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Globalization is accompanied by increasing current account imbalances. They can undermine the positive impacts of increasing international cooperation and trade on economic growth and income convergence. At the same time, climate change challenges the global community and requests for co-operative action. Regional energy transformation due to climate policies and the resulting regional mitigation costs are key variables of climate economic analysis. This study is the first that include current account imbalances and imperfect capital markets to investigate potential market feedback mechanisms between climate policies, energy sector transformation and capital markets. Furthermore, it answers the question whether the capital-intensive transformation towards zero-carbon economies increases the policy cost of mitigation under the condition of imperfect capital markets. First results demonstrate a dominant baseline effect of capital market imperfections on macroeconomic variables, and moderate effects on mitigation costs in global climate policy scenarios. For some regions (e.g. Middle East) estimates of relatively high mitigation costs are revised downwards, if imperfect capital markets are considered.

The decarbonization of India’s economy will affect economic actors differently. Here we study the distributional effects of climate policy in India, taking the specific role of structural economic change into account. We contrast distributional effects from climate policy with distributional effects from structural change and quantify how far carbon pricing supports structural change and economic development. We develop and apply a comprehensive model framework that combines long-term growth and medium-term trade dynamics related to structural change with detailed household income and expenditure data for India. Our results emphasize that distributional effects from structural change are stronger than from carbon pricing. Consequently, governments should not focus solely on the distributional effects of climate policy, but also consider the larger context of economic transformation processes when designing and implementing social policies.

This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.

We analyze the burden sharing of climate stabilization under socio-economic scenario uncertainty and for various burden-sharing regimes. For this purpose, we quantify mitigation efforts in terms of emission reductions and mitigation costs for a number of major world regions, considering scenarios with and without climate finance. The influence of socio-economic drivers on the burden sharing is crucial, but it has not yet been studied in the context of the most recent scenario framework—the shared socio-economic pathway scenarios (SSPs). Here, we show that sustainable development as represented by the SSP1 scenario reduces the challenges of burden sharing and makes it easier to achieve equitable climate policies. In contrast, in a scenario with fossil-fueled development (SSP5), the risk of political infeasibility—measured by the variation of mitigation costs across regions and the amount of implied international transfers—increases with most burden-sharing regimes.

Integrated assessment models (IAMs) have emerged as key tools for building and assessing long term climate mitigation scenarios. Due to their central role in the recent IPCC assessments, and international climate policy analyses more generally, and the high uncertainties related to future projections, IAMs have been critically assessed by scholars from different fields receiving various critiques ranging from adequacy of their methods to how their results are used and communicated. Although IAMs are conceptually diverse and evolved in very different directions, they tend to be criticised under the umbrella of ‘IAMs’. Here we first briefly summarise the IAM landscape and how models differ from each other. We then proceed to discuss six prominent critiques emerging from the recent literature, reflect and respond to them in the light of IAM diversity and ongoing work and suggest ways forward. The six critiques relate to (a) representation of heterogeneous actors in the models, (b) modelling of technology diffusion and dynamics, (c) representation of capital markets, (d) energy-economy feedbacks, (e) policy scenarios, and (f) interpretation and use of model results.

Ambitious climate policies, as well as economic development, education, technological progress and less resource-intensive lifestyles, are crucial elements for progress towards the UN Sustainable Development Goals (SDGs). However, using an integrated modelling framework covering 56 indicators or proxies across all 17 SDGs, we show that they are insufficient to reach the targets. An additional sustainable development package, including international climate finance, progressive redistribution of carbon pricing revenues, sufficient and healthy nutrition and improved access to modern energy, enables a more comprehensive sustainable development pathway. We quantify climate and SDG outcomes, showing that these interventions substantially boost progress towards many aspects of the UN Agenda 2030 and simultaneously facilitate reaching ambitious climate targets. Nonetheless, several important gaps remain; for example, with respect to the eradication of extreme poverty (180 million people remaining in 2030). These gaps can be closed by 2050 for many SDGs while also respecting the 1.5 °C target and several other planetary boundaries. Current action is insufficient to meet both the Paris Agreement and the Sustainable Development Goals. Integrated model-based analysis shows that strong interventions across many dimensions, together with ambitious lifestyle change, are needed to enable real progress towards the UN Agenda 2030.

