Data description paper
11 Mar 2021
Data description paper
| 11 Mar 2021
Country-resolved combined emission and socio-economic pathways based on the Representative Concentration Pathway (RCP) and Shared Socio-Economic Pathway (SSP) scenarios
Johannes Gütschow et al.
Related authors
Francesco N. Tubiello, Kevin Karl, Alessandro Flammini, Johannes Gütschow, Griffiths Obli-Laryea, Giulia Conchedda, Xueyao Pan, Sally Yue Qi, Hörn Halldórudóttir Heiðarsdóttir, Nathan Wanner, Roberta Quadrelli, Leonardo Rocha Souza, Philippe Benoit, Matthew Hayek, David Sandalow, Erik Mencos Contreras, Cynthia Rosenzweig, Jose Rosero Moncayo, Piero Conforti, and Maximo Torero
Earth Syst. Sci. Data, 14, 1795–1809, https://doi.org/10.5194/essd-14-1795-2022, https://doi.org/10.5194/essd-14-1795-2022, 2022
Short summary
Short summary
The paper presents results from the new FAOSTAT database on food system emissions, covering all countries over the time series 1990–2019. Results indicate and further clarify – updated to 2019 – the relevance of emissions from crop and livestock production processes within the farm gate; from conversion of natural ecosystems to agriculture, such as deforestation and peat degradation; and from use of fossil fuels for energy and other industrial processes along food supply chains.
Annika Günther, Johannes Gütschow, and Mairi Louise Jeffery
Geosci. Model Dev., 14, 5695–5730, https://doi.org/10.5194/gmd-14-5695-2021, https://doi.org/10.5194/gmd-14-5695-2021, 2021
Short summary
Short summary
The mitigation components of the nationally determined contributions (NDCs) under the Paris Agreement are essential in our fight against climate change. Regular updates with increased ambition are requested to limit global warming to 1.5–2 °C. The new and easy-to-update open-source tool NDCmitiQ can be used to quantify the NDCs' mitigation targets and construct resulting emissions pathways. In use cases, we show target uncertainties from missing clarity, data, and methodological challenges.
M. Louise Jeffery, Johannes Gütschow, Robert Gieseke, and Ronja Gebel
Earth Syst. Sci. Data, 10, 1427–1438, https://doi.org/10.5194/essd-10-1427-2018, https://doi.org/10.5194/essd-10-1427-2018, 2018
Short summary
Short summary
Developed countries are required to report detailed greenhouse gas emissions data to the UN on an annual basis. The reporting tables are complex, do not fit well with existing hierarchical reporting guidelines, and are not machine-readable. We present a processed version of the reported data in a consistent hierarchy, and in a format that is machine-readable and easy-to-use. The emissions data are also aggregated into
basketsof gases using global warming equivalency metrics from IPCC reports.
Johannes Gütschow, M. Louise Jeffery, Robert Gieseke, Ronja Gebel, David Stevens, Mario Krapp, and Marcia Rocha
Earth Syst. Sci. Data, 8, 571–603, https://doi.org/10.5194/essd-8-571-2016, https://doi.org/10.5194/essd-8-571-2016, 2016
Short summary
Short summary
This paper provides the methodology for the creation of historical country-resolved time series of greenhouse gas emissions from different datasets which are individually incomplete in terms of years, gases, and/or countries. The combination of datasets is carried out using the PRIMAP model (www.primap.org). The resulting time series can be viewed interactively on www.pik-potsdam.de/primap-live. It will be used for climate policy analysis, e.g. the historical responsibility for climate change.
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
Short summary
Short summary
We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Francesco N. Tubiello, Kevin Karl, Alessandro Flammini, Johannes Gütschow, Griffiths Obli-Laryea, Giulia Conchedda, Xueyao Pan, Sally Yue Qi, Hörn Halldórudóttir Heiðarsdóttir, Nathan Wanner, Roberta Quadrelli, Leonardo Rocha Souza, Philippe Benoit, Matthew Hayek, David Sandalow, Erik Mencos Contreras, Cynthia Rosenzweig, Jose Rosero Moncayo, Piero Conforti, and Maximo Torero
Earth Syst. Sci. Data, 14, 1795–1809, https://doi.org/10.5194/essd-14-1795-2022, https://doi.org/10.5194/essd-14-1795-2022, 2022
Short summary
Short summary
The paper presents results from the new FAOSTAT database on food system emissions, covering all countries over the time series 1990–2019. Results indicate and further clarify – updated to 2019 – the relevance of emissions from crop and livestock production processes within the farm gate; from conversion of natural ecosystems to agriculture, such as deforestation and peat degradation; and from use of fossil fuels for energy and other industrial processes along food supply chains.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
Short summary
Short summary
We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Annika Günther, Johannes Gütschow, and Mairi Louise Jeffery
Geosci. Model Dev., 14, 5695–5730, https://doi.org/10.5194/gmd-14-5695-2021, https://doi.org/10.5194/gmd-14-5695-2021, 2021
Short summary
Short summary
The mitigation components of the nationally determined contributions (NDCs) under the Paris Agreement are essential in our fight against climate change. Regular updates with increased ambition are requested to limit global warming to 1.5–2 °C. The new and easy-to-update open-source tool NDCmitiQ can be used to quantify the NDCs' mitigation targets and construct resulting emissions pathways. In use cases, we show target uncertainties from missing clarity, data, and methodological challenges.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
Short summary
Short summary
We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Malte Meinshausen, Zebedee R. J. Nicholls, Jared Lewis, Matthew J. Gidden, Elisabeth Vogel, Mandy Freund, Urs Beyerle, Claudia Gessner, Alexander Nauels, Nico Bauer, Josep G. Canadell, John S. Daniel, Andrew John, Paul B. Krummel, Gunnar Luderer, Nicolai Meinshausen, Stephen A. Montzka, Peter J. Rayner, Stefan Reimann, Steven J. Smith, Marten van den Berg, Guus J. M. Velders, Martin K. Vollmer, and Ray H. J. Wang
Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, https://doi.org/10.5194/gmd-13-3571-2020, 2020
Short summary
Short summary
This study provides the future greenhouse gas (GHG) concentrations under the new set of so-called SSP scenarios (the successors of the IPCC SRES and previous representative concentration pathway (RCP) scenarios). The projected CO2 concentrations range from 350 ppm for low-emission scenarios by 2150 to more than 2000 ppm under the high-emission scenarios. We also provide concentrations, latitudinal gradients, and seasonality for most of the other 42 considered GHGs.
Anders Levermann, Ricarda Winkelmann, Torsten Albrecht, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Philippe Huybrechts, Jim Jordan, Gunter Leguy, Daniel Martin, Mathieu Morlighem, Frank Pattyn, David Pollard, Aurelien Quiquet, Christian Rodehacke, Helene Seroussi, Johannes Sutter, Tong Zhang, Jonas Van Breedam, Reinhard Calov, Robert DeConto, Christophe Dumas, Julius Garbe, G. Hilmar Gudmundsson, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, William H. Lipscomb, Malte Meinshausen, Esmond Ng, Sophie M. J. Nowicki, Mauro Perego, Stephen F. Price, Fuyuki Saito, Nicole-Jeanne Schlegel, Sainan Sun, and Roderik S. W. van de Wal
Earth Syst. Dynam., 11, 35–76, https://doi.org/10.5194/esd-11-35-2020, https://doi.org/10.5194/esd-11-35-2020, 2020
Short summary
Short summary
We provide an estimate of the future sea level contribution of Antarctica from basal ice shelf melting up to the year 2100. The full uncertainty range in the warming-related forcing of basal melt is estimated and applied to 16 state-of-the-art ice sheet models using a linear response theory approach. The sea level contribution we obtain is very likely below 61 cm under unmitigated climate change until 2100 (RCP8.5) and very likely below 40 cm if the Paris Climate Agreement is kept.
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
Geosci. Model Dev., 12, 4375–4385, https://doi.org/10.5194/gmd-12-4375-2019, https://doi.org/10.5194/gmd-12-4375-2019, 2019
Short summary
Short summary
Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.
M. Louise Jeffery, Johannes Gütschow, Robert Gieseke, and Ronja Gebel
Earth Syst. Sci. Data, 10, 1427–1438, https://doi.org/10.5194/essd-10-1427-2018, https://doi.org/10.5194/essd-10-1427-2018, 2018
Short summary
Short summary
Developed countries are required to report detailed greenhouse gas emissions data to the UN on an annual basis. The reporting tables are complex, do not fit well with existing hierarchical reporting guidelines, and are not machine-readable. We present a processed version of the reported data in a consistent hierarchy, and in a format that is machine-readable and easy-to-use. The emissions data are also aggregated into
basketsof gases using global warming equivalency metrics from IPCC reports.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
Short summary
Short summary
Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Alexander Nauels, Malte Meinshausen, Matthias Mengel, Katja Lorbacher, and Tom M. L. Wigley
Geosci. Model Dev., 10, 2495–2524, https://doi.org/10.5194/gmd-10-2495-2017, https://doi.org/10.5194/gmd-10-2495-2017, 2017
Short summary
Short summary
The MAGICC sea level model projects global sea level rise by emulating process-based estimates for all major sea level drivers and applying them to available climate scenarios and their extensions to 2300. The MAGICC sea level projections are well within the ranges of the fifth IPCC assessment report. Due to its efficient structure, this emulator is a powerful tool for exploring sea level uncertainties and investigating sea level responses for a wide range of climate mitigation pathways.
Malte Meinshausen, Elisabeth Vogel, Alexander Nauels, Katja Lorbacher, Nicolai Meinshausen, David M. Etheridge, Paul J. Fraser, Stephen A. Montzka, Peter J. Rayner, Cathy M. Trudinger, Paul B. Krummel, Urs Beyerle, Josep G. Canadell, John S. Daniel, Ian G. Enting, Rachel M. Law, Chris R. Lunder, Simon O'Doherty, Ron G. Prinn, Stefan Reimann, Mauro Rubino, Guus J. M. Velders, Martin K. Vollmer, Ray H. J. Wang, and Ray Weiss
Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, https://doi.org/10.5194/gmd-10-2057-2017, 2017
Short summary
Short summary
Climate change is primarily driven by human-induced increases of greenhouse gas (GHG) concentrations. Based on ongoing community efforts (e.g. AGAGE and NOAA networks, ice cores), this study presents historical concentrations of CO2, CH4, N2O and 40 other GHGs from year 0 to year 2014. The data is recommended as input for climate models for pre-industrial, historical runs under CMIP6. Global means, but also latitudinal by monthly surface concentration fields are provided.
Johannes Gütschow, M. Louise Jeffery, Robert Gieseke, Ronja Gebel, David Stevens, Mario Krapp, and Marcia Rocha
Earth Syst. Sci. Data, 8, 571–603, https://doi.org/10.5194/essd-8-571-2016, https://doi.org/10.5194/essd-8-571-2016, 2016
Short summary
Short summary
This paper provides the methodology for the creation of historical country-resolved time series of greenhouse gas emissions from different datasets which are individually incomplete in terms of years, gases, and/or countries. The combination of datasets is carried out using the PRIMAP model (www.primap.org). The resulting time series can be viewed interactively on www.pik-potsdam.de/primap-live. It will be used for climate policy analysis, e.g. the historical responsibility for climate change.
T. Schneider von Deimling, G. Grosse, J. Strauss, L. Schirrmeister, A. Morgenstern, S. Schaphoff, M. Meinshausen, and J. Boike
Biogeosciences, 12, 3469–3488, https://doi.org/10.5194/bg-12-3469-2015, https://doi.org/10.5194/bg-12-3469-2015, 2015
Short summary
Short summary
We have modelled the carbon release from thawing permafrost soils under various scenarios of future warming. Our results suggests that up to about 140Pg of carbon could be released under strong warming by end of the century. We have shown that abrupt thaw processes under thermokarst lakes can unlock large amounts of perennially frozen carbon stored in deep deposits (which extend many metres into the soil).
