The third LCA phase aims to evaluate the environmental impacts of the system under study based on the inventory results in relation to the goal and scope of the study. To this end, the inventory results are further processed with respect to the pre-established environmental impacts and social preferences (Guinée et al, 2001).
The impact assessment is a quantitative and/or qualitative process that is used to characterize and interpret the negative consequences of the environmental impacts identified during the inventory phase. Five steps are followed for the impact assessment: classification;
characterization; normalization; grouping; and weighting (Guinée et al, 2001; ISO 14040, 2006; Goedkoop and Oele, 2007). The last three steps are optional but are frequently followed as their results facilitate the interpretation of the results of the entire analysis during the fourth LCA phase.
During the classification, the impact categories are refined and finalized, taking into account the degree of required detail that has been specified during the first LCA phase. The inventory data is then assigned to the defined impact categories. During this process, it is possible that some data is allocated to more than one impact category. The impact categories that are usually taken into account concern degradation of the ecosystem, waste of natural resources, degradation of the quality of human life and consequences to human health (see Figure 8.2). Examples of impact categories considered in building-related LCAs can be found in Table 8.1.
In the special case of building-related LCAs where site-specific environmental impacts are also involved, the following site-specific impacts may also be considered (Kotaji et al, 2003; IEA, 2004):
• neighbourhood impacts (e.g. microclimate, glare and solar access);
• indoor environment (e.g. indoor air quality and thermal comfort);
• local ecology (e.g. land surface occupation and ecologically sensitive areas);
• local infrastructure (e.g. water supply and transport systems).
Moreover, during the construction stage, several types of substances can affect the health of workers (Kotaji et al, 2003). Traditional LCA aggregates all of the loadings and calculates impacts at the regional or global scale – local impacts that are connected to a building, such as those mentioned above, are not addressed. In order, therefore, to apply LCA to buildings, either the site-specific impacts are excluded from the assessment by appropriately setting the system boundaries, or they are inventoried and classified separately (Kotaji et al,
2003; IEA, 2004). In the second case, a more extensive data collection is needed at the LCIA stage, when a more balanced view of building performance is obtained. Unfortunately, current LCA models and tools are not able to account for the majority of site-specific impacts, and the best available alternative is to combine LCA with more passive and qualitative evaluation tools in order to obtain a generic and balanced view of building performance (Kotaji et al, 2003; IEA, 2004; Blom, 2006).
During the second step of impact assessment (i.e.
characterization), the inventory data is quantified and summarized within each impact category. To this end, appropriate characterization methods are specified in order to assess the inventory data’s contribution to the impact category or categories to which it has been assigned. There are several methods that may be employed (e.g. the eco-indicator method) (Goedkoop and Spriensma, 2001; Goedkoop and Oele, 2007).
However, since the results of this phase are particularly important for the overall outcome of the LCA study, it is essential that the characterization method selected for each impact category is explicitly reported and analysed.
Specification of the characterization method is followed by a calculation of the category indicators based on the inventory data that is quantified and aggregated through the use of appropriate characterization factors that reflect the relative contribution of the LCI results into a single result for each impact category. This result, called the category indicator result, expresses the contribution of the specific impact category in terms of equivalent amount of an emitted reference substance (e.g. the global warming potential impact indicator result is expressed in terms of emitted kilograms of CO2equivalents). The set of all category indicator results comprises the environmental profile of the system under study.
Normalization (i.e. the third step of impact assessment) is used to assess the magnitude of the effect that a particular impact category has upon the wider environmental problem. According to ISO 14040 (2006), normalization is the calculation of the category indicator results in relation to a base case. The base case may refer to a particular geographical area (e.g. Greece, Europe, etc.), a person (e.g. Greek citizen, European citizen, etc.), or another system for a given time period.
Additionally, other types of information may be taken
into account, such as a future desirable state. The main aim of normalizing the category indicator results is to better understand the relative importance, as well as the magnitude, of the results as far as the system under study is concerned. Normalization is also used for the compatibility check of the results and the preparation of data for the next phases. The outcome of this step is an alternative environmental profile for the system under study called the normalized environmental profile.
During the grouping step of the impact assessment, the different impact categories are aggregated into one or more sets. Grouping may be based either on the classification of the impact category indicators according to a nominal scale (e.g. specific emissions) or on the sorting of the impact category indicators according to an ordinal scale (e.g. high, medium and low priority).
Finally, during the last step of impact assessment (i.e. weighting), specific weights are defined for the impact category indicators’ results that have been assessed during normalization. The weights reflect the relative importance of each category indicator’s result according to some given social values and preferences.
The category indicator results are then multiplied by their weights and aggregated, resulting in a new alternative profile for the system under study called the weighted environmental profile.
Weighting is especially helpful when attempting to reduce LCA to a single score, as far as the environmental impact is concerned, and when making comparisons between alternative buildings or designs. Such a reduction is certainly useful when someone does not have the time or interest to delve into the details.
However, aggregation can suffer from a lack of detail.
Moreover, weighting is not allowed across impact categories for public comparisons between products, according to ISO 14040 (2006), due to the fact that the weights are largely based on subjective views.
