Ric Hoefnagels

Global solid biomass trade for energy by 2020: an assessment of potential import streams and supply costs to North‐West Europe under different sustainability constraints

The expected use of solid biomass for large‐scale heat and power production across North–West Europe (NW EU) has led to discussions about its sustainability, especially due to the increasing import dependence of the sector. While individual Member States and companies have put forward sustainability criteria, it remains unclear how different requirements will influence the availability and cost of solid biomass and thus how specific regions will satisfy their demand in a competitive global market. We combined a geospatially explicit least‐cost biomass supply model with a linear optimization solver to assess global solid biomass trade streams by 2020 with a particular focus on NW EU. We apply different demand and supply scenarios representing varying policy developments and sustainability requirements. We find that the projected EU solid biomass demand by 2020 can be met across all scenarios, almost exclusively via domestic biomass. The exploitation of domestic agricultural residue and energy crop potentials, however, will need to increase sharply. Given sustainability requirements for solid biomass as for liquid biofuels, extra‐EU imports may reach 236 PJ by 2020, i.e., 400% of their 2010 levels. Intra‐EU trade is expected to grow with stricter sustainability requirements up to 548 PJ, i.e., 280% of its 2010 levels by 2020. Increasing sustainability requirements can have different effects on trade portfolios across NW EU. Excluding pulpwood pellets may drive the supply costs of import dependent countries, foremost the Netherlands and the UK, whereas excluding additional forest biomass may entail higher costs for Germany and Denmark which rely on regional biomass. Excluding solid biomass fractions may create short‐term price hikes. Our modeling results are strongly influenced by parameterization choices, foremost assumed EU biomass supply volumes and costs and assumed relations between criteria and supply. The model framework is suited for the inclusion of dynamic supply–demand interactions and other world regions.

Life-cycle analysis of greenhouse gas emissions from renewable jet fuel production

BackgroundThe introduction of renewable jet fuel (RJF) is considered an important emission mitigation measure for the aviation industry. This study compares the well-to-wake (WtWa) greenhouse gas (GHG) emission performance of multiple RJF conversion pathways and explores the impact of different co-product allocation methods. The insights obtained in this study are of particular importance if RJF is included as an emission mitigation instrument in the global Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA).ResultsFischer–Tropsch pathways yield the highest GHG emission reduction compared to fossil jet fuel (86–104%) of the pathways in scope, followed by Hydrothermal Liquefaction (77–80%) and sugarcane- (71–75%) and corn stover-based Alcohol-to-Jet (60–75%). Feedstock cultivation, hydrogen and conversion inputs were shown to be major contributors to the overall WtWa GHG emission performance. The choice of allocation method mainly affects pathways yielding high shares of co-products or producing co-products which effectively displace carbon intensive products (e.g., electricity).ConclusionsRenewable jet fuel can contribute to significant reduction of aviation-related GHG emissions, provided the right feedstock and conversion technology are used. The GHG emission performance of RJF may be further improved by using sustainable hydrogen sources or applying carbon capture and storage. Based on the character and impact of different co-product allocation methods, we recommend using energy and economic allocation (for non-energy co-products) at a global level, as it leverages the universal character of energy allocation while adequately valuing non-energy co-products.

Optimization of Biomass Transport and Logistics

Global demand for lignocellulosic biomass is growing, driven by a desire to increase the contribution of renewable energy to the world energy mix. A barrier to the expansion of this industry is that biomass is not always geographically where it needs to be, nor does it have the characteristics required for efficient handling, storage, and conversion, due to low energy density compared to fossil fuels. Technologies exist that can create a more standardized feedstock for conversion processes and decrease handling and transport costs; however, the cost associated with those operations often results in a feedstock that is too expensive. The disconnect between quantity of feedstock needed to meet bioenergy production goals, the quality required by the conversion processes, and the cost bioenergy producers are able to pay creates a need for new and improved technologies that potentially remove barriers associated with biomass use.

