Urban retrofitting: identifying disruptive and sustaining technologies using performative and foresight techniques

Cities, which are now inhabited by a majority of the world's population, are not only an important source of global environmental and resource depletion problems, but can also act as important centres of technological innovation and social learning in the continuing quest for a low carbon future. Planning and managing large-scale transitions in cities to deal with these pressures require an understanding of urban retrofitting at city scale. In this context performative techniques (such as backcasting and roadmapping) can provide valuable tools for helping cities develop a strategic view of the future. However, it is also important to identify ‘disruptive’ and ‘sustaining’ technologies which may contribute to city-based sustainability transitions. This paper presents research findings from the EPSRC Retrofit 2050 project, and explores the relationship between technology roadmaps and transition theory literature, highlighting the research gaps at urban/city level. The paper develops a research methodology to describe the development of three guiding visions for city-regional retrofit futures, and identifies key sustaining and disruptive technologies at city scale within these visions using foresight (horizon scanning) techniques. The implications of the research for city-based transition studies and related methodologies are discussed.

‘Low carbon’ scenarios, roadmaps, transitions and pathways: an overview and discussion

There are a range of studies based in the low carbon arena which use various ‘futures’- based techniques as ways of exploring uncertainties. These techniques range from ‘scenarios’ and ‘roadmaps’ through to ‘transitions’ and ‘pathways’ as well as ‘vision’-based techniques. The overall aim of the paper is therefore to compare and contrast these techniques to develop a simple working typology with the further objective of identifying the implications of this analysis for RETROFIT 2050. Using recent examples of city-based and energy-based studies throughout, the paper compares and contrasts these techniques and finds that the distinctions between them have often been blurred in the field of low carbon. Visions, for example, have been used in both transition theory and futures/Foresight methods, and scenarios have also been used in transition-based studies as well as futures/Foresight studies. Moreover, Foresight techniques which capture expert knowledge and map existing knowledge to develop a set of scenarios and roadmaps which can inform the development of transitions and pathways can not only help potentially overcome any ‘disconnections’ that may exist between the social and the technical lenses in which such future trajectories are mapped, but also promote a strong ‘co-evolutionary’ content.

Effects of polydispersity on the order-disorder transition of diblock copolymer melts

The effect of polydispersity on an AB diblock copolymer melt is investigated using latticebased Monte Carlo simulations. We consider melts of symmetric composition, where the B blocks are monodisperse and the A blocks are polydisperse with a Schultz-Zimm distribution. In agreement with experiment and self-consistent field theory (SCFT), we find that polydispersity causes a significant increase in domain size. It also induces a transition from flat to curved interfaces, with the polydisperse blocks residing on the inside of the interfacial curvature. Most importantly, the simulations show a relatively small shift in the order-disorder transition (ODT) in agreement with experiment, whereas SCFT incorrectly predicts a sizable shift towards higher temperatures.

Community based ecotourism as a panacea for protected areas: the use of common property theory in its analysis and development

Tourism is the worlds largest employer, accounting for 10% of jobs worldwide (WTO, 1999). There are over 30,000 protected areas around the world, covering about 10% of the land surface(IUCN, 2002). Protected area management is moving towards a more integrated form of management, which recognises the social and economic needs of the worlds finest areas and seeks to provide long term income streams and support social cohesion through active but sustainable use of resources. Ecotourism - 'responsible travel to natural areas that conserves the environment and improves the well- being of local people' (The Ecotourism Society, 1991) - is often cited as a panacea for incorporating the principles of sustainable development in protected area management. However, few examples exist worldwide to substantiate this claim. In reality, ecotourism struggles to provide social and economic empowerment locally and fails to secure proper protection of the local and global environment. Current analysis of ecotourism provides a useful checklist of interconnected principles for more successful initiatives, but no overall framework of analysis or theory. This paper argues that applying common property theory to the application of ecotourism can help to establish more rigorous, multi-layered analysis that identifies the institutional demands of community based ecotourism (CBE). The paper draws on existing literature on ecotourism and several new case studies from developed and developing countries around the world. It focuses on the governance of CBE initiatives, particularly the interaction between local stakeholders and government and the role that third party non-governmental organisations can play in brokering appropriate institutional arrangements. The paper concludes by offering future research directions."

Unraveling the electronic structures of low-valent naphthalene and anthracene iron complexes: x-ray, spectroscopic, and density functional theory studies

Naphthalene and anthracene transition metalates are potent reagents, but their electronic structures have remained poorly explored. A study of four Cp*-substituted iron complexes (Cp* = pentamethylcyclopentadienyl) now gives rare insight into the bonding features of such species. The highly oxygen- and water-sensitive compounds [K(18-crown- 6){Cp*Fe(η4-C10H8)}] (K1), [K(18-crown-6){Cp*Fe(η4-C14H10)}] (K2), [Cp*Fe(η4-C10H8)] (1), and [Cp*Fe(η4-C14H10)] (2) were synthesized and characterized by NMR, UV−vis, and 57Fe Mössbauer spectroscopy. The paramagnetic complexes 1 and 2 were additionally characterized by electron paramagnetic resonance (EPR) spectroscopy and magnetic susceptibility measurements. The molecular structures of complexes K1, K2, and 2 were determined by single-crystal X-ray crystallography. Cyclic voltammetry of 1 and 2 and spectroelectrochemical experiments revealed the redox properties of these complexes, which are reversibly reduced to the monoanions [Cp*Fe(η4-C10H8)]− (1−) and [Cp*Fe(η4-C14H10)]− (2−) and reversibly oxidized to the cations [Cp*Fe(η6-C10H8)]+ (1+) and [Cp*Fe(η6-C14H10)]+ (2+). Reduced orbital charges and spin densities of the naphthalene complexes 1−/0/+ and the anthracene derivatives 2−/0/+ were obtained by density functional theory (DFT) methods. Analysis of these data suggests that the electronic structures of the anions 1− and 2− are best represented by low-spin FeII ions coordinated by anionic Cp* and dianionic naphthalene and anthracene ligands. The electronic structures of the neutral complexes 1 and 2 may be described by a superposition of two resonance configurations which, on the one hand, involve a low-spin FeI ion coordinated by the neutral naphthalene or anthracene ligand L, and, on the other hand, a low-spin FeII ion coordinated to a ligand radical L•−. Our study thus reveals the redox noninnocent character of the naphthalene and anthracene ligands, which effectively stabilize the iron atoms in a low formal, but significantly higher spectroscopic oxidation state.

Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels

Monte Carlo algorithms often aim to draw from a distribution π by simulating a Markov chain with transition kernel P such that π is invariant under P. However, there are many situations for which it is impractical or impossible to draw from the transition kernel P. For instance, this is the case with massive datasets, where is it prohibitively expensive to calculate the likelihood and is also the case for intractable likelihood models arising from, for example, Gibbs random fields, such as those found in spatial statistics and network analysis. A natural approach in these cases is to replace P by an approximation Pˆ. Using theory from the stability of Markov chains we explore a variety of situations where it is possible to quantify how ’close’ the chain given by the transition kernel Pˆ is to the chain given by P . We apply these results to several examples from spatial statistics and network analysis.