Switzerland submitted its formal climate plan months before the Paris Agreement1 and was among the first countries that met the “midnight survival deadline”2,3. The Swiss long-term climate strategy4 aims at net-zero greenhouse gas (GHG) emissions in 2050, with an intermediate target of a 50% reduction in 2030 from the 1990 levels. Both targets are to be achieved using Internationally Transferred Mitigation Options (ITMOs). The domestic mitigation effort in 2030 should reach at least 37.5% GHG emissions reduction from the 1990 levels—the amount of ITMOs needed to achieve the 2050 target is currently unspecified.

However, the Swiss voters rejected key measures included in the amended CO2 Act in June 2021. The Swiss direct democracy revealed major societal concerns on energy transition’s feasibility and costs, which are also concealed in many countries worldwide5. The rejection of the amended CO2 Act has roots in the many challenges Switzerland faces in achieving its pledges.

First, the Swiss energy strategy6 aims to gradually phase out existing nuclear power (safety is the sole criterion for the phase-out time) that supplies 36% of the electricity today. This entails an energy security challenge7, also confronted by many countries aiming at decommissioning strategic energy supply assets8.

Second, Switzerland starts from a low-carbon baseline—the country is at the Top-5 of the energy transition index9. It needs to maintain its carbon-free electricity supply and make progress in decarbonising industry, buildings and transport4 that have less clear emissions reduction trajectories than the energy transformation sector10.

Third, Switzerland has limited domestic renewable resources11 and depends on imported energy carriers that risk the security of supply. Solar photovoltaics have the largest potential for further development, albeit at low irradiation levels. Hydropower has little room for expansion. Low wind speeds, natural landscape preservation, and population density challenge wind power. Wood, which is important in the global decarbonisation pathways12,13, is confronted by forest management and preservation14. Biogas faces high costs and complex logistics due to the many small farms15.

Fourth, domestic CO2 capture and storage are surrounded by large geological uncertainties16. Switzerland should connect to international CO2 transport networks and storage sites17, competing for access with other European countries. Moreover, there is some social resistance to onshore domestic CO2 sequestration in Switzerland16, a phenomenon attributable to the unfamiliarity of the population with CO2 capture, storage and utilisation projects.

Fifth, the population increase in Switzerland for the next 30 years is projected to be 20%—one of the highest in Europe18. Without strong efficiency measures, energy security and emissions mitigation goals are at risk.

Switzerland needs robust, feasible solutions for its energy transition. Identifying these solutions requires frameworks that reflect societal, political and technical realities and not overly abstract models19. Such a framework is the Swiss TIMES Energy systems Model (STEM)20, with rich techno-economic details and sectoral interdependencies supported by state-of-the-art technology assessment21. While TIMES-based frameworks are widely used for assessing decarbonisation pathways22,23,24, STEM includes unique features identified as important in literature when assessing the energy transition19: long-time horizon, high temporal resolution, consumer segmentation, grids topology, unit commitment, energy and ancillary services markets, demand shifts, variability of renewables representation, age structures of assets, endogenous load and demand curves.

The work described in this study was performed within the Scenarios and Modelling Joint Activity (see “Methods” and Note #2 in the Supplementary Information) of eight large collaborative energy research programmes of major Swiss universities, the Swiss Competence Centres for Energy Research (SCCERs), during 2013-202025. Each SCCER programme promoted collaboration across different disciplines and dealt with a particular challenge of the Swiss energy transition: decarbonisation of buildings, decarbonisation of industry, decarbonisation of mobility, electricity supply and grid infrastructure, electricity and heat storage, biomass potential for energy uses, society. The Joint Activity Scenarios and Modelling (JASM) combined the modelling capabilities of all eight SCCERs to develop a set of scenarios for the transition of the Swiss energy system towards net-zero emissions by 2050. In JASM, STEM was coupled with several sector-specific models, e.g., for buildings, grids and industry.

The analysis with STEM in JASM fills the research gap in scenarios assessing net-zero emissions for Switzerland. So far, only the pledges made in 2015 of reducing emissions by 70–85% in 2050 from 1990 levels26 were assessed, including energy system transformation27, economic implications28,29, social perceptions30, the need for system flexibility31, and the role of transport32, domestic biomass resources33 and efficiency34. A few studies have assessed a net-zero Swiss energy system by 2050 but focused on the electricity sector35 or neglected transition effects36,37. These studies overestimate technology deployment rates and underestimate costs. The Swiss Federal Office of Energy produced the “Energy Perspectives 2050+”38 to assess net-zero emissions pathways for Switzerland. Still, the employed framework is commercial with little transparency and weak in representing sector coupling and interdependencies. Recently, a quantitative scenario analysis towards net-zero emissions in Switzerland was published by the Swiss Association of Electricity Enterprises (VSE)39. The study uses results from Energy Perspectives 2050+ as inputs for the energy demand and assesses the energy supply sectors configuration at snapshot years. A qualitative scenario analysis on net-zero emissions pathways in Switzerland is also available in the literature, providing a scenario framework for assessing the co-evolution of society and decarbonised energy systems40.

Our work contributes to the literature by quantifying energy system transformation pathways reflecting different contextual factors and transition lock-ins. It informs on future energy system configurations and is addressed mainly to decision-makers and the general public. The analysis of this paper results from alternative pathways regarding the deployment of renewable energy, the level of energy security, the degree of market integration and the speed of the technical progress in energy technologies. It suggests technically feasible solutions, although we should acknowledge that these could entail political and societal challenges regarding their implementation that are not addressed in this work.

We find that achieving net-zero CO2 emissions by 2050 requires scaling up renewable energy technologies. The installed capacity of solar PV needs to double almost every decade from now to 2050. Wind energy deployment needs to accelerate in Switzerland at unprecedented rates to contribute to the winter electricity supply. Failing to deploy domestic renewable energy sources puts energy security at risk. Electrification of final energy consumption needs to reach 50% in 2050 (from 28% in 2050), but the electricity consumption per capita is slightly reduced from today by employing energy savings practices. Hydrogen penetrates industry and mobility sectors and it is used directly or indirectly via synthetic fuels in 2050. Carbon capture and bioenergy play an important role in reaching deep decarbonisation. About 9 Mt CO2 are captured in 2050, with half of them from negative emissions technologies. Overall, a cost-efficient deep decarbonisation of the Swiss energy system requires all options to be on the table. The increase in energy system cost to achieve a carbon-free energy system depends on resource availability and exploitation, social acceptance of new technologies, technology progress and innovation, and integration of local, national and global energy markets. According to the analysis with STEM of seven contrasted scenarios with different socio-economic, technical and geopolitical contexts (see section “A suite of contrasted net-zero scenarios”), the average increase in per capita energy system cost is between 320 and 1390 CHF2019 per year compared to a Baseline scenario.

Results and discussion

A suite of contrasted net-zero scenarios

We define several net-zero scenarios to address the role of resource availability, technological progress, energy market integration and social acceptance (Table 1). They benchmarked against a business-as-usual trajectory. All scenarios consider 60 years lifetime for nuclear power plants and share the same macroeconomic and demographic assumptions41. The GDP increases by 1.2% p.a. from 2020 to 2050, and the population grows from 8.7 million today to 10.4 million in 2050. Resource potentials41,42 and technical progress assumptions11,41,42 vary consistently across the scenarios.

