Today’s map shows an estimate of a household’s carbon footprint based on consumption of various goods and services. You can explore the map here. The maps and data come from the CoolClimate Network at the University of California Berkeley. One thing that becomes clear as you explore the map: the carbon emissions from goods and services doesn’t vary all that much as geography changes (at least in the Twin Cities metro). The big changes across the transect are mostly due to changes in transportation usage and housing-related sources (energy usage).
This consumption-based emissions inventory differs from other approaches explored on streets.mn, like the geographic inventory, because it looks at emissions throughout the supply-chain related to purchases a household makes, regardless of where on earth the emissions originated (think of a computer you buy that is made in China, the emissions are still counted at your household). Here’s a bit from the FAQ on the methodology:
The model uses national household energy, transportation, and consumer expenditures surveys along with local census, weather and other data – 37 variables in total – to approximate greenhouse gas emissions resulting from the energy, transportation, food, goods and services consumed by average households in essentially all populated U.S. zip codes. See the paper and online supporting materials for detailed descriptions of the methods.
The FAQ (and research it is based on), has some interesting discussion of the implications for local and regional planning (the title of the paper is Suburban sprawl cancels carbon-footprint savings of dense urban cores):
Population dense central cities have significantly lower carbon footprints than less dense central cites; however, these cities also have more extensive suburbs. When considering the net effect of all metropolitan residents (suburbs and central city residents together), larger, more populous and population-dense metropolitan areas have slightly higher average carbon footprints than less populous and lower population-dense metropolitan areas.
i. Note: this is the primary finding of the paper that is used in the title. The implication for policy is that suburban sprawl undermines, or cancels, the benefits of urban population density. Urban development planning should focus on impacts at metropolitan as well as more local scales, as is typical in regional transportation planning.
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