نوع مقاله : یادداشت فنی
دانشکدهی مهندسی عمران، دانشگاه صنعتی شریف
عنوان مقاله [English]
Nowadays, mass production of construction waste is one of the most important environmental issues. Construction industry consumes a large amount of materials and resources, especially in developing countries. Inefficient usage of bulk materials results in production of construction waste. According to sustainable development guidelines, mass production of construction waste is one of the issues of focused concern. In Iran, there is no clear record or valid data about different aspects of construction waste production. Quantification of the construction waste production is one of the new concepts in waste management. Therefore, the aim of this research is to quantify construction waste production of bulk materials in residential buildings. The focus of this study is on rebar, concrete, brick, and cement waste produced in the buildings.The urban developers may utilize the results to regulate more detailed and precise rules to control the production of construction waste. The dependent variable of the study is the amount of waste produced for every type of material in percent. The independent variables of the study are location of residential buildings, type of contract, area of every story, and number of stories in every residential building. Furthermore, two frequent types of contracts for residential buildings cost-plus and lump-sum contracts are investigated. Obtained data is analyzed by SPSS software using linear regression, and then are verified and validated to extract the best and most convenient regressions. The criteria for validation and verification of the quantitative equations are derived from statistical references and the most recent and related studies. The result is four valid and verified quantitative models describing the amount of waste materials produced in terms of independent variables. Results show that choosing cost-plus contract leads to more construction waste production than lump-sum contract. The positive and negative effects of other dependent variables, such as location, number of stories, or area of each story are determined too.