Articles | Volume 25, issue 19
https://doi.org/10.5194/acp-25-12675-2025
© Author(s) 2025. 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-25-12675-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A technology-based global non-methane volatile organic compounds (NMVOC) emission inventory under the MEIC framework
Ruochong Xu
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Hanchen Ma
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Jingxian Li
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, People's Republic of China
Dan Tong
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Liu Yan
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, People's Republic of China
Lanyuan Wang
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, People's Republic of China
Xinying Qin
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Qingyang Xiao
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, People's Republic of China
Xizhe Yan
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Hanwen Hu
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, 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
Nana Wu
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Huaxuan Wang
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, People's Republic of China
Yuexuanzi Wang
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
Xiaodong Liu
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, 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
Kebin He
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, People's Republic of China
Institute for Carbon Neutrality, Tsinghua University, Beijing 100084, People's Republic of China
Qiang Zhang
CORRESPONDING AUTHOR
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, People's Republic of China
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Ruili Wu, Christopher W. Tessum, Yang Zhang, Chaopeng Hong, Yixuan Zheng, Xinyin Qin, Shigan Liu, and Qiang Zhang
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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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Yuqiang Zhang, Drew Shindell, Karl Seltzer, Lu Shen, Jean-Francois Lamarque, Qiang Zhang, Bo Zheng, Jia Xing, Zhe Jiang, and Lei Zhang
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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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Xiaotong Wang, Wen Yi, Zhaofeng Lv, Fanyuan Deng, Songxin Zheng, Hailian Xu, Junchao Zhao, Huan Liu, and Kebin He
Atmos. Chem. Phys., 21, 13835–13853, https://doi.org/10.5194/acp-21-13835-2021, https://doi.org/10.5194/acp-21-13835-2021, 2021
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This study updates our previous Ship Emission Inventory Model to version 2.0 (SEIM v2.0) and develops high-spatiotemporal ship emission inventories of China’s inland rivers and a 200 nautical mile coastal zone in 2016–2019. The 4-year consecutive daily ship emissions and emission structure changes are analyzed from the national to port levels. The results of this study can provide high-quality datasets for air quality modeling and observation experiment verifications.
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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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.
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.
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.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy
Atmos. Chem. Phys., 21, 457–481, https://doi.org/10.5194/acp-21-457-2021, https://doi.org/10.5194/acp-21-457-2021, 2021
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We simulate the atmospheric chemical processes of an important sulfur-containing organic aerosol species, which is produced by the reaction between sulfur dioxide and formaldehyde. We can predict its distribution on a global scale. We find it is particularly rich in East Asia. This aerosol species is more abundant in the colder season partly because of weaker sunlight.
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.
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.
Cited articles
Baidya, S. and Borken-Kleefeld, J.: Atmospheric emissions from road transportation in India, Energy Policy, 37, 3812–3822, https://doi.org/10.1016/j.enpol.2009.07.010, 2009.
Bianchi, F., Kurteìn, T., Riva, M., Mohr, C., Rissanen, M. P., Roldin, P., Berndt, T., Crounse, J., Wennberg, P., Mentel, T., Wildt, J., Junninen, H., Jokinen, T., Kulmala, M., Worsnop, D. R., Thornton, J. A., Donahue, N., Kjaergaard, H., and Ehn, M.: Highly oxygenated organic molecules (HOM) from gas-phase autoxidation involving peroxy radicals: A key contributor to atmospheric aerosol, Chem. Rev., 119, 3472–3509, https://doi.org/10.1021/acs.chemrev.8b00395, 2019.
Bo, Y., Cai, H., and Xie, S. D.: Spatial and temporal variation of historical anthropogenic NMVOCs emission inventories in China, Atmos. Chem. Phys., 8, 7297–7316, https://doi.org/10.5194/acp-8-7297-2008, 2008.
Bond, T., Venkataraman, C., and Masera, O.: Global atmospheric impacts of residential fuels, Energy Sustain. Dev., 8, 20–32, https://doi.org/10.1016/s0973-0826(08)60464-0, 2004.
Bond, T. C., Bhardwaj, E., Dong, R., Jogani, R., Jung, S., Roden, C., Streets, D. G., and Trautmann, N. M.: Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850–2000, Glob. Biogeochem. Cycles, 21, GB2018, https://doi.org/10.1029/2006gb002840, 2007.
