Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-845-2022
© Author(s) 2022. 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-14-845-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
23 Feb 2022
Data description paper |
| 23 Feb 2022
| 23 Feb 2022
Estimating CO2 emissions for 108 000 European cities
Daniel Moran
CORRESPONDING AUTHOR
Industrial Ecology Programme, Department of Energy and Process
Engineering, Norwegian University of Science and Technology, Trondheim,
Norway
Peter-Paul Pichler
Department of Social Metabolism and Impacts, Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
Heran Zheng
Industrial Ecology Programme, Department of Energy and Process
Engineering, Norwegian University of Science and Technology, Trondheim,
Norway
Helene Muri
Industrial Ecology Programme, Department of Energy and Process
Engineering, Norwegian University of Science and Technology, Trondheim,
Norway
Jan Klenner
Industrial Ecology Programme, Department of Energy and Process
Engineering, Norwegian University of Science and Technology, Trondheim,
Norway
Diogo Kramel
Industrial Ecology Programme, Department of Energy and Process
Engineering, Norwegian University of Science and Technology, Trondheim,
Norway
Johannes Többen
Department of Social Metabolism and Impacts, Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
Helga Weisz
Department of Social Metabolism and Impacts, Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
Thomas Wiedmann
Sustainability Assessment Program, School of Civil and Environmental
Engineering, UNSW Sydney, Australia
Annemie Wyckmans
Faculty for Architecture and Design, Norwegian University of Science and
Technology, Trondheim, Norway
Anders Hammer Strømman
Industrial Ecology Programme, Department of Energy and Process
Engineering, Norwegian University of Science and Technology, Trondheim,
Norway
Kevin R. Gurney
School of Informatics, Computing, and Cyber Systems, Northern Arizona
University, Flagstaff, AZ, USA
Viewed
Total article views: 8,058 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 21 Sep 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,791 | 2,122 | 145 | 8,058 | 120 | 117 |
- HTML: 5,791
- PDF: 2,122
- XML: 145
- Total: 8,058
- BibTeX: 120
- EndNote: 117
Total article views: 4,629 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 23 Feb 2022)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,466 | 1,060 | 103 | 4,629 | 99 | 95 |
- HTML: 3,466
- PDF: 1,060
- XML: 103
- Total: 4,629
- BibTeX: 99
- EndNote: 95
Total article views: 3,429 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 21 Sep 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,325 | 1,062 | 42 | 3,429 | 21 | 22 |
- HTML: 2,325
- PDF: 1,062
- XML: 42
- Total: 3,429
- BibTeX: 21
- EndNote: 22
Viewed (geographical distribution)
Total article views: 8,058 (including HTML, PDF, and XML)
Thereof 7,517 with geography defined
and 541 with unknown origin.
Total article views: 4,629 (including HTML, PDF, and XML)
Thereof 4,397 with geography defined
and 232 with unknown origin.
Total article views: 3,429 (including HTML, PDF, and XML)
Thereof 3,120 with geography defined
and 309 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
14 citations as recorded by crossref.
- The increasing emission divide between cities of the Global North and Global South: Towards adjustable mitigation scenarios at the city level Y. Jabareen 10.1177/00420980231152846
- Key predictors of greenhouse gas emissions for cities committing to mitigate and adapt to climate change C. Franco et al. 10.1016/j.cities.2023.104342
- Urban emissions and land use efficiency scenarios for avoiding increments of global warming Ş. Kılkış 10.1016/j.energy.2024.132174
- Key Predictors of Greenhouse Gas Emissions for Cities Committing to Mitigate and Adapt to Climate Change C. Franco et al. 10.2139/ssrn.4183235
- Rethinking urban riparian ecosystems as a frontline strategy to counter climate change: mapping 60 years of carbon sequestration evolution in Padua, Italy F. Peroni et al. 10.3389/fclim.2023.1235886
- Predicting European cities’ climate mitigation performance using machine learning A. Hsu et al. 10.1038/s41467-022-35108-5
- Environmental monitoring in European regions using the sustainable development goals (SDG) framework P. Nakhle et al. 10.1016/j.indic.2023.100332
- Urban Scaling Functions: Emission, Pollution and Health C. La Porta & S. Zapperi 10.1007/s11524-024-00888-2
- Cities: Allocating climate change responsibilities at planetary scale M. Hachaichi 10.1016/j.uclim.2022.101329
- Kuznets and the cities: Urban level EKC evidence from Europe M. Rizzati et al. 10.1016/j.ecolind.2023.110143
- Prediction of greenhouse gas emissions for cities and local municipalities monitoring their advances to mitigate and adapt to climate change C. Franco et al. 10.1016/j.scs.2022.104114
- Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method Y. Wang et al. 10.5194/essd-15-3597-2023
- Assessing urban emissions through different methodologies: an analysis of Brazilian cities E. de Souza Leão et al. 10.1007/s11027-022-09994-5
- Carbon Monitor Cities near-real-time daily estimates of CO2 emissions from 1500 cities worldwide D. Huo et al. 10.1038/s41597-022-01657-z
12 citations as recorded by crossref.
- The increasing emission divide between cities of the Global North and Global South: Towards adjustable mitigation scenarios at the city level Y. Jabareen 10.1177/00420980231152846
- Key predictors of greenhouse gas emissions for cities committing to mitigate and adapt to climate change C. Franco et al. 10.1016/j.cities.2023.104342
- Urban emissions and land use efficiency scenarios for avoiding increments of global warming Ş. Kılkış 10.1016/j.energy.2024.132174
- Key Predictors of Greenhouse Gas Emissions for Cities Committing to Mitigate and Adapt to Climate Change C. Franco et al. 10.2139/ssrn.4183235
- Rethinking urban riparian ecosystems as a frontline strategy to counter climate change: mapping 60 years of carbon sequestration evolution in Padua, Italy F. Peroni et al. 10.3389/fclim.2023.1235886
- Predicting European cities’ climate mitigation performance using machine learning A. Hsu et al. 10.1038/s41467-022-35108-5
- Environmental monitoring in European regions using the sustainable development goals (SDG) framework P. Nakhle et al. 10.1016/j.indic.2023.100332
- Urban Scaling Functions: Emission, Pollution and Health C. La Porta & S. Zapperi 10.1007/s11524-024-00888-2
- Cities: Allocating climate change responsibilities at planetary scale M. Hachaichi 10.1016/j.uclim.2022.101329
- Kuznets and the cities: Urban level EKC evidence from Europe M. Rizzati et al. 10.1016/j.ecolind.2023.110143
- Prediction of greenhouse gas emissions for cities and local municipalities monitoring their advances to mitigate and adapt to climate change C. Franco et al. 10.1016/j.scs.2022.104114
- Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method Y. Wang et al. 10.5194/essd-15-3597-2023
2 citations as recorded by crossref.
Latest update: 26 Jul 2024
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.
This paper presents the modeling methods used for the website https://openghgmap.net, which...
Altmetrics
Final-revised paper
Preprint