AIMS

This Project will support and develop a cohort of PhD students who will contribute to specific objectives of the research programme and also represent an expansion of future research capacity at the interface of energy and environmental research.

TOPICS

Further details of these studentships are given below and their research contributions are discussed under the relevant Projects.

Investigating the impact of the electrification of transport to reduce carbon emissions on Natural Capital

Researcher:  Appointed, Started: October 2016, Supervisor: Dr Astley Hastings, University of Aberdeen

The four low carbon energy pathways proposed in the fourth CCC report are Ambitious Nuclear, Ambitious renewables, Ambitious CCS and Higher Energy Efficiency. This represents 2 levels of the electrification of transport in the four scenarios.

One of the technologies proposed to reduce carbon emissions from energy consumption is the electrification of transportation.  The widespread adoption of transport electrification will impact natural capital from the additional power generation required, the infrastructure to electrify rail networks, the charging infrastructure for road vehicles, the manufacture and use of new road and rail vehicles and the disposal and recycling of the older more carbon intensive equipment. This PhD project aims to quantify the value of the impacts of the transport electrification levels proposed by the fourth CCC report on Natural Capital.

The Optimal Spatial Design of Policies with Environmental Impacts

Researcher:  Gemma Dellafield, Started: October 2016, Supervisors: Professor Brett Day of University of Exeter; Professor Ian Bateman of University of Exeter; Dr Paolo Agnolucci of University College London

This project will study the optimal spatial design of policies. While the quantitative methods developed in the studentship will be applicable across a broad range of contexts, the particular area of application will concern where to place multiple new energy generation facilities and the transmission infrastructure to connect them to markets. That particular location decision requires trade-offs along multiple dimensions including engineering feasibility, construction costs, market access and, of principal interest, damages to natural capital and the ecosystems services it provides.

Solving such spatial policy problems (often termed facilities location problems) is complex. The decision involves choosing where to place each of a set of different components across a broad range of possible locations. Moreover, the location-specific costs and benefits of those multiple siting decisions may not be independent. For example, placing two generation facilities close to each other may reduce costs by allowing shared use of transmission infrastructure. Alternatively, the cumulative impacts on the environment resulting from placing two generation facilities in close proximity may exceed the sum of either located in isolation. To add to the complexity, the costs and benefits of environmental impacts are not known with certainty. Indeed it is often the case that credible values span a significant range. Ultimately, what we are faced with is a complex combinatorial choice problem to be made under conditions of uncertainty. Quite a challenge!

This research will build on work begun as part of the National Ecosystem Assessment Follow On Project (Bateman, Day et al., 2014) in which methods of Mixed Integer Linear Programming were employed to design optimal spatial policies for the siting of new mixed woodlands in the UK (Day and De Gol, in preparation). Moreover, the work will break new academic ground by exploring methods of robust spatial optimization, methods that specifically acknowledge uncertainties in the costs and benefits of the environmental impacts of energy infrastructure siting decisions. The robust optimization routines will search for a spatial configuration of the energy system that, while seeking to optimize net benefits, protects against excessive losses if the costs of ecosystem service damages turn out to be at the extremes of expected ranges.

The importance of visual impact on public acceptance of renewable and non-conventional energy sources

Researcher:  Pip Roddis, Started: October 2016, Supervisors: Dr Steve Carver, Dr Martin Dallimer and Dr Guy Ziv, University of Leeds

This project focuses on the question of visual impact from renewable (e.g. wind, solar, hydro, tidal, bioenergy) and non-conventional (e.g. shale gas) energy sources and how this is likely to affect public acceptability across a range of landscape types, spatial scales, stakeholders and socio-demographic groups. Public acceptability may also be influenced by environmental impacts/risks, governance and planning procedures, noise/traffic issues etc. The research will build on the experience of the NERC funded "Energy-scapes" project which considered optimal mixes of energy supply within mixed landscapes where conflicting demands from agriculture, settlement and biodiversity exists across spatial scales from local to national. The research will integrate 2D modelling of land availability (e.g. GIS-based multi-criteria site suitability analyses), 3D visual impact analyses (e.g. based on photographic landscape perception studies and high-ended viewshed analyses), monetary and non-monetary assessments of preference and value, and participatory GIS (e.g. using "Map-Me", a 2D fuzzy online community mapping tool developed at Lancaster and Leeds). It is envisaged that these analyses will be done initially at a local-regional level and scaled up to inform other work packages within the ADVENT Project and ultimately strategic thinking within UK and European land and energy policy.

