Carbon footprints of 13 000 cities

By Daniel Moran, Keiichiro Kanemoto, Magnus Jiborn, Richard Wood, Johannes Többen, Karen C. Seto. Environmental Research Letters, 2018

344 citations recorded by the source corpus.

While it is understood that cities generate the majority of carbon emissions, for most cities, towns, and rural areas around the world no carbon footprint (CF) has been estimated. The Gridded Global Model of City Footprints (GGMCF) presented here downscales national CFs into a 250 m gridded model using data on population, purchasing power, and existing subnational CF studies from the US, China, EU, and Japan. Studies have shown that CFs are highly concentrated by income, with the top decile of earners driving 30%–45% of emissions. Even allowing for significant modeling uncertainties, we find that emissions are similarly concentrated in a small number of cities. The highest emitting 100 urban areas (defined as contiguous population clusters) account for 18% of the global carbon footprint. While many of the cities with the highest footprints are in countries with high carbon footprints, nearly one quarter of the top cities (41 of the top 200) are in countries with relatively low emissions. In these cities population and affluence combine to drive footprints at a scale similar to those of cities in high-income countries. We conclude that concerted action by a limited number of local governments can have a disproportionate impact on global emissions.

Subfields: Economics and Econometrics, Environmental Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/069f5d424bddc6034de8c686770a9b89074bb5cd

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Citations in the corpus

The Carbon Footprint of Bitcoin (2019, neutral): “9 MtCO2, a ratio that sits between the levels produced by Jordan and Sri Lanka(12) and is comparable to the level of Kansas City.(13) The magnitude of these carbon emissions, combined with the risk of collusion and concerns about control over the monetary system, might justify regulatory interventio”
Global anthropogenic emissions in urban areas: patterns, trends, and challenges (2021, background): “Compared to previous studies [30, 31], the novelties of this work are the detailed spatial distributions of emissions of both GHG gases (CO2 and non-CO2) and air pollutants from urban settlements, calculated for different activities; all of which are available for the past 45 years.”
Entropy-based Chinese city-level MRIO table framework (2021, methodology): “employment and demographic data) in an attempt to capture local heterogeneity and global environmental implications (Chavez & Ramaswami, 2013; Christis et al., 2019; Moran et al., 2018; Zheng, Meng, et al., 2019).”
The statistical physics of cities (2019, background): “This emission is also concentrated in some urban areas: the 100 highestemitting urban areas account for 18% of the global carbon footprint [87].”