Which of the following would not be considered part of the built environment?

10.4.1 Collecting data for planning

As shown by Fig. 10.3, the characterization of the UBE in the Plan phase should define the input data for hazard, vulnerability and exposure modeling, by preferably using quick data collection and representation tools to ensure a rapid large scale application and the definition of different scenarios also by low-trained technicians (Dolce et al., 2018).

The hazard modeling (Cimellaro et al., 2017; Dolce et al., 2003; Ntokos and Ntokou, 2020; Tsompanakis, 2015) can be based on the definition of significant return periods for earthquake magnitude (or ground motion) evaluations, or by using historical data to trace probable recurring conditions (e.g. by also using earthquake intensity values in view of adopting macroseismic methods for building damage assessment). Local amplification phenomena can be considered if micro-zoning data are available. These data are then linked to UBE vulnerability modeling (e.g. compare to the previous book chapters) that should be able to provide an estimation of damage levels in the UBE, by both considering debris along the OS in the UBE and building collapse (also compare to Section 10.2 related issues).

Then, the exposure modeling should firstly involve the UBE layout, in terms of the configuration of the OS and paths (streets) network, their geometry (plan and section-related data, to trace the buildings heights characterization), and their internal layout (to point out accessible/inaccessible areas by evacuees and rescuers, or significant obstacles, e.g. parking areas, green spaces) (Bernardini et al., 2018; Francini et al., 2018; French et al., 2019; Shrestha et al., 2018; Zlateski et al., 2020). In particular, the OS network “is composed of nodes that are placed at crossroads and squares or, generally, in each significant plan variation along the streets. Thus, links represent parts of the street network between pairs of nodes” (Zlateski et al., 2020, p. 21).

The UBE use can be retrieved for both buildings and OS in the UBE, to quantify the number of people present in the scenario and to qualify their features, when data are available (e.g. age, gender) (Bernardini et al., 2016a; Hassanzadeh, 2019; Li et al., 2019; Zlateski et al., 2020). Census data about population in UBE (Hassanzadeh, 2019; Jena et al., 2019) can be generally used to characterize homogeneous wide areas (e.g. [pp/km2], supply more detailed data about the building occupancy (e.g. thanking to fire safety codes, expressing occupancy in [pp/m2]) or even provide comprehensive citizens’ position and their typologies in case of GIS integration (e.g. by local/street-scale surveys). In this sense, the position of high-exposure and strategical buildings (e.g. hospitals, public administration structures, hotels, other buildings open to the public) should be assessed in the UBE layout (Italian technical commission for seismic micro-zoning, 2014; Zlateski et al., 2020). Nevertheless, the variations of the hosted users in the UBE should be addressed, by introducing possible variations over the time due to, e.g. (Bernardini et al., 2018; Emori et al., 2016; Hassanzadeh, 2019; Li et al., 2019):

differences between night and day (working) time in buildings (e.g. residential versus tertiary areas) depending on their intended use and spatiotemporal dynamics in the UBE;

weekly, monthly or seasonal presence of visitors in the UBE (e.g. holiday time);

mass-gatherings inside buildings, due to activities hosted inside them (e.g. cinemas, theaters);

mass-gathering in the OS, which can be both focused in specific areas of the UBE or involving a large part of it.

Critical pre-disaster conditions can be defined depending on (Anglade et al., 2020; Bernardini et al., 2016a; Shapira et al., 2015): the maximum value of the human presences, to have the maximum impact on direct (casualties due to buildings damage/collapse) and indirect (e.g. evacuation) losses; different statistical-based analysis of the exposure conditions over the time, to describe different probability levels of an earthquake scenario.

Finally, in view of the evacuation process assessment, the exposure modeling should also consider the evacuation plan, in the view of existing or proposed EEMS. According to Section 10.2.1 consolidated assumptions, the following elements should be identified (at least): a) gathering areas into the UBE layout assumed (Codified gathering Areas-CA); b) rescuers’ Access Points (AP) linking the UBE with external areas and the strategical Access Routes (AR) inside the UBE; c) main Evacuation Paths (EP, composed by one or more links) connecting the CA (as nodes) and having free access; d) nodes as decision points in the UBE layout linking EPs/APs, such as main crossroads, and CA. In this process, the UBE can be divided into sub-UBE sharing similar features and minimum emergency plan elements to ensure self-organization during the evacuation (Xu et al., 2016; Zhao et al., 2017).

17.2 Domain-specific examples and applications

Built environment can be defined in several ways:

The term built environment refers to the human-made surroundings that provide the setting for human activity, ranging in scale from buildings and parks or green space to neighborhoods and cities that can often include their supporting infrastructure, such as water supply or energy networks. The built environment is a material, spatial, and cultural product of human labor that combines physical elements and energy in forms for living, working, and playing. It has been defined as “the human-made space in which people live, work, and recreate on a day-to-day basis” (Wikipedia, //en.wikipedia.org/wiki/Built_environment).

