In the evaluation of environmental performance, it is necessary to analyze the potential effects related to not only the building materials or products, but also to the operation of the building. For example, the assessment of fossil fuel depletion for a building life cycle is based on its materials orproducts’ embodied energy (energy consumed in extraction, transport, manufacture, and installation), plus the operational energy needed to run the building over its lifetime.
The definition of the environmental indicators and parameters is based on the work that is being carried out in the European Centre for Normalization [12]. The methodology uses the same indicators and parameters that the experts found relevant in the building environmental performance assessment.
At the societal performance assessment, the methodology considers the parameters related to the health and comfort performance of buildings during their use and operation. In order to facilitate its use and understanding by all the Portuguese construction market’s actors, the methodology does not consider parameters that can raise some kind of complexity and subjectivity in the assessment. The list of societal parameters presented in Figure 1 reflects the functional requirements of a residential building, according to national construction codes.
The economic performance parameters were defined in order to include all costs related to a building’s life-cycle, from cradle to grave. The economical performance analysis is not complete unless the residual value is evaluated. The residual value of a system (or component) is the market value of it at the end of its service life, or at the end of the study period.
3.4. Quantification of Parameters
After selecting the parameters, it is necessary to proceed with their quantification. Quantification is essential for comparing different solutions, aggregating parameters, and accurate assessing solutions. The quantification method should be anticipated. There are several quantification methods: previous studies results, simulation tools, expert opinion, databases processing, etc. [13].
At the level of the quantification of the environmental parameters, there are some aspects to overcome. These aspects mainly deal with the availability of fundamental local LCI environmental data for all construction materials and products used in buildings. While there is no local LCI data, it is possible to use the information given in Environmental Products Declarations (EPDs) and other LCI databases from nearby countries. Another way is to use an external life-cycle assessment (LCA) tool to quantify the environmental parameters.
After quantifying the economic parameters listed in Figure 3, the next step is to calculate the sum of the total net present value (NPV) of the different costs. This sum will result in just one economic performance parameter: life-cycle costs.
3.5. Normalization of Parameters and Aggregation
The objective of the normalization of parameters is to avoid the scale effects in the aggregation of parameters inside each indicator and to solve the problem that for some parameters, “higher is better” while for others, “lower is better”. Normalization is done using the Diaz-Balteiro [14], Equation 1.
In this equation, Pi is the value of ith parameter. P*i and P*i are the best and standard values of the ith sustainable parameter, respectively. The best value of a parameter represents the best practice available and the worst value represents the standard practice or the minimum legal requirement.
Normalization, in addition to turning dimensionless the value of the parameters considered in the assessment, converts the values into a scale bounded between 0 (worst value) and 1 (best value). This equation is valid for both situations: “higher is better” and “lower is better”.
As stated before, building sustainability assessment across different fields involves the use of numerous indicators and tens of parameters. A long list of parameters with their associated values will not be useful for assessing a solution. The best way is to combine parameters with each other inside each dimension in order to obtain the performance of the solution in each indicator [15].
The methodology uses a complete aggregation method for each indicator, according to Equation 2.
iniijPwI.1Σ==
(2)
The indicator Ij is the result of the weighting average of all the normalized parametersiP; wi is the weight of the ith parameter. The sum of all weights must be equal to 1.
Difficulties in this method lie in the setting of the weight of each parameter and in the possible compensation between parameters. Since weights are strongly linked to the objectives of the project and to the relative importance of each parameter in the assessment of each indicator, higher weights must be adopted for parameters of major importance in the project. The possible compensation between parameters is limited inside each indicator.
Table 1. Relative importance weig