This chapter introduces an interdisciplinary perspective to investigate the transition process and to identify empirical evidence of social-ecological tipping points (SETPs) in the case studies on coal and carbon intensive regions (CCIRs) analyzed in the project TIPPING+. The interdisciplinary lens considers different modes of thought, frameworks, and multiple perspectives and interests from diverse stakeholders, a systems’ understanding, and different culture considerations across the CCIRs. Within this interdisciplinary process, we applied various lenses to study the potential for SETPs by combining insights from human geography, social psychology, regional socio-technical systems, and political economy perspectives on the phases of low carbon transitions and on the justice component of the transitions. Subsequently, this chapter gives an overview of how the eight CCIRs case studies in this book have applied various interdisciplinary lenses to investigate the regional transition and the emergence of SETPs.

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A crucial task to accelerate global decarbonisation is to understand how to enable fast, equitable, low-carbon transformations in Coal and Carbon Intensive Regions (CCIRs). In this early literature review we underlined the relevance of the boundary concept of social-ecological tipping points (SETPs) and showed that the research and policy usage of SETPs applied to accelerate structural regional sustainability transformations faces three key challenges: (I) integrating theoretical and empirical contributions from diverse social and ecological sciences, together with complexity theory (II) designing open transdisciplinary assessment processes able to represent multiple qualities of systemic change and enable regionally situated transformative capacities, and (III) moving away from one-directional metaphors of social change, or static or homogeneous conceptions of individual agency and single equilibrium in energy transitions; and instead, focus on understanding the conditions and capacities for the emergence of systemic transformations and regenerative processes across multiple levels and forms of agency. We refer to these complex and place-situated processes as learning to enable regional transformative emergence.

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The rapid uptake of renewable energy technologies in recent decades has increased the demand of energy researchers, policymakers and energy planners for reliable data on the spatial distribution of their costs and potentials. For onshore wind energy this has resulted in an active research field devoted to analysing these resources for regions, countries or globally. A particular thread of this research attempts to go beyond purely technical or spatial restrictions and determine the realistic, feasible or actual potential for wind energy. Motivated by these developments, this paper reviews methods and assumptions for analysing geographical, technical, economic and, finally, feasible onshore wind potentials. We address each of these potentials in turn, including aspects related to land eligibility criteria, energy meteorology, and technical developments of wind turbine characteristics such as power density, specific rotor power and spacing aspects. Economic aspects of potential assessments are central to future deployment and are discussed on a turbine and system level covering levelized costs depending on locations, and the system integration costs which are often overlooked in such analyses. Non-technical approaches include scenicness assessments of the landscape, constraints due to regulation or public opposition, expert and stakeholder workshops, willingness to pay/accept elicitations and socioeconomic cost-benefit studies. For each of these different potential estimations, the state of the art is critically discussed, with an attempt to derive best practice recommendations and highlight avenues for future research.

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The authors wish to point out a typesetting error in Equation (1) of the above paper, published as [1] in this journal. An addition sign “+” was mistakenly replaced with a multiplication sign “∙” in this equation, as shown in Equation (1a) below. [Formula presented] There correct version of this equation is given in Equation (1b): [Formula presented]where n is the lifetime of the technology, I0 the investment [$], Mt the annual costs in year t [$/year], Et energy produced in year t [MWh/year] and i the interest rate. The authors apologise for any inconveince caused. This minor error has no implications for the validity of the conclusions and recommendations presented in section 6 of the original paper.@en

The history of concentrating solar power (CSP) is characterized by a boom-bust pattern caused by policy support changes. Following the 2014–2016 bust phase, the combination of Chinese support and several low-cost projects triggered a new boom phase. We investigate the near- to mid-term cost, industry, market and policy outlook for the global CSP sector and show that CSP costs have decreased strongly and approach cost-competitiveness with new conventional generation. Industry has been strengthened through the entry of numerous new companies. However, the project pipeline is thin: no project broke ground in 2019 and only four projects are under construction in 2020. The only remaining large support scheme, in China, has been canceled. Without additional support soon creating a new market, the value chain may collapse and recent cost and technological advances may be undone. If policy support is renewed, however, the global CSP sector is prepared for a bright future.@en

The European potential for renewable electricity is sufficient to enable fully renewable supply on different scales, from self-sufficient, subnational regions to an interconnected continent. We not only show that a continental-scale system is the cheapest, but also that systems on the national scale and below are possible at cost penalties of 20% or less. Transmission is key to low cost, but it is not necessary to vastly expand the transmission system. When electricity is transmitted only to balance fluctuations, the transmission grid size is comparable to today's, albeit with expanded cross-border capacities. The largest differences across scales concern land use and thus social acceptance: in the continental system, generation capacity is concentrated on the European periphery, where the best resources are. Regional systems, in contrast, have more dispersed generation. The key trade-off is therefore not between geographic scale and cost, but between scale and the spatial distribution of required generation and transmission infrastructure.@en

