Articles | Volume 15, issue 7
https://doi.org/10.5194/essd-15-3183-2023
© Author(s) 2023. 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-15-3183-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
26 Jul 2023
Data description paper |
| 26 Jul 2023
| 26 Jul 2023
Decadal growth in emission load of major air pollutants in Delhi
Saroj Kumar Sahu
CORRESPONDING AUTHOR
Environmental Science, Department of Botany, Utkal University, Bhubaneswar, India
Poonam Mangaraj
CORRESPONDING AUTHOR
Environmental Science, Department of Botany, Utkal University, Bhubaneswar, India
National Institute of Advanced Studies, Indian Institute of Science – Campus, Bangalore, India
Gufran Beig
CORRESPONDING AUTHOR
National Institute of Advanced Studies, Indian Institute of Science – Campus, Bangalore, India
Related authors
Ashirbad Mishra, Poonam Mangaraj, Pallavi Sahoo, Gufran Beig, Rajesh Janardanan, and Saroj Kumar Sahu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-65, https://doi.org/10.5194/essd-2025-65, 2025
Preprint under review for ESSD
Short summary
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.
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
Short summary
Short summary
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.
Ying Chen, Oliver Wild, Edmund Ryan, Saroj Kumar Sahu, Douglas Lowe, Scott Archer-Nicholls, Yu Wang, Gordon McFiggans, Tabish Ansari, Vikas Singh, Ranjeet S. Sokhi, Alex Archibald, and Gufran Beig
Atmos. Chem. Phys., 20, 499–514, https://doi.org/10.5194/acp-20-499-2020, https://doi.org/10.5194/acp-20-499-2020, 2020
Short summary
Short summary
PM2.5 and O3 are two major air pollutants. Some mitigation strategies focusing on reducing PM2.5 may lead to substantial increase in O3. We use statistical emulation combined with atmospheric transport model to perform thousands of sensitivity numerical studies to identify the major sources of PM2.5 and O3 and to develop strategies targeted at both pollutants. Our scientific evidence suggests that regional coordinated emission control is required to mitigate PM2.5 whilst preventing O3 increase.
Ashirbad Mishra, Poonam Mangaraj, Pallavi Sahoo, Gufran Beig, Rajesh Janardanan, and Saroj Kumar Sahu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-65, https://doi.org/10.5194/essd-2025-65, 2025
Preprint under review for ESSD
Short summary
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.
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
Atmos. Chem. Phys., 24, 789–806, https://doi.org/10.5194/acp-24-789-2024, https://doi.org/10.5194/acp-24-789-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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.
Ying Chen, Oliver Wild, Edmund Ryan, Saroj Kumar Sahu, Douglas Lowe, Scott Archer-Nicholls, Yu Wang, Gordon McFiggans, Tabish Ansari, Vikas Singh, Ranjeet S. Sokhi, Alex Archibald, and Gufran Beig
Atmos. Chem. Phys., 20, 499–514, https://doi.org/10.5194/acp-20-499-2020, https://doi.org/10.5194/acp-20-499-2020, 2020
Short summary
Short summary
PM2.5 and O3 are two major air pollutants. Some mitigation strategies focusing on reducing PM2.5 may lead to substantial increase in O3. We use statistical emulation combined with atmospheric transport model to perform thousands of sensitivity numerical studies to identify the major sources of PM2.5 and O3 and to develop strategies targeted at both pollutants. Our scientific evidence suggests that regional coordinated emission control is required to mitigate PM2.5 whilst preventing O3 increase.
