drops
aloft, J. Atmos. Sci., 33, 851–864,
https://doi.org/10.1175/1520-0469(1976)033<0851:TVASOC>2.0.CO;2, 1976.
Bei, N., Wu, J., Elser, M., Feng, T., Cao, J., El-Haddad, I., Li, X., Huang, R., Li, Z., Long, X., Xing, L., Zhao, S., Tie, X., Prévôt, A. S. H., and Li, G.: Impacts of meteorological uncertainties on the haze formation in Beijing–Tianjin–Hebei (BTH) during wintertime: a case study, Atmos. Chem. Phys., 17, 14579–14591, https://doi.org/10.5194/acp-17-14579-2017, 2017.
Beig, G., Chate, D. M., Ghude, S. D., Mahajan, A. S., Srinivas, R., Ali, K.,
Sahu, S. K., Parkhi, N., Surendran, D., and Trimbake, H. R.: Quantifying the
effect of air quality control measures during the 2010 Commonwealth Games at
Delhi, India, Atmos. Environ., 80, 455–463,
https://doi.org/10.1016/j.atmosenv.2013.08.012, 2013.
Bellouin, N., Jones, A., Haywood, J., and Christopher, S. A.: Updated
estimate of aerosol direct radiative forcing from satellite observations and
comparison against the Hadley Centre climate model, J. Geophys. Res.-Atmos.,
113, D10205, https://doi.org/10.1029/2007JD009385, 2008.
Benas, N., Meirink, J. F., Karlsson, K.-G., Stengel, M., and Stammes, P.: Satellite observations of aerosols and clouds over southern China from 2006 to 2015: analysis of changes and possible interaction mechanisms, Atmos. Chem. Phys., 20, 457–474, https://doi.org/10.5194/acp-20-457-2020, 2020.
Bennartz, R., Fan, J., Rausch, J., Leung, L. R., and Heidinger, A. K.:
Pollution from China increases cloud droplet number, suppresses rain over
the East China Sea, Geophys. Res. Lett., 38, L09704,
https://doi.org/10.1029/2011GL047235, 2011.
Bharali, C., Nair, V. S., Chutia, L., and Babu, S. S.: Modeling of the
effects of wintertime aerosols on boundary layer properties over the Indo
Gangetic Plain, J. Geophys. Res.-Atmos., 124, 4141–4157,
https://doi.org/10.1029/2018JD029758, 2019.
Bhattacharya, A., Chakraborty, A., and Venugopal, V.: Role of aerosols in
modulating cloud properties during active–break cycle of Indian summer
monsoon, Clim. Dynam., 49, 2131–2145,
https://doi.org/10.1007/s00382-016-3437-4, 2017.
Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multiscale Air
Quality (CMAQ) model aerosol component 1. Model description, J. Geophys. Res.-Atmos., 108, 4183, https://doi.org/10.1029/2001JD001409, 2003.
Binkowski, F. S. and Shankar, U.: The regional particulate matter model: 1.
Model description and preliminary results, J. Geophys. Res.-Atmos., 100,
26191–26209, https://doi.org/10.1029/95JD02093, 1995.
Bollasina, M. A., Ming, Y., and Ramaswamy, V.: Anthropogenic aerosols and
the weakening of the South Asian summer monsoon, Science, 334,
502–505, https://doi.org/10.1126/science.1204994, 2011.
Bran, S. H., Jose, S., and Srivastava, R.: Investigation of optical and
radiative properties of aerosols during an intense dust storm: A regional
climate modeling approach, J. Atmos. Solar-Terr. Phy., 168, 21–31,
https://doi.org/10.1016/j.jastp.2018.01.003, 2018.
Briant, R., Tuccella, P., Deroubaix, A., Khvorostyanov, D., Menut, L., Mailler, S., and Turquety, S.: Aerosol–radiation interaction modelling using online coupling between the WRF 3.7.1 meteorological model and the CHIMERE 2016 chemistry-transport model, through the OASIS3-MCT coupler, Geosci. Model Dev., 10, 927–944, https://doi.org/10.5194/gmd-10-927-2017, 2017.
Brunekreef, B. and Holgate, S. T.: Air pollution and health, Lancet, 360,
1233–1242, https://doi.org/10.1016/S0140-6736(02)11274-8, 2002.
Brunner, D., Savage, N., Jorba, O., Eder, B., Giordano, L., Badia, A.,
Balzarini, A., Baro, R., Bianconi, R., and Chemel, C.: Comparative analysis
of meteorological performance of coupled chemistry-meteorology models in the
context of AQMEII phase 2, Atmos. Environ., 115, 470–498,
https://doi.org/10.1016/j.atmosenv.2014.12.032, 2015.
Byun, D. and Schere, K. L.: Review of the governing equations, computational
algorithms, and other components of the Models-3 Community Multiscale Air
Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77,
https://doi.org/10.1115/1.2128636, 2006.
Campbell, P., Zhang, Y., Yahya, K., Wang, K., Hogrefe, C., Pouliot, G.,
Knote, C., Hodzic, A., San Jose, R., and Perez, J. L.: A multi-model
assessment for the 2006 and 2010 simulations under the Air Quality Model
Evaluation International Initiative (AQMEII) phase 2 over North America:
Part I. Indicators of the sensitivity of O3 and PM2.5 formation
regimes, Atmos. Environ., 115, 569–586,
https://doi.org/10.1016/j.atmosenv.2014.12.026, 2015.
Campbell, P., Zhang, Y., Wang, K., Leung, R., Fan, J., Zheng, B., Zhang, Q.,
and He, K.: Evaluation of a multi-scale WRF-CAM5 simulation during the 2010
East Asian Summer Monsoon, Atmos. Environ., 169, 204–217,
https://doi.org/10.1016/j.atmosenv.2017.09.008, 2017.
Carlton, A. G., Bhave, P. V, Napelenok, S. L., Edney, E. O., Sarwar, G.,
Pinder, R. W., Pouliot, G. A., and Houyoux, M.: Model representation of
secondary organic aerosol in CMAQv4.7, Environ. Sci. Technol., 44,
8553–8560, https://doi.org/10.1021/es100636q, 2010.
Casazza, M., Lega, M., Liu, G., Ulgiati, S., and Endreny, T. A.: Aerosol
pollution, including eroded soils, intensifies cloud growth, precipitation,
and soil erosion: A review, J. Clean. Prod., 189, 135–144,
https://doi.org/10.1016/j.jclepro.2018.04.004, 2018.
Chang, S.: Characteristics of aerosols and cloud
condensation nuclei (CCN) over China investigated by the two-way coupled WRFCMAQ
air quality model, MS thesis, College of Environmental and Resource
Sciences, Zhejiang University, China, 79 pp., 2018.
Chapman, E. G., Gustafson Jr., W. I., Easter, R. C., Barnard, J. C., Ghan, S. J., Pekour, M. S., and Fast, J. D.: Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources, Atmos. Chem. Phys., 9, 945–964, https://doi.org/10.5194/acp-9-945-2009, 2009.
Chen, D.-S., Ma, X., Xie, X., Wei, P., Wen, W., Xu, T., Yang, N., Gao, Q.,
Shi, H., and Guo, X.: Modelling the effect of aerosol feedbacks on the
regional meteorology factors over China, Aerosol. Air. Qual. Res., 15,
1559–1579, https://doi.org/10.4209/aaqr.2014.11.0272, 2015.
Chen, J., Li, C., Ristovski, Z., Milic, A., Gu, Y., Islam, M. S., Wang, S.,
Hao, J., Zhang, H., and He, C.: A review of biomass burning: Emissions and
impacts on air quality, health and climate in China, Sci. Total Environ.,
579, 1000–1034, https://doi.org/10.1016/j.scitotenv.2016.11.025, 2017.
Chen, L., Gao, Y., Zhang, M., Fu, J. S., Zhu, J., Liao, H., Li, J., Huang, K., Ge, B., Wang, X., Lam, Y. F., Lin, C.-Y., Itahashi, S., Nagashima, T., Kajino, M., Yamaji, K., Wang, Z., and Kurokawa, J.: MICS-Asia III: multi-model comparison and evaluation of aerosol over East Asia, Atmos. Chem. Phys., 19, 11911–11937, https://doi.org/10.5194/acp-19-11911-2019, 2019a.
Chen, L., Zhu, J., Liao, H., Gao, Y., Qiu, Y., Zhang, M., Liu, Z., Li, N., and Wang, Y.: Assessing the formation and evolution mechanisms of severe haze pollution in the Beijing–Tianjin–Hebei region using process analysis, Atmos. Chem. Phys., 19, 10845–10864, https://doi.org/10.5194/acp-19-10845-2019, 2019b.
Chen, S., Huang, J., Zhao, C., Qian, Y., Leung, L. R., and Yang, B.:
Modeling the transport and radiative forcing of Taklimakan dust over the
Tibetan Plateau: A case study in the summer of 2006, J. Geophys. Res.-Atmos., 118, 797–812, https://doi.org/10.1002/jgrd.50122, 2013.
Chen, S., Zhao, C., Qian, Y., Leung, L. R., Huang, J., Huang, Z., Bi, J.,
Zhang, W., Shi, J., and Yang, L.: Regional modeling of dust mass balance and
radiative forcing over East Asia using WRF-Chem, Aeolian Res., 15, 15–30,
https://doi.org/10.1016/j.aeolia.2014.02.001, 2014.
Chen, S., Huang, J., Kang, L., Wang, H., Ma, X., He, Y., Yuan, T., Yang, B., Huang, Z., and Zhang, G.: Emission, transport, and radiative effects of mineral dust from the Taklimakan and Gobi deserts: comparison of measurements and model results, Atmos. Chem. Phys., 17, 2401–2421, https://doi.org/10.5194/acp-17-2401-2017, 2017a.
Chen, S., Huang, J., Qian, Y., Zhao, C., Kang, L., Yang, B., Wang, Y., Liu,
Y., Yuan, T., and Wang, T.: An overview of mineral dust modeling over East
Asia, J. Meteorol. Res., 31, 633–653,
https://doi.org/10.1007/s13351-017-6142-2, 2017b.
Chen, X., Wang, Z., Yu, F., Pan, X., Li, J., Ge, B., Wang, Z., Hu, M., Yang,
W., and Chen, H.: Estimation of atmospheric aging time of black carbon
particles in the polluted atmosphere over central-eastern China using
microphysical process analysis in regional chemical transport model, Atmos.
Environ., 163, 44–56, https://doi.org/10.1016/j.atmosenv.2017.05.016, 2017.
Chen, X., Yang, W., Wang, Z., Li, J., Hu, M., An, J., Wu, Q., Wang, Z.,
Chen, H., and Wei, Y.: Improving new particle formation simulation by
coupling a volatility-basis set (VBS) organic aerosol module in
NAQPMS+APM, Atmos. Environ., 204, 1–11,
https://doi.org/10.1016/j.atmosenv.2019.01.053, 2019.
Chen, X., Yu, F., Yang, W., Sun, Y., Chen, H., Du, W., Zhao, J., Wei, Y., Wei, L., Du, H., Wang, Z., Wu, Q., Li, J., An, J., and Wang, Z.: Global–regional nested simulation of particle number concentration by combing microphysical processes with an evolving organic aerosol module, Atmos. Chem. Phys., 21, 9343–9366, https://doi.org/10.5194/acp-21-9343-2021, 2021.
Chen, Y., Zhang, Y., Fan, J., Leung, L.-Y. R., Zhang, Q., and He, K.:
Application of an online-coupled regional climate model, WRF-CAM5, over East
Asia for examination of ice nucleation schemes: Part I. Comprehensive model
evaluation and trend analysis for 2006 and 2011, 3, 627–667,
https://doi.org/10.3390/cli3030627, 2015.
Choobari, O. A., Zawar-Reza, P., and Sturman, A.: The global distribution of
mineral dust and its impacts on the climate system: A review, Atmos. Res.,
138, 152–165, https://doi.org/10.1016/j.atmosres.2013.11.007, 2014.
Conibear, L., Butt, E. W., Knote, C., Arnold, S. R., and Spracklen, D. V.:
Residential energy use emissions dominate health impacts from exposure to
ambient particulate matter in India, Nat. Commun., 9, 1–9,
https://doi.org/10.1038/s41467-018-02986-7, 2018a.
Conibear, L., Butt, E. W., Knote, C., Arnold, S. R., and Spracklen, D. V.:
Stringent Emission Control Policies Can Provide Large Improvements in Air
Quality and Public Health in India, GeoHealth, 2, 196–211,
https://doi.org/10.1029/2018gh000139, 2018b.
Conti, G. O., Heibati, B., Kloog, I., Fiore, M., and Ferrante, M.: A review
of AirQ Models and their applications for forecasting the air pollution
health outcomes, Environ. Sci. Pollut. Res., 24, 6426–6445,
https://doi.org/10.1007/s11356-016-8180-1, 2017.
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017.
Cuchiara, G. C., Li, X., Carvalho, J., and Rappenglück, B.:
Intercomparison of planetary boundary layer parameterization and its impacts
on surface ozone concentration in the WRF/Chem model for a case study in
Houston/Texas, Atmos. Environ., 96, 175–185,
https://doi.org/10.1016/j.atmosenv.2014.07.013, 2014.
Dahutia, P., Pathak, B., and Bhuyan, P. K.: Vertical distribution of
aerosols and clouds over north-eastern South Asia: Aerosol-cloud
interactions, Atmos. Environ., 215, 116882,
https://doi.org/10.1016/j.atmosenv.2019.116882, 2019.
Ding, A. J., Huang, X., Nie, W., Sun, J. N., Kerminen, V., Petäjä,
T., Su, H., Cheng, Y. F., Yang, X., and Wang, M. H.: Enhanced haze pollution
by black carbon in megacities in China, Geophys. Res. Lett., 43, 2873–2879,
https://doi.org/10.1002/2016GL067745, 2016.
Ding, Q., Sun, J., Huang, X., Ding, A., Zou, J., Yang, X., and Fu, C.: Impacts of black carbon on the formation of advection–radiation fog during a haze pollution episode in eastern China, Atmos. Chem. Phys., 19, 7759–7774, https://doi.org/10.5194/acp-19-7759-2019, 2019.
Dipu, S., Prabha, T. V, Pandithurai, G., Dudhia, J., Pfister, G., Rajesh,
K., and Goswami, B. N.: Impact of elevated aerosol layer on the cloud
macrophysical properties prior to monsoon onset, Atmos. Environ., 70,
454–467, https://doi.org/10.1016/j.atmosenv.2012.12.036, 2013.
Donat, M. G., Lowry, A. L., Alexander, L. V, O'Gorman, P. A., and Maher, N.:
More extreme precipitation in the world's dry and wet regions, Nat. Clim.
Chang., 6, 508–513, https://doi.org/10.1038/nclimate2941, 2016.
Dong, X., Fu, J. S., Huang, K., Zhu, Q., and Tipton, M.: Regional Climate
Effects of Biomass Burning and Dust in East Asia: Evidence From Modeling and
Observation, Geophys. Res. Lett., 46, 11490–11499,
https://doi.org/10.1029/2019GL083894, 2019.
Easter, R. C., Ghan, S. J., Zhang, Y., Saylor, R. D., Chapman, E. G.,
Laulainen, N. S., Abdul-Razzak, H., Leung, L. R., Bian, X., and Zaveri, R.
A.: MIRAGE: Model description and evaluation of aerosols and trace gases, J. Geophys. Res.-Atmos., 109, D20210, https://doi.org/10.1029/2004JD004571, 2004.
Eck, T. F., Holben, B. N., Reid, J. S., Xian, P., Giles, D. M., Sinyuk, A.,
Smirnov, A., Schafer, J. S., Slutsker, I., and Kim, J.: Observations of the
interaction and transport of fine mode aerosols with cloud and/or fog in
Northeast Asia from Aerosol Robotic Network and satellite remote sensing, J. Geophys. Res.-Atmos., 123, 5560–5587, https://doi.org/10.1029/2018JD028313,
2018.
El-Harbawi, M.: Air quality modelling, simulation, and computational
methods: a review, Environ. Rev., 21, 149–179,
https://doi.org/10.1139/er-2012-0056, 2013.
Fahey, K. M. and Pandis, S. N.: Optimizing model performance: variable size
resolution in cloud chemistry modeling, Atmos. Environ., 35, 4471–4478,
https://doi.org/10.1016/S1352-2310(01)00224-2, 2001.
Fahey, K. M., Carlton, A. G., Pye, H. O. T., Baek, J., Hutzell, W. T., Stanier, C. O., Baker, K. R., Appel, K. W., Jaoui, M., and Offenberg, J. H.: A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1, Geosci. Model Dev., 10, 1587–1605, https://doi.org/10.5194/gmd-10-1587-2017, 2017.
Fan, J., Rosenfeld, D., Yang, Y., Zhao, C., Leung, L. R., and Li, Z.:
Substantial contribution of anthropogenic air pollution to catastrophic
floods in Southwest China, Geophys. Res. Lett., 42, 6066–6075,
https://doi.org/10.1002/2015GL064479, 2015.
Fan, J., Wang, Y., Rosenfeld, D., and Liu, X.: Review of aerosol-cloud
interactions: Mechanisms, significance, and challenges, J. Atmos. Sci., 73,
4221–4252, https://doi.org/10.1175/JAS-D-16-0037.1, 2016.
Fan, J., Rosenfeld, D., Zhang, Y., Giangrande, S. E., Li, Z., Machado, L. A.
T., Martin, S. T., Yang, Y., Wang, J., and Artaxo, P.: Substantial
convection and precipitation enhancements by ultrafine aerosol particles,
Science, 359, 411–418, https://doi.org/10.1126/science.aan8461,
2018.
Fast, J. D., Gustafson Jr, W. I., Easter, R. C., Zaveri, R. A., Barnard, J.
C., Chapman, E. G., Grell, G. A., and Peckham, S. E.: Evolution of ozone,
particulates, and aerosol direct radiative forcing in the vicinity of
Houston using a fully coupled meteorology-chemistry-aerosol model, J. Geophys. Res.-Atmos., 111, D21305, https://doi.org/10.1029/2005JD006721, 2006.
Feingold, G., Eberhard, W. L., Veron, D. E., and Previdi, M.: First
measurements of the Twomey indirect effect using ground-based remote
sensors, Geophys. Res. Lett., 30, 1287, https://doi.org/10.1029/2002GL016633,
2003.
Feng, Y., Kotamarthi, V. R., Coulter, R., Zhao, C., and Cadeddu, M.: Radiative and thermodynamic responses to aerosol extinction profiles during the pre-monsoon month over South Asia, Atmos. Chem. Phys., 16, 247–264, https://doi.org/10.5194/acp-16-247-2016, 2016.
Foley, K. M., Roselle, S. J., Appel, K. W., Bhave, P. V., Pleim, J. E., Otte, T. L., Mathur, R., Sarwar, G., Young, J. O., Gilliam, R. C., Nolte, C. G., Kelly, J. T., Gilliland, A. B., and Bash, J. O.: Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7, Geosci. Model Dev., 3, 205–226, https://doi.org/10.5194/gmd-3-205-2010, 2010.
Forkel, R., Brunner, D., Baklanov, A., Balzarini, A., Hirtl, M., Honzak, L.,
Jiménez-Guerrero, P., Jorba, O., Pérez, J. L., and San José, R.:
A multi-model case study on aerosol feedbacks in online coupled
chemistry-meteorology models within the cost action ES1004 EuMetChem, in:
Air pollution modeling and its application XXIV, Springer, 23–28,
https://doi.org/10.1007/978-3-319-24478-5_4, 2016.
Fu, P., Aggarwal, S. G., Chen, J., Li, J., Sun, Y., Wang, Z., Chen, H.,
Liao, H., Ding, A., and Umarji, G. S.: Molecular markers of secondary
organic aerosol in Mumbai, India, Environ. Sci. Technol., 50, 4659–4667,
https://doi.org/10.1021/acs.est.6b00372, 2016.
Gao, C., Zhang, X., Xiu, A., Huang, L., Zhao, H., Wang, K., and Tong, Q.:
Spatiotemporal distribution of biogenic volatile organic compounds emissions
in China, Acta Sci. Circumstantiae, 39, 4140–4151,
https://doi.org/10.13671/j.hjkxxb.2019.0243, 2019.
Gao, C., Xiu, A., Zhang, X., Tong, Q., Zhao, H., Zhang, S., Yang, G., and Zhang, M.:
Data used to create figures and tables in the ACP manuscript “Two-way coupled
meteorology and air quality models in Asia: a systematic review and meta-analysis of
impacts of aerosol feedbacks on meteorology and air quality” by Gao et al. (2022), Zenodo [data set], https://doi.org/10.5281/zenodo.6141615, 2022.
Gao, J., Zhu, B., Xiao, H., Kang, H., Pan, C., Wang, D., and Wang, H.: Effects of black carbon and boundary layer interaction on surface ozone in Nanjing, China, Atmos. Chem. Phys., 18, 7081–7094, https://doi.org/10.5194/acp-18-7081-2018, 2018.
Gao, M., Guttikunda, S. K., Carmichael, G. R., Wang, Y., Liu, Z., Stanier,
C. O., Saide, P. E., and Yu, M.: Health impacts and economic losses
assessment of the 2013 severe haze event in Beijing area, Sci. Total
Environ., 511, 553–561, https://doi.org/10.1016/j.scitotenv.2015.01.005,
2015.
Gao, M., Carmichael, G. R., Saide, P. E., Lu, Z., Yu, M., Streets, D. G., and Wang, Z.: Response of winter fine particulate matter concentrations to emission and meteorology changes in North China, Atmos. Chem. Phys., 16, 11837–11851, https://doi.org/10.5194/acp-16-11837-2016, 2016a.
Gao, M., Carmichael, G. R., Wang, Y., Saide, P. E., Yu, M., Xin, J., Liu, Z., and Wang, Z.: Modeling study of the 2010 regional haze event in the North China Plain, Atmos. Chem. Phys., 16, 1673–1691, https://doi.org/10.5194/acp-16-1673-2016, 2016b.
Gao, M., Carmichael, G. R., Wang, Y., Saide, P. E., Liu, Z., Xin, J., Shan,
Y., and Wang, Z.: Chemical and Meteorological Feedbacks in the Formation of
Intense Haze Events, in: Air Pollution in Eastern Asia: An Integrated
Perspective, Springer, 437–452,
https://doi.org/10.1007/978-3-319-59489-7_21, 2017a.
Gao, M., Liu, Z., Wang, Y., Lu, X., Ji, D., Wang, L., Li, M., Wang, Z.,
Zhang, Q., and Carmichael, G. R.: Distinguishing the roles of meteorology,
emission control measures, regional transport, and co-benefits of reduced
aerosol feedbacks in “APEC Blue”, Atmos. Environ., 167, 476–486,
https://doi.org/10.1016/j.atmosenv.2017.08.054, 2017b.
Gao, M., Saide, P. E., Xin, J., Wang, Y., Liu, Z., Wang, Y., Wang, Z.,
Pagowski, M., Guttikunda, S. K., and Carmichael, G. R.: Estimates of health
impacts and radiative forcing in winter haze in eastern China through
constraints of surface PM2.5 predictions, Environ. Sci. Technol., 51,
2178–2185, https://doi.org/10.1021/acs.est.6b03745, 2017c.
Gao, M., Han, Z., Liu, Z., Li, M., Xin, J., Tao, Z., Li, J., Kang, J.-E., Huang, K., Dong, X., Zhuang, B., Li, S., Ge, B., Wu, Q., Cheng, Y., Wang, Y., Lee, H.-J., Kim, C.-H., Fu, J. S., Wang, T., Chin, M., Woo, J.-H., Zhang, Q., Wang, Z., and Carmichael, G. R.: Air quality and climate change, Topic 3 of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III) – Part 1: Overview and model evaluation, Atmos. Chem. Phys., 18, 4859–4884, https://doi.org/10.5194/acp-18-4859-2018, 2018a.
Gao, M., Ji, D., Liang, F., and Liu, Y.: Attribution of aerosol direct
radiative forcing in China and India to emitting sectors, Atmos. Environ.,
190, 35–42, https://doi.org/10.1016/j.atmosenv.2018.07.011, 2018b.
Gao, Y. and Zhang, M.: Changes in the diurnal variations of clouds and
precipitation induced by anthropogenic aerosols over East China in August
2008, Atmos. Pollut. Res., 9, 513–525,
https://doi.org/10.1016/j.apr.2017.11.013, 2018.
Gao, Y., Zhang, M., Liu, X., and Zhao, C.: Model Analysis of the
Anthropogenic Aerosol Effect on Clouds over East Asia, Atmos. Ocean. Sci.
Lett., 5, 1–7, https://doi.org/10.1080/16742834.2012.11446968, 2012.
Gao, Y., Zhao, C., Liu, X., Zhang, M., and Leung, L. R.: WRF-Chem
simulations of aerosols and anthropogenic aerosol radiative forcing in East
Asia, Atmos. Environ., 92, 250–266,
https://doi.org/10.1016/j.atmosenv.2014.04.038, 2014.
Gao, Y., Zhang, M., Liu, Z., Wang, L., Wang, P., Xia, X., Tao, M., and Zhu, L.: Modeling the feedback between aerosol and meteorological variables in the atmospheric boundary layer during a severe fog–haze event over the North China Plain, Atmos. Chem. Phys., 15, 4279–4295, https://doi.org/10.5194/acp-15-4279-2015, 2015.
Gao, Y., Zhang, M., Liu, X., and Wang, L.: Change in diurnal variations of
meteorological variables induced by anthropogenic aerosols over the North
China Plain in summer 2008, Theor. Appl. Climatol., 124, 103–118,
https://doi.org/10.1007/s00704-015-1403-4, 2016.
García-Díez, M., Fernández, J., Fita, L., and Yagüe, C.:
Seasonal dependence of WRF model biases and sensitivity to PBL schemes over
Europe, Q. J. Roy. Meteor. Soc., 139, 501–514,
https://doi.org/10.1002/qj.1976, 2013.
Ge, C., Wang, J., and Reid, J. S.: Mesoscale modeling of smoke transport over the Southeast Asian Maritime Continent: coupling of smoke direct radiative effect below and above the low-level clouds, Atmos. Chem. Phys., 14, 159–174, https://doi.org/10.5194/acp-14-159-2014, 2014.
Georgiou, G. K., Christoudias, T., Proestos, Y., Kushta, J., Hadjinicolaou, P., and Lelieveld, J.: Air quality modelling in the summer over the eastern Mediterranean using WRF-Chem: chemistry and aerosol mechanism intercomparison, Atmos. Chem. Phys., 18, 1555–1571, https://doi.org/10.5194/acp-18-1555-2018, 2018.
Gery, M. W., Whitten, G. Z., Killus, J. P., and Dodge, M. C.: A
photochemical kinetics mechanism for urban and regional scale computer
modeling, J. Geophys. Res.-Atmos., 94, 12925–12956,
https://doi.org/10.1029/JD094iD10p12925, 1989.
Ghan, S. J. and Zaveri, R. A.: Parameterization of optical properties for
hydrated internally mixed aerosol, J. Geophys. Res.-Atmos., 112, D10201,
https://doi.org/10.1029/2006JD007927, 2007.
Ghude, S. D., Chate, D. M., Jena, C., Beig, G., Kumar, R., Barth, M. C.,
Pfister, G. G., Fadnavis, S., and Pithani, P.: Premature mortality in India
due to PM2.5 and ozone exposure, Geophys. Res. Lett., 43, 4650–4658,
https://doi.org/10.1002/2016GL068949, 2016.
Giglio, L., Randerson, J. T., van der Werf, G. R., Kasibhatla, P. S., Collatz, G. J., Morton, D. C., and DeFries, R. S.: Assessing variability and long-term trends in burned area by merging multiple satellite fire products, Biogeosciences, 7, 1171–1186, https://doi.org/10.5194/bg-7-1171-2010, 2010.
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O.,
and Lin, S.: Sources and distributions of dust aerosols simulated with the
GOCART model, J. Geophys. Res.-Atmos., 106, 20255–20273,
https://doi.org/10.1029/2000JD000053, 2001.
