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Many decisions are made during the life cycle of a product, e.g., whether to replace a product or to keep using it. To pinpoint the “greener” choice, the consequential environmental effects of each choice should be estimated. Hereto, only activities occurring after the decision should be considered and, thus, not necessarily the complete product life cycle. Decisions are taken at different levels in the economy, ranging from small scale (e.g., few individual purchases) to large scale (e.g., policies). In this article, we introduce a framework that mainly focuses on the small-scale decision of replacement of a product in usage, illustrated in case of a petrol versus an electric car. For a fixed time span of usage (functional unit), the product system composition varies based on the selected time of replacement. Many market mechanisms occur within the cause-effect chain, for which argued presumptions are necessary. For example, the purchase of the alternative product is reasoned to possibly induce an additional product supply. Moreover, if the product is not obsolete after initial usage, it is sold in the secondhand market and will thus displace the average market mix. The developed framework for this small-scale replacement decision is different from the alternative consequential approach of ecoinvent that covers a different decision, namely, a marginal increase in demand, e.g., of car usage, at market level. In our framework, a ratio for the amount of newly car produced per purchase is introduced. For the case study, the global warming potential over 100 years is estimated, this using general data from databases and time-varying market mix (in composition), car technology, and electricity mix. A set of equations is introduced that serves as a first simplified framework. Bearing in mind limitations, if the petrol car is disposed of as waste after initial usage whereas the electric car resold, it is estimated that a replacement of the petrol car by the electric car at any time lowers the impact on climate change. A better characterization of impact over time and market and agent-based modeling should be at the core of further efforts, especially when upscaling to large-scale decisions. Framework and insights are provided on the modeling of the environmental effects of a replacement decision. Finally, this article may serve as a stepping-stone towards an integrated consequential modeling of sustainability impact of product-related decisions, looking beyond a normative consideration of a fixed product life cycle.

This paper proposes a new bi-objective optimization model, trading-off cost and environmental impacts, for sizing the key electrical and thermal devices in a zero energy building (ZEB), i.e., a building that roughly generates as much renewable energy as it consumes annually. A salient novel feature is the consideration of the environmental impacts, computed through a rigorous life cycle assessment approach, of buying electricity from the grid and manufacturing devices. Furthermore, an enhancement of the proposed model, as compared to the existing models, is to prioritize storing the ZEB excess of energy rather than selling it to the grid. The proposed solution approach of the initial mixed-integer nonlinear programming model relies on McCormick relaxation linearization to obtain a more tractable mixed-integer linear model. An augmented ϵ-constraint method is applied to solve the obtained bi-objective model. Finally, considering the building owners' willingness-to-pay for environmental impacts, a decision-making criterion is proposed to select the optimal size of the devices among all non-dominated solutions of the Pareto front.

The important focus of the energy strategy of the European Union relies on the concept of zero energy building (ZEB), which is, by definition, a building that roughly produces yearly as much renewable energy as it consumes. This article proposes an enhanced mixed-integer nonlinear programming model for optimal sizing of photovoltaic (PV) and battery energy storage systems to comply with the definition of a ZEB. A salient novel feature of the proposed model is that it factors in the environmental impacts, computed through rigorous life cycle assessment methodology, of buying electricity from the grid and manufacturing battery and PV systems. Furthermore, an adjustable parameter is introduced to make the model adaptive from the perspective of the building owner's willingness-to-pay for environmental impacts. The proposed model is then rigorously reformulated, managing to accumulate its nonlinearity in only one constraint per time interval. Eventually, the reformulated model is linearized to a mixed-integer linear programming model using the McCormick relaxation technique. The case study conducted on archetypal buildings in Luxembourg reveals that the proposed McCormick-based linear model is able to provide high accuracy results with reasonable computational effort.