International audience; For dynamic computable general equilibrium (CGE) modeling, long-term baseline construction is key and depends on the applied methods and the sources of projections considered. For dynamic CGE models, baseline assumptions and base data are both important determinants of results. This paper reviews the assumptions made by 24 modeling teams on baseline macroeconomic drivers, understood as factor accumulation and gross domestic product (GDP) growth. We critically review the various methods, identifying state-of-the-art practices and propose simple guidelines, particularly focusing on consistency between data sources and models, which is intended to help dynamic CGE modelers build their own baselines.

Ambitious climate policy increases the cost of energy and therefore has important interactions with the prospects of development in the countries of Sub-Saharan Africa. These interactions include the potential for gain for the continent in the form of new trade opportunities and climate finance. In this paper we quantify the costs and benefits of climate policy in Sub-Saharan Africa. Using an Integrated Assessment Model, we consider key characteristics of the continent, including the favorable conditions for renewable energy. A newly designed scenario analysis allows identifying the main drivers of the results. We show that Sub-Saharan Africa could implement climate policy in line with the 2 °C target at roughly net zero costs if the international community follows up on its commitment towards supporting developing countries as declared in the Paris Agreement. Sub-Saharan Africa could become an important supplier of energy from biomass and could thus even benefit from more ambitious climate policy due to higher demand for this source of energy. The absence of a painful trade-off between short-term development and long-term climate stabilization could provide policy-makers with a much richer policy option space than previously considered. One such option is to link climate policy with poverty reduction through, for example, the provision of clean electricity.

Research on low-carbon transformation pathways has focused on carbon pricing as a means for climate stabilization. By contrast, technology policies remain the more prominent national climate policy...

Purpose Bioenergy is a key component of climate change mitigation strategies aiming at low stabilization. Its versatility and capacity to generate negative emissions when combined with carbon capture and storage add degrees of freedom to the timing of emission reductions. This paper aims to explore the robustness of a bioenergy-based mitigation strategy by addressing several dimensions of uncertainty on biomass potential, bioenergy use and induced land use change emissions. Design/methodology/approach Different mitigation scenarios were explored by two different energy-economy optimization models coupled to the same land use model, which provides a common basis for the second generation bioenergy dynamics in the two energy-economy models. Findings Using bioenergy is found to be a robust mitigation strategy as demonstrated by high biomass shares in primary energy demand in both models and in all mitigation scenarios. Practical implications A variety of possible storylines about future uses of biomass exist. The comparison of the technology choices preferred by the applied models helps understand how future emission reductions can be achieved under alternative storylines. Originality/value The presented comparison-based assessment goes beyond other comparison studies because both energy-economy models are coupled to the same land use model.

We present two solution algorithms for a large-scale integrated assessment model of climate change mitigation: the well known Negishi algorithm and a newly developed Nash algorithm. The algorithms are used to calculate the Pareto-optimum and competitive equilibrium, respectively, for the global model that includes trade in a number of goods as an interaction between regions. We demonstrate that in the absence of externalities both algorithms deliver the same solution. The Nash algorithm is computationally much more effective, and scales more favorably with the number of regions. In the presence of externalities between regions the two solutions differ, which we demonstrate by the inclusion of global spillovers from learning-by-doing in the energy sector. The non-cooperative treatment of the spillover externality in the Nash algorithm leads to a delay in the expansion of renewable energy installations compared to the cooperative solution derived using the Negishi algorithm.

We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI-E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. The approach has created long-lasting coupled models available for use in research for the future at a secure and user-friendly web portal.