The global biodiversity implications of a UK transition to a low carbon economy

Researcher:  Seb Dunnett, Started: October 2016, Supervisors: Dr Felix Eigenbrod (University of Southampton), Dr Richard Pearson (University College London), Prof Gail Taylor (University of Southampton)

Conserving global biodiversity in the face of climate change is widely recognized to be a major global challenge (e.g. Thomas et al. 2004; Pearson et al. 2014) that is likely to be considerably exacerbated by the potential synergistic and additive effects of other drivers of species declines such as land use change (Jetz et al. 2007; Eigenbrod et al. 2014). Furthermore, analyses of global trade patterns have shown that it is Northern demand for goods and services that is largely driving greenhouse gas emissions and land use change in the developing world (e.g. Weinzettel et al. 2013). While decarbonisation of global energy supplies is likely to reduce the impacts of climate change on biodiversity, the impacts of such shifts in energy production away from fossil fuels may have other negative impacts on biodiversity (Agarwala et al. 2014), with the global-scale impacts of decarbonisation on biodiversity remaining largely unknown.

The aim of this project is examine the potential global biodiversity implications of a UK transition to a low carbon economy. This work will consist of spatially modelling the degree to which current and future UK (and global) energy demand will spatially coincide with areas of known high biodiversity (e.g., biodiversity hotspots, ecoregions) and ranges of species classified as endangered on the IUCN’s Red List. It will also look at potential synergistic impacts of climate change and energy demand on species distributions. This work will build on existing spatial models (e.g. Eigenbrod et al. 2014) as well as coupled global trade hydrological model (in review) developed in Southampton by the lead supervisor Dr Felix Eigenbrod and co-supervisor Prof Gail Taylor, as well as extensive bioclimatic niche modelling expertise of Dr Richard Pearson at UCL (e.g. Pearson et al 2014).

Going Carbon Negative:  Can Bioenergy with Carbon Capture and Storage (BECCS) be part of the solution? Developing a framework to assess the impacts on UK and global natural capital

Researcher:  Casper Donaldson, Started: October 2016, Supervisors: Professor Gail Taylor (University of Southampton), Dr Felix Eigenbrod (University of Southampton), Dr Astley Hastings (University of Southampton)

Several Energy and Climate Change future scenarios identify 'Bioenergy with Carbon Capture and Storage'- (BECCS) as a significant enabler of the move towards a low carbon economy. This reflects the ability of these two technologies in combination, to effectively remove large amounts of CO2 from the atmosphere whilst at the same time, providing heat, power and liquid biofuels, leading to the concept of 'carbon negative energy' (IPCC, 2013). National UK assessments such as CCC (CCC, 2011) and the Energy White paper (DECC, 2011) and indeed, within the global IPCC assessment (IPCC, 2013), identify BECCS as having a central role in decarbonisation strategies. Although this is an attractive option, there remain significant technical barriers to deployment and to date, no consideration has been made of the impacts of wide-scale deployment on natural capital and ecosystem services. At the same time, the UK Natural Capital Committee (NEA, 2014) is recommending that Government endorses a long-term plan to maintain and improve natural capital and that natural capital should be incorporated into generational planning of UK infrastructure. Carbon stocks (soils), wildlife (biodiversity) and water resources have been identified as natural capital that is significantly threatened at present and that without careful consideration in future, may lead to the loss of considerable benefits that flow from this natural capital, including food, energy and climate regulation. These components of natural capital are particularly relevant to BECCS. It has also been recognised that these assets have a significant spatial dimension in the UK (Bateman et al., 2013) and elsewhere and this spatiality must be considered in any future policy developments, including consumption-based metrics that reflect the full impact of our global footprint, here in the delivery of a low carbon economy for the UK.

