Investigation of municipal solid waste forecasting, electricity generation from biogas, and greenhouse gas mitigation potential using a BILSTM-Based deep learning model: The case of Sirnak province

Rapid population growth, urbanization, and changing consumption patterns have led to a continuous increase in Municipal Solid Waste (MSW) quantities, making sustainable waste management and the assessment of environmental benefits such as energy recovery increasingly essential. Particularly, biogas production and electricity generation from MSW contribute to reducing Greenhouse Gas (GHG) emissions by decreasing fossil fuel consumption. This study aims to forecast MSW quantities for the period 2025–2045 in the province of Şırnak using the BiLSTM deep learning model, and to examine the biogas production potential, electricity generation capacity, and GHG emission impacts based on these forecasts. The model was developed in Python using annual MSW data for Şırnak from 2007 to 2024, along with a dataset consisting of 12 financial, social, and demographic variables. The dataset was split into 80% for training and 20% for testing. After training the model with the 2007–2024 data and performing hyperparameter optimization, a low Mean Absolute Percentage Error (MAPE) of 3.83% was achieved, while 5-fold cross-validation yielded an average MAPE of 7.99%. These results indicate that the model has high accuracy and reliability. Forecast results show that MSW quantities, which are approximately 298,090 tons in 2025, are projected to reach around 825,929 tons by 2045-an increase of 63.9%. According to LandGEM-based calculations, methane production potential is projected to rise from about 2.47 million m³ in 2025 to 6.86 million m³ in 2045. Under the assumption of a 75% methane collection efficiency, approximately 1.85 million m³ and 5.14 million m³ of methane can be recovered in 2025 and 2045, respectively. The electricity generation potential is estimated at 5,157 MWh for 2025 and 14,315 MWh for 2045, with a cumulative generation of approximately 225,478 MWh. The optimum installed capacity of the biogas power plant was calculated as 1.63 MW. Furthermore, the use of biogas is projected to prevent an average of 141,375 tons of CO₂-equivalent GHG emissions compared to fossil fuels. The findings demonstrate that BiLSTM-based MSW forecasting is a reliable tool for waste management and energy planning, that biogas utilization contributes to reducing environmental impacts by replacing fossil fuels, and that the resulting electricity generation supports a sustainable waste-to-energy conversion approach.