Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2893-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2893-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
21 Jun 2024
Data description article |
| 21 Jun 2024
| 21 Jun 2024
Development of a high-resolution integrated emission inventory of air pollutants for China
Nana Wu
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Ruochong Xu
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
Shigan Liu
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
Xiaodong Liu
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
Qinren Shi
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
Ying Zhou
Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
Yu Zhao
State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Rd., Nanjing, Jiangsu 210023, China
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
Yu Song
State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
Junyu Zheng
Sustainable Energy and Environmental Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511458, China
Qiang Zhang
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
Kebin He
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
Institute for Carbon Neutrality, Tsinghua University, Beijing 100084, China
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Meng Li, Junichi Kurokawa, Qiang Zhang, Jung-Hun Woo, Tazuko Morikawa, Satoru Chatani, Zifeng Lu, Yu Song, Guannan Geng, Hanwen Hu, Jinseok Kim, Owen R. Cooper, and Brian C. McDonald
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In this work, we developed MIXv2, a mosaic Asian emission inventory for 2010–2017. With high spatial (0.1°) and monthly temporal resolution, MIXv2 integrates anthropogenic and open biomass burning emissions across seven sectors following a mosaic methodology. It provides CO2 emissions data alongside nine key pollutants and three chemical mechanisms. Our publicly accessible gridded monthly emissions data can facilitate long-term atmospheric and climate model analyses.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
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Xipeng Jin, Xuhui Cai, Xuesong Wang, Qianqian Huang, Yu Song, Ling Kang, Hongsheng Zhang, and Tong Zhu
Atmos. Chem. Phys., 24, 259–274, https://doi.org/10.5194/acp-24-259-2024, https://doi.org/10.5194/acp-24-259-2024, 2024
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Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
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Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Chen Gu, Lei Zhang, Zidie Xu, Sijia Xia, Yutong Wang, Li Li, Zeren Wang, Qiuyue Zhao, Hanying Wang, and Yu Zhao
Atmos. Chem. Phys., 23, 4247–4269, https://doi.org/10.5194/acp-23-4247-2023, https://doi.org/10.5194/acp-23-4247-2023, 2023
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We demonstrated the development of a high-resolution emission inventory and its application to evaluate the effectiveness of emission control actions, by incorporating the improved methodology, the best available data, and air quality modeling. We show that substantial efforts for emission controls indeed played an important role in air quality improvement even with worsened meteorological conditions and that the contributions of individual measures to emission reduction were greatly changing.
Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev., 16, 1641–1659, https://doi.org/10.5194/gmd-16-1641-2023, https://doi.org/10.5194/gmd-16-1641-2023, 2023
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Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Jingyu An, Cheng Huang, Dandan Huang, Momei Qin, Huan Liu, Rusha Yan, Liping Qiao, Min Zhou, Yingjie Li, Shuhui Zhu, Qian Wang, and Hongli Wang
Atmos. Chem. Phys., 23, 323–344, https://doi.org/10.5194/acp-23-323-2023, https://doi.org/10.5194/acp-23-323-2023, 2023
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This paper aims to build up an approach to establish a high-resolution emission inventory of intermediate-volatility and semi-volatile organic compounds in city-scale and detailed source categories and incorporate it into the CMAQ model. We believe this approach can be widely applied to improve the simulation of secondary organic aerosol and its source contributions.
Zhaofeng Lv, Zhenyu Luo, Fanyuan Deng, Xiaotong Wang, Junchao Zhao, Lucheng Xu, Tingkun He, Yingzhi Zhang, Huan Liu, and Kebin He
Atmos. Chem. Phys., 22, 15685–15702, https://doi.org/10.5194/acp-22-15685-2022, https://doi.org/10.5194/acp-22-15685-2022, 2022
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This study developed a hybrid model, CMAQ-RLINE_URBAN, to predict the urban NO2 concentrations at a high spatial resolution. To estimate the influence of various street canyons on the dispersion of air pollutants, a new parameterization scheme was established based on computational fluid dynamics and machine learning methods. This work created a new method to identify the characteristics of vehicle-related air pollution at both city and street scales simultaneously and accurately.
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.
