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Global typology of urban energy use and potentials for an urbanization mitigation wedge
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Significance: Many case studies of specific cities have investigated factors that contribute to urban energy use and greenhouse-gas emissions. The analysis in this study is based on data from 274 cities and three global datasets and provides a typology of urban attributes of energy use. The results highlight that appropriate policies addressing urban climate change mitigation differ with type of city. A global urbanization wedge, corresponding in particular to energy-efficient urbanization in Asia, might reduce urban energy use by more than 25%, compared with a business-as-usual scenario.
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“Urban planning, street space rededication, smart logistical systems and increased street connectivity with smaller distances have the largest potential to reduce the need for travel 33,34 , with a counterfactual potential of 25% reduction in urban energy use in 2050 considering only newly built cities (repercussion effects in the buildings sector are included in this estimate) 35 .”
From Demand-side solutions to climate change mitigation consistent with high levels of well-being (2022) · cites this paper as [35]
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“Creutzig et al. [151] related the energy use of 300 cities worldwide to historical structural factors such as fuel taxes (which have a strong impact on urban sprawl).”
From Tackling climate change with machine learning (2023) · cites this paper as [151]
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“For instance, urban sprawl influences the energy use from transport, as wider cities tend to be more car-oriented [151,189,228].”
From Tackling climate change with machine learning (2023) · cites this paper as [151]
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Cites
Draper, N. R., & Smith, H. (2005) · Technometrics · doi:10.1198/tech.2005.s303 · Cited by 17,993
Travel and the Built Environment
Ewing, R., & Cervero, R. (2010) · Journal of the American Planning Association · doi:10.1080/01944361003766766 · Cited by 5,775
Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools
Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211658109 · Cited by 5,086
Self-citationDraper, N. R., & Smith, H. (1998) · Wiley series in probability and statistics · doi:10.1002/9781118625590 · Cited by 5,086
Location and Land Use: Toward a General Theory of Land Rent
Alonso, W. (1964) · Cited by 3,820
Alonso, W. (1964) · Harvard University Press eBooks · doi:10.4159/harvard.9780674730854 · Cited by 3,673
Fixed-and random-effects models in meta-analysis.
Hedges, L. V., & Vevea, J. L. (1998) · Psychological Methods · doi:10.1037/1082-989x.3.4.486 · Cited by 2,977
Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis
Hansen, B. E. (1996) · Econometrica · doi:10.2307/2171789 · Cited by 2,312
A Guide to Modern Econometrics
Verbeek, M. (2000) · RePEc: Research Papers in Economics · Cited by 1,777
Carbon Footprint of Nations: A Global, Trade-Linked Analysis
Hertwich, E. G., & Peters, G. P. (2009) · Environmental Science & Technology · doi:10.1021/es803496a · Cited by 1,715
Cited by
Sorted by citations
Future urban land expansion and implications for global croplands
d’Amour, C. B., Reitsma, F., Baiocchi, G., Barthel, S., Güneralp, B., Erb, K., Haberl, H., Creutzig, F., & Seto, K. C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1606036114 · Cited by 1,464
Self-citationGao, J., & O’Neill, B. C. (2020) · Nature Communications · doi:10.1038/s41467-020-15788-7 · Cited by 709
Consumption-based emission accounting for Chinese cities
Mi, Z., Zhang, Y., Guan, D., Shan, Y., Liu, Z., Cong, R., Yuan, X.-C., & Wei, Y. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.06.094 · Cited by 637
