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Stranded investment associated with rapid energy system changes under the mid-century strategy in Japan

Stranded investment associated with rapid energy system changes under the mid-century strategy in... Japan’s mid-century strategy to reduce greenhouse gas (GHG) emissions by 80% by 2050 requires rapid energy system changes, which may lead to stranded assets in fossil fuel-related infrastructure. Existing studies have shown that massive stranding of assets in the energy supply side is possible; few studies have involved economy-wide stranded asset analysis. In this study, we estimated stranded investments in both the energy supply and demand sectors in Japan in the context of near- term goals for 2030 and the mid-century strategy. To this end, multiple emission scenarios for Japan were assessed based on various emission reduction targets for 2030 and 2050. The results show that stranded investments in the energy supply sec- tors occur mainly in coal power plants without carbon capture and storage (CCS), especially in scenarios without enhanced near-term mitigation targets. Increases of stranded investment in demand sectors were observed primarily under stringent mitigation scenarios, which exceed the 80% reduction target. In particular, investment for oil and gas heating systems in the buildings sector may be stranded at levels up to $20 billion US between 2021 and 2050. We further simulated a scenario incorporating a subsidy for devices that do not use fossil fuels as a sector-specific policy; this reduced the amount of stranded investment in the buildings sector. We confirmed the benefit of enhancing near-term mitigation targets to avoid generating stranded investments. These findings support the importance of inclusive energy and climate policy design involving not only pricing of carbon emissions but also complementary cross-sector economy-wide policies. Keywords Stranded asset · Climate change mitigation · Mid-century strategy · Electrification · Energy policy · Energy system transformation Introduction The Paris Agreement requires that parties submit Nation- ally Determined Contributions (NDCs), which include miti- gation targets for reducing emissions of greenhouse gases (GHGs) by 2030, and encourages each party to formulate Handled by Masa Sugiyama, University of Tokyo, Japan. a long-term low-emission development strategy, known as Electronic supplementary material The online version of this the mid-century strategy (MCS), which focuses mainly on article (https ://doi.org/10.1007/s1162 5-020-00862 -2) contains emission reduction targets in 2050 and later. Japan was the supplementary material, which is available to authorized users. sixth-largest emitter of GHGs in 2018 (Olivier and Peters * Ken Oshiro 2020) and has submitted an NDC of reducing GHG emis- koshiro@athehost.env.kyoto-u.ac.jp sions by 26.0% in 2030 relative to the 2013 level. As a long- term national target, the government of Japan has submit- Kyoto University, C1-3, Kyotodaigaku-Katsura, ted an MCS that includes the quantitative goal of reducing Nishikyo-ku, Kyoto, Japan GHG emissions by 80% in 2050 and the aim of achieving National Institute for Environmental Studies, 16-2 Onogawa, decarbonization of society as soon as possible in the sec- Tsukuba, Ibaraki, Japan ond half of this century. Regarding the consistency between International Institute for Applied System Analysis (IIASA), these national targets and the global goals stated in the Paris Schlossplatz 1, 2361 Laxenburg, Austria Vol.:(0123456789) 1 3 478 Sustainability Science (2021) 16:477–487 Agreement, Oshiro et al. (2019) have suggested that the on disruptive changes between the US NDC and MCS, and 80% reduction goal by 2050 would be on track to the global quantified stranded coal capacity by 2050 using the Global 2 °C goal in terms of the carbon budget based on the cost Change Assessment Model (GCAM). Wang et al. (2019) effectiveness allocation whereas additional efforts would and Malik et al. (2020) estimated the stranded coal capac- be required for 1.5 °C goal, although the national emission ity under the low-emission scenarios in China and India, ranges implied by the global pathways are largely depend- respectively, using both global and national IAMs. These ing on the effort sharing scheme (van den Berg et al. 2019). studies stressed that near-term actions including enhance- In this regard, several studies have assessed the energy ment of NDCs are effective for avoiding the stranding of and economic implications of Japan’s near- to mid-term high-carbon infrastructure such as coal power plants without emission pathways using energy system models and inte- carbon capture and storage (CCS). Meanwhile, few studies grated assessment models (IAMs), that integrate relevant have focused on the energy demand sectors rather than on disciplines such as energy, economy, agriculture, and land the energy supply sector (Davis et al. 2010; IRENA 2017). use into single modeling framework (Fujimori et al. 2019; Therefore, the economy-wide risk of stranded investment Kato and Kurosawa 2019; Oshiro et al. 2019; Silva Herran and measures to avoid those risks remain unclear. et al. 2019; Sugiyama et al. 2019). Generally, these national Given this background, the present study aims to clarify scenario analyses have suggested that attainment of both the the risk of stranded investment in the context of rapid energy NDC and MCS targets without strengthening the near-term system transformation in both energy demand and supply target would require rapid emission reductions between 2030 sectors. To this end, we quantified the stranded investment and 2050, which would involve non-linear energy system arising from rapid energy system transition between 2030 transformation during this period (Oshiro et al. 2017). Such and 2050 in Japan using a bottom-up energy system model. rapid transformation would involve dramatic increases in In addition, this study aims to explore the policy implica- the carbon price and associated mitigation costs during this tions of stranded investment risk mitigation. period (Fujimori et al. 2019; Sugiyama et al. 2019). In this regard, technological, economic and political feasibility is a critical challenge for reaching the mid-century goals. Materials and methods In terms of the feasibility of such drastic energy system changes, existing studies have pointed out transition risks, Model such as carbon lock-in, stranded investment, and premature retirement relative to the expected lifetime of fossil fuel- We used AIM/Enduse [Japan], which is a dynamic recursive related infrastructure (Campiglio et al. 2018; Mercure et al. partial equilibrium model that explicitly represents individ- 2018; Seto et al. 2016). At the global scale, several stud- ual energy-use technologies in both the energy supply and ies using IAMs have indicated that the lack of short-term demand sectors as listed in Table 1. The operating conditions mitigation actions would lead to premature phase-out of coal and amount of new installation of each technology, along power plants and stranding of fossil fuel assets, resulting in with the resulting energy use and GHG emissions, are calcu- increased stranded investment in the energy supply sectors lated based on linear programming to minimize total energy (Bertram et al. 2015; Cui et al. 2019; Johnson et al. 2015). system costs. The results are subject to exogenous param- At the national level, Iyer et al. (2017) explicitly focused eters, including a technological parameter, energy service Table 1 Technology options included AIM/Enduse [Japan] Sector Technology option Industrial sector Sector specific energy technologies in steel, cement, petrochemical and paper production (e.g. CCS for steel/cement production, Next generation coke oven, electric furnace, naphtha catalytic cracker), high efficient industrial boiler, industrial heat pump, high efficient motor, inverter Buildings sector High efficient air conditioner, high efficient water heater (e.g. heat pump water heater), electric heat pump water heater, fuel cell, high efficient lighting, high efficient appliance, high performance building envelope including thermal insulation Transport sector Fuel economy improvement, hybrid electric vehicle, plug-in hybrid electric vehicle, battery electric vehicle (BEV), fuel-cell electric vehicle (FCEV), natural gas vehicle, biofuel, high efficient train, high efficient ship, high efficient aircraft Power generation sector IGCC w/CCS, IGCC wo/CCS, IGFC w/CCS, IGFC wo/CCS, Advanced gas combined cycle (ACC) w/CCS, ACC wo/CCS, Fuel cell gas combined cycle w/ or wo/CCS, Nuclear, Onshore wind power, Offshore wind power, Solar PV, Geothermal, Bioenergy, Hydropower, Pumped hydro storage, Stationary battery storage, Reinforcing electricity interconnection capacity, Hydrogen generation by electrolysis 1 3 Sustainability Science (2021) 16:477–487 479 demands, and emissions constraints. The detailed model lifetime of coal power plants with their