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Purpose
Rarely considered in environmental assessment methods, potential land use impacts on a series of ecosystem services must be accounted for in widely used decision-making tools such as life cycle assessment (LCA). The main goal of this study is to provide an operational life cycle impact assessment characterization method that addresses land use impacts at a global scale by developing spatially differentiated characterization factors (CFs) and assessing the extent of their spatial variability using different regionalization levels.Methods
The proposed method follows the recommendations of previous work and falls within the framework and principles for land use impact assessment established by the United Nations Environment Programme/Society of Environmental Toxicology and Chemistry Life Cycle Initiative. Based on the spatial approach suggested by Saad et al. (Int J Life Cycle Assess 16: 198–211, 2011), the intended impact pathways that are modeled pertain to impacts on ecosystem services damage potential and focus on three major ecosystem services: (1) erosion regulation potential, (2) freshwater regulation potential, and (3) water purification potential. Spatially-differentiated CFs were calculated for each biogeographic region of all three regionalization scale (Holdridge life regions, Holdridge life zones, and terrestrial biomes) along with a nonspatial world average level. In addition, seven land use types were assessed considering both land occupation and land transformation interventions.Results and discussion
A comprehensive analysis of the results indicates that, when compared to all resolution schemes, the world generic averaged CF can deviate for various ecosystem types. In the case of groundwater recharge potential impacts, this range varied up to factors of 7, 4.7, and 3 when using the Holdridge life zones, the Holdridge regions, and the terrestrial biomes regionalization levels, respectively. This validates the importance of introducing a regionalized assessment and highlights how a finer scale increases the level of detail and consequently the discriminating power across several biogeographic regions, which could not have been captured using a coarser scale. In practice, the implementation of such regionalized CFs suggests that an LCA practitioner must identify the ecosystem in which land occupation or transformation activities occur in addition to the traditional inventory data required—namely, the land use activity and the inventory flow.Conclusions
The variability of CFs across all three regionalization levels provides an indication of the uncertainty linked to nonspatial CFs. Among other assumptions and value choices made throughout the study, the use of ecological borders over political boundaries was deemed more relevant to the interpretation of environmental issues related to specific functional ecosystem behaviors. 相似文献Objective uncertainty quantification (UQ) of a product life-cycle assessment (LCA) is a critical step for decision-making. Environmental impacts can be measured directly or by using models. Underlying mathematical functions describe a model that approximate the environmental impacts during various LCA stages. In this study, three possible uncertainty sources of a mathematical model, i.e., input variability, model parameter (differentiate from input in this study), and model-form uncertainties, were investigated. A simple and easy to implement method is proposed to quantify each source.
MethodsVarious data analytics methods were used to conduct a thorough model uncertainty analysis; (1) Interval analysis was used for input uncertainty quantification. A direct sampling using Monte Carlo (MC) simulation was used for interval analysis, and results were compared to that of indirect nonlinear optimization as an alternative approach. A machine learning surrogate model was developed to perform direct MC sampling as well as indirect nonlinear optimization. (2) A Bayesian inference was adopted to quantify parameter uncertainty. (3) A recently introduced model correction method based on orthogonal polynomial basis functions was used to evaluate the model-form uncertainty. The methods are applied to a pavement LCA to propagate uncertainties throughout an energy and global warming potential (GWP) estimation model; a case of a pavement section in Chicago metropolitan area was used.
Results and discussionResults indicate that each uncertainty source contributes to the overall energy and GWP output of the LCA. Input uncertainty was shown to have significant impact on overall GWP output; for the example case study, GWP interval was around 50%. Parameter uncertainty results showed that an assumption of ±?10% uniform variation in the model parameter priors resulted in 28% variation in the GWP output. Model-form uncertainty had the lowest impact (less than 10% variation in the GWP). This is because the original energy model is relatively accurate in estimating the energy. However, sensitivity of the model-form uncertainty showed that even up to 180% variation in the results can be achieved due to lower original model accuracies.
ConclusionsInvestigating each uncertainty source of the model indicated the importance of the accurate characterization, propagation, and quantification of uncertainty. The outcome of this study proposed independent and relatively easy to implement methods that provide robust grounds for objective model uncertainty analysis for LCA applications. Assumptions on inputs, parameter distributions, and model form need to be justified. Input uncertainty plays a key role in overall pavement LCA output. The proposed model correction method as well as interval analysis were relatively easy to implement. Research is still needed to develop a more generic and simplified MCMC simulation procedure that is fast to implement.
