Climate change is a global problem that affects the whole planet as one. Emissions from different countries con- tribute the same to this environmental aspect defined as the effect of anthropogenic emissions which enhance the radioactive forcing of the atmosphere, causing the tem- perature at the earth’s surface to rise . Several gases have influence in this impact, being carbon dioxide the main contributor and the reference to measure the effect of the rest gases. Developed countries are especially concerned about reducing greenhouse gas (GHG) emis- sions as it was established in the Kyoto protocol and fur- ther European policies for energy .
Although it is often claimed that the world economy is becoming less carbon intensive, that is true only to a very minor extent at best, and not at all in recent years. Current economic growth in China and India, coupled with an apparent reluctance on the part of those countries as well as the United States to accept limits on carbonemissions might give one a somewhat pessimistic view of the possibility that humanity will voluntarily make the steps needed to avoid serious anthropogenic interference in the climate system. One way to look at the scenario presented in this paper is that it serves as a kind of best-case result (for global climate) in the case that political and societal insti- tutions do not demonstrate the foresight needed for a smooth decarbonization of the energy system. The limited-fossil-fuel future described here, which is seen as unrealistically pessimistic by some, might be barely sufficient to limit CO 2 concentrations to the doubling of pre-industrial levels that optimists hope
Carbon taxation is the most cost-effective way of reducing emissions, since it induces behavioural changes in economic agents. However, due to its disproportionately negative impacts on poorer households in the absence of appropriate policy design, there is opposition to an increase in the carbon tax, notwithstand- ing increasing awareness of climate change. In addition to carbon taxation (or environmental taxes in general), governments are implementing several policies regarding shifting power production and trans- portation from fossilfuel-based technologies to cleaner energies, increasing energy efficiency, etc. On the other hand, several governments, including the Irish government, also conduct various fossilfuel subsidy schemes to support certain sectors, commodities, or households. Ironically, the budgetary cost of these subsidies is much larger than the environmental tax collections in many country cases. This phenomenon implies that governments actually have a wider fiscal space in the alleviation of the adverse climate change impacts by removing these subsidies rather than levying new environmental taxes or increasing the existing environmental tax rates/levels.
Yet climate policy has tended to focus on promoting low-carbon alternatives (e.g. through carbon pricing, energy efficiency standards or renewable energy support), rather than directly tackling fossil fuels. In one important respect, however, this situation has changed: in the past years, governments, analysts, international organizations and non- governmental organizations (NGOs) have increasingly drawn attention to the subsidies handed out by governments for the production and consumption of fossil fuels. The issue has been taken up in international forums such as the Group of 20 (G20) and the Rio?20 summit, and several international organizations—such as the International Monetary Fund (IMF) and the Organisation for Economic Co-operation and Development (OECD)—and NGOs—such as the GlobalSubsidies Initiative (GSI)—have provided insights into the scale of such subsidies, as well as their environmental, social and economic implications. By lowering the costs of fossil energy, fossilfuelsubsidies pose a serious barrier for the transition towards a low-carbon economy. Nonetheless, such subsidies are not addressed by the main intergovernmental venue for international cooperation on climate change, the UNFCCC. Although parties to the UNFCCC are free to pursue fossilfuel subsidy reform as a mitigation policy under the climate regime, the UNFCCC, the Kyoto Protocol and the Paris Agreement do not contain rules specific to fossilfuelsubsidies. However, as this article argues, the evolution of the climate regime—which is currently transitioning from a system of internationally agreed binding targets towards a system of nationally determined mitigation contributions—offers new opportunities to include fossilfuelsubsidies within its scope.
Our results also show that reduced population growth could make a signiﬁcant contribution to globalemissions reductions. Several analyses have estimated how much emissions would have to be reduced by 2050 to meet long-term policy goals such as avoiding warming of more than 2 °C (27) or preventing a doubling of CO 2 concentrations through implementation of a portfolio of mitigation measures characterized as “stabilization wedges” (28). Our estimate that following a lower population path could reduce emissions 1.4–2.5 GtC/y by 2050 is equivalent to 16–29% of the emission reductions necessary to achieve these goals or approxi- mately 1–1.5 wedges of emissions reductions ( SI Text has details of this calculation). By the end of the century, the effect of slower population growth would be even more signiﬁcant, reducing total emissions from fossilfuel use by 37–41% across the two scenarios. One caveat is that we have not made any assumptions about how reduced population growth occurs; rather, we treat alter- native population growth paths as exogenous. Economic de- velopment is one factor that can facilitate declines in fertility and slower population growth. If it were assumed that increases in economic growth rates were driving fertility decline, our results would differ: faster economic growth would have an upward effect on emissions, offsetting the emissions reductions caused by slower population growth to some degree.
