Engineering topics

Sano, Fuminori

Publications and source records attributed to Sano, Fuminori.

3 records

DOE OSTI2022

Global biomass supply modeling for long-run management of the climate system

Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.

09 BIOMASS FUELS↗

DOE OSTI2022

The contribution of bioenergy to the decarbonization of transport: a multi-model assessment

The expected growth in the demand for passenger and freight services exacerbates the challenges of reducing transport GHG emissions, especially as commercial low-carbon alternatives to petroleum fuels are limited for shipping, air and long-distance road travel. Biofuels can offer a pathway to significantly reduce emissions from these sectors, as they can easily substitute for conventional liquid fuels in internal combustion engines. In this paper, we assess the potential of bioenergy to reduce transport GHG emissions through an analysis leveraging various integrated assessment models and scenarios, as part of the 33rd Energy Modeling Forum study (EMF-33). Furthermore, we find that bioenergy can contribute a significant, albeit not dominant, proportion of energy supply to the future transport sector: in scenarios aiming to keep the temperature increase below 2 °C by the end of the twenty-first century, models project that in 2100 bioenergy can provide on average 42 EJ/yr (ranging from 5 to 85 EJ/yr) for transport (compared to 3.7 EJ in 2018), mainly through lignocellulosic fuels. This makes up 9–62% of final transport energy use. Only a small amount of bioenergy is projected to be used in transport through electricity and hydrogen pathways, with a larger role for biofuels in road passenger transport than in freight. The association of carbon capture and storage (CCS) with bioenergy technologies (BECCS) is a key determinant in the role of biofuels in transport, because of the competition for biomass feedstock to provide other final energy carriers along with carbon removal. Among models that consider CCS in the biofuel conversion process the average market share of biofuels is 21% in 2100 (ranging from 2 to 44%), compared to 10% (0–30%) for models that do not. Cumulative direct emissions from the transport sector account for half of the emission budget (from 306 to 776 out of 1,000 GtCO 2 ). However, the carbon intensity of transport decreases as much as other energy sectors in 2100 when accounting for process emissions, including carbon removal from BECCS. Lignocellulosic fuels become more attractive for transport decarbonization if BECCS is not feasible for any energy sectors. Since global transport service demand increases and biomass supply is limited, its allocation to and within the transport sector is uncertain and sensitive to assumptions about political as well as technological and socioeconomic factors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Integrated assessment model diagnostics: key indicators and model evolution

Integrated assessment models (IAMs) form a prime tool in informing climate mitigation strategies. Diagnostic indicators that allow to compare these models can help to describe and explain differences in model projections. This also increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler et al., 2015). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index (RAI), emission reduction type index (ERT), inertia timescale (IT), fossil fuel reduction (FFR), transformation index (TI) and cost per abatement value (CAV). We apply the approach to 17 IAMs, including both older version as well as their latest versions, as applied in the IPCC 6th Assessment Report (AR6). The study shows that the approach can be easily applied and allows for comparison of model versions in time. The indicators and their trends can often be explained in terms of model characteristics and changes. We show that together, the set of six indicators can provide an useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend across the different models.

54 ENVIRONMENTAL SCIENCES↗