Related subject area
Antroposphere – Energy and Emissions
Global Carbon Budget 2021
Pre- and post-production processes increasingly dominate greenhouse gas emissions from agri-food systems
High-resolution spatial-distribution maps of road transport exhaust emissions in Chile, 1990–2020
Estimating CO2 emissions for 108 000 European cities
Emissions of greenhouse gases from energy use in agriculture, forestry and fisheries: 1970–2019
A global seamless 1 km resolution daily land surface temperature dataset (2003–2020)
High-resolution inventory of atmospheric emissions from transport, industrial, energy, mining and residential activities in Chile
PAPILA dataset: a regional emission inventory of reactive gases for South America based on the combination of local and global information
Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery
Global anthropogenic CO2 emissions and uncertainties as a prior for Earth system modelling and data assimilation
A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019
High-resolution seasonal and decadal inventory of anthropogenic gas-phase and particle emissions for Argentina
African anthropogenic emissions inventory for gases and particles from 1990 to 2015
Global Covenant of Mayors, a dataset of greenhouse gas emissions for 6200 cities in Europe and the Southern Mediterranean countries
Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI
Global CO2 uptake by cement from 1930 to 2019
CDIAC-FF: global and national CO2 emissions from fossil fuel combustion and cement manufacture: 1751–2017
Facility-scale inventory of dairy methane emissions in California: implications for mitigation
A comparative study of anthropogenic CH4 emissions over China based on the ensembles of bottom-up inventories
Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling
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)
Timely estimates of India's annual and monthly fossil CO2 emissions
A comparison of estimates of global carbon dioxide emissions from fossil carbon sources
Spatio-temporal assessment of the polychlorinated biphenyl (PCB) sediment contamination in four major French river corridors (1945–2018)
Global Carbon Budget 2019
Global CO2 emissions from cement production, 1928–2018
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Francesco N. Tubiello, Kevin Karl, Alessandro Flammini, Johannes Gütschow, Griffiths Obli-Laryea, Giulia Conchedda, Xueyao Pan, Sally Yue Qi, Hörn Halldórudóttir Heiðarsdóttir, Nathan Wanner, Roberta Quadrelli, Leonardo Rocha Souza, Philippe Benoit, Matthew Hayek, David Sandalow, Erik Mencos Contreras, Cynthia Rosenzweig, Jose Rosero Moncayo, Piero Conforti, and Maximo Torero
Earth Syst. Sci. Data, 14, 1795–1809, https://doi.org/10.5194/essd-14-1795-2022, https://doi.org/10.5194/essd-14-1795-2022, 2022
Short summary
Short summary
The paper presents results from the new FAOSTAT database on food system emissions, covering all countries over the time series 1990–2019. Results indicate and further clarify – updated to 2019 – the relevance of emissions from crop and livestock production processes within the farm gate; from conversion of natural ecosystems to agriculture, such as deforestation and peat degradation; and from use of fossil fuels for energy and other industrial processes along food supply chains.
Mauricio Osses, Néstor Rojas, Cecilia Ibarra, Víctor Valdebenito, Ignacio Laengle, Nicolás Pantoja, Darío Osses, Kevin Basoa, Sebastián Tolvett, Nicolás Huneeus, Laura Gallardo, and Benjamín Gómez
Earth Syst. Sci. Data, 14, 1359–1376, https://doi.org/10.5194/essd-14-1359-2022, https://doi.org/10.5194/essd-14-1359-2022, 2022
Short summary
Short summary
This paper presents a detailed estimate of on-road vehicle emissions for Chile, between 1990–2020, and an analysis of emission trends for greenhouse gases and local pollutants. Data are disaggregated by type of vehicle and region at 0.01° × 0.01°. While the vehicle fleet grew 5-fold, CO2 emissions increased at a lower rate and local pollutants decreased. These trends can be explained by changes in improved vehicle technologies, better fuel quality and enforcement of emission standards.
Daniel Moran, Peter-Paul Pichler, Heran Zheng, Helene Muri, Jan Klenner, Diogo Kramel, Johannes Többen, Helga Weisz, Thomas Wiedmann, Annemie Wyckmans, Anders Hammer Strømman, and Kevin R. Gurney
Earth Syst. Sci. Data, 14, 845–864, https://doi.org/10.5194/essd-14-845-2022, https://doi.org/10.5194/essd-14-845-2022, 2022
Short summary
Short summary
This paper presents the modeling methods used for the website https://openghgmap.net, which provides estimates of CO2 emissions for 108 000 European cities.
Alessandro Flammini, Xueyao Pan, Francesco Nicola Tubiello, Sally Yue Qiu, Leonardo Rocha Souza, Roberta Quadrelli, Stefania Bracco, Philippe Benoit, and Ralph Sims
Earth Syst. Sci. Data, 14, 811–821, https://doi.org/10.5194/essd-14-811-2022, https://doi.org/10.5194/essd-14-811-2022, 2022
Short summary
Short summary
Fossil-fuel-based energy used in agriculture, for crop and livestock production as well as in fisheries, generates significant amounts of greenhouse gases (GHG), which are typically not accounted for within the agriculture sector of national GHG inventories. Using activity data from UNSD and IEA, we construct a new database of energy use in agriculture and related emissions, covering the period 1970–2019 by country and by fossil fuel type, including emissions from electricity used on the farm.
Tao Zhang, Yuyu Zhou, Zhengyuan Zhu, Xiaoma Li, and Ghassem R. Asrar
Earth Syst. Sci. Data, 14, 651–664, https://doi.org/10.5194/essd-14-651-2022, https://doi.org/10.5194/essd-14-651-2022, 2022
Short summary
Short summary
We generated a global seamless 1 km daily (mid-daytime and mid-nighttime) land surface temperature (LST) dataset (2003–2020) using MODIS LST products by proposing a spatiotemporal gap-filling framework. The average root mean squared errors of the gap-filled LST are 1.88°C and 1.33°C, respectively, in mid-daytime and mid-nighttime. The global seamless LST dataset is unique and of great use in studies on urban systems, climate research and modeling, and terrestrial ecosystem studies.
Nicolás Álamos, Nicolás Huneeus, Mariel Opazo, Mauricio Osses, Sebastián Puja, Nicolás Pantoja, Hugo Denier van der Gon, Alejandra Schueftan, René Reyes, and Rubén Calvo
Earth Syst. Sci. Data, 14, 361–379, https://doi.org/10.5194/essd-14-361-2022, https://doi.org/10.5194/essd-14-361-2022, 2022
Short summary
Short summary
This study presents the first high-resolution national inventory of anthropogenic emissions for Chile (Inventario Nacional de Emisiones Antropogénicas, INEMA). Emissions for vehicular, industrial, energy, mining and residential sectors are estimated for the period 2015–2017 and spatially distributed onto a high-resolution grid (1 × 1 km). This inventory will support policies seeking to mitigate climate change and improve air quality by providing qualified scientific spatial emission information.
Paula Castesana, Melisa Diaz Resquin, Nicolás Huneeus, Enrique Puliafito, Sabine Darras, Darío Gómez, Claire Granier, Mauricio Osses Alvarado, Néstor Rojas, and Laura Dawidowski
Earth Syst. Sci. Data, 14, 271–293, https://doi.org/10.5194/essd-14-271-2022, https://doi.org/10.5194/essd-14-271-2022, 2022
Short summary
Short summary
This work presents the results of the first joint effort of South American and European researchers to generate regional maps of emissions. The PAPILA dataset is a collection of annual emission inventories of reactive gases (CO, NOx, NMVOCs, NH3, and SO2) from anthropogenic sources in the region for the period 2014–2016. This was developed on the basis of the CAMS-GLOB-ANT v4.1 dataset, enriching it with derived data from locally available emission inventories for Argentina, Chile, and Colombia.
