Predicting E-Waste Trajectory: A Comparative Analysis
摘要
E-waste is being reckoned as the part of hazardous refuse growing fastest worldwide. Precise estimation of E-waste levels may lead to more efficient disposal processes. This study conducts a comparative analysis of global and Indian E-waste generation, examining past and future trends using time series forecasting models such as Auto ARIMA, LGBM Regressor, XGB Regressor, Random Forest Regressor, and Time GPT. The forecast extends to 2032. Among the models, XGB Regressor consistently showed the lowest error metrics, making it the preferred model for predicting per capita E-waste generation. The study forecasts that global E-waste generation will reach 84.47 MT by 2032, while India’s E-waste will rise to 7.269 MT. India’s share of global E-waste is projected to increase from 6.61% in 2022 to 8.61% by 2032, whereas the U.S. is expected to see a decline from 11.45% in 2019 to 9.72% by 2032. India may also advance from third to second place globally in E-waste generation in the near future.