Xipeng Jin, Xuhui Cai, Mingyuan Yu, Yu Song, Xuesong Wang, Hongsheng Zhang, and Tong Zhu
Atmos. Chem. Phys., 22, 11409–11427, https://doi.org/10.5194/acp-22-11409-2022, https://doi.org/10.5194/acp-22-11409-2022, 2022
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Meteorological discontinuities in the vertical direction define the lowest atmosphere as the boundary layer, while in the horizontal direction it identifies the contrast zone as the internal boundary. Both of them determine the polluted air mass dimension over the North China Plain. This study reveals the boundary layer structures under three categories of internal boundaries, modified by thermal, dynamical, and blending effects. It provides a new insight to understand regional pollution.
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.
Suxia Yang, Bin Yuan, Yuwen Peng, Shan Huang, Wei Chen, Weiwei Hu, Chenglei Pei, Jun Zhou, David D. Parrish, Wenjie Wang, Xianjun He, Chunlei Cheng, Xiao-Bing Li, Xiaoyun Yang, Yu Song, Haichao Wang, Jipeng Qi, Baolin Wang, Chen Wang, Chaomin Wang, Zelong Wang, Tiange Li, E Zheng, Sihang Wang, Caihong Wu, Mingfu Cai, Chenshuo Ye, Wei Song, Peng Cheng, Duohong Chen, Xinming Wang, Zhanyi Zhang, Xuemei Wang, Junyu Zheng, and Min Shao
Atmos. Chem. Phys., 22, 4539–4556, https://doi.org/10.5194/acp-22-4539-2022, https://doi.org/10.5194/acp-22-4539-2022, 2022
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We use a model constrained using observations to study the formation of nitrate aerosol in and downwind of a representative megacity. We found different contributions of various chemical reactions to ground-level nitrate concentrations between urban and suburban regions. We also show that controlling VOC emissions are effective for decreasing nitrate formation in both urban and regional environments, although VOCs are not direct precursors of nitrate aerosol.
Ruili Wu, Christopher W. Tessum, Yang Zhang, Chaopeng Hong, Yixuan Zheng, Xinyin Qin, Shigan Liu, and Qiang Zhang
Geosci. Model Dev., 14, 7621–7638, https://doi.org/10.5194/gmd-14-7621-2021, https://doi.org/10.5194/gmd-14-7621-2021, 2021
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Reduced-complexity air quality models are less computationally intensive and easier to use. We developed a reduced-complexity air quality Intervention Model for Air Pollution over China (InMAP-China) to rapidly predict the air quality and estimate the health impacts of emission sources in China. We believe that this work will be of great interest to a broad audience, including environmentalists in China and scientists in relevant fields at both national and local institutes.
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.
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.
Cited articles
An, J., Huang, Y., Huang, C., Wang, X., Yan, R., Wang, Q., Wang, H., Jing, S., Zhang, Y., Liu, Y., Chen, Y., Xu, C., Qiao, L., Zhou, M., Zhu, S., Hu, Q., Lu, J., and Chen, C.: Emission inventory of air pollutants and chemical speciation for specific anthropogenic sources based on local measurements in the Yangtze River Delta region, China, Atmos. Chem. Phys., 21, 2003–2025, https://doi.org/10.5194/acp-21-2003-2021, 2021.
Bo, X., Jia, M., Xue, X., Tang, L., Mi, Z., Wang, S., Cui, W., Chang, X., Ruan, J., Dong, G., Zhou, B., and Davis, S. J.: Effect of strengthened standards on Chinese ironmaking and steelmaking emissions, Nat. Sustain., 4, 811–820, https://doi.org/10.1038/s41893-021-00736-0, 2021.
Chen, H., Huang, Y., Shen, H., Chen, Y., Ru, M., Chen, Y., Lin, N., Su, S., Zhuo, S., Zhong, Q., Wang, X., Liu, J., Li, B., and Tao, S.: Modeling temporal variations in global residential energy consumption and pollutant emissions, Appl. Energ., 184, 820–829, https://doi.org/10.1016/j.apenergy.2015.10.185, 2016.
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.
Cheng, J., Tong, D., Liu, Y., Bo, Y., Zheng, B., Geng, G., He, K., and Zhang, Q.: Air quality and health benefits of China's current and upcoming clean air policies, Faraday Discuss., 226, 584–606, https://doi.org/10.1039/D0FD00090F, 2021a.
Cheng, J., Tong, D., Liu, Y., Yu, S., Yan, L., Zheng, B., Geng, G., He, K., and Zhang, Q.: Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios, Geophys. Res. Lett., 48, e2021GL093197, https://doi.org/10.1029/2021GL093197, 2021b.
