Multiple sources of information can be used to better inform emissions modelers. For

example, if a state and/or industry has shown steady decreases in gross product over the past five

years, that information could temper (or be used in place of) a projected 30% growth predicted

from EGAS over the next 10 years. Such a discrepancy would simply highlight the fact that all

models, including REMI or those used by DOE can produce results that are not consistent with

other expectations. In addition, because of changes in technologies and fuel efficiency, economic

growth is not necessarily a sufficient indicator of emissions growth. While this guidance does not

provide a prescriptive approach for combining such information, the authors recognize that

predicting the future of emissions is not an exact science and therefore multiple sources of

information should be used to develop an informed approach.

EGAS. The latest EGAS model at this time is version 5 (http://www.epa.gov/ttn/ecas/egas5.htm)

The default version of EGAS relies primarily on three sources of data: (1) state-specific economic

data from the Regional Economic Model, Inc. (REMI) Policy Insight ® model (version 5.5) that

includes population growth estimates, (2) Region-specific fuel-use projections from the U.S.

Department of Energy (DOE) Annual Energy Outlook 2004, and (3) VMT projections included in

the MOBILE6.0 model. EGAS outputs growth factors that do not include control information for

a user-define base year and multiple future years through 2035. EGAS uses default cross-walks

from these data sources to SIC, SCC and MACT codes. The DOE data are used to compute

growth factors assigned by default to stationary source fuel combustion sectors, the VMT

projections are used for on-road mobile, and the REMI data are used for the remaining sectors.

Additionally, EGAS5 supports emissions modelers adding new data sources, changing

assignments of data sources to SICs, SCCs, and MACT codes, and creating custom configurations

of data that best represent the growth expected in their modeling region. The additional sources

of information listed below can be input into EGAS to develop such custom scenarios. It should

 

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