Using monte carlo simulation in life cycle assessment for electric and internal combustion vehicles

1 Background

The U.S. Government has encouraged shifting from internal combustion engine vehicles (ICEVs) to alternatively fueled vehicles such as electric vehicles (EVs) for three primary reasons: reducing oil dependence, reducing greenhouse gas emissions, and reducing Clean Air Act criteria pollutant emissions. In comparing these vehicles, there is uncertainty and variability in emission factors and performance variables, which cause wide variation in reported outputs.

2 Objectives

A model was developed to demonstrate the use of Monte Carlo simulation to predict life cycle emissions and energy consumption differences between the ICEV versus the EV on a per kilometer (km) traveled basis. Three EV technologies are considered: lead-acid, nickel-cadmium, and nickel metal hydride batteries.

3 Methods

Variables were identified to build life cycle inventories between the EVs and ICEV. Distributions were selected for each of the variables and input to Monte Carlo Simulation soft-ware called Crystal Ball 2000®.

4 Results and Discussion

All three EV options reduce U.S. oil dependence by shifting to domestic coal. The life cycle energy consumption per kilometer (km) driven for the EVs is comparable to the ICEV; however, there is wide variation in predicted energy values. The model predicts that all three EV technologies will likely increase oxides of sulfur and nitrogen as well as particulate matter emissions on a per km driven basis. The model shows a high probability that volatile organic compounds and carbon monoxide emissions are reduced with the use of EVs. Lead emissions are also predicted to increase for lead-acid battery EVs. The EV will not reduce greenhouse gas emissions substantially and may even increase them based on the current U.S. reliance on coal for electricity generation. The EV may benefit public health by relocating air pollutants from urban centers, where traffic is concentrated, to rural areas where electricity generation and mining generally occur. The use of Monte Carlo simulation in life cycle analysis is demonstrated to be an effective tool to provide further insight on the likelihood of emission outputs and energy consumption.     

Life Cycle Assessment of Diesel and Electric Public Transportation Buses

The Clean Air Act in the United States identifies diesel‐powered motor vehicles, including transit buses, as significant sources of several criteria pollutants that contribute to ground‐level ozone formation or smog. The effects of air pollution in urban areas are often more significant due to congestion and can lead to respiratory and cardiovascular health impacts. Life cycle assessment (LCA) has been utilized in the literature to compare conventional gasoline‐powered passenger cars with various types of electric and hybrid‐powered alternatives, however, no similarly detailed studies exist for mass transit buses. LCA results from this study indicate that the use phase, consisting of diesel production/combustion for the conventional bus and electricity generation for the electric bus, dominates most impact categories; however, the effects of battery production are significant for global warming, carcinogens, ozone depletion, and eco‐toxicity. There is a clear connection between the mix of power‐generation technologies and the preference for the diesel or electric bus. With the existing U.S. average grid, there is a strong preference for the conventional diesel bus over the electric bus when considering global warming impacts alone. Policy makers must consider regional variations in the electricity grid prior to recommending the use of battery electric buses to reduce carbon dioxide (CO₂) emissions. This study found that the electric bus was preferable in only eight states, including Washington and Oregon. Improvements in battery technology reduce the life cycle impacts from the electric bus, but the electricity grid makeup is the dominant variable.     

Regional assessment of local emissions of electric vehicles using traffic simulations for a use case in Germany

Purpose

In order to assess the global and local environmental impacts of different penetration rates of electric vehicles (EVs) within a region, we developed a life cycle approach based on a detailed traffic simulation assessing local emissions for individual roads with a high time resolution. The aim was to estimate the reduction potential of local emissions such as particulate matter within a region through a substitution of conventional with electric vehicles.

Materials and methods

The chosen approach assessing local emissions includes a detailed traffic simulation of a vehicle fleet composed of individual vehicles with a daily schedule. The driving pattern is modeled based on a survey of driving patterns in Germany. Incorporation of traffic density for each road and emissions of electric and conventional vehicles permits conclusions on the reduction potential for each street. Moreover, a feasible reduction potential for a particular region can be assessed. A case study for Aachen, Germany is presented within this paper. For the classification of the local emissions with the usual life cycle assessment approach, a comparison of EV, PHEV, and conventional vehicles has been conducted for Germany providing the results for impact categories according to CML 2001.

