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This paper explores optimal near-term technology R&D in the face of uncertain damages caused by the buildup of greenhouse gases. The paper puts particular emphasis on understanding how optimal near-term R&D expenditures might vary based on the technologies pursued in the R&D program. The exploration is conducted in the context of varying impacts from R&D on the global abatement cost function. The R&D planning problem is considered first within a theoretical framework and is then pursued in a stylized application using the DICE model. The paper provides intuition into the circumstances under which near-term technology R&D might increase or decrease under uncertainty, thereby serving as a hedge against climate uncertainty. [ABSTRACT FROM AUTHOR]

Greenhouse gases emission inventories are computed with rather low precision. Moreover, their uncertainty distributions may be asymmetric. This should be accounted for in the compliance and trading rules. In this paper we model the uncertainty of inventories as intervals or using fuzzy numbers. The latter allows us to better shape the uncertainty distributions. The compliance and emission trading rules obtained generalize the results for the symmetric uncertainty distributions that were considered in the earlier papers by the present authors (Nahorski et al., Water Air & Soil Pollution. Focus 7(4-5):539-558, ; Nahorski and Horabik, , J Energy Eng 134(2):47-52, ). However, unlike in the symmetric distribution, in the asymmetric fuzzy case it is necessary to apply approximations because of nonlinearities in the formulas. The final conclusion is that the interval uncertainty rules can be applied, but with a much higher substitutional noncompliance risk, which is a parameter of the rules. [ABSTRACT FROM AUTHOR]

The assessment of greenhouse gases emitted to and removed from the atmosphere is high on the international political and scientific agendas. Growing international concern and cooperation regarding the climate change problem have increased the need for policy-oriented solutions to the issue of uncertainty in, and related to, inventories of greenhouse gas (GHG) emissions. The approaches to addressing uncertainty discussed in this Special Issue reflect attempts to improve national inventories, not only for their own sake but also from a wider, systems analytical perspective-a perspective that seeks to strengthen the usefulness of national inventories under a compliance and/or global monitoring and reporting framework. These approaches demonstrate the benefits of including inventory uncertainty in policy analyses. The authors of the contributed papers show that considering uncertainty helps avoid situations that can, for example, create a false sense of certainty or lead to invalid views of subsystems. This may eventually prevent related errors from showing up in analyses. However, considering uncertainty does not come for free. Proper treatment of uncertainty is costly and demanding because it forces us to make the step from 'simple to complex' and only then to discuss potential simplifications. Finally, comprehensive treatment of uncertainty does not offer policymakers quick and easy solutions. The authors of the papers in this Special Issue do, however, agree that uncertainty analysis must be a key component of national GHG inventory analysis. Uncertainty analysis helps to provide a greater understanding and better science helps us to reduce and deal with uncertainty. By recognizing the importance of identifying and quantifying uncertainties, great strides can be made in ongoing discussions regarding GHG inventories and accounting for climate change. The 17 papers in this Special Issue deal with many aspects of analyzing and dealing with uncertainty in emissions estimates. [ABSTRACT FROM AUTHOR]

Despite the growing concern about actual on-going climate change, there is little consensus on the scale and timing of actions needed to stabilise the concentrations of greenhouse gases. Many countries are unwilling to implement mitigation strategies, at least in the short term, and no agreement on an ambitious global stabilisation target has yet been reached. It is thus likely that international climate policies will be characterized by a high degree of uncertainty over the stringency of the climate objective, and that some countries might delay their participation to global action. What additional economic costs will this delay in the adoption of mitigation measures imply? What would the optimal short-term strategy be given the uncertainty surrounding the climate policy to come? Is there a hedging strategy that decision makers can adopt to cope with delayed action and uncertain targets? This paper addresses these questions by quantifying the economic implications of delaying mitigation action, and by computing the optimal abatement strategy in the presence of uncertainty about a global stabilisation target (which will be agreed upon in future climate negotiations). Results point to short-term inaction as the key determinant for the economic costs of ambitious climate policies. They also indicate that there is an effective hedging strategy that could minimise the cost of climate policy uncertainty over the global stabilisation target: a short-term moderate climate policy would be a good strategy to reduce the costs of delayed action and to cope with uncertainty about the outcome of future climate negotiations. By contrast, failing to curb emissions in the short term imposes rapidly increasing additional costs of compliance. [ABSTRACT FROM AUTHOR]

