Modeling the Radical Chemistry in an Oxidation ... - ACS Publications

Mar 19, 2015 - Chemical Sciences Division, Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder,. Colorado 80305...
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Modeling the Radical Chemistry in an Oxidation Flow Reactor: Radical Formation and Recycling, Sensitivities, and the OH Exposure Estimation Equation Rui Li,†,‡,§ Brett B. Palm,‡,∥ Amber M. Ortega,‡,§ James Hlywiak,⊥ Weiwei Hu,‡,∥ Zhe Peng,‡,∥ Douglas A. Day,‡,∥ Christoph Knote,#,∇ William H. Brune,⊥ Joost A. de Gouw,†,‡,∥ and Jose L. Jimenez*,‡,∥ †

Chemical Sciences Division, Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, Colorado 80305, United States ‡ Cooperative Institute for Research in Environmental Sciences, §Department of Atmospheric & Oceanic Sciences, and ∥Department of Chemistry and Biochemistry, University of Colorado, Boulder, Colorado 80309, United States ⊥ Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania 16802, United States # Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado 80301, United States S Supporting Information *

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.

1. INTRODUCTION

experimental verification and improvement of atmospheric photochemical models. Large environmental chamber reactors range from a few to hundreds of cubic meters. The wall material is most commonly a Teflon film, but stainless steel is also used. A variety of photolytic OH radical generation methods are used in several

Environmental chambers and flow reactors have a long history of use for simulating the chemical and physical processes in the Earth’s atmosphere, such as the photochemical degradation of atmospheric pollutants (e.g., volatile organic compounds, VOCs) and the formation of products (e.g., oxygenated VOCs and secondary organic aerosols, SOA);1−5 cloud microphysics and aerosol−climate interactions;6 and the kinetics and spectroscopy of atmospheric species and reactions.7,8 These reactors have many different designs that result in different advantages and limitations for quantitative © 2015 American Chemical Society

Special Issue: Mario Molina Festschrift Received: September 20, 2014 Revised: March 18, 2015 Published: March 19, 2015 4418

DOI: 10.1021/jp509534k J. Phys. Chem. A 2015, 119, 4418−4432

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The Journal of Physical Chemistry A Table 1. List of Reactions and Their Rate Constants in the OFR Model #

reactions

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

O2 + hν (185 nm) → 2O(3P) O3 + hν (254 nm) → O2 + O(1D) H2O2 + hν (185 nm) → HO2 + H H2O2 + hν (254 nm) → 2OH HO2 + hν (254 nm) → OH+O(1D) HO2 + hν (185 nm) → OH + O(1D) H2O + hν (185 nm) → OH + H O(1D) + H2O → 2OH O(1D) + N2 → O(3P) O(1D) + O2 → O(3P) O(1D) + CO2 → O(3P) + CO2 O(1D) + O3 → 2O2 O(1D) + O3 → O2 + O + O O(1D) + H2 → OH + H O(1D) + N2 + M → N2O O(1D) + N2O → N2 + O2 or 2NO O + OH → O2 + H O + HO2 → OH + O2 O + H2O2 → OH + HO2 O + O3 → 2O2 H + O3 → OH + O2 OH + O3 → HO2 + O2 HO2 + NO → OH + NO2 HO2 + O3 → OH + 2O2 OH + HO2 → H2O + O2 H + HO2 → 2OH H + HO2 → O + H2O H + HO2 → O2 + H2 OH + H2 → H2O + H OH + OH → H2O + O O + NO2 → NO + O2 O + NO2 → O2 + NO2 O + HO2NO2 → products H + NO2 → OH + NO OH + NO3 → HO2 + NO2 OH + HONO → H2O + NO2 HO2 + NO3 → OH + NO2 + O2 NO + NO3 → 2NO2 NO3 + NO3 → 2NO2 + O2 N2O5 + H2O → 2HNO3 NO + O3→ NO2 + O2 NO2 + O3 → NO3 + O2 HO2 + NO2 + M → HONO2 + M HO2 + NO2 + M → HOONO + M OH + HNO4 → products OH + H2O2 → H2O + HO2 OH + NO2 + M → HNO3 + M O + O2 + M → O3 + M H + O2 + M → HO2 + M OH + OH + M → H2O2 + M OH + SO2 + M → HOSO2 + M HOSO2 + O2 → HO2 + SO3 HO2 + HO2 → H2O2 + O2

53 54 55 56 57 58

O + NO + M → NO2 + M O + NO2 + M → NO3 + M NO2 + NO3 + M → N2O5 + M OH + CO + M → H + CO2 + M OH + CO + M → HOCO + M HOCO + O2 → HO2 + CO2

reaction rate constant

low-pressure limit rate constant (ko)

high-pressure limit rate constant (kh)

2 × 10−31M(300/T)3.4 9.1 × 10−32M(300/T)3.9

2.9 × 10−12(300/T)1.1 4.2 × 10−11(300/T)0.5

1.8 × 10−31M(300/T)3.0

2.8 × 10−11

4.4 × 10−32M(300/T)1.3 6.9 × 10−31M(300/T) 3.3 × 10−31M(300/T)4.3

7.5 × 10−11(300/T)−0.2 2.6 × 10−11 1.6 × 10−12

9 × 10−32(300/T)1.5 2.5 × 10−31(300/T)1.8 2.0 × 10−30(300/T)4.4 1.5 × 10−13(300/T)−0.6 5.9 × 10−33(300/T)1.4

3.0 2.2 1.4 2.1 1.1

1.1 × 10−20 × flux185a 1.03 × 10−17 × flux254b 1 × 10−19 × flux185 6.7 × 10−20 × flux254 2.63 × 10−19 × flux254 + 3.68 × 10−18 × flux185 6.78 × 10−20 × flux185 1.63 × 10−10e60/T 2.15 × 10−11e110/T 3.3 × 10−11e55/T 7.5 × 10−11e115/T 1.20 × 10−10 1.20 × 10−10 1.20 × 10−10 2.8 × 10−36M(300/T)0.9 1.19 × 10−10e20/T 2.2 × 10−11e180/T 3.0 × 10−11e200/T 1.4 × 10−12e−2000/T 8.0 × 10−12e−2060/T 1.4 × 10−10e−470/T 1.7 × 10−12e−940/T 3.5 × 10−12e270/T 1.0 × 10−14e−490/T 4.8 × 10−11e250/T 7.20 × 10−11 1.60 × 10−12 6.90 × 10−12 2.8 × 10−12e−1800/T 1.80 × 10−12 5.1 × 10−12e210/T 1.0 × 10−11 7.80 × 10−11e−3400/T 4.0 × 10−10e−340/T 2.2 × 10−11 1.80 × 10−11e−390/T 3.5 × 10−12 1.50 × 10−11e170/T 8.5 × 10−13 e−2450/T 2.0 × 10−21 3.0 × 10−12e−1500/T 1.2 × 10−13e−2450/T Eq(1)b 1.3 × 10−12e380/T 1.80 × 10−12 Eq(1) 6.0 × 10−31M(300/T)2.4 Eq(1) Eq(1) Eq(1) 1.3−12e−330/T (3.0 × 10−13e460/T + 2.1 × 10−33Me920/T) × (1 + 1.4e−21H2O × 102200/T) Eq(1) Eq(1) Eq(1) Eq(2)c Eq(1) 1.5 × 10−12 4419

× × × × ×

10−11 10−11(300/T)0.7 10−12(300/T)0.7 109(300/T)6.1 10−12(300/T)−1.3

DOI: 10.1021/jp509534k J. Phys. Chem. A 2015, 119, 4418−4432

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The Journal of Physical Chemistry A Table 1. continued # 59 a

reactions OH + HNO3 → H2O + NO3

low-pressure limit rate constant (ko)

reaction rate constant

high-pressure limit rate constant (kh)

Eq(3)d

Flux185 and flux254 are the photon fluxes at 185 and 254 nm emitted from the low-pressure Hg lamps after accounting for attenuation by O2, O3, and −20

−20

−17

H2O, assuming 7 cm as the average distance, flux185(t) = flux1850 × e[−7×(1.1×10 ×O2+6.78×10 ×H2O)] and flux254(t) = flux2540 × e[−7×(1.03×10 ×O3(t))], where flux1850 and flux2540 are the actinic flux density (photons cm−2 s−1) at 185 and 254 nm from the Hg lamp emission; flux185, flux254, and O3 are reaction time (t) dependent. bEq(1) = [ko × M/(1 + ko × M/kh)] × 0.6∧{1 + [log10(ko × M/kh)]2}−1. cEq(2) = ko/[1 + ko/(kh/M)] × 0.6∧{1 + [log10(ko/(kh/M))]2}−1. dEq(3) = k00 + (k01 × M)/(1 + (k01 × M)/k02); k00 = 2.4 × 10−14e460/T; k01 = 6.5 × 10−34e1335/T; k02 = 2.7 × 10−17e2199/T.

cubic meter chambers, such as natural sunlight,9−11 xenon arc lamps,12 and UV black lights.13−15 A nonphotolytic source of OH can also be used based on the reaction of O3 with alkenes.16 Oxidation flow reactors (OFRs) are an alternative to environmental chambers and have advantages of a wide range of integrated oxidant exposure times over short residence times (∼minutes) with reduced wall effects,17,18 allowing much faster experimental sequences and easier modification for deployment in field studies.19 These reactors often use low-pressure mercury (Hg) lamps to generate OH radicals.17,18 For example, recent studies have shown the significant influence of OH aging on SOA properties and concentrations.19−22 As semivolatile SOA precursors have been found to be an important part of SOA evolution, their reactions with OH require substantial increase in the time scale of the chamber experiments due to their low volatility.22−24 These studies have shown that an important quantity for SOA aging studies is the OH exposure (OHexp), which is the integral of the OH concentration over time in the reactor and has units of molecules cm−3 s. The fast measurements and high OH exposures achievable with OFRs make it possible to study the evolution of a system from low to high OH aging on short time scales. Low-pressure Hg lamps have been studied and reviewed in detail before.25−27 Briefly, in the gas discharge, electrons are produced and accelerated by the electric field. During their travel in the lamp, the collisions with Hg atoms result in kinetic energy transfer from the electrons to Hg atoms. The electronically excited Hg atoms return to lower-energy states with spontaneous radiation emissions. Because of its high emission