Giorgi, F. and Chameides, W. L.: Rainout lifetimes of highly soluble
aerosols and gases as inferred from simulations with a general circulation
model, J. Geophys. Res.-Atmos., 91, 14367–14376,
https://doi.org/10.1029/JD091iD13p14367, 1986.
Gong, S. L., Barrie, L. A., and Blanchet, J.: Modeling sea-salt aerosols in
the atmosphere: 1. Model development, J. Geophys. Res.-Atmos., 102,
3805–3818, https://doi.org/10.1029/96JD02953, 1997.
Gong, S. L., Barrie, L. A., Blanchet, J., Von Salzen, K., Lohmann, U.,
Lesins, G., Spacek, L., Zhang, L. M., Girard, E., and Lin, H.: Canadian
Aerosol Module: A size-segregated simulation of atmospheric aerosol
processes for climate and air quality models 1. Module development, J. Geophys. Res.-Atmos., 108, AAC-3, https://doi.org/10.1029/2001JD002002,
2003a.
Gong, S. L., Zhang, X. Y., Zhao, T. L., McKendry, I. G., Jaffe, D. A., and
Lu, N. M.: Characterization of soil dust aerosol in China and its transport
and distribution during 2001 ACE-Asia: 2. Model simulation and validation,
J. Geophys. Res.-Atmos., 108, 4262, https://doi.org/10.1029/2002JD002633, 2003b.
Goren, T. and Rosenfeld, D.: Decomposing aerosol cloud radiative effects
into cloud cover, liquid water path and Twomey components in marine
stratocumulus, Atmos. Res., 138, 378–393,
https://doi.org/10.1016/j.atmosres.2013.12.008, 2014.
Govardhan, G., Nanjundiah, R. S., Satheesh, S. K., Krishnamoorthy, K., and
Kotamarthi, V. R.: Performance of WRF-Chem over Indian region: Comparison
with measurements, J. Earth Syst. Sci., 124, 875–896,
https://doi.org/10.1007/s12040-015-0576-7, 2015.
Govardhan, G. R., Nanjundiah, R. S., Satheesh, S. K., Moorthy, K. K., and
Takemura, T.: Inter-comparison and performance evaluation of chemistry
transport models over Indian region, Atmos. Environ., 125, 486–504,
https://doi.org/10.1016/j.atmosenv.2015.10.065, 2016.
Gray, L. J., Beer, J., Geller, M., Haigh, J. D., Lockwood, M., Matthes, K.,
Cubasch, U., Fleitmann, D., Harrison, G., and Hood, L.: Solar influences on
climate, Rev. Geophys., 48, RG4001, https://doi.org/10.1029/2009RG000282, 2010.
Grell, G., Freitas, S. R., Stuefer, M., and Fast, J.: Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts, Atmos. Chem. Phys., 11, 5289–5303, https://doi.org/10.5194/acp-11-5289-2011, 2011.
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G.,
Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within
the WRF model, Atmos. Environ., 39, 6957–6975,
https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005.
Griffin, R. J., Cocker III, D. R., Seinfeld, J. H., and Dabdub, D.: Estimate
of global atmospheric organic aerosol from oxidation of biogenic
hydrocarbons, Geophys. Res. Lett., 26, 2721–2724,
https://doi.org/10.1029/1999GL900476, 1999.
Groß, S., Esselborn, M., Weinzierl, B., Wirth, M., Fix, A., and Petzold, A.: Aerosol classification by airborne high spectral resolution lidar observations, Atmos. Chem. Phys., 13, 2487–2505, https://doi.org/10.5194/acp-13-2487-2013, 2013.
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006.
Guo, J., Deng, M., Fan, J., Li, Z., Chen, Q., Zhai, P., Dai, Z., and Li, X.:
Precipitation and air pollution at mountain and plain stations in northern
China: Insights gained from observations and modeling, J. Geophys. Res.-Atmos., 119, 4793–4807, https://doi.org/10.1002/2013JD021161, 2014.
Guo, J., Liu, H., Li, Z., Rosenfeld, D., Jiang, M., Xu, W., Jiang, J. H., He, J., Chen, D., Min, M., and Zhai, P.: Aerosol-induced changes in the vertical structure of precipitation: a perspective of TRMM precipitation radar, Atmos. Chem. Phys., 18, 13329–13343, https://doi.org/10.5194/acp-18-13329-2018, 2018.
Gurjar, B. R., Ravindra, K., and Nagpure, A. S.: Air pollution trends over
Indian megacities and their local-to-global implications, Atmos. Environ.,
142, 475–495, https://doi.org/10.1016/j.atmosenv.2016.06.030, 2016.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative
forcing due to tropospheric aerosols: A review, Rev. Geophys., 38, 513–543,
https://doi.org/10.1029/1999RG000078, 2000.
He, J. and Zhang, Y.: Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments, Atmos. Chem. Phys., 14, 9171–9200, https://doi.org/10.5194/acp-14-9171-2014, 2014.
He, J., Zhang, Y., Wang, K., Chen, Y., Leung, L. R., Fan, J., Li, M., Zheng,
B., Zhang, Q., and Duan, F.: Multi-year application of WRF-CAM5 over East
Asia-Part I: Comprehensive evaluation and formation regimes of O3 and
PM2.5, Atmos. Environ., 165, 122–142,
https://doi.org/10.1016/j.atmosenv.2017.06.015, 2017.
Hess, M., Koepke, P., and Schult, I.: Optical properties of aerosols and clouds: The
software package OPAC, B. Am. Meteorol. Soc., 79, 831–844,
https://doi.org/10.1175/1520-0477(1998)079<0831:OPOAAC>2.0.CO;2, 1998.
Hodshire, A. L., Akherati, A., Alvarado, M. J., Brown-Steiner, B., Jathar,
S. H., Jimenez, J. L., Kreidenweis, S. M., Lonsdale, C. R., Onasch, T. B.,
and Ortega, A. M.: Aging effects on biomass burning aerosol mass and
composition: A critical review of field and laboratory studies, Environ.
Sci. Technol., 53, 10007–10022, https://doi.org/10.1021/acs.est.9b02588,
2019.
Hodzic, A. and Jimenez, J. L.: Modeling anthropogenically controlled secondary organic aerosols in a megacity: a simplified framework for global and climate models, Geosci. Model Dev., 4, 901–917, https://doi.org/10.5194/gmd-4-901-2011, 2011.
Hong, C., Zhang, Q., Zhang, Y., Tang, Y., Tong, D., and He, K.: Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects, Geosci. Model Dev., 10, 2447–2470, https://doi.org/10.5194/gmd-10-2447-2017, 2017.
Hong, C., Zhang, Q., Zhang, Y., Davis, S. J., Tong, D., Zheng, Y., Liu, Z.,
Guan, D., He, K., and Schellnhuber, H. J.: Impacts of climate change on
future air quality and human health in China, P. Natl. Acad. Sci. USA, 116,
17193–17200, https://doi.org/10.1073/pnas.1812881116, 2019.
Hu, X., Klein, P. M., and Xue, M.: Evaluation of the updated YSU planetary
boundary layer scheme within WRF for wind resource and air quality
assessments, J. Geophys. Res.-Atmos., 118, 10–490,
https://doi.org/10.1002/jgrd.50823, 2013.
Huang, J., Wang, T., Wang, W., Li, Z., and Yan, H.: Climate effects of dust
aerosols over East Asian arid and semiarid regions, J. Geophys. Res.-Atmos.,
119, 11–398, https://doi.org/10.1002/2014JD021796, 2014.
Huang, L., Lin, W., Li, F., Wang, Y., and Jiang, B.: Climate impacts of the
biomass burning in Indochina on atmospheric conditions over southern China,
Aerosol Air Qual. Res., 19, 2707–2720,
https://doi.org/10.4209/aaqr.2019.01.0028, 2019.
Huang, X., Song, Y., Zhao, C., Cai, X., Zhang, H., and Zhu, T.: Direct
radiative effect by multicomponent aerosol over China, J. Climate, 28,
3472–3495, https://doi.org/10.1175/JCLI-D-14-00365.1, 2015.
Huang, X., Ding, A., Liu, L., Liu, Q., Ding, K., Niu, X., Nie, W., Xu, Z., Chi, X., Wang, M., Sun, J., Guo, W., and Fu, C.: Effects of aerosol–radiation interaction on precipitation during biomass-burning season in East China, Atmos. Chem. Phys., 16, 10063–10082, https://doi.org/10.5194/acp-16-10063-2016, 2016.
Illingworth, A. J., Barker, H. W., Beljaars, A., Ceccaldi, M., Chepfer, H.,
Clerbaux, N., Cole, J., Delanoë, J., Domenech, C., and Donovan, D. P.:
The EarthCARE satellite: The next step forward in global measurements of
clouds, aerosols, precipitation, and radiation, B. Am. Meteorol. Soc.,
96, 1311–1332, https://doi.org/10.1175/BAMS-D-12-00227.1, 2015.
Im, U., Bianconi, R., Solazzo, E., Kioutsioukis, I., Badia, A., Balzarini,
A., Baró, R., Bellasio, R., Brunner, D., and Chemel, C.: Evaluation of
operational on-line-coupled regional air quality models over Europe and
North America in the context of AQMEII phase 2. Part I: Ozone, Atmos.
Environ., 115, 404–420, https://doi.org/10.1016/j.atmosenv.2014.09.042,
2015a.
Im, U., Bianconi, R., Solazzo, E., Kioutsioukis, I., Badia, A., Balzarini,
A., Baró, R., Bellasio, R., Brunner, D., and Chemel, C.: Evaluation of
operational online-coupled regional air quality models over Europe and North
America in the context of AQMEII phase 2. Part II: Particulate matter,
Atmos. Environ., 115, 421–441,
https://doi.org/10.1016/j.atmosenv.2014.08.072, 2015b.
IPCC: Climate change 2007: Synthesis Report. Contribution of Working Groups
I, II and III to the Fourth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Solomon, S. D., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt,
K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007.
IPCC: Climate change 2014: Synthesis Report. Contribution of Working Groups
I, II and III to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K.,
Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY,
USA, 1535 pp., 2013.
IPCC: Climate Change 2021: The Physical Science
Basis. Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zha, P.,
Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis,
M. I., Huang, M., Leitzell, K., Lonnoy, E. Matthews, J. B. R., Maycock, T. K.,
Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press,
https://www.ipcc.ch/report/ar6/wg1/#FullReport (last access: 20 March 2022), 2021.
Jacobson, M. Z.: Developing, coupling, and applying a
gas, aerosol, transport, and radiation model to study urban and regional air pollution,
Ph.D. thesis, Department of Atmospheric Sciences, University of California, United
States, 436 pp., 1994.
Jacobson, M. Z.: Development and application of a new air pollution modeling
system – Part III. Aerosol-phase simulations, Atmos. Environ., 31, 587–608,
https://doi.org/10.1016/S1352-2310(96)00201-4, 1997a.
Jacobson, M. Z.: Numerical techniques to solve condensational and
dissolutional growth equations when growth is coupled to reversible
reactions, Aerosol Sci. Technol., 27, 491–498,
https://doi.org/10.1080/02786829708965489, 1997b.
Jacobson, M. Z.: Fundamentals of atmospheric modeling, Cambridge University
Press, https://web.stanford.edu/group/efmh/jacobson/FAMbook/FAMbook.html (last access:
20 March 2022), 1999.
Jacobson, M. Z.: Strong radiative heating due to the mixing state of black
carbon in atmospheric aerosols, Nature, 409, 695–697,
https://doi.org/10.1038/35055518, 2001.
Jacobson, M. Z.: Analysis of aerosol interactions with numerical techniques
for solving coagulation, nucleation, condensation, dissolution, and
reversible chemistry among multiple size distributions, J. Geophys. Res.-Atmos., 107, AAC-2, https://doi.org/10.1029/2001JD002044, 2002.
Jacobson, M. Z.: Development of mixed-phase clouds from multiple aerosol
size distributions and the effect of the clouds on aerosol removal, J. Geophys. Res.-Atmos., 108, 4366, https://doi.org/10.1029/2002JD002691, 2003.
Jacobson, M. Z.: History of, processes in, and numerical techniques in
GATOR-GCMOM, https://web.stanford.edu/group/efmh/jacobson/GATOR/GATOR-GCMOMHist.pdf (last access: 20 March 2022), 2012a.
Jacobson, M. Z.: Investigating cloud absorption effects: Global absorption
properties of black carbon, tar balls, and soil dust in clouds and aerosols,
J. Geophys. Res.-Atmos., 117, D06205, https://doi.org/10.1029/2011JD017218, 2012b.
Jacobson, M. Z. and Jadhav, V.: World estimates of PV optimal tilt angles
and ratios of sunlight incident upon tilted and tracked PV panels relative
to horizontal panels, Sol. Energy, 169, 55–66,
https://doi.org/10.1016/j.solener.2018.04.030, 2018.
Jacobson, M. Z. and Turco, R. P.: Simulating condensational growth,
evaporation, and coagulation of aerosols using a combined moving and
stationary size grid, Aerosol Sci. Technol., 22, 73–92,
https://doi.org/10.1080/02786829408959729, 1995.
Jacobson, M. Z., Turco, R. P., Jensen, E. J., and Toon, O. B.: Modeling
coagulation among particles of different composition and size, Atmos.
Environ., 28, 1327–1338, https://doi.org/10.1016/1352-2310(94)90280-1,
1994.
Jacobson, M. Z., Lu, R., Turco, R. P., and Toon, O. B.: Development and
application of a new air pollution modeling system-part I: Gas-phase
simulations, Atmos. Environ., 30, 1939–1963,
https://doi.org/10.1016/1352-2310(95)00139-5, 1996a.
Jacobson, M. Z., Tabazadeh, A., and Turco, R. P.: Simulating equilibrium
within aerosols and nonequilibrium between gases and aerosols, J. Geophys. Res.-Atmos., 101, 9079–9091, https://doi.org/10.1029/96JD00348, 1996b.
Jacobson, M. Z., Kaufman, Y. J., and Rudich, Y.: Examining feedbacks of
aerosols to urban climate with a model that treats 3-D clouds with aerosol
inclusions, J. Geophys. Res.-Atmos., 112, D24205,
https://doi.org/10.1029/2007JD008922, 2007.
