Background and Reflections on the Life Cycle Assessment Harmonization Project

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

SummaryA systematic review and harmonization of life cycle assessment (LCA) literature of nuclear electricity generation technologies was performed to determine causes of and, where possible, reduce variability in estimates of life cycle greenhouse gas (GHG) emissions to clarify the state of knowledge and inform decision making. LCA literature indicates that life cycle GHG emissions from nuclear power are a fraction of traditional fossil sources, but the conditions and assumptions under which nuclear power are deployed can have a significant impact on the magnitude of life cycle GHG emissions relative to renewable technologies.Screening 274 references yielded 27 that reported 99 independent estimates of life cycle GHG emissions from light water reactors (LWRs). The published median, interquartile range (IQR), and range for the pool of LWR life cycle GHG emission estimates were 13, 23, and 220 grams of carbon dioxide equivalent per kilowatt‐hour (g CO2‐eq/kWh), respectively. After harmonizing methods to use consistent gross system boundaries and values for several important system parameters, the same statistics were 12, 17, and 110 g CO2‐eq/kWh, respectively. Harmonization (especially of performance characteristics) clarifies the estimation of central tendency and variability.To explain the remaining variability, several additional, highly influential consequential factors were examined using other methods. These factors included the primary source energy mix, uranium ore grade, and the selected LCA method. For example, a scenario analysis of future global nuclear development examined the effects of a decreasing global uranium market‐average ore grade on life cycle GHG emissions. Depending on conditions, median life cycle GHG emissions could be 9 to 110 g CO2‐eq/kWh by 2050.

Assessing the greenhouse gas mitigation potential of urban precincts with hybrid life cycle assessment

The primary goal of this work was to assess the magnitude and variability of published life cycle greenhouse gas (GHG) emission estimates for three types of geothermal electricity generation technologies: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash, and HT binary. These technologies were chosen to align the results of this report with technologies modeled in National Renewable Energy Laboratory's (NREL's) Regional Energy Deployment Systems (ReEDs) model. Although we did gather and screen life cycle assessment (LCA) literature on hybrid systems, dry steam, and two geothermal heating technologies, we did not analyze published GHG emission estimates for these technologies. In our systematic literature review of the LCA literature, we screened studies in two stages based on a variety of criteria adapted from NREL's Life Cycle Assessment (LCA) Harmonization study (Heath and Mann 2012). Of the more than 180 geothermal studies identified, only 29 successfully passed both screening stages and only 26 of these included estimates of life cycle GHG emissions. We found that the median estimate of life cycle GHG emissions (in grams of carbon dioxide equivalent per kilowatt-hour generated [g CO2eq/kWh]) reported by these studies are 32.0, 47.0, and 11.3 for EGS binary, HT flash, and HT binary, respectively (Figure ES-1). We also found that the total life cycle GHG emissions are dominated by different stages of the life cycle for different technologies. For example, the GHG emissions from HT flash plants are dominated by the operations phase owing to the flash cycle being open loop whereby carbon dioxide entrained in the geothermal fluids is released to the atmosphere. This is in contrast to binary plants (using either EGS or HT resources), whose GHG emissions predominantly originate in the construction phase, owing to its closed-loop process design. Finally, by comparing this review's literature-derived range of HT flash GHG emissions to data from currently operating geothermal plants, we found that emissions from operational plants exhibit more variability and the median of emissions from operational plants is twice the median of operational emissions reported by LCAs. Further investigation is warranted to better understand the cause of differences between published LCAs and estimates from operational plants and to develop LCA analytical approaches that can yield estimates closer to actual emissions.

Summary A systematic review and harmonization of life cycle assessment (LCA) literature of utility‐scale wind power systems was performed to determine the causes of and, where possible, reduce variability in estimates of life cycle greenhouse gas (GHG) emissions. Screening of approximately 240 LCAs of onshore and offshore systems yielded 72 references meeting minimum thresholds for quality, transparency, and relevance. Of those, 49 references provided 126 estimates of life cycle GHG emissions. Published estimates ranged from 1.7 to 81 grams CO 2 ‐equivalent per kilowatt‐hour (g CO 2 ‐eq/kWh), with median and interquartile range (IQR) both at 12 g CO 2 ‐eq/kWh. After adjusting the published estimates to use consistent gross system boundaries and values for several important system parameters, the total range was reduced by 47% to 3.0 to 45 g CO 2 ‐eq/kWh and the IQR was reduced by 14% to 10 g CO 2 ‐eq/kWh, while the median remained relatively constant (11 g CO 2 ‐eq/kWh). Harmonization of capacity factor resulted in the largest reduction in variability in life cycle GHG emission estimates. This study concludes that the large number of previously published life cycle GHG emission estimates of wind power systems and their tight distribution suggest that new process‐based LCAs of similar wind turbine technologies are unlikely to differ greatly. However, additional consequential LCAs would enhance the understanding of true life cycle GHG emissions of wind power (e.g., changes to other generators’ operations when wind electricity is added to the grid), although even those are unlikely to fundamentally change the comparison of wind to other electricity generation sources.