Related subject area
Domain: ESSD – Atmosphere | Subject: Energy and Emissions
A daily sunshine duration (SD) dataset in China from Himawari AHI imagery (2016–2023)
Residential heating emissions for the Western Balkans
Four-dimensional aircraft emission inventory dataset of Landing and takeoff cycle in China (2019–2023)
The global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2
Global gridded NOx emissions using TROPOMI observations
In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes
Modeling fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles in 1970–2020
Comparison of observation- and inventory-based methane emissions for eight large global emitters
Constructing a measurement-based spatially explicit inventory of US oil and gas methane emissions (2021)
State of Wildfires 2023–2024
Global Emissions Inventory from Open Biomass Burning (GEIOBB): utilizing Fengyun-3D global fire spot monitoring data
Integrating Point Sources to Map Anthropogenic Atmospheric Mercury Emissions in China, 1978–2021
Development of a high-resolution integrated emission inventory of air pollutants for China
Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil
Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors
A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013–2022)
CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil, and biofuel CO2 emission inventories
A global catalogue of CO2 emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles
Global Carbon Budget 2023
Spatiotemporally resolved emissions and concentrations of styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) in the US Gulf region
High-resolution emission inventory of full-volatility organic compounds from cooking in China during 2015–2021
Global carbon uptake of cement carbonation accounts 1930–2021
A dense station-based, long-term and high-accuracy dataset of daily surface solar radiation in China
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2020
Improved catalog of NOx point source emissions (version 2)
The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies
Indicators of Global Climate Change 2022: annual update of large-scale indicators of the state of the climate system and human influence
Emission trends of air pollutants and CO2 in China from 2005 to 2021
Ten years of 1 Hz solar irradiance observations at Cabauw, the Netherlands, with cloud observations, variability classifications, and statistics
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019
Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data
Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling
Retrievals of XCO2, XCH4 and XCO from portable, near-infrared Fourier transform spectrometer solar observations in Antarctica
Carbon fluxes from land 2000–2020: bringing clarity to countries' reporting
DeepOWT: a global offshore wind turbine data set derived with deep learning from Sentinel-1 data
Zhanhao Zhang, Shibo Fang, and Jiahao Han
Earth Syst. Sci. Data, 17, 1427–1439, https://doi.org/10.5194/essd-17-1427-2025, https://doi.org/10.5194/essd-17-1427-2025, 2025
Short summary
Short summary
We generate a daily sunshine duration dataset in China at a spatial resolution of 5 km using Himawari AHI data from 2016 to 2023 fitted with an Ångström–Prescott model at different days of year (DOYs). These high-resolution sunshine duration data provide important support for accurate radiation resource assessments in China.
Christian Asker, Eef van Dongen, and Olivier Tasse
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-462, https://doi.org/10.5194/essd-2024-462, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Air pollution adversely affects health, ecosystems and infrastructure. In this work we have developed a methodology and created a dataset for describing air pollution sources for heating of individual houses for the Western Balkan region. The dataset has high spatial resolution and can help understand the air pollution situation in the region.
Jianlei Lang, Zekang Yang, Ying Zhou, Chaoyu Wen, and Xiaoqing Cheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-494, https://doi.org/10.5194/essd-2024-494, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This study established a four-dimensional (hourly, 0.03° × 0.03° × 34 height layers) aircraft emission inventory dataset in the Landing and takeoff cycle for China during 2019–2023, considering actual running time and flight trajectory. The dataset reflects unique horizontal and height spatial characteristics and hourly temporal variations of aircraft emissions and the impact of COVID-19 on the emissions, providing essential information for environmental analysis and policy decisions.
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.
Anthony Rey-Pommier, Alexandre Héraud, Frédéric Chevallier, Philippe Ciais, Theodoros Christoudias, Jonilda Kushta, and Jean Sciare
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-410, https://doi.org/10.5194/essd-2024-410, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
In this study, we estimate emissions of nitrogen oxides (NOx) in 2022 at high-resolution at the global scale, using satellite observations. We provide maps of the emissions and identify several types of sources. Our results are similar to the EDGAR emission inventory. However, differences are found in countries with lower observation densities and lower emissions.
Astrid Lampert, Rudolf Hankers, Thomas Feuerle, Thomas Rausch, Matthias Cremer, Maik Angermann, Mark Bitter, Jonas Füllgraf, Helmut Schulz, Ulf Bestmann, and Konrad B. Bärfuss
Earth Syst. Sci. Data, 16, 4777–4792, https://doi.org/10.5194/essd-16-4777-2024, https://doi.org/10.5194/essd-16-4777-2024, 2024
Short summary
Short summary
We conducted flights above the North Sea and investigated changes in the wind field. The research aircraft measured wind speed, wind direction, temperature, humidity and sea surface at high resolution. Wind parks reduce the wind speed, and the data help to determine how long it takes for the wind speed to recover. The coast also plays an important role, and the wind speed varies with distance from the coast. The results help in wind park planning and better estimating the energy yield.
Liu Yan, Qiang Zhang, Bo Zheng, and Kebin He
Earth Syst. Sci. Data, 16, 4497–4509, https://doi.org/10.5194/essd-16-4497-2024, https://doi.org/10.5194/essd-16-4497-2024, 2024
Short summary
Short summary
A new database of fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020 is developed with the fleet turnover model built in this study. Based on this database, the evolution of the global vehicle stock over 50 years is analyzed, the dominant emission contributors by vehicle and fuel type are identified, and the age distribution of on-road CO2 emissions is characterized further.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Mark Omara, Anthony Himmelberger, Katlyn MacKay, James P. Williams, Joshua Benmergui, Maryann Sargent, Steven C. Wofsy, and Ritesh Gautam
Earth Syst. Sci. Data, 16, 3973–3991, https://doi.org/10.5194/essd-16-3973-2024, https://doi.org/10.5194/essd-16-3973-2024, 2024
Short summary
Short summary
We review, analyze, and synthesize previous peer-reviewed measurement-based data on facility-level oil and gas methane emissions and use these data to develop a high-resolution spatially explicit inventory of US basin-level and national methane emissions. This work provides an improved assessment of national methane emissions relative to government inventories in support of accurate and comprehensive methane emissions assessment, attribution, and mitigation.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
Short summary
Short summary
This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Yang Liu, Jie Chen, Yusheng Shi, Wei Zheng, Tianchan Shan, and Gang Wang
Earth Syst. Sci. Data, 16, 3495–3515, https://doi.org/10.5194/essd-16-3495-2024, https://doi.org/10.5194/essd-16-3495-2024, 2024
Short summary
Short summary
Open biomass burning has a significant impact on regional and global air quality. To enhance the quantification of global emissions from open biomass burning, we have developed the Global Emissions Inventory from Open Biomass Burning (GEIOBB) dataset, which provides a global daily-scale database at 1 km resolution of multiple pollutant emissions. This database aids global-scale environmental analysis of biomass burning.
