Articles | Volume 25, issue 4
https://doi.org/10.5194/acp-25-2291-2025
© 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-25-2291-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Feb 2025
Research article |
| 21 Feb 2025
| 21 Feb 2025
Identifying missing sources and reducing NOx emissions uncertainty over China using daily satellite data and a mass-conserving method
Lingxiao Lu
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Shanxi Key Laboratory of Environmental Remote Sensing Applications, China University of Mining and Technology, Xuzhou 221116, China
Jason Blake Cohen
CORRESPONDING AUTHOR
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Shanxi Key Laboratory of Environmental Remote Sensing Applications, China University of Mining and Technology, Xuzhou 221116, China
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Shanxi Key Laboratory of Environmental Remote Sensing Applications, China University of Mining and Technology, Xuzhou 221116, China
Xiaolu Li
Shanxi Key Laboratory of Environmental Remote Sensing Applications, China University of Mining and Technology, Xuzhou 221116, China
School of Geographic Sciences, Taiyuan Normal University, Jinzhong 030619, China
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Shanxi Key Laboratory of Environmental Remote Sensing Applications, China University of Mining and Technology, Xuzhou 221116, China
Related authors
Bo Zheng, Jason Blake Cohen, Lingxiao Lu, Wei Hu, Pravash Tiwari, Simone Lolli, Andrea Garzelli, Hui Su, and Kai Qin
EGUsphere, https://doi.org/10.5194/egusphere-2025-1446, https://doi.org/10.5194/egusphere-2025-1446, 2025
Short summary
Short summary
This study provides TROPOMI with a new methane emission estimation method that can accurately identify emission sources. Our results generate non-negative emission datasets using objective selection and filtering methods. The results include lower minimum emission thresholds for all power grids and fewer false positives. The new method provides more robust emission quantification in the face of data uncertainty, going beyond traditional plume identification and background subtraction.
Fan Lu, Kai Qin, Jason Blake Cohen, Qin He, Pravash Tiwari, Wei Hu, Chang Ye, Yanan Shan, Qing Xu, Shuo Wang, and Qiansi Tu
Atmos. Chem. Phys., 25, 5837–5856, https://doi.org/10.5194/acp-25-5837-2025, https://doi.org/10.5194/acp-25-5837-2025, 2025
Short summary
Short summary
This work describes a field campaign and new fast emissions estimation approach to attribute methane from a large known and previously unknown coal mine in Shanxi, China. The emissions computed are shown to be larger than known oil and gas sources, indicating that methane from coal mines may play a larger role in the global methane budget. The results are found to be slightly larger than or similar to satellite observational campaigns over the same region.
Bo Zheng, Jason Blake Cohen, Lingxiao Lu, Wei Hu, Pravash Tiwari, Simone Lolli, Andrea Garzelli, Hui Su, and Kai Qin
EGUsphere, https://doi.org/10.5194/egusphere-2025-1446, https://doi.org/10.5194/egusphere-2025-1446, 2025
Short summary
Short summary
This study provides TROPOMI with a new methane emission estimation method that can accurately identify emission sources. Our results generate non-negative emission datasets using objective selection and filtering methods. The results include lower minimum emission thresholds for all power grids and fewer false positives. The new method provides more robust emission quantification in the face of data uncertainty, going beyond traditional plume identification and background subtraction.
Kai Qin, Hongrui Gao, Xuancen Liu, Qin He, Pravash Tiwari, and Jason Blake Cohen
Earth Syst. Sci. Data, 16, 5287–5310, https://doi.org/10.5194/essd-16-5287-2024, https://doi.org/10.5194/essd-16-5287-2024, 2024
Short summary
Short summary
Satellites have brought new opportunities for monitoring atmospheric NO2, although the results are limited by clouds and other factors, resulting in missing data. This work proposes a new process to obtain reliable data products with high coverage by reconstructing the raw data from multiple satellites. The results are validated in terms of traditional methods as well as variance maximization and demonstrate a good ability to reproduce known polluted and clean areas around the world.
Qiansi Tu, Frank Hase, Kai Qin, Jason Blake Cohen, Farahnaz Khosrawi, Xinrui Zou, Matthias Schneider, and Fan Lu
Atmos. Chem. Phys., 24, 4875–4894, https://doi.org/10.5194/acp-24-4875-2024, https://doi.org/10.5194/acp-24-4875-2024, 2024
Short summary
Short summary
Four-year satellite observations of XCH4 are used to derive CH4 emissions in three regions of China’s coal-rich Shanxi province. The wind-assigned anomalies for two opposite wind directions are calculated, and the estimated emission rates are comparable to the current bottom-up inventory but lower than the CAMS and EDGAR inventories. This research enhances the understanding of emissions in Shanxi and supports climate mitigation strategies by validating emission inventories.
Kai Qin, Wei Hu, Qin He, Fan Lu, and Jason Blake Cohen
Atmos. Chem. Phys., 24, 3009–3028, https://doi.org/10.5194/acp-24-3009-2024, https://doi.org/10.5194/acp-24-3009-2024, 2024
Short summary
Short summary
We compute CH4 emissions and uncertainty on a mine-by-mine basis, including underground, overground, and abandoned mines. Mine-by-mine gas and flux data and 30 min observations from a flux tower located next to a mine shaft are integrated. The observed variability and bias correction are propagated over the emissions dataset, demonstrating that daily observations may not cover the range of variability. Comparisons show both an emissions magnitude and spatial mismatch with current inventories.