Results and discussion

Based on simulation results, an estimation of the reduction potential for Aachen for different penetration rates of electric vehicles including particulate matter (PM₁₀), carbon monoxide (CO), and nitrogen oxygen (NOx) is carried out. Electric vehicles possess the highest reduction potential for CO and NOx. Assuming 50?% of the total vehicle fleet in 2010 substituted by electric vehicles, local emissions of CO reduce by 46.6?%, for NOx by 38.8?%, and for PM₁₀ by 22.4?%. Due to fluctuations in driving patterns throughout a day, the results are highly time dependent. However, improvements in combustion engine technologies results in an increased reduction potential for conventional vehicles. The direct comparison between the vehicle types showed that the benefit of electric vehicles depends on the considered impact category.

Conclusions

Electric vehicles are able to reduce local emissions within a region. Moreover, this approach focusing on the use phase of vehicles within a regional assessment and the resulting local emissions as well as the detailed analysis of the driving behavior allows a distinguished assessment of the reduction potential of electric vehicles. Additionally, an assessment of policy measures such as drive restrictions for conventional vehicles can be simulated on the base of this approach.     

A new hybrid method for reducing the gap between WTW and LCA in the carbon footprint assessment of electric vehicles

Purpose

The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO₂ emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.

Methods

The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.

Results and discussion

A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.

Conclusions

The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.

     

Model for the Part Manufacturing and Vehicle Assembly Component of the Vehicle Life Cycle Inventory

A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The model is based on a process‐level approach, accounting for all significant materials by their transformation processes (aluminum castings, polyethylene blow molding; etc.) and plant operation activities (painting; heating, ventilation, and air conditioning [HVAC], etc.) germane to VMA. Using quantitative results for these material/transformation process pairings, a percent‐by‐weight material/transformation distribution (MTD) function was developed that permits the model to be applied to a range of vehicles, both conventional and advanced (e.g., hybrid electric, light weight, aluminum intensive). Upon consolidation of all inputs, the model reduces to two terms: one proportional to vehicle mass and a plant overhead per vehicle term. When the model is applied to a materially well‐characterized conventional vehicle, reliable estimates of cumulative energy consumption (34 gigajoules/vehicle) and carbon dioxide (CO₂) emissions (2 tonnes/vehicle) with coefficients of variation are computed for the VMA life cycle stage. Due to the more comprehensive coverage of manufacturing operations, our energy estimates are on the higher end of previously published values. Nonetheless, they are still somewhat underestimated due to a lack of data on overhead operations in part manufacturing facilities and transportation of parts and materials between suppliers and vehicle manufacturing operations. For advanced vehicles, the material/transformation process distribution developed above needs some adjusting for different materials and components. Overall, energy use and CO₂ emissions from the VMA stage are about 3.5% to 4.5% of total life cycle values for vehicles.     

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.     

Empirical Fuel Consumption and CO2 Emissions of Plug‐In Hybrid Electric Vehicles

Plug‐in hybrid electric vehicles (PHEVs) combine electric and conventional propulsion. Official fuel consumption values of PHEVs are based on standardized driving cycles, which show a growing discrepancy with real‐world fuel consumption. However, no comprehensive empirical results on PHEV fuel consumption are available, and the discrepancy between driving cycle and empirical fuel consumption has been conjectured to be large for PHEV. Here, we analyze real‐world fuel consumption data from 2,005 individual PHEVs of five PHEV models and observe large variations in individual fuel consumption with deviation from test‐cycle values in the range of 2% to 120% for PHEV model averages. Deviations are larger for short‐ranged PHEVs. Among others, range and vehicle power are influencing factors for PHEV model fuel consumption with average direct carbon dioxide (CO₂) emissions decreasing by 2% to 3% per additional kilometer (km) of electric range. Additional simulations show that PHEVs recharged from renewable electricity can noteworthily reduce well‐to‐wheel CO₂ emissions of passenger cars, but electric ranges should not exceed 200 to 300 km since battery production is CO₂‐intense. Our findings indicate that regulations should (1) be based on real‐world fuel consumption measurements for PHEV, (2) take into account charging behavior and annual mileages, and (3) incentivize long‐ranged PHEV.     

