Environmental impacts of hybrid and electric vehicles—a review

Purpose

A literature review is undertaken to understand how well existing studies of the environmental impacts of hybrid and electric vehicles (EV) address the full life cycle of these technologies. Results of studies are synthesized to compare the global warming potential (GWP) of different EV and internal combustion engine vehicle (ICEV) options. Other impacts are compared; however, data availability limits the extent to which this could be accomplished.

Method

We define what should be included in a complete, state-of-the-art environmental assessment of hybrid and electric vehicles considering components and life cycle stages, emission categories, impact categories, and resource use and compare the content of 51 environmental assessments of hybrid and electric vehicles to our definition. Impact assessment results associated with full life cycle inventories (LCI) are compared for GWP as well as emissions of other pollutants. GWP results by life cycle stage and key parameters are extracted and used to perform a meta-analysis quantifying the impacts of vehicle options.

Results

Few studies provide a full LCI for EVs together with assessment of multiple impacts. Research has focused on well to wheel studies comparing fossil fuel and electricity use as the use phase has been seen to dominate the life cycle of vehicles. Only very recently have studies begun to better address production impacts. Apart from batteries, very few studies provide transparent LCIs of other key EV drivetrain components. Estimates of EV energy use in the literature span a wide range, 0.10?C0.24?kWh/km. Similarly, battery and vehicle lifetime plays an important role in results, yet lifetime assumptions range between 150,000?C300,000?km. CO₂ and GWP are the most frequently reported results. Compiled results suggest the GWP of EVs powered by coal electricity falls between small and large conventional vehicles while EVs powered by natural gas or low-carbon energy sources perform better than the most efficient ICEVs. EV results in regions dependant on coal electricity demonstrated a trend toward increased SO _x emissions compared to fuel use by ICEVs.

Conclusions

Moving forward research should focus on providing consensus around a transparent inventory for production of electric vehicles, appropriate electricity grid mix assumptions, the implications of EV adoption on the existing grid, and means of comparing vehicle on the basis of common driving and charging patterns. Although EVs appear to demonstrate decreases in GWP compared to conventional ICEVs, high efficiency ICEVs and grid-independent hybrid electric vehicles perform better than EVs using coal-fired electricity.     

Life Cycle Assessment of Electric and Fuel Cell Vehicle Transport Based on Forest Biomass

Use of biomass‐based electricity and hydrogen in alternative transport could provide environmentally sustainable transport options with possible improvements in greenhouse gas balance. We perform a life cycle assessment of electric vehicle (EV) and fuel cell vehicle (FCV) powered by bioelectricity and biohydrogen, respectively, derived from Norwegian boreal forest biomass, considering the nonclimate neutrality of biological carbon dioxide (CO₂) emissions and alteration in surface albedo resulting from biomass harvesting—both with and without CO₂ capture and storage (CCS)—while benchmarking these options against EVs powered by the average European electricity mix. Results show that with due consideration of the countering effects from global warming potential (GWP) factors for biogenic CO₂ emissions and change in radiative forcing of the surface for the studied region, bioenergy‐based EVs and FCVs provide reductions of approximately 30%, as compared to the reference EV powered by the average European electricity mix. With CCS coupled to bioenergy production, the biomass‐based vehicle transport results in a net global warming impact reduction of approximately 110% to 120% (giving negative GWP and creating a climate‐cooling benefit from biomass use). Other environmental impacts vary from ?60% to +60%, with freshwater eutrophication showing maximum reductions (40% for the EV case and 60% for the FCV case) and photochemical oxidation showing a maximum increase (60% in the FCV value chain).     

