Environmental and economic impact of using new-generation wide-base tires

Purpose

New-generation wide-base tire (NG-WBT) is known for improving fuel economy and at the same time for potentially causing a greater damage to pavement. No study has been conducted to evaluate the net environmental saving of the combined system of pavements and NG-WBT. This study adopted a holistic approach (life cycle assessment [LCA] and life cycle costing [LCC]) to quantitatively evaluate the environmental and economic impact of using NG-WBT.

Methods

The net effect of different levels of market penetration of NG-WBT on energy consumption, global warming potential (GWP), and cost based on the fatigue cracking and rutting performance of two different asphalt concrete (AC) pavement structures was evaluated. The performance of pavements was determined based on pavement design lives; pavement surface characteristics, and pavement critical strain responses obtained from the artificial neural network (ANN) based on finite element (FE) simulations were used to calculate design lives of pavements. Based on the calculated design lives, life cycle inventory (LCI) and cost databases, and rolling resistance (RR) models previously developed by the University of Illinois at Urbana-Champaign (UIUC) were used to calculate the environmental and economic impact of the combined system.

Results and discussion

The fuel economy improvement using NG-WBT is 1.5% per axle. Scenario-based case studies were conducted. Considering 0% NG-WBT market penetration (or 100% standard dual tire assembly [DTA]) as a baseline, scenario 1 assumed the same fatigue and rutting potential between NG-WBT and DTA; therefore, the only difference came from fuel economy improvement of using NG-WBT. In scenario 2, pavement fatigue cracking potential determined the pavement design life; both thick and thin AC overlay sections experienced positive net environmental savings, but mixed net economic savings. In scenario 3, pavement rutting potential determined the pavement design life; the thick AC overlay section experienced positive net environmental savings, but mixed net economic savings. The thin section experienced negative net environmental and economic savings.

Conclusions

The outcomes of scenario-based case studies indicated that NG-WBT can result in significant savings in life cycle energy consumption and cost, and GWP; however, these benefits were sensitive to the method used to determine the pavement performance; especially, a small change in pavement strain can result in significant change in pavement life. In addition, the effect of fuel price/economy improvement, discount rate, and International Roughness Index (IRI) threshold values was studied in the sensitivity analyses.

     

Model uncertainty analysis using data analytics for life-cycle assessment (LCA) applications

Purpose

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.

Methods

Various 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 discussion

Results 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.

Conclusions

Investigating 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.

     

Designing hybrid life cycle assessment models based on uncertainty and complexity

Purpose

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.

Methods

This 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 Discussion

The 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.

Conclusion

The 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.

     

Process simulation and gate-to-gate life cycle assessment of hydrometallurgical refractory gold concentrate processing

Purpose

Currently, almost all cyanide-free gold leaching processes are still in the development stage. Proactively investigating their environmental impacts prior to commercialization is of utmost importance. In this study, a detailed refractory gold concentrate process simulation with mass and energy balance was built for state-of-the-art technology with (i) pressure oxidation followed by cyanidation and, compared to alternative cyanide-free technology, with (ii) pressure oxidation followed by halogen leaching. Subsequently, the simulated mass balance was used as life cycle inventory data in order to evaluate the environmental impacts of the predominant cyanidation process and a cyanide-free alternative.

Methods

The environmental indicators for each scenario are based on the mass balance produced with HSC Sim steady-state simulation. The simulated mass balances were evaluated to identify the challenges in used technologies. The HSC Sim software is compatible with the GaBi LCA software, where LCI data from HSC-Sim is directly exported to. The simulation produces a consistent life cycle inventory (LCI). In GaBi LCA software, the environmental indicators of global warming potential (GWP), acidification potential (AP), terrestrial eutrophication potential (EP), and water depletion (Water) are estimated.

