Review and expert survey of allocation methods used in life cycle assessment of milk and beef

Purpose Beef and dairy production systems produce several by-products, such as fertilizers, bioenergy, hides, and pet foods, among which the environmental impacts arising from production should be allocated. The choice of allocation method therefore inevitably affects the results of life cycle assessment (LCA) for milk and beef. The aims of this study were to map out the different allocation methods used in dairy and beef LCA studies and to clarify the rationale for selecting a certain method. Methods A literature review was conducted to identify the different allocation methods used in LCA studies of milk and beef production and the products using beef by-products as a raw material. The justifications for the use of different methods in the studies were also collected. To map out the perspectives of LCA practitioners and further clarify the reasoning behind the use of certain allocation methods, a mixed method survey with quantitative questions and qualitative explanatory fields was sent to the authors included in the literature review. Results and discussion The literature review showed that the most commonly used allocation method between milk and meat was biophysical allocation, which is also the recommended method in LCA guidelines of milk production. Economic allocation was the second most common method, although the rationale for using economic allocation was weak. By-products, such as inedible body parts, were not considered in milk studies and were taken into account in only a small number of beef studies. This might be because most of the studies have cradle-to-farm gate system boundaries. According to the survey, a significantly higher share of LCA practitioners would allocate impacts also to these by-products. Conclusions The allocation is usually done between milk and meat, and other by-products are not taken into account. Since these materials are an unavoidable part of production and there are numerous uses for them, these outputs should be recognized as products and also taken into consideration in LCA studies.

Making the use of scenarios in LCA easier: the superstructure approach

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 common understanding of simplification approaches in published LCA studies—a review and mapping

Purpose This paper aims to investigate the common understanding of the variety of simplifications in LCA, by reviewing what simplification approaches are described in LCA and propose how these simplifications can be categorised. Such an overview can give guidance to researchers/practitioners as to how they should document simplifications and explain their implications to decision-makers. Methods The basis for this study is a systematic literature review of simplification approaches in LCA, including both previously published overviews of categories of LCA simplification approaches and LCA case studies using different simplification approaches. The PRISMA statement protocol (Moher et al. 2009) was used to minimise the risk of bias, increase scientific validity and provide guidelines for conducting the review. Results and discussion In all, ten categories of simplification were identified in the literature. Initially, six simplification approaches were identified based on previous categories. However, not all approaches found in case studies fit into these six previously published categories; these were therefore examined and grouped with regard to what was simplified and how, and four additional categories were identified. The identified simplification categories were mapped and explained in terms of their role in the different stages of the LCA framework. Our results support the idea that simplifications in LCA are most often motivated by a lack of data. Most simplifications target the inventory analysis step, with an aim to reduce the inventory analysis effort. Conclusions and recommendations There is a need for a common simplification terminology and reporting standard. As this study shows, the categories of simplification from early studies remain relevant despite the development in LCA over the years, but additional categories are needed to cover the different types of simplification being applied in LCAs. What this study also highlights is despite recommendations that have been around for decades, there is still a lack of clear documentation of simplification with consistent terminology. One way, to ensure more transparent documentation of simplified studies and to improve the ability to interpret them and compare results, could be to include the development of a communication standard, with clear terminology as well as investigation of the applicability of different simplification approaches for different product systems and application areas. Due to the wide variety of purposes, scenarios and products assessed, it is impossible to devise a one-size-fits-all approach for simplifications. LCA practitioners need to describe, explain and evaluate the simplifications used.

Reviewing ISO Compliant Multifunctionality Practices in Environmental Life Cycle Modeling

The standard ISO 14044:2006 defines the hierarchical steps to follow when solving multifunctionality issues in life cycle assessment (LCA). However, the practical implementation of such a hierarchy has been debated for twenty-five years leading to different implementation practices from LCA practitioners. The first part of this study discussed the main steps where the ISO hierarchy has been implemented differently and explored current multifunctionality practices in peer-reviewed studies. A text-mining process was applied to quantitatively assess such practices in the 532 multifunctional case studies found in the literature. In the second part of the study, citation network analysis (CNA) was used to identify the major publications that influenced the development of the multifunctionality-debate in LCA, i.e., the key-route main path. The identified publications were then reviewed to detect the origins of the different practices and their underlying theories. Based on these insights, this study provided some “food for thought” on current practices to move towards consistent methodology. We believe that such an advancement is urgently needed for better positioning LCA as a tool for sustainability decision-making. In particular, consistent allocation practices could be especially beneficial in bioeconomy sectors, where production processes are usually multifunctional, and where current allocation practices are not harmonized yet.

Archetypes of Goal and Scope Definitions for Consistent Allocation in LCA

The selection of an appropriate allocation procedure for co-production and recycling in Life Cycle Assessment (LCA) depends on the goal and scope of the analysis. However, it is not always clear when partitioning or system expansion can be applied, or when to conduct an attributional or a consequential LCA, both for LCA practitioners and users of LCA results. In this paper, the influence of the goal and scope on the selected modeling approaches is clarified. The distinction between process-oriented and product-oriented LCAs, between system expansion and substitution, and between the cut-off approach and other allocation procedures are highlighted. Archetypes of goal and scope definitions are developed. These archetypes reflect the minimum amount of information required to select an allocation procedure. It is demonstrated via an illustrative example that the question “what is the environmental impact of a product” can result in at least 15 different research questions requiring at least five different modeling methods. Finally, perspectives are provided on the use of attributional and consequential approaches to evaluate the environmental, social, and economic sustainability of products and processes.