Purpose The objective is to demonstrate an operational tool for dynamic LCA, based on the model by Tiruta-Barna et al. (J Clean Prod 116:198-206, Tiruta-Barna et al. 2016). The main innovation lies in the combination of full temporalization of the background inventory and a graph search algorithm leading to full dynamic LCI, further coupled to dynamic LCIA. The following objectives were addressed: (1) development of a database with temporal parameters for all processes of ecoinvent 3.2, (2) implementation of the model and the database in integrated software, and (3) demonstration on a case study comparing a conventional internal combustion engine car to an electric one. Methods Calculation of dynamic LCA (including temporalization of background and foreground system) implies (i) a dynamic LCI model, (ii) a temporal database including temporal characterization of ecoinvent 3.2, (iii) a graph search algorithm, and (iv) dynamic LCIA models, in this specific case for climate change. The dynamic LCI model relies on a supply chain modeling perspective, instead of an accounting one. Unit processes are operations showing a specific functioning over time. Mass and energy exchanges depend on specific supply models. Production and supply are described by temporal parameters and functions. The graph search algorithm implements the dynamic LCI model, using the temporal database, to derive the life cycle environmental interventions scaled to the functional unit and distributed over time. The interventions are further combined with the dynamic LCIA models to obtain the temporally differentiated LCA results. Results and discussion A web-based tool for dynamic LCA calculations (DyPLCA) implementing the dynamic LCI model and temporal database was developed. The tool is operational and available for testing (http://dyplca.univ-lehavre.fr/). The case study showed that temporal characterization of background LCI can change significantly the LCA results. It is fair to say that temporally differentiated LCI in the background offers little interest for activities with high downstream emissions. It can provide insightful results when applied to life cycle systems where significant environmental interventions occur upstream. Those systems concern, for example, renewable electricity generation, for which most emissions are embodied in an infrastructure upstream. It is also observed that a higher degree of infrastructure contribution leads to higher spreading of impacts over time. Finally, a potential impact of the time window choice and discounting was observed in the case study, for comparison and decision-making. Time differentiation as a whole may thus influence the conclusions of a study. Conclusions The feasibility of dynamic LCA, including full temporalization of background system, was demonstrated through the development of a web-based tool and temporal database. It was showed that considering temporal differentiation across the complete life cycle, especially in the background system, can significantly change the LCA results. This is particularly relevant for product systems showing significant environmental interventions and material exchanges over long time periods upstream to the functional unit. A number of inherent limitations were discussed and shall be considered as opportunities for further research. This requires a collegial effort, involving industrial experts from different sectors.

According to the Intergovernmental Panel on Climate Change (IPCC), in 2010 the transport sector was responsible for 23% of the total energy-related CO2 emissions (6.7 GtCO2) worldwide. Policy makers in Luxembourg are well-aware of the challenges and are setting ambitious objectives at country level for the mid and long term. However, a framework to assess environmental impacts from a life cycle perspective on the scale of transport policy scenarios, rather than individual vehicles, is lacking. We present a novel framework linking activity-based modeling with life cycle assessment (LCA) and a proof-of-concept case study for the French cross-border commuters working in Luxembourg. Our framework allows for the evaluation of specific policies formulated on the trip level as well as aggregated evaluation of environmental impacts from a life cycle perspective. The results of our proof-of-concept-based case study suggest that only a combination of: (1) policy measures improving the speed and coverage of the public transport system, (2) policy measures fostering electric mobility, and (3) external factors such as de-carbonizing the electricity mix will allow to counteract the expected increase in impacts due to the increase of mobility needs of the growing commuting population in the long term.

To evaluate the sustainability of any economic system, the impact of related products and processes should be considered, which is exactly the aim of life cycle sustainability assessment (LCSA). A first challenge for the current LCSA methodology of circular economy systems, is the consideration of finite and variable loops (e.g. paper fibres can commonly only be recycled a few times). Second, because impact is time-dependant (e.g. financial flows are valued less in the future), loops should be propagated over time. Therefore, we bring forward a general iterative modelling approach (process-by-process) in which flows are tracked over time. A third challenge remains on how to potentially distribute impacts among related products. We present an overview of various approaches, their implications for finite variable loops, whether databases are existing and in which context they should be applied (e.g. for attributional or consequential thinking). A general six-step framework is provided to guide the practitioner. To illustrate this, we developed a simplistic tool (FLOREC BASIC) and performed two case studies. A fictional case on profit generation for flooring reuse, showcases that when considering discounting (10%), producer profit drops about a third. For a case on linerboard recycling, the water scarcity impact is 11% higher for 5 times recycling instead of infinite times. However, when considering the consequential effect on the market, effects are the opposite; linerboard recycling has a higher water scarcity impact, because of its considerable water consumption, compared to incineration with displacement of alternative energy sources that have high water scarcity impact.

Assessing the environmental impacts of electricity generation is fundamental for designing a low-carbon future for our societies. The amount of data collected for that purpose has significantly increased over the past decade due to the emergence of various methods, such as life cycle assessment and input-output analysis. We present here a comparison of environmental assessment methods for geothermal plants, based on physical and/or monetary data. Results show that some hybrid (mass-monetary) inventories yield results that vary significantly between impact categories. However, for the particular geothermal system investigated, direct emissions of geothermal fluids dominate the few impact categories to which they contribute.