Methodology and applications of city level CO2 emission accounts in China
Shan, Y., Guan, D., Liu, J., Mi, Z., Liu, Z., Liu, J., Schroeder, H., Cai, B., Chen, Y., Shao, S., et al. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.06.075 · Cited by 593
Demand-side solutions to climate change mitigation consistent with high levels of well-being
Creutzig, F., Niamir, L., Bai, X., Callaghan, M., Cullen, J., Díaz-José, J., Figueroa, M., Grubler, A., Lamb, W. F., Leip, A., et al. (2022) · Nature Climate Change · doi:10.1038/s41558-021-01219-y · Cited by 579
Self-citationUnequal household carbon footprints in China
Wiedenhofer, D., Guan, D., Liu, Z., Meng, J., Zhang, N., & Wei, Y. (2016) · Nature Climate Change · doi:10.1038/nclimate3165 · Cited by 523
City-level climate change mitigation in China
Shan, Y., Guan, D., Hubacek, K., Zheng, B., Davis, S. J., Jia, L., Liu, J., Liu, Z., Fromer, N. A., Mi, Z., et al. (2018) · Science Advances · doi:10.1126/sciadv.aaq0390 · Cited by 476
Carbon footprints of 13 000 cities
Moran, D. D., Kanemoto, K., Jiborn, M., Wood, R. A., Többen, J., & Seto, K. C. (2018) · Environmental Research Letters · doi:10.1088/1748-9326/aac72a · Cited by 417
Self-citationDemuzere, M., Kittner, J., Martilli, A., Mills, G. M., Moede, C., Stewart, I. D., van Vliet, J., & Bechtel, B. (2022) · Earth system science data · doi:10.5194/essd-14-3835-2022 · Cited by 429
China’s CO2 peak before 2030 implied from characteristics and growth of cities
Wang, H., Lu, X., Deng, Y., Sun, Y., Nielsen, C., Liu, Y., Zhu, G., Bu, M., Bi, J., & McElroy, M. B. (2019) · Nature Sustainability · doi:10.1038/s41893-019-0339-6 · Cited by 336
Beyond Technology: Demand-Side Solutions for Climate Change Mitigation
Creutzig, F., Milan, B. F., Haberl, H., Khosla, R., Mulugetta, Y., & Seto, K. C. (2016) · Annual Review of Environment and Resources · doi:10.1146/annurev-environ-110615-085428 · Cited by 347
Self-citationChange, I. P. O. C. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009157926.004 · Cited by 379
The Routledge Handbook of Urbanization and Global Environmental Change
Seto, K. C., SOLECKI, W. D., & Griffith, C. A. (2015) · Routledge eBooks · doi:10.4324/9781315849256 · Cited by 291
Self-citationCarbon emissions of cities from a consumption-based perspective
Mi, Z., Zheng, J., Meng, J., Zheng, H., Li, X., Coffman, D., Woltjer, J., Wang, S., & Guan, D. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.10.137 · Cited by 289
Smart city as a tool for sustainable mobility and transport decarbonisation
Zawieska, J., & Pieriegud, J. (2017) · Transport Policy · doi:10.1016/j.tranpol.2017.11.004 · Cited by 287
Climate change, equity and the Sustainable Development Goals: an urban perspective
Reckien, D., Creutzig, F., Fernandez, B., Lwasa, S., Tovar-Restrepo, M., McEvoy, D., & Satterthwaite, D. (2017) · Environment and Urbanization · doi:10.1177/0956247816677778 · Cited by 300
Self-citationPopulation–Urbanization–Energy Nexus: A Review
Avtar, R., Tripathi, S., Aggarwal, A. K., & Kumar, P. (2019) · Resources · doi:10.3390/resources8030136 · Cited by 294
Urban infrastructure choices structure climate solutions
Creutzig, F., Agoston, P., Minx, J. C., Canadell, J. G., Andrew, R. M., Quéré, C. L., Peters, G. P., Sharifi, A., Yamagata, Y., & Dhakal, S. (2016) · Nature Climate Change · doi:10.1038/nclimate3169 · Cited by 266
Self-citationToward a Resource‐Efficient Built Environment: A Literature Review and Conceptual Model
Ness, D. A., & Xing, K. (2017) · Journal of Industrial Ecology · doi:10.1111/jiec.12586 · Cited by 268
Urban sustainability assessment: An overview and bibliometric analysis
Sharifi, A. (2020) · Ecological Indicators · doi:10.1016/j.ecolind.2020.107102 · Cited by 308
From Low- to Net-Zero Carbon Cities: The Next Global Agenda
