Search

Purpose Much progress has recently been made in modelling future background systems for LCA by including future scenario data, e.g. from Integrated Assessment Models (IAMs), into life cycle inventory (LCI) databases. A key problem is, however, that this yields potentially dozens of scenario LCI databases (i.e. LCI databases that represent different scenarios and reference years), instead of a single background database, which is very impractical for LCA modelling purposes. This paper proposes an approach to overcome this problem. Methods The approach consists of transforming all scenario LCI databases into a single superstructure database and an associated scenario difference file. The superstructure database is also a regular LCI database, but is constructed to contain all unique exchanges (elementary and intermediate flows) and processes that exist across all scenario LCI databases. The scenario difference file stores the differences between all scenarios and can be used to turn the superstructure into a specific scenario LCI database. This is very fast as it can be done in memory during LCA calculations. Results and discussion A key advantage of the superstructure approach is that a single LCI database can be used to represent different background systems. Therefore, the practitioner does not need to re-link a foreground system to multiple LCI databases, which is work-intensive and invites modelling errors. LCA results for all scenarios and reference years can be calculated automatically. We also illustrate how the superstructure approach has been implemented in the Activity Browser open source LCA software. Although this paper introduces the superstructure approach for background scenarios, it can also be used to model foreground scenarios, and even, as implemented in the Activity Browser, combinations of background and foreground scenarios. Finally, we briefly discuss further challenges that need to be addressed for a more widespread use of background scenarios in LCA. Conclusions The superstructure approach presents a practical solution for making the use of future background scenarios more wide-spread and, therefore, to overcome the problem of performing prospective LCA with temporally inconsistent foreground and background systems. The implementation in the Activity Browser makes the approach available for anyone and may serve as inspiration for other LCA software to implement the superstructure approach or a similar concept. While this may be an important technical milestone, additional coordination between data providers, scenario generators, LCA practitioners, and software developers will be required to further facilitate the use of background scenarios in prospective LCA studies.

The environmental benefits of low-carbon technologies, such as photovoltaic modules, have been under debate because their large-scale deployment will require a drastic increase in metal production. This is of concern because higher metal demand may induce ore grade decline and can thereby further intensify the environmental footprint of metal supply. To account for this interlinkage known as the “energy-resource nexus”, energy and metal supply scenarios need to be assessed in conjunction. We investigate the trends of future impacts of metal supplies and low-carbon technologies, considering both metal and electricity supply scenarios. We develop metal supply scenarios for copper, nickel, zinc, and lead, extending previous work. Our scenarios consider developments such as ore grade decline, energy-efficiency improvements, and secondary production shares. We also include two future electricity supply scenarios from the IMAGE model using a recently published methodology. Both scenarios are incorporated into the background database of ecoinvent to realize an integrated modeling approach, that is, future metal supply chains make use of future electricity and vice versa. We find that impacts of the modeled metal supplies and low-carbon technologies may decrease in the future. Key drivers for impact reductions are the electricity transition and increasing secondary production shares. Considering both metal and electricity scenarios has proven valuable because they drive impact reductions in different categories, namely human toxicity (up to −43%) and climate change (up to −63%), respectively. Thus, compensating for lower ore grades and reducing impacts beyond climate change requires both greener electricity and also sustainable metal supply. This article met the requirements for a Gold-Gold JIE data openness badge described at http://jie.click/badges.

The world is shifting to electric vehicles to mitigate climate change. Here, we quantify the future demand for key battery materials, considering potential electric vehicle fleet and battery chemistry developments as well as second-use and recycling of electric vehicle batteries. We find that in a lithium nickel cobalt manganese oxide dominated battery scenario, demand is estimated to increase by factors of 18–20 for lithium, 17–19 for cobalt, 28–31 for nickel, and 15–20 for most other materials from 2020 to 2050, requiring a drastic expansion of lithium, cobalt, and nickel supply chains and likely additional resource discovery. However, uncertainties are large. Key factors are the development of the electric vehicles fleet and battery capacity requirements per vehicle. If other battery chemistries were used at large scale, e.g. lithium iron phosphate or novel lithium-sulphur or lithium-air batteries, the demand for cobalt and nickel would be substantially smaller. Closed-loop recycling plays a minor, but increasingly important role for reducing primary material demand until 2050, however, advances in recycling are necessary to economically recover battery-grade materials from end-of-life batteries. Second-use of electric vehicles batteries further delays recycling potentials.

