Gällivare Municipality covers an area of around 16,800 sq. km. and has a population of 17,431 in 2022. The economy is heavily dependent on the mining industry, which provides the majority of employment opportunities for the local population. Gällivare is undergoing significant changes over the past decade. The town has been relocated to accommodate the increased mining activity, which has involved the demolition and movement of houses as well as the construction of new residential areas. Additionally, there is the restructuring of the ore-to-steel supply chain in Northern Sweden, to produce fossil free steel. The projects aim to leverage the availability of cheap electricity and abundant resources such as iron ore and water in the region. For example, the world’s first fossil-free sponge iron production plant is under construction in Gällivare. These projects are expected to provide new job opportunities and attract other companies in the renewable energy industry to the area. The municipality is putting forth strong efforts to make Gällivare a socially sustainable place and to attract more people to the area. These factors are anticipated to influence the municipality's energy system, resulting in increased demand for energy-intensive services and products.

Gällivare, has an installed capacity of 610 MW hydropower, 121 MW wind power, and 0.16 MW solar power. The primary district heating source is a 40 MW biomass-based combined heat and power (CHP) plant. Gällivare generates the electricity and district heating to meet its demand but imports all other fuels such as biomass and transportation fuels. Industry followed by transport and residential sectors are the major energy consumers. Figure 1 represents the energy demand per sector per fuel type (left) and electricity fuel mix (right) used to meet the demand for the year 2020. For transport sector, the passenger travel demand was 230 million passenger-km and the freight demand was 66 million ton-km in 2020. Figure 2 shows the final energy consumption (FEC) per sector per fuel type (left) and end-use CO2 emissions (right) for the year 2020. FEC refers to the total energy used by end users, such as households, excluding the energy consumed by the energy sector itself while emissions indicate the CO2 released from the energy used. In Gällivare, the share of renewable energy in FEC is around 85 percent in 2020 [21].

Figure 1

(left) Energy demand per sector per fuel type; (right) electricity fuel mix for Gällivare for the year 2020

Figure 2

(left) Final energy consumption per sector per fuel type (renewable fuel includes ambient heat and biomass; fossil fuel includes, petrol, diesel and natural gas); (right) end-use CO2 emissions from fuel imports (up-stream), ELC&DH generation (tail-pipe)

The EU has implemented varied climate and energy targets. Table 1 shows the selected EU targets aimed at addressing climate change (NECPs), improving air quality (NEC), promoting renewable energy (RED), and enhancing energy efficiency. The table includes the national targets proposed by EU for its nations (common targets for all members or specific targets for Sweden) and the targets implemented by Sweden to adhere to the EU targets. It also includes local level targets proposed for Gällivare based on higher-level targets.

The targets, RED, NECP, and NEC were chosen for assessment as they are particularly relevant for the municipality and align with its targets and ambitions. Gällivare has set a municipal net-zero CO₂ emissions target for 2030 and a geographical net-zero CO₂ target for 2045. The municipality is determined to become a sustainable society with the support of the world's first fossil free sponge iron plant (Hydrogen Breakthrough Ironmaking Technology, HYBRIT, [22]), for example by utilizing industrial waste heat in the municipal district heating systems [23]. Leveraging HYBRIT and the cheap electricity in the north of Sweden, it also aims to promote and integrate hydrogen and electricity-based vehicles in the road transport [21]. Moreover, these targets directly address key aspects of sustainable development, including SDG3 (Good Health and Well-being), SDG7 (Affordable and Clean Energy), SDG13 (Climate Action), and SDG11 (Sustainable Cities and Communities). They also indirectly impact other SDGs such as SDG8 (Decent Work and Economic Growth), SDG12 (Responsible Consumption and Production), and SDG14 (Life on Land) [24] which are also the focus areas for the municipality [25].

SSP1 [40] combined with national support for green industries serves as the baseline for all scenarios. In SSP1, the world progressively shifts toward a more inclusive, sustainable, and environmentally conscious development path. This scenario assumes reduced costs for renewable technologies (and hence electricity), high taxes on fossil fuels, increased growth in green industries, and improvements in the efficiency of green technologies.

National support for green industries involves fostering sustainable practices and advancing green technologies through proactive government intervention. This support manifests in several critical ways, including substantial investments in research and development and subsidies for green industries to drive innovation and growth. Renewable electricity generation is prioritized to reduce electricity costs for green industries, making sustainable practices more economically viable. Additionally, significant subsidies are provided for low-carbon vehicles to accelerate the transition to a low-carbon transportation sector. Further details on how these assumptions impact the local level are included in the working paper (Paper III, [38]). Apart from the locally defined targets described below, all other assumptions regarding fuel supply (import limits, fuel prices, taxes, subsidies), demand (demand growth), and technologies (technical specifications, cost, technology availability) remains the same in all scenarios.

In the RED scenario, aligned with the EU's RED, a 29% renewable energy share in the transport sector—encompassing passenger, freight, road, and rail—must be achieved by 2030. The target is applied at the local level and extrapolated to the end of the model horizon, 2050.

The APT scenario is inspired by the NEC to improve the local air quality. Swedish national targets set for 2020 and 2030 are mapped to the local level and are projected to 2050. The Swedish focus is on agriculture, energy consumption, energy supply, industrial processes, transport, and waste management. In this scenario, the targets are applied to the transport sector, as in Gällivare the majority of emissions are from this sector (assuming equal reduction from all identified sectors).

The CTA scenario, inspired by the NECPs, includes targets for CO2 emission reduction from fuel imports, ELC&DH production, energy use in transport, residential, commercial and industrial sectors. Emissions from fuel imports include those generated during extraction or cultivation and harvesting, processing, and transportation of fossil fuels [41] and biofuels [42]. The target is to achieve net zero emissions by 2045 and is supported by interim targets for milestone years 2025, 2035, and 2040. Although the model includes emission factors for CH4 and N2O, these are excluded from the study as their sources, such as fossil fuel extraction for CH4 and agriculture for N2O [43], are not relevant for Gällivare.

The maximum aggregated anthropogenic CO2 emissions [44] to limit the global warming to 1.5°C and 2°C is determined as two different CBs for Gällivare.

Carbon Budget 2°C (CB2). The calculation of remaining carbon budget [45] for Gällivare with an 83 percent chance of not exceeding 2°C is based on the study [46], which has developed and presented the remaining CB for Sweden in accordance with the temperature and equity targets of the Paris Agreement. In the study, the regional CBs were developed in cooperation with the county administrative boards of Sweden. Our study uses this data for Gällivare located in Norrbotten county to estimate its remaining CB. The steps and assumptions involved are as follows:

1. A 14% annual reduction in CO2 emissions from 2024 to 2036 is estimated as needed to contribute to meet the Paris agreement, which is in line with the annual reduction identified for Norrbotten in [46]. This is a simplification, when the reduction in [46] encompasses all sectors, while this study excludes the industry sector, which is the most challenging to mitigate.

2. The emissions for each year, with a 14% annual reduction, is calculated using eq. 1: Emission s t =Emission s t−1 ∗(1−0.14) (1)

3. In year 2023, the CO2 emission in Gällivare was 25 ktons (Emissions₂₀₂₃ = 25)

4. The carbon budget left to be used between year 2024 to 2036 is calculated using eq. 2: C B 2024to2036 = ∑ t=2023 2036 Emission s t C B 2024to2036 =140kton (2)

Carbon Budget 1.5°C (CB1.5). Calculation of the carbon budget left for Gällivare with a 50 percent chance of not exceeding 1.5°C is based on the approximations in [1] and [47] which estimates that the global carbon budget left for a ‘50 percent chance of not exceeding 1.5°C’ is 0.46 for an ‘83 percent chance of not exceeding 2°C’.

