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E
Attributes of Life Cycle Assessment
While it is the intention of all life cycle assessments (LCAs) to cover technologies
from “cradle to grave” in a systematic way, there is significant variability in the
assumptions, boundaries, and methodologies used in these assessments. Therefore,
comparisons of LCA should be done with caution; each is an approximation of a
technology’s actual impact. A major complication in comparing LCAs is that there is no
set standard by which such analyses are carried out. There are two basic kinds of LCAs:
economic input/output (EIO) and process analysis (PA). PA can be thought of as a
“bottom-up” approach in which specific information for the energy and emissions
associated with each component of the technology is determined then combined together
to get a complete life-cycle impact. In addition to being very time intensive, the utility of
the PA can be limited by the fact that there is often a lack of information concerning one
of more components of the technology and this can lead to truncation errors.
EIO on the other hand does not track individual components, but instead uses
economy sector level data to quantify the relationship between energy and the materials
and processes produced. As compared to PA, EIO can be thought of as being a “top-
down” approach. While having the advantage of being less time and data intensive, the
accuracy of the EIO is limited by its dependence upon highly aggregated data that may or
may not be appropriate for the specific process or material being considered.
Recent investigations suggest that EIO analyses tend to give higher energy use
and emissions estimates than PA; perhaps because PA is only able to consider the subset
of processes for which data are available (Fthenakis and Kim, 2007; Odeh and Cockerill,
2008). A third method, sometimes referred to as the “hybrid” LCA, attempts to address
this issue by combining aspects of both techniques: using the PA approach where specific
data are available and the EIO method where such data are not available.
To provide a coherent and consistent framework for LCA’s, various agencies
have compiled life cycle inventory (LCI) databases that list the materials and energy
inputs required for various technologies. For example, ECLIPSE (Frankl et al., 2004) is a
LCI assessment project developed in Europe that looks at emissions and resource
consumption. Other PA-type LCI databases include DEAM (Ecobilan, 2001), Franklin
(Franklin Associates, 2008) and Ecoinvent (Pre Consultants, 2007b). EIO analyses
typically rely on economic databases that are complied by governmental bodies. For
example in the United States, the Department of Commerce generates data on air
emission and water and energy use for 485 commodity sectors from various data sources.
Beyond the choice of LCA method and LCI database, there are any number of
other factors that can affect LCA results and cause discrepancies between analyses.
Assumptions about power plant capacity (or lifetime output), plant life expectancy, and
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energy infrastructure influence LCA results. In general, when comparing installations of
the same energy technology, those with longer plant life expectancies and greater
electrical output to the grid will have lower lifetime emissions per unit of electricity.
The nature of the underlying energy structure that supports the manufacture,
operation, and dismantling of a given facility are also quite important. For example, the
construction of a wind turbine in Sweden where much of the energy is produced using
renewable sources will generally have less embedded CO2 emissions than the same
turbine produced in the United States, where coal-fired power plants generate a
significant fraction of the electricity available on the grid.
A further source of discrepancies for LCAs arises from the fact that these
assessments are aimed at technologies that are often undergoing continuous modification
and improvement. Comparisons cited here of an LCA for a given technology may differ
because the technology under consideration evolved over the period from one LCA to
another. This is especially true for solar and wind technologies where the ongoing rate of
innovations is quite rapid. A further complication arises from the fact that some LCAs
assess impacts for a hypothetical, future installation of the technology.
Another shortcoming of LCA is that it only addresses a single environmental
impact. If one is in the position of choosing one technology over another, it would be
desirable to have a more integrated understanding of the overall environmental impact of
one technology over another. Environmental valuation methods attempt to do this by
estimating the overall ecosystem impact of a technology using currency or “willingness
to pay” as the unit to integrate across types of impacts. Impact categories included in
environmental valuation methods typically relate to damages to humans, ecosystems and
resources. ExternE (European Commission, 1997) and Eco-indicator 99 (Pre
Consultants, 2007a) are examples of environmental valuation methods used in Europe.
The main criticism of environmental valuation methods is of the step where
disparate effects of LCA’s are weighted and normalized into a single value per
technology. Often the development of a single value is not adequate to capture the
complexities of a technology and metrics like “willingness to pay” can vary over time.
For this reason we limit our discussion to LCA results.
REFERENCES
Ecobilan, P. 2001. TEAM/DEAM. 2001. PriceWaterhouseCoopers, Bethesda, Md.
European Commission. 1997. External Costs of Electricity Generation in Greece.
ExternE Project. Available at http://externe.jrc.es/reports.html.
Frankl, P., Corrado, A., and S. Lombardelli. 2004. Photovoltaic (PV) Systems. Final
Report. ECLIPSE (Environmental and Ecological Life Cycle Inventories for
present and future Power Systems in Europe), European Commission. January.
Franklin Associates, visited April 7, 2008, http://www.fal.com/lifecycle.html.
Fthenakis, V.M., and H.C. Kim. 2007. Greenhouse-gas emissions from solar electric- and
nuclear power: A life-cycle study. Energy Policy 35:2549-2557.
Odeh, N.A. and T.T. Cockerill. 2008. Life cycle GHG assessment of fossil fuel power
plants with carbon capture and storage, Energy Policy 38:367-380.
Pre Consultants. 2007a. Available at http://www.pre.nl/eco-indicator99.
Pre Consultants. 2007b. Available at http://www.pre.nl/ecoinvent/.
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