Hou Jiang, Ling Yao, Ning Lu, Jun Qin, Tang Liu, Yujun Liu, and Chenghu Zhou
Earth Syst. Sci. Data, 13, 5389–5401, https://doi.org/10.5194/essd-13-5389-2021, https://doi.org/10.5194/essd-13-5389-2021, 2021
Short summary
Short summary
A multi-resolution (0.8, 0.3, and 0.1 m) photovoltaic (PV) dataset is established using satellite and aerial images. The dataset contains 3716 samples of PVs installed on various land and rooftop types. The dataset can support multi-scale PV segmentation (e.g., concentrated PVs, distributed ground PVs, and fine-grained rooftop PVs) and cross applications between different resolutions (e.g., from satellite to aerial samples and vice versa), as well as other research related to PVs.
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.
S. Enrique Puliafito, Tomás R. Bolaño-Ortiz, Rafael P. Fernandez, Lucas L. Berná, Romina M. Pascual-Flores, Josefina Urquiza, Ana I. López-Noreña, and María F. Tames
Earth Syst. Sci. Data, 13, 5027–5069, https://doi.org/10.5194/essd-13-5027-2021, https://doi.org/10.5194/essd-13-5027-2021, 2021
Short summary
Short summary
GEAA-AEIv3.0M atmospheric emissions inventory is the first high-spatial-resolution inventory (approx. 2.5 km × 2.5 km) with monthly variability from 1995 to 2020, including greenhouse gases, ozone precursors, acidifying gases, and particulate matter, from all Argentine productive activities. The main benefit of GEAA-AEIv3.0M is to map emissions with better temporal resolution to support air quality and climate modeling, to evaluate pollutant mitigation strategies by Argentine decision makers.
Sekou Keita, Catherine Liousse, Eric-Michel Assamoi, Thierno Doumbia, Evelyne Touré N'Datchoh, Sylvain Gnamien, Nellie Elguindi, Claire Granier, and Véronique Yoboué
Earth Syst. Sci. Data, 13, 3691–3705, https://doi.org/10.5194/essd-13-3691-2021, https://doi.org/10.5194/essd-13-3691-2021, 2021
Short summary
Short summary
This inventory fills the gap in African regional inventories, providing biofuel and fossil fuel emissions that take into account African specificities. It could be used for air quality modeling. We show that all pollutant emissions are globally increasing during the period 1990–2015. Also, West Africa and East Africa emissions are largely due to domestic fire and traffic activities, while southern Africa and northern Africa emissions are largely due to industrial and power plant sources.
Albana Kona, Fabio Monforti-Ferrario, Paolo Bertoldi, Marta Giulia Baldi, Georgia Kakoulaki, Nadja Vetters, Christian Thiel, Giulia Melica, Eleonora Lo Vullo, Alessandra Sgobbi, Christofer Ahlgren, and Brieuc Posnic
Earth Syst. Sci. Data, 13, 3551–3564, https://doi.org/10.5194/essd-13-3551-2021, https://doi.org/10.5194/essd-13-3551-2021, 2021
Short summary
Short summary
The Global Covenant of Mayors for Climate & Energy (GCoM), the largest international initiative to promote climate action at the city level, has collected a large amount of information on urban greenhouse gas emissions.
Here we present the harmonised, completed and verified GCoM emission dataset, originating from 6200 cities among its signatories, complemented with a set of useful ancillary data. This knowledge will contribute to covering the lack of consistent datasets of cities' emissions.
Steffen Beirle, Christian Borger, Steffen Dörner, Henk Eskes, Vinod Kumar, Adrianus de Laat, and Thomas Wagner
Earth Syst. Sci. Data, 13, 2995–3012, https://doi.org/10.5194/essd-13-2995-2021, https://doi.org/10.5194/essd-13-2995-2021, 2021
Short summary
Short summary
A catalog of point sources of nitrogen oxides was created using satellite observations of NO2. Key for the identification of point sources was the divergence, i.e., the difference between upwind and downwind levels of NO2.
The catalog lists 451 locations, of which 242 could be automatically matched to power plants. Other point sources are metal smelters, cement plants, or industrial areas. The catalog thus allows checking and improving of existing emission inventories.
Rui Guo, Jiaoyue Wang, Longfei Bing, Dan Tong, Philippe Ciais, Steven J. Davis, Robbie M. Andrew, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 13, 1791–1805, https://doi.org/10.5194/essd-13-1791-2021, https://doi.org/10.5194/essd-13-1791-2021, 2021
Short summary
Short summary
Using a life-cycle approach, we estimated the CO2 process emission and uptake of cement materials produced and consumed from 1930 to 2019; ~21 Gt of CO2, about 55 % of the total process emission, had been abated through cement carbonation. China contributed the greatest to the cumulative uptake, with more than 6 Gt (~30 % of the world total), while ~59 %, or more than 12 Gt, of the total uptake was attributed to mortar. Cement CO2 uptake makes up a considerable part of the human carbon budget.
Dennis Gilfillan and Gregg Marland
Earth Syst. Sci. Data, 13, 1667–1680, https://doi.org/10.5194/essd-13-1667-2021, https://doi.org/10.5194/essd-13-1667-2021, 2021
Alison R. Marklein, Deanne Meyer, Marc L. Fischer, Seongeun Jeong, Talha Rafiq, Michelle Carr, and Francesca M. Hopkins
Earth Syst. Sci. Data, 13, 1151–1166, https://doi.org/10.5194/essd-13-1151-2021, https://doi.org/10.5194/essd-13-1151-2021, 2021
Short summary
Short summary
Dairy cow farms produce half of California's (CA) methane (CH4) emissions. Current CH4 emission inventories lack regional variation in management and are inadequate to assess CH4 mitigation measures. We develop a spatial database of CH4 emissions for CA dairy farms including farm-scale herd demographics and management data. This database is useful to predict CH4 emission reductions from mitigation efforts, to compare with atmospheric CH4 observations and to attribute emissions to specific farms.
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.
Marc Guevara, Oriol Jorba, Carles Tena, Hugo Denier van der Gon, Jeroen Kuenen, Nellie Elguindi, Sabine Darras, Claire Granier, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, https://doi.org/10.5194/essd-13-367-2021, 2021
Short summary
Short summary
The temporal variability of atmospheric emissions is linked to changes in activity patterns, emission processes and meteorology. Accounting for the change in temporal emission characteristics is a key aspect for modelling the trends of air pollutants. This work presents a dataset of global and European emission temporal profiles to be used for air quality modelling purposes. The profiles were constructed considering the influences of local sociodemographic factors and climatological conditions.