Yuying Cui, Qingru Wu, Shuxiao Wang, Kaiyun Liu, Shengyue Li, Zhezhe Shi, Daiwei Ouyang, Zhongyan Li, Qinqin Chen, Changwei Lü, Fei Xie, Yi Tang, Yan Wang, and Jiming Hao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-252, https://doi.org/10.5194/essd-2024-252, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
A comprehensive emission inventory has been developed at a resolution of 0.25°×0.3125° for total mercury (HgT) and each mercury species, namely gaseous elemental mercury (Hg0), gaseous oxidized mercury (HgII), and particulate-bound mercury (HgP). The inventory stems from the Point-source Integrated China Atmospheric Mercury Emission Model, ensuring both temporal and spatial coherence.
Nana Wu, Guannan Geng, Ruochong Xu, Shigan Liu, Xiaodong Liu, Qinren Shi, Ying Zhou, Yu Zhao, Huan Liu, Yu Song, Junyu Zheng, Qiang Zhang, and Kebin He
Earth Syst. Sci. Data, 16, 2893–2915, https://doi.org/10.5194/essd-16-2893-2024, https://doi.org/10.5194/essd-16-2893-2024, 2024
Short summary
Short summary
The commonly used method for developing large-scale air pollutant emission datasets for China faces challenges due to limited availability of detailed parameter information. In this study, we develop an efficient integrated framework to gather such information by harmonizing seven heterogeneous inventories from five research institutions. Emission characterizations are analyzed and validated, demonstrating that the dataset provides more accurate emission magnitudes and spatiotemporal patterns.
Leonardo Hoinaski, Robson Will, and Camilo Bastos Ribeiro
Earth Syst. Sci. Data, 16, 2385–2405, https://doi.org/10.5194/essd-16-2385-2024, https://doi.org/10.5194/essd-16-2385-2024, 2024
Short summary
Short summary
We introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database for air quality studies in Brazil. The database encompasses hourly datasets of meteorology, emission sources, and ambient concentrations of multiple air pollutants covering the Brazilian territory. It combines local inventories, consolidated datasets, and internationally recommended models to provide essential data for developing air pollution control policies, even in data-scarce areas.
Ville-Veikko Paunu, Niko Karvosenoja, David Segersson, Susana López-Aparicio, Ole-Kenneth Nielsen, Marlene Schmidt Plejdrup, Throstur Thorsteinsson, Dam Thanh Vo, Jeroen Kuenen, Hugo Denier van der Gon, Jukka-Pekka Jalkanen, Jørgen Brandt, and Camilla Geels
Earth Syst. Sci. Data, 16, 1453–1474, https://doi.org/10.5194/essd-16-1453-2024, https://doi.org/10.5194/essd-16-1453-2024, 2024
Short summary
Short summary
Air pollution is an important cause of adverse health effects, even in Nordic countries. To assess their health impacts, emission inventories with high spatial resolution are needed. We studied how national data and methods for the spatial distribution of the emissions compare to a European level inventory. For road transport the methods are well established, but for machinery and off-road emissions the current recommendations for the spatial distribution of these emissions should be improved.
Weijun Quan, Zhenfa Wang, Lin Qiao, Xiangdong Zheng, Junli Jin, Yinruo Li, Xiaomei Yin, Zhiqiang Ma, and Martin Wild
Earth Syst. Sci. Data, 16, 961–983, https://doi.org/10.5194/essd-16-961-2024, https://doi.org/10.5194/essd-16-961-2024, 2024
Short summary
Short summary
Radiation components play important roles in various fields such as the Earth’s surface radiation budget, ecosystem productivity, and human health. In this study, a dataset consisting of quality-assured daily data of nine radiation components is presented based on the in situ measurements at the Shangdianzi regional GAW station in China during 2013–2022. The dataset can be applied in the validation of satellite products and numerical models and investigation of atmospheric radiation.