中国省级火电供应生命周期清单分析

应用生命周期评价方法,建立了我国各省区的火电供应生命周期清单。清单分析结果表明,我国各省区单位火电供应的生命周期清单之间,及与全国单位火电供应的生命周期清单之间均存在一定差异,以总能源投入和全球变暖潜值为例进行了分析。在全球变暖潜值方面,我国单位火电供应的平均值为1.05kg/k Wh。云南等15个省区的单位火电全球变暖潜值与全国平均水平相差±10%以上。如果基于全国单位火电供应的平均全球变暖潜值计算各省火电总量全球变暖潜值,与基于各省单位火电全球变暖潜值计算的结果相比,也存在一定的差距。15个省区与基于全国平均值计算的结果相差±10%以上,表明了核算各省区火电清单的必要性。中国省级火电供应生命周期清单为省区级别的材料、产品、产业等生命周期评价提供数据支撑,也为各省区电力节能减排提供了理论基础。     

Comparative environmental and economic life cycle assessment of biogas production from perennial wild plant mixtures and maize (Zea mays L.) in southwest Germany

Maize silage is the main biogas co‐substrate in Germany, but its use is often questioned due to negative environmental impacts. Perennial wild plant mixtures (WPM) are increasingly considered alternatives, as these extensive systems improve soil quality and enhance agrobiodiversity. Methane yields per hectare however do not match those of maize. This study examined whether the potential advantages of replacing maize with WPM for biogas production are counteracted by lower yields and associated effects. Life cycle assessment and life cycle cost assessment were used to compare the environmental and economic performance of electricity generation from WPM in two establishment procedures, ‘standard’ (WPM E1) and ‘under maize’ (WPM E2). These metrics were benchmarked against those of maize. The production of 1 kWh electricity was chosen as functional unit. The life cycle inventory of the agricultural phase was based on multi‐annual field trials in southwest Germany. Both WPM E1 and E2 had lower marine eutrophication and global warming potentials than maize. The GWP favourability was however sensitive to the assumptions made with regard to the amount and fate of carbon sequestered in the soil. WPM E1 performed less favourable than WPM E2. This was mainly due to lower yields, which could, in turn, result in potential indirect land use impacts. These impacts may outweigh the carbon sequestration benefits of WPM cultivation. Maize performed best in terms of economic costs, freshwater eutrophication, terrestrial acidification, fine particulate matter and ozone formation. We conclude that the widespread deployment of WPM systems on productive agricultural land should only take place if permanent soil carbon sequestration can be ensured. In either case, WPM cultivation could be a valid alternative for bioenergy buffers and marginal land where competitive yields of common crops cannot be guaranteed, but which could accommodate low‐input cultivation systems.     

Environmental Effects of Steam Explosion Pretreatment on Biogas from Maize—Case Study of a 500-kW Austrian Biogas Facility

Potential environmental impacts of biogas electricity from agricultural residues (maize stover) with steam explosion (SE) pretreatment were compared to a typical Austrian biogas system (maize silage) using the method of life cycle assessment. Besides the biogas plant, the system includes substrate production, a combined heat-and-power (CHP) unit, digestate management, and transportation. The stover scenario (including construction and operation of the SE unit) results in lower total climate change impacts than those of the typical biogas system (239 g CO₂-eq/kWh electricity vs. 287 g CO₂-eq/kWh electricity; 100-year global warming potential (GWP)), and this holds also for the other impact categories (e.g., cumulative energy demand, acidification, eutrophication). While uncertainties in other areas could change the results, based on the uncertainty information considered, the overall results for the two scenarios were significantly different. Methane slip emissions from the CHP exhaust account for the largest GWP share in both scenarios. Other large GWP contributions are from substrate production and grid electricity for plant operations. The findings were robust against worst-case assumptions about the energy requirements of the SE pretreatment.     