Many European politicians argue that the EU should set tougher emission targets than what is required by the Kyoto protocol, and moreover, that emission trading with other countries outside EU should be limited so as to keep emission quota prices high. One of the arguments, frequently cited for such a policy, is the need for technological development. However, the literature on climate change and technological innovation does not unambiguously support the need for setting high emission taxes today. In this paper we investigate the relationship between emission taxes and technological change further by modeling innovation activity explicitly. In our model both the amount of R&D and the amount of carbon abatement are decided in a decentralized way by the market as a response to an emission tax. Moreover, we introduce several distinct failures in the market for new innovations, among others, insufficient patent protection and intertemporal knowledge spill-overs. Our findings suggest that governments should under some circumstances set a higher carbon tax today if we have technological change driven by R&D than if we have pure exogenous technological change. Based on numerical simulations these circumstances are (a) positive intertemporal knowledge spillovers and/or (b) weak patent protection. [ABSTRACT FROM AUTHOR]

A 2030 climate and energy policy framework was endorsed by the European Council in 2014. The main elements are a binding 40 % greenhouse gas (GHG) reduction target compared to 1990, a renewable energy share of 27 %, and an energy savings target of at least 27 % by 2030. In this paper, we assess the impact of these targets on the European land use, land use change, and forestry (LULUCF) sector using a Europe focused global land use model linked with a detailed forest management model. We show that implementing a 40 % GHG emission reduction target by 2030 may only have a small negative impact on the domestic LULUCF sink if the additional biomass demand for energy is mostly met through ligno-cellulosic energy crops rather than forest removals. However, if the increased biomass demand were met through higher rates of forest harvest removals, a more negative impact on the LULUCF sink could be expected. [ABSTRACT FROM AUTHOR]

Climate policies must consider radiative forcing from Kyoto greenhouse gases, as well as other forcing constituents, such as aerosols and tropospheric ozone that result from air pollutants. Non-Kyoto forcing constituents contribute negative, as well as positive forcing, and overall increases in total forcing result in increases in global average temperature. Non-Kyoto forcing modeling is a relatively new component of climate management scenarios. This paper describes and assesses current non-Kyoto radiative forcing modeling within five integrated assessment models. The study finds negative forcing from aerosols masking (offsetting) approximately 25 % of positive forcing in the near-term in reference non-climate policy projections. However, masking is projected to decline rapidly to 5-10 % by 2100 with increasing Kyoto emissions and assumed reductions in air pollution-with the later declining to as much as 50 % and 80 % below today's levels by 2050 and 2100 respectively. Together they imply declining importance of non-Kyoto forcing over time. There are however significant uncertainties and large differences across models in projected non-Kyoto emissions and forcing. A look into the modeling reveals differences in base conditions, relationships between Kyoto and non-Kyoto emissions, pollution control assumptions, and other fundamental modeling. In addition, under climate policy scenarios, we find air pollution and resulting non-Kyoto forcing reduced to levels below those produced by air pollution policies alone-e.g., China sulfur emissions fall an additional 45-85 % by 2050. None of the models actively manage non-Kyoto forcing for climate implications. Nonetheless, non-Kyoto forcing may be influencing mitigation results, including allowable carbon dioxide emissions, and further evaluation is merited. [ABSTRACT FROM AUTHOR]

In this paper we consider the buying/selling prices of carbon dioxide (CO) emission permits in trading models with uncertainty. Permission prices, although usually omitted from standard models, may significantly influence the trading market. We thus undertook to construct a more realistic trade model and to compare it with the standard one. To do this, we introduced several important changes to the standard model, namely, (1) a new optimized quality function; and (2) transactions with price negotiations between regions. We also enhanced the model using methods described in the literature to allow it to deal with reported emissions uncertainty. Additionally, we used an original method of simulating this kind of market based on a specialized evolutionary algorithm (EA). [ABSTRACT FROM AUTHOR]

pproximately half of human-induced carbon dioxide (CO) emissions are taken up by the land and ocean, and the rest stays in the atmosphere, increasing the global concentration and acting as a major greenhouse-gas (GHG) climate-forcing element. Although GHG mitigation is now in the political arena, the exact spatial distribution of the land sink is not well known. In this paper, an estimation of mean European net ecosystem exchange (NEE) carbon fluxes for the period 1998-2001 is performed with three mesoscale and two global transport models, based on the integration of atmospheric CO measurements into the same Bayesian synthesis inverse approach. A special focus is given to sub-continental regions of Europe making use of newly available CO concentration measurements in this region. Inverse flux estimates from the five transport models are compared with independent flux estimates from four ecosystem models. All inversions detect a strong annual carbon sink in the southwestern part of Europe and a source in the northeastern part. Such a dipole, although robust with respect to the network of stations used, remains uncertain and still to be confirmed with independent estimates. Comparison of the seasonal variations of the inversion-based net land biosphere fluxes (NEP) with the NEP predicted by the ecosystem models indicates a shift of the maximum uptake period, from June in the ecosystem models to July in the inversions. This study thus improves on the understanding of the carbon cycle at sub-continental scales over Europe, demonstrating that the methodology for understanding regional carbon cycle is advancing, which increases its relevance in terms of issues related to regional mitigation policies. [ABSTRACT FROM AUTHOR]