Ruben Urraca, Greet Janssens-Maenhout, Nicolás Álamos, Lucas Berna-Peña, Monica Crippa, Sabine Darras, Stijn Dellaert, Hugo Denier van der Gon, Mark Dowell, Nadine Gobron, Claire Granier, Giacomo Grassi, Marc Guevara, Diego Guizzardi, Kevin Gurney, Nicolás Huneeus, Sekou Keita, Jeroen Kuenen, Ana Lopez-Noreña, Enrique Puliafito, Geoffrey Roest, Simone Rossi, Antonin Soulie, and Antoon Visschedijk
Earth Syst. Sci. Data, 16, 501–523, https://doi.org/10.5194/essd-16-501-2024, https://doi.org/10.5194/essd-16-501-2024, 2024
Short summary
Short summary
CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories providing gridded (0.1×0.1) monthly emissions of anthropogenic CO2. Regional inventories include country-specific information and finer spatial resolution than global inventories. CoCO2-MOSAIC provides harmonized access to these datasets and can be considered as a regionally accepted reference to assess the quality of global inventories, as done in the current paper.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 16, 337–373, https://doi.org/10.5194/essd-16-337-2024, https://doi.org/10.5194/essd-16-337-2024, 2024
Short summary
Short summary
A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical locations. Information on the temporal and vertical distributions of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Chi-Tsan Wang, Bok H. Baek, William Vizuete, Lawrence S. Engel, Jia Xing, Jaime Green, Marc Serre, Richard Strott, Jared Bowden, and Jung-Hun Woo
Earth Syst. Sci. Data, 15, 5261–5279, https://doi.org/10.5194/essd-15-5261-2023, https://doi.org/10.5194/essd-15-5261-2023, 2023
Short summary
Short summary
Hazardous air pollutant (HAP) human exposure studies usually rely on local measurements or dispersion model methods, but those methods are limited under spatial and temporal conditions. We processed the US EPA emission data to simulate the hourly HAP emission patterns and applied the chemical transport model to simulate the HAP concentrations. The modeled HAP results exhibit good agreement (R is 0.75 and NMB is −5.6 %) with observational data.
Zeqi Li, Shuxiao Wang, Shengyue Li, Xiaochun Wang, Guanghan Huang, Xing Chang, Lyuyin Huang, Chengrui Liang, Yun Zhu, Haotian Zheng, Qian Song, Qingru Wu, Fenfen Zhang, and Bin Zhao
Earth Syst. Sci. Data, 15, 5017–5037, https://doi.org/10.5194/essd-15-5017-2023, https://doi.org/10.5194/essd-15-5017-2023, 2023
Short summary
Short summary
This study developed the first full-volatility organic emission inventory for cooking sources in China, presenting high-resolution cooking emissions during 2015–2021. It identified the key subsectors and hotspots of cooking emissions, analyzed emission trends and drivers, and proposed future control strategies. The dataset is valuable for accurately simulating organic aerosol formation and evolution and for understanding the impact of organic emissions on air pollution and climate change.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 15, 4947–4958, https://doi.org/10.5194/essd-15-4947-2023, https://doi.org/10.5194/essd-15-4947-2023, 2023
Short summary
Short summary
This is about global and regional cement process carbon emissions and CO2 uptake calculations from 1930 to 2019. The global cement production is rising to 4.4 Gt, causing processing carbon emission of 1.81 Gt (95% CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95% CI: 19.6–22.6 Gt CO2) has offset 55.2% of cement process CO2 emissions (41.5 Gt, 95% CI: 38.7–47.1 Gt CO2) since 1930.
Wenjun Tang, Junmei He, Jingwen Qi, and Kun Yang
Earth Syst. Sci. Data, 15, 4537–4551, https://doi.org/10.5194/essd-15-4537-2023, https://doi.org/10.5194/essd-15-4537-2023, 2023
Short summary
Short summary
In this study, we have developed a dense station-based, long-term dataset of daily surface solar radiation in China with high accuracy. The dataset consists of estimates of global, direct and diffuse radiation at 2473 meteorological stations from the 1950s to 2021. Validation indicates that our station-based radiation dataset clearly outperforms the satellite-based radiation products. Our dataset will contribute to climate change research and solar energy applications in the future.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
Short summary
Short summary
Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Steffen Beirle, Christian Borger, Adrian Jost, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3051–3073, https://doi.org/10.5194/essd-15-3051-2023, https://doi.org/10.5194/essd-15-3051-2023, 2023
Short summary
Short summary
We present a catalog of nitrogen oxide emissions from point sources (like power plants or metal smelters) based on satellite observations of NO2 combined with meteorological wind fields.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
Short summary
Short summary
This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, https://doi.org/10.5194/essd-15-2279-2023, 2023
Short summary
Short summary
This study compiled China's emission inventory of air pollutants and CO2 during 2005–2021 (ABaCAS-EI v2.0) based on unified emission-source framework. The emission trends and its drivers are analyzed. Key sectors and regions with higher synergistic reduction potential of air pollutants and CO2 are identified. Future control measures are suggested. The dataset and analyses provide insights into the synergistic reduction of air pollutants and CO2 emissions for China and other developing countries.