The identified CB is applied to emissions within the municipal boundary i.e., it is applied only to energy production and energy use emissions within the municipal boundary excluding export emissions. This is because the CB [46] is calculated based on the Paris Agreement following a top-down approach and excluding import emissions ensures that emissions from traded goods are not double counted by both exporting and importing countries.

ELC&DH accounts for the least emissions, approximately 1% in Gällivare (Figure 4). Despite the sector being largely decarbonized, emissions persist due to the use of peat as fuel in CHP plants. The municipality has made a conscious effort to reduce peat usage and increase biomass utilization. Currently, the CHP plants are primarily using biomass, a trend expected to continue. On average (across the scenarios and model years), around 13% of emissions stem from fuel imports (both fossil and biofuel imports). This highlights the importance of accounting for indirect emissions associated with fuel use within the municipality. The largest share, 87% on average, arises from fuel use in the transport sector.

Figure 4

CO2 emissions from fuel imports (up-stream), ELC&DH generation (tail-pipe), and transportation (tail-pipe) in different scenarios

In the RED scenario, renewable energy integration in transport cuts emissions by half by 2030, maintaining this reduction through 2050, highlighting the need for updated future targets over reliance on trends. In the CTA scenario, net zero target is attained by 2045. Import emissions decrease with the reduction in fossil fuel use and/or the adoption of biofuels characterized by very low import emissions. In the APT scenario, the air pollution targets contribute to the reduction of CO2 emissions without specific CO2 reduction targets. This shows that the localized EU air pollution targets correspond the localized EU carbon reduction targets and, in this case, resulting in 100 percent emission reduction by 2050. CB1.5 is a highly ambitious scenario which achieves net zero target before 2030, drastically reducing emissions from all sources. CB2 is a relatively less ambitious scenario achieving net zero emissions before 2040. This budget provides more flexibility to the municipality but with a trade-off concerning the temperature rise. As the CB is only applied to emissions within municipal boundary, emissions from the import of biofuels persists. Results shows that defining CBs corresponds the achievement of net zero target, however, the trajectory depends on the budget included (e.g., CB1.5 is fast track path compared to CB2).

In the following discussions, the term EV (electric vehicles) includes BEV (battery electric vehicles), PHEV (plug-in hybrid electric vehicles), and HEV (hybrid electric vehicles). Fossil fuels include diesel, gasoline, and compressed natural gas and biofuels include biodiesel, biogas, bioethanol, and biomethanol.

As mentioned, renewable energy share in the FEC is already high in Gällivare. Consequently, the EU RED is not relevant for Gällivare. The municipality should set more ambitious renewable energy targets, leveraging its advanced starting point and focusing on sectors with high improvement potential, particularly transport. For example, focussing particularly on the transport sector. With the ELC&DH sectors nearly decarbonized, the renewable energy share in final energy consumption largely depends on the transport sector. This approach will better reflect local conditions and support continued progress towards sustainable energy goals.

The fossil fuels used in scenarios mainly comprise of diesel for heavy freight and buses, and gasoline (major share) and natural gas for cars. In the beginning of model horizon liquid biofuels primarily comprise biodiesel (major share) and bioethanol, with biomethanol being included from 2040 for freight transport to meet climate target. Similarly gaseous biofuels, such as biogas, cars replace natural gas in cars and light freight, trains, and cars are electrified. This mix is similar in all scenarios and exceptions will be detailed.

In the RED scenario, fossil fuels are replaced by electricity in cars and light trucks, and by biofuels in buses and heavy trucks to meet renewable target (Figure 5). The share of electricity in fuel mix is comparatively higher around 2040. This trend is driven by the payback period of EVs, where higher initial costs are offset by lower operational costs and greater efficiency compared to ICEVs [48]. Currently, there is an excess of cheap renewable electricity in Northern Sweden. However, electricity demand rises across all sectors over time, including the industrial and transport sectors, leading to higher costs. This increase often triggers a shift towards biofuels as a more competitive alternative. Similar to RED, this fuel shift to biofuels is visible in all scenarios. Hence to keep the investments in EVs, it should be made affordable by investing in more cost-effective renewables.

