Life cycle assessment (LCA) of electricity generation technologies: Overview, comparability and limitations (original) (raw)
Abstract
Electricity generation is a key contributor to global emissions of greenhouse gases (GHG), NO_x_ and SO2 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 SO2 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 SO2) and nuclear power (60% for GHG, 82% for NO_x_ and 92% for SO2); 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.
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 CO2 emissions [1]. Emissions of greenhouse gases (GHG), such as CO2 and CH4, from energy generation have been addressed in numerous studies (e.g., [2], [3], [4], [5], [6], [7], [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], [11], [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 SO2). 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], [17], [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 CO2/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 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, NO_x_, and SO2 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.
Section snippets
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
Emissions included
Emissions of GHG, NO_x_ and SO2 were selected based on their contribution to several critical LCA impact categories and on their importance in decision making and strategic planning. Worldwide, the energy sector contributes 19% and 56% of overall NO_x_ and SO2 emissions [38], respectively, while contributions to GHG emissions amount to 40% [1]. In addition to NH3, emissions of NO_x_ and SO2 are largely responsible for acidification (SO2, NO_x_ and NH3) and eutrophication (NO_x_ and NH3). Because NH3 is
Results
In the following sections, the results for electricity generation technologies are evaluated by energy source. For each electricity generation technology, GHG (labeled CO2-eq.), NO_x_ and SO2 emissions were evaluated and categorized according to contributions from the following three life cycle phases: (1) fuel provision (from the extraction of fuel to the gate of the plant), (2) plant operation (operation and maintenance, including residue disposal), and (3) infrastructure (commissioning and
Discussion
In the following sections, critical methodological aspects influencing the results of the LCA case studies discussed in the previous section are identified and evaluated. To the extent that data availability permits, the aspects identified are quantitatively evaluated. Suggestions are provided for consistent comparisons between individual technologies and for the criteria for data selection in LCA studies.
Conclusions
Emission data for GHG, NO_x_ and SO2 were evaluated based on a critical review of 167 LCA case studies of important electricity generation technologies. Significant variations in the results were found, even for the same individual technology. A range of both technological and methodological differences were identified and evaluated with respect to their importance for LCA results. The most important technological aspects were, for fossil fuel technologies, the energy recovery efficiency and the
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