相似文献Purpose
Despite the fundamental role of ecosystem goods and services in sustaining human activities, there is no harmonized and internationally agreed method for including them in life cycle assessment (LCA). The main goal of this study was to develop a globally applicable and spatially resolved method for assessing land use impacts on the erosion regulation ecosystem service.Methods
Soil erosion depends much on location. Thus, unlike conventional LCA, the endpoint method was regionalized at the grid cell level (5 arcmin, approximately 10?×?10 km2) to reflect the spatial conditions of the site. Spatially explicit characterization factors were not further aggregated at broader spatial scales.Results and discussion
Life cycle inventory data of topsoil and topsoil organic carbon (SOC) losses were interpreted at the endpoint level in terms of the ultimate damage to soil resources and ecosystem quality. Human health damages were excluded from the assessment. The method was tested on a case study of five 3-year agricultural rotations, two of them with energy crops, grown in several locations in Spain. A large variation in soil and SOC losses was recorded in the inventory step, depending on climatic and edaphic conditions. The importance of using a spatially explicit model and characterization factors is shown in the case study.Conclusions
The regionalized assessment takes into account the differences in soil erosion-related environmental impacts caused by the great variability of soils. Taking this regionalized framework as the starting point, further research should focus on testing the applicability of the method through the complete life cycle of a product and on determining an appropriate spatial scale at which to aggregate characterization factors in order to deal with data gaps on the location of processes, especially in the background system. Additional research should also focus on improving the reliability of the method by quantifying and, insofar as it is possible, reducing uncertainty. 相似文献Life Cycle Assessment (LCA) is the process of systematically assessing impacts when there is an interaction between the environment and human activity. Machine learning (ML) with LCA methods can help contribute greatly to reducing impacts. The sheer number of input parameters and their uncertainties that contribute to the full life cycle make a broader application of ML complex and difficult to achieve. Hence a systems engineering approach should be taken to apply ML in isolation to aspects of the LCA. This study addresses the challenge of leveraging ML methods to deliver LCA solutions. The overarching hypothesis is that: LCA underpinned by ML methods and informed by dynamic data paves the way to more accurate LCA while supporting life cycle decision making.
MethodsIn this study, previous research on ML for LCA were considered, and a literature review was undertaken.
ResultsThe results showed that ML can be a useful tool in certain aspects of the LCA. ML methods were shown to be applied efficiently in optimization scenarios in LCA. Finally, ML methods were integrated as part of existing inventory databases to streamline the LCA across many use cases.
ConclusionsThe conclusions of this article summarise the characteristics of existing literature and provide suggestions for future work in limitations and gaps which were found in the literature.
相似文献Uncertainty analyses in life cycle assessment (LCA) literature have focused primarily on the life cycle inventory (LCI) phase, but LCA experts generally agree that the life cycle impact assessment (LCIA) phase is likely to contribute even more to the overall uncertainty of an LCA result. The magnitude of perceived uncertainties in characterization relative to that in LCI, however, has not been examined in the literature. Here, we use the pedigree approach to gauge the perceived uncertainty in the characterization phase relative to the LCI phase. In addition, we evaluate the level of approval on the pedigree approach as a means to characterize uncertainty in LCA.
MethodsApplying the Numeral Unit Spread Assessment Pedigree (NUSAP) approach to environmental risk assessment literature, we extracted the criteria for evaluating the uncertainty in the characterization phase. We used expert elicitation to identify a pool of experts and conducted a survey, to which 47 LCA practitioners from 12 countries responded. In order to reduce personal biases in perceived geometric standard deviation (GSD) values, we used two reference questions on weight and life expectancy at birth for calibration.
ResultsNearly half (49%) of respondents expressed their approval to the pedigree matrix approach as a means of characterizing uncertainties in LCA, and responses were highly sensitive to the respondent’s familiarity with the pedigree matrix. For instance, respondents who are highly familiar with the pedigree matrix were more polarized, with 15% and 19% of them expressing either strong approval or strong disapproval, respectively. Respondents less familiar with the pedigree approach were generally more favorable to its use. Compared with LCI, variability in characterization factors was influenced more strongly by geographical correlation and reliability of the underlying model, which showed 11 to 16% larger average GSDs when compared with the comparable criteria for LCI. Conversely, temporal correlation criterion was a less significant factor in characterization than in LCI.