expected or planned description, including equations and parameter assump- lifetimes. Johnson et al. (2015) appraised stranded invest- tions, was reported by Kainuma et al. (2003). For this study, ment in monetary units by multiplying the stranded capac- we used a model that incorporates an electricity dispatch ity with the annualized cost. In this paper, we quantified module and a detailed regional classification scheme that stranded capacity and investments. Here, stranded capacity divides Japan into 10 regions (Oshiro et al. 2017; Oshiro is estimated as the stock quantity that is never in operation and Masui 2015). The model used in this study employs a in each time step. The assumptions for the expected lifetime 1-h time representation for electricity load to account for the of each infrastructure and device type are summarized in impacts of variable renewable energies (VREs), whereas the Table S1 in the ESM. The stranded investment calculation previous version had 3-h resolution. The power sector mod- in this paper followed the method of Johnson et al. (2015), ule includes measures taken to integrate VREs into the grid, which entails multiplying the stranded capacity by the annu- such as electricity storage, demand response (DR) using bat- alized investment of each technology using a 5% interest tery-powered electric vehicles and heat pump devices, and rate. To measure the amount of stranded investments associ- interconnections. The capacity of the energy infrastructure ated with climate policy implementation, the stranded capac- is calculated based on newly installed capacity and residual ity and investment are represented in this study as additional capacity remaining today, which is in turn calculated based values compared to the baseline case wherein no additional on the constructed year, capacity, and expected lifetime of climate policy is implemented, unless otherwise noted. each plant. In the energy demand sectors, numerous mitiga- Detailed descriptions of stranded investment estimation in tion options are included in the sectors of industry, build- this study, including the equations used, can be found in the ings, and transportation, such as energy-efficient devices Supplementary texts in the ESM. and fuel changes. The details of these parameter assump- tions have been reported previously (Fujimori et al. 2019). Introduction of CCS is considered in the power and industry Scenario sectors, while CCS-ready and conversion to CCS-equipped plant after operation are not taken into account in the model. Assumptions on climate policy, socio-economic, and tech- The solution horizon of AIM/Enduse [Japan] is based on nology developments are based on the harmonized sce- recursive dynamic which is myopic for technological and nario design of the Energy Modeling Forum (EMF) 35 economical changes in the future. In each period, investment Japan Model Intercomparison Project (JMIP) (Sugiyama for energy technologies is determined by minimization of et al., under review). We assumed several scenarios based total energy system costs which include initial, operation and on a combination of different mitigation levels in 2030 and management and emission costs of technologies. The detail 2050 and considering various emission reduction speeds on investment calculation is summarized in the Electronic (Table  2). The 26by30 + 80by50 scenario, which meets Supplementary Material (ESM). It means that technological the NDC target (26% reduction in 2030 with respect to the and economic changes, such as availability of new technol- 2013 level) and the 80% reduction goal by 2050 of Japan’s ogy, changes of carbon prices and energy import prices, are MCS, was used as the central scenario. We also assessed not taken into consideration in investment calculation. the 36by30 and 16by30 scenarios for the 2030 target, which achieve 36% and 16% reductions, respectively. In terms of Stranded investment calculation the 2050 target, 70%, 85%, and 90% scenarios, referred to as 70by50, 85by50 and 90by50, were also taken into con- In the existing literature, several indicators are used to rep- sideration. In addition to the 70by50 and 90by50 scenarios resent the impacts of stranded assets in terms of physical which are included in Sugiyama et al. (under review) for the or monetary units. For example, Bertram et al. (2015); Iyer sensitivity analysis, the 85by50 scenario is also evaluated et al. (2017); Malik et al. (2020) used physical indicators because of non-linear behavior of Japan’s energy systems such as the idling capacity of coal power plants as stranded where the reduction level exceed around 80% in the exist- asset indicators. Cui et al. (2019) compared the average real ing literatures (Oshiro et al. 2019, 2018). Mitigation begins Table 2 Summary of mitigation 2050 policy scenarios 70% 80% (MCS) 85% 90% 2030 policy 16% 16by30 + 70by50 16by30 + 80by50 16by30 + 85by50 16by30 + 90by50 26% (NDC) 26by30 + 70by50 26by30 + 80by50 26by30 + 85by50 26by30 + 90by50 36% 36by30 + 70by50 36by30 + 80by50 36by30 + 85by50 36by30 + 90by50 1 3 480 Sustainability Science (2021) 16:477–487 in 2020 for all scenarios, and the emission trajectories are the emissions reductions targets for 2030 and 2050, which linearly interpolated between 2020 and 2030 and between are summarized in Fig. S1. As depicted in Fig.  1a–d, in 2030 and 2050. all mitigation scenarios, increase of low-carbon resources In the baseline scenario, no specific climate policy is which include renewables, nuclear and fossil fuel with CCS, taken into account, whereas mitigation options whose energy efficiency improvement, and electrification are key investment can be recovered owning to their energy sav- options to meet the long-term goals. While the share of low- ing, so called no regret options, can be introduced even in carbon resources declines around 2015 due to the suspension the baseline scenario in AIM/Enduse [Japan]. It should be of nuclear power, it reaches 70% or more by 2050 owing to noted that there are critical issues to assume a baseline as deployment of renewables, restart of nuclear power plants no-policy scenario (Grant et al. 2020), the baseline scenario and CCS. Generally, energy supply-side indicators, such as in this study, however, did not consider additional policy the proportions of low-carbon resources in primary energy since Japan’s emission pathways and associated energy sys- supply and power generation, vary among scenarios after tem are very close between the no-policy and current policy 2030 (Fig. 1a–b, Figs. S2 and S3). In the energy demand scenario according to the multi-model studies conducted in sectors, development of energy efficiency and electrifica - Roelfsema et al. (2020). Also, the climate impacts on energy tion are drivers of decarbonization, and variations among system, which are pointed out in Grant et al. (2020), are not scenarios are found mainly after 2040, later than the energy taken into consideration in this study. supply indicators (Fig. 1c, d, Fig. S4). Carbon prices and In addition to the scenarios in EMF35-JMIP, sectoral energy system costs increase over time, with especially rapid policy scenarios were assessed in this study to explore their changes after 2040 in the 90by50 scenarios (Fig. 1e, f). In effects in reducing stranded investment. As a sectoral pol- the 36by30 scenarios, high carbon price and energy system icy, we assumed introduction of a subsidy after 2030 that costs are observed in 2030 due to the additional emission accounts for one-third of the installation cost of electrified reductions. In those scenarios, the carbon price reaches devices in the buildings sector, such as high-efficiency air around $3,000 US per t-CO by 2050, and additional total conditioners and heat pump water heaters, based on a policy energy system costs relative to the baseline account for in Japan called the ASSET (Advanced technologies promo- around 2% of GDP in 2050. tion Subsidy Scheme with Emission reduction Targets) scheme, implemented by the Ministry of the Environment Stranded investments (IGES et al. 2016). The assumption on nuclear power availability follows Stranded investments accumulated between 2021 and 2050 Oshiro et al. (2017), where the nuclear power generation are summarized in Fig.  2a. The total amount of stranded is generally identical to that stated in the NDC, with an investment under the 16by30 scenarios is double or more extension of lifetime to 60 years for some nuclear plants. those of the 26by30 and 36by30 scenarios, mainly due to This assumption is identical with the LimNUC case in the greater stranded investment in the energy supply sector. By JMIP harmonized scenario (Sugiyama et al., under review). contrast, in terms of 2050 emission levels, the variations in In terms of socio-economic conditions, GDP growth is stranded investment among scenarios are moderate, espe- based on that of the NDC until 2030, equivalent to around cially among the 80by50, 85by50, and 90by50 scenarios. 1.7% growth, and with the Shared Socio-economic Pathway Stranded investment in energy demand sectors is generally (SSP) 2 assumption thereafter (Riahi et al. 2017). Population smaller than that in the energy supply sectors, but reaches growth is consistent with the medium-fertility and medium- around $20 billion US in the 90by50 reduction scenarios. mortality estimate of the National Institute of Population Energy demand investments are stranded mainly in the and Social Security Research (IPSS 2017). These assump- buildings sector, where they increase dramatically from tions are identical with the HarmDem scenario of Sugiyama 2040 to 2050 in the 85by50 and 90by50 reduction scenarios et al. (under review). The assumptions underlying the socio- (Fig. S5). Long-term stranded investment is also observed in economic and energy service demand indicators used in this the industry sector, but its impact is smaller than that of the study are summarized in Table S2. buildings sector. Stranded investment in the transport sector is mainly due to short-term stranding of the public transport such as train because of its relatively longer lifetime and Results residual inefficient capacities. In the 90by50 reduction sce- narios, the stranded investments in energy demand sectors Energy system changes exceed those of energy supply sectors. Figure 2b shows the relationship between the cumula- As show in Fig. 1, long-term energy system changes in both tive stranded investment and cumulative CO emissions the energy supply and demand sectors are needed to achieve during 2021–2050. The gray area indicates the 95–105% 1 3 Sustainability Science (2021) 16:477–487 481 Share of low carbon in Share of low carbon in Final energy a b c primary energy electricity relative to 2010 80% 100% 100% 60% 75% 75% 40% 50% 50% 20% 25% 25% 0% 0% 0% 2010 2020 2030 2040 2050 2010 2020203020402050 2020 2030 2040 2050 Share of electricity in Carbon prices (US$/t−CO ) Energy system costs d e 2 f final energy (% of GDP) 50% 2.0% 40% 1.5% 30% 1.0% 20% 0.5% 10% 0.0% 0% 0 2010 2020 2030 2040 2050 2010 2020203020402050 2010 2020 2030 2040 2050 16by30 26by30 36by30 70by50 80by50 85by50 90by50 Fig. 1 Energy system transitions in the different scenarios. Share of d Share of electricity in total final energy demand. e Carbon prices. f low-carbon energies in a primary energy supply and b electricity sup- Additional energy system costs per GDP relative to the baseline. The ply, where low-carbon energies include renewables, nuclear and fossil line color refers to the emission reduction rate in 2050 relative to the fuel with CCS. c Final energy consumption relative to the 2010 level. 2010 level range of the 26by30 + 80by50 scenario carbon budget, which energy demand sectors and the speed of emission reduction. is consistent with Japan’s NDC and MCS. At the levels of Although stranded investment in energy demand sectors is the NDC and MCS, the stranded investment in the 16by30 trivial with changes of less than 5% in annual emissions, it scenario accounts for more than $75 billion US, which is rises exponentially at higher emission reduction rates. approximately three times larger than that in the 26by30 scenarios. This result suggests that 2030 emission levels are Stranded investment in energy supply the key determinant of stranded investment within a carbon budget category. As shown in Fig. 2a, the energy supply sector is the largest The amount of stranded investments is affected by the contributor to total stranded investment in most scenarios. speed of emissions reduction and energy system transition. This result is due to the rapid system transition in the energy Figure 3 shows the relationships between stranded invest- supply sector, especially upscaling of low-carbon energies, ments and the speed of C O emission reduction, which differ and the associated phase-out of fossil fuel-related infrastruc- between the energy supply and demand sectors. In the energy ture. Figure 4a shows the stranded coal capacity over time supply sector, stranded investment increases in the 2–5% without CCS. Because the capacity factor of coal power range of annual emission reductions and becomes saturated plants without CCS in 2050 approaches zero in all scenarios in scenarios where the emission reduction rate exceeds 5%. (Fig. 4b), the stranded capacity in 2050 is comparable to The near-term goal level also drives saturation of stranded the residual coal capacity shown in Fig. S6. In the 16by30 investments in the energy supply sector. By contrast, there is scenarios, because installation of new coal plants continues an exponential relationship between stranded investments in until 2030 (Fig. S7), stranded capacity accounts for more 1 3 482 Sustainability Science (2021) 16:477–487 a b < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MCS S S S S S S S S S S S NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MCS S S S S S S S S S S S ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% 20 25 70by50 80by50 85by50 90by50 20 22 24 Cumulative CO emissions (Gt−CO ) 2 2 Residential Industry 70by50 80by50 85by50 90by50 Commercial Energy Supply Transportation 16by30 26by30 36by30 Fig. 2 a Cumulative stranded investment between 2021 and 2050. sectors resulted in negative value. b Cumulative stranded investments The horizontal axis refers to the emission reduction level in 2050. as a function of cumulative C O emissions between 2021 and 2050. The placement of bars refers to the 2030 target. Because the addi- The colors of shaded area refer to the level of carbon budgets tional investments from the baseline scenarios are shown here, some than 30 GW between 2040 and 2050. By contrast, stranded Stranded investment in energy demand capacity peaks before 2040 in the 26by30 and 36by30 sce- narios, with levels around 10 GW or less by 2050. Because Increased stranded investments in energy demand sec- the stranded coal capacity peaks around 2030–2040 and tors occur mainly under deep decarbonization scenarios declines thereafter in most scenarios, stranded investment that require 85% and 90% emission reductions by 2050. in energy supply sectors becomes saturated, as shown in In particular, the buildings sector would face premature Fig. 3b. The capacity factor of gas power plants accounts for retirement of fossil fuel-related devices (e.g., oil and gas around 20% or less by 2050 in the 80by50–90by50 scenarios space- and water-heating systems). Figure  5a shows the (Fig. 4c), and stranded gas capacity without CCS is limited investment in non-fossil technologies in the buildings compared with that of coal (Fig. S8). This difference is due sector, including renewables, electricity, heat, and hydro- to the role of gas power plants as back-up power generation gen under selected scenarios in which the carbon budgets resources for integration of VREs into the electricity grid in are similar to that of the 26by30 + 80by50 scenario. The conjunction with other resources, such as electricity storage results in other scenarios are summarized in Fig. S 10. batteries and demand responses. In the 16by30 + 90by50 scenario, non-fossil investment Figure S9a depicts the comparison of the stranded coal increases by more than six times between 2040 and 2050. capacity and capacity of coal with CCS. Since the capacity In the 26by30 + 80by50 and 26by30 + 85by50 scenarios, of coal with CCS accounts for around a half of peak stranded the investment level is doubled and tripled during this capacity in some scenarios, it suggests the possibility of period, respectively, leading to increased electrification reducing stranded investment by introducing power plants rates between 2040 and 2050 (Fig. 1d). Similarly, stranded with CCS-ready. Nevertheless, the peak stranded capacity investment can occur in the industry and transport sec- still reaches more than 20GW in the most of 16by30 sce- tors, but these impacts are smaller than those in the build- narios when assuming CCS-ready is fully implemented for ings sector (Fig.  2a, Fig. S5). While lifetime of sector coal power plants (Fig. S9b). specific technologies in the industry sector is assumed around 30  years similar to thermal power plants in the power sector, stranded investment in the industry sector is much smaller than that in the power sector. It is because some industrial technologies are already introduced in 1 3 Cumulative stranded investment (billion US$) 16by30 26by30 36by30 Cumulative stranded investment (billion US$) Sustainability Science (2021) 16:477–487 483 Total stranded energy investments 2050 policy 2030 policy 70by50 16by30 80by50 26by30 85by50 36by30 90by50 0% 5% 10% 15% 20% Annual rate of CO emissions reduction (%/yr) Stranded investment in energy supply Stranded investment in energy demand b c 0% 5% 10% 15% 20% 0% 5% 10%15% 20% Annual rate of CO emissions reduction (%/yr) Annual rate of CO emissions reduction (%/yr) 2 2 Fig. 3 Relationship between average annual rate of CO emissions reduction and stranded investment in a energy sector, b energy supply sectors, and c energy demand sectors the baseline scenario and