Despite increasing empirical evidence of strong links between climate and economic growth, there is no established model to describe the dynamics of how different types of climate shocks affect growth patterns. Here we present the first comprehensive, comparative analysis of the long-term dynamics of one-time, temporary climate shocks on production factors, and factor productivity, respectively, in a Ramsey-type growth model. Damages acting directly on production factors allow us to study dynamic effects on factor allocation, savings and economic growth. We find that the persistence of impacts on economic activity is smallest for climate shocks directly impacting output, and successively increases for direct damages on capital, loss of labor and productivity shocks, related to different responses in savings rates and factor-specific growth. Recurring shocks lead to large welfare effects and long-term growth effects, directly linked to the persistence of individual shocks. Endogenous savings and shock anticipation both have adaptive effects but do not eliminate differences between impact channels or significantly lower the dissipation time. Accounting for endogenous growth mechanisms increases the effects. We also find strong effects on income shares, important for distributional implications. This work fosters conceptual understanding of impact dynamics in growth models, opening options for links to empirics.

Globalization is accompanied by increasing current account imbalances. They can undermine the positive impacts of increasing international cooperation and trade on economic growth. By applying an economic growth model that requests for long-term compensation of short-term current account deficits, we derive patterns of international trade. Model output, however, is challenged by empirical data – which is related to the Lucas Paradox. This paper demonstrates how, based on the assumption of differentiated time preferences, model results and empirical data are reconciled with each other. The method presented here yields an indirect estimate of the rates of time preference across regions. Our results suggest that the time preference rate is low in emerging Asian countries, while the USA and Europe are characterized by above world-average rates. Based on the applied model that differentiates between trade in energy resources and a composite good, simulated trade patterns of these three world regions significantly differ from each other and also from trade patterns that occur in resource exporting countries.

This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development.

This study investigates the use of bioenergy for achieving stringent climate stabilization targets and it analyzes the economic drivers behind the choice of bioenergy technologies. We apply the integrated assessment framework REMIND-MAgPIE to show that bioenergy, particularly if combined with carbon capture and storage (CCS) is a crucial mitigation option with high deployment levels and high technology value. If CCS is available, bioenergy is exclusively used with CCS. We find that the ability of bioenergy to provide negative emissions gives rise to a strong nexus between biomass prices and carbon prices. Ambitious climate policy could result in bioenergy prices of 70 $/GJ (or even 430 $/GJ if bioenergy potential is limited to 100 EJ/year), which indicates a strong demand for bioenergy. For low stabilization scenarios with BECCS availability, we find that the carbon value of biomass tends to exceed its pure energy value. Therefore, the driving factor behind investments into bioenergy conversion capacities for electricity and hydrogen production are the revenues generated from negative emissions, rather than from energy production. However, in REMIND modern bioenergy is predominantly used to produce low-carbon fuels, since the transport sector has significantly fewer low-carbon alternatives to biofuels than the power sector. Since negative emissions increase the amount of permissible emissions from fossil fuels, given a climate target, bioenergy acts as a complement to fossils rather than a substitute. This makes the short-term and long-term deployment of fossil fuels dependent on the long-term availability of BECCS.

We introduce endogenous directed technical change into numerical integrated climate and development policy assessment. We distinguish expenditures on innovation (R&D) and imitation (international technology spillovers) and consider the role of capital investment in creating and implementing new technologies. Our main contribution is to calibrate and numerically solve the model and to examine the model’s sensitivity. As an application, we assess a carbon budget-based climate policy and vary the beginning of energy-saving technology transfer. Accordingly, China is a main beneficiary of early technology transfer. Herein, our results highlight the importance of timely international technology transfer for efficiently meeting global emission targets. Most of the consumption gains from endogenous growth are captured in the baseline. Moreover, mitigation costs turn out to be insensitive to changes in most of the parameters of endogenous growth. A higher effectivity of energy-specific relative to labor-specific expenditures on innovation and imitation reduces mitigation costs, though.

