Editing IPCC:AR6/SR15/Chapter-4 (section)

=== 4.3.1 Energy System Transitions ===

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This section discusses the feasibility of mitigation and adaptation options related to the energy system transition. Only options relevant to 1.5°C and with significant changes since AR5 are discussed, which means that for options like hydropower and geothermal energy, the chapter refers to AR5 and does not provide a discussion. Socio-technical inertia of energy options for 1.5°C-consistent pathways are increasingly being surmounted as fossil fuels start to be phased out. Supply-side mitigation and adaptation options and energy demand-side options, including energy efficiency in buildings and transportation, are discussed in Section 4.3.3; options around energy use in industry are discussed in Section 4.3.4.

Section 4.5 assesses the feasibility in a systematic manner based on the approach outlined in Cross-Chapter Box 3 in Chapter 1.

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==== 4.3.1.1 Renewable electricity: solar and wind ====

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All renewable energy options have seen considerable advances over the years since AR5, but solar energy and both onshore and offshore wind energy have had dramatic growth trajectories. They appear well underway to contribute to 1.5°C-consistent pathways (IEA, 2017c; IRENA, 2017b; REN21, 2017) <sup>[[#fn:r86|86]]</sup> .

The largest growth driver for renewable energy since AR5 has been the dramatic reduction in the cost of solar photovoltaics (PV) (REN21, 2017) <sup>[[#fn:r87|87]]</sup> . This has made rooftop solar competitive in sunny areas between 45° north and south latitude (Green and Newman, 2017b) <sup>[[#fn:r88|88]]</sup> , though IRENA (2018) <sup>[[#fn:r89|89]]</sup> suggests it is cost effective in many other places too. Solar PV with batteries has been cost effective in many rural and developing areas (Pueyo and Hanna, 2015; Szabó et al., 2016; Jimenez, 2017) <sup>[[#fn:r90|90]]</sup> , for example 19 million people in Bangladesh now have solar-battery electricity in remote villages and are reporting positive experiences on safety and ease of use (Kabir et al., 2017) <sup>[[#fn:r91|91]]</sup> . Small-scale distributed energy projects are being implemented in developed and developing cities where residential and commercial rooftops offer potential for consumers becoming producers (called prosumers) (ACOLA, 2017; Kotilainen and Saari, 2018) <sup>[[#fn:r92|92]]</sup> . Such prosumers could contribute significantly to electricity generation in sun-rich areas like California (Kurdgelashvili et al., 2016) <sup>[[#fn:r93|93]]</sup> or sub-Saharan Africa in combination with micro-grids and mini-grids (Bertheau et al., 2017) <sup>[[#fn:r94|94]]</sup> . It could also contribute to universal energy access (SDG 7) as shown by (IEA, 2017c) <sup>[[#fn:r95|95]]</sup> .

The feasibility of renewable energy options depends to a large extent on geophysical characteristics of the area where the option is implemented. However, technological advances and policy instruments make renewable energy options increasingly attractive in other areas. For example, solar PV is deployed commercially in areas with low solar insolation, like northwest Europe (Nyholm et al., 2017) <sup>[[#fn:r96|96]]</sup> . Feasibility also depends on grid adaptations (e.g., storage, see below) as renewables grow (IEA, 2017c) <sup>[[#fn:r97|97]]</sup> . For regions with high energy needs, such as industrial areas (see Section 4.3.4), high-voltage DC transmission across long distances would be needed (MacDonald et al., 2016) <sup>[[#fn:r98|98]]</sup> .

Another important factor affecting feasibility is public acceptance, in particular for wind energy and other large-scale renewable facilities (Yenneti and Day, 2016; Rand and Hoen, 2017; Gorayeb et al., 2018) <sup>[[#fn:r99|99]]</sup> that raise landscape management (Nadaï and Labussière, 2017) <sup>[[#fn:r100|100]]</sup> and distributional justice (Yenneti and Day, 2016) <sup>[[#fn:r101|101]]</sup> challenges. Research indicates that financial participation and community engagement can be effective in mitigating resistance (Brunes and Ohlhorst, 2011; Rand and Hoen, 2017) <sup>[[#fn:r102|102]]</sup> (see Section 4.4.3).

