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This paper analyses the impact of postponing global mitigation action on abatement costs and energy systems changes in China and India. It compares energy-system changes and mitigation costs from a global and two national energy-system models under two global emission pathways with medium likelihood of meeting the 2 °C target: a least-cost pathway and a pathway that postpones ambitious mitigation action, starting from the Copenhagen Accord pledges. Both pathways have similar 2010–2050 cumulative greenhouse gas emissions. The analysis shows that postponing mitigation action increases the lock-in in less energy efficient technologies and results in much higher cumulative mitigation costs. The models agree that carbon capture and storage (CCS) and nuclear energy are important mitigation technologies, while the shares of biofuels and other renewables vary largely over the models. Differences between India and China with respect to the timing of emission reductions and the choice of mitigation measures relate to differences in projections of rapid economic change, capital stock turnover and technological development. Furthermore, depending on the way it is implemented, climate policy could increase indoor air pollution, but it is likely to provide synergies for energy security. These relations should be taken into account when designing national climate policies.

Abstract Cost-effective achievement of the Paris Agreement’s long-term goals requires the unanimous phase-out of coal power generation by mid-century. However, continued investments in coal power plants will make this transition difficult. India is one of the major countries with significant under construction and planned increase in coal power capacity. To ascertain the likelihood and consequences of the continued expansion of coal power for India’s future mitigation options, we use harmonised scenario results from national and global models along with projections from various government reports. Both these approaches estimate that coal capacity is expected to increase until 2030, along with rapid developments in wind and solar power. However, coal capacity stranding of the order of 133–237 GW needs to occur after 2030 if India were to pursue an ambitious climate policy in line with a well-below 2 °C target. Earlier policy strengthening starting after 2020 can reduce stranded assets (14–159 GW) but brings with it political economy and renewable expansion challenges. We conclude that a policy limiting coal plants to those under construction combined with higher solar targets could be politically feasible, prevent significant stranded capacity, and allow higher mitigation ambition in the future.

AbstractIf transdisciplinary sustainability research is to contribute to sustainability transitions, issues of power dynamics need to be understood and accounted for. However, examples of concrete methods that put this into practice are sparse. This paper presents a conceptual and methodological framework that develops a better understanding of the power phenomenon, while providing actionable knowledge. By focussing on the context of social innovation in energy transitions, we demonstrate how different theoretical conceptualisations of power can be translated into a collaborative, transdisciplinary research design. In a facilitated process, researchers, policy workers and practitioners from diverse social innovation fields developed and tested the Transformative Power Lab approach and co-wrote a ‘Power Guide’ as a strategic exploration of power dynamics in sustainability transitions, specifically regarding social innovation in energy transitions. Based on the insights that emerged during this process, we discuss how transdisciplinary and action-oriented approaches in sustainability transition studies might benefit from this approach and, potentially, develop it further.

Abstract‘Environmental non-migration’ refers to the spatial continuity of an individual’s residence at the same place despite environmental risk. Moreover, this is a largely under-researched topic, especially within the climate change adaptation discourse, but is increasingly coming to the attention of scientists and policymakers for sustainable adaptation planning. So far, there exists hardly any conceptual and methodical guidelines to study environmental non-migration. Considering this research gap, this paper explores environmental non-migration based on the notion that factors of livelihood resilience can partly explain the decision to non-migration. Here, livelihood resilience is seen as an outcome of the interactions between societal and environmental conditions of an individual household. These conditions inform the decisions (to stay or to migrate) taken in case of a hazard or creeping environmental change. Their influence generalises the spectrum of migration decision-making (to stay or to migrate), which is conceptualised by four broad outcomes categorised into voluntary and involuntary, and non-migrants and migrants. This analytical concept is operationalised through an empirical example in southwest coastal Bangladesh. The results suggest that the Livelihood Resilience Index (LRI) relates to the voluntary nature of migration decisions once they are made. Still, only a household’s resilience cannot predict the decisions the household makes to stay or migrate. The paper concludes that the proposed analytical concept, with its exemplary factors, maybe an initial means to holistically explore migration decisions in the context of natural hazards and climate and environmental change. However, environmental non-migration remains complex and multi-faceted, and its assessment requires deeper examination at various scales.