typically occur quite late in the production history. Rutledge (2011) also discussed the important differences between “re- serves” (coal that can be produced economically with cur- rent technology) versus “resources” (coal that could poten- tially be produced in the future), and the tendency for large amounts of coal to move between these classifications due to periodic changes in estimation techniques or policies. Im- portantly, Rutledge (2011) pointed out that there is a fur- ther category (called “additional recoverable reserves”) that has proven very unreliable in historical surveys. However the SRES predictions for high future coal production (Naki- cenovic and Swart, 2000) are dependent on a single, appar- ently anomalous estimate of additional recoverable reserves by the World Energy Council (WEC, 1998). The WEC sub- sequently downwardly revised its estimates, and by 2007 was stating global coal reserves totaling less than one quarter of their 1998 estimated value (WEC, 2007). While Rutledge (2011) predicted only ultimate coal production, a prediction for future coal production rates was presented by Patzek and Croft (2010) via a multi-Hubbert cycle analysis for differ- ent producing regions, concluding that global coal produc- tion (and associated GHG emissions) could peak as early as 2011, and decline to half of the peak production rate by 2047. This result may be overly pessimistic, and the limita- tions of the multi-Hubbert cycle approach were discussed by Anderson and Conder (2011). Most notably, this approach can allow overly complex curves to be produced that provide an excellent match to the historical data but lack a physical basis and therefore do not aid in future predictions. How- ever, independent forecasts by Mohr and Evans (2009) and H¨o¨ok et al. (2010b) using different methods also suggest that world coal production will probably reach a peak be- fore 2050, falling well short of the IPCC’s high emissions scenarios.
This paper reviewed studies to assess the economic, environmental and social impacts of fossil-fuel subsidy reform. There are a few empirical assessments of fossil-fuel subsidy reform (Hope and Singh, 1995). The majority of the studies that have been undertaken to date are based on partial- and general- equilibrium models. Of these, only six (Burniaux et al., 1992; Larsen and Shah, 1992; IEA, 1999; OECD, 2000; Saunders and Schneider, 2000; Burniaux et al., 2009) have considered fossil-fuel subsidy reform on a multi-country and multi-fuel basis. All six studies are reasonably comprehensive in terms of considering multiple global economic factors and all utilize the price-gap approach to calculating subsidies. They therefore focus on the impacts of removing subsidies to consumers, which are largely provided in developing countries. The removal of producer subsidies, which are provided in almost all countries, are thus not included in the analyses. The models differ in their assumptions and approaches. Each of the six main studies has strengths and weaknesses. For example, the IEA (1999) study did not account for world price or trade effects, and OECD (2000) excluded the transportation sector. Burniaux et al.’s (1992) results placed significant emphasis on the development and use of a higher emitting synthetic fuel, which may or may not occur. Only Saunders and Schneider (2000) presented results of the impacts of fossil-fuel subsidy reform on non-energy sectors in a disaggregated way. Likewise, only the OECD (2000) considered producer subsidies, and provided information on the fuel cross-price elasticity assumptions utilized in the model. Burniaux et al. (2009) was the only study to examine the interplay of fossil-fuel subsidy removal with other climate-change mitigation measures.
The full menu or analysis of mitigation, adaptation, and climate amelioration options available to the globalcarbon industry is beyond the scope of this paper. A partial list includes developing carbon capture and storage capacity (Allen et al. 2009a ), funding adaptation programs (such as the UNFCCC Adaptation Fund), investing in or developing technologies and programs to realize the enormous global potential for efficient use of carbon fuels (Lovins 2011 ), developing low- or zero-carbon alternative fuels and power generation systems, funding geo-engineering research, publicly committing to capture and store or remove carbon dioxide from the atmosphere commensurate with their historic emissions, supporting international climate diplomacy and domestic climate legislation (as leading multina- tional oil and gas companies have begun to do), and, in the event liability for historic and/or future emissions is not averted, setting aside financial reserves to cover potential climate liability claims. Greater transparency, including comprehensive reporting of all direct and product-related emissions, and full disclosure to investors of potential liabilities stemming from company operations or products, material risks to company assets, or material threats to future profits from climate change is warranted (Hancock 2005 ; Coburn et al. 2011 ).