Understanding the future of lithium: Part 2, temporally and spatially resolved life‐cycle assessment modeling

An array of emerging technologies, from electric vehicles to renewable energy systems, relies on large‐format lithium ion batteries (LIBs). LIBs are a critical enabler of clean energy technologies commonly associated with air pollution and greenhouse gas mitigation strategies. However, LIBs require lithium, and expanding the supply of lithium requires new lithium production capacity, which, in turn, changes the environmental impacts associated with lithium production since different resource types and ore qualities will be exploited. A question of interest is whether this will lead to significant changes in the environmental impacts of primary lithium over time. Part one of this two‐part article series describes the development of a novel resource production model that predicts future lithium demand and production characteristics (e.g., timing, location, and ore type). In this article, part two, the forecast is coupled with anticipatory life‐cycle assessment (LCA) modeling to estimate the environmental impacts of producing battery‐grade lithium carbonate equivalent (LCE) each year between 2018 and 2100. The result is a normalized life‐cycle impact intensity for LCE that reflects the changing resource type, quantity, and region of production. Sustained growth in lithium demands through 2100 necessitates extraction of lower grade resources and mineral deposits, especially after 2050. Despite the reliance on lower grade resources and differences in impact intensity for LCE production from each deposit, the LCA results show only small to modest increases in impact, for example, carbon intensity increases from 3.2 kg CO₂e/kg LCE in 2020 to 3.3 kg CO₂e/kg LCE in 2100.     

Life cycle analysis of biochemical cellulosic ethanol under multiple scenarios

Cellulosic ethanol is widely believed to offer substantial environmental advantages over petroleum fuels and grain‐based ethanol, particularly in reducing greenhouse gas emissions from transportation. The environmental impacts of biofuels are largely caused by precombustion activities, feedstock production and conversion facility operations. Life cycle analysis (LCA) is required to understand these impacts. This article describes a field‐to‐blending terminal LCA of cellulosic ethanol produced by biochemical conversion (hydrolysis and fermentation) using corn stover or switchgrass as feedstock. This LCA develops unique models for most elements of the biofuel production process and assigns environmental impact to different phases of production. More than 30 scenarios are evaluated, reflecting a range of feedstock, technology and scale options for near‐term and future facilities. Cellulosic ethanol, as modeled here, has the potential to significantly reduce greenhouse gas (GHG) emissions compared to petroleum‐based liquid transportation fuels, though substantial uncertainty exists. Most of the conservative scenarios estimate GHG emissions of approximately 45–60 g carbon dioxide equivalent per MJ of delivered fuel (g CO₂e MJ^?1) without credit for coproducts, and 20–30 g CO₂e MJ^?1 when coproducts are considered. Under most scenarios, feedstock production, grinding and transport dominate the total GHG footprint. The most optimistic scenarios include sequestration of carbon in soil and have GHG emissions below zero g CO₂e MJ^?1, while the most pessimistic have life‐cycle GHG emissions higher than petroleum gasoline. Soil carbon changes are the greatest source of uncertainty, dominating all other sources of GHG emissions at the upper bound of their uncertainty. Many LCAs of biofuels are narrowly constrained to GHG emissions and energy; however, these narrow assessments may miss important environmental impacts. To ensure a more holistic assessment of environmental performance, a complete life cycle inventory, with over 1100 tracked material and energy flows for each scenario is provided in the online supplementary material for this article.     

