Design and management of sustainable built environments

The United Nation Intergovernmental Panel on Climate Change (IPCC) makes it clear that climate change is due to human activities and it recognises buildings as a distinct sector among the seven analysed in its 2007 Fourth Assessment Report. Global concerns have escalated regarding carbon emissions and sustainability in the built environment. The built environment is a human-made setting to accommodate human activities, including building and transport, which covers an interdisciplinary field addressing design, construction, operation and management. Specifically, Sustainable Buildings are expected to achieve high performance throughout the life-cycle of siting, design, construction, operation, maintenance and demolition, in the following areas: • energy and resource efficiency; • cost effectiveness; • minimisation of emissions that negatively impact global warming, indoor air quality and acid rain; • minimisation of waste discharges; and • maximisation of fulfilling the requirements of occupants’ health and wellbeing. Professionals in the built environment sector, for example, urban planners, architects, building scientists, engineers, facilities managers, performance assessors and policy makers, will play a significant role in delivering a sustainable built environment. Delivering a sustainable built environment needs an integrated approach and so it is essential for built environment professionals to have interdisciplinary knowledge in building design and management . Building and urban designers need to have a good understanding of the planning, design and management of the buildings in terms of low carbon and energy efficiency. There are a limited number of traditional engineers who know how to design environmental systems (services engineer) in great detail. Yet there is a very large market for technologists with multi-disciplinary skills who are able to identify the need for, envision and manage the deployment of a wide range of sustainable technologies, both passive (architectural) and active (engineering system),, and select the appropriate approach. Employers seek applicants with skills in analysis, decision-making/assessment, computer simulation and project implementation. An integrated approach is expected in practice, which encourages built environment professionals to think ‘out of the box’ and learn to analyse real problems using the most relevant approach, irrespective of discipline. The Design and Management of Sustainable Built Environment book aims to produce readers able to apply fundamental scientific research to solve real-world problems in the general area of sustainability in the built environment. The book contains twenty chapters covering climate change and sustainability, urban design and assessment (planning, travel systems, urban environment), urban management (drainage and waste), buildings (indoor environment, architectural design and renewable energy), simulation techniques (energy and airflow), management (end-user behaviour, facilities and information), assessment (materials and tools), procurement, and cases studies ( BRE Science Park). Chapters one and two present general global issues of climate change and sustainability in the built environment. Chapter one illustrates that applying the concepts of sustainability to the urban environment (buildings, infrastructure, transport) raises some key issues for tackling climate change, resource depletion and energy supply. Buildings, and the way we operate them, play a vital role in tackling global greenhouse gas emissions. Holistic thinking and an integrated approach in delivering a sustainable built environment is highlighted. Chapter two demonstrates the important role that buildings (their services and appliances) and building energy policies play in this area. Substantial investment is required to implement such policies, much of which will earn a good return. Chapters three and four discuss urban planning and transport. Chapter three stresses the importance of using modelling techniques at the early stage for strategic master-planning of a new development and a retrofit programme. A general framework for sustainable urban-scale master planning is introduced. This chapter also addressed the needs for the development of a more holistic and pragmatic view of how the built environment performs, , in order to produce tools to help design for a higher level of sustainability and, in particular, how people plan, design and use it. Chapter four discusses microcirculation, which is an emerging and challenging area which relates to changing travel behaviour in the quest for urban sustainability. The chapter outlines the main drivers for travel behaviour and choices, the workings of the transport system and its interaction with urban land use. It also covers the new approach to managing urban traffic to maximise economic, social and environmental benefits. Chapters five and six present topics related to urban microclimates including thermal and acoustic issues. Chapter five discusses urban microclimates and urban heat island, as well as the interrelationship of urban design (urban forms and textures) with energy consumption and urban thermal comfort. It introduces models that can be used to analyse microclimates for a careful and considered approach for planning sustainable cities. Chapter six discusses urban acoustics, focusing on urban noise evaluation and mitigation. Various prediction and simulation methods for sound propagation in micro-scale urban areas, as well as techniques for large scale urban noise-mapping, are presented. Chapters seven and eight discuss urban drainage and waste management. The growing demand for housing and commercial developments in the 21st century, as well as the environmental