Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-3413-2020
© Author(s) 2020. 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-12-3413-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
15 Dec 2020
Data description paper |
| 15 Dec 2020
| 15 Dec 2020
A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)
Department of Physics and Atmospheric Science, Dalhousie University,
Halifax, NS, Canada
Department of Energy, Environmental, and Chemical Engineering,
Washington University in St. Louis, St. Louis, MO, USA
Steven J. Smith
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD, USA
Patrick O'Rourke
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, College Park, MD, USA
Kushal Tibrewal
Department of Chemical Engineering, Indian Institute of Technology
Bombay, Mumbai, Maharashtra, India
Chandra Venkataraman
Department of Chemical Engineering, Indian Institute of Technology
Bombay, Mumbai, Maharashtra, India
Eloise A. Marais
School of Physics and Astronomy, University of Leicester, Leicester,
UK
now at: Department of Geography, University College London, London, UK
Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
Monica Crippa
European Commission, Joint Research Centre (JRC), Via E. Fermi 2749
(T.P. 123), 21027 Ispra, Varese, Italy
Michael Brauer
School of Population and Public Health, University of British
Columbia, Vancouver, BC, Canada
Institute for Health Metrics and Evaluation, University of Washington,
Seattle, WA, USA
Randall V. Martin
Department of Energy, Environmental, and Chemical Engineering,
Washington University in St. Louis, St. Louis, MO, USA
Department of Physics and Atmospheric Science, Dalhousie University,
Halifax, NS, Canada
Related authors
Steven J. Smith, Erin E. McDuffie, and Molly Charles
Atmos. Chem. Phys., 22, 13201–13218, https://doi.org/10.5194/acp-22-13201-2022, https://doi.org/10.5194/acp-22-13201-2022, 2022
Short summary
Short summary
Emissions into the atmosphere of greenhouse gases (GHGs) and air pollutants, quantified in emission inventories, impact human health, ecosystems, and the climate. We review how air pollutant and GHG inventory activities have historically been structured and their different uses and requirements. We discuss the benefits of increasing coordination between air pollutant and GHG inventory development efforts, but also caution that there are differences in appropriate methodologies and applications.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
Short summary
Short summary
The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Betty Croft, Randall V. Martin, Richard H. Moore, Luke D. Ziemba, Ewan C. Crosbie, Hongyu Liu, Lynn M. Russell, Georges Saliba, Armin Wisthaler, Markus Müller, Arne Schiller, Martí Galí, Rachel Y.-W. Chang, Erin E. McDuffie, Kelsey R. Bilsback, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 1889–1916, https://doi.org/10.5194/acp-21-1889-2021, https://doi.org/10.5194/acp-21-1889-2021, 2021
Short summary
Short summary
North Atlantic Aerosols and Marine Ecosystems Study measurements combined with GEOS-Chem-TOMAS modeling suggest that several not-well-understood key factors control northwest Atlantic aerosol number and size. These synergetic and climate-relevant factors include particle formation near and above the marine boundary layer top, particle growth by marine secondary organic aerosol on descent, particle formation/growth related to dimethyl sulfide, sea spray aerosol, and ship emissions.
Yiqi Zheng, Joel A. Thornton, Nga Lee Ng, Hansen Cao, Daven K. Henze, Erin E. McDuffie, Weiwei Hu, Jose L. Jimenez, Eloise A. Marais, Eric Edgerton, and Jingqiu Mao
Atmos. Chem. Phys., 20, 13091–13107, https://doi.org/10.5194/acp-20-13091-2020, https://doi.org/10.5194/acp-20-13091-2020, 2020
Short summary
Short summary
This study aims to address a challenge in biosphere–atmosphere interactions: to what extent can biogenic organic aerosol (OA) be modified through human activities? From three surface network observations, we show OA is weakly dependent on sulfate and aerosol acidity in the summer southeast US, on both long-term trends and monthly variability. The results are in strong contrast to a global model, GEOS-Chem, suggesting the need to revisit the representation of aqueous-phase secondary OA formation.
Huirong Yang, Kai Wu, Huizhong Shen, Greet Janssens-Maenhout, Monica Crippa, Diego Guizzardi, and Minqiang Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2025-3914, https://doi.org/10.5194/egusphere-2025-3914, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We compare six major anthropogenic CO2 emission inventories in China during the period 2000–2023 to assess emission trends and uncertainties. National emissions show a clear three‑phase pattern, with uncertainties below 5 % (1σ) at the national scale but much higher at the provincial level (10–50 %, 1σ). High-emission regions often have the largest uncertainties. Our findings support more accurate emission estimates and the verification emission reduction policies.
Bertrand Bessagnet, Narayan Thapa, Dikra Prasad Bajgai, Ravi Sahu, Arshini Saikia, Arineh Cholakian, Laurent Menut, Guillaume Siour, Tenzin Wangchuk, Monica Crippa, and Kamala Gurung
EGUsphere, https://doi.org/10.5194/egusphere-2025-3641, https://doi.org/10.5194/egusphere-2025-3641, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
This study highlights the use of numerical tools at very to support the Air Quality monitoring strategy in the Himalayan valley which suffer from Air Pollution. For the first time ever, a high resolution simulation is performed in Bhutan showing the high PM2.5 concentrations within the valleys and potential contaminations up to the glaciers enhancing climate related risks.
Hui Li, Philippe Ciais, Pramod Kumar, Didier A. Hauglustaine, Frédéric Chevallier, Grégoire Broquet, Dylan B. Millet, Kelley C. Wells, Jinghui Lian, and Bo Zheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-424, https://doi.org/10.5194/essd-2025-424, 2025
Preprint under review for ESSD
Short summary
Short summary
We present the first global, multi-year maps of monthly isoprene emissions (2013–2020) derived from satellite isoprene observations, averaging 456 TgC yr-1. The dataset reveals two emission peaks linked to 2015–2016 El Niño and 2019–2020 extreme heat events, driven mainly by tropical regions such as the Amazon. It highlights the region-specific sensitivity of biogenic isoprene emissions to temperature anomalies, providing new insights into their roles in air quality and climate feedbacks.
Manjola Banja, Monica Crippa, Diego Guizzardi, Marilena Muntean, Federico Pagani, and Enrico Pisoni
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-385, https://doi.org/10.5194/essd-2025-385, 2025
Preprint under review for ESSD
Short summary
Short summary
Global efforts to decrease emissions rely on inventories that differ widely in scope and methodology. Alongside national inventories, independent databases provide yearly globally consistent emission inventories. Comparing independent inventories with countries submissions provides clear and consistent track of the real progress. Improvement of emissions inventories, reporting timelines, and statistical systems are essential to ensure reliable and comparable data.
Rimal Abeed, Audrey Fortems-Cheiney, Grégoire Broquet, Robin Plauchu, Isabelle Pison, Antoine Berchet, Elise Potier, Bo Zheng, Gaëlle Dufour, Adriana Coman, Dilek Savas, Guillaume Siour, Henk Eskes, Beatriz Revilla-Romero, Antony Delavois, and Philippe Ciais
EGUsphere, https://doi.org/10.5194/egusphere-2025-3329, https://doi.org/10.5194/egusphere-2025-3329, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We investigate changes in air pollution from nitrogen oxides NOx (=NO+NO2) across Eastern China from 2019 to 2021, using a satellite-based modelling approach. Our results show a drop in pollution in 2020 in most provinces, and along the China-Mongolia-Russia Economic Corridor. The analysis also captures emission variations during the Lunar New Year. By estimating emissions at the provincial level, the study provides insights into how major events and policy measures influence local air quality.
Yawen Kong, Bo Zheng, and Yuxi Liu
Atmos. Chem. Phys., 25, 5959–5976, https://doi.org/10.5194/acp-25-5959-2025, https://doi.org/10.5194/acp-25-5959-2025, 2025
Short summary
Short summary
Current high-resolution satellite remote sensing technologies provide a unique opportunity to derive timely high-resolution emission data. We developed an emission inversion system to assimilate satellite NO2 data to obtain daily kilometer-scale NOx emission inventories. Our results enhance inventory accuracy, allowing us to capture the effects of pollution control policies on daily emissions (e.g., during COVID-19 lockdowns) and improve fine-scale air quality modeling.
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
Short summary
Short summary
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.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, P. Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gómez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal L. Weagle, and Xi Zhao
Atmos. Chem. Phys., 25, 4665–4702, https://doi.org/10.5194/acp-25-4665-2025, https://doi.org/10.5194/acp-25-4665-2025, 2025
Short summary
Short summary
Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Here, we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the data sets to model output.
William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-188, https://doi.org/10.5194/essd-2025-188, 2025
Preprint under review for ESSD
Short summary
Short summary
This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
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
Short summary
Short summary
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.
Mingrui Ma, Jiachen Cao, Dan Tong, Bo Zheng, and Yu Zhao
Atmos. Chem. Phys., 25, 2147–2166, https://doi.org/10.5194/acp-25-2147-2025, https://doi.org/10.5194/acp-25-2147-2025, 2025
Short summary
Short summary
We combined two global climate change pathways and three national emission control scenarios to analyze the future evolution of reactive nitrogen (Nr) deposition till the 2060s in China with air quality modeling. We show China’s clean air and carbon neutrality policies would overcome the adverse effects of climate change and efficiently reduce Nr deposition. The outflow of Nr fluxes from mainland China to the west Pacific would also be clearly reduced from continuous stringent emission controls.
Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer
EGUsphere, https://doi.org/10.5194/egusphere-2025-438, https://doi.org/10.5194/egusphere-2025-438, 2025
Short summary
Short summary
This study develops the fine mineral dust simulation in GEOS-Chem by: 1) implementing a new dust emission scheme with further refinements; 2) revisiting the size distribution of emitted dust; 3) explicitly tracking fine dust for emission, transport and deposition in 4 size bins; 4) updating the parametrization for below-cloud scavenging. All revisions significantly reduce the overestimation of surface fine dust from 73% to 21% while retaining comparable skill in representing columnar abundance.