Life Cycle Assessment of a Lithium‐Ion Battery Vehicle Pack

Electric vehicles (EVs) have no tailpipe emissions, but the production of their batteries leads to environmental burdens. In order to avoid problem shifting, a life cycle perspective should be applied in the environmental assessment of traction batteries. The aim of this study was to provide a transparent inventory for a lithium‐ion nickel‐cobalt‐manganese traction battery based on primary data and to report its cradle‐to‐gate impacts. The study was carried out as a process‐based attributional life cycle assessment. The environmental impacts were analyzed using midpoint indicators. The global warming potential of the 26.6 kilowatt‐hour (kWh), 253‐kilogram battery pack was found to be 4.6 tonnes of carbon dioxide equivalents. Regardless of impact category, the production impacts of the battery were caused mainly by the production chains of battery cell manufacture, positive electrode paste, and negative current collector. The robustness of the study was tested through sensitivity analysis, and results were compared with preceding studies. Sensitivity analysis indicated that the most effective approach to reducing climate change emissions would be to produce the battery cells with electricity from a cleaner energy mix. On a per‐kWh basis, cradle‐to‐gate greenhouse gas emissions of the battery were within the range of those reported in preceding studies. Contribution and structural path analysis allowed for identification of the most impact‐intensive processes and value chains. This article provides an inventory based mainly on primary data, which can easily be adapted to subsequent EV studies, and offers an improved understanding of environmental burdens pertaining to lithium‐ion traction batteries.     

Cattle feed or bioenergy? Consequential life cycle assessment of biogas feedstock options on dairy farms

On‐farm anaerobic digestion (AD) of wastes and crops can potentially avoid greenhouse gas (GHG) emissions, but incurs extensive environmental effects via carbon and nitrogen cycles and substitution of multiple processes within and outside farm system boundaries. Farm models were combined with consequential life cycle assessment (CLCA) to assess plausible biogas and miscanthus heating pellet scenarios on dairy farms. On the large dairy farm, the introduction of slurry‐only AD led to reductions in global warming potential (GWP) and resource depletion burdens of 14% and 67%, respectively, but eutrophication and acidification burden increases of 9% and 10%, respectively, assuming open tank digestate storage. Marginal GWP burdens per Mg dry matter (DM) feedstock codigested with slurry ranged from –637 kg CO₂e for food waste to +509 kg CO₂e for maize. Codigestion of grass and maize led to increased imports of concentrate feed to the farm, negating the GWP benefits of grid electricity substitution. Attributing grass‐to‐arable land use change (LUC) to marginal wheat feed production led to net GWP burdens exceeding 900 kg CO₂e Mg^?1 maize DM codigested. Converting the medium‐sized dairy farm to a beef‐plus‐AD farm led to a minor reduction in GWP when grass‐to‐arable LUC was excluded, but a 38% GWP increase when such LUC was attributed to marginal maize and wheat feed required for intensive compensatory milk production. If marginal animal feed is derived from soybeans cultivated on recently converted cropland in South America, the net GWP burden increases to 4099 kg CO₂e Mg^?1 maize DM codigested – equivalent to 55 Mg CO₂e yr^?1 per hectare used for AD‐maize cultivation. We conclude that AD of slurry and food waste on dairy farms is an effective GHG mitigation option, but that the quantity of codigested crops should be strictly limited to avoid potentially large international carbon leakage via animal feed displacement.     

Life cycle sustainability assessment of autonomous heavy‐duty trucks

Connected and automated vehicles (CAVs) are emerging technologies expected to bring important environmental, social, and economic improvements in transportation systems. Given their implications in terms of air quality and sustainable and safer movement of goods, heavy‐duty trucks (HDTs), carrying the majority of U.S. freight, are considered an ideal domain for the application of CAV technology. An input–output (IO) model is developed based on the Eora database—a detailed IO database that consists of national IO tables, covering almost the entire global economy. Using the Eora‐based IO model, this study quantifies and assesses the environmental, economic, and social impacts of automated diesel and battery electric HDTs based on 20 macro‐level indicators. The life cycle sustainability performances of these HDTs are then compared to that of a conventional diesel HDT. The study finds an automated diesel HDT to cause 18% more fatalities than an automated electric HDT. The global warming potential (GWP) of automated diesel HDTs is estimated to be 4.7 thousand metric tons CO₂‐eq. higher than that of automated electric HDTs. The health impact costs resulting from an automated diesel HDT are two times higher than that of an automated electric HDT. Overall, the results also show that automation brings important improvements to the selected sustainability indicators of HDTs such as global warming potential, life cycle cost, GDP, decrease in import, and increase in income. The findings also show that there are significant trade‐offs particularly between mineral and fossil resource losses and environmental gains, which are likely to complicate decision‐making processes regarding the further development and commercialization of the technology.     