Cheng, Z., Wang, S., Fu, X., Watson, J. G., Jiang, J., Fu, Q., Chen, C., Xu, B., Yu, J., Chow, J. C., and Hao, J.: Impact of biomass burning on haze pollution in the Yangtze River delta, China: a case study in summer 2011, Atmos. Chem. Phys., 14, 4573–4585, https://doi.org/10.5194/acp-14-4573-2014, 2014.
Chou, M.-D., Suarez, M. J., Ho, C.-H., Yan, M. M. H., and Lee, K.-T.: Parameterizations for Cloud Overlapping and Shortwave Single-Scattering Properties for Use in General Circulation and Cloud Ensemble Models, J. Climate, 11, 202–214, https://doi.org/10.1175/1520-0442(1998)011<0202:PFCOAS>2.0.CO;2, 1998.
Crippa, M., Guizzardi, D., Butler, T., Keating, T., Wu, R., Kaminski, J., Kuenen, J., Kurokawa, J., Chatani, S., Morikawa, T., Pouliot, G., Racine, J., Moran, M. D., Klimont, Z., Manseau, P. M., Mashayekhi, R., Henderson, B. H., Smith, S. J., Suchyta, H., Muntean, M., Solazzo, E., Banja, M., Schaaf, E., Pagani, F., Woo, J.-H., Kim, J., Monforti-Ferrario, F., Pisoni, E., Zhang, J., Niemi, D., Sassi, M., Ansari, T., and Foley, K.: The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies, Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, 2023.
Deng, F., Lv, Z., Qi, L., Wang, X., Shi, M., and Liu, H.: A big data approach to improving the vehicle emission inventory in China, Nat. Commun., 11, 2801, https://doi.org/10.1038/s41467-020-16579-w, 2020.
Endresen, Ø., Sørgård, E., Behrens, H. L., Brett, P. O., and Isaksen, I. S. A.: A historical reconstruction of ships' fuel consumption and emissions, J. Geophys. Res.-Atmos., 112, D12301, https://doi.org/10.1029/2006JD007630, 2007.
Geng, G., Zhang, Q., Martin, R. V., Lin, J., Huo, H., Zheng, B., Wang, S., and He, K.: Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis, Atmos. Chem. Phys., 17, 4131–4145, https://doi.org/10.5194/acp-17-4131-2017, 2017.
Geng, G., Zheng, Y., Zhang, Q., Xue, T., Zhao, H., Tong, D., Zheng, B., Li, M., Liu, F., Hong, C., He, K., and Davis, S. J.: Drivers of PM2.5 air pollution deaths in China 2002–2017, Nat. Geosci., 14, 645–650, https://doi.org/10.1038/s41561-021-00792-3, 2021.
Gu, C., Zhang, L., Xu, Z., Xia, S., Wang, Y., Li, L., Wang, Z., Zhao, Q., Wang, H., and Zhao, Y.: High-resolution regional emission inventory contributes to the evaluation of policy effectiveness: a case study in Jiangsu Province, China, Atmos. Chem. Phys., 23, 4247–4269, https://doi.org/10.5194/acp-23-4247-2023, 2023.
Hong, S. Y. and Lim, J.-O. J.: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6), Asia-Pac. J. Atmos. Sci., 42, 129–151, 2006.
Huang, C., Hu, Q., Wang, H., Qiao, L., Jing, S. a., Wang, H., Zhou, M., Zhu, S., Ma, Y., Lou, S., Li, L., Tao, S., Li, Y., and Lou, D.: Emission factors of particulate and gaseous compounds from a large cargo vessel operated under real-world conditions, Environ. Pollut., 242, 667–674, https://doi.org/10.1016/j.envpol.2018.07.036, 2018.
Huang, X., Li, M., Li, J., and Song, Y.: A high-resolution emission inventory of crop burning in fields in China based on MODIS Thermal Anomalies/Fire products, Atmos. Environ., 50, 9–15, https://doi.org/10.1016/j.atmosenv.2012.01.017, 2012a.
Huang, X., Song, Y., Li, M., Li, J., Huo, Q., Cai, X., Zhu, T., Hu, M., and Zhang, H.: A high-resolution ammonia emission inventory in China, Global Biogeochem. Cy., 26, GB1030, https://doi.org/10.1029/2011GB004161, 2012b.