Using LCA‐based Decomposition Analysis to Study the Multidimensional Contribution of Technological Innovation to Environmental Pressures

This article presents a general framework for macroenvironmental assessment, combining life cycle assessment (LCA) with the IPAT equation, and explores its combination with decomposition analysis to assess the multidimensional contribution of technological innovation to environmental pressures. This approach is illustrated with a case study in which carbon dioxide (CO₂) and nitrogen oxides (NO_x) air emissions from diesel passenger cars in Europe during the period 1990–2005 are first decomposed using index decomposition analysis into technology, consumption activity, and population growth effects. By a second decomposition, the contribution of a specific innovation (diesel engine) is calculated on the basis of the technology and consumption activity effects, through a technological comparison with a relevant alternative and the calculation of the rebound effect, respectively. The empirical analysis for diesel passenger cars highlights the discrepancies between the micro (LCA) and macro (IPAT‐LCA) analytical approaches. Thus, whereas diesel engines present a relatively less‐pollutant environmental product profile than their gasoline counterparts, total CO₂ and NO_x emissions would have increased partly as a consequence of their introduction, mainly driven by the increase in travel demand caused by the induced direct price rebound effect from fuel savings and fuel price differences. The counterintuitive result shows the need for such an analysis.     

Are future recycling benefits misleading? Prospective life cycle assessment of lithium-ion batteries

Life cycle assessment (LCA) quantifies the whole-life environmental impacts of products and is essential for helping policymakers and manufacturers transition toward sustainable practices. However, typical LCA estimates future recycling benefits as if it happens today. For long-lived products such as lithium-ion batteries, this may be misleading since there is a considerable time gap between production and recycling. To explore this temporal mismatch problem, we apply future electricity scenarios from an integrated assessment model—IMAGE—using “premise” in Brightway2 to conduct a prospective LCA (pLCA) on the global warming potential of six battery chemistries and four recycling routes. We find that by 2050, electricity decarbonization under an RCP2.6 scenario mitigates production impacts by 57%, so to reach zero-carbon batteries it is important to decarbonize upstream heat, fuels, and direct emissions. For the best battery recycling case, data for 2020 gives a net recycling benefit of −22 kg CO₂e kWh⁻¹ which reduces the net impact of production and recycling from 71 to 49 kg CO₂e kWh⁻¹. However, for recycling in 2040 with decarbonized electricity, net recycling benefits would be nearly 75% lower (−6 kg CO₂e kWh⁻¹), giving a net impact of 65 kg CO₂e kWh⁻¹. This is because materials recycled in the future substitute lower-impact processes due to expected electricity decarbonization. Hence, more focus should be placed on mitigating production impacts today instead of relying on future recycling. These findings demonstrate the importance of pLCA in tackling problems such as temporal mismatch that are difficult to capture in typical LCA.     

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.     

Environmental Impact of Public Charging Facilities for Electric Two‐Wheelers

The environmental characterization of the charging infrastructure required to operate electric vehicles (EVs) is usually overlooked in the literature. Only rudimentary life cycle inventories of EV charging facilities are available. This lack of information is especially noticeable in environmental studies of the environmental performance of electric two‐wheelers (E2Ws), none of which have included an analysis of charging facilities, even though they constitute the most successful electric‐drive market in the world. This article focuses on characterizing the life cycle of the global warming potential (GWP) and primary energy demand (PED) of two conventional charging facility designs that are widely implemented for charging E2Ws in public spaces. The relative environmental relevance of charging facilities per kilowatt‐hour (kWh) supplied to E2Ws is determined by considering a range of use scenarios (variability in the service ratio) and the effect of upgrading the electricity mix to include more renewable energy sources. Savings of over 3 metric tons (tonnes) of carbon dioxide equivalent emissions and 56 equivalent gigajoules can be achieved by implementing an optimized charging facility design. The internalization of the relative environmental burden from the charging facility per kWh supplied to E2Ws can increase the GWP of E2Ws’ use phase from 1% to 20% and the PED from 1% to 13%. Although the article focuses on one particular case scenario, the research is intended to provide complementary criteria for further research on the life cycle management of electric mobility systems. Thus, a series of factors that can influence the environmental performance of EV charging networks at the macro scale are discussed.     

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).     