Supply-side climate policies cover, inter alia, extraction taxes, subsidy reform, moratoria or quotas, or a reduced extraction from public lands (Green and Dennis, 2018). The economic theory informing much supply-side policy discourse suggests that coun- tries cooperating to cut emissions can enhance their effectiveness by cutting production as well as demand for fossil fuels (ibid 2018). Without such steps, free riders in terms of mitigation effort will bene ﬁ t from cheaper fossil fuels, as market price adjusts to a lowering of overall demand, causing cross-border ‘ carbon leakage ’ . Moreover, producers would likely accelerate extraction to secure rents before demand falls signi ﬁ cantly (the ‘ green paradox ’ ). While national governments guard their right to govern fossilfuel development and any related transition, international institutions can nevertheless, at least in principle, in ﬂ uence behaviour, constrain activity, and shape expectations in potentially helpful ways (Van Asselt, 2014). By fostering greater transparency and learning, for example, some of the lock-ins noted above could be loosened, particularly related to subsidies. International in- stitutions may be able to ease geo-political tensions provoked by radical supply-side interventions.
cluding 6226 point sources, 2017 ESRI clumps, and 3071 non-ESRI clumps. The clump with the largest annual emis- sion budget is Shanghai, which emits 47 Mt C yr −1 . A large fraction of the non-ESRI clumps is found within China mainly located near the southeastern coast, which may be explained by the recent rapid urbanization (Shan et al., 2018; Wang et al., 2016) in this region. This is not documented by the ESRI map. The large number of non-ESRI clumps in China highlights the necessity of considering emitters out- side the major cities (at least) in this country. In addition, the mean area of an emission clump is larger in China than over other continents and regions. This is because the southeast- ern coast of China is densely populated, even within rural areas (yellow-green outside the urban area of the ESRI urban map in Fig. 4e), and because the emission rates per capita is also high in China compared to the world average (Janssens- Maenhout et al., 2017). As a result, our algorithm finds more non-ESRI clumps and larger areas for each clump in China than other regions.
Contemporary increases in atmospheric carbon dioxide concentration are in large part the result of anthropogen carbon dioxide emissions from fossilfuel combustion. Scenario analysis is commonly used to generate projections future carbon dioxide emissions, the resulting atmospheric concentrations and climate impact. In most scenar modelling published to date, carbon dioxide emission scenarios are based on demand-side (socioeconomic an technology) factors. The fossilfuel resource is assumed ample enough that supply-side factors do not drive futu emission scenarios. This review of the literature on non-renewable resource extraction rate modelling and empiric studies of the globalfossilfuel resource base suggests this assumption is unsafe. Supply-side factors can be expecte to drive extraction rates and therefore carbon dioxide emissions as fossilfuel resources become significant depleted. It is likely that the future carbon dioxide emission trajectory will become dominated by supply-side facto during the 21st century. By omitting this possibility, most scenario analysis is too narrow. An implication of suc narrow scenario analysis is that policy driven by the UNFCCC’s agreement to “avoid dangerous climate change targets only demand-side factors to the exclusion of supply-side factors. As supply-side factors come to drive th carbon dioxide emission trajectory, policy focus should switch from demand-side factors to supply-side factors.
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ergy systems optimization model formulated as an in- tertemporal linear programming problem (see  for a schematic representation of the structure of the model). With a 5% discount rate, the model is designed to deter- mine the cost-optimal energy strategy (e.g., the cost-op- timal choice of technology options) from 2010 to 2050 at 10-year intervals for each of 70 world regions so that total discounted global energy system costs are mini- mized under constraints on the satisfaction of exoge- nously given energy end-use demands, the availability of primary energy resources, material and energy balances, the maximum market growth rates of new technologies, etc. In the model, price-induced energy demand reduc- tions and energy efficiency improvements, fuel switching to less carbon-intensive fuels, and CO 2 capture and stor-
To back up our arguments, we put forward a new IAM of macroeconomic growth and climate change with three features that are not present in the DICE, FUND or PAGE models (Rezai and van der Ploeg, 2015). First, we allow extraction costs to increase as the finite stock of fossilfuel reserves is depleted. This creates a scarcity rent on fossilfuel and a motive not to burn all available reserves. Second, existing IAMs have used rather simple carbon cycles on coarse time grids with the implication that the amount that is left of burning one ton of carbon today at any future is independent of past or current stocks of carbon in the atmosphere. Others have shown that the carbon cycle of DICE can be well represented with a two- or three-box carbon cycle (Golosov et al., 2014; Gerlagh and Liski, 2013), but also abstract from history dependence. The Oxford carbon cycle (e.g., Allen et al., 2009) does give a role for memory and captures the carbon cycle and temperature changes much better and we therefore use this as our carbon cycle. For this cycle cumulative carbonemissions are the main driving force of changes in global mean temperature and this is why we focus on cumulative emissions too. Third, our IAM optimally determines the time at which fossilfuel is phased out and renewable energy is phased in. The transition to the carbon-free phase occurs at the moment that the rise in extraction costs as reserves are depleted plus the rise in the social cost of carbon together with the fall in the cost of renewable energy are sufficiently strong to price fossilfuel out of the market. Our IAM has a finer, annual grid than other IAMs so the timing of energy transitions can be pinpointed more precisely.
