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The goal of limiting global temperature rise to “well below” 2 °C has been reaffirmed in the Paris Agreement on climate change at the 21st Conference of the Parties (COP21). Almost all countries submitted their decarbonization targets in their Intended Nationally Determined Contributions (INDC) to the United Nations Framework Convention on Climate Change (UNFCCC) and India did as well. India’s nationally determined contribution (NDC) aims to reduce greenhouse gas (GHG) emissions intensity of national GDP in 2030 by 33–35% compared to 2005. This paper analyzes how India’s NDC commitments compare with emission trajectories consistent with well below 2 °C and 1.5 °C global temperature stabilization goals. A top-down computable general equilibrium model is used for the analysis. Our analysis shows that there are significant emission gaps between NDC and global climate stabilization targets in 2030. The energy system requires significant changes, mostly relying on renewable energy and carbon capture and storage (CCS) technology. The mitigation costs would increase if India delays its abatement efforts and is locked into NDC pathways till 2030. India’s GHG emissions would peak 10 years earlier under 1.5 °C global temperature stabilization compared to the 2 °C goal. The results imply that India would need financial and technological support from developed countries to achieve emissions reductions aligned with the global long-term goal.

Abstract Japan’s mid-century strategy for reducing greenhouse gas emissions by 80% in 2050 would require large-scale energy system transformation and associated increases in mitigation costs. Nevertheless, the role of energy demand reduction, especially reductions related to energy services such as behavioral changes and material use efficiency improvements, have not been sufficiently evaluated. This study aims to identify key challenges and opportunities of the decarbonization goal when considering the role of energy service demand reduction. To this end, we used a detailed bottom-up energy system model in conjunction with an energy service demand model to explore energy system changes and their cost implications. The results indicate that final energy demand in 2050 can be cut by 37% relative to the no-policy case through energy service demand reduction measures. Although the lack of carbon capture and storage would cause mitigation costs to double or more, these economic impacts can be offset by energy service demand reduction. Among energy demand sectors, the impact of industrial service demand reduction is largest, as it contributes to reducing residual emissions from the industry sector. These findings highlight the importance of energy service demand reduction measures for meeting national climate goals in addition to technological options.

AbstractClimate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators.

The industry sector is a major energy consumer and GHG emitter. Effective climate change mitigation strategies will require a significant reduction of industrial emissions. To better understand the variations in the projected industrial pathways for both baseline and mitigation scenarios, we compare key input and structure assumptions used in energy-models in relation to the modeled sectors' mitigation potential. It is shown that although all models show in the short term similar trends in a baseline scenario, where industrial energy demand increases steadily, after 2050 energy demand spans a wide range across the models (between 203 and 451 EJ/yr). In Non-OECD countries, the sectors energy intensity is projected to decline relatively rapidly but in the 2010–2050 period this is offset by economic growth. The ability to switch to alternative fuels to mitigate GHG emissions differs across models with technologically detailed models being less flexible in switching from fossil fuels to electricity. This highlights the importance of understanding economy-wide mitigation responses and costs and is therefore an area for improvements. By looking at the cement sector in more detail, we show that analyzing each industrial sub-sector separately can improve the interpretation and accuracy of outcomes, and provide insights in the feasibility of GHG abatement.

Abstract Japan is the sixth largest greenhouse gas emitter in 2016 and plays an important role to attain the long-term climate goals of the Paris Agreement. One of the key policy issues in Japan's energy and environmental policy arena is the energy system transition to achieve 80% emissions reduction in 2050, a current policy goal set in 2016. To contribute to the ongoing policy debate, this paper focuses on energy-related CO2 emissions and analyzes such decarbonization scenarios that are consistent with the government goals. We employ six energy-economic and integrated assessment models to reveal decarbonization challenges in the energy system. The modeling results show that Japan's mitigation scenarios are characterized by high marginal costs of abatement. They also suggest that the industrial sector is likely to have a large final energy share and significant residual emissions under the 80% reduction scenario, though it is generally thought that the transport sector would have large decarbonization challenges. The present findings imply that not only energy policy but also industrial policy may be relevant to the long-term environmental target. Given the high marginal costs exceeding those of negative emissions technologies that could place a cost ceiling, further model development would be crucial.

Abstract This paper performs energy model hindcasting which compared the historical energy simulation results with the observations. We used one of the Integrated Assessment Models and simulated global historical energy consumption from 1981 to 2010 associated with exogenous socioeconomic assumptions, as is typically performed for future scenario. The simulation period was chosen with consideration of data availability and structural constancy of the model. Based on comparison with observations, there are three main findings. First, the global aggregated primary energy shows high reproducibility. In terms of energy source specific results, the fitness in electricity, coal, and biomass consumption were high. However, that of crude oil and natural gas is lower than others. This could be due to the price elasticity assumption, implying that the model can be improved with regard to this element. Second, the reproducibility increases as the simulation is close to the base year 2005. Third, although the global aggregated information shows high reproducibility, some disaggregated regions have lower reproducibility. Furthermore, high income countries tend to show higher reproducibility than in low income countries. Given the uncertainties in the ability of IAMs to reproduce certain aspects of the energy system, forecasts must be treated with caution.

AbstractThe building sector is highly sensitive to climate change, where energy is used for numerous purposes such as heating, cooling, cooking and lighting. Space heating and cooling account for a large proportion of overall energy use, and the associated energy demand is also affected by climate change. Here, we project the economic impact of changes in energy demand for space heating and cooling under multiple climatic conditions. We use an economic model coupled with an end-use technology model to explicitly represent the investment costs for air-conditioning technologies, which influence the macroeconomy. We conclude that the negative effects on the economy from increases in the use of space cooling are sufficiently large to neutralize the positive impacts from reductions in space heating usage under climate change, which results in significant economic loss. The economic loss under the highest emissions scenario (RCP8.5) would correspond to a −0.34% (−0.39% to −0.18%) change in global gross domestic product (GDP) in 2100 compared with GDP without any climate change, while the impact under the lowest emissions scenario (RCP2.6) would result in a −0.03% (−0.07% to −0.01%) change in global GDP in 2100. The economic losses are mainly generated by incremental technological costs and not by changes in energy demand itself. The amount of economic loss can vary substantially based on assumptions of technological costs, population and income. To reduce the negative impacts of climate change measures for reducing the costs of air conditioning will be an important consideration for the building sector in the future.

Abstract Integrated assessment models (IAMs) form a prime tool in informing about climate mitigation strategies. Diagnostic indicators that allow comparison across these models can help describe and explain differences in model projections. This increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler (2015 Technol. Forecast. Soc. Change 90 45–61)). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, to systematically and routinely assess IAM behaviour, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index, emission reduction type index, inertia timescale, fossil fuel reduction, transformation index and cost per abatement value. We apply the approach to 17 IAMs, assessing both older as well as their latest versions, as applied in the IPCC 6th Assessment Report. The study shows that the approach can be easily applied and used to indentify key differences between models and model versions. Moreover, we demonstrate that this comparison helps to link model behavior to model characteristics and assumptions. We show that together, the set of six indicators can provide 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.