Contemporary global policy, driven by concern for the environment, imposes increasingly stringent goals for reducing CO2 emissions. Therefore, there is an urgent need to develop effective models that allow an accurate prediction of CO2 emissions from vehicles powered by alternative fuels such as CNG. This article presents the process of creating one of the first models of CO2 emission for a vehicle powered by CNG. Emission modelling is based on data obtained from chassis dynamometer tests and road tests using the portable emission measurement system (PEMS). CO2 emission modelling was conducted in Python programming language using the Optuna framework for the XGBoost technique. The models obtained were validated, with indicators R2 0.9 and RMSE 0.49 for data from chassis dynamometer tests, and R2 0.7, RMSE 0.71 for road test data. This work has the potential to be used by transportation decision makers involved in environmental analyses and policymaking for urban areas.

This study examines the dynamic fluid behavior of a PWM-controlled Solenoid-Operated Gas Admission Valve (SOGAV) for large-bore CNG engines using 3D CFD simulations with dynam-ic mesh techniques. The research focuses on the influence of orifice geometry variations in the multi-hole restrictor and pressure differentials between the inlet and outlet on flow stability, turbulence, and valve performance. Results demonstrate that multi-hole restrictors with differ-ent-sized orifices improve flow uniformity and reduce turbulence, thereby mitigating flow re-sistance. Transient simulations further reveal standing wave formation and pressure wave in-terference, emphasizing that steady-state models cannot capture critical transient phenomena, such as accelerated and decelerated jet-like flows and flow separation. These findings provide key insights into SOGAV optimization, contributing to enhanced fuel efficiency and engine re-sponsiveness, meeting the performance requirements of modern gas engines.