Pramod Kumar, Grégoire Broquet, Didier Hauglustaine, Maureen Beaudor, Lieven Clarisse, Martin Van Damme, Pierre Coheur, Anne Cozic, Bo Zheng, Beatriz Revilla Romero, Antony Delavois, and Philippe Ciais
EGUsphere, https://doi.org/10.5194/egusphere-2025-162, https://doi.org/10.5194/egusphere-2025-162, 2025
Short summary
Short summary
Global maps of the NH3 emissions over 2019–2022 are derived using IASI NH3 spaceborne observations, the LMDZ-INCA chemistry-transport model at 1.27°×2.5° resolution and mass balance approach. The average global NH3 emissions over the period are ~98 Tg NH3 yr-1, which is significantly higher than three reference inventories. The analysis provides confidence in the seasonal variability and regional budgets, and provides new insights into NH3 emissions at global and regional scales.
Hui Li, Jiaxin Qiu, and Bo Zheng
Atmos. Chem. Phys., 25, 1949–1963, https://doi.org/10.5194/acp-25-1949-2025, https://doi.org/10.5194/acp-25-1949-2025, 2025
Short summary
Short summary
We conduct a sensitivity analysis with 31 tests on various factors including prior emissions, model resolution, satellite constraint, and other system configurations to assess the vulnerability of emission estimates across temporal, sectoral, and regional dimensions. This reveals the robustness of emissions estimated by this air-pollution-satellite-based CO2 emission inversion system, with relative change between tests and base inversion below 4.0 % for national annual NOx and CO2 emissions.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, 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, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-601, https://doi.org/10.5194/essd-2024-601, 2025
Preprint under review for ESSD
Short summary
Short summary
The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
Chimurkar Navinya, Taveen Singh Kapoor, Gupta Anurag, Chandra Venkataraman, Harish C. Phuleria, and Rajan K. Chakrabarty
Atmos. Chem. Phys., 24, 13285–13297, https://doi.org/10.5194/acp-24-13285-2024, https://doi.org/10.5194/acp-24-13285-2024, 2024
Short summary
Short summary
Brown carbon (BrC) aerosols show an order-of-magnitude variation in their light absorption strength. Our understanding of BrC from real-world biomass burning remains limited, complicating the determination of its radiative impact. Our study reports absorption properties of BrC emitted from four major biomass burning sources using field measurements in India. It develops an absorption parameterization for BrC and examines the spatial variability in BrC's absorption strength across India.
Deepangsu Chatterjee, Randall V. Martin, Chi Li, Dandan Zhang, Haihui Zhu, Daven K. Henze, James H. Crawford, Ronald C. Cohen, Lok N. Lamsal, and Alexander M. Cede
Atmos. Chem. Phys., 24, 12687–12706, https://doi.org/10.5194/acp-24-12687-2024, https://doi.org/10.5194/acp-24-12687-2024, 2024
Short summary
Short summary
We investigate the hourly variation of NO2 columns and surface concentrations by applying the GEOS-Chem model to interpret aircraft and ground-based measurements over the US and Pandora sun photometer measurements over the US, Europe, and Asia. Corrections to the Pandora columns and finer model resolution improve the modeled representation of the summertime hourly variation of total NO2 columns to explain the weaker hourly variation in NO2 columns than at the surface.
Haihui Zhu, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Chi Li, Jun Meng, Christopher R. Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
Atmos. Chem. Phys., 24, 11565–11584, https://doi.org/10.5194/acp-24-11565-2024, https://doi.org/10.5194/acp-24-11565-2024, 2024
Short summary
Short summary
Ambient fine particulate matter (PM2.5) contributes to 4 million deaths globally each year. Satellite remote sensing of aerosol optical depth (AOD), coupled with a simulated PM2.5–AOD relationship (η), can provide global PM2.5 estimations. This study aims to understand the spatial patterns and driving factors of η to guide future measurement and modeling efforts. We quantified η globally and regionally and found that its spatial variation is strongly influenced by aerosol composition.
Brian L. Boys, Randall V. Martin, and Trevor C. VandenBoer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2994, https://doi.org/10.5194/egusphere-2024-2994, 2024
Short summary
Short summary
A widely used dry deposition parameterization for NO2 is updated by including a well-known heterogeneous hydrolysis reaction on deposition surfaces. This mechanistic update eliminates a large low bias of -80 % in simulated NO2 nocturnal deposition velocities evaluated against long-term eddy covariance flux observations over Harvard Forest. We highlight the importance of canopy surface area effects as well as soil NO emission in formulating and evaluating NO2 dry deposition parameterizations.
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.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Short summary
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
Short summary
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Monica Crippa, Diego Guizzardi, Federico Pagani, Marcello Schiavina, Michele Melchiorri, Enrico Pisoni, Francesco Graziosi, Marilena Muntean, Joachim Maes, Lewis Dijkstra, Martin Van Damme, Lieven Clarisse, and Pierre Coheur
Earth Syst. Sci. Data, 16, 2811–2830, https://doi.org/10.5194/essd-16-2811-2024, https://doi.org/10.5194/essd-16-2811-2024, 2024
Short summary
Short summary
Knowing where emissions occur is essential for planning effective emission reduction measures and atmospheric modelling. Disaggregating national emissions over high-resolution grids requires spatial proxies that contain information on the location of different emission sources. This work incorporates state-of-the-art spatial information to improve the spatial representation of global emissions with the Emissions Database for Global Atmospheric Research (EDGAR).
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Antonin Soulie, Claire Granier, Sabine Darras, Nicolas Zilbermann, Thierno Doumbia, Marc Guevara, Jukka-Pekka Jalkanen, Sekou Keita, Cathy Liousse, Monica Crippa, Diego Guizzardi, Rachel Hoesly, and Steven J. Smith
Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, https://doi.org/10.5194/essd-16-2261-2024, 2024
Short summary
Short summary
Anthropogenic emissions are the result of transportation, power generation, industrial, residential and commercial activities as well as waste treatment and agriculture practices. This work describes the new CAMS-GLOB-ANT gridded inventory of 2000–2023 anthropogenic emissions of air pollutants and greenhouse gases. The methodology to generate the emissions is explained and the datasets are analysed and compared with publicly available global and regional inventories for selected world regions.
Fei Liu, Steffen Beirle, Joanna Joiner, Sungyeon Choi, Zhining Tao, K. Emma Knowland, Steven J. Smith, Daniel Q. Tong, Siqi Ma, Zachary T. Fasnacht, and Thomas Wagner
Atmos. Chem. Phys., 24, 3717–3728, https://doi.org/10.5194/acp-24-3717-2024, https://doi.org/10.5194/acp-24-3717-2024, 2024
Short summary
Short summary
Using satellite data, we developed a coupled method independent of the chemical transport model to map NOx emissions across US cities. After validating our technique with synthetic data, we charted NOx emissions from 2018–2021 in 39 cities. Our results closely matched EPA estimates but also highlighted some inconsistencies in both magnitude and spatial distribution. This research can help refine strategies for monitoring and managing air quality.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
Short summary
Short summary
Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
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.
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.
Hamza Ahsan, Hailong Wang, Jingbo Wu, Mingxuan Wu, Steven J. Smith, Susanne Bauer, Harrison Suchyta, Dirk Olivié, Gunnar Myhre, Hitoshi Matsui, Huisheng Bian, Jean-François Lamarque, Ken Carslaw, Larry Horowitz, Leighton Regayre, Mian Chin, Michael Schulz, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Vaishali Naik
Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023, https://doi.org/10.5194/acp-23-14779-2023, 2023
Short summary
Short summary
We examine the impact of the assumed effective height of SO2 injection, SO2 and BC emission seasonality, and the assumed fraction of SO2 emissions injected as SO4 on climate and chemistry model results. We find that the SO2 injection height has a large impact on surface SO2 concentrations and, in some models, radiative flux. These assumptions are a
hiddensource of inter-model variability and may be leading to bias in some climate model results.
Yanshun Li, Randall V. Martin, Chi Li, Brian L. Boys, Aaron van Donkelaar, Jun Meng, and Jeffrey R. Pierce
Atmos. Chem. Phys., 23, 12525–12543, https://doi.org/10.5194/acp-23-12525-2023, https://doi.org/10.5194/acp-23-12525-2023, 2023
Short summary
Short summary
We developed and evaluated processes affecting within-day (diel) variability in PM2.5 concentrations in a chemical transport model over the contiguous US. Diel variability in PM2.5 for the contiguous US is driven by early-morning accumulation into a shallow mixed layer, decreases from mid-morning through afternoon with mixed-layer growth, increases from mid-afternoon through evening as the mixed-layer collapses, and decreases overnight as emissions decrease.
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.
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.
Haihui Zhu, Randall V. Martin, Betty Croft, Shixian Zhai, Chi Li, Liam Bindle, Jeffrey R. Pierce, Rachel Y.-W. Chang, Bruce E. Anderson, Luke D. Ziemba, Johnathan W. Hair, Richard A. Ferrare, Chris A. Hostetler, Inderjeet Singh, Deepangsu Chatterjee, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jack E. Dibb, Joshua S. Schwarz, and Andrew Weinheimer
Atmos. Chem. Phys., 23, 5023–5042, https://doi.org/10.5194/acp-23-5023-2023, https://doi.org/10.5194/acp-23-5023-2023, 2023
Short summary
Short summary
Particle size of atmospheric aerosol is important for estimating its climate and health effects, but simulating atmospheric aerosol size is computationally demanding. This study derives a simple parameterization of the size of organic and secondary inorganic ambient aerosol that can be applied to atmospheric models. Applying this parameterization allows a better representation of the global spatial pattern of aerosol size, as verified by ground and airborne measurements.
