Comprehensive Methods for Dealing with Uncertainty in Assessing Sustainability Part 1: The MIVES – Monte Carlo Method

Comprehensive Methods for Dealing with Uncertainty in Assessing Sustainability Part 1: The MIVES – Monte Carlo Method

M. Pilar de la Cruz (University of La Coruña, Spain), Alberto Castro (University of La Coruña, Spain), Alfredo del Caño (University of La Coruña, Spain), Diego Gómez (Intacta Gestión Ambiental, Spain), Manuel Lara (University of La Coruña, Spain) and Juan J. Cartelle (University of La Coruña, Spain)
DOI: 10.4018/978-1-4666-6631-3.ch004
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Abstract

Integrated Value Method for Sustainability Evaluation (MIVES) is a deterministic method based on requirement trees, value functions, and the Analytic Hierarchy Process. It allows integrating environmental, social, and economic sustainability indicators in a global index. The value functions make it possible to consider non-linearity in the assessment. MIVES takes into account the relative weight of the various model indicators. Deterministic models can cause significant problems in terms of adequately managing project sustainability. A method not only has to estimate the sustainability index at the end of the project. It also has to evaluate the degree of uncertainty that may make it difficult to achieve the sustainability objective. Uncertainty can affect indicators, weights, and value function shapes. This chapter presents a method for sustainability assessment, taking into account uncertainty. It is based on MIVES and the Monte Carlo simulation technique. An example of potential application is proposed, related to power plants.
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Introduction

Sustainable development can be defined in various ways, depending on the analytical standpoint. The most commonly accepted guidelines were introduced by the United Nations in 1987 and enshrined in the Brundtland Report (United Nations Organization, 1987). According to this document, development is deemed sustainable when it satisfies present needs without compromising the capacity of future generations to satisfy their own needs. In a faithful interpretation of the Río Declaration on the Environment and Development (United Nations Organization, 1992), human beings are said to have the right to a healthy and productive life in harmony with nature. Consequently, the declaration covers aspects related to the economy (productive life), society (healthy life) and the environment (in harmony with nature).

In this chapter and the following one, when sustainability is mentioned, it will be understood that this term embraces these three pillars. This means that a range of aspects must be taken into account; some of them are qualitative, and others, quantitative, measured with different units. It is necessary to carry out an assessment to determine if an activity makes a greater, lesser, or equal contribution to sustainability than others do.

The MIVES method (Integrated Value Method for Sustainability Evaluation) is a combination of techniques based on a requirement tree (Gómez et al., 2012a) (Figure 2), value analysis (Alarcón et al., 2011), and the Analytic Hierarchy Process (AHP) (Saaty, 1980, 2006). Conventionally, sustainability assessment is done by performing life-cycle analysis (LCA) (Graedel, 1998, International Organization for Standardization, 2002, 2006a, 2006b; Matthews et al., 2002). The result of LCA is a set of assessments related to climate change (measured in equivalent CO2 emissions per unit of product), acidification (equivalent SO2 emissions), or eutrophication (equivalent PO43-), among other many aspects. MIVES is used to transform different types of variables, measured with different units, into the same unit. It makes it possible to consider non-linearity in the assessment. Moreover, it takes into account the relative importance of the different aspects included in that evaluation. Finally, it helps to integrate environmental, social, and economic sustainability indicators in a single, global sustainability index. For this reason, it is useful to compare the various design alternatives and choose those that contribute most to sustainable development.

The majority of assessment models currently used are based on a weighted scoring system for different sustainability indicators. Research is being done at the moment on more sophisticated alternatives, such as through fuzzy mathematics or fuzzy logic, or AHP, among others.

Among these is the MIVES method. It has been used to evaluate the sustainability of structural systems (Aguado et al., 2012; Gómez et al., 2012b), as well as buildings (Cuadrado et al., 2012; San José & Cuadrado, 2010; San José & Garrucho, 2010), building subsystems (Pons & Aguado, 2012), and aspects of health and safety in construction (Reyes et al., 2014), to name but a few. In reality, it is a generic methodology that can be applied to any decision-making process. The first objective of this chapter is to provide readers with an overview of all the technique encompassed by the MIVES method.

It is important to bear in mind that MIVES is a deterministic method; it does not allow one to consider the uncertainty that could affect the variables included in sustainability assessment models. Uncertainty does indeed exist: in the value of the inputs or sustainability indicators, their weighting, and the geometry of the value functions that will subsequently be explained. Until now methods have been established for considering the uncertainty in indicators (del Caño et al., 2012), but not in the other variables. The second objective in this chapter is to explain how to generalize this method so that it can embrace every kind of variable found in a MIVES model. This method will now be referred to as the MIVES-Monte Carlo method.

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