This study investigated the impact of driving style and traffic condition on emissions and fuel consumption using a selected range of real-world transient drive cycles, using both diesel and a diesel-biodiesel blend on a turbocharged diesel engine. Using 30 drivers, six different transient cycles were developed based on different driving styles (timid, normal and aggressive) and traffic conditions (off-peak and peak hour) from real-world measurements performed in an urban driving environment (e.g., urban road, motorway, school zone, residential area, hospital zone, and city centre) using the guidelines presented in the US Code of Federal Regulations, Title 40, Part 86. In this paper, engine operating parameters (engine speed and load), gaseous emissions (NO x , CO and CO 2 ), particulate matter emissions (PM and PN), and fuel consumption were investigated in relation to driving style, traffic condition and fuel type, using different data analysis methods such as Kernel density estimation (KDE) and Analysis of variance (ANOVA). The investigation revealed that engine behaviour during real-world transient operation is entirely different from steady-state operation, which results in significantly high emissions. Driving style has a strong influence on emissions, evident from emission results as well as ANOVA analysis. Aggressive driving generates a higher number of transient micro-trips which ultimately results in an overshoot in emissions. A moderate increment in CO 2 and NO x emissions (up to 37% and 38% respectively) and a high increment in CO emission (up to 88%) was observed for the aggressive cycles. PM and PN emission increased significantly (up to 112% and 538% respectively) for aggressive cycles. Biodiesel showed a promising impact in PM and PN emission reduction (up to 71% PM and 68% PN respectively) regardless of the driving style and traffic condition. In general, off-peak cycles demonstrated more severe results for real-world transient emission generation because of comparatively higher sharp acceleration and turbocharger lag events. Fuel consumption is dominated by traffic conditions where peak hour cycles increased the brake-specific fuel consumption