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.
Peng Wang, Ruhan Zhang, Shida Sun, Meng Gao, Bo Zheng, Dan Zhang, Yanli Zhang, Gregory R. Carmichael, and Hongliang Zhang
Atmos. Chem. Phys., 23, 2983–2996, https://doi.org/10.5194/acp-23-2983-2023, https://doi.org/10.5194/acp-23-2983-2023, 2023
Short summary
Short summary
In China, the number of vehicles has jumped significantly in the last decade. This caused severe traffic congestion and aggravated air pollution. In this study, we developed a new temporal allocation approach to quantify the impacts of traffic congestion. We found that traffic congestion worsens air quality and the health burden across China, especially in the urban clusters. More effective and comprehensive vehicle emission control policies should be implemented to improve air quality in China.
Chi Li, Randall V. Martin, Ronald C. Cohen, Liam Bindle, Dandan Zhang, Deepangsu Chatterjee, Hongjian Weng, and Jintai Lin
Atmos. Chem. Phys., 23, 3031–3049, https://doi.org/10.5194/acp-23-3031-2023, https://doi.org/10.5194/acp-23-3031-2023, 2023
Short summary
Short summary
Models are essential to diagnose the significant effects of nitrogen oxides (NOx) on air pollution. We use an air quality model to illustrate the variability of NOx resolution-dependent simulation biases; how these biases depend on specific chemical environments, driving mechanisms, and vertical variabilities; and how these biases affect the interpretation of satellite observations. High-resolution simulations are thus critical to accurately interpret NOx and its relevance to air quality.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev., 16, 1459–1466, https://doi.org/10.5194/gmd-16-1459-2023, https://doi.org/10.5194/gmd-16-1459-2023, 2023
Short summary
Short summary
We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry–climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated with aviation ozone is 7.6 % higher when using the less recent version of the data.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, and Bo Zheng
Atmos. Chem. Phys., 23, 789–807, https://doi.org/10.5194/acp-23-789-2023, https://doi.org/10.5194/acp-23-789-2023, 2023
Short summary
Short summary
The large uncertainties in OH simulated by atmospheric chemistry models hinder accurate estimates of CH4 chemical loss through the bottom-up method. This study presents a new approach based on OH precursor observations and a chemical box model to improve the tropospheric OH distributions simulated by atmospheric chemistry models. Through this approach, both the global OH burden and the corresponding methane chemical loss reach consistency with the top-down method based on MCF inversions.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
Short summary
Short summary
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
Short summary
Short summary
Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. 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.
Steven J. Smith, Erin E. McDuffie, and Molly Charles
Atmos. Chem. Phys., 22, 13201–13218, https://doi.org/10.5194/acp-22-13201-2022, https://doi.org/10.5194/acp-22-13201-2022, 2022
Short summary
Short summary
Emissions into the atmosphere of greenhouse gases (GHGs) and air pollutants, quantified in emission inventories, impact human health, ecosystems, and the climate. We review how air pollutant and GHG inventory activities have historically been structured and their different uses and requirements. We discuss the benefits of increasing coordination between air pollutant and GHG inventory development efforts, but also caution that there are differences in appropriate methodologies and applications.
Yawen Kong, Bo Zheng, Qiang Zhang, and Kebin He
Atmos. Chem. Phys., 22, 10769–10788, https://doi.org/10.5194/acp-22-10769-2022, https://doi.org/10.5194/acp-22-10769-2022, 2022
Short summary
Short summary
We developed a Bayesian atmospheric inversion system based on the 4D local ensemble transform Kalman filter (4D-LETKF) algorithm coupled with GEOS-Chem from the latest Orbiting Carbon Observatory-2 (OCO-2) V10r XCO2 retrievals. This is the first adaptation of 4D-LETKF to an OCO-2-based global carbon inversion system. We inferred global gridded carbon fluxes and investigated their magnitudes, variations, and partitioning schemes to understand the global and regional carbon budgets for 2015–2020.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
Short summary
Short summary
The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
Short summary
Short summary
A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Sumanta Sarkhel, Gunter Stober, Jorge L. Chau, Steven M. Smith, Christoph Jacobi, Subarna Mondal, Martin G. Mlynczak, and James M. Russell III
Ann. Geophys., 40, 179–190, https://doi.org/10.5194/angeo-40-179-2022, https://doi.org/10.5194/angeo-40-179-2022, 2022
Short summary
Short summary
A rare gravity wave event was observed on the night of 25 April 2017 over northern Germany. An all-sky airglow imager recorded an upward-propagating wave at different altitudes in mesosphere with a prominent wave front above 91 km and faintly observed below. Based on wind and satellite-borne temperature profiles close to the event location, we have found the presence of a leaky thermal duct layer in 85–91 km. The appearance of this duct layer caused the wave amplitudes to diminish below 91 km.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
Short summary
Short summary
The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Fei Liu, Zhining Tao, Steffen Beirle, Joanna Joiner, Yasuko Yoshida, Steven J. Smith, K. Emma Knowland, and Thomas Wagner
Atmos. Chem. Phys., 22, 1333–1349, https://doi.org/10.5194/acp-22-1333-2022, https://doi.org/10.5194/acp-22-1333-2022, 2022
Short summary
Short summary
In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
Youwen Sun, Hao Yin, Xiao Lu, Justus Notholt, Mathias Palm, Cheng Liu, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 18589–18608, https://doi.org/10.5194/acp-21-18589-2021, https://doi.org/10.5194/acp-21-18589-2021, 2021
Short summary
Short summary
This study uses high-resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method, and the exposure–response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements over the Sichuan Basin in 2020. These unexpected O3 enhancements were induced by meteorological anomalies and caused dramatically high health risks.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
Short summary
Short summary
Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, and Antoon Visschedijk
Earth Syst. Sci. Data, 13, 5311–5335, https://doi.org/10.5194/essd-13-5311-2021, https://doi.org/10.5194/essd-13-5311-2021, 2021
Short summary
Short summary
People worry that growing man-made carbon dioxide (CO2) concentrations lead to climate change. Global models, use of observations, and datasets can help us better understand behaviour of CO2. Here a tool to compute uncertainty in man-made CO2 sources per country per year and month is presented. An example of all sources separated into seven groups (intensive and average energy, industry, humans, ground and air transport, others) is presented. Results will be used to predict CO2 concentrations.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
Short summary
Short summary
We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
Yuqiang Zhang, Drew Shindell, Karl Seltzer, Lu Shen, Jean-Francois Lamarque, Qiang Zhang, Bo Zheng, Jia Xing, Zhe Jiang, and Lei Zhang
Atmos. Chem. Phys., 21, 16051–16065, https://doi.org/10.5194/acp-21-16051-2021, https://doi.org/10.5194/acp-21-16051-2021, 2021
Short summary
Short summary
In this study, we use a global chemical transport model to simulate the effects on global air quality and human health due to emission changes in China from 2010 to 2017. By performing sensitivity analysis, we found that the air pollution control policies not only decrease the air pollutant concentration but also bring significant co-benefits in air quality to downwind regions. The benefits for the improved air pollution are dominated by PM2.5.
Gaëlle Dufour, Didier Hauglustaine, Yunjiang Zhang, Maxim Eremenko, Yann Cohen, Audrey Gaudel, Guillaume Siour, Mathieu Lachatre, Axel Bense, Bertrand Bessagnet, Juan Cuesta, Jerry Ziemke, Valérie Thouret, and Bo Zheng
Atmos. Chem. Phys., 21, 16001–16025, https://doi.org/10.5194/acp-21-16001-2021, https://doi.org/10.5194/acp-21-16001-2021, 2021
Short summary
Short summary
The IASI observations and the LMDZ-OR-INCA model simulations show negative ozone trends in the Central East China region in the lower free (3–6 km column) and the upper free (6–9 km column) troposphere. Sensitivity studies from the model show that the Chinese anthropogenic emissions contribute to more than 50 % in the trend. The reduction in NOx emissions that has occurred since 2013 in China seems to lead to a decrease in ozone in the free troposphere, contrary to the increase at the surface.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
Short summary
Short summary
Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
Short summary
Short summary
The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Youwen Sun, Hao Yin, Cheng Liu, Emmanuel Mahieu, Justus Notholt, Yao Té, Xiao Lu, Mathias Palm, Wei Wang, Changgong Shan, Qihou Hu, Min Qin, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 11759–11779, https://doi.org/10.5194/acp-21-11759-2021, https://doi.org/10.5194/acp-21-11759-2021, 2021
Short summary
Short summary
The variability, sources, and transport of ethane (C2H6) over eastern China from 2015 to 2020 were studied using ground-based Fourier transform infrared (FTIR) spectroscopy and GEOS-Chem simulations. C2H6 variability is driven by both meteorological and emission factors. The reduction in C2H6 in recent years over eastern China points to air quality improvement in China.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
Short summary
Short summary
Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Jun Meng, Randall V. Martin, Paul Ginoux, Melanie Hammer, Melissa P. Sulprizio, David A. Ridley, and Aaron van Donkelaar
Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, https://doi.org/10.5194/gmd-14-4249-2021, 2021
Short summary
Short summary
Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.
Bo Zheng, Qiang Zhang, Guannan Geng, Cuihong Chen, Qinren Shi, Mengshi Cui, Yu Lei, and Kebin He
Earth Syst. Sci. Data, 13, 2895–2907, https://doi.org/10.5194/essd-13-2895-2021, https://doi.org/10.5194/essd-13-2895-2021, 2021
Short summary
Short summary
Here we report the monthly anthropogenic pollutant emissions in China during the COVID-19 pandemic by using a bottom-up approach based on near-real-time data. The COVID lockdowns were estimated to have reduced China's emissions substantially between January and March in 2020, with the largest reduction in February. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to levels comparable to those of 2019 through December 2020.