Interpretation
This particular LCA phase is not specific for buildings (Kotaji et al, 2003), nor does it present any particularities when applied in this field. Moreover, it is very difficult to be standardized in the sense that there are no strict and rigorous rules applicable to each case.
Generally, during interpretation, the results of all previous analyses are interpreted and used as a basis for
decision-making regarding actions that are expected to improve both the system under study, as well as the environment and human welfare. Moreover, the results of all previous analyses, all choices that were made and all hypotheses assumed are assessed through sensitivity analyses to ensure consistency, completeness, soundness and robustness (Guinée et al, 2001).
Based on the analyses and assessments discussed in this chapter, conclusions are drawn and recommendations are made for decision-making regarding the system under study.
Conclusions
LCA was not originally conceived as a tool for analysing buildings or other complex and long-lived products or processes. Nevertheless, its applicability in this sector is accelerating rapidly, and is currently considered as one of the major tools supporting the efforts towards achieving sustainable buildings (Kotaji et al, 2003; IEA, 2004). Moreover, although LCA has a significant contribution to make with regard to environmental concerns, it has, at the same time, several limitations due to its complexity.
In order to perform a detailed LCA of a system, all of the related processes and environmental impacts should be identified and analysed. This results in an extremely complex and time-consuming procedure, with increased data and specialized knowledge requirements.
Other problems result from the fact that LCA cannot take into account or predict future changes in current technology or demand. This limits the validity of LCA results over time. Moreover, it does not take into account the effects caused by possible changes in methodological choices or decisions regarding the boundaries set or the specific system. As a result, LCA is limited to the analysis of impacts that are known and that can be quantified, and, in practice, it must be combined with sensitivity analyses and/or other approaches to account for the effects of the choices and assumptions considered.
Generally, the application of LCA may be limited by a lack of (UNEP, 2005):
• appropriate acknowledgement of its necessity/utility;
• specialized knowledge;
• a necessary budget;
• appropriate data and methods.
In addition, when applied in buildings, adaptation is needed for LCA to account for the long lifespan; local impacts; wide boundaries; maintenance, renovation and replacement needs; adaptation to changing expectations, users and technologies; occupants’ behaviour; and diverse interests of the building’s involved stakeholders.
However, if a clear justification is provided for adopting this particular assessment method, if the principles of the method are adopted consciously in building applications, if the way in which the analysed results are to be communicated both internally and externally is clearly defined, and if a reasonable budget is available, then LCA may become a powerful tool towards developing sustainable buildings, leading to a more environmentally friendly building sector.
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Introduction
Building research, particularly with respect to energy performance, appears to be undergoing a transformation not seen since the first oil crisis.
Governments have begun to recognize the scale and urgency of the challenge presented by climate change and that buildings can make a substantial contribution to reducing national carbon emissions (DTI, 2007).
Thus, building research is likely to focus increasingly on climate change mitigation and adaptation strategies across the built stock. In research terms, this translates into a rapid shift from more familiar small-scale projects, such as exemplar or prototype buildings of design and academic interest, to field studies that generate the kind and scale of empirical evidence that can inform energy policies at the national level.
The dynamic interactions between people and their built environment form a complex system that renders research of any detail or duration in this area a major challenge. These are not clinical trials, laboratory bench studies or just occupant questionnaires, but involve extensive environmental monitoring, detailed building and social surveys, and sometimes require major interventions in people’s homes, such as replacing heating systems or refurbishment. So, apart from dealing with participant recruitment, ethical issues and the often intrusive nature of the work, the sheer logistics and organization of such studies represent a major undertaking within typical resource and financial constraints. On the other hand, it is people living and working in buildings that essentially make this fieldwork interesting; they can highlight the limitations and confound the predictions of purely
technical or physical models. They are essentially why we still need to do this type of research.
The aim of this chapter is to guide researchers along a practical methodology for these studies both to address fully the specific research questions under investigation and underpinned by benchmark methods, and to recognize the potential for wider supplementary research that can add considerable value to the original study.
There are numerous related issues, such as statistical methods of recruitment to obtain representative samples or detailed energy analysis, that have been dealt with elsewhere and moreover would require a volume in their own right (BRE, 2005; Fowler, 2008). Hence, this chapter focuses on the underlying principles and techniques that guide the selection and implementation of methods to undertake this type of research.
The topics are illustrated via a case study of 29 dwellings in Milton Keynes, situated about 75km north-west of London, that were originally monitored for hourly energy and temperature from 1989 to 1991.
The dwellings essentially follow conventional UK housing design but were constructed to higher standards of energy performance than required by building regulations at that time. They incorporated energy efficiency features, such as increased floor and wall insulation, double-glazing and condensing boilers, so that they broadly complied with building standards of a decade later (Edwards, 1990). During 2005 to 2006, a follow-up study was undertaken in 14 of the gas centrally heated homes from the original study to determine if internal temperature or energy consumption had changed over the intervening years.
The original and follow-up studies are referred to as MK0 and MK1, respectively (Summerfield et al, 2007).