The unique feature of the 2.-0 SDG framework is the use of sustainable wellbeing (utility) as a comprehensive summary indicator for all social, ecosystem and economic impacts. This indicator provides a single, quantitative endpoint for all causal impact pathways that have their starting point in the many different pressure (LCI) indicators, measurable at the level of specific production or consumption activities. Each pressure indicator is linked to the endpoint via the indicators for 169 targets of the 17 UN Sustainable Development Goals (SDGs). The endpoint is expressed in units of Quality-Adjusted person-Life-Years.
The comprehensive impact pathway framework can be applied to differentiate major from minor impact pathways, to identify impact pathways that are not explicitly covered by any of the 169 sustainability targets, and to point out trade-offs and synergies between the targets and their indicators. Due to the use of a single endpoint, the framework allows to quantify such trade-offs and synergies, to compare business decisions, performance and improvement options across industry sectors. Thereby, the 2.-0 LCSA framework contrasts with the “cherry-picking” approach to the SDGs in current business applications. Instead, we support a rational choice of business development strategies through matching the sphere of influence of each specific business enterprise with the impact pathway framework.
The project provides estimated uncertainty ranges on each of the causal links of the impact pathways, using numerical data when possible and verbal scales when numerical data are insufficient.
The project builds on and extends the impact assessment method developed by 2.-0 LCA consultants for social footprinting, which has been successfully tested for feasibility in global supply chain contexts, to support different business decisions, from single product purchases to larger policy changes, using a product life-cycle assessment approach to link specific company data to a global multi-regional input-output database with environmental and socio-economic extensions (see e.g. Schenker & Weidema 2017). The method has a low data requirement for screening purposes, and can be based exclusively on open data sources, with options for extending the level of detail when more data are available.
The project provides an actionable and rational method for businesses and governments to integrate the SDGs into decision making and monitoring, and will therefore contribute substantially to streamline and coordinate action and increase efficiency in implementing the 2030 Agenda.
Presentation of the project (9 min video on youtube): https://youtu.be/z8P6O5hP1rA
The project deliverables include:
Project members have early access to project deliverables. See below for deliverables that have already become open access.
The early development work was partly funded by the UNEP Life Cycle Initiative as part of the project “Linking the UN Sustainable Development Goals to life cycle impact pathway frameworks” and the EU Horizon project HyperCOG under grant agreement No.869886.
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Relative importance of sustainability impact pathways – A first rough assessment
Data collection guideline for pressure indicators for LCSA
Data files for Life Cycle SDG Assessment
This file provides the necessary impact data, links to SDG indicators, and a 2022 update of the Social Footprint method. The file also includes instructions for software implementation and guidance for performing a quantitative life cycle sustainability impact assessment, applying an impact pathway framework that links pressures from human activities via cause-effect chains to their impact on sustainable wellbeing.
The unique contribution of the current method is the use of sustainable wellbeing (utility, measured in Quality-Adjusted person-Life-Years, QALY) as a comprehensive summary indicator for all social, ecosystem and economic impacts. This allows to quantify trade-offs and synergies between impact categories, to compare business decisions, performance, and improvement options across industry sectors. By applying the exhaustive ‘capitals’ approach to defining the Areas of Protection, the method ensures comprehensiveness in terms the set of impact categories covered.
Data is in the form of a Zip file (27.4MB)
“Relative importance of sustainability impact pathways – A first rough assessment” provides guidance to focus the data collection and the development of further precision and accuracy of indicators and characterisation factors (linking the quantified impacts to their quantified causes) on the impact pathways that are of particularly high relative importance. This top-down assessment of importance is done by using Quality-Adjusted person-Life-Year (QALY) as a unit for sustainable wellbeing, informed by the annual UN measures of subjective wellbeing, and using the exhaustive classification of the so-called capital models as ‘Safeguard subjects’ to provide a structured and exhaustive account of the current impacts (estimated for year 2019) on each of the ‘Areas of Protection’, covering both instrumental values (productivity, value added, or income) and the intrinsic values of natural and manufactured assets, human capabilities, and social networks.
The report is prepared by Bo P. Weidema for the 2.-0 SDG Club and the UNEP Life Cycle Initiative as part of the project “Linking the UN Sustainable Development Goals to life cycle impact pathway frameworks”.
