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A high degree of consensus exists in the climate sciences over the role that human interference with the atmosphere is playing in changing the climate. Following the Paris Agreement, a similar consensus exists in the policy community over the urgency of policy solutions to the climate problem. The context for climate policy is thus moving from agenda setting, which has now been mostly established, to impact assessment, in which we identify policy pathways to implement the Paris Agreement. Most integrated assessment models currently used to address the economic and technical feasibility of avoiding climate change are based on engineering perspectives with a normative systems optimisation philosophy, suitable for agenda setting, but unsuitable to assess the socio-economic impacts of a realistic baskets of climate policies. Here, we introduce a fully descriptive, simulation-based integrated assessment model designed specifically to assess policies, formed by the combination of (1) a highly disaggregated macro-econometric simulation of the global economy based on time series regressions (E3ME), (2) a family of bottom-up evolutionary simulations of technology diffusion based on cross-sectional discrete choice models (FTT), and (3) a carbon cycle and atmosphere circulation model of intermediate complexity (GENIE-1). We use this combined model to create a detailed global and sectoral policy map and scenario that sets the economy on a pathway that achieves the goals of the Paris Agreement with >66% probability of not exceeding 2$^\circ$C of global warming. We propose a blueprint for a new role for integrated assessment models in this upcoming policy assessment context., Comment: 23 pages + Supplementary Information 26 pages

Transport generates a large and growing component of global greenhouse gas emissions contributing to climate change. Effective transport emissions reduction policies are needed in order to reach a climate target well below 2$^\circ$C. Representations of technology evolution in current Integrated Assessment Models (IAM) make use of systems optimisations that may not always provide sufficient insight on consumer response to realistic policy packages for extensive use in policy-making. Here, we introduce FTT:Transport, an evolutionary technology diffusion simulation model for road transport technology, as an IAM sub-component, which features sufficiently realistic features of consumers and of existing technological trajectories that enables to simulate the impact of detailed climate policies in private passenger road transport. Integrated to the simulation-based macroeconometric IAM E3ME-FTT, a plausible scenario of transport decarbonisation is given, defined by a detailed transport policy package, that reaches sufficient emissions reductions to achieve the 2$^\circ$C target of the Paris Agreement., Comment: 15 pages, 3 figures, Supplementary Information 67 pages

Studies report that firms do not invest in cost-effective green technologies. While economic barriers can explain parts of the gap, behavioural aspects cause further under-valuation. This could be partly due to systematic deviations of decision-making agents' perceptions from normative benchmarks, and partly due to their diversity. This paper combines available behavioural knowledge into a simple model of technology adoption. Firms are modelled as heterogeneous agents with different behavioural responses. To quantify the gap, the model simulates their investment decisions from different theoretical perspectives. While relevant parameters are uncertain at the micro-level, using distributed agent perspectives provides a realistic representation of the macro adoption rate. The model is calibrated using audit data for proposed investments in energy efficient electric motors. The inclusion of behavioural factors reduces significantly expected adoption rates: from 81% using a normative optimisation perspective, down to 20% using a behavioural perspective. The effectiveness of various policies is tested., Comment: 21 pages, 6 figures, 7 tables, to appear in Environmental Innovation and Societal Transitions

This paper outlines a critical gap in the assessment methodology used to estimate the macroeconomic costs and benefits of climate policy. It shows that the vast majority of models used for assessing climate policy use assumptions about the financial system that sit at odds with the observed reality. In particular, the models' assumptions lead to `crowding out' of capital, which cause them to show negative impacts from climate policy in virtually all cases. We compare this approach with that of the E3ME model, which follows non-equilibrium economic theory and adopts a more empirical approach. While the non-equilibrium model also has limitations, its treatment of the financial system is more consistent with reality and it shows that green investment need not crowd out investment in other parts of the economy -- and may therefore offer an economic stimulus. The implication of this finding is that standard CGE models consistently over-estimate the costs of climate policy in terms of GDP and welfare, potentially by a substantial amount. These findings overly restrict the range of possible emission pathways accessible using climate policy from the viewpoint of the decision-maker, and may also lead to misleading information used for policy making. Improvements in both modelling approaches should be sought with some urgency -- both to provide a better assessment of potential climate policy and to improve understanding of the dynamics of the global financial system more generally., Comment: 6000 words, 12 pages