Results and discussion

The life cycle assessment revealed that the GWP for cyanidation was 10.1 t CO₂-e/kg Au, whereas the halogen process indicated a slightly higher GWP of 12.6 t CO₂-e/kg Au. The difference is partially explained by the fact that the footprint is calculated against produced units of Au; total recovery by the halogen leaching route for gold was only 87.3%, whereas the cyanidation route could extract as much as 98.5% of gold. The addition of a second gold recovery unit to extract gold also from the washing water in the halogen process increased gold recovery up to 98.5%, decreasing the GWP of the halogen process to 11.5 t CO₂-e/kg Au. However, both evaluated halogen processing scenarios indicated a slightly higher global warming potential when compared to the dominating cyanidation technology.

Conclusions

The estimated environmental impacts predict that the development-stage cyanide-free process still has some challenges compared to cyanidation; as in the investigated scenarios, the environmental impacts were generally higher for halogen leaching. Further process improvements, for example in the form of decreased moisture in the feed for halide leaching, and the adaptation of in situ gold recovery practices in chloride leaching may give the cyanide-free processing options a competitive edge.

     

An integrated environment and cost assessment method based on LCA and LCC for mechanical product manufacturing

Purpose

The purpose of this study is to provide an integrated method to identify the resource consumption, environmental emission, and economic cost for mechanical product manufacturing from economic and ecological dimensions and ultimately to provide theoretical and data support of energy conservation and emission reduction for mechanical product manufacturing.

Methods

The applied research methods include environmental life cycle assessment (LCA) and life cycle cost (LCC). In life cycle environmental assessment, the inventory data are referred from Chinese Life Cycle Database and midpoint approach and EDIP2003 and CML2001 models of life cycle impact assessment (LCIA) are selected. In life cycle cost assessment, three cost categories are considered. The proposed environment and cost assessment method is based on the theory of social willingness to pay for potential environmental impacts. With the WD615 Steyr engine as a case, life cycle environment and cost are analyzed and evaluated.

Results and discussion

The case study indicates that, in different life cycle phases, the trend of cost result is generally similar to the environmental impacts; the largest proportion of cost and environmental impact happened in the two phases of “material production” and “component manufacturing” and the smallest proportion in “material transport” and “product assembly.” The environmental impact category of Chinese resource depletion potential (CRDP) accounted for the largest proportion, followed by global warming potential (GWP) and photochemical ozone creation potential (POCP), whereas the impacts of eutrophication potential (EP) and acidification potential (AP) are the smallest. The life cycle “conventional cost” accounted for almost all the highest percentage in each phase (except “material transport” phase), which is more than 80% of the total cost. The “environmental cost” and “possible cost” in each phase are relatively close, and the proportion of which is far below the “conventional cost.”

Conclusions

The proposed method enhanced the conventional LCA. The case results indicate that, in a life cycle framework, the environment and cost analysis results could support each other, and focusing on the environment and cost analysis for mechanical product manufacturing will contribute to a more comprehensive eco-efficiency assessment. Further research on the life cycle can be extended to phases of “early design,” “product use,” and “final disposal.” Other LCIA models and endpoint indicators are advocated for this environmental assessment. Environmental cost can also be further investigated, and the relevant social willingness to pay for more environmental emissions is advocated to be increased.

     

Reviewing the potential for including habitat fragmentation to improve life cycle impact assessments for land use impacts on biodiversity

Purpose

The biosphere is progressively subjected to a variety of pressures resulting from anthropogenic activities. Habitat conversion, resulting from anthropogenic land use, is considered the dominant factor driving terrestrial biodiversity loss. Hence, adequate modelling of land use impacts on biodiversity in decision-support tools, like life cycle assessment (LCA), is a priority. State-of-the-art life cycle impact assessment (LCIA) characterisation models for land use impacts on biodiversity translate natural habitat transformation and occupation into biodiversity impacts. However, the currently available models predominantly focus on total habitat loss and ignore the spatial configuration of the landscape. That is, habitat fragmentation effects are ignored in current LCIAs with the exception of one recently developed method.

Methods

Here, we review how habitat fragmentation may affect biodiversity. In addition, we investigate how land use impacts on biodiversity are currently modelled in LCIA and how missing fragmentation impacts can influence the LCIA model results. Finally, we discuss fragmentation literature to evaluate possible methods to include habitat fragmentation into advanced characterisation models.

Results and discussion

We found support in available ecological literature for the notion that habitat fragmentation is a relevant factor when assessing biodiversity loss. Moreover, there are models that capture fragmentation effects on biodiversity that have the potential to be incorporated into current LCIA characterisation models.

Conclusions and recommendations

To enhance the credibility of LCA biodiversity assessments, we suggest that available fragmentation models are adapted, expanded and subsequently incorporated into advanced LCIA characterisation models and promote further efforts to capture the remaining fragmentation effects in LCIA characterisation models.

     

Life cycle assessment of California unsweetened almond milk

Purpose

Plant-based alternatives to dairy milk have grown in popularity over the last decade. Almond milk comprises the largest share of plant-based milk in the US market and, as with so many food products, stakeholders in the supply chain are increasingly interested in understanding the environmental impacts of its production, particularly its carbon footprint and water consumption. This study undertakes a life cycle assessment (LCA) of a California unsweetened almond milk.

Methods

The scope of this LCA includes the production of almond milk in primary packaging at the factory gate. California produces all US almonds, which are grown under irrigated conditions. Spatially resolved modeling of almond cultivation and primary data collection from one almond milk supply chain were used to develop the LCA model. While the environmental indicators of greatest interest are global warming potential (GWP) and freshwater consumption (FWC), additional impact categories from US EPA’s TRACI assessment method are also calculated. Co-products are accounted for using economic allocation, but mass-based allocation and displacement are also tested to understand the effect of co-product allocation choices on results.

Results and discussion

The GWP and FWC of one 48 oz. (1.42 L) bottle of unsweetened almond milk are 0.71 kg CO₂e and 175 kg of water. A total of 0.39 kg CO₂e (or 55%) of the GWP is attributable to the almond milk, with the remainder attributable to packaging. Almond cultivation alone is responsible for 95% of the FWC (167 kg H₂O), because of irrigation water demand. Total primary energy consumption (TPE) is estimated at 14.8 MJ. The 48 oz. (1.42 L) PET bottle containing the almond milk is the single largest contributor to TPE (42%) and GWP (35%). Using recycled PET instead of virgin PET for the bottle considerably reduces all impact indicators except for eutrophication potential.

Conclusions

For the supply chain studied here, packaging choices provide the most immediate opportunities for reducing impacts related to GWP and TPE, but would not result in a significant reduction in FWC because irrigation water for almond cultivation is the dominant consumer. To provide context for interpretation, average US dairy milk appears to have about 4.5 times the GWP and 1.8 times the FWC of the studied almond milk on a volumetric basis.

     

Life cycle assessment of electrical and thermal energy systems for commercial buildings

