Why are both A−1${\mathbf{A}}^{-1}$ and (I−A)−1${(\mathbf{I}-\mathbf{A})}^{-1}$ used in life cycle assessment (LCA) matrix computations? This is a question that, in our experience of teaching LCA, ...students often wonder about and struggle with. A brief survey of the literature suggests that the question can also confuse experienced LCA practitioners. Here, we seek to unify the computational structures of the two LCA approaches to achieve greater clarity and consistency, especially to make them easier to teach. We first show how small but crucial differences in the set‐up of the two approaches lead to the use of A$\mathbf{A}$ versus I−A$\mathbf{I}-\mathbf{A}$. Then, we discuss the options to unify the presentations in a coherent way. We do not prescribe one way or the other. A larger point we hope to stress is the importance of unification, which may have both pedagogical and methodological benefits.
•A biofueled tractor diesel engine was exergetically, economically, and environmentally studied.•Biodiesel could improve the exergetic, economic, and environmental indicators of the system.•There was ...no clear pattern of the effects of bioethanol on the investigated indicators.•Biofuel blends were exergetically, economically, and environmentally superior to diesel.•The best results were found for the blend containing 10 vol% biodiesel and 4 vol% bioethanol.
This study aimed to analyze a heavy-duty tractor diesel engine operating on diesel-biodies-bioethanol blends using exergetic, economic, and environmental life cycle assessment analyses. Diesel was mixed with biodiesel and bioethanol with volumetric ratios of 5–15% and 2–6%, respectively. Nine diesel–biodiesel-bioethanol blends and one baseline fuel were tested at different PTO shaft speeds ranging from 800 to 1000 rpm under full load operating conditions. Various exergetic, economic, and environmental indicators were computed to facilitate decision-making on fuel composition and PTO shaft speed. In general, increasing biodiesel concentration in the fuel blend could improve the exergetic, economic, and environmental indicators of the system. However, there was no clear pattern of the effects of bioethanol on the investigated indicators. Interestingly, most of the prepared fuel blends were exergetically, economically, and environmentally superior to diesel. The lowest weighted environmental impact (52.1 mPts/GJ) and PTO shaft power generation cost (0.18 USD/kWh) were found for the fuel blend containing 10 vol% biodiesel and 4 vol% bioethanol at the PTO shaft speed of 1000 rpm. This fuel blend also showed the highest resource utilization efficiency (29.3%) and environmental sustainability (26.1%) at the PTO shaft speed of 1000 rpm. The weighted environmental impact and PTO shaft power generation cost of the selected fuel blend were 44.3% and 46.2% lower than those of diesel, respectively. The resource utilization efficiency and environmental sustainability of the selected fuel blend were 97.3% and 99.8% higher than those of diesel, respectively. Overall, substituting a portion of diesel with biodiesel and bioethanol was proved to be an attractive strategy from the exergetic, economic, and environmental perspectives. The results obtained can be valuable in practical applications to enhance the sustainability and viability of power production in agricultural activities. The applied exergetic, economic, and environmental methodologies appear to be reliable and comprehensive tools for assessing the whole-life sustainability and viability of mineral-biofuel blends.
Rechargeable batteries are necessary for the decarbonization of the energy systems, but life‐cycle environmental impact assessments have not achieved consensus on the environmental impacts of ...producing these batteries. Nonetheless, life cycle assessment (LCA) is a powerful tool to inform the development of better‐performing batteries with reduced environmental burden. This review explores common practices in lithium‐ion battery LCAs and makes recommendations for how future studies can be more interpretable, representative, and impactful. First, LCAs should focus analyses of resource depletion on long‐term trends toward more energy and resource‐intensive material extraction and processing rather than treating known reserves as a fixed quantity being depleted. Second, future studies should account for extraction and processing operations that deviate from industry best‐practices and may be responsible for an outsized share of sector‐wide impacts, such as artisanal cobalt mining. Third, LCAs should explore at least 2–3 battery manufacturing facility scales to capture size‐ and throughput‐dependent impacts such as dry room conditioning and solvent recovery. Finally, future LCAs must transition away from kg of battery mass as a functional unit and instead make use of kWh of storage capacity and kWh of lifetime energy throughput.