Table 1 Outline of the net-zero CO2 emissions scenarios and the business-as-usual scenario for Switzerland.

Overarching features of STEM are given in the “Methods” section in the subsection entitled “The Swiss TIMES Energy Systems Model (STEM)” and in Supplementary Information Note 1. The links of STEM with the other sectoral models in SCCER JASM, which provided direct or indirect (in the form of side-constraints) input to STEM regarding technical and societal barriers in the deployment of energy technologies and infrastructures are described in Supplementary Information Note 2.

More details on the scenario definition are also given in the “Methods” section and specifically in the “Scenario design” subsection. The main assumptions of the assessed scenarios are described in Supplementary Information Note 3 and provided in Supplementary Data 1.

The following sections discuss results and provide insights from the net-zero scenarios. Additional results from the scenario analysis are given in Supplementary Information Note 5. A detailed comparison of all scenarios is provided in Supplementary Information Note 7. In addition, a comparison between the net-zero scenarios of this study and those from the Swiss Federal Office of Energy (the “Energy Perspectives 2050+” study38) is presented in Supplementary Information Note 6. At the same time, an additional variant of CLI, which assumes 50 years lifetime for the existing Swiss nuclear plants, is discussed in Supplementary Material Note 8. Extensive result tables from all seven scenarios assessed are available in Supplementary Data 2. Finally, all codes and data needed to reproduce the charts shown in Figs. 16, which are discussed in the next sections, are provided in Supplementary Data 3.

Fig. 1: Main developments in end-use sectors in the net-zero scenarios.
figure 1

Panel (a) shows the final energy consumption by sector in each net-zero CO2 emissions scenario, excluding consumption in international aviation. Panel (b) displays the average demand for space heating in terms of kWh per square metre across all residential buildings in Switzerland for the BAU, CLI, ANTI and SECUR scenarios. Panel (c) provides the contribution of the different heating technologies in the residential heating supply in the different scenarios for the year 2020 and 2050. Finally, panel (d) presents the mix of car drivetrains in 2050. The bold numbers at the top of each bar denote the total of the quantities shown in the bar. As shown in the figure, residential and transport sectors bear most of the energy transition effort. The transition requires an accelerated build-up of electric heating and mobility. The share of heat pumps in 2030 in the CLI scenario rises to 35%, before reaching 77% in 2050. In SECUR, heat pumps supply 45% of the space heating demand in 2030 to cope with the reduction of imported gas to half of today’s quantities, and their share reaches 72% in 2050. In transport, the share of electric cars in 2030 must be at least 25% of the total car stock across all scenarios, while by 2050 eight every ten cars in Switzerland run with electricity.

Fig. 2: Electricity and hydrogen demand by sector and demand for biogenic and synthetic zero-carbon fuels by sector (electricity storage refers to stationary storage).
figure 2

Panel (a) shows the electricity demand by sector in the CLI scenario, while the dotted line represents the total electricity demand in the BAU scenario. Panel (b) compares the electricity demand by sector in 2050 across all the net-zero CO2 emissions scenarios assessed in the study. Panel (c) displays the hydrogen consumption by sector, including the hydrogen directly injected into the natural gas grid. Finally, panel (d) shows the consumption of the zero-carbon fuels, of biogenic or synthetic source, by sector in the different net-zero scenarios assessed in the study. The bold numbers at the top of each bar denote the total of the quantities shown in the bar.

Fig. 3: Energy supply development related to electricity and hydrogen production.
figure 3

Panel (a) displays the electricity supply by major source in the CLI scenario from 2020 to 2050 and compares it with the total electricity supply in BAU. Panel (b) focuses on the electricity supply by major source for the different net-zero CO2 emissions scenarios in 2050. Panel (c) presents the hydrogen supply by major technology in the different net-zero CO2 emissions scenarios in 2050. Panel (d) shows the net imports by major energy source in the CLI, ANTI and SECUR scenarios—the net imports of the MARKETS, INNOV and LC scenarios are similar to the ones in CLI and, therefore, are not shown in the figure and the reader is directed to Supplementary Data 2 for these imports. The bold numbers at the top of each bar denote the total of the quantities shown in the bar. The net imports in MARKETS, INNOV and LC are quite similar to CLI and they are not shown in the figure. For the net imports in MARKETS, INNOV and LC please see Supplementary Information Note 7). In SECUR, gas imports in 2030 are reduced to half from today’s levels towards complete import independency by 2050. Achieving energy security and net-zero emissions goals would require almost two times the deployment of renewable energy that is seen in CLI to produce synthetic e-gases. Still, clean molecules must be imported to decarbonise the transport sector in Switzerland.

Fig. 4: Dispatch of power plants and deployment of electricity storage and flexibility options.
figure 4

Panel (a) shows the seasonal electricity dispatch in the CLI scenario for 2050. Panel (b) displays the electricity hourly dispatch in the CLI scenario for a typical Saturday in summer 2050, with the x-axis denoting the hours within the typical Saturday. Panel (c) presents the uptake of the electricity storage from 2020 to 2050. Finally, panel (d) shows the electricity profile across the typical days and hours of STEM for charging the electric cars (on the left axis) and the profile of the electricity that is feedback to the grid from the electric cars (on the right axis). The bold numbers at the top of each bar denote the total of the quantities shown in the bar. The electricity dispatch is given in seasonal and hourly scales. The latter refer to the typical hours and days in STEM. STEM identifies four seasons (FAL- autumn, WIN- winter, SPR- spring, SUM- summer) and three typical days in a season (SA- Saturday, SU- Sunday, WK- working day) with hourly resolution (H1–H24 hours in a day). For the different types of battery storage the following abbreviations are used: HV High Voltage, MV Medium Voltage, and LV Low Voltage. Pump storage capacities in 2030 include Nant de Drance (900 MW at generator) that came online in 2022 and Ritom II (120 MW at generator) plants that is expected to be online by 2025. The flexibility provided by the transport sector is via smart charging and vehicle-to-grid schemes in the CLI scenario. The charging and vehicle-to-grid profiles are given for each typical day and hour in STEM.

Fig. 5: CO2 emissions trajectory for net-zero and CO2 captured.
figure 5

Panel (a) shows the CO2 emissions by sector excluding the emissions from international aviation, which are not part of the climate change mitigation target of Switzerland. Panel (b) shows the CO2 captured in industry, electricity production, hydrogen production, biofuel production, and direct air capture. Panel (c) compares the amounts of the captured CO2 by source across the net-zero emissions scenarios assessed in the study. Finally, panel (d) provides insights into the required negative emissions needed in each net-zero emissions scenario from direct air capture and CO2 capture from bioenergy for electricity, hydrogen and biofuel production. The bold numbers at the top of each bar denote the total of the quantities shown in the bar.

Fig. 6: Cost of the Swiss energy system to reach net-zero CO2 emissions in 2050.
figure 6

Panel (a) shows the difference in cumulative discounted energy system costs by sector between each net-zero CO2 emissions scenario and the BAU scenario—the applied social discount rate is 2.5%. Panel (b) presents the difference in the cumulative discounted energy system costs by type of expenditure between each net-zero CO2 emissions scenario and the BAU scenario. Panel (c) displays the increase in the cumulative energy system cost in each scenario compared to the energy system cost of the BAU scenario. Panel (d) shows the per capita discounted cumulative energy system cost in each net-zero scenario, while panel (e) displays the exponential evolution of the annual per capita energy system cost in each scenario (with the average undiscounted per capita energy system cost from 2020 to 2050 given in the parenthesis). Finally, panel (f) shows the undiscounted annual energy system cost as percentage of the gross domestic product in Switzerland. The bold numbers at the top of each bar denote the total of the quantities shown in the bar. The reported costs are calculated by taking the difference between the energy system cost of the net-zero and BAU scenarios, i.e. the reported costs for the climate change mitigation scenarios come on top of the BAU costs. The costs in the end-use sectors refer to investment and operating costs for: demand and energy conservation technologies, on-site energy supply and storage technologies (e.g., CHPs, solar PV, batteries, thermal storage) and distribution infrastructure. The costs in the energy conversion sector refer to investment and operating costs for: power plants (other than on-site CHPs and solar PV in end-use sectors), utility-scale storage for energy carriers and heat, hydrogen and biofuel production, and transmission infrastructure. The upstream sector costs include purchases and sales related to the cross-border trade and investment and operation costs of cross-border infrastructure. In MARKETS and INNOV, the costs are benchmarked with variants of BAU having the same energy markets integration and technological progress as in MARKETS and INNOV. Comparing MARKETS with the original BAU results in a policy cost of 6 billion CHF2019 instead of the 75 billion CHF2019 shown in the figure. The policy cost of INNOV, when comparing it with the original BAU scenario, is −17 billion CHF2019 instead of 58 billion CHF2019). The social discount rate used in the cost calculations is 2.5%. It should be noted that the increase in the energy system cost is affected (a) by the emissions reductions in BAU, (b) by the choice of the social discount rate, and (c) by the market conditions and technical progress assumed in each net-zero scenario compared to BAU.

Per capita final energy consumption in 2050 is similar to today’s world average

In realising the net-zero emissions target, Switzerland moves towards a “2000 Watt” society43. This implies a per capita final energy consumption of around 50 GJ/yr. in 2050 compared to 109 GJ/yr. in 2000 in the CLI scenario— exceeding the −54% target in the Swiss energy strategy 20186. The buildings and transport sectors bear the most efficiency improvement efforts (Fig. 1). On average, the space heating energy consumption across all buildings reduces from 87 kWh/sqm (2010-2020 average) to 45 kWh/sqm in 2050. Renovation rates of the existing residential buildings accelerate from 0.9% p.a. in 2020 to 1.7% p.a. on average for 2020–2050, and the adoption of the MINERGIE® standards44 amplifies.

As electrification of the space heating is probably irrealisable for all buildings45, wood/biogas and district heating warrant further consideration and double their share in 2050 from today. Transport calls for a portfolio of drivetrains. Its transition is characterised by (a) the period until 2030 with many options competing; (b) the period 2030–2040 with rapid penetration of electric vehicles; and (c) the period 2040–2050 with the dawn of fuel cell drivetrains for large vehicles and long-distance transport.

Achieving net-zero and minimising import dependency (SECUR scenario) requires bringing forward the energy efficiency efforts observed in the CLI scenario by a decade. In SECUR, the per capita final energy consumption drops to 45 GJ in 2050. As low electricity imports in winter challenge electro-mobility, uptake of fuel cell vehicles is the highest in SECUR—powered via domestic green hydrogen.

Failing to accelerate renewable deployment (ANTI scenario) necessitates improvements in energy efficiency at the levels of SECUR. Heating and mobility are not decarbonised in 2050. Reliance on bioenergy with CO2 Capture and Sequestration (CCS) increases by shifting wood from end-use to energy conversion (by 2050, 49% of bioenergy in ANTI is used in electricity and hydrogen production vs 44% in CLI, and only 35% today—Fig. 2).

Electricity consumption exceeds oil and gas together for the first time in history by 2040, but zero-carbon molecules are needed

Invariably across all scenarios, electrification of final energy reaches 50% in 2050 compared to 28% today. Efficiency gains in stationary sectors maintain electricity consumption at today’s levels. However, transport alone increases electricity demand by 10 TWh/yr. in 2050 from today (Fig. 2).

Domestically produced hydrogen is of growing importance. While hydrogen first enters industry by 2030, the automotive applications lead to improvements in fuel cells that spill over to other applications and carry forward infrastructure development. Next to transport, new uses of hydrogen in district heating supply occur by 2040, driven by fuel cell CHP micro-grids that help avoid high upfront costs of cogeneration in buildings (Fig. 2). Hydrogen also becomes important when targeting energy security and reduction of import dependency. Domestic e-fuel synthesis from green hydrogen via high-temperature electrolysis compensates for the curtailed imports (SECUR scenario). However, limited deployment of renewables delays hydrogen penetration by a decade (ANTI scenario), jeopardising the decarbonisation of sectors requiring zero-carbon molecules and necessitating increased energy efficiency measures and imports.

Domestic bioenergy use doubles in 2050 from today, requiring full mobilisation of waste, manure and forest wood resources. Compared to today, there is a shift in bioenergy use and uptake from end-uses to energy conversion sectors. This shift starts to be more pronounced after 2030 (Fig. 2) as biogenic CHPs penetrate district heating, wood with CCS for electricity and hydrogen production delivers negative emissions, and swarms of load-following biogenic CHPs provide flexibility for better integration of solar PV and wind33 technology. For heat supply, pellets replace wood chips and firewood due to their higher energy density, efficiency, and easier distribution.

However, the decarbonisation of transport requires imported biogenic and synthetic electricity-based liquid fuels (short: e-fuels). These are also indispensable in the SECUR scenario (Fig. 3), signalling that import independence across the entire energy system is a formidable task.

A carbon-free electricity supply requires doubling wind and solar production in each decade from today to 2050

A carbon-free electricity supply after a nuclear phase-out requires an unprecedented deployment of solar and wind power (Fig. 3). At a minimum, non-hydro renewable electricity would need to compensate for today’s nuclear electricity (ANTI scenario). By 2050, the electricity sector delivers 2 Mt CO2/yr. negative emissions via CCS deployment at 50% of the waste incineration plants and additional investment in 300 MW of large-scale wood-based electricity generation with CCS.

Regarding domestic hydrogen production, electrolysis is the main option until 2040. While electrolysis could cover all hydrogen needs, it is costly to integrate it into the energy system at a large scale. Thus, a cost-effective mix to supply high hydrogen demands beyond 2040 includes green and blue hydrogen. Wood gasification with CCS occurs in all scenarios, delivering 1.6 Mt CO2/yr. negative emissions in 2050, but it is challenged by limited wood resources and the availability of adequate CO2 transport and storage infrastructure, like all CCS technology.

In the SECUR scenario, electrolysis becomes a major option to meet high domestic needs for hydrogen and fuel synthesis that compensate for oil and gas imports curtailment. Wood gasification cannot be further scaled up due to resource limits and competition from other sectors. Hence, high-temperature electrolysis is deployed to fill the supply gap. In 2050, 31 TWh/yr. of electricity are consumed to produce 26 TWh of hydrogen—of which more than 50% is directed to fuel synthesis (Supplementary Information Note 7). Still, the domestic supply of e-fuels is insufficient to cover the transport demand. Imports of e-fuels from renewable-based hydrogen occur in all scenarios, with a maximum of 58 PJ/yr. in ANTI and a minimum of 11 PJ/yr. in SECUR (close to today’s levels of imported biofuels). The analysis from SECUR and ANTI scenarios clearly shows that ailing to deploy domestic renewables puts energy security at risk.