Integrated Life Cycle Assessment and Life Cycle Cost Model for Comparing Plug‐in versus Wireless Charging for an Electric Bus System

An integrated life cycle assessment and life cycle cost (LCC) model was developed to compare the life cycle performance of plug‐in charging versus wireless charging for an electric bus system. The model was based on a bus system simulation using existing transit bus routes in the Ann Arbor–Ypsilanti metro area in Michigan. The objective is to evaluate the LCCs for an all‐electric bus system utilizing either plug‐in or wireless charging and also compare these costs to both conventional pure diesel and hybrid bus systems. Despite a higher initial infrastructure investment for off‐board wireless chargers deployed across the service region, the wireless charging bus system has the lowest LCC of US$0.99 per bus‐kilometer among the four systems and has the potential to reduce use‐phase carbon emissions attributable to the lightweighting benefits of on‐board battery downsizing compared to plug‐in charging. Further uncertainty analysis and sensitivity analysis indicate that the unit price of battery pack and day or night electricity price are key parameters in differentiating the LCCs between plug‐in and wireless charging. Additionally, scenario analyses on battery recycling, carbon emission pricing, and discount rates were conducted to further analyze and compare their respective life cycle performance.     

Life cycle assessment of recirculating aquaculture systems: A case of Atlantic salmon farming in China

Recirculating aquaculture systems (RAS) are an alternative technology to tackle the major environmental challenges associated with conventional cage culture systems. In order to systematically assess the environmental performance of RAS farming, it is important to take the whole life cycle into account so as to avoid ad hoc and suboptimal environmental measures. So far, the application of life cycle assessment (LCA) in aquaculture, especially to indoor RAS, is still in progress. This study reports on an LCA of Atlantic salmon harvested at an indoor RAS farm in northern China. Results showed that 1 tonne live‐weight salmon production required 7,509 kWh farm‐level electricity and generated 16.7 tonnes of CO₂ equivalent (eq), 106 kg of SO₂ eq, 2.4 kg of P eq, and 108 kg of N eq (cradle‐to‐farm gate). In particular, farm‐level electricity use and feed product were identified as primary contributors to eight of nine impact categories assessed (54–95% in total), except the potential marine eutrophication (MEU) impact (dominated by the grow‐out effluents). Among feed ingredients (on a dry‐weight basis), chicken meal (5%) and krill meal (8%) dominated six and three, respectively, of the nine impact categories. Suggested environmental improvement measures for this indoor RAS farm included optimization of stocking density, feeding management, grow‐out effluent treatment, substitution of feed ingredients, and selection of electricity generation sources. In a generic context, this study can contribute to a better understanding of the life cycle environmental impacts of land‐based salmon RAS operations, as well as science‐based communication among stakeholders on more eco‐friendly farmed salmon.     

Fuel Economy and Greenhouse Gas Emissions Labeling for Plug‐In Hybrid Vehicles from a Life Cycle Perspective

Fuel economy has been an effective indicator of vehicle greenhouse gas (GHG) emissions for conventional gasoline‐powered vehicles due to the strong relationship between fuel economy and vehicle life cycle emissions. However, fuel economy is not as accurate an indicator of vehicle GHG emissions for plug‐in hybrid (PHEVs) and pure battery electric vehicles (EVs). Current vehicle labeling efforts by the U.S. Environmental Protection Agency (EPA) and Department of Transportation have been focused on providing energy and environmental information to consumers based on U.S. national average data. This article explores the effects of variations in regional grids and regional daily vehicle miles traveled (VMT) on the total vehicle life cycle energy and GHG emissions of electrified vehicles and compare these results with information reported on the label and on the EPA's fuel economy Web site. The model results suggest that only 25% of the life cycle emissions from a representative PHEV are reflected on current vehicle labeling. The results show great variation in total vehicle life cycle emissions due to regional grid differences, including an approximately 100 gram per mile life cycle GHG emissions difference between the lowest and highest electric grid regions and up to a 100% difference between the state‐specific emission values within the same electric grid regions. Unexpectedly, for two regional grids the life cycle GHG emissions were higher in electric mode than in gasoline mode. We recommend that labels include stronger language on their deficiencies and provide ranges for GHG emissions from vehicle charging in regional electricity grids to better inform consumers.     

