Assessment of Vehicle Emission Inventories at Urban Roads using Principal Component Analysis

Abstract

The study endeavored to develop the vehicle emission inventory by analyzing quantity, quality and probable sources of pollutants in the atmosphere of two different road segments of Dhaka city. One road is a major arterial road (R1), where traffic comprises with large portion of motor cars and another road is a national highway (R2), where traffic comprises with heavy vehicles, such as, buses, trucks and freight vehicle. Vehicle emission monitoring revealed that CO2 shared more than 99% of total air pollutants, which is a major greenhouse gas resulting global warming. Two models were proposed to estimate vehicle emission inventory using Principal component analysis (PCA), where PCA1 and PCA2 were developed for the vehicle emission inventory of R1 and R2 road respectively. Each of the model have two components, where first component comprised with particulate matter PM10, SO2, black and organic carbon and second component comprised with CO2 and CH4 gases. The PCA1 and PCA2 can explain 96.28% and 98.63% variability of measured dataset respectively. The proposed technique can help the concerned authority to explore vehicle emission inventory with better accuracy.