Wouter B. Mol, Wouter H. Knap, and Chiel C. van Heerwaarden
Earth Syst. Sci. Data, 15, 2139–2151, https://doi.org/10.5194/essd-15-2139-2023, https://doi.org/10.5194/essd-15-2139-2023, 2023
Short summary
Short summary
We describe a dataset of detailed measurements of sunlight reaching the surface, recorded at a rate of one measurement per second for 10 years. The dataset includes detailed information on direct and scattered sunlight; classifications and statistics of variability; and observations of clouds, atmospheric composition, and wind. The dataset can be used to study how the atmosphere influences sunlight variability and to validate models that aim to predict this variability with greater accuracy.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
Short summary
Short summary
This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Akash Biswal, Vikas Singh, Leeza Malik, Geetam Tiwari, Khaiwal Ravindra, and Suman Mor
Earth Syst. Sci. Data, 15, 661–680, https://doi.org/10.5194/essd-15-661-2023, https://doi.org/10.5194/essd-15-661-2023, 2023
Short summary
Short summary
This paper presents detailed emission estimates of on-road traffic exhaust emissions of nine major pollutants for Delhi. We use advanced traffic data and emission factors as a function of speed to estimate emissions for each hour and 100 m × 100 m spatial resolution. We examine the source contribution according to the vehicle, fuel, road and Euro types to identify the most polluting vehicles. These data are useful for high-resolution air quality modelling for developing suitable strategies.
Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
Short summary
Short summary
To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the European Union requires an independent validation of emitted CO2. For this validation, atmospheric measurements of CO2 can be used, together with first-guess estimates of CO2 emissions and uptake. To quickly inform end users, it is imperative that this happens in near real-time. To aid these efforts, we create estimates of European CO2 exchange at high resolution in near real time.
David F. Pollard, Frank Hase, Mahesh Kumar Sha, Darko Dubravica, Carlos Alberti, and Dan Smale
Earth Syst. Sci. Data, 14, 5427–5437, https://doi.org/10.5194/essd-14-5427-2022, https://doi.org/10.5194/essd-14-5427-2022, 2022
Short summary
Short summary
We describe measurements made in Antarctica using an EM27/SUN, a near-infrared, portable, low-resolution spectrometer from which we can retrieve the average atmospheric concentration of several greenhouse gases. We show that these measurements are reliable and comparable to other, similar ground-based measurements. Comparisons to the ESA's Sentinel-5 precursor (S5P) satellite demonstrate the usefulness of these data for satellite validation.
Giacomo Grassi, Giulia Conchedda, Sandro Federici, Raul Abad Viñas, Anu Korosuo, Joana Melo, Simone Rossi, Marieke Sandker, Zoltan Somogyi, Matteo Vizzarri, and Francesco N. Tubiello
Earth Syst. Sci. Data, 14, 4643–4666, https://doi.org/10.5194/essd-14-4643-2022, https://doi.org/10.5194/essd-14-4643-2022, 2022
Short summary
Short summary
Despite increasing attention on the role of land use CO2 fluxes in climate change mitigation, there are large differences in available databases. Here we present the most updated and complete compilation of land use CO2 data based on country submissions to United Nations Framework Convention on Climate Change and explain differences with other datasets. Our dataset brings clarity of land use CO2 fluxes and helps track country progress under the Paris Agreement.
Thorsten Hoeser, Stefanie Feuerstein, and Claudia Kuenzer
Earth Syst. Sci. Data, 14, 4251–4270, https://doi.org/10.5194/essd-14-4251-2022, https://doi.org/10.5194/essd-14-4251-2022, 2022
Short summary
Short summary
The DeepOWT (Deep-learning-derived Offshore Wind Turbines) data set provides offshore wind energy infrastructure locations and their temporal deployment dynamics from July 2016 until June 2021 on a global scale. It differentiates between offshore wind turbines, platforms under construction, and offshore wind farm substations. It is derived by applying deep-learning-based object detection to Sentinel-1 imagery.
Cited articles
Akimoto, H.: Global air quality and pollution, Science, 302, 1716–1719, https://doi.org/10.1126/science.1092666, 2003.
Beig, G., Srinivas, R., Parkhi, N. S., Carmichael, G. R., Singh, S., Sahu, S. K., Rathod, A., and Maji, S.: Anatomy of the winter 2017 air quality emergency in Delhi, Sci. Total Environ., 681, 305–311, https://doi.org/10.1016/j.scitotenv.2019.04.347, 2019.