Rechargeable batteries are necessary for the decarbonization of the energy systems, but life‐cycle environmental impact assessments have not achieved consensus on the environmental impacts of producing these batteries. This article highlights underlying reasons for the discrepancies in energy and environmental impact estimates and recommends better practices for more transparent, interpretable battery life‐cycle assessments.
The book contains a collection of articles dealing with how the extraction of mineral resources can be considered in environmental analyses such as Life Cycle Assessment (LCA). The consumption of ...resources, e.g., metals, is increasing strongly worldwide. This is associated with more energy use; environmental pollution; and social, economic, and political consequences. An increase is also expected for the coming decades. At the same time, modern products and technologies, even in the field of renewable energies, require a large number of critical raw materials. A crucial question here is the exhaustibility of natural resources. What is the relevance of resource depletion today? Must a geological shortage of metals be expected in the foreseeable future? How could such a thing be considered in the LCA of products and weighed against other environmental aspects? The articles in question have been written over the past three years by leading experts in both geology and environmental sciences and show the breadth of the controversial discussion.
Excess Food Energy Intake (EFEI), namely Metabolic Food Waste (MFW) corresponds to excess calorie intake related to overconsumption of food and is responsible for overweight (OW) and obesity (OB) ...conditions. Identifying its causes and impacts could be important, so that it can be prevented and reduced, generating health, environmental and societal benefits. Therefore, this research quantifies MFW among OW and OB adult populations (18–75 years) in Italy and its environmental and social implications. Life cycle assessment (LCA) through the Simapro 9.5 software was used and then, the results were monetized according to the Environmental Price Handbook to understand the real environmental cost. Finally, Social LCA (S-LCA) was considered following the Product Social Impact Assessment (PSILCA) guidelines to understand the potential social risks behind the food that ends up on our plates. The results highlight the amount of MFW in Italy is 2696 billion kcal/year corresponding to 1.59 Mtons over-consumed food/year, while the impacts are mainly related to global warming (8.78 Mtons CO2 eq/year, or 2.29 % of the total Italian CO2 emissions), terrestrial ecotoxicity (843,451 tons 1.4-DCB/year), freshwater ecotoxicity (222,483 tons 1.4 DCB eq/year), and land consumption (8 million m2a eq/year), mostly due to the meat, fats and oils and sweets overconsumption. Impacts monetization also shows that MFW could induce an environmental price of € 1340/per capita/year, and finally, the S-LCA reveals how overconsumption of food has the potential to affect gender discrimination, water depletion, trade union, and social discrimination due to the high proportion of labor migrants in the agricultural sector.
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•Excess Food Energy Intake, or Metabolic Food Waste is responsible for overweight and obesity conditions.•Environmental and social implications of MFW were quantified considering the overweight and obese adult population in Italy.•The MFW in Italy is 2,696 billion kcal/year or 1.59 Mtons of food, corresponding to 8.78 Mtons CO2 eq/year.•Impacts monetization also shows that MFW could induce an environmental price of € 1,340/per capita/year.•Food overconsumption can potentially affect gender discrimination, water depletion, trade unions, and social discrimination.
The life cycle sustainability assessment (LCSA) is a tool to assess sustainability from a life cycle perspective, which has been receiving increased attention over the years. This work presents a ...systematic review of the current application of LCSA, presenting the foundations, main methods, current operationalization state, and major challenges to its broad implementation. The review protocol considered the search of keywords in Scopus and Web of Science databases. The search has considered the literature published or in the press until December 2018, resulting in the selection of 144 articles written in English. Of those, 71 articles operationalize LCSA in real case studies, while the remaining consist of review, viewpoint, and methodological development articles. This review demonstrates that the use of LCSA has been increasing in recent years. Today, the most applied approach is to consider LCSA as the sum of life cycle assessment, life cycle costing, and social life cycle assessment because it is built on the methodologies that already exist and are under continuous development. However, the lack of harmonization of the methodology is a central challenge to its operationalization. Therefore, LCSA still requires further improvement in, among others, definition of coherent system boundaries, the development of robust databases to allow the assessment of economic and social perspectives, definition of impact categories that allow comparability between studies, development of impact assessment methods, development of methods to carry out uncertainty analysis, and communication strategies. Besides, further case studies should be developed to support the improvement of the methodology and a better understanding of the interaction of the environmental, economic, and social aspects.
