To achieve the European Union's goal of climate neutrality by 2050, negative emissions may be required to compensate for emissions exceeding allocated carbon budgets. Therefore, carbon removal technologies such as bioenergy with carbon capture (BECCS) and direct air capture (DAC) may need to play a pivotal role in the power system. To design carbon removal strategies, more insights are needed into the impact of sustainable biomass availability and the feasibility of carbon capture and storage (CCS), including the expensive and energy-intensive DAC on achieving net-zero and net-negative targets. Therefore, in this study the European power system in 2050 is modelled at an hourly resolution in the cost-minimization PLEXOS modelling platform. Three climate-neutral scenarios with targets of 0, -1, and -3.9 Mt CO₂/year (which agree with varying levels of climate justice) are assessed for different biomass levels, and CCS availability. Findings under baseline assumptions reveal that in a climate-neutral power system with biomass and CCS options, it is cost-effective to complement variable renewable energy with a mix of combined cycle natural gas turbines (CCNGT) for flexibility and BECCS as base load to compensate for the CO₂ emissions from natural gas and additional carbon removal in the net-negative scenarios. The role of these technologies becomes more prominent, with -3.9 GtCO₂/year target. Limited biomass availability necessitates additional 0.4–4 GtCO₂/year DAC, 10–50 GW CCNGT with CCS, and 10–50 GW nuclear. Excluding biomass doubles system costs and increases reliance on nuclear energy up to 300 TWh/year. The absence of CCS increases costs by 78%, emphasizing significant investments in bioenergy, nuclear power, hydrogen storage, and biogas. Sensitivity analysis and limitations of the study are fully discussed.

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We model the evolution of the Central Western Europe power system until 2040 with an increasing carbon price and strong growth of variable renewable energy sources (vRES) for four electricity market designs: the current energy-only market, a reformed energy-only market, both also with the addition of a capacity market. Each design is modelled for two decarbonisation pathways: one targeting net-zero emissions by 2040 for a 2 °C warming limit, and the other targeting −850 Mt CO₂ y‾ for a 1.5 °C warming limit. We compare these scenarios against the high-level objectives of delivering low-carbon electricity reliably to consumers at the lowest possible cost. Our results suggest that both 2 °C and 1.5 °C compliant systems could be achieved and deliver electricity reliably. In terms of cost, we find the 1.5 °C warming scenarios lead to system costs which are twice as high as the 2 °C scenarios due to the high cost of negative emission technologies – in particular direct air carbon capture (DAC). To make a 1.5 °C target more affordable, policymakers should investigate lower cost alternatives in other sectors, and increase research and development in DAC to reduce its cost.

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In this study, we model seven scenarios for the European power system in 2050 based on 100% renewable energy sources, assuming different levels of future demand and technology availability, and compare them with a scenario which includes low-carbon non-renewable technologies. We find that a 100% renewable European power system could operate with the same level of system adequacy as today when relying on European resources alone, even in the most challenging weather year observed in the period from 1979 to 2015. However, based on our scenario results, realising such a system by 2050 would require: (i) a 90% increase in generation capacity to at least 1.9 TW (compared with 1 TW installed today), (ii) reliable cross-border transmission capacity at least 140 GW higher than current levels (60 GW), (iii) the well-managed integration of heat pumps and electric vehicles into the power system to reduce demand peaks and biogas requirements, (iv) the implementation of energy efficiency measures to avoid even larger increases in required biomass demand, generation and transmission capacity, (v) wind deployment levels of 7.5 GW y−1 (currently 10.6 GW y−1) to be maintained, while solar photovoltaic deployment to increase to at least 15 GW y−1 (currently 10.5 GW y−1), (vi) large-scale mobilisation of Europe's biomass resources, with power sector biomass consumption reaching at least 8.5 EJ in the most challenging year (compared with 1.9 EJ today), and (vii) increasing solid biomass and biogas capacity deployment to at least 4 GW y−1 and 6 GW y−1 respectively. We find that even when wind and solar photovoltaic capacity is installed in optimum locations, the total cost of a 100% renewable power system (∼530 €bn y−1) would be approximately 30% higher than a power system which includes other low-carbon technologies such as nuclear, or carbon capture and storage (∼410 €bn y−1). Furthermore, a 100% renewable system may not deliver the level of emission reductions necessary to achieve Europe's climate goals by 2050, as negative emissions from biomass with carbon capture and storage may still be required to offset an increase in indirect emissions, or to realise more ambitious decarbonisation pathways.@en