A reliable low-carbon energy system requires coordinated flexibility from all its actors

In achieving the net-zero target, a suite of flexible options need to be deployed: energy storage, Power-to-X (PtX), demand-side response (DSR) in heating and electric loads, grid-to-vehicle (G2V) and vehicle-to-grid (V2G) services in transport (Fig. 4).

Pump hydrostorage of 4.5 GW with around 520 GWh storage capacity balances the high-voltage grid. It is complemented with 2.1 GW batteries providing 11.5 GWh storage at the medium- and low-voltage grid. Smart G2V absorbs excess electricity, with a maximum charging requirement of 6 GW on a summer Sunday at noon—on average, 75% of the EVs are charged at this time. V2G schemes could provide 2 GWp in spring and summer evenings if EVs have been charged with low-cost electricity. In 2050, the contribution of V2G is around 1 TWh/yr., with 13% of the EVs participating in this scheme. DSR enables intra-day shifts of electricity loads of 620 MWp in buildings and 110 MWp in industry, in line with estimated Swiss potentials46.

Thermal storage gains interest due to the increased coupling of electricity and heat systems. About 35 GWh of storage (of which 70% is low temperature) at weekly and daily time scales are needed in 2050 in CLI. Embedded thermal storage in heat pumps and water heaters enable intra-day shifts of 3 TWh/yr. of electricity used for heating in buildings in 2050, decoupling the time of heat provision from electricity consumption.

The seasonal balancing of the energy system is achieved via electricity imports, Power-to-X, and thermal storage. Electricity imports emerge in all scenarios in winter in 2050, ranging from 3 TWh/yr. (in SECUR) to 8 TWh/yr. (in MARKETS/INNOV), which are similar to BAU (7 TWh/yr. in 2050) and the winter imports observed for Switzerland in the past decade47. P2X contributes to seasonal balancing via hydrogen or synthetic fuels storage of up to 2 TWh/yr. in 2050. About 1.4 TWh/yr. seasonal thermal storage is also deployed as local or virtual community grid storage.

The need for secondary operating reserve (aFRR+) increase by 44% in 2050 from today’s levels. On average, hydropower provides 75% of the aFRR+ demand, aggregated distributed units (CHPs, batteries, heat pumps) 20%, and electric vehicles 5%.

Without CO2 capture and negative emissions, the net-zero target cannot be achieved

The net-zero scenarios require 370 Mt additional cumulative CO2 reductions from 2020 to 2050 relative to the emissions trajectory of the BAU scenario. While system-wide net zero CO2 emissions are achieved, industry emissions remain in 2050. These are offset via CO2 capture in electricity and hydrogen production (Fig. 5).

CO2 capture emerges from 2040 and amounts to about 9 Mt CO2/yr. in 2050. SECUR has the lowest amount of captured CO2 as the goal for zero import dependency also implies the elimination of imported fossil fuels. In contrast, LC has the highest amounts of captured CO2 because hard-to-abate emissions from buildings that have limited mitigation options are offset via CCS. On average, across all scenarios, about half of the captured CO2 in 2050 is from negative emission technologies, viz.BECCS and DACCS (Fig. 5).

Based on the current estimates that the domestic CO2 sequestration potential in Switzerland is 50 Mt CO248, regulations and policy agreements are necessary to access European infrastructures for transferring and storing CO2 outside Switzerland49.

Four pillars for deep decarbonisation in Switzerland

The analysis highlights four pillars for deep decarbonisation in Switzerland. First, to unlock domestic renewable potentials for solar PV and bioenergy whilst maintaining at least the current levels of hydropower. Second, to foster energy and emissions markets integration by fortifying the availability of imported zero-carbon fuels and securing access to international CO2 storage sites, e.g., in the North Sea. Third, to scale up technology innovation and improve emerging technologies. Finally, the fourth pillar is lifting socio-economic barriers related to the storage of captured CO2 and creating public awareness to accept the domestic deployment of negative emissions technologies.

Today, the average energy system cost per capita, as the model calculates, is around 3200 CHF2019 per year. The BAU scenario, which reduces the CO2 emissions by 42% in 2050 from 1990 levels, entails an increase to about 5700 CHF2019 in 2030 and 7000 CHF2019 in 2050. These costs relate to the maintenance and replacement of existing infrastructure and investments in new technologies (also to cope with the nuclear phase-out). As the BAU scenario does not include decarbonisation targets, it can be argued that these costs reflect the increase in the system cost to supply the future energy service demands by accounting for the ageing and phase-out of the existing assets. In CLI, the per capita energy system cost rises to around 5900 CHF2019 in 2030 and 8500 CHF2019 in 2050. Hence, the increase in energy system cost due to the decarbonisation of the Swiss energy system starts at about 200 CHF2019/capita and reaches 1500 CHF2019/capita in 2050.

The SECUR scenario entails an energy system cost per capita increase of 6500 CHF2019 in 2030 and 9600 CHF2019 in 2050. In ANTI, the limited deployment of domestic renewables induces an additional per capita cost of 6200 CHF2019 in 2030 and 10700 CHF2019 in 2050 (Fig. 6). Hence, the cost of achieving net-zero CO2 emissions by 2050 is about 1000—3700 CHF2019 above the BAU per capita cost in 2050.

The difference in the energy system cost between the net-zero scenarios and BAU shows a shift from low capital expenditure (CAPEX) and high operational expenditure (OPEX) in BAU to high CAPEX and low OPEX. Transport and residential sectors bear the highest policy costs. However, there are cost savings from reduced imports of fossil fuels (Fig. 6). The cumulative discounted energy system costs from 2020 to 2050 increase by 4–19% of the BAU costs to net-zero CO2 emissions. ANTI and SECUR display the highest costs, while MARKETS and INNOV are the lowest. This shows that citizen mobilisation and national and international policy co-design are important for the energy transition. Across all scenarios, the cumulative discounted per capita policy cost to achieve net-zero emissions from 2020 to 2050 varies between 5800 and 25400 CHF2019 discounted at 2.5% (or, on average, 320–1390 CHF2019/yr. and per capita, undiscounted).


Despite the limited domestic resources and the population growth of at least 20% projected for the next 30 years, it is technically feasible for Switzerland to achieve net-zero CO2 emissions, even within the context of increased energy security and import independence. Table 2 summarises key energy transition enablers for which societal, market or technical barriers must be removed to avoid financial burdens.

Table 2 Main enablers of the Swiss energy transition (see also Supplementary Information Note 5 for additional results).

The energy system transformation requires decisive actions in each sector to reduce uncertainty in investors and society. Energy transition policies must account for systemic interdependencies. For example, imposing emissions standards in buildings and vehicles could create cost-inefficiencies if the potential of other sectors to mitigate at a lower cost is neglected. Or, implementing technology bans too early could increase energy bills for consumers. Even the most well-designed policies become expensive if citizens do not accept them or inefficiencies from non-energy sectors persist (e.g., lengthy licensing procedures). The analysis finds a sweet-point in policy implementation between the CLI scenario, which includes several sectoral policies and the LC scenario, which follows a cost-optimal trajectory. Moreover, fostering technology innovation (INNOV scenario) and integration into international energy markets (MARKETS scenario) reduces costs to 60% of CLI’s costs.

