Physical properties of particulate matter (PM) from late model heavy-duty diesel vehicles operating with advanced PM and NO x emission control technologies

Emission control technologies designed to meet the 2007 and 2010 emission standards for heavy-duty diesel vehicles (HDDV) remove effectively the non-volatile fraction of particles, but are comparatively less efficient at controlling the semi-volatile components. A collaborative study between the California Air Resources Board (CARB) and the University of Southern California was initiated to investigate the physicochemical and toxicological characteristics of the semi-volatile and non-volatile particulate matter (PM) fractions from HDDV emissions. This paper reports the physical properties, including size distribution, volatility (in terms of number and mass), surface diameter, and agglomeration of particles emitted from HDDV retrofitted with advanced emission control devices. Four vehicles in combination with six after-treatment devices (V-SCRT®, Z-SCRT®, CRT®, DPX, Hybrid-CCRT®, EPF) were tested under three driving cycles: steady state (cruise), transient (urban dynamometer driving schedule, UDDS), and idle. An HDDV without any control device is served as the baseline vehicle. Substantial reduction of PM mass emissions (>90%) was accomplished for the HDDV operating with advanced emission control technologies. This reduction was not observed for particle number concentrations under cruise conditions, with the exceptions of the Hybrid-CCRT® and EPF vehicles, which were efficient in controlling both—mass and number emissions. In general, significant nucleation mode particles (<50nm) were formed during cruise cycles in comparison with the UDDS cycles, which emit higher PM mass in the accumulation mode. The nucleation mode particles (<50nm) were mainly internally mixed, and evaporated considerably between 150 and 230°C. Compared to the baseline vehicle, particles from vehicles with controls (except of the Hybrid-CCRT®) had a higher mass specific surface area. [Copyright &y& Elsevier]