Jianping Guo, Jian Zhang, Jia Shao, Tianmeng Chen, Kaixu Bai, Yuping Sun, Ning Li, Jingyan Wu, Rui Li, Jian Li, Qiyun Guo, Jason B. Cohen, Panmao Zhai, Xiaofeng Xu, and Fei Hu
Earth Syst. Sci. Data, 16, 1–14, https://doi.org/10.5194/essd-16-1-2024, https://doi.org/10.5194/essd-16-1-2024, 2024
Short summary
Short summary
A global continental merged high-resolution (PBLH) dataset with good accuracy compared to radiosonde is generated via machine learning algorithms, covering the period from 2011 to 2021 with 3-hour and 0.25º resolution in space and time. The machine learning model takes parameters derived from the ERA5 reanalysis and GLDAS product as input, with PBLH biases between radiosonde and ERA5 as the learning targets. The merged PBLH is the sum of the predicted PBLH bias and the PBLH from ERA5.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
Short summary
Short summary
Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Xiaolu Li, Jason Blake Cohen, Kai Qin, Hong Geng, Xiaohui Wu, Liling Wu, Chengli Yang, Rui Zhang, and Liqin Zhang
Atmos. Chem. Phys., 23, 8001–8019, https://doi.org/10.5194/acp-23-8001-2023, https://doi.org/10.5194/acp-23-8001-2023, 2023
Short summary
Short summary
Remotely sensed NO2 and surface NOx are combined with a mathematical method to estimate daily NOx emissions. The results identify new sources and improve existing estimates. The estimation is driven by three flexible factors: thermodynamics of combustion, chemical loss, and atmospheric transport. The thermodynamic term separates power, iron, and cement from coking, boilers, and aluminum. This work finds three causes for the extremes: emissions, UV radiation, and transport.
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
Short summary
Short summary
Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
Zexia Duan, Zhiqiu Gao, Qing Xu, Shaohui Zhou, Kai Qin, and Yuanjian Yang
Earth Syst. Sci. Data, 14, 4153–4169, https://doi.org/10.5194/essd-14-4153-2022, https://doi.org/10.5194/essd-14-4153-2022, 2022
Short summary
Short summary
Land–atmosphere interactions over the Yangtze River Delta (YRD) in China are becoming more varied and complex, as the area is experiencing rapid land use changes. In this paper, we describe a dataset of microclimate and eddy covariance variables at four sites in the YRD. This dataset has potential use cases in multiple research fields, such as boundary layer parametrization schemes, evaluation of remote sensing algorithms, and development of climate models in typical East Asian monsoon regions.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
Short summary
Short summary
Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Shuo Wang, Jason Blake Cohen, Chuyong Lin, and Weizhi Deng
Atmos. Chem. Phys., 20, 15401–15426, https://doi.org/10.5194/acp-20-15401-2020, https://doi.org/10.5194/acp-20-15401-2020, 2020
Short summary
Short summary
We analyze global measurements of aerosol height from fires. A plume rise model reproduces measurements with a low bias in five regions, while a statistical model based on satellite measurements of trace gasses co-emitted from the fires reproduces measurements without bias in eight regions. We propose that the magnitude of the pollutants emitted may impact their height and subsequent downwind transport. Using satellite data allows better modeling of the global aerosol distribution.
Cited articles
Alcamo, J., Bouwman, A., Edmonds, J., Grubler, A., Morita, T., and Sugandhy, A.: An evaluation of the IPCC IS92 emission scenarios, Clim. Change 1994, 247–304 pp., https://pure.iiasa.ac.at/4465 (last access: 11 February 2025), 1995.
Alvarado, M. J., Logan, J. A., Mao, J., Apel, E., Riemer, D., Blake, D., Cohen, R. C., Min, K.-E., Perring, A. E., Browne, E. C., Wooldridge, P. J., Diskin, G. S., Sachse, G. W., Fuelberg, H., Sessions, W. R., Harrigan, D. L., Huey, G., Liao, J., Case-Hanks, A., Jimenez, J. L., Cubison, M. J., Vay, S. A., Weinheimer, A. J., Knapp, D. J., Montzka, D. D., Flocke, F. M., Pollack, I. B., Wennberg, P. O., Kurten, A., Crounse, J., Clair, J. M. St., Wisthaler, A., Mikoviny, T., Yantosca, R. M., Carouge, C. C., and Le Sager, P.: Nitrogen oxides and PAN in plumes from boreal fires during ARCTAS-B and their impact on ozone: an integrated analysis of aircraft and satellite observations, Atmos. Chem. Phys., 10, 9739–9760, https://doi.org/10.5194/acp-10-9739-2010, 2010.
Amstel, A. V., Olivier, J., and Janssen, L.: Analysis of differences between national inventories and an Emissions Database for Global Atmospheric Research (EDGAR), Environ. Sci. Policy, 2, 275–293, https://doi.org/10.1016/S1462-9011(99)00019-2, 1999.
Bao, X.: Urban rail transit present situation and future development trends in China: Overall analysis based on national policies and strategic plans in 2016–2020, Urban Rail Transit, 4, 1–12, 2018.
Bauwens, M., Compernolle, S., Stavrakou, T., Müller, J. -F., Van Gent, J., Eskes, H., Levelt, P. F., Van Der A, R., Veefkind, J. P., Vlietinck, J., Yu, H., and Zehner, C.: Impact of Coronavirus Outbreak on NO2 Pollution Assessed Using TROPOMI and OMI Observations, Geophys. Res. Lett., 47, e2020GL087978, https://doi.org/10.1029/2020GL087978, 2020.
Bechle, M. J., Millet, D. B., and Marshall, J. D.: Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area, Atmos. Environ., 69, 345–353, 2013.
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.: Megacity Emissions and Lifetimes of Nitrogen Oxides Probed from Space, Science, 333, 1737–1739, https://doi.org/10.1126/science.1207824, 2011.
Beirle, S., Borger, C., Dörner, S., Li, A., Hu, Z., Liu, F., Wang, Y., and Wagner, T.: Pinpointing nitrogen oxide emissions from space, Sci. Adv., 5, eaax9800, https://doi.org/10.1126/sciadv.aax9800, 2019.
Beirle, S., Borger, C., Dörner, S., Eskes, H., Kumar, V., de Laat, A., and Wagner, T.: Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI, Earth Syst. Sci. Data, 13, 2995–3012, https://doi.org/10.5194/essd-13-2995-2021, 2021.
Boersma, K. F., Jacob, D. J., Trainic, M., Rudich, Y., DeSmedt, I., Dirksen, R., and Eskes, H. J.: Validation of urban NO2 concentrations and their diurnal and seasonal variations observed from the SCIAMACHY and OMI sensors using in situ surface measurements in Israeli cities, Atmos. Chem. Phys., 9, 3867–3879, https://doi.org/10.5194/acp-9-3867-2009, 2009.
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., Woo, J., and Klimont, Z.: A technology-based global inventory of black and organic carbon emissions from combustion, J. Geophys. Res.-Atmos., 109, 2003JD003697, https://doi.org/10.1029/2003JD003697, 2004.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K., Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U., Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C. S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, https://doi.org/10.1002/jgrd.50171, 2013.
Brewer, A. W., Mcelroy, C. T., and Kerr, J. B.: Nitrogen Dioxide Concentrations in the Atmosphere, Nature, 246, 129–133, https://doi.org/10.1038/246129a0, 1973.
Cai, B., Cui, C., Zhang, D., Cao, L., Wu, P., Pang, L., Zhang, J., and Dai, C.: China city-level greenhouse gas emissions inventory in 2015 and uncertainty analysis, Appl. Energy, 253, 113579, https://doi.org/10.1016/j.apenergy.2019.113579, 2019.
Carson, R. T., Jeon, Y., and McCubbin, D. R.: The relationship between air pollution emissions and income: US data, Environ. Dev. Econ., 2, 433–450, 1997.
Chang, S. and Kim, W. B.: The economic performance and regional systems of China's cities, Rev. Urban Reg. Dev. Stud., 6, 58–77, 1994.
Charfeddine, L. and Kahia, M.: Impact of renewable energy consumption and financial development on CO2 emissions and economic growth in the MENA region: a panel vector autoregressive (PVAR) analysis, Renew. Energy, 139, 198–213, 2019.
Chen, T.-M., Kuschner, W. G., Gokhale, J., and Shofer, S.: Outdoor air pollution: nitrogen dioxide, sulfur dioxide, and carbon monoxide health effects, Am. J. Med. Sci., 333, 249–256, 2007.
Cohen, J. B.: Quantifying the occurrence and magnitude of the Southeast Asian fire climatology, Environ. Res. Lett., 9, 114018, https://doi.org/10.1088/1748-9326/9/11/114018, 2014.
Cohen, J. B. and Prinn, R. G.: Development of a fast, urban chemistry metamodel for inclusion in global models, Atmos. Chem. Phys., 11, 7629–7656, https://doi.org/10.5194/acp-11-7629-2011, 2011.
Cohen, J. B. and Wang, C.: Estimating global black carbon emissions using a top-down Kalman Filter approach, J. Geophys. Res.-Atmos., 119, 307–323, https://doi.org/10.1002/2013JD019912, 2014.
Cohen, J. B., Prinn, R. G., and Wang, C.: The impact of detailed urban-scale processing on the composition, distribution, and radiative forcing of anthropogenic aerosols, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011GL047417, 2011.
Cohen, J. B., Lecoeur, E., and Hui Loong Ng, D.: Decadal-scale relationship between measurements of aerosols, land-use change, and fire over Southeast Asia, Atmos. Chem. Phys., 17, 721–743, https://doi.org/10.5194/acp-17-721-2017, 2017.
Collins, W. J., Fry, M. M., Yu, H., Fuglestvedt, J. S., Shindell, D. T., and West, J. J.: Global and regional temperature-change potentials for near-term climate forcers, Atmos. Chem. Phys., 13, 2471–2485, https://doi.org/10.5194/acp-13-2471-2013, 2013.
Copernicus: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2025.
