Articles | Volume 18, issue 2
https://doi.org/10.5194/essd-18-1367-2026
© Author(s) 2026. 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-18-1367-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A gridded (0.1° × 0.1°) methane emission dataset for India for 2023 to redefine global climate studies
Ashirbad Mishra
Dept. of Environmental Science, Berhampur University, India
Poonam Mangaraj
Research Institute for Humanity and Nature, Kyoto, Japan
Sustainable Futures Collaborative (SFC), New Delhi, India
Pallavi Sahoo
Dept. of Environmental Science, Berhampur University, India
Gufran Beig
National Institute of Advanced Studies, Indian Institute of Science-Campus, Bangalore, India
Rajesh Janardanan
Satellite Observation Center, National Institute for Environmental Studies, Tsukuba, Japan
Dept. of Environmental Science, Berhampur University, India
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Saroj Kumar Sahu, Poonam Mangaraj, Gufran Beig, Marianne T. Lund, Bjørn Hallvard Samset, Pallavi Sahoo, and Ashirbad Mishra
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-310, https://doi.org/10.5194/essd-2023-310, 2023
Revised manuscript not accepted
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Elevated emission of particulate matter is not limited to urban areas, led to poor air quality across the country. Emission Inventory is the first line of defensive tools for air quality management and understanding and identification of the source of pollutants. The present work is an attempt to develop a high-resolution (~10 km) national inventory of particulate pollutants in India for 2020 using IPCC methodology. The developed dataset is vital piece of information for mitigation strategies.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Ailish M. Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matilda Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
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Our paper uses novel satellite datasets and high-resolution emissions datasets alongside a back-trajectory model to investigate the balance of local and external sources influencing NOx air pollution changes in Delhi. We find in the post-monsoon season that NOx from local and non-local transport emissions contributes most to poor air quality in Delhi. Therefore, air quality mitigation strategies in Delhi and surrounding regions are used to control this issue.
Saroj Kumar Sahu, Poonam Mangaraj, Gufran Beig, Marianne T. Lund, Bjørn Hallvard Samset, Pallavi Sahoo, and Ashirbad Mishra
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-310, https://doi.org/10.5194/essd-2023-310, 2023
Revised manuscript not accepted
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Elevated emission of particulate matter is not limited to urban areas, led to poor air quality across the country. Emission Inventory is the first line of defensive tools for air quality management and understanding and identification of the source of pollutants. The present work is an attempt to develop a high-resolution (~10 km) national inventory of particulate pollutants in India for 2020 using IPCC methodology. The developed dataset is vital piece of information for mitigation strategies.
Saroj Kumar Sahu, Poonam Mangaraj, and Gufran Beig
Earth Syst. Sci. Data, 15, 3183–3202, https://doi.org/10.5194/essd-15-3183-2023, https://doi.org/10.5194/essd-15-3183-2023, 2023
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The developed emission inventory identifies all the potential anthropogenic sources active in the Delhi NCR. The decadal change (2010–2020) and the changing policies have also been illustrated to observe the modulation in the sectorial emission trend. Emission hotspots with possible source-specific mitigation strategies have also been highlighted to improve the air quality of the Delhi NCR. The provided dataset is a vital tool for air quality and chemical transport modeling studies.
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
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Short summary
This study refines India’s methane inventory, addressing data gaps and improving climate research. It identifies 25 sources, including agriculture, wetlands, and fossil fuels, enhancing India’s global data representation. Emissions peak in the Indo-Gangetic Plain and coastal states, highlighting mitigation priorities. Urban emissions are lower, suggesting underestimation. This dataset helps policymakers design targeted reduction strategies, supporting India’s climate goals and global efforts.
This study refines India’s methane inventory, addressing data gaps and improving climate...
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