In the past, deforestation, mainly driven by the conversion of natural forests to agricultural land, contributed up to one-fifth of global human induced carbon dioxide (CO 2 ) emissions. Substitution of bioenergy for fossil energy is an intensely discussed option for mitigating CO 2 emissions. This paper, by applying a global land-use model and a global energy–economy–climate model, explores how demand for cellulosic bioenergy crops will add an additional pressure on the land system in the future. In accordance with other studies, we find that CO 2 emissions from land use change due to energy crop production will be an important factor in the GHG balance of bioenergy if natural forests will not be protected. But restricting land availability for biomass plantations by conserving natural forests requires additional efforts in the agricultural sector: First, our simulation results indicate that significant additional crop yield increases will be needed due to the combination of forest conservation and the cultivation of dedicated bioenergy crops. Secondly, our simulation results show that forest conservation in combination with increasing demand for dedicated bioenergy crops will lead to higher agricultural production costs of approximately 20%.

Biomass from cellulosic bioenergy crops is seen as a substantial part of future energy systems, especially if climate policy aims at stabilizing CO2 concentration at low levels. However, among other concerns of sustainability, the large-scale use of bioenergy is controversial because it is hypothesized to increase the competition for land and therefore raise N2O emissions from agricultural soils due to intensification. We apply a global land-use model that is suited to assess agricultural non-CO2 GHG emissions. First, we describe how fertilization of cellulosic bioenergy crops and associated N2O emissions are implemented in the land-use model and how future bioenergy demand is derived by an energy-economy-climate model. We then assess regional N2O emissions from the soil due to large-scale bioenergy application, the expansion of cropland and the importance of technological change for dedicated bioenergy crops. Finally, we compare simulated N2O emissions from the agricultural sector with CO2 emissions from the energy sector to investigate the real contribution of bioenergy for low stabilization scenarios. As a result, we find that N2O emissions due to energy crop production are a minor factor. Nevertheless, these co-emissions can be significant for the option of removing CO2 from the atmosphere (by combining bioenergy use with carbon capture and storage (CCS) options) possibly needed at the end of the century for climate mitigation. Furthermore, our assessment shows that bioenergy crops will occupy large shares of available cropland and will require high rates of technological change at additional costs.

The impacts of the availability of low-carbon technologies on the regional distribution of mitigation costs are analyzed in a global multi-regional integrated assessment model. Three effects on regional consumption losses are distinguished: domestic measures, trade of fossil energy carriers and trade of emission permits. Key results are: (i) GDP losses and a redirection of investments in the energy system towards capital-intensive technologies are major contributions to regional consumption losses. (ii) A devaluation of tradable fossil energy endowments contributes largely to the mitigation costs of fossil fuel exporters. (iii) In case of reduced availability of low-carbon technologies, the permit market volume and associated monetary redistributions increase. The results suggest that the availability of a broad portfolio of low-carbon technologies could facilitate negotiations on the permit allocation scheme in a global cap-and-trade system.

Can near-term public support of renewable energy technologies contain the increase of mitigation costs due to delays of implementing emission caps at the global level? To answer this question we design a set of first and second best scenarios to analyze the impact of early deployment of renewable energy technologies on welfare and emission timing to achieve atmospheric carbon stabilization by 2100. We use the global multiregional energy–economy–climate hybrid model REMIND-R as a tool for this analysis. An important design feature of the policy scenarios is the timing of climate policy. Immediate climate policy contains the mitigation costs at less than 1% even if the CO2 concentration target is 410 ppm by 2100. Delayed climate policy increases the costs significantly because the absence of a strong carbon price signal continues the carbon intensive growth path. The additional costs can be decreased by early technology policies supporting renewable energy technologies because emissions grow less, alternative energy technologies are increased in capacity and their costs are reduced through learning by doing. The effects of early technology policy are different in scenarios with immediate carbon pricing. In the case of delayed climate policy, the emission path can be brought closer to the first-best solution, whereas in the case of immediate climate policy additional technology policy would lead to deviations from the optimal emission path. Hence, technology policy in the delayed climate policy case reduces costs, but in the case of immediate climate policy they increase. However, the near-term emission reductions are smaller in the case of delayed climate policies. At the regional level the effects on mitigation costs are heterogeneously distributed. For the USA and Europe early technology policy has a positive welfare effect for immediate and delayed climate policies. In contrast, India looses in both cases. China loses in the case of immediate climate policy, but profits in the delayed case. Early support of renewable energy technologies devalues the stock of emission allowances, and this effect is considerable for delayed climate policies. In combination with the initial allocation rule of contraction and convergence a relatively well-endowed country like India loses and potential importers like the EU gain from early renewable deployment.

