Will McDowall

Circular Economy Policies in China and Europe

The idea of a circular economy (CE) has become prominent in both European and Chinese policy making. Chinese and European perspectives on a CE share a common conceptual basis and exhibit many similar concerns in seeking to enhance resource efficiency. Yet they also differ, and this article explores differences in the focus of CE policy in China and Europe. We present evidence on the differing understandings of the CE concept in Chinese and European policy discourse, drawing on qualitative and quantitative analysis of policy documents, media articles, and academic publications. We show that the Chinese perspective on the CE is broad, incorporating pollution and other issues alongside waste and resource concerns, and it is framed as a response to the environmental challenges created by rapid growth and industrialization. In contrast, Europes conception of the CE has a narrower environmental scope, focusing more narrowly on waste and resources and opportunities for business. We then examine similarities and differences in the focus of policy activity in the two regions and in the indicators used to measure progress. We show differences in the treatment of issues of scale and place and different priorities across value chains (from design to manufacture, consumption, and waste management). We suggest some reasons for the divergent policy articulation of the CE concept and suggest lessons that each region can learn from the other.

Multi-cluster Technology Learning in TIMES: A Transport Sector Case Study with TIAM-UCL

The costs of technologies often fall over time due to a range of processes including learning-by-doing. This is a well-characterized concept in the economics of innovation, in which learning about a particular technology, and hence cost reduction, is related to cumulative investments in that technology. This chapter provides a case study applying technology learning endogenously in a TIMES model. It describes many of the key challenges in modelling technology learning endogenously, both in terms of the interpretation and policy relevance of the results, and in terms of methodological challenges. The chapter then presents a case study, exploring a multi-cluster learning approach where many key technologies (fuel cells, automotive batteries, and electric drivetrains) are shared across a set of transport modes (cars, buses and LGVs) and technologies (hybrid and plug-in hybrid fuel cell vehicles, battery electric vehicles, hybrid and plug-in hybrid petrol and diesel vehicles). The multi-region TIAM-UCL Global energy system model has been used to model the multi-cluster approach. The analysis is used to explore the competitive and/or complementary relationship between hydrogen and electricity as low-carbon transport fuels.

Towards a sustainable hydrogen economy: role of carbon price for achieving GHG emission targets

Abstract This work studies the role of carbon price in the development of a sustainable hydrogen infrastructure that satisfies the concerted greenhouse gas (GHG) emission targets in the United Kingdom (UK) for the next decades. In particular, the optimal design of a hydrogen infrastructure for the transport sector in the UK that leads a transition towards a sustainable hydrogen economy is sought. The problem is solved with an optimisation-based framework consisting of a multi-period spatially-explicit mixed-integer linear programming (MILP) formulation. The future hydrogen demand is predicted according to a logistic diffusion model that reaches the 50% of the market share in 2070. Additionally, UK carbon price policies that penalise carbon emissions are incorporated into the economic objective function to be minimised, which consists of the total cost for constructing and operating the infrastructure. By comparing the CO2 emissions obtained in the optimisation problem with the carbon budgets set by the UK Government to succeed in the 2050 European GHG emission directives, it is possible to determine the pertinence of carbon prices.

The use of computerized models in different policy formulation venues: The MARKAL energy model

At a particular point in time, a policy formulation tool may provide real opportunities for learning or serve to rationalize preexisting decisions (Hertin et al. 2009). This chapter examines the varying uses to which a particular energy system model – MARKAL – has been put in the UK. We define the scope of policy venues to include all policysalient institutions using the model: academicconsulting research groups, government departments and nondepartmental government bodies. We view MARKAL as a boundary object (Star and Griesemer 1989) that has served the differing but intersecting needs of academic, consulting and policy communities over a sustained period of time, helping both to inform and justify major and innovative climate and energy policy commitments. We suggest that the model has functioned to bind mutually supportive epistemic communities across academic and policy worlds, helping to develop and maintain, both materially and cognitively, a networked and influential community with shared assumptions and goals in which economic and technical models are privileged. We reflect on how the model has both been advantaged by changing understandings (images) (Baumgartner and Jones 2002) of the energy policy problem, as climate objectives have increased in salience, while also playing a role in policy path creation, that is by supporting significant new climate policy commitments. In seeking to explain the above, we connect literatures on boundary objects in policy formulation and on the way in which changing images of a policy problem can allow new analytic and policy options to enter political and policy spaces. We observe how MARKAL has played a transformative role in this context, while itself also being transformed, as the modelling process has become more