Gridded Carbon Footprint

Gridded estimate of carbon footprints across 189 countries

  • Source: NTNU/LU/Shinshu/Yale

The Global Gridded Model of Carbon Footprints (GGMCF), created by the Norwegian University of Science and Technology (NTNU), shows a gridded estimate of carbon emissions across 189 countries for the year of 2013 with a 250 square meter resolution. The GGMCF was built in four steps:

(1) National Carbon Footprints (CFs) of consumption (CFn) for 189 countries covering ~100% of global carbon dioxide (CO2) emissions were taken from the Eora multi-region input-output (MRIO) database for the year 2015.

(2) For the EU, UK, USA, Japan, and China, existing subnational CF models were used to disaggregate CFn into subnational regions CFr, where the regions r range in size from postcode to province. In steps 3 and 4 these subnational regions are treated the same as countries. The term 'regions' is used to mean the collection of disaggregated subnational regions plus countries which are not disaggregated.

(3) Within each region the CFr was disaggregated between urban vs rural residents according to the difference in urban vs rural resident expenditure patterns and the total urban vs rural population. For 76 countries (a mixture of developed and developing coutnries, driving 19% of global CO2 emissions) no comparative expenditure data were available. In these countries all households were assumed to have a national average expenditure pattern.

(4) CFs of grid cells within a region were calculated by further disaggregating step 3 using gridded population maps and gridded income data. The first step involved in identifying the urban and rural grid cells and subsequently distributing the total urban and rural footprint on the basis of the share of aggregate purchasing power in each cell. Urban cells were identified using the GHS-SMOD layer of urban areas (high and low density population clusters). GHS-SMOD uses a clustering algorithm to identify urban areas as clusters of contiguous cells within a total population and population density above the specified thresholds. Aggregate purchasing power per grid cell was determined by multiplying the population in the cell by the mean purchasing power at that location. Carbon footprints of cities are then defined as the CF of those cells in teh GHS-SMOD layer that are high-density clusters of contiguous grid cells with ≥1500 inhabitants/km2 and within a minimum population of 50,000.

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Formal name

Global Gridded Model of Carbon Footprints (GGMCF)


While many of the urban areas with the highest CF are in countries with high carbon footprints, 41 of the top 200 (e.g. Dhaka, Cairo, Lima) are in countries where total and per capita emissions are low (e.g. Senegal, Egypt, Peru). In these urban areas, population and affluence combine to drive footprints at a similar scale as counterparts in the highest income countries.

Suggested citation

Moran, D., Kanemoto K; Jiborn, M., Wood, R., Többen, J., and Seto, K.C. (2018) Carbon footprints of 13,000 cities. Environmental Research Letters DOI: 10.1088/1748-9326/aac72a. Accessed through Resource Watch, (date).


Norwegian University of Science and Technology (NTNU)
Shinshu University (Shinshu)
Lund University (LU)
Yale University (Yale)

Geographic coverage


Spatial resolution

250 m

Date of content



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