Borken-Kleefeld, J. and Chen, Y.: New emission deterioration rates for gasoline cars–Results from long-term measurements, Atmos. Environ., 101, 58–64, https://doi.org/10.1016/j.atmosenv.2014.11.013, 2015.
Chen, C., Xu, R., Tong, D., Qin, X., Cheng, J., Liu, J., Zheng, B., Yan, L., and Zhang, Q.: A striking growth of CO2 emissions from the global cement industry driven by new facilities in emerging countries, Environ. Res. Lett., 17, 044007, https://doi.org/10.1088/1748-9326/ac48b5, 2022.
Chiang, H. L., Tsai, J. H., Yao, Y. C., and Ho, W. Y.: Deterioration of gasoline vehicle emissions and effectiveness of tune-up for high-polluted vehicles, Transp. Res. D: Transp. Environ., 13, 47–53, https://doi.org/10.1016/j.trd.2007.07.004, 2008.
Chong, W. W. F., Ng, J. H., Rajoo, S., and Chong, C. T.: Passenger transportation sector gasoline consumption due to friction in Southeast Asian countries, Energy Convers. Manag., 158, 346–358, https://doi.org/10.1016/j.enconman.2017.12.083, 2018.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Cui, C., Li, S., Zhao, W., Liu, B., Shan, Y., and Guan, D.: Energy-related CO2 emission accounts and datasets for 40 emerging economies in 2010–2019, Earth Syst. Sci. Data, 15, 1317–1328, https://doi.org/10.5194/essd-15-1317-2023, 2023.
Denier van der Gon, H. A. C., Bergström, R., Fountoukis, C., Johansson, C., Pandis, S. N., Simpson, D., and Visschedijk, A. J. H.: Particulate emissions from residential wood combustion in Europe – revised estimates and an evaluation, Atmos. Chem. Phys., 15, 6503–6519, https://doi.org/10.5194/acp-15-6503-2015, 2015.
European Bureau for Research on Industrial Transformation and Emissions (EU-BRITE): Reference Document on Best Available Techniques for the Manufacture of Large Volume Inorganic Chemicals – Ammonia, Acids and Fertilisers, https://eippcb.jrc.ec.europa.eu/reference/large-volume-inorganic-chemicals-ammonia-acids-and-fertilisers (last access: 12 July 2022), 2007.
European Environmental Agency (EEA): EMEP/EEA air pollutant emission inventory guidebook 2023, https://www.eea.europa.eu/publications/emep-eea-guidebook-2023 (last access: 21 July 2024), 2023.
European Monitoring and Evaluation Programme (EMEP)/Centre on Emission Inventories and Projections (CEIP): The Emissions Database, https://www.ceip.at/webdab-emission-database (last access: 18 December 2023), 2023.
Food and Agriculture Organization (FAO): FAOSTAT, https://www.fao.org/faostat/en/#data (last access: 7 March 2024), 2022.
Fry, M. M., Schwarzkopf, M. D., Adelman, Z., and West, J. J.: Air quality and radiative forcing impacts of anthropogenic volatile organic compound emissions from ten world regions, Atmos. Chem. Phys., 14, 523–535, https://doi.org/10.5194/acp-14-523-2014, 2014.
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.
Geng, G., Liu, Y., Liu, Y., Liu, S., Cheng, J., Yan, L., Wu, N., Hu, H., Tong, D. Zheng, B., Yin, Z., He, K., and Zhang, Q.: Efficacy of China's clean air actions to tackle PM2.5 pollution between 2013 and 2020, Nat. Geosci., 17, 987–994, https://doi.org/10.1038/s41561-024-01540-z, 2024.
Gkatzelis, G. I., Coggon, M. M., McDonald, B. C., Peischl, J., Aikin, K. C., Gilman, J. B., Trainer, M., and Warneke, C.: Identifying volatile chemical product tracer compounds in US cities, Environ. Sci. Technol., 55, 188–199, https://doi.org/10.1021/acs.est.0c05467, 2020.
