How green are British cities? Scaling relations and CO2 emissions

How green or environmentally friendly urban areas are in comparison with rural areas is a topic that has received much attention in recent years. This is understandable because urban areas already emit around 70% of the global greenhouse gases. This percentage is likely to rise in the near future. This follows because the majority of the future growth in the global population is expected to be in urban areas. Key questions for the future relate to how green the cities will be, especially in terms of energy use and the emission of global greenhouse gases. Are there, for example, particular sizes or forms of cities that are energy efficient and have comparatively low emission rates of greenhouse gases? One of the most important of the greenhouse gases is carbon dioxide (CO2), whose human-activity related emission is widely regarded as a major contributing factor to recent global warming. The rate of CO2 emission is thus one measure of how green or environmentally friendly urban areas are. In view of this, we here report the results of a study of estimated residential and transportation CO2 emissions (at local authority levels) from 406 areas in the UK in relation to various other factors such as population, population density, fuel consumption, and income. We present as maps the variation in CO2 per capita throughout the UK. For transport CO2, there are notable lows in emission per capita in large cities and urban areas such as London, Liverpool-Manchester, and Glasgow-Edinburgh. For residential CO2 per capita, the low values are again in the large cities and city clusters. The highest emission values, however, are very clearly in the rural areas, in particular in the western part of Wales, in North England and in Scotland, particularly in the Highlands. These variations can partly be explained in terms of the climate in these areas. The residential CO2 shows a close-to-linear scaling relation with population; that is, the scaling exponent is 0.92. This implies that as the population grows, residential CO2 emissions grow at a similar but slightly lower rate. By contrast, transport CO2 shows a clear sub-linear relation with population; that is, the scaling exponent is 0.66. This implies that as the population grows, transport CO2 emissions grow at a much lower rate. We also analysed the residential CO2 emission in relation to population density, measured as number of people per square kilometre (N/km2). The resulting relation is non-linear and suggests that as the density increases the CO2 emission per capita decreases somewhat. All these results may suggest that large-population and dense areas in the UK are greener in terms of CO2 emission than smaller ones. However, calculated population sizes depend on city-boundary definitions, and there is not at present a general agreement as to how city boundaries should be defined. Thus, populations may not necessarily be the best parameter to measure CO2 against, and the results need to be put into a wider context before firm conclusions can be drawn. For Greater London we analysed transport and residential CO2 emissions per capita in relation to urban density, fuel consumption, and income. The results show strong correlations between fuel consumption and CO2 emissions. Urban density also shows some correlation with residential CO2 emissions and fuel consumption, but hardly any with residential CO2 emissions per capita or average weekly income per household. By contrast, there is considerable correlation between income per household and residential CO2 emissions per capita. This last correlation illustrates how socio-economic factors may affect CO2 emissions and other environmental parameters that, to a large degree, determine whether or not an urban area is environmentally friendly or green.

Published in:
Proceedings of the International Symposium on Applied Urban Modelling
Presented at:
AUM2015 - The 5th Symposium on Applied Urban Modelling - Green Cities, University of Cambridge - UK, 24-29 June, 2015

 Record created 2015-07-31, last modified 2018-03-17

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