Effects of highway alignment on real-world vehicle emissions under expressway conditions

Roadway alignment can affect vehicle operation and real-world exhaust emissions, but evidence for expressway conditions remains limited beyond longitudinal grade. This study examined second-by-second CO and NOx emissions from a China VI light-duty gasoline vehicle using PEMS data collected over a 62.4 km expressway route. Six alignment variables were evaluated: longitudinal slope gradient, cross slope gradient, horizontal curve radius, horizontal curve length, vertical curve radius, and vertical curve length. Grouped comparison, pairwise correlation, speed-coupled visualization, vehicle specific power (VSP) analysis, and spatially grouped machine-learning interpretation were applied. Within the tested vehicle-route case, longitudinal slope gradient showed the strongest and most consistent association with both pollutants, while larger horizontal curve radii were generally associated with lower emissions. VSP was positively associated with both pollutants, supporting a power-demand-related interpretation of the grade response. The grouped machine-learning models showed modest out-of-spatial-block predictive performance, while SHAP analysis identified recurring multivariable associations within the tested vehicle–route case. The findings provide empirical evidence for understanding alignment-related emission responses under expressway operation, although their applicability to other vehicle types and road environments warrants further investigation.