27. University of Minnesota, College of Architecture and Landscape Architecture. 2002. Minnesota Sustainable
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28. University of Minnesota, College of Architecture and Landscape Architecture, 2004, Minnesota Building
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29. Green Building Initiative
. 2004. Green Globes, The Green Building Initiative, Portland OR
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30. To access EPA's energy performance rating system called Target Finder go to:
www.energystar.gov/index.cfm?c=target_finder.bus_target_finder, February 13, 2005.
31. U.S. Climate Change Technology Program. 2003. Technology Options for the Near and Long Term, U.S.
Department of Energy, Washington, DC, pp. 24, 27, 30. November.
32. Newell, R., A. Jaffe, and R. Stavins. 1999. The induced innovation hypothesis and energy saving techno
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33. See, e.g., Goulder, L.H. 2004. Induced Technological Change and Climate Policy, Pew Center on Global
Climate Change, Arlington, VA.
34. U.S. Climate Change Technology Program, 2003, op cit, p. 21.
35. Brown, M.A., Mark D. Levine, Walter Short, and Jonathan G. Koomey. 2001. Scenarios for a clean energy
future. Energy Policy 29(14): 1179 1196; Office of Technology Assessment (OTA). 1991. Changing by Degrees: Steps
to Reduce Greenhouse Gases. OTA 0 482. U.S. Government Printing Office, Washington, DC, February; National
Academy of Sciences. 1992. Policy Implications of Greenhouse Warming: Mitigation, Adaptation, and the Science Base.
National Academy Press, Washington, DC; Tellus Institute. 1998. Policies and Measures to Reduce CO
Emissions in the
United States: An Analysis of Options for 2005 and 2010. Tellus Institute, Boston, MA, August.
36. Interlaboratory Working Group. 2000. Scenarios for a Clean Energy Future. ORNL/CON 476 and LBNL
44029. Oak Ridge National Laboratory, Oak Ridge, TN, and Lawrence Berkeley National Laboratory, Berkeley, CA,
November, http://www.ornl.gov/sci/eere/cef/index.htm, February 4, 2005. The Scenarios for a Clean Energy Future was a
study conducted by five DOE National Laboratories that involved enumerating on a technology by technology basis the
difference between current practice and best practice, where best practice is defined as the utilization of the energy
technologies with the lowest life cycle costs. Keeping in mind the natural rate of turnover of new equipment and con
sumer purchases, one can then estimate the size of the lost opportunities or gap that exists. Brown et al. (2001, op cit)
used this technology based accounting approach and concluded that removing obstacles to energy efficiency through
policy interventions initiated in the year 2000 could have reduced the forecasted U.S. energy consumption in 2010 by
10 percent. By 2020, the reduction could grow to nearly 20 percent.
37. DOE National Laboratory Directors. 1998. Technology Opportunities to Reduce U.S. Greenhouse Gas Emissions.
Oak Ridge National Laboratory, Oak Ridge, TN. September, http://www.ornl.gov/~webworks/cppr/y2003/rpt/110512.pdf,
February 4, 2005.
38. The energy efficiency gap is the difference between the actual level of investment in energy efficiency
and the higher level that would be cost beneficial from the consumer's and society's point of view. Jaffe, A.B., and R.N.
Stavins. 1994. The energy efficiency gap, Energy Policy 22(10): 804 810.
39. Sutherland, R.J. 1996. The economics of energy conservation policy, Energy Policy 24(4): 361 370.
40. Braithwait, S., and D. Caves. 1994. Three biases in cost efficiency tests of utility energy efficiency pro
grams. The Energy Journal 15(1): 95 120.
41. For a detailed examination of the U.S. housing industry and the homebuilding process, see Scott Hassell,
Anny Wong, Ari Houser, Debra Knopman, and Mark Bernstein. 2003. Building Better Homes. Rand Corporation,
42. EIA. 1999. Commercial Buildings Energy Consumption Survey, table B12, p. 46 48. EIA, Washington, DC.
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