the most of technologies are because the sectoral policy would cause earlier retirement of exhausted in the mitigation scenarios. fossil based devices between 2030 and 2040 (Fig. S12). The required subsidy accounts for about $15 billion US per year in Eec ff ts of sectoral policies 2050, which is equivalent to around 0.2% of GDP (Fig. S13). The amount of subsidy is similar across all scenarios because Given the impacts of stranded investments in the buildings end-use electrification is the important mitigation option by sector under the most stringent scenarios, the effects of sec- 2050. Although the implementation of sectoral policies is toral policies on reducing the stranded investment were esti- effective for avoiding generating stranded investments, the mated. Figure 5b and Fig. S11 show comparison of stranded cumulative amount of stranded investment in the buildings investments in the buildings sector between scenarios with sector in the 16by30 + 90by50 scenario is much larger than that and without the sector-specific policies that promote near-term in the 26by30 + 80by50 scenario. This result implies that near- penetration of non-fossil infrastructure. Sectoral policies can term mitigation is still a critical driver of stranded investment reduce stranded investments in the buildings sector by one- in both the energy demand and supply sectors, even though the third in the 16by30 + 90by50 scenario. In the most scenarios, sectoral specific policies are implemented. sectoral policies result in decrease of stranded investment in the buildings sector, whereas in the limited scenarios, such as the 36by30 + 80by50 scenario, stranded investments in the SecPol scenario is larger than that of NoSecPol scenario 1 3 Stranded investment (billion US$/yr) Stranded investment (billion US$/yr) Stranded investment (billion US$/yr) 484 Sustainability Science (2021) 16:477–487 70by50 80by50 85by50 90by50 16by30 26by30 36by30 Coal without CCS Gas without CCS b c 80% 80% 16by30 26by30 60% 60% 36by30 40% 40% 20% 20% 0% 0% 2030 2040 2050 2030 2040 2050 Fig. 4 a Stranded coal capacity for power generation without CCS, and average capacity factor of b coal power plant without CCS, and c gas without CCS scenarios. This result is mainly due to the need for removal Discussion and conclusion of residual emissions from fossil fuel-related infrastructure in the demand sectors, such as gas and oil heaters and boil- Based on the scenario analysis presented in the previous ers, to attain rapid electrification. In some scenarios with a sections, we explored two processes driving increases in 90% reduction in 2050, the amount of stranded investment in stranded investment. First, energy supply investment can be energy demand sectors exceeds that in energy supply sectors. stranded beginning in the near term due to delayed mitiga- From these findings, it is reconfirmed that weak near-term tion action and associated development of emission-inten- mitigation actions would exacerbate the feasibilities of long- sive infrastructure, such as coal-fired power plants without term climate goals. CCS. In this case, the energy supply infrastructure becomes Nevertheless, the impacts of stranded investment can be idle when the emission constraints become stringent. Sec- reduced through near-term actions and sectoral policy imple- ond, energy demand investment becomes stranded during mentation. In the energy supply sector, the stranded coal rapid emission reductions and the associated energy sys- capacity can be reduced by half or more by strengthening tem transition around 2050 under the deep decarbonization 1 3 70by50 80by50 85by50 y50 2020 90b 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 Capacity factor (%) Stranded capacity (GW) Capacity factor (%) Sustainability Science (2021) 16:477–487 485 a 120 b Residential Commercial 538% −33% 205% 10 114% −26% 45% 37% 125% 30% −20% −13% −18% 0 0 36by30 26by30 26by30 16by30 36by30 26by30 26by30 16by30 +70by50 +80by50 +85by50 +90by50 +70by50 +80by50 +85by50 +90by50 Fig. 5 a Investments for non-fossil-based technologies in the build- narios without sector specific policy. SecPol indicates scenarios with ings sector. Non-fossil technologies include renewables, electricity, sector specific policy. Only the scenarios where carbon budget cat- heat, and hydrogen. b Cumulative stranded investment between 2021 egory is same with the 26by30 + 80by50 scenario are presented and 2050 in the buildings sectors. NoSecPol indicates the default sce- the 2030 emission target. Implementation of CCS-ready for of total power generation, equivalent to 277 billion kWh coal power plants would also be effective to reduce stranded in 2030. In this study, coal power generation in 2030 was coal capacity, while their economic attractiveness is depend- estimated at 0.86 EJ in the 26by30 scenarios (239 billion ing on the remaining lifetime of power plants. In energy kWh) based on a cost-optimization mechanism. If the energy demand sectors, stranded investments can also be reduced policy is implemented as planned, stranded capacity may by implementing sector-specific policies, such as a sub- become greater than the estimates reported in this study. sidy for devices that do not use fossil fuels. A 33% subsidy Third, whereas stranded investment is represented by the for electrified technologies such as heat pump space- and cumulative investment between 2021 and 2050, as shown in water-heating systems would lessen stranded investments Fig. 2, the stranding of long-life infrastructure such as coal in the buildings sector by one-third. This finding indicates power plants without CCS could occur after 2050, especially that holistic policy design in conjunction with implementa- in the 26by30 and 16by30 scenarios, as shown in Fig. 4a. tion of a simple carbon pricing policy could make the deep Although the cumulative amount of stranded investment by decarbonization goal feasible. 2050 which was similar between the 26by30 and 36by30 There are several limitations and caveats to interpreta- scenarios than that of the 26by30 scenario, would be greater tion of the stranded investment estimates in this study. First, if impacts in the second half of this century were considered. in this study, we used a myopic energy system model that Fourth, while this study considered only a subsidy for elec- does not account for future changes in the operating rate of trified devices as a sectoral policy, many other policies that each infrastructure type; hence, the stranded capacity might can reduce stranded investment risks are possible. For exam- be overestimated compared to the intertemporal model. ple, a fossil fuel use ban would directly reduce the amount of Nevertheless, according to an existing multi-model study stranded investment in energy demand sectors. In addition, (Bertram et al. 2015), the amount of stranded investment support for other decarbonized energy carriers in addition estimated with a myopic model is not always higher than to electricity, such as the renewable sources of bioenergy, that based on intertemporal optimization. Therefore, the heat, and hydrogen, would be effective. Policies promoting model type used for each time horizon would not signifi- structural changes, such as effective urban design targeting cantly affect the key findings of this study. Secondly, Japan’s effective use of centralized district heating, would also help NDC states that the share of coal is targeted at around 26% to reduce the stranding of investment in end-use devices. 1 3 NoSecPol SecPol NoSecPol SecPol NoSecPol SecPol NoSecPol SecPol Investment additions (billion US$/yr) Cumulative stranded investment (billion US$) 486 Sustainability Science (2021) 16:477–487 Cui RY, Hultman N, Edwards MR, He L, Sen A, Surana K, McJeon The findings of this study have several policy implica- H, Iyer G, Patel P, Yu S, Nace T, Shearer C (2019) Quantifying tions in the Japanese context. First, in accordance with operational lifetimes for coal power plants under the Paris goals. existing modeling investigations, this study confirmed the Nature Commun 10:4759. https ://doi.org/10.1038/s4146 7-019- requirement for high carbon prices of around $3,000 US 12618 -3 Davis SJ, Caldeira K, Matthews HD (2010) Future CO2 emissions per t-CO in 2050 under the 90by50 scenario (Fig.  1e). and climate change from existing energy infrastructure. Science While implementation of carbon pricing alone might cre- 329:1330–1333. https ://doi.org/10.1126/scien ce.11885 66 ate stranded investments in energy demand sectors, the Fujimori S, Oshiro K, Shiraki H, Hasegawa T (2019) Energy transfor- impact of stranded investment can be reduced significantly mation cost for the Japanese mid-century strategy. 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EMF 35 JMIP study T, Rogelj J, Strefler J, Drouet L, Krey V, Luderer G, Harmsen M, for Japan’s long-term climate and energy policy: scenario designs Takahashi K, Baumstark L, Doelman JC, Kainuma M, Klimont Z, and key findings. Sustain Sci (under review) Marangoni G, Lotze-Campen H, Obersteiner M, Tabeau A, Tavoni van den Berg NJ, van Soest HL, Hof AF, den Elzen MGJ, van Vuuren M (2017) The Shared socioeconomic pathways and their energy, DP, Chen W, Drouet L, Emmerling J, Fujimori S, Höhne N, land use, and greenhouse gas emissions implications: an overview. Kõberle AC, McCollum D, Schaeffer R, Shekhar S, Vishwana- Glob Environ Change 42:153–168. https://doi.or g/10.1016/j.gloen than SS, Vrontisi Z, Blok K (2019) Implications of various effort- vcha.2016.05.009 sharing approaches for national carbon budgets and emission path- Roelfsema M, van Soest HL, Harmsen M, van Vuuren DP, Bertram C, ways. 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Stranded investment associated with rapid energy system changes under the mid-century strategy in Japan

