Kingston University Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
Catalysis Hub Featured PhD Programmes
University of Kent Featured PhD Programmes
University of Southampton Featured PhD Programmes

Adaptive decision making for climate change mitigation

This project is no longer listed on and may not be available.

Click here to search for PhD studentship opportunities
  • Full or part time
    Prof P Taylor
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

The complexity of climate change mitigation makes it hard to imagine how changes in the short-term will lead to the necessary system reconfiguration in the long-term. This challenge is exacerbated by the fact that the speed of technological change is moderated by society, politics and the economy; the desirable technology-led scenarios we are adept at describing won’t happen without associated social, political and economic change. If action in the short-term is ineffective in the face of these moderating factors it may be necessary to shift to more a more radical approach to intervention in order to accelerate system change and avoid dangerous climate change.

Tools or approaches are needed to support and inform decisions in the face of real uncertainty about the nature of a reconfigured system, how parts of the system might change or about how effective interventions might be. There are tools and approaches which aim to achieve a balance between the understanding of uncertainty and system complexity and the articulation of policy pathways that are both adaptive and dynamic (Haasnoot et al., 2013). To date such approaches have been predominantly used in water resource management and adaptation to a changing climate. A good example of this is the adaptive planning approach used for Thames Estuary 2100 project (Reeder and Ranger, 2010), which provides an adaptive routemap of options for a long-lived infrastructure decision with high sunk-costs under high uncertainty.

This project will explore the application of adaptive and dynamic decision making approaches to climate change mitigation. It will focus on two specific case studies:

- Achieving flexibility and co-ordination in energy system change. Most, if not all, scenarios for a low carbon UK energy system envisage a significant role for variable renewable electricity generation technologies, such as wind and solar. However, these technologies pose challenges to the energy system in terms of balancing supply and demand over periods from seconds through to days. At the moment, this balancing is largely achieved by using flexible fossil fuel plant, but a number of non-fossil fuel alternatives are showing promise including new forms of energy storage and greater uptake of demand side response (DSR). However, the pace and direction of the co-evolution of these alternatives with a rapidly changing energy system is highly uncertain (Taylor et al., 2014). Decision making relating to the roll-out of energy storage and DSR needs to become more flexible if it is to be responsive both to developments in the technologies themselves and to wider energy system trends. Without this flexibility there is significant risk of locking-out these options in favour of a new generation of flexible fossil-fuel plant and thereby limiting the climate change mitigating potential of the energy system in the longer-term. This case study will work alongside the EPSRC-funded Consortium for Modelling and Analysis of Decentralised Energy Storage, part of the SUPERGEN Energy Storage Hub.

- Adaptive business model innovation in the energy system. Business models used in the energy system, particularly those relating to energy supply, severely limit the potential of demand reduction, which is essential in energy system decarbonisation (Hall and Roelich, 2015). The current lock-in to supply-driven models is caused by both business decision processes and an unsupportive policy environment. It is almost impossible to change business models without systemic change in regulation, however it is equally difficult to determine what this systemic change is and how it will be implemented in a system so strongly locked-in to current approached. This case study will work alongside the Local Government Information Unit (LGIU) and the Centre for Industrial Energy, Materials and Products (CIE-MAP). It will explore how businesses can transition towards demand-reduction-led business models and how policy and regulation would need to adapt in parallel to enable this.

The project would be based in the School of Earth and Environment but have close links with both the School of Process and Chemical Engineering (where Peter Taylor holds a split post) and the School of Civil Engineering (where Katy Roelich holds a split UAF).

Entry requirements/necessary background for students:
Applicants must have a minimum of a UK upper second class honours degree (2.1), or equivalent in a relevant engineering, economics or social science discipline.


Haasnoot, M. et al. (2013) Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world. Global Environmental Change, 23, 485-498.

Hall, S. and Roelich, K. (2015) Local Electricity Supply: Opportunities, archetypes and outcomes. Report for the Department for Energy and Climate Change’s Local Supply Working Group.

Reeder, T and Ranger, N. (2010) How do you adapt in an uncertain world? Lessons from the Thames Estuary 2100 project. World Resources Report Uncertainty Series

Taylor, P. et al. (2013) Analysing pathways for energy storage in the UK using a coevolutionary framework, Energy Policy, 63, 230-243.

How good is research at University of Leeds in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 79.20

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

FindAPhD. Copyright 2005-2019
All rights reserved.