Bottom-up studies estimating the use of renewable energy in the future, either at the global or at the national level, are plentiful, especially in the grey literature. It is hotly debated whether a fully renewable energy or electricity system, with or without biomass, is possible (Jacobson et al., 2015, 2017) <sup>[[#fn:r103|103]]</sup> or not (Clack et al., 2017; Heard et al., 2017) <sup>[[#fn:r104|104]]</sup> , and by what year. Scale-up estimates vary with assumptions about costs and technological maturity, as well as local geographical circumstances and the extent of storage used (Ghorbani et al., 2017; REN21, 2017) <sup>[[#fn:r105|105]]</sup> . Several countries have adopted targets of 100% renewable electricity (IEA, 2017c) <sup>[[#fn:r106|106]]</sup> as this meets multiple social, economic and environmental goals and contributes to mitigation of climate change (REN21, 2017) <sup>[[#fn:r107|107]]</sup> .

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==== 4.3.1.2 Bioenergy and biofuels ====

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Bioenergy is renewable energy from biomass. Biofuel is biomass-based energy used in transport. Chapter 2 suggests that pathways limiting warming to 1.5°C would enable supply of 67–310 (median 150) EJ yr <sup>−1</sup> (see Table 2.8) from biomass. Most scenarios find that bioenergy is combined with carbon dioxide capture and storage (CCS, BECCS) if it is available but also find robust deployment of bioenergy independent of the availability of CCS (see Chapter 2, Section 2.3.4.2 and Section 4.3.7 for a discussion of BECCS). Detailed assessments indicate that deployment is similar for pathways limiting global warming to below 2°C (Chum et al., 2011; P. Smith et al., 2014; Creutzig et al., 2015b) <sup>[[#fn:r108|108]]</sup> . There is however ''high agreement'' that the sustainable bioenergy potential in 2050 would be restricted to around 100 EJ yr <sup>−1</sup> (Slade et al., 2014; Creutzig et al., 2015b) <sup>[[#fn:r109|109]]</sup> . Sustainable deployment at such or higher levels envisioned by 1.5°C-consistent pathways may put significant pressure on available land, food production and prices (Popp et al., 2014b; Persson, 2015; Kline et al., 2017; Searchinger et al., 2017) <sup>[[#fn:r110|110]]</sup> , preservation of ecosystems and biodiversity (Creutzig et al., 2015b; Holland et al., 2015; Santangeli et al., 2016) <sup>[[#fn:r111|111]]</sup> , and potential water and nutrient constraints (Gerbens-Leenes et al., 2009; Gheewala et al., 2011; Bows and Smith, 2012; Smith and Torn, 2013; Bonsch et al., 2016; Lampert et al., 2016; Mouratiadou et al., 2016; Smith et al., 2016b; Wei et al., 2016; Mathioudakis et al., 2017) <sup>[[#fn:r112|112]]</sup> ; but there is still ''low agreement'' on these interactions (Robledo-Abad et al., 2017) <sup>[[#fn:r113|113]]</sup> . Some of the disagreement on the sustainable capacity for bioenergy stems from global versus local assessments. Global assessments may mask local dynamics that exacerbate negative impacts and shortages while at the same time niche contexts for deployment may avoid trade-offs and exploit co-benefits more effectively. In some regions of the world (e.g., the case of Brazilian ethanol, see Box 4.7, where land may be less of a constraint, the use of bioenergy is mature and the industry is well developed), land transitions could be balanced with food production and biodiversity to enable a global impact on CO <sub>2</sub> emissions (Jaiswal et al., 2017) <sup>[[#fn:r114|114]]</sup> .

