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Life cycle assessment (LCA) of electricity generation technologies: Overview,
comparability and limitations
Turconi, Roberto; Boldrin, Alessio; Astrup, Thomas Fruergaard
Published in:
Renewable and Sustainable Energy Reviews
Link to article, DOI:
10.1016/j.rser.2013.08.013
Publication date:
2013
Document Version
Peer reviewed version
Link back to DTU Orbit
Citation (APA):
Turconi, R., Boldrin, A., & Astrup, T. F. (2013). Life cycle assessment (LCA) of electricity generation
technologies: Overview, comparability and limitations. Renewable and Sustainable Energy Reviews, 28, 555-
565. https://doi.org/10.1016/j.rser.2013.08.013
1
Accepted for publication in Renewable and Sustainable Energy Reviews
Life cycle assessment (LCA) of electricity generation
technologies: overview, comparability and limitations
Roberto Turconi, Alessio Boldrin & Thomas Astrup
Department of Environmental Engineering
Technical University of Denmark
Kgs. Lyngby, Denmark
“NOTE: this is the author’s version of a work that was accepted for publication in Renewable and
Sustainable Energy Reviews. Changes resulting from the publishing process, such as peer review,
editing, corrections, structural formatting, and other quality control mechanisms may not be
reflected in this document. Minor changes may have been made to this manuscript since it was
accepted for publication. A definitive version is published in Renewable and Sustainable Energy
Reviews, vol 28, pp 555-565, doi: dx.doi.org/10.1016/j.rser.2013.08.013”
2
Abstract
Electricity generation is a key contributor to global emissions of greenhouse gases (GHG), NO
x
and
SO
2
and their related environmental impact. A critical review of 167 case studies involving the life
cycle assessment (LCA) of electricity generation based on hard coal, lignite, natural gas, oil,
nuclear, biomass, hydroelectric, solar photovoltaic (PV) and wind was carried out to identify
ranges of emission data for GHG, NO
x
and SO
2
related to individual technologies. It was shown
that GHG emissions could not be used as a single indicator to represent the environmental
performance of a system or technology. Emission data were evaluated with respect to three life
cycle phases (fuel provision, plant operation, and infrastructure). Direct emissions from plant
operation represented the majority of the life cycle emissions for fossil fuel technologies, whereas
fuel provision represented the largest contribution for biomass technologies (71% for GHG, 54%
for NO
x
and 61% for SO
2
) and nuclear power (60% for GHG, 82% for NO
x
and 92% for SO
2
);
infrastructures provided the highest impact for renewables. These data indicated that all three
phases should be included for completeness and to avoid problem shifting. The most critical
methodological aspects in relation to LCA studies were identified as follows: definition of the
functional unit, the LCA method employed (e.g., IOA, PCA and hybrid), the emission allocation
principle and/or system boundary expansion. The most important technological aspects were
identified as follows: the energy recovery efficiency and the flue gas cleaning system for fossil fuel
technologies; the electricity mix used during both the manufacturing and the construction phases
for nuclear and renewable technologies; and the type, quality and origin of feedstock, as well as
the amount and type of co-products, for biomass-based systems. This review demonstrates that
the variability of existing LCA results for electricity generation can give rise to conflicting decisions
regarding the environmental consequences of implementing new technologies.
Keywords: Life cycleassessment, Electricity generation, Emission factors, Environmental impacts,
Emissions
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1. Introduction
Between 1990 and 2008, world energy consumption increased by 40% [1]. Today, 68% of the
energy utilized worldwide originates from fossil fuels (i.e., coal, natural gas and oil), with electricity
generation being responsible for 40% of global CO
2
emissions [1]. Emissions of greenhouse gases
(GHG), such as CO
2
and CH
4
, from energy generation have been addressed in numerous studies
(e.g., [2–8]), which often play a key role in developing GHG mitigation strategies for the energy
sector [9]. However, the extent to which these studies provide accurate, robust and comparable
information can be questioned with respect to their usefulness for long-term decision-making.
Life cycle assessment (LCA), carbon footprinting and other GHG accounting approaches are
commonly used for decision support [10–12]. In LCA, potential environmental impacts associated
with the life cycle of a product/service are assessed based on a life cycle inventory (LCI), which
includes relevant input/output data and emissions compiled for the system associated with the
product/service in question. The comprehensive scope of LCA is useful in avoiding problem-
shifting from one life cycle phase to another, from one region to another, or from one
environmental problem to another [13]. Although a carbon footprint may have more appeal than
LCA due to the simplicity of the approach [14], carbon footprints involve only a single indicator,
which may result in oversimplification. By optimizing the system performance based only on GHG
emissions, new environmental burdens may be introduced from other environmental emissions
(e.g., NO
x
and SO
2
). A holistic or system-level perspective is therefore essential in the assessment,
and the range of emission types included in a study may critically affect the outcome; although
described as "full LCA studies", some studies (e.g., [16–18]) include only GHG emissions. Overall
emissions can be categorized into direct emissions (e.g., from the stack of a power plant) and
indirect emissions (e.g., related either to upstream provision of fuel, resources, goods, etc. or to
downstream management of residues and utilization of by-products). Accounting only for direct
emissions from electricity generation and failing to include indirect emissions may result in
inaccurate conclusions and lead to decisions that do not provide the intended environmental
benefits. Previous studies have clearly indicated that indirect GHG emissions from fossil fuels may
represent up to 25% of the overall emissions related to electricity generation [15]; this value is
even higher for renewable technologies [8].