The aim of this project is to bring together thinking from the energy and natural capital evaluation approaches, using  the considerable number of tools emerging from NEA and elsewhere (including ADVENT and UKERC Pathways Theme) and to develop a framework to understand the likely implications of BECCS for the UK and more widely. In particular, the National Ecosystem Assessment scenarios and valuation approaches (Bateman et al. 2013), Land Use Change model (TIM) and early outputs from WP1 in ADVENT and UKERC energy pathways will be used, alongside a case study approach with specific BECCS options targeted, to develop a framework for future considerations of impacts of BECCS on natural capital and ecosystem services. Taking value from our on-going work on global I/O modelling with respect to water and being extended in UKERC 3 for a range of ecosystem services, we will use these to address the central question of feasibility of CCS for the UK and how trade-offs for natural capital and ecosystem services may operate at the spatial scale. We will focus on land-based natural capital and ecosystem services but will also consider the impacts of pipelines off-shore, using expertise within the ADVENT consortium.

Econometric modelling of natural resources and economic growth

Researcher:  Theodoros Arvanitopoulos, Started: October 2016, Supervisors: Dr Paolo Agnolucci, Senior Lecturer in Environmental and Resource Economics, University College London; Professor Brett Day of University of Exeter.

This project is centred on understanding the relationship between the use of natural resources and economic variables such as economic growth, employment and trade in the UK.  The aim is to assess historical evidence about the use of a number of natural resources on the one hand, e.g. water consumption, consumption of materials and demand for land, and economic growth. Analysis could be implemented at the sectoral level, e.g. assessing the production function of a number of industrial sectors, at the local level, e.g. implementing the analysis for England, Wales and Scotland separately or for the UK as a whole. The work will involve a number of econometric techniques including those relating to the analysis of time series and panel data. Issues include reverse causality, (e.g. does economic growth cause demand for water or does water consumption causes economic growth?), structural breaks, time-varying coefficients, changes in the policies affecting consumption of natural resources and in the structure of the economy across time. Analysis will support the development of a Computable General Equilibrium (CGE) model of the UK economy and the project will provide a complementary, historical and data-based perspective on the CGE model developed for the ADVENT project. In addition, the project will explore how small-scale econometric models, e.g. VARs with limited number of variables, could be linked with CGE models.

Mixed-method evaluations in the Environment-Energy Nexus

Researcher:  Alexandros Sfyridis, Started: October 2016, Supervisors: Dr Paolo Agnolucci, Senior Lecturer in Environmental and Resource Economics, University College London, Prof Paul Ekins, Professor of Energy and Environment Policy, Dr Nicola Beaumont, Plymouth Marine Laboratory

This project is centred on the evaluation of interventions at the Environment-Energy Nexus with a specific focus on the natural capital implications of policies aiming at delivering low carbon energy in the UK. It will focus on integrating different evaluation methodologies to develop and implement a mixed-method approach which takes into account aspects including:  behaviour of complex systems, environmental valuation, energy-environment relationships, chancy evaluations, realism of the policy and of the causal mechanism, long and complex causal chain, nested systems, time-delays, uncertainty and resistance to change. Example of methodologies which could be adopted are: Structural Equation Modelling, Process Tracing, Bayesian Networks, Qualitative Comparative Analysis, System Dynamic Models, Contribution Analysis, and Programme Evaluation Econometrics e.g. RDD, DiD, propensity score matching.

Siting energy infrastructure to optimise natural capital

Researcher:     To be appointed                    Host Institution: University of East Anglia

OUTPUTS

This Project will contribute to meeting ADVENT’s science goals as well as wider issues of developing research practice and achieving societal impact.