Conclusions and discussionOverall, survey respondents viewed LCIA characterization as only marginally more uncertain than LCI, but with a wider variability in responses on characterization than LCI. This finding indicates the need for additional research to develop more thorough methods for characterizing uncertainties in life cycle impact assessment that are compatible with the uncertainty measures in LCI.
相似文献Life cycle assessment (LCA) is a data-intensive methodology; therefore, experts usually focus collection efforts on a few activities, while generic data on remaining activities are taken from databases. Even though increased availability of databases has facilitated LCA takeoff, assuring data quality is fundamental to ensure meaningful results and reliable interpretation.
MethodsEcoinvent has become a global reference for inventory data. Its current version released three impact partition modeling options—the recycled content, “allocation at the point of substitution” (APOS), and consequential models—whose adequate choice is crucial for yielding meaningful assessments. Tutorials and manuals describe the distribution algorithm that backs each system model, to ground decision-making regarding the best fit to a study’s goals. We performed a systematic literature review to investigate—within the papers published on the International Journal of LCA (IJLCA)—how transparently authors addressed the system model choices.
Results and discussionAbout 70% of LCA practitioners continued to use earlier versions of ecoinvent after version 3 was launched in 2013. The number of papers using versions 3.x only showed an increased growth trend 2 years later. Eighty-three papers actually adopted the newest version of the database. From those, only 29 papers clearly mentioned the adopted system model. Our SLR also suggests a trend regarding authorship profile of LCA-related studies: the number of studies conducted by practitioners aware of the intricacies of sound modeling of background and foreground data might have been surpassed by those conducted by non-LCA specialists who use LCA as a supporting tool for investigations in applied fields, and merely scratch the surface.
ConclusionsOur results point to a need for a caveat: ecoinvent users must take time to understand the general concept behind each system model and practice one of the most important actions when performing an LCA—state methodological choices clearly.
相似文献Industrial symbiosis network (ISN) facilitation tools seek to holistically evaluate the environmental and economic performance of ISNs through life cycle assessment (LCA) and life cycle costing (LCC). ISNs have many stakeholders with diverse interests in the LCA and LCC results thus requiring multi-level analysis. The objective of this review was to examine the state-of-the-art methodologies used in LCAs and LCCs of ISNs and understand how multi-level analysis can be conducted.
MethodsThe systematic literature review methodology was applied to develop a corpus of peer-reviewed LCA and LCC studies of ISNs published between 2010 and 2019 without any geographic boundary. Abstracts were reviewed to shortlist studies that conducted an LCA or LCC of an ISN with numerical results. LCA and LCC methodologies used in the shortlisted studies were collected and categorized. Each methodology was examined to understand how the foreground and background systems are represented, how waste-to-resource exchanges are analyzed, and how the results can be computed at the network, entity, and flow levels.
Results and discussionThe review yielded 42 LCA studies and 11 LCC studies of ISNs that used eight different methodologies. Process-based LCA was used in 71% of the LCA studies, whereas tiered hybrid LCA was used in 14% of the studies. Waste-to-resource exchanges in ISN scenarios were represented either through process analysis or as a black box. Fewer LCC studies that evaluate the economic performance of ISNs exist compared with LCA studies. Economic studies often evaluated financial feasibility, net present value, profitability, or payback period of specific waste-to-resource exchanges or the network overall.
ConclusionsThe insights derived from this review chart future areas of research in multi-level modeling and analysis of the life cycle environmental and economic performance of ISNs. To improve the model construction and analysis process, research should be explored in developing a methodology for constructing a single model that represents multiple entities linked together by waste-to-resource exchanges and can provide LCA and LCC results for different stakeholder perspectives. The lack of LCC studies of ISNs merits the need for more research in this area at both the network and entity levels to quantify potential economic trade-offs between stakeholders. Developing a methodology for unified LCA and LCC modeling and analysis of ISNs can help ISN facilitation tool developers conduct simultaneous life cycle environmental and economic analysis of the potential symbiosis connections identified and how they contribute to the overall network.
相似文献Trade is increasingly considered a significant contributor to environmental impacts. The assessment of the impacts of trade is usually performed via environmentally extended input–output analysis (EEIOA). However, process-based life cycle assessment (LCA) applied to traded goods allows increasing the granularity of the analysis and may be essential to unveil specific impacts due to traded products.