Jacobson, M. Z., Nghiem, S. V, Sorichetta, A., and Whitney, N.: Ring of
impact from the mega-urbanization of Beijing between 2000 and 2009, J. Geophys. Res.-Atmos., 120, 5740–5756, https://doi.org/10.1002/2014JD023008,
2015.
Jacobson, M. Z., Nghiem, S. V, and Sorichetta, A.: Short-term impacts of the
megaurbanizations of New Delhi and Los Angeles between 2000 and 2009, J. Geophys. Res.-Atmos., 124, 35–56, https://doi.org/10.1029/2018JD029310,
2019.
Jena, C., Ghude, S. D., Pfister, G. G., Chate, D. M., Kumar, R., Beig, G.,
Surendran, D. E., Fadnavis, S., and Lal, D. M.: Influence of springtime
biomass burning in South Asia on regional ozone (O3): A model based
case study, Atmos. Environ., 100, 37–47,
https://doi.org/10.1016/j.atmosenv.2014.10.027, 2015.
Jeong, J. I. and Park, R. J.: Winter monsoon variability and its impact on
aerosol concentrations in East Asia, Environ. Pollut., 221, 285–292,
https://doi.org/10.1016/j.envpol.2016.11.075, 2017.
Jia, X. and Guo, X.: Impacts of Anthropogenic Atmospheric Pollutant on
Formation and Development of a Winter Heavy Fog Event, Chinese J. Atmos.
Sci., 36, 995–1008, https://doi.org/10.1007/s11783-011-0280-z, 2012.
Jia, X., Quan, J., Zheng, Z., Liu, X., Liu, Q., He, H., and Liu, Y.: Impacts
of Anthropogenic Aerosols on Fog in North China Plain, J. Geophys. Res.-Atmos., 124, 252–265, https://doi.org/10.1029/2018JD029437, 2019.
Jiang, B., Huang, B., Lin, W., and Xu, S.: Investigation of the effects of
anthropogenic pollution on typhoon precipitation and microphysical processes
using WRF-Chem, J. Atmos. Sci., 73, 1593–1610,
https://doi.org/10.1175/JAS-D-15-0202.1, 2016.
Jiang, B., Lin, W., Li, F., and Chen, B.: Simulation of the effects of
sea-salt aerosols on cloud ice and precipitation of a tropical cyclone,
Atmos. Sci. Lett., 20, e936, https://doi.org/10.1002/asl.936, 2019a.
Jiang, B., Lin, W., Li, F., and Chen, J.: Sea-salt aerosol effects on the
simulated microphysics and precipitation in a tropical cyclone, J. Meteorol.
Res., 33, 115–125, https://doi.org/10.1007/s13351-019-8108-z, 2019b.
Jimenez, P. A., Hacker, J. P., Dudhia, J., Haupt, S. E., Ruiz-Arias, J. A.,
Gueymard, C. A., Thompson, G., Eidhammer, T., and Deng, A.: WRF-Solar:
Description and clear-sky assessment of an augmented NWP model for solar
power prediction, B. Am. Meteorol. Soc., 97, 1249–1264,
https://doi.org/10.1175/BAMS-D-14-00279.1, 2016.
Jin, Q., Wei, J., Yang, Z.-L., Pu, B., and Huang, J.: Consistent response of Indian summer monsoon to Middle East dust in observations and simulations, Atmos. Chem. Phys., 15, 9897–9915, https://doi.org/10.5194/acp-15-9897-2015, 2015.
Jin, Q., Yang, Z.-L., and Wei, J.: High sensitivity of Indian summer monsoon
to Middle East dust absorptive properties, Sci. Rep.-UK, 6, 1–8,
https://doi.org/10.1038/srep30690, 2016a.
Jin, Q., Yang, Z.-L., and Wei, J.: Seasonal responses of Indian summer
monsoon to dust aerosols in the Middle East, India, and China, J. Climate, 29,
6329–6349, https://doi.org/10.1175/JCLI-D-15-0622.1, 2016b.
Jung, J., Souri, A. H., Wong, D. C., Lee, S., Jeon, W., Kim, J., and Choi,
Y.: The Impact of the Direct Effect of Aerosols on Meteorology and Air
Quality Using Aerosol Optical Depth Assimilation During the KORUS-AQ
Campaign, J. Geophys. Res.-Atmos., 124, 8303–8319,
https://doi.org/10.1029/2019JD030641, 2019.
Kajino, M., Ueda, H., Han, Z., Kudo, R., Inomata, Y., and Kaku, H.: Synergy
between air pollution and urban meteorological changes through
aerosol-radiation-diffusion feedback – A case study of Beijing
in January 2013, Atmos. Environ., 171, 98–110,
https://doi.org/10.1016/j.atmosenv.2017.10.018., 2017.
Kant, S., Panda, J., and Gautam, R.: A seasonal analysis of
aerosol-cloud-radiation interaction over Indian region during 2000–2017,
Atmos. Environ., 201, 212–222,
https://doi.org/10.1016/j.atmosenv.2018.12.044, 2019.
Kedia, S., Cherian, R., Islam, S., Das, S. K., and Kaginalkar, A.: Regional
simulation of aerosol radiative effects and their influence on rainfall over
India using WRFChem model, Atmos. Res., 182, 232–242,
https://doi.org/10.1016/j.atmosres.2016.07.008, 2016.
Kedia, S., Kumar, S., Islam, S., Hazra, A., and Kumar, N.: Aerosols impact
on the convective and non-convective rain distribution over the Indian
region: Results from WRF-Chem simulation, Atmos. Environ., 202, 64–74,
https://doi.org/10.1016/j.atmosenv.2019.01.020, 2019a.
Kedia, S., Vellore, R. K., Islam, S., and Kaginalkar, A.: A study of
Himalayan extreme rainfall events using WRF-Chem, Meteorol. Atmos. Phys.,
131, 1133–1143, https://doi.org/10.1007/s00703-018-0626-1, 2019b.
Keita, S. A., Girard, E., Raut, J.-C., Leriche, M., Blanchet, J.-P., Pelon, J., Onishi, T., and Cirisan, A.: A new parameterization of ice heterogeneous nucleation coupled to aerosol chemistry in WRF-Chem model version 3.5.1: evaluation through ISDAC measurements, Geosci. Model Dev., 13, 5737–5755, https://doi.org/10.5194/gmd-13-5737-2020, 2020.
Kim, B., Schwartz, S. E., Miller, M. A., and Min, Q.: Effective radius of
cloud droplets by ground-based remote sensing: Relationship to aerosol, J. Geophys. Res.-Atmos., 108, 4740, https://doi.org/10.1029/2003JD003721, 2003.
Knote, C., Hodzic, A., Jimenez, J. L., Volkamer, R., Orlando, J. J., Baidar, S., Brioude, J., Fast, J., Gentner, D. R., Goldstein, A. H., Hayes, P. L., Knighton, W. B., Oetjen, H., Setyan, A., Stark, H., Thalman, R., Tyndall, G., Washenfelder, R., Waxman, E., and Zhang, Q.: Simulation of semi-explicit mechanisms of SOA formation from glyoxal in aerosol in a 3-D model, Atmos. Chem. Phys., 14, 6213–6239, https://doi.org/10.5194/acp-14-6213-2014, 2014.
Koch, D. and Del Genio, A. D.: Black carbon semi-direct effects on cloud cover: review and synthesis, Atmos. Chem. Phys., 10, 7685–7696, https://doi.org/10.5194/acp-10-7685-2010, 2010.
Kong, X., Forkel, R., Sokhi, R. S., Suppan, P., Baklanov, A., Gauss, M.,
Brunner, D., Barò, R., Balzarini, A., Chemel, C., Curci, G.,
Jiménez-Guerrero, P., Hirtl, M., Honzak, L., Im, U., Pérez, J. L.,
Pirovano, G., San Jose, R., Schlünzen, K. H., Tsegas, G., Tuccella, P.,
Werhahn, J., Žabkar, R., and Galmarini, S.: Analysis of
meteorology-chemistry interactions during air pollution episodes using
online coupled models within AQMEII phase-2, Atmos. Environ., 115, 527–540,
https://doi.org/10.1016/j.atmosenv.2014.09.020, 2015.
Kuik, F., Lauer, A., Churkina, G., Denier van der Gon, H. A. C., Fenner, D., Mar, K. A., and Butler, T. M.: Air quality modelling in the Berlin–Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data, Geosci. Model Dev., 9, 4339–4363, https://doi.org/10.5194/gmd-9-4339-2016, 2016.
Kulmala, M., Laaksonen, A., and Pirjola, L.: Parameterizations for sulfuric
acid/water nucleation rates, J. Geophys. Res.-Atmos., 103, 8301–8307,
https://doi.org/10.1029/97JD03718, 1998.
Kumar, P., Sokolik, I. N., and Nenes, A.: Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN, Atmos. Chem. Phys., 9, 2517–2532, https://doi.org/10.5194/acp-9-2517-2009, 2009.
Kumar, R., Naja, M., Pfister, G. G., Barth, M. C., and Brasseur, G. P.: Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem): set-up and meteorological evaluation, Geosci. Model Dev., 5, 321–343, https://doi.org/10.5194/gmd-5-321-2012, 2012a.
Kumar, R., Naja, M., Pfister, G. G., Barth, M. C., Wiedinmyer, C., and Brasseur, G. P.: Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem): chemistry evaluation and initial results, Geosci. Model Dev., 5, 619–648, https://doi.org/10.5194/gmd-5-619-2012, 2012b.
Kumar, R., Barth, M. C., Pfister, G. G., Naja, M., and Brasseur, G. P.: WRF-Chem simulations of a typical pre-monsoon dust storm in northern India: influences on aerosol optical properties and radiation budget, Atmos. Chem. Phys., 14, 2431–2446, https://doi.org/10.5194/acp-14-2431-2014, 2014.
Kuniyal, J. C. and Guleria, R. P.: The current state of aerosol-radiation
interactions: a mini review, J. Aerosol Sci., 130, 45–54,
https://doi.org/10.1016/j.jaerosci.2018.12.010, 2019.
Lau, W. K. M., Kim, K.-M., Shi, J.-J., Matsui, T., Chin, M., Tan, Q.,
Peters-Lidard, C., and Tao, W.-K.: Impacts of aerosol–monsoon interaction
on rainfall and circulation over Northern India and the Himalaya Foothills,
Clim. Dynam., 49, 1945–1960, https://doi.org/10.1007/s00382-016-3430-y, 2017.
Lee, H.-H., Chen, S.-H., Kumar, A., Zhang, H., and Kleeman, M. J.:
Improvement of aerosol activation/ice nucleation in a source-oriented
WRF-Chem model to study a winter Storm in California, Atmos. Res., 235,
104790, https://doi.org/10.1016/j.atmosres.2019.104790, 2020.
Lee, Y. C., Yang, X., and Wenig, M.: Transport of dusts from East Asian and
non-East Asian sources to Hong Kong during dust storm related events
1996–2007, Atmos. Environ., 44, 3728–3738,
https://doi.org/10.1016/j.atmosenv.2010.03.034, 2010.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The
contribution of outdoor air pollution sources to premature mortality on a
global scale, Nature, 525, 367, https://doi.org/10.1038/nature15371, 2015.
Lelieveld, J., Bourtsoukidis, E., Brühl, C., Fischer, H., Fuchs, H.,
Harder, H., Hofzumahaus, A., Holland, F., Marno, D., and Neumaier, M.: The
South Asian monsoon-pollution pump and purifier, Science, 361,
270–273, https://doi.org/10.1126/science.aar2501, 2018.
Li, J., Wang, Z., Wang, X., Yamaji, K., Takigawa, M., Kanaya, Y., Pochanart,
P., Liu, Y., Irie, H., and Hu, B.: Impacts of aerosols on summertime
tropospheric photolysis frequencies and photochemistry over Central Eastern
China, Atmos. Environ., 45, 1817–1829,
https://doi.org/10.1016/j.atmosenv.2011.01.016, 2011.
Li, J., Chen, X., Wang, Z., Du, H., Yang, W., Sun, Y., Hu, B., Li, J., Wang,
W., and Wang, T.: Radiative and heterogeneous chemical effects of aerosols
on ozone and inorganic aerosols over East Asia, Sci. Total Environ., 622,
1327–1342, https://doi.org/10.1016/j.scitotenv.2017.12.041, 2018.
Li, J., Nagashima, T., Kong, L., Ge, B., Yamaji, K., Fu, J. S., Wang, X., Fan, Q., Itahashi, S., Lee, H.-J., Kim, C.-H., Lin, C.-Y., Zhang, M., Tao, Z., Kajino, M., Liao, H., Li, M., Woo, J.-H., Kurokawa, J., Wang, Z., Wu, Q., Akimoto, H., Carmichael, G. R., and Wang, Z.: Model evaluation and intercomparison of surface-level ozone and relevant species in East Asia in the context of MICS-Asia Phase III – Part 1: Overview, Atmos. Chem. Phys., 19, 12993–13015, https://doi.org/10.5194/acp-19-12993-2019, 2019.
Li, L. and Liao, H.: Role of the Radiative Effect of Black Carbon in
Simulated PM2.5 Concentrations during a Haze Event in China, Atmos.
Ocean. Sci. Lett., 7, 434–440,
https://doi.org/10.3878/j.issn.1674-2834.14.0023, 2014.
Li, L. and Sokolik, I. N.: The Dust Direct Radiative Impact and Its
Sensitivity to the Land Surface State and Key Minerals in the WRF-Chem-DuMo
Model: A Case Study of Dust Storms in Central Asia, J. Geophys. Res.-Atmos.,
123, 4564–4582, https://doi.org/10.1029/2017JD027667, 2018.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017.
Li, M., Wang, T., Xie, M., Li, S., Zhuang, B., Chen, P., Huang, X., and Han,
Y.: Agricultural fire impacts on ozone photochemistry over the Yangtze River
Delta region, East China, J. Geophys. Res.-Atmos., 123, 6605–6623,
https://doi.org/10.1029/2018JD028582, 2018.