Hallquist, M., Wenger, J. C., Baltensperger, U., Rudich, Y., Simpson, D., Claeys, M., Dommen, J., Donahue, N. M., George, C., Goldstein, A. H., Hamilton, J. F., Herrmann, H., Hoffmann, T., Iinuma, Y., Jang, M., Jenkin, M. E., Jimenez, J. L., Kiendler-Scharr, A., Maenhaut, W., McFiggans, G., Mentel, Th. F., Monod, A., Prévôt, A. S. H., Seinfeld, J. H., Surratt, J. D., Szmigielski, R., and Wildt, J.: The formation, properties and impact of secondary organic aerosol: current and emerging issues, Atmos. Chem. Phys., 9, 5155–5236, https://doi.org/10.5194/acp-9-5155-2009, 2009.
Heald, C. L. and Kroll, J. H.: The fuel of atmospheric chemistry: Toward a complete description of reactive organic carbon, Sci. Adv., 6, eaay8967, https://doi.org/10.1126/sciadv.aay8967, 2020.
Hendriks, C., Forsell, N., Kiesewetter, G., Schaap, M., and Schöpp, W.: Ozone concentrations and damage for realistic future European climate and air quality scenarios, Atmos. Environ., 144, 208–219, https://doi.org/10.1016/j.atmosenv.2016.08.026, 2016.
Hobbs, P. J., Webb, J., Mottram, T. T., Grant, B., and Misselbrook, T. M.: Emissions of volatile organic compounds originating from UK livestock agriculture, J. Sci. Food Agric., 84, 1414–1420, https://doi.org/10.1002/jsfa.1810, 2004.
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.
Huang, G., Brook, R., Crippa, M., Janssens-Maenhout, G., Schieberle, C., Dore, C., Guizzardi, D., Muntean, M., Schaaf, E., and Friedrich, R.: Speciation of anthropogenic emissions of non-methane volatile organic compounds: a global gridded data set for 1970–2012, Atmos. Chem. Phys., 17, 7683–7701, https://doi.org/10.5194/acp-17-7683-2017, 2017.
Intergovernmental Panel on Climate Change (IPCC): IPCC Guidelines for National Greenhouse Gas Inventories, https://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html (last access: 20 February 2022), 2006.
International Council on Clean Transportation (ICCT): Technology pathways for diesel engines used in non-road vehicles and equipment, https://theicct.org/publication/technology-pathways-for-diesel-engines-used-in-non-road-vehicles-and-equipment/ (last access: 5 November 2023), 2016.
International Energy Agency (IEA): World Energy, Oil, and Natural Gas Statistics, https://www.iea.org/data-and-statistics (last access: 3 August 2022), 2022.
Keita, S., Liousse, C., Assamoi, E.-M., Doumbia, T., N'Datchoh, E. T., Gnamien, S., Elguindi, N., Granier, C., and Yoboué, V.: African anthropogenic emissions inventory for gases and particles from 1990 to 2015, Earth Syst. Sci. Data, 13, 3691–3705, https://doi.org/10.5194/essd-13-3691-2021, 2021.
Klimont, Z., Amann, M., and Cofala, J.: Estimating costs for controlling emissions of volatile organic compounds (VOC) from stationary sources in Europe, IIASA Interim Report, IIASA, Laxenburg, Austria, https://pure.iiasa.ac.at/id/eprint/6195/ (last access: 14 April 2025), 2000.
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.
Klimont, Z., Cofala, J., Xing, J., Wei, W., Zhang, C., Wang, S., Kejun, J., Bhandari, P., Mathur, R., Purohit, P., Rafaj, P., Chambers, A., Amann, M., and Hao, J.: Projections of SO2, NOx and carbonaceous aerosols emissions in Asia, Tellus B: Chem. Phys. Meteorol., 61, 602–617, https://doi.org/10.1111/j.1600-0889.2009.00428.x, 2009.
Kourtidis, K. A., Ziomas, I. C., Rappenglueck, B., Proyou, A., and Balis, D.: Evaporative traffic hydrocarbon emissions, traffic CO and speciated HC traffic emissions from the city of Athens, Atmos. Environ., 33, 3831–3842, https://doi.org/10.1016/s1352-2310(98)00395-1, 1999.
Kurokawa, J. and Ohara, T.: Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in ASia (REAS) version 3, Atmos. Chem. Phys., 20, 12761–12793, https://doi.org/10.5194/acp-20-12761-2020, 2020.
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.
Laurent, A. and Hauschild, M. Z.: Impacts of NMVOC emissions on human health in European countries for 2000–2010: Use of sector-specific substance profiles, Atmos. Environ., 85, 247–255, https://doi.org/10.1016/j.atmosenv.2013.11.060, 2014.
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, 2011.