Figure 5

Fuel mix in the transport sector under different scenarios (‘others’ include active modes of transport such as walking and biking)

FEC is reduced in all scenarios, primarily due to the shift to more efficient technologies for meeting travel demand. For example, among cars, BEVs are about 3 times more efficient, HEVs about 1.5 times, and PHEVs about 2 times more efficient than ICEVs [49]. Figure 5 shows a major shift to EVs in passenger car transport, which is consistent across all scenarios. This indicates that all localized EU targets for carbon and air pollution reduction enhances the integration of renewable energy and improvements in energy efficiency, leading to the reduction of FEC. In the CTA, APT, CB1.5 and CB2 scenarios, the fossil-free status is achieved by 2045, 2050, 2030 and 2035 respectively. The fuel mix gradually shifts from fossil fuels to electricity and biofuels. In APT, unlike other scenarios, a significant portion of gaseous biofuels is used in cars, buses, and freight. This shift is driven by the adoption of biofuels with lower pollutant emissions to meet air pollution targets effectively.

The municipality of Gällivare should set more ambitious and localized energy and emissions targets that build on transport sector. This includes continuing the transition towards EVs and promoting biofuels where appropriate. Also, planning for rising electricity demand across sectors is essential to manage costs and maintain EV competitiveness and making strategic investments in local renewable energy capacity is crucial. Additionally, the municipality should consider the implications of indirect emissions from fuel imports.

SO2 achieves 100% reduction by 2050 in all scenarios compared to 2020 levels, primarily due to decreased reliance on fossil fuels, the major source of SO2 emissions (Figure 6). Despite reductions in fossil fuel usage, NOX and PM emissions persist in all scenarios (except APT), primarily due to use of biofuels. Achieving significant reductions in these pollutants while continuing biofuel use requires further advancements in engine technologies and the adoption of next-generation biofuels [50].

Figure 6

Air pollutant and CO2 emissions from fuel use in transport sector, represented as percentage change from the year 2020 for each scenario

The APT scenario results show that extrapolating the national air pollutant targets results in 100% reduction at local level by 2050 compared to 2020 levels. Following the APT scenario, the maximum emission reduction occurs in the CTA scenario. This is primarily due to constraints on import emissions (along with net zero target), which limit biofuel usage, encouraging a shift towards EVs, especially in passenger cars. For instance, SO2 is reduced by approximately 100%, NOX by 50%, NMVOC by around 97%, NH3 by about 80%, and PM2.5 by roughly 40% (averaged across 2030, 2040, and 2050). CTA is followed by the CB1.5 and CB2 scenarios, which achieves significant reductions due to strict carbon budget constraints that limit fossil fuel usage. REC shows the least reduction in air pollutant emissions due to the less ambitious target.

Unlike CO2 emissions, which have global implications, air pollution and air quality issues are highly local. They are influenced not only by transport but also by industrial activities and urban development. Presumably, targets for air quality improvement in Gällivare will need to be more stringent compared to 2030 reduction targets, especially considering the ongoing infrastructure developments in the area both industrial and socio-cultural. Results show that the localized EU targets for carbon reduction corresponds the reduction of air pollutants. However, the fact that a 100% reduction in air pollutants is achieved only in the APT scenario underscores the need for specific air pollution targets to effectively improve air quality.

Private car stock. In Gällivare, nearly 60-70 percent of emissions in the transport sector are generated by cars and buses and hence are discussed in detail in the rest of the section. In Figure 7, which depicts the total stock of passenger cars, there is a noticeable trend towards BEVs. Despite high initial costs, BEVs are preferred for their low operating costs resulting from cheap electricity. In the RED scenario, although over 50 percent of the vehicle stock is composed of BEVs and HEVs, PHEVs are also preferred due to the scenario's lower ambition, allowing a shift to more affordable vehicles that can run on both fossil fuels and biofuels. These hybrid vehicles offer a middle ground, with costs lower than BEVs but higher than ICEVs, and efficiency higher than ICEVs but lower than BEVs. Among the hybrid options, PHEVs are the least preferred due to their comparatively high costs when compared to HEVs though they offer higher efficiency.