The aviation industry accounts for more than 2% of global CO ₂ emissions. Biojet fuel is expected to make an essential contribution to the decarbonization of the aviation sector. Brazil is seen as a key player in developing sustainable aviation biofuels owing to its long-standing experience with biofuels. Nevertheless, a clear understanding of what policies may be conducive to the emergence of a biojet fuel supply chain is lacking. We extended a spatially explicit agent-based model to explore the emergence of a biojet fuel supply chain from the existing sugarcane–ethanol supply chain. The model accounts for new policies (feed-in tariff and capital investment subsidy) and new considerations into the decision making about production and investment in processing capacity. We found that in a tax-free gasoline regime, a feed-in tariff above 3 R$/L stimulates the production of biojet fuel. At higher levels of gasoline taxation (i.e., 2.46 R$/L), however, any feed-in tariff is insufficient to ensure the production of biojet fuel. Thus, at these levels of gasoline taxation, it is needed to introduce regulations on the production of biojet fuel to ensure its production. Given the current debate about the future direction of the biofuel policy in Brazil, we recommend further research into the effect of market mechanisms based on greenhouse gas emissions on the emergence of a Brazilian biojet fuel supply chain.

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Biomass feedstock can be used for the production of biofuels or biobased chemicals to reduce anthropogenic greenhouse gas (GHG) emissions. Earlier studies about the techno-economic performance of biofuel or biobased chemical production varied in biomass feedstock, conversion process, and other techno-economic assumptions. This made a fair comparison between different industrial processing pathways difficult. The aim of this study is to quantify uniformly the factory-gate production costs and the GHG emission intensity of biobased ethanol, ethylene, 1,3-propanediol (PDO), and succinic acid, and to compare them with each other and their respective fossil equivalent products. Brazilian sugarcane and eucalyptus are used as biomass feedstock in this study. A uniform approach is applied to determine the production costs and GHG emission intensity of biobased products, taking into account feedstock supply, biobased product yield, capital investment, energy, labor, maintenance, and processing inputs. Economic performance and net avoided GHG emissions of biobased chemicals depend on various uncertain factors, so this study pays particular attention to uncertainty by means of a Monte Carlo analysis. A sensitivity analysis is also performed. As there is uncertainty associated with the parameters used for biobased product yield, feedstock cost, fixed capital investment, industrial scale, and energy costs, the results are presented in ranges. The 60% confidence interval ranges of the biobased product production costs are 0.64–1.10 US$ kg ⁻¹ ethanol, 1.18–2.05 US$ kg ⁻¹ ethylene, 1.37–2.40 US$ kg ⁻¹ 1,3-PDO, and 1.91–2.57 US$ kg ⁻¹ succinic acid. The cost ranges of all biobased products partly or completely overlap with the ranges of the production costs of the fossil equivalent products. The results show that sugarcane-based 1,3-PDO and to a lesser extent succinic acid have the highest potential benefit. The ranges of GHG emission reduction are 1.29–2.16, 3.37–4.12, 2.54–5.91, and 0.47–5.22 CO _2eq kg ⁻¹ biobased product for ethanol, ethylene, 1,3-PDO, and succinic acid respectively. Considering the potential GHG emission reduction and profit per hectare, the pathways using sugarcane score are generally better than eucalyptus feedstock due to the high yield of sugarcane in Brazil. Overall, it was not possible to choose a clear winner, (a) because the best performing biobased product strongly depends on the chosen metric, and (b) because of the large ranges found, especially for PDO and succinic acid, independent of the chosen metric. To quantify the performance better, more data are required regarding the biobased product yield, equipment costs, and energy consumption of biobased industrial pathways, but also about the production costs and GHG emission intensity of fossil-equivalent products.

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With the growing penetration of zero-marginal-cost wind and solar photovoltaics leading to falling electricity wholesale prices in the energy-only market, several European countries have implemented capacity remuneration mechanisms (CRMs) in an attempt to ensure security of supply (SoS). However, the literature is far from conclusive whether CRMs are indeed a necessary and/or cost-effective way of ensuring SoS. In this study, we quantitatively compare three different market designs under different levels of wind and PV growth for the interconnected systems of Germany, France, Belgium and the Netherlands. Preliminary results show that average electricity prices decrease in markets supplemented with a CRM, as does the volatility of electricity prices. Whether or not the contribution of a CRM to SoS is worth the cost (and its possible adverse impact on energy market functioning) of implementing a CRM also remains to be evaluated.@en

The Brazilian government aims to increase the share of biofuels in the energy mix to around 18% by 2030, which implies an increase of ethanol production from currently 27 bln liters to over 50 bln liters per year. Biofuel policies play an important role in ethanol production, consumption, and investment in processing capacity. Nevertheless, a clear understanding of how current policies affect the evolution of the market is lacking. We developed a spatially-explicit agent-based model to analyze the impact of different blend mandates and taxes levied on gasoline, hydrous, and anhydrous ethanol on investment in processing capacity and on production and consumption of ethanol. The model uses land use projections by the PCRaster Land Use Change model and incorporates the institutions governing the actors’ strategic decision making with regard to production and consumption of ethanol, and the institutions governing the interaction among actors. From the investigated mix of policy measures, we find that an increase of the gasoline tax leads to the highest increased investments in sugarcane processing capacity. We also find that a gasoline tax above 1.23 R$/l and a tax exemption for hydrous ethanol may lead to doubling the production of ethanol by 2030 (relative to 2016).

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Wood pellet imports are expected to increase in the European Union and Southeast Asia by 2030, considering pellets are the main feedstock used for co-firing in power plants throughout these regions. Due to the material's physical and biological properties, the equipment at an import terminal need to be different than what is used for other bulk material. Thus, most of the common problems associated with handling can be avoided. Dust emission and explosions, degradation in storage, self-heating and ignition are important criteria when designing a wood pellet port terminal, and can greatly affect associated logistics. Despite some availability of data concerning the handling of pellets, there is a lack of insight into the equipment and operations of actual handling facilities. A detailed literature research was performed in order to ascertain the level of the scientific background on the subject. Subsequently, visits in pellet facilities in the Netherlands and in-depth interviews with representatives were conducted and serve as a means of gaining an overview of current industry practices and equipment used for the handling of wood pellets. The main objective of this work is to evaluate the state-of-the-art in wood pellet handling in import terminals. This way, future bottlenecks can be identified and actions needed to overcome them can be determined. The analysis performed shows that while wood pellet terminals might be able to cope with the low amounts being traded currently, a reexamination and redesign of terminal facilities to accommodate the increased volumes will probably be required by 2030.

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This paper investigates the optimization of biomass terminal equipment deployment. A mixed integer linear programming model is developed and applied to minimize the terminal's investment and operational costs related to dedicated and partially used or shared equipment between a terminal's operational steps. The results minimize annual terminal costs through equipment and infrastructure selection and utilization. Tipping points where the technology and equipment type or size change in relation to the increasing throughput are highlighted. Analytical results emphasize the importance of storage costs in all biomass terminals, as well as the critical influence of operational costs in larger facilities.

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Biofuel production is not cost competitive and thus requires governmental intervention. The effect of the institutional framework on the development of the biofuel sector is not yet well understood. This paper aims to analyze how biofuel production and production capacity could have evolved in Germany in the period 1992–2014. The effects of an agricultural policy intervention (liberalization of the agricultural market) and a bioenergy policy intervention (a tax on biodiesel after an initial exemption) are explored. Elements of the Modeling Agent systems based on Institutional Analysis (MAIA) framework, complex adaptive systems (CAS) theory, and Neo Institutional Economics (NIE) theory were used to conceptualize and formalize the system in an agent-based model. It was found that an early liberalization of the agricultural market led to an under-production of biodiesel; a late liberalization led to the collapse of biodiesel production. An early introduction of the biodiesel tax led to stagnation in biodiesel production and production capacity; a late introduction led to an increase in sunk costs provided that the biofuel quota is binding. Also, a lack of agents’ adaptation mechanism to forecast prices led to a decrease in patterns of biodiesel production when an external shock was introduced in the system. In sum, we argue that system behavior is influenced by individual behavior which is shaped by institutions.

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The economic performance of biofuels supply chains depends on the interaction of technical characteristics as technological pathways and logistics, and social structures as actor behavior, their interactions and institutions. Traditional approaches focus on the technical problems only. Little attention has been paid to the institutional analysis of biofuel supply chains. This paper aims to extend the analysis of the effect of institutions on the emergence of biofuel supply chains by developing a conceptual framework that combines elements of complex adaptive systems, (neo) institutional economics and socio-technical systems theory. These elements were formalized into an agent-based model. The proposed method is illustrated by a case study on a biodiesel supply chain in Germany. It was found that the patterns in production capacity result from investors basing their decisions on optimistic perceptions of the market development that increase with a favorable institutional framework. Conversely, patterns in biodiesel production cannot be completely explained by this mechanism. The proposed framework assisted the model conceptualization phase and allowed the incorporation of social structures into the agent-based model. This approach could be developed further to provide insights on the effect of different future deployment strategies on bioenergy systems emergence and development.