Researchers have been analyzing the costs of carbon sequestration for approximately twelve years. The purpose of this paper is to critically review the carbon sequestration cost studies of the past dozen years that have evaluated the cost-effectiveness of the forestry option. Several conclusions emerge. While carbon sequestration cost studies all contain essentially the same components they are not comparable on their face due to the inconsistent use of terms, geographic scope, assumptions, program definitions, and methods. For example, there are at least three distinct definitions for a `ton of carbon'' that in turn lead to significantly different meanings for the metric `dollars per ton of carbon''. This difference in carbon accounting further complicates comparison of studies. After adjusting for the variation among the studies, it appears that carbon sequestration may play a substantial role in a global greenhouse gas emissions abatement program. In the cost range of 10 to 150 dollars per ton of carbon it may be possible to sequester 250 to 500 million tons per year in the United States, and globally upwards of 2,000 million tons per year, for several decades. However, there are two unresolved issues that may seriously affect the contribution of carbon sequestration to a greenhouse gas mitigation program, and they will likely have counteracting effects. First, the secondary benefits of agricultural land conversion to forests may be as great as the costs. If that is the case, then the unit costs essentially disappear, making carbon sequestration a no-regrets strategy. In the other direction, if leakage is a serious issue at both the national and international levels, as suggested by some studies, then it may occur that governments will expend billions of dollars in subsidies or other forms of incentives, with little or no net gain in carbon, forests or secondary benefits. Preliminary results suggest that market interactions in carbon sequestration program analyses require considerably more attention. This is especially true for interactions between the forest and agricultural land markets and between the wood product sink and the timber markets. [ABSTRACT FROM AUTHOR]

This paper presents an approach to estimating world-regional carbon mitigation cost functions for the years 2020, 2050, and 2100. The approach explicitly includes uncertainty surrounding such carbon reduction costs. It is based on the analysis of global energy-economy-environment scenarios described for the 21st century. We use one baseline scenario and variants thereof to estimate cumulative costs of carbon mitigation as a function of cumulative carbon emission reductions. For our baseline for estimating carbon mitigation cost curves, we use the so-called IIASA F scenario. The F scenario is a high-growth, high-emissions scenario designed specifically to be used as a reference against which to evaluate alternatives. Carbon emissions and energy systems costs in the F scenario are then compared with (reduced) emissions and (higher) costs (including macroeconomic adjustment costs) of alternative scenarios taken from the IIASA scenario database. As a kind of sensitivity analysis of our approach, we also present the results of a scenario involving assumptions on particularly rapid technological progress. [ABSTRACT FROM AUTHOR]

It is often claimed that mitigation of greenhouse gases and adaptation to climate change are complementary strategies. If this means that it will usually be optimal to use both mitigation and adaptation to deal with climate change; and that a perceived increase in the damages caused by climate change should require an increase in both mitigation and adaptation, then simple economic analysis would support such an interpretation. However, complementarity has a more technical meaning in economics, which implies if the costs of mitigation fell, then the optimal response would be to increase the level of both mitigation and adaptation. We develop a range of economic models to explore the relationship between mitigation and adaptation; and show that in general adaptation and mitigation will be substitutes. We also find that it is possible for complementarity to occur in the special case where adaptation costs depend on the amount of mitigation. [ABSTRACT FROM AUTHOR]

We develop a method for finding optimal greenhouse gas reduction rates under ongoing uncertainty and re-evaluation of climate parameters over future decades. Uncertainty about climate change includes both overall climate sensitivity and the risk of extreme tipping point events. We incorporate both types of uncertainty into a stochastic model of climate and the economy that has the objective of reducing global greenhouse gas emissions at lowest overall cost over time. Solving this problem is computationally challenging; we introduce a two-step-ahead approximate dynamic programming algorithm to solve the finite time horizon stochastic problem. The uncertainty in climate sensitivity may narrow in the future as the behavior of the climate continues to be observed and as climate science progresses. To incorporate this future knowledge, we use a Bayesian framework to update the two correlated uncertainties over time. The method is illustrated with the DICE integrated assessment model, adding in current estimates of climate sensitivity uncertainty and tipping point risk with an endogenous updating of climate sensitivity based on the occurrence of tipping point events; the method could also be applied to other integrated assessment models with different characterizations of uncertainties and risks. [ABSTRACT FROM AUTHOR]