In this paper, we present an intertemporal optimization model that is designed to analyze climate policy scenarios within a globalized world which is characterized by the existence of technological spillovers. We consider a type of technological spillovers that is bound to bilateral capital trade. Importing foreign capital that increases the efficiency of energy use represents a mitigation option that extends the commonly modeled portfolio. The technical details of the model are presented in this paper. The model is solved numerically. First model applications highlight the differences between climate policy analyses which either take or do not take technological spillovers into account. In the final part, we apply the model to investigate first-mover advantages and commitment incentives in climate policy scenarios. The existence of both is supported by simulation results.

Within this paper, we present the novel hybrid model REMIND-R and its application in a climate policy context based on the EU target to avoid a warming of the Earth’s atmosphere by more than 2°C compared to the pre-industrial level. This paper aims to identify necessary long-term changes in the energy system and the magnitude of costs to attain such a climate protection target under different designs of the post-2012 climate policy regime. The regional specification of mitigation costs is analyzed in the context of globalization where regions are linked by global markets for emission permits, goods, and several resources. From simulation experiments with REMIND-R, it turns out that quite different strategies of restructuring the energy system are pursued by the regions. Furthermore, it is demonstrated that the variance of mitigation costs is higher across regions than across policy regimes. First-order impacts, in particular, reduced rents from trade in fossil resources, prevail regardless of the design of the policy regime.

Endogenous technology scenarios for meeting low stabilization CO 2 targets are derived in this study and assessed regarding emission reductions and mitigation costs. The aim is to indentify the most important technology options for achieving low stabilization targets. The significance of an option is indicated by its achieved emission reduction and the mitigation cost increase, if this option were not available. Quantitative results are computed using a global multi-regional hard-linked hybrid model that integrates the economy, the energy sector and the climate system. The model endogenously determines the optimal deployment of technologies subject to a constraint on climate change. The alternative options in the energy sector comprise the most important mitigation technologies: renewables, biomass, nuclear, carbon capture and sequestration (CCS), and biomass with CCS as well as energy efficiency improvements. The results indicate that the availability of CCS technologies and espec. biomass with CCS is highly desirable for achieving low stabilization goals at low costs. The option of nuclear energy is different: although it could play an important role in the primary energy mix, mitigation costs would only mildly increase, if it could not be expanded. Therefore, in order to promote prudent climate change mitigation goals, support of CCS technologies reduces the costs and–thus–is desirable from a social point of view.

In this paper we present an algorithm that deals with trade interactions within a multi-region model. In contrast to traditional approaches this algorithm is able to handle spillover externalities. We focus on technological spillovers which are due to capital trade. The algorithm of finding a pareto-optimal solution in an intertemporal framework is embedded in a decomposed optimization process. The paper analyzes convergence and equilibrium properties of this algorithm. In the final part of the paper, we apply the algorithm to investigate possible impacts of technological spillovers. While benefits of technological spillovers are significant for the capital-importing region, benefits for the capital-exporting region depend on the type of regional disparities and the resulting specialization and terms-of-trade effects.

