Proposed estimation models for electronic waste (e-waste) quantities under limited data and uncertainty

Along with technological changes and developments, electronic waste (e-waste) generation has increased rapidly in recent years. Therefore, estimating the amount of e-waste generation has become essential for e-waste management. However, the uncertainty of e-waste generation and product lifespans and the limited e-waste data make e-waste estimation difficult. Three different methodological approaches are presented for e-waste estimation with the scope of this thesis: First, the Improved Carnegie Mellon (GCM) method based on input-output analysis is proposed. In this model, e-waste estimation is modelled by considering the product lifespan is variable according to the sales year of the product, unlike the classical Carnegie Mellon method. Secondly, a systematic forecasting approach is proposed for e-waste generation, and this approach is applied in Turkey's waste mobile phone (ACT) estimation and forecasting for 2001-2035. The proposed approach considers sales data and dynamic product lifespan and selects the best-performing model using alternative time series models while forecasting. Subsequently, material quantities and revenue potentials are calculated. With the proposed approach, it is forecasted that the amount of ACT to be generated in Turkey will exceed 11.5 million and have a revenue potential of fifty-two million dollars in 2035. Thirdly, Trigonometry Based Discrete Grey Model (TBDGM(1,1)) is proposed for e-waste estimation. The proposed model generated successful results thanks to its ability to model the e-waste generation with nonlinear data structure with trigonometric expressions and to optimize the model parameters with a metaheuristic algorithm. Using this model, Turkey's e-waste generation is modelled, and the amount of e-waste generation is forecasted for 2021-2030. As a result, it is expected that the proposed models and approaches within the scope of the thesis will contribute to all stakeholders involved in the e-waste management process in strategic and tactical level decisions.