MethodsThis study assesses the environmental impacts of the European trade, considering two modelling approaches: respectively EEIOA, using EXIOBASE 3 as supporting database, and process-based LCA. The interpretation of the results is pivotal to improve the robustness of the assessment and the identification of hotspots. The hotspot identification focuses on temporal trends and on the contribution of products and substances to the overall impacts. The inventories of elementary flows associated with EU trade, for the period 2000–2010, have been characterized considering 14 impact categories according to the Environmental Footprint (EF2017) Life Cycle Impact Assessment method.
Results and discussionThe two modelling approaches converge in highlighting that in the period 2000–2010: (i) EU was a net importer of environmental impacts; (ii) impacts of EU trade and EU trade balance (impacts of imports minus impacts of exports) were increasing over time, regarding most impact categories under study; and (iii) similar manufactured products were the main contributors to the impacts of exports from EU, regarding most impact categories. However, some results are discrepant: (i) larger impacts are obtained from IO analysis than from process-based LCA, regarding most impact categories, (ii) a different set of most contributing products is identified by the two approaches in the case of imports, and (iii) large differences in the contributions of substances are observed regarding resource use, toxicity, and ecotoxicity indicators.
ConclusionsThe interpretation step is crucial to unveil the main hotspots, encompassing a comparison of the differences between the two methodologies, the assumptions, the data coverage and sources, the completeness of inventory as basis for impact assessment. The main driver for the observed divergences is identified to be the differences in the impact intensities of goods, both induced by inherent properties of the IO and life cycle inventory databases and by some of this study’s modelling choices. The combination of IO analysis and process-based LCA in a hybrid framework, as performed in other studies but generally not at the macro-scale of the full trade of a country or region, appears a potential important perspective to refine such an assessment in the future.
相似文献Within the field of life cycle assessment (LCA), simplifications are a response to the practical restrictions in the context of a study. In the 1990s, simplifications were part of a debate on streamlining within LCA. Since then, many studies have been published on simplifying LCA but with little attention to systematise the approaches available. Also, despite being pervasive during the making of LCA studies, simplifications remain often invisible in the final results. This paper therefore reviews the literature on simplification in LCA in order to systematise the approaches found today.
MethodsA review of the LCA simplification literature was conducted. The systematic search and selection process led to a sample of 166 publications. During the review phase, the conceptual contributions to the simplification discourse were evaluated. A dataset of 163 entries was created, listing the conceptual contributions to the simplification debate. An empirically grounded analysis led to the generative development of a systematisation of simplifications according to their underlying simplifying logic.
Results and discussionFive simplifying logics were identified: exclusion, inventory data substitution, qualitative expert judgment, standardisation and automation. Together, these simplifying logics inform 13 simplification strategies. The identified logics represent approaches to handle the complexities of product systems and expectations of the users of LCA results with the resources available to the analyst. Each simplification strategy is discussed with regard to its main applications and challenges.
ConclusionsThis paper provides a first systematisation of the different simplification logics frequently applied in LCA since the original streamlining discussion. The presented terminology can help making communication about simplification more explicit and transparent, thus important for the credibility of LCA. Despite the pervasiveness of simplification in LCA, there is a relative lack of research on simplification per se, making further research describing simplification as a practice and analysing simplifications methodologically desirable.
相似文献Purpose
The protocols of carbon footprints generally define three scopes for different greenhouse gas (GHG) emissions levels. The most important carbon footprint emissions source comes from upstream indirect emissions of scope 3 for products that do not consume energy during their use phase. Upstream scope 3 GHG inventory can usually be analyzed through input–output or hybrid LCA analysis. The economic input–output life cycle analysis (EIO-LCA) and the hybrid LCA model have been widely used for this purpose. However, a cutoff error exists in the hybrid model, and the lack of a truncation criterion between process and IO inventory may lead to a high level of uncertainty in the hybrid model. This study attempts to improve the problem of cutoff uncertainty in hybrid LCA and proposes a method to minimize the cutoff uncertainty.Methods
The way to improve the cutoff uncertainty could follow two steps. First, through the IO inventory analysis of EIO-LCA, we can define the emissions by various tiers of product components. The IO inventory indicator can provide a definitive criterion for the process inventory of the hybrid model. Second, we connect the process- and IO-LCI according to the IO inventory result. The advantage of the process inventory is that it provides detailed manufacturing information on the target while the IO encompasses a complete system boundary. For improvements, the process inventory can catch the most important process of the GHG emissions, and the IO inventory could compensate for the remainder of the incomplete system inventory.Results and discussion
In this case study, the printed circuit board production process is used to evaluate the efficiency of the improved method. The threshold M was set to 70 in this case study, and the IO inventory provides the remaining 30 %. For the integrated hybrid model, the tier 3 process inventory takes only 64 % while the incorporation of the proposed method can include 92 % of the total emissions, which shows the cutoff uncertainty can be reduced through the improvement.Conclusions
This study provides a clear guideline for process and IO cutoff criteria, which can help the truncation uncertainty. When higher precision is required, process LCI will need to play an important role, and thus, a higher M value should be set. In this situation, the emissions from IO-LCI would be smaller than the emissions from the process LCI. The appropriate solution would attain a comfortable balance between data accuracy and time and labor consumption. 相似文献The novelty of the O-LCA method and the existing differences with the established product LCA practice, as well as the unique structure each organization, pose a broad range of methodological and application challenges, in addition to the general methodological gaps in LCA. In order to provide practitioners with lessons learned for future applications and boost future method development efforts, the paper discusses those challenges.