Green bonds have emerged as a key instrument to fund projects contributing to climate change mitigation or environmental protection. However, a consistent, robust and comparable standard for the estimation of the environmental impacts of green bonds is lacking, hampering growth in sustainable finance. As encouraged by second-party opinion reports, the use of life cycle assessment (LCA) allows for the complete environmental evaluation of projects over their life cycle. Here we estimate the LCA-based impacts along several environmental metrics of a set of green bonds for renewable power plants issued by the European Investment Bank from 2015–2018. Life cycle avoided greenhouse gas (GHG) emissions varied by a factor of 12 from 29 to 359 t CO2 eq./M€ invested—information that is not available to investors at the outset, indicating that funds are unlikely to be allocated efficiently. Furthermore, linking environmental impact indicators to the Sustainable Development Goals unveils significant trade-offs. Bonds may perform well on water use and emissions, while having a negative impact on waste and land use. Conducting LCA of green bonds comes at a cost of additional methodological challenges and increased data needs compared with current reporting practices. However, the ready infrastructure of LCA databases and methodologies can provide the necessary tools to meet future reporting requirements as the EU taxonomy framework and standardization of impact reporting evolve.

One of the key drivers that influence building energy consumption is the demand for space heating. Particularly in countries with cold climates and a large stock of residential buildings with central heating, building energy management systems (BEMS) are an option to reduce energy consumption and greenhouse gas (GHG) emissions. These systems can be combined with existing space heating technologies and other efficiency measures, such as building insulation. They are ideal for retrofitting purposes owing to their low up-front costs. A prospective life cycle assessment model is used to analyze the environmental impacts of the technology today, in 2030, and in 2050. This allows for a first-ever, order-of-magnitude assessment of the environmental impacts of BEMS over their life cycle. The assessment is based on manufacturer information and generic life cycle inventory data for electronic components. Future impacts are based on changes in electricity generation following the International Energy Agency's 2 degree and 6 degree scenarios, and are used to assess the contribution of BEMS to global energy and GHG saving goals. Results show substantially lower life cycle GHG emissions and higher savings of environmental impacts per kilowatt-hour of heating when compared to natural gas or electric heating. Potential net emissions savings range from approximately 0.4 kilograms carbon dioxide equivalent (kg CO2-eq) when avoiding natural gas heating to over 1 kg CO2-eq when avoiding electric heating in regions with GHG-intensive electricity generation. At present, BEMS can avoid at least 40 times the GHG emissions that they require for production and use, when deployed in regions with cold climates.

Artificial lighting is a major source of electricity demand globally. As the demand for lighting services grows over the next 40 years, especially in developing countries, efficient light-source technologies such as light-emitting diodes (LEDs) can reduce the energy consumed for lighting services and therefore its environmental impacts. LED technologies in both residential and commercial/industrial applications are expected to see dramatic improvements in luminous efficacy over the coming decades, potentially leading to more environmentally benign lighting. A scenario-based, integrated hybrid life cycle assessment quantifies and confirms the environmental benefits of deploying efficient light sources in all global regions through 2050, with electricity generation following the International Energy Agency's (IEA) BLUE Map scenario for limiting climate change to 2 degrees Celsius. Data used for previous assessments of light sources is updated and harmonized to reflect recent and expected future improvements in luminous efficacy and materials efficiency for LED lamps and luminaires. The aggregate life cycle greenhouse gas (GHG) emissions of global light provision can be reduced by more than a factor of 7 owing to decarbonization of electricity generation, increased adoption of efficient light sources, and future advances in LED technology. Estimates of the technological capability and market penetration of efficient light sources show that by 2050, a 2.5 to 2.9 times growth in the global demand for lighting services can be accommodated while still meeting IEA GHG mitigation goals and increasing metal depletion just 20% above 2010 estimates.

Decarbonization of electricity generation can support climate-change mitigation and presents an opportunity to address pollution resulting from fossil-fuel combustion. Generally, renewable technologies require higher initial investments in infrastructure than fossil-based power systems. To assess the tradeoffs of increased up-front emissions and reduced operational emissions, we present, to our knowledge, the first global, integrated life-cycle assessment (LCA) of long-term, wide-scale implementation of electricity generation from renewable sources (i.e., photovoltaic and solar thermal, wind, and hydropower) and of carbon dioxide capture and storage for fossil power generation. We compare emissions causing particulate matter exposure, freshwater ecotoxicity, freshwater eutrophication, and climate change for the climate-change-mitigation (BLUE Map) and business-as-usual (Baseline) scenarios of the International Energy Agency up to 2050. We use a vintage stock model to conduct an LCA of newly installed capacity year-by-year for each region, thus accounting for changes in the energy mix used to manufacture future power plants. Under the Baseline scenario, emissions of air and water pollutants more than double whereas the low-carbon technologies introduced in the BLUE Map scenario allow a doubling of electricity supply while stabilizing or even reducing pollution. Material requirements per unit generation for low-carbon technologies can be higher than for conventional fossil generation: 11–40 times more copper for photovoltaic systems and 6–14 times more iron for wind power plants. However, only two years of current global copper and one year of iron production will suffice to build a low-carbon energy system capable of supplying the world's electricity needs in 2050. © 2014 National Academy of Sciences

Limiting climate change by stabilizing the global temperature requires the near complete phase-out of conventional fossil fuel power generation and its replacement through technologies with low greenhouse gas emissions, such as renewable energy, nuclear power, and fossil fuel power plants with CO2 capture and storage. We investigate the environmental and resource co-benefits and adverse trade-offs for a wide range of candidate electricity generation technologies using an integrated life cycle approach. Most renewable energy technologies provide substantial benefits in terms of emission reductions. Additional material demand for manufacturing energy conversion devices ranges between 0.1 and 3 times annual global production in 2010.

Stabilizing global temperature will require a shift to renewable or nuclear power from fossil power and the large-scale deployment of CO2 capture and storage (CCS) for remaining fossil fuel use. Non-climate co-benefits of low-carbon energy technologies, especially reduced mortalities from air pollution and decreased ecosystem damage, have been important arguments for policies to reduce CO2 emissions. Taking into account a wide range of environmental mechanisms and the complex interactions of the supply chains of different technologies, we conducted the first life cycle assessment of potential human health and ecological impacts of a global low-carbon electricity scenario. Our assessment indicates strong human health benefits of low-carbon electricity. For ecosystem quality, there is a significant trade-off between reduced pollution and climate impacts and potentially significant ecological impacts from land use associated with increased biopower utilization. Other renewables, nuclear power and CCS show clear ecological benefits, so that the climate mitigation scenario with a relatively low share of biopower has lower ecosystem impacts than the baseline scenario. Energy policy can maximize co-benefits by supporting other renewable and nuclear power and developing biomass supply from sources with low biodiversity impact. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

The targeted transition towards an electricity system with low or even negative greenhouse gas emissions affords a chance to address other environmental concerns as well, but may potentially have to adjust to the limited availability of assorted non-fossil resources. Life cycle assessment (LCA) is widely recognized as a method appropriate to assess and compare product systems taking into account a wide range of environmental impacts. Yet, LCA could not inform the latest assessment of co-benefits and trade-offs of climate change mitigation by the Intergovernmental Panel on Climate Change due to the lack of comparative assessments of different electricity generation technologies addressing a wide range of environmental impacts and using a consistent set of methods. This paper contributes to filling this gap. A consistent set of life cycle inventories of a wide range of electricity generation technologies is assessed using the Recipe midpoint methods. The life-cycle inventory modeling addresses the production and deployment of the technologies in nine different regions. The analysis shows that even though low-carbon power requires a larger amount of metals than conventional fossil power, renewable and nuclear power leads to a reduction of a wide range of environmental impacts, while CO2 capture and storage leads to increased non-GHG impacts. Biomass has relatively modest co-benefits, if at all. The manufacturing of low-carbon technologies is important compared to their operation, indicating that it is important to choose the most desirable technologies from the outset. © 2017. This is the authors’ accepted and refereed manuscript to the article. LOCKED until 3.4.2019 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Thin-film photovoltaic (PV) technologies have improved significantly recently, and similar improvements are projected into the future, warranting reevaluation of the environmental implications of PV to update and inform policy decisions. By conducting a hybrid life cycle assessment using the most recent manufacturing data and technology roadmaps, we compare present and projected environmental, human health, and natural resource implications of electricity generated from two common thin-film PV technologies-copper indium gallium selenide (CIGS) and cadmium telluride (CdTe)-in the United States (U.S.) to those of the current U.S. electricity mix. We evaluate how the impacts of thin films can be reduced by likely cost-reducing technological changes: (1) module efficiency increases, (2) module dematerialization, (3) changes in upstream energy and materials production, and (4) end-of-life recycling of balance of system (BOS). Results show comparable environmental and resource impacts for CdTe and CIGS. Compared to the U.S. electricity mix in 2010, both perform at least 90% better in 7 of 12 and at least 50% better in 3 of 12 impact categories, with comparable land use, and increased metal depletion unless BOS recycling is ensured. Technological changes, particularly efficiency increases, contribute to 35-80% reductions in all impacts by 2030.