Sustainability Science , Volume 16 (2) – Sep 18, 2020

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Springer Journals
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Copyright © The Author(s) 2020
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1862-4065
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10.1007/s11625-020-00862-2
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Abstract

Japan’s mid-century strategy to reduce greenhouse gas (GHG) emissions by 80% by 2050 requires rapid energy system changes, which may lead to stranded assets in fossil fuel-related infrastructure. Existing studies have shown that massive stranding of assets in the energy supply side is possible; few studies have involved economy-wide stranded asset analysis. In this study, we estimated stranded investments in both the energy supply and demand sectors in Japan in the context of near- term goals for 2030 and the mid-century strategy. To this end, multiple emission scenarios for Japan were assessed based on various emission reduction targets for 2030 and 2050. The results show that stranded investments in the energy supply sec- tors occur mainly in coal power plants without carbon capture and storage (CCS), especially in scenarios without enhanced near-term mitigation targets. Increases of stranded investment in demand sectors were observed primarily under stringent mitigation scenarios, which exceed the 80% reduction target. In particular, investment for oil and gas heating systems in the buildings sector may be stranded at levels up to $20 billion US between 2021 and 2050. We further simulated a scenario incorporating a subsidy for devices that do not use fossil fuels as a sector-specific policy; this reduced the amount of stranded investment in the buildings sector. We confirmed the benefit of enhancing near-term mitigation targets to avoid generating stranded investments. These findings support the importance of inclusive energy and climate policy design involving not only pricing of carbon emissions but also complementary cross-sector economy-wide policies. Keywords Stranded asset · Climate change mitigation · Mid-century strategy · Electrification · Energy policy · Energy system transformation Introduction The Paris Agreement requires that parties submit Nation- ally Determined Contributions (NDCs), which include miti- gation targets for reducing emissions of greenhouse gases (GHGs) by 2030, and encourages each party to formulate Handled by Masa Sugiyama, University of Tokyo, Japan. a long-term low-emission development strategy, known as Electronic supplementary material The online version of this the mid-century strategy (MCS), which focuses mainly on article (https ://doi.org/10.1007/s1162 5-020-00862 -2) contains emission reduction targets in 2050 and later. Japan was the supplementary material, which is available to authorized users. sixth-largest emitter of GHGs in 2018 (Olivier and Peters * Ken Oshiro 2020) and has submitted an NDC of reducing GHG emis- koshiro@athehost.env.kyoto-u.ac.jp sions by 26.0% in 2030 relative to the 2013 level. As a long- term national target, the government of Japan has submit- Kyoto University, C1-3, Kyotodaigaku-Katsura, ted an MCS that includes the quantitative goal of reducing Nishikyo-ku, Kyoto, Japan GHG emissions by 80% in 2050 and the aim of achieving National Institute for Environmental Studies, 16-2 Onogawa, decarbonization of society as soon as possible in the sec- Tsukuba, Ibaraki, Japan ond half of this century. Regarding the consistency between International Institute for Applied System Analysis (IIASA), these national targets and the global goals stated in the Paris Schlossplatz 1, 2361 Laxenburg, Austria Vol.:(0123456789) 1 3 478 Sustainability Science (2021) 16:477–487 Agreement, Oshiro et al. (2019) have suggested that the on disruptive changes between the US NDC and MCS, and 80% reduction goal by 2050 would be on track to the global quantified stranded coal capacity by 2050 using the Global 2 °C goal in terms of the carbon budget based on the cost Change Assessment Model (GCAM). Wang et al. (2019) effectiveness allocation whereas additional efforts would and Malik et al. (2020) estimated the stranded coal capac- be required for 1.5 °C goal, although the national emission ity under the low-emission scenarios in China and India, ranges implied by the global pathways are largely depend- respectively, using both global and national IAMs. These ing on the effort sharing scheme (van den Berg et al. 2019). studies stressed that near-term actions including enhance- In this regard, several studies have assessed the energy ment of NDCs are effective for avoiding the stranding of and economic implications of Japan’s near- to mid-term high-carbon infrastructure such as coal power plants without emission pathways using energy system models and inte- carbon capture and storage (CCS). Meanwhile, few studies grated assessment models (IAMs), that integrate relevant have focused on the energy demand sectors rather than on disciplines such as energy, economy, agriculture, and land the energy supply sector (Davis et al. 2010; IRENA 2017). use into single modeling framework (Fujimori et al. 2019; Therefore, the economy-wide risk of stranded investment Kato and Kurosawa 2019; Oshiro et al. 2019; Silva Herran and measures to avoid those risks remain unclear. et al. 2019; Sugiyama et al. 2019). Generally, these national Given this background, the present study aims to clarify scenario analyses have suggested that attainment of both the the risk of stranded investment in the context of rapid energy NDC and MCS targets without strengthening the near-term system transformation in both energy demand and supply target would require rapid emission reductions between 2030 sectors. To this end, we quantified the stranded investment and 2050, which would involve non-linear energy system arising from rapid energy system transition between 2030 transformation during this period (Oshiro et al. 2017). Such and 2050 in Japan using a bottom-up energy system model. rapid transformation would involve dramatic increases in In addition, this study aims to explore the policy implica- the carbon price and associated mitigation costs during this tions of stranded investment risk mitigation. period (Fujimori et al. 2019; Sugiyama et al. 2019). In this regard, technological, economic and political feasibility is a critical challenge for reaching the mid-century goals. Materials and methods In terms of the feasibility of such drastic energy system changes, existing studies have pointed out transition risks, Model such as carbon lock-in, stranded investment, and premature retirement relative to the expected lifetime of fossil fuel- We used AIM/Enduse [Japan], which is a dynamic recursive related infrastructure (Campiglio et al. 2018; Mercure et al. partial equilibrium model that explicitly represents individ- 2018; Seto et al. 2016). At the global scale, several stud- ual energy-use technologies in both the energy supply and ies using IAMs have indicated that the lack of short-term demand sectors as listed in Table 1. The operating conditions mitigation actions would lead to premature phase-out of coal and amount of new installation of each technology, along power plants and stranding of fossil fuel assets, resulting in with the resulting energy use and GHG emissions, are calcu- increased stranded investment in the energy supply sectors lated based on linear programming to minimize total energy (Bertram et al. 2015; Cui et al. 2019; Johnson et al. 2015). system costs. The results are subject to exogenous param- At the national level, Iyer et al. (2017) explicitly focused eters, including a technological parameter, energy service Table 1 Technology options included AIM/Enduse [Japan] Sector Technology option Industrial sector Sector specific energy technologies in steel, cement, petrochemical and paper production (e.g. CCS for steel/cement production, Next generation coke oven, electric furnace, naphtha catalytic cracker), high efficient industrial boiler, industrial heat pump, high efficient motor, inverter Buildings sector High efficient air conditioner, high efficient water heater (e.g. heat pump water heater), electric heat