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•There are several approaches to conduct LCSA.•LCSA = LCA + LCC + SLCA is the most used approach.•Multi-criteria decision analysis (MCDA) methods are widely used to assess LCSA.•Methodological challenges for operationalization of LCSA are identified.
Digital tools based on Building Information Modelling (BIM) provide the potential to facilitate environmental performance assessments of buildings. Various tools that use a BIM model for automatic ...quantity take-off as basis for Life Cycle Assessment (LCA) have been developed recently. This paper describes the first application of such a BIM-LCA tool to evaluate the embodied global warming potential (GWP) throughout the whole design process of a real building. 34 states of the BIM model are analysed weekly. The results show that the embodied GWP during the design phase is twice as high as for the final building. These changes can be mainly attributed to the designers' approach of using placeholder materials that are refined later, besides other reasons. As such, the embodied GWP is highly overestimated and a BIM-based environmental assessment during the design process could be misleading and counterproductive. Finally, three alternatives to the established automatic quantity take-off are discussed for future developments.
•First application of a BIM-LCA approach throughout the design process of a real building•Tracking of design decisions using 34 fixed states of the continuously evolving BIM model•Identification of limitations of the current BIM-LCA approach•Proposals for future effective environmental performance improvement during the design phase
Purpose
Good background data are an important requirement in LCA. Practitioners generally make use of LCI databases for such data, and the ecoinvent database is the largest transparent unit-process ...LCI database worldwide. Since its first release in 2003, it has been continuously updated, and version 3 was published in 2013. The release of version 3 introduced several significant methodological and technological improvements, besides a large number of new and updated datasets. The aim was to expand the content of the database, set the foundation for a truly global database, support regionalized LCIA, offer multiple system models, allow for easier integration of data from different regions, and reduce maintenance efforts. This article describes the methodological developments.
Methods
Modeling choices and raw data were separated in version 3, which enables the application of different sets of modeling choices, or system models, to the same raw data with little effort. This includes one system model for Consequential LCA. Flow properties were added to all exchanges in the database, giving more information on the inventory and allowing a fast calculation of mass and other balances. With version 3.1, the database is generally water-balanced, and water use and consumption can be determined. Consumption mixes called market datasets were consistently added to the database, and global background data was added, often as an extrapolation from regional data.
Results and discussion
In combination with hundreds of new unit processes from regions outside Europe, these changes lead to an improved modeling of global supply chains, and a more realistic distribution of impacts in regionalized LCIA. The new mixes also facilitate further regionalization due to the availability of background data for all regions.
Conclusions
With version 3, the ecoinvent database substantially expands the goals and scopes of LCA studies it can support. The new system models allow new, different studies to be performed. Global supply chains and market datasets significantly increase the relevance of the database outside of Europe, and regionalized LCA is supported by the data. Datasets are more transparent, include more information, and support, e.g., water balances. The developments also support easier collaboration with other database initiatives, as demonstrated by a first successful collaboration with a data project in Québec. Version 3 has set the foundation for expanding ecoinvent from a mostly regional into a truly global database and offers many new insights beyond the thousands of new and updated datasets it also introduced.
Process‐based Life Cycle Assessments (PLCA) rely on detailed descriptions of extensive value chains and their associated exchanges with the environment, but major data gaps limit the completeness of ...these system descriptions and lead to truncations in inventories and underestimations of impacts. Hybrid Life Cycle Assessments (HLCA) aim to combine the strength of PLCA and Environmentally Extended Input Output (EEIO) analysis to obtain more specific and complete system descriptions. Currently, however, most HLCAs only remediate truncation of processes that are specific to each case study (foreground processes), and these processes are then linked to (truncated) generic background processes from a non‐hybridized PLCA database. A hybrid PLCA‐EEIO database is therefore required to completely solve the truncation problems of PLCA and thus obtain a comprehensive product system coverage. This paper describes the construction of such a database using pyLCAIO, a novel framework and open‐source software enabling the streamlined hybridization of entire PLCA and EEIO databases. We applied this framework to the PLCA database Ecoinvent3.5 and the multiregional EEIO database EXIOBASE 3. Thanks to the correction for truncation in this new hybrid database, the median and average life cycle global warming potential (GWP) of its processes increased by 7% and 14%, respectively. These corrections only reflect the truncations that could be readily identified and estimated in a semi‐automated manner; and we anticipate that further database integration should lead to higher levels of correction in the future.
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