Crutzen, P.: The influence of nitrogen oxides on the atmospheric ozone content, Q. J. Roy. Meteor. Soc., 96, 320–325, 1970.
Dados, N. and Connell, R.: The Global South, Contexts, 11, 12–13, https://doi.org/10.1177/1536504212436479, 2012.
De Foy, B., Wilkins, J. L., Lu, Z., Streets, D. G., and Duncan, B. N.: Model evaluation of methods for estimating surface emissions and chemical lifetimes from satellite data, Atmos. Environ., 98, 66–77, https://doi.org/10.1016/j.atmosenv.2014.08.051, 2014.
Deng, W., Cohen, J. B., Wang, S., and Lin, C.: Improving the understanding between climate variability and observed extremes of global NO2 over the past 15 years, Environ. Res. Lett., 16, 054020, https://doi.org/10.1088/1748-9326/abd502, 2021.
Dhakal, S.: Urban energy use and carbon emissions from cities in China and policy implications, Energ. Policy, 37, 4208–4219, 2009.
Ding, K., Huang, X., Ding, A., Wang, M., Su, H., Kerminen, V.-M., Petäjä, T., Tan, Z., Wang, Z., and Zhou, D.: Aerosol-boundary-layer-monsoon interactions amplify semi-direct effect of biomass smoke on low cloud formation in Southeast Asia, Nat. Commun., 12, 6416, https://doi.org/10.1038/s41467-021-26728-4, 2021.
Drysdale, W. S., Vaughan, A. R., Squires, F. A., Cliff, S. J., Metzger, S., Durden, D., Pingintha-Durden, N., Helfter, C., Nemitz, E., Grimmond, C. S. B., Barlow, J., Beevers, S., Stewart, G., Dajnak, D., Purvis, R. M., and Lee, J. D.: Eddy covariance measurements highlight sources of nitrogen oxide emissions missing from inventories for central London, Atmos. Chem. Phys., 22, 9413–9433, https://doi.org/10.5194/acp-22-9413-2022, 2022.
EPMAP (Environmental Protection Map): Permit Data, EPMAP [data set], https://data.epmap.org/product/permit (last access: 11 February 2025), 2025 (in Chinese).
European Commission Joint Research Centre: GHG emissions of all world: 2021 report., Publications Office, LU, JRC126363, https://doi.org/10.2760/173513, 2021.
European Space Agency: Sentinel-5P level 2 nitrogen dioxide (NO2), Copernicus Sentinel Missions [data set], https://documentation.dataspace.copernicus.eu/Data/SentinelMissions/Sentinel5P.html#sentinel-5p-level-2-nitrogen-dioxide (last access: 11 February 2025), 2025.
Evangeliou, N., Thompson, R. L., Eckhardt, S., and Stohl, A.: Top-down estimates of black carbon emissions at high latitudes using an atmospheric transport model and a Bayesian inversion framework, Atmos. Chem. Phys., 18, 15307–15327, https://doi.org/10.5194/acp-18-15307-2018, 2018.
Geddes, J. A. and Murphy, J. G.: Observations of reactive nitrogen oxide fluxes by eddy covariance above two midlatitude North American mixed hardwood forests, Atmos. Chem. Phys., 14, 2939–2957, https://doi.org/10.5194/acp-14-2939-2014, 2014.
Giglio, L., Randerson, J. T., and Van Der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res.-Biogeosci., 118, 317–328, https://doi.org/10.1002/jgrg.20042, 2013.
Haas, J. and Ban, Y.: Urban growth and environmental impacts in Jing-Jin-Ji, the Yangtze, River Delta and the Pearl River Delta, Int. J. Appl. Earth Obs. Geoinformation, 30, 42–55, https://doi.org/10.1016/j.jag.2013.12.012, 2014.
Haszpra, L., Hidy, D., Taligás, T., and Barcza, Z.: First results of tall tower based nitrous oxide flux monitoring over an agricultural region in Central Europe, Atmos. Environ., 176, 240–251, https://doi.org/10.1016/j.atmosenv.2017.12.035, 2018.
He, Q., Qin, K., Cohen, J. B., Li, D., and Kim, J.: Quantifying uncertainty in ML‐derived atmosphere remote sensing: Hourly surface NO2 estimation with GEMS, Geophys. Res. Lett., e2024GL110468, https://doi.org/10.1029/2024GL110468, 2024.
Henderson, B. H., Pinder, R. W., Crooks, J., Cohen, R. C., Carlton, A. G., Pye, H. O. T., and Vizuete, W.: Combining Bayesian methods and aircraft observations to constrain the HO. + NO2 reaction rate, Atmos. Chem. Phys., 12, 653–667, https://doi.org/10.5194/acp-12-653-2012, 2012.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Rozum, I.: ERA5 hourly data on single levels from 1979 to present, Copernic. Clim. Change Serv. (C3s) Clim. Data Store (Cds), 10, https://doi.org/10.24381/cds.bd0915c6, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Schepers, D.: The ERA5 global reanalysis, Q. J. R. Meteorol. Soc., 146, 1999–2049, 2020.
Holmes, C. D., Prather, M. J., Søvde, O. A., and Myhre, G.: Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions, Atmos. Chem. Phys., 13, 285–302, https://doi.org/10.5194/acp-13-285-2013, 2013.