Li, M., Wang, T., Xie, M., Li, S., Zhuang, B., Huang, X., Chen, P., Zhao,
M., and Liu, J.: Formation and evolution mechanisms for two extreme haze
episodes in the Yangtze River Delta region of China during winter 2016, J. Geophys. Res.-Atmos., 124, 3607–3623, https://doi.org/10.1029/2019JD030535,
2019.
Li, M. M., Wang, T., Han, Y., Xie, M., Li, S., Zhuang, B., and Chen, P.:
Modeling of a severe dust event and its impacts on ozone photochemistry over
the downstream Nanjing megacity of eastern China, Atmos. Environ., 160,
107–123, https://doi.org/10.1016/j.atmosenv.2017.04.010, 2017a.
Li, M. M., Wang, T., Xie, M., Zhuang, B., Li, S., Han, Y., and Chen, P.:
Impacts of aerosol-radiation feedback on local air quality during a severe
haze episode in Nanjing megacity, eastern China, Tellus B, 69, 1–16, https://doi.org/10.1080/16000889.2017.1339548, 2017b.
Li, Z., Niu, F., Fan, J., Liu, Y., Rosenfeld, D., and Ding, Y.: Long-term
impacts of aerosols on the vertical development of clouds and precipitation,
Nat. Geosci., 4, 888–894, https://doi.org/10.1038/ngeo1313, 2011.
Li, Z., Lau, W. K. M., Ramanathan, V., Wu, G., Ding, Y., Manoj, M. G., Liu,
J., Qian, Y., Li, J., Zhou, T., Fan, J., Rosenfeld, D., Ming, Y., Wang, Y.,
Huang, J., Wang, B., Xu, X., Lee, S. S., Cribb, M., Zhang, F., Yang, X.,
Zhao, C., Takemura, T., Wang, K., Xia, X., Yin, Y., Zhang, H., Guo, J.,
Zhai, P. M., Sugimoto, N., Babu, S. S., and Brasseur, G. P.: Aerosol and
monsoon climate interactions over Asia, Rev. Geophys., 54, 866–929,
https://doi.org/10.1002/2015RG000500, 2016.
Li, Z., Wang, Y., Guo, J., Zhao, C., Cribb, M. C., Dong, X., Fan, J., Gong,
D., Huang, J., and Jiang, M.: East Asian study of tropospheric aerosols and
their impact on regional clouds, precipitation, and climate (EAST-AIRCPC),
J. Geophys. Res.-Atmos., 124, 13026–13054,
https://doi.org/10.1029/2019JD030758, 2019.
Liao, J., Wang, T., Wang, X., Xie, M., Jiang, Z., Huang, X., and Zhu, J.:
Impacts of different urban canopy schemes in WRF/Chem on regional climate
and air quality in Yangtze River Delta, China, Atmos. Res., 145, 226–243,
https://doi.org/10.1016/j.atmosres.2014.04.005, 2014.
Lin, C.-Y., Zhao, C., Liu, X., Lin, N.-H., and Chen, W.-N.: Modelling of
long-range transport of Southeast Asia biomass-burning aerosols to Taiwan
and their radiative forcings over East Asia, Tellus B,
66, 23733, https://doi.org/10.3402/tellusb.v66.23733, 2014.
Lin, N.-H., Sayer, A. M., Wang, S.-H., Loftus, A. M., Hsiao, T.-C., Sheu,
G.-R., Hsu, N. C., Tsay, S.-C., and Chantara, S.: Interactions between
biomass-burning aerosols and clouds over Southeast Asia: Current status,
challenges, and perspectives, Environ. Pollut., 195, 292–307,
https://doi.org/10.1016/j.envpol.2014.06.036, 2014.
Liu, C., Wang, T., Chen, P., Li, M., Zhao, M., Zhao, K., Wang, M., and Yang,
X.: Effects of Aerosols on the Precipitation of Convective Clouds: A Case
Study in the Yangtze River Delta of China, J. Geophys. Res.-Atmos., 124,
7868–7885, https://doi.org/10.1029/2018JD029924, 2019.
Liu, G., Shao, H., Coakley Jr, J. A., Curry, J. A., Haggerty, J. A., and
Tschudi, M. A.: Retrieval of cloud droplet size from visible and microwave
radiometric measurements during INDOEX: Implication to aerosols' indirect
radiative effect, J. Geophys. Res.-Atmos., 108, AAC 2-1–AAC 2-10,
https://doi.org/10.1029/2001JD001395, 2003.
Liu, L., Huang, X., Ding, A., and Fu, C.: Dust-induced radiative feedbacks
in north China: A dust storm episode modeling study using WRF-Chem, Atmos.
Environ., 129, 43–54, https://doi.org/10.1016/j.atmosenv.2016.01.019,
2016.
Liu, L., Bai, Y., Lin, C., and Yang, H.: Evaluation of Regional Air Quality
Numerical Forecasting System in Central China and Its Application for
Aerosol Radiative Effect, Meteorol. Mon., 44, 1179–1190,
https://doi.org/10.7519/j.issn.1000-0526.2018.09.006, 2018.
Liu, Q., Jia, X., Quan, J., Li, J., Li, X., Wu, Y., Chen, D., Wang, Z., and
Liu, Y.: New positive feedback mechanism between boundary layer meteorology
and secondary aerosol formation during severe haze events, Sci. Rep.-UK, 8,
1–8, https://doi.org/10.1038/s41598-018-24366-3, 2018.
Liu, X., Easter, R. C., Ghan, S. J., Zaveri, R., Rasch, P., Shi, X., Lamarque, J.-F., Gettelman, A., Morrison, H., Vitt, F., Conley, A., Park, S., Neale, R., Hannay, C., Ekman, A. M. L., Hess, P., Mahowald, N., Collins, W., Iacono, M. J., Bretherton, C. S., Flanner, M. G., and Mitchell, D.: Toward a minimal representation of aerosols in climate models: description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5, 709–739, https://doi.org/10.5194/gmd-5-709-2012, 2012.
Liu, X., Zhang, Y., Zhang, Q., and He, K.: Application of online-coupled
WRF/Chem-MADRID in East Asia: Model evaluation and climatic effects of
anthropogenic aerosols, Atmos. Environ., 124, 321–336,
https://doi.org/10.1016/j.atmosenv.2015.03.052, 2016.
Liu, Z., Yim, S. H. L., Wang, C., and Lau, N. C.: The Impact of the Aerosol
Direct Radiative Forcing on Deep Convection and Air Quality in the Pearl
River Delta Region, Geophys. Res. Lett., 45, 4410–4418,
https://doi.org/10.1029/2018GL077517, 2018.
Liu, Z., Ming, Y., Zhao, C., Lau, N. C., Guo, J., Bollasina, M., and Yim, S. H. L.: Contribution of local and remote anthropogenic aerosols to a record-breaking torrential rainfall event in Guangdong Province, China, Atmos. Chem. Phys., 20, 223–241, https://doi.org/10.5194/acp-20-223-2020, 2020.
Lohmann, U. and Diehl, K.: Sensitivity studies of the importance of dust ice
nuclei for the indirect aerosol effect on stratiform mixed-phase clouds, J.
Atmos. Sci., 63, 968–982, https://doi.org/10.1175/JAS3662.1, 2006.
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Ma, X. and Wen, W.: Modelling the Effect of Black Carbon and Sulfate Aerosol
on the Regional Meteorology Factors, in: IOP Conf. Ser. Earth Environ. Sci.,
12002, https://doi.org/10.1088/1755-1315/78/1/012002, 2017.
Ma, X., Chen, D., Wen, W., Sheng, L., Hu, J., Tong, H., and Wei, P.: Effect
of Particle Pollution on Regional Meteorological Factors in China, J.
Beijing Univ. Technol., 42, 285–295, https://doi.org/10.11936/bjutxb2015040075,
2016.
Mailler, S., Menut, L., Khvorostyanov, D., Valari, M., Couvidat, F., Siour, G., Turquety, S., Briant, R., Tuccella, P., Bessagnet, B., Colette, A., Létinois, L., Markakis, K., and Meleux, F.: CHIMERE-2017: from urban to hemispheric chemistry-transport modeling, Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, 2017.
Makar, P. A., Gong, W., Hogrefe, C., Zhang, Y., Curci, G., Žabkar, R.,
Milbrandt, J., Im, U., Balzarini, A., Baró, R., Bianconi, R., Cheung,
P., Forkel, R., Gravel, S., Hirtl, M., Honzak, L., Hou, A.,
Jiménez-Guerrero, P., Langer, M., Moran, M. D., Pabla, B., Pérez, J.
L., Pirovano, G., San José, R., Tuccella, P., Werhahn, J., Zhang, J.,
and Galmarini, S.: Feedbacks between air pollution and weather, part 2:
Effects on chemistry, Atmos. Environ., 115, 499–526,
https://doi.org/10.1016/j.atmosenv.2014.10.021, 2015a.
Makar, P. A., Gong, W., Milbrandt, J., Hogrefe, C., Zhang, Y., Curci, G.,
Žabkar, R., Im, U., Balzarini, A., Baró, R., Bianconi, R., Cheung,
P., Forkel, R., Gravel, S., Hirtl, M., Honzak, L., Hou, A.,
Jiménez-Guerrero, P., Langer, M., Moran, M. D., Pabla, B., Pérez, J.
L., Pirovano, G., San José, R., Tuccella, P., Werhahn, J., Zhang, J.,
and Galmarini, S.: Feedbacks between air pollution and weather, Part 1:
Effects on weather, Atmos. Environ., 115, 442–469,
https://doi.org/10.1016/j.atmosenv.2014.12.003, 2015b.
Manisalidis, I., Stavropoulou, E., Stavropoulos, A., and Bezirtzoglou, E.:
Environmental and health impacts of air pollution: A review, Front. Public
He., 8, 14, https://doi.org/10.3389/fpubh.2020.00014, 2020.
Marelle, L., Raut, J.-C., Law, K. S., Berg, L. K., Fast, J. D., Easter, R. C., Shrivastava, M., and Thomas, J. L.: Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic, Geosci. Model Dev., 10, 3661–3677, https://doi.org/10.5194/gmd-10-3661-2017, 2017.
Martin, D. E. and Leight, W. G.: Objective temperature estimates from mean
circulation patterns, Mon. Weather Rev., 77, 275–283,
https://doi.org/10.1175/1520-0493(1949)077<0275:OTEFMC>2.0.CO;2, 1949.
Martin, S. T., Schlenker, J. C., Malinowski, A., Hung, H., and Rudich, Y.:
Crystallization of atmospheric sulfate-nitrate-ammonium particles, Geophys.
Res. Lett., 30, 2102, https://doi.org/10.1029/2003GL017930, 2003.
Mass, C. and Ovens, D.: Fixing WRF's high speed wind bias: A new subgrid
scale drag parameterization and the role of detailed verification, in: 24th
conference on weather and forecasting and 20th conference on numerical
weather prediction, preprints, 91st American meteorological society annual
meeting, University of Washington, United States, 26 January 2011, 615–617, 2011.
McCormick, R. A. and Ludwig, J. H.: Climate modification by atmospheric
aerosols, Science, 156, 1358–1359,
https://doi.org/10.1126/science.156.3780.1358, 1967.
McMurry, P. H. and Friedlander, S. K.: New particle formation in the
presence of an aerosol, Atmos. Environ., 13, 1635–1651,
https://doi.org/10.1016/0004-6981(79)90322-6, 1979.
Miao, Y., Liu, S., Zheng, Y., and Wang, S.: Modeling the feedback between
aerosol and boundary layer processes: a case study in Beijing, China,
Environ. Sci. Pollut. Res., 23, 3342–3357,
https://doi.org/10.1007/s11356-015-5562-8, 2016.
Miao, Y., Guo, J., Liu, S., Zhao, C., Li, X., Zhang, G., Wei, W., and Ma,
Y.: Impacts of synoptic condition and planetary boundary layer structure on
the trans-boundary aerosol transport from Beijing-Tianjin-Hebei region to
northeast China, Atmos. Environ., 181, 1–11,
https://doi.org/10.1016/j.atmosenv.2018.03.005, 2018.
Napari, I., Noppel, M., Vehkamäki, H., and Kulmala, M.: Parametrization
of ternary nucleation rates for H2SO4-NH3-H2O vapors, J. Geophys. Res.-Atmos., 107, AAC 6-1–AAC 6-6,
https://doi.org/10.1029/2002JD002132, 2002.
Nenes, A., Pandis, S. N., and Pilinis, C.: ISORROPIA: A new thermodynamic
equilibrium model for multiphase multicomponent inorganic aerosols, Aquat.
Geochem., 4, 123–152, https://doi.org/10.1023/A:1009604003981, 1998.
Nguyen, G. T. H., Shimadera, H., Sekiguchi, A., Matsuo, T., and Kondo, A.:
Investigation of aerosol direct effects on meteorology and air quality in
East Asia by using an online coupled modeling system, Atmos. Environ., 207,
182–196, https://doi.org/10.1016/j.atmosenv.2019.03.017., 2019a.
Nguyen, G. T. H., Shimadera, H., Uranishi, K., Matsuo, T., Kondo, A., and
Thepanondh, S.: Numerical assessment of PM2.5 and O3 air quality
in continental Southeast Asia: Baseline simulation and aerosol direct
effects investigation, Atmos. Environ., 219, 117054,
https://doi.org/10.1016/j.atmosenv.2019.117054, 2019b.
North, G. R., Pyle, J. A., and
Zhang, F.: Encyclopedia of atmospheric sciences, Academic Press, Cambridge,
Massachusetts, United States, 2874 pp., 2014.
Odum, J. R., Jungkamp, T. P. W., Griffin, R. J., Flagan, R. C., and
Seinfeld, J. H.: The atmospheric aerosol-forming potential of whole gasoline
vapor, Science, 276, 96–99,
https://doi.org/10.1126/science.276.5309.96, 1997.
Park, S.-Y., Lee, H.-J., Kang, J.-E., Lee, T., and Kim, C.-H.: Aerosol
radiative effects on mesoscale cloud-precipitation variables over Northeast
Asia during the MAPS-Seoul 2015 campaign, Atmos. Environ., 172, 109–123,
https://doi.org/10.1016/j.atmosenv.2017.10.044, 2018.