MethodsThe challenges included in this paper were mainly identified from a survey administered to the road testers and from experiences during the piloting process. These are complemented with case studies from literature. The focus of the paper is on challenges exclusive to the organizational approach, although some additional issues common to product LCA but intensified in organizational LCA are also included. Each issue is characterized and exemplified, recommendations of reference standards are analyzed, and possible solutions discussed.
Results and discussionWith the goal and scope of O-LCA, some challenging issues were to select part of an organization as the reporting organization, and the operability of the reporting flow. Regarding the system boundary, the challenges were which parts of the supply chain should be included in the study, problems when setting the system boundary for the service sector, how to include supporting activities, and how to prepare the right system boundary diagrams. Regarding the inventory stage, the discussion starts with alternatives to the categorization of the inventory into activities and the aggregation of those activities into groups. It includes an equivalence table for an easier transfer from other organizational frameworks (ISO 14069 and the GHG Protocol). Some challenges during impact assessment and interpretation were the assessment of local impacts, scoping performance tracking, and the use of O-LCA results for an organization’s strategy.
ConclusionsThe review of challenges is not meant as a complete overview of all possible challenges—new challenges may arise in future case studies. Further application testing is needed, along with research to support a future revision of the O-LCA Guidance, in line with the issues highlighted in this paper and new challenges may arise in future case studies. O-LCA has the potential to contribute in the future implementation of the life cycle concept in environmental management systems, in the development of organizational footprint metrics for region-specific impacts, and in the social dimension of life cycle assessment.
相似文献A scalable life cycle inventory (LCI) model, which provides mass composition and gate-to-gate manufacturing data for a power electronic inverter unit intended for controlling electric vehicle propulsion motors, was developed. The purpose is to fill existing data gaps for life cycle assessment (LCA) of electric vehicles. The model comprises new and easy-to-use data with sufficient level of detail to enable proper component scaling and in-depth analysis of inverter units. The aim of this article (part II) is to describe the modeling of all production steps and present new datasets. Another objective is to explain the strategies for data collection, system boundaries, and how unit process datasets were made to interact properly with the scalable design model (part I).
MethodsData for the manufacturing of the inverter unit was collected from a variety of literature, technical specifications, factory data, site visits, and expert interviews. The model represents current levels of technology and modern industrial scale production. Industry data dates back to 2012. Some older literature is referred to, but only if it was found to remain relevant. Upstream, new data has been gathered to the point where the Ecoinvent database can be used to model a full cradle-to-gate inventory. To make the LCI model easy to use, each flow crossing the system boundary is reported with a recommended linked flow to this database.
Results and discussionThe screening and modeling of manufacturing inverter units resulted in a substantial compilation of new inventory data. In close integration with the design model, which is scalable in size over a range of 20–200 kW in nominal power and 250–700 V in DC system voltage (part I), it forms a comprehensive scalable LCI model of a typical automotive power electronic inverter unit intended for traction motor control. New production data covers electroplating of gold, electro-galvanization, machining and anodizing of aluminum, ceramic substrate fabrication, direct copper bonding, photoimaging and regenerative etching, power module assembly with a two-step soldering process, and the assembly of automotive printed circuit boards.
ConclusionsInterviews with experts were found to be vital for effective data collection and the reporting of details a key to maintaining data usability over time, for reuse, rework, and criticism by other LCA practitioners.