This article proposes a fundamental methodological shift in the modelling of policy interventions for sustainability transitions in order to account for complexity (e.g. self-reinforcing mechanism arising from multi-agent interactions) and agent heterogeneity (e.g. differences in consumer and investment behaviour). We first characterise the uncertainty faced by climate policy-makers and its implications for investment decision-makers. We then identify five shortcomings in the equilibrium and optimisation-based approaches most frequently used to inform sustainability policy: (i) their normative, optimisation-based nature, (ii) their unrealistic reliance on the full-rationality of agents, (iii) their inability to account for mutual influences among agents and capture related self-reinforcing (positive feedback) processes, (iv) their inability to represent multiple solutions and path-dependency, and (v) their inability to properly account for agent heterogeneity. The aim of this article is to introduce an alternative modelling approach based on complexity dynamics and agent heterogeneity, and explore its use in four key areas of sustainability policy, namely (1) technology adoption and diffusion, (2) macroeconomic impacts of low-carbon policies, (3) interactions between the socio-economic system and the natural environment, and (4) the anticipation of policy outcomes. The practical relevance of the proposed methodology is discussed by reference to four applications: the diffusion of transport technology, the impact of low-carbon investment on income and employment, the management of cascading uncertainties, and the cross-sectoral impact of biofuels policies. The article calls for a fundamental methodological shift aligning the modelling of the socio-economic system with that of the climatic system, for a combined and realistic understanding of the impact of sustainability policies., Comment: 20 pages, 5 figures, to appear in Global Environmental Change

The effectiveness of fiscal policy to influence vehicle purchases for emissions reductions in private passenger road transport depends on its ability to incentivise consumers to make choices oriented towards lower emissions vehicles. However, car purchase choices are known to be strongly socially determined, and this sector is highly diverse due to significant socio-economic differences between consumer groups. Here, we present a comprehensive dataset and analysis of the structure of the 2012 private passenger vehicle fleet-years in six major economies across the World (UK, USA, China, India, Japan and Brazil) in terms of price, engine size and emissions distributions. We argue that choices and aggregate elasticities of substitution can be predicted using this data, enabling to evaluate the effectiveness of potential fiscal and technological change policies on fleet-year emissions reductions. We provide tools to do so based on the distributive structure of prices and emissions in segments of a diverse market, both for conventional as well as unconventional engine technologies. We find that markets differ significantly between nations, and that correlations between engine sizes, emissions and prices exist strongly in some markets and not strongly in others. We furthermore find that markets for unconventional engine technologies have patchy coverages of varying levels. These findings are interpreted in terms of policy strategy., Comment: 12 pages, 5 figures, 2 tables + 8 pages Supplementary Information included, to appear in this final form in Environmental Research Letters

Conventional economic analysis of stringent climate change mitigation policy generally concludes various levels of economic slowdown as a result of substantial spending on low carbon technology. Equilibrium economics however could not explain or predict the current economic crisis, which is of financial nature. Meanwhile the economic impacts of climate policy find their source through investments for the diffusion of environmental innovations, in parts a financial problem. Here, we expose how results of economic analysis of climate change mitigation policy depend entirely on assumptions and theory concerning the finance of the diffusion of innovations, and that in many cases, results are simply re-iterations of model assumptions. We show that, while equilibrium economics always predict economic slowdown, methods using non-equilibrium approaches suggest the opposite could occur. We show that the solution to understanding the economic impacts of reducing greenhouse gas emissions lies with research on the dynamics of the financial sector interacting with innovation and technology developments, economic history providing powerful insights through important analogies with previous historical waves of innovation., Comment: 13 pages and 5 figures

This paper presents an analysis of climate policy instruments for the decarbonisation of the global electricity sector in a non-equilibrium economic and technology diffusion perspective. Energy markets are driven by innovation, path-dependent technology choices and diffusion. However, conventional optimisation models lack detail on these aspects and have limited ability to address the effectiveness of policy interventions because they do not represent decision-making. As a result, known effects of technology lock-ins are liable to be underestimated. In contrast, our approach places investor decision-making at the core of the analysis and investigates how it drives the diffusion of low-carbon technology in a highly disaggregated, hybrid, global macroeconometric model, FTT:Power-E3MG. Ten scenarios to 2050 of the electricity sector in 21 regions exploring combinations of electricity policy instruments are analysed, including their climate impacts. We show that in a diffusion and path-dependent perspective, the impact of combinations of policies does not correspond to the sum of impacts of individual instruments: synergies exist between policy tools. We argue that the carbon price required to break the current fossil technology lock-in can be much lower when combined with other policies, and that a 90% decarbonisation of the electricity sector by 2050 is affordable without early scrapping., Comment: 18 pages, 6 figures, 3 appendices