Decarbonisation of residential heat entails Herculean efforts50,51. Carbon and energy performance requirements, mandates for solar energy in buildings and incentives for renewable and district heating could help reduce emissions, but they would need to be complemented with cost- and benefit-sharing between energy companies, tenants and landlords in order to improve the attractiveness of renovations, accelerate smart technologies, and lift the split of incentives barrier. To avoid jeopardising industry’s competitiveness, market designs for low-carbon intensity products, industrial symbiosis52, technology standards, voluntary agreements, and timely replacement of ageing infrastructure with low-carbon alternatives can form a possible portfolio of policy options. Decarbonisation enablers in transport include clean vehicles, incentives for new infrastructure, increased digitalisation to support demand management, automated and connected mobility, and efficient multi-modality. Biofuels and e-fuels are part of the solution only when considering land-use and carbon sources needed for their production53. Strengthening and expanding the emissions trading scheme to new sectors (buildings, transport, and small industries) could accelerate the energy transition and mitigate financial burdens from evasive taxation. The shift of electricity production to lower grid levels will require closer cooperation between System Operators and participation for storage and flexible consumers in energy and ancillary services markets. Energy security calls for support to technologies that can contribute to winter electricity supply, such as alpine PV, wind, geothermal, storage and demand-side response. To realise the deployment of these technologies, simplifying the permitting procedures for new renewable projects is required next to financial incentives. As the energy transition requires every domestic renewable kWh of energy, it is also necessary to lift financial and logistic obstacles in biogas production from manure and pursue balanced forest wood management by considering non-energetic uses and eco-services14.

Hydrogen deployment requires strong climate policy signals to mitigate investment risks. Pilot projects for negative emissions technologies can confirm their potential and gradually expand their deployment. The energy transition is costly without closer integration with the EU energy, carbon markets, and infrastructure.

However, the solutions found at the national level need to align with energy supply and demand options at the Cantonal or municipalities levels, as Swiss policy-making procedures are highly decentralised. The energy transition implications to all sustainability dimensions must be further assessed and emphasised. Quantifying external costs for cost-benefit analysis and Multi-Criteria Decision Analysis, including environmental and social aspects of the energy transition, while accounting for different stakeholder preferences, are currently pursued within an integrated framework including STEM. Another development in progress with STEM is to lift the limitation of exogenous lifestyle changes and sustainable and circular economy and improve the representation of consumer energy behaviour and social acceptance of new technologies by pursuing closer collaboration with scholars from Social Sciences and Humanities. Finally, the need to account for the co-evolution of energy, economy, environment and social systems is not fully accounted for in our analysis as the employed framework is a partial equilibrium bottom-up techno-economic model. To this end, more collaborative and interdisciplinary research is needed, including the fields of energy systems analysis, economics, social sciences and humanities, and political sciences, to address this limitation in our work.


The Swiss TIMES energy systems model (STEM)

The Swiss TIMES Energy Systems Model (STEM)20 is based on The Integrated MARKAL-EFOM System (TIMES) framework developed by the International Energy Agency’s Energy System Technologies Analysis Program (IEA-ETSAP)54. STEM is a partial equilibrium framework representing the entire energy system, from an engineering techno-economic perspective, with a full range of energy processes, including exploitation, conversion, transmission, distribution, storage, and energy end-use. As STEM is a bottom-up technology-rich model, it does not explicitly include broader socio-technical or political perspectives of the energy system and energy transition55. The model consists of the following sectors of the energy system:

  • Upstream sector, including the production and extraction of resources, energy imports and exports

  • Conversion sector that includes electricity and heat production, hydrogen production, production of biofuels and e-fuels

  • Final energy consumption sectors, including industry, services, residential, transport and agriculture

  • CO2 capture, sequestration and utilisation sectors

STEM aims to supply energy services at a minimum energy system cost by simultaneously making energy technology investments and operating decisions to reach a demand-supply equilibrium state. The equilibrium found by STEM has the property that the total surplus is maximised. STEM has a long-term horizon. This analysis focuses on the developments until 2050, with reporting years 2020, 2030, 2040 and 2050. We apply a 2.5% social discount rate and technology-specific interest rates of up to 5.5%, depending on the sector and technologies. In each year, 288 operating hours are considered, representing four seasons, three average days per season (viz. working day, Saturday and Sunday), with 24 h resolution.

For each energy service demand sector and energy use, the model considers hourly profiles, which are given exogenously20, but the hourly energy consumption needed to meet the hourly energy service demand is fully endogenous56. Based on construction year and size, different residential building classes are distinguished. The transport sector includes passenger and freight transport, with different modes and many types of vehicles for each mode. Stock-based material flow analysis approach for the evolution of building stock45, discrete choice methods for appliances, Gompertz functions for car ownership, etc., are used to project energy service demands for the subsectors according to the scenarios’ macroeconomic and demographic developments. Climate change impacts on heating and cooling demands, as well as on energy resources (e.g., water), are explicitly accounted for based on the climate scenarios that are consistent with the energy scenarios41.

STEM includes options for producing synthetic fuels, and it explicitly represents the storage, transport and distribution required for the secondary energy carriers. A particular emphasis was given to the electricity sector to address systems with high shares of variable renewable energy. Four electricity grid transmission and distribution levels are represented, from very high to low voltage33. STEM includes direct current (DC) power flow model modelling of the electricity transmission grid with 15 nodes and 319 bi-directional lines57,58. Technical operating constraints for the hydrothermal power plants are approximated via a continuous relaxation of the unit commitment problem59. They include ramping rates, minimum stable operating levels, part-load efficiency losses, minimum online and offline times and start-up costs. While it is unsuitable for analysing actual system operation, it is valuable for including short-term decisions in long-term planning. The energy supply and use assets can be retired before the end of their technical lifetime when they have higher fixed or operating costs than the investment cost of new alternatives60.

While energy service demands are determined exogenously based on macroeconomic and demographic developments, the model endogenously considers energy savings measures for each end-use to reduce energy consumption. These include the switch to a more efficient technology or another energy carrier like electricity, building renovations (walls, windows, floors, roof), adopting waste heat recovery practices, optimisation of motor drive operations and other industrial equipment, investments in specific industrial processes and measures that reduce consumption, and many others. Supplementary Information Note 1 elaborates a list of the technical measures in the model that characterises the demand reduction in our modelling framework. The costs for deploying such measures are fully accounted for in the objective function when minimising the total energy system cost.

Though STEM includes many technical and policy measures, changes in consumer behaviour or lifestyles, such as lowering indoor temperatures, are not considered because of the lack of reliable costs associated with the shift in consumer behaviour (e.g., discomfort costs). STEM is a bottom-up techno-economic partial equilibrium modelling framework. In this regard, consumer behaviour and acceptance of new technologies (in the meaning of openness or willingness to invest) is approximated by side constraints regarding the deployment level of these technologies or the access to the remaining exploitable and sustainable renewable energy potential.

