$C{O}_2$ Emission based prioritization of bridge maintenance projects using neutrosophic fuzzy sets based decision making approach

Abstract

Climate change is one of the most challenging problems for the world, which leads researchers to study on the decrease of its impact to the environment at several disciplines. One of the most adverse effects on environment can be observed in transportation area. Hence, in this paper, the impact of bridge maintenance on the environment is inquired in the bridge maintenance prioritization perspective. The aim of this paper is to rank the bridge maintenance projects using type-2 neutrosophic number (T2NN) based fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) and TOPSIS (Technique For Order Preference By Similarity To An Ideal Solution) to test five alternative bridges, where a critical environmental criterion is introduced in this model, which addresses to additional $C{O}_2$ emission because of truck detours in the event of a bridge closures. The applicability of the proposed model is demonstrated in a case study in Turkey. The evaluation findings show that the ranking results are robust and the $C{O}_2$ emission criterion is found to be the dominant criterion in the multi-criteria decision-making model proposed in this paper.

Introduction

Climate change is one of the most challenging problems in today's world. As one of the most generated greenhouse gasses (GHG), carbon dioxide $\left(C{O}_2\right)$ has an increasing effect on global warming (Ritchie & Roser, 2017). The USA has one of the highest $C{O}_2$ emissions per capita (Ritchie & Roser, 2017) and it continues to increase each year. Even though the U.S. Energy Information Administration (EIA) projects that total $C{O}_2$ emissions will decrease until 2020 because of the change from fuel to electricity ¹ the world $C{O}_2$ emissions are expected to increase by the end of 2050 especially among non-OECD member countries (Marchal et al., 2011).

The construction sector is responsible for 39% of $C{O}_2$ emissions in 2018, including the manufacturing of the materials (Guggemos & Horvath, 2005). Besides, the substantial usage of nonrenewable energy makes the construction sector even more critical, and there is room for further improvements to reduce $C{O}_2$ emissions created by the construction industry (BIS, 2010; Levermore, 2008). Therefore, life cycle analysis (LCA) is an important concept for the construction industry and was investigated in recent years. Yet, the focus of LCA analysis in the sector is buildings rather than infrastructure facilities (Atmaca & Atmaca, 2015; Guggemos & Horvath, 2005; Kua & Maghimai, 2017; Levermore, 2008; Stephan & Stephan, 2016).

Here, another important source of $C{O}_2$ is the materials used that ranges from the substitution of the materials such as asphalt (Mladenovič et al., 2015), sand (Kua, 2013), and even cement (Crossin, 2015). In the US to minimize the environmental damages of bridge paints, new coating systems are developed (Itoh & Kitagawa, 2003). A study discusses the different $C{O}_2$ emissions of steel and concrete and found that reinforced concrete has lower embodied energy depending on the case (Kua & Maghimai, 2017). Another study investigates the usage of alternative structural systems extensively by considering many elements such as materials, transportation, and fuel emissions (Cole, 1998).

The concept of embodied energies is especially important for infrastructures such as roads, bridges, and tunnels because they are the reason for over 90% of life cycle emissions (Huang et al., 2015; Stephan & Stephan, 2016). The LCA studies test that infrastructure construction is mainly based on material use (Huang et al., 2015). The same applies to maintenance activities. The operational energy that includes the heating, cooling, etc. of the building covers most of the $C{O}_2$ emissions of a building. Yet, for a bridge, this stage does not include many aspects. Therefore, the major source of $C{O}_2$ emissions is the construction and maintenance of the bridges. In this paper, the $C{O}_2$ emission is much more tested as an additional fuel consumption because of truck detours.

Testing alternatives should not only base on traditional cost evaluation methods. Instead, it should consider environmental costs as an important parameter. In this perspective, this study aims to develop a multi-criteria decision-making (MCDM) methodology to assess the bridge maintenance projects based on their $C{O}_2$ emissions. Especially, in the analysis section of this paper, it is shown that the highest importance weight among the criteria is assigned to the $C{O}_2$ emissions by the decision-makers, which also supports the claim of this paper. One contribution of this paper is to propose a new model to assess different maintenance projects by taking the environment into the heart of the methodology.

This study proposes a new hybridizing type-2 neutrosophic number (T2NN) based fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) and TOPSIS (Technique For Order Preference By Similarity To An Ideal Solution) model to prioritize the bridge maintenance projects. One of the major contributions of this study is to present a prioritizing tool using expert knowledge. Another contribution is to develop a hybrid MCDM model named fuzzy T2NN based WASPAS and TOPSIS that enables the alternative evaluation from qualitative and quantitative information and provides the best alternative for decision-makers.