Background
At the COP21, cities were recognised as key actors in combatting climate change. In supporting cities, climate city networks such as transnational climate networks (TCNs) and national climate networks (NCNs) have emerged to enable cities in building capacities and formulating climate policy whilst also encouraging citizen engagement and participation in public decision-making. This paper addresses the question whether and how TCN or NCN membership enables municipalities to implement citizen participation in public decision-making. Six propositions are presented addressing: presumed influence of TCN membership on citizen participation, organization of citizen participation, initiator capacity, goal setting, involvement of stakeholders, participatory methods used, and planning processes. A multi-case study research design is used to verify these propositions, comprising of four medium-sized cities in the Netherlands and three in Belgium.

Results
Results of the analysis of four cities in The Netherlands show that municipalities having membership to climate city networks only to a low extent empower citizen participation via local climate agendas. Citizen participation emerges rather bottom-up via local initiatives or capacity building via EU framework programs—outside TCNs or NCNs—that better suit financial needs and provide more immediate benefits to municipalities. None of the six propositions were confirmed. A more positive image resulted from the Belgian cases that moderately confirmed four out of six propositions (i.e., organizing citizen participation, goal setting, selection of methods, and planning), and featured indirect empowerment via externally funded implementation projects following firm integration of participation in local climate policy through TCN influence.

Conclusions
In terms of citizen participation selected municipalities in the Netherlands having TCN and/or NCN membership only to a small extent differ from those not having membership. This is partly due to poor implementation of TCNs and NCNs—with Covenant of Mayors and ‘Klimaatverbond’ lacking support structure and capacity—having lost importance during the past years. However, there is reason to believe that context makes a difference as revealed by the cases from Belgium, which revealed more positive results.@en

In their Policy Forum, “The costs of ‘costless’ climate mitigation” (1 December 2023, p. 1001), M. J. Kotchen et al. assert that the greenhouse gas mitigation potential identified by the Intergovernmental Panel on Climate Change (IPCC) in its latest assessment report is larger and cheaper than what is found in widely used cost-benefit–based (as opposed to processbased) integrated assessment models such as DICE, FUND, and PAGE. They suggest that the IPCC report underestimates the costs of mitigation by excluding hidden or nonmonetary costs in various sectors. Their criticism of the IPCC assessment is unfounded.@en

Indonesia has large renewable energy resources that are not always located in regions where they are needed. Sub-sea power transmission cables, or island links, could connect Indonesia's high-demand islands, like Java, to large-resource islands. However, the role of island links in Indonesia's energy transition has been explored in a limited fashion. Considering Indonesia's current fossil fuel dependency, this is a critical knowledge gap. Here we assess the role of island links in Indonesia's full power sector decarbonisation via energy system optimisation modelling and an extensive scenario and sensitivity analysis. We find that island links could be crucial by providing access to the most cost-effective resources across the country, like onshore photovoltaics (PV) and hydropower from Kalimantan and geothermal from Sumatera. In 2050, 43 GW of inter-island transmission lines enable 410 GWp of PV providing half of total generation, coupled with 100 GW of storage, at levelised system costs of 60 US$(2021)/MWh. Without island links, Java could still be supplied locally, but at 15% higher costs due to larger offshore floating PV and storage capacity requirements. Regardless of the degree of interconnection, biomass, large hydro, and geothermal remain important dispatchable generators with at least 62 GW and 23% of total generation throughout all tested scenarios. Full decarbonisation by 2040 mitigates an additional 464 MtCO2e compared to decarbonisation by 2050, but poses more challenges for renewables upscaling and fossil capacity retirement.@en

Although causal evidence synthesis is critical for the policy sciences—whether it be analysis for policy or analysis of policy—its repeatable, systematic, and transparent execution remains challenging due to the growing volume, variety, and velocity of policy-relevant evidence generation as well as the complex web of relationships within which policies are usually situated. To address these shortcomings, we develop a novel, semi-automated approach to synthesizing causal evidence from policy-relevant documents. Specifically, we propose the use of natural language processing (NLP) for the extraction of causal evidence and subsequent homogenization of the text; causal mapping for the collation, visualization, and summarization of complex interdependencies within the policy system; and graph analytics for further investigation of the structure and dynamics of the causal map. We illustrate this approach by applying it to a collection of 28 articles on the emissions trading scheme (ETS), a policy instrument of increasing importance for climate change mitigation. In all, we find 300 variables and 284 cause-effect pairs in our input dataset (consisting of 4524 sentences), which are reduced to 70 unique variables and 119 cause-effect pairs after homogenization. We create a causal map depicting these relationships and analyze it to demonstrate the perspectives and policy-relevant insights that can be obtained. We compare these with select manually conducted, previous meta-reviews of the policy instrument, and find them to be not only broadly consistent but also complementary. We conclude that, despite remaining limitations, this approach can help synthesize causal evidence for policy analysis, policy making, and policy research.