Site‐specific life cycle assessment of a pilot floating offshore wind farm based on suppliers’ data and geo‐located wind data

Renewable energy systems are essential in coming years to ensure an efficient energy supply while maintaining environmental protection. Despite having low environmental impacts during operation, other phases of the life cycle need to be accounted for. This study presents a geo‐located life cycle assessment of an emerging technology, namely, floating offshore wind farms. It is developed and applied to a pilot project in the Mediterranean Sea. The materials inventory is based on real data from suppliers and coupled to a parameterized model which exploits a geographic information system wind database to estimate electricity production. This multi‐criteria assessment identified the extraction and transformation of materials as the main contributor to environmental impacts such as climate change (70% of the total 22.3 g CO₂ eq/kWh), water use (73% of 6.7 L/kWh), and air quality (76% of 25.2 mg PM2.5/kWh), mainly because of the floater's manufacture. The results corroborate the low environmental impact of this emerging technology compared to other energy sources. The electricity production estimates, based on geo‐located wind data, were found to be a critical component of the model that affects environmental performance. Sensitivity analyses highlighted the importance of the project's lifetime, which was the main parameter responsible for variations in the analyzed categories. Background uncertainties should be analyzed but may be reduced by focusing data collection on significant contributors. Geo‐located modeling proved to be an effective technique to account for geographical variability of renewable energy technologies and contribute to decision‐making processes leading to their development.     

Uncertainty Quantification in Life Cycle Assessments: Interindividual Variability and Sensitivity Analysis in LCA of Air‐Conditioning Systems

The life cycle environmental profile of energy‐consuming products, such as air conditioning, is dominated by the products’ use phase. Different user behavior patterns can therefore yield large differences in the results of a cradle‐to‐grave assessment. Although this variation and uncertainty is increasingly recognized, it remains often poorly characterized in life cycle assessment (LCA) studies. Today, pervasive sensing presents the opportunity to collect rich data sets and improve profiling of use‐phase parameters, in turn facilitating quantification and reduction of this uncertainty in LCA. This study examined the case of energy use in building cooling systems, focusing on global warming potential (GWP) as the impact category. In Singapore, building cooling systems or air conditioning consumes up to 37% of national electricity demand. Lack of consideration of variation in use‐phase interaction leads to the oversized designs, wasted energy, and therefore reducible GWP. Using a high‐resolution data set derived from sensor observations, energy use and behavior patterns of single‐office occupants were characterized by probabilistic distributions. The interindividual variability and use‐phase variables were propagated in a stochastic model for the life cycle of air‐conditioning systems and simulated by way of Monte Carlo analysis. Analysis of the generated uncertainties identified plausible reductions in global warming impact through modifying user interaction. Designers concerned about the environmental profile of their products or systems need better representation of the underlying variability in use‐phase data to evaluate the impact. This study suggests that data can be reliably provided and incorporated into the life cycle by proliferation of pervasive sensing, which can only continue to benefit future LCA.     

Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale

Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricity produced by individual gas‐ and oil‐fired power plants across the world. The regression model uses power plant characteristics as predictors, including capacity, age, fuel type (fuel oil or natural gas), and technology type (single or combined cycle) of the plant. The predictive power of the model was relatively high (R² = 81% for predictions). Fuel and technology type were identified as the most important predictors. Estimated emission factors ranged from 0.45 to 1.16 kilograms carbon dioxide equivalents per kilowatt‐hour (kg CO₂‐eq/kWh) and were clearly different between natural gas combined cycle (0.45 to 0.57 kg CO₂‐eq/kWh), natural gas single cycle (0.66 to 0.85 kg CO₂‐eq/kWh), oil combined cycle power plants (0.63 to 0.79 kg CO₂‐eq/kWh), and oil single cycle (0.94 to 1.16 kg CO₂‐eq/kWh). Our results thus indicate that emission data averaged by fuel and technology type can be profitably used to estimate the emissions of individual plants.     

