The unintended consequences of decarbonising the built environment: A UK case study

The case for taking action to tackle climate change is now persuasive. It is developed countries that must reduce GHG emissions most and this paper focuses on one such country – the UK. We address issues associated with the decarbonisation of the built environment and the housing stock in particular. We demonstrate the potential for significant unintended consequences and discuss the complexity involved in attempting to understand such processes. We argue the urgent need for the formation of multi- and inter-disciplinary teams with the diverse range of skill sets required to think together and to address these issues. Such teams must involve (at least) Building Physicists, Engineers, Economists, Epidemiologists, Statisticians, Behavioural Scientists, Complexity Scientists and Policy Makers. Without a coordinated and concerted programme of relevant research it is difficult to imagine how the necessary policy will be formulated and implemented effectively without the potential for enormous and irreversible mistakes

The "can you trust it?" problem of simulation science in the design of socio-technical systems

We need a science of complex systems that can underpin attempts to design, plan, engineer and manage systems for "desirable" outcomes. A great problem is that conventional scientific approcaches cannot be applied to many of the pressing problems faced by politicians, planners and social administrators. Even when there is agreement on the goals, there may be disagreement on how to achieve them

Facets of trust in simulation studies

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordThe purpose of a modelling and simulation (M&S) study for real-world operations management applications is to support decision-making and inform potential action, therefore investigating the aspects of the modelling process which influence trust is important. Previous work has considered the question of trust through the lens of model validation. However, whilst a simulation model may be technically well executed, stakeholders’ trust in the results may also depend upon intangible factors such as interpersonal relationships. Existing literature has also focused on the credibility of the simulation practitioner, however the credibility attribute belongs to the stakeholder, and it ignores the trust aspects that may exist between the stakeholders and the model itself. In this paper, we argue that different facets of trust emerge throughout the stages of a simulation study, and both influence, and are influenced by, the interaction between the model, the modeller and the stakeholders of the study. We present a synthesis of existing literature and extend it by proposing a formative model of trust which presents a conceptualisation of this tripartite relationship. Our contribution is the identification of the different facets of trust in the lifecycle of a modelling and simulation study. We argue that these interacting facets converge via the three-way relationship between modeller, model and stakeholders toward epistemic trust in the knowledge generated by the simulation study and ultimately model acceptability and implementation. To the best of our knowledge, ours is the first study that focuses solely on the question of trust in an M&S study.Economic and Social Research Council (ESRC

A complex systems perspective on innovation, investment and regulation of evolving telecommunications networks

This thesis is a Doctoral Thesis of the International Executive Doctorate Programme (DBA) at the School of Management, Cranfield University, UK. The purpose of the study is to present the results of the research dedicated to the topic of Infrastructure Sharing, a common method to make use of the limited infrastructure resources of many stakeholders. The research aims to develop a decision support tool for a National Regulating Authority (NRA) on the basis of a software simulation representing infrastructure in use as complex systems consisting of agent and infrastructure networks. By applying a computational Agent-Based Modelling (ABM) approach to policy decisions, i.e. influence of Duct and Pole Access (DPA) to incumbent telecommunication infrastructures, the research investigates regulatory considerations that stimulate the development of alternative networks. The final deliverable of the research is a simulation tool that provides a solid foundation for simulating experiments, which allows analysis of demand for broadband services by different subgroups of users. The results of the study are of value for regulators, practitioners, representatives of telecommunication and other network industries, and scholars who deal with the topic of sustainable infrastructure development and recognise the value of a complex system perspective

Changes in exposure to PM2.5 in English dwellings: an unintended consequence of energy efficient refurbishment of the housing stock