Li, K., Jacob, D. J., Liao, H., Zhu, J., Shah, V., Shen, L., Bates, K. H., Zhang, Q., and Zhai, S.: A two-pollutant strategy for improving ozone and particulate air quality in China, Nat. Geosci., 12, 906–910, https://doi.org/10.1038/s41561-019-0464-x, 2019a.
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, 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, 2019b.
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.
McDonald, B. C., Goldstein, A. H., and Harley, R. A.: Long-term trends in California mobile source emissions and ambient concentrations of black carbon and organic aerosol, Environ. Sci. Technol., 49, 5178–5188, https://doi.org/10.1021/es505912b, 2015.
McDonald, B. C., De Gouw, J. A., Gilman, J. B., Jathar, S. H., Akherati, A., Cappa, C. D., Jimenez, J. L., Lee-Taylor, J., Hayes, P., McKeen, S. A., Cui, Y. Y., Kim, S., Gentner, D. R., Isaacman-Vanwertz, G., Goldstein, A. H., Harley, R. A., Frost, G. J., Roberts, J. M., Ryerson, T. B., and Trainer, M.: Volatile chemical products emerging as largest petrochemical source of urban organic emissions, Science, 359, 760–764, https://doi.org/10.1126/science.aaq0524, 2018.
Meng, J., Yang, H., Yi, K., Liu, J., Guan, D., Liu, Z., Mi, Z., Coffman, D., Wang, X., Zhong, Q., Huang, T., Meng, W., and Tao, S.: The slowdown in global air-pollutant emission growth and driving factors, One Earth, 1, 138–148, https://doi.org/10.1016/j.oneear.2019.08.013, 2019.
Mo, Z., Cui, R., Yuan, B., Cai, H., McDonald, B. C., Li, M., Zheng, J., and Shao, M.: A mass-balance-based emission inventory of non-methane volatile organic compounds (NMVOCs) for solvent use in China, Atmos. Chem. Phys., 21, 13655–13666, https://doi.org/10.5194/acp-21-13655-2021, 2021.
Observatory of Economic Complexity (OEC): Harmonized System (HS) Products, https://oec.world/en/product-landing/hs (last access: 11 January 2024), 2022.
Oliveira, K., Guevara, M., Kuenen, J., Jorba, O., García-Pando, C. P., and Denier van der Gon, H.: Enhancing anthropogenic NMVOC emission speciation for European air quality modelling, Environ. Pollut., 126510, https://doi.org/10.1016/j.envpol.2025.126510, 2025.
Paliwal, U., Sharma, M., and Burkhart, J. F.: Monthly and spatially resolved black carbon emission inventory of India: uncertainty analysis, Atmos. Chem. Phys., 16, 12457–12476, https://doi.org/10.5194/acp-16-12457-2016, 2016.
Pandey, A. and Venkataraman, C.: Estimating emissions from the Indian transport sector with on-road fleet composition and traffic volume, Atmos. Environ., 98, 123–133, https://doi.org/10.1016/j.atmosenv.2014.08.039, 2014.
Pandey, A., Sadavarte, P., Rao, A. B., and Venkataraman, C.: Trends in multi-pollutant emissions from a technology-linked inventory for India: II. Residential, agricultural and informal industry sectors, Atmos. Environ., 99, 341–352, https://doi.org/10.1016/j.atmosenv.2014.09.080, 2014.
Pandey, K. and Sahu, L. K.: Emissions of volatile organic compounds from biomass burning sources and their ozone formation potential over India, Curr. Sci., 1270–1279, https://www.jstor.org/stable/24102344 (last access: 22 September 2025), 2014.
Partha, D. B., Xiong, Y., Prime, N., Smith, S. J., and Huang, Y.: Long-term impacts of global solid biofuel emissions on ambient air quality and human health for 2000–2019, GeoHealth, 9, e2024GH001130, https://doi.org/10.1029/2024gh001130, 2025.
Plant, G., Kort, E. A., Brandt, A. R., Chen, Y., Fordice, G., Gorchov Negron, A. M., Schwietzke, S., Smith, M., and Zavala-Araiza, D.: Inefficient and unlit natural gas flares both emit large quantities of methane, Science, 377, 1566–1571, https://doi.org/10.1126/science.abq0385, 2022.
Pye, H. O. T., Place, B. K., Murphy, B. N., Seltzer, K. M., D'Ambro, E. L., Allen, C., Piletic, I. R., Farrell, S., Schwantes, R. H., Coggon, M. M., Saunders, E., Xu, L., Sarwar, G., Hutzell, W. T., Foley, K. M., Pouliot, G., Bash, J., and Stockwell, W. R.: Linking gas, particulate, and toxic endpoints to air emissions in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM), Atmos. Chem. Phys., 23, 5043–5099, https://doi.org/10.5194/acp-23-5043-2023, 2023.
Qin, M., She, Y., Wang, M., Wang, H., Chang, Y., Tan, Z., An, J., Huang, J., Yuan, Z., Lu, J., Wang, Q., Liu, G., Liu, Z., Xie, X., Li, J., Liao, H., Pye, H. O. T., Huang, C., Guo, S., Hu, M., Zhang, Y., Jacob, D., and Hu, J.: Increased urban ozone in heatwaves due to temperature-induced emissions of anthropogenic volatile organic compounds, Nat. Geosci., 18, 50–56, https://doi.org/10.1038/s41561-024-01608-w, 2025.
Qin, X., Tong, D., Liu, F., Wu, R., Zheng, B., Zheng, Y., Liu, J., Xu, R., Chen, C., Yan, L., and Zhang, Q.: Global and regional drivers of power plant CO2 emissions over the last three decades revealed from unit-based database, Earth's Future, 10, e2022EF002657, https://doi.org/10.1029/2022ef002657, 2022.
Reiter, M. S. and Kockelman, K. M.: The problem of cold starts: A closer look at mobile source emissions levels, Transp. Res. D: Transp. Environ., 43, 123–132, https://doi.org/10.1016/j.trd.2015.12.012, 2016.
Rowlinson, M. J., Evans, M. J., Carpenter, L. J., Read, K. A., Punjabi, S., Adedeji, A., Fakes, L., Lewis, A., Richmond, B., Passant, N., Murrells, T., Henderson, B., Bates, K. H., and Helmig, D.: Revising VOC emissions speciation improves the simulation of global background ethane and propane, Atmos. Chem. Phys., 24, 8317–8342, https://doi.org/10.5194/acp-24-8317-2024, 2024.
Rubin, J. I., Kean, A. J., Harley, R. A., Millet, D. B., and Goldstein, A. H.: Temperature dependence of volatile organic compound evaporative emissions from motor vehicles, J. Geophys. Res. Atmos., 111, https://doi.org/10.1029/2005jd006458, 2006.
Sadavarte, P. and Venkataraman, C.: Trends in multi-pollutant emissions from a technology-linked inventory for India: I. Industry and transport sectors, Atmos. Environ., 99, 353–364, https://doi.org/10.1016/j.atmosenv.2014.09.081, 2014.
Saundry, P. D.: Review of the United States energy system in transition, Energy Sustain. Soc., 9, 4, https://doi.org/10.1186/s13705-018-0178-8, 2019.
Sharma, G., Sinha, B., Pallavi, Hakkim, H., Chandra, B. P., Kumar, A., and Sinha, V.: Gridded emissions of CO, NOx, SO2, CO2, NH3, HCl, CH4, PM2.5, PM10, BC, and NMVOC from open municipal waste burning in India, Environ. Sci. Technol., 53, 4765–4774, https://doi.org/10.1021/acs.est.8b07076, 2019.
Sharma, S., Goel, A., Gupta, D., Kumar, A., Mishra, A., Kundu, S., Chatani, S., and Klimont, Z.: Emission inventory of non-methane volatile organic compounds from anthropogenic sources in India, Atmos. Environ., 102, 209–219, https://doi.org/10.1016/j.atmosenv.2014.11.070, 2015.
Sharma, S., Chatani, S., Mahtta, R., Goel, A., and Kumar, A.: Sensitivity analysis of ground level ozone in India using WRF-CMAQ models, Atmos. Environ., 131, 29–40, https://doi.org/10.1016/j.atmosenv.2016.01.036, 2016.
Shen, H., Huang, Y., Wang, R., Zhu, D., Li, W., Shen, G., Wang, B., Zhang, Y., Chen, Y., Lu, Y., Chen, H., Li, T., Sun, K., Li, B., Liu, W., Liu, J., and Tao, S.: Global atmospheric emissions of polycyclic aromatic hydrocarbons from 1960 to 2008 and future predictions, Environ. Sci. Technol., 47, 6415–6424, https://doi.org/10.1021/es400857z, 2013.