Penner, J. E., Dong, X., and Chen, Y.: Observational evidence of a change in
radiative forcing due to the indirect aerosol effect, Nature, 427, 231–234,
https://doi.org/10.1038/nature02234, 2004.
Quaas, J., Boucher, O., Bellouin, N., and Kinne, S.: Satellite-based
estimate of the direct and indirect aerosol climate forcing, J. Geophys. Res.-Atmos., 113, D05204, https://doi.org/10.1029/2007JD008962, 2008.
Qiu, Y., Liao, H., Zhang, R., and Hu, J.: Simulated impacts of direct
radiative effects of scattering and absorbing aerosols on surface layer
aerosol concentrations in China during a heavily polluted event in february
2014, J. Geophys. Res., 122, 5955–5975,
https://doi.org/10.1002/2016JD026309, 2017.
Ramboll Environment and Health:
User's Guide: Comprehensive Air quality Model with extensions, Version 7.10,
Ramboll, Novato, CA, https://camxwp.azurewebsites.net/Files/CAMxUsersGuide_v7.10.pdf (last access: 20 March 2022),
2020.
Reid, J. S., Koppmann, R., Eck, T. F., and Eleuterio, D. P.: A review of biomass burning emissions part II: intensive physical properties of biomass burning particles, Atmos. Chem. Phys., 5, 799–825, https://doi.org/10.5194/acp-5-799-2005, 2005.
Rohde, R. A. and Muller, R. A.: Air pollution in China: mapping of
concentrations and sources, PLoS One, 10, e0135749,
https://doi.org/10.1371/journal.pone.0135749, 2015.
Rosenfeld, D.: Suppression of rain and snow by urban and industrial air
pollution, Science, 287, 1793–1796,
https://doi.org/10.1126/science.287.5459.1793, 2000.
Rosenfeld, D., Lohmann, U., Raga, G. B., O'Dowd, C. D., Kulmala, M., Fuzzi,
S., Reissell, A., and Andreae, M. O.: Flood or drought: How do aerosols
affect precipitation?, Science, 321, 1309–1313,
https://doi.org/10.1126/science.1160606, 2008.
Rosenfeld, D., Andreae, M. O., Asmi, A., Chin, M., de Leeuw, G., Donovan, D.
P., Kahn, R., Kinne, S., Kivekäs, N., and Kulmala, M.: Global
observations of aerosol-cloud-precipitation-climate interactions, Rev.
Geophys., 52, 750–808, https://doi.org/10.1002/2013RG000441, 2014.
Rosenfeld, D., Zhu, Y., Wang, M., Zheng, Y., Goren, T., and Yu, S.:
Aerosol-driven droplet concentrations dominate coverage and water of oceanic
low-level clouds, Science, 363, 1–9,
https://doi.org/10.1126/science.aav0566, 2019.
Saleh, R., Robinson, E. S., Tkacik, D. S., Ahern, A. T., Liu, S., Aiken, A.
C., Sullivan, R. C., Presto, A. A., Dubey, M. K., and Yokelson, R. J.:
Brownness of organics in aerosols from biomass burning linked to their black
carbon content, Nat. Geosci., 7, 647–650, https://doi.org/10.1038/ngeo2220,
2014.
Sarangi, C., Tripathi, S. N., Tripathi, S., and Barth, M. C.: Aerosol-cloud
associations over Gangetic Basin during a typical monsoon depression event
using WRF-Chem simulation, J. Geophys. Res.-Atmos., 120, 10–974,
https://doi.org/10.1002/2015JD023634, 2015.
Satheesh, S. K. and Moorthy, K. K.: Radiative effects of natural aerosols: A
review, Atmos. Environ., 39, 2089–2110,
https://doi.org/10.1016/j.atmosenv.2004.12.029, 2005.
Sato, Y. and Suzuki, K.: How do aerosols affect cloudiness?, Science, 363, 580–581, https://doi.org/10.1126/science.aaw3720, 2019.
Saylor, R. D., Baker, B. D., Lee, P., Tong, D., Pan, L., and Hicks, B. B.:
The particle dry deposition component of total deposition from air quality
models: right, wrong or uncertain?, Tellus B, 71,
1550324, https://doi.org/10.1080/16000889.2018.1550324, 2019.
Seaman, N. L.: Meteorological modeling for air-quality assessments, Atmos.
Environ., 34, 2231–2259, https://doi.org/10.1016/S1352-2310(99)00466-5,
2000.
Seethala, C., Pandithurai, G., Fast, J. D., Polade, S. D., Reddy, M. S., and
Peckham, S. E.: Evaluating WRF-Chem multi-scale model in simulating aerosol
radiative properties over the tropics-a case study over India, MAPAN-Journal of Metrology Society of India, 26, 269–284,
https://doi.org/10.1007/s12647-011-0025-2, 2011.
Seinfeld, J. and Pandis, S.:
Atmospheric chemistry and physics, in: Environment: an interdisciplinary anthology,
edited by: Kramer, A. and Rumold, R., Yale University Press, New Haven, United
States, 454–468, https://doi.org/10.12987/9780300150315, 2008.
Sekiguchi, A., Shimadera, H., and Kondo, A.: Impact of aerosol direct effect
on wintertime PM2.5 simulated by an online coupled meteorology-air
quality model over east asia, Aerosol Air Qual. Res., 18, 1068–1079,
https://doi.org/10.4209/aaqr.2016.06.0282, 2018.
Sekiguchi, M., Nakajima, T., Suzuki, K., Kawamoto, K., Higurashi, A.,
Rosenfeld, D., Sano, I., and Mukai, S.: A study of the direct and indirect
effects of aerosols using global satellite data sets of aerosol and cloud
parameters, J. Geophys. Res.-Atmos., 108, 4699,
https://doi.org/10.1029/2002JD003359, 2003.
Shahid, M. Z., Shahid, I., Chishtie, F., Shahzad, M. I., and Bulbul, G.:
Analysis of a dense haze event over North-eastern Pakistan using WRF-Chem
model and remote sensing, J. Atmos. Solar-Terr. Phy., 182, 229–241,
https://doi.org/10.1016/j.jastp.2018.12.007, 2019.
Shao, Y.: Simplification of a dust emission scheme and comparison with data,
J. Geophys. Res.-Atmos., 109, D10202, https://doi.org/10.1029/2003JD004372, 2004.
Shao, Y. and Dong, C. H.: A review on East Asian dust storm climate,
modelling and monitoring, Glob. Planet. Change, 52, 1–22,
https://doi.org/10.1016/j.gloplacha.2006.02.011, 2006.
Shen, H., Shi, H., Shi, H., and Ma, X.: Simulation Study of Influence of
Aerosol Pollution on Regional Meteorological Factors in
Beijing-Tianjin-Hebei Region, J. Anhui Agric. Sci., 43, 207–210,
https://doi.org/10.13989/j.cnki.0517-6611.2015.25.217, 2015.
Shen, X., Jiang, X., Liu, D., Zu, F., and Fan, S.: Simulations of
Anthropogenic Aerosols Effects on the Intensity and Precipitation of Typhoon
Fitow (1323) Using WRF-Chem Model, Chinese J. Atmos. Sci., 41, 960–974,
https://doi.org/10.3878/j.issn.1006-9895.1703.16216, 2017.
Singh, P., Sarawade, P., and Adhikary, B.: Carbonaceous Aerosol from Open
Burning and its Impact on Regional Weather in South Asia, Aerosol Air Qual.
Res., 20, 419–431, https://doi.org/10.4209/aaqr.2019.03.0146, 2020.
Slinn, W. G. N.: Precipitation
scavenging, in: Atmospheric science and power production, edited by: Randerson, D.,
U.S. Department of Energy, Washington, D.C., United States, 466–532, 1984,
1984.
Soni, P., Tripathi, S. N., and Srivastava, R.: Radiative effects of black
carbon aerosols on Indian monsoon: a study using WRF-Chem model, Theor.
Appl. Climatol., 132, 115–134, https://doi.org/10.1007/s00704-017-2057-1,
2018.
Srinivas, R., Panicker, A. S., Parkhi, N. S., Peshin, S. K., and Beig, G.:
Sensitivity of online coupled model to extreme pollution event over a mega
city Delhi, Atmos. Pollut. Res., 7, 25–30,
https://doi.org/10.1016/j.apr.2015.07.001, 2016.
Su, L. and Fung, J. C. H.: Investigating the role of dust in ice nucleation within clouds and further effects on the regional weather system over East Asia – Part 1: model development and validation, Atmos. Chem. Phys., 18, 8707–8725, https://doi.org/10.5194/acp-18-8707-2018, 2018a.
Su, L. and Fung, J. C. H.: Investigating the role of dust in ice nucleation within clouds and further effects on the regional weather system over East Asia – Part 2: modification of the weather system, Atmos. Chem. Phys., 18, 11529–11545, https://doi.org/10.5194/acp-18-11529-2018, 2018b.
Sud, Y. C. and Walker, G. K.: A review of recent
research on improvement of physical parameterizations in the GLA GCM, National
Aeronautics and Space Administration, United States, Open File Rep. 100771, 70 pp.,
1990.
Sun, K., Liu, H., Wang, X., Peng, Z., and Xiong, Z.: The aerosol radiative
effect on a severe haze episode in the Yangtze River Delta, J. Meteorol.
Res., 31, 865–873, https://doi.org/10.1007/s13351-017-7007-4, 2017.
Takemura, T., Nakajima, T., Higurashi, A., Ohta, S., and Sugimoto, N.:
Aerosol distributions and radiative forcing over the Asian Pacific region
simulated by Spectral Radiation-Transport Model for Aerosol Species
(SPRINTARS), J. Geophys. Res.-Atmos., 108, 8659,
https://doi.org/10.1029/2002JD003210, 2003.
Tang, Y., Han, Y., Ma, X., and Liu, Z.: Elevated heat pump effects of dust
aerosol over Northwestern China during summer, Atmos. Res., 203, 95–104,
https://doi.org/10.1016/j.atmosres.2017.12.004, 2018.
Ten Hoeve, J. E. and Jacobson, M. Z.: Worldwide health effects of the
Fukushima Daiichi nuclear accident, Energy Environ. Sci., 5, 8743–8757,
https://doi.org/10.1039/c2ee22019a, 2012.
Thompson, G. and Eidhammer, T.: A study of aerosol impacts on clouds and
precipitation development in a large winter cyclone, J. Atmos. Sci., 71,
3636–3658, https://doi.org/10.1175/JAS-D-13-0305.1, 2014.
Toon, O. B., McKay, C. P., Ackerman, T. P., and Santhanam, K.: Rapid
calculation of radiative heating rates and photodissociation rates in
inhomogeneous multiple scattering atmospheres, J. Geophys. Res.-Atmos., 94,
16287–16301, https://doi.org/10.1029/JD094iD13p16287, 1989.
Tremback, C., Tripoli, G., Arritt, R., Cotton, W. R., and
Pielke, R. A.: The regional atmospheric modeling system, in: Proceedings of an
International Conference on Development Applications of Computer Techniques
Environmental Studies, Los Angeles, United States, November 1986, 601–607, 1986.
Tsay, S.-C., Hsu, N. C., Lau, W. K.-M., Li, C., Gabriel, P. M., Ji, Q.,
Holben, B. N., Welton, E. J., Nguyen, A. X., and Janjai, S.: From BASE-ASIA
toward 7-SEAS: A satellite-surface perspective of boreal spring
biomass-burning aerosols and clouds in Southeast Asia, Atmos. Environ., 78,
20–34, https://doi.org/10.1016/j.atmosenv.2012.12.013, 2013.
Twomey, S.: The influence of pollution on the shortwave albedo of clouds, J.
Atmos. Sci., 34, 1149–1152,
https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977.
US Environmental Protection Agency:
Meteorological Model Performance for Annual 2016 Simulation WRF v3.8, Techn.
Support Documentation, https://www.epa.gov/sites/default/files/2020-10/documents/met_model_performance-2016_wrf.pdf (last access: 20 March 2022),
2019.
Uno, I., Wang, Z., Chiba, M., Chun, Y. S., Gong, S. L., Hara, Y., Jung, E.,
Lee, S., Liu, M., and Mikami, M.: Dust model intercomparison (DMIP) study
over Asia: Overview, J. Geophys. Res.-Atmos., 111, D12213,
https://doi.org/10.1029/2005JD006575, 2006.
Vehkamäki, H., Kulmala, M., Napari, I., Lehtinen, K. E. J., Timmreck,
C., Noppel, M., and Laaksonen, A.: An improved parameterization for sulfuric
acid-water nucleation rates for tropospheric and stratospheric conditions,
J. Geophys. Res.-Atmos., 107, AAC 3-1–AAC 3-10,
https://doi.org/10.1029/2002JD002184, 2002.
Wang, D., Jiang, B., Lin, W., and Gu, F.: Effects of aerosol-radiation
feedback and topography during an air pollution event over the North China
Plain during December 2017, Atmos. Pollut. Res., 10, 587–596,
https://doi.org/10.1016/j.apr.2018.10.006, 2019a.
Wang, H. and Niu, T.: Sensitivity studies of aerosol data assimilation and
direct radiative feedbacks in modeling dust aerosols, Atmos. Environ., 64,
208–218, https://doi.org/10.1016/j.atmosenv.2012.09.066, 2013.
Wang, H., Zhang, X., Gong, S., Chen, Y., Shi, G., and Li, W.: Radiative
feedback of dust aerosols on the East Asian dust storms, J. Geophys. Res.-Atmos., 115, D23214, https://doi.org/10.1029/2009JD013430, 2010.
Wang, H., Shi, G., Zhu, J., Chen, B., Che, H., and Zhao, T.: Case study of
longwave contribution to dust radiative effects over East Asia, Chinese Sci.
Bull., 58, 3673–3681, https://doi.org/10.1007/s11434-013-5752-z, 2013.
Wang, H., Shi, G. Y., Zhang, X. Y., Gong, S. L., Tan, S. C., Chen, B., Che, H. Z., and Li, T.: Mesoscale modelling study of the interactions between aerosols and PBL meteorology during a haze episode in China Jing–Jin–Ji and its near surrounding region – Part 2: Aerosols' radiative feedback effects, Atmos. Chem. Phys., 15, 3277–3287, https://doi.org/10.5194/acp-15-3277-2015, 2015.
Wang, H., Peng, Y., Zhang, X., Liu, H., Zhang, M., Che, H., Cheng, Y., and Zheng, Y.: Contributions to the explosive growth of PM2.5 mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China, Atmos. Chem. Phys., 18, 17717–17733, https://doi.org/10.5194/acp-18-17717-2018, 2018.
Wang, J., Wang, S., Jiang, J., Ding, A., Zheng, M., Zhao, B., Wong, D. C.,
Zhou, W., Zheng, G., Wang, L., Pleim, J. E., and Hao, J.: Impact of
aerosol-meteorology interactions on fine particle pollution during China's
severe haze episode in January 2013, Environ. Res. Lett., 9, 1–7,
https://doi.org/10.1088/1748-9326/9/9/094002, 2014.
Wang, J., Allen, D. J., Pickering, K. E., Li, Z., and He, H.: Impact of
aerosol direct effect on East Asian air quality during the EAST-AIRE
campaign, J. Geophys. Res.-Atmos., 121, 6534–6554,
https://doi.org/10.1002/2016JD025108, 2016.
Wang, J., Xing, J., Mathur, R., Pleim, J. E., Wang, S., Hogrefe, C., Gan,
C.-M., Wong, D. C., and Hao, J.: Historical trends in PM2.5-related
premature mortality during 1990–2010 across the northern hemisphere,
Environ. Health Perspect., 125, 400–408, https://doi.org/10.1289/EHP298,
2017.
Wang, K., Yahya, K., Zhang, Y., Hogrefe, C., Pouliot, G., Knote, C., Hodzic,
A., San Jose, R., Perez, J. L., and Jiménez-Guerrero, P.: A multi-model
assessment for the 2006 and 2010 simulations under the Air Quality Model
Evaluation International Initiative (AQMEII) Phase 2 over North America:
Part II. Evaluation of column variable predictions using satellite data,
Atmos. Environ., 115, 587–603,
https://doi.org/10.1016/j.atmosenv.2014.07.044, 2015.
Wang, K., Zhang, Y., Zhang, X., Fan, J., Leung, L. R., Zheng, B., Zhang, Q.,
and He, K.: Fine-scale application of WRF-CAM5 during a dust storm episode
over East Asia: Sensitivity to grid resolutions and aerosol activation
parameterizations, Atmos. Environ., 176, 1–20,
https://doi.org/10.1016/j.atmosenv.2017.12.014, 2018.
Wang, L., Fu, J. S., Wei, W., Wei, Z., Meng, C., Ma, S., and Wang, J.: How
aerosol direct effects influence the source contributions to PM2.5
concentrations over Southern Hebei, China in severe winter haze episodes,
Front. Environ. Sci. Eng., 12, 13,
https://doi.org/10.1007/s11783-018-1014-2, 2018.
Wang, Z., Wang, Z., Li, J., Zheng, H., Yan, P., and Li, J.: Development of a
meteorology-chemistry two-way coupled numerical model (WRF-NAQPMS) and its
application in a severe autumn haze simulation over the
Beijing-Tianjin-Hebei area, China. Clim, Environ. Res., 19, 153–163,
https://doi.org/10.3878/j.issn.1006-9585.2014.13231, 2014.
Wang, Z., Huang, X., and Ding, A.: Dome effect of black carbon and its key influencing factors: a one-dimensional modelling study, Atmos. Chem. Phys., 18, 2821–2834, https://doi.org/10.5194/acp-18-2821-2018, 2018.
Wang, Z., Huang, X., and Ding, A.: Optimization of vertical grid setting for
air quality modelling in China considering the effect of aerosol-boundary
layer interaction, Atmos. Environ., 210, 1–13,
https://doi.org/10.1016/j.atmosenv.2019.04.042, 2019.
Wang, Z. F., Li, J., Wang, Z., Yang, W., Tang, X., Ge, B., Yan, P., Zhu, L.,
Chen, X., and Chen, H.: Modeling study of regional severe hazes over
mid-eastern China in January 2013 and its implications on pollution
prevention and control, Sci. China Earth Sci., 57, 3–13,
https://doi.org/10.1007/s11430-013-4793-0, 2014.
Wendisch, M., Keil, A., Müller, D., Wandinger, U., Wendling, P.,
Stifter, A., Petzold, A., Fiebig, M., Wiegner, M., and Freudenthaler, V.:
Aerosol-radiation interaction in the cloudless atmosphere during LACE 98 1.
Measured and calculated broadband solar and spectral surface insolations, J. Geophys. Res.-Atmos., 107, LAC 6-1–LAC 6-20,
https://doi.org/10.1029/2000JD000226, 2002.
Wexler, A. S., Lurmann, F. W., and Seinfeld, J. H.: Modelling urban and
regional aerosols-I. Model development, Atmos. Environ., 28, 531–546,
https://doi.org/10.1016/1352-2310(94)90129-5, 1994.
Whitby, K. T.: The physical characteristics of sulfur aerosols, in: Sulfur
in the Atmosphere, Elsevier, 135–159,
https://doi.org/10.1016/B978-0-08-022932-4.50018-5, 1978.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Wilcox, E. M.: Direct and semi-direct radiative forcing of smoke aerosols over clouds, Atmos. Chem. Phys., 12, 139–149, https://doi.org/10.5194/acp-12-139-2012, 2012.
Wong, D. C., Pleim, J., Mathur, R., Binkowski, F., Otte, T., Gilliam, R., Pouliot, G., Xiu, A., Young, J. O., and Kang, D.: WRF-CMAQ two-way coupled system with aerosol feedback: software development and preliminary results, Geosci. Model Dev., 5, 299–312, https://doi.org/10.5194/gmd-5-299-2012, 2012.
Wu, J., Bei, N., Hu, B., Liu, S., Zhou, M., Wang, Q., Li, X., Liu, L., Feng, T., Liu, Z., Wang, Y., Cao, J., Tie, X., Wang, J., Molina, L. T., and Li, G.: Aerosol–radiation feedback deteriorates the wintertime haze in the North China Plain, Atmos. Chem. Phys., 19, 8703–8719, https://doi.org/10.5194/acp-19-8703-2019, 2019a.
Wu, J., Bei, N., Hu, B., Liu, S., Zhou, M., Wang, Q., Li, X., Liu, L., Feng, T., Liu, Z., Wang, Y., Cao, J., Tie, X., Wang, J., Molina, L. T., and Li, G.: Is water vapor a key player of the wintertime haze in North China Plain?, Atmos. Chem. Phys., 19, 8721–8739, https://doi.org/10.5194/acp-19-8721-2019, 2019b.
Wu, L., Su, H., and Jiang, J. H.: Regional simulation of aerosol impacts on
precipitation during the East Asian summer monsoon, J. Geophys. Res.-Atmos.,
118, 6454–6467, https://doi.org/10.1002/jgrd.50527, 2013.
Wu, W. and Zhang, Y.: Effects of particulate matter (PM2.5) and
associated acidity on ecosystem functioning: response of leaf litter
breakdown, Environ. Sci. Pollut. Res., 25, 30720–30727,
https://doi.org/10.1007/s11356-018-2922-1, 2018.
Wu, Y., Han, Y., Voulgarakis, A., Wang, T., Li, M., Wang, Y., Xie, M.,
Zhuang, B., and Li, S.: An agricultural biomass burning episode in eastern
China: Transport, optical properties, and impacts on regional air quality,
J. Geophys. Res.-Atmos., 122, 2304–2324,
https://doi.org/10.1002/2016JD025319, 2017.
Xie, M., Liao, J., Wang, T., Zhu, K., Zhuang, B., Han, Y., Li, M., and Li, S.: Modeling of the anthropogenic heat flux and its effect on regional meteorology and air quality over the Yangtze River Delta region, China, Atmos. Chem. Phys., 16, 6071–6089, https://doi.org/10.5194/acp-16-6071-2016, 2016.
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D. C., and Wei, C.: Can a coupled meteorology–chemistry model reproduce the historical trend in aerosol direct radiative effects over the Northern Hemisphere?, Atmos. Chem. Phys., 15, 9997–10018, https://doi.org/10.5194/acp-15-9997-2015, 2015a.
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D. C., Wei, C., Gilliam, R., and Pouliot, G.: Observations and modeling of air quality trends over 1990–2010 across the Northern Hemisphere: China, the United States and Europe, Atmos. Chem. Phys., 15, 2723–2747, https://doi.org/10.5194/acp-15-2723-2015, 2015b.
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C., Wong, D. C., Wei, C.,
and Wang, J.: Air pollution and climate response to aerosol direct radiative
effects: A modeling study of decadal trends across the northern hemisphere,
J. Geophys. Res.-Atmos., 120, 12–221, https://doi.org/10.1002/2015JD023933,
2015c.
Xing, J., Wang, J., Mathur, R., Pleim, J., Wang, S., Hogrefe, C., Gan,
C.-M., Wong, D. C., and Hao, J.: Unexpected benefits of reducing aerosol
cooling effects, Environ. Sci. Technol., 50, 7527–7534,
https://doi.org/10.1021/acs.est.6b00767, 2016.
Xing, J., Wang, J., Mathur, R., Wang, S., Sarwar, G., Pleim, J., Hogrefe, C., Zhang, Y., Jiang, J., Wong, D. C., and Hao, J.: Impacts of aerosol direct effects on tropospheric ozone through changes in atmospheric dynamics and photolysis rates, Atmos. Chem. Phys., 17, 9869–9883, https://doi.org/10.5194/acp-17-9869-2017, 2017.
Yahya, K., Wang, K., Gudoshava, M., Glotfelty, T., and Zhang, Y.:
Application of WRF/Chem over North America under the AQMEII Phase 2: Part I.
Comprehensive evaluation of 2006 simulation, Atmos. Environ., 115, 733–755,
https://doi.org/10.1016/j.atmosenv.2014.08.063, 2015.
Yan, J., Wang, X., Gong, P., Wang, C., and Cong, Z.: Review of brown carbon
aerosols: Recent progress and perspectives, Sci. Total Environ., 634,
1475–1485, https://doi.org/10.1016/j.scitotenv.2018.04.083, 2018.
Yang, J., Duan, K., Kang, S., Shi, P., and Ji, Z.: Potential feedback
between aerosols and meteorological conditions in a heavy pollution event
over the Tibetan Plateau and Indo-Gangetic Plain, Clim. Dynam., 48,
2901–2917, https://doi.org/10.1007/s00382-016-3240-2, 2017.
Yang, J., Kang, S., Ji, Z., and Chen, D.: Modeling the origin of
anthropogenic black carbon and its climatic effect over the Tibetan Plateau
and surrounding regions, J. Geophys. Res.-Atmos., 123, 671–692,
https://doi.org/10.1002/2017JD027282, 2018.
Yang, T. and Liu, Y.: Impact of anthropogenic pollution on “7.21” extreme
heavy rainstorm, J. Meteorol. Sci., 37, 742–752,
https://doi.org/10.3969/2016jms.0074, 2017a.
Yang, T. and Liu, Y.: Mechanism analysis of the impacts of aerosol direct
effects on a rainstorm, J. Trop. Meteorol., 33, 762–773,
https://doi.org/10.16032/j.issn.1004-4965.2017.05.019, 2017b.
Yang, Y., Tang, J., Sun, J., Wang, L., Wang, X., Zhang, Y., Qu, Q., and
Zhao, W.: Synoptic Effect of a Heavy Haze Episode over North China, Clim.
Environ. Res., 20, 555–570,
https://doi.org/10.3878/j.issn.1006-9585.2015.15018, 2015.
Yang, Y., Fan, J., Leung, L. R., Zhao, C., Li, Z., and Rosenfeld, D.:
Mechanisms contributing to suppressed precipitation in Mt. Hua of central
China. Part I: Mountain valley circulation, J. Atmos. Sci., 73, 1351–1366,
https://doi.org/10.1175/JAS-D-15-0233.1, 2016.
Yang, Y., Zhao, C., Dong, X., Fan, G., Zhou, Y., Wang, Y., Zhao, L., Lv, F.,
and Yan, F.: Toward understanding the process-level impacts of aerosols on
microphysical properties of shallow cumulus cloud using aircraft
observations, Atmos. Res., 221, 27–33,
https://doi.org/10.1016/j.atmosres.2019.01.027, 2019.
Yao, H., Song, Y., Liu, M., Archer-Nicholls, S., Lowe, D., McFiggans, G., Xu, T., Du, P., Li, J., Wu, Y., Hu, M., Zhao, C., and Zhu, T.: Direct radiative effect of carbonaceous aerosols from crop residue burning during the summer harvest season in East China, Atmos. Chem. Phys., 17, 5205–5219, https://doi.org/10.5194/acp-17-5205-2017, 2017.
Yasunari, T. J. and Yamazaki, K.: Impacts of Asian dust storm associated
with the stratosphere-to-troposphere transport in the spring of 2001 and
2002 on dust and tritium variations in Mount Wrangell ice core, Alaska,
Atmos. Environ., 43, 2582–2590,
https://doi.org/10.1016/j.atmosenv.2009.02.025, 2009.
Yiğit, E., Knížová, P. K., Georgieva, K., and Ward, W.: A
review of vertical coupling in the Atmosphere–Ionosphere system: Effects of
waves, sudden stratospheric warmings, space weather, and of solar activity,
J. Atmos. Solar-Terr. Phy., 141, 1–12,
https://doi.org/10.1016/j.jastp.2016.02.011, 2016.
Yoo, J.-W., Jeon, W., Park, S.-Y., Park, C., Jung, J., Lee, S.-H., and Lee,
H. W.: Investigating the regional difference of aerosol feedback effects
over South Korea using the WRF-CMAQ two-way coupled modeling system, Atmos.
Environ., 218, 116968, https://doi.org/10.1016/j.atmosenv.2019.116968, 2019.
Yoon, J., Chang, D. Y., Lelieveld, J., Pozzer, A., Kim, J., and Yum, S. S.:
Empirical evidence of a positive climate forcing of aerosols at elevated
albedo, Atmos. Res., 229, 269–279,
https://doi.org/10.1016/j.atmosres.2019.07.001, 2019.
