Summary of different GHG accounting methods, and the correlation of the resulting GHGs normalized indifferent metrics with an aggregate urban energy/carbon intensity index (UEI) of cities
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Table 2. Summary of different GHG accounting methods, and the correlation of the resulting GHGs normalized indifferent metrics with an aggregate urban energy/carbon intensity index (UEI) of cities. (a) Results for 20 US cities of diverse types, each modeled as a two-region MRIO with GHG intensity of electricity use modeled to vary randomly from ±50% higher or lower compared to the larger economy. (b) Results for the same 20 US cities in a SRIO; all cities have the same electricity GHG intensity as 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.