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Energy-use benchmarks for the case-study cities

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posted on 2013-07-03, 00:00 authored by Anu Ramaswami, Abel Chavez

Table 1.  Energy-use benchmarks for the case-study cities. Comparative state-level benchmark shown in [bracket]. (Note: energy-use data: local retrieved from bottom-up data (ICLEI 2010), state retrieved from (EIA 2012); employment statistics: local retrieved from (MIG 2010), state retrieved from (Census 2011); population and households: local retrieved from (MIG 2010), state retrieved from (Census 2011); vehicles miles traveled (VMT): local retrieved from (ICLEI 2010), state retrieved from (FHWA 2008).)

Abstract

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.

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