Background, Aim and Scope The objective of this life cycle assessment (LCA) study is to develop LCA models for energy systems in order to assess the potential environmental impacts that might result from meeting energy demands in buildings. The scope of the study includes LCA models of the average electricity generation mix in the USA, a natural gas combined cycle (NGCC) power plant, a solid oxide fuel cell (SOFC) cogeneration system; a microturbine (MT) cogeneration system; an internal combustion engine (ICE) cogeneration system; and a gas boiler. Methods LCA is used to model energy systems and obtain the life cycle environmental indicators that might result when these systems are used to generate a unit energy output. The intended use of the LCA analysis is to investigate the operational characteristics of these systems while considering their potential environmental impacts to improve building design using a mixed integer linear programming (MILP) optimization model. Results The environmental impact categories chosen to assess the performance of the energy systems are global warming potential (GWP), acidification potential (AP), tropospheric ozone precursor potential (TOPP), and primary energy consumption (PE). These factors are obtained for the average electricity generation mix, the NGCC, the gas boiler, as well as for the cogeneration systems at different part load operation. The contribution of the major emissions to the emission factors is discussed. Discussion The analysis of the life cycle impact categories indicates that the electrical to thermal energy production ratio has a direct influence on the value of the life cycle PE consumption factors. Energy systems with high electrical to thermal ratios (such as the SOFC cogeneration systems and the NGCC power plant) have low PE consumption factors, whereas those with low electrical to thermal ratios (such as the MT cogeneration system) have high PE consumption factors. In the case of GWP, the values of the life cycle GWP obtained from the energy systems do not only depend on the efficiencies of the systems but also on the origins of emissions contributing to GWP. When evaluating the life cycle AP and TOPP, the types of fuel as well as the combustion characteristics of the energy systems are the main factors that influence the values of AP and TOPP. Conclusions An LCA study is performed to eraluate the life cycle emission factors of energy systems that can be used to meet the energy demand of buildings. Cogeneration systems produce utilizable thermal energy when used to meet a certain electrical demand which can make them an attractive alternative to conventional systems. The life cycle GWP, AP, TOPP and PE consumption factors are obtained for utility systems as well as cogeneration systems at different part load operation levels for the production of one kWh of energy output. Recommendations and Perspectives Although the emission factors vary for the different energy systems, they are not the only factors that influence the selection of the optimal system for building operations. The total efficiencies of the system play a significant part in the selection of the desirable technology. Other factors, such as the demand characteristics of a particular building, influence the selection of energy systems. The emission factors obtained from this LCA study are used as coefficients of decision variables in the formulation of an MILP to optimize the selection of energy systems based on environmental criteria by taking into consideration the system efficiencies, emission characteristics, part load operation, and building energy demands. Therefore, the emission factors should not be regarded as the only criteria for choosing the technology that could result in lower environmental impacts, but rather one of several factors that determine the selection of the optimum energy system. ESS-Submission Editor: Arpad Horvath (horvath@ce.berkeley.edu)     

Could the recycled yarns substitute for the virgin cotton yarns: a comparative LCA

Purpose

Cotton yarns spun from natural fibers are widely used in the apparel industry. Most of waste cotton goods are now disposed by incineration or landfill, which brings resource and environmental challenges to the society. Using the waste cotton to spin yarns is an alternative way to forward a more sustainable future. In this research, two scenarios for the environmental impacts of yarns spun from corresponding fibers are investigated, including recycled cotton fibers and virgin cotton fibers.

Methods

The life cycle assessment (LCA) has been conducted according to the collected data from on-site investigation of typical production factories. The life cycle for the recycled cotton yarn production is divided into five stages, i.e., raw material acquisition, transportation, breaking, mixing, and spinning. The life cycle of virgin cotton yarn production is been divided into four stages, i.e., raw material acquisition, transportation, mixing, and spinning. The functional unit is 1000 kg produced yarns which are used for weaving into the fabrics. Notable impacts on climate change, fossil depletion, water depletion, and human toxicity were observed.

Results

The life cycle impact assessment (LCIA) results show that environmental impacts of recycled cotton yarns are far less than those of virgin cotton yarns, except for climate change and water depletion. The reason is that the land occupation and irrigation water have great impact on environmental impacts of cotton cultivation. In spinning, the electricity is the key factor whose environmental impacts account for the most in the virgin cotton yarn scenario, while the electricity and water consumptions are the key factors for the recycled cotton yarn scenario in the life cycle of yarn production. The sensitivity analysis indicates that improving energy efficiency can significantly reduce environmental burdens for both the two scenarios. The uncertainty distribution of water depletion, human toxicity, fossil depletion, and climate change of the two scenarios were determined with a 90% confidence interval.

