Carbon footprints of cities and other human settlements in the UK

By J. Minx, G. Baiocchi, T. Wiedmann, J. Barrett, Felix Creutzig, Kuishuang Feng, M. Förster, Peter-Paul Pichler, Helga Weisz, Klaus Hubacek. 2013

373 citations recorded by the source corpus.

A growing body of literature discusses the CO2 emissions of cities. Still, little is known about emission patterns across density gradients from remote rural places to highly urbanized areas, the drivers behind those emission patterns and the global emissions triggered by consumption in human settlements—referred to here as the carbon footprint. In this letter we use a hybrid method for estimating the carbon footprints of cities and other human settlements in the UK explicitly linking global supply chains to local consumption activities and associated lifestyles. This analysis comprises all areas in the UK, whether rural or urban. We compare our consumption-based results with extended territorial CO2 emission estimates and analyse the driving forces that determine the carbon footprint of human settlements in the UK. Our results show that 90% of the human settlements in the UK are net importers of CO2 emissions. Consumption-based CO2 emissions are much more homogeneous than extended territorial emissions. Both the highest and lowest carbon footprints can be found in urban areas, but the carbon footprint is consistently higher relative to extended territorial CO2 emissions in urban as opposed to rural settlement types. The impact of high or low density living remains limited; instead, carbon footprints can be comparatively high or low across density gradients depending on the location-specific socio-demographic, infrastructural and geographic characteristics of the area under consideration. We show that the carbon footprint of cities and other human settlements in the UK is mainly determined by socio-economic rather than geographic and infrastructural drivers at the spatial aggregation of our analysis. It increases with growing income, education and car ownership as well as decreasing household size. Income is not more important than most other socio-economic determinants of the carbon footprint. Possibly, the relationship between lifestyles and infrastructure only impacts carbon footprints significantly at higher spatial granularity.

Subfields: Environmental Engineering, Health, Toxicology and Mutagenesis, Transportation

View Paper: https://www.semanticscholar.org/paper/c82c5236efab5e802dac33194f9fe1adb612b30d

How researchers see this paper

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In Environmental Engineering

1. D. Guan
2. Jing Meng
3. Richard Wood
4. Zhifu Mi
5. Yuli Shan
6. Manfred Lenzen
7. Edgar G. Hertwich
8. Zhu Liu

In Health, Toxicology and Mutagenesis

1. Jing Meng
2. D. Guan
3. Richard Wood
4. Olga V. Wilhelmi
5. Edgar G. Hertwich
6. Mary Hayden
7. Karen C. Seto
8. Zhu Liu

In Transportation

1. Zhu Liu
2. Kjartan Steen‐Olsen
3. Jing Meng
4. Richard Wood
5. D. Ivanova
6. Yuli Shan
7. Edgar G. Hertwich
8. Karen C. Seto

Citations in the corpus

• Carbon emissions of cities from a consumption-based perspective (2019, background): “Only a few studies have investigated consumption-based cities [41-43].”
• Mapping the carbon footprint of EU regions (2017, background): “It has been previously suggested that geographic and infrastructural effects may be more significant at a finer spatial detail (Minx et al 2013).”
• Household time use, carbon footprints, and urban form: a review of the potential contributions of everyday living to the 1.5 °C climate target (2018, background): “Secondly, household size is consistently identified as a key factor in reducing per-capita carbon footprints, when income differences are controlled for [8,38,40,47,49,53].”
• Entropy-based Chinese city-level MRIO table framework (2021, background): “Some studies explore consumption heterogeneity by disaggregating final demands using household survey data at the subnational level, but this approach fails to capture heterogeneity in industrial structures (Ivanova et al., 2016; Minx et al., 2013).”
• Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city (2018, background): “[30] evaluated the carbon footprint of citied in UK,”
• Urban Sustainability and Resilience: From Theory to Practice (2016, background): “The first is concerned with the number of people within a defined politico-administrative boundary, such as municipalities and state territories [16].”
• Carbon footprints of 13 000 cities (2018, background): “Minx and colleagues (Minx et al 2013) found that in the UK the CF of cities is mainly determined by socio-economic rather than geographic and infrastructural drivers, and that income is one of the main determinants.”
• Consumption-based emission accounting for Chinese cities (2016, background): “Few studies have researched consumption-based emissions for cities [36,37].”