Seto, K. C., Churkina, G., Hsu, A., Keller, M., Newman, P. W. G., Qin, B., & Ramaswami, A. (2021) · Annual Review of Environment and Resources · doi:10.1146/annurev-environ-050120-113117 · Cited by 277
Self-citationAn emissions-socioeconomic inventory of Chinese cities
Shan, Y., Liu, J., Liu, Z., Shao, S., & Guan, D. (2019) · Scientific Data · doi:10.1038/sdata.2019.27 · Cited by 238
Jiang, D. (2019) · Computer Communications · doi:10.1016/j.comcom.2019.10.035 · Cited by 236
Bashir, M. F., Ma, B., Shahbaz, M. Q., Shahzad, U., & Vo, X. V. (2021) · Energy · doi:10.1016/j.energy.2021.120366 · Cited by 214
Factors affecting low-carbon consumption behavior of urban residents: A comprehensive review
Ding, Z., Jiang, X., Liu, Z., Long, R., Xu, Z., & Cao, Q. (2018) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2018.01.013 · Cited by 211
Shan, Y., Fang, S., Cai, B., Zhou, Y., Li, D., Feng, K., & Hubacek, K. (2021) · One Earth · doi:10.1016/j.oneear.2020.12.004 · Cited by 210
Building up or spreading out? Typologies of urban growth across 478 cities of 1 million+
Mahtta, R., Mahendra, A., & Seto, K. C. (2019) · Environmental Research Letters · doi:10.1088/1748-9326/ab59bf · Cited by 213
Self-citationWu, H., Abbas, Q., Alharthi, M., Mohsin, M., Hanif, I., Vo, X. V., & Hesary, F. T. (2020) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2020.06.177 · Cited by 188
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336
Self-citationZhou, Y., Shan, Y., Liu, G., & Guan, D. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.07.038 · Cited by 181
The Role of Urbanization in the Global Carbon Cycle
Churkina, G. (2016) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2015.00144 · Cited by 176
Reducing Urban Greenhouse Gas Footprints
Pichler, P., Zwickel, T., Chávez, A., Kretschmer, T., Wallack, J. S., & Weisz, H. (2017) · Scientific Reports · doi:10.1038/s41598-017-15303-x · Cited by 173
Self-citationThree‐scope carbon emission inventories of global cities
Wiedmann, T., Chen, G., Owen, A., Manfred Lenzen, A., Doust, M., Barrett, J., & Steele, K. (2020) · Journal of Industrial Ecology · doi:10.1111/jiec.13063 · Cited by 180
Impact of Urban Density and Building Height on Energy Use in Cities
Resch, E., Bohne, R. A., Kvamsdal, T., & Lohne, J. (2016) · Energy Procedia · doi:10.1016/j.egypro.2016.09.142 · Cited by 168
The Material Stock–Flow–Service Nexus: A New Approach for Tackling the Decoupling Conundrum
Haberl, H., Wiedenhofer, D., Erb, K., Görg, C., & Krausmann, F. (2017) · Sustainability · doi:10.3390/su9071049 · Cited by 178
Demand, Services and Social Aspects of Mitigation
(IPCC), I. P. O. C. C. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009157926.007 · Cited by 244
Learning about urban climate solutions from case studies
Lamb, W. F., Creutzig, F., Callaghan, M. W., & Minx, J. C. (2019) · Nature Climate Change · doi:10.1038/s41558-019-0440-x · Cited by 163
Self-citationZhou, Y., Li, X., Chen, W., Meng, L., Wu, Q., Gong, P., & Seto, K. C. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2214813119 · Cited by 172
Self-citationWiedenhofer, D., Smetschka, B., Akenji, L., Jalas, M., & Haberl, H. (2018) · Current Opinion in Environmental Sustainability · doi:10.1016/j.cosust.2018.02.007 · Cited by 163
Bibri, S. E. (2018) · European Journal of Futures Research · doi:10.1186/s40309-018-0142-z · Cited by 160
Machine learning for geographically differentiated climate change mitigation in urban areas
Milojevic-Dupont, N., & Creutzig, F. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102526 · Cited by 170
Self-citationGómez-Echeverri, L. F. (2018) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2016.0444 · Cited by 164
Urban Systems and Other Settlements
Change, I. P. O. C. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009157926.010 · Cited by 212
The statistical physics of cities