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Biomass is the largest source of renewable energy carrier in the European Union (EU) contributing to over 60% of renewable energy, with the majority of supply coming from domestic sources. However, an increasing significant amount of feedstock is imported, either due to domestic undersupply or higher production costs within the country. This article provides an up-to-date view of bioenergy supply, demand and trade in Northwest Europe to 2030. Projections of the energy system model Green-X are compared to recent national studies concerning bioenergy imports. The results show that there is a sizeable gap of the projection bandwidths after the 2020 horizon. Projections might under- or overestimate biomass potential in certain cases, depending on whether they are derived from national reports or regional models, whether future policy developments were taken into account etc. The ranges of biomass consumption are multiple times apart by 2020 already, and the gap increases by 2030. Total biomass imports in the region can range between 14 and 44.3 Mt by 2020 and 18.5–60 Mt by 2030.

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Transitioning towards a sustainable energy system requires the large-scale introduction of novel energy demand and supply technologies. Such novel technologies are often expensive at the point of their market introduction but eventually become cheaper due to technological learning. In order to quantify potentials for price and cost decline, the experience curve approach has been extensively applied to renewable and non-renewable energy supply technologies. However, its application to energy demand technologies is far less frequent. Here, we provide the first comprehensive review of experience curve analyses for energy demand technologies. We find a widespread trend towards declining prices and costs at an average learning rate of 18 ± 9%. This finding is consistent with the results for energy supply technologies and for manufacturing in general. Learning rates for individual energy demand technologies are symmetrically distributed around the arithmetic mean of the data sample. Absolute variation of learning rates within individual technology clusters of 7 ± 4%-points and between technology clusters of 7 ± 5%-points both contribute to the overall variability of learning rates. Our results show that technological learning is as important for energy demand technologies as it is for energy supply technologies. Applying the experience curve approach to forecast technology costs involves, however, unresolved uncertainties, as we demonstrate in a case study for the micro-cogeneration technology.

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Large appliances are major power consumers in households of industrialized countries. Although their energy efficiency has been increasing substantially in past decades, still additional energy efficiency potentials exist. Energy policy that aims at realizing these potentials faces, however, growing concerns about possible adverse effects on commodity prices. Here, we address these concerns by applying the experience curve approach to analyze long-term price and energy efficiency trends of three wet appliances (washing machines, laundry dryers, and dishwashers) and two cold appliances (refrigerators and freezers). We identify a robust long-term decline in both specific price and specific energy consumption of large appliances. Specific prices of wet appliances decline at learning rates (LR) of 29±8% and thereby much faster than those of cold appliances (LR of 9±4%). Our results demonstrate that technological learning leads to substantial price decline, thus indicating that the introduction of novel and initially expensive energy efficiency technologies does not necessarily imply adverse price effects in the long term. By extending the conventional experience curve approach, we find a steady decline in the specific energy consumption of wet appliances (LR of 20-35%) and cold appliances (LR of 13-17%). Our analysis suggests that energy policy might be able to bend down energy experience curves.

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High costs often prevent the market diffusion of novel and efficient energy technologies. Monitoring cost and price decline for these technologies is thus important in order to establish effective energy policy. Here, we present experience curves and cost-benefit analyses for condensing gas boilers produced and sold in the Netherlands between 1981 and 2006. For the most dominant boiler type on the Dutch market, i.e., condensing gas combi boilers, we identify learning rates of 14±1% for the average price and 16±8% for the additional price relative to non-condensing devices. Economies of scale, competitive sourcing of boiler components, and improvements in boiler assembly are among the main drivers behind the observed price decline. The net present value of condensing gas combi boilers shows an overall increasing trend. Purchasing in 2006 a gas boiler of this type instead of a non-condensing device generates a net present value of 970 EUR (Euro) and realizes CO₂ (carbon dioxide) emission savings at negative costs of -120 EUR per tonne CO₂. We attribute two-thirds of the improvements in the cost-benefit performance of condensing gas combi boilers to technological learning and one-third to a combination of external effects and governmental policies.

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