Shrivastava, M., Cappa, C. D., Fan, J., Goldstein, A. H., Guenther, A. B., Jimenez, J. L., Kuang, C., Laskin, A., Martin, S. T., Ng, N. L., Petaja, T., Pierce, J. R., Rasch, P. J., Roldin, P., Seinfeld, J. H., Shilling, J., Smith, J. N., Thornton, J. A., Volkamer, R., Wang, J., Worsnop, D. R., Zaveri, R. A., Zelenyuk, A., and Zhang, Q.: Recent advances in understanding secondary organic aerosol: Implications for global climate forcing, Rev. Geophys., 55, 509–559, https://doi.org/10.1002/2016rg000540, 2017.
Singer, B. C., Kirchstetter, T. W., Harley, R. A., Kendall, G. R., and Hesson, J. M.: A fuel-based approach to estimating motor vehicle cold-start emissions, J. Air Waste Manage. Assoc., 49, 125–135, https://doi.org/10.1080/10473289.1999.10463785, 1999.
Stewart, G. J., Nelson, B. S., Acton, W. J. F., Vaughan, A. R., Hopkins, J. R., Yunus, S. S., Hewitt, C. N., Wild, O., Nemitz, E., Gadi, R., Sahu, L. K., Mandal, T. K., Guijar, B. R., Rickard, A. R., Lee, J. D., and Hamilton, J. F.: Emission estimates and inventories of non-methane volatile organic compounds from anthropogenic burning sources in India, Atmos. Environ. X, 11, 100115, https://doi.org/10.1016/j.aeaoa.2021.100115, 2021.
Strum, M. and Scheffe, R.: National review of ambient air toxics observations, J. Air Waste Manag. Assoc., 66, 120–133, https://doi.org/10.1080/10962247.2015.1076538, 2016.
Tran, H., Polka, E., Buonocore, J. J., Roy, A., Trask, B., Hull, H., and Arunachalam, S.: Air quality and health impacts of onshore oil and gas flaring and venting activities estimated using refined satellite-based emissions, GeoHealth, 8, e2023GH000938, https://doi.org/10.1029/2023gh000938, 2024.
United Nation Statistics Division (UNSD): UNdata, https://data.un.org/Default.aspx (last access: 7 March 2024), 2022a.
United Nation Statistics Division (UNSD): UN Statistical Yearbooks 1970–2021, https://unstats.un.org/UNSDWebsite/Publications/StatisticalYearbook/ (last access: 20 June 2022), 2022b.
United Nation Statistics Division (UNSD): UN Comtrade Database, https://comtradeplus.un.org/ (last access: 10 March 2024), 2022c.
United Nations (UN): World Population Prospects 2021, United Nations (UN), Department of Economic and Social Affairs, Population Division, https://population.un.org/wpp/ (last access: 15 March 2022), 2021.
United Nations Framework Convention on Climate Change (UNFCCC): National Inventory Submissions, https://di.unfccc.int/flex_annex1 (last access: 7 March 2024), 2022.
United States Geological Survey (USGS): Nitrogen Statistics and Information, https://www.usgs.gov/centers/national-minerals-information-center/nitrogen-statistics-and-information (last access: 30 January 2023), 2022.
US Environmental Protection Agency (EPA): Compilation of air pollutant emission factors from stationary sources (AP-42), Chapter 1–13, https://www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-air-emissions-factors-stationary-sources (last access: 23 December 2023), 1995.
US Environmental Protection Agency (EPA): Procedures document for national emission inventory criteria air pollutants 1985–1999, https://www.epa.gov/sites/default/files/2015-07/documents/aerr_final_rule.pdf (last access: 23 August 2023), 2001.
US Environmental Protection Agency (EPA): Exhaust and crankcase emission factors for nonroad compression-ignition engines in MOVES3.0.2, https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1013KWQ.pdf (last access: 23 November 2023), 2021.