Attributional and Consequential Environmental Assessment of the Shift to Lead-Free Solders (10 pp)

- Goal, Scope, Background. As of July 1st, 2006, lead will be banned in most solder pastes used in the electronics industry. This has called for environmental evaluation of alternatives to tin-lead solders. Our life cycle assessment (LCA) has two aims: (i) to compare attributional and consequential LCA methodologies, and (ii) to compare a SnPb solder (62% tin, 36% lead, 2% silver) to a Pb-free solder (95.5% tin, 3.8% silver, 0.7% copper). Methods An attributional LCA model describes the environmental impact of the solder life cycle. Ideally, it should include average data on each unit process within the life cycle. The model does not include unit processes other than those of the life cycle investigated, but significant cut-offs within the life cycle can be avoided through the use of environmentally expanded input-output tables. A consequential LCA model includes unit processes that are significantly affected irrespective of whether they are within or outside the life cycle. Ideally, it should include marginal data on bulk production processes in the background system. Our consequential LCA model includes economic partial equilibrium models of the lead and scrap lead markets. However, both our LCA models are based on data from the literature or from individual production sites. The partial equilibrium models are based on assumptions. The life cycle impact assessment is restricted to global warming potential (GWP). Results and Discussion The attributional LCA demonstrates the obvious fact that the shift from SnPb to Pb-free solder means that lead is more or less eliminated from the solder life cycle. The attributional LCA results also indicate that the Pb-free option contributes 10% more to the GWP than SnPb. Despite the poor quality of the data, the consequential LCA demonstrates that, when lead use is eliminated from the solder life cycle, the effect is partly offset by increased lead use in batteries and other products. This shift can contribute to environmental improvement because lead emissions are likely to be greatly reduced, while batteries can contribute to reducing GWP, thereby offsetting part of the GWP increase in the solder life cycle. Conclusions The shift from SnPb to Pb-free solder is likely to result in reduced lead emissions and increased GWP. Attributional and consequential LCAs yield complementary knowledge on the consequences of this shift in solder pastes. At present, consequential LCA is hampered by the lack of readily available marginal data and the lack of input data to economic partial equilibrium models. However, when the input to a consequential LCA model is in the form of quantitative assumptions based on a semi-qualitative discussion, the model can still generate new knowledge. Recommendations and Outlook Experts on partial equilibrium models should be involved in consequential LCA modeling in order to improve the input data on price elasticity, marginal production, and marginal consumption.     

Life cycle assessment of electrical and thermal energy systems for commercial buildings