pressure caused by climate change, has increased the focus on sustainable urban drainage systems (SUDS). Chapter seven discusses the SUDS concept which is an integrated approach to surface water management. It takes into consideration quality, quantity and amenity aspects to provide a more pleasant habitat for people as well as increasing the biodiversity value of the local environment. Chapter eight discusses the main issues in urban waste management. It points out that population increases, land use pressures, technical and socio-economic influences have become inextricably interwoven and how ensuring a safe means of dealing with humanity’s waste becomes more challenging. Sustainable building design needs to consider healthy indoor environments, minimising energy for heating, cooling and lighting, and maximising the utilisation of renewable energy. Chapter nine considers how people respond to the physical environment and how that is used in the design of indoor environments. It considers environmental components such as thermal, acoustic, visual, air quality and vibration and their interaction and integration. Chapter ten introduces the concept of passive building design and its relevant strategies, including passive solar heating, shading, natural ventilation, daylighting and thermal mass, in order to minimise heating and cooling load as well as energy consumption for artificial lighting. Chapter eleven discusses the growing importance of integrating Renewable Energy Technologies (RETs) into buildings, the range of technologies currently available and what to consider during technology selection processes in order to minimise carbon emissions from burning fossil fuels. The chapter draws to a close by highlighting the issues concerning system design and the need for careful integration and management of RETs once installed; and for home owners and operators to understand the characteristics of the technology in their building. Computer simulation tools play a significant role in sustainable building design because, as the modern built environment design (building and systems) becomes more complex, it requires tools to assist in the design process. Chapter twelve gives an overview of the primary benefits and users of simulation programs, the role of simulation in the construction process and examines the validity and interpretation of simulation results. Chapter thirteen particularly focuses on the Computational Fluid Dynamics (CFD) simulation method used for optimisation and performance assessment of technologies and solutions for sustainable building design and its application through a series of cases studies. People and building performance are intimately linked. A better understanding of occupants’ interaction with the indoor environment is essential to building energy and facilities management. Chapter fourteen focuses on the issue of occupant behaviour; principally, its impact, and the influence of building performance on them. Chapter fifteen explores the discipline of facilities management and the contribution that this emerging profession makes to securing sustainable building performance. The chapter highlights a much greater diversity of opportunities in sustainable building design that extends well into the operational life. Chapter sixteen reviews the concepts of modelling information flows and the use of Building Information Modelling (BIM), describing these techniques and how these aspects of information management can help drive sustainability. An explanation is offered concerning why information management is the key to ‘life-cycle’ thinking in sustainable building and construction. Measurement of building performance and sustainability is a key issue in delivering a sustainable built environment. Chapter seventeen identifies the means by which construction materials can be evaluated with respect to their sustainability. It identifies the key issues that impact the sustainability of construction materials and the methodologies commonly used to assess them. Chapter eighteen focuses on the topics of green building assessment, green building materials, sustainable construction and operation. Commonly-used assessment tools such as BRE Environmental Assessment Method (BREEAM), Leadership in Energy and Environmental Design ( LEED) and others are introduced. Chapter nineteen discusses sustainable procurement which is one of the areas to have naturally emerged from the overall sustainable development agenda. It aims to ensure that current use of resources does not compromise the ability of future generations to meet their own needs. Chapter twenty is a best-practice exemplar - the BRE Innovation Park which features a number of demonstration buildings that have been built to the UK Government’s Code for Sustainable Homes. It showcases the very latest innovative methods of construction, and cutting edge technology for sustainable buildings. In summary, Design and Management of Sustainable Built Environment book is the result of co-operation and dedication of individual chapter authors. We hope readers benefit from gaining a broad interdisciplinary knowledge of design and management in the built environment in the context of sustainability. We believe that the knowledge and insights of our academics and professional colleagues from different institutions and disciplines illuminate a way of delivering sustainable built environment through holistic integrated design and management approaches. Last, but not least, I would like to take this opportunity to thank all the chapter authors for their contribution. I would like to thank David Lim for his assistance in the editorial work and proofreading.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Briefing: re-engineering the city 2020–2050 – urban foresight and transition management