The “built environment encompasses places and spaces created or modified by people including buildings, parks, and transportation systems.” In recent years, public health research has expanded the definition of built environment to include healthy food access, community gardens, walkability, and bikability (//www.ieltsinternational.com/).

A built environment is developed in order to satisfy residents' requirements. Human needs can be physiological or social and are related to security, respect, and self-expression. People want their built environment to be aesthetically attractive and to be in an accessible place with a well-developed infrastructure, convenient communication access, and good roads, and the dwelling should also be comparatively cheap, comfortable, with low maintenance costs, and have sound and thermal insulation of walls. People are also interested in ecologically clean and almost noiseless environments, with sufficient options for relaxation, shopping, fast access to work or other destinations, and good relationships with neighbors.

It must be admitted that the most serious problems of built environments (eg, unemployment, vandalism, lack of education, robberies) are not always related to the direct physical structure of housing. Increasing investment into the development of social and recreational centers, such as athletic clubs, physical fitness centers, and family entertainment centers, the infrastructure, a good neighborhood and better education of young people, can solve such problems. Investment, purchase and sale of a property, and its registration have related legal issues. The legal system of a country aims to reflect its existing social, economic, political, and technical state and the requirements of the market economy. As illustrated, the life cycle of the built environment can be assessed taking into account many quantitative and qualitative criteria. Life cycle of the built environment quantitative and qualitative analyses aspects are presented in Fig. 17.1.

Each one of these Level 1 aspects subsystems (see Fig. 17.1) based on the principle of a tree diagram can be discussed in much greater detail. To illustrate, the life cycle of the built environment described according to an example of the ith level aspects subsystem could be energy. In view of the global practice, any analysis of various aspects characteristic to the life cycle of the built environment focuses on the analysis of energy. Life cycle of the energy-efficient built environment application areas are presented in Fig. 17.2.

Potential applications of the IoT for the built environment are many and various, fitting into almost all activities done by persons, organizations, and the community as a whole. Libelium (2014) has released the document “Top 50 Internet of Things Applications”. Based on Libelium (2014), here is an overview of the applications used in the built environment:

Domotic and home automation: Energy and water use (energy and water supply consumption monitoring to obtain advice on how to save cost and resources), remote control appliances (switching on and off appliances remotely to avoid accidents and save energy), intrusion detection systems (detection of window and door openings and violations to prevent intruders), art and goods preservation (monitoring of conditions inside museums and art warehouses).

Smart cities: Smart parking (monitoring of parking spaces availability in the city), structural health (monitoring of vibrations and material conditions in buildings, bridges, and historical monuments), noise urban maps (sound monitoring in bar areas and centric zones in real-time), electromagnetic field levels (measurement of the energy radiated by cell stations and WiFi routers), traffic congestion (monitoring of vehicles and pedestrian levels to optimize driving and walking routes), smart lighting (intelligent and weather-adaptive lighting in street lights), waste management (detection of rubbish levels in containers to optimize the trash collection routes), smart roads (intelligent highways with warning messages and diversions according to climate conditions and unexpected events like accidents or traffic jams).

Smart environment: Forest fire detection (monitoring of combustion gases and preemptive fire conditions to define alert zones), air pollution (control of CO2 emissions of factories, pollution emitted by cars), snow level monitoring (snow level measurement to know in real time the quality of ski tracks and allow security corps avalanche prevention), landslide and avalanche prevention (monitoring of soil moisture, vibrations, and earth density to detect dangerous patterns in land conditions), earthquake early detection (distributed control in specific places of tremors).

Smart water: Potable water monitoring (monitor the quality of tap water in cities), chemical leakage detection in rivers (detect leakages and wastes of factories in rivers), swimming pool remote measurement (control remotely the swimming pool conditions), pollution levels in the sea (control real-time leakages and wastes in the sea), water leakages (detection of liquid presence outside tanks and pressure variations along pipes), river floods (monitoring of water level variations in rivers, dams, and reservoirs).

Smart metering: Smart grid (energy consumption monitoring and management), tank level (monitoring of water, oil, and gas levels in storage tanks and cisterns), photovoltaic installations (monitoring and optimization of performance in solar energy plants), water flow (measurement of water pressure in water transportation systems), silos stock calculation (measurement of emptiness level and weight of the goods).

Security and emergencies: Perimeter access control (access control to restricted areas and detection of people in nonauthorized areas), liquid presence (liquid detection in data centers, warehouses, and sensitive building grounds to prevent breakdowns and corrosion), radiation levels (distributed measurement of radiation levels in nuclear power stations surroundings to generate leakage alerts), explosive and hazardous gases (detection of gas levels and leakages in industrial environments, surroundings of chemical factories, and inside mines).