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, 2012.
Huang, Z., Zhong, Z., Sha, Q., Xu, Y., Zhang, Z., Wu, L., Wang, Y., Zhang, L., Cui, X., and Tang, 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.
Jacob, D. J., Heikes, E., Fan, S., Logan, J. A., Mauzerall, D., Bradshaw, J., Singh, H., Gregory, G., Talbot, R., and Blake, D.: Origin of ozone and NOx in the tropical troposphere: A photochemical analysis of aircraft observations over the South Atlantic basin, J. Geophys. Res.-Atmos., 101, 24235–24250, 1996.
Jin, X., Zhu, Q., and Cohen, R. C.: Direct estimates of biomass burning NOx emissions and lifetimes using daily observations from TROPOMI, Atmos. Chem. Phys., 21, 15569–15587, https://doi.org/10.5194/acp-21-15569-2021, 2021.
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.
Karl, T., Graus, M., Striednig, M., Lamprecht, C., Hammerle, A., Wohlfahrt, G., Held, A., Von Der Heyden, L., Deventer, M. J., Krismer, A., Haun, C., Feichter, R., and Lee, J.: Urban eddy covariance measurements reveal significant missing NOx emissions in Central Europe, Sci. Rep., 7, 2536, https://doi.org/10.1038/s41598-017-02699-9, 2017.
Karl, T., Lamprecht, C., Graus, M., Cede, A., Tiefengraber, M., Vila-Guerau De Arellano, J., Gurarie, D., and Lenschow, D.: High urban NOx triggers a substantial chemical downward flux of ozone, Sci. Adv., 9, eadd2365, https://doi.org/10.1126/sciadv.add2365, 2023.
Kong, H., Lin, J., Chen, L., Zhang, Y., Yan, Y., Liu, M., Ni, R., Liu, Z., and Weng, H.: Considerable Unaccounted Local Sources of NOx Emissions in China Revealed from Satellite, Environ. Sci. Technol., 56, 7131–7142, 2022.
Kong, H., Lin, J., Zhang, Y., Li, C., Xu, C., Shen, L., Liu, X., Yang, K., Su, H., and Xu, W.: High natural nitric oxide emissions from lakes on Tibetan Plateau under rapid warming, Nat. Geosci., 16, 474–477, 2023.
Lamsal, L. N., Krotkov, N. A., Celarier, E. A., Swartz, W. H., Pickering, K. E., Bucsela, E. J., Gleason, J. F., Martin, R. V., Philip, S., Irie, H., Cede, A., Herman, J., Weinheimer, A., Szykman, J. J., and Knepp, T. N.: Evaluation of OMI operational standard NO2 column retrievals using in situ and surface-based NO2 observations, Atmos. Chem. Phys., 14, 11587–11609, https://doi.org/10.5194/acp-14-11587-2014, 2014.
Laughner, J. L. and Cohen, R. C.: Direct observation of changing NOx lifetime in North American cities, Science, 366, 723–727, https://doi.org/10.1126/science.aax6832, 2019.
Le Bris, T., Cadavid, F., Caillat, S., Pietrzyk, S., Blondin, J., and Baudoin, B.: Coal combustion modelling of large power plant, for NOx abatement, Fuel, 86, 2213–2220, https://doi.org/10.1016/j.fuel.2007.05.054, 2007.
Lee, H., Kim, S., Brioude, J., Cooper, O., Frost, G., Kim, C., Park, R., Trainer, M., and Woo, J.: Transport of NOx in East Asia identified by satellite and in situ measurements and Lagrangian particle dispersion model simulations, J. Geophys. Res.-Atmos., 119, 2574–2596, 2014.
Lee, J. D., Helfter, C., Purvis, R. M., Beevers, S. D., Carslaw, D. C., Lewis, A. C., Møller, S. J., Tremper, A., Vaughan, A., and Nemitz, E. G.: Measurement of NOx Fluxes from a Tall Tower in Central London, UK and Comparison with Emissions Inventories, Environ. Sci. Technol., 49, 1025–1034, https://doi.org/10.1021/es5049072, 2015.
Leue, C., Wenig, M., Wagner, T., Klimm, O., Platt, U., and Jähne, B.: Quantitative analysis of NOx emissions from Global Ozone Monitoring Experiment satellite image sequences, J. Geophys. Res.-Atmos., 106, 5493–5505, https://doi.org/10.1029/2000JD900572, 2001.
Li, L., Hoffmann, M. R., and Colussi, A. J.: Role of nitrogen dioxide in the production of sulfate during Chinese haze-aerosol episodes, Environ. Sci. Technol., 52, 2686–2693, 2018.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017.
Li, X., Cohen, J. B., Qin, K., Geng, H., Wu, X., Wu, L., Yang, C., Zhang, R., and Zhang, L.: Remotely sensed and surface measurement- derived mass-conserving inversion of daily NOx emissions and inferred combustion technologies in energy-rich northern China, Atmos. Chem. Phys., 23, 8001–8019, https://doi.org/10.5194/acp-23-8001-2023, 2023a.