UK legislation will result in energy efficiency gains through increased insulation, and airtightness in UK housing in the coming decades. This limited-focus policy approach has led to an array of possible unintended consequences, including likely changes in Indoor Air Quality (IAQ) and exposure profiles for airborne pollutants such as PM2.5. Quantification of any changes in indoor concentrations of PM2.5 is needed due to known impacts on population health. This thesis seeks to address whether the introduction of energy efficiency and ventilation strategies will lead to negative unintended consequences by increasing PM2.5 concentrations in English dwellings, or provide health co-benefits by reducing indoor PM2.5; what factors influence such concentrations and whether their contribution can be quantified? Its geographical focus is the English housing stock commencing with London, comparing London with another location (Milton Keynes) and finally extending to the whole English stock. It considers possible differences in exposure as experienced by different income groups and tenures. It investigates the range of interacting factors that contribute to indoor PM2.5 exposures including for example; external meteorological conditions/pollutant concentrations; location; building characteristics; ventilation type; indoor sources; occupant income and behaviour. Such complexity requires a modelling approach. Building archetypes representative of English dwellings and validated ventilation and indoor pollutant simulation techniques are used to model both current and future changes in indoor PM2.5 exposures. Highlights of the research findings include (1) The application of purpose provided ventilation and removal of indoor generated PM2.5 at source are critical to the overall reduction of indoor exposure in most cases; (2) Increasing envelope airtightness alone reduces ventilation heat loss, assisting CO2 reduction targets whilst also reducing ingress of external PM2.5, but substantially increases indoor sourced PM2.5 concentrations with possible overall negative health consequences; (3) Building characteristics, location, income level and occupant behaviour influence individual exposure where energy efficiency measures are implemented; (4) Households below the low income threshold are more likely to experience greater indoor PM2.5 concentrations, although further monitoring research is needed to confirm/refute this; (5) The models constructed for this study have a possible wider applicability for other airborne pollutants, locations, and building stocks

Supporting design planning through process model simulation

Modelling and analysis of design processes is non-trivial and predicting the behaviour of such systems is especially challenging. Nonetheless, the effective planning of design projects is critical for many engineering companies. Based on the findings from a thorough literature review and an extensive industrial case study, this thesis identified four themes on which subsequent process analyses focused: modelling and representation; scale and connectivity; rework, and the product-process link. The case study also provided a deeper understanding of the practical challenges of planning in industry. In order to meet these challenges, both the Signposting modelling framework and simulation tool were enhanced to provide increased functionality for process modelling, representation and analysis. Further, novel approaches for process analysis - the use of hypothetical models and confidence profiles that link product and process information - were proposed. A software tool was developed to automatically generate such hypothetical models. Simulation analyses were performed on both hypothetical and real-world models. The results elucidated the effects of structural variations in terms of scale and connectivity on project performance. They also showed how task reordering due to rework can lead to major process delays, even when the time taken to rework failed tasks is extremely short. Further, the simulation analyses demonstrated how confidence profiles could be used to identify rework early in the process and reduce the resulting project schedule impact. The results from the simulation analyses were evaluated against historical data from the case study company and heuristics for design planning were defined. Overall, this research demonstrated how simulation analysis of both real-world and hypothetical models, using the enhanced Signposting tool, can provide useful insights into design process planning.Prof. John Clarkson; Cambridge European Trust; Isaac Newton Fund; Churchill College

Estimating the Adaptation Deficit - An empirical analysis of the constraints on climate change adaptation in agriculture

Agricultural adaptation to climate change is often simulated by changes in land use over time. Land use is commonly optimised in economic models, which rests on the neoclassical economic assumption of rational choice among farmers. A wealth of experimental and empirical evidence demonstrates that rational choice can be a poor approximation of human decision making. Models simulating adaptation by optimising producers’ behaviour are in effect simulating adaptive potential. Much evidence demonstrates that adaptive potential does not necessarily translate into adaptation. This investigation focuses on the ways by which farmers’ real-world adaptive behaviours depart from those assumed by the dominant economic models of agricultural responses to climate change. These departures are characterised as adaptation constraints, and they are assessed through an empirical case study of adaptive behaviours in the Hikurangi catchment, New Zealand. Data are collected using a mixed methodology comprising an extensive survey of rural decision making, to which this study contributes, and a suite of semi-structured interviews. The interviews give an understanding of the origins and processes of adaptation constraints, while the surveys provide information about the extent to which they impact adaptive propensity. These adaptation constraints are then formalised as mathematical rules and written into an existing agent-based model of land use change, which is substantially modified for the purposes of this study. Different combinations of constraints are then tested in order to produce estimates of their economic impacts. The constraints on adaptation are found to significantly reduce profits relative to a specification that assumes rational choice among farmers. This is understood to be the first empirically derived estimate of the extent of the adaptation deficit. The size of the deficit identified in this study implies that current economic models are likely to significantly underestimate the costs of adaptation to climate change, the benefits of climate change mitigation, and the residual loss and damage climate change will cause.This work was supported entirely by a Woolf Fisher Trust PhD scholarship, which is part funded by the Woolf Fisher Trust and part by the Cambridge Commonwealth Trus

