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

Economic performance and GHG emission intensity of sugarcane- and eucalyptus-derived biofuels and biobased chemicals in Brazil

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

Impact of increased wood pellet demand on biodiversity in the south-eastern United States

Increasing wood pellet exports from the United States are projected to lead to changes in land use and timberland management, including a shift from natural timberland to pine plantations. These projected changes may impact biodiversity. This study aims to quantify potential biodiversity impacts of increased wood pellet demand in the south-eastern United States in a spatially explicit manner. We determined differences according to an index of potential species richness (for total, threatened and endemic species and four taxonomic groups) between scenarios of high and low demand for wood pellets, while taking into account potential developments in other wood markets and other land uses. Increased demand for wood pellets was projected to cause both positive and negative biodiversity impacts. Negative shifts in total potential species richness were projected for areas in Florida, coastal Virginia and North Carolina, and parts of the Gulf Coast. Positive shifts in total potential species richness were projected in parts of Oklahoma and Arkansas. In some locations, the direction of change differed per taxonomic group, highlighting the importance of analysing different taxonomic groups. Shifts in potential species richness due to increased wood pellet demand were considerably smaller compared to the changes due to other drivers, such as urbanization and increased timber demand. Biodiversity impacts due to wood pellet demand should therefore be considered in the context of other drivers of land-use change and biodiversity loss. Our results provide information that allows policymakers, industry and NGOs to focus on areas of concern and take appropriate mitigation measures to limit negative biodiversity impacts and promote positive impacts. The spatially explicit approach presented in this study can be applied to different regions and drivers of land-use change, to show how projected demand for an internationally traded commodity may lead to impacts on land use and biodiversity in the procurement region

Economic performance and GHG emission intensity of sugarcane- and eucalyptus-derived biofuels and biobased chemicals in Brazil

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