pump water heater, fuel cell, high efficient lighting, high efficient appliance, high performance building envelope including thermal insulation Transport sector Fuel economy improvement, hybrid electric vehicle, plug-in hybrid electric vehicle, battery electric vehicle (BEV), fuel-cell electric vehicle (FCEV), natural gas vehicle, biofuel, high efficient train, high efficient ship, high efficient aircraft Power generation sector IGCC w/CCS, IGCC wo/CCS, IGFC w/CCS, IGFC wo/CCS, Advanced gas combined cycle (ACC) w/CCS, ACC wo/CCS, Fuel cell gas combined cycle w/ or wo/CCS, Nuclear, Onshore wind power, Offshore wind power, Solar PV, Geothermal, Bioenergy, Hydropower, Pumped hydro storage, Stationary battery storage, Reinforcing electricity interconnection capacity, Hydrogen generation by electrolysis 1 3 Sustainability Science (2021) 16:477–487 479 demands, and emissions constraints. The detailed model lifetime of coal power plants with their expected or planned description, including equations and parameter assump- lifetimes. Johnson et al. (2015) appraised stranded invest- tions, was reported by Kainuma et al. (2003). For this study, ment in monetary units by multiplying the stranded capac- we used a model that incorporates an electricity dispatch ity with the annualized cost. In this paper, we quantified module and a detailed regional classification scheme that stranded capacity and investments. Here, stranded capacity divides Japan into 10 regions (Oshiro et al. 2017; Oshiro is estimated as the stock quantity that is never in operation and Masui 2015). The model used in this study employs a in each time step. The assumptions for the expected lifetime 1-h time representation for electricity load to account for the of each infrastructure and device type are summarized in impacts of variable renewable energies (VREs), whereas the Table S1 in the ESM. The stranded investment calculation previous version had 3-h resolution. The power sector mod- in this paper followed the method of Johnson et al. (2015), ule includes measures taken to integrate VREs into the grid, which entails multiplying the stranded capacity by the annu- such as electricity storage, demand response (DR) using bat- alized investment of each technology using a 5% interest tery-powered electric vehicles and heat pump devices, and rate. To measure the amount of stranded investments associ- interconnections. The capacity of the energy infrastructure ated with climate policy implementation, the stranded capac- is calculated based on newly installed capacity and residual ity and investment are represented in this study as additional capacity remaining today, which is in turn calculated based values compared to the baseline case wherein no additional on the constructed year, capacity, and expected lifetime of climate policy is implemented, unless otherwise noted. each plant. In the energy demand sectors, numerous mitiga- Detailed descriptions of stranded investment estimation in tion options are included in the sectors of industry, build- this study, including the equations used, can be found in the ings, and transportation, such as energy-efficient devices Supplementary texts in the ESM. and fuel changes. The details of these parameter assump- tions have been reported previously (Fujimori et al. 2019). Introduction of CCS is considered in the power and industry Scenario sectors, while CCS-ready and conversion to CCS-equipped plant after operation are not taken into account in the model. Assumptions on climate policy, socio-economic, and tech- The solution horizon of AIM/Enduse [Japan] is based on nology developments are based on the harmonized sce- recursive dynamic which is myopic for technological and nario design of the Energy Modeling Forum (EMF) 35 economical changes in the future. In each period, investment Japan Model Intercomparison Project (JMIP) (Sugiyama for energy technologies is determined by minimization of et al., under review). We assumed several scenarios based total energy system costs which include initial, operation and on a combination of different mitigation levels in 2030 and management and emission costs of technologies. The detail 2050 and considering various emission reduction speeds on investment calculation is summarized in the Electronic (Table  2). The 26by30 + 80by50 scenario, which meets Supplementary Material (ESM). It means that technological the NDC target (26% reduction in 2030 with respect to the and economic changes, such as availability of new technol- 2013 level) and the 80% reduction goal by 2050 of Japan’s ogy, changes of carbon prices and energy import prices, are MCS, was used as the central scenario. We also assessed not taken into consideration in investment calculation. the 36by30 and 16by30 scenarios for the 2030 target, which achieve 36% and 16% reductions, respectively. In terms of Stranded investment calculation the 2050 target, 70%, 85%, and 90% scenarios, referred to as 70by50, 85by50 and 90by50, were also taken into con- In the existing literature, several indicators are used to rep- sideration. In addition to the 70by50 and 90by50 scenarios resent the impacts of stranded assets in terms of physical which are included in Sugiyama et al. (under review) for the or monetary units. For example, Bertram et al. (2015); Iyer sensitivity analysis, the 85by50 scenario is also evaluated et al. (2017); Malik et al. (2020) used physical indicators because of non-linear behavior of Japan’s energy systems such as the idling capacity of coal power plants as stranded where the reduction level exceed around 80% in the exist- asset indicators. Cui et al. (2019) compared the average real ing literatures (Oshiro et al. 2019, 2018). Mitigation begins Table 2 Summary of mitigation 2050 policy scenarios 70% 80% (MCS) 85% 90% 2030 policy 16% 16by30 + 70by50 16by30 + 80by50 16by30 + 85by50 16by30 + 90by50 26% (NDC) 26by30 + 70by50 26by30 + 80by50 26by30 + 85by50 26by30 + 90by50 36% 36by30 + 70by50 36by30 + 80by50 36by30 + 85by50 36by30 + 90by50 1 3 480 Sustainability Science (2021) 16:477–487 in 2020 for all scenarios, and the emission trajectories are the emissions reductions targets for 2030 and 2050, which linearly interpolated between 2020 and 2030 and between are summarized in Fig. S1. As depicted in Fig.  1a–d, in 2030 and 2050. all mitigation scenarios, increase of low-carbon resources In the baseline scenario, no specific climate policy is which include renewables, nuclear and fossil fuel with CCS, taken into account, whereas mitigation options whose energy efficiency improvement, and electrification are key investment can be recovered owning to their energy sav- options to meet the long-term goals. While the share of low- ing, so called no regret options, can be introduced even in carbon resources declines around 2015 due to the suspension the baseline scenario in AIM/Enduse [Japan]. It should be of nuclear power, it reaches 70% or more by 2050 owing to noted that there are critical issues to assume a baseline as deployment of renewables, restart of nuclear power plants no-policy scenario (Grant et al. 2020), the baseline scenario and CCS. Generally, energy supply-side indicators, such as in this study, however, did not consider additional policy the proportions of low-carbon resources in primary energy since Japan’s emission pathways and associated energy sys- supply and power generation, vary among scenarios after tem are very close between the no-policy and current policy 2030 (Fig. 1a–b, Figs. S2 and S3). In the energy demand scenario according to the multi-model studies conducted in sectors, development of energy efficiency and electrifica - Roelfsema et al. (2020). Also, the climate impacts on energy tion are drivers of decarbonization, and variations among system, which are pointed out in Grant et al. (2020), are not scenarios are found mainly after 2040, later than the energy taken into consideration in this study. supply indicators (Fig. 1c, d, Fig. S4). Carbon prices and In addition to the scenarios in EMF35-JMIP, sectoral energy system costs increase over time, with especially rapid policy scenarios were assessed in this study to explore their changes after 2040 in the 90by50 scenarios (Fig. 1e, f). In effects in reducing stranded investment. As a sectoral pol- the 36by30 scenarios, high carbon price and energy system icy, we assumed introduction of a subsidy after 2030 that costs are observed in 2030 due to the additional emission accounts for one-third of the installation cost of electrified reductions. In those scenarios, the carbon price reaches devices in the buildings sector, such as high-efficiency air around $3,000 US per t-CO by 2050, and additional total conditioners and heat pump water heaters, based on a policy energy system costs relative to the baseline account for in Japan called the ASSET (Advanced technologies promo- around 2% of GDP in 2050. tion Subsidy Scheme with Emission reduction Targets) scheme, implemented by the Ministry of the Environment Stranded investments (IGES et al. 2016). The assumption on nuclear power availability follows Stranded investments accumulated between 2021 and 2050 Oshiro et al. (2017), where the nuclear power generation are summarized in Fig.  2a. The total amount of stranded is generally identical to that stated in the NDC, with an investment under the 16by30 scenarios is double or more extension of lifetime to 60 years for some nuclear plants. those of the 26by30 and 36by30 scenarios, mainly due to This assumption is identical with the LimNUC case in the greater stranded investment in the energy supply sector. By JMIP harmonized scenario (Sugiyama et al., under review). contrast, in terms of 2050 emission levels, the variations in In terms of socio-economic conditions, GDP growth is stranded investment among scenarios are moderate, espe- based on that of the NDC until 2030, equivalent to around cially among the 80by50, 85by50, and 90by50 scenarios. 