Youwen Sun, Hao Yin, Yuan Cheng, Qianggong Zhang, Bo Zheng, Justus Notholt, Xiao Lu, Cheng Liu, Yuan Tian, and Jianguo Liu
Atmos. Chem. Phys., 21, 9201–9222, https://doi.org/10.5194/acp-21-9201-2021, https://doi.org/10.5194/acp-21-9201-2021, 2021
Short summary
Short summary
We quantified the variability, source, and transport of urban CO over the Himalayas and Tibetan Plateau (HTP) by using measurement, model simulation, and the analysis of meteorological fields. Urban CO over the HTP is dominated by anthropogenic and biomass burning emissions from local, South Asia and East Asia, and oxidation sources. The decreasing trends in surface CO since 2015 in most cities over the HTP are attributed to the reduction in local and transported CO emissions in recent years.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Jingsha Xu, Di Liu, Xuefang Wu, Tuan V. Vu, Yanli Zhang, Pingqing Fu, Yele Sun, Weiqi Xu, Bo Zheng, Roy M. Harrison, and Zongbo Shi
Atmos. Chem. Phys., 21, 7321–7341, https://doi.org/10.5194/acp-21-7321-2021, https://doi.org/10.5194/acp-21-7321-2021, 2021
Short summary
Short summary
Source apportionment of fine aerosols in an urban site of Beijing used a chemical mass balance (CMB) model. Seven primary sources (industrial/residential coal burning, biomass burning, gasoline/diesel vehicles, cooking and vegetative detritus) explained an average of 75.7 % and 56.1 % of fine OC in winter and summer, respectively. CMB was found to resolve more primary OA sources than AMS-PMF, but the latter apportioned more secondary OA sources.
Youwen Sun, Hao Yin, Cheng Liu, Lin Zhang, Yuan Cheng, Mathias Palm, Justus Notholt, Xiao Lu, Corinne Vigouroux, Bo Zheng, Wei Wang, Nicholas Jones, Changong Shan, Min Qin, Yuan Tian, Qihou Hu, Fanhao Meng, and Jianguo Liu
Atmos. Chem. Phys., 21, 6365–6387, https://doi.org/10.5194/acp-21-6365-2021, https://doi.org/10.5194/acp-21-6365-2021, 2021
Short summary
Short summary
This study mapped the drivers of HCHO variability from 2015 to 2019 over eastern China. Hydroxyl (OH) radical production rates from HCHO photolysis were evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO abundance were analyzed. Contributions of various emission sources and geographical regions to the observed HCHO summertime enhancements were determined.
Efisio Solazzo, Monica Crippa, Diego Guizzardi, Marilena Muntean, Margarita Choulga, and Greet Janssens-Maenhout
Atmos. Chem. Phys., 21, 5655–5683, https://doi.org/10.5194/acp-21-5655-2021, https://doi.org/10.5194/acp-21-5655-2021, 2021
Short summary
Short summary
We conducted an extensive analysis of the structural uncertainty of the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases, which adds a much needed reliability dimension to the accuracy of the emission estimates. The study undertakes in-depth analyses of the implication of aggregating emissions from different sources and/or countries on the accuracy. Results are presented for all emissions sectors according to IPCC definitions.
Xiaohui Lin, Wen Zhang, Monica Crippa, Shushi Peng, Pengfei Han, Ning Zeng, Lijun Yu, and Guocheng Wang
Earth Syst. Sci. Data, 13, 1073–1088, https://doi.org/10.5194/essd-13-1073-2021, https://doi.org/10.5194/essd-13-1073-2021, 2021
Short summary
Short summary
CH4 is a potent greenhouse gas, and China’s anthropogenic CH4 emissions account for a large proportion of global total emissions. However, the existing estimates either focus on a specific sector or lag behind real time by several years. We collected and analyzed 12 datasets and compared them to reveal the spatiotemporal changes and their uncertainties. We further estimated the emissions from 1990–2019, and the estimates showed a robust trend in recent years when compared to top-down results.
Betty Croft, Randall V. Martin, Richard H. Moore, Luke D. Ziemba, Ewan C. Crosbie, Hongyu Liu, Lynn M. Russell, Georges Saliba, Armin Wisthaler, Markus Müller, Arne Schiller, Martí Galí, Rachel Y.-W. Chang, Erin E. McDuffie, Kelsey R. Bilsback, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 1889–1916, https://doi.org/10.5194/acp-21-1889-2021, https://doi.org/10.5194/acp-21-1889-2021, 2021
Short summary
Short summary
North Atlantic Aerosols and Marine Ecosystems Study measurements combined with GEOS-Chem-TOMAS modeling suggest that several not-well-understood key factors control northwest Atlantic aerosol number and size. These synergetic and climate-relevant factors include particle formation near and above the marine boundary layer top, particle growth by marine secondary organic aerosol on descent, particle formation/growth related to dimethyl sulfide, sea spray aerosol, and ship emissions.
Francesco Canonaco, Anna Tobler, Gang Chen, Yulia Sosedova, Jay Gates Slowik, Carlo Bozzetti, Kaspar Rudolf Daellenbach, Imad El Haddad, Monica Crippa, Ru-Jin Huang, Markus Furger, Urs Baltensperger, and André Stephan Henry Prévôt
Atmos. Meas. Tech., 14, 923–943, https://doi.org/10.5194/amt-14-923-2021, https://doi.org/10.5194/amt-14-923-2021, 2021
Short summary
Short summary
Long-term ambient aerosol mass spectrometric data were analyzed with a statistical model (PMF) to obtain source contributions and fingerprints. The new aspects of this paper involve time-dependent source fingerprints by a rolling technique and the replacement of the full visual inspection of each run by a user-defined set of criteria to monitor the quality of each of these runs more efficiently. More reliable sources will finally provide better instruments for political mitigation strategies.
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375, https://doi.org/10.5194/gmd-14-365-2021, https://doi.org/10.5194/gmd-14-365-2021, 2021
Short summary
Short summary
Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
Diego Santaren, Grégoire Broquet, François-Marie Bréon, Frédéric Chevallier, Denis Siméoni, Bo Zheng, and Philippe Ciais
Atmos. Meas. Tech., 14, 403–433, https://doi.org/10.5194/amt-14-403-2021, https://doi.org/10.5194/amt-14-403-2021, 2021
Short summary
Short summary
Atmospheric transport inversions with synthetic data are used to assess the potential of new satellite observations of atmospheric CO2 to monitor anthropogenic emissions from regions, cities and large industrial plants. The analysis, applied to a large ensemble of sources in western Europe, shows a strong dependence of the results on different characteristics of the spaceborne instrument, on the source emission budgets and spreads, and on the wind conditions.
Yilong Wang, Grégoire Broquet, François-Marie Bréon, Franck Lespinas, Michael Buchwitz, Maximilian Reuter, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, and Philippe Ciais
Geosci. Model Dev., 13, 5813–5831, https://doi.org/10.5194/gmd-13-5813-2020, https://doi.org/10.5194/gmd-13-5813-2020, 2020
Yiqi Zheng, Joel A. Thornton, Nga Lee Ng, Hansen Cao, Daven K. Henze, Erin E. McDuffie, Weiwei Hu, Jose L. Jimenez, Eloise A. Marais, Eric Edgerton, and Jingqiu Mao
Atmos. Chem. Phys., 20, 13091–13107, https://doi.org/10.5194/acp-20-13091-2020, https://doi.org/10.5194/acp-20-13091-2020, 2020
Short summary
Short summary
This study aims to address a challenge in biosphere–atmosphere interactions: to what extent can biogenic organic aerosol (OA) be modified through human activities? From three surface network observations, we show OA is weakly dependent on sulfate and aerosol acidity in the summer southeast US, on both long-term trends and monthly variability. The results are in strong contrast to a global model, GEOS-Chem, suggesting the need to revisit the representation of aqueous-phase secondary OA formation.
Yuanhong Zhao, Marielle Saunois, Philippe Bousquet, Xin Lin, Antoine Berchet, Michaela I. Hegglin, Josep G. Canadell, Robert B. Jackson, Makoto Deushi, Patrick Jöckel, Douglas Kinnison, Ole Kirner, Sarah Strode, Simone Tilmes, Edward J. Dlugokencky, and Bo Zheng
Atmos. Chem. Phys., 20, 13011–13022, https://doi.org/10.5194/acp-20-13011-2020, https://doi.org/10.5194/acp-20-13011-2020, 2020
Short summary
Short summary
Decadal trends and variations in OH are critical for understanding atmospheric CH4 evolution. We quantify the impacts of OH trends and variations on the CH4 budget by conducting CH4 inversions on a decadal scale with an ensemble of OH fields. We find the negative OH anomalies due to enhanced fires can reduce the optimized CH4 emissions by up to 10 Tg yr−1 during El Niño years and the positive OH trend from 1986 to 2010 results in a ∼ 23 Tg yr−1 additional increase in optimized CH4 emissions.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
Short summary
Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Priyanka deSouza, Ralph A. Kahn, James A. Limbacher, Eloise A. Marais, Fábio Duarte, and Carlo Ratti
Atmos. Meas. Tech., 13, 5319–5334, https://doi.org/10.5194/amt-13-5319-2020, https://doi.org/10.5194/amt-13-5319-2020, 2020
Short summary
Short summary
This paper presents a novel method to constrain the size distribution derived from low-cost optical particle counters (OPCs) using satellite data to develop higher-quality particulate matter (PM) estimates. Such estimates can enable cities that do not have access to expensive reference air quality monitors, especially those in the global south, to develop effective air quality management plans.