Barthélemy, M. (2019) · Nature Reviews Physics · doi:10.1038/s42254-019-0054-2 · Cited by 154
Wang, Z., Cui, C., & Peng, S. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.11.272 · Cited by 153
Xu, L., Du, H., & Zhang, X. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.125169 · Cited by 150
Urban mental health: challenges and perspectives
Okkels, N., Kristiansen, C. B., Munk-Jørgensen, P., & Sartorius, N. (2018) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000413 · Cited by 136
High-Resolution Maps of Material Stocks in Buildings and Infrastructures in Austria and Germany
Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G., Fishman, T., et al. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.0c05642 · Cited by 150
Parnell, S. M., Elmqvist, T., McPhearson, T., Nagendra, H., Sörlin, S., Haase, D., Güneralp, B., Dahiya, B., Bai, X., Alberti, M., et al. (2018) · Cambridge University Press eBooks · doi:10.1017/9781316647554 · Cited by 158
Upscaling urban data science for global climate solutions
Creutzig, F., Lohrey, S., Bai, X., Baklanov, A., Dawson, R., Dhakal, S., Lamb, W. F., McPhearson, T., Minx, J., Munoz, E., et al. (2019) · Global Sustainability · doi:10.1017/sus.2018.16 · Cited by 137
Self-citationGreenhouse gas emissions from global cities under SSP/RCP scenarios, 1990 to 2100
Gurney, K. R., Kılkış, Ş., Seto, K. C., Lwasa, S., Moran, D. D., Riahi, K., Keller, M., Rayner, P. J., & Luqman, M. (2022) · Global Environmental Change · doi:10.1016/j.gloenvcha.2022.102478 · Cited by 137
Self-citationEstimating population and urban areas at risk of coastal hazards, 1990–2015: how data choices matter
MacManus, K., Balk, D. L., Engin, H., McGranahan, G., & Inman, R. (2021) · Earth system science data · doi:10.5194/essd-13-5747-2021 · Cited by 136
Physical and virtual carbon metabolism of global cities
Chen, S., Chen, B., Feng, K., Liu, Z., Fromer, N. A., Tan, X., Alsaedi, A., Hayat, T., Weisz, H., Schellnhuber, H. J., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-13757-3 · Cited by 135
Carreón, J. R., & Worrell, E. (2017) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2017.08.004 · Cited by 136
Policy-Relevant Assessment of Urban CO2 Emissions
Lauvaux, T., Gurney, K. R., Miles, N. L., Davis, K. J., Richardson, S. J., Deng, A. J., Nathan, B. J., Oda, T., Wang, J. A., Hutyra, L. R., et al. (2020) · Environmental Science & Technology · doi:10.1021/acs.est.0c00343 · Cited by 132
Worldwide Scaling of Waste Generation in Urban Systems
Lu, M., Zhou, C., Wang, C., Jackson, R. B., & Kempes, C. P. (2022) · Nature Cities · doi:10.1038/s44284-023-00021-5 · Cited by 163
Industrial Ecology: The role of manufactured capital in sustainability
Weisz, H., Suh, S., & Graedel, T. E. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1506532112 · Cited by 134
City density and CO2 efficiency
Gudipudi, R., Fluschnik, T., Ros, A. G. C., Walther, C., & Kropp, J. P. (2016) · Energy Policy · doi:10.1016/j.enpol.2016.01.015 · Cited by 130
Change, I. P. O. C. (2023) · Cambridge University Press eBooks · doi:10.1017/9781009157926.012 · Cited by 212
Tardioli, G., Kerrigan, R., Oates, M., O’Donnell, J., & Finn, D. (2018) · Building and Environment · doi:10.1016/j.buildenv.2018.05.035 · Cited by 125
Xie, L., Yan, H., Shuhan, Z., & Chu, W. (2019) · China Economic Review · doi:10.1016/j.chieco.2019.101374 · Cited by 127
Does urbanization lead to less residential energy consumption? A comparative study of 136 countries
Wang, Q., Lin, J., Zhou, K., Fan, J., & Kwan, M. (2020) · Energy · doi:10.1016/j.energy.2020.117765 · Cited by 127
Yu, Y., Zhang, N., & Kim, J. D. (2020) · Energy Policy · doi:10.1016/j.enpol.2020.111354 · Cited by 126
Making more effective use of human behavioural science in conservation interventions