Climate mitigation by dairy intensification depends on intensive use of spared grassland

Milk and beef production cause 9% of global greenhouse gas (GHG) emissions. Previous life cycle assessment (LCA) studies have shown that dairy intensification reduces the carbon footprint of milk by increasing animal productivity and feed conversion efficiency. None of these studies simultaneously evaluated indirect GHG effects incurred via teleconnections with expansion of feed crop production and replacement suckler‐beef production. We applied consequential LCA to incorporate these effects into GHG mitigation calculations for intensification scenarios among grazing‐based dairy farms in an industrialized country (UK), in which milk production shifts from average to intensive farm typologies, involving higher milk yields per cow and more maize and concentrate feed in cattle diets. Attributional LCA indicated a reduction of up to 0.10 kg CO₂e kg^?1 milk following intensification, reflecting improved feed conversion efficiency. However, consequential LCA indicated that land use change associated with increased demand for maize and concentrate feed, plus additional suckler‐beef production to replace reduced dairy‐beef output, significantly increased GHG emissions following intensification. International displacement of replacement suckler‐beef production to the “global beef frontier” in Brazil resulted in small GHG savings for the UK GHG inventory, but contributed to a net increase in international GHG emissions equivalent to 0.63 kg CO₂e kg^?1 milk. Use of spared dairy grassland for intensive beef production can lead to net GHG mitigation by replacing extensive beef production, enabling afforestation on larger areas of lower quality grassland, or by avoiding expansion of international (Brazilian) beef production. We recommend that LCA boundaries are expanded when evaluating livestock intensification pathways, to avoid potentially misleading conclusions being drawn from “snapshot” carbon footprints. We conclude that dairy intensification in industrialized countries can lead to significant international carbon leakage, and only achieves GHG mitigation when spared dairy grassland is used to intensify beef production, freeing up larger areas for afforestation.     

Including albedo in time‐dependent LCA of bioenergy

Albedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time‐dependent LCA, which accounts for the timing of emissions and their impacts. We employed field‐measured albedo and life cycle emissions data along with time‐dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time (?T) and as GWP. The bioenergy system analysed was heat and power production from short‐rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of ?T per hectare (?3.8 × 10^–11 K in year 100) and GWP₁₀₀ per MJ fuel (?12.2 g CO₂e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP₁₀₀, 36% of ?T in year 50 and 6% of ?T in year 100. Albedo dominated the short‐term temperature response (10–20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with ?T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first‐order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses.     

玉米秸秆基纤维素乙醇生命周期能耗与温室气体排放分析

生命周期评价是目前分析产品或工艺的环境负荷唯一标准化工具,利用其生命周期分析方法可以有效地研究纤维素乙醇生命周期能耗与温室气体排放问题。为了定量解释以玉米秸秆为原料的纤维素乙醇的节能和温室气体减排潜力,利用生命周期分析方法对以稀酸预处理、酶水解法生产的玉米秸秆基乙醇进行了生命周期能耗与温室气体排放分析,以汽车行驶1 km为功能单位。结果表明：与汽油相比,纤维素乙醇E100 (100％乙醇) 和E10 (乙醇和汽油体积比=1∶9) 生命周期化石能耗分别减少79.63％和6.25％,温室气体排放分别减少53.98％和6.69％;生物质阶段化石能耗占到总化石能耗68.3％,其中氮肥和柴油的生命周期能耗贡献最大,分别占到生物质阶段的45.78％和33.26％;工厂电力生产过程的生命周期温室气体排放最多,占净温室气体排放量的42.06％,提升技术减少排放是降低净排放的有效措施。     

Nitrogen rate and landscape impacts on life cycle energy use and emissions from switchgrass‐derived ethanol

