Purpose
Due to the large environmental challenges posed by the transport sector, reliable and state-of-the art data for its life cycle assessment is essential for enabling a successful transition towards more sustainable systems. In this paper, the new electric passenger car transport and vehicle datasets, which have been developed for ecoinvent version 3, are presented.Methods
The new datasets have been developed with a strong modular approach, defining a hierarchy of datasets corresponding to various technical components in the vehicle. A vehicle is therefore modelled by linking together the various component datasets. Also, parameters and mathematical formulas have been introduced in order to define the amount of exchanges in the datasets through common transport and vehicle characteristics. This supports users in the choice of the amount of exchanges and enhances the transparency of the dataset.Results
The new transport dataset describes the transport over 1 km with a battery electric passenger car taking into account the vehicle production and end of life, the energy consumption due to the use phase, non-exhaust emissions, maintenance and road infrastructure. The dataset has been developed and is suitable for a compact class vehicle.Conclusions
A new electric passenger car transport dataset has been developed for version 3 of the ecoinvent database which exploits modularisation and parameters with the aim of facilitating users in adapting the data to their specific needs. Apart from the direct use of the transport dataset for background data, the various datasets for the different components can also be used as building blocks for virtual vehicles.Despite the wide use of LCA for environmental profiling, the approach for determining the system boundary within LCA models continues to be subjective and lacking in mathematical rigor. As a result, life cycle models are often developed in an ad hoc manner, and are difficult to compare. Significant environmental impacts may be inadvertently left out. Overcoming this shortcoming can help elicit greater confidence in life cycle models and their use for decision making.
MethodsThis paper describes a framework for hybrid life cycle model generation by selecting activities based on their importance, parametric uncertainty, and contribution to network complexity. The importance of activities is determined by structural path analysis—which then guides the construction of life cycle models based on uncertainty and complexity indicators. Information about uncertainty is from the available life cycle inventory; complexity is quantified by cost or granularity. The life cycle model is developed in a hierarchical manner by adding the most important activities until error requirements are satisfied or network complexity exceeds user-specified constraints.
Results and DiscussionThe framework is applied to an illustrative example for building a hybrid LCA model. Since this is a constructed example, the results can be compared with the actual impact, to validate the approach. This application demonstrates how the algorithm sequentially develops a life cycle model of acceptable uncertainty and network complexity. Challenges in applying this framework to practical problems are discussed.
ConclusionThe presented algorithm designs system boundaries between scales of hybrid LCA models, includes or omits activities from the system based on path analysis of environmental impact contribution at upstream network nodes, and provides model quality indicators that permit comparison between different LCA models.
相似文献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. 相似文献Purpose
The main aim of the study is to assess the environmental and economic impacts of the lodging sector located in the Himalayan region of Nepal, from a life cycle perspective. The assessment should support decision making in technology and material selection for minimal environmental and economic burden in future construction projects.Methods
The study consists of the life cycle assessment and life cycle costing of lodging in three building types: traditional, semi-modern and modern. The life cycle stages under analysis include raw material acquisition, manufacturing, construction, use, maintenance and material replacement. The study includes a sensitivity analysis focusing on the lifespan of buildings, occupancy rate and discount and inflation rates. The functional unit was formulated as the ‘Lodging of one additional guest per night’, and the time horizon is 50 years of building lifespan. Both primary and secondary data were used in the life cycle inventory.Results and discussion
The modern building has the highest global warming potential (kg CO2-eq) as well as higher costs over 50 years of building lifespan. The results show that the use stage is responsible for the largest share of environmental impacts and costs, which are related to energy use for different household activities. The use of commercial materials in the modern building, which have to be transported mostly from the capital in the buildings, makes the higher GWP in the construction and replacement stages. Furthermore, a breakdown of the building components shows that the roof and wall of the building are the largest contributors to the production-related environmental impact.Conclusions
The findings suggest that the main improvement opportunities in the lodging sector lie in the reduction of impacts on the use stage and in the choice of materials for wall and roof.Background, aim, and scope