Pengfei Han, Ning Zeng, Tom Oda, Xiaohui Lin, Monica Crippa, Dabo Guan, Greet Janssens-Maenhout, Xiaolin Ma, Zhu Liu, Yuli Shan, Shu Tao, Haikun Wang, Rong Wang, Lin Wu, Xiao Yun, Qiang Zhang, Fang Zhao, and Bo Zheng
Atmos. Chem. Phys., 20, 11371–11385, https://doi.org/10.5194/acp-20-11371-2020, https://doi.org/10.5194/acp-20-11371-2020, 2020
Short summary
Short summary
An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for quantification of carbon budget and emissions reductions towards the Paris Agreement goals. Here we assessed 9 global and regional inventories. Our findings highlight the significance of using locally measured coal emission factors. We call on the enhancement of physical measurements for validation and provide comprehensive information for inventory, monitoring, modeling, assimilation, and reducing emissions.
Cited articles
ADE: Australian Department of the Environment: National Pollution
Inventory, 2017/2018,
http://www.npi.gov.au/npidata/action/load/advance-search (lastaccess: 15
August 2019), 2019.
Ahmadov, R., McKeen, S., Trainer, M., Banta, R., Brewer, A., Brown, S., Edwards, P. M., de Gouw, J. A., Frost, G. J., Gilman, J., Helmig, D., Johnson, B., Karion, A., Koss, A., Langford, A., Lerner, B., Olson, J., Oltmans, S., Peischl, J., Pétron, G., Pichugina, Y., Roberts, J. M., Ryerson, T., Schnell, R., Senff, C., Sweeney, C., Thompson, C., Veres, P. R., Warneke, C., Wild, R., Williams, E. J., Yuan, B., and Zamora, R.: Understanding high wintertime ozone pollution events in an oil- and natural gas-producing region of the western US, Atmos. Chem. Phys., 15, 411–429, https://doi.org/10.5194/acp-15-411-2015, 2015.
Ainsworth, E. A.: Understanding and improving global crop response to ozone
pollution, Plant J., 90, 886–897, https://doi.org/10.1111/tpj.13298, 2017.
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C.,
Höglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., Rafaj, P.,
Sandler, R., Schöpp, W., Wagner, F., and Winiwarter, W.: Cost-effective
control of air quality and greenhouse gases in Europe: Modeling and policy
applications, Environ. Modell. Softw., 26, 1489–1501,
https://doi.org/10.1016/j.envsoft.2011.07.012, 2011.
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C.,
Hoglund-Isaksson, L., Kiesewetter, G., Klimont, Z., Schopp, W., Vellinga,
N., and Winiwarter, W.: Adjusted historic emission data, projections, and
optimized emission reduction targets for 2030 – a comparison with COM data
2013, IIASA, Laxenburg, Austria, available at: http://ec.europa.eu/environment/air/pdf/review/TSAP_16a.pdf
(last access: 15 January 2018), 2015.
Argentina UNFCCC Submission: Argentinian Inventory 1990–2012, submitted to
UNFCCC, 2016.
Avnery, S., Mauzerall, D. L., Liu, J., and Horowitz, L. W.: Global crop
yield reductions due to surface ozone exposure: 1. Year 2000 crop production
losses and economic damage, Atmos. Environ., 45, 2284–2296, https://doi.org/10.1016/j.atmosenv.2010.11.045, 2011.
Behera, S. N., Sharma, M., Aneja, V. P., and Balasubramanian, R.: Ammonia in
the atmosphere: a review on emission sources, atmospheric chemistry and
deposition on terrestrial bodies, Environ. Sci. Pollut.
R., 20, 8092–8131, https://doi.org/10.1007/s11356-013-2051-9, 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, https://doi.org/10.1126/science.1207824, 2011.
Boden, T. A., Marland, G., and Andres, R. J.: Global, Regional, and National
Fossil-Fuel CO2 Emissions, Carbon Dioxide Information Analysis Center,
US Department of Energy, Oak Ridge, USA, 2016.
Boden, T. A., Marland, G., and Andres, R. J.: Global, Regional, and National
Fossil-Fuel CO2 Emissions, Carbon Dioxide Information Analysis Center,
US Department of Energy, Oak Ridge, USA, https://doi.org/10.3334/CDIAC/00001_V2017, 2017.
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., Woo, J.‐H., and Klimont, Z.: A technology‐based global inventory of black and organic carbon emissions from combustion, J. Geophys. Res., 109, D14203, https://doi.org/10.1029/2003JD003697, 2004.
Dong, R., Jogani, R., Jung, S., Roden, C., Streets, D. G., and Trautmann, N. M.: Historical emissions of black and organic carbon aerosol from energy‐related combustion, 1850–2000, Global Biogeochem. Cycles, 21, GB2018, https://doi.org/10.1029/2006GB002840, 2007.
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.
BP: BP Statistical Review of World Energy, available at: https://www.bp.com/statisticalreview (last
access: 15 January 2018), 2015.
BP: Statistical Review of World Energy: 2019, available at: https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2019-full-report.pdf
(last access: 23 January 2020), 2019.
Brock, C. A., Washenfelder, R. A., Trainer, M., Ryerson, T. B., Wilson, J.
C., Reeves, J. M., Huey, L. G., Holloway, J. S., Parrish, D. D., Hübler,
G., and Fehsenfeld, F. C.: Particle growth in the plumes of coal-fired power
plants, J. Geophys. Res.-Atmos., 107, D124155,
https://doi.org/10.1029/2001JD001062, 2002.
Carter, E. M., Shan, M., Yang, X., Li, J., and Baumgartner, J.: Pollutant
Emissions and Energy Efficiency of Chinese Gasifier Cooking Stoves and
Implications for Future Intervention Studies, Environ. Sci. Technol., 48,
6461–6467, https://doi.org/10.1021/es405723w, 2014.
Castellanos, P. and Boersma, K. F.: Reductions in nitrogen oxides over
Europe driven by environmental policy and economic recession, Sci.
Rep.-UK, 2, 265, https://doi.org/10.1038/srep00265, 2012.
CEDS: v2017_08_30, available at: https://esgf-node.llnl.gov/search/input4mips/ (last access: 7 January
2020), 2017a.
CEDS: v2017_10_05, available at: https://esgf-node.llnl.gov/search/input4mips/ (last access: 7 January
2020), 2017b.
Chameides, W. L.: The photochemical role of tropospheric nitrogen oxides,
Geophys. Res. Lett., 5, 17–20, https://doi.org/10.1029/GL005i001p00017, 1978.
Chen, Y., Roden, C. A., and Bond, T. C.: Characterizing Biofuel Combustion
with Patterns of Real-Time Emission Data (PaRTED), Environ. Sci. Technol.,
46, 6110–6117, https://doi.org/10.1021/es3003348, 2012.
Commoner, B., Bartlett, P. W., Eisl, H., and Couchot, K.: Air Transport of
Dioxin from North American Sources to Ecologically Vulnerable Receptors in
Nunavut, Arctic Canada: Final Report to the North American Commission for
Environmental Cooperation, available at: http://www3.cec.org/islandora/en/item/1596-long-range-air-transport-dioxin-from-north-american-sources-ecologically-vulnerable-en.pdf
(last access: 25 April 2020), 2000.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Crippa, M., Janssens-Maenhout, G., Guizzardi, D., Van Dingenen, R., and Dentener, F.: Contribution and uncertainty of sectorial and regional emissions to regional and global PM2.5 health impacts, Atmos. Chem. Phys., 19, 5165–5186, https://doi.org/10.5194/acp-19-5165-2019, 2019.
Crutzen, P. J.: The influence of nitrogen oxides on the atmospheric ozone
content, Q. J. Roy. Meteor. Soc., 96, 320–325,
https://doi.org/10.1002/qj.49709640815, 1970.
de Gouw, J. A., Parrish, D. D., Frost, G. J., and Trainer, M.: Reduced
emissions of CO2, NOx, and SO2 from US power plants owing to switch from
coal to natural gas with combined cycle technology, Earths Future, 2,
75–82, https://doi.org/10.1002/2013EF000196, 2014.
Denier van der Gon, H. A. C., Bergström, R., Fountoukis, C., Johansson, C., Pandis, S. N., Simpson, D., and Visschedijk, A. J. H.: Particulate emissions from residential wood combustion in Europe – revised estimates and an evaluation, Atmos. Chem. Phys., 15, 6503–6519, https://doi.org/10.5194/acp-15-6503-2015, 2015.
DICE-Africa: DICE-Africa User Manual, available at: https://www2.acom.ucar.edu/modeling/dice-africa (last access: 9 January
2020), 2016.
Doxsey-Whitfield, E., MacManus, K., Adamo, S. B., Pistolesi, L., Squires,
J., Borkovska, O., and Baptista, S. R.: Taking Advantage of the Improved
Availability of Census Data: A First Look at the Gridded Population of the
World, Version 4, Papers in Applied Geography, 1, 226–234,
https://doi.org/10.1080/23754931.2015.1014272, 2015.
Duncan, B. N., Yoshida, Y., de Foy, B., Lamsal, L. N., Streets, D. G., Lu,
Z., Pickering, K. E., and Krotkov, N. A.: The observed response of Ozone
Monitoring Instrument (OMI) NO2 columns to NOx emission controls on power
plants in the United States: 2005–2011, Atmos. Environ., 81, 102–111,
https://doi.org/10.1016/j.atmosenv.2013.08.068, 2013.
ECCC: Environment and Climate Change Canada, EN_APEI-Canada,
Canada's 2019 Air Pollutant Emissions Inventory, available at: http://data.ec.gc.ca/data/substances/monitor/canada-s-air-pollutant-emissions-inventory/APEI_Tables_Canada_Provinces_Territories/?lang, last access: 13 August 2019.
EC-JRC: Emissions Database for Global Atmospheric Research (EDGAR), release
EDGARv4.3.2, available at: https://edgar.jrc.ec.europa.eu/overview.php?v (last access: 12 August 2019), 2018.