Switchgrass‐derived ethanol has been proposed as an alternative to fossil fuels to improve sustainability of the US energy sector. In this study, life cycle analysis (LCA) was used to estimate the environmental benefits of this fuel. To better define the LCA environmental impacts associated with fertilization rates and farm‐landscape topography, results from a controlled experiment were analyzed. Data from switchgrass plots planted in 2008, consistently managed with three nitrogen rates (0, 56, and 112 kg N ha^?1), two landscape positions (shoulder and footslope), and harvested annually (starting in 2009, the year after planting) through 2014 were used as input into the Greenhouse gases, Regulated Emissions and Energy use in transportation (GREET) model. Simulations determined nitrogen (N) rate and landscape impacts on the life cycle energy and emissions from switchgrass ethanol used in a passenger car as ethanol–gasoline blends (10% ethanol:E10, 85% ethanol:E85s). Results indicated that E85s may lead to lower fossil fuels use (58 to 77%), greenhouse gas (GHG) emissions (33 to 82%), and particulate matter (PM2.5) emissions (15 to 54%) in comparison with gasoline. However, volatile organic compounds (VOCs) and other criteria pollutants such as nitrogen oxides (NOx), particulate matter (PM10), and sulfur dioxides (SO_x) were higher for E85s than those from gasoline. Nitrogen rate above 56 kg N ha^?1 yielded no increased biomass production benefits; but did increase (up to twofold) GHG, VOCs, and criteria pollutants. Lower blend (E10) results were closely similar to those from gasoline. The landscape topography also influenced life cycle impacts. Biomass grown at the footslope of fertilized plots led to higher switchgrass biomass yield, lower GHG, VOCs, and criteria pollutants in comparison with those at the shoulder position. Results also showed that replacing switchgrass before maximum stand life (10–20 years.) can further reduce the energy and emissions reduction benefits.     

Optimal design of flax fiber reinforced polymer composite as a lightweight component for automobiles from a life cycle assessment perspective

The present study combines the generalized rule‐of‐mixture (ROM) model and the Ashby material selection method for the life cycle assessment (LCA) of flax fiber reinforced polymers (FRPs) and glass FRPs (GFRPs). The ROM model allows life cycle environmental impact predictions according to specific parameters of flax FRPs such as fiber format, volume fraction, manufacturing technique, and load‐bearing capacity. The comparisons applied in this study are constructed on two common composite structures: mat panels and injection molded struts with equal stiffness and strength as the design criteria. On the one hand, the parametric LCA predicts that the equal strength design criterion for flax FRPs contributes to consistent mass increases, subsequently resulting in higher life cycle environmental impacts compared to the reference GFRPs; on the other hand, under the equal stiffness criterion the flax mat polypropylene (flax mat‐PP) film helps with mass reduction in reference to the glass mat‐PP composite, leading to the 20–50% life cycle environmental impact reductions for most impact categories. The subsequent evaluation of the influences of the fiber volume fraction on flax FRPs shows different patterns. For the short flax fiber‐PP composite, a steady decrease of the life cycle CO₂ emissions can be observed with the increasing fiber volume fraction. However, for the flax mat‐PP composite, depending on the tensile modulus of the flax fiber, the optimal volume fractions of the fiber change from 28 to 32% v/v, whereby the lowest life cycle greenhouse gas (GHG) emissions can be achieved.     

Impacts of biogenic CO2 emissions on human health and terrestrial ecosystems: the case of increased wood extraction for bioenergy production on a global scale

Biofuels are a potentially important source of energy for our society. Common practice in life cycle assessment (LCA) of bioenergy has been to assume that any carbon dioxide (CO₂) emission related to biomass combustion equals the amount absorbed in biomass, thus assuming no climate change impacts. Recent developments show the significance of contributions of biogenic CO₂ emissions during the time they stay in the atmosphere. The goal of this article is to develop a global, spatially explicit method to quantify the potential impact on human health and terrestrial ecosystems of biogenic carbon emissions coming from forest wood extraction for biofuel production. For this purpose, changes in aboveground carbon stock (ΔC_forest) due to an increase in wood extraction via changes in rotation time are simulated worldwide with a 0.5° × 0.5° grid resolution. Our results show that both impacts and benefits can be obtained. When the extraction increase is reached by creating a longer rotation time, new growth is allowed resulting in carbon benefits. In a case study, we assessed the life cycle impacts of heat production via wood to determine the significance of including biogenic CO₂ emissions due to changes in forest management. Impacts of biogenic CO₂ dominate the total climate change impacts from a wood stove. Depending on the wood source country, climate change impacts due to heat production from wood either have an important share in the overall impacts on human health and terrestrial ecosystems, or allow for a large additional CO₂ sink.