The carbon intensity of bioenergy, key for both bioenergy as an emission-neutral energy option and BECCS as a CDR measure, is still a matter of debate (Buchholz et al., 2016; Liu et al., 2018) <sup>[[#fn:r115|115]]</sup> and depends on management (Pyörälä et al., 2014; Torssonen et al., 2016; Baul et al., 2017; Kilpeläinen et al., 2017) <sup>[[#fn:r116|116]]</sup> ; direct and indirect land-use change emissions (Plevin et al., 2010; Schulze et al., 2012; Harris et al., 2015; Repo et al., 2015; DeCicco et al., 2016; Qin et al., 2016) <sup>[[#fn:r117|117]]</sup> <sup>[[#fn:2|2]]</sup> ; the feedstock considered; and time frame (Zanchi et al., 2012; Daioglou et al., 2017; Booth, 2018; Sterman et al., 2018) <sup>[[#fn:r118|118]]</sup> , as well as the availability of coordinated policies and management to minimize negative side effects and trade-offs, particularly those around food security (Stevanović et al., 2017) <sup>[[#fn:r119|119]]</sup> and livelihood and equity considerations (Creutzig et al., 2013; Calvin et al., 2014) <sup>[[#fn:r120|120]]</sup> .

Biofuels are a part of the transport sector in some cities and countries, and may be deployed as a mitigation option for aviation, shipping and freight transport (see Section 4.3.3.5) as well as industrial decarbonization (IEA, 2017g) <sup>[[#fn:r121|121]]</sup> (Section 4.3.4), though only Brazil has mainstreamed ethanol as a substantial, commercial option. Lower emissions and reduced urban air pollution have been achieved there by use of ethanol and biodiesel as fuels (Hill et al., 2006; Salvo et al., 2017) <sup>[[#fn:r122|122]]</sup> (see Box 4.7).

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==== 4.3.1.3 Nuclear energy ====

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Many scenarios in Chapter 2 and in AR5 (Bruckner et al., 2014) <sup>[[#fn:r123|123]]</sup> project an increase in the use of nuclear power, while others project a decrease. The increase can be realized through existing mature nuclear technologies or new options (generation III/IV reactors, breeder reactors, new uranium and thorium fuel cycles, small reactors or nuclear cogeneration).

Even though scalability and speed of scaling of nuclear plants have historically been high in many nations, such rates are currently not achieved anymore. In the 1960s and 1970s, France implemented a programme to rapidly get 80% of its power from nuclear in about 25 years (IAEA, 2018) <sup>[[#fn:r124|124]]</sup> , but the current time lag between the decision date and the commissioning of plants is observed to be 10-19 years (Lovins et al., 2018) <sup>[[#fn:r125|125]]</sup> . The current deployment pace of nuclear energy is constrained by social acceptability in many countries due to concerns over risks of accidents and radioactive waste management (Bruckner et al., 2014) <sup>[[#fn:r126|126]]</sup> . Though comparative risk assessment shows health risks are low per unit of electricity production (Hirschberg et al., 2016) <sup>[[#fn:r127|127]]</sup> , and land requirement is lower than that of other power sources (Cheng and Hammond, 2017) <sup>[[#fn:r128|128]]</sup> , the political processes triggered by societal concerns depend on the country-specific means of managing the political debates around technological choices and their environmental impacts (Gregory et al., 1993) <sup>[[#fn:r129|129]]</sup> . Such differences in perception explain why the 2011 Fukushima incident resulted in a confirmation or acceleration of phasing out nuclear energy in five countries (Roh, 2017) <sup>[[#fn:r130|130]]</sup> while 30 other countries have continued using nuclear energy, amongst which 13 are building new nuclear capacity, including China, India and the United Kingdom (IAEA, 2017; Yuan et al., 2017) <sup>[[#fn:r131|131]]</sup> .

