Modeling the Radical Chemistry in an Oxidation Flow Reactor: Radical Formation and Recycling, Sensitivities, and the OH Exposure Estimation Equation

Abstract

Oxidation flow reactors (OFRs) containing low-pressure mercury (Hg) lamps that emit UV light at both 185 and 254 nm ("OFR185") to generate OH radicals and O3 are used in many areas of atmospheric science and in pollution control devices. The widely used potential aerosol mass (PAM) OFR was designed for studies on the formation and oxidation of secondary organic aerosols (SOA), allowing for a wide range of oxidant exposures and short experiment duration with reduced wall loss effects. Although fundamental photochemical and kinetic data applicable to these reactors are available, the radical chemistry and its sensitivities have not been modeled in detail before; thus, experimental verification of our understanding of this chemistry has been very limited. To better understand the chemistry in the OFR185, a model has been developed to simulate the formation, recycling, and destruction of radicals and to allow the quantification of OH exposure (OHexp) in the reactor and its sensitivities. The model outputs of OHexp were evaluated against laboratory calibration experiments by estimating OHexp from trace gas removal and were shown to agree within a factor of 2. A sensitivity study was performed to characterize the dependence of the OHexp, HO2/OH ratio, and O3 and H2O2 output concentrations on reactor parameters. OHexp is strongly affected by the UV photon flux, absolute humidity, reactor residence time, and the OH reactivity (OHR) of the sampled air, and more weakly by pressure and temperature. OHexp can be strongly suppressed by high OHR, especially under low UV light conditions. A OHexp estimation equation as a function of easily measurable quantities was shown to reproduce model results within 10% (average absolute value of the relative errors) over the whole operating range of the reactor. OHexp from the estimation equation was compared with measurements in several field campaigns and shows agreement within a factor of 3. The improved understanding of the OFR185 and quantification of OHexp resulting from this work further establish the usefulness of such reactors for research studies, especially where quantifying the oxidation exposure is important.

The Caltech Photooxidation Flow Tube reactor: design, fluid dynamics and characterization

“…Such reactors comprise both chambers and flow reactors. The flow tube reactor has emerged as a widely used platform (Bruns et al, 2015;Chen et al, 2013;Ezell et al, 2010;Kang et al, 2007Kang et al, , 2011Karjalainen et al, 2016;Keller and Burtscher, 2012;Khalizov et al, 2006;Lambe et al, 2011aLambe et al, , b, 2012Lambe et al, , 2015Li et al, 2015;Ortega et al, 2013Ortega et al, , 2016Palm et al, 2016;Peng et al, 2015Peng et al, , 2016Simonen et al, 2016;Tkacik et al, 2014). The flow tube reactor is generally operated under steadystate conditions.…”

Assessing the degree of plug flow in oxidation flow reactors (OFRs): a study on a potential aerosol mass (PAM) reactor

“…Furthermore, combining a phenomenological model to an associated RTD can impact kinetics (and yields) further. The RTD generated by Lambe et al (2011a) employed in Li et al (2015) may lead to greater than 10 % error if the two PFRs in parallel model suggested by Lambe et al (2011a) are not applicable. In these scenarios, ensuring a high degree of plug flow can not only maximize exposure, but minimize the distribution of aged compounds (e.g., first-or secondgeneration compounds) that are due to different exit ages because of recirculation or stagnation.…”

“…Because the mechanism of exposure between traditional chambers OFRs was different, validating the OFR concept began by replicating data obtained from traditional chambers Lambe et al, 2015;Liu et al, 2015), and assessing whether the chemistry was realistic McNeill et al, 2008;Peng et al, 2015;Renbaum and Smith, 2011). Consequently, much modeling work has focused on pure chemical reactions and comparison of SOA yields between the two (Bruns et al, 2015;Lambe et al, 2015;Li et al, 2015;Ortega et al, 2016;Peng et al, 2015). However, little modeling work has been done on understanding hydrodynamics or flow fields inside OFRs so that the flow patterns can be improved.…”

“…However, little modeling work has been done on understanding hydrodynamics or flow fields inside OFRs so that the flow patterns can be improved. In a study from Li et al (2015), it appears that residence time distributions (RTDs) that deviate significantly from plug flow in the PAM result only in an ∼ 10 % error of reported values such as OH exposure , which is conducive to OFRs being viewed as tubular reactors. Following an experimentally determined RTD (Lambe et al, 2011) in a PAM OFR, Peng et al extend the model developed by , to include this non-ideal RTD, suggesting model disagreement at high exposures.…”

Constraining nucleation, condensation, and chemistry in oxidation flow reactors using size-distribution measurements and aerosol microphysical modelling

“…20 Palm et al (2016) compared the total SOA formed in the OFR during the BEACHON campaign to the predicted yield from the measured VOCs for OH oxidation in the OFR. For the analysis, they included the measured MT, sesquiterpene (SQT), isoprene, and toluene concentrations and used low-NO x (to match the OFR chemical regime, Li et al, 2015;Peng et al, 25 2015), OA-concentration-dependent chamber-derived particle yields for each species. They determined that MTs contributed on average 87% of the SOA predicted to form from these VOC precursors, but on average, the maximum measured SOA formation was 4.4 times higher than the predicted SOA formation.…”