STEM endogenously accounts for the stochastic variation of renewable energy availability, demand, and the residual load curve61. Besides energy markets, the requirements for primary and secondary operating reserves are endogenously modelled with explicit representation of ancillary services markets62. Hence, STEM includes both market- and technical-based flexibility mechanisms. For example, STEM represents energy storage, demand-side management schemes in the end-use sectors, grid-to-vehicle and vehicle-to-grid services from electric vehicles and detailed Power-to-X pathways31. The energy storage options are at different time scales and sizes, ranging from daily storage options to weekly and seasonal storage options31. In addition, we distinguish between centralised and large-scale storage (e.g. pumped hydro and large stationary batteries) and distributed storage (e.g. batteries and heat storage). The demand-side management schemes enable the shifting of electricity loads related to heating, cooking, washing, etc., also based on discomfort costs, shifting windows, and maximum load constraints derived from Swiss consumer surveys63,64,65 and international studies66,67.

The cross-border electricity trade in STEM is modelled through exogenous hourly electricity import price profiles. These profiles are based on interfacing STEM with complicated electricity systems and grid simulation models for the transmission grid of Switzerland and Europe, assuming European developments align with the ENTSO-E TYNDP scenarios41. Additionally, trade patterns concerning the potential of Switzerland to export excess electricity to the neighbouring countries are considered, which result from transmission grid reliability constraints and other power plant dispatching constraints in Switzerland and its neighbours.

Regarding modelling the district heating infrastructure, we apply an approach that considers the aggregate of the corresponding network infrastructure, distinguishing between existing and newly built equipment. When a pipeline comes to the end of its life, it can be replaced with a new investment or refurbished. In this regard, STEM does not allow disinvestments in the district heating network. However, the model ensures that the overall annualised investment and operating, and maintenance costs of the district heating infrastructure are covered in each year of the projection period. The connections to district heating of existing buildings68 are explicitly modelled in STEM. When existing buildings are demolished, their connections can be used by new buildings built in the same locations. The development of the building stock is based on a detailed dynamic stock model. The model was developed in cooperation with our partners in this project from the University of Geneva45. New buildings can also require new district heating connections, depending on the overall energy system cost minimisation. When the new connections exceed the current capacity of the process, then a new investment is made. The overall district heating potential is limited in the model at around 18 TWh/yr.69.

Particular emphasis has been given to STEM for modelling battery electric vehicles. The charging and discharging profiles of electric vehicles are endogenously determined in STEM. We distinguish four consumer segments with different driving profiles and, consequently, charging and discharging needs. For each consumer segment, there is also a set of constraints to guarantee that the electric vehicle cannot be used if there is not enough energy in the battery to perform the requested trip at a given time. With the consumer segmentation and the set of constraints for having enough energy in the battery to complete the car trips, we try to improve the realism of the resulting charging and discharging profiles. The modelling of electric vehicles in STEM allows each vehicle’s battery to provide electricity back to the grid (at a cost reflecting the necessary electronic equipment to achieve the reverse electricity flow). Thus, the estimation of the number of electric cars participating in vehicle-to-grid schemes is calculated from the model results. It is based on the driving, charging and discharging profiles of the different consumer segments, the amount of electricity these segments give to the grid, and the total number of cars in each segment—all these aspects are endogenously determined by STEM based on the mobility energy service demands32.

The emissions included in STEM are CO2 from fuel combustion and CO2 from the cement production process, which are generated by decomposing raw materials. The model does not include the CO2 emissions from international aviation and navigation in the overall mitigation target since these are not included in the Swiss National Determined Contribution and are not part of the Paris Agreement of 2015. STEM also does not calculate other non-CO2 Kyoto GHGs related to the following sectors: from agriculture related to livestock, manure management, agricultural soils, liming, and urea applications; from the waste sector on solid waste disposal, biological treatment of solid waste, incineration and open burning of waste (other than the waste consumption for cogeneration of electricity and heat) and shredding; from fire damages; from land use, land use change and forestry.

STEM lacks endogenous mitigation options and technologies for non-CO2 GHG emissions. Marginal Abatement Cost Curves (MACCs) can approximate emissions reductions from N2O, CH4, SF6, etc., but these would need to be exogenously calculated based on complementary modelling frameworks and studies. In the context of the present study, performed within the project Swiss Competence Centre for Energy Research Joint Scenario and Modelling (SCCER JASM), such complementary modelling competencies to provide STEM with these MACCs were not available. Hence, we focused on the transformation of energy systems to achieve net-zero CO2 emissions. This implies that the remaining non-CO2 emissions in 2050, around 5.7 Mt CO2-eq if the targets for reducing the non-CO2 GHG stated in the Long-Term Climate Strategy of Switzerland4 are met, should be compensated abroad in our analysis, as noted in the Swiss National Determined Contribution26.

Most of the 5.7 Mt CO2-eq that remain in 2050 and compensated abroad are emitted from the agriculture sector. This sector does not have mitigation options in STEM other than those for emissions from fuel combustion. Agriculture accounted for about 14% of the total GHG emissions in Switzerland in 2019, and in the Long-Term Climate Strategy of Switzerland the sector accounts for more than 95% of the remaining GHG emissions in 2050. We include the CO2 emissions from fuel combustion in agriculture (about 10% of the total emissions from agriculture) but not the non-CO2 GHG that are predominately related to biological and biophysical processes and come from diffuse sources or sources that fluctuate in terms of time and space. The complexity of the Swiss agriculture sector, with many small farms and various business operations, challenges the development of generally applicable mitigation measures—an argument also noted in the Long-Term Climate Strategy of Switzerland4. Given that more data and research is needed for identifying mitigation options for the GHG emissions from agriculture, and given that the Swiss climate change mitigation policy relies on the use of Internationally Transferred Mitigation Options for offsetting these emissions, we opted to exclude non-CO2 emissions in our analysis. However, in an ongoing project, we have established collaborations with researchers from the agriculture and forestry sectors to assess potential mitigation options for the sector.

Finally, CO2 domestic and cross-border pipelines are also considered for transferring captured emissions. As stated above, additional details about the structure and features of STEM are provided in Supplementary Information Note 1.

Scenario design

The scenario analysis was performed within the Swiss Competence Centre for Energy Research (SCCER) Joint Activity Scenarios and Modelling (JASM)70 by using the Swiss TIMES energy systems model (STEM) of Paul Scherrer Institute. The SCCER energy programme25 is a collection of eight university-networked research activities in Switzerland from 2013 to 2020 on energy efficiency, energy grids, electricity supply, economy, society, energy behaviour, mobility and biomass resources and technologies. It was funded by InnoSuisse, aiming to provide solutions to the technical, social and political challenges of the Swiss energy transition. In JASM, modelling teams from the eight SCCERs worked together to analyse the technical feasibility of energy transformation pathways to net-zero. This approach is different from other efforts to define long-term energy strategy for Switzerland, as it is based on the combined output of the Swiss energy systems research community. In JASM, a framework that soft-links various energy systems and sectoral technical-economic models from the project partners was developed. All models used a consistent set of drivers and scenario definitions41, derived from the Swiss Administrative Federal Offices.

In the context of the SCCER JASM, STEM is enhanced via the collaboration with the other modelling teams regarding renewable potentials, import prices, the potential for domestic sequestration of CO2, cross-border trade infrastructure, characterisation of electricity, hydrogen, biofuel and synthetic fuel production technologies, the definition of end-use technologies such as boilers, appliances and vehicles, climate change impacts on energy demand and energy resources (e.g. water), and side-constraints reflecting consumer energy behaviour and social acceptance. The links between STEM and the rest of the sectoral models and approaches employed in SCCER JASM are detailed in Supplementary Information Note 2.