1.7% growth, and with the Shared Socio-economic Pathway Stranded investment in energy demand sectors is generally (SSP) 2 assumption thereafter (Riahi et al. 2017). Population smaller than that in the energy supply sectors, but reaches growth is consistent with the medium-fertility and medium- around $20 billion US in the 90by50 reduction scenarios. mortality estimate of the National Institute of Population Energy demand investments are stranded mainly in the and Social Security Research (IPSS 2017). These assump- buildings sector, where they increase dramatically from tions are identical with the HarmDem scenario of Sugiyama 2040 to 2050 in the 85by50 and 90by50 reduction scenarios et al. (under review). The assumptions underlying the socio- (Fig. S5). Long-term stranded investment is also observed in economic and energy service demand indicators used in this the industry sector, but its impact is smaller than that of the study are summarized in Table S2. buildings sector. Stranded investment in the transport sector is mainly due to short-term stranding of the public transport such as train because of its relatively longer lifetime and Results residual inefficient capacities. In the 90by50 reduction sce- narios, the stranded investments in energy demand sectors Energy system changes exceed those of energy supply sectors. Figure 2b shows the relationship between the cumula- As show in Fig. 1, long-term energy system changes in both tive stranded investment and cumulative CO emissions the energy supply and demand sectors are needed to achieve during 2021–2050. The gray area indicates the 95–105% 1 3 Sustainability Science (2021) 16:477–487 481 Share of low carbon in Share of low carbon in Final energy a b c primary energy electricity relative to 2010 80% 100% 100% 60% 75% 75% 40% 50% 50% 20% 25% 25% 0% 0% 0% 2010 2020 2030 2040 2050 2010 2020203020402050 2020 2030 2040 2050 Share of electricity in Carbon prices (US$/t−CO ) Energy system costs d e 2 f final energy (% of GDP) 50% 2.0% 40% 1.5% 30% 1.0% 20% 0.5% 10% 0.0% 0% 0 2010 2020 2030 2040 2050 2010 2020203020402050 2010 2020 2030 2040 2050 16by30 26by30 36by30 70by50 80by50 85by50 90by50 Fig. 1 Energy system transitions in the different scenarios. Share of d Share of electricity in total final energy demand. e Carbon prices. f low-carbon energies in a primary energy supply and b electricity sup- Additional energy system costs per GDP relative to the baseline. The ply, where low-carbon energies include renewables, nuclear and fossil line color refers to the emission reduction rate in 2050 relative to the fuel with CCS. c Final energy consumption relative to the 2010 level. 2010 level range of the 26by30 + 80by50 scenario carbon budget, which energy demand sectors and the speed of emission reduction. is consistent with Japan’s NDC and MCS. At the levels of Although stranded investment in energy demand sectors is the NDC and MCS, the stranded investment in the 16by30 trivial with changes of less than 5% in annual emissions, it scenario accounts for more than $75 billion US, which is rises exponentially at higher emission reduction rates. approximately three times larger than that in the 26by30 scenarios. This result suggests that 2030 emission levels are Stranded investment in energy supply the key determinant of stranded investment within a carbon budget category. As shown in Fig. 2a, the energy supply sector is the largest The amount of stranded investments is affected by the contributor to total stranded investment in most scenarios. speed of emissions reduction and energy system transition. This result is due to the rapid system transition in the energy Figure 3 shows the relationships between stranded invest- supply sector, especially upscaling of low-carbon energies, ments and the speed of C O emission reduction, which differ and the associated phase-out of fossil fuel-related infrastruc- between the energy supply and demand sectors. In the energy ture. Figure 4a shows the stranded coal capacity over time supply sector, stranded investment increases in the 2–5% without CCS. Because the capacity factor of coal power range of annual emission reductions and becomes saturated plants without CCS in 2050 approaches zero in all scenarios in scenarios where the emission reduction rate exceeds 5%. (Fig. 4b), the stranded capacity in 2050 is comparable to The near-term goal level also drives saturation of stranded the residual coal capacity shown in Fig. S6. In the 16by30 investments in the energy supply sector. By contrast, there is scenarios, because installation of new coal plants continues an exponential relationship between stranded investments in until 2030 (Fig. S7), stranded capacity accounts for more 1 3 482 Sustainability Science (2021) 16:477–487 a b < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MC < NDC&MCS S S S S S S S S S S S NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS NDC&MCS > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MC > NDC&MCS S S S S S S S S S S S ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% ± 5% 20 25 70by50 80by50 85by50 90by50 20 22 24 Cumulative CO emissions (Gt−CO ) 2 2 Residential Industry 70by50 80by50 85by50 90by50 Commercial Energy Supply Transportation 16by30 26by30 36by30 Fig. 2 a Cumulative stranded investment between 2021 and 2050. sectors resulted in negative value. b Cumulative stranded investments The horizontal axis refers to the emission reduction level in 2050. as a function of cumulative C O emissions between 2021 and 2050. The placement of bars refers to the 2030 target. Because the addi- The colors of shaded area refer to the level of carbon budgets tional investments from the baseline scenarios are shown here, some than 30 GW between 2040 and 2050. By contrast, stranded Stranded investment in energy demand capacity peaks before 2040 in the 26by30 and 36by30 sce- narios, with levels around 10 GW or less by 2050. Because Increased stranded investments in energy demand sec- the stranded coal capacity peaks around 2030–2040 and tors occur mainly under deep decarbonization scenarios declines thereafter in most scenarios, stranded investment that require 85% and 90% emission reductions by 2050. in energy supply sectors becomes saturated, as shown in In particular, the buildings sector would face premature Fig. 3b. The capacity factor of gas power plants accounts for retirement of fossil fuel-related devices (e.g., oil and gas around 20% or less by 2050 in the 80by50–90by50 scenarios space- and water-heating systems). Figure  5a shows the (Fig. 4c), and stranded gas capacity without CCS is limited investment in non-fossil technologies in the buildings compared with that of coal (Fig. S8). This difference is due sector, including renewables, electricity, heat, and hydro- to the role of gas power plants as back-up power generation gen under selected scenarios in which the carbon budgets resources for integration of VREs into the electricity grid in are similar to that of the 26by30 + 80by50 scenario. The conjunction with other resources, such as electricity storage results in other scenarios are summarized in Fig. S 10. batteries and demand responses. In the 16by30 + 90by50 scenario, non-fossil investment Figure S9a depicts the comparison of the stranded coal increases by more than six times between 2040 and 2050. capacity and capacity of coal with CCS. Since the capacity In the 26by30 + 80by50 and 26by30 + 85by50 scenarios, of coal with CCS accounts for around a half of peak stranded the investment level is doubled and tripled during this capacity in some scenarios, it suggests the possibility of period, respectively, leading to increased electrification reducing stranded investment by introducing power plants rates between 2040 and 2050 (Fig. 1d). Similarly, stranded with CCS-ready. Nevertheless, the peak stranded capacity investment can occur in the industry and transport sec- still reaches more than 20GW in the most of 16by30 sce- tors, but these impacts are smaller than those in the build- narios when assuming CCS-ready is fully implemented for ings sector (Fig.  2a, Fig. S5). While lifetime of sector coal