Huang, Z., Zhong, Z., Sha, Q., Xu, Y., Zhang, Z., Wu, L., Wang, Y., Zhang, L., Cui, X., Tang, M., Shi, B., Zheng, C., Li, Z., Hu, M., Bi, L., Zheng, J., and Yan, M.: An updated model-ready emission inventory for Guangdong Province by incorporating big data and mapping onto multiple chemical mechanisms, Sci. Total Environ., 769, 144535, https://doi.org/10.1016/j.scitotenv.2020.144535, 2021.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., Denier van der Gon, H., Kuenen, J. J. P., Klimont, Z., Frost, G., Darras, S., Koffi, B., and Li, M.: HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution, Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, 2015.
Kain, J. S.: The Kain–Fritsch Convective Parameterization: An Update, J. Appl. Meteorol., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
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.
Kurokawa, J., Ohara, T., Morikawa, T., Hanayama, S., Janssens-Maenhout, G., Fukui, T., Kawashima, K., and Akimoto, H.: Emissions of air pollutants and greenhouse gases over Asian regions during 2000–2008: Regional Emission inventory in ASia (REAS) version 2, Atmos. Chem. Phys., 13, 11019–11058, https://doi.org/10.5194/acp-13-11019-2013, 2013.
Li, B., Chen, L., Shen, W., Jin, J., Wang, T., Wang, P., Yang, Y., and Liao, H.: Improved gridded ammonia emission inventory in China, Atmos. Chem. Phys., 21, 15883–15900, https://doi.org/10.5194/acp-21-15883-2021, 2021.
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., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., Zhang, Q., and He, K.: Anthropogenic emission inventories in China: a review, Natl. Sci. Rev., 4, 834–866, https://doi.org/10.1093/nsr/nwx150, 2017a.
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, 2017b.
Li, M., Kurokawa, J., Zhang, Q., Woo, J.-H., Morikawa, T., Chatani, S., Lu, Z., Song, Y., Geng, G., Hu, H., Kim, J., Cooper, O. R., and McDonald, B. C.: MIXv2: a long-term mosaic emission inventory for Asia (2010–2017), Atmos. Chem. Phys., 24, 3925–3952, https://doi.org/10.5194/acp-24-3925-2024, 2024.
Li, S., Wang, S., Wu, Q., Zhang, Y., Ouyang, D., Zheng, H., Han, L., Qiu, X., Wen, Y., Liu, M., Jiang, Y., Yin, D., Liu, K., Zhao, B., Zhang, S., Wu, Y., and Hao, J.: Emission trends of air pollutants and CO2 in China from 2005 to 2021, Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, 2023.
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, F., Beirle, S., Zhang, Q., Dörner, S., He, K., and Wagner, T.: NOx lifetimes and emissions of cities and power plants in polluted background estimated by satellite observations, Atmos. Chem. Phys., 16, 5283–5298, https://doi.org/10.5194/acp-16-5283-2016, 2016.
Liu, H., Fu, M., Jin, X., Shang, Y., Shindell, D., Faluvegi, G., Shindell, C., and He, K.: Health and climate impacts of ocean-going vessels in East Asia, Nat. Clim. Change, 6, 1037–1041, https://doi.org/10.1038/nclimate3083, 2016.
Liu, H., Wu, B., Liu, S., Shao, P., Liu, X., Zhu, C., Wang, Y., Wu, Y., Xue, Y., Gao, J., Hao, Y., and Tian, H.: A regional high-resolution emission inventory of primary air pollutants in 2012 for Beijing and the surrounding five provinces of North China, Atmos. Environ., 181, 20–33, https://doi.org/10.1016/j.atmosenv.2018.03.013, 2018.
Liu, H., Meng, Z.-H., Lv, Z.-F., Wang, X.-T., Deng, F.-Y., Liu, Y., Zhang, Y.-N., Shi, M.-S., Zhang, Q., and He, K.-B.: Emissions and health impacts from global shipping embodied in US–China bilateral trade, Nat. Sustain., 2, 1027–1033, https://doi.org/10.1038/s41893-019-0414-z, 2019.
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., 20, 7783–7799, https://doi.org/10.5194/acp-20-7783-2020, 2020.
