Articles | Volume 20, issue 9
https://doi.org/10.5194/acp-20-5729-2020
© Author(s) 2020. 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-20-5729-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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14 May 2020
Research article | Highlight paper |
| 14 May 2020
| 14 May 2020
Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Jing Cheng
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Sha Yu
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, University Research Court, College Park, MD 20742, USA
Liu Yan
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Chaopeng Hong
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Yu Qin
State Key Joint Laboratory of Environment Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing 100084,
People's Republic of China
Hongyan Zhao
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Yixuan Zheng
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
Guannan Geng
State Key Joint Laboratory of Environment Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing 100084,
People's Republic of China
Meng Li
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
State Key Joint Laboratory of Environment Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing 100084,
People's Republic of China
Yuxuan Zhang
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
State Key Joint Laboratory of Environment Simulation and Pollution
Control, School of Environment, Tsinghua University, Beijing 100084,
People's Republic of China
Leon Clarke
Center for Global Sustainability, School of Public Policy, University of Maryland, College Park, MD 20742, USA
Qiang Zhang
CORRESPONDING AUTHOR
Ministry of Education Key Laboratory for Earth System Modelling,
Department of Earth System Science, Tsinghua University, Beijing 100084,
People's Republic of China
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The large uncertainties in OH simulated by atmospheric chemistry models hinder accurate estimates of CH4 chemical loss through the bottom-up method. This study presents a new approach based on OH precursor observations and a chemical box model to improve the tropospheric OH distributions simulated by atmospheric chemistry models. Through this approach, both the global OH burden and the corresponding methane chemical loss reach consistency with the top-down method based on MCF inversions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Qingyang Xiao, Guannan Geng, Shigan Liu, Jiajun Liu, Xia Meng, and Qiang Zhang
Atmos. Chem. Phys., 22, 13229–13242, https://doi.org/10.5194/acp-22-13229-2022, https://doi.org/10.5194/acp-22-13229-2022, 2022
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We provided complete coverage PM2.5 concentrations at a 1-km resolution from 2000 to the present, carefully considering the significant changes in land use characteristics in China. This high-resolution PM2.5 data successfully revealed the local-scale PM2.5 variations. We noticed changes in PM2.5 spatial patterns in association with the clean air policies, with the pollution hotspots having transferred from urban centers to rural regions with limited air quality monitoring.
Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 15, 5497–5514, https://doi.org/10.5194/amt-15-5497-2022, https://doi.org/10.5194/amt-15-5497-2022, 2022
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Satellite observations provide information on the sources of SO2, an important pollutant that affects both air quality and climate. However, these observations suffer from relatively poor data quality due to weak signals of SO2. Here, we use a machine learning technique to analyze satellite SO2 observations in order to reduce the noise and artifacts over relatively clean areas while keeping the signals near pollution sources. This leads to significant improvement in satellite SO2 data.
Yawen Kong, Bo Zheng, Qiang Zhang, and Kebin He
Atmos. Chem. Phys., 22, 10769–10788, https://doi.org/10.5194/acp-22-10769-2022, https://doi.org/10.5194/acp-22-10769-2022, 2022
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We developed a Bayesian atmospheric inversion system based on the 4D local ensemble transform Kalman filter (4D-LETKF) algorithm coupled with GEOS-Chem from the latest Orbiting Carbon Observatory-2 (OCO-2) V10r XCO2 retrievals. This is the first adaptation of 4D-LETKF to an OCO-2-based global carbon inversion system. We inferred global gridded carbon fluxes and investigated their magnitudes, variations, and partitioning schemes to understand the global and regional carbon budgets for 2015–2020.
Le Yuan, Olalekan A. M. Popoola, Christina Hood, David Carruthers, Roderic L. Jones, Haitong Zhe Sun, Huan Liu, Qiang Zhang, and Alexander T. Archibald
Atmos. Chem. Phys., 22, 8617–8637, https://doi.org/10.5194/acp-22-8617-2022, https://doi.org/10.5194/acp-22-8617-2022, 2022
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Emission estimates represent a major source of uncertainty in air quality modelling. We developed a novel approach to improve emission estimates from existing inventories using air quality models and routine in situ observations. Using this approach, we derived improved estimates of NOx emissions from the transport sector in Beijing in 2016. This approach has great potential in deriving timely updates of emissions for other pollutants, particularly in regions undergoing rapid emission changes.
Marios Panagi, Roberto Sommariva, Zoë L. Fleming, Paul S. Monks, Gongda Lu, Eloise A. Marais, James R. Hopkins, Alastair C. Lewis, Qiang Zhang, James D. Lee, Freya A. Squires, Lisa K. Whalley, Eloise J. Slater, Dwayne E. Heard, Robert Woodward-Massey, Chunxiang Ye, and Joshua D. Vande Hey
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-379, https://doi.org/10.5194/acp-2022-379, 2022
Revised manuscript not accepted
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A dispersion model and a box model were combined to investigate the evolution of VOCs in Beijing once they are emitted from anthropogenic sources. It was determined that during the winter time the VOC concentrations in Beijing are driven predominantly by sources within Beijing and by a combination of transport and chemistry during the summer. Furthermore, the results in the paper highlight the need for a season specific policy.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nickolay Krotkov, Fei Liu, and Henk Eskes
Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, https://doi.org/10.5194/acp-22-4201-2022, 2022
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The COVID-19 lockdown had a large impact on anthropogenic emissions and particularly on nitrogen dioxide (NO2). A new method of isolation of background, urban, and industrial components in NO2 is applied to estimate the lockdown impact on each of them. From 16 March to 15 June 2020, urban NO2 declined by −18 % to −28 % in most regions of the world, while background NO2 typically declined by less than −10 %.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Yaqing Zhou, Nan Ma, Qiaoqiao Wang, Zhibin Wang, Chunrong Chen, Jiangchuan Tao, Juan Hong, Long Peng, Yao He, Linhong Xie, Shaowen Zhu, Yuxuan Zhang, Guo Li, Wanyun Xu, Peng Cheng, Uwe Kuhn, Guangsheng Zhou, Pingqing Fu, Qiang Zhang, Hang Su, and Yafang Cheng
Atmos. Chem. Phys., 22, 2029–2047, https://doi.org/10.5194/acp-22-2029-2022, https://doi.org/10.5194/acp-22-2029-2022, 2022
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This study characterizes size-resolved particle effective densities and their evolution associated with emissions and aging processes in a rural area of the North China Plain. Particle effective density exhibits a high-frequency bimodal distribution, and two density modes exhibit opposite trends with increasing particle size. SIA and BC mass fractions are key factors of particle effective density, and a value of 0.6 g cm−3 is appropriate to represent BC effective density in bulk particles.
Fei Liu, Zhining Tao, Steffen Beirle, Joanna Joiner, Yasuko Yoshida, Steven J. Smith, K. Emma Knowland, and Thomas Wagner
Atmos. Chem. Phys., 22, 1333–1349, https://doi.org/10.5194/acp-22-1333-2022, https://doi.org/10.5194/acp-22-1333-2022, 2022
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In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
Youwen Sun, Hao Yin, Xiao Lu, Justus Notholt, Mathias Palm, Cheng Liu, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 18589–18608, https://doi.org/10.5194/acp-21-18589-2021, https://doi.org/10.5194/acp-21-18589-2021, 2021
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This study uses high-resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method, and the exposure–response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements over the Sichuan Basin in 2020. These unexpected O3 enhancements were induced by meteorological anomalies and caused dramatically high health risks.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Yuqiang Zhang, Drew Shindell, Karl Seltzer, Lu Shen, Jean-Francois Lamarque, Qiang Zhang, Bo Zheng, Jia Xing, Zhe Jiang, and Lei Zhang
Atmos. Chem. Phys., 21, 16051–16065, https://doi.org/10.5194/acp-21-16051-2021, https://doi.org/10.5194/acp-21-16051-2021, 2021
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In this study, we use a global chemical transport model to simulate the effects on global air quality and human health due to emission changes in China from 2010 to 2017. By performing sensitivity analysis, we found that the air pollution control policies not only decrease the air pollutant concentration but also bring significant co-benefits in air quality to downwind regions. The benefits for the improved air pollution are dominated by PM2.5.
Gaëlle Dufour, Didier Hauglustaine, Yunjiang Zhang, Maxim Eremenko, Yann Cohen, Audrey Gaudel, Guillaume Siour, Mathieu Lachatre, Axel Bense, Bertrand Bessagnet, Juan Cuesta, Jerry Ziemke, Valérie Thouret, and Bo Zheng
Atmos. Chem. Phys., 21, 16001–16025, https://doi.org/10.5194/acp-21-16001-2021, https://doi.org/10.5194/acp-21-16001-2021, 2021
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The IASI observations and the LMDZ-OR-INCA model simulations show negative ozone trends in the Central East China region in the lower free (3–6 km column) and the upper free (6–9 km column) troposphere. Sensitivity studies from the model show that the Chinese anthropogenic emissions contribute to more than 50 % in the trend. The reduction in NOx emissions that has occurred since 2013 in China seems to lead to a decrease in ozone in the free troposphere, contrary to the increase at the surface.
Yuan Cheng, Qin-qin Yu, Jiu-meng Liu, Xu-bing Cao, Ying-jie Zhong, Zhen-yu Du, Lin-lin Liang, Guan-nan Geng, Wan-li Ma, Hong Qi, Qiang Zhang, and Ke-bin He
Atmos. Chem. Phys., 21, 15199–15211, https://doi.org/10.5194/acp-21-15199-2021, https://doi.org/10.5194/acp-21-15199-2021, 2021
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Open burning policies in Heilongjiang Province experienced a rapid transition during 2018 to 2020. This study evaluated the responses of PM2.5 pollution to this transition and suggested that neither of the policies could be considered successful. In addition, heterogeneous reactions were found to be at play in secondary aerosol formation, even in the frigid atmosphere in Heilongjiang. The unique haze in northeast China deserves more attention.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Youwen Sun, Hao Yin, Cheng Liu, Emmanuel Mahieu, Justus Notholt, Yao Té, Xiao Lu, Mathias Palm, Wei Wang, Changgong Shan, Qihou Hu, Min Qin, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 11759–11779, https://doi.org/10.5194/acp-21-11759-2021, https://doi.org/10.5194/acp-21-11759-2021, 2021
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The variability, sources, and transport of ethane (C2H6) over eastern China from 2015 to 2020 were studied using ground-based Fourier transform infrared (FTIR) spectroscopy and GEOS-Chem simulations. C2H6 variability is driven by both meteorological and emission factors. The reduction in C2H6 in recent years over eastern China points to air quality improvement in China.
Gongda Lu, Eloise A. Marais, Tuan V. Vu, Jingsha Xu, Zongbo Shi, James D. Lee, Qiang Zhang, Lu Shen, Gan Luo, and Fangqun Yu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-428, https://doi.org/10.5194/acp-2021-428, 2021
Revised manuscript not accepted
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Emission controls were imposed in Beijing-Tianjin-Hebei in northern China in autumn-winter 2017. We find that regional PM2.5 targets (15 % decrease relative to previous year) were exceeded. Our analysis shows that decline in precursor emissions only leads to less than half (43 %) the improved air quality. Most of the change (57 %) is due to interannual variability in meteorology. Stricter emission controls may be necessary in years with unfavourable meteorology.
Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
Atmos. Chem. Phys., 21, 11405–11421, https://doi.org/10.5194/acp-21-11405-2021, https://doi.org/10.5194/acp-21-11405-2021, 2021
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Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asian-Pacific Economic Cooperation (APEC) conference affect the mixing state and light absorption of BC and the associated implications for BC-PBL interactions.
Benjamin A. Nault, Duseong S. Jo, Brian C. McDonald, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Jason C. Schroder, James Allan, Donald R. Blake, Manjula R. Canagaratna, Hugh Coe, Matthew M. Coggon, Peter F. DeCarlo, Glenn S. Diskin, Rachel Dunmore, Frank Flocke, Alan Fried, Jessica B. Gilman, Georgios Gkatzelis, Jacqui F. Hamilton, Thomas F. Hanisco, Patrick L. Hayes, Daven K. Henze, Alma Hodzic, James Hopkins, Min Hu, L. Greggory Huey, B. Thomas Jobson, William C. Kuster, Alastair Lewis, Meng Li, Jin Liao, M. Omar Nawaz, Ilana B. Pollack, Jeffrey Peischl, Bernhard Rappenglück, Claire E. Reeves, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Min Shao, Jacob M. Sommers, James Walega, Carsten Warneke, Petter Weibring, Glenn M. Wolfe, Dominique E. Young, Bin Yuan, Qiang Zhang, Joost A. de Gouw, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 11201–11224, https://doi.org/10.5194/acp-21-11201-2021, https://doi.org/10.5194/acp-21-11201-2021, 2021
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Secondary organic aerosol (SOA) is an important aspect of poor air quality for urban regions around the world, where a large fraction of the population lives. However, there is still large uncertainty in predicting SOA in urban regions. Here, we used data from 11 urban campaigns and show that the variability in SOA production in these regions is predictable and is explained by key emissions. These results are used to estimate the premature mortality associated with SOA in urban regions.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
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Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Qingyang Xiao, Yixuan Zheng, Guannan Geng, Cuihong Chen, Xiaomeng Huang, Huizheng Che, Xiaoye Zhang, Kebin He, and Qiang Zhang
Atmos. Chem. Phys., 21, 9475–9496, https://doi.org/10.5194/acp-21-9475-2021, https://doi.org/10.5194/acp-21-9475-2021, 2021
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We used both statistical methods and a chemical transport model to assess the contribution of meteorology and emissions to PM2.5 during 2000–2018. Both methods revealed that emissions dominated the long-term PM2.5 trend with notable meteorological effects ranged up to 37.9 % of regional annual average PM2.5. The meteorological contribution became more beneficial to PM2.5 control in southern China but more unfavorable in northern China during the studied period.
Bo Zheng, Qiang Zhang, Guannan Geng, Cuihong Chen, Qinren Shi, Mengshi Cui, Yu Lei, and Kebin He
Earth Syst. Sci. Data, 13, 2895–2907, https://doi.org/10.5194/essd-13-2895-2021, https://doi.org/10.5194/essd-13-2895-2021, 2021
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Here we report the monthly anthropogenic pollutant emissions in China during the COVID-19 pandemic by using a bottom-up approach based on near-real-time data. The COVID lockdowns were estimated to have reduced China's emissions substantially between January and March in 2020, with the largest reduction in February. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to levels comparable to those of 2019 through December 2020.
Youwen Sun, Hao Yin, Yuan Cheng, Qianggong Zhang, Bo Zheng, Justus Notholt, Xiao Lu, Cheng Liu, Yuan Tian, and Jianguo Liu
Atmos. Chem. Phys., 21, 9201–9222, https://doi.org/10.5194/acp-21-9201-2021, https://doi.org/10.5194/acp-21-9201-2021, 2021
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We quantified the variability, source, and transport of urban CO over the Himalayas and Tibetan Plateau (HTP) by using measurement, model simulation, and the analysis of meteorological fields. Urban CO over the HTP is dominated by anthropogenic and biomass burning emissions from local, South Asia and East Asia, and oxidation sources. The decreasing trends in surface CO since 2015 in most cities over the HTP are attributed to the reduction in local and transported CO emissions in recent years.
Jingsha Xu, Di Liu, Xuefang Wu, Tuan V. Vu, Yanli Zhang, Pingqing Fu, Yele Sun, Weiqi Xu, Bo Zheng, Roy M. Harrison, and Zongbo Shi
Atmos. Chem. Phys., 21, 7321–7341, https://doi.org/10.5194/acp-21-7321-2021, https://doi.org/10.5194/acp-21-7321-2021, 2021
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Source apportionment of fine aerosols in an urban site of Beijing used a chemical mass balance (CMB) model. Seven primary sources (industrial/residential coal burning, biomass burning, gasoline/diesel vehicles, cooking and vegetative detritus) explained an average of 75.7 % and 56.1 % of fine OC in winter and summer, respectively. CMB was found to resolve more primary OA sources than AMS-PMF, but the latter apportioned more secondary OA sources.
Youwen Sun, Hao Yin, Cheng Liu, Lin Zhang, Yuan Cheng, Mathias Palm, Justus Notholt, Xiao Lu, Corinne Vigouroux, Bo Zheng, Wei Wang, Nicholas Jones, Changong Shan, Min Qin, Yuan Tian, Qihou Hu, Fanhao Meng, and Jianguo Liu
Atmos. Chem. Phys., 21, 6365–6387, https://doi.org/10.5194/acp-21-6365-2021, https://doi.org/10.5194/acp-21-6365-2021, 2021
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This study mapped the drivers of HCHO variability from 2015 to 2019 over eastern China. Hydroxyl (OH) radical production rates from HCHO photolysis were evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO abundance were analyzed. Contributions of various emission sources and geographical regions to the observed HCHO summertime enhancements were determined.
Jun Liu, Dan Tong, Yixuan Zheng, Jing Cheng, Xinying Qin, Qinren Shi, Liu Yan, Yu Lei, and Qiang Zhang
Atmos. Chem. Phys., 21, 1627–1647, https://doi.org/10.5194/acp-21-1627-2021, https://doi.org/10.5194/acp-21-1627-2021, 2021
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In this study, we investigated the decadal changes in carbon dioxide and air pollutant emissions in China's cement industry for the period 1990–2015 based on intensive unit-based information. We found that from 1990 to 2015, accompanied by a 10.3-fold increase in cement production, CO2, SO2, and NOx emissions from China's cement industry increased by 627 %, 56 %, and 659 %, whereas CO, PM2.5, and PM10 emissions decreased by 9 %, 63 %, and 59 %, respectively.
Diego Santaren, Grégoire Broquet, François-Marie Bréon, Frédéric Chevallier, Denis Siméoni, Bo Zheng, and Philippe Ciais
Atmos. Meas. Tech., 14, 403–433, https://doi.org/10.5194/amt-14-403-2021, https://doi.org/10.5194/amt-14-403-2021, 2021
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Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO2 to monitor anthropogenic emissions from regions, cities and large industrial plants. The analysis, applied to a large ensemble of sources in western Europe, shows a strong dependence of the results on different characteristics of the spaceborne instrument, on the source emission budgets and spreads, and on the wind conditions.
Erin E. McDuffie, Steven J. Smith, Patrick O'Rourke, Kushal Tibrewal, Chandra Venkataraman, Eloise A. Marais, Bo Zheng, Monica Crippa, Michael Brauer, and Randall V. Martin
Earth Syst. Sci. Data, 12, 3413–3442, https://doi.org/10.5194/essd-12-3413-2020, https://doi.org/10.5194/essd-12-3413-2020, 2020
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Global emission inventories are vital to understanding the impacts of air pollution on the environment, human health, and society. We update the open-source Community Emissions Data System (CEDS) to provide global gridded emissions of seven key air pollutants from 1970–2017 for 11 source sectors and multiple fuel types, including coal, solid biofuel, and liquid oil and natural gas. This dataset includes both monthly global gridded emissions and annual national totals.
Yarong Peng, Hongli Wang, Qian Wang, Shengao Jing, Jingyu An, Yaqin Gao, Cheng Huang, Rusha Yan, Haixia Dai, Tiantao Cheng, Qiang Zhang, Meng Li, Li Li, Shengrong Lou, Shikang Tao, Qinyao Hu, Jun Lu, and Changhong Chen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1108, https://doi.org/10.5194/acp-2020-1108, 2020
Revised manuscript not accepted
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The evolution of NMHCs emissions and the effectiveness of control measures were investigated based on long term measurements in a megacity of China. Discrepancies between measurements and emission inventories emphasized the need for emission validation both in speciation and sources. Varied trends of NMHCs speciation and sources suggested the differential effect of the past control measures, which provided new insights into future clean air policies in polluted region including China.
W. Joe F. Acton, Zhonghui Huang, Brian Davison, Will S. Drysdale, Pingqing Fu, Michael Hollaway, Ben Langford, James Lee, Yanhui Liu, Stefan Metzger, Neil Mullinger, Eiko Nemitz, Claire E. Reeves, Freya A. Squires, Adam R. Vaughan, Xinming Wang, Zhaoyi Wang, Oliver Wild, Qiang Zhang, Yanli Zhang, and C. Nicholas Hewitt
Atmos. Chem. Phys., 20, 15101–15125, https://doi.org/10.5194/acp-20-15101-2020, https://doi.org/10.5194/acp-20-15101-2020, 2020
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Air quality in Beijing is of concern to both policy makers and the general public. In order to address concerns about air quality it is vital that the sources of atmospheric pollutants are understood. This work presents the first top-down measurement of volatile organic compound (VOC) emissions in Beijing. These measurements are used to evaluate the emissions inventory and assess the impact of VOC emission from the city centre on atmospheric chemistry.