Erin E. McDuffie, Steven J. Smith, Patrick O'Rourke, Kushal Tibrewal, Chandra Venkataraman, Eloise A. Marais, Bo Zheng, Monica Crippa, Michael Brauer, and Randall V. Martin
Earth Syst. Sci. Data, 12, 3413–3442, https://doi.org/10.5194/essd-12-3413-2020, https://doi.org/10.5194/essd-12-3413-2020, 2020
Short summary
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.
Robbie M. Andrew
Earth Syst. Sci. Data, 12, 2411–2421, https://doi.org/10.5194/essd-12-2411-2020, https://doi.org/10.5194/essd-12-2411-2020, 2020
Short summary
Short summary
India is the world's third-largest emitter of carbon dioxide and is developing rapidly. While India has pledged an emissions-intensity reduction as its contribution to the Paris Agreement, the country does not regularly report emissions statistics, making tracking progress difficult. Here I compile monthly energy and industrial activity data, allowing for the production of estimates of India's CO2 emissions by month and calendar year.
Robbie M. Andrew
Earth Syst. Sci. Data, 12, 1437–1465, https://doi.org/10.5194/essd-12-1437-2020, https://doi.org/10.5194/essd-12-1437-2020, 2020
Short summary
Short summary
There are now several global datasets with estimates of global CO2 emissions from fossil sources, but the totals from these differ. Sometimes the range of these estimates has been used to indicate uncertainty in global emissions. In this paper I discuss the reasons why these datasets differ, particularly their different system boundaries: which emissions sources are included and which are omitted. Analysis is both qualitative and quantitative.
André-Marie Dendievel, Brice Mourier, Alexandra Coynel, Olivier Evrard, Pierre Labadie, Sophie Ayrault, Maxime Debret, Florence Koltalo, Yoann Copard, Quentin Faivre, Thomas Gardes, Sophia Vauclin, Hélène Budzinski, Cécile Grosbois, Thierry Winiarski, and Marc Desmet
Earth Syst. Sci. Data, 12, 1153–1170, https://doi.org/10.5194/essd-12-1153-2020, https://doi.org/10.5194/essd-12-1153-2020, 2020
Short summary
Short summary
Polychlorinated biphenyl indicators (ΣPCBi) from sediment cores, bed and flood deposits, suspended particulate matter, and dredged sediments along the major French rivers (1945–2018) are compared with socio-hydrological drivers. ΣPCBi increased from 1945 to the 1990s due to urban and industrial emissions. It gradually decreased with the implementation of regulations. Specific ΣPCBi fluxes reveal the amount of PCB-polluted sediment transported by French rivers to European seas over 40 years.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
Short summary
Short summary
The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Robbie M. Andrew
Earth Syst. Sci. Data, 11, 1675–1710, https://doi.org/10.5194/essd-11-1675-2019, https://doi.org/10.5194/essd-11-1675-2019, 2019
Short summary
Short summary
Global production of cement has grown very rapidly in recent years, and, after fossil fuels and land-use change, it is the third-largest source of society's emissions of carbon dioxide. This paper draws on a large variety of available datasets, prioritising official data and emission factors, to produce both global and country-level estimates of these
processemissions from cement production.
Cited articles
Andres, R. J., Fielding, D. J., Marland, G., Boden, T. A., Kumar, N., and
Kearney, A. T.: Carbon Dioxide Emissions from Fossil-Fuel Use, Tellus B, 51, 759–765,
https://doi.org/10.1034/j.1600-0889.1999.t01-3-00002.x, 1999. a, b
Boden, T., Marland, G., and Andres, R.: Global, Regional, and National
Fossil-Fuel CO2 Emissions,
Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, USA,
https://doi.org/10.3334/CDIAC/00001_V2017, 2017. a, b
Bolt, J. and van Zanden, J. L.: The Maddison Project: Collaborative
Research on Historical National Accounts, Econ. Hist. Rev., 67,
627–651, https://doi.org/10.1111/1468-0289.12032, 2014. a
Calvin, K., Bond-Lamberty, B., Clarke, L., Edmonds, J., Eom, J., Hartin, C.,
Kim, S., Kyle, P., Link, R., Moss, R., McJeon, H., Patel, P., Smith, S.,
Waldhoff, S., and Wise, M.: The SSP4: A World of Deepening
Inequality, Global Environ. Chang., 42, 284–296,
https://doi.org/10.1016/j.gloenvcha.2016.06.010, 2017. a, b, c, d
Chang, C.-P. and Lee, C.-C.: Are per Capita Carbon Dioxide Emissions Converging
among Industrialized Countries? New Time Series Evidence with Structural
Breaks, Environ. Dev. Econ., 13, 497–515,
https://doi.org/10.1017/S1355770X08004361, 2008. a
Chertow, M.: The IPAT Equation and Its Variants, J. Ind.
Ecol., 4, 13–29,
2000. a
Climate Analytics and New Climate Institute: Climate Action Tracker, available at:
https://climateactiontracker.org/, last access: 31 January 2020. a
Crespo Cuaresma, J.: Income Projections for Climate Change Research: A
Framework Based on Human Capital Dynamics, Global Environ. Chang., 42,
226–236, https://doi.org/10.1016/j.gloenvcha.2015.02.012, 2017. a, b
Dellink, R., Chateau, J., Lanzi, E., and Magné, B.: Long-Term Economic
Growth Projections in the Shared Socioeconomic Pathways, Global
Environ. Chang., 42, 200–2014, https://doi.org/10.1016/j.gloenvcha.2015.06.004,
2017. a, b, c, d
du Pont, Y. R., Jeffery, M. L., Gütschow, J., Christoff, P., and
Meinshausen, M.: National Contributions for Decarbonizing the World Economy
in Line with the G7 Agreement, Environ. Res. Lett., 11,
054005, https://doi.org/10.1088/1748-9326/11/5/054005, 2016. a
Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Farahani, E., Kadner, S.,
Seyboth, K., Adler, A., Baum, I., Brunner, S., Eickemeier, P., Kriemann, B.,
Savolainen, J., Schlömer, S., von Stechow, C., Zwickel, T., and Minx, J.: Climate Change 2014: Mitigation of Climate Change:
Working Group III Contribution to the Fifth Assessment Report of the
Intergovernmental Panel On Climate Change, Cambridge University Press, Cambridge, UK,, available at:
https://www.ipcc.ch/report/ar5/wg3/ (last access: 22 February 2016), 2014. a
Ehrlich, P. R. and Holdren, J. P.: Impact of Population Growth, Science,
171, 1212–1217, 1971. a
Feenstra, R. C., Inklaar, R., and Timmer, M. P.: The Next Generation of the
Penn World Table, Am. Econ. Rev., 105, 3150–3182,
https://doi.org/10.1257/aer.20130954, 2015. a, b
Feenstra, R. C., Inklaar, R., and Timmer, M. P.: Penn World Table Version
9.1,
Am. Econ. Rev., 105, 3150–3182,
https://doi.org/10.15141/S50T0R, 2019. a, b
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. a
Fricko, O., Havlik, P., Rogelj, J., Klimont, Z., Gusti, M., Johnson, N., Kolp,
P., Strubegger, M., Valin, H., Amann, M., Ermolieva, T., Forsell, N.,
Herrero, M., Heyes, C., Kindermann, G., Krey, V., McCollum, D. L.,
Obersteiner, M., Pachauri, S., Rao, S., Schmid, E., Schoepp, W., and Riahi,
K.: The Marker Quantification of the Shared Socioeconomic Pathway 2:
A Middle-of-the-Road Scenario for the 21st Century, Global Environ.
Chang., 42, 251–267, https://doi.org/10.1016/j.gloenvcha.2016.06.004, 2017. a, b
Fujimori, S., Hasegawa, T., Masui, T., Takahashi, K., Herran, D. S., Dai, H.,
Hijioka, Y., and Kainuma, M.: SSP3: AIM Implementation of Shared
Socioeconomic Pathways, Global Environ. Chang., 42, 268–283,
https://doi.org/10.1016/j.gloenvcha.2016.06.009, 2017. a, b
Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850–2005) harmonized with future projections according to the Shared Socio-economic Pathways (2006–2100), Earth Syst. Sci. Data, 10, 847–856, https://doi.org/10.5194/essd-10-847-2018, 2018. a
Geiger, T. and Frieler, K.: Continuous National Gross Domestic Product
(GDP) Time Series for 195 Countries: Past Observations (1850–2005)
Harmonized with Future Projections According the Shared Socio-Economic
Pathways (2006–2100), GFZ Data Services, https://doi.org/10.5880/pik.2017.003, 2017. a
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. a, b, c
Gütschow, J.: The PRIMAP-Hist Socio-Eco Historical GDP and
Population Time Series (1850–2017) (v2.1), GFZ Data Services, https://doi.org/10.5880/PIK.2019.019, 2019. a, b, c
Gütschow, J., Jeffery, M. L., Gieseke, R., Gebel, R., Stevens, D., Krapp, M., and Rocha, M.: The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571–603, https://doi.org/10.5194/essd-8-571-2016, 2016. a, b, c
Gütschow, J., Jeffery, M. L., Gieseke, R., and Gebel, R.: The
PRIMAP-Hist National Historical Emissions Time Series (1850–2015) (v1.2), GFZ Data Services,
https://doi.org/10.5880/PIK.2018.003, 2018. a, b
Gütschow, J., Jeffery, M. L., Günther, A., and Meinshausen, M.: Country
Resolved Combined Emission and Socio-Economic Pathways Based on the RCP
and SSP Scenarios, Zenodo, https://doi.org/10.5281/zenodo.3638137, 2020. a, b, c
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. a, b, c
Höhne, N., Blum, H., Fuglestvedt, J., Skeie, R. B., Kurosawa, A., Hu, G.,
Lowe, J., Gohar, L., Matthews, B., Nioac de Salles, A. C., and Ellermann,
C.: Contributions of Individual Countries' Emissions to Climate Change and
Their Uncertainty, Climatic Change, 106, 359–391,
https://doi.org/10.1007/s10584-010-9930-6, 2010. a, b
Houghton, J. T., Meira Filho, L., Callander, B., Harris, N., Kattenberg, A.,
and Maskell, K.: Climate Change 1995, The Science of Climate
Change, Cambridge University Press, Cambridge, UK, 1996. a
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., Bergamaschi, P., Pagliari, V., Olivier, J. G. J., Peters, J. A. H. W., van Aardenne, J. A., Monni, S., Doering, U., Petrescu, A. M. R., Solazzo, E., and Oreggioni, G. D.: EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012, Earth Syst. Sci. Data, 11, 959–1002, https://doi.org/10.5194/essd-11-959-2019, 2019. a
Jewell, J. and Anderson, K.: Climate-Policy Models Debated, Nature, 573,
448–449, 2019. a
Jiang, L. and O'Neill, B. C.: Global Urbanization Projections for the Shared
Socioeconomic Pathways, Global Environ. Chang., 42, 192–199,
https://doi.org/10.1016/j.gloenvcha.2015.03.008, 2017. a
Jobert, T., Karanfil, F., and Tykhonenko, A.: Convergence of per Capita Carbon
Dioxide Emissions in the EU: Legend or Reality?, Energ. Econ.,
32, 1364–1373, https://doi.org/10.1016/j.eneco.2010.03.005, 2010. a
JRC and PBL: Emission Database for Global Atmospheric Research
Release Version 4.3.2, EDGAR, https://doi.org/10.2904/JRC_DATASET_EDGAR, 2017. a
KC, S. and Lutz, W.: The Human Core of the Shared Socioeconomic Pathways:
Population Scenarios by Age, Sex and Level of Education for All Countries
to 2100, Global Environ. Chang., 42, 181–192,
https://doi.org/10.1016/j.gloenvcha.2014.06.004, 2017. a, b, c, d
Klein Goldewijk, C.: Anthropogenic Land-Use Estimates for the Holocene,
HYDE 3.2, DANS, https://doi.org/10.17026/dans-25g-gez3, 2017. a
Klein Goldewijk, K., Beusen, A., Doelman, J., and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, 2017. a
Kriegler, E., Bauer, N., Popp, A., Humpenöder, F., Leimbach, M., Strefler,
J., Baumstark, L., Bodirsky, B. L., Hilaire, J., Klein, D., Mouratiadou, I.,
Weindl, I., Bertram, C., Dietrich, J.-P., Luderer, G., Pehl, M., Pietzcker,
R., Piontek, F., Lotze-Campen, H., Biewald, A., Bonsch, M., Giannousakis,
A., Kreidenweis, U., Müller, C., Rolinski, S., Schultes, A., Schwanitz,
J., Stevanovic, M., Calvin, K., Emmerling, J., Fujimori, S., and Edenhofer,
O.: Fossil-Fueled Development (SSP5): An Energy and Resource
Intensive Scenario for the 21st Century, Global Environ. Chang., 42,
297–315, https://doi.org/10.1016/j.gloenvcha.2016.05.015, 2017. a, b
Landman, W.: Book Review: Climate Change 2007: The Physical Science Basis, S. Afr. Geogr. J., 92, 86–87, https://doi.org/10.1080/03736245.2010.480842, 2010. a
Leimbach, M., Kriegler, E., Roming, N., and Schwanitz, J.: Future Growth
Patterns of World Regions – A GDP Scenario Approach, Global
Environ. Chang., 42, 215–225, https://doi.org/10.1016/j.gloenvcha.2015.02.005,
2017. a, b
Liddle, B.: Revisiting World Energy Intensity Convergence for Regional
Differences, Appl. Energ., 87, 3218–3225,
https://doi.org/10.1016/j.apenergy.2010.03.030, 2010. a, b
Maddison Project: The Maddison Project 2013 Version, available at:
http://www.ggdc.net/maddison/maddison-project/home.htm (last access: 16 June 2017), 2013. a
Markandya, A., Pedroso-Galinato, S., and Streimikiene, D.: Energy Intensity
in Transition Economies: Is There Convergence towards the EU
Average?, Energ. Econ., 28, 121–145, https://doi.org/10.1016/j.eneco.2005.10.005,
2006. a, b
Marland, G. and Rotty, R. M.: Carbon Dioxide Emissions from Fossil Fuels: A
Procedure for Estimation and Results for 1950–1982, Tellus B, 36, 232–261,
https://doi.org/10.1111/j.1600-0889.1984.tb00245.x, 1984. a, b
Masui, T., Matsumoto, K., Hijioka, Y., Kinoshita, T., Nozawa, T., Ishiwatari,
S., Kato, E., Shukla, P. R., Yamagata, Y., and Kainuma, M.: An Emission
Pathway for Stabilization at 6 Wm−2 Radiative Forcing, Climatic Change,
109, 59–76, https://doi.org/10.1007/s10584-011-0150-5, 2011. a
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T.,
Lamarque, J.-F., Matsumoto, K., Montzka, S., Raper, S. C. B., Riahi, K.,
Thomson, A., Velders, G. J. M., and Vuuren, D. P.: The RCP Greenhouse Gas
Concentrations and Their Extensions from 1765 to 2300, Climatic Change, 109,
213–241, https://doi.org/10.1007/s10584-011-0156-z, 2011. a
Meinshausen, M., Jeffery, L., Guetschow, J., Robiou du Pont, Y., Rogelj, J.,
Schaeffer, M., Höhne, N., den Elzen, M., Oberthür, S., and
Meinshausen, N.: National Post-2020 Greenhouse Gas Targets and
Diversity-Aware Leadership, Nat. Clim. Change, 5, 1098–1106,
https://doi.org/10.1038/nclimate2826, 2015. a
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017. a
Moss, R. H., Edmonds, J., Hibbard, K., Manning, M. R., Rose, S. K., van
Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G.,
Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer,
R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next
Generation of Scenarios for Climate Change Research and Assessment, Nature,
463, 747–56, https://doi.org/10.1038/nature08823, 2010. a
Nakicenovic, N. and Swart, R.: Special Report on Emissions Scenarios:
A Special Report of Working Group III of the Intergovernmental
Panel on Climate Change, Cambridge University Press, Cambridge, UK,
2000. a
Nakicenovic, N., Alcamo, J., Davis, G., de Vries, B., Fenhann, J., Gaffin,
S., Gregory, K., Grübler, A., Yong Jung, T., Kram, T., La Rovere, E. L.,
Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L.,
Riahi, K., Roehrl, A., Rogner, H.-H., Sankovski, A., Schlesinger, M., Shukla,
P., Smith, S., Swart, R., van Rooijen, S., Victor, N., and Dadi, Z.:
Emissions Scenarios, Special Report of Working Group III of the
Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK,
2000. a
Nakicenovic, N., Lempert, R. J., and Janetos, A. C.: A Framework for the
Development of New Socio-Economic Scenarios for Climate Change
Research: Introductory Essay, Climatic Change, 122, 351–361,
https://doi.org/10.1007/s10584-013-0982-2, 2014. a
Ordás Criado, C. and Grether, J.-M.: Convergence in per Capita CO2
Emissions: A Robust Distributional Approach, Resour. Energy
Econ., 33, 637–665, https://doi.org/10.1016/j.reseneeco.2011.01.003, 2011. a
Owen, B., Lee, D. S., and Lim, L.: Flying into the Future: Aviation Emissions
Scenarios to 2050, Environ. Sci. Technol., 44, 2255–2260,
https://doi.org/10.1021/es902530z, 2010. a
Panopoulou, E. and Pantelidis, T.: Club Convergence in Carbon Dioxide
Emissions, Environ. Resour. Econ., 44, 47–70,
https://doi.org/10.1007/s10640-008-9260-6, 2009. a
Peters, G. P., Andrew, R. M., Canadell, J. G., Fuss, S., Jackson, R. B.,
Korsbakken, J. I., Le Quéré, C., and Nakicenovic, N.: Key Indicators
to Track Current Progress and Future Ambition of the Paris Agreement,
Nat. Clim. Change, 7, 118–122, https://doi.org/10.1038/nclimate3202, 2017. a
PRIMAP: Paris Reality Check, available at:
https://www.pik-potsdam.de/paris-reality-check/ (last access: 2 January 2020), 2020. a
QUANTIFY: QUANTIFY Project Website, available at:
https://www.pa.op.dlr.de/quantify/ (last access: 5 February 2017), 2010. a
Riahi, K., Grübler, A., and Nakicenovic, N.: Scenarios of Long-Term
Socio-Economic and Environmental Development under Climate Stabilization,
Technol. Forecast. Soc., 74, 887–935,
https://doi.org/10.1016/j.techfore.2006.05.026, 2007. a
Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann,
G., Nakicenovic, N., and Rafaj, P.: RCP 8.5 – A Scenario of
Comparatively High Greenhouse Gas Emissions, Climatic Change, 109, 33–57,
https://doi.org/10.1007/s10584-011-0149-y, 2011. a
Riahi, K., van Vuuren, D., Kriegler, E., Edmonds, J., O'Neill, B., Fujimori,
S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A.,
Cuaresma, C. J., Samir, K., Leimback, M., Jiang, L., Kram, T., Rao, S.,
Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F.,
Da Silva, L., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D.,
Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G.,
Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J., Kainuma, M., Klimont,
Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A., and
Tavoni, M.: The Shared Socioeconomic Pathways and Their Energy, Land Use, and
Greenhouse Gas Emissions Implications: An Overview, Global Environ.
Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009, 2017. a, b, c, d, e, f, g, h
Robiou du Pont, Y. and Meinshausen, M.: Warming Assessment of the Bottom-up
Paris Agreement Emissions Pledges, Nat. Commun., 9, 4810,
https://doi.org/10.1038/s41467-018-07223-9, 2018. a
Robiou du Pont, Y., Jeffery, M. L., Gütschow, J., Rogelj, J., Christoff,
P., and Meinshausen, M.: Equitable Mitigation to Achieve the Paris
Agreement Goals, Nat. Clim. Change, 7, 38–43,
https://doi.org/10.1038/nclimate3186, 2016. a
Rogelj, J., Popp, A., Calvin, K. V., Luderer, G., Emmerling, J., Gernaat, D.,
Fujimori, S., Strefler, J., Hasegawa, T., Marangoni, G., Krey, V., Kriegler,
E., Riahi, K., van Vuuren, D. P., Doelman, J., Drouet, L., Edmonds, J.,
Fricko, O., Harmsen, M., Havlík, P., Humpenöder, F., Stehfest, E.,
and Tavoni, M.: Scenarios towards Limiting Global Mean Temperature Increase
below 1.5 ∘C, Nat. Clim. Change, 8, 325–332,
https://doi.org/10.1038/s41558-018-0091-3, 2018. a, b, c, d, e, f
Romero-Ávila, D.: Convergence in Carbon Dioxide Emissions among
Industrialised Countries Revisited, Energ. Econ., 30, 2265–2282,
https://doi.org/10.1016/j.eneco.2007.06.003, 2008. a
Smith, T., Jalkanen, J., Anderson, B., Corbett, J., Faber, J., Hanayama, S.,
O'Keeffe, E., Parker, S., Johansson, L., Aldous, L., Raucci, C., Traut, M.,
Ettinger, S., Nelissen, D., Lee, D., Ng, S., Agrawal, A., Winebrake, J.,
Hoen, M., and Pandey, A.: Third IMO GHG Study 2014: Executive Summary
and Final Report, International Maritime Organization, available at:
http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Documents/Third%20Greenhouse%20Gas%20Study/GHG3%20Executive%20Summary%20and%20Report.pdf (last access: 21 January 2020),
2014. a
SSP: SSP Model Documentation, available at:
https://tntcat.iiasa.ac.at/SspDb/download/iam_scenario_doc/SSP_Model_Documentation.pdf (last access: 9 January 2020),
2015. a
Stegman, A. and McKibbin, W. J.: Convergence and per Capita Carbon Emissions,
Brookings Discussion Papers in International Economics, available at:
https://www.brookings.edu/research/convergence-and-per-capita-carbon-emissions/ (last access: 8 August 2013),
2005. a
Strazicich, M. and List, J.: Are CO2 Emission Levels Converging among
Industrial Countries?, Environ. Resour. Econ., 24, 263–271,
https://doi.org/10.1023/A:1022910701857, 2003. a
The World Bank: Global Purchasing Power Parities and Real Expenditures – 2005 International Comparison Program, The World Bank, available at:
http://pubdocs.worldbank.org/en/982121487105148964/2005ICPReport-FinalwithNewAppG.pdf (last access: 13 January 2020),
2008. a
The World Bank: Purchasing Power Parities and the Real Size of World
Economies: A Comprehensive Report of the 2011 International
Comparison Program, The World Bank, available at: https://elibrary.worldbank.org/doi/abs/10.1596/978-1-4648-0329-1 (last access: 13 January 2020),
2014. a
Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P.,
Delgado-Arias, S., Bond-Lamberty, B., Wise, M., Clarke, L. E., and
Edmonds, J.: RCP4.5: A Pathway for Stabilization of Radiative Forcing
by 2100, Climatic Change, 109, 77–94, https://doi.org/10.1007/s10584-011-0151-4, 2011. a
van Vuuren, D. P., Lucas, P. L., and Hilderink, H. B. M.: Downscaling Drivers
of Global Environmental Change, Technical Report, Netherlands Environmental
Assessment Agency, available at: https://www.pbl.nl/en/publications/DownscalingDriversOfGlobalEnvironmentalChangeScenarios (last access: 17 October 2012),
2006. a, b, c, d, e
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard,
K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J. F., Masui, T.,
Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The
Representative Concentration Pathways: An Overview, Climatic Change, 109,
5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011a. a, b
van Vuuren, D. P., Stehfest, E., Elzen, M. G. J., Kram, T., Vliet, J.,
Deetman, S., Isaac, M., Klein Goldewijk, K., Hof, A., Mendoza Beltran, A.,
Oostenrijk, R., and Ruijven, B.: RCP2.6: Exploring the Possibility to
Keep Global Mean Temperature Increase below 2 ∘C, Climatic
Change, 109, 95–116, https://doi.org/10.1007/s10584-011-0152-3, 2011b. a
van Vuuren, D. P., Kriegler, E., O'Neill, B. C., Ebi, K. L., Riahi, K.,
Carter, T. R., Edmonds, J., Hallegatte, S., Kram, T., Mathur, R., and
Winkler, H.: A New Scenario Framework for Climate Change Research:
Scenario Matrix Architecture, Climatic Change, 122, 373–386,
https://doi.org/10.1007/s10584-013-0906-1, 2014. a
van Vuuren, D. P., Stehfest, E., Gernaat, D. E. H. J., Doelman, J. C., van
den Berg, M., Harmsen, M., de Boer, H. S., Bouwman, L. F., Daioglou, V.,
Edelenbosch, O. Y., Girod, B., Kram, T., Lassaletta, L., Lucas, P. L., van
Meijl, H., Müller, C., van Ruijven, B. J., van der Sluis, S., and
Tabeau, A.: Energy, Land-Use and Greenhouse Gas Emissions Trajectories under
a Green Growth Paradigm, Global Environ. Chang., 42, 237–250,
https://doi.org/10.1016/j.gloenvcha.2016.05.008, 2017. a, b
World Climate Research Programme: CMIP Phase 6 (CMIP6), available at: https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6, last access: 14 March 2019. a
Short summary
Climate policy analysis needs scenarios of future greenhouse gas emission to assess countries' emission targets and current trends. The models generating these scenarios work on a regional resolution. Scenarios are often made available only on a very coarse regional resolution. In this paper we use per country projections of gross domestic product (GDP) from the Shared Socio-Economic Pathways (SSPs) to derive country-level data from published regional emission scenarios.
Climate policy analysis needs scenarios of future greenhouse gas emission to assess countries'...