Cities may be responsible for up to 70% of global carbon emissions and 75% of global energy consumption and by 2050 it is estimated that 70% of the world's population could live in cities. The critical challenge for contemporary urbanism, therefore, is to understand how to develop the knowledge, capacity and capability for public agencies, the private sector and multiple users in city regions systemically to re-engineer their built environment and urban infrastructure in response to climate change and resource constraints. Re-Engineering the City 2020–2050: Urban Foresight and Transition Management (Retrofit 2050) is a major new interdisciplinary project funded under the Engineering and Physical Science Research Council's (EPSRC) Sustainable Urban Environments Programme which seeks to address this challenge. This briefing describes the background and conceptual framing of Retrofit 2050 project, its aims and objectives and research approach.

Knowledge dissemination in the global service marketing community

Purpose– The evolution of the service marketing field was marked by the emergence of a global, vigorous and tolerant community of service marketing researchers. This paper seeks to examine the history of the service marketing community and argues that it may be an archetype for building the emergent global service research community. Design/methodology/approach– The study combines qualitative and quantitative approaches. The authors interviewed four pioneering service scholars and also collected descriptive data (e.g. Authorship, Affiliation, Title, Keywords) of all service related articles published in 13 top peer‐reviewed marketing and service journals over the last 30 years (5,432 articles; 6,450 authors). In a dynamic analysis the authors mapped global collaboration between countries over time and detected clusters of international collaboration. Findings– Findings suggest a growing international collaboration for the USA and the UK, while for other countries like Israel the global collaboration started from a high level and decreases now. Further, the service marketing community never became polarized and there were always contributions from researchers all over the world. Research limitations/implications– As the global service research community is developing, service marketing becomes a research neighborhood within the broader service research community. Simultaneously, other research neighborhoods are emerging within this new community (e.g. service arts, service management, service engineering, service science). Originality/value– Anchored on the social evolution and biological evolution metaphors, this study explains the evolution of the service marketing field from both qualitative and quantitative perspectives. Furthermore, it explains the development of the service marketing community as an archetype for building the global service research community.

A survey of data mining techniques for social media analysis

Social network has gained remarkable attention in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. The heavy reliance on social network sites causes them to generate massive data characterised by three computational issues namely; size, noise and dynamism. These issues often make social network data very complex to analyse manually, resulting in the pertinent use of computational means of analysing them. Data mining provides a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules [44]. Data mining techniques are used for information retrieval, statistical modelling and machine learning. These techniques employ data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey discusses different data mining techniques used in mining diverse aspects of the social network over decades going from the historical techniques to the up-to-date models, including our novel technique named TRCM. All the techniques covered in this survey are listed in the Table.1 including the tools employed as well as names of their authors.

Knowledge transfer of the Western concept of ‘quality’

This paper addresses one of the issues in contemporary globalisation theory: the extent to which there is ‘one best way’ in which business can be done and organisations managed. It uses Czarniawska’s ‘Travels of Ideas’ model as an organising framework to present and understand how the concept of ‘Quality’, so important in contemporary approaches to manufacturing & services, and their management, travelled to, and impinged on, a newly opened vehicle assembly plant in Poland. The extent to which new meanings were mutually created in the process of translation is discussed, using ethnographic reporting and analysis techniques commonly used in diffusion research. Parallels between the process of translation as an idea becomes embedded into a new cultural location, and the processes which contemporary research has identified as important to organisational learning, are briefly discussed in conclusion.