An alternative approach to multi-region modeling will be presented. This approach (called modular approach) is able to reproduce results obtained with the traditional as well as a modified Negishi approach. We redesigned the Negishi approach to make it applicable in modeling technological spillovers induced by foreign direct investments. While the modular approach is able to completely internalize the external effects from technological spillovers, which result in higher welfare gains, the modified Negishi approach cannot completely internalize them. The latter is due to the fact that shadow prices from sectoral production functions are used in order to feed the process of iteratively adjusting the Negishi welfare weights. Under the modular approach, the way of finding an equilibrium solution in a dynamic and multi-regional framework is allocation-based and differs from existing price-oriented methods. We discuss the characteristics of the underlying adjustment algorithm which, in contrast to the joint maximization of the Negishi approach, is embedded in a decentralized optimization process. Results from numerical model experiments will demonstrate the advantage of this novel approach.

This document describes the REMIND model in its version 1.6. REMIND is an integrated assessment model of the energy-economy-climate system. REMIND stands for “Regional Model of Investments and Development.”

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.

Carbon emissions trading is a key instrument of climate policy. It helps to bring about emission reductions in that place where they are least costly. However, fair burden sharing is about more than just cost-efficiency. While focussing on the instrument of emissions trading, this paper touches upon equity issues that frame decisions on emission rights allocation. The analysis is based on the ICLIPS model. The model study gives new insights on how the equal per capita allocation principle influences the intertemporal emission paths and about the distribution of mitigation costs in the long run. Apart from the intuitive economic evaluation of model results, this paper also attempts to provide an evaluation from an equity point of view. For a variety of assumptions, model results show that several developing countries could benefit considerably from joining an international emissions trading system, thereby becoming potential collaborators in post-Kyoto climate agreements.

The Agriculture and Land Use (AgLU) model is a top-downeconomic model with just enough structure to simulate globalland-use change and the resulting carbon emissions over one century.These simulations are done with and without a carbon policy representedby a positive carbon price. Increases in the carbon price createincentives for production of commercial biomass that affect thedistribution of other land types and, therefore, carbon emissionsfrom land-use change. Commercial biomass provides a link betweenthe agricultural and energy systems. The Integrated Assessmentof Climate Protection Strategies (ICLIPS) core model uses AgLUto provide estimates of carbon emissions from land-use changeas one component of total greenhouse gas emissions. Each majorland-use type is assigned an average carbon density used to calculatea total carbon stock; carbon emissions from land-use change arecalculated as the change in carbon stock between time periods.Significant carbon emissions from land-use change are presenteven in the reference scenario. An aggressive ICLIPS mitigationscenario results in carbon emissions from land-use change upto 800 million metric tons per year above the AgLU referencescenario.

In integrated assessments of climate change, greenhouse-gasemissions and climate change impacts provide the linkages betweenthe world economy and the climate system. Key climatic processesoperate at the scales of centuries. This requires highlyaggregated models for portraying the dynamics of the economicsystem. An extended Ramsey-type optimal growth model is presentedas the appropriate tool to be integrated with a reduced-formclimate model in the ICLIPS integrated assessment. Theeleven-region model of the world economy involves exogenouspopulation and endogenous investment dynamics with productivityprogress based on a technological diffusion model. World regionsare linked via intertemporal trade flows of the compositeconsumption/investment good, capital mobility, and emission permittrading. Coupled with the ICLIPS Climate Model, the AggregatedEconomic Model can determine corridors of permitted long-termcarbon emission paths or, as primarily discussed in this paper,specific cost-effective emission trajectories. The sensitivity ofmitigation costs to externally specified climate change/impactconstraints and to assumptions about non-CO2 greenhouse-gasemissions is also discussed.

The tolerable windows approach (TWA) allows the climate policyformulation process to be safeguarded in the following way. First,guardrails are defined in order to exclude intolerable climatechange impacts, on the one hand, and unacceptable socioeconomicconsequences of climate change mitigation measures, on the other.Second, a scientific analysis is conducted to investigate thefeatures of those emission paths that are compatible with theguardrail constraints. The fundamental methodology of the TWA isbest described in terms of the theory of differentialinclusions. This emerging mathematical theory already providesnumerical methods applicable as long as the underlying integratedassessment models are of limited complexity. In order to identifyemissions corridors, we propose a novel calculation schemeapplicable also for large-scale integrated assessment models.