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Current bioenergy development has emphasized on degraded land, since the sustainability of bioenergy in the forest sector remains a subject of debate related with emissions and deforestation risk. Thus, this study aims to open new perspectives of how degraded land and social forestry can be potentially combined to significantly impact the energy transition and environmental-societal enhancement. Considering sustainability of Bali as a small island with its unique customary governance structure, a model of biomass energy optimization using geospatial fuzzy-multicriteria analysis was developed to select potential green energy source sites. Firstly, potential degraded land and social forestry were mapped to identify potential feedstock, then normalized using Euclidian Distance and Fuzzy Logic based on identified five sustainability criteria. They are availability of raw material, road, port, transmission, and demand proximities. Meanwhile, using identified three restriction criteria, i.e. protected area, slope and land-use restrictions, a restriction map was developed. The two maps were then integrated using Geospatial-based multicriteria analysis, fuzzy logic and Analytical Hierarchy Process (AHP) weighting method, to further identify potential green energy source map. The integration shown a significant increase of 60 % in land availability for bioenergy development. Results of study recognized potential 36,527 ha of degraded land; 21,671 ha of social forestry; and 40 optimal locations for bioenergy facilities, considering various spatial and temporal criteria. To conclude, the identified 120 social forestry sites in Bali involving 78,385 household provide opportunity to a community based socio-economic coupled with revitalizing environment efforts, which lead to massive net zero emissions community participation. Further, the integration of social forestry and degraded land should be highly recommended to policy maker in bioenergy development.

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Indonesia has large renewable energy resources that are not always located in regions where they are needed. Sub-sea power transmission cables, or island links, could connect Indonesia's high-demand islands, like Java, to large-resource islands. However, the role of island links in Indonesia's energy transition has been explored in a limited fashion. Considering Indonesia's current fossil fuel dependency, this is a critical knowledge gap. Here we assess the role of island links in Indonesia's full power sector decarbonisation via energy system optimisation modelling and an extensive scenario and sensitivity analysis. We find that island links could be crucial by providing access to the most cost-effective resources across the country, like onshore photovoltaics (PV) and hydropower from Kalimantan and geothermal from Sumatera. In 2050, 43 GW of inter-island transmission lines enable 410 GWp of PV providing half of total generation, coupled with 100 GW of storage, at levelised system costs of 60 US$(2021)/MWh. Without island links, Java could still be supplied locally, but at 15% higher costs due to larger offshore floating PV and storage capacity requirements. Regardless of the degree of interconnection, biomass, large hydro, and geothermal remain important dispatchable generators with at least 62 GW and 23% of total generation throughout all tested scenarios. Full decarbonisation by 2040 mitigates an additional 464 MtCO2e compared to decarbonisation by 2050, but poses more challenges for renewables upscaling and fossil capacity retirement.@en

High-temperature heat pumps (HTHPs) are an emerging technology to improve overall process efficiency and reduce energy demand while enabling a switch from fossil fuels to renewable electricity. New industrial HTHP technologies aim to achieve an output heat temperature of 250 °C, suitable for decarbonising the food and beverages industry considering its temperature requirements of <250 °C. Here, we employ a bottom-up approach to investigate the techno-economic feasibility of integrating new HTHP technologies into heat processes of the German food and beverages industry and estimate emissions reduction potentials under waste heat scenarios. Our results indicate that the new HTHP technologies could meet 12 TWh of process heat demand in the German food and beverages industry and cut emissions by 9% considering Germany's current electricity fuel mix. A modest carbon tax of 38 €/t CO2 eq. or higher makes the HTHPs cost-competitive with an optimised fossil fuel-based alternative.@en

Negative emission technologies such as biomass with carbon capture and storage (bioCCS) may become an important instrument to limit global warming. Currently, estimates of CO2 avoidance cost for bioCCS vary widely. Using a case study of a cement plant, this paper illustrates how this variance is partially attributable to the system boundary choices made by modellers. The estimated avoidance cost for the bioCCS-in-cement plant ranged from 48-321€2017/t CO2(eq) and the net CO2(eq) from -660 to 16 kg CO2(eq)/t cement, without any change in the technological model, equipment and input costs, or lifecycle emissions, but by changing the system boundaries used for cost and emission accounting, reflecting the different boundaries seen in bioCCS literature. To allow for more comparable bioCCS cost estimates, studies should always account for costs and emissions of both biomass production and the full chain of carbon capture, transport, and permanent storage, as both are fundamental to the role of bioCCS as a potential “negative emission technology”. We also advocate for clear decomposition of metrics, separation of “avoided emissions” from physical flows of greenhouse gases; and explicit consideration of the temporality of the bioCCS system. With these guidelines, the range of avoidance cost of the bioCCS-in-cement plant shrinks to 157-193€2017/t CO2(eq) for near-term estimates and to 89-107€2017/t CO2(eq) for longer-term estimates.@en