STEM explores possible energy futures based on contrasted scenarios. Unlike forecasts, scenarios do not presuppose knowledge of the main drivers of the energy system. Instead, they consist of a set of coherent assumptions about the future trajectories of these drivers, leading to a cohesive organisation of the energy system under study. A scenario builder carefully tests the hypotheses for internal consistency. A scenario definition requires at least four inputs: energy service demands, resources and potentials, policy settings, description and availability of technologies.

In developing the SCCER JASM scenarios, we examined two key methodologies:71 (a) using input from knowledge carriers such as scientific experts or stakeholders; (b) using intuitive logics (IL) or scenario axes. We also considered using the newly developed Cross Impact Balance (CIB) approach71 that enables the traceability and reproducibility of scenarios’ construction processes. At the same time, CBI can lead to scenarios with better consistency and more complete assumption sets than the two traditional approaches mentioned before. However, CIB was evaluated as unattractive to our exercise because of the considerable time and human resources required (which were unavailable to us) and the quality risks associated with its use by non-experienced teams in this method.

Therefore, in the SCCER JASM study, we based the scenario design process on our expertise with the scenario development methods we followed for the World Energy Council (WEC) scenarios72. The WEC methodology combines developing scenarios using three axes, the so-called energy trilemma, which refers to a balance between affordability, sustainability and security in energy system transformation73, and stakeholder expertise73. In SCCER JASM, the scenario axes were based on research and policy questions in Switzerland within the active discourse from 2017 to 2020, which was the timeframe within which the current exercise was performed. These mostly referred to the technical feasibility of transforming the Swiss energy system to a carbon-free energy supply and use and its economic implications regarding energy system costs and required investments in energy infrastructure. The technical feasibility of the presented pathways does not directly imply social, economic, or political feasibility.

Thus, the scenarios aim at exploring technically plausible pathways for reaching carbon neutrality by 2050 by adopting socio-economic drivers from Swiss Administrative and Federal Offices41. It should be noted that the assessed pathways presented in this study are only a subset of all the possible future energy system developments, and they are neither mutually exclusive nor forecasts. The main scenario axes used in their construction are: (a) technology development; (b) market integration; (c) security of energy supply. The first axis relates to sustainability, as new and immature technologies are needed in a decarbonised energy system. The second axis relates to market integration and trade of energy carriers, and emissions permits can reduce the mitigation costs. The third axis relates to the security of energy supply, which applies to different time and spatial scales, i.e., from hourly to annual and from local to global.

The BAU scenario extrapolates the energy consumption trends and energy policies in place for the future. It tries to answer the research question, “where does Switzerland land in terms of CO2 emissions in 2050 if we continue the business-as-usual practices?”. The scenario reflects the energy and climate policy instruments currently in force but not measures under discussion and not included in the energy and climate Swiss legislation until 2019. Table 3 shows the major energy and climate policies implemented in the Baseline scenario.

Table 3 Major energy and climate policies implemented in the BAU scenario for Switzerland.

The CLI scenario assumes that the world gradually shifts to implement green economy strategies. Most governments agree on driving environmental sustainability through related policies and practices. Emissions trading markets are globally introduced, and many international governments support standards and protocols to improve energy efficiency and adopt circular economy practices. Society has become aware of the challenges related to climate change mitigation and embraces cleaner and smarter lifestyles than in the BAU scenario. Shifts in energy consumer behaviour towards energy efficiency gradually developed in CLI from 2020 onwards. Thus, energy demand is reduced in the end-use sectors as more energy-sufficient lifestyles are developed. In this scenario, due to the global cooperation and effort in mitigating climate change, Internationally Transferred Mitigation Options (ITMOs) are available for Switzerland at competitive prices, which help the country compensate for a part of the domestic emissions abroad. Besides, CO2 grids are developed, connecting the European countries, and regulations enabling carbon emissions transportation for sequestration abroad are enacted after 2030.

Until 2030 the energy sector in Switzerland is regulated through taxes, feed-in tariffs, capital subsidies and state-funded building renovation programmes to encourage clean energy solutions. Switzerland implements climate change mitigation policies to achieve emissions cuts by 2030, many of which are described in the revised CO2 Act74. A key subset of these policies is provided in Table 4.

Table 4 Major policies implement in the CLI scenario in Switzerland.

Besides the core net-zero scenario, i.e. CLI, four additional scenarios are defined that are aimed at providing insights into the following questions related to energy transition towards net-zero CO2 emissions: (a) what if the renewable expansion is not realised due to low population mobilisation (scenario ANTI); (b) what if the current bilateral energy agreements between Switzerland and the EU fail (ANTI and SECUR); (c) can Switzerland achieve the net-zero ambition by merely relying on domestic resources (SECUR); (d) what are the benefits for the energy transition cost, if increased integration between Swiss and international markets is achieved (MARKETS); (e) how the speed of the transition and its cost is affected by high innovation in low-carbon and clean technologies (INNOV); (f) which sectoral policies are incompatible with a least-cost trajectory to net-zero (LC). The design of these scenarios ensures comparability with CLI, and to some extent, among themselves.

The ANTI scenario assumes an international context with low cooperation in mitigating climate change. Due to the fragmented climate policies worldwide, R&D expenditures in low-carbon technologies are stagnated. There is limited technological progress, and, as a result, both consumers and utilities are faced with high upfront capital costs when adopting low-carbon solutions for energy supply and use. The integration of the Swiss and international energy markets is weaker in ANTI than in CLI, which hinders the availability of imported zero-carbon fuels and energy carriers, including electricity. However, environmental sensitivity still develops at local scales, and climate change mitigation goals are not abandoned. Communities seek to build a more sustainable future locally, and consumers rely on best-fit local solutions for energy supply and demand that maximise local benefits. They increasingly desire products and energy services customised for local contexts, which implies a high willingness to pay for these products. Individualistic lifestyles emerge with uneven energy efficiency and equipment replacement efforts between different consumer groups. A decentralised energy supply supports the development of local energy networks, accelerated building renovations to minimise import dependency at the community level, and widespread e-mobility and intelligent mobility. Local self-sufficiency becomes a priority in the ANTI scenario, which could often conflict with nationally-wide energy and climate targets. There is limited tolerance from society regarding landscape changes for implementing renewable and other low-carbon projects that do not directly benefit the local communities. In this context, we argue that the focus in ANTI is more on adaptation than mitigation, as capital-intensive projects for reducing the carbon footprint of the Swiss energy system are postponed to the future. Regarding implemented sectoral climate policies, the ANTI scenario extrapolates the BAU policies.

