Correlation between community-wide infrastructure footprint (CIF) GHGs covering Scopes 1+2, expressed in different metrics versus an aggregate urban energy/carbon intensity index (UEI) of cities: (a) GHGCIF Scopes1+2/resident (capita) versus UEI, and, (b) GHGCIF Scopes1+2/GDP versus UEI
Figure 2. Correlation between community-wide infrastructure footprint (CIF) GHGs covering Scopes 1+2, expressed in different metrics versus an aggregate urban energy/carbon intensity index (UEI) of cities: (a) GHGCIF Scopes1+2/resident (capita) versus UEI, and, (b) GHGCIF Scopes1+2/GDP versus UEI. An increasing UEI index indicates higher intensity of energy use (or carbon use) in residential, transportation and commercial–industrial activities within a city, relative to other cities. The data are from models of 20 US cities of diverse economies, each modeled in a two-region MRIO with GHG intensity of electricity use in the different cities ranging from ±50% higher or lower compared to the larger economy.
Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility–connectivity, waste management/sanitation and public amenities to support community-wide activities in cities—all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community—its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input–output models of 20 US cities shows that GHGCIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHGCBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.