A possible reconceptualization of food engineering discipline

Food industry is critical to any nation’s health and well-being; it is also critical to the economic health of a nation, since it can typically constitute over a fifth of the nation’s manufacturing GDP. Food Engineering is a discipline that ought to be at the heart of the food industry. Unfortunately, this discipline is not playing its rightful role today: engineering has been relegated to play the role of a service provider to the food industry, instead of it being a strategic driver for the very growth of the industry. This paper hypothesises that food engineering discipline, today, seems to be continuing the way it was in the last century, and has not risen to the challenges that it really faces. This paper therefore categorises the challenges as those being posed by: 1. Business dynamics, 2. Market forces, 3. Manufacturing environment and 4. Environmental Considerations, and finds the current scope and subject-knowledge competencies of food engineering to be inadequate in meeting these challenges. The paper identifies: a) health, b) environment and c) security as the three key drivers of the discipline, and proposes a new definition of food engineering. This definition requires food engineering to have a broader science base which includes biophysical, biochemical and health sciences, in addition to engineering sciences. This definition, in turn, leads to the discipline acquiring a new set of subject-knowledge competencies that is fit-for-purpose for this day and age, and hopefully for the foreseeable future. The possibility of this approach leading to the development of a higher education program in food engineering is demonstrated by adopting a theme based curriculum development with five core themes, supplemented by appropriate enabling and knowledge integrating courses. At the heart of this theme based approach is an attempt to combine engineering of process and product in a purposeful way, termed here as Food Product Realisation Engineering. Finally, the paper also recommends future development of two possible niche specialisation programs in Nutrition and Functional Food Engineering and Gastronomic Engineering. It is hoped that this reconceptualization of the discipline will not only make it more purposeful for the food industry, but it will also make the subject more intellectually challenging and attract bright young minds to the discipline.

Review of current in vivo measurement techniques for quantifying enteric methane emission from ruminants

Ruminant husbandry is a major source of anthropogenic greenhouse gases (GHG). Filling knowledge gaps and providing expert recommendation are important for defining future research priorities, improving methodologies and establishing science-based GHG mitigation solutions to government and non-governmental organisations, advisory/extension networks, and the ruminant livestock sector. The objectives of this review is to summarize published literature to provide a detailed assessment of the methodologies currently in use for measuring enteric methane (CH4) emission from individual animals under specific conditions, and give recommendations regarding their application. The methods described include respiration chambers and enclosures, sulphur hexafluoride tracer (SF6) technique, and techniques based on short-term measurements of gas concentrations in samples of exhaled air. This includes automated head chambers (e.g. the GreenFeed system), the use of carbon dioxide (CO2) as a marker, and (handheld) laser CH4 detection. Each of the techniques are compared and assessed on their capability and limitations, followed by methodology recommendations. It is concluded that there is no ‘one size fits all’ method for measuring CH4 emission by individual animals. Ultimately, the decision as to which method to use should be based on the experimental objectives and resources available. However, the need for high throughput methodology e.g. for screening large numbers of animals for genomic studies, does not justify the use of methods that are inaccurate. All CH4 measurement techniques are subject to experimental variation and random errors. Many sources of variation must be considered when measuring CH4 concentration in exhaled air samples without a quantitative or at least regular collection rate, or use of a marker to indicate (or adjust) for the proportion of exhaled CH4 sampled. Consideration of the number and timing of measurements relative to diurnal patterns of CH4 emission and respiratory exchange are important, as well as consideration of feeding patterns and associated patterns of rumen fermentation rate and other aspects of animal behaviour. Regardless of the method chosen, appropriate calibrations and recovery tests are required for both method establishment and routine operation. Successful and correct use of methods requires careful attention to detail, rigour, and routine self-assessment of the quality of the data they provide.

MODELLING OF HIGH-PRESSURE PHASE EQUILIBRIUM IN SYSTEMS OF INTEREST IN THE FOOD ENGINEERING FIELD USING THE PENG-ROBINSON EQUATION OF STATE WITH TWO DIFFERENT MIXING RULES

In this work, thermodynamic models for fitting the phase equilibrium of binary systems were applied, aiming to predict the high pressure phase equilibrium of multicomponent systems of interest in the food engineering field, comparing the results generated by the models with new experimental data and with those from the literature. Two mixing rules were used with the Peng-Robinson equation of state, one with the mixing rule of van der Waals and the other with the composition-dependent mixing rule of Mathias et al. The systems chosen are of fundamental importance in food industries, such as the binary systems CO(2)-limonene, CO(2)-citral and CO(2)-linalool, and the ternary systems CO(2)-Limonene-Citral and CO(2)-Limonene-Linalool, where high pressure phase equilibrium knowledge is important to extract and fractionate citrus fruit essential oils. For the CO(2)-limonene system, some experimental data were also measured in this work. The results showed the high capability of the model using the composition-dependent mixing rule to model the phase equilibrium behavior of these systems.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of Document Collections

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.