Liu, M., Song, Y., Yao, H., Kang, Y., Li, M., Huang, X., and Hu, M.: Estimating emissions from agricultural fires in the North China Plain based on MODIS fire radiative power, Atmos. Environ., 112, 326–334, https://doi.org/10.1016/j.atmosenv.2015.04.058, 2015.
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.
Lv, Z., Liu, H., Ying, Q., Fu, M., Meng, Z., Wang, Y., Wei, W., Gong, H., and He, K.: Impacts of shipping emissions on PM2.5 pollution in China, Atmos. Chem. Phys., 18, 15811–15824, https://doi.org/10.5194/acp-18-15811-2018, 2018.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, https://doi.org/10.1029/97JD00237, 1997.
Ni, H., Han, Y., Cao, J., Chen, L. W. A., Tian, J., Wang, X., Chow, J. C., Watson, J. G., Wang, Q., Wang, P., Li, H., and Huang, R.-J.: Emission characteristics of carbonaceous particles and trace gases from open burning of crop residues in China, Atmos. Environ., 123, 399–406, https://doi.org/10.1016/j.atmosenv.2015.05.007, 2015.
Ohara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X., and Hayasaka, T.: An Asian emission inventory of anthropogenic emission sources for the period 1980–2020, Atmos. Chem. Phys., 7, 4419–4444, https://doi.org/10.5194/acp-7-4419-2007, 2007.
Paulot, F., Jacob, D. J., Pinder, R. W., Bash, J. O., Travis, K., and Henze, D. K.: Ammonia emissions in the United States, European Union, and China derived by high-resolution inversion of ammonium wet deposition data: Interpretation with a new agricultural emissions inventory (MASAGE_NH3), J. Geophys. Res.-Atmos., 119, 4343–4364, https://doi.org/10.1002/2013JD021130, 2014.
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. Energ., 235, 1169–1182, https://doi.org/10.1016/j.apenergy.2018.11.043, 2019.
Pleim, J. E.: A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part I: Model Description and Testing, J. Appl. Meteorol. Clim., 46, 1383–1395, https://doi.org/10.1175/JAM2539.1, 2007.
Reisen, F., Meyer, C. P., and Keywood, M. D.: Impact of biomass burning sources on seasonal aerosol air quality, Atmos. Environ., 67, 437–447, https://doi.org/10.1016/j.atmosenv.2012.11.004, 2013.
Schneider, A., Friedl, M. A., and Potere, D.: A new map of global urban extent from MODIS satellite data, Environ. Res. Lett., 4, 044003, https://doi.org/10.1088/1748-9326/4/4/044003, 2009.
Sha, Q., Zhu, M., Huang, H., Wang, Y., Huang, Z., Zhang, X., Tang, M., Lu, M., Chen, C., Shi, B., Chen, Z., Wu, L., Zhong, Z., Li, C., Xu, Y., Yu, F., Jia, G., Liao, S., Cui, X., Liu, J., and Zheng, J.: A newly integrated dataset of volatile organic compounds (VOCs) source profiles and implications for the future development of VOCs profiles in China, Sci. Total Environ., 793, 148348, https://doi.org/10.1016/j.scitotenv.2021.148348, 2021.
Song, Y., Liu, B., Miao, W., Chang, D., and Zhang, Y.: Spatiotemporal variation in nonagricultural open fire emissions in China from 2000 to 2007, Global Biogeochem. Cy., 23, GB2008, https://doi.org/10.1029/2008GB003344, 2009.
Streets, D. G., Bond, T. C., Carmichael, G. R., Fernandes, S. D., Fu, Q., He, D., Klimont, Z., Nelson, S. M., Tsai, N. Y., Wang, M. Q., Woo, J. H., and Yarber, K. F.: An inventory of gaseous and primary aerosol emissions in Asia in the year 2000, J. Geophys. Res.-Atmos., 108, 8809, https://doi.org/10.1029/2002JD003093, 2003.
Tang, L., Jia, M., Yang, J., Li, L., Bo, X., and Mi, Z.: Chinese industrial air pollution emissions based on the continuous emission monitoring systems network, Scientific Data, 10, 153, https://doi.org/10.1038/s41597-023-02054-w, 2023.
United Nations Conference on Trade and Development (UNCTAD): Review of Maritime Transport 2014, United Nations, https://doi.org/10.18356/5a566ab1-en, 2014.
