No abstract

During last decade, design for deconstruction (DfD) has attracted the attention of researchers and project managers as an environmentally friendly alternative to the conventional demolition of buildings. Yet, the intensity of raw materials consumption, waste generation and greenhouse gas (GhG) emission in the construction industry proves that current methods of selecting building components have failed to make the deconstruction effectively feasible. Specifically, in the material selection process, most research studies concentrate on assessing environmental and economic aspects while in selecting material for DfD various factors must be considered. To overcome this gap, this study aims to propose a DfD-based material selection model which enables designers to choose materials that make the recyclability and reusability of building components feasible. To this end, the Kano model is first applied to categorize selection criteria identified via a questionnaire. After extracting the weights of criteria by using Fuzzy-Analytical Hierarchy Process, a Technique for Order Preference by Similarity to the Ideal Solution-based multi-criteria decision-making framework is proposed for choosing the best possible alternatives. Based on the research results, the framework enables designers to find decent materials in terms of DfD requirements. A numerical example is also provided to examine the proposed framework for selecting the most appropriate materials for walls.

Construction and Demolition Waste (CDW) has recently received significant attention in the most developing countries, such as Iran. Since CDW generation is unavoidable, so development and implementation of an appropriate CDW management is widely recognized as an essential need. Different alternatives in CDW management have been proposed and implemented currently. In this study, a novel framework was established based on the Fuzzy Analytic Hierarchy Process approach in order to assess different CDW management alternatives in Tehran, Iran. Proposed alternatives (including landfilling, recycling, reusing, and reduction) were investigated with respect to 16 different individual criteria. The criteria were divided into four different groups, namely environmental, social, technical, economic. A database in this study was established through a questionnaire survey. The relative significance of alternatives with respect to each criterion was assessed. The obtained results revealed that reduction has the highest and landfilling has the lowest priorities. Furthermore, it was found that economic criteria have the highest and social criteria have the lowest importance among the studied criteria. Also, the proposed framework can be used as a beneficial tool that will assist decision-makers in determining the most suitable CDW management alternatives in the case of different criteria that are completely/partially in conflict.

No abstract

Landfilling of municipal solid waste (MSW) is one of the serious environmental concerns as improper location of MSW landfill site can release the pollutants into the surrounding environment. The process of selecting MSW landfill site is a complicated decision making problem since it is subjected to simultaneous assessment of several environmental criteria, rules, and restrictions besides sociocultural and economic ones. The current study suggests a framework based on Multicriteria spatial decision support systems (MC-SDSS) to select landfill site. The MC-SDSS is an advanced method to integrate multiple criteria decision analysis (MCDA) and geographical information systems (GIS) techniques. This approach enables the incorporation of several conflicting objectives and preferences into spatial decision models. In this study, 14 criteria were chosen and then divided into environmental, sociocultural, and economic categories. Finally, suitability maps were generated based on the MC-SDSS analysis. The developed method was implemented in a real case study in Arak city in northwestern region of Iran, which is environmentally sensitive area. The suitability maps of the case study in Arak showed that 10% (391 km) is least suitable area, 23% (942 km) is low suitable, 37% (1507 km) is moderate suitable, 19% (783 km) is suitable, and 11% (489 km) is most suitable locations for landfill site, and finally, three best alternative sites were introduced for the final landfill site.