Costs of nuclear power have increased over time in some developed nations, principally due to market conditions where increased investment risks of high-capital expenditure technologies have become significant. ‘Learning by doing’ processes often failed to compensate for this trend because they were slowed down by the absence of standardization and series effects (Grubler, 2010) <sup>[[#fn:r132|132]]</sup> . What the costs of nuclear power are and have been is debated in the literature (Lovering et al., 2016; Koomey et al., 2017) <sup>[[#fn:r133|133]]</sup> . Countries with liberalized markets that continue to develop nuclear employ de-risking instruments through long-term contracts with guaranteed sale prices (Finon and Roques, 2013) <sup>[[#fn:r134|134]]</sup> . For instance, the United Kingdom works with public guarantees covering part of the upfront investment costs of newly planned nuclear capacity. This dynamic differs in countries such as China and South Korea, where monopolistic conditions in the electric system allow for reducing investment risks, deploying series effects and enhancing the engineering capacities of users due to stable relations between the security authorities and builders (Schneider et al., 2017) <sup>[[#fn:r135|135]]</sup> .

The safety of nuclear plants depends upon the public authorities of each country. However, because accidents affect worldwide public acceptance of this industry, questions have been raised about the risk of economic and political pressures weakening the safety of the plants (Finon, 2013; Budnitz, 2016) <sup>[[#fn:r136|136]]</sup> . This raises the issue of international governance of civil nuclear risks and reinforced international cooperation involving governments, companies and engineering (Walker and Lönnroth, 1983; Thomas, 1988; Finon, 2013) <sup>[[#fn:r137|137]]</sup> , based on the experience of the International Atomic Energy Agency.

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==== 4.3.1.4 Energy storage ====

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The growth in electricity storage for renewables has been around grid flexibility resources (GFR) that would enable several places to source more than half their power from non-hydro renewables (Komarnicki, 2016) <sup>[[#fn:r138|138]]</sup> . Ten types of GFRs within smart grids have been developed (largely since AR5)(Blaabjerg et al., 2004; IRENA, 2013; IEA, 2017d; Majzoobi and Khodaei, 2017) <sup>[[#fn:r139|139]]</sup> , though how variable renewables can be balanced  without hydro or natural gas-based power back-up at a larger scale would still need demonstration. Pumped hydro comprised 150 GW of storage capacity in 2016, and grid-connected battery storage just 1.7 GW, but the latter grew between 2015 to 2016 by 50% (REN21, 2017) <sup>[[#fn:r140|140]]</sup> . Battery storage has been the main growth feature in energy storage since AR5 (Breyer et al., 2017) <sup>[[#fn:r141|141]]</sup> . This appears to the result of significant cost reductions due to mass production for electric vehicles (EVs) (Nykvist and Nilsson, 2015; Dhar et al., 2017) <sup>[[#fn:r142|142]]</sup> . Although costs and technical maturity look increasingly positive, the feasibility of battery storage is challenged by concerns over the availability of resources and the environmental impacts of its production (Peters et al., 2017) <sup>[[#fn:r143|143]]</sup> . Lithium, a common element in the earth’s crust, does not appear to be restricted and large increases in production have happened in recent years with eight new mines in Western Australia where most lithium is produced (GWA, 2016) <sup>[[#fn:r144|144]]</sup> . Emerging battery technologies may provide greater efficiency and recharge rates (Belmonte et al., 2016) <sup>[[#fn:r145|145]]</sup> but remain significantly more expensive due to speed and scale issues compared to lithium ion batteries (Dhar et al., 2017; IRENA, 2017a) <sup>[[#fn:r146|146]]</sup> .

Research and demonstration of energy storage in the form of thermal and chemical systems continues, but large-scale commercial systems are rare (Pardo et al., 2014) <sup>[[#fn:r147|147]]</sup> . Renewably derived synthetic liquid (like methanol and ammonia) and gas (like methane and hydrogen) are increasingly being seen as a feasible storage options for renewable energy (producing fuel for use in industry during times when solar and wind are abundant) (Bruce et al., 2010; Jiang et al., 2010; Ezeji, 2017) <sup>[[#fn:r148|148]]</sup> but, in the case of carbonaceous storage media, would need a renewable source of carbon to make a positive contribution to GHG reduction (von der Assen et al., 2013; Abanades et al., 2017) <sup>[[#fn:r149|149]]</sup> (see also Section 4.3.4.5). The use of electric vehicles as a form of storage has been modelled and evaluated as an opportunity, and demonstrations are emerging (Dhar et al., 2017; Green and Newman, 2017a) <sup>[[#fn:r150|150]]</sup> , but challenges to upscaling remain.