Summary This systematic review and harmonization of life cycle assessments (LCAs) of utility‐scale coal‐fired electricity generation systems focuses on reducing variability and clarifying central tendencies in estimates of life cycle greenhouse gas (GHG) emissions. Screening 270 references for quality LCA methods, transparency, and completeness yielded 53 that reported 164 estimates of life cycle GHG emissions. These estimates for subcritical pulverized, integrated gasification combined cycle, fluidized bed, and supercritical pulverized coal combustion technologies vary from 675 to 1,689 grams CO 2 ‐equivalent per kilowatt‐hour (g CO 2 ‐eq/kWh) (interquartile range [IQR]= 890–1,130 g CO 2 ‐eq/kWh; median = 1,001) leading to confusion over reasonable estimates of life cycle GHG emissions from coal‐fired electricity generation. By adjusting published estimates to common gross system boundaries and consistent values for key operational input parameters (most importantly, combustion carbon dioxide emission factor [CEF]), the meta‐analytical process called harmonization clarifies the existing literature in ways useful for decision makers and analysts by significantly reducing the variability of estimates (−53% in IQR magnitude) while maintaining a nearly constant central tendency (−2.2% in median). Life cycle GHG emissions of a specific power plant depend on many factors and can differ from the generic estimates generated by the harmonization approach, but the tightness of distribution of harmonized estimates across several key coal combustion technologies implies, for some purposes, first‐order estimates of life cycle GHG emissions could be based on knowledge of the technology type, coal mine emissions, thermal efficiency, and CEF alone without requiring full LCAs. Areas where new research is necessary to ensure accuracy are also discussed.

Life cycle greenhouse gas emission reduction potential of battery electric vehicle

Impacts of alternative fuel combustion in cement manufacturing: Life cycle greenhouse gas, biogenic carbon, and criteria air contaminant emissions

We suggest a 2D-plot representation combined with life cycle greenhouse gas (GHG) emissions and life cycle cost for various energy conversion technologies. In general, life cycle assessment (LCA) not only analyzes at the use phase of a specific technology, but also covers widely related processes of before and after its use. We use life cycle GHG emissions and life cycle cost (LCC) to compare the energy conversion process for eight resources such as coal, natural gas, nuclear power, hydro power, geothermal power, wind power, solar thermal power, and solar photovoltaic (PV) power based on the reported LCA and LCC data. Among the eight sources, solar PV and nuclear power exhibit the highest and the lowest LCCs, respectively. On the other hand, coal and wind power locate the highest and the lowest life cycle GHG emissions. In addition, we used the 2D plot to show the life cycle performance of GHG emissions and LCCs simultaneously and realized a correlation that life cycle GHG emission is largely inversely proportional to the corresponding LCCs. It means that an expensive energy source with high LCC tends to have low life cycle GHG emissions, or is environmental friendly. For future study, we will measure the technological maturity of the energy sources to determine the direction of the specific technology development based on the 2D plot of LCCs versus life cycle GHG emissions.

Introducing demand to supply ratio as a new metric for understanding life cycle greenhouse gas (GHG) emissions from rainwater harvesting systems