Background, Aim and Scope The objective of this life cycle assessment (LCA) study is to develop LCA models for energy systems in order to assess the potential environmental impacts that might result from meeting energy demands in buildings. The scope of the study includes LCA models of the average electricity generation mix in the USA, a natural gas combined cycle (NGCC) power plant, a solid oxide fuel cell (SOFC) cogeneration system; a microturbine (MT) cogeneration system; an internal combustion engine (ICE) cogeneration system; and a gas boiler. Methods LCA is used to model energy systems and obtain the life cycle environmental indicators that might result when these systems are used to generate a unit energy output. The intended use of the LCA analysis is to investigate the operational characteristics of these systems while considering their potential environmental impacts to improve building design using a mixed integer linear programming (MILP) optimization model. Results The environmental impact categories chosen to assess the performance of the energy systems are global warming potential (GWP), acidification potential (AP), tropospheric ozone precursor potential (TOPP), and primary energy consumption (PE). These factors are obtained for the average electricity generation mix, the NGCC, the gas boiler, as well as for the cogeneration systems at different part load operation. The contribution of the major emissions to the emission factors is discussed. Discussion The analysis of the life cycle impact categories indicates that the electrical to thermal energy production ratio has a direct influence on the value of the life cycle PE consumption factors. Energy systems with high electrical to thermal ratios (such as the SOFC cogeneration systems and the NGCC power plant) have low PE consumption factors, whereas those with low electrical to thermal ratios (such as the MT cogeneration system) have high PE consumption factors. In the case of GWP, the values of the life cycle GWP obtained from the energy systems do not only depend on the efficiencies of the systems but also on the origins of emissions contributing to GWP. When evaluating the life cycle AP and TOPP, the types of fuel as well as the combustion characteristics of the energy systems are the main factors that influence the values of AP and TOPP. Conclusions An LCA study is performed to eraluate the life cycle emission factors of energy systems that can be used to meet the energy demand of buildings. Cogeneration systems produce utilizable thermal energy when used to meet a certain electrical demand which can make them an attractive alternative to conventional systems. The life cycle GWP, AP, TOPP and PE consumption factors are obtained for utility systems as well as cogeneration systems at different part load operation levels for the production of one kWh of energy output. Recommendations and Perspectives Although the emission factors vary for the different energy systems, they are not the only factors that influence the selection of the optimal system for building operations. The total efficiencies of the system play a significant part in the selection of the desirable technology. Other factors, such as the demand characteristics of a particular building, influence the selection of energy systems. The emission factors obtained from this LCA study are used as coefficients of decision variables in the formulation of an MILP to optimize the selection of energy systems based on environmental criteria by taking into consideration the system efficiencies, emission characteristics, part load operation, and building energy demands. Therefore, the emission factors should not be regarded as the only criteria for choosing the technology that could result in lower environmental impacts, but rather one of several factors that determine the selection of the optimum energy system. ESS-Submission Editor: Arpad Horvath (horvath@ce.berkeley.edu)     

Life Cycle Greenhouse Gas Emissions of Electricity Generated from Conventionally Produced Natural Gas

This research provides a systematic review and harmonization of the life cycle assessment (LCA) literature of electricity generated from conventionally produced natural gas. We focus on estimates of greenhouse gases (GHGs) emitted in the life cycle of electricity generation from natural gas‐fired combustion turbine (NGCT) and combined‐cycle (NGCC) systems. The smaller set of LCAs of liquefied natural gas power systems and natural gas plants with carbon capture and storage were also collected, but analyzed to a lesser extent. A meta‐analytical process we term “harmonization” was employed to align several system boundaries and technical performance parameters to better allow for cross‐study comparisons, with the aim of clarifying central tendency and reducing variability in estimates of life cycle GHG emissions. Of over 250 references identified, 42 passed screens for technological relevance and study quality, providing a total of 69 estimates for NGCT and NGCC. Harmonization increased the median estimates in each category as a result of several factors not typically considered in the previous research, including the regular clearing of liquids from a well, and consolidated the interquartile range for NGCC to 420 to 480 grams of carbon dioxide equivalent per kilowatt‐hour (g CO₂‐eq/kWh) and for NGCT to 570 to 750 g CO₂‐eq/kWh, with medians of 450 and 670 CO₂‐eq/kWh, respectively. Harmonization of thermal efficiency had the largest effect in reducing variability; methane leakage rate is likely similarly influential, but was unharmonized in this assessment as a result of the significant current uncertainties in its estimation, an area that is justifiably receiving significant research attention.     

Life cycle environmental impacts of decommissioning Magnox nuclear power plants in the UK

Purpose

Full life cycle assessment (LCA) impacts from decommissioning have rarely been assessed, largely because few sites have been decommissioned so that the impacts of decommissioning are currently uncertain. This paper presents the results of an LCA study of the ongoing decommissioning of the Magnox power plant at Trawsfynydd in the UK. These results have been used to estimate the potential environmental impacts for the whole UK Magnox fleet of 11 reactors that will have to be decommissioned during this century.

Methods

The functional unit is defined as ‘decommissioning one Magnox power plant’. The system boundary considers all stages in the life cycle of decommissioning, including site management, waste retrieval, plant deconstruction, packaging and storage of intermediate- and low-level wastes (ILW and LLW). High-level waste, i.e. waste fuel is excluded as it was being removed from the site to be reprocessed at Sellafield. The environmental impacts have been estimated using the CML 2001 methodology. Primary data have been sourced from the Trawsfynydd site and the background from Ecoinvent.

