Methodological framework to find links between life cycle sustainability assessment categories and the UN Sustainable Development Goals based on literature

Life cycle sustainability assessment (LCSA) can be used as a tool to understand how products and operating systems can meet the United Nations’ Sustainable Development Goals (SDGs). However, existing linkages between SDGs and LCSA are limited and an analysis of coverage in literature is needed. In this paper, we propose a generic methodological framework establishing connections between LCSA categories at micro-level and SDGs at macro-level based on derivation from the literature. The qualitative heuristic research method developed builds on keyword literature search, bibliometric analysis, mapping, and narrative literature review for connection rationales. By using qualitative assessment levels, an assessment of linkages between LCSA categories and SDGs reveal that “technology development,” “public commitment to sustainability issues,” “access to material resources,” and “education provided in the local community” have the highest number of reported relationships with SDGs. Twenty-two LCSA categories were found with no direct/indirect connection with any SDG; reasons include absence of life cycle thinking perspective in SDGs and lack of sustainability-based discussion for workers, consumers, and value chain actors' stakeholder groups. Despite these gaps, the results provide new insights for industries looking to measure the contribution of their product systems along their life cycle in the context of SDGs supporting them to some extent, to select LCSA categories with either highest number of identified relationships to SDGs or that contribute to prioritized list of SDGs. The approach provides a starting point to improve transparency and consistency of reporting of sustainability performance of product systems by connecting LCSA to the global agenda for sustainable development.     

The Relevance of Circular Economy Practices to the Sustainable Development Goals

This paper identifies the extent to which circular economy (CE) practices are relevant for the implementation of the Sustainable Development Goals (SDGs). The results of a literature review and a matching exercise to determine the relationship between CE practices and SDG targets show that CE practices, potentially, can contribute directly to achieving a significant number of SDG targets. The strongest relationships exist between CE practices and the targets of SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 8 (Decent Work and Economic Growth), SDG 12 (Responsible Consumption and Production), and SDG 15 (Life on Land). The paper also explores synergies that can be created through CE practices among several of the SDG targets. Furthermore, it identifies several potential trade‐offs between targets for decent work, safe working environments, human health and current CE practices relating to recycling of municipal waste, e‐waste and wastewater, and provides suggestions how these can be overcome. The paper concludes that CE practices can be applied as a “toolbox” and specific implementation approaches for achieving a sizeable number of SDG targets. Further empirical research is necessary to determine which specific types of partnerships and means of implementation are required to apply CE practices in the SDG context.     

Quantity,Components, and Value of Waste Materials Landfilled in the United States

The current system of production and consumption needs end‐of‐life disposal to function, but the linkage between upstream production‐consumption with the downstream landfill as terminus is, at best, a tenuous, one‐way relationship, suggesting a partial system failure. A starting point to fix this link is to confront, systematically, the messy “black box” that is mixed waste landfilling, interrogate its contents locally, and determine a baseline that can be used to scale up results. Here, we develop a detailed model characterizing landfilled municipal solid waste (MSW) in the United States across the dimensions of material quantity, quality, location, and time. The model triangulates measurements spanning 1,161 landfills (representing up to 95% of landfilled MSW) and 15,169 solid waste samples collected and analyzed at 222 sites across the United States. We confirm that landfilled quantities of paper (63 million megagrams [Mg]), food waste (35 million Mg), plastic (32 million Mg, textiles (10 million Mg), and electronic waste (3.5 million Mg) are far larger than computed by previous top‐down U.S. government estimates. We estimate the cost of MSW landfill disposal in 2015 (10.7 billion U.S. dollars [USD]) and gross lost commodity value of recyclable material (1.4 billion USD). Further, we estimate landfill methane emissions to be up to 14% greater (mass basis) than the 2015 U.S. inventory. By principally relying on measurements of waste quantity and type that are recorded annually, the model can inform more effective, targeted interventions to divert waste materials from landfill disposal, improve local, regional, and national emission estimates, enhance dissipative loss estimates in material flow analyses, and illuminate the dynamics linking material, energy, and economic dimensions to production, consumption, and disposal cycles.     