Retail: Supply-chain control (monitoring of storage conditions along the supply chain and product tracking for traceability purposes), NFC payment (payment processing based on location or activity duration for public transport, gyms, theme parks, etc.), intelligent shopping applications (getting advice in the point of sale according to customer habits, preferences, presence of allergic components for them, or expiring dates), smart product management (control of rotation of products in shelves and warehouses to automate restocking processes).

According to Friess (2012), the following list of aspects provides a wide but certainly not exhaustive compilation of the current IoT issues at stake:

Architecture: Development and refinement of structural reference frameworks for the arrangement of physical and logical hardware and software components, including questions of object identification, virtualization, and decentralization; also ensuring interoperability across application sectors.

Security and trust issues: Development of mechanisms and frameworks (by design) for ensuring that all users in business and private contexts trust the applications and maintain a certain power of control on their data across the full data and information life cycle.

Software and middleware platforms: Support for analysis and processing of data flows from sensing devices and a high quantity of object instances, complemented with event filtering and management capabilities and including complexity management considerations.

Interfaces: Integration of multimodal interface approaches for enriching all kinds of man–machine interaction for both changing the user experience and coping with the information density.

Smart sensors: Integration of sensing and reasoning capabilities into networked and energy-harvesting devices.

Testing and standardization: Current IoT dispositions are still ongoing and effects on mass deployments need to be much better understood. Testing and large-scale pilots are absolutely crucial and should also lead subsequently to standardization for ensuring interoperability and reducing complexity.

Business models: A sound exploitation of the IoT business potential is still missing and new business models for the existing incumbents but also new and innovative players need to be developed.

Societal and ethical implications: The IoT has already started to change our lives virtually but questions about the physical and logical usage coupled with considerations of needs for privacy, inclusiveness of the society, and evolution of social behavior remain very valid and only partly addressed.

IoT governance: Often misunderstood, IoT governance is, in particular, about the governance of the IoT and their context of usage rather than Internet aspects. New models, mechanisms, and frameworks covering legal aspects too are necessary for guaranteeing proper trust, identity, and liability management.

International cooperation: The IoT is a truly global subject that shows interesting application cases in different parts of the world. Moreover, as it will only work if a certain level of interoperability is maintained, a common understanding among the different nations involved is pivotal.

Integration of results from other disciplines: Basic ICT (information and communications technology), robotics, nanotechnology, biomedicine, and cognitive sciences provide a rich source of inspiration and applications for developing the IoT further on.

Potential applications of the IoT for the built environment are many and various, fitting into almost all activities done by persons, organizations, and the community as a whole. These (smart home, real-time information about the city's environment, Oxford Flood Network, waste collection for smart cities, wireless monitoring systems in the field of civil engineering, urban intelligence platform, emotional gateway to Minneapolis, waste management, cyber security challenges in smart cities, smart environment monitoring system for pollution, health e-research system, negotiation in cyber-physical systems, real-time safety early warning system for cross-passage construction, RFID-plants in the smart city) are provided in brief next.

All of Samsung's products would be built on platforms that are open and compatible with other products and 90% of its products—which range from smartphones to refrigerators—would be able to connect to the Web by 2017. In 5 years, every product in the company's entire catalog is expected to be Internet-connected. In effect, Samsung is readying for the IoT, the term for the concept of using sensors and other technologies to hook just about anything you can think of into the Internet. Samsung introduced a new home-monitoring subscription service that will send immediate texts or calls to the smartphone of a user or designated contacts about problems or emergencies at their home, such as a flood, fire, plumbing leak, or a pet out in the yard when a storm is starting. The premium service also includes built-in DVR services for cameras (watch around your home for different issues), alert for different issues (for example, grandma did not get up this morning; my kid did not get home from school on time; my dog is out in the yard and there's a storm coming, etc.) (Tibken, 2015).

This summer, data scientists and architects in Chicago are working on a new form of civic infrastructure: highly visible, aesthetically pleasing, 1-foot-square boxes mounted on light poles that track environmental conditions around them. Those small boxes represent a big idea: Inside each one, about a dozen sensors measure heat, humidity, air quality, carbon monoxide, and carbon dioxide levels, and light and noise levels, and those data will be made publicly available so that they can be used by application developers and researchers as well as the city. About 50 will be installed this year in the Loop area of the city (Crawford, 2014).