Yu, F.: Binary H2SO4-H2O homogeneous nucleation based on
kinetic quasi-unary nucleation model: Look-up tables, J. Geophys. Res.-Atmos., 111, D04201, https://doi.org/10.1029/2005JD006358, 2006.
Yu, F. and Luo, G.: Simulation of particle size distribution with a global aerosol model: contribution of nucleation to aerosol and CCN number concentrations, Atmos. Chem. Phys., 9, 7691–7710, https://doi.org/10.5194/acp-9-7691-2009, 2009.
Yu, H., Kaufman, Y. J., Chin, M., Feingold, G., Remer, L. A., Anderson, T. L., Balkanski, Y., Bellouin, N., Boucher, O., Christopher, S., DeCola, P., Kahn, R., Koch, D., Loeb, N., Reddy, M. S., Schulz, M., Takemura, T., and Zhou, M.: A review of measurement-based assessments of the aerosol direct radiative effect and forcing, Atmos. Chem. Phys., 6, 613–666, https://doi.org/10.5194/acp-6-613-2006, 2006.
Yuan, T., Chen, S., Huang, J., Wu, D., Lu, H., Zhang, G., Ma, X., Chen, Z.,
Luo, Y., and Ma, X.: Influence of dynamic and thermal forcing on the
meridional transport of Taklimakan Desert dust in spring and summer, J.
Clim., 32, 749–767, https://doi.org/10.1175/JCLI-D-18-0361.1, 2019.
Zaveri, R. A., Easter, R. C., Fast, J. D., and Peters, L. K.: Model for
simulating aerosol interactions and chemistry (MOSAIC), J. Geophys. Res.-Atmos., 113, D13204, https://doi.org/10.1029/2007JD008782, 2008.
Zhan, J., Chang, W., Li, W., Wang, Y., Chen, L., and Yan, J.: Impacts of
meteorological conditions, aerosol radiative feedbacks, and emission
reduction scenarios on the coastal haze episodes in southeastern China in
December 2013, J. Appl. Meteorol. Climatol., 56, 1209–1229,
https://doi.org/10.1175/JAMC-D-16-0229.1, 2017.
Zhang, B., Wang, Y., and Hao, J.: Simulating aerosol–radiation–cloud feedbacks on meteorology and air quality over eastern China under severe haze conditionsin winter, Atmos. Chem. Phys., 15, 2387–2404, https://doi.org/10.5194/acp-15-2387-2015, 2015.
Zhang, H., DeNero, S. P., Joe, D. K., Lee, H.-H., Chen, S.-H., Michalakes, J., and Kleeman, M. J.: Development of a source oriented version of the WRF/Chem model and its application to the California regional PM10
Zhang, H., Cheng, S., Li, J., Yao, S., and Wang, X.: Investigating the
aerosol mass and chemical components characteristics and feedback effects on
the meteorological factors in the Beijing-Tianjin-Hebei region, China,
Environ. Pollut., 244, 495–502,
https://doi.org/10.1016/j.envpol.2018.10.087, 2019.
Zhang, L., Wang, T., Lv, M., and Zhang, Q.: On the severe haze in Beijing
during January 2013: Unraveling the effects of meteorological anomalies with
WRF-Chem, Atmos. Environ., 104, 11–21,
https://doi.org/10.1016/j.atmosenv.2015.01.001, 2015.
Zhang, L., Gong, S., Zhao, T., Zhou, C., Wang, Y., Li, J., Ji, D., He, J., Liu, H., Gui, K., Guo, X., Gao, J., Shan, Y., Wang, H., Wang, Y., Che, H., and Zhang, X.: Development of WRF/CUACE v1.0 model and its preliminary application in simulating air quality in China, Geosci. Model Dev., 14, 703–718, https://doi.org/10.5194/gmd-14-703-2021, 2021.
Zhang, X., Zhang, Q., Hong, C., Zheng, Y., Geng, G., Tong, D., Zhang, Y.,
and Zhang, X.: Enhancement of PM2.5 Concentrations by
Aerosol-Meteorology Interactions Over China, J. Geophys. Res.-Atmos., 123,
1179–1194, https://doi.org/10.1002/2017JD027524, 2018.
Zhang, X. Y., Gong, S. L., Shen, Z. X., Mei, F. M., Xi, X. X., Liu, L. C.,
Zhou, Z. J., Wang, D., Wang, Y. Q., and Cheng, Y.: Characterization of soil
dust aerosol in China and its transport and distribution during 2001
ACE-Asia: 1. Network observations, J. Geophys. Res.-Atmos., 108, 4261,
https://doi.org/10.1029/2002JD002632, 2003a.
Zhang, X. Y., Gong, S. L., Zhao, T. L., Arimoto, R., Wang, Y. Q., and Zhou,
Z. J.: Sources of Asian dust and role of climate change versus
desertification in Asian dust emission, Geophys. Res. Lett., 30, 2272,
https://doi.org/10.1029/2003GL018206, 2003b.
Zhang, Y.: Online-coupled meteorology and chemistry models: history, current status, and outlook, Atmos. Chem. Phys., 8, 2895–2932, https://doi.org/10.5194/acp-8-2895-2008, 2008.
Zhang, Y., Pun, B., Vijayaraghavan, K., Wu, S., Seigneur, C., Pandis, S. N.,
Jacobson, M. Z., Nenes, A., and Seinfeld, J. H.: Development and application
of the model of aerosol dynamics, reaction, ionization, and dissolution
(MADRID), J. Geophys. Res.-Atmos., 109, D01202,
https://doi.org/10.1029/2003JD003501, 2004.
Zhang, Y., Hu, X. M., Howell, G. W., Sills, E., Fast, J. D.,
Gustafson Jr, W. I., Zaveri, R. A., Grell, G. A., Peckham, S. E., and McKeen, S. A.:
Modeling atmospheric aerosols in WRF/CHEM, in: WRF/MM5 Users's Workshop, 27–30 June 2005,
Boulder, Colorado, United States, 1–4, 2005.
Zhang, Y., Pan, Y., Wang, K., Fast, J. D., and Grell, G. A.:
WRF/Chem-MADRID: Incorporation of an aerosol module into WRF/Chem and its
initial application to the TexAQS2000 episode, J. Geophys. Res.-Atmos., 115, D18202,
https://doi.org/10.1029/2009JD013443, 2010.
Zhang, Y., Karamchandani, P., Glotfelty, T., Streets, D. G., Grell, G.,
Nenes, A., Yu, F., and Bennartz, R.: Development and initial application of
the global-through-urban weather research and forecasting model with
chemistry (GU-WRF/Chem), J. Geophys. Res.-Atmos., 117, D20206,
https://doi.org/10.1029/2012JD017966, 2012.
Zhang, Y., Zhang, X., Cai, C., Wang, K., and Wang, L.: Studying
Aerosol-Cloud-Climate Interactions over East Asia Using WRF/Chem, in: Air
Pollution Modeling and its Application XXIII, Springer, 61–66,
https://doi.org/10.1007/978-3-319-04379-1_10, 2014.
Zhang, Y., Chen, Y., Fan, J., and Leung, L.-Y. R.: Application of an
online-coupled regional climate model, WRF-CAM5, over East Asia for
examination of ice nucleation schemes: part II. Sensitivity to heterogeneous
ice nucleation parameterizations and dust emissions, Climate, 3, 753–774,
https://doi.org/10.3390/cli3030753, 2015a.
Zhang, Y., Zhang, X., Wang, K., He, J., Leung, L. R., Fan, J., and Nenes,
A.: Incorporating an advanced aerosol activation parameterization into
WRF-CAM5: Model evaluation and parameterization intercomparison, J. Geophys. Res.-Atmos., 120, 6952–6979, https://doi.org/10.1002/2014JD023051, 2015b.
Zhang, Y., Fan, S., Li, H., and Kang, B.: Effects of aerosol radiative
feedback during a severe smog process over eastern China, Acta Meteorol.,
74, 465–478, https://doi.org/10.11676/qxxb2016.028, 2016a.
Zhang, Y., He, J., Zhu, S., and Gantt, B.: Sensitivity of simulated chemical
concentrations and aerosol-meteorology interactions to aerosol treatments
and biogenic organic emissions in WRF/Chem, J. Geophys. Res.-Atmos., 121,
6014–6048, https://doi.org/10.1002/2016JD024882, 2016b.
Zhang, Y., Zhang, X., Wang, K., Zhang, Q., Duan, F., and He, K.: Application
of WRF/Chem over East Asia: Part II. Model improvement and sensitivity
simulations, Atmos. Environ., 124, 301–320,
https://doi.org/10.1016/j.atmosenv.2015.07.023, 2016c.
Zhang, Y., Zhang, X., Wang, L., Zhang, Q., Duan, F., and He, K.: Application
of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison
with MM5/CMAQ, Atmos. Environ., 124, 285–300,
https://doi.org/10.1016/j.atmosenv.2015.07.022., 2016d.
Zhang, Y., Wang, K., and He, J.: Multi-year application of WRF-CAM5 over
East Asia-Part II: Interannual variability, trend analysis, and aerosol
indirect effects, Atmos. Environ., 165, 222–239,
https://doi.org/10.1016/j.atmosenv.2017.06.029, 2017.
Zhao, B., Liou, K., Gu, Y., Li, Q., Jiang, J. H., Su, H., He, C., Tseng,
H.-L. R., Wang, S., and Liu, R.: Enhanced PM2.5 pollution in China due
to aerosol-cloud interactions, Sci. Rep.-UK, 7, 1–11,
https://doi.org/10.1038/s41598-017-04096-8, 2017.
Zhao, B., Wang, Y., Gu, Y., Liou, K.-N., Jiang, J. H., Fan, J., Liu, X.,
Huang, L., and Yung, Y. L.: Ice nucleation by aerosols from anthropogenic
pollution, Nat. Geosci., 12, 602–607,
https://doi.org/10.1038/s41561-019-0389-4, 2019.
Zhong, M., Saikawa, E., Liu, Y., Naik, V., Horowitz, L. W., Takigawa, M., Zhao, Y., Lin, N.-H., and Stone, E. A.: Air quality modeling with WRF-Chem v3.5 in East Asia: sensitivity to emissions and evaluation of simulated air quality, Geosci. Model Dev., 9, 1201–1218, https://doi.org/10.5194/gmd-9-1201-2016, 2016.
Zhong, M., Chen, F., and Saikawa, E.: Sensitivity of projected PM2.5-
and O3-related health impacts to model inputs: A case study in mainland
China, Environ. Int., 123, 256–264,
https://doi.org/10.1016/j.envint.2018.12.002, 2019.
Zhong, S., Qian, Y., Zhao, C., Leung, R., and Yang, X.: A case study of
urbanization impact on summer precipitation in the Greater Beijing
Metropolitan Area: Urban heat island versus aerosol effects, J. Geophys. Res.-Atmos., 120, 10–903, https://doi.org/10.1002/2015JD023753, 2015.
Zhong, S., Qian, Y., Zhao, C., Leung, R., Wang, H., Yang, B., Fan, J., Yan, H., Yang, X.-Q., and Liu, D.: Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China, Atmos. Chem. Phys., 17, 5439–5457, https://doi.org/10.5194/acp-17-5439-2017, 2017.
Zhou, C., Gong, S., Zhang, X., Liu, H., Xue, M., Cao, G., An, X., Che, H.,
Zhang, Y., and Niu, T.: Towards the improvements of simulating the chemical
and optical properties of Chinese aerosols using an online coupled
model-CUACE/Aero, Tellus B, 64, 18965,
https://doi.org/10.3402/tellusb.v64i0.18965, 2012.
Zhou, C., Zhang, X., Gong, S., Wang, Y., and Xue, M.: Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system, Atmos. Chem. Phys., 16, 145–160, https://doi.org/10.5194/acp-16-145-2016, 2016.
Zhou, C. H., Gong, S. L., Zhang, X. Y., Wang, Y. Q., Niu, T., Liu, H. L., Zhao, T. L., Yang, Y. Q., and Hou, Q.: Development and evaluation of an operational SDS forecasting system for East Asia: CUACE/Dust, Atmos. Chem. Phys., 8, 787–798, https://doi.org/10.5194/acp-8-787-2008, 2008.
Zhou, D., Ding, K., Huang, X., Liu, L., Liu, Q., Xu, Z., Jiang, F., Fu, C., and Ding, A.: Transport, mixing and feedback of dust, biomass burning and anthropogenic pollutants in eastern Asia: a case study, Atmos. Chem. Phys., 18, 16345–16361, https://doi.org/10.5194/acp-18-16345-2018, 2018.
Zhou, M., Zhang, L., Chen, D., Gu, Y., Fu, T.-M., Gao, M., Zhao, Y., Lu, X.,
and Zhao, B.: The impact of aerosol-radiation interactions on the
effectiveness of emission control measures, Environ. Res. Lett., 14, 24002,
https://doi.org/10.1088/1748-9326/aaf27d, 2019.
Zhou, Y., Gong, S., Zhou, C., Zhang, L., He, J., Wang, Y., Ji, D., Feng, J.,
Mo, J., and Ke, H.: A new parameterization of uptake coefficients for
heterogeneous reactions on multi-component atmospheric aerosols, Sci. Total
Environ., 781, 146372, https://doi.org/10.1016/j.scitotenv.2021.146372,
2021.
Zhuang, B., Jiang, F., Wang, T., Li, S., and Zhu, B.: Investigation on the
direct radiative effect of fossil fuel black-carbon aerosol over China,
Theor. Appl. Climatol., 104, 301–312,
https://doi.org/10.1007/s00704-010-0341-4, 2011.
Short summary
With ever-growing applications of two-way coupled meteorology and air quality models in Asia over the past decade, this paper summarizes the current status and research focuses, as well as how aerosol effects impact model performance, meteorology, and air quality. These models enable investigations of ARI and ACI effects induced by natural and anthropogenic aerosols in Asia, which has serious air pollution problems. The current gaps and perspectives are also presented and discussed.
With ever-growing applications of two-way coupled meteorology and air quality models in Asia...
Altmetrics
Final-revised paper
Preprint