农业废弃物养分循环利用技术模式评估模型的研究进展

农业废弃物的养分循环利用技术模式是实现农业循环经济的重要手段,其评估模型为优化养分循环利用技术提供了重要支撑。本文总结了农业废弃物养分循环技术模式评估框架、评估模型及评价指标、模型的数据源及其不确定性分析,以及模型应用尺度的研究进展。当前,常用于评估养分流动的模型主要是过程数学模型和产业生态学模型。过程数学模型和产业生态学模型在评估结果的可靠性和模拟尺度上存在较大差异,前者主要集中在实验室或中试规模,精度较高;后者可以实现从微观到宏观的多尺度模拟,数据的获取方式导致其具有较高的不确定性。最后,本文对农业废弃物养分循环利用技术评估模型的研究进行展望,提出为了在区域尺度上实现对农业生产系统废弃物资源化利用技术的准确评估,可以将过程数学模型与工业生态学模型相结合,建立可靠的模型框架和数据库,同时,在工厂、农场、村落、乡镇、区域等地理尺度进行模型拓展研究。     

A framework to open the black box of the use phase in circular economy life cycle assessments: The case of shell jacket reuse

Life cycle assessments of circular economy measures (CE LCA) of consumer products have been criticized for oversimplifying important aspects of the use phase such as user behavior and rebound effects, limiting our understanding of the environmental performance of circular economy measures. This study tests the usefulness of a framework designed to facilitate accounting for such aspects, by applying the framework to a case study of reuse of shell jackets enabled by “premium secondhand” outdoor stores. Methods for collecting use phase data were user surveys and interviews with store managers. Using the framework on this case study generated several novel insights which are interesting in themselves and as inputs to CE LCA. For instance, secondhand shell jackets have a significantly lower frequency of use during their first use span compared to the second and to shell jackets in the linear reference scenario. This implies that reuse in this case does not function as a mere use extension of otherwise similar use phases as is commonly assumed. The generation of such insights, which hitherto have been lacking in CE LCAs, points to the usefulness of the framework as a tool for opening the “black box” of the use phase in CE LCAs to improve understanding of the environmental performance of circular economy measures.     

Data representativeness in LCA: A framework for the systematic assessment of data quality relative to technology characteristics

A shortcoming in current data quality assessment schemes is that the data quality information is not used systematically to identify the critical data in a life cycle inventory (LCI) model. In addition, existing criteria employed to evaluate representativeness lack relevance to the specific context of a study. A novel framework is proposed herein for the evaluation of the representativeness of LCI data, including an analysis of the importance of the data and a modification of quality criteria based on unit process characteristics. Temporal characteristics are analyzed by identifying the technology shift, because data generated before this time are considered outdated. Geographical and technological characteristics are analyzed by defining a “related area” and a “related technology,” which is done by identifying a number of relevant geographical and technical factors, and then comparing the collected data with these factors. The framework was illustrated in a case study on household waste incineration in Denmark. The results demonstrated the applicability of the method in practice, and they provided data quality criteria unique to waste incineration unit processes, for example, different time intervals to evaluate temporal representativeness. However, the proposed method is time demanding, and thus sector‐level characteristic analyses are feasible instead of the user having to do the analyses.     

A review of methods to trace material flows into final products in dynamic material flow analysis: Comparative application of six methods to the United States and EXIOBASE3 regions,Part 2

Modeling pathways toward sustainable production and consumption requires improved spatio-temporal and material coverage of end-use product stocks. Momentarily, studies on inflow-driven, dynamic material flow analysis (dMFA) extrapolate scarce information on material end-use shares (i.e., ratios that split economy-wide material consumption to different end-use products) for single countries and years across longer time periods and global regions. Therefore, in part 1 of this work, we reviewed five methods to derive material end-use shares which use industry shipment data in physical units and monetary input–output tables (MIOTs). Herein, we comparatively apply these methods to the United States, drawing on detailed national data, as well as the multi-regional input–output model EXIOBASE3. To better match MIOT and dMFA system definitions, we propose the end-use transfer method, which re-routes specific intermediate outputs to final demand in MIOTs. In closing, we conclude on 12 points for improved end-use shares. We find mixed results regarding the fit between end-use shares derived from industry shipments and MIOTs: for detailed national data, we find good fit for some materials (e.g., aluminum), while others deviate strongly (e.g., steel). In many cases, the temporal trend of MIOT-derived end-use shares roughly agrees with industry shipments. For EXIOBASE3, we find good fit for some countries and materials, but substantial mismatches for others. Despite mixed results, combining MIOT-based end-use shares with industry shipments and auxiliary country-level data could enable improved temporal, geographical, and end-use resolution. However, the scarcity, documentation, and quality of input data are key limitations for more accurate and detailed end-use shares. This article met the requirements for a gold-gold data openness badge described at http://jie.click/badges .