Right now, cities collect information in the form of permit applications, inspection results, and other service-related inputs. Analysis of these data can help cities know how the city is doing and assist it in targeting its efforts. But information about the well-being of a city—the quality of lives lived on its streets—is harder to come by. The Array of Things, as Chicago's Urban Center for Computation and Data calls this project, will start providing real-time information about the city's environment. For example, sensors will be able to detect mobile devices that have Bluetooth turned on, so the city will have information about the level of pedestrian density in a particular area. The city, as well as any researcher, will know about fine-grained pollution levels in different neighborhoods for the first time. Now it's moving to understand its weather, pollution, and noise in a transparent, public-friendly way. This means that the city will be able to investigate reams of these data, combine it with other information, and make predictions about its future that inform how the city allocates its resources and changes its policies. It's crowded? Change the traffic light patterns. Pollution is a problem in particular neighborhoods? Find out why and fix it. Gathering these data will not solve all of Chicago's challenges, such as a shooting rate that remains among the nation's highest. But making a better city also means improving the quality of daily life at street level. Investing time and money in data makes sense, and it's changing how local government works. Chicago, the quintessential American city, is quickly becoming the nation's leading city for data analytics (Crawford, 2014).

Oxford Flood Network is installing sensors around Oxford. Network have several on the Thames and Castle Mill Stream area and some under floors to detect rising water when the time comes. The levels are very low at the moment, but we know how quickly that can change. Oxford Flood Network is collecting a list of people who are happy to host a sensor (50 × 50 × 100 mm) and/or gateway device (90 × 60 × 26 mm). There is no cost to the host for the device, but inhabitants will need to help keep it up and running by checking it periodically online and perhaps changing the battery once a year. Oxford Flood Network will use the sensors to create a detailed map of water levels around the city in higher detail than the Environment Agency's existing sensors. Oxford Flood Network involves communities and citizens, improving literacy in the IoT (Handsome, 2015).

Until now collecting waste has been done with static routes and schedules. Containers are collected every day or every week regardless of whether they are full or not. This causes unnecessary costs, poor equipment utilization, and the constant nuisance of container overfill. Enevo ONe uses smart wireless sensors to gather fill-level data from waste containers and sends it to a cloud-based analytics platform. The platform then generates accurate forecasts for ideal container pick-up schedules and routes that can be can be accessed directly by the driver through any cellular-enabled tablet or smartphone. The Enevo ONe service provides not only monitoring, scheduling, and optimized routes, but truly smart waste collection plans, which are the result of millions of complex calculations regarding fill-level trends and projections, scheduling constraints, and routing options. Collection based on Enevo's smart plans significantly reduces costs, emissions, road wear, vehicle wear, noise pollution, and work hours. Enevo ONe provides up to 50% in direct cost savings in waste logistics. And that's not all. Reducing the amount of overfull containers means less litter and happier customers (Enevo, 2015).

A long-term deployment has been set up to demonstrate the capabilities and the ease of use of wireless monitoring systems in the field of civil engineering. In this application tensile forces of cable stays of a cable-stayed bridge are monitored by tracking natural frequencies of cable vibrations. Wireless sensors (accelerometer, air temperature, air humidity), running on a single set of batteries were installed on six stays to measure cable acceleration. Since energy resources are limited and data communication is an energy-consuming task, the amount of transmitted data has to be kept small in order to extend system lifetime. In this case, the acceleration time series is processed on the node and reduced to one frequency value, which has to be transmitted over the air. The concept of data reduction by means of processing raw data on the sensor node level is demonstrated in the deployment at the Stork Bridge in Winterthur. The installation has been running since 2006 and is one of the first long-term wireless monitoring applications worldwide (Decentlab, 2015).

Founded in 2012 and based in New York City, Placemeter is an urban intelligence platform that quantifies the movement of modern cities, at scale. Placemeter ingests any kind of video to analyze pedestrian and vehicular movement, revealing hidden patterns and strategic opportunities. Placemeter (2015) platform leverages proprietary computer vision technology to gather data without identity detection from live streams and archival video. Placemeter is using feeds from hundreds of traffic video cameras to study 10 million pedestrian movements each day. It's using that data to help businesses learn how to market to pedestrian consumers. Placemeter also says it wants to use the data to help consumers with information such as when to visit your neighborhood coffee bar when the line is shorter. Placemeter says it does not store the video, nor does their analysis involve facial recognition (Patterson, 2014).

Placemeter is turning disused smartphones into big data. Measuring data about how the city moves in real time, being able to make predictions on that, is definitely a good way to help cities work better. That's the vision of Placemeter—to build a data platform where anyone at any time can know how busy the city is, and use that. City residents send Placemeter a little information about where they live and what they see from their window. In turn, Placemeter sends participants a kit to convert their unused smartphone into a street sensor, and agrees to pay cash as long as the device stays on and collects data. The more action outside—the more shops, pedestrians, traffic, and public space—the more the view is worth (Jaffe, 2014).

