Suchergebnisse

As the EU energy system transitions to low carbon, the technology choices should consider a broader set of criteria. The use of Life Cycle Assessment (LCA) prevents burden shift across life cycle stages or impact categories, while the use of Energy System Models (ESM) allows evaluating alternative policies, capacity evolution and covering all the sectors. This study does an ex-post LCA analysis of results from JRC-EU-TIMES and estimates the environmental impact indicators across 18 categories in scenarios that achieve 80–95% CO 2 emission reduction by 2050. Results indicate that indirect CO 2 emissions can be as large as direct ones for an 80% CO 2 reduction target and up to three times as large for 95% CO 2 reduction. Impact across most categories decreases by 20–40% as the CO 2 emission target becomes stricter. However, toxicity related impacts can become 35–100% higher. The integrated framework was also used to evaluate the Power-to-Methane (PtM) system to relate the electricity mix and various CO 2 sources to the PtM environmental impact. To be more attractive than natural gas, the climate change impact of the electricity used for PtM should be 123–181 gCO 2eq /kWh when the CO 2 comes from air or biogenic sources and 4–62 gCO 2eq /kWh if the CO 2 is from fossil fuels. PtM can have an impact up to 10 times larger for impact categories other than climate change. A system without PtM results in ~4% higher climate change impact and 9% higher fossil depletion, while having 5–15% lower impact for most of the other categories. This is based on a scenario where 9 parameters favor PtM deployment and establishes the upper bound of the environmental impact PtM can have. Further studies should work towards integrating LCA feedback into ESM and standardizing the methodology.

As the EU energy system transitions to low carbon, the technology choices should consider a broader set of criteria. The use of Life Cycle Assessment (LCA) prevents burden shift across life cycle stages or impact categories, while the use of Energy System Models (ESM) allows evaluating alternative policies, capacity evolution and covering all the sectors. This study does an ex-post LCA analysis of results from JRC-EU-TIMES and estimates the environmental impact indicators across 18 categories in scenarios that achieve 80–95% CO2 emission reduction by 2050. Results indicate that indirect CO2 emissions can be as large as direct ones for an 80% CO2 reduction target and up to three times as large for 95% CO2 reduction. Impact across most categories decreases by 20–40% as the CO2 emission target becomes stricter. However, toxicity related impacts can become 35–100% higher. The integrated framework was also used to evaluate the Power-to-Methane (PtM) system to relate the electricity mix and various CO2 sources to the PtM environmental impact. To be more attractive than natural gas, the climate change impact of the electricity used for PtM should be 123–181 gCO2eq/kWh when the CO2 comes from air or biogenic sources and 4–62 gCO2eq/kWh if the CO2 is from fossil fuels. PtM can have an impact up to 10 times larger for impact categories other than climate change. A system without PtM results in ~4% higher climate change impact and 9% higher fossil depletion, while having 5–15% lower impact for most of the other categories. This is based on a scenario where 9 parameters favor PtM deployment and establishes the upper bound of the environmental impact PtM can have. Further studies should work towards integrating LCA feedback into ESM and standardizing the methodology.

Fuel cell electric vehicles (FCEV) currently have the challenge of high CAPEX mainly associated to the fuel cell. This study investigates strategies to promote FCEV deployment and overcome this initial high cost by combining a detailed simulation model of the passenger transport sector with an energy system model. The focus is on an energy system with 95% CO 2 reduction by 2050. Soft-linking by taking the powertrain shares by country from the simulation model is preferred because it considers aspects such as car performance, reliability and safety while keeping the cost optimization to evaluate the impact on the rest of the system. This caused a 14% increase in total cost of car ownership compared to the cost before soft-linking. Gas reforming combined with CO 2 storage can provide a low-cost hydrogen source for FCEV in the first years of deployment. Once a lower CAPEX for FCEV is achieved, a higher hydrogen cost from electrolysis can be afforded. The policy with the largest impact on FCEV was a purchase subsidy of 5 k€ per vehicle in the 2030–2034 period resulting in 24.3 million FCEV (on top of 67 million without policy) sold up to 2050 with total subsidies of 84 bln€. 5 bln€ of R&D incentives in the 2020–2024 period increased the cumulative sales up to 2050 by 10.5 million FCEV. Combining these two policies with infrastructure and fuel subsidies for 2030–2034 can result in 76 million FCEV on the road by 2050 representing more than 25% of the total car stock. Country specific incentives, split of demand by distance or shift across modes of transport were not included in this study.

This paper provides a method to identify drivers, barriers and synergies (DBS) related to the deployment of a CO 2 pipeline network. The method was demonstrated for the West Mediterranean region (WMR) (i.e. Spain, Portugal and Morocco). The method comprises a literature review, analysis of embedded pipeline trajectories, interviews with experts, and workshops with stakeholders. Subsequently, the collected information was used to identify route specific DBS in several CO 2 pipeline network deployment scenarios that were modeled for the WMR. Most identified DBS apply to CO 2 pipeline transport in general. The barriers (e.g. technical knowledge gaps, outstanding legislative issues, lack of financial incentive) can in principle be tackled to make the design, construction and operation of a CO 2 pipeline network possible, but could sometimes lead to somewhat higher costs. Furthermore, there are also facilitating processes (e.g. experience with CO 2 pipeline transport for EOR). Cost benefits due to pipeline oversizing were identified as a route specific driver, whereas crossings of mountains, water and nature areas are route specific barriers. Installing CO 2 pipelines along natural gas pipelines could be either a route specific synergy or barrier, depending on site conditions. Finally, several key measures were proposed to enable CO 2 pipeline networks in the future.

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.

This report quantifies the required emission reductions of the EU aviation sector to achieve carbon-neutral growth up to 2030. It explores the role of Renewable Jet Fuel (RJF) in reducing aviation CO2 emissions and available feedstock and technology options to produce RJF towards 2030. Four possible RJF deployment scenarios (varying in the level of RJF deployment) are formulated and evaluated in terms of cost and impact on the EU bioenergy portfolio. The report concludes with key preconditions for RJF deployment in the EU towards 2030.

It is commonly recognized that large uncertainties exist in modelled biofuel-induced indirect land-use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general methodology to stochastically calculate direct and indirect land-use change (dLUC and iLUC) caused by an increasing demand for biofuels, with an integrated economic - land-use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land-use change model PLUC. We quantify important uncertainties in the modelling chain. Next, dLUC and iLUC projections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell-based (5 × 5 km 2 ) probabilities of dLUC range from 0 to 0.77, and of iLUC from 0 to 0.43, indicating that it is difficult to project exactly where dLUC and iLUC will occur, with more difficulties for iLUC than for dLUC. At country level, dLUC area can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, while iLUC area is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, the iLUC area in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation for iLUC indicators should not be implemented in legislation. For future studies, we emphasize the need for provision of quantitative uncertainty estimates together with the calculated LUC indicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land-use change, such as greenhouse gas emissions.

Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, landuse and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts. We summarize technological options, outline the state-of-theart knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end-use efficiency, improved land carbon-stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small-scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100 EJ: high agreement; 100–300 EJ: medium agreement; above 300 EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245 EJ yr 1 to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large-scale deployment (>200 EJ), together with BECCS, could help to keep global warming below 2° degrees of preindustrial levels; but such high deployment of land-intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options. ; publishedVersion ; © 2015. This is the authors' accepted and refereed manuscript to the article. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ DOI:10.1111/gcbb.12205