Scenario-Based Simulation Model for Assessing the Electrification of Urban Rickshaw Fleets in Nepal: A Study of Dharan City

Abstract

This study develops a dynamic, scenario-based simulation model to evaluate the techno-economic and environmental viability of transitioning urban rickshaw fleets from petrol to electric in Dharan, Nepal—a representative secondary city experiencing rapid urbanization. Integrating fleet dynamics, emission accounting, and total cost of ownership (TCO) within a Python-based Monte Carlo framework, the model assesses outcomes under Baseline, Conservative, and Policy Accelerated scenarios from 2016 to 2040. Findings reveal that the Policy Accelerated pathway, characterized by robust subsidies, fuel taxation, and synchronized grid decarbonization, can achieve up to 95% fleet electrification by 2040. This transition reduces well-to-wheel CO₂, PM_2.5, and NO_x emissions by 72%, 91%, and 78% respectively, while also cutting the lifetime cost of e-rickshaws by 39% compared to business-as-usual. Economically, e-rickshaws achieve a positive net present value (NPV) of NPR 0.7 billion with an operator payback period of 5-7 years. Sensitivity analysis identifies fuel taxes and purchase incentives as the most effective policy levers. The results underscore that the greatest climate and health benefits are realized through an integrated strategy that concurrently targets vehicle electrification and power sector decarbonization. This study provides a replicable analytical framework and evidence-based policy roadmap for sustainable urban mobility in developing economies.