Wang, W., Khanna, N., Lin, J., and Liu, X.: Black carbon emissions and reduction potential in China: 2015–2050, J. Environ. Manage., 329, 117087, https://doi.org/10.1016/j.jenvman.2022.117087, 2023.
Wang, X., Lei, Y., Yan, L., Liu, T., Zhang, Q., and He, K.: A unit-based emission inventory of SO2, NOx and PM for the Chinese iron and steel industry from 2010 to 2015, Sci. Total Environ., 676, 18–30, https://doi.org/10.1016/j.scitotenv.2019.04.241, 2019.
Wu, N., Geng, G., Yan, L., Bi, J., Li, Y., Tong, D., Zheng, B., and Zhang, Q.: Improved spatial representation of a highly resolved emission inventory in China: evidence from TROPOMI measurements, Environ. Res. Lett., 16, 084056, https://doi.org/10.1088/1748-9326/ac175f, 2021.
Wu, N., Geng, G., Qin, X., Tong, D., Zheng, Y., Lei, Y., and Zhang, Q.: Daily Emission Patterns of Coal-Fired Power Plants in China Based on Multisource Data Fusion, ACS Environ. Au., 2, 363–372, https://doi.org/10.1021/acsenvironau.2c00014, 2022.
Wu, N., Geng, G., Xu, R., Liu, S., Liu, X., Shi, Q., Zhou, Y., Zhao, Y., Liu, H., Song, Y., Zheng, J., and Zhang, Q.: INTAC: a high-resolution INTegrated emission inventory of Air pollutants for China in 2017 [Data set], Zenodo, https://doi.org/10.5281/zenodo.10459198, 2024.
Wu, Q., Han, L., Li, S., Wang, S., Cong, Y., Liu, K., Lei, Y., Zheng, H., Li, G., Cai, B., and Hao, J.: Facility-Level Emissions and Synergistic Control of Energy-Related Air Pollutants and Carbon Dioxide in China, Environ. Sci. Technol., 57, 4504–4512, https://doi.org/10.1021/acs.est.2c07704, 2023.
Xiao, Q., Geng, G., Xue, T., Liu, S., Cai, C., He, K., and Zhang, Q.: Tracking PM2.5 and O3 Pollution and the Related Health Burden in China 2013–2020, Environ. Sci. Technol., 56, 6922–6932, https://doi.org/10.1021/acs.est.1c04548, 2022.
Xiu, A. and Pleim, J. E.: Development of a Land Surface Model. Part I: Application in a Mesoscale Meteorological Model, J. Appl. Meteorol., 40, 192–209, https://doi.org/10.1175/1520-0450(2001)040<0192:DOALSM>2.0.CO;2, 2001.
Yang, Y. and Zhao, Y.: Quantification and evaluation of atmospheric pollutant emissions from open biomass burning with multiple methods: a case study for the Yangtze River Delta region, China, Atmos. Chem. Phys., 19, 327–348, https://doi.org/10.5194/acp-19-327-2019, 2019.
Yin, L., Du, P., Zhang, M., Liu, M., Xu, T., and Song, Y.: Estimation of emissions from biomass burning in China (2003–2017) based on MODIS fire radiative energy data, Biogeosciences, 16, 1629–1640, https://doi.org/10.5194/bg-16-1629-2019, 2019.
Zhang, J., Liu, L., Zhao, Y., Li, H., Lian, Y., Zhang, Z., Huang, C., and Du, X.: Development of a high-resolution emission inventory of agricultural machinery with a novel methodology: A case study for Yangtze River Delta region, Environ. Pollut., 266, 115075, https://doi.org/10.1016/j.envpol.2020.115075, 2020.
Zhang, Q. and Geng, G.: Impact of clean air action on PM2.5 pollution in China, Science China Earth Sciences, 62, 1845–1846, https://doi.org/10.1007/s11430-019-9531-4, 2019.
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, 2019.
Zhang, Y., Bo, X., Zhao, Y., and Nielsen, C. P.: Benefits of current and future policies on emissions of China's coal-fired power sector indicated by continuous emission monitoring, Environ. Pollut., 251, 415–424, https://doi.org/10.1016/j.envpol.2019.05.021, 2019.