Many studies evaluate the results of applying different life cycle impact assessment (LCIA) methods to the same life cycle inventory (LCI) data and demonstrate that the assessment results would be different with different LICA methods used. Although the importance of uncertainty is recognized, most studies focus on individual stages of LCA, such as LCI and normalization and weighting stages of LCIA. However, an important question has not been answered in previous studies: Which part of the LCA processes will lead to the primary uncertainty? The understanding of the uncertainty contributions of each of the LCA components will facilitate the improvement of the credibility of LCA.Methodology
A methodology is proposed to systematically analyze the uncertainties involved in the entire procedure of LCA. The Monte Carlo simulation is used to analyze the uncertainties associated with LCI, LCIA, and the normalization and weighting processes. Five LCIA methods are considered in this study, i.e., Eco-indicator 99, EDIP, EPS, IMPACT 2002+, and LIME. The uncertainty of the environmental performance for individual impact categories (e.g., global warming, ecotoxicity, acidification, eutrophication, photochemical smog, human health) is also calculated and compared. The LCA of municipal solid waste management strategies in Taiwan is used as a case study to illustrate the proposed methodology.Results
The primary uncertainty source in the case study is the LCI stage under a given LCIA method. In comparison with various LCIA methods, EDIP has the highest uncertainty and Eco-indicator 99 the lowest uncertainty. Setting aside the uncertainty caused by LCI, the weighting step has higher uncertainty than the normalization step when Eco-indicator 99 is used. Comparing the uncertainty of various impact categories, the lowest is global warming, followed by eutrophication. Ecotoxicity, human health, and photochemical smog have higher uncertainty.Discussion
In this case study of municipal waste management, it is confirmed that different LCIA methods would generate different assessment results. In other words, selection of LCIA methods is an important source of uncertainty. In this study, the impacts of human health, ecotoxicity, and photochemical smog can vary a lot when the uncertainties of LCI and LCIA procedures are considered. For the purpose of reducing the errors of impact estimation because of geographic differences, it is important to determine whether and which modifications of assessment of impact categories based on local conditions are necessary.Conclusions
This study develops a methodology of systematically evaluating the uncertainties involved in the entire LCA procedure to identify the contributions of different assessment stages to the overall uncertainty. Which modifications of the assessment of impact categories are needed can be determined based on the comparison of uncertainty of impact categories.Recommendations and perspectives
Such an assessment of the system uncertainty of LCA will facilitate the improvement of LCA. If the main source of uncertainty is the LCI stage, the researchers should focus on the data quality of the LCI data. If the primary source of uncertainty is the LCIA stage, direct application of LCIA to non-LCIA software developing nations should be avoided. 相似文献This study aims at finding the environmental impacts generated by an electric disk insulator supply chain, used for the distribution of electricity by an open wire system, through a case study. This study also aims at benchmarking the environmental impacts of an electric insulator manufacturing process by taking ideal condition of zero waste as reference.
MethodsCradle-to-grave life cycle assessment (LCA) has been carried out by following the guidelines provided in ISO 14040 series standards and using Umberto NXT software. ReCiPe endpoint and ReCiPe midpoint impact assessment methodologies have been used to calculate environmental impacts under various categories. The primary data has been collected from a medium-scale manufacturer of electric disk insulators located at Bikaner in north-west India. The secondary data has been taken from ecoinvent 3.0 database and literature. The environmental impacts using endpoint assessment (ecosystem quality, human health, and resources) and midpoint assessment (climate change, fossil depletion, human toxicity, metal depletion, ozone depletion, terrestrial acidification, and water depletion) categories have been computed. Finally, the results are compared and benchmarked against the ideal zero waste condition using three different production scenarios. The limitation of this study is that the data has been collected only from one manufacturer and its supply chain.
Results and discussionIt has been found that the use of steel, electricity, and fuel; transportation of product; and disposal of water generate high environmental impacts in the supply chain. It has also been found that in the electric disk insulator supply chain, the raw material extraction phase has the highest environmental impacts followed by manufacturing, disposal, transportation, and installation phases. This study has also found that benchmark scenario “B” (zero waste condition) is environmentally more efficient in comparison to scenario “A” (actual recycling condition) and scenario “C” (maximum waste condition).
ConclusionsThis study has identified that raw materials, resources, and processes in the supply chain of an electric disk insulator manufacturing unit are responsible for the environmental damage. The various manufacturing processes and installation of the electric disk insulators are similar for all manufacturers except the machinery efficiency and the generated waste. This study provides environmental impacts associated with an electric disk insulator manufacturing process under zero waste or ideal conditions (scenario B). These results are used as a benchmark to compare environmental performance of electric disk insulator supply chain operating under actual conditions.