Yilong Wang, Grégoire Broquet, François-Marie Bréon, Franck Lespinas, Michael Buchwitz, Maximilian Reuter, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, and Philippe Ciais
Geosci. Model Dev., 13, 5813–5831, https://doi.org/10.5194/gmd-13-5813-2020, https://doi.org/10.5194/gmd-13-5813-2020, 2020
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Antoine Berchet, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, Makoto Deushi, Patrick Jöckel, Douglas Kinnison, Ole Kirner, Sarah Strode, Simone Tilmes, Edward J. Dlugokencky, and Bo Zheng
Atmos. Chem. Phys., 20, 13011–13022, https://doi.org/10.5194/acp-20-13011-2020, https://doi.org/10.5194/acp-20-13011-2020, 2020
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Decadal trends and variations in OH are critical for understanding atmospheric CH4 evolution. We quantify the impacts of OH trends and variations on the CH4 budget by conducting CH4 inversions on a decadal scale with an ensemble of OH fields. We find the negative OH anomalies due to enhanced fires can reduce the optimized CH4 emissions by up to 10 Tg yr−1 during El Niño years and the positive OH trend from 1986 to 2010 results in a ∼ 23 Tg yr−1 additional increase in optimized CH4 emissions.
Ruqian Miao, Qi Chen, Yan Zheng, Xi Cheng, Yele Sun, Paul I. Palmer, Manish Shrivastava, Jianping Guo, Qiang Zhang, Yuhan Liu, Zhaofeng Tan, Xuefei Ma, Shiyi Chen, Limin Zeng, Keding Lu, and Yuanhang Zhang
Atmos. Chem. Phys., 20, 12265–12284, https://doi.org/10.5194/acp-20-12265-2020, https://doi.org/10.5194/acp-20-12265-2020, 2020
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In this study we evaluated the model performances for simulating secondary inorganic aerosol (SIA) and organic aerosol (OA) in PM2.5 in China against comprehensive datasets. The potential biases from factors related to meteorology, emission, chemistry, and atmospheric removal are systematically investigated. This study provides a comprehensive understanding of modeling PM2.5, which is important for studies on the effectiveness of emission control strategies.
Wei Tao, Hang Su, Guangjie Zheng, Jiandong Wang, Chao Wei, Lixia Liu, Nan Ma, Meng Li, Qiang Zhang, Ulrich Pöschl, and Yafang Cheng
Atmos. Chem. Phys., 20, 11729–11746, https://doi.org/10.5194/acp-20-11729-2020, https://doi.org/10.5194/acp-20-11729-2020, 2020
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We simulated the thermodynamic and multiphase reactions in aerosol water during a wintertime haze event over the North China Plain. It was found that aerosol pH exhibited a strong spatiotemporal variability, and multiple oxidation pathways were predominant for particulate sulfate formation in different locations. Sensitivity tests further showed that ammonia, crustal particles, and dissolved transition metal ions were important factors for multiphase chemistry during haze episodes.
Pengfei Han, Ning Zeng, Tom Oda, Xiaohui Lin, Monica Crippa, Dabo Guan, Greet Janssens-Maenhout, Xiaolin Ma, Zhu Liu, Yuli Shan, Shu Tao, Haikun Wang, Rong Wang, Lin Wu, Xiao Yun, Qiang Zhang, Fang Zhao, and Bo Zheng
Atmos. Chem. Phys., 20, 11371–11385, https://doi.org/10.5194/acp-20-11371-2020, https://doi.org/10.5194/acp-20-11371-2020, 2020
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An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for quantification of carbon budget and emissions reductions towards the Paris Agreement goals. Here we assessed 9 global and regional inventories. Our findings highlight the significance of using locally measured coal emission factors. We call on the enhancement of physical measurements for validation and provide comprehensive information for inventory, monitoring, modeling, assimilation, and reducing emissions.
Amir H. Souri, Caroline R. Nowlan, Gonzalo González Abad, Lei Zhu, Donald R. Blake, Alan Fried, Andrew J. Weinheimer, Armin Wisthaler, Jung-Hun Woo, Qiang Zhang, Christopher E. Chan Miller, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 20, 9837–9854, https://doi.org/10.5194/acp-20-9837-2020, https://doi.org/10.5194/acp-20-9837-2020, 2020
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For the first time, we provide a joint nonlinear optimal estimate of NOx and NMVOC emissions during the KORUS-AQ campaign by simultaneously incorporating SAO's new product of HCHO columns from OMPS and OMI tropospheric NO2 columns into a regional model. Results demonstrate a promising improvement in the performance of the model in terms of HCHO and NO2 concentrations, which in turn enables us to quantify the impact of the emission changes on different pathways of ozone formation and loss.
Cited articles
Alcamo, J. and Kreileman, E.: Emission scenarios and global climate
protection, Global Environ. Chang., 6, 305–334,
https://doi.org/10.1016/S0959-3780(96)00030-1, 1996.
Amann, M., Klimont, Z. and Wagner, F.: Regional and Global Emissions of Air
Pollutants: Recent Trends and Future Scenarios, Annu. Rev. Env. Resour., 38,
31–55, https://doi.org/10.1146/annurev-environ-052912-173303, 2013.
Belete, G. F., Voinov, A., Arto, I., Dhavala, K., Bulavskaya, T., Niamir,
L., Moghayer, S., and Filatova, T.: Exploring Low-Carbon Futures: A Web
Service Approach to Linking Diverse Climate-Energy-Economy Models, Energies,
12, 2880, https://doi.org/10.3390/en12152880, 2019.
Belaissaoui, B., Le Moullec, Y., and Favre, E.: Energy efficiency of a hybrid
membrane/condensation process for VOC (Volatile Organic Compounds) recovery
from air: A generic approach, Energy, 95, 291–302,
https://doi.org/10.1016/j.energy.2015.12.006, 2016.
Braspenning Radu, O., van den Berg, M., Klimont, Z., Deetman, S.,
Janssens-Maenhout, G., Muntean, M., Heyes, C., Dentener, F., and van Vuuren,
D. P.: Exploring synergies between climate and air quality policies using
long-term global and regional emission scenarios, Atmos. Environ., 140,
577–591, https://doi.org/10.1016/j.atmosenv.2016.05.021, 2016.
Cao, Z., Shen, L., Liu, L., and Zhong, S.: Analysis on major drivers of
cement consumption during the urbanization process in China, J. Clean.
Prod., 133, 304–313, https://doi.org/10.1016/j.jclepro.2016.05.130, 2016.
Calvin, K., Bond-Lamberty, B., Clarke, L., Edmonds, J., Eom, J., Hartin, C.,
Kim, S., Kyle, P., Link, R., Moss, R., McJeon, H., Patel, P., Smith, S.,
Waldhoff, S., and Wise, M.: The SSP4: A world of deepening inequality, Global
Environ. Chang., 42, 284–296, https://doi.org/10.1016/j.gloenvcha.2016.06.010, 2017.
Calvin, K., Bond-Lamberty, B., Jones, A., Shi, X., Di Vittorio, A., and
Thornton, P.: Characteristics of human-climate feedbacks differ at different
radiative forcing levels, Glob. Planet. Change, 180, 126–135,
https://doi.org/10.1016/j.gloplacha.2019.06.003, 2019.