This study characterized and evaluated the life cycle greenhouse gas (GHG) emissions from different wind electricity generation systems by (a) performing a comprehensive review of the wind electricity generation system life cycle assessment (LCA) studies and (b) statistically evaluating the life cycle GHG emissions (expressed in grams of carbon dioxide equivalent per kilowatt hour, gCO2e/kWh). A categorization index (with unique category codes, formatted as ‘axis of rotation-installed location-power generation capacity’) was adopted for use in this study to characterize the reviewed wind electricity generation systems. The unique category codes were labeled by integrating the names from the three wind power sub-classifications, i.e., the axis of rotation of the wind turbine [horizontal axis wind turbine (HAWT), vertical axis wind turbine (VAWT)], the location of the installation [onshore (ON), offshore (OFF)], and the electricity production capacity [small (S), intermediate (I), large (L)]. The characterized wind electricity generation systems were statistically evaluated to assess the reduction in life cycle GHG emissions. A total of five unique categorization codes (HAWT-ON-S, HAWT-ON-I, HAWT-ON-L, HAWT-OFF-L, VAWT-ON-S) were designated to the 29 wind electricity generation LCA studies (representing 74 wind system cases) using the proposed categorization index. The mean life cycle GHG emissions resulting from the use of HAWT-ON-S (N = 3), HAWT-ON-I (N = 4), HAWT-ON-L (N = 58), HAWT-OFF-L (N = 8), and VAWT-ON-S (N = 1) wind electricity generation systems are 38.67, 11.75, 15.98, 12.9, and 46.4 gCO2e/kWh, respectively. The HAWT-ON-I wind electricity generation systems produced the minimum life cycle GHGs than other wind electricity generation systems.

Considering Battery Degradation in Life Cycle Greenhouse Gas Emission Analysis of Electric Vehicles

Summary In reviewing life cycle assessment (LCA) literature of utility‐scale concentrating solar power (CSP) systems, this analysis focuses on reducing variability and clarifying the central tendency of published estimates of life cycle greenhouse gas (GHG) emissions through a meta‐analytical process called harmonization. From 125 references reviewed, 10 produced 36 independent GHG emissions estimates passing screens for quality and relevance: 19 for parabolic trough (trough) technology and 17 for power tower (tower) technology. The interquartile range (IQR) of published estimates for troughs and towers were 83 and 20 grams of carbon dioxide equivalent per kilowatt‐hour (g CO 2 ‐eq/kWh), 1 respectively; median estimates were 26 and 38 g CO 2 ‐eq/kWh for trough and tower, respectively. Two levels of harmonization were applied. Light harmonization reduced variability in published estimates by using consistent values for key parameters pertaining to plant design and performance. The IQR and median were reduced by 87% and 17%, respectively, for troughs. For towers, the IQR and median decreased by 33% and 38%, respectively. Next, five trough LCAs reporting detailed life cycle inventories were identified. The variability and central tendency of their estimates are reduced by 91% and 81%, respectively, after light harmonization. By harmonizing these five estimates to consistent values for global warming intensities of materials and expanding system boundaries to consistently include electricity and auxiliary natural gas combustion, variability is reduced by an additional 32% while central tendency increases by 8%. These harmonized values provide useful starting points for policy makers in evaluating life cycle GHG emissions from CSP projects without the requirement to conduct a full LCA for each new project.

Greenhouse gas emissions from renewable energy sources: A review of lifecycle considerations

This study evaluated the life cycle greenhouse gas (GHG) emissions from different hydroelectricity generation systems by first performing a comprehensive review of the hydroelectricity generation system life cycle assessment (LCA) studies and then subsequent computation of statistical metrics to quantify the life cycle GHG emissions (expressed in grams of carbon dioxide equivalent per kilowatt hour, gCO2e/kWh). A categorization index (with unique category codes, formatted as “facility type-electric power generation capacity”) was developed and used in this study to evaluate the life cycle GHG emissions from the reviewed hydroelectricity generation systems. The unique category codes were labeled by integrating the names of the two hydro power sub-classifications, i.e., the facility type (impoundment (I), diversion (D), pumped storage (PS), miscellaneous hydropower works (MHPW)) and the electric power generation capacity (micro (µ), small (S), large (L)). The characterized hydroelectricity generation systems were statistically evaluated to determine the reduction in corresponding life cycle GHG emissions. A total of eight unique categorization codes (I-S, I-L, D-µ, D-S, D-L, PS-L, MHPW-µ, MHPW-S) were designated to the 19 hydroelectricity generation LCA studies (representing 178 hydropower cases) using the proposed categorization index. The mean life cycle GHG emissions resulting from the use of I-S (N = 24), I-L (N = 8), D-µ (N = 3), D-S (N = 133), D-L (N = 3), PS-L (N = 3), MHPW-µ (N = 3), and MHPW-S (N = 1) hydroelectricity generation systems are 21.05 gCO2e/kWh, 40.63 gCO2e/kWh, 47.82 gCO2e/kWh, 27.18 gCO2e/kWh, 3.45 gCO2e/kWh, 256.63 gCO2e/kWh, 19.73 gCO2e/kWh, and 2.78 gCO2e/kWh, respectively. D-L hydroelectricity generation systems produced the minimum life cycle GHGs (considering the hydroelectricity generation system categories with a representation of at least two cases).