Data collection guideline for pressure indicators for Life Cycle based Sustainability Assessment” that covers the specific issues of each pressure category indicator (in LCA parlance called inventory indicators) in the above framework. The pressure category indicators are organised in groups, covering the triple bottom line of economic, ecosystem (resources and emissions), and social (mainly occupational) indicators that are relevant for data collection in the foreground system, i.e., the activities that are under direct control of a decision maker.
This guideline is prepared by Bo P. Weidema of 2.-0 LCA consultants, Denmark, for the 2.-0 SDG Club and the UNEP Life Cycle Initiative as part of the project “Linking the UN Sustainable Development Goals to life cycle impact pathway frameworks”.
We are grateful to UNEP Life Cycle Initiative and the following business members of the project for supporting the development:
• ArcelorMittal (corporate.arcelormittal.com)
• Corbion (Corbion.com)
• Janus (janus.co.jp)
• Novozymes (Novozymes.com)
The use of Semantic Web and linked data increases the possibility of data accessibility, interpretability, and interoperability. It supports cross-domain data and knowledge sharing and avoids the creation of research data silos. Widely adopted in several research domains, the use of the Semantic Web has been relatively limited with respect to sustainability assessments. A primary barrier is that the framework of the principles and technologies required to link and query data from the Semantic Web is often beyond the scope of industrial ecologists. Linking of a dataset to Semantic Web requires the development of a semantically linked core ontology in addition to the use of existing ontologies. Ontologies provide logical meaning to the data and the possibility to develop machine-readable data format. To enable and support the uptake of semantic ontologies, we present a core ontology developed specifically to capture the data relevant for life cycle sustainability assessment. We further demonstrate the utility of the ontology by using it to integrate data relevant to sustainability assessments, such as EXIOBASE and the Yale Stocks and Flow Database to the Semantic Web. These datasets can be accessed by the machine-readable endpoint using SPARQL, a semantic query language. The present work provides the foundation necessary to enhance the use of Semantic Web with respect to sustainability assessments. Finally, we provide our perspective on the challenges toward the adoption of Semantic Web technologies and technical solutions that can address these challenges.
The current global interest in circular economy (CE) opens an opportunity to make society’s consumption and production patterns more resource efficient and sustainable. However, such growing interest calls for precaution as well, as there is yet no harmonised method to assess whether a specific CE strategy contributes towards sustainable consumption and production. Life cycle assessment (LCA) is very well suited to assess the sustainability impacts of CE strategies. This position paper of the Life Cycle Initiative (hosted by UNEP) provides an LCA perspective on the development, adoption, and implementation of CE, while pointing out strengths and challenges in LCA as an assessment methodology for CE strategies.
This position paper provides an LCA perspective on the development, adoption, and implementation of CE, while pointing out strengths and challenges in LCA as an assessment technique for CE strategies.
The main objective of the LIFE-REthinkWASTE project is to endow municipalities with a “plug and play” governance scheme based on the PAYT (Pay As You Throw) and KAYT (Know As You Throw) paradigms to increase waste separation, reduce waste generation, and increase the effective recovery rates, whilst simultaneously reducing the average household waste bill. This objective will be tackled by adapting and re-addressing the waste management plans and other management/normative drivers (e.g., regulations, financial plans, and service contracts) according to a new paradigm in urban waste policy fares based on a combined approach of PAYT (supported by big data) and KAYT, and inspired by a novel social innovation approach.
A summary of the main results is available in this poster.
EU manufacturing companies are facing increasingly competitive and dynamic markets. To compete in the modern world, companies in the process industry need highly flexible manufacturing environments, capable of continuously adapting to changing conditions by means of advanced technologies and decision-making processes that take advantage of big data in real-time. Enterprises need to harness the knowledge held within their data streams to become more energy and resource-efficient while improving safety and lowering their environmental impact.
Cognitive manufacturing refers to a new manufacturing paradigm where machines are fully connected through wireless networks, monitored by sensors, and controlled by advanced computational intelligence to fine-tune product quality, optimise performance and sustainability, and reduce costs. Read more at http://www.hypercog.eu/ or at https://cordis.europa.eu/project/id/869886
A video giver a overview of the goals of the project, with the various project partners explaining the visions for the project: https://vimeo.com/859690816