power plants (Fig. S9b). specific technologies in the industry sector is assumed around 30  years similar to thermal power plants in the power sector, stranded investment in the industry sector is much smaller than that in the power sector. It is because some industrial technologies are already introduced in 1 3 Cumulative stranded investment (billion US$) 16by30 26by30 36by30 Cumulative stranded investment (billion US$) Sustainability Science (2021) 16:477–487 483 Total stranded energy investments 2050 policy 2030 policy 70by50 16by30 80by50 26by30 85by50 36by30 90by50 0% 5% 10% 15% 20% Annual rate of CO emissions reduction (%/yr) Stranded investment in energy supply Stranded investment in energy demand b c 0% 5% 10% 15% 20% 0% 5% 10%15% 20% Annual rate of CO emissions reduction (%/yr) Annual rate of CO emissions reduction (%/yr) 2 2 Fig. 3 Relationship between average annual rate of CO emissions reduction and stranded investment in a energy sector, b energy supply sectors, and c energy demand sectors the baseline scenario and the most of technologies are because the sectoral policy would cause earlier retirement of exhausted in the mitigation scenarios. fossil based devices between 2030 and 2040 (Fig. S12). The required subsidy accounts for about $15 billion US per year in Eec ff ts of sectoral policies 2050, which is equivalent to around 0.2% of GDP (Fig. S13). The amount of subsidy is similar across all scenarios because Given the impacts of stranded investments in the buildings end-use electrification is the important mitigation option by sector under the most stringent scenarios, the effects of sec- 2050. Although the implementation of sectoral policies is toral policies on reducing the stranded investment were esti- effective for avoiding generating stranded investments, the mated. Figure 5b and Fig. S11 show comparison of stranded cumulative amount of stranded investment in the buildings investments in the buildings sector between scenarios with sector in the 16by30 + 90by50 scenario is much larger than that and without the sector-specific policies that promote near-term in the 26by30 + 80by50 scenario. This result implies that near- penetration of non-fossil infrastructure. Sectoral policies can term mitigation is still a critical driver of stranded investment reduce stranded investments in the buildings sector by one- in both the energy demand and supply sectors, even though the third in the 16by30 + 90by50 scenario. In the most scenarios, sectoral specific policies are implemented. sectoral policies result in decrease of stranded investment in the buildings sector, whereas in the limited scenarios, such as the 36by30 + 80by50 scenario, stranded investments in the SecPol scenario is larger than that of NoSecPol scenario 1 3 Stranded investment (billion US$/yr) Stranded investment (billion US$/yr) Stranded investment (billion US$/yr) 484 Sustainability Science (2021) 16:477–487 70by50 80by50 85by50 90by50 16by30 26by30 36by30 Coal without CCS Gas without CCS b c 80% 80% 16by30 26by30 60% 60% 36by30 40% 40% 20% 20% 0% 0% 2030 2040 2050 2030 2040 2050 Fig. 4 a Stranded coal capacity for power generation without CCS, and average capacity factor of b coal power plant without CCS, and c gas without CCS scenarios. This result is mainly due to the need for removal Discussion and conclusion of residual emissions from fossil fuel-related infrastructure in the demand sectors, such as gas and oil heaters and boil- Based on the scenario analysis presented in the previous ers, to attain rapid electrification. In some scenarios with a sections, we explored two processes driving increases in 90% reduction in 2050, the amount of stranded investment in stranded investment. First, energy supply investment can be energy demand sectors exceeds that in energy supply sectors. stranded beginning in the near term due to delayed mitiga- From these findings, it is reconfirmed that weak near-term tion action and associated development of emission-inten- mitigation actions would exacerbate the feasibilities of long- sive infrastructure, such as coal-fired power plants without term climate goals. CCS. In this case, the energy supply infrastructure becomes Nevertheless, the impacts of stranded investment can be idle when the emission constraints become stringent. Sec- reduced through near-term actions and sectoral policy imple- ond, energy demand investment becomes stranded during mentation. In the energy supply sector, the stranded coal rapid emission reductions and the associated energy sys- capacity can be reduced by half or more by strengthening tem transition around 2050 under the deep decarbonization 1 3 70by50 80by50 85by50 y50 2020 90b 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 70by50 80by50 85by50 90by50 Capacity factor (%) Stranded capacity (GW) Capacity factor (%) Sustainability Science (2021) 16:477–487 485 a 120 b Residential Commercial 538% −33% 205% 10 114% −26% 45% 37% 125% 30% −20% −13% −18% 0 0 36by30 26by30 26by30 16by30 36by30 26by30 26by30 16by30 +70by50 +80by50 +85by50 +90by50 +70by50 +80by50 +85by50 +90by50 Fig. 5 a Investments for non-fossil-based technologies in the build- narios without sector specific policy. SecPol indicates scenarios with ings sector. Non-fossil technologies include renewables, electricity, sector specific policy. Only the scenarios where carbon budget cat- heat, and hydrogen. b Cumulative stranded investment between 2021 egory is same with the 26by30 + 80by50 scenario are presented and 2050 in the buildings sectors. NoSecPol indicates the default sce- the 2030 emission target. Implementation of CCS-ready for of total power generation, equivalent to 277 billion kWh coal power plants would also be effective to reduce stranded in 2030. In this study, coal power generation in 2030 was coal capacity, while their economic attractiveness is depend- estimated at 0.86 EJ in the 26by30 scenarios (239 billion ing on the remaining lifetime of power plants. In energy kWh) based on a cost-optimization mechanism. If the energy demand sectors, stranded investments can also be reduced policy is implemented as planned, stranded capacity may by implementing sector-specific policies, such as a sub- become greater than the estimates reported in this study. sidy for devices that do not use fossil fuels. A 33% subsidy Third, whereas stranded investment is represented by the for electrified technologies such as heat pump space- and cumulative investment between 2021 and 2050, as shown in water-heating systems would lessen stranded investments Fig. 2, the stranding of long-life infrastructure such as coal in the buildings sector by one-third. This finding indicates power plants without CCS could occur after 2050, especially that holistic policy design in conjunction with implementa- in the 26by30 and 16by30 scenarios, as shown in Fig. 4a. tion of a simple carbon pricing policy could make the deep Although the cumulative amount of stranded investment by decarbonization goal feasible. 2050 which was similar between the 26by30 and 36by30 There are several limitations and caveats to interpreta- scenarios than that of the 26by30 scenario, would be greater tion of the stranded investment estimates in this study. First, if impacts in the second half of this century were considered. in this study, we used a myopic energy system model that Fourth, while this study considered only a subsidy for elec- does not account for future changes in the operating rate of trified devices as a sectoral policy, many other policies that each infrastructure type; hence, the stranded capacity might can reduce stranded investment risks are possible. For exam- be overestimated compared to the intertemporal model. ple, a fossil fuel use ban would directly reduce the amount of Nevertheless, according to an existing multi-model study stranded investment in energy demand sectors. In addition, (Bertram et al. 2015), the amount of stranded investment support for other decarbonized energy carriers in addition estimated with a myopic model is not always higher than to electricity, such as the renewable sources of bioenergy, that based on intertemporal optimization. Therefore, the heat, and hydrogen, would be effective. Policies promoting model type used for each time horizon would not signifi- structural changes, such as effective urban design targeting cantly affect the key findings of this study. Secondly, Japan’s effective use of centralized district heating, would also help NDC states that the share of coal is targeted at around 26% to reduce the stranding of investment in end-use devices. 1 3 NoSecPol SecPol NoSecPol SecPol NoSecPol SecPol NoSecPol SecPol Investment additions (billion US$/yr) Cumulative stranded investment (billion US$) 486 Sustainability Science (2021) 16:477–487 Cui RY, Hultman N, Edwards MR, He L, Sen A, Surana K, McJeon The findings of this study have several policy implica- H, Iyer G, Patel P, Yu S, Nace T, Shearer C (2019) Quantifying tions in the Japanese context. 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