Zhang, Y., Zhao, Y., Gao, M., Bo, X., and Nielsen, C. P.: Air quality and health benefits from ultra-low emission control policy indicated by continuous emission monitoring: a case study in the Yangtze River Delta region, China, Atmos. Chem. Phys., 21, 6411–6430, https://doi.org/10.5194/acp-21-6411-2021, 2021.
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.
Zhao, Y., Qiu, L. P., Xu, R. Y., Xie, F. J., Zhang, Q., Yu, Y. Y., Nielsen, C. P., Qin, H. X., Wang, H. K., Wu, X. C., Li, W. Q., and Zhang, J.: Advantages of a city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China, Atmos. Chem. Phys., 15, 12623–12644, https://doi.org/10.5194/acp-15-12623-2015, 2015.
Zhao, Y., Mao, P., Zhou, Y., Yang, Y., Zhang, J., Wang, S., Dong, Y., Xie, F., Yu, Y., and Li, W.: Improved provincial emission inventory and speciation profiles of anthropogenic non-methane volatile organic compounds: a case study for Jiangsu, China, Atmos. Chem. Phys., 17, 7733–7756, https://doi.org/10.5194/acp-17-7733-2017, 2017a.
Zhao, Y., Zhou, Y., Qiu, L., and Zhang, J.: Quantifying the uncertainties of China's emission inventory for industrial sources: From national to provincial and city scales, Atmos. Environ., 165, 207–221, https://doi.org/10.1016/j.atmosenv.2017.06.045, 2017b.
Zhao, Y., Xia, Y., and Zhou, Y.: Assessment of a high-resolution NOX emission inventory using satellite observations: A case study of southern Jiangsu, China, Atmos. Environ., 190, 135–145, https://doi.org/10.1016/j.atmosenv.2018.07.029, 2018.
Zhao, Y., Yuan, M., Huang, X., Chen, F., and Zhang, J.: Quantification and evaluation of atmospheric ammonia emissions with different methods: a case study for the Yangtze River Delta region, China, Atmos. Chem. Phys., 20, 4275–4294, https://doi.org/10.5194/acp-20-4275-2020, 2020.
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., Tong, D., Chen, C., Hong, C., Li, M., Geng, G., Lei, Y., Huo, H., and He, K.: Resolution dependence of uncertainties in gridded emission inventories: a case study in Hebei, China, Atmos. Chem. Phys., 17, 921–933, https://doi.org/10.5194/acp-17-921-2017, 2017.
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, B., Cheng, J., Geng, G., Wang, X., Li, M., Shi, Q., Qi, J., Lei, Y., Zhang, Q., and He, K.: Mapping anthropogenic emissions in China at 1 km spatial resolution and its application in air quality modeling, Sci. Bull., 66, 612–620, https://doi.org/10.1016/j.scib.2020.12.008, 2021.
Zheng, H., Cai, S., Wang, S., Zhao, B., Chang, X., and Hao, J.: Development of a unit-based industrial emission inventory in the Beijing–Tianjin–Hebei region and resulting improvement in air quality modeling, Atmos. Chem. Phys., 19, 3447–3462, https://doi.org/10.5194/acp-19-3447-2019, 2019.
Zheng, J., He, M., Shen, X., Yin, S., and Yuan, Z.: High resolution of black carbon and organic carbon emissions in the Pearl River Delta region, China, Sci. Total Environ., 438, 189–200, https://doi.org/10.1016/j.scitotenv.2012.08.068, 2012.
Zhou, Y., Xing, X., Lang, J., Chen, D., Cheng, S., Wei, L., Wei, X., and Liu, C.: A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China, Atmos. Chem. Phys., 17, 2839–2864, https://doi.org/10.5194/acp-17-2839-2017, 2017a.
Zhou, Y., Zhao, Y., Mao, P., Zhang, Q., Zhang, J., Qiu, L., and Yang, Y.: Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu Province, China, Atmos. Chem. Phys., 17, 211–233, https://doi.org/10.5194/acp-17-211-2017, 2017b.
Short summary
The commonly used method for developing large-scale air pollutant emission datasets for China faces challenges due to limited availability of detailed parameter information. In this study, we develop an efficient integrated framework to gather such information by harmonizing seven heterogeneous inventories from five research institutions. Emission characterizations are analyzed and validated, demonstrating that the dataset provides more accurate emission magnitudes and spatiotemporal patterns.
The commonly used method for developing large-scale air pollutant emission datasets for China...
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