Cheng, J., Su, J., Cui, T., Li, X., Dong, X., Sun, F., Yang, Y., Tong, D., Zheng, Y., Li, Y., Li, J., Zhang, Q., and He, K.: Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis, Atmos. Chem. Phys., 19, 6125–6146, https://doi.org/10.5194/acp-19-6125-2019, 2019.
China State Council: Action Plan on Prevention and Control of Air Pollution,
China State Council, Beijing, China, available at:
http://www.gov.cn/zwgk/2013-09/12/content_2486773.htm (last
access: 10 August 2018), 2013.
China State Council: Three-Year Action Plan for Winning the Blue Sky Defense
Battle, China State Council, Beijing, China, available at:
http://www.gov.cn/zhengce/content/2018-07/03/content_5303158.htm (last access: 10 September 2019), 2018.
Clarke, L., Kyle, P.,
Wise, M., Calvin, K., Edmonds, J., Kim, S., Placet, M., and Smith, S.:
CO2 emissions mitigation and technological advance: an updated analysis of advanced technology scenarios, PNNL Report Pacific Northwest National Laboratory, Richmond, 2008.
Clarke, L., Eom, J., Marten, E. H., Horowitz, R., Kyle, P., Link, R.,
Mignone, B. K., Mundra, A., and Zhou, Y.: Effects of long-term climate change
on global building energy expenditures, Energy Econ., 72, 667–677,
https://doi.org/10.1016/j.eneco.2018.01.003, 2018.
Cofala, J., Amann, M., Klimont, Z., Kupiainen, K., and Höglund-Isaksson,
L.: Scenarios of global anthropogenic emissions of air pollutants and
methane until 2030, Atmos. Environ., 41, 8486–8499,
https://doi.org/10.1016/j.atmosenv.2007.07.010, 2007.
Collins, W. D., Craig, A. P., Truesdale, J. E., Di Vittorio, A. V., Jones, A. D., Bond-Lamberty, B., Calvin, K. V., Edmonds, J. A., Kim, S. H., Thomson, A. M., Patel, P., Zhou, Y., Mao, J., Shi, X., Thornton, P. E., Chini, L. P., and Hurtt, G. C.: The integrated Earth system model version 1: formulation and functionality, Geosci. Model Dev., 8, 2203–2219, https://doi.org/10.5194/gmd-8-2203-2015, 2015.
Dong, N., You, L., Cai, W., Li, G., and Lin, H.: Land use projections in
China under global socioeconomic and emission scenarios: Utilizing a
scenario-based land-use change assessment framework, Global Environ. Chang.,
50, 164–177, https://doi.org/10.1016/j.gloenvcha.2018.04.001, 2018.
Edmonds, J. and Reilly, J.: Global energy and CO2 to the year 2050,
IEA/ORAU Working Paper Contribution No. 82-6, 1982.
Edmonds, J. and Reilly, J.: Global Energy and CO2 to the Year 2050, The Energy Journal, 4, 21–47, 1983.
Edmonds, J., Reilly, J., Trabalka, J. R., and Reichle, D. E.: An Analysis of
Possible Future Atmospheric Retention of Fossil Fuel CO2, TR013,
DOE/OR/21400-1, National Technical Information Service, U.S. Department of
Commerce, Springfield Virginia 22161, 1984.
European Commission, Joint Research Centre: Common Waste Water and Waste Gas
Treatment/Management Systems in the Chemical Sector, available at:
https://eippcb.jrc.ec.europa.eu/reference/cww.html (last
access: 11 October 2019), 2016.
Fawcett, A. A., Iyer, G. C., Clarke, L. E., Edmonds, J. A., Hultman, N. E.,
McJeon, H. C., Rogelj, J., Schuler, R., Alsalam, J., Asrar, G. R., Creason,
J., Jeong, M., McFarland, J., Mundra, A., and Shi, W.: Can Paris pledges
avert severe climate change?, Science, 350, 1168–1169,
https://doi.org/10.1126/science.aad5761, 2015.
Geng, G., Zhang, Q., Tong, D., Li, M., Zheng, Y., Wang, S., and He, K.: Chemical composition of ambient PM2.5 over China and relationship to precursor emissions during 2005–2012, Atmos. Chem. Phys., 17, 9187–9203, https://doi.org/10.5194/acp-17-9187-2017, 2017.
Geng, G., Xiao, Q., Zheng, Y., Tong, D., Zhang, Y., Zhang, X., Zhang, Q.,
He, K., and Liu, Y.: Impact of China's Air Pollution Prevention and Control
Action Plan on PM2.5 chemical composition over eastern China, Sci. China
Earth Sci., 62, 1872–1884, https://doi.org/10.1007/s11430-018-9353-x, 2019.
Gidden, M. J., Riahi, K., Smith, S. J., Fujimori, S., Luderer, G., Kriegler, E., van Vuuren, D. P., van den Berg, M., Feng, L., Klein, D., Calvin, K., Doelman, J. C., Frank, S., Fricko, O., Harmsen, M., Hasegawa, T., Havlik, P., Hilaire, J., Hoesly, R., Horing, J., Popp, A., Stehfest, E., and Takahashi, K.: Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century, Geosci. Model Dev., 12, 1443–1475, https://doi.org/10.5194/gmd-12-1443-2019, 2019.
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Hong, C., Zhang, Q., He, K., Guan, D., Li, M., Liu, F., and Zheng, B.: Variations of China's emission estimates: response to uncertainties in energy statistics, Atmos. Chem. Phys., 17, 1227–1239, https://doi.org/10.5194/acp-17-1227-2017, 2017.
Huo, H., Lei, Y., Zhang, Q., Zhao, L., and He, K.: China's coke industry:
Recent policies, technology shift, and implication for energy and the
environment, Energy Policy, 51, 397–404, https://doi.org/10.1016/j.enpol.2012.08.041,
2012.
Huo, H., Zheng, B., Wang, M., Zhang, Q., and He, K.-B.: Vehicular air
pollutant emissions in China: evaluation of past control policies and future
perspectives, Mitig. Adapt. Strateg. Glob. Change., 20, 719–733,
https://doi.org/10.1007/s11027-014-9613-0, 2015.
International Energy Agency (IEA): Energy balances & global energy
statistics, 2011.
Jiang, K., He, C., Dai, H., Liu, J., and Xu, X.: Emission scenario analysis
for China under the global 1.5 ∘C target, Carbon Manag., 9,
481–491, https://doi.org/10.1080/17583004.2018.1477835, 2018.
Ju, X.-T., Xing, G.-X., Chen, X.-P., Zhang, S.-L., Zhang, L.-J., Liu, X.-J.,
Cui, Z.-L., Yin, B., Christie, P., Zhu, Z.-L., and Zhang, F.-S.: Reducing
environmental risk by improving N management in intensive Chinese
agricultural systems, P. Natl. Acad. Sci. USA, 106, 3041–3046,
https://doi.org/10.1073/pnas.0813417106, 2009.
Kang, Y., Liu, M., Song, Y., Huang, X., Yao, H., Cai, X., Zhang, H., Kang, L., Liu, X., Yan, X., He, H., Zhang, Q., Shao, M., and Zhu, T.: High-resolution ammonia emissions inventories in China from 1980 to 2012, Atmos. Chem. Phys., 16, 2043–2058, https://doi.org/10.5194/acp-16-2043-2016, 2016.
Klimont, Z., Streets, D. G., Gupta, S., Cofala, J., Lixin, F., and Ichikawa,
Y.: Anthropogenic emissions of non-methane volatile organic compounds in
China, Atmos. Environ., 36, 1309–1322,
https://doi.org/10.1016/S1352-2310(01)00529-5, 2002.
Kramer, G. J. and Haigh, M.: No quick switch to low-carbon energy, Nature,
462, 568–569, https://doi.org/10.1038/462568a, 2009.
Lasseter, R. H. and Piagi, P.: Microgrid: a conceptual solution, in: PESC,
Aachen, Germany, 20–25, 2004.
Lei, Y., Zhang, Q., He, K. B., and Streets, D. G.: Primary anthropogenic aerosol emission trends for China, 1990–2005, Atmos. Chem. Phys., 11, 931–954, https://doi.org/10.5194/acp-11-931-2011, 2011a.
Lei, Y., Zhang, Q., Nielsen, C., and He, K.: An inventory of primary air
pollutants and CO2 emissions from cement production in China,
1990–2020, Atmos. Environ., 45, 147–154, 2011b.
Li, M., Zhang, Q., Streets, D. G., He, K. B., Cheng, Y. F., Emmons, L. K., Huo, H., Kang, S. C., Lu, Z., Shao, M., Su, H., Yu, X., and Zhang, Y.: Mapping Asian anthropogenic emissions of non-methane volatile organic compounds to multiple chemical mechanisms, Atmos. Chem. Phys., 14, 5617–5638, https://doi.org/10.5194/acp-14-5617-2014, 2014.
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., Zhang, Q., Zheng, B., Tong, D., Lei, Y., Liu, F., Hong, C., Kang, S., Yan, L., Zhang, Y., Bo, Y., Su, H., Cheng, Y., and He, K.: Persistent growth of anthropogenic non-methane volatile organic compound (NMVOC) emissions in China during 1990–2017: drivers, speciation and ozone formation potential, Atmos. Chem. Phys., 19, 8897–8913, https://doi.org/10.5194/acp-19-8897-2019, 2019.
Li, N., Chen, W., Rafaj, P., Kiesewetter, G., Schöpp, W., Wang, H.,
Zhang, H., Krey, V., and Riahi, K.: Air Quality Improvement Co-benefits of
Low-Carbon Pathways toward Well Below the 2 ∘C Climate Target in
China, Environ. Sci. Technol., 53, 5576–5584, https://doi.org/10.1021/acs.est.8b06948,
2019.
Liang, X., Zhang, S., Wu, Y., Xing, J., He, X., Zhang, K. M., Wang, S., and
Hao, J.: Air quality and health benefits from fleet electrification in
China, Nat. Sustain., 2, 962–971, https://doi.org/10.1038/s41893-019-0398-8, 2019.
Liu, F., Zhang, Q., Tong, D., Zheng, B., Li, M., Huo, H., and He, K. B.: High-resolution inventory of technologies, activities, and emissions of coal-fired power plants in China from 1990 to 2010, Atmos. Chem. Phys., 15, 13299–13317, https://doi.org/10.5194/acp-15-13299-2015, 2015.
Liu, J., Zheng, Y., Geng, G., Hong, C., Li, M., Li, X., Liu, F., Tong, D., Wu, R., Zheng, B., He, K., and Zhang, Q.: Decadal changes in anthropogenic source contribution of PM2.5 pollution and related health impacts in China, 1990–2015, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-895, in review, 2019.
Lu, Z., Zhang, Q., and Streets, D. G.: Sulfur dioxide and primary carbonaceous aerosol emissions in China and India, 1996–2010, Atmos. Chem. Phys., 11, 9839–9864, https://doi.org/10.5194/acp-11-9839-2011, 2011.
Miketa, A. and Schrattenholzer, L.: Equity implications of two
burden-sharing rules for stabilizing greenhouse-gas concentrations, Energ.
Policy, 34, 877–891, https://doi.org/10.1016/j.enpol.2004.08.050, 2006.
Ministry of Ecology and Environment, the People's Republic of China: 2013
Report on the State of the Ecology and Environment in China, Beijing, China,
available at:
http://english.mee.gov.cn/Resources/Reports/soe/soe2011/201606/P020160601591756378883.pdf
(last access: 10 September 2019), 2014.
Ministry of Ecology and Environment, the People's Republic of China: 2017
Report on the State of the Ecology and Environment in China, Beijing, China,
available at:
http://english.mee.gov.cn/Resources/Reports/soe/SOEE2017/201808/P020180801597738742758.pdf
(last access: 10 September 2019), 2018.
National Bureau of Statistics (NBS): China Energy Statistical Yearbook (2006
editions), China Statistics Press, Beijing, China, 2006.
National Bureau of Statistics (NBS): China Energy Statistical Yearbook (2007
editions), China Statistics Press, Beijing, China, 2007.
National Bureau of Statistics (NBS): China Energy Statistical Yearbook (2016
editions), China Statistics Press, Beijing, China, 2016.
National Development and Reform Commission: 13th FYP development plan for
renewable energy, available at:
http://www.ndrc.gov.cn/zcfb/zcfbghwb/201612/W020161216661816762488.pdf
(access at: 26 May 2019), 2016 (in Chinese).
O'Neill, B. C., Dalton, M., Fuchs, R., Jiang, L., Pachauri, S., and Zigova,
K.: Global demographic trends and future carbon emissions, P. Natl. Acad.
Sci. USA, 107, 17521–17526, https://doi.org/10.1073/pnas.1004581107, 2010.
O'Neill, B. C., Kriegler, E., Riahi, K., Ebi, K. L., Hallegatte, S., Carter,
T. R., Mathur, R., and van Vuuren, D. P.: A new scenario framework for
climate change research: the concept of shared socioeconomic pathways,
Clim. Change, 122, 387–400, https://doi.org/10.1007/s10584-013-0905-2, 2014.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.
Pachauri, R. K., Allen, M. R., Barros, V. R., Broome, J., Cramer, W., Christ,
R., Church, J. A., Clarke, L., Dahe, Q., Dasgupta, P., and Dubash, N. K.:
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, IPCC, p. 151, 2014.
Pan, B., Lam, S. K., Mosier, A., Luo, Y., and Chen, D.: Ammonia
volatilization from synthetic fertilizers and its mitigation strategies: A
global synthesis, Agr. Ecosyst. Environ., 232, 283–289,
https://doi.org/10.1016/j.agee.2016.08.019, 2016.
Peng, L., Zhang, Q., Yao, Z., Mauzerall, D. L., Kang, S., Du, Z., Zheng, Y.,
Xue, T., and He, K.: Underreported coal in statistics: A survey-based solid
fuel consumption and emission inventory for the rural residential sector in
China, Appl. Energy, 235, 1169–1182, https://doi.org/10.1016/j.apenergy.2018.11.043,
2019.
Rao, S., Klimont, Z., Smith, S. J., Van Dingenen, R., Dentener, F., Bouwman,
L., Riahi, K., Amann, M., Bodirsky, B. L., van Vuuren, D. P., Aleluia Reis,
L., Calvin, K., Drouet, L., Fricko, O., Fujimori, S., Gernaat, D., Havlik,
P., Harmsen, M., Hasegawa, T., Heyes, C., Hilaire, J., Luderer, G., Masui,
T., Stehfest, E., Strefler, J., van der Sluis, S., and Tavoni, M.: Future air
pollution in the Shared Socio-economic Pathways, Global Environ. Chang., 42,
346–358, https://doi.org/10.1016/j.gloenvcha.2016.05.012, 2017.
Ray, D. K., Mueller, N. D., West, P. C., and Foley, J. A.: Yield Trends Are
Insufficient to Double Global Crop Production by 2050, PLOS ONE, 8,
e66428, https://doi.org/10.1371/journal.pone.0066428, 2013.
Reilly, J. M., Edmonds, J. A., Gardner, R. H., and Brenkert, A. L.: Uncertainty Analysis of the IEA/ORAU CO2 Emissions Model, The Energy Journal, 8, 1–29, 1987.
Rezaie, B. and Rosen, M. A.: District heating and cooling: Review of
technology and potential enhancements, Appl. Energy, 93, 2–10,
https://doi.org/10.1016/j.apenergy.2011.04.020, 2012.
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O'Neill, B. C.,
Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W.,
Popp, A., Cuaresma, J. C., Kc, S., Leimbach, M., Jiang, L., Kram, T., Rao,
S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da
Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D.,
Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G.,
Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M.,
Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A.,
and Tavoni, M.: The Shared Socioeconomic Pathways and their energy, land
use, and greenhouse gas emissions implications: An overview, Global Environ.
Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009, 2017.
Shi, J., Chen, W., and Yin, X.: Modelling building's decarbonization with
application of China TIMES model, Appl. Energy, 162, 1303–1312,
https://doi.org/10.1016/j.apenergy.2015.06.056, 2016.
Shen, G., Ru, M., Du, W., Zhu, X., Zhong, Q., Chen, Y., Shen, H., Yun, X.,
Meng, W., Liu, J., Cheng, H., Hu, J., Guan, D., and Tao, S.: Impacts of air
pollutants from rural Chinese households under the rapid residential energy
transition, Nat. Commun., 10, 3405, https://doi.org/10.1038/s41467-019-11453-w, 2019.
Silva Herran, D., Tachiiri, K., and Matsumoto, K.: Global energy system
transformations in mitigation scenarios considering climate uncertainties,
Appl. Energy, 243, 119–131, https://doi.org/10.1016/j.apenergy.2019.03.069, 2019.
Sinha, E., Michalak, A. M., Calvin, K. V., and Lawrence, P. J.: Societal
decisions about climate mitigation will have dramatic impacts on
eutrophication in the 21st century, Nat. Commun., 10, 939,
https://doi.org/10.1038/s41467-019-08884-w, 2019.
Tian, H., Liu, K., Hao, J., Wang, Y., Gao, J., Qiu, P., and Zhu, C.: Nitrogen
Oxides Emissions from Thermal Power Plants in China: Current Status and
Future Predictions, Environ. Sci. Technol., 47, 11350–11357,
https://doi.org/10.1021/es402202d, 2013.
Tong, D., Zhang, Q., Liu, F., Geng, G., Zheng, Y., Xue, T., Hong, C., Wu,
R., Qin, Y., Zhao, H., Yan, L., and He, K.: Current Emissions and Future
Mitigation Pathways of Coal-Fired Power Plants in China from 2010 to 2030,
Environ. Sci. Technol., 52, 12905–12914, https://doi.org/10.1021/acs.est.8b02919,
2018a.
Tong, D., Zhang, Q., Davis, S. J., Liu, F., Zheng, B., Geng, G., Xue, T.,
Li, M., Hong, C., Lu, Z., Streets, D. G., Guan, D., and He, K.: Targeted
emission reductions from global super-polluting power plant units, Nat.
Sustain., 1, 59–68, https://doi.org/10.1038/s41893-017-0003-y, 2018b.
Tong, D., Zhang, Q., Zheng, Y., Caldeira, K., Shearer, C., Hong, C., Qin, Y.,
and Davis, S. J.: Committed emissions from existing energy infrastructure
jeopardize 1.5 ∘C climate target, Nature, 572, 373–377,
https://doi.org/10.1038/s41586-019-1364-3, 2019.
The Ministry of Public Security of the People's Republic of China: China's
private cars exceed 200 million for first time, available at:
https://www.mps.gov.cn/n2254314/n6409334/c6852472/content.html, last access: 4 March 2020 (in Chinese).
Turner, P. A., Field, C. B., Lobell, D. B., Sanchez, D. L., and Mach, K. J.:
Unprecedented rates of land-use transformation in modelled climate change
mitigation pathways, Nat. Sustain., 1, 240–245,
https://doi.org/10.1038/s41893-018-0063-7, 2018.
United Nations Framework Convention on Climate Change: China's Nationally
Determined Contribution, available at:
https://www4.unfccc.int/sites/ndcstaging/PublishedDocuments/China First/China's First NDC Submission.pdf
(last access: 9 May 2019), 2015.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A.,
Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T.,
Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The
representative concentration pathways: an overview, Clim. Change, 109, 5,
https://doi.org/10.1007/s10584-011-0148-z, 2011.
Vittorio, A. V. D., Mao, J., Shi, X., Chini, L., Hurtt, G., and Collins, W.
D.: Quantifying the Effects of Historical Land Cover Conversion Uncertainty
on Global Carbon and Climate Estimates, Geophys. Res. Lett., 45,
974–982, https://doi.org/10.1002/2017GL075124, 2018.
Wang, H. and Chen, W.: Modelling deep decarbonization of industrial energy
consumption under 2-degree target: Comparing China, India and Western
Europe, Appl. Energy, 238, 1563–1572, https://doi.org/10.1016/j.apenergy.2019.01.131,
2019.
Wang, K., Tian, H., Hua, S., Zhu, C., Gao, J., Xue, Y., Hao, J., Wang, Y.,
and Zhou, J.: A comprehensive emission inventory of multiple air pollutants
from iron and steel industry in China: Temporal trends and spatial variation
characteristics, Sci. Total Environ., 559, 7–14,
https://doi.org/10.1016/j.scitotenv.2016.03.125, 2016.
Wang, S. X., Zhao, B., Cai, S. Y., Klimont, Z., Nielsen, C. P., Morikawa, T., Woo, J. H., Kim, Y., Fu, X., Xu, J. Y., Hao, J. M., and He, K. B.: Emission trends and mitigation options for air pollutants in East Asia, Atmos. Chem. Phys., 14, 6571–6603, https://doi.org/10.5194/acp-14-6571-2014, 2014.