Conclusions

The LCIA results reveal recycled cotton yarn is a viable alternative to relieve resource and environmental pressure. About 0.5 ha of agricultural land can be saved, 6600 kg CO₂ eq can be reduced, and 2783 m³ irrigation water can be saved by using 1000 kg of the recycled cotton yarns. It can be concluded that the recycled cotton fibers can be served as a substitute for virgin cotton fibers to reduce agricultural land and avoid environmental impacts generated from the cotton planting.

     

Life cycle assessment-based selection of a sustainable lightweight automotive engine hood design

Purpose

This study presents a life cycle assessment (LCA)-based sustainable and lightweight automotive engine hood design and compares the life cycle energy consumption and potential environmental impacts of a steel (baseline) automotive engine hood with three types of lightweight design: advanced high strength steel (AHSS), aluminum, and carbon fiber.

Methods

A “cradle-to-grave” LCA including the production, use, and end-of-life stages is conducted in accordance with the ISO 14040/14044 standards. Onsite data collected by Chinese automotive companies in 2015 are used in the assessment. The Cumulative Energy Demand v1.09 method is applied to evaluate cumulative energy demand (CED), and the International Panel on Climate Change 2013 100a method is used to estimate global warming potential (GWP 100a).

Results and discussion

Among the different lightweight designs for the engine hood, the aluminum design is the most sustainable and has the lowest CED and GWP (100a) from a life cycle perspective, which is based on a lifetime driving distance of approximately 150,000 km. In addition, the AHSS design is also sustainable and lightweight. The carbon fiber design results in higher CED and GWP (100a) values than the steel (baseline) design during the life cycle but results in the largest CED and GWP (100a) savings through waste material recycling. The AHSS design exhibits the best break-even distance based on CED and GWP (100a) within 150,000 km.

Conclusions

Sensitivity analysis results show that the lifetime driving distance and material recycling rate have the largest impacts on the overall CEDs and GWPs of the three lightweight designs.

     

Environmental impacts of European trade: interpreting results of process-based LCA and environmentally extended input–output analysis towards hotspot identification

Purpose

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.

Methods

This 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 discussion

The 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.

Conclusions

The 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.

     

The environmental impact of packaging in food supply chains—does life cycle assessment of food provide the full picture?

Purpose

Due to the urgency and the magnitude of the environmental problems caused by food supply chains, it is important that the recommendations for packaging improvements given in life cycle assessment (LCA) studies of food rest on a balanced consideration of all relevant environmental impacts of packaging. The purpose of this article is to analyse the extent to which food LCAs include the indirect environmental impact of packaging in parallel to its direct impact. While the direct environmental impact of food packaging is the impact caused by packaging materials’ production and end-of-life, its indirect environmental impact is caused by its influence on the food product’s life cycle, e.g. by its influence on food waste and on logistical efficiency.

Methods

The article presents a review of 32 food LCAs published in peer-reviewed scientific journals over the last decade. The steps of the food product’s life cycle that contribute to the direct and indirect environmental impacts of packaging provide the overall structure of the analytical framework used for the review. Three aspects in the selected food LCAs were analysed: (1) the defined scope of the LCAs, (2) the sensitivity and/or scenario analyses and (3) the conclusions and recommendations.

Results and discussion

While in packaging LCA literature, there is a trend towards a more systematic consideration of the indirect environmental impact of packaging, it is unclear how food LCAs handle this aspect. The results of the review show that the choices regarding scope and sensitivities/scenarios made in food LCAs and their conclusions about packaging focus on the direct environmental impact of packaging. While it is clear that not all food LCAs need to analyse packaging in detail, this article identifies opportunities to increase the validity of packaging-related conclusions in food LCAs and provides specific recommendations for packaging-related food LCA methodology.

Conclusions

Overall, we conclude that the indirect environmental impact of packaging is insufficiently considered in current food LCA practice. Based on these results, this article calls for a more systematic consideration of the indirect environmental impact of packaging in future food LCAs. In addition, it identifies a need for more packaging research that can provide the empirical data that many food LCA practitioners currently lack. In particular, LCA practitioners would benefit if there were more knowledge and data available about the influence of certain packaging characteristics (e.g. shape, weight and type of material) on consumer behaviour.