Applications of Complexity Theory in an English Metropolitan Police Force

This research addresses the question “Can the methods of complexity theory be used in UK policing as an enabling tool for policy intervention, in providing evidence of possible consequences before policies are implemented?” A literature study shows complexity theory is without consensus on epistemology and application. Methodology is developed for exploring motivational consequences of policies on the workforce, involving building mathematical models using hypernetwork theory as the basis for computer simulation and a promising route to engage with practitioners. It is illustrated by the motivation of Police Community Support Officers (PCSOs) in the Neighbourhood Policing system of Greater Manchester Police. The computational model is based on qualitative data collected using Thematic Coding. This produced ‘behavioural codes’ defined as vertices. Six most prevalent were selected and combined into a hypersimplex: Purpose (feedback) Availability of supervision Threat of harm Relevance to role Orientation to geographic responsibility Lone working The acronym facilitated design of the simulation. It also offers a conceptual model where combinations of vertices connect in given scenarios, supporting dialogue between policy maker and computer modeller and insights into simulated possible policy consequences on staff. This enables the policy maker to explore sufficient conditions for outcomes to be obtained that satisfied the policy objectives but not at the expense of staff motivation. Experiments established two concepts: combinatorial compensation and combinatorial tempering as adaptation of simulated policy conditions. The nature of hypernetworks introduce non-linearity into policy design, as multiple dimensions are being considered to achieve objectives, where combinations are not predictable from individual dimensions. A central tenet of the thesis is complexity science can be applied without computer programming skills, and ‘modelling’ can be done long before writing code. Following this there is an iterative interaction as the policy maker uses the program and requests the programmer for new or changed functionality. The method is proposed as a general framework for Agent-Based Modelling (ABM) of human systems

Exploring the potential of complexity theory in urban regeneration processes.

The research project was conceived out of a desire to explore the potential application of complexity theory in understanding urban regeneration processes. The science is still in its infancy, having been born out of a general milieu of, and paralleled, the dissatisfaction with the classical science approach to the problems of the world. At the heart of the complexity project is, therefore, the defiance of the reductionist paradigm in favour of holism and emphasis on emergent properties in the understanding of complex systems. As a new way of thinking and one that boasts of its ability to cut across disciplinary boundaries, the emerging science has found its maiden expression in many spheres of the social and physical inquiry - offering, in each case, potential solutions to the vexing problems and questions that have survived the test of time. In urban studies, such questions reside within the general thesis of the persistence of the urban problem in the midst of a myriad of theoretical tools and policies designed to secure a better understanding and tackle the problem. The translation of this promising theoretical platform into the study and the pursuit of the research agenda were conducted through the case study of the Hulme inner city area in Manchester. The task basically involved three phases of analysis. The first was a historical narrative that attempted to weigh the evolution of the Hulme regeneration processes between 1960 and 1990 against the characteristic features of complex systems, with the aim of establishing a case for conceptualisation of urban regeneration as a subject of complexity. Using selected analytical tools of social network analysis, the second phase sought to quantify the regeneration networks of Hulme so as to weigh them against the deprivation indices for the area between 1990 and 2000, with the aim of testing for any correlations and their implications in the complexity project. Though equally facilitated by social network analysis, the third level was more concerned about investigating the enabling environment for the evolution of urban regeneration networks than mere quantification of the network parameters. Put together, the three levels of analysis provided a framework that serves as a fundamental analytical framework for urban regeneration processes. It offers a much more robust, emergent based, holistic approach to urban regeneration than that which iscontained in many of the contemporary claims of holism. The study's emphasis on intervention without violation of natural (social) order does not only provide a (potentially) essential tool for analysis but also sheds light on questions of the appropriate institutional thickness that is desirable for innovation. Being an exploratory undertaking, the study does not purport to be an exhaustive account of the issues raised, especially that complexity theory is itself still an emerging phenomenon