On the back end, Placemeter converts the smartphone images into statistical data using proprietary computer vision. The company first detects moving objects and classifies them either as people or as 11 types of vehicles or other common urban elements, such as food carts. A second layer of analysis connects this movement with behavioral patterns based on the location—how many cars are speeding down a street, for instance, or how many people are going into a store. Placemeter taking all measures to ensure anonymity. The smartphone sensors do not capture anything that goes on in a meter's home (such as conversations), and the street images themselves are analyzed by the computer, then deleted without being stored (Jaffe, 2014).

Efforts to quantify city life with big data are not new, but Placemeter's clear advance is its ability to count pedestrians. With its army of smartphone eyes, Placemeter promises a much wider net of real-time data dynamic enough to recognize not only that a person exists but also that person's behavior, from walking speed to retail interest to general interaction with streets or public spaces. The benefits could extend to both private and public entities alike. Investors might use Placemeter data to find the best location for a store, while retailers could learn things like their sidewalk-to-store conversion rate and how it compares to other stores on the block. Meanwhile, municipal agencies could detect the use of benches or near misses at intersections—and generally evaluate (and perhaps improve) public projects more quickly than they might otherwise. In the future people can use Placemeter data to know when a basketball court is free or when the grocery store will be least crowded. It's this grassroots approach to big data that could make Placemeter a powerful platform for government accountability (Jaffe, 2014).

It needs between 2500 and 2700 video feeds to properly cover the city. With high-resolution cameras Placemeter says it can detect the gender of pedestrians with between 75% and 80% accuracy. This opens the potential for advertisements to be targeted to a more appropriate audience. Better foot traffic data could let retailers know whether they're paying too much for a location. The location of a store can make a huge difference in its success. Placemeter wants to sell its foot traffic data to businesses to help them get a better opportunity. Placemeter is trying to find inefficiency in the market. Ultimately the price starts to increase to a level that accurately reflects how good or bad the area is. Placemeter is trying to effectively short circuit that (McFarland, 2014).

Minneapolis Interactive Macro Mood Installation (MIMMI) is an emotional gateway to Minneapolis, bringing residents and visitors together to experience and participate in the collective mood of the city. MIMMI is a large, air-pressurized sculpture suspended from a slender structure located at the Minneapolis Convention Center Plaza. Cloud-like in concept, the sculpture hovers 30 feet above the ground, gathering emotive information online from Minneapolis residents and visitors to the plaza. MIMMI analyzes this information in real time, creating abstracted light displays and triggering misting in response to this input, creating light shows at nighttime and cooling microclimates during the daytime. Whether the city is elated following a Minnesota Twins win or frustrated from the afternoon commute, MIMMI responds, changing behavior throughout the day and night. To understand the city's mood, MIMMI sources information from local Twitter feeds and uses textual analysis to detect the emotion of those tweets, a process developed by INVIVIA's technologists using open source technology. By aggregating the positivity and negativity of tweets in real time, MIMMI transmits the abstracted emotion of the city to a series of WiFi-enabled LED bulbs and an integrated water misting system. The low-energy lights, hung inside of the sculpture material and stretching throughout the entire shape, display the mood beginning at sunset. The color of the lights shifts from cool colors (negative) to warm and hot colors (positive) depending on the mood, with rate of the lights' change depending on the rate of tweets (Minneapolis, 2015).

If the city mood is particularly “sad” or emotional for any particular reason, visitors to the plaza can come together to lift MIMMI's (and the city's collective) spirits, as MIMMI can detect movement at the plaza and include this information in its analytics. The more people present and moving around under the cloud, the more active MIMMI will become, responding either with increased lighting or misting depending on the time of day. Dance, high activity, and movement will positively affect MIMMI's mood displays. The website, www.minneapolis.org/mimmi, will catalog the mood of the city generated by MIMMI over the summer and fall, allowing visitors to see daily and weekly trends in the city's emotions. When visitors using iOS (iPhones) arrive at the plaza, the app will transform into an augmented reality view of MIMMI, providing a wholly new way of looking at the installation with additional animations emphasizing the city's current mood (Minneapolis, 2015).

Homes, cars, public venues, and other social systems are now on their path to the full connectivity known as the IoT. Standards are evolving for all of these potentially connected systems. They will lead to unprecedented improvements in the quality of life. To benefit from them, city infrastructures and services are changing with new interconnected systems for monitoring, control, and automation. Intelligent transportation, public and private, will access a web of interconnected data from GPS locations to weather and traffic updates. Integrated systems will aid public safety, emergency responders, and in disaster recovery (Elmaghraby and Losavio, 2014). Elmaghraby and Losavio (2014) examine two important and entangled challenges: security and privacy. Security includes illegal access to information and attacks causing physical disruptions in service availability. As digital citizens are more and more instrumented with data available about their location and activities, privacy seems to disappear (Elmaghraby and Losavio, 2014).