EC-JRC/PBL: Emission Database for Global Atmospheric Research (EDGAR),
release EDGAR v4.2 FT2012, available at: http://edgar.jrc.ec.europa.eu (last
access: 15 January 2018), 2012.
EC-JRC/PBL: Emission Database for Global Atmospheric Research (EDGAR),
release version 4.3.1, available at: http://edgar.jrc.ec.europa.eu/overview.php?v (last
access: 15 January 2018), 2016.
EIA: US Energy Information Administration: Table 10.2a: Renewable Energy
Cnsumption, Residential and Commercial Sectors, available at: https://www.eia.gov/totalenergy/data/monthly/#renewable (last access:
26 August 2019), 2019.
EIA: US Energy Information Administration: Drilling Productivity Report, available at: https://www.eia.gov/petroleum/drilling/, last access: 7 April
2020.
Elguindi, N., Granier, C., Stavrakou, T., Darras, S., Bauwens, M., Cao, H.,
Chen, C., Denier van der Gon, H. A. C., Dubovik, O., Fu, T. M., Henze, D.
K., Jiang, Z., Keita, S., Kuenen, J. J. P., Kurokawa, J., Liousse, C.,
Miyazaki, K., Müller, J. F., Qu, Z., Solmon, F., and Zheng, B.:
Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions
From Bottom-Up Inventories, Top-Down Estimates, and Emission Scenarios,
Earths Future, 8, e2020EF001520, https://doi.org/10.1029/2020EF001520, 2020.
EMEP: Officially reported emission data to the European Monitoring and
Evaluation Programme: EMEP_NFR14_LEVEL1 data, available at:
https://www.ceip.at/ms/ceip_home1/ceip_home/webdab_emepdatabase/reported_emissiondata/, last access: 19 December
2019.
FAOSTAT: FAOSTAT-Forestry database, available at: http://www.fao.org/forestry/statistics/84922/en/ (last access: 15 January
2018), 2015.
Feng, L., Smith, S. J., Braun, C., Crippa, M., Gidden, M. J., Hoesly, R., Klimont, Z., van Marle, M., van den Berg, M., and van der Werf, G. R.: The generation of gridded emissions data for CMIP6, Geosci. Model Dev., 13, 461–482, https://doi.org/10.5194/gmd-13-461-2020, 2020.
FINN: Fire INventory from NCAR, Version 1.5, available at: http://bai.acom.ucar.edu/Data/fire/ (last access: 4 March 2020), 2018.
GBD 2017 Risk Factor Collaborators: 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, The Lancet,
392, 1923–1994, https://doi.org/10.1016/S0140-6736(18)32225-6,
2018.
GBD MAPS Working Group: Burden of Disease Attributable to Coal-Burning and
Other Major Sources of Air Pollution in China, Special Report 20, Health
Effects Institute, available at: https://www.healtheffects.org/publication/burden-disease-attributable-coal-burning-and-other-air-pollution-sources-china (last access: 1 December 2020), 2016.
GBD MAPS Working Group: Burden of Disease Attributable to Major Air
Pollution Sources in India, Special Report 21, Health Effects Institute
available at: https://www.healtheffects.org/publication/gbd-air-pollution-india,
(last access: 1 December 2020) 2018.
GFED: Global Fire Emissions Database, available at: http://globalfiredata.org/index.html (last access: 15 March 2020), 2019.
Gidden, M. J., Riahi, K., Smith, S. J., Fujimori, S., Luderer, G., Kriegler, E., van Vuuren, D. P., van den Berg, M., Feng, L., Klein, D., Calvin, K., Doelman, J. C., Frank, S., Fricko, O., Harmsen, M., Hasegawa, T., Havlik, P., Hilaire, J., Hoesly, R., Horing, J., Popp, A., Stehfest, E., and Takahashi, K.: Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century, Geosci. Model Dev., 12, 1443–1475, https://doi.org/10.5194/gmd-12-1443-2019, 2019.
Guan, D., Liu, Z., Geng, Y., Lindner, S., and Hubacek, K.: The gigatonne gap
in China's carbon dioxide inventories, Nat. Clim. Change, 2, 672–675,
https://doi.org/10.1038/nclimate1560, 2012.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative
forcing due to tropospheric aerosols: A review, Rev. Geophys., 38,
513–543, https://doi.org/10.1029/1999RG000078, 2000.
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Hoesly, R., O'Rourke, P., Braun, C., Feng, L., Smith, S. J., Pitkanen, T.,
Siebert, J., Vu, L., Presley, M., Bolt, R., Goldstein, B., and Kholod, N.:
CEDS: Community Emissions Data System (Version Dec-23-2019), Zenodo, https://doi.org/10.5281/zenodo.3592073, 2019.
Hong, C., Zhang, Q., He, K., Guan, D., Li, M., Liu, F., and Zheng, B.: Variations of China's emission estimates: response to uncertainties in energy statistics, Atmos. Chem. Phys., 17, 1227–1239, https://doi.org/10.5194/acp-17-1227-2017, 2017.
HTAP2: RETRO NMVOC Ratio, available at: http://iek8wikis.iek.fz-juelich.de/HTAPWiki/WP1.1?action (last access: 7 January
2020), 2013.
Huang, G., Brook, R., Crippa, M., Janssens-Maenhout, G., Schieberle, C., Dore, C., Guizzardi, D., Muntean, M., Schaaf, E., and Friedrich, R.: Speciation of anthropogenic emissions of non-methane volatile organic compounds: a global gridded data set for 1970–2012, Atmos. Chem. Phys., 17, 7683–7701, https://doi.org/10.5194/acp-17-7683-2017, 2017.
IEA: World Energy Statistics, available at: http://www.iea.org/statistics/
(last access: 15 January 2018), 2015.
IEA: World Energy Statistics 2019 Edition, Database Documentation, available at:
http://wds.iea.org/wds/pdf/WORLDBES_Documentation.pdf, last access: 17 September 2019.
IIASA: GAINS – Sulfur content of fuels, available at: http://gains.iiasa.ac.at/models/index.html (last access: 15 January 2018), 2014.
IIASA: ECLIPSE v5a, available at: https://www.iiasa.ac.at/web/home/research/researchPrograms/air/ECLIPSEv5a.html
(last access: 7 January 2020), 2015.
IPCC: Summary for Policy Makers, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D.,
Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, Y., Xia,
Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge,
United Kingdom and New York, USA, 1–29, 2013.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., Denier van der Gon, H., Kuenen, J. J. P., Klimont, Z., Frost, G., Darras, S., Koffi, B., and Li, M.: HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution, Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, 2015.
Jayarathne, T., Stockwell, C. E., Bhave, P. V., Praveen, P. S., Rathnayake, C. M., Islam, Md. R., Panday, A. K., Adhikari, S., Maharjan, R., Goetz, J. D., DeCarlo, P. F., Saikawa, E., Yokelson, R. J., and Stone, E. A.: Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): emissions of particulate matter from wood- and dung-fueled cooking fires, garbage and crop residue burning, brick kilns, and other sources, Atmos. Chem. Phys., 18, 2259–2286, https://doi.org/10.5194/acp-18-2259-2018, 2018.
Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang,
Q., Kroll, J. H., DeCarlo, P. F., Allan, J. D., Coe, H., Ng, N. L., Aiken,
A. C., Docherty, K. S., Ulbrich, I. M., Grieshop, A. P., Robinson, A. L.,
Duplissy, J., Smith, J. D., Wilson, K. R., Lanz, V. A., Hueglin, C., Sun, Y.
L., Tian, J., Laaksonen, A., Raatikainen, T., Rautiainen, J., Vaattovaara,
P., Ehn, M., Kulmala, M., Tomlinson, J. M., Collins, D. R., Cubison, M. J.,
Dunlea, J., Huffman, J. A., Onasch, T. B., Alfarra, M. R., Williams, P. I.,
Bower, K., Kondo, Y., Schneider, J., Drewnick, F., Borrmann, S., Weimer, S.,
Demerjian, K., Salcedo, D., Cottrell, L., Griffin, R., Takami, A., Miyoshi,
T., Hatakeyama, S., Shimono, A., Sun, J. Y., Zhang, Y. M., Dzepina, K.,
Kimmel, J. R., Sueper, D., Jayne, J. T., Herndon, S. C., Trimborn, A. M.,
Williams, L. R., Wood, E. C., Middlebrook, A. M., Kolb, C. E.,
Baltensperger, U., and Worsnop, D. R.: Evolution of Organic Aerosols in the
Atmosphere, Science, 326, 1525, https://doi.org/10.1126/science.1180353, 2009.
Klein Goldewijk, K., Beusen, A., van Drecht, G., and de Vos, M.: The HYDE
3.1 spatially explicit database of human-induced global land-use change over
the past 12,000 years, Global Ecol. Biogeogr., 20, 73–86,
https://doi.org/10.1111/j.1466-8238.2010.00587.x, 2011.
Klimont, Z., Kupiainen, K., Heyes, C., Purohit, P., Cofala, J., Rafaj, P., Borken-Kleefeld, J., and Schöpp, W.: Global anthropogenic emissions of particulate matter including black carbon, Atmos. Chem. Phys., 17, 8681–8723, https://doi.org/10.5194/acp-17-8681-2017, 2017.
Krotkov, N. A., McLinden, C. A., Li, C., Lamsal, L. N., Celarier, E. A., Marchenko, S. V., Swartz, W. H., Bucsela, E. J., Joiner, J., Duncan, B. N., Boersma, K. F., Veefkind, J. P., Levelt, P. F., Fioletov, V. E., Dickerson, R. R., He, H., Lu, Z., and Streets, D. G.: Aura OMI observations of regional SO2 and NO2 pollution changes from 2005 to 2015, Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, 2016.