相似文献Purpose
Earlier studies on agricultural life cycle assessment recommend that practitioners use two functional units—product weight and land area—because agriculture entails commodity production and land use. However, there are still ambiguities in this approach from the perspective of decision support. The purpose of this paper is to provide recommendations to support farming conversion decisions on the basis of a framework constructed on two alternative views of agricultural production. Organic conversion of arable farming is selected as a case study.Methods
Four types of conversion were constructed on the basis of land-oriented expression, in which inputs into and outputs from land were depicted, and product-oriented expression, in which inputs into and outputs from products were depicted. Then, the frequencies for each type were counted using LCI databases and data from journal papers.Results
The results can be summarized as follows: (1) trade-off conversion, in which improvements in environmental impacts per area unit are involved in decrease of yield per area unit, is common. (2) Conversion tended to be efficient; that is, environmental impacts per product unit tended to improve. (3) Within trade-off conversion, the conversion tended to be efficient. (4) When conversion was efficient, there were trade-offs.Conclusions
Since the results for one expression were not always derivable from the results for another expression, the recommendation of this study is to use the two expressions complementarily, knowing that win–win conversion is rare. In addition, there is a general recommendation to use decision criteria rather than trying to make decisions on the basis of multiple functional units because comparisons based on the two functional units are not on the same level. 相似文献Purpose
The interest in life cycle assessment (LCA) studies has increased over the years, and one of the main ways of disseminating these studies is through the publication of articles in scientific journals. Coauthorship relations form a social network where it is possible to identify how research is organized and structured in a specific field of knowledge. This paper aims to show the spread of these studies and the configuration of a collaboration network based on coauthorship relations between researchers of LCA considering some properties of social networks. 相似文献Purpose
Current ecodesign instruments usually focus on improving single life cycle stages, like the energy efficiency classes for motors put on the European market, which focus on the use stage. Resulting trade-offs between the life cycle stages are however often not integrated properly, like for instance trade-offs between manufacturing stage and use stage. The goal of this study was to evaluate the trade-offs between the additional efforts of producing energy-efficient motors (achieved, e.g., via different materials for certain components) and the advantages gained from the improved efficiency in operation.Methods
For this case study, a life cycle assessment methodology according to ISO 14040/44 was applied for the whole life cycle (cradle to grave) of three electric motors, each from a different efficiency class, and one serving as baseline. The motors under study have the following specifications in common: asynchronous technology, 110 kW nominal power, cast iron series, and 4-poles. To evaluate the use stage, two different operational profiles were studied for 20 years’ service life.Results and discussion
The results clearly indicated the dominance of the use stage in the motors’ life cycles and that an increase in efficiency pays off environmentally within the first month of operation in the applied load-time profiles. The dominating environmental impact categories, like ionizing radiation and global warming potential, relate to the consumption of electricity. The study results indicated also that the increase of the analyzed motors’ efficiency encompasses trade-offs between the stages materials, manufacturing, and end-of-life versus the use stage in regard to toxicity and (metal) resource depletion aspects, i.e., a burden shifting between energy-related impacts and the toxicity- and resource depletion-related impacts.Conclusions
In the analyzed study set-ups, including the modeled energy generation scenarios for Europe in 2050, an environmental break-even is achieved in less than a month in all impact categories except for human toxicity. Thus, the further improvement of energy efficiency of drive systems is and will stay a central ecodesign lever. However, toxicity and resource depletion trade-offs should be considered carefully within decision support and decision-making, and further research on related characterization models is necessary. Further, it is concluded that the load-time profile as well as the motors’ service life have a high influence, and therefore, designing drive systems in context with the application seems to be an important approach to facilitate ecodesign.The building sector is one of the most relevant sectors in terms of environmental impact. Different functional units (FUs) can be used in life cycle assessment (LCA) studies for a variety of purposes. This paper aimed to present different FUs used in the LCA of buildings and evaluate the influence of FU choice and setting in comparative studies.
MethodsAs an example, we compared the “cradle to grave” environmental performance of four typical Brazilian residential buildings with different construction typologies, i.e., multi-dwelling and single dwelling, each with high and basic standards. We chose three types of FU for comparison: a dwelling with defined lifetime and occupancy parameters, an area of 1 m2 of dwelling over a year period, and the accommodation of an occupant person of the dwelling over a day.
Results and discussionThe FU choice was found to bias the results considerably. As expected, the largest global warming indicator (GWi) values per dwelling unit and occupant were identified for the high standard dwellings. However, when measured per square meter, lower standard dwellings presented the largest GWi values. This was caused by the greater concentration of people per square meter in smaller area dwellings, resulting in larger water and energy consumption per square meter. The sensitivity analysis of FU variables such as lifetime and occupancy showed the GWi contribution of the infrastructure more relevant compared with the operation in high and basic standard dwellings. The definition of lifetime and occupancy parameters is key to avoid bias and to reduce uncertainty of the results when performing a comparison of dwelling environmental performances.
ConclusionsThis paper highlights the need for adequate choice and setting of FU to support intended decision-making in LCA studies of the building sector. The use of at least two FUs presented a broader picture of building performance, helping to guide effective environmental optimization efforts from different approaches and levels of analysis. Information regarding space, time, and service dimensions should be either included in the FU setting or provided in the building LCA study to allow adjustment of the results for subsequent comparison.
相似文献