     

Advances in application of machine learning to life cycle assessment: a literature review

Purpose

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.

Methods

In this study, previous research on ML for LCA were considered, and a literature review was undertaken.

Results

The 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.

Conclusions

The 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.

     

Comparative life cycle assessment of car disc brake systems—case study results and method discussion about comparative LCAs

Purpose

Two life cycle assessment (LCA) studies comparing a new low-particulate-matter-emission disc brake and a reference disc brake were presented. The purpose was to identify the difference in potential environmental impacts due to a material change in the new disc brake parts. Additionally, the validity was investigated for the simplification method of omitting identical parts in comparative LCA. This was done by comparing the results between the simplified and the full LCA model.

Methods

The two disc brakes, new disc brake and reference disc brake, were assessed according to the LCA ISO standards. The ReCiPe 2016 Midpoint (hierarchist) impact assessment method was chosen. Simplifying a comparative LCA is possible, all identical parts can be omitted, and only the ones that differ need to be assessed. In this paper, this simplification was called comparative LCA with an omission of identical parts.

Results and discussion

The comparative impacts were analysed over seventeen impact categories. The new disc brake alternative used more resources during the manufacture of one disc compared to the reference disc brake alternative. The shorter life length of the reference disc demanded a higher number of spare part discs to fulfil the same functional unit, but this impact was reduced due to material recycling. The new disc brake impacts were connected primarily to the coating and secondly to the pad manufacture and materials. The validity of the simplification method was investigated by comparing the results of the two LCA models. The impact differences were identical independent of the LCA model, and the same significant impact categories could be identified. Hence, the purpose of the study could be fulfilled, and the simplification was valid.

Conclusions

Both LCA models, simplified and full, revealed that the new disc brake had limited environmental advantages. The omission of identical parts made it more challenging to determine if an impact was significant or insignificant. The simplification seemed to be reasonable.

     

Effect of methodological choice on the estimated impacts of wool production and the significance for LCA-based rating systems

Purpose

One aim of LCA-based rating tools developed by the apparel industry is to promote a change in demand for textiles by influencing consumer preferences based on the environmental footprint of textiles. Despite a growing consensus that footprints developed using attributional LCA (aLCA) are not suitable to inform decisions that will impact supply and demand, these tools continue to use aLCA. This paper analyses the application of the LCA methods to wool production, specifically the application of aLCA methods that provide a retrospective assessment of impacts and consequential (cLCA) methods that estimate the impacts of a change.

Methods

Attributional and consequential life cycle inventories (LCIs) were developed and analysed to examine how the different methodological approaches affect the estimated environmental impacts of wool.

Results and discussion

Life cycle impact assessment (LCIA) of aLCI and cLCI for wool indicates that estimated global warming and water stress impacts may be considerably lower for additional production of wool, as estimated by cLCIA, than for current production as estimated by aLCIA. However, fossil resource impacts for additional production may be greater than for current production when increased wool production was assumed to displace dedicated sheep meat production.

Conclusions

This work supports the notion that the use of a retrospective assessment method (i.e. aLCA) to produce information that will guide consumer preferences may not adequately represent the impacts of a consumer’s choice because the difference between aLCIA and cLCIA results may be relatively large. As such, rating tools based on attributional LCA are unlikely to be an adequate indicator of the sustainability of textiles used in the apparel industry.

     

Environmental payback periods of reusable alternatives to single-use plastic kitchenware products

Purpose

Many consumers are transitioning away from single-use plastic products and turning to reusable alternatives. Oftentimes, this change is being made with the assumption that these alternatives have fewer environmental impacts; however, reusable products are frequently made from more environmentally intensive materials and have use phase impacts. This study used LCA to examine the GWP, water consumption, and primary nonrenewable energy use associated with reusable alternatives for single-use plastic kitchenware products and determined environmental payback periods.