Li, X., Cohen, J. B., Qin, K., Geng, H., Wu, X., Wu, L., Yang, C., Zhang, R., and Zhang, L.: Remotely sensed and surface measurement- derived mass-conserving inversion of daily NOx emissions and inferred combustion technologies in energy-rich northern China, Atmos. Chem. Phys., 23, 8001–8019, https://doi.org/10.5194/acp-23-8001-2023, 2023b.
Lin, C., Cohen, J. B., Wang, S., Lan, R., and Deng, W.: A new perspective on the spatial, temporal, and vertical distribution of biomass burning: quantifying a significant increase in CO emissions, Environ. Res. Lett., 15, 104091, https://doi.org/10.1088/1748-9326/abaa7a, 2020.
Liu, E., Wang, Y., Chen, W., Chen, W., and Ning, S.: Evaluating the transformation of China's resource-based cities: An integrated sequential weight and TOPSIS approach, Socioecon. Plann. Sci., 77, 101022, https://doi.org/10.1016/j.seps.2021.101022, 2021.
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, 2016.
Logan, J. A.: Nitrogen oxides in the troposphere: Global and regional budgets, J. Geophys. Res., 88, 10785, https://doi.org/10.1029/JC088iC15p10785, 1983.
Lu, L., Cohen, J., Qin, K., Li, X., and He, Q.: Identifying Missing Sources and Reducing NOx Emissions Uncertainty over China using Daily Satellite Data and a Mass-Conserving Method, Figshare, https://doi.org/10.6084/M9.FIGSHARE.25014023.V1, 2024a.
Lu, L., Cohen, J. B., Qin, K., Tiwari, P., Hu, W., Gao, H., and Zheng, B.: Observational Uncertainty Causes Over Half of Top-Down Nox Emissions Over Northern China to Be Either Biased or Unreliable, https://doi.org/10.2139/ssrn.4984749, 2024b.
Lu, Z., Streets, D. G., de Foy, B., Lamsal, L. N., Duncan, B. N., and Xing, J.: Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005–2014, Atmos. Chem. Phys., 15, 10367–10383, https://doi.org/10.5194/acp-15-10367-2015, 2015.
Lund, M. T., Aamaas, B., Stjern, C. W., Klimont, Z., Berntsen, T. K., and Samset, B. H.: A continued role of short-lived climate forcers under the Shared Socioeconomic Pathways, Earth Syst. Dynam., 11, 977–993, https://doi.org/10.5194/esd-11-977-2020, 2020.
Martin, R. V., Jacob, D. J., Chance, K., Kurosu, T. P., Palmer, P. I., and Evans, M. J.: Global inventory of nitrogen oxide emissions constrained by space-based observations of NO2 columns, J. Geophys. Res.-Atmos., 108, 2003JD003453, https://doi.org/10.1029/2003JD003453, 2003.
Martin, R. V., Sioris, C. E., Chance, K., Ryerson, T. B., Bertram, T. H., Wooldridge, P. J., Cohen, R. C., Neuman, J. A., Swanson, A., and Flocke, F. M.: Evaluation of space-based constraints on global nitrogen oxide emissions with regional aircraft measurements over and downwind of eastern North America, J. Geophys. Res.-Atmos., 111, 2005JD006680, https://doi.org/10.1029/2005JD006680, 2006.
Mijling, B., van der A, R. J., and Zhang, Q.: Regional nitrogen oxides emission trends in East Asia observed from space, Atmos. Chem. Phys., 13, 12003–12012, https://doi.org/10.5194/acp-13-12003-2013, 2013.
Monks, P. S., Archibald, A. T., Colette, A., Cooper, O., Coyle, M., Derwent, R., Fowler, D., Granier, C., Law, K. S., Mills, G. E., Stevenson, D. S., Tarasova, O., Thouret, V., von Schneidemesser, E., Sommariva, R., Wild, O., and Williams, M. L.: Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer, Atmos. Chem. Phys., 15, 8889–8973, https://doi.org/10.5194/acp-15-8889-2015, 2015.
Napelenok, S. L., Pinder, R. W., Gilliland, A. B., and Martin, R. V.: A method for evaluating spatially-resolved NOx emissions using Kalman filter inversion, direct sensitivities, and space-based NO2 observations, Atmos. Chem. Phys., 8, 5603–5614, https://doi.org/10.5194/acp-8-5603-2008, 2008.
Olivier, J. G. J., Bouwman, A. F., Van Der Maas, C. W. M., and Berdowski, J. J. M.: Emission database for global atmospheric research (Edgar), Environ. Monit. Assess., 31–31, 93–106, https://doi.org/10.1007/BF00547184, 1994.
Oreggioni, G. D., Monforti Ferraio, F., Crippa, M., Muntean, M., Schaaf, E., Guizzardi, D., Solazzo, E., Duerr, M., Perry, M., and Vignati, E.: Climate change in a changing world: Socio-economic and technological transitions, regulatory frameworks and trends on global greenhouse gas emissions from EDGAR v.5.0, Glob. Environ. Change, 70, 102350, https://doi.org/10.1016/j.gloenvcha.2021.102350, 2021.
Prather, M. J.: Time scales in atmospheric chemistry: Theory, GWPs for CH4 and CO, and runaway growth, Geophys. Res. Lett., 23, 2597–2600, 1996.
Prinn, R. G.: Development and application of earth system models, P. Natl. Acad. Sci. USA, 110, 3673–3680, 2013.
