Dynamic System Modeling of PM₂.₅ Emissions and Concentrations in DKI Jakarta Based on BAU, Moderate, and Aggressive Scenarios

Background: Rapid urbanization, increasing motor vehicle use, and high dependence on fossil-based energy sources have contributed to persistently elevated PM₂.₅ concentrations. Although various policies have been implemented, their long-term effectiveness under different intervention levels has not been sufficiently evaluated using an integrated and dynamic approach. Objective: This study aims to develop a system dynamics model to project PM₂.₅ emissions and concentration trends in DKI Jakarta up to 2040 under three scenarios: Business as Usual (BAU), Moderate, and Aggressive intervention. Method: A system dynamics modeling approach was employed by integrating key variables, including motor vehicle growth, electric vehicle (EV) adoption, electricity consumption, renewable energy penetration, and industrial activity. The model was calibrated using historical data from 2018 to 2023. Three scenarios were simulated: BAU without additional intervention, Moderate with approximately 20% EV penetration and a 30% renewable energy mix, and Aggressive with EV penetration of ≥50% and a renewable energy mix of ≥70%. Result: Under the BAU scenario, PM₂.₅ concentrations decline only marginally (approximately ±40% by 2040). The Moderate scenario achieves approximately ±60% reduction, though insufficient to meet optimal air quality standards. The Aggressive scenario demonstrates the most substantial impact, with reductions reaching approximately ±80%. Conclusion: Aggressive policy interventions combining high EV penetration and substantial renewable energy adoption are essential for significant PM₂.₅ reductions in DKI Jakarta. System dynamics modeling provides a robust framework for evaluating long-term air quality policies and supporting evidence-based decision-making.