Balmford, A. P., Bradbury, R. B., Bauer, J. M., Broad, S., Burgess, G., Burgman, M. A., Byerly, H., Clayton, S., Espelosin, D., Ferraro, P. J., et al. (2021) · Biological Conservation · doi:10.1016/j.biocon.2021.109256 · Cited by 129
Davis, K. J., Deng, A. J., Lauvaux, T., Miles, N. L., Richardson, S. J., Sarmiento, D. P., Gurney, K. R., Hardesty, R. M., Bonin, T. A., Brewer, W. A., et al. (2017) · Elementa Science of the Anthropocene · doi:10.1525/elementa.188 · Cited by 128
Zhu, Y., Shi, Y., Wu, J., Wu, L., & Xiong, W. (2017) · Ecological Economics · doi:10.1016/j.ecolecon.2017.12.020 · Cited by 124
Feasible mitigation actions in developing countries
Jakob, M., Steckel, J. C., Klasen, S., Lay, J., Grunewald, N., Martínez‐Zarzoso, I., Renner, S., & Edenhofer, O. (2014) · Nature Climate Change · doi:10.1038/nclimate2370 · Cited by 123
Evolving Narratives of Low-Carbon Futures in Transportation
Creutzig, F. (2015) · Transport Reviews · doi:10.1080/01441647.2015.1079277 · Cited by 120
Self-citationThe Environmental Impact of Sharing: Household and Urban Economies in CO2 Emissions
Fremstad, A., Underwood, A., & Zahran, S. (2017) · Ecological Economics · doi:10.1016/j.ecolecon.2017.08.024 · Cited by 119
Urban energy exchanges monitoring from space
Chrysoulakis, N., Grimmond, S., Feigenwinter, C., Lindberg, F., Gastellu‐Etchegorry, J., Marconcini, M., Mitraka, Z., Stagakis, S., Crawford, B., Olofson, F., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-29873-x · Cited by 115
Global trends toward urban street-network sprawl
Barrington-Leigh, C. P., & Millard‐Ball, A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1905232116 · Cited by 113
A spatial typology of human settlements and their CO2 emissions in England
Baiocchi, G., Creutzig, F., Minx, J. C., & Pichler, P. (2015) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.06.001 · Cited by 113
Self-citationGlobally elevated greenhouse gas emissions from polluted urban rivers
Xu, W., Wang, G., Liu, S., Wang, J., McDowell, W. H., Huang, K., Raymond, P. A., Yang, Z., & Xia, X. (2024) · Nature Sustainability · doi:10.1038/s41893-024-01358-y · Cited by 108
Zhang, Q., Yang, J., Sun, Z., & Wu, F. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.05.071 · Cited by 107
Wiedenhofer, D., Fishman, T., Plank, B., Miatto, A., Lauk, C., Haas, W., Haberl, H., & Krausmann, F. (2021) · Global Environmental Change · doi:10.1016/j.gloenvcha.2021.102410 · Cited by 107
Local strategies for China's carbon mitigation: An investigation of Chinese city-level CO2 emissions
Cai, B., Guo, H., Cao, L., Guan, D., & Bai, H. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.01.054 · Cited by 106
The scale and drivers of carbon footprints in households, cities and regions across India
Lee, J., Taherzadeh, O., & Kanemoto, K. (2020) · Global Environmental Change · doi:10.1016/j.gloenvcha.2020.102205 · Cited by 107
A global dataset of CO2 emissions and ancillary data related to emissions for 343 cities
Nangini, C., Peregon, A. M., Ciais, P., Weddige, U., Vogel, F., Wang, J., Bréon, F., Bachra, S., Wang, Y., Gurney, K. R., et al. (2019) · Scientific Data · doi:10.1038/sdata.2018.280 · Cited by 105
Self-citationLi, X., & Zhou, W. (2018) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2018.06.244 · Cited by 104
Low-carbon developments in Northeast China: Evidence from cities
Liu, X., Duan, Z., Shan, Y., Duan, H., Wang, S., Song, J., & Wang, X. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.12.060 · Cited by 100
Exploring the economic case for climate action in cities
Gouldson, A., Colenbrander, S., Sudmant, A., McAnulla, F., Kerr, N., Sakai, P., Hall, S., Papargyropoulou, E., & Kuylenstierna, J. (2015) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.07.009 · Cited by 90
The consumption-based black carbon emissions of China's megacities
Meng, J., Mi, Z., Yang, H., Shan, Y., Guan, D., & Liu, J. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.02.185 · Cited by 100
