Kumar Atul, Samadder S R
Department of Environmental Science & Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India.
Department of Environmental Science & Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India.
Waste Manag. 2017 Oct;68:3-15. doi: 10.1016/j.wasman.2017.07.034. Epub 2017 Jul 27.
Accurate prediction of the quantity of household solid waste generation is very much essential for effective management of municipal solid waste (MSW). In actual practice, modelling methods are often found useful for precise prediction of MSW generation rate. In this study, two models have been proposed that established the relationships between the household solid waste generation rate and the socioeconomic parameters, such as household size, total family income, education, occupation and fuel used in the kitchen. Multiple linear regression technique was applied to develop the two models, one for the prediction of biodegradable MSW generation rate and the other for non-biodegradable MSW generation rate for individual households of the city Dhanbad, India. The results of the two models showed that the coefficient of determinations (R) were 0.782 for biodegradable waste generation rate and 0.676 for non-biodegradable waste generation rate using the selected independent variables. The accuracy tests of the developed models showed convincing results, as the predicted values were very close to the observed values. Validation of the developed models with a new set of data indicated a good fit for actual prediction purpose with predicted R values of 0.76 and 0.64 for biodegradable and non-biodegradable MSW generation rate respectively.
准确预测家庭固体废物产生量对于城市固体废物(MSW)的有效管理至关重要。在实际操作中,建模方法通常被证明有助于精确预测城市固体废物产生率。在本研究中,提出了两个模型,它们建立了家庭固体废物产生率与社会经济参数之间的关系,如家庭规模、家庭总收入、教育程度、职业和厨房使用的燃料。应用多元线性回归技术开发了这两个模型,一个用于预测印度丹巴德市单个家庭的可生物降解城市固体废物产生率,另一个用于预测不可生物降解城市固体废物产生率。这两个模型的结果表明,使用选定的自变量,可生物降解废物产生率的决定系数(R)为0.782,不可生物降解废物产生率的决定系数为0.676。所开发模型的准确性测试显示出令人信服的结果,因为预测值与观测值非常接近。用一组新数据对所开发模型进行验证表明,对于实际预测目的,该模型拟合良好,可生物降解和不可生物降解城市固体废物产生率的预测R值分别为0.76和0.64。