The SECUR scenario assumes that the world gravitates toward a multi-polar order, weakening the international governance systems. As a result, economic volatility increases and international trade agreements are not fully implemented due to rising nationalistic policies that make export-oriented growth less critical as a financial strategy. Most countries use whatever capabilities they have to achieve national-wide security in energy supply. Due to weakened international structures, access to energy resources becomes complicated, and import duties increase energy import prices. The shift in priority from environmental sustainability to energy supply security triggers conflicting objectives, but the overall global climate change mitigation targets are not abandoned. Switzerland relies upon its domestic energy resources, including hydropower and other renewable energy sources. The Swiss society is keener in the SECUR scenario than in CLI in fully exploiting sustainable domestic renewable resources to reduce the carbon intensity of the energy system. In SECUR, there is a higher social acceptance than in CLI in implementing projects based on new renewable energy forms such as bioenergy, geothermal and solar. Priority for consumers and utilities in SECUR is the secure and reliable operation of the Swiss energy system, given the weak integration of Swiss and international energy markets. The reduction of the overall import dependency in future is a priority. Domestic grid reinforcement is highly acceptable in SECUR and desirable to mitigate congestion for a secure and reliable grid operation. In terms of implemented sectoral policies, the SECUR scenario includes the ones of CLI. The SECUR scenario relaxes the domestic sustainable exploitable renewable energy potentials to their maximum values in the literature. It additionally imposes a constraint on annual net imports of all energy carriers to be as close as possible to zero without deviating from the net-zero CO2 emissions target in 2050. The right-hand side of the constraint is found by continuously tightening the constraint and keeping the feasibility of the climate target.

The MARKETS scenario is a variant of CLI, which assumes higher global cooperation and integration of the Swiss and international energy markets beyond the levels considered in the core scenarios. Therefore, the MARKETS variant allows increased availability of imported biofuels, synthetic e-fuels, hydrogen and electricity. Priority in MARKETS is decarbonisation through affordable energy, which is also achieved via the development of local energy markets and intelligent prosumage schemes in coordination with national energy markets. As a result, technologies enabling sector coupling, prosumers and storages, demand-side management and vehicle-to-grid enjoy economies of scale, and their costs are lower than in the core scenarios. In supporting domestic and national markets integration, grid congestion is eliminated to a large extent by reinforcing domestic grids. With the focus on new business models based on renewable energy and P2X pathways, the social acceptance for using domestic renewable energy resources is higher than in the core scenarios and similar to the levels in SECUR. All policies included in the CLI scenario are also implemented in MARKETS.

The INNOV scenario is a variant of MARKETS. It assumes the same developments as MARKETS regarding integrating local, national and international energy markets and that a global effort exists to mitigate climate change and achieve the Paris Agreements. Closer international coordination is assumed concerning implementing climate change policies worldwide and reducing the costs of low-carbon technologies in energy supply and demand via increased R&D expenditures worldwide. Circular economy policies and schemes emerge globally, and there is a high level of material efficiency that results in lower energy conservation and renovation costs compared to the core scenarios. Moreover, in the context of a global joint effort to reduce GHG emissions, consumers also have high social acceptance for new technologies. Thus, the costs of clean and low-carbon technologies, such as renewable technologies, alternative vehicles and CCS, and energy supply and demand efficiency measures are lower in this variant than in the core scenarios. As INNOV builds on MARKETS, grid reinforcement and high availability of imported zero-carbon fuels and energy carriers are also assumed in this variant.

The LC scenario is another variant of CLI in which we sought the cost-optimal emissions reduction trajectory by excluding the sectoral policies in CLI (see Table 3 and “Table 4”). The LC scenario is regarded as the Least Cost solution and used as a benchmark to identify sectoral policies in CLI that could potentially entail high costs for energy consumers. The only constraints given to the LC scenario are the resource potentials, which are set to the levels of CLI, and the overarching CO2 emissions reduction targets for 2030 and 2050.

The scenario design and quantification are based on systematic and informed research regarding alternative pathways and their costs. The derived paths are realistic and technically feasible under the evolving uncertainty of technical progress, resources, societal structures, national and international energy policies and markets.

All scenario assumptions used as input to the model are given in Supplementary Information Note 3 and Supplementary Data 1 with the key scenario parameters accompanying this manuscript. Further comparisons of the scenario results are provided in Supplementary Information Note 7. Detailed results are given in Supplementary Data 2 with energy balance tables for each scenario.

It should be noted that quantifying the scenarios by STEM assumes rational agents. In this regard, many of the policy interventions included in the scenarios are of financial nature. Moreover, aspects regarding lifestyle changes and sustainable and circular economy can only be given exogenously to our framework as part of a coherent storyline. An endogenous assessment of these aspects is beyond the scope of this paper as STEM needs further development to capture them. It is a limitation of our work, which we aim to address in future research with stronger collaboration with scholars from the social sciences and humanities fields.

Finally, the assessed scenarios did not include aggressive energy demand reductions in their hypotheses. While aspects of efficient lifestyles and circular economy are included in the scenarios, including ambitious energy savings due to lifestyle changes and beyond the levels achieved with technical measures needs extensive assessment of the energy saving potential that can be achieved with such changes. Such estimates are not yet available for Switzerland in a format that quantitative energy systems models like STEM can use. Thus, to avoid creating a paper exercise by arbitrarily changing the energy demand levels due to lifestyle changes, we opted for the scenario definitions to follow a conservative approach. Still, such a conservative approach is not necessarily out of context, given the uncertainty surrounding the energy demand development and associated with the future lifestyle changes affecting energy consumption behaviour and patterns. We aim to collaborate closely with the social sciences community in Switzerland to identify potential energy demand reductions associated with changes in energy consumption behaviour for the future years. Nevertheless, we should note that the model result regarding the need for accelerating renewable energy and introducing negative emissions technologies to meet the net-zero CO2 emissions target is robust, as a recent study that assumed ambitious demand reductions due to lifestyle changes at global scales shows75.

The meaning of the “policy cost” in a partial equilibrium framework like STEM

In a partial equilibrium framework, the term “policy cost” is defined as the difference in the total energy system cost with and without a specific policy/target, i.e., between the BAU and the suite of the net-zero CO2 emissions scenarios assessed. Given that we do not account for feedback on the energy system to the rest of the economic sectors, we cannot claim that this is the overall cost associated with a specific policy measure. As we also do not account for the distributional impacts of the increased costs on different income classes, our results on the costs of the energy transition have limited information about the affordability of the energy transition.

The total energy system cost comprises: (a) capital costs for investing into and dismantling technologies for energy conversion, transmission and use, renovations and energy savings; (b) fixed and variable operation and maintenance costs; (c) costs for imports and domestic resource extraction and production; (d) revenues from exports; (e) delivery costs for energy carriers; (f) taxes and subsidies of energy carriers and technologies; (g) revenues from recuperation of embedded commodities accrued when a technology’s dismantling releases some valuable commodities and; (h) salvage value of technologies and embedded commodities at the end of the planning horizon. Moreover, the cost structure of the model is vintage-dependent. Thus, the costs for renewing the existing energy system infrastructure, independently of its decarbonisation, are included in the analysis.

The model’s objective is the discounted system cost from 2020 to 2050. For the discounting, a social discount rate of 2.5% is used. It should be noted that sectoral interest rates are applied for investments in energy technologies in the different sectors, which are higher than the social discount rate. In the end-use sectors, the interest rate is set to 5.5%, which implies a 3% risk premium (or hurdle rate) in the investment decision. In the supply sectors, the interest rate for investing in large-scale energy supply technologies is 2.5%, while the interest rate for investing in medium and small-sized energy technologies is 5.5%.

Further, we calculate costs for the baseline scenario (BAU), which does not achieve decarbonisation targets but extrapolates the current energy supply and consumption trends and the stated energy and climate policies in the Swiss legislation.

Our analysis does not include external costs associated with environmental damage, resource depletion, or human health. Moreover, our analysis does not include the distributional impacts of the energy transition on households of different income classes. Thus, it does not address equity concerns and affordability of the energy transition.