An integrated assessment model (IAM) conceived in the vein ofthe inverse approach is introduced. The model is designed tohelp social actors in making informed judgments about climatechange impact targets, mitigation costs, and implementation mechanisms.Based on these normative decisions, the model verifies whetherthere exist long-term future emission paths that satisfy theuser-defined constraints. If they do, the model determines anemission corridor containing all permissible emission trajectories.An overview of the IAM is provided and short descriptions ofthe model components are presented. Forward and inverse modesof application are explained. Examples based on impacts of climatechange on aggregated potential crop production in Western Europeand South Asia illustrate how the model can be applied in differentmodes. The examples demonstrate how the inverse approach separatessocial judgments shaping climate policy from the model-basedanalysis of their implications. The examples also show the differencein climate change tolerance between developed regions in temperatezones and less developed regions in already warm climate zones.

(2002). Exploring Options for Global Climate Policy. A New Analytical Framework. Environment: Science and Policy for Sustainable Development: Vol. 44, No. 5, pp. 22-34.

This contribution presents an analysis within the framework of the tolerable windows approach (TWA) applied to climate change decision support. The TWA starts with an explicit normative specification of guard-rails, which exclude intolerable climate impacts as well as unacceptable socioeconomic consequences of mitigation measures. In a subsequent step, a scientific analysis of the relevant elements of the Earth System is carried out to obtain all climate protection strategies that are compatible with the predefined constraints. In the first part of the paper we demonstrate a new method of implementing the underlying inverse approach in order to determine the set of all admissible emission paths. This method is based on a control theoretic analysis of the TWA problem. The second part is subject to the application of this method and the discussion of results. Thereafter, we focus on the question of how the shape of emission corridors is influenced by economic constraints.

The Tolerable Windows Approach (TWA) to Integrated Assessments (IA) of global warming is based on external normative specifications of tolerable sets of climate impacts as well as proposed emission quotas and policy instruments for implementation. In a subsequent step, the complete set of admissible climate protection strategies which are compatible with these normative inputs is determined by scientific analysis. In doing so, minimum requirements concerning global and national greenhouse gas emission paths can be determined. In this paper we present the basic methodological elements of TWA, discuss its relation to more conventional approaches to IA like cost–benefit analyses, and present some preliminary results obtained by a reduced-form climate model.

In this contribution, I introduce the construct of climate protection expenditure in order to link strategies of greenhouse gas emission reduction with macroeconomic variables. In contrast to other studies which have been based on a baseline concept, this study proceeds from a base year concept in order to determine emission reductions and their costs. Climate protection expenditure will be calculated as a regionally differentiated, intertemporal trajectory. This results from a macroeconomic extension of a fuzzy optimization model including a new climate protection cost function. Climate change impacts are considered implicitly within a boundary concept. Then, a climate stabilization scenario based on a control function will be demonstrated; its economic implications and some policy-making aspects will be discussed.

This document describes the REMIND model in its version 1.5. REMIND is an integrated assessment model of the energy-economy-climate system. REMIND stands for “Regional Model of Investments and Development.”

An increasing number of models have been developed to support global warming response policies. The model constructors are facing a lot of uncertainties which limit the evidence of these models. The support of climate policy decision-making is only possible in a semi-quantitative way, as presented by aFuzzy model. The model design is based on an optimization approach, integrated in a bounded risk decision-making framework. Given some regional emission-related and impact-related restrictions, optimal emission paths can be calculated. The focus is not only on carbon dioxide but on other greenhouse gases too. In the paper, the components of the model will be described. Cost coefficients, emission boundaries and impact boundaries are represented asFuzzy parameters. TheFuzzy model will be transformed into a computational one by using an approach of Rommelfanger. In the second part, some problems of applying the model to computations will be discussed. This includes discussions on the data situation and the presentation, as well as interpretation of results of sensitivity analyses. The advantage of theFuzzy approach is that the requirements regarding data precision are not so strong. Hence, the effort for data acquisition can be reduced and computations can be started earlier.

