Unraveling nonlinear and interaction effects of various determinants on bus gaseous emissions.

Urban transit buses equipped with large-displacement engines operate on circular routes several times throughout the day, emitting large amounts of environmentally hazardous exhaust. Hence, understanding the intricate associations between bus emissions and multiple contributors is beneficial for creating sustainable transportation systems, while previous studies focusing on statistical methods fail to unravel them. This paper innovatively leverages the bagged decision tree approach to delineate such complex relationships based on the data collected from CNG-fueled and diesel-powered buses.