The sustainability transformation calls for policies that consider the global consequences of local lifestyles. We used stakeholders' visions of sustainable lifestyles across Europe to build 19 scenarios of sufficiency (net reductions) and 17 of green consumption (shift in consumption patterns). We applied Environmentally Extended Multi-Regional Input-Output analysis to model scenarios by assuming widespread adoption of the proposed lifestyles changes. Finally, we estimated the domestic and foreign implications for land, water, carbon and human toxicity potential. We distinguish the options with most potential from those that are seemingly fruitless or present backfire risks. While our method allows for testing a large number scenarios under a consistent framework, further work is needed to add robustness to the scenarios. However, we do find a range of indicative results that have strong potential to contribute to mitigation efforts. Services: We find that a local and sharing service economy has a maximum reduction potential of 18% of the European carbon footprint (CF). Clothing & Appliances: Sharing and extending lifetimes of clothes and devices could diminish CF by approximately 3%. Transport: Reducing motorized transport by remote work and active travel could mitigate between 9 and 26% of CF. Food: Vegan diets could spare 4% of the land and reduce up to 14% of CF. Bio-economy: Switching to biomaterials and bioenergy tend to reduce carbon and toxic emissions at the risk of increasing water and land use. Housing: Passive housing and decentralized renewable energy reduces carbon emissions up to 5 and 14%, respectively. We characterize the sensitivity of our results by modelling income rebound effects and confirm the importance of deterring expenditure in resource intensive goods.@en

Carbon capture and storage (CCS) is a potential key-technology to mitigate greenhouse gas (GHG) emissions as its use can lead to lower mitigation cost. However, research on other economic impacts of using CCS is scarce. In this paper, we look into economic upstream impacts of CCS use in terms of employment, Gross Value Added (GVA) and import dependency on the macro- and sector-level in Western Europe. We determine these impacts by a static comparison of two scenarios of power production with and without CCS (differences in energy efficiency investments between these scenarios were not accounted for). The two scenarios, both representing a stringent climate policy regime, were produced with the energy-system-simulation-model (TIMER) following the same emission profile until 2050. Data from the two scenarios were respectively implemented into a projected version of a global-multiregional IO-Model (EXIOBASE). Macro-level results suggest slightly higher gross employment, but lower Gross Value Added (GVA) (by 25%), and higher import dependency in the CCS-including scenario compared to the CCS-excluding scenario, given that biomass with CCS (BECCS) is available. Sector-level results show disproportionally higher differences between the scenarios in GVA and employment for some sectors compared to other sectors. Particularly, sectors providing fuels (here mostly bio-energy) have significantly higher GVA and employment in the CCS scenario. This study thus reveals interesting upstream economic effects, which can be linked to the technology choice. However, the exact quantitative results depend strongly on model assumptions. Results therefore need to be further explored in other models.@en

Purpose: Environmental life-cycle assessment (LCA) is broadly applied and recently social and economic LCA have emerged. However, the development of a general framework for social LCA is still at an early stage of development. The aims of this paper are to systematically discuss general considerations regarding social LCA, to build a consistent and operationalized framework for a number of indicators and to test the framework through application on a case study. Methods: The first step was to define the scope of the framework starting from a comprehensive review of concepts of social sustainability and social well-being, focusing on the conditions potentially affected by large-scale introduction of novel technologies. Secondly, main areas of concern for social well-being were defined. This resulted in the identification of four main areas of concern. The third step was to make an inventory of potential social indicators and select a number of indicators that could make the framework operational. Additionally, factors for weighting and normalization were developed. Results and discussion: The framework developed in this paper is based on four categories and 11 indicators and follows a life-cycle perspective. Six of the indicators are quantitative and are assessed using an input-output model linked to databases from the International Labour Organization. The remaining five indicators are qualitative indicators which are mapped using expert elicitation and a literature review. Identified concerns regarding the qualitative indicators are “flagged” and provided alongside the results of the quantitative assessment, which are aggregated into one single score by means of a weighted and normalized arithmetical mean. The paper illustrates the application of the methodology in a case study examining the deployment of carbon capture and storage technologies in Europe. Conclusions: The paper presents a framework that can be used to explore potential impacts on social well-being resulting from the large-scale implementation of novel technologies. The selection of a limited number of indicators (11) keeps the methodology simple and transparent. Although the framework provides a useful approach in allowing both quantitative or qualitative identification of potential areas of concern, the results remain highly explorative in nature. The inherent value-laden and context specific nature of social aspects remains one of the key challenges for developing a general applicable framework.@en

This paper shows the results of a sustainability assessment of deploying carbon capture and storage in European coal power plants in 2030, versus a scenario without CCS. The assessment examines potential impacts in five categories: impacts on human health, impacts on the natural environment, impacts on exhaustive resources, impacts on prosperity and impacts on social well-being. The analysis is undertaken in a prospective framework for the year 2030 under the economic scenarios which are based on the Blue map scenario of the IEA Energy Technology Perspectives.@en

This paper shows the results of a sustainability assessment of deploying carbon capture and storage in European coal power plants in 2030, versus a scenario without CCS. The assessment examines potential impacts in five categories: impacts on human health, impacts on the natural environment, impacts on exhaustive resources, impacts on prosperity and impacts on social well-being. The analysis is undertaken in a prospective framework for the year 2030 under the economic scenarios which are based on the Blue map scenario of the IEA Energy Technology Perspectives.@en

This paper shows the results of a sustainability assessment of deploying carbon capture and storage in European coal power plants in 2030, versus a scenario without CCS. The assessment examines potential impacts in five categories: impacts on human health, impacts on the natural environment, impacts on exhaustive resources, impacts on prosperity and impacts on social well-being. The analysis is undertaken in a prospective framework for the year 2030 under the economic scenarios which are based on the Blue map scenario of the IEA Energy Technology Perspectives.@en

This paper shows the results of a sustainability assessment of deploying carbon capture and storage in European coal power plants in 2030, versus a scenario without CCS. The assessment examines potential impacts in five categories: impacts on human health, impacts on the natural environment, impacts on exhaustive resources, impacts on prosperity and impacts on social well-being. The analysis is undertaken in a prospective framework for the year 2030 under the economic scenarios which are based on the Blue map scenario of the IEA Energy Technology Perspectives.@en