Marian Leimbach

Modeling Agriculture and Land Use in an Integrated Assessment Framework

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.

Climate change decision-support and the tolerable windows approach

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.

The value of bioenergy in low stabilization scenarios: an assessment using REMIND-MAgPIE

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

INTEGRATED ASSESSMENT OF LONG-TERM CLIMATE POLICIES: PART 1 - MODEL PRESENTATION

/GJ (or even 430

Methodological aspects of the tolerable windows approach

/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.

Development of a Fuzzy optimization model, supporting global warming decision-making

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.

On the regional distribution of mitigation costs in a global cap-and-trade regime

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.

Equity and carbon emissions trading: a model analysis

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.

Economic Development and Emission Control over the Long Term: The ICLIPS Aggregated Economic Model

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.

Description of the REMIND Model (Version 1.5)

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.