Wave energy is a rich and highly accessible renewable energy resource, that has largely been under-developed. Studies from the sector have tried to show the potential of benefits wave energy in “simple cases” or via small hybrid systems, the large scale incorporation of wave energy has not yet been fully investigated. Our approach uses a fully dynamic climate driven energy system model, which has undergone modifications to include wave energy converters and their associated dependencies. This study explores the system dynamics and important elements that will be used for large scale wave energy integration; in a fully coupled European Energy System. We explore the cost pathways of different wave energy converters, the impact of climate data, and the impact of transmission capacity expansion under cost-optimal configurations of a multi-renewable European power system. From this preliminary approach we aim to provide the boundary conditions, and assumptions that will govern the integration of wave energy into the European Energy System up to 2050.@en

Renewable electricity generation will need to be rapidly scaled to address climate change and other environmental challenges. Doing so effectively will require an understanding of resource availability. We review estimates for renewable electricity of the global technical potential, defined as the amount of electricity that could be produced with current technologies when accounting for geographical and technical limitations as well as conversion efficiencies; economic potential, which also includes cost; and feasible potential, which accounts for societal and environmental constraints. We consider utility-scale and rooftop solar photovoltaics, concentrated solar power, onshore and offshore wind, hydropower, geothermal electricity, and ocean (wave, tidal, ocean thermal energy conversion, and salinity gradient energy) technologies. We find that the reported technical potential for each energy resource ranges over several orders of magnitude across and often within technologies. Therefore, we also discuss the main factors explaining why authors find such different results. According to this review and on the basis of the most robust studies, we find that technical potentials for utility-scale solar photovoltaic, concentrated solar power, onshore wind, and offshore wind are above 100 PWh/year. Hydropower, geothermal electricity, and ocean thermal energy conversion have technical potentials above 10 PWh/year. Rooftop solar photovoltaic, wave, and tidal have technical potentials above 1 PWh/year. Salinity gradient has a technical potential above 0.1 PWh/year. The literature assessing the global economic potential of renewables, which considers the cost of each renewable resource, shows that the economic potential is higher than current and near-future electricity demand. Fewer studies have calculated the global feasible potential, which considers societal and environmental constraints. While these ranges are useful for assessing the magnitude of available energy sources, they may omit challenges for large-scale renewable portfolios.

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Ocean Thermal Energy Conversion (OTEC) is an emerging renewable energy technology using the ocean’s heat to produce electricity. Given its early development stage, OTEC’s economics are still uncertain and there is no global assessment of its economic potential, yet. Here, we present the model pyOTEC that designs OTEC plants for best economic performance considering the spatiotemporally specific availability and seasonality of ocean thermal energy resources. We apply pyOTEC to more than 100 regions with technically feasible sites to obtain an order-of-magnitude estimation of OTEC’s global technical and economic potential. We find that OTEC’s global technical potential of 107 PWh/year could cover 11 PWh of 2019 electricity demand. At ≥ 120 MWgross, there are OTEC plants with Levelised Cost of Electricity (LCOE) below 15 US¢(2021)/kWh in 15 regions, including China, Brazil, and Indonesia. In the short-to-medium term, however, small island developing states are OTEC’s most relevant niche. Systems below 10 MWgross could fully and cost-effectively substitute Diesel generators on islands where that is more challenging with other renewables. With the global analysis, we also corroborate that most OTEC plants return the best economic performance if designed for worst-case surface and deep-sea water temperatures, which we further back up with a sensitivity analysis. We lay out pyOTEC’s limitations and fields for development to expand and refine our findings. The model as well as key data per region are publically accessible online.@en

Geospatial analysis is useful for mapping the potential of renewables like solar PV. However, recent studies do not address PV’s bankable potential for which project financing can be secured. This paper proposes a framework that incorporates project finance into geospatial analyses to obtain the bankable potential of renewables. We demonstrate our framework for Indonesia, and compare the bankable potential with the socio-economic potential mostly used in literature. Using average inputs On average, the technical potential is 12,200 TWh/year and the socio-economic potential is 152.7 TWh/year if capped by 2030 demand (34% coverage). Considering PV’s financing risks, PV’s bankable potential is 16.0 TWh under current conditions if capped by 2030 demand (3.6% coverage). Both economic potentials are mainly in East Indonesia and absent on Java due to tariffs and land availability. For the bankable potential, the risk perception by banks and investors is another key influence. With a feed-in tariff of 11.5 US¢(2021)/kWh and temporary lift of import restrictions, the bankable potential is 23 TWh if capped by 2030 demand (5.2% coverage) and spreads to Java. For more widespread bankability, additional temporary measures are recommended until the PV’s costs have decreased further and trust by financial institutions has increased.@en

Corporate climate initiatives such as the Science-Based Targets initiative and RE100 have gained significant prominence in recent years, with considerable increases in membership and several ex-ante studies stating how they could bring substantive emissions reductions beyond national goals. However, studies evaluating their progress are scarce, raising questions on how members achieve targets and whether their contributions are genuinely additional. Here we assess these initiatives by disaggregating membership by sector and geographic region and then thoroughly evaluating their progress between 2015–2019 using public environmental data disclosed by 102 of their largest members by revenue. Our results show that the collective Scope 1 and 2 emissions of these companies have fallen by 35.6%, with companies generally on track or exceeding scenarios keeping global warming below 2 °C. However, most of these reductions are concentrated in a small number of intensive companies. Most members show little evidence of emission reductions within their operations, only achieving progress via renewable electricity purchases. We highlight how intermediate steps regarding data robustness and implementation of sustainability measures are lacking: 75% of public company data is independently verified at low levels of assurance, and 71% of renewable electricity is obtained through low-impact or undisclosed sourcing models.@en

Purpose: The purpose of this paper is to present a comprehensive analysis of the carbon footprint of the Delft University of Technology (TU Delft), including direct and indirect emissions from utilities, logistics and purchases, as well as a discussion about the commonly used method. Emissions are presented in three scopes (scope 1 reports direct process emissions, scope 2 reports emissions from purchased energy and scope 3 reports indirect emissions from the value chain) to identify carbon emission hotspots within the university’s operations. Design/methodology/approach: The carbon footprint was calculated using physical and monetary activity data, applying a process and economic input-output analysis. Findings: TU Delft’s total carbon footprint in 2018 is calculated at 106 ktCO2eq. About 80% are indirect (scope 3) emissions, which is in line with other studies. Emissions from Real estate and construction, Natural gas, Equipment, ICT and Facility services accounted for about 64% of the total footprint, whereas Electricity, Water and waste-related carbon emissions were negligible. These findings highlight the need to reduce universities’ supply chain emissions. Originality/value: A better understanding of carbon footprint hotspots can facilitate strategies to reduce emissions and finally achieve carbon neutrality. In contrast to other work, it is argued that using economic input-output models to calculate universities’ carbon footprints is a questionable practice, as they can provide only an initial estimation. Therefore, the development of better-suited methods is called for.@en

Ocean Thermal Energy Conversion (OTEC) is a promising renewable energy technology that is the most economical at large scale. But contemporary literature does not address how OTEC could reach such scale with current technology, and what the techno-economic impact of location-dependent factors and technological learning are. This paper tackles these issues by simulating OTEC's upscaling with a model that implements OTEC to meet local electricity demand and extrapolates to the global relevance of OTEC. The model uses a learning rate for investment costs and cost of finance. This study shows that up to 45 GW of OTEC capacity can be installed in Indonesia with national demand coverage of 22% in 2050. Even with small cost reduction rates, OTEC could be profitable and cost-competitive against other power generation technologies with an aggregated Net Present Value (NPV) of up to US$ 23 billion. OTEC's upscaling could be funded via state budget reallocation or international financial institutions, e.g. via the feed-in tariff suggested in the paper. However, large-scale OTEC is only feasible in regions with high electricity demand and until that size is reached, upscaling must be coordinated globally, e.g. with the proposed upscaling strategy. To contribute to the global energy transition, OTEC needs to grow by 28% per year, a rate similar to wind power and solar PV. This paper provides good reasons to fight for the attention of global decision makers and future research could focus on refining the concepts of this study.@en