相似文献Organic agriculture (OA) has gained widespread popularity due to its view as a more sustainable method of farming. Yet OA and conventional agriculture (CA) can be found to have similar or varying environmental performance using tools such as life cycle assessment (LCA). However, the current state of LCA does not accurately reflect the effects of OA; thus the aim of the present study was to identify gaps in the inventory stage and suggest improvements.
MethodsThis article presents for the first time a critical analysis of the life cycle inventory (LCI) of state-of-the-art organic crop LCIs from current and recommended LCA databases ecoinvent and AGRIBALYSE®. The effects of these limitations on LCA results were analyzed and detailed ways to improve upon them were proposed.
Results and discussionThrough this analysis, unrepresentative plant protection product (PPP) manufacturing and organic fertilizer treatment inventories were found to be the main limitations in background processes, due to either the lack of available usage statistics, exclusion from the study, or use of unrepresentative proxies. Many organic crop LCIs used synthetic pesticide or mineral fertilizer proxies, which may indirectly contain OA prohibited chemicals. The effect of using these proxies can contribute between 4–78% to resource and energy-related impact categories. In a foreground analysis, the fertilizer and PPP emission models utilized by ecoinvent and AGRIBALYSE® were not well adapted to organic-authorized inputs and used simplified modeling assumptions. These critical aspects can be transferred to respective LCAs that use this data, potentially yielding unrepresentative results for relevant categories. To improve accuracy and to contribute novel data to the scientific community, new manufacturing LCIs were created for a few of the missing PPPs, as well as recommendations for fertilizer treatment LCIs and more precise emission models for PPPs and fertilizers.
ConclusionsThe findings in the present article add much needed transparency regarding the limitations of available OA LCIs, offers guidance on how to make OA LCIs more representative, allow for more accurate comparisons between conventional and OA, and help practitioners to better adapt LCA methodology to OA systems.
相似文献In recent years, the building sector has highlighted the importance of operational energy and efficient resource management in order to reduce the environmental impacts of buildings. However, differences in building-specific properties (building location, size, construction material, etc.) pose a major challenge in development of generic policy on buildings. The aim of this study was to investigate the relationship between energy and resource management policies, and building-specific characteristics on environmental impacts of refurbished office buildings in New Zealand.
MethodsLife Cycle Assessment (LCA) was performed for 17 office buildings operating under seven representative climatic conditions found in New Zealand. Each building was assessed under four policy scenarios: (i) business-as-usual, (ii) use of on-site photovoltaic (PV) panels, (iii) electricity supply from a renewable energy grid, and (iv) best practice construction activities adopted at site. The influence of 15 building-specific characteristics in combination with each scenario was evaluated. The study adopted regression analysis, more specifically Kruskal-Wallis and General Additive Modeling (GAM), to support interpretation of the LCA results.
Results and discussionAll the chosen policies can significantly contribute to climate change mitigation as compared to business-as-usual. However, the Kruskal-Wallis results highlight policies on increasing renewable energy sources supplying national grid electricity can substantially reduce the impacts across most environmental impact categories. Better construction practices should be prioritized over PV installation as use of on-site PV significantly increases the environmental impacts related to use of resources. The GAM results show on-site PV could be installed in low-rise buildings in regions with long sunshine hours. The results also show the strong influence of façade elements and technical equipment in determining the environmental performance of small and large buildings, respectively. In large multi-storied buildings, efficient HVAC and smaller window area are beneficial features, while in small buildings the choice of façade materials with low embodied impacts should be prioritized.
ConclusionsIn general, the study highlighted the importance of policies on increasing renewable energy supply from national grid electricity to substantially reduce most of the impacts related to buildings. In addition, the study also highlighted the importance of better construction practices and building-specific characteristics to reduce the impacts related to resource use. These findings can support policy makers to prioritize strategies to improve the environmental performance of existing buildings in New Zealand and in regions with similar building construction and climate.
相似文献Several models are available in the literature to estimate agricultural emissions. From life cycle assessment (LCA) perspective, there is no standardized procedure for estimating emissions of nitrogen or other nutrients. This article aims to compare four agricultural models (PEF, SALCA, Daisy and Animo) with different complexity levels and test their suitability and sensitivity in LCA.