SOLECKI, W. D., Seto, K. C., Balk, D. L., Bigio, A. G., Boone, C. G., Creutzig, F., Fragkias, M., Lwasa, S., Marcotullio, P. J., Romero‐Lankao, P., et al. (2015) · Urban Climate · doi:10.1016/j.uclim.2015.07.001 · Cited by 105
Self-citationOn the conditions of ‘late urbanisation’
Fox, S., & Goodfellow, T. (2021) · Urban Studies · doi:10.1177/00420980211032654 · Cited by 96
The future of Russia’s renewable energy sector: Trends, scenarios and policies
Proskuryakova, L. N., & Ermolenko, G. V. (2019) · Renewable Energy · doi:10.1016/j.renene.2019.05.096 · Cited by 95
Trade openness and urbanization impact on renewable and non-renewable energy consumption in China
Han, J., Zeeshan, M., Ullah, I., Rehman, A., & Afridi, F. E. A. (2022) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-18353-x · Cited by 93
Urban Big Data and Sustainable Development Goals: Challenges and Opportunities
Kharrazi, A., Qin, H., & Zhang, Y. (2016) · Sustainability · doi:10.3390/su8121293 · Cited by 93
Impacts of land use and socioeconomic patterns on urban heat Island
Tang, J., Di, L., Xiao, J., Lu, D., & Zhou, Y. (2017) · International Journal of Remote Sensing · doi:10.1080/01431161.2017.1295485 · Cited by 91
Measuring Urban Carbon Footprint from Carbon Flows in the Global Supply Chain
Hu, Y., Lin, J., Cui, S., & Khanna, N. Z. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b00985 · Cited by 89
Using explainable machine learning to understand how urban form shapes sustainable mobility
Wagner, F., Milojevic-Dupont, N., Franken, L., Zekar, A., Thies, B., Koch, N., & Creutzig, F. (2022) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2022.103442 · Cited by 89
Self-citationXu, C., Haase, D., Su, M., & Yang, Z. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.113671 · Cited by 86
Novel validated method for GIS based automated dynamic urban building energy simulations
Nageler, P. J., Zahrer, G., Heimrath, R., Mach, T., Mauthner, F., Leusbrock, I., Schranzhofer, H., & Hochenauer, C. (2017) · Energy · doi:10.1016/j.energy.2017.07.151 · Cited by 87
City Carbon Footprint Networks
Chen, G., Wiedmann, T., Hadjikakou, M., & Rowley, H. V. (2016) · Energies · doi:10.3390/en9080602 · Cited by 85
Deetjen, T. A., Conger, J. P., Leibowicz, B. D., & Webber, M. E. (2018) · Sustainable Cities and Society · doi:10.1016/j.scs.2018.06.023 · Cited by 80
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Self-citation
Metadata
- Authors
- Creutzig, F., Baiocchi, G., Bierkandt, R., Pichler, P.-P., & Seto, K. C.
- Affiliations
- Mercator Research Institute on Global Commons and Climate Change (DE)
- University of Maryland, College Park (US)
- Potsdam Institute for Climate Impact Research (DE)
- Yale University (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2015-01-12
- Volume
- 112
- Issue
- 20
- Pages
- 6283-6288
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4443311
- OpenAlex
- W2123954521
- Cited by
- 598
- References
- 39
- Citations by year
- 2026: 54 · 2025: 53 · 2024: 50 · 2023: 37 · 2022: 50 · 2021: 56 · 2020: 56 · 2019: 56 · 2018: 97 · 2017: 44 · 2016: 25 · 2015: 18
- FWCI
- 18.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Publication Database PIK (Potsdam Institute for Climate Impact Research (PIK)) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Environment, and Transportation Policies
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Energy, Environment, Economic Growth
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Sustainable Development
- Keywords
- urban energy consumption, climate change mitigation, urban greenhouse gas emissions, transportation energy use, compact city, urban planning policy, transport planning policy, gasoline prices, population density, urban expansion, urban typology
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