Air pollution is a major environmental change that causes many hazardous effects on human beings, which needs to be controlled (Jamil et al., 2015). Jamil et al. (2015) deployed wireless sensor network (WSN) nodes for constant monitoring of the air pollution around the city and the moving public transport buses and cars. The data of the air pollution particles such as gases, smoke, and other pollutants is collected via sensors on the public transport buses and the data is being analyzed when the buses and cars reach back to the source destination after passing through the stationary nodes around the city (Jamil et al., 2015).

Clarke and Steele (2014) introduce a novel system to capture aggregate population health research data via utilizing smartphone capabilities while fully maintaining the anonymity and privacy of each individual contributing such data. A key and novel capability of this system is the support for customizable data collection, without the need to know specific details about an individual. The customized collection rules can be deployed on the local device based on detailed local data, and the resultant collection can be measured by the anonymous data collection network (Clarke and Steele, 2014).

In the near future, the IoT is expected to penetrate all aspects of the physical world, including homes and urban spaces. In order to handle the massive amount of data that becomes collectible and to offer services on top of this data, the most convincing solution is the federation of the IoT and cloud computing. Yet, the wide adoption of this promising vision, especially for application areas such as pervasive health care, assisted living, and smart cities, is hindered by severe privacy concerns of the individual users. Hence, user acceptance is a critical factor to turn this vision into reality (Henze et al., 2015).

With the rapid development of urbanization in China, the number and size of underground space development projects are increasing quickly. At the same time, more and more accidents are causing underground construction to increasingly become a focus of social attention. Therefore, this research presents a real-time safety early warning system to prevent accidents and improve safety management in underground construction, based on IoT technology. The proposed system seamlessly integrates a fiber Bragg grating sensor system and a radio frequency identification (RFID)-based labor tracking system. This system has been validated and verified through a real-world application at the cross passage construction site in the Yangtze Riverbed Metro Tunnel project in Wuhan, China (Ding et al., 2013).

A city may become smart and green through strategic deployment of information and communication technology infrastructure and services to achieve sustainability policy objectives in which trees have to be involved. Plants not only constitute green space useful to contrast urban pollution effects or provide ecosystemic benefits to residents but they can also be used as bioindicators and their involvement in communication networks can represent a significant contribution to build a smart, green city. RFID tags can be easily associated with plants, externally or internally. This latter approach is particularly indicated if the identification of trees needs to be secured since its production, eliminating the risk of tag losses or removal. Interesting applications may be derived by implementing RFID tags in biomonitoring systems in order to guarantee a real-time data communication in which tags may act as antennas for multifunctional green spaces (Luvisi and Lorenzini, 2014).

6.5.1 Introduction

The built environment has a strong impact on both human and environmental health. Buildings and the infrastructure surrounding them consume great quantities of materials and energy during construction, operations, and eventual deconstruction at the end of the buildings life (Sinha et al., 2013). There are accepted measures for analysing the environmental impacts of buildings and the materials and activities surrounding them such as life-cycle costing and assessment (ISO/IEC, 2006). As with environmental impacts, the built environment affects the people who use it in a variety of ways including psychologically, socially and physiologically. However, unlike the environmental impacts of the built environment, the methods for understanding how buildings impact their users are not currently as well established.

Human health impacts in buildings stem from different elements and aspects of the building itself. These include the environment and location of the building, its design, materials, maintenance, accessibility, safety and the management of the building (in terms of thermal comfort, lighting, etc.). Certain health impacts are easier to understand, and control, than others. For example, emissions from materials (such as formaldehyde) in buildings are readily assessable and limits are placed on these emissions by legislation in many places (EPA, 2016; CEN, 1992). Emission measurements, though, are an indirect measure of the impact buildings have on human health impact and are focused on preventing harm.

Harm prevention is an incredibly important aspect of building design, maintenance and management, but modern building design paradigms are pushing beyond preventative measures and are beginning to incorporate both environmental and human health interventions that are intended to create positive effects (Derr and Kellert, 2013; Dolan et al., 2016; Mang and Reed, 2012). For building users, these positive effects include health and behaviour impacts, which can translate to reduced pressures on health care systems, better job performance and more time at work (Danna and Griffin, 1999). This chapter will examine some of the primary concerns related to human health in the built environment, the interventions that can be used to create positive health impacts, as well as the design paradigms and research examining positive health interventions in the built environment. In each case, emphasis will be placed on the role of bio-based materials.

Abstract:

The built environment is a significant contributor to global greenhouse gas emissions. In many industrialised nations more than 40% of carbon emissions are the result of energy consumption by buildings. There is therefore significant potential through refurbishment of the existing building stock to significantly reduce energy consumption and the associated carbon dioxide emissions. This chapter evaluates the problem and provides best practice advice on refurbishment measures aimed at reducing a building’s overall energy consumption. The chapter also includes case study examples and provides details on how refurbishment measures can be assessed through post-occupancy evaluation.