The building sector plays a key role in energy transition and carbon reduction while capturing the dynamic characteristics (e.g. materials, energy performance, and environmental impact) of building stock is a great challenge during the gradual process. This study presents a bottom-up dynamic building stock model that links dynamic material flow analysis with building energy modeling. The environmental impact of material and energy requirements is assessed by considering future electricity mix. The model is applied to evaluate the pathways to the climate-neutral energy supply of residential building stock in the Netherlands by 2050. Results show that space heating demand decreases by about 2/3 by 2050, while the energy for hot water increases to 92% of space heating demand. 80% of public grid electricity for appliances and lighting can be potentially substituted if rooftop photovoltaic (PV) systems are installed on 50% of renovated buildings and all the new buildings. Greenhouse gas (GHG) emissions of operational energy are reduced by approximately 60–90%, depending on the electricity mix. Annual GHG emissions from material production are not as important as those related to operational energy. Insulation materials account for a large proportion of the carbon footprint of material production. The model has a high spatial and temporal resolution and can be linked with local energy source availability (e.g. buildings or neighborhoods) to provide more accurate support for policymaking.

The Activity Browser is an open source software for advanced Life Cycle Assessment (LCA). The Activity Browser provides a graphical user interface (GUI) to the brightway LCA framework and makes common tasks such as managing projects and databases, modeling life cycle inventories, and analyzing LCA results easier and more intuitive. In addition, it provides advanced features for LCA modeling and data analyses and thus facilitates state-of-the-art LCA research. It can be extended to implement novel LCA modeling approaches and analyses as needed., Software Impacts, 3, ISSN:2665-9638

Summary The present article aims to determine the current carbon footprint (CF) of Zernez, a Swiss mountain village, and to identify reduction potentials of greenhouse gas (GHG) emissions. For this purpose, material and energy flows were assessed mainly based on detailed household surveys, interviews, and energy bills, but also by means of other information sources, for example, national statistics, traffic censuses, and literature values. To set up the GHG balance, special attention was paid to the consistent definition of system boundaries by adopting two fundamentally different perspectives: purely geographical accounting (PGA) and the consumption-based footprint (CBF) method. Each of these two perspectives total approximately 10 tonnes of carbon dioxide equivalents per capita per year. The PGA revealed that 70% of the direct emissions in Zernez are caused by agricultural activities, whereas no consumption area dominated the consumption-induced CF. For the identification of targeted measures, both perspectives were considered in a complementary manner. The building stock and its underlying energy supply system showed a GHG reduction potential of 80%. The building sector was thus detected as a reasonable first step for the municipality to adopt GHG mitigation strategies. In the case of Zernez, building-stock-related measures are predicted to decrease the current CF by 13% (CBF) and 17% (PGA), respectively.

Sustainable use of wood may contribute to coping with energy and material resource challenges. The goal of this study is to increase knowledge of the environmental effects of wood use by analyzing the complete value chain of all wooden goods produced or consumed in Switzerland. We start from a material flow analysis of current wood use in Switzerland. Environmental impacts related to the material flows are evaluated using life cycle assessment–based environmental indicators. Regarding climate change, we find an overall average benefit of 0.5 tonnes carbon dioxide equivalent per cubic meter of wood used. High environmental benefits are often achieved when replacing conventional heat production and energy‐consuming materials in construction and furniture. The environmental performance of wood is, however, highly dependent on its use and environmental indicators. To exploit the mitigation potential of wood, we recommend to (1) apply its use where there are high substitution benefits like the replacement of fossil fuels for energy or energy‐intensive building materials, (2) take appropriate measures to minimize negative effects like particulate matter emissions, and (3) keep a systems perspective to weigh effects like substitution and cascading against each other in a comprehensive manner. The results can provide guidance for further in‐depth studies and prospective analyses of wood‐use scenarios.

Summary Industrial ecology (IE) is a maturing scientific discipline. The field is becoming more data and computation intensive, which requires IE researchers to develop scientific software to tackle novel research questions. We review the current state of software programming and use in our field and find challenges regarding transparency, reproducibility, reusability, and ease of collaboration. Our response to that problem is fourfold: First, we propose how existing general principles for the development of good scientific software could be implemented in IE and related fields. Second, we argue that collaborating on open source software could make IE research more productive and increase its quality, and we present guidelines for the development and distribution of such software. Third, we call for stricter requirements regarding general access to the source code used to produce research results and scientific claims published in the IE literature. Fourth, we describe a set of open source modules for standard IE modeling tasks that represent our first attempt at turning our recommendations into practice. We introduce a Python toolbox for IE that includes the life cycle assessment (LCA) framework Brightway2, the ecospold2matrix module that parses unallocated data in ecospold format, the pySUT and pymrio modules for building and analyzing multiregion input-output models and supply and use tables, and the dynamic_stock_model class for dynamic stock modeling. Widespread use of open access software can, at the same time, increase quality, transparency, and reproducibility of IE research.

Cascading, the use of the same unit of a resource in multiple successional applications, is considered as a viable means to improve the efficiency of resource utilization and to decrease environmental impacts. Wood, as a regrowing but nevertheless limited and increasingly in demand resource, can be used in cascades, thereby increasing the potential efficiency per unit of wood. This study aims to assess the influence of cascading wood utilization on optimizing the overall environmental impact of wood utilization. By combining a material flow model of existing wood applications both for materials provision and energy production - with an algebraic optimization tool, the effects of the use of wood in cascades can be modelled and quantified based on life cycle impact assessment results for all production processes. To identify the most efficient wood allocation, the effects of a potential substitution of non-wood products were taken into account in a part of the model runs. The considered environmental indicators were global warming potential, particulate matter formation, land occupation and an aggregated single score indicator. We found that optimizing either the overall global warming potential or the value of the single score indicator of the system leads to a simultaneous relative decrease of all other considered environmental impacts. The relative differences between the impacts of the model run with and without the possibility of a cascading use of wood were 7% for global warming potential and the single score indicator, despite cascading only influencing a small part of the overall system, namely wood panel production. Cascading led to savings of up to 14% of the annual primary wood supply of the study area. We conclude that cascading can improve the overall performance of a wood utilization system. (C) 2015 Elsevier Ltd. All rights reserved.

The optimal size and location of bioenergy plants with regards to environmental and economic performance are assessed with a spatially explicit value chain model of the production of synthetic natural gas (SNG) from wood. It consists of several individual models for the availability, harvest, transportation, conversion of wood to SNG, electricity and heat, and the use of these products to substitute non-renewable energy services. An optimization strategy is used to choose the optimal technology configuration for plant sizes from 5 to 200 MW and different locations for any desired weighting between the environmental performance based on life cycle assessment (LCA) and the economic performance. While the economic optima are found at plant sizes between 100 and 200 MW, the environmental optima are found in the range of 5e40 MW. This trade-off can be minimized at plant sizes above 25 MW according to the presented model. The most important driver of the environmental performance is the efficient substitution of non-renewable energy, which is a site-specific factor. In comparison to this, spatial factors such as wood availability, harvest, and transportation, have a smaller influence on the environmental performance, at least for a country of the size of Switzerland. The main drivers of the economic performance are the revenues from the sale of the SNG plant’s products and the SNG production costs, but transportation and wood costs also play a role.

Purpose: The environmental performance of products or services is often a result of a number of key decisions that shape their life cycles (e.g., techology choices). This paper introduces a modular LCA approach that is capable of reducing the effort involved in performing scenario analyses and optimization when several key choices along a product’s value chain lead to many alternative life cycles. Methods: The main idea is that the value chain of a product can be divided into interconnected but exchangeable modules, which together represent a full life cycle. A module is comprised of unit processes from the practitioner’s LCI database. The inputs, outputs, and system boundaries of each module can be tailored to the context of the studied system. Alternatives arise whenever multiple modules produce substitutable products. Unlike in conventional LCI databases, no copies are necessary to represent the same process with different inputs. A module-product matrix is used to store this information. It can be used as a basis for an automated scenario analysis of all alternatives or as an input to an optimization model. Results and discussion: Our approach is illustrated in two case studies: (1) Passenger car fuel choices are modeled by 15 modules representing 33 alternative value chains for diesel, petrol, natural gas and electric cars. The automated comparison of LCA results indicates that electric mobility is often the preferable option from a climate perspective, but impacts depend strongly on the electricity source. (2) A dynamic optimization model including stocks is built from eight modules to analyze the optimal use of wood for material and energy applications. Results indicate that although direct substitution benefits are higher for energy applications, cascading use of wood can maximize environmental performance over the entire life cycle. Conclusions: The modular LCA approach permits an efficient modeling and comparison of alternative product life cycles, enabling practitioners to focus on key decisions. It can be applied to exploit a potential that is hidden in LCI databases, which is that they contain many specific inventories but not all useful combinations in the context of scenario analyses. The user-defined level of abstraction that is introduced through modules can be helpful in the communication of LCA results. The modular approach also facilitates the integration of LCA and optimization as well as other industrial ecology methods. An open source software is provided to enable others to apply and further develop our implementation of a modular LCA approach., The International Journal of Life Cycle Assessment, 21 (4), ISSN:0948-3349, ISSN:1614-7502

The optimal use of forest energy wood, industrial wood residues, waste wood, agricultural residues, animal manure, biowaste, and sewage sludge in 2010 and 2030 was assessed for Europe. An energy system model was developed comprising 13 principal fossil technologies for the production of heat, electricity, and transport and 173 bioenergy conversion routes. The net environmental benefits of substituting fossil energy with bioenergy were calculated for all approximately 1500 combinations based on life cycle assessment (LCA) results. An optimization model determines the best use of biomass for different environmental indicators within the quantified EU-27 context of biomass availability and fossil energy utilization. Key factors determining the optimal use of biomass are the conversion efficiencies of bioenergy technologies and the kind and quantity of fossil energy technologies that can be substituted. Provided that heat can be used efficiently, optimizations for different environmental indicators almost always indicate that woody biomass is best used for combined heat and power generation, if coal, oil, or fuel oil based technologies can be substituted. The benefits of its conversion to SNG or ethanol are significantly lower. For non-woody biomass electricity generation, transportation, and heating yield almost comparable benefits as long as high conversion efficiencies and optimal substitutions are assured. The shares of fossil heat, electricity, and transportation that could be replaced with bioenergy are also provided.

The conversion of wood to synthetic natural gas (SNG) via gasification and catalytic methanation is a renewable close to commercialization technology that could substitute fossil fuels and alleviate global warming. In order to assure that it is beneficial from the environmental perspective, a cradle to grave life cycle assessment (LCA) of SNG from a first-of-its-kind polygeneration unit for heating, electricity generation, and transportation was conducted. These SNG systems were compared to fossil and conventional wood reference systems and environmental benefits from their substitution evaluated. Finally, we conduct sensitivity analysis for expected technological improvements and factors that could decrease environmental performance. It is shown that substituting fossil technologies with SNG systems is environmentally beneficial with regard to global warming and for selected technologies also with regard to aggregated environmental impacts. On the condition that process heat is used efficiently, technological improvements such as increased efficiency and denitrification could further increase this advantage. On the other hand, lower GHG emissions and aggregated impacts are partly compensated by other environmental effects, e.g. eutrophication, ecotoxicity, and respiratory disease caused by inorganics. Since more efficient alternatives exist for the generation of heat and electricity from wood, it is argued that SNG is best used for transportation. In the light of a growing demand for renewable transportation fuels and commercial scale technological development being only in its initial stage, the production of SNG from wood seems to be a promising technology for the near future.

This paper analyzes the sustainable domestic biomass potential for bioenergy in Switzerland. Relevant biomass resources were selected based on expert interviews and literature analyses. A definition of technical and sustainable biomass potentials was developed. The technical and sustainable biomass potentials were then assessed based on technical and sustainability constraints. The sustainable potentials were further subdivided into the already energetically-used potential and the remaining biomass potential. Data was collected from the literature and supplementary interviews with field experts. Finally, the primary energy potential from biomass was calculated and compared to the current Swiss energy demand. We show that there is currently no sustainable potential for agricultural biomass, such as energy crops, crop residues and grass. On the other hand, there is a substantial potential from woody biomass, manure and waste biomass. The main constraints that limit the sustainable biomass potential are competing material utilizations, economic factors as well as the Swiss biofuels policy. Currently, 3.6% of Switzerland's energy demand is met by biomass resources, whereas the remaining potential could provide an additional 3.3%. Hence, with respect to a sustainable energy supply, bioenergy in Switzerland could cover a total share of 7%.