We introduce endogenous directed technical change into numerical integrated climate and development policy assessment. We distinguish expenditures on innovation (R&D) and imitation (international technology spillovers) and consider the role of capital investment in creating and implementing new technologies. Our main contribution is to calibrate and numerically solve the model and to examine the model’s sensitivity. As an application, we assess a carbon budget-based climate policy and vary the beginning of energy-saving technology transfer. Accordingly, China is a main beneficiary of early technology transfer. Herein, our results highlight the importance of timely international technology transfer for efficiently meeting global emission targets. Most of the consumption gains from endogenous growth are captured in the baseline. Moreover, mitigation costs turn out to be insensitive to changes in most of the parameters of endogenous growth. A higher effectivity of energy-specific relative to labor-specific expenditures on innovation and imitation reduces mitigation costs, though.

International audience; This paper synthesizes the results from the model intercomparison exercise among regionalized global energy-economy models conducted in the context of the RECIPE project. The economic adjustment effects of long-term climate policy are investigated based on the cross-comparison of the intertemporal optimization models ReMIND-R and WITCH as well as the recursive dynamic computable general equilibrium model IMACLIM-R. A number of robust findings emerge. If the international community takes immediate action to mitigate climate change, the costs of stabilizing atmospheric CO 2 concentrations at 450 ppm (roughly 530-550 ppm-e) discounted at 3% are estimated to be 1. 4% or lower of global consumption over the twenty-first century. Second best settings with either a delay in climate policy or restrictions to the deployment of low-carbon technologies can result in substantial increases of mitigation costs. A delay of global climate policy until 2030 would render the 450 ppm target unachievable. Renewables and CCS are found to be the most critical mitigation technologies, and all models project a rapid switch of investments away from freely emitting energy conversion technologies towards renewables, CCS and nuclear. Concerning end use sectors, the models consistently show an almost full scale decarbonization of the electricity sector by the middle of the twenty-first century, while the decarbonization of non-electric energy demand, in particular in the transport sector remains incomplete in all mitigation scenarios. The results suggest that assumptions about low-carbon alternatives for non-electric energy demand are of key importance for the costs and achievability of very low stabilization scenarios. 2011 Springer Science+Business Media B.V.

International audience; This paper analyzes the regional distribution of climate change mitigation costs in a global cap-and-trade regime. Four stylized burden-sharing rules are considered, ranging from GDP-based permit allocations to schemes that foresee a long-term convergence of per-capita emission permits. The comparison of results from three structurally different hybrid, integrated energy-economy models allows us to derive robust insights as well as identify sources of uncertainty with respect to the regional distribution of the costs of climate change mitigation. We find that regional costs of climate change mitigation may deviate substantially from the global mean. For all models, the mitigation cost average of the four scenarios is higher for China than for the other macro-regions considered. Furthermore, China suffers above-world-average mitigation costs for most burden-sharing rules in the long-term. A decomposition of mitigation costs into (a) primary (domestic) abatement costs and (b) permit trade effects, reveals that the large uncertainty about the future development of carbon prices results in substantial uncertainties about the financial transfers associated with carbon trade for a given allocation scheme. This variation also implies large uncertainty about the regional distribution of climate policy costs. © 2012 Springer Science+Business Media B.V.

The incomplete knowledge about ecological phenomena requires to complement the use of quantitative models by the application of qualitative models and methods. In this context, there are some deficits within the applied ecological research. In this paper, the integrated application of quantitative and qualitative models will be demonstrated within the framework of an advisory system which is used to determine the risk of groundwater contamination by nitrate. The advisory system aims at politicians and decision makers. The structure of the advisory system and the interactions of its components will be described. The main focus is on the concrete realization of the coupling between expert system and dynamic models (forest and agricultural soil model). The pursued approach of coupling is distinguished by the isolated development of an expert system and models, and by the simulation-based knowledge acquisition.