Onshore wind potentials are commonly mapped with site selection criteria that either fully include or exclude land for wind farms. However, current research rarely addresses the variability of these criteria, possibly resulting in overly conservative or optimistic potentials. This paper proposes a method to account for the variability of site selection criteria in resource assessments. We distinguish between static and flexible, non-binary criteria and assess onshore wind's technical and economic potential with bias-corrected ERA5 data, 28 turbine power curves, and a turbine-specific cost model. For Indonesia, we show that our flexible mapping approach improves the transparency of resource potential assessments and could contribute to more informed and useful recommendations. These recommendations could address the (1) calibration of site exclusion thresholds, (2) dilemmas of preferring one land type over others, (3) location-specific challenges of wind farm deployment, and (4) more direct support schemes for affected stakeholders and wind farm operators.. We report a technical potential of 207–1,994 TWh/year in Indonesia, which could cover more than 50% of 2030 electricity demand on all islands. LCOEs range between 5.8 and 24.5 US¢(2021)/kWh with an economic potential of 16 TWh/year, which improves to 31–212 TWh/year with a carbon tax of 100 US$(2021)/tCO2e.@en

The current focus of offshore wind industry and academia lies on regions with strong winds, neglecting areas with mild resources. Photovoltaics' cost reductions have shown that even mild resources can be harnessed economically, especially where electricity prices are high. Here, we study the technical and economic potential of offshore wind power in Indonesia as an example of mild-resource areas, using bias-corrected ERA5 data, turbine-specific power curves, and a detailed cost model. We show that low-wind-speed turbines could produce up to 6,816 TWh/year, which is 25 times Indonesia's electricity generation in 2018 and 3 times the projected 2050 generation, and up to 166 PWh/year globally. Although not yet competitive against current offshore turbines, low-wind turbines could become a crucial piece of the global climate mitigation effort in regions with vast marine areas and high electricity prices. As low-wind-speed turbines are not yet on the market, we recommend prioritizing their development.

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Many questions remain regarding the exploitation of wave energy and its interaction with our energy systems. Particularly about their likely role in future multi-renewable power systems, given the resource’s abundance, predictability, and high energy density. The objective of this paper is to present the expansion of the renewable energy capabilities of an open-source dynamic energy system model with novel wave energy converters subroutines paired with high-resolution metocean from the ERA5. The expansion allows for the model to assess the wave energy technical resource across Europe’s coastlines; Estimate the renewable wave energy capacity potential; Derive renewable wave generation availability time series of different devices; And consider wave energy technologies in a power flow optimization of the European transmission grid. It establishes the basis to perform future exploratory investigations of wave energy converters under a high renewable European electricity grid.@en

The chemical sector is hydrocarbon intensive, using primarily fossil fuels as both fuel and feedstock. To achieve carbon-neutrality, it is likely that negative CO2 emissions will be needed to offset the carbon embodied in chemical products. This study presents first-order estimates of the decarbonization potential of combining bioenergy and biofeedstock use with carbon capture and storage (bio-CCS) for ethanol, ammonia, urea, and hydrogen. For each, net CO2 of emissions minus atmospheric removals was estimated over the whole life cycle including chemical synthesis, upstream supply chains, product use, and waste disposal. With aggressive bio-CCS using technologies that are currently commercially available, CO2 negative production was estimated to be possible for all chemicals modelled, except urea. With the use of biomass for both feedstock and fuel and capture of both high-purity and dilute CO2 streams, the estimated net CO2 was -30 g/MJ for maize bioethanol; -50 g/MJ for stover bioethanol; -50 g/MJ for merchant hydrogen; -1.2 t/t N for ammonia and 0.2 t/t N for urea. The potential for negative CO2 emissions is higher in cases where more CO2 can be captured during chemical production. However, all cases were sensitive to assumptions regarding the specific configuration and upstream supply chains.

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Wave energy can provide significant benefits as renewables acquire more share in electricity production. So far, focus for the development of wave energy is given to areas with resources ≥ 25 kW/m, with moderate resources often not considered. Furthermore, waves have larger uncertainties associated with diverse portfolio of converters leading to higher Levelized Cost of Electricity (LCoE). This study challenges the notion of economic viability for moderate resources, therefore the methodology and results of this analysis are globally applicable. Several different types of wave converters suggest multi-zonal applicability, underlying the dependence on the diverse wave energy resource that can be harvested. It is clear that different zones favour alternative converters, common characteristic is that all have nominal capacity below 1 MW. Optimally selected converters, attain capacity factors over 30%, with LCoE depending more on discount rate-capital pairs, mean LCoE values are from 150 to 250/MWh with lowest value 60 €/MWh. Investment amortisation also depends on resource and LCoE pairs with an offshore wave farm able to retrieve its capital in 3.8 years (optimal case), 10 years (average). Projects with ≥3 Million €/MW and a higher risk discount of 10% are viable only for high performing devices with capacity factors ≥40%.

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