Electricity is an essential energy carrier in modern societies, and emission data related to
electricity generation are used extensively for accounting and reporting purposes. Datasets and
emission factors for electricity generation (e.g., kg CO
2
/MWh) are used often when performing
LCA and/or GHG accounting of products. However, despite the importance of data reliability and
the large number of studies that assess electricity generation, significant discrepancies can be
found among LCI datasets for similar electricity technologies. Edenhofer et al. [19] attributed these
differences to technology characteristics, local conditions and LCA methodological aspects. Over
the past two decades, LCA guidelines (e.g., ISO 14040 [20] and the ILCD handbook [21]) have been
developed in an attempt to ensure coherence and comparability among LCA studies. However,
these guidelines allow individual researchers to subjectively interpret fundamental methodological
aspects (e.g., choice of system boundaries, allocation procedures, and which emissions to include
in the assessment). Therefore, a simple statement of compliance accompanying these guidelines is
not sufficient to ensure that the results are accurate and robust. Consequently, both LCI data and
LCA results can be misused, whether incidentally or intentionally, when the scope of the original
LCA study and the requirements of a user do not coincide [22]. To prevent misuse and unjustified
4
decisions, it is thus important that i) methodological choices are described transparently and the
scope of the LCA study is narrowly defined and that ii) coherent, appropriate choices are made
regarding the system boundaries and LCI datasets to reduce the gap between the modeled system
and reality. Various approaches exist today among LCA practitioners, but the importance of
methodological choices, emission types and contributions from individual life cycle phases has not
been critically evaluated in the context of electricity generation. A systematic overview of the
consequences of methodological choices and technology performance is needed to provide a
transparent and balanced foundation for future LCA modeling of electricity technologies.
The objective of this study was to provide a systematic overview of important emissions from electricity
generation technologies based on a critical review of relevant LCA studies in the literature. Emission factors
for GHG, NOx, and SO
2
were selected as key indicators for environmental performance during electricity
generation. These emissions were evaluated by i) highlighting important technological differences (e.g.,
conversion efficiencies and gas cleaning technology) among the assessed technologies, ii) identifying critical
methodological choices in LCA studies that affected the results (e.g., system boundaries, functional unit
definition and assessment approach), and iii) whenever possible, providing examples illustrating the
quantitative importance of these aspects. The intention was to provide a sound basis for selection of data
and methodology with respect to LCA modeling of electricity generation.
This paper first provides a critical analysis of the current LCA methodological framework (Section 2),
followed by an outline of the selection criteria applied to emissions data and LCA case studies included in
the review (Section 3). In Section 4, emission data for electricity generation are evaluated according to the
energy source and contributions from fuel provision, plant operation and infrastructure. Section 5
evaluates the importance of key methodological choices and their effect on the results from the LCA
studies.
2. LCA methodology aspects
The current regulatory framework for LCA is defined by ISO 14040 [20] and ISO 14044 [23]. An LCA
study is generally carried out by iterating four phases (goal and scope definition, inventory
analysis, impact assessment, interpretation) and is used to quantify major potential environmental
impacts related to the product or service in question. LCAs are often applied as decision support
tools for selection between different alternatives providing the same product or service. An LCA is
quantified by the concept of a "functional unit" that defines the product or service. The functional
unit thereby ensures comparability among the alternative scenarios.
Current ISO standards provide guidelines for carrying out an LCA study, but allow freedom for
interpretation of key methodological issues [14]. Consequently, subjective choices and approaches
may lead to results that are incompatible with other studies having identical goals and scope.
When selecting LCI datasets for electricity production, it is possible to use harmonized data. A
meta-analytical harmonization of both technical and methodological aspects of life cycle GHG
emissions of energy generation aims to reduce the variability of estimated emission factors and is
done by conforming methodological choices (e.g., system boundaries, allocation procedures, and
emissions) and technical aspects (e.g., efficiencies and fuel quality). Harmonized emission factors
are available for specific technologies: coal [24] (with a focus on the characteristics of the fuel,
combustion technology type and thermal efficiency), nuclear energy [25] (with a focus on the
primary energy mix, uranium grade and enrichment and the LCA approach), solar PV [26,27] (with
a focus on the type of application, meteorological characteristics, performance ratio, lifetime,
efficiency and area of the module) and wind energy [28,29] (with a focus on the technology type,
capacity, lifetime and capacity factor). However, appropriate LCI datasets reflecting the local
![Table 2. Life cycle emission factors for electricity generation from selected technologies. Factors at the top of the table refer to electricity output [kg/MWhout], while values at the bottom of the table refer to fuel input [kg/GJin].](/figures/table-2-life-cycle-emission-factors-for-electricity-8gtl0tc5.webp)