The role of bioenergy and biochemicals in CO2 mitigation through the energy system – a scenario analysis for the Netherlands

Bioenergy as well as bioenergy with carbon capture and storage are key options to embark on cost‐efficient trajectories that realize climate targets. Most studies have not yet assessed the influence on these trajectories of emerging bioeconomy sectors such as biochemicals and renewable jet fuels (RJFs). To support a systems transition, there is also need to demonstrate the impact on the energy system of technology development, biomass and fossil fuel prices. We aim to close this gap by assessing least‐cost pathways to 2030 for a number of scenarios applied to the energy system of the Netherlands, using a cost‐minimization model. The type and magnitude of biomass deployment are highly influenced by technology development, fossil fuel prices and ambitions to mitigate climate change. Across all scenarios, biomass consumption ranges between 180 and 760 PJ and national emissions between 82 and 178 Mt CO2. High technology development leads to additional 100–270 PJ of biomass consumption and 8–20 Mt CO2 emission reduction compared to low technology development counterparts. In high technology development scenarios, additional emission reduction is primarily achieved by bioenergy and carbon capture and storage. Traditional sectors, namely industrial biomass heat and biofuels, supply 61–87% of bioenergy, while wind turbines are the main supplier of renewable electricity. Low technology pathways show lower biochemical output by 50–75%, do not supply RJFs and do not utilize additional biomass compared to high technology development. In most scenarios the emission reduction targets for the Netherlands are not met, as additional reduction of 10–45 Mt CO2 is needed. Stronger climate policy is required, especially in view of fluctuating fossil fuel prices, which are shown to be a key determinant of bioeconomy development. Nonetheless, high technology development is a no‐regrets option to realize deep emission reduction as it also ensures stable growth for the bioeconomy even under unfavourable conditions.

Renewable jet fuel supply scenarios in the European Union in 2021-2030 in the context of proposed biofuel policy and competing biomass demand

This study presents supply scenarios of nonfood renewable jet fuel (RJF) in the European Union (EU) toward 2030, based on the anticipated regulatory context, availability of biomass and conversion technologies, and competing biomass demand from other sectors (i.e., transport, heat, power, and chemicals). A cost optimization model was used to identify preconditions for increased RJF production and the associated emission reductions, costs, and impact on competing sectors. Model scenarios show nonfood RJF supply could increase from 1 PJ in 2021 to 165–261 PJ/year (3.8–6.1 million tonne (Mt)/year) by 2030, provided advanced biofuel technologies are developed and adequate (policy) incentives are present. This supply corresponds to 6%–9% of jet fuel consumption and 28%–41% of total nonfood biofuel consumption in the EU. These results are driven by proposed policy incentives and a relatively high fossil jet fuel price compared to other fossil fuels. RJF reduces aviation‐related combustion emission by 12–19 Mt/year CO2‐eq by 2030, offsetting 53%–84% of projected emission growth of the sector in the EU relative to 2020. Increased RJF supply mainly affects nonfood biofuel use in road transport, which remained relatively constant during 2021–2030. The cost differential of RJF relative to fossil jet fuel declines from 40 €/GJ (1,740 €/t) in 2021 to 7–13 €/GJ (280–540 €/t) in 2030, because of the introduction of advanced biofuel technologies, technological learning, increased fossil jet fuel prices, and reduced feedstock costs. The cumulative additional costs of RJF equal €7.7–11 billion over 2021–2030 or €1.0–1.4 per departing passenger (intra‐EU) when allocated to the aviation sector. By 2030, 109–213 PJ/year (2.5–4.9 Mt/year) RJF is produced from lignocellulosic biomass using technologies which are currently not yet commercialized. Hence, (policy) mechanisms that expedite technology development are cardinal to the feasibility and affordability of increasing RJF production.

