• Energy Research

We present an overview of results from 11 integrated assessment models (IAMs) that participated in the 33rd study of the Stanford Energy Modeling Forum (EMF-33) on the viability of large-scale deployment of bioenergy for achieving long-run climate goals. The study explores future bioenergy use across models under harmonized scenarios for future climate policies, availability of bioenergy technologies, and constraints on biomass supply. This paper provides a more transparent description of IAMs that span a broad range of assumptions regarding model structures, energy sectors, and bioenergy conversion chains. Without emission constraints, we find vastly different CO2 emission and bioenergy deployment patterns across models due to differences in competition with fossil fuels, the possibility to produce large-scale bio-liquids, and the flexibility of energy systems. Imposing increasingly stringent carbon budgets mostly increases bioenergy use. A diverse set of available bioenergy technology portfolios provides flexibility to allocate bioenergy to supply different final energy as well as remove carbon dioxide from the atmosphere by combining bioenergy with carbon capture and sequestration (BECCS). Sector and regional bioenergy allocation varies dramatically across models mainly due to bioenergy technology availability and costs, final energy patterns, and availability of alternative decarbonization options. Although much bioenergy is used in combination with CCS, BECCS is not necessarily the driver of bioenergy use. We find that the flexibility to use biomass feedstocks in different energy sub-sectors makes large-scale bioenergy deployment a robust strategy in mitigation scenarios that is surprisingly insensitive with respect to reduced technology availability. However, the achievability of stringent carbon budgets and associated carbon prices is sensitive. Constraints on biomass feedstock supply increase the carbon price less significantly than excluding BECCS because carbon removals are still realized and valued. Incremental sensitivity tests find that delayed readiness of bioenergy technologies until 2050 is more important than potentially higher investment costs.

AbstractBioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

Abstract In order to achieve the Paris Agreement target of well below 2-degrees centigrade goal, developed countries have committed to reducing their emissions considerably during the coming decades. In order to achieve the ambitious target of an 80 % CO2 emission reduction in Japan by 2050 (compared to 2013 levels), various energy efficient and low-carbon technologies on the supply and demand sides of the energy system must be deployed at reasonable cost. In this study, we investigate the possibility of achieving the emission reduction targets in Japan using the TIMES-Japan framework, which employs a least cost optimization approach. The contribution of carbon capture and storage (CCS) in achieving the emission reduction targets is studied in various scenarios as alongside the evaluation of two important emission reducing technologies in the same energy sector as CCS. Results of the analysis reveals the importance of hydrogen import on the supply side and the electrification of steel-making furnaces (EAF) on the demand side in order to obtain “feasible” scenarios. The minimum amount of CCS capacity is calculated for each scenario and the results vary between 5 and 150 million tons of CO2 by 2050. The range of minimum CCS capacity is wide and affected by the availability of hydrogen imports and EAF for steelmaking in various scenarios; while extremely low CCS capacity results in a very high energy system cost. Based on the results of our analysis, policy implications for appropriate levels of CCS, hydrogen import and EAF deployment are discussed.

AbstractJapan’s long-term strategy submitted to the United Nations Framework Convention on Climate Change emphasizes the importance of improving the electrification rates to reducing GHG emissions. Using the five models participating in Energy Modeling Forum 35 Japan Model Intercomparison project (JMIP), we focused on the demand-side decarbonization and analyzed the final energy composition required to achieve 80% reductions in GHGs by 2050 in Japan. The model results show that the electricity share in final energy use (electrification rate) needs to reach 37–66% in 2050 (26% in 2010) to achieve the emissions reduction of 80%. The electrification rate increases mainly due to switching from fossil fuel end-use technologies (i.e. oil water heater, oil stove and combustion-engine vehicles) to electricity end-use technologies (i.e. heat pump water heater and electric vehicles). The electricity consumption in 2050 other than AIM/Hub ranged between 840 and 1260 TWh (AIM/Hub: 1950TWh), which is comparable to the level seen in the last 10 years (950–1035 TWh). The pace at which electrification rate must be increased is a challenge. The model results suggest to increase the electrification pace to 0.46–1.58%/yr from 2030 to 2050. Neither the past electrification pace (0.30%/year from 1990 to 2010) nor the outlook of the Ministry of Economy, Trade and Industry (0.15%/year from 2010 to 2030) is enough to reach the suggested electrification rates in 2050. Therefore, more concrete measures to accelerate dissemination of electricity end-use technologies across all sectors need to be established.

Abstract Climate extremes have remarkable impacts on ecosystems and are expected to increase with future global warming. However, only few studies have focused on the ecological extreme events and their drivers in China. In this study, we carried out an analysis of negative extreme events in gross primary productivity (GPP) in China and the sub-regions during 1982–2015, using monthly GPP simulated by 12 process-based models (TRENDYv6) and an observation-based model (Yao-GPP). Extremes were defined as the negative 5th percentile of GPP anomalies, which were further merged into individual extreme events using a three-dimensional contiguous algorithm. Spatio-temporal patterns of negative GPP anomalies were analyzed by taking the 1000 largest extreme events into consideration. Results showed that the effects of extreme events decreased annual GPP by 2.8% (i.e. 208 TgC year−1) in TRENDY models and 2.3% (i.e. 151 TgC year−1) in Yao-GPP. Hotspots of extreme GPP deficits were mainly observed in North China (−53 gC m−2 year−1) in TRENDY models and Northeast China (−42 gC m−2 year−1) in Yao-GPP. For China as a whole, attribution analyses suggested that extreme low precipitation was associated with 40%–50% of extreme negative GPP events. Most events in northern and western China could be explained by meteorological droughts (i.e. low precipitation) while GPP extreme events in southern China were more associated with temperature extremes, in particular with cold spells. GPP was revealed to be much more sensitive to heat/drought than to cold/wet extreme events. Combined with projected changes in climate extremes in China, GPP negative anomalies caused by drought events in northern China and by temperature extremes in southern China might be more prominent in the future.

This paper explores the role of negative emissions technologies (NETs) in energy systems, bioenergy with carbon capture and storage (BECCS) and direct air capture (DAC) with geological carbon storage (DACCS) in particular, using a bottom-up energy system model TIMES-Japan that participated in the 35th study of the Stanford Energy Modeling Forum (EMF 35 JMIP) focusing on the energy transitions for the long-run climate goals. Modeling results show that large-scale deployment of NETs is essential to achieve the net-zero vision of Japan’s long-term strategy, however, these NETs might not be enough in the case of the highest energy service demands. Within the feasible solution space, earlier deployment of BECCS with domestic biomass can contribute effectively to achieve the target with the support of the DACCS at the later period if both technologies are available. It shows feasible results without DACCS only in the lowest energy service demands, implying the importance of urgent research, development, and deployment of DACCS. Furthermore, this study shows that earlier deployment of DAC system with CO2 utilization in fuel production is a cost-effective way to lead the large-scale deployment of the DAC as NETs.

AbstractAn integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.