Integrated assessment models (IAMs) are computer-based instruments used to assess the implications of human activity on the human and earth system. They are simultaneously also used to explore possible response strategies to climate change. As IAMs operate simplified representations of real-world processes within their model structures, they have been frequently criticised to insufficiently represent the opportunities and challenges in future energy systems over time. To test whether projections by IAMs diverge in systematic ways from projections made by technology experts we elicited expert opinion on prospective change for two indicators and compared these with the outcomes of IAM studies. We specifically focused on five (energy) technology families (solar, wind, biomass, nuclear, and carbon capture and storage or CCS) and compared the considered implications of the presence or absence of climate policy on the growth and diffusion of these technologies over the short (2030) to medium (2050) term. IAMs and experts were found to be in relatively high agreement on system change in a business-as-usual scenario, albeit with significant differences in the estimated magnitude of technology deployment over time. Under stringent climate policy assumptions, such as the internationally agreed upon objective to limit global mean temperature increase to no more than 2 °C, we found that the differences in estimated magnitudes became smaller for some technologies and larger for others. Compared to experts, IAM simulations projected a greater reliance on nuclear power and CCS to meet a 2 °C climate target. In contrast, experts projected a stronger growth in renewable energy technologies, particularly solar power. We close by discussing several factors that are considered influential to the alignment of the IAM and expert perspectives in this study.

This study assesses the socio-economic impacts in terms of value added, imports and employment of sugarcane-derived bioethanol production in Northeast (NE) Brazil. An extended inter-regional Input–Output (IO) model has been developed and is used to analyse three scenarios, all projected for 2020: a business-as-usual scenario (BaU) which projects current practices, and two scenarios that consider more efficient agricultural practices and processing efficiency (scenario A) and in addition an expansion of the sector into new areas (scenario B). By 2020 in all scenarios, value added and imports increase compared to the current situation. The value added by the sugarcane–ethanol sector in the NE region is 2.8 billion US$ in the BaU scenario, almost 4 billion US$ in scenario A, and 9.4 billion US$ in scenario B. The imports in the region will grow with 4% (BaU scenario), 38% (scenario A) and 262% (scenario B). This study shows that the large reduction of employment (114,000 jobs) due to the replacement of manual harvesting by mechanical harvesting can be offset by additional production and indirect effects. The total employment in the region by 2020 grows with 10% in scenario A (around 12,500 jobs) and 126% in scenario B (around 160,000 jobs). The indirect effects of sugarcane production in the NE are large in the rest of Brazil due to the import of inputs from these regions. The use of an extended inter-regional IO model can quantify direct and indirect socio-economic effects at regional level and can provide insight in the linkages between regions. The application of the model to NE Brazil has demonstrated significant positive socio-economic impacts that can be achieved when developing and expanding the sugarcane–ethanol sector in the region under the conditions studied here, not only for the NE region itself but also for the economy of the rest of Brazil.

The European Union (EU) is committed to reducing its greenhouse gas (GHG) emission levels by 80%–95% in 2050 compared to 1990 levels. Various approaches have been developed to secure and evaluate the progress made towards this objective. To gain insights into how EU Member States are aligning to this collective long-term objective, we systematically compare the planning and ex-ante evaluation processes for five EU countries (respectively Denmark, France, Germany, the Netherlands and the United Kingdom). The comparative analysis consists of a qualitative comparison of (1) the governance of long-term policy planning and evaluation processes, (2) the national arrangement for quantitative (model-based) ex-ante policy evaluation and (3) the national arrangement for qualitative ex-ante policy evaluation (stakeholder participation). In a second step we conduct a quantitative comparison of national model-based ex-ante evaluation studies to assess the relative differences between the considered routes and the differences across the various countries. Although the five Member States plan policies along the same EU objective, we find a high diversity in how long-term commitments are established, governed and evaluated on the national level. Model-based scenario analyses are commonly used to explore and evaluate the possible national routes towards the EU 2050 objective. However, as these processes mostly concentrate on domestic action, they pay little attention to how domestic policies are affected by, or affecting, other international activities throughout Europe. Hence, current findings suggest that cross-border collaboration and stakeholder participation could further strengthen the analytical understanding of required transformative change in Europe and subsequently lead to a more durable long-term solution over time.

Increasing the realism with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society since actors, decision-making, and institutions are the defining elements of transition pathways. In this paper, we explore how this can be done by conducting a model-based scenario analysis. The increasing focus on implementation and transition dynamics towards long-term objectives requires a better comprehension of what drives change and how those changes can be accelerated. We explore opportunities that arise from a deeper engagement of quantitative systems modeling with socio-technical transitions studies, initiative-based learning, and applied economics. We argue that a number of opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches.