Today, even in developed countries, performing life-cycle assessment (LCA) is still a challenging and complex process, mixed with the possibility of significant errors—namely due to unreliable input data derived from unrepresentative sampling. Some scientific texts illustrate the so-called Smart World—where such errors are minimized via the exchange of information between everything globally. This may sound contradictory to the fact that now almost half the world population do not even have internet access. However, this chapter shows—by reasoning, review, and synthesis of the literature, theories, and data—that the emergence of the Smart World is plausible. Yet, it will not necessarily be sustainable, unless “smartness” is (re)defined in line with the Sustainable Development Goals. Otherwise, also, LCA might become obsolete, or its goals may transmute to non-sustainable ones. Focusing on examples from the construction industry and their interactions with other sectors, some shortcuts are also suggested to facilitate innovations and development of LCA and decision-making procedures.
TopIntroduction
So far, the most common type of Life-Cycle Assessment (LCA) in practice is the Environmental Life-Cycle Assessment (E-LCA) which deals with the environmental inputs and outputs of products, services or activities (e.g., carbon footprint, energy, and materials resource efficiency). Another type of LCA is the Economic Life-Cycle Assessment whose scope is frequently narrowed to Life-Cycle Cost Analysis (LCCA). Social types of LCA (S-LCA), dealing more with qualitative parameters, are more challenging and less common. Life-Cycle Sustainability Assessment (LCSA) is a framework to integrate different models concerning all the three bottom lines of sustainability (environmental, economic and social). As LCSA is a framework of methods, its application is limited by those incorporated methods such as S-LCA which is still in infancy (Onat, Kucukvar, Halog, & Cloutier, 2017; Guinée et al., 2011; Hunkeler & Rebitzer, 2005).
Although the necessity of LCA has been expressed by some governments and as a new trend it is being included in building standards (International Organization for Standardization, 2006a, 2006b; CEN - European Committee For Standardization, 2012, 2014), rating systems (Dgnb, 2011; USGBC, 2017), and laws (Liu, Wang, & Su, 2016; etool, 2018); even performing the most common types of LCA (E-LCA) is still difficult, time-consuming and sometimes results in unreliable estimates; because LCA requires precise, up-to-date complex input information that varies from time-to-time, place-to-place, and case-to-case. Such required information and databases, especially in many developing countries, typically either do not exist or are based on statistically unrepresentative sampling because of lack of observation and data collection (Onat et al., 2017; Reap, Roman, Duncan, & Bras, 2008; Saadah & AbuHijleh, 2010). I.e., for some developing countries—e.g., China (Greenhouse Gas Protocol, n.d.), India (thinkstep and GaBi Solutions, n.d.), and Malaysia (SIRIM, n.d.)—Life Cycle Inventory Databases (LCID) have been developed, but in most countries, such regional databases do not exist yet. For instance, regarding the available databases in the UAE, Prof. Abu-Hijleh—“Head of PhD in Architecture and Sustainable Built Environment, and MSc. in Sustainable Design of Built Environment Programmes”, The British University in Dubai (The British University in Dubai, n.d.)—was asked why they had used the database of Bath University for LCA research (Saadah & AbuHijleh, 2010) in Dubai. They responded that there is no LCID of materials in the UAE and it is extremely hard to calculate since many items are imported from different countries. They hypothetically used the values taken from the Bath University database as it was the most complete one (B. Abu-Hijleh, personal communication, October 29, 2016).
On the other hand, some scholars—by referring to recent rapid technological advances especially in Information and Communications Technology (ICT)—promise the emergence of the so-called Smart World in which anything would be tracked anywhere and anytime through the use of Artificial Intelligence (AI) and the Internet of Things (IoT) (Zhu, Leung, Shu, & Ngai, 2015). It enables collecting real-time data (e.g., energy and carbon input/outputs) associated with objects via a network of sensors, that makes LCA much more precise and automated compared with today’s conventional methods (Tao, Zuo, Da Xu, Lv, & Zhang, 2014), and thus LCA can better serve the procedures of optimal design and informed decision making.
This may sound in contrast with the current technological condition in many developing countries that is still unfavorable; nearly half the world population today still do not even have access to the internet (Luxton, 2016).
This chapter, in line with and as an interrelating step forward to previous studies—e.g., see (Ahvenniemi, Huovila, Pinto-Seppä, & Airaksinen, 2017; Clark, 2004; Onat et al., 2017; Etzkowitz & Leydesdorff, 1995; Leydesdorff & Deakin, 2011; Lombardi et al., 2012; Shahabian, 2018; Peschl & Fundneider, 2008)—tries to answer the following questions via reasoning and triangulating existing theories and information: