GREENHOUSE GAS EMISSION BASELINES ■ 49excluded or included primarily depends on whether the baseline GHG mea-
sures are only to inform local government policy or are to be a wider refl ection
of the carbon dependence of urban economies. If aviation and marine emis-
sions are included, then they should refl ect the global connections that exist
between cities—and thus include all emissions from international transporta-
tion. (Data to support such calculations are already collected at national levels
but not reported in national totals as per the UNFCCC.) Th e methodology
of Ramaswami and others (2008) addresses issues with assigning emissions
when passengers transfer between fl ights and incorporates most relevant cross-
boundary energy fl ows critical for functioning of cities. Overall, resolution of
these diff erences seems tractable.
Th e emissions attributable to urban areas may be considered from diff erent
perspectives. Emissions can be strictly based on spatially limited geographic
boundaries of an urban area or on a broader consideration that also includes
signifi cant cross-boundary embodied energy fl ows occurring in cities. Emission
attribution can also be made based on “producer” and “consumer” approaches
or a combination of both or hybrid approach (Ramaswami and others 2008).
Care must be taken in applying a hybrid approach to avoid double counting.
It is important that an emissions baseline is produced to meet its purpose.
It may be of interest to local government, urban policy makers, or both. It may,
if it is for policy purposes, need to provide data that enable a region to help
deliver national and international commitments on emissions reduction. It
may be used for public communication about GHG emissions, which oft en is
also an implicit goal in developing baselines.
Th e baseline emissions include those for cities and some wider metropolitan
regions. Merits exist for developing baseline emissions for both. Cities have a
single administrative authority (albeit subject to national, provincial, and state
governments), enabling them to have potentially greater control over emissions
reductions. Metropolitan regions sometimes have more fragmented political
authority, yet these regions typically have higher per capita emissions than
cities because of low-density suburbs (Glaeser and Kahn 2008; VandeWeghe
and Kennedy 2007), airports, and oft en higher concentrations of industry.
A strong point of the methodology reviewed in this chapter is that it applies
equally well to cities and to metropolitan regions.
Aside from the discussed diff erences with emissions from, for example,
waste and airline and marine activities, the greatest uncertainty in urban GHG
baselines lies with emissions from road transportation. In table 2.2, we dis-
tinguished between three techniques for estimating gasoline consumption in
urban areas (sales, models and surveys, and scaling). Diff erences between these
techniques may be less than 5 percent (Kennedy and others 2010). Th is uncer-
tainty might be reduced further, however, if new urban transportation models