Abstract

The built environment, which encompasses the places where we live and work and the ways we travel, is important for human health. Today, we face an epidemic of chronic diseases, many of which can be prevented by engaging in healthy behaviors every day. This can occur in places where it is easy to be physically active for transport and recreation, socially connect with family and community, and eat nutritious food available in shops and harvested from local gardens. These issues are explored in our article showing how action for a health-supportive environment is also good for environmental sustainability.

5.1 Building Construction Systems and Materials

The built environment on the world scale is diverse regarding different living standards (influencing the space area per capita), climatic conditions (influencing the cooling and heating demand, and envelope design), and construction technology (influencing the material choice, construction system, and fabrication). The choice of construction systems, construction technique, building components and materials is usually based on a multi-criteria approach and should cover different aspects, including:

Functionality

Technical Performance

Architectural Aesthetics

Economic Cost

Sustainability

Durability and Maintenance

The large number of materials in the selection parameters often makes it difficult and tedious to choose a given component (see Fig. 6.3). Gauvreau-Lemelin and Attia (2017) proved that very few studies have assessed the holistic environmental impact of NZEB. Therefore, the first question that needs to be answered when designing NZEB is:

What is the most suitable building construction system for a NZEB?

Worldwide, there are several types of building construction systems shown below. For each of those building construction systems, different combinations of building materials can be used, including brick, concrete, steel, aluminum, copper, plastic, glass, ceramics, and plaster.

Timber Construction (framed or post and column)

Load-Bearing Masonry Wall Construction

Steel Frame Structure

Precast Concrete Construction

Earthen Construction

Ideally, the question needs to be answered during the early design stages. During the first design iteration, priority should be given to components with clear ingredient and environmental impact documentation. During early design stages, it is possible to find sufficient materials and components that are readily available, minimally processed, nontoxic, and renewable or recyclable. The focus should be on the structural system in relation to the fabrication and construction on-site or off-site. The optimal sustainable and cost-effective structural system should be selected first. This can be done by eliminating undesirable substances, where energy-intensive and polluting materials, products, and processes are used only if no other better equivalent product is available. Undesirable materials and products typically relate to building construction systems and components which imply a large consumption of fossil-based resources and those which are known to contain toxic substances. The use of products that are coming from very far and transported over thousands of kilometers is undesirable too. A positive list of potential materials can be created by emphasizing renewable materials like timber and avoiding fossil fuel based products, especially insulation materials. The positive list should include solar panels.

After deciding on the most suitable structural and construction system, the envelope construction should be addressed. The choice of a low-carbon envelope system encourages reducing the quantities of concrete, aluminum, and steel as well as the overall embodied energy of the facade. This step involves the selection of the insulation material in combination with the envelope and construction technology. Locally harvested or produced materials, recycled content materials, bio-based materials like earth, hemp, bamboo, and timber are smart choices (Attia et al., 2013). Natural and recycled materials can be used in NZEB construction including curved glulam beams and recycled steel. Concrete mixed with volcanic ash requires lower temperatures to mix it and has an expected longer lifespan. However, we should not underestimate the importance of other performance criteria including fire safety, hygrothermal efficiency, material durability, water proofing, and thermal mass. Between a market-driven logic of architects, contractors, construction purchasing agents, and the sustainability consultant the design team must find a market-driven logic that embraces sustainability and decreases the embodied energy, increases operational efficiencies of the buildings, and reduces carbon emissions to save costs. Finally, the design team should prepare their NZEB solutions to be ready for disassembly. NZEB construction systems and material assemblies are mostly hybrid and therefore they require to be easily disassembled for reuse or recycling. As mentioned in Section 4.1, the European Union aims to transform the construction industry to design NZEB as material banks for the future through the BAMB project.

Abstract

The built environment contributes up to 50% of the UK's carbon emissions. Most buildings' analyses focus on the "carbon operating cost" of buildings rather than the embodied "carbon capital cost" and do not take into account a building lifespan. In this paper a new carbon accounting framework is presented modelled on financial accounting principles, with a carbon balance sheet and profit and loss. It is argued that it is illogical to discount future emissions of carbon but that it is reasonable to depreciate carbon assets and liabilities. Like Value Added Tax (VAT) accounting in financial transactions, the proposed carbon accounting method enables a proper, explicit and transparent allocation of carbon assets and liabilities to multiple agents in complex supply chains over distinct temporal, spatial and organisational boundaries.