Wei, W., Wang, S., Hao, J., and Cheng, S.: Projection of anthropogenic
volatile organic compounds (VOCs) emissions in China for the period
2010–2020, Atmos. Environ., 45, 6863–6871,
https://doi.org/10.1016/j.atmosenv.2011.01.013, 2011.
World Health Organization: WHO Air Quality Guidelines for Particulate
Matter, Ozone, Nitrogen Dioxide and Sulfur Dioxide, Global Update 2005:
Summary of Risk Assessment. Geneva, WHO, available:
http://whqlibdoc.who.int/hq/2006/WHO_SDE_PHE_OEH_06.02_eng.pdf (last
access: 11 October 2019), 2006.
Xing, J., Wang, S. X., Chatani, S., Zhang, C. Y., Wei, W., Hao, J. M., Klimont, Z., Cofala, J., and Amann, M.: Projections of air pollutant emissions and its impacts on regional air quality in China in 2020, Atmos. Chem. Phys., 11, 3119–3136, https://doi.org/10.5194/acp-11-3119-2011, 2011.
Xu, P., Koloutsou-Vakakis, S., Rood, M. J., and Luan, S.: Projections of
NH3 emissions from manure generated by livestock production in China to 2030 under six mitigation scenarios, Sci. Total. Environ., 607–608, 78–86, https://doi.org/10.1016/j.scitotenv.2017.06.258, 2017.
Xue, T., Zheng, Y., Tong, D., Zheng, B., Li, X., Zhu, T., and Zhang, Q.:
Spatiotemporal continuous estimates of PM2.5 concentrations in China,
2000–2016: A machine learning method with inputs from satellites, chemical
transport model, and ground observations, Environ. Int., 123, 345–357,
https://doi.org/10.1016/j.envint.2018.11.075, 2019a.
Xue, T., Liu, J., Zhang, Q., Geng, G., Zheng, Y., Tong, D., Liu, Z., Guan,
D., Bo, Y., Zhu, T., He, K., and Hao, J.: Rapid improvement of PM2.5
pollution and associated health benefits in China during 2013–2017, Sci.
China Earth Sci., 62, 1847–1856, https://doi.org/10.1007/s11430-018-9348-2, 2019b.
Yu, S., Horing, J., Liu, Q., Dahowski, R., Davidson, C., Edmonds, J., Liu,
B., Mcjeon, H., McLeod, J., Patel, P., and Clarke, L.: CCUS in China's
mitigation strategy: insights from integrated assessment modeling, Int. J.
Greenh. Gas Con., 84, 204–218, https://doi.org/10.1016/j.ijggc.2019.03.004, 2019.
Zhang, J. and Smith, K. R.: Household Air Pollution from Coal and Biomass
Fuels in China: Measurements, Health Impacts, and Interventions, Environ.
Health Perspect., 115, 848–855, https://doi.org/10.1289/ehp.9479, 2007.
Zhang, J., Xiao, J., Chen, X., Liang, X., Fan, L., and Ye, D.: Allowance and
allocation of industrial volatile organic compounds emission in China for
year 2020 and 2030, J. Environ. Sci., 69, 155–165,
https://doi.org/10.1016/j.jes.2017.10.003, 2018.
Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H., Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., Chen, D., Duan, L., Lei, Y., Wang, L. T., and Yao, Z. L.: Asian emissions in 2006 for the NASA INTEX-B mission, Atmos. Chem. Phys., 9, 5131–5153, https://doi.org/10.5194/acp-9-5131-2009, 2009.
Zhang, Q., Zheng, Y., Tong, D., Shao, M., Wang, S., Zhang, Y., Xu, X., Wang,
J., He, H., Liu, W., Ding, Y., Lei, Y., Li, J., Wang, Z., Zhang, X., Wang,
Y., Cheng, J., Liu, Y., Shi, Q., Yan, L., Geng, G., Hong, C., Li, M., Liu,
F., Zheng, B., Cao, J., Ding, A., Gao, J., Fu, Q., Huo, J., Liu, B., Liu,
Z., Yang, F., He, K., and Hao, J.: Drivers of improved PM2.5 air quality in China from 2013 to 2017, P. Natl. Acad. Sci. USA, 116, 24463–24469,
https://doi.org/10.1073/pnas.1907956116, 2019a.
Zhang, S., Yi, B.-W., Worrell, E., Wagner, F., Crijns-Graus, W., Purohit,
P., Wada, Y. and Varis, O.: Integrated assessment of
resource-energy-environment nexus in China's iron and steel industry, J.
Clean. Prod., 232, 235–249, https://doi.org/10.1016/j.jclepro.2019.05.392, 2019b.
Zhao, B., Wang, S. X., Liu, H., Xu, J. Y., Fu, K., Klimont, Z., Hao, J. M., He, K. B., Cofala, J., and Amann, M.: NOx emissions in China: historical trends and future perspectives, Atmos. Chem. Phys., 13, 9869–9897, https://doi.org/10.5194/acp-13-9869-2013, 2013.
Zhao, Y., Nielsen, C. P., Lei, Y., McElroy, M. B., and Hao, J.: Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China, Atmos. Chem. Phys., 11, 2295–2308, https://doi.org/10.5194/acp-11-2295-2011, 2011.
Zheng, B., Huo, H., Zhang, Q., Yao, Z. L., Wang, X. T., Yang, X. F., Liu, H., and He, K. B.: High-resolution mapping of vehicle emissions in China in 2008, Atmos. Chem. Phys., 14, 9787–9805, https://doi.org/10.5194/acp-14-9787-2014, 2014.
Zheng, B., Zhang, Q., Borken-Kleefeld, J., Huo, H., Guan, D., Klimont, Z.,
Peters, G. P., and He, K.: How will greenhouse gas emissions from motor
vehicles be constrained in China around 2030?, Appl. Energy, 156, 230–240,
https://doi.org/10.1016/j.apenergy.2015.07.018, 2015.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zheng, H., Zhao, B., Wang, S., Wang, T., Ding, D., Chang, X., Liu, K., Xing,
J., Dong, Z., Aunan, K., Liu, T., Wu, X., Zhang, S., and Wu, Y.: Transition
in source contributions of PM2.5 exposure and associated premature mortality
in China during 2005–2015, Environ. Int., 132, 105111,
https://doi.org/10.1016/j.envint.2019.105111, 2019.
Zhou, S., Kyle, G. P., Yu, S., Clarke, L. E., Eom, J., Luckow, P.,
Chaturvedi, V., Zhang, X., and Edmonds, J. A.: Energy use and CO2 emissions
of China's industrial sector from a global perspective, Energ. Policy, 58,
284–294, https://doi.org/10.1016/j.enpol.2013.03.014, 2013.
Short summary
Future trends in air pollution and greenhouse gas emissions in China are of great concern to the community. Here we developed a sophisticated dynamic projection model to understand 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios. By coupling strong low-carbon transitions and clean air policy, emissions of major air pollutants in China will be reduced by 58–87 % during 2015–2050. This work can support future co-governance policy design.
Future trends in air pollution and greenhouse gas emissions in China are of great concern to the...
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