Kurokawa, J., Ohara, T., Morikawa, T., Hanayama, S., Janssens-Maenhout, G., Fukui, T., Kawashima, K., and Akimoto, H.: Emissions of air pollutants and greenhouse gases over Asian regions during 2000–2008: Regional Emission inventory in ASia (REAS) version 2, Atmos. Chem. Phys., 13, 11019–11058, https://doi.org/10.5194/acp-13-11019-2013, 2013.
Lacey, F. and Henze, D.: Global climate impacts of country-level primary
carbonaceous aerosol from solid-fuel cookstove emissions, Environ.
Res. Lett., 10, 114003, https://doi.org/10.1088/1748-9326/10/11/114003, 2015.
Lacey, F. G., Marais, E. A., Henze, D. K., Lee, C. J., van Donkelaar, A.,
Martin, R. V., Hannigan, M. P., and Wiedinmyer, C.: Improving present day
and future estimates of anthropogenic sectoral emissions and the resulting
air quality impacts in Africa, Faraday Discuss., 200, 397–412,
https://doi.org/10.1039/C7FD00011A, 2017.
Lamsal, L. N., Martin, R. V., Padmanabhan, A., van Donkelaar, A., Zhang, Q., Sioris, C. E., Chance, K., Kurosu, T. P., and Newchurch, M. J.: Application of satellite observations for timely updates to global anthropogenic NOx emission inventories, Geophys. Res. Lett., 38, L05810, https://doi.org/10.1029/2010GL046476, 2011.
Lei, Y., Zhang, Q., He, K. B., and Streets, D. G.: Primary anthropogenic aerosol emission trends for China, 1990–2005, Atmos. Chem. Phys., 11, 931–954, https://doi.org/10.5194/acp-11-931-2011, 2011.
Lelieveld, J., Klingmüller, K., Pozzer, A., Burnett, R. T., Haines, A.,
and Ramanathan, V.: Effects of fossil fuel and total anthropogenic emission
removal on public health and climate, P. Natl. Acad. Sci. USA, 116, 7192,
https://doi.org/10.1073/pnas.1819989116, 2019.
Li, C., McLinden, C., Fioletov, V., Krotkov, N., Carn, S., Joiner, J.,
Streets, D., He, H., Ren, X., Li, Z., and Dickerson, R. R.: India Is
Overtaking China as the World's Largest Emitter of Anthropogenic Sulfur
Dioxide, Sci. Rep.-UK, 7, 14304, https://doi.org/10.1038/s41598-017-14639-8, 2017.
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B.,
Cui, H., Man, H., Zhang, Q., and He, K.: Anthropogenic emission inventories
in China: a review, Natl. Sci. Rev., 4, 834–866, https://doi.org/10.1093/nsr/nwx150,
2017a.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017b.
Liang, C.-K., West, J. J., Silva, R. A., Bian, H., Chin, M., Davila, Y., Dentener, F. J., Emmons, L., Flemming, J., Folberth, G., Henze, D., Im, U., Jonson, J. E., Keating, T. J., Kucsera, T., Lenzen, A., Lin, M., Lund, M. T., Pan, X., Park, R. J., Pierce, R. B., Sekiya, T., Sudo, K., and Takemura, T.: HTAP2 multi-model estimates of premature human mortality due to intercontinental transport of air pollution and emission sectors, Atmos. Chem. Phys., 18, 10497–10520, https://doi.org/10.5194/acp-18-10497-2018, 2018.
Liu, Z., Guan, D., Wei, W., Davis, S. J., Ciais, P., Bai, J., Peng, S.,
Zhang, Q., Hubacek, K., Marland, G., Andres, R. J., Crawford-Brown, D., Lin,
J., Zhao, H., Hong, C., Boden, T. A., Feng, K., Peters, G. P., Xi, F., Liu,
J., Li, Y., Zhao, Y., Zeng, N., and He, K.: Reduced carbon emission
estimates from fossil fuel combustion and cement production in China,
Nature, 524, 335–338, https://doi.org/10.1038/nature14677, 2015.
Lu, Z., Zhang, Q., and Streets, D. G.: Sulfur dioxide and primary carbonaceous aerosol emissions in China and India, 1996–2010, Atmos. Chem. Phys., 11, 9839–9864, https://doi.org/10.5194/acp-11-9839-2011, 2011.
Marais, E. A. and Wiedinmyer, C.: Air Quality Impact of Diffuse and
Inefficient Combustion Emissions in Africa (DICE-Africa), Environ. Sci.
Technol., 50, 10739–10745, https://doi.org/10.1021/acs.est.6b02602, 2016.
Marais, E. A., Silvern, R. F., Vodonos, A., Dupin, E., Bockarie, A. S.,
Mickley, L. J., and Schwartz, J.: Air Quality and Health Impact of Future
Fossil Fuel Use for Electricity Generation and Transport in Africa, Environ.
Sci. Technol., 53, 13524–13534, https://doi.org/10.1021/acs.est.9b04958, 2019.
Mauzerall, D. L., Sultan, B., Kim, N., and Bradford, D. F.: NOx emissions
from large point sources: variability in ozone production, resulting health
damages and economic costs, Atmos. Environ., 39, 2851–2866, https://doi.org/10.1016/j.atmosenv.2004.12.041, 2005.
McDonald, B. C., de Gouw, J. A., Gilman, J. B., Jathar, S. H., Akherati, A.,
Cappa, C. D., Jimenez, J. L., Lee-Taylor, J., Hayes, P. L., McKeen, S. A.,
Cui, Y. Y., Kim, S.-W., Gentner, D. R., Isaacman-VanWertz, G., Goldstein, A.
H., Harley, R. A., Frost, G. J., Roberts, J. M., Ryerson, T. B., and
Trainer, M.: Volatile chemical products emerging as largest petrochemical
source of urban organic emissions, Science, 359, 760,
https://doi.org/10.1126/science.aaq0524, 2018.
McDuffie, E. E., Hoesly, R., O'Rourke, P., Braun, C., Feng, L., Smith, S.
J., Pitkanen, T., Seibert, J. J., Vu, L., Presley, M., Bolt, R., Goldstein,
B., and Kholod, N.: CEDS_GBD-MAPS_SourceCode_2020_v1.0, Zenodo, https://doi.org/10.5281/zenodo.3865670,
2020a.
McDuffie, E. E., Smith, S. J., O'Rourke, P., Tibrewal, K., Venkataraman, C.,
Marais, E. A., Zheng, B., Crippa, M., Brauer, M., and Martin, R. V.:
CEDS_GBD-MAPS: Data Snapshot (2014–2015), Zenodo, https://doi.org/10.5281/zenodo.3833935,
2020b.
McDuffie, E. E., Smith, S. J., O'Rourke, P., Tibrewal, K., Venkataraman, C.,
Marais, E. A., Zheng, B., Crippa, M., Brauer, M., and Martin, R. V.:
CEDS_GBD-MAPS: Global Anthropogenic Emission Inventory of
NOx, SO2, CO, NH3, NMVOCs, BC, and OC from 1970–2017 (Version
2020_v1.0), Zenodo, https://doi.org/10.5281/zenodo.3754964,
2020c.
McLinden, C. A., Fioletov, V., Boersma, K. F., Krotkov, N., Sioris, C. E., Veefkind, J. P., and Yang, K.: Air quality over the Canadian oil sands: A first assessment using satellite observations, Geophys. Res. Lett., 39, L04804, https://doi.org/10.1029/2011GL050273, 2012.
McLinden, C. A., Fioletov, V., Shephard, M. W., Krotkov, N., Li, C., Martin,
R. V., Moran, M. D., and Joiner, J.: Space-based detection of missing sulfur
dioxide sources of global air pollution, Nat. Geosci., 9, 496,
https://doi.org/10.1038/ngeo2724,
2016.
MEGAN: The Model of Emissions of Gases and Aerosols from Nature, Version
3.1, available at: https://sites.google.com/uci.edu/bai/megan/data-and-code
(last access: 4 March 2020), 2019.
Meidiana, C. and Gamse, T.: Development of Waste Management Practices in
Indonesia, European Journal of Scientific Research, 40, 199–210, 2010.
Mickley, L. J., Jacob, D. J., Field, B. D., and Rind, D.: Effects of future climate change on regional air pollution episodes in the United States, Geophys. Res. Lett., 31, L24103, https://doi.org/10.1029/2004GL021216, 2004.
Moravek, A., Murphy, J. G., Hrdina, A., Lin, J. C., Pennell, C., Franchin, A., Middlebrook, A. M., Fibiger, D. L., Womack, C. C., McDuffie, E. E., Martin, R., Moore, K., Baasandorj, M., and Brown, S. S.: Wintertime spatial distribution of ammonia and its emission sources in the Great Salt Lake region, Atmos. Chem. Phys., 19, 15691–15709, https://doi.org/10.5194/acp-19-15691-2019, 2019.
Mozurkewich, M.: The dissociation constant of ammonium nitrate and its
dependence on temperature, relative humidity and particle size, Atmos.
Environ., 27, 261–270, https://doi.org/10.1016/0960-1686(93)90356-4, 1993.
Nagpure, A. S., Ramaswami, A., and Russell, A.: Characterizing the Spatial
and Temporal Patterns of Open Burning of Municipal Solid Waste (MSW) in
Indian Cities, Environ. Sci. Technol., 49, 12904–12912,
https://doi.org/10.1021/acs.est.5b03243, 2015.
NEI: 2011 National Emissions Inventory (NEI) Data, available at: https://www.epa.gov/air-emissions-inventories/2011-national-emissions-inventory-nei-data (last access: 12 December 2020),
2013.
Paulot, F., Jacob, D. J., Pinder, R. W., Bash, J. O., Travis, K., and Henze,
D. K.: Ammonia emissions in the United States, European Union, and China
derived by high-resolution inversion of ammonium wet deposition data:
Interpretation with a new agricultural emissions inventory
(MASAGE_NH3), J. Geophys. Res.-Atmos., 119, 4343–4364,
https://doi.org/10.1002/2013JD021130, 2014.