The approach is demonstrated by applying the model to two energy-efficient buildings of the UK National Energy Foundation, a new Light-Weight building and an older High Thermal Mass one, designed for a lifespan of 50 and 150 years, respectively. The analysis shows that cement based materials, metal and insulation are the major carbon liabilities, with concrete foundations the main structural component responsible. On an operating carbon basis, the newest building produces the least CO2. In aggregate, the new building is more efficient with an annual carbon cost, including depreciated carbon capital costs, of ~ 14 tonnes of CO2/year, vs. ~ 21 tonnes of CO2/year for the longer lasting building. The best discounted annual capital carbon cost was for a (notional) building constructed by increasing the lifetime of the 50-year building to 150 years. However, in all buildings the discounted carbon capital cost was less than 11% of the total operating costs, showing that improvements in operating efficiency (carbon P&L) are the most important contribution to carbon emissions.

10.4 Structural materials for buildings

The built environment is the largest of all consumers of materials. The aggregated embodied energy of the materials in buildings, too, is large. We are talking GJ now, not MJ, and the functional unit is “per unit area (m2) of floor space.” The embodied energy of a building is the energy used to acquire raw materials, manufacture building products, and transport and install them when it is first built. Frequently the embodied energy is a large fraction of a building’s life-energy, so it is architects and civil engineers who look most closely at the embodied energies of the materials they use. What are they?

A local realtor (real estate agent) advertises “an exceptional property boasting wood construction with delightful concrete car-parking space with exquisite steel-framed roof that has to be seen to be appreciated.” Filter out the noise and you are left with three words: wood, concrete, steel. These are, indeed, the principal materials of the structure of buildings. The structure is just one of the material-intensive parts of a building. It provides the frame, meaning the structure that carries the self-weight and working loads, resists the wind forces, and, where needed, supports the dynamic loads of earthquakes. The structure is clad and insulated by the envelope. It provides weather protection, thermal insulation, radiation screening, acoustic separation, and the color, texture, and short-term durability of the building. The building has to work and therefore it needs services: internal dividers, water, gas, electricity, heating and cooling, ventilation, control of light and sound, and disposal of waste. And there is the interior: the materials that the occupants see, use, and feel—the floor and wall coverings, furnishings, and fittings. The four different groups—structure, envelope, services, interior—have different primary functions. All four are material-hungry (Table 10.5).

Table 10.5. Embodied energy per m2, concrete frame building

Embodied energy (GJ/m2)% of totalSite work0.296Structure0.9321Envelope1.2628Services1.1123Construction1.377Interior finishes0.3014Total4.52

The initial embodied energy per unit area of floor space of a building depends on what it is made of and where. An approximate figure is 4.5 GJ/m2; we’ll get more specific in a moment. Figure 10.5 shows where it goes: about a quarter each into the materials of the structure, those of the envelope, those of the services, and those of site preparation, building work, and interior lumped together. They differ most in the choice of materials for the structure.

Table 10.6 compares the structural embodied energy per m2 of a steel-framed, a reinforced concrete, and a wood-framed building. The wood frame has the lowest value, the steel frame the highest. The steel frame is 72% more energy intensive than wood and 33% more so than concrete.

Table 10.6. Embodied energy/m2 of alternative building structures

Structural typeMass of materials (kg/m2)Embodied energy* (GJ/m2)Steel frame86 steel, 625 concrete1.2Reinforced concrete frame68 steel, 900 concrete0.9Wood frame80 timber0.67

Postscript. If wood is the most energy-efficient material for building structures, why are not all buildings made of wood? As always, there are other considerations. There is the obvious constraint of scale: wood is economic for small structures but for buildings above four stories in height, steel and concrete are more practical. There is availability: where wood is plentiful (Massachusetts, USA), wood is widely used, but elsewhere (London, UK) it is not. There are issues of recyclability: steel is easily recycled, but re-using wood or concrete at end of life is more difficult. The trade-off between all of these determines the final choice.

7.6.2 European committee for standardisation (CEN)

Many ‘built environment/construction works’ EPD schemes now exist in Europe following the ISO standards. Most of these incorporate common elements but due to the flexibility of the ISO standards, the PCR they follow and the EPD that they produce are different from country to country.

To avoid barriers to trade of goods and services, European harmonisation is necessary. This agenda became the subject of a CEN Mandate, under instruction from the EU Enterprise Directorate. The Mandate was written to develop a harmonised approach for ‘sustainability of construction works’ of which LCA would be an important part. The mandate was accepted in late 2004 and work on the standards began in 2005.

In response to the mandate, Technical Committee TC350 was established by CEN to develop ‘horizontal standardised methods for the assessment of the integrated environmental performance of buildings’. Although the original mandate extended only to ‘environmental performance of buildings’, the work has subsequently been broadened to consider socio-economic aspects as well.

TC350 consists of five Working Groups under the leadership of a single Task Group; the work programme is split horizontally into framework, building and product levels; and vertically into environmental, social and economic dimensions. The initiative will deliver European Standards (EN), Technical Reports (TR) and Technical Specifications (TS).

Through TC350 the goal of the Commission is to provide a method for the voluntary delivery of environmental information that supports the construction of sustainable works including new and existing buildings.