Ioanna Mouratiadou

Description of the REMIND Model (Version 1.5)

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.”

A Multi-Model Analysis Of Post-2020 Mitigation Efforts Of Five Major Economies

This paper looks into the regional mitigation strategies of five major economies (China, EU, India, Japan, and USA) in the context of the 2°C target, using a multi-model comparison. In order to stay in line with the 2°C target, a tripling or quadrupling of mitigation ambitions is required in all regions by 2050, employing vigorous decarbonization of the energy supply system and achieving negative emissions during the second half of the century. In all regions looked at, decarbonization of energy supply (and in particular power generation) is more important than reducing energy demand. Some differences in abatement strategies across the regions are projected: In India and the USA the emphasis is on prolonging fossil fuel use by coupling conventional technologies with carbon storage, whereas the other main strategy depicts a shift to carbon-neutral technologies with mostly renewables (China, EU) or nuclear power (Japan). Regions with access to large amounts of biomass, such as the USA, China, and the EU, can make a trade-off between energy related emissions and land related emissions, as the use of bioenergy can lead to a net increase in land use emissions. After supply-side changes, the most important abatement strategy focuses on end-use efficiency improvements, leading to considerable emission reductions in both the industry and transport sectors across all regions. Abatement strategies for non-CO2 emissions and land use emissions are found to have a smaller potential. Inherent model, as well as collective, biases have been observed affecting the regional response strategy or the available reduction potential in specific (end-use) sectors.

Using Fuzzy Cognitive Maps to Support the Analysis of Stakeholders’ Views of Water Resource Use and Water Quality Policy

This chapter is based on two separate case studies concerned with water use and water use policy. One is a study concerning public participation in the Water Framework Directive (WFD) of the European Union (EU) (Mouratiadou & Moran, 2007), and focuses on data collected in the Pinios river basin in Greece. The other is based on previously unpublished research by the authors on transboundary river issues in the Maritza river basin shared between Bulgaria, Greece and Turkey. Apart from the obvious similarities of location and their focus on water resources, the two studies are linked by some underlying factors that directly impact on our choice of fuzzy cognitive maps (FCMs) as an analytical method.

Will economic growth and fossil fuel scarcity help or hinder climate stabilization? Overview of the RoSE multi-model study

We investigate the extent to which future energy transformation pathways meeting ambitious climate change mitigation targets depend on assumptions about economic growth and fossil fuel availability. The analysis synthesizes results from the RoSE multi-model study aiming to identify robust and sensitive features of mitigation pathways under these inherently uncertain drivers of energy and emissions developments. Based on an integrated assessment model comparison exercise, we show that economic growth and fossil resource assumptions substantially affect baseline developments, but in no case they lead to the significant greenhouse gas emission reduction that would be needed to achieve long-term climate targets without dedicated climate policy. The influence of economic growth and fossil resource assumptions on climate mitigation pathways is relatively small due to overriding requirements imposed by long-term climate targets. While baseline assumptions can have substantial effects on mitigation costs and carbon prices, we find that the effects of model differences and the stringency of the climate target are larger compared to that of baseline assumptions. We conclude that inherent uncertainties about socio-economic determinants like economic growth and fossil resource availability can be effectively dealt with in the assessment of mitigation pathways.

Setting the System Boundaries of “Energy for Water” for Integrated Modeling

Modeling Page Kyle,*,† Nils Johnson,‡ Evan Davies, David L. Bijl, Ioanna Mouratiadou, Michela Bevione, Laurent Drouet, Shinichiro Fujimori, Yaling Liu,† and Mohamad Hejazi† †Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland 20740, United States ‡International Institute for Applied Systems Analysis, Laxenburg, Austria University of Alberta, Edmonton, Alberta, Canada Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, Netherlands Potsdam Institute for Climate Impact Research, Potsdam, Germany Fondazione Eni Enrico Mattei, Milan, Italy National Institute for Environmental Studies, Tsukuba, Japan

Water demand for electricity in deep decarbonisation scenarios: a multi-model assessment

This study assesses the effects of deep electricity decarbonisation and shifts in the choice of power plant cooling technologies on global electricity water demand, using a suite of five integrated assessment models. We find that electricity sector decarbonisation results in co-benefits for water resources primarily due to the phase-out of water-intensive coal-based thermoelectric power generation, although these co-benefits vary substantially across decarbonisation scenarios. Wind and solar photovoltaic power represent a win-win option for both climate and water resources, but further expansion of nuclear or fossil- and biomass-fuelled power plants with carbon capture and storage may result in increased pressures on the water environment. Further to these results, the paper provides insights on the most crucial factors of uncertainty with regards to future estimates of water demand. These estimates varied substantially across models in scenarios where the effects of decarbonisation on the electricity mix were less clear-cut. Future thermal and water efficiency improvements of power generation technologies and demand-side energy efficiency improvements were also identified to be important factors of uncertainty. We conclude that in order to ensure positive effects of decarbonisation on water resources, climate policy should be combined with technology-specific energy and/or water policies.

Robust strategies of climate change mitigation in interacting energy, economy and land use systems

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.

Using a Bio-Economic Model to Assess the Cost-Effectiveness of Measures Against Nitrogen Pollution

Water resource management is an inherently complex, multi-scale and multi-disciplinary process involving many interdependent components. As each of these components is the focus of several socio-economic and scientific disciplines, an approach that crosses disciplinary boundaries is needed to provide constructive input to policy making. Scientific approaches have been developed that study the complex relationships between the economic and ecological systems and that aim to provide knowledge for sustainable management of water resources. Such approaches are interdisciplinary in nature, where interdisciplinarity refers to the cooperation of many scientific disciplines, in order to analyse the relationship between the economic and natural system (Baumgartner et al. 2008). Bio-economic modelling is one of those.