Philip, S., Martin, R. V., Snider, G., Weagle, C. L., van Donkelaar, A.,
Brauer, M., Henze, D. K., Klimont, Z., Venkataraman, C., Guttikunda, S. K.,
and Zhang, Q.: Anthropogenic fugitive, combustion and industrial dust is a
significant, underrepresented fine particulate matter source in global
atmospheric models, Environ. Res. Lett., 12, 044018,
https://doi.org/10.1088/1748-9326/aa65a4, 2017.
RAQC: Regional Air Quality Council: Summary of State Implementation Plans, available at: https://raqc.egnyte.com/dl/KZXQmQtFaQ/2019_SIP_Summaries_Update.pdf (last access: 23 January 2020), 2019.
Reyna-Bensusan, N., Wilson, D. C., and Smith, S. R.: Uncontrolled burning of
solid waste by households in Mexico is a significant contributor to climate
change in the country, Environ. Res., 163, 280–288, https://doi.org/10.1016/j.envres.2018.01.042, 2018.
Sadavarte, P. and Venkataraman, C.: Trends in multi-pollutant emissions
from a technology-linked inventory for India: I. Industry and transport
sectors, Atmos. Environ., 99, 353–364, https://doi.org/10.1016/j.atmosenv.2014.09.081, 2014.
Saxena, P. and Seigneur, C.: On the oxidation of SO2 to sulfate in
atmospheric aerosols, Atmos. Environ., 21, 807–812,
https://doi.org/10.1016/0004-6981(87)90077-1, 1987.
Schöpp, W., Klimont, Z., Suutari, R., and Cofala, J.: Uncertainty
analysis of emission estimates in the RAINS integrated assessment model,
Environ. Sci. Policy, 8, 601–613, https://doi.org/10.1016/j.envsci.2005.06.008, 2005.
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.
Shindell, D. and Smith, C. J.: Climate and air-quality benefits of a
realistic phase-out of fossil fuels, Nature, 573, 408–411,
https://doi.org/10.1038/s41586-019-1554-z, 2019.
SMoG-India: Speciated Multi-pollutant Generator, available at: https://sites.google.com/view/smogindia (last access: 28 February 2020),
2019.
South Korea National Institute of Environmental Research: National air
pollutants emission service, available at: http://airemiss.nier.go.kr/ (last
access: 15 Janurary 2018), 2016.
Stevens, C. J., Dise, N. B., Mountford, J. O., and Gowing, D. J.: Impact of
Nitrogen Deposition on the Species Richness of Grasslands, Science, 303,
1876, https://doi.org/10.1126/science.1094678, 2004.
Stohl, A., Aamaas, B., Amann, M., Baker, L. H., Bellouin, N., Berntsen, T. K., Boucher, O., Cherian, R., Collins, W., Daskalakis, N., Dusinska, M., Eckhardt, S., Fuglestvedt, J. S., Harju, M., Heyes, C., Hodnebrog, Ø., Hao, J., Im, U., Kanakidou, M., Klimont, Z., Kupiainen, K., Law, K. S., Lund, M. T., Maas, R., MacIntosh, C. R., Myhre, G., Myriokefalitakis, S., Olivié, D., Quaas, J., Quennehen, B., Raut, J.-C., Rumbold, S. T., Samset, B. H., Schulz, M., Seland, Ø., Shine, K. P., Skeie, R. B., Wang, S., Yttri, K. E., and Zhu, T.: Evaluating the climate and air quality impacts of short-lived pollutants, Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, 2015.
Streets, D. G., Canty, T., Carmichael, G. R., de Foy, B., Dickerson, R. R.,
Duncan, B. N., Edwards, D. P., Haynes, J. A., Henze, D. K., Houyoux, M. R.,
Jacob, D. J., Krotkov, N. A., Lamsal, L. N., Liu, Y., Lu, Z., Martin, R. V.,
Pfister, G. G., Pinder, R. W., Salawitch, R. J., and Wecht, K. J.: Emissions
estimation from satellite retrievals: A review of current capability, Atmos.
Environ., 77, 1011–1042, https://doi.org/10.1016/j.atmosenv.2013.05.051, 2013.
TEPA: Taiwan Emission Data System, available at: https://erdb.epa.gov.tw/eng/DataRepository/EnvMonitor/ReportInspectAirTEDS.aspx?topic1 (last access: 15 January 2018), 2016.
The World Bank: World Development Indicators, available at: http://databank.worldbank.org/data/download/WDI_excel.zip (last
access: 15 January 2018), 2016.
Travis, K. R., Jacob, D. J., Fisher, J. A., Kim, P. S., Marais, E. A., Zhu, L., Yu, K., Miller, C. C., Yantosca, R. M., Sulprizio, M. P., Thompson, A. M., Wennberg, P. O., Crounse, J. D., St. Clair, J. M., Cohen, R. C., Laughner, J. L., Dibb, J. E., Hall, S. R., Ullmann, K., Wolfe, G. M., Pollack, I. B., Peischl, J., Neuman, J. A., and Zhou, X.: Why do models overestimate surface ozone in the Southeast United States?, Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, 2016.
UN: World Urbanization Prospects: The 2014 Revision, available at: https://esa.un.org/unpd/wup/CD-ROM/WUP2014_XLS_CD_FILES/WUP2014-F01-Total_Urban_Rural.xls (last access: 15 January 2018), 2014.
UN: UN World Population Prospects: The 2015 Revision, available at: http://esa.un.org/unpd/wpp/DVD/ (last access: 15 January 2018), 2015.
UN: World urbanization prospects: The 2018 revision, annual percentage of
population at mid-year residing in urban areas by region, subregion, country
and area, 1950–2050, available at: https://population.un.org/wup/Download/ (last access: 24 July 2019), 2018.
UN: World Population Prospects 2019: Total population (both sexes combined)
by region, subregion and country, annually for 1950 to 2100, available at: https://esa.un.org/unpd/wpp/Download/Standard/Population/ (last access: 24 July 2019), 2019.
UNFCCC: National Inventory Submissions of Annex I Parties to the UNFCCC, available at: https://di.unfccc.int/ (last access: 12 August 2019), 2019.
US EPA: An inventory of sources and environmental releases of dioxin-like
compounds in the US for the years 1987, 1995, and 2000, US Environmental
Protection Agency, Washington DC, USA, EPA/600/P-03/002F, 667 pp., 2006.
US EPA: Criteria Air Pollutants, available at: https://www.epa.gov/criteria-air-pollutants (last access: 23 January
2020), 2018.
US EPA: National Annual Emissions Trend: 1970–2018, available at: https://www.epa.gov/air-emissions-inventories/air-pollutant-emissions-trends-data, last
access: 26 August 2019.
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.
Venkataraman, C., Brauer, M., Tibrewal, K., Sadavarte, P., Ma, Q., Cohen, A., Chaliyakunnel, S., Frostad, J., Klimont, Z., Martin, R. V., Millet, D. B., Philip, S., Walker, K., and Wang, S.: Source influence on emission pathways and ambient PM2.5 pollution over India (2015–2050), Atmos. Chem. Phys., 18, 8017–8039, https://doi.org/10.5194/acp-18-8017-2018, 2018.
Venkataraman, C., Bhushan, M., Dey, S., Ganguly, D., Gupta, T., Habib, G., Kesarkar, A., Phuleria, H., and Raman, R. S.: Indian Network Project on Carbonaceous Aerosol Emissions, Source Apportionment and Climate Impacts (COALESCE), B. Am. Meteorol. Soc., 101, E1052–E1068, 2020.
Wang, S., Zhang, Q., Martin, R. V., Philip, S., Liu, F., Li, M., Jiang, X.,
and He, K.: Satellite measurements oversee China's sulfur dioxide emission
reductions from coal-fired power plants, Environ. Res. Lett., 10,
114015, https://doi.org/10.1088/1748-9326/10/11/114015, 2015.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Wiedinmyer, C., Yokelson, R. J., and Gullett, B. K.: Global Emissions of
Trace Gases, Particulate Matter, and Hazardous Air Pollutants from Open
Burning of Domestic Waste, Environ. Sci. Technol., 48, 9523–9530,
https://doi.org/10.1021/es502250z, 2014.
Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H., Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., Chen, D., Duan, L., Lei, Y., Wang, L. T., and Yao, Z. L.: Asian emissions in 2006 for the NASA INTEX-B mission, Atmos. Chem. Phys., 9, 5131–5153, https://doi.org/10.5194/acp-9-5131-2009, 2009.
Zhao, Y., Nielsen, C. P., Lei, Y., McElroy, M. B., and Hao, J.: Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China, Atmos. Chem. Phys., 11, 2295–2308, https://doi.org/10.5194/acp-11-2295-2011, 2011.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zheng, B., Chevallier, F., Yin, Y., Ciais, P., Fortems-Cheiney, A., Deeter, M. N., Parker, R. J., Wang, Y., Worden, H. M., and Zhao, Y.: Global atmospheric carbon monoxide budget 2000–2017 inferred from multi-species atmospheric inversions, Earth Syst. Sci. Data, 11, 1411–1436, https://doi.org/10.5194/essd-11-1411-2019, 2019.
Short summary
Global emission inventories are vital to understanding the impacts of air pollution on the environment, human health, and society. We update the open-source Community Emissions Data System (CEDS) to provide global gridded emissions of seven key air pollutants from 1970–2017 for 11 source sectors and multiple fuel types, including coal, solid biofuel, and liquid oil and natural gas. This dataset includes both monthly global gridded emissions and annual national totals.
Global emission inventories are vital to understanding the impacts of air pollution on the...
Altmetrics
Final-revised paper
Preprint