Beig, G., Sahu, S. K., Singh, V., Tikle, S., Sobhana, S. B., Gargeva, P., Ramakrishna, K., Rathod, A., and Murthy, B. S.: Objective evaluation of stubble emission of North India and quantifying its impact on air quality of Delhi, Sci. Total Environ., 709, 136126, https://doi.org/10.1016/j.scitotenv.2019.136126, 2020.
Beig, G., Sahu, S. K., Anand, V., Bano, S., Maji, S., Rathod, A., Korhale, N., Sobhana, S. B., Parkhi, N., Mangaraj, P., Srinivas, R., Peshin, S. N., Singh, S., Latha, R., Shinde, R., and Trimbake, K.: India's Maiden air quality forecasting framework for megacities of divergent environments: The SAFAR-project, Environ. Modell. Softw., 145, 105204, https://doi.org/10.1016/j.envsoft.2021.105204, 2021.
Chakrabarty, R. K., Pervez, S., Chow, J. C., Watson, J. G., Dewangan, S., Robles, J., and Tian, G.: Funeral pyres in South Asia: Brown carbon aerosol emissions and climate impacts, Environ. Sci. Tech. Let., 1, 44–48, https://doi.org/10.1021/ez4000669, 2013.
Cohen, R., Sexton, K. G., and Yeatts, K. B.: Hazard assessment of United Arab Emirates (UAE) incense smoke, Sci. Total Environ., 458, 176–86, https://doi.org/10.1016/j.scitotenv.2013.03.101, 2013.
Cole-Hunter, T., Johnston, F. H., Marks, G. B., Morawska, L., Morgan, G. G., Overs, M., Porta-Cubas, A., and Cowie, C. T.: The health impacts of waste-to-energy emissions: a systematic review of the literature, Environ. Res. Lett., 15, 123006, https://doi.org/10.1088/1748-9326/abae9f, 2020.
DDA (Delhi Development Authority): Annual Report 2019–20, https://dda.gov.in/sites/default/files/Annual_Report_2019-20_English.pdf (last access: 12 June 2021), 2020.
Delhi Urban Shelter Improvement Board: List of JJ Bastis, https://delhishelterboard.in/main/wp-content/uploads/2019/10/JJBastisList675.pdf (last access: 15 April 2020), 2019.
DGCA (Directorate General of Civil Aviation): Handbook on Civil Aviation Statistics 2019–20, https://www.dgca.gov.in/digigov-portal/?page=4252/4205/sericename, last access: 12 June 2020.
DoT (Department of Telecommunications): Telecom Statistics of India. Economics Research Unit Ministry of Communications, Government of India, New Delhi, https://dot.gov.in/sites/default/files/Telecom Statistics India-2019.pdf?download=1 (last access: 5 September 2021), 2019.
Down to Earth: https://www.downtoearth.org.in/coverage/when-will-india-be-able-to-control-pollution--17950 (last access: 8 June 2022), 2015.
DPCC (Delhi Pollution Control Committee): Status of Solid Waste Management in Delhi, https://www.dpcc.delhigovt.nic.in/solidwastemanagement, last access: 15 March 2020.
GBD (Global Burden of Disease): Burden of disease from the joint effects of household and ambient air pollution for 2016. Version 2. Summary of results, World Health Organization, Geneva Switzerland, https://cdn.who.int/media/docs/default-source/air-quality-database/aqd-2018/ap_joint_effect_bod_results_may2018.pdf (last access: 9 June 2020), 2018.
Guttikunda, S. and Calori, G.: A GIS based emissions inventory at 1 km×1 km spatial resolution for air pollution analysis in Delhi, India, Atmos. Environ., 67, 101–111, https://doi.org/10.1016/j.atmosenv.2012.10.040, 2013.
HEI (Health Effects Institute): State of Global Air/2019. A special report on global exposure to air pollution and its disease burden, ISSN 2578-6873, https://www.stateofglobalair.org/sites/default/files/soga_2019_report.pdf (last access: 10 September 2020), 2019.
HEI (Health Effects Institute): State of Global Air/2020. A special report on global exposure to air pollution and its health impacts, ISSN 2578-6873, https://www.stateofglobalair.org/, last access: 14 September 2020.
India Today: Air quality worsens in Delhi with onset of winter, “severe” in Noida,
https://www.indiatoday.in/india/story/air-quality-worsens-delhi-onset-of-winter-severe-category-noida-
2303441-2022-11-30, last access: 30 November 2022.
IPCC (Intergovernmental Panel on Climate Change): Special Report on Emissions Scenarios, ISBN 0-521-80081, https://www.ipcc.ch/report/emissions-scenarios/ (last access: 27 April 2021), 2000.
Jaiprakash, Habib, G., Kumar, A., Sharma, A., and Haider, M.: On-road emissions of CO, CO2, and NOx from four wheeler and emission estimates for Delhi, J. Environ. Sci., 53, 39–47, https://doi.org/10.1016/j.jes.2016.01.034, 2016.
Kumar, R., Gupta, N., Kumar, D., Mavi, A. K., Singh, K., and Kumar, M.: Monitoring of indoor particulate matter during burning of mosquito coil, incense sticks and dhoop, Indian Journal of Allergy, Asthma and Immunology, 28, 68–73, https://doi.org/10.4103/0972-6691.140770, 2014.
Li, L., Maher, K., Navarre-Sitchler, A., Druhan, J., Meile, C., Lawrence, C., Moore, J., Perdrial, J., Sullivan, P., Thompson, A., Jin, L., Bolton, E. W., Brantley, S. L., Dietrich, W. E., Mayer, K. U., Steefel, C. I., Valocchi, A., Zachara, J., Kocar, B., Mcintosh, J., Tutolo, B. M., Kumar, M., Sonnenthal, E., Bao, C., and Beisman, J.: Expanding the role of reactive transport models in critical zone processes, Earth-Sci. Rev., 165, 280–301, https://doi.org/10.1016/j.earscirev.2016.09.001, 2017.
Mangaraj, P., Sahu, S. K., Beig, G., and Samal, B.: Development and assessment of inventory of air pollutants that deteriorate air quality in Indian Megacity Bengaluru, J. Clean. Prod., 360, 132209, https://doi.org/10.1016/j.jclepro.2022.132209, 2022a.
Mangaraj, P., Sahu, S. K., Beig, G., and Yadav, R.: A comprehensive high-resolution gridded emission inventory of anthropogenic sources of air pollutants in Indian megacity Kolkata, SN Appl. Sci., 4, 117, https://doi.org/10.1007/s42452-022-05001-3, 2022b.
Manisalidis, I., Stavropoulou, E., Stavropoulos, A., and Bezirtzoglou, E.: Environmental and Health Impacts of Air Pollution: A Review, Front. Public Health, 8, 14, https://doi.org/10.3389/fpubh.2020.00014, 2020.
Ministry of Civil Aviation: Annual Report 2019–20, https://www.civilaviation.gov.in/sites/default/files/annual-report-2019-2020.pdf, last access: 12 June 2020.
Mishra, D. and Goyal, P.: Quantitative Assessment of the Emitted Criteria Pollutant in Delhi Urban Area, Aerosol Air Qual. Res., 15, 1601–1612, https://doi.org/10.4209/aaqr.2014.05.0104, 2015.
Molina, L. T., Molina, M. J., Slott, R. S., Kolb, C. E., Gbor, P. K., Meng, F., Singh, R. B., Galvez, O., Sloan, J. J., Anderson, W. P., Tang, X., Hu, M., Xie, S., Shao, M., Zhu, T., Zhang, Y. H., Gurjar, B. R., Artaxo, P. E., Oyola, P., Gramsch, E., Hidalgo, D., and Gertler, A. W.: Air Quality in Selected Megacities, J. Air Waste Manage., 54, 1–73, https://doi.org/10.1080/10473289.2004.10471015, 2004.
Molina, M. J. and Molina, L. T.: Megacities and Atmospheric Pollution, J. Air Waste Manage., 54, 644–680, https://doi.org/10.1080/10473289.2004.10470936, 2004.
MoRTH (Ministry of Road Transport and Highways): Annual Report 2019–20, https://www.morth.nic.in/, last access: 11 September 2020.
MoRTH (Ministry of Road Transport and Highways, Government of India): Notification. G. S. R. 653(E), The Gazette of India: Extraordinary [Part II – Sect. 3(i)], Ministry of Road Transport and Highways, Government of India, New Delhi, India, https://morth.nic.in/Circulars-Notifications-related-to-Vehicle-Scrapping-Policy, last access: 21 December 2021.
NEERI (National Environmental Engineering Research Institute): Air Quality Monitoring, Emission Inventory & Source Apportionment Studies for Delhi, https://cpcb.nic.in/displaypdf.php?id=RGVsaGkucGRm (last access: 21 February 2020), 2010.
Permadi, D. A., Kim Oanh, N. T., and Vautard, R.: Integrated emission inventory and modeling to assess distribution of particulate matter mass and black carbon composition in Southeast Asia, Atmos. Chem. Phys., 18, 2725–2747, https://doi.org/10.5194/acp-18-2725-2018, 2018.
PWD (Public Works Department): Road and Building Construction Works, https://www.pwddelhi.gov.in/Home/ProjectProgress?pwd=Tg3814v+U9lMV5dBcmZueR/JLRTSNPoIqdU52zWDuaG5M+Um4MKP/xsb5s6WOV9t, last access: 12 June 2020.
Rainfall Statistics of India: Hydromet Division, Indian Meteorological Department, Lodi Road, New Delhi, Report No. MoES/IMD/HS/RAINFALL REPORT/30, http://hydro.imd.gov.in/hydrometweb/(S(k1llxc451oipskqly0iiwv55))/PRODUCTS/Publications/Rainfall%20Statistics%20of%20India%20-%202019/Rainfall%20Statistics%20of%20India%20-%202019.pdf, (last access: 15 August 2020), 2019.
SAFAR-Delhi-2010: Development of High Resolution Emission Inventory for National Capital Region Delhi, Ministry of Earth Sciences, Govt. of India, Special Scientific Report, SAFAR-2010A, http://safar.tropmet.res.in/source.pdf (last access: 1 September 2022), 2010.
SAFAR-Delhi-2018: SAFAR-High Resolution Emission Inventory of Megacity Delhi 2018. Ministry of Earth Sciences, Govt. of India, Special Scientific Report, SAFAR-Delhi-2018A, ISSN 0252-1075, http://safar.tropmet.res.in/source.pdf (last access: 1 September 2022), 2018.
Sahu, S. K., Beig, G., and Parkhi, N. S.: Emissions inventory of anthropogenic PM2.5 and PM10 in Delhi during Commonwealth Games 2010, Atmos. Environ., 45, 6180–6190, https://doi.org/10.1016/j.atmosenv.2011.08.014, 2011.
Sahu, S. K., Beig, G., and Parkhi, N.: High Resolution Emission Inventory of NOx and CO for Mega City Delhi, India, Aerosol Air Qual. Res., 15, 1137–1144, https://doi.org/10.4209/aaqr.2014.07.0132, 2015.
Sahu, S. K., Mangaraj, P., Beig, G., Samal, A., Pradhan, C., Dash, S., and Tyagi, B.: Quantifying the high resolution seasonal emission of air pollutants from crop residue burning in India, Environ. Pollut., 286, 117165, https://doi.org/10.1016/j.envpol.2021.117165, 2021.
Sahu, S. K., Mangaraj, P., and Beig, G.: Gridded Surface Emission Data for Delhi-NCR, Version V2, Zenodo [data set], https://doi.org/10.5281/zenodo.7715595, 2023.
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, M. and Dikshit, O.: Comprehensive Study on Air Pollution and Green House Gases (GHGs) in Delhi, https://cerca.iitd.ac.in/uploads/Reports/1576211826iitk.pdf (last access: 5 September 2022), 2016.
Sindhwani, R., Goyal, P., Kumar, S., and Kumar, A.: Anthropogenic Emission Inventory of Criteria Air Pollutants of an Urban Agglomeration – National Capital Region (NCR), Delhi, Aerosol Air Qual. Res., 15, 1681–1697, https://doi.org/10.4209/aaqr.2014.11.0271, 2015.
Singh, V., Sahu, S. K., Kesarkar, A. P., and Biswal, A.: Estimation of high resolution emissions from road transport sector in a megacity Delhi, Urban Climate, 26, 109–120, https://doi.org/10.1016/j.uclim.2018.08.011, 2018.
Stanaway, J. D., Afshin, A., Gakidou, E., et al.: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017, Lancet, 392, 1923–1994, https://doi.org/10.1016/S0140-6736(18)32225-6, 2018.
TERI (The Energy and Resources Institute) and ARAI (The Automotive Research Association of India): Source Apportionment of PM2.5 & PM10 of Delhi NCR for Identification of Major Sources, https://www.teriin.org/sites/default/files/2018-08/Report_SA_AQM-Delhi-NCR_0.pdf (last access: 17 February 2022), 2018.
Transport Department, Govt. of Delhi: https://transport.delhi.gov.in/ (last access: 15 February 2023), 2019.
UNEP (United Nations Environment Programme): Air Pollution in Asia and the Pacific: Science-based solutions, ISBN 978-92-807-3725-7, https://wedocs.unep.org/20.500.11822/26861 (last access: 8 February 2022), 2019.
World Air Quality Report: Region & City PM2.5 Ranking, https://www.iqair.com/world-most-polluted-cities/world-air-quality-report-2019-en.pdf (last access: 8 February 2022), 2019.
World Air Quality Report: Region & City PM2.5 Ranking, https://www.iqair.com/world-most-polluted-cities/world-air-quality-report-2020-en.pdf (last access: 10 February 2022), 2020.
Short summary
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.
The developed emission inventory identifies all the potential anthropogenic sources active in...
Altmetrics
Final-revised paper
Preprint