MethodsRequired input data, obtained outputs, and main characteristics of the models are presented. Then, the performance of the models was evaluated according to their potential feasibility to be used in estimating nitrogen emissions in LCA using an adapted version of the criteria proposed by the United Nations Framework Convention on Climate Change (UNFCCC), and other relevant studies, to judge their suitability in LCA. Finally, nitrogen emissions from a case study of irrigated maize in Spain were estimated using the selected models and were tested in a full LCA to characterize the impacts.
Results and discussionAccording to the set of criteria, the models scored, from best to worst: Daisy (77%), SALCA (74%), Animo (72%) and PEF (70%), being Daisy the most suitable model to LCA framework. Regarding the case study, the estimated emissions agreed to literature data for the irrigated corn crop in Spain and the Mediterranean, except N2O emissions. The impact characterization showed differences of up to 56% for the most relevant impact categories when considering nitrogen emissions. Additionally, an overview of the models used to estimate nitrogen emissions in LCA studies showed that many models have been used, but not always in a suitable or justified manner.
ConclusionsAlthough mechanistic models are more laborious, mainly due to the amount of input data required, this study shows that Daisy could be a suitable model to estimate emissions when fertilizer application is relevant for the environmental study. In addition, and due to LCA urgently needing a solid methodology to estimate nitrogen emissions, mechanistic models such as Daisy could be used to estimate default values for different archetype scenarios.
相似文献In support of the sustainable development of our societies, future engineers should have elementary knowledge in sustainability assessment and use of life cycle assessment. Publications on pedagogical experience with teaching life cycle assessment (LCA) in high-level education are however scarce. Here, we describe and discuss 20 years of experience in teaching LCA at MSc level in an engineering university with the ambition to share our insights and inspire teaching of LCA as part of a university curriculum.
MethodsWe detail the design of an LCA course taught at the Technical University of Denmark since 1997. The course structure relies on (i) a structured combination of theoretical teaching, practical assignments and hands-on practice on LCA case studies, and (ii) the conduct of real-life LCA case studies in collaboration with companies or other organisations. Through the semester-long duration of the course, students from different engineering backgrounds perform full-fledged LCA studies in groups, passing through two iterations—a screening LCA supporting a more targeted LCA.
Results and discussionThe course design, which relies on a learning-by-doing principle, is transparently described to inspire LCA teachers among the readers. Historical evolution and statistics about the course, including its 192 case studies run in collaboration with 105 companies and institutions, are analysed and serve as basis to discuss the benefits and challenges of its different components, such as the theory acquisition, the assignment work, the LCA software learning, the conduct of case studies, the merits of industrial collaborations and grading approaches.
ConclusionsWe demonstrate the win-win situation created by the setting of the course, in which the students are actively engaged and learn efficiently how to perform an LCA while the collaborating companies often get useful insights into their analysed case studies. The course can also be an eye opener for companies unfamiliar with LCA, who get introduced to life cycle thinking and the potential benefits of LCA. We have no hesitation in recommending industries and LCA teachers to engage into such collaborations even in the fundamental teaching of LCA techniques.
相似文献This paper aims to demonstrate how LCA can be improved by the use of linear programming (LP) (i) to determine the optimal choice between new technologies, (ii) to identify the optimal region for supplying the feedstock, and (iii) to deal with multifunctional processes without specifying a certain main product. Furthermore, the contribution of LP in the context of consequential LCA and LCC is illustrated.
MethodsWe create a mixed integer linear program (MILP) for the environmental and economic assessment of new technologies. The model is applied in order to analyze two residual beech wood-based biorefinery concepts in Germany. In terms of the optimal consequences for the system under study, the principle of the program is to find a scaling vector that minimizes the life cycle impact indicator results of the system. We further transform the original linear program to extend the assessment by life cycle costing (LCC). Thereby, two multi-objective programming methods are used, weighted goal programming and epsilon constraint method.
Results and discussionThe consequential case studies demonstrate the possibility to determine optimal locations of newly developed technologies. A high number of potential system modifications can be studied simultaneously without matrix inversion. The criteria for optimal choices are represented by the objective functions and the additional constraints such as the available feedstock in a region. By combining LCA and LCC targets within a multi-objective programming approach, it is possible to address environmental and economic trade-offs in consequential decision-making.
ConclusionsThis article shows that linear programming can be used to extend standard LCA in the field of technological choices. Additional consequential research questions can be addressed such as the determination of the optimal number of new production plants and the optimal regions for supplying the resources. The modifications of the program by additional profit requirements (LCC) into a goal program and Pareto optimization problem have been identified as promising steps toward a comprehensive multi-objective LCSA.
相似文献