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==== 4.3.1.5 Options for adapting electricity systems to 1.5°C ====

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Climate change has started to disrupt electricity generation and, if climate change adaptation options are not considered, it is predicted that these disruptions will be lengthier and more frequent (Jahandideh-Tehrani et al., 2014; Bartos and Chester, 2015; Kraucunas et al., 2015; van Vliet et al., 2016) <sup>[[#fn:r151|151]]</sup> . Adaptation would both secure vulnerable infrastructure and ensure the necessary generation capacity (Minville et al., 2009; Eisenack and Stecker, 2012; Schaeffer et al., 2012; Cortekar and Groth, 2015; Murrant et al., 2015; Panteli and Mancarella, 2015; Goytia et al., 2016) <sup>[[#fn:r152|152]]</sup> . The literature shows ''high agreement'' that climate change impacts need to be planned for in the design of any kind of infrastructure, especially in the energy sector (Nierop, 2014) <sup>[[#fn:r153|153]]</sup> , including interdependencies with other sectors that require electricity to function, including water, data, telecommunications and transport (Fryer, 2017) <sup>[[#fn:r154|154]]</sup> .

Recent research has developed new frameworks and models that aim to assess and identify vulnerabilities in energy infrastructure and create more proactive responses (Francis and Bekera, 2014; Ouyang and Dueñas-Osorio, 2014; Arab et al., 2015; Bekera and Francis, 2015; Knight et al., 2015; Jeong and An, 2016; Panteli et al., 2016; Perrier, 2016; Erker et al., 2017; Fu et al., 2017) <sup>[[#fn:r155|155]]</sup> . Assessments of energy infrastructure adaptation, while limited, emphasize the need for redundancy (Liu et al., 2017) <sup>[[#fn:r156|156]]</sup> . The implementation of  controllable and islandable microgrids, including the use of residential batteries, can increase resiliency, especially after extreme weather events (Qazi and Young Jr., 2014; Liu et al., 2017) <sup>[[#fn:r157|157]]</sup> . Hybrid renewables-based power systems with non-hydro capacity, such as with high-penetration wind generation, could provide the required system flexibility (Canales et al., 2015) <sup>[[#fn:r158|158]]</sup> . Overall, there is ''high agreement'' that hybrid systems, taking advantage of an array of sources and time of use strategies, can help make electricity generation more resilient (Parkinson and Djilali, 2015) <sup>[[#fn:r159|159]]</sup> , given that energy security standards are in place (Almeida Prado et al., 2016) <sup>[[#fn:r160|160]]</sup> .

Interactions between water and energy are complex (IEA, 2017g) <sup>[[#fn:r161|161]]</sup> . Water scarcity patterns and electricity disruptions will differ across regions. There is ''high agreement'' that mitigation and adaptation options for thermal electricity generation (if that remains fitted with CCS) need to consider increasing water shortages, taking into account other factors such as ambient water resources and demand changes in irrigation water (Hayashi et al., 2018) <sup>[[#fn:r162|162]]</sup> . Increasing the efficiency of power plants can reduce emissions and water needs (Eisenack and Stecker, 2012; van Vliet et al., 2016) <sup>[[#fn:r163|163]]</sup> , but applying CCS would increase water consumption (Koornneef et al., 2012) <sup>[[#fn:r164|164]]</sup> . The technological, economic, social and institutional feasibility of efficiency improvements is high, but insufficient to limit temperature rise to 1.5°C (van Vliet et al., 2016) <sup>[[#fn:r165|165]]</sup> .

In addition, a number of options for water cooling management systems have been proposed, such as hydraulic measures (Eisenack and Stecker, 2012) <sup>[[#fn:r166|166]]</sup> and alternative cooling technologies (Chandel et al., 2011; Eisenack and Stecker, 2012; Bartos and Chester, 2015; Murrant et al., 2015; Bustamante et al., 2016; van Vliet et al., 2016; Huang et al., 2017b) <sup>[[#fn:r167|167]]</sup> . There is ''high agreement'' on the technological and economic feasibility of these technologies, as their absence can severely impact the functioning of the power plant as well as safety and security standards.