Using Dynamic Relative Climate Impact curves to quantify the climate impact of bioenergy production systems over time

The climate impact of bioenergy is commonly quantified in terms of CO2 equivalents, using a fixed 100‐year global warming potential as an equivalency metric. This method has been criticized for the inability to appropriately address emissions timing and the focus on a single impact metric, which may lead to inaccurate or incomplete quantification of the climate impact of bioenergy production. In this study, we introduce Dynamic Relative Climate Impact (DRCI) curves, a novel approach to visualize and quantify the climate impact of bioenergy systems over time. The DRCI approach offers the flexibility to analyze system performance for different value judgments regarding the impact category (e.g., emissions, radiative forcing, and temperature change), equivalency metric, and analytical time horizon. The DRCI curves constructed for fourteen bioenergy systems illustrate how value judgments affect the merit order of bioenergy systems, because they alter the importance of one‐time (associated with land use change emissions) versus sustained (associated with carbon debt or foregone sequestration) emission fluxes and short‐ versus long‐lived climate forcers. Best practices for bioenergy production (irrespective of value judgments) include high feedstock yields, high conversion efficiencies, and the application of carbon capture and storage. Furthermore, this study provides examples of production contexts in which the risk of land use change emissions, carbon debt, or foregone sequestration can be mitigated. For example, the risk of indirect land use change emissions can be mitigated by accompanying bioenergy production with increasing agricultural yields. Moreover, production contexts in which the counterfactual scenario yields immediate or additional climate impacts can provide significant climate benefits. This paper is accompanied by an Excel‐based calculation tool to reproduce the calculation steps outlined in this paper and construct DRCI curves for bioenergy systems of choice.

Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market

ABSTRACT Many factors may globally affect the trade pattern for industrial-grade wood pellets, with one such factor being the decision strategies by potential buyers and suppliers to optimize feedstock price and volume. This study investigated the industrial-grade wood pellet market assuming potential buyers and suppliers optimize their decision independently. A non-cooperative, bi-level, Stackelberg, leader-follower game model was developed to predict potential resource distribution in global competitive feedstock markets for industrial-grade wood pellets. Based on historic trade patterns and expected future production and demand structures, a set of potential buyers and suppliers of industrial-grade wood pellets were identified for 2022, 2030, and 2040. Projected trade volume and patterns among buyers and suppliers were identified in different scenarios. Potential buyers for US-sourced industrial grade-wood pellet were identified. Results shows that the expected demand growth from the European Union, South Korea, and Japan until the year 2030 limits the resources available to the USA. Competitive prices offered by international buyers cause the US industry to primarily sell overseas. International trade could contribute to 83.4% of the total volume in 2022 and 90.2% of the total trade value in 2022. High-demand markets with a respective high willingness-to-pay dominate international trade.

Combined Cycle Gas Turbine (CCGT) Plants

Technological learning is a key driver behind the improvement of energy technologies and subsequent reduction of production costs. Understanding how and why production costs for energy technologies decline, and whether they will continue to do so in the future, is of crucial importance for policy makers, industrial stakeholders and scientists alike. This timely and informative book therefore provides a comprehensive review of technological development and cost reductions for renewable energy, clean fossil fuel and energy-efficient demand-side technologies. It responds to the need for a quality-controlled data set of experience curves, including assessment of measurement methodology, technological knowledge and associated cost. The expert contributors present a thorough overview and discussion of the pitfalls of applying the experience curve approach, including aspects such as geographical system boundaries, whether the slope of the experience curves is constant or not, statistical error and sensitivity analysis of experience curves, and whether the experience curve approach can be utilized to quantify improvements in energy efficiency. A clear set of recommendations for the use of the experience curve approach is also prescribed. Providing a significant contribution to the current literature on energy and climate models, scenario analysis, and methodological lessons on experience curves, this book will strongly appeal to academics and students in the areas focusing on energy and public sector economics. Policy makers in these fields will also find the book to be of great interest.