This study examines model-specific assumptions and projections of methane (CH 4) emissions in deep mitigation scenarios generated by integrated assessment models (IAMs). For this, scenarios of nine models are compared in terms of sectoral and regional CH 4 emission reduction strategies, as well as resulting climate impacts. The models' projected reduction potentials are compared to sector and technology-specific reduction potentials found in literature. Significant cost-effective and nonclimate policy related reductions are projected in the reference case (10-36% compared to a "frozen emission factor" scenario in 2100). Still, compared to 2010, CH 4 emissions are expected to rise steadily by 9-72% (up to 412 to 654 Mt CH 4 /year). Ambitious CO 2 reduction measures could by themselves lead to a reduction of CH 4 emissions due to a reduction of fossil fuels (22-48% compared to the reference case in 2100). However, direct CH 4 mitigation is crucial and more effective in bringing down CH 4 (50-74% compared to the reference case). Given the limited reduction potential, agriculture CH 4 emissions are projected to constitute an increasingly larger share of total anthropogenic CH 4 emissions in mitigation scenarios. Enteric fermentation in ruminants is in that respect by far the largest mitigation bottleneck later in the century with a projected 40-78% of total remaining CH 4 emissions in 2100 in a strong (2°C) climate policy case.

Several studies have shown that the greenhouse gas reduction resulting from the current nationally determined contributions (NDCs) will not be enough to meet the overall targets of the Paris Climate Agreement. It has been suggested that more ambition mitigations of short-lived climate forcer (SLCF) emissions could potentially be a way to reduce the risk of overshooting the 1.5 or 2°C target in a cost-effective way. In this study, we employ eight state-of-the-art integrated assessment models (IAMs) to examine the global temperature effects of ambitious reductions of methane, black and organic carbon, and hydrofluorocarbon emissions. The SLCFs measures considered are found to add significantly to the effect of the NDCs on short-term global mean temperature (GMT) (in the year 2040: − 0.03 to − 0.15°C) and on reducing the short-term rate-of-change (by − 2 to 15%), but only a small effect on reducing the maximum temperature change before 2100. This, because later in the century under assumed ambitious climate policy, SLCF mitigation is maximized, either directly or indirectly due to changes in the energy system. All three SLCF groups can contribute to achieving GMT changes.

The relatively short atmospheric lifetimes of methane (CH4) and black carbon (BC) have focused attention on the potential for reducing anthropogenic climate change by reducing Short-Lived Climate Forcer (SLCF) emissions. This paper examines radiative forcing and global mean temperature results from the Energy Modeling Forum (EMF)-30 multi-model suite of scenarios addressing CH4 and BC mitigation, the two major short-lived climate forcers. Central estimates of temperature reductions in 2040 from an idealized scenario focused on reductions in methane and black carbon emissions ranged from 0.18–0.26 °C across the nine participating models. Reductions in methane emissions drive 60% or more of these temperature reductions by 2040, although the methane impact also depends on auxiliary reductions that depend on the economic structure of the model. Climate model parameter uncertainty has a large impact on results, with SLCF reductions resulting in as much as 0.3–0.7 °C by 2040. We find that the substantial overlap between a SLCF-focused policy and a stringent and comprehensive climate policy that reduces greenhouse gas emissions means that additional SLCF emission reductions result in, at most, a small additional benefit of ~ 0.1 °C in the 2030–2040 time frame.

The persistent uncertainty about mid-century CO 2 emissions targets is likely to affect not only the technological choices that energy-producing firms will make in the future but also their current investment decisions. We illustrate this effect on CO 2 price and global energy transition within a MERGE-type general-equilibrium model framework, by considering simple stochastic CO 2 policy scenarios. In these scenarios, economic agents know that credible long-run CO 2 emissions targets will be set in 2020, with two possible outcomes: either a "hard cap" or a "soft cap". Each scenario is characterized by the relative probabilities of both possible caps. We derive consistent stochastic trajectories -with two branches after 2020 -for prices and quantities of energy commodities and CO 2 emissions permits. The impact of uncertain long-run CO 2 emissions targets on prices and technological trajectories is discussed. In addition, a simple marginal approach allows us to analyze the Hotelling rule with risk premia observed for certain scenarios.

This report develops an analytical framework that assesses the macroeconomic, environmental and distributional consequences of energy subsidy reforms. The framework is applied to the case of Indonesia to study the consequences in this country of a gradual phase out of all energy consumption subsidies between 2012 and 2020. The energy subsidy estimates used as inputs to this modelling analysis are those calculated by the International Energy Agency, using a synthetic indicator known as "price gaps". The analysis relies on simulations made with an extended version of the OECD's ENV-Linkages model. The phase out of energy consumption subsidies was simulated under three stylised redistribution schemes: direct payment on a per household basis, support to labour incomes, and subsidies on food products. The modelling results in this report indicate that if Indonesia were to remove its fossil fuel and electricity consumption subsidies, it would record real GDP gains of 0.4% to 0.7% in 2020, according to the redistribution scheme envisaged. The redistribution through direct payment on a per household basis performs best in terms of GDP gains. The aggregate gains for consumers in terms of welfare are higher, ranging from 0.8% to 1.6% in 2020. Both GDP and welfare gains arise from a more efficient allocation of resources across sectors resulting from phasing out energy subsidies. Meanwhile, a redistribution scheme through food subsidies tends to create other inefficiencies. The simulations show that the redistribution scheme ultimately matters in determining the overall distributional performance of the reform. Cash transfers, and to a lesser extent food subsidies, can make the reform more attractive for poorer households and reduce poverty. Mechanisms that compensate households via payments proportional to labour income are, on the contrary, more beneficial to higher income households and increase poverty. This is because households with informal labour earnings, which are not eligible for these payments, are more represented among the poor. The analysis also shows that phasing out energy subsidies is projected to reduce Indonesian CO2 emissions from fuel combustion by 10.8% to 12.6% and GHG emissions by 7.9% to 8.3%, in 2020 in the various scenarios, with respect to the baseline. These emission reductions exclude emissions from deforestation, which are large but highly uncertain and for which the model cannot make reliable projections.