Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk ...to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, while addressing the major challenges for their effective implementation.
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•Impacts on the health of city dwellers due to high air pollution exposure are unknown.•Conventional sparse monitoring stations are unable to identify pollution hotspots.•Low-cost micro-scale sensing allows capturing real-time high-grained pollution data.•Fundamental drivers behind the rise of low-cost sensing and challenges are discussed.
With cities accounting for approximately two thirds of the global demand for energy, there is significant scope to optimize energy usage of cities, in particular by improving the use of the built ...form. Large non-domestic buildings are increasingly the focus of attention, due to their substantial demands and associated environmental impacts such as CO2 emissions. Various approaches have been adopted to address building energy efficiency, with more recent studies relating consumption patterns to human occupancy. This paper proposes a new method to measure activity, using WiFi connections as a proxy for human occupancy. Data on the number of WiFi connections and energy consumption (electricity, steam and chilled water) were compared for two buildings within the Massachusetts Institute of Technology's campus. The results of the study demonstrate: the operation of the heating, ventilation and air conditioning (HVAC) systems adhered more closely to factors other than occupancy i.e. external temperature, whilst a small part of the electricity levels did correlate with the occupancy. In order to present possible solutions to address the disconnect between the HVAC system and occupancy levels, this paper identifies future steps that could begin to improve energy usage.
•Need for effective BEMS to recognise spatio-temporal variability of energy demand.•Overview of current state-of-the-art of sensors for BEMS is presented.•Impact of low-cost sensing for efficient ...energy management system is discussed.•Lack of affordable services for large-scale data analysis is underlined.•Support of IoT and M2M communication to facilitate Adaptive EMS is envisioned.
Rapid growth in the global population requires expansion of building stock, which in turn calls for increased energy demand. This demand varies in time and also between different buildings, yet, conventional methods are only able to provide mean energy levels per zone and are unable to capture this inhomogeneity, which is important to conserve energy. An additional challenge is that some of the attempts to conserve energy, through for example lowering of ventilation rates, have been shown to exacerbate another problem, which is unacceptable indoor air quality (IAQ). The rise of sensing technology over the past decade has shown potential to address both these issues simultaneously by providing high-resolution tempo-spatial data to systematically analyse the energy demand and its consumption as well as the impacts of measures taken to control energy consumption on IAQ. However, challenges remain in the development of affordable services for data analysis, deployment of large-scale real-time sensing network and responding through Building Energy Management Systems. This article presents the fundamental drivers behind the rise of sensing technology for the management of energy and IAQ in urban built environments, highlights major challenges for their large-scale deployment and identifies the research gaps that should be closed by future investigations.
In the present paper an apparatus of tools and methods is presented to evaluate, at the design stage, the risks over a set of objectives through buildings lifetime. To this purpose a tool is first ...presented to relate technological requirements of each technical elements to the pertinent maintenance interventions. Then a process is also proposed to estimate the risks on user requirements runningMonte Carlo simulations. The risk management process proposed in the present work aims to support designers and promoters in making predictions on the outcomes of long, not standardized, multivariable dependent processes – as the building process is – in order to indicate the attitude of a designed building to meet a framework of important objectives through its lifetime.
Inland waterways often consist of large numbers of man-made objects to ensure navigability. These objects are of many different types, ages and sizes, and deteriorate in uncountable of different ...ways. In order to ensure that the deterioration of the objects does not result in a loss of navigability, interventions must be executed. This, however, produces costs, in terms of both labour and material costs and costs of loss of service if the waterway is rendered non-navigable during intervention. In this paper, a methodology is presented to determine optimal multiple time period intervention programmes for inland waterways. The optimal intervention programme is the one that has highest net benefit, i.e. overall benefits minus overall costs, where benefits are the reduction in risk of failure. A genetic algorithm is used to overcome the problem of combinatorial explosion when many objects, in many states, over many time periods are to be considered. The exact formulation of the genome, as well as the genetic fitness function, are presented. They are used to determine an optimal intervention programme for a fictive inland waterway network. The results are presented and discussed, and an outlook is provided on further steps to improve this methodology.
In metropolitan areas, real estate investments, such as buildings, can be highly profitable. The profitability, however, can be uncertain, as adaptations might be required in the long-term to enable ...the modification of the building to adapt it to new uses. In building adaptation for use transitions, an important aspect is the modification of the ceiling height of the ground floor to meet the floor height requirements of different uses. Designs that include flexible ceilings instead of rigid ceilings have relatively low future adaptation costs, but are relatively expensive. Such designs are, therefore, only beneficial when the use transition costs over the life of the building are higher than the cost difference between the flexible and the rigid design. Because of the difficulties in predicting the number and types of adaptations that will occur over the life of a building, and the fact that flexible designs are more expensive, investors, to their own detriment, often build rigidly for current needs only. In the work presented in this article, a new process was developed and tested that uses Monte Carlo simulations to estimate costs and benefits of alternative ceiling designs, considering uncertainty on use transitions. The process is shown by using it to estimate the net-benefit over 70 years for an investor related to a fictive building in London with flexible ceilings and the same building with rigid ceilings. It was considered that multiple use transitions among five use categories (residential, retail, industrial, office, and other) were possible. It is shown that the process can be used to gain more insight into how buildings should be designed to maximize investor net-benefit, taking into consideration uncertain variables, such as use-change rate, construction costs and durations, discount factors and rents. A discussion of possible improvements to the process is given.
•Design choices based on average conditions don’t guaranty optimal investments.•Ceiling design optimization requires considering the uncertainty on use transitions.•A Monte-Carlo based process is proposed to design ceilings considering uncertainty.•In dense urban areas the process is needed to optimize ceiling investments.
Decision making for effective infrastructure integration is challenging because the performance of long‐lasting facilities is often difficult to foresee or well beyond the designer's control. We ...propose a new approach for integrating the construction/retrofitting of two or more types of facilities. Infrastructure integration has many perceived benefits, but practitioners also express serious doubts, particularly when it comes to civil engineering works. To substantiate this approach, we test all of the major options for integrating a ground source heat pump system with the construction/retrofitting of an archetypal office building. We use actual data from the United Kingdom, which represent a middle‐of‐the‐road setting among major developed countries. The model highlights the sensitivity of the range of cost‐effective solutions to the embedding of future options. The findings point to a clear need for appropriate standards for managing infrastructure integration. We expect this kind of model to find increasing applications among infrastructure complexes, particularly as cities become denser and more multifunctional.
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