The goal of this study was to identify drivers of environmental impact and quantify their influence on the environmental performance of wooden and massive residential and office buildings. We performed a life cycle assessment and used thermal simulation to quantify operational energy demand and to account for differences in thermal inertia of building mass. Twenty-eight input parameters, affecting operation, design, material, and exogenic building properties were sampled in a Monte Carlo analysis. To determine sensitivity, we calculated the correlation between each parameter and the resulting life cycle inventory and impact assessment scores. Parameters affecting operational energy demand and energy conversion are the most influential for the building’s total environmental performance. For climate change, electricity mix, ventilation rate, heating system, and construction material rank the highest. Thermal inertia results in an average 2–6% difference in heat demand. Nonrenewable cumulative energy demand of wooden buildings is 18% lower, compared to a massive variant. Total cumulative energy demand is comparable. The median climate change impact is 25% lower, including end-of-life material credits and 22% lower, when credits are excluded. The findings are valid for small offices and residential buildings in Switzerland and regions with similar building culture, construction material production, and climate., Environmental Science & Technology, 49 (16), ISSN:0013-936X, ISSN:1520-5851

This paper presents a regionalized LCA-based multiobjective optimization model of building energy demand and supply for the case of a Swiss municipality for the minimization of greenhouse gas emissions and particulate matter formation. The results show that the environmental improvement potential is very large: in the optimal case, greenhouse gas emissions from energy supply could be reduced by more than 75% and particulate emissions by over 50% in the municipality. This scenario supposes a drastic shift of heat supply systems from a fossil fuel dominated portfolio to a portfolio consisting of mainly heat pump and woodchip incineration systems. In addition to a change in heat supply technologies, roofs, windows and walls would need to be refurbished in more than 65% of the municipality's buildings. The full potential of the environmental impact reductions will hardly be achieved in reality, particularly in the short term, for example, because of financial constraints and social acceptance, which were not taken into account in this study. Nevertheless, the results of the optimization model can help policy makers to identify the most effective measures for improvement at the decision making level, for example, at the building level for refurbishment and selection of heating systems or at the municipal level for designing district heating networks. Therefore, this work represents a starting point for designing effective incentives to reduce the environmental impact of buildings. While the results of the optimization model are specific to the municipality studied, the model could readily be adapted to other regions.

This study discusses the potential of applying agent-based modeling (ABM) to wood markets. A corresponding model of the wood market of a Swiss canton, consisting of a coupled roundwood and wood fuel market, is presented. The model includes wood-producing agents, such as public foresters and private forest owners, roundwood-consuming agents, such as sawmills, different classes of wood fuel consumers, and in-between wood traders. Other important model elements include agent interaction and negotiation, execution and scheduling structures, and agent adaptation mechanisms. Two sets of scenarios demonstrate the model's power for scenario exploration. The first set of scenarios analyzes the effects of an excess and scarce supply of wood on both markets. The second set looks for the optimal number of roundwood agents in the market from the perspective of the various stakeholders involved. Taking a more in-depth view of important design decisions and their pros and cons, this study argues that ABM offers new opportunities for the explorative study of wood markets as a result of these markets' special characteristics.

Life cycle assessment of wood energy: factors for high ecological benefits Wood energy is increasingly used to replace non-renewable energy sources. Energy wood is a limited resource and should therefore be used wisely not only to maximize the economic but also the environmental benefits associated with its use. This article assesses the environmental burdens associated with wood energy (for heat, electricity and transportation) and the benefits that may arise when non-renewable energy technologies are substituted. It is shown that from a global warming perspective the use of wood energy seems almost always beneficial, but this effect may be significantly reduced if biogenic CO2 is taken into account. The method of ecological scarcity on the other hand, which considers several additional environmental dimensions and combines these into a single score, shows significantly lower environmental benefits of wood in comparison with non- renewable energy. One of the principal reasons for this are air emissions associated with wood energy such as particulate matter, nitrogen oxides (NOx) and volatile organic carbon (VOC). Considerable environmental benefits can be achieved in both cases if the following three key factors are respected: 1) a wise choice of the substituted technology and the underlying energy carrier, 2) a high efficiency in the conversion from energy contained in biomass to final energy, and 3) the implementation of measures to reduce air emissions such as particle filters and, if possible, more advanced flue gas cleaning. The article then discusses the limits of the comparison and selected issues within the life cycle assessment methodology that need further development.

Bioenergy from woodfuel has a considerable potential to substitute fossil fuels and alleviate global warming. One issue so far not systematically addressed is the question of the optimal size of bioenergy plants with regards to environmental and economic performance. The aim of this work is to fill this gap by modeling the entire production chain of wood and its conversion to bioenergy in a synthetic natural gas plant both with respect to economic and environmental performance. Several spatially explicit submodels for the availability, harvest, transportation and conversion of wood were built and joined in a multi-objective optimization model to determine optimal plant sizes for any desired weighting of environmental impacts and profits. We find a trade-off between environmental and economic optimal plant sizes. While the economic optima range between 75 – 200 MW, the environmental optima are with 10 – 40 MW significantly smaller. Moreover, the economic optima are highly location specific and tend to be smaller if the biomass resource in the geographic region of the plant is scarcer. The results are robust with regards to the effect on global warming as well as with respect to the aggregated environmental impact assessment methods Ecoindicator ’99 and Ecological Scarcity 2006.

The quantities of e-waste are expected to increase sharply in Chile. The purpose of this paper is to provide a quantitative data basis on generated e-waste quantities. A material flow analysis was carried out assessing the generation of e-waste from computer equipment (desktop and laptop PCs as well as CRT and LCD-monitors). Import and sales data were collected from the Chilean Customs database as well as from publications by the International Data Corporation. A survey was conducted to determine consumers' choices with respect to storage, re-use and disposal of computer equipment. The generation of e-waste was assessed in a baseline as well as upper and lower scenarios until 2020. The results for the baseline scenario show that about 10,000 and 20,000 tons of computer waste may be generated in the years 2010 and 2020, respectively. The cumulative e-waste generation will be four to five times higher in the upcoming decade (2010-2019) than during the current decade (2000-2009). By 2020, the shares of LCD-monitors and laptops will increase more rapidly replacing other e-waste including the CRT-monitors. The model also shows the principal flows of computer equipment from production and sale to recycling and disposal. The re-use of computer equipment plays an important role in Chile. An appropriate recycling scheme will have to be introduced to provide adequate solutions for the growing rate of e-waste generation.

Purpose: Version 3 of ecoinvent includes more data, new modeling principles, and, for the first time, several system models: the “Allocation, cut-off by classification” (Cut-off) system model, which replicates the modeling principles of version 2, and two newly introduced models called “Allocation at the point of substitution” (APOS) and “Consequential” (Wernet et al. 2016). The aim of this paper is to analyze and explain the differences in life cycle impact assessment (LCIA) results of the v3.1 Cut-off system model in comparison to v2.2 as well as the APOS and Consequential system models. Methods: In order to do this, functionally equivalent datasets were matched across database versions and LCIA results compared to each other. In addition, the contribution of specific sectors was analyzed. The importance of new and updated data as well as new modeling principles is illustrated through examples. Results and discussion: Differences were observed in between all database versions using the impact assessment methods Global Warming Potential (GWP100a), ReCiPe Endpoint (H/A), and Ecological Scarcity 2006 (ES’06). The highest differences were found for the comparison of the v3.1 Cut-off and v2.2. At average, LCIA results increased by 6, 8, and 17 % and showed a median dataset deviation of 13, 13, and 21 % for GWP, ReCiPe, and ES’06, respectively. These changes are due to the simultaneous update and addition of new data as well as through the introduction of global coverage and spatially consistent linking of activities throughout the database. As a consequence, supply chains are now globally better represented than in version 2 and lead, e.g., in the electricity sector, to more realistic life cycle inventory (LCI) background data. LCIA results of the Cut-off and APOS models are similar and differ mainly for recycling materials and wastes. In contrast, LCIA results of the Consequential version differ notably from the attributional system models, which is to be expected due to fundamentally different modeling principles. The use of marginal instead of average suppliers in markets, i.e., consumption mixes, is the main driver for result differences. Conclusions: LCIA results continue to change as LCI databases evolve, which is confirmed by a historical comparison of v1.3 and v2.2. Version 3 features more up-to-date background data as well as global supply chains and should, therefore, be used instead of previous versions. Continuous efforts will be required to decrease the contribution of Rest-of-the-World (RoW) productions and thereby improve the global coverage of supply chains., The International Journal of Life Cycle Assessment, 21 (9), ISSN:0948-3349, ISSN:1614-7502