At the heart of technology transitions lie complex processes of social and industrial dynamics. The quantitative study of sustainability transitions requires modelling work, which necessitates a theory of technology substitution. Many, if not most, contemporary modelling approaches for future technology pathways overlook most aspects of transitions theory, for instance dimensions of heterogenous investor choices, dynamic rates of diffusion and the profile of transitions. A significant body of literature however exists that demonstrates how transitions follow S-shaped diffusion curves or Lotka-Volterra systems of equations. This framework is used ex-post since timescales can only be reliably obtained in cases where the transitions have already occurred, precluding its use for studying cases of interest where nascent innovations in protective niches await favourable conditions for their diffusion. In principle, scaling parameters of transitions can, however, be derived from knowledge of industrial dynamics, technology turnover rates and technology characteristics. In this context, this paper presents a theory framework for evaluating the parameterisation of S-shaped diffusion curves for use in simulation models of technology transitions without the involvement of historical data fitting, making use of standard demography theory applied to technology at the unit level. The classic Lotka-Volterra competition system emerges from first principles from demography theory, its timescales explained in terms of technology lifetimes and industrial dynamics. The theory is placed in the context of the multi-level perspective on technology transitions, where innovation and the diffusion of new socio-technical regimes take a prominent place, as well as discrete choice theory, the primary theoretical framework for introducing agent diversity., Comment: 24 pages, 5 figures, 2014

We report angle-resolved photoelectron spectroscopy measurements of the quantum critical metal Sr3Ru2O7 revealing itinerant Ru 4d-states confined over large parts of the Brillouin zone to an energy range of < 6 meV, nearly three orders of magnitude lower than the bare band width. We show that this energy scale agrees quantitatively with a characteristic thermodynamic energy scale associated with quantum criticality and illustrate how it arises from the hybridization of light and strongly renormalized, heavy quasiparticle bands. For the largest Fermi surface sheet we find a marked k-dependence of the renormalization and show that it correlates with the Ru 4d - O 2p hybridization.

This work introduces a model of Future Technology Transformations for the power sector (FTT:Power), a representation of global power systems based on market competition, induced technological change (ITC) and natural resource use and depletion. It is the first component of a family of sectoral bottom-up models of technology, designed for integration into the global macroeconometric model E3MG. ITC occurs as a result of technological learning produced by cumulative investment and leads to highly nonlinear, irreversible and path dependent technological transitions. The model uses a dynamic coupled set of logistic differential equations. As opposed to traditional bottom-up energy models based on systems optimisation, such differential equations offer an appropriate treatment of the times and structure of change involved in sectoral technology transformations, as well as a much reduced computational load. Resource use and depletion are represented by local cost-supply curves, which give rise to different regional energy landscapes. The model is explored for a single global region using two simple scenarios, a baseline and a mitigation case where the price of carbon is gradually increased. While a constant price of carbon leads to a stagnant system, mitigation produces successive technology transitions leading towards the gradual decarbonisation of the global power sector., Comment: 14 pages, 6 figures, submitted to Energy Policy

This paper presents an assessment of global economic energy potentials for all major natural energy resources. This work is based on both an extensive literature review and calculations using natural resource assessment data. Economic potentials are presented in the form of cost-supply curves, in terms of energy flows for renewable energy sources, or fixed amounts for fossil and nuclear resources, with strong emphasis on uncertainty, using a consistent methodology that allow direct comparisons to be made. In order to interpolate through available resource assessment data and associated uncertainty, a theoretical framework and a computational methodology are given based on statistical properties of different types of resources, justified empirically by the data, and used throughout. This work aims to provide a global database for natural energy resources ready to integrate into models of energy systems, enabling to introduce at the same time uncertainty over natural resource assessments. The supplementary material provides theoretical details and tables of data and parameters that enable this extensive database to be adapted to a variety of energy systems modelling frameworks., Comment: 17 pages, 14 figures, 2 tables, 18 pages supplementary information with 2 additional figures and 10 additional data tables

The upper critical field $H_{c2}$ of purple bronze Li$_{0.9}$Mo$_6$O$_{17}$ is found to exhibit a large anisotropy, in quantitative agreement with that expected from the observed electrical resistivity anisotropy. With the field aligned along the most conducting axis, $H_{c2}$ increases monotonically with decreasing temperature to a value five times larger than the estimated paramagnetic pair-breaking field. Theories for the enhancement of $H_{c2}$ invoking spin-orbit scattering or strong-coupling superconductivity are shown to be inadequate in explaining the observed behavior, suggesting that the pairing state in Li$_{0.9}$Mo$_6$O$_{17}$ is unconventional and possibly spin-triplet., Comment: 9 pages, 4 Main Figures, 5 Supplementary Information Figures; Accepted for publication in Physical Review Letters