We provide a review description of atmospheric inversion methods for the determination of fluxes of long-lived trace gases based on measurements of atmospheric concentration. Emphasis is given to technical aspects of inversion settings, which are crucial to inter-compare and understand inversion results. We briefly sketch the formalism used in such methods, then provide a summary of major currents in research and contemporary problems. Most attention is given to carbon dioxide (CO) which poses the threat of future climate change. Therefore, there is keen interest in better understanding where and when CO emitted by the combustion of fossil fuels is reabsorbed by land ecosystems and oceans. Using the information contained in concentration fields observed from ground-based networks and from upcoming satellite observations in order to constrain the geographic distribution of surface fluxes is an inverse problem; it consists of finding a set of fluxes that optimally matches the observations available. We review the application of inverse methods to quantify the distribution of the sources and sinks of CO at the surface of the Earth based on global measurements of atmospheric concentration and three-dimensional models of atmospheric transport. We describe the use of top-down atmospheric inversion methods in terms of numerical transport modeling and atmospheric observation networks, and detail some of the currently important issues in assigning uncertainties. [ABSTRACT FROM AUTHOR]

Substantially postponing the emission reductions, compared to the ranges indicated in IPCC’s recent assessment for 2020 as required for meeting the longterm 2°C target, increases the risk of exceeding this target. The costs of a delay strategy are lower in the short term, but leads to higher costs in the longer term. The analysis shows if the emission reductions are postponed to 2030 it is not likely that higher emissions from the earlier years can be fully compensated in future decades in a so-called ‘delayed action scenario’. A full compensation would require emission reduction rates in the coming decades that are much higher than those found in the scenario literature. Without compensation, the risk of exceeding the global temperature rise target of 2°C will increase. This confirms that it is not only the reduction commitments for 2050 that determine the risk of exceeding the 2°C target, but also the path between now and 2050. To meet this 2°C target, more ambitious 2020 reduction targets are needed for the developed and developing countries than those that have been pledged so far. [ABSTRACT FROM AUTHOR]

We analyze the interaction of climate and development policy that has taken place since the early 1990s. Increasing dissatisfaction about the results of traditional development cooperation and the appeal of climate policy as a new policy field led to a rapid reorientation of aid flows. At the turn of the century, over 7% of aid flows were spent on greenhouse gas emissions mitigation. However, the contribution of emissions mitigation projects to the central development objective of poverty reduction as specified in the Millennium Development Goals is limited and other project types are likely to be much more effective. Adaptation to climate change can be expected to have higher synergies with poverty alleviation than mitigation, primarily through its impact on health, the conservation of arable land and the protection against natural disasters. An analysis of the Clean Development Mechanism shows that projects addressing the poor directly are very rare; even small renewable energy projects in rural areas tend to benefit rich farmers and the urban population. Use of development aid for CDM projects and / or their preparation via capacity building is thus clearly not warranted. We further analyze whether the use of development aid for climate policy could be justified as a countermeasure against the emission increase related to successful development itself. However, countries that are achieving an improvement of human development from a low level are unlikely to increase their energy consumption substantially. Only at a level where the middle class expands rapidly, energy consumption and greenhouse gas emissions soar. Thus targeting middle class energy consumption by appliance efficiency standards and public transport-friendly urban planning are the most effective measures to address developing country emissions. Rural renewable energy provision in poor countries has a much higher impact on poverty, but a much lower impact on greenhouse gas emissions. We conclude that while there are valid reasons for long-term collaboration with emerging economies on greenhouse gas mitigation, there should be a separate budget line for such activities to avoid "obfuscation" of a decline of resources aimed at poverty alleviation. Nevertheless, mitigation will remain attractive for donors because it ensures quick disbursements and relatively simple measures of success. Moreover, mitigation activities in developing countries provide politicians in industrialized countries with a welcome strategy to divert the attention of their constituencies from the lack of success in reducing greenhouse gas emissions domestically. [ABSTRACT FROM AUTHOR]

We estimate the domestic environmental and health benefits of exploiting China's energy-related CDM potential. Exploiting the CDM potential may save between 3,000 and 40,000 lives annually. Additional gains are estimated to reach upwards from 1 billion RMB annually. The key to these gains is the fact that actions and measures to reduce CO2 emissions also reduce emissions of TSP and SO2. In our estimate, exploiting the CDM-potential will cut SO2-emissions by between one-half and three million tons annually. To arrive at these conclusions we synthesize a significant body of recent research on co-benefits of climate abatement in China. [ABSTRACT FROM AUTHOR]

Provides information on the Tolerable Windows Approach (TWA), an approach to analyzing global change mitigation policy. Functions of TWA; Casting the TWA in the larger context of assessment methods; Role of economics and discounting in exercising the TWA.