Qin, K., Lu, L., Liu, J., He, Q., Shi, J., Deng, W., Wang, S., and Cohen, J. B.: Model-free daily inversion of NOx emissions using TROPOMI (MCMFE-NOx) and its uncertainty: Declining regulated emissions and growth of new sources, Remote Sens. Environ., 295, 113720, https://doi.org/10.1016/j.rse.2023.113720, 2023.
Rigby, M., Montzka, S. A., Prinn, R. G., White, J. W., Young, D., O'doherty, S., Lunt, M. F., Ganesan, A. L., Manning, A. J., and Simmonds, P. G.: Role of atmospheric oxidation in recent methane growth, P. Natl. Acad. Sci. USA, 114, 5373–5377, 2017.
Rollins, A. W., Browne, E. C., Min, K.-E., Pusede, S. E., Wooldridge, P. J., Gentner, D. R., Goldstein, A. H., Liu, S., Day, D. A., and Russell, L. M.: Evidence for NOx control over nighttime SOA formation, Science, 337, 1210–1212, 2012.
Russell, A. R., Perring, A. E., Valin, L. C., Bucsela, E. J., Browne, E. C., Wooldridge, P. J., and Cohen, R. C.: A high spatial resolution retrieval of NO2 column densities from OMI: method and evaluation, Atmos. Chem. Phys., 11, 8543–8554, https://doi.org/10.5194/acp-11-8543-2011, 2011.
S5P-PAL Data Portal: TROPOMI PAL V02.03.01 NO2, S5P-PAL Data Portal NO2, ESA [data set], https://data-portal.s5p-pal.com/ (last access: 11 July 2023), 2023.
Sand, M., Berntsen, T. K., von Salzen, K., Flanner, M. G., Langner, J., and Victor, D. G.: Response of Arctic temperature to changes in emissions of short-lived climate forcers, Nat. Clim. Change, 6, 286–289, 2016.
Schwerdt, C.: Modelling NOx-formation in combustion processes, MSc Theses, 45, http://lup.lub.lu.se/student-papers/record/8847808 (last access: 17 February 2025), 2006.
Seinfeld, J. H.: Urban Air Pollution: State of the Science, Science, 243, 745–752, https://doi.org/10.1126/science.243.4892.745, 1989.
Shindell, D., Kuylenstierna, J. C., Vignati, E., van Dingenen, R., Amann, M., Klimont, Z., Anenberg, S. C., Muller, N., Janssens-Maenhout, G., and Raes, F.: Simultaneously mitigating near-term climate change and improving human health and food security, Science, 335, 183–189, 2012.
Stavrakou, T., Müller, J.-F., Bauwens, M., De Smedt, I., Lerot, C., Van Roozendael, M., Coheur, P.-F., Clerbaux, C., Boersma, K. F., Van Der A, R., and Song, Y.: Substantial Underestimation of Post-Harvest Burning Emissions in the North China Plain Revealed by Multi-Species Space Observations, Sci. Rep., 6, 32307, https://doi.org/10.1038/srep32307, 2016.
Sun, K.: Derivation of Emissions From Satellite-Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations, Geophys. Res. Lett., 49, e2022GL101102, https://doi.org/10.1029/2022GL101102, 2022.
Tan, Z., Lu, K., Dong, H., Hu, M., Li, X., Liu, Y., Lu, S., Shao, M., Su, R., and Wang, H.: Explicit diagnosis of the local ozone production rate and the ozone-NOx-VOC sensitivities, Sci. Bull., 63, 1067–1076, 2018.
Tiwari, P., Cohen, J. B., Lu, L., Wang, S., Li, X., Guan, L., Liu, Z., Li, Z., and Qin, K.: Multi-platform observations and constraints reveal overlooked urban sources of black carbon in Xuzhou and Dhaka, Commun. Earth. Environ., 6, 38, https://doi.org/10.1038/s43247-025-02012-x, 2025.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
van Geffen, J., Boersma, K. F., Eskes, H., Sneep, M., ter Linden, M., Zara, M., and Veefkind, J. P.: S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI, Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, 2020.
van Geffen, J., Eskes, H., Compernolle, S., Pinardi, G., Verhoelst, T., Lambert, J.-C., Sneep, M., ter Linden, M., Ludewig, A., Boersma, K. F., and Veefkind, J. P.: Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data, Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022, 2022.
Vaughan, A. R., Lee, J. D., Misztal, P. K., Metzger, S., Shaw, M. D., Lewis, A. C., Purvis, R. M., Carslaw, D. C., Goldstein, A. H., Hewitt, C. N., Davison, B., Beevers, S. D., and Karl, T. G.: Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories, Faraday Discuss., 189, 455–472, https://doi.org/10.1039/C5FD00170F, 2016.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., De Vries, J., Otter, G., Claas, J., Eskes, H., De Haan, J., and Kleipool, Q.: TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications, Remote Sens. Environ., 120, 70–83, 2012.
Wang, S., Streets, D. G., Zhang, Q., He, K., Chen, D., Kang, S., Lu, Z., and Wang, Y.: Satellite detection and model verification of NOx emissions from power plants in Northern China, Environ. Res. Lett., 5, 044007, https://doi.org/10.1088/1748-9326/5/4/044007, 2010.
