![]() ![]() Important note about the city names: The GGMCF is fundamentally based on the EU's GHS-SMOD gridded population model. Details about how these are calculated are provided in the paper and the SI. if the Footprint of a city is reported as 20 ±5, it means there is a 67% chance the city's CF is between 15-25, and a 95% chance the CF is between 10 and 20. These can be interpreted in the normal way: e.g. The CF of each cluster is reported as a mean estimate with a standard deviation. The mean per-capita CFs are also shown as a median estimate with an associated uncertainty range. Taking the city's estimated population as given, model provides results for each city with an associated uncertainty range. Additionally, the population within these clusters may include exurbs and other areas and may not correspond to the city's official population. This does not correspond directly to the precise legal jurisdiction for many cities. We use the GHS-SMOD definition of "cities" as contiguous population clusters. Additionally, defining the city population and bounds is hard. When interpreting the results please keep in mind that the results from a global top-down model will never be as precise as more detailed local or bottom-up assessments. The model estimates the carbon footprint (CF) of individual cities. Local action at the city and state level can meaningfully affect national and global emissions.In wealthy, high-consumption, high-footprint localities such measures may require only a small investment relative to median income, yet accomplish large reductions in total footprint emissions Radical decarbonization measures (limiting nonelectric vehicles requiring 100% renewable electricity) can induce substantial emissions reductions beyond city boundaries.For large and high-income cities, their total Scope 3 footprint is much larger than the city's direct emissions.In these cities population and affluence combine to drive footprints at a similar scale as the highest income cities 41 of the top 200 cities are in countries where total and per capita emissions are low e.g.We define cities as population clusters, but in practice mapping footprints to local jurisdictional bounds is complex.In most countries (98 of 187 assessed), the top three urban areas drive more than one-quarter of national emissions.100 cities drive 18% of global emissions. ![]() Globally, carbon footprints are highly concentrated into a small number of dense, high-income cities and affluent suburbs.Some other observations based on the results include: This means concerted action by a small number of local mayors and governments has the potential to significantly reduce national total carbon footprints. One observation that can be made based on this model is in many countries, a small number of large and or affluent cities drive a significant share of national total emissions. The dataset is also available on the WRI ResourceWatch platform ( blog). World Economic Forum, NASA's Earth Observatory blog, US News & World Report, National Geographic, among others. This article from Scientific American also gives a nice overview of the study. Is described in the open-access publication It incorporates existing subnational models for the US, China, Japan, EU, and UK. This model provides a globally consistent, spatially resolved (250m), estimate ofĬarbon footprints (also called Scope 3 emissions) in per capita and absolute terms across 189 countries. Global Gridded Model of Carbon Footprints (GGMCF) ![]()
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