US Environmental Protection Agency (EPA): National Emissions Inventory (NEI), https://www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei (last access: 20 March 2024), 2023.
von Schneidemesser, E., Coates, J., Van Der Gon, H. D., Visschedijk, A. J. H., and Butler, T. M.: Variation of the NMVOC speciation in the solvent sector and the sensitivity of modelled tropospheric ozone, Atmos. Environ., 135, 59–72, https://doi.org/10.1016/j.atmosenv.2016.03.057, 2016.
von Schneidemesser, E., McDonald, B. C., Denier van der Gon, H., Crippa, M., Guizzardi, D., Borbon, A., Dominutti, P., Huang, G., Jansens-Maenhout, G., Li, M., Ou-Yang, C., Tisinai, S., and Wang, J. L.: Comparing urban anthropogenic NMVOC measurements with representation in emission inventories-a global perspective, J. Geophys. Res. Atmos., e2022JD037906, https://doi.org/10.1029/2022jd037906, 2023.
West, J. J., Fiore, A. M., Naik, V., Horowitz, L. W., Schwarzkopf, M. D., and Mauzerall, D. L.: Ozone air quality and radiative forcing consequences of changes in ozone precursor emissions, Geophys. Res. Lett., 34, https://doi.org/10.1029/2006gl029173, 2007.
World Steel Association: Steel Statistical Yearbooks 1978–2020, https://worldsteel.org/publications/bookshop/ (last access: 1 August 2022), 2021.
Wu, R., Bo, Y., Li, J., Li, L., Li, Y., and Xie, S.: Method to establish the emission inventory of anthropogenic volatile organic compounds in China and its application in the period 2008–2012, Atmos. Environ., 127, 244–254, https://doi.org/10.1016/j.atmosenv.2015.12.015, 2016.
Wu, W., Fu, T. M., Arnold, S. R., Spracklen, D. V., Zhang, A., Tao, W., Wang, X., Hou, Y., Mo, J., Chen, J., Li, Y., Feng, X., Lin, H., Huang, Z., Zheng, J., Shen, H., Zhu, L., Wang, C., Ye, J., and Yang, X.: Temperature-dependent evaporative anthropogenic VOC emissions significantly exacerbate regional ozone pollution, Environ. Sci. Technol., 58, 5430–5441, https://doi.org/10.1021/acs.est.3c09122, 2024.
Xiong, Y., Du, K., and Huang, Y.: One-third of global population at cancer risk due to elevated volatile organic compounds levels, npj Clim. Atmos. Sci., 7, 54, https://doi.org/10.1038/s41612-024-00598-1, 2024.
Xu, R.: MEIC-global-NMVOC emissions, Zenodo [data set], https://doi.org/10.5281/zenodo.14978149, 2025.
Xu, R., Tong, D., Davis, S. J., Qin, X., Cheng, J., Shi, Q., Liu, Y., Chen, C., Yan, L., Yan, X., Wang, H., Zheng, D., He, K., and Zhang, Q.: Plant-by-plant decarbonization strategies for the global steel industry, Nat. Clim. Change, 13, 1067–1074, https://doi.org/10.1038/s41558-023-01808-z, 2023.
Xu, R., Tong, D., Xiao, Q., Qin, X., Chen, C., Yan, L., Cheng, J., Cui, C., Hu, H., Liu, W., Yan, X., Wang, H., Liu, X., Geng, G., Lei, Y., Guan, D., He, K., and Zhang, Q.: MEIC-global-CO2: A new global CO2 emission inventory with highly-resolved source category and sub-country information, Sci. China Earth Sci., 67, 450–465, https://doi.org/10.1007/s11430-023-1230-3, 2024.
Yan, L., Zhang, Q., Zheng, B., and He, K.: Modeling fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles in 1970–2020, Earth Syst. Sci. Data, 16, 4497–4509, https://doi.org/10.5194/essd-16-4497-2024, 2024.
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.
Zauli-Sajani, S., Thunis, P., Pisoni, E., Bessagnet, B., Monforti-Ferrario, F., De Meij, A., Pekar, F., and Vignati, E.: Reducing biomass burning is key to decrease PM2.5 exposure in European cities, Sci. Rep., 14, 10210, https://doi.org/10.1038/s41598-024-60946-2, 2024.
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.
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., 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, 2017.
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., 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.
Short summary
In this study, we developed a new global emission inventory for non-methane volatile organic compounds (NMVOC) for the period of 1970–2020, with a focus on improving the representation of NMVOC-emission-related technologies. Our analysis revealed that activity growth, technology advancements, and policy-driven emission controls were key driving forces of NMVOC emission changes, but their roles were different across sectors and regions.
In this study, we developed a new global emission inventory for non-methane volatile organic...
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