Wang, S., Cohen, J. B., Lin, C., and Deng, W.: Constraining the relationships between aerosol height, aerosol optical depth and total column trace gas measurements using remote sensing and models, Atmos. Chem. Phys., 20, 15401–15426, https://doi.org/10.5194/acp-20-15401-2020, 2020.
Wang, S., Cohen, J. B., Deng, W., Qin, K., and Guo, J.: Using a New Top-Down Constrained Emissions Inventory to Attribute the Previously Unknown Source of Extreme Aerosol Loadings Observed Annually in the Monsoon Asia Free Troposphere, Earths Fut., 9, e2021EF002167, https://doi.org/10.1029/2021EF002167, 2021.
Wang, S., Cohen, J. B., Wang, X., Chen, W., Deng, W., Tiwari, P., Yang, Y., and Lolli, S.: Observationally constrained mass balance box model analysis of aerosol mitigation potential using fan powered filters, Environ. Res. Commun., 5, 125012, https://doi.org/10.1088/2515-7620/ad1422, 2023.
Wang, Y., Yin, S., Fang, X., and Chen, W.: Interaction of economic agglomeration, energy conservation and emission reduction: Evidence from three major urban agglomerations in China, Energy, 241, 122519, https://doi.org/10.1016/j.energy.2021.122519, 2022.
Wu, F.: China's emergent city-region governance: a new form of state spatial selectivity through state-orchestrated rescaling, Int. J. Urban Reg. Res., 40, 1134–1151, 2016.
Wu, N., Geng, G., Xu, R., Liu, S., Liu, X., Shi, Q., Zhou, Y., Zhao, Y., Liu, H., Song, Y., Zheng, J., Zhang, Q., and He, K.: Development of a high-resolution integrated emission inventory of air pollutants for China, Earth Syst. Sci. Data, 16, 2893–2915, https://doi.org/10.5194/essd-16-2893-2024, 2024.
Yang, C., Xia, R., Li, Q., Liu, H., Shi, T., and Wu, G.: Comparing hillside urbanizations of Beijing-Tianjin-Hebei, Yangtze River Delta and Guangdong–Hong Kong–Macau greater Bay area urban agglomerations in China, Int. J. Appl. Earth Obs. Geoinform., 102, 102460, https://doi.org/10.1016/j.jag.2021.102460, 2021.
Zhang, M., Song, Y., Cai, X., and Zhou, J.: Economic assessment of the health effects related to particulate matter pollution in 111 Chinese cities by using economic burden of disease analysis, J. Environ. Manage., 88, 947–954, 2008.
Zhang, X., van der A, R., Ding, J., Zhang, X., and Yin, Y.: Significant contribution of inland ships to the total NOx emissions along the Yangtze River, Atmos. Chem. Phys., 23, 5587–5604, https://doi.org/10.5194/acp-23-5587-2023, 2023.
Zhao, C. and Wang, Y.: Assimilated inversion of NOx emissions over east Asia using OMI NO2 column measurements, Geophys. Res. Lett., 36, 2008GL037123, https://doi.org/10.1029/2008GL037123, 2009.
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, 2021.
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, 2017.
Zhou, Y., Zhang, Y., Zhao, B., Lang, J., Xia, X., Chen, D., and Cheng, S.: Estimating air pollutant emissions from crop residue open burning through a calculation of open burning proportion based on satellite-derived fire radiative energy, Environ. Pollut., 286, 117477, https://doi.org/10.1016/j.envpol.2021.117477, 2021.
Zhu, L., Jacob, D. J., Mickley, L. J., Marais, E. A., Cohan, D. S., Yoshida, Y., Duncan, B. N., González Abad, G., and Chance, K. V.: Anthropogenic emissions of highly reactive volatile organic compounds in eastern Texas inferred from oversampling of satellite (OMI) measurements of HCHO columns, Environ. Res. Lett., 9, 114004, https://doi.org/10.1088/1748-9326/9/11/114004, 2014.
Zhuang, Z., Li, C., Hsu, W.-L., Gu, S., Hou, X., and Zhang, C.: Spatiotemporal changes in the supply and demand of ecosystem services in China's Huai River basin and their influencing factors, Water, 14, 2559, https://doi.org/10.3390/w14162559, 2022.
Zyrichidou, I., Koukouli, M. E., Balis, D., Markakis, K., Poupkou, A., Katragkou, E., Kioutsioukis, I., Melas, D., Boersma, K. F., and Van Roozendael, M.: Identification of surface NOx emission sources on a regional scale using OMI NO2, Atmos. Environ., 101, 82–93, https://doi.org/10.1016/j.atmosenv.2014.11.023, 2015.
Short summary
This study applies an approach that assimilates NO2 vertical column densities from TROPOMI in a mass-conserving manner and inverts daily NOx emissions, presented over rapidly changing regions in China. Source attribution is quantified by the local thermodynamics of the combustion temperature (NOx/NO2). Emission results identify sources which do not exist in the a priori datasets, especially medium industrial sources located next to the Yangtze River.
This study applies an approach that assimilates NO2 vertical column densities from TROPOMI in a...
Altmetrics
Final-revised paper
Preprint