Results and discussion

Most impacts from decommissioning are due to the plant deconstruction (25–75 %) and ILW storage and disposal (25–70 %). For the example of global warming potential (GWP), estimated at 241 kt CO₂ eq./functional unit, or 3.5 g CO₂ eq./kWh of electricity generated during the lifetime of the plant, 55 % of the impact is from plant deconstruction and 30 % from ILW disposal. The results for the whole UK Magnox fleet indicate that the impacts vary greatly for different sites. For example, the GWP ranges from 0.89 to 7.14 g CO₂ eq./kWh. If the impacts from storage of waste fuel at Sellafield are included in the estimates, the GWP increases on average by four times. Overall, decommissioning of the UK Magnox reactors would generate 2 Mt of CO₂ eq. without and 11 Mt of CO₂ eq. with the waste from Sellafield. This represents 0.4 and 2 % of the total UK annual emissions, respectively.

Conclusions

The impacts of decommissioning can vary greatly at different sites depending on the amount of waste and electricity generated by the plants. Delaying decommissioning to allow the energy system to decarbonise could reduce the environmental impacts, e.g. GWP could be reduced by 50 %. The impacts could also be reduced by reducing the volume of waste and increasing recycling of materials. For example, recycling 70 % of steel would reduce the impacts on average by 34 %.     

Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada

Purpose

This paper assesses facility-specific life cycle greenhouse gas (GHG) emission intensities for electricity-generating facilities in the province of Ontario in 2008. It offers policy makers, researchers and other stakeholders of the Ontario electricity system with data regarding some of the environmental burdens from multiple generation technology currently deployed in the province.

Methods

Methods involved extraction of data and analysis from several publically accessible datasets, as well as from the LCA literature. GHG emissions data for operation of power plants came from the Government of Canada GHG registry and the Ontario Power Generation (OPG) Sustainable Development reports. Facility-specific generation data came from the Independent Electricity System Operator in Ontario and the OPG.

Results

Full life cycle GHG intensity (tonnes of CO₂ equivalent per gigawatt hour) estimates are provided for 4 coal facilities, 27 natural gas facilities, 1 oil/natural gas facility, 3 nuclear facilities, 7 run-of-river hydro facilities and 37 reservoir hydro facilities, and 7 wind facilities. Average (output weighted) life cycle GHG intensities are calculated for each fuel type in Ontario, and the life cycle GHG intensity for the Ontario grid as a whole (in 2008) is estimated to be 201 t CO₂e/GWh.

Conclusions

The results reflect only the global warming impact of electricity generation, and they are meant to inform a broader discussion which includes other environmental, social, cultural, institutional and economic factors. This full range of factors should be included in decisions regarding energy policy for the Province of Ontario, and in future work on the Ontario electricity system.     

Life cycle of CO2-emissions from electric vehicles and gasoline vehicles utilizing a process-relational model

This article aims at estimating life cycle CO₂ emissions from electric vehicles (EV) and gasoline vehicles (GV), although the estimation in this study is not an LCA according to ISO14040s. For this purpose, a mathematical tool called the Process-relational model was developed. The Process-relational model is used for establishing life cycle inventories. The model has a structure which improved the principle of input-output analysis in econometrics that only one product is generated by one process. This model enabled us to overcome difficulties of LCA in retracing complicated repercussions among production systems. Then, life cycle CO₂, emissions from electric vehicles (EV) and gasoline vehicles (GV) were estimated with this model. Estimated results indicated that the manufacture and driving of EV resulted in less CO₂ emissions than chose of GV. However, the difference between EV and GV dramatically changed depending on traffic situations. Namely, the difference became larger as the average velocity of the vehicles became lower. We also compared CO₂, emission from manufacturing EV with that from driving EV. The share of manufacture was shown to increase in total CO₂, emissions as the average velocity of the EV became higher. In conclusion, we clarified the direction of research and development of EV and GV for reducing the life cycle CO₂.