Effective Density and Volatility of Particles Emitted from Gasoline Direct Injection Vehicles and Implications for Particle Mass Measurement

Abstract

The effective density and volatility of particulate emissions from five gasoline direct injection (GDI) passenger vehicles were measured using a tandem differential mobility analyzer (DMA) and centrifugal particle mass analyzer (CPMA) system. The measurements were conducted on a chassis dynamometer at three steady-state operating conditions. A thermodenuder was employed to find the volatility and mixing state of the particles as well as the effective density of nascent and non-volatile particles (defined as particle phase remaining after denuding at 200 C). The mass-mobility exponent ranged between 2.4 and 2.7 for nascent (or undenuded) particles and between 2.5 and 2.7 for non-volatile particles; higher than typical diesel soot. The effective density function was 4278d m ¡0.438 § 76.3 kg/m 3 (for mobility diameter, d m , in nm) for nascent particles and 3215d m ¡0.395 § 37.9 kg/m 3 for non-volatile particles. The effective density functions of the non-volatile particles were fairly similar for the conditions studied. The uncertainty in using the effective density and mixing state data to determine the mass concentration of the aerosol by integrating mobility size distributions was examined. The uncertainty in mass concentration is minimized when only the non-volatile component is measured. However, the uncertainty in the mass concentration increases substantially if nascent particles are measured due to uncertainties in the particle mixing state and their associated effective densities. Furthermore, transient vehicle operation (cold-starts, accelerations, and decelerations) would likely change the mixing state of the exhaust particles suggesting it is difficult to accurately measure the mass concentration of undenuded GDI exhaust particulate using integrated size distribution methods.

Insight into winter haze formation mechanisms based on aerosol hygroscopicity and effective density measurements

“…The ambient particles in urban areas are mostly complex mixtures of elemental carbon (EC), organics (OC), and secondary inorganic aerosols (SIA) . The effective density of nascent traffic particles varies from approximately 0.9 g cm −3 to below 0.4 g cm −3 , decreasing with the increase of particle size, because there are more voids between primary particles in relatively larger aggregates (Momenimovahed and Olfert, 2015). The effective density of OC is in between that of EC and SIA and varies with source.…”

“…The effective density of OC is in between that of EC and SIA and varies with source. The effective density of combustion particles increases by filling the voids in the agglomerate particles with condensed semivolatile materials or by restructuring agglomerates with hygroscopic SIA (Momenimovahed and Olfert, 2015;Zhang et al, 2008).…”

“…In urban air, the population of near-hydrophobic particles can be assumed to consist largely of freshly emitted combustion particles containing high mass fractions of soot and water-insoluble organic compounds (Swietlicki et al, 2008;Massling et al, 2009). In contrast, secondary sulfate or nitrate aged particles are more hygroscopic, and their relative abundance is primarily responsible for the hygroscopic growth of ambient particles at elevated RH (Topping et al, 2005;Aggarwal et al, 2007;Gysel et al, 2007).…”

Methodology for quantifying the volatile mixing state of an aerosol

“…Combined these give an uncertainty on the order of 16% of the total mass concentration (with 95% confidence) neglecting uncertainty due to the SMPS data inversion, as shown by Momenimovahed and Olfert (2015).…”

“…In this technique, a DMA is used to select a monodisperse aerosol that is then denuded or coated, followed by a particle mass analyzer so that the change in particle mass statistics with and without denuding/coating of the aerosol can be quantified. This technique has been used to determine the mass fraction of volatile material on coated particles from flames (Zhang et al 2008;Pagels et al 2009;Schnitzler et al 2014), a Diesel engine (Sakurai et al 2003), gasoline direct injection engines (Momenimovahed and Olfert 2015), a natural-gas direct-injection compressionignition engine , and ambient aerosols (Kuwata et al 2009;Rissler et al 2014). …”