Highly correlated electron materials are systems in which many new states of matter can emerge. A particular situation which favours the formation of exotic phases of the electron liquid in complex materials is that where a quantum critical point (QCP) is present the phase diagram. Neighbouring regions in parameter space reveal unusual physical properties, described as non-Fermi liquid behaviour. One of the important problems in quantum criticality is to find out how the Fermi surface (FS) of a material evolves near a QCP. The traditional method for studying the FS of materials is the de Haas van Alphen effect (dHvA). A quantum critical end point (QCEP) has been reported in the highly correlated metal Sr3Ru2O7, which is tuned using a magnetic field high enough to perform the dHvA experiment. It moreover features a new emergent phase in the vicinity of the QCEP, a nematic type of electron ordering. The subject of this thesis is the study of the FS of Sr3Ru2O7 using the dHvA effect. Three aspects were explored. The first was the determination of the FS at fields both above and below that where the QCEP arises. The second was the search for quantum oscillations inside the nematic phase. The third was a reinvestigation of the behaviour of the quasiparticle effective masses near the FS. A complete robust model for the FS of Sr3Ru2O7 at zero fields was determined. Moreover, the new measurements of the quasiparticle masses revealed that no mass enhancements exist anywhere around the QCEP. Finally, we report dHvA oscillations inside the nematic phase, which suggests that the carriers consist of Landau quasiparticles., Comment: PhD Thesis, University of St. Andrews

We report detailed investigation of quantum oscillations in Sr3Ru2O7, observed inductively (the de Haas-van Alphen effect) and thermally (the magnetocaloric effect). Working at fields from 3 T to 18 T allowed us to straddle the metamagnetic transition region and probe the low- and high-field Fermi liquids. The observed frequencies are strongly field-dependent in the vicinity of the metamagnetic transition, and there is evidence for magnetic breakdown. We also present the results of a comprehensive rotation study. The most surprising result concerns the field dependence of the measured quasiparticle masses. Contrary to conclusions previously drawn by some of us as a result of a study performed with a much poorer signal to noise ratio, none of the five Fermi surface branches for which we have good field-dependent data gives evidence for a strong field dependence of the mass. The implications of these experimental findings are discussed., Comment: 12 pages, 12 figures, submitted to PRB

We report measurements of quantum oscillations detected in the putative nematic phase of Sr3Ru2O7. Significant improvements in sample purity enabled the resolution of small amplitude dHvA oscillations between two first order metamagnetic transitions delimiting the phase. Two distinct frequencies were observed, and their amplitudes follow the normal Lifshitz-Kosevich profile. The Fermi surface sheets seem to correspond to a subset of those detected outside the phase. Variations of the dHvA frequencies are explained in terms of a chemical potential shift produced by reaching a peak in the density of states, and an anomalous field dependence of the oscillatory amplitude provides information on domains., Comment: 4 pages, 4 figures

Although Sr3Ru2O7 has not been reported to exhibit superconductivity so far, ac susceptibility measurements revealed multiple superconducting transitions occurring in the Sr3Ru2O7 region cut from Sr3Ru2O7-Sr2RuO4 eutectic crystals. Based on various experimental results, some of us proposed the scenario in which Sr2RuO4 thin slabs with a few layers of the RuO2 plane are embedded in the Sr3Ru2O7 region as stacking faults and multiple superconducting transitions arise from the distribution of the slab thickness. To examine this scenario, we measured the resistivity along the ab plane (rho_ab) using a Sr3Ru2O7-region sample cut from the eutectic crystal, as well as along the c axis (rho_c) using the same crystal. As a result, we detected resistance drops associated with superconductivity only in rho_ab, but not in rho_c. These results support the Sr2RuO4 thin-slab scenario. In addition, we measured the resistivity of a single crystal of pure Sr3Ru2O7 with very high quality and found that pure Sr3Ru2O7 does not exhibit superconductivity down to 15 mK., Comment: 4 pages, 2 figures, Int. Conf. on Low Temperature Physics (LT25)

The low-energy electronic structure of the itinerant metamagnet Sr3Ru2O7 is investigated by angle resolved photoemission and density functional calculations. We find well-defined quasiparticle bands with resolution limited line widths and Fermi velocities up to an order of magnitude lower than in single layer Sr2RuO4. The complete topography, the cyclotron masses and the orbital character of the Fermi surface are determined, in agreement with bulk sensitive de Haas - van Alphen measurements. An analysis of the dxy band dispersion reveals a complex density of states including van Hove singularities (vHs) near the Fermi level; a situation which is favorable for magnetic instabilities., Comment: 5 pages, 3 figures, to appear in Phys. Rev. Lett