Table 1.
Basic properties of selected urban expressway.
Fig 1.
Representation of Ningbo urban expressway network and the position of each traffic checkpoint.
(Base map and data from OpenStreetMap and OpenStreetMap Foundation).
Table 2.
Conversion coefficient of gasoline.
Fig 2.
Histograms for different values of network traffic density in June 20, 2022.
(a) K = 10veh/km-ln. (b) K = 15veh/km-ln. (c) K = 20veh/km-ln.
Fig 3.
The relationship between network flow and density (left) and the relationship between network density heterogeneity and density (right) for different directions of expressways. (a),(b) the east-west direction of NanHuan. (c),(d) the west-east direction of NanHuan.
Fig 4.
CE-MFD in different directions of expressways.
(a) the east-west direction of NanHuan. (b) the west-east direction of NanHuan. (c) the north-south direction of JiChang. (d) the south-north direction of JiChang.
Fig 5.
The data are distinguished according to the standard deviation.
(a) relationship between the average network flow and the average network traffic density. (b) network emissions and the average network traffic density.
Fig 6.
The data are distinguished according to the total number of links in the network I.
(a) relationship between the average network flow and the average network traffic density. (b) network emissions and the average network traffic density.
Fig 7.
Impact of BEV penetration on emissions under different road network heterogeneity.
Table 3.
Traffic emissions for different network heterogeneity and BEV penetration rate.