Development of a Waste Generation Prediction Model Using Independent Macro Variables in Various Sectors (Case Study: Tehran)

According to statistics from the Ministry of Interior of Iran, more than 75% of the waste produced in the country is landfilled. Many of the programs proposed by waste management organizations and municipalities have not been effective due to the failure to consider the impacts of various economic and non-economic variables on waste generation. Therefore, this study aims to increase the effectiveness of proposed waste management programs for Tehran in line with sustainable development. An empirical modeling approach was used, utilizing 120 months of data (April 2011 to March 2021) to develop models for predicting different types of waste generation. Additionally, the statistical relationship between 32 macroeconomic variables, including industry and mining, agriculture, urban management, population, and climate, and five waste generation variables was examined at a 90% confidence level. The results indicate that 79% of the variations in the total waste generation tonnage, 73.4% of the variations in the mixed waste tonnage at the source, 80.3% of the variations in the separated dry waste tonnage at the source, and 81.4% of the variations in the construction and demolition waste tonnage in Tehran can be predicted using the models developed in this study.