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==== 4.3.1.6 Carbon dioxide capture and storage in the power sector ====

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The AR5 (IPCC, 2014b) <sup>[[#fn:r168|168]]</sup> as well as Chapter 2, Section 2.4.2, assign significant emission reductions over the course of this century to CO <sub>2</sub> capture and storage (CCS) in the power sector. This section focuses on CCS in the fossil-fuelled power sector; Section 4.3.4 discusses CCS in non-power industry, and Section 4.3.7 discusses bioenergy with CCS (BECCS). Section 2.4.2 puts the cumulative CO <sub>2</sub> stored from fossil-fuelled power at 410 (199–470 interquartile range) GtCO <sub>2</sub> over this century. Such modelling suggests that CCS in the power sector can contribute to cost-effective achievement of emission reduction requirements for limiting warming to 1.5°C. CCS may also offer employment and political advantages for fossil fuel-dependent economies (Kern et al., 2016) <sup>[[#fn:r169|169]]</sup> , but may entail more limited co-benefits than other mitigation options (that, e.g., generate power) and therefore relies on climate policy incentives for its business case and economic feasibility. Since 2017, two CCS projects in the power sector capture 2.4 MtCO <sub>2</sub> annually, while 30 MtCO <sub>2</sub> is captured annually in all CCS projects (Global CCS Institute, 2017) <sup>[[#fn:r170|170]]</sup> .

The technological maturity of CO <sub>2</sub> capture options in the power sectors has improved considerably (Abanades et al., 2015; Bui et al., 2018) <sup>[[#fn:r171|171]]</sup> , but costs have not come down between 2005 and 2015 due to limited learning in commercial settings and increased energy and resources costs (Rubin et al., 2015) <sup>[[#fn:r172|172]]</sup> . Storage capacity estimates vary greatly, but Section 2.4.2 as well as literature (V. Scott et al., 2015) <sup>[[#fn:r173|173]]</sup> indicate that perhaps 10,000 GtCO <sub>2</sub> could be stored in underground reservoirs. Regional availability of this may not be sufficient, and it requires efforts to have this storage and the corresponding infrastructure available at the necessary rates and times (de Coninck and Benson, 2014) <sup>[[#fn:r174|174]]</sup> . CO <sub>2</sub> retention in the storage reservoir was recently assessed as 98% over 10,000 years for well-managed reservoirs, and 78% for poorly regulated ones (Alcalde et al., 2018) <sup>[[#fn:r175|175]]</sup> .  A paper reviewing 42 studies on public perception of CCS (Seigo et al., 2014) <sup>[[#fn:r176|176]]</sup> found that social acceptance of CCS is predicted by trust, perceived risks and benefits. The technology itself mattered less than the social context of the project. Though insights on communication of CCS projects to the general public and inhabitants of the area around the CO <sub>2</sub> storage sites have been documented over the years, project stakeholders are not consistently implementing these lessons, although some projects have observed good practices (Ashworth et al., 2015) <sup>[[#fn:r177|177]]</sup> .

CCS in the power sector is hardly being realized at scale, mainly because the incremental costs of capture, and the development of transport and storage infrastructures are not sufficiently compensated by market or government incentives (IEA, 2017c) <sup>[[#fn:r178|178]]</sup> . In the two full-scale projects in the power sector mentioned above, part of the capture costs are compensated for by revenues from enhanced oil recovery (EOR) (Global CCS Institute, 2017) <sup>[[#fn:r179|179]]</sup> , demonstrating that EOR helps developing CCS further. EOR is a technique that uses CO <sub>2</sub> to mobilize more oil out of depleting oil fields, leading to additional CO <sub>2</sub> emissions by combusting the additionally recovered oil (Cooney et al., 2015) <sup>[[#fn:r180|180]]</sup> .

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