A method for choosing adapted life cycle assessment indicators as a driver of environmental learning: a French textile case study

Despite alefforts for a sustainable production system, many companies are still struggling to implement environmental aspects in their daily product development processes. Among the evaluation and improvement methods, life cycle assessment (LCA) is one of the most popular tools to achieve this goal. Up to date, LCA has been applied to many products, services, and industrial systems to evaluate their environmental impact aspects. However, there is a wide range of indicators available to be applied for LCA, and choosing an inappropriate indicator may lead the product designer to achieve wrong and weak results. Therefore, this paper proposes to overcome this difficulty by developing a method that can be used as a knowledge transfer to product designers and LCA practitioners in order to help them to make the most appropriate choice of LCA indicators. This method should have some characteristics, such as (a) to be adaptable to a given context and (b) to be dynamic, scalable, and easy to learn. The purpose of this paper is to present the Evaluation Method for Choosing Indicator (EMCI) developed to facilitate the learning process of LCA methods and to quickly select their most appropriate indicators. To validate the EMCI method, a case study on a French textile industry has been implemented. The focus was to evaluate how LCA indicators and methods were chosen to be integrated into the suitable eco-design LCA tool.

Getting ready for PROPER and other policies: global learnings and key success factors for Indonesia

Indonesia introduced new policies, like PROPER, that require companies to develop LCA capacity. Currently, LCA expertise is still developing. Therefore, the question arises how the development of LCA expertise and a growth of LCA Practitioners can be achieved. In this article learnings and key success factors from global best practices are identified and illustrated based on case studies. The key success factors are 1) harmonization and guidance, 2) capacity building, 3) focus on business value and 4) ease of use. These Key Success Factors can give Indonesia and its LCA practitioners a head start in implementing and embedding LCA in policy implementation and compliance by private companies. Developing a program that provides the following six elements a) Introduction to LCA training, b) Training for managers and policy makers, c) Learning by doing with screening LCAs, d) Facilitate easy to use tools, e) Develop Product Category Rules (PCR) and f) Create a label or other verified report/certificate can accelerate the development of LCA expertise and the implementation of LCA practices.

Developing Adequate Communication of Waste Footprints of Products for a Circular Economy—A Stakeholder Consultation

Relatively few consumers are conscious of the waste generated in the course of producing the goods that they consume, although most are aware of the amount of waste they dispose of. This article reports on a small-scale survey (N = 28) among stakeholders aimed at developing adequate communication of preconsumer waste footprints of consumer goods in the context of the circular economy. Life cycle assessment (LCA) practitioners and consumers assessed five methodological details of an approach for calculating and communicating a product waste footprint (PWF). Most of the respondents expressed that the guidelines described in the proposed PWF methodology are good enough for the purposes of differentiating waste and byproducts, and defining which material flow shall be accounted for. Some LCA practitioners declared that the proposed streamlined method may not be adequate for conveying the environmental significance of waste types. The respondents also expressed that the PWF concept would be primarily useful and/or needed for consumers and government, and in the contexts of improving environmental awareness of consumers, environmental policy making, visualizing waste flows in a circular economy, and improving resource efficiency in industry, and less useful/needed in a business-to-business context. The PWF has been successfully used by diverse stakeholder groups in Sweden mostly to promote sustainable production and consumption across society. A notable example is the ‘invisible waste’ (#invisiblewaste) campaign of the Swedish Waste Management Association (Avfall Sverige). The concerns of the LCA experts have therefore not held true. The symbolic power and parsimony of the PWF concept appears to be effective in sensitizing consumers towards waste issues so that circular economy strategies beyond recycling are possible to be fully realized.

Structured evaluation of food loss and waste prevention and avoidable impacts: A simplified method

Interest in life-cycle assessment (LCA) for foodstuffs has increased over recent years. In the same period, there could also be noticed an increased focus on food losses and waste (FLW); hence the need for guidance or a method that assesses the environmental impacts of FLW when analyzing agrifood systems with the use of LCA. This study introduces a method of assessing FLW in the context of supply chain LCA through: i) calculating the impacts of the food supply chain with the associated FLW, in order to account for the overall environmental impacts; and ii) assessing the benefits of FLW prevention strategies. After the method is presented, a practical application follows. The results of this study show that this method is able to aid LCA practitioners to include FLW on their LCA for food studies so as not to underestimate the impacts. Furthermore, the method is able to aid decision makers to assess the benefits of implementing a FLW prevention action in comparison to a baseline scenario. This method has some limitations: the attributional approach, lack of guidelines on how to estimate prevention potentials, as well as lack of guidelines to estimate additional impacts due to prevention actions.

The Importance of Data Quality in Using LCA Approach as A Decision Supporting Tool: Comprative Case Study between Injection Moulding Machines in Processing Polypropylene

Indonesia is developing an awareness of life cycle perspective, where a product cannot only be analysed in a certain phase but shall be analysed throughout its life cycle. In developing this concept, the understanding of data quality in selecting and recording datasets is important. Many LCA practitioners often neglected the importance of understanding different types of datasets and tracking and documenting dataset. The objective of this paper is to understand the effect of technology coverage in data quality of Life cycle assessment (LCA) and the use of LCA approach as a decision supporting tool. A case study comparing two production methods of a product made of polypropylene (PP) is conducted. Injection moulding machines used in these two plants are different in terms of technology aspect. Comparison between injection moulding machines in these plants was conducted and actual data from the production site were gathered. SimaPro 8 by Pre Consultants is used for life cycle assessment of the machines. Two types of methods, i.e. TRACI and ReCipe, are used in impact assessment stage. The result implied that the technology difference shows significant variation of impact related to energy consumption between both plants. Therefore careful consideration must be taken when using and recording datasets to ensure suitability of the datasets for reuse.