A recent article in this journal claimed to assess the socio-technical potential for onshore wind energy in Europe. We find the article to be severely flawed and raise concerns in five general areas. Firstly, the term socio-technical is not precisely defined, and is used by the authors to refer to a potential that others term as merely technical. Secondly, the study fails to account for over a decade of research in wind energy resource assessments. Thirdly, there are multiple issues with the use of input data and, because the study is opaque about many details, the effect of these errors cannot be reproduced. Fourthly, the method assumes a very high wind turbine capacity density of 10.73 MW/km2 across 40% of the land area in Europe with a generic 30% capacity factor. Fifthly, the authors find an implausibly high onshore wind potential, with 120% more capacity and 70% more generation than the highest results given elsewhere in the literature. Overall, we conclude that new research at higher spatial resolutions can make a valuable contribution to wind resource potential assessments. However, due to the missing literature review, the lack of transparency and the overly simplistic methodology, Enevoldsen et al. (2019) potentially mislead fellow scientists, policy makers and the general public.@en

There is a large literature suggesting that improvements in energy efficiency support efforts at climate mitigation. Addressing a conceptual gap in that literature, however, we evaluate whether there are any conditions under which policies to promote improvements in energy efficiency could be counterproductive to efforts to limit climate change to 1.5 °C global warming from pre-industrial times. We identify three conditions under which this could be the case. The first condition is if policies for energy efficiency have a political opportunity cost, in terms of crowding out or delaying policies aimed at decarbonizing energy supply. There is an extensive literature in the fields of political science and policy studies to suggest that this is possible, but there have been no studies examining whether it has actually happened or is likely to happen in the future. The second condition is if investments in energy efficiency improvements come at a higher cost, per unit of fossil energy avoided, than do investments in new renewable energy supply. Current cost estimates suggest that there are some energy efficiency investments for which this is the case, but it is difficult to predict whether this will remain the case in the future. The third condition is if policies for energy efficiency, or specific investments in energy efficiency, were to delay the complete decarbonization of energy supply by more than some critical value. We show that critical delay is quite short—measured in weeks to months—in the case of a 1.5 °C temperature target, assuming constrained availability of negative emission technologies. It is impossible to say whether any of these conditions is likely, but in theory, each of them would appear to be possible.@en

After three years of low growth and an increase in global costs, the announcement and implementation of the Chinese demonstration programme for concentrating solar power (CSP) has changed the outlook for the technology from gloomy to better than ever. Here, we analyse the Chinese CSP strategy, its drivers, and its effects on CSP industry and costs in China and globally. We find that the Chinese demonstration programme has led to the emergence of new CSP industry actors, and that it helped to the reduce global average costs of new CSP stations to USD 0.12 per kWh. However, the Chinese expansion, which is supplied almost exclusively by Chinese companies, follows a wholly different cost trajectory than the expansion in the rest of the world, which is almost exclusively served by non-Chinese companies: whereas costs in both markets have decreased, the cost of Chinese CSP stations under construction is 40% lower than that of plants built elsewhere. We conclude that the Chinese support programme has thus succeeded in its central aims of leapfrogging and has built up a domestic industry capable of building stations and most components at lower costs than foreign competitors. However, Chinese companies are not yet active outside China, nor do we find many foreign participants in the Chinese market. The effects of the Chinese CSP programme on markets and industries outside China have thus far been limited: the Chinese and non-Chinese markets currently largely exist in parallel, each with their own supply chains. Whether the new Chinese companies seek to and manage to conquer the global market as well remains to be seen but so far, they have not.@en

In the version of this Analysis originally published, the total learning rate for parabolic trough stations with 6–8 hours of thermal storage (Fig. 2b) was calculated to be 25%. After publication, the authors found a code error that caused the learning curve fit function to believe that the first station in the dataset was marked as 1 GW and not 0 GW. As a result, the estimated learning rates for the complete timespan were too high. The correct learning rates should be 2.7% for Fig. 2a and 6.8% for Fig. 2b (instead of 5.2% and 25.2%, respectively). These learning rate fit curves have been updated and the captions have been corrected. For consistency with Fig. 2a, a fit for 2011–2017 has been added to Fig. 2b, showing a learning rate of 17.5% (R2 = 0.337). The text has been modified in the abstract and the sections ‘Observed investment cost development and learning rates’, ‘Policy regime impacts on cost development’ and ‘Conclusions’ to reflect the quantitative changes to the learning rates. Supplementary Notes 1, 3 and 4 and Supplementary Figs. 2, 6 and 7 and their captions have also been updated to reflect the new learning rates. In the caption of Supplementary Fig. 2b, “(2008–2017 learning rate=0.21, R2=0.468)” has been changed to “(2008–2017 learning rate=0.06, R2=0.513; 2011–2017 learning rate=0.079, R2=0.072)”. In the caption of Supplementary Fig. 6b, “(2008–2017 learning rate=0.289, R2=0.715)” has been changed to “(2008–2017 learning rate=0.077, R2=0.631; 2011–2017 learning rate=0.225, R2=0.498)”. In the caption of Supplementary Fig. 7, “(a) parabolic trough (PT) stations with <1 hour thermal storage (2011–2014 learning rate=0.297, R2=0.972 (US$) and learning rate=0.27, R2=0.909 (€)); and (b) PT stations with 6–8 hours of thermal storage (2008–2017 learning rate=0.252, R2=0.621 (US$) and learning rate=0.138, R2=0.502 (€))” has been changed to “(a) parabolic trough (PT) stations with <1 hour thermal storage (2011–2014 learning rate=0.297, R2=0.972 (US$) and 2011–2014 learning rate=0.27, R2=0.909 (€)); and (b) PT stations with 6-8 hours of thermal storage (2011–2017 learning rate=0.175, R2=0.337 (US$) and 2011–2017 learning rate=0.072, R2=0.149 (€))”. The underlying data were correct as originally published and remain unchanged.@en

Because solar and wind resources are available throughout Europe, a transition to an electricity system based on renewables could simultaneously be a transition to an autarkic one. We investigate to which extent electricity autarky on different levels is possible in Europe, from the continental, to the national, regional, and municipal levels, assuming that electricity autarky is only possible when the technical potential of renewable electricity exceeds local demand. We determine the technical potential of roof-mounted and open field photovoltaics, as well as on- and offshore wind turbines through an analysis of surface eligibility, considering land cover, settlements, elevation, and protected areas as determinants of eligibility for renewable electricity generation. In line with previous analyses we find that the technical-social potential of renewable electricity is greater than demand on the European and national levels. For subnational autarky, the situation is different: here, demand exceeds potential in several regions, an effect that is stronger the higher population density is. To reach electricity autarky below the national level, regions would need to use very large fractions or all of their non-built-up land for renewable electricity generation. Subnational autarky requires electricity generation to be in close proximity to demand and thus increases the pressure on non-built-up land especially in densely populated dense regions where pressure is already high. Our findings show that electricity autarky below the national level is often not possible in densely populated areas in Europe.@en

Concentrating solar power (CSP) capacity has expanded slower than other renewable technologies and its costs are still high. Until now, there have been too few CSP projects to derive robust conclusions about its cost development. Here we present an empirical study of the cost development of all operating CSP stations and those under construction, examining the roles of capacity growth, industry continuity, and policy support design. We identify distinct CSP expansion phases, each characterized by different cost pressure in the policy regime and different industry continuity. In 2008-2011, with low cost pressure and following industry discontinuity, costs increased. In the current phase, with high cost pressure and continuous industry development, costs decreased rapidly, with learning rates exceeding 20%. Data for projects under construction suggest that this trend is continuing and accelerating. If support policies and industrial structure are sustained, we see no near-term factors that would hinder further cost decreases.@en

Previous studies have demonstrated the possibility of maintaining a reliable electric power system with high shares of renewables, but only assuming the deployment of specific technologies in precise ratios, careful demand-side management, or grid-scale storage technologies. Any scalable renewable technology that could provide either baseload or dispatchable power would allow greater flexibility in planning a balanced system, and therefore would be especially valuable. Many analysts have suggested that concentrating solar power (CSP) could do just that. Here we systematically test this proposition for the first time. We simulate the operation of CSP plant networks incorporating thermal storage in four world regions where CSP is already being deployed, and optimize their siting, operation and sizing to satisfy a set of realistic demand scenarios. In all four regions, we show that with an optimally designed and operated system, it is possible to guarantee up to half of peak capacity before CSP plant costs substantially increase.@en

In a recent article, Trainer argues that electricity from concentrating solar power (CSP) in winter would be unreliable and prohibitively expensive, even if generated in premium desert sites. However, he does not carry out a detailed analysis of the reliability or the cost, but bases his conclusion on five arguments, each of which is either irrelevant or erroneous. In particular, his research question, concerning the cost of a CSP kilowatt-hour during winter is irrelevant, and the answer misleading, because the power station will deliver electricity in summer too. A more relevant and not misleading question would be about the performance - the yearly levelised costs of electricity and the reliability - of a CSP fleet. We argue based on a detailed analysis of the performance of CSP in four deserts worldwide, that a coordinated fleet of CSP stations can indeed provide fully dispatchable electricity, and in some cases even baseload, at low cost.@en

This paper reviews the potential vulnerability of solar energy systems to future extreme event risks as a consequence of climate change. We describe the three main technologies likely to be used to harness sunlight-thermal heating, photovoltaic (PV), and concentrating solar power (CSP)-and identify critical climate vulnerabilities for each one. We then compare these vulnerabilities with assessments of future changes in mean conditions and extreme event risk levels. We do not identify any vulnerabilities severe enough to halt development of any of the technologies mentioned, although we do find a potential value in exploring options for making PV cells more heat-resilient and for improving the design of cooling systems for CSP.

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