Methods

The environmental impacts for each reusable alternative are calculated on the functional units of 1 use, 1 year (5 uses/week), and 5 years (5 uses/week). Payback periods are calculated for each reusable alternative and defined as the number of times a consumer must reuse an alternative in order for the environmental impact per use to be equivalent to the environmental impact for the single-use product. The research explored the sensitivity of the results to different consumer washing and reuse behaviors, as well as local conditions such as overall transportation distances and the carbon intensity of different electricity grids. Product types studied included straws (4 reusable, 2 single-use), sandwich storage (2 reusable, 3 single-use), coffee cups (3 reusable, 2 single-use), and forks (1 single-use, 3 reusable).

Results and discussion

Environmental impacts associated with the reusable alternatives were highly dependent on the use phase due to dishwashing, making payback period sensitive to washing frequency and method, and for GWP, carbon intensity of the energy grid (used for water heating). For single-use products, the material/manufacturing phase was the largest contributor to overall impacts. It was found that nine of the twelve reusable alternatives were able to breakeven in all three environmental indicators. The coffee cup product type was the only product type to have one reusable alternative, the ceramic mug, and have the shortest payback period for all three impact categories. Both the bamboo straw and beeswax wrap were unable to breakeven in any scenario due to high use phase impacts from manual washing.

Conclusions

The research found that reusable alternatives can payback the environmental impacts of GWP, water consumption, and energy use associated with their more resource intensive materials, but it is dependent on number of uses, consumer behavior, and for GWP, carbon intensity of the energy grid. A key takeaway is that consumer behavior and use patterns influence the ultimate environmental impact of reusable kitchenware products.

Recommendations

Some recommendations for consumers looking to reduce the overall impact of kitchenware products include the following:

1. 1)

   Not always assuming reusable is the best option.

2. 2)

   Extending product lifetime.

3. 3)

   Researching which reusable option has the lowest impact.

4. 4)

   Following best practice washing behaviors.

5. 5)

   Not washing products after every use.

6. 6)

   Advocating for integration of renewables into the local energy grid.

7. 7)

   Reducing consumption of these product types (reusable or single-use).

     

The environmental consequences of a change in Australian cotton lint production

Purpose

Changes in the production of Australian cotton lint are expected to have a direct environmental impact, as well as indirect impacts related to co-product substitution and induced changes in crop production. The environmental consequences of a 50% expansion or contraction in production were compared to Australian cotton production’s current environmental footprint. Both were then assessed to investigate whether current impacts are suitable for predicting the environmental impact of a change in demand for cotton lint.

Methods

A consequential life cycle assessment (LCA) model of Australian cotton lint production (cradle-to-gin gate) was developed using plausible scenarios regarding domestic regions and technologies affected by changes in supply, with both expansion (additional cotton) and contraction (less cotton) being modelled. Modelling accounted for direct impacts from cotton production and indirect impacts associated with changes to cotton production, including co-product substitution and changes to related crops at regional and global scales. Impact categories assessed included climate change, fossil energy demand, freshwater consumption, water stress, marine and freshwater eutrophication, land occupation and land-use change.

Results and discussion

For both the expansion and contraction scenarios, the changes to climate change impacts (including iLUC) and water impacts were less than would be assumed from current production as determined using attributional LCA. However, the opposite was true for all other impact categories, indicating trade-offs across the impact categories. Climate change impacts under both scenarios were relatively minor because these were largely offset by iLUC. Similarly, under the contraction scenario, water impacts were dominated by indirect impacts associated with regional crops. A sensitivity analysis showed that the results were sufficiently robust to indicate the quantum of changes that could be expected.

Conclusions

A complex array of changes in technologies, production regions and related crops were required to model the environmental impacts of a gross change in cotton production. Australian cotton lint production provides an example of legislation constraining the direct water impacts of production, leading to a contrast between impacts estimated by attributional and consequential LCA. This model demonstrated that indirect products and processes are important contributors to the environmental impacts of Australian cotton lint.