Figure 7

Total vehicle stock of passenger cars in different scenarios (BEV- battery electric vehicles, PHEV- plug-in hybrid electric vehicles, HEV- hybrid electric vehicles and ICEV- internal combustion engine vehicles)

The vehicle stock completely shifts to BEVs by 2040 in the CTA scenario, due to the strict emission targets. The restriction on import emissions also plays a significant role here, limiting the import of biofuels and thereby driving the shift to BEVs. This shift is further supported by the applicability of low-emission fuels to other subsectors such as buses or freight transport, as passenger cars are comparatively easier to electrify. Similarly, in the APT scenario, air pollution targets restrict the use of biofuels due to their associated pollutants, which drives the switch to BEVs. However, a few investments in ICEVs are still made, resulting in around 5-10% of the vehicle stock continuing to use fossil fuels. In these cases, ICEVs are preferred over HEVs or PHEVs due to cost considerations, as the air pollutant targets allow some flexibility for fossil fuel usage. Also, the fossil fuels are blended with biofuels. In the CB1.5 scenario, PHEVs are preferred around 2050 over HEVs due to their higher compatibility with biofuel blends, which is comparatively lower for HEV technology. However, in the CB2 scenario, ICEVs, HEVs, and PHEVs are all preferred, utilizing the flexibility allowed in the CB scenario.

Bus stock. ICEVs are highly invested in the bus vehicle stock, as shown in Figure 8. However, to meet the respective scenario targets, BEVs are also invested in, followed by the usage of biofuels in ICEVs. BEVs receive less investment due to their higher costs compared to ICEVs. In the case of buses, BEVs are twice as expensive, and PHEVs and HEVs are 3-4 times more expensive than ICEVs on average (across different models) [49] . The RED scenario shows the least investment in BEVs due to cost and target considerations, when compared to other scenarios with more ambitious targets. The APT scenario shows the highest investment in BEVs due to stricter air pollutant targets. The CTA, CB1.5, and CB2 scenarios show similar investments in BEVs. In the CTA scenario, this is due to restrictions on import emissions. In the CB1.5 and CB2 scenarios, it is due to the strict carbon budgets (CB) that must be achieved, so early investments in BEVs support this goal. These scenarios also show investments in ICEVs that use only biofuels (with the CTA scenario additionally shifting to fuels with the lowest CO₂ emissions).

Figure 8

Total vehicle stock for inter and intra city buses (BEV- battery electric vehicles, ICEV- internal combustion engine vehicles, ICEV-BF – ICEV only using biofuels)

The above results show that the investments are highly reflective of the targets and impacts vehicle investments differently. This emphasizes the necessity for local-level targets to be designed with a comprehensive understanding of the system, rather than following higher-level targets. For example, no investments have been made in hydrogen fuel cell vehicles (HFCVs), and there are no specific policies supporting hydrogen adoption. However, HYBRIT can be seen as a potential hydrogen supplier and the municipality can design infrastructure and policies based on this potential starting with the municipality’s vehicle fleet.

A set of sustainability indicators, as proposed in [18], is applied to evaluate the sustainability status of each energy transition pathway (here named as scenario). These indicators (Table 2) are either included in the model or are assessed outside the model.

The indicator selection process was designed to ensure a comprehensive assessment of sustainability within the energy transition pathways for northern Swedish municipalities. The selection process was conducted in three phases: identifying globally recognized SDGs and their relevance to Sweden, refining the indicators to those pertinent to the energy transition in Sweden’s northern municipalities, and further filtering them for integration into the energy system optimization model (ESOM). The study considered both quantitative and qualitative criteria to ensure that the selected indicators were not only measurable but also reflective of local sustainability challenges. Quantitative criteria included data availability, measurability, and alignment with model parameters, ensuring that the indicators could be effectively incorporated into the ESOM for scenario analysis. Meanwhile, qualitative criteria focused on policy relevance, local applicability, and stakeholder priorities, ensuring that the selected indicators resonated with municipal sustainability goals.

To justify the selection of thresholds, the study employed a combination of national and international benchmarks, local policy targets, and expert consultations. For instance, SDG indicators that aligned with existing national climate and energy policies, such as Sweden’s net-zero emissions goal for 2045, were prioritized. Additionally, thresholds for renewable energy share and energy efficiency improvements were set based on Swedish and EU energy policies. In cases where standard thresholds were unavailable, the study established new benchmarks through municipality-level discussions and contextual analysis. Some indicators, such as the material footprint of electric vehicle adoption, required a hybrid approach, where model outputs were supplemented with external estimates to quantify sustainability trade-offs. This rigorous and structured methodology ensured that the indicator selection process was both data-driven and policy-aligned, enabling a holistic assessment of sustainability across different energy transition pathways (Refer [18] for further details).

Heatmap is employed to illustrate the results of the application of the sustainability indicators (Figure 9). The result may not represent all the changes throughout the model horizon but reflects the status in the year 2050. The quantitative values of the result indicators for T7.3.1 and T8.4 are calculated outside the model based on the model results, while all other indicators are directly obtained from the model results. For T7.1.1, fossil fuel share in FEC is included rather than renewable share to have a common base for comparison.

Figure 9

Sustainability indicator values for the year 2050 for Gällivare energy system (TRA -transport sector). Higher indicator values (shown in blue) indicate negative impacts on the environment or society, while lower values (shown in yellow) indicate positive impacts

The heatmap can be divided into two halves, with the upper half representing economic sustainability [51] linked to economic impacts, and the lower half focusing on environmental sustainability [51] related to environmental degradation. The economic sustainability is indicated using the marginal cost of services such as electricity, travel by car and bus. Marginal cost of service refers to the additional cost incurred to meet one more unit of energy demand (or energy service), in this context its one unit of electricity supply or one unit of passenger-km travel. Marginal cost of electricity is high in scenarios with high BEV penetration (CTA, APT) due to the increased demand and resulting competition for the supply. The variation in marginal cost of travel by bus and car in the different scenarios aligns with the outcomes of fuel use (Figure 5) and vehicle stock (Figure 7, Figure 8). In bus travel, the cost initially increases with the adoption of BEVs and use of biofuels, but the long-term benefits from BEVs (particularly low running cost), eventually leads to cost reduction. In cars, due to the ease of electrification compared to other vehicles, such as buses, all scenarios show significant investment in EVs, which initially increases costs which decreases subsequently. The APT scenario differs from the other scenarios in both bus and car cases, due to constraint on biofuel use, resulting in increased investments in BEVs and the selection of least air pollutant-emitting biofuels. This shift leads to increased costs throughout the model horizon.

Hence, in terms of economic sustainability, the RED, CB1.5, and CB2 emerge as more sustainable scenarios, indicating a lower transition costs thus minimizing economic burden. Conversely, the CTA and APT scenarios involve higher costs for transition, placing a comparatively higher greater burden on society. In the environmental sustainability assessment, the APT scenario ranks as the most sustainable, followed by CB2, CB1.5 and CTA. While these scenarios (CBs and CTA) reduce CO₂ emissions by 2050, they have higher air pollutant levels indicating its impact local air quality and health. The RED scenario is the least sustainable due to high environmental impacts, highlighting the need for greater ambition.

The primary differences across these scenarios lie in the specific targets they aim to achieve and the pace at which these targets are pursued. The variations reflect differing priorities in what is considered most critical—whether it be reducing greenhouse gas emissions, minimizing air pollution, or adhering to carbon budgets—and the speed at which these goals are met, ranging from gradual transitions as in CTA to more immediate, aggressive measures as in CB1.5. One would assume that the implementation of stringent policies would result in high social burden, but the results indicate otherwise.