Optimizing landfill gas emissions mitigation in Kuwait: Waste-to-energy solutions enhanced by machine learning integration

Rapid population growth and increasing waste generation are intensifying municipal solid waste (MSW) management challenges in Kuwait. Annual MSW production exceeds 2.5 million tons, with cumulative waste expected to reach approximately 61.6 million tons between 2018 and 2038, placing substantial pressure on non-engineered landfills and exacerbating greenhouse gas (GHG) emissions. This study evaluates national-scale waste-to-energy (WtE) strategies—landfill gas (LFG) recovery and incineration—to mitigate environmental impacts and enhance energy recovery. The U.S. EPA LandGEM model was integrated with five machine learning algorithms (Decision Tree, Support Vector Machine, Random Forest, Neural Network, and Gradient Boosting) to improve methane generation predictions. The optimized Gradient Boosting model reduced prediction error from ∼25 % to < 8 % and achieved ∼95 % accuracy, enabling reliable 20-year power forecasts. Three WtE scenarios were assessed: (A1) incineration-only, (A2) full LFG recovery, and (A3) a hybrid system combining both technologies. Scenario A1, represented by the Kabd WtE facility, treats roughly 1.2 million tons of MSW annually and generates ∼650 GWh/year. Scenario A2 achieves a maximum of ∼6.48 × 10⁵ MWh/year and sustains energy recovery for decades after landfill closure. The hybrid Scenario A3 delivers the strongest performance, producing an average of ∼8.2 × 10⁵ MWh/year and reaching a peak of ∼865 GWh/year—equivalent to ∼3 % of Kuwait’s residential electricity demand—while reducing GHG emissions by ∼48 %. The economic assessment, incorporating avoided landfill operating costs, reduced landfilled tonnage, and electricity revenues, indicates that the hybrid WtE system could yield annual savings of approximately US$30 million while enabling electricity export to neighboring regions. These results demonstrate that ML-enhanced LFG modeling, combined with a hybrid WtE system, can shift Kuwait’s MSW management from disposal-oriented practices toward an integrated resource-recovery framework, offering a scalable model for other rapidly urbanizing arid regions.