     

Screening LCA of torrent control structures in Austria

Purpose

The purpose of this article is to find a suitable life cycle assessment (LCA) method to quantify the most important environmental burdens caused by construction processes of torrent control structures. To find these environmental burdens, 17 construction projects of the “Austrian Service for Torrent and Avalanche Control” (WLV) were analyzed using the “cradle to gate with options” LCA methodology (CEN, 2013).

Methods

This article explains an LCA methodology for the product stage and the construction process of torrent control structures following existing standards. The iterative approach of LCA methodology (ISO, 2006a) was used to record all important processes of the system and to supplement missing information. The LCA methodology has been developed from existing standards of the construction and product sector. Since the production of some construction materials takes place locally, the generic data, for Austria, was adapted. Wood inherent biogenic carbon and primary energy, used as raw material, are treated as materials inherent properties (CEN, 2014). The contribution of the various processes was reproduced by hotspot.

Results and discussion

Hotspots of the different stages are related to the construction materials used. The emissions and primary energy inputs in the product stage are clearly dominated by concrete and steel. If these two materials are used sparingly, the focus is on machine application and transportation. Depending on the selected scenarios, the smallest share of emissions, in relation to the total result of product and construction stage emitted by transport, is 3% and the maximum share is 69%. The greatest environmental impacts in the construction stage are caused by excavation work and transportation on-site. With an average of 4% in the construction stage, the transport of workers to the construction site cannot be neglected as is done in the building sector.

Conclusions

The conclusion of this study is that existing LCA models can be adapted to protective structures. In contrast to conventional buildings, the construction process and transportation are much more important and cannot be neglected. Shifting the hotspots to these processes requires specific calculation rules for that particular field. There is still a need for research to find a suitable functional unit and to develop a methodology for the use and end of life stage of these structures.

     

Energy simulation and LCA for macro-scale analysis of eco-innovations in the housing stock

Purpose

Energy consumption of buildings is one of the major drivers of environmental impacts. Life cycle assessment (LCA) may support the assessment of burdens and benefits associated to eco-innovations aiming at reducing these environmental impacts. Energy efficiency policies however typically focus on the meso- or macro-scale, while interventions are typically taken at the micro-scale. This paper presents an approach that bridges this gap by using the results of energy simulations and LCA studies at the building level to estimate the effect of micro-scale eco-innovations on the macro-scale, i.e. the housing stock in Europe.

Methods

LCA and dynamic energy simulations are integrated to accurately assess the life cycle environmental burdens and benefits of eco-innovation measures at the building level. This allows quantitatively assessing the effectiveness of these measures to lower the energy use and environmental impact of buildings. The analysis at this micro-scale focuses on 24 representative residential buildings within the EU. For the upscaling to the EU housing stock, a hybrid approach is used. The results of the micro-scale analysis are upscaled to the EU housing stock scale by adopting the eco-innovation measures to (part of) the EU building stock (bottom–up approach) and extrapolating the relative impact reduction obtained for the reference buildings to the baseline stock model. The reference buildings in the baseline stock model have been developed by European Commission-Joint Research Centre based on a statistical analysis (top–down approach) of the European housing stock. The method is used to evaluate five scenarios covering various aspects: building components (building envelope insulation), technical installations (renewable energy), user behaviour (night setback of the setpoint temperature), and a combined scenario.

Results and discussion

Results show that the proposed combination of bottom–up and top–down approaches allow accurately assessing the impact of eco-innovation measures at the macro-scale. The results indicate that a combination of policy measures is necessary to lower the environmental impacts of the building stock to a significative extent.

Conclusions

Interventions addressing energy efficiency at building level may lead to the need of a trade-off between resource efficiency and environmental impacts. LCA integrated with dynamic energy simulation may help unveiling the potential improvements and burdens associated to eco-innovations.