But will the average per capita income of people throughout the world econ- omy grow at all during the next century or two? We cannot be sure that it will in view of the fact that oil and gas production will begin to decline within the next years because of resource depletion and the availability of fossil energy has been the source of most economic growth during the past century. If per capita income fell by % a year, the impact that the losses caused by global warming would have on people’s lives in future would be greater, not less. Accordingly, we suggest that the value calculated by the ExternE study using the % discount rate (a rate which makes any damage taking place years in the future totally negligible) and which assumes a high climate sensitivity to the release of the gas be accepted as the minimum subsidy being taken. This puts the damage at € per tonne of carbon released in prices, which converts to € per tonne of CO released.
Nonetheless largely similar results hold in a much broader sample of countries. In Table 9, I present estimates of the mean and median maximum emission intensities (relative to the corresponding UK intensity) as well as the mean and median rate of decline of emission intensities after a peak is reached for a variety of data samples. In the entire sample, emissions tend to peak much higher than the UK’s intensity - on average 1.56 times that of the UK and the rate of decline tends to be much higher than that of the UK as well - 2.39%. Notice, however, the large difference between the medians and the means. This is indicative that outliers are driving the results. Two obvious groups of countries spring to mind as potential culprits - OPEC countries and current or former communist regimes. Both groups of countries are notorious for subsidizing carbon energy and heavy industry, which - as I argue in the paper - drives up emission intensities. Also, after the collapse of communism, many of these heavy industries were shut as subsidies were revoked which would con- tribute to rapidly declining intensity. Excluding OPEC and Communist countries from the sample brings down the mean to 0.83 - the same as in the OECD and the growth rate to -1.64% - faster than the OECD but not statistically different from that of the UK. Notice that since excluding OPEC countries does not significantly affect the rate of decline of intensity but does impact the average level at which countries peaked, this implies that emission intensities peaked at high levels in both OPEC and communist countries, but that intensities in OPEC countries have remained high, whereas those in communist countries have tended to fall rapidly. This is consistent with the rapid decline of intensity after the collapse of communism in former-eastern bloc countries.
financial costs of subsidies calculated as the sum of direct costs (from the previous section) and indirect financial costs of subsidies, which are simply the difference between GDP measures in a world with and without subsidies. Notice that indirect costs are massive and follow a similar pattern to direct costs. In 1980, they amounted to $122 billion, which was approximately 42 per cent of direct costs at the time. Their value falls to $12 billion by 1998 when they constitute only 9.2 per cent of direct costs. However, as subsidies exploded in the 2000s, so did the indirect costs of these subsidies. By 2010, the global indirect financial costs of subsidies reached $838 billion or 85 per cent of global direct subsidies. Thus, in 2010, the combined direct and indirect financial costs were a stunning $1.82 trillion. Figure Figure 14(b), plots these total financial costs as a fraction of global GDP. The total financial costs of subsidies oscillate between 0.4 per cent of global GDP in 1998, to an astounding 3.8 per cent in 2010. Second, Figures 14(c) and 14(d), decompose the indirect costs by country. Once more, we observe that China, the former Soviet Union and the US account for the vast majority of indirect subsidies. Interestingly, China bears a disproportionately greater share of the indirect costs than the direct costs. The reason is that China’s subsidy rates are higher than those of the US. Consequently, the extent of the misallocation in China is greater than in other countries.
We then shared out the reduction in energy expenditures across relevant fuels in proportion to residential or commercial expenditures on these energy sources. Using average prices, we then calculated by how much the subsidy reduced the quantity demanded of relevant fuels at the prevailing market prices. 29 (Details of these estimates can be found in Appendix C.) For each fuel in the sector, we then added the quantity at the prevailing market quantity and price and generated a new demand curve for the fuel. We then used the altered demand curve in the simulation model to determine what the energy- market prices and quantities would have been in the absence of the energy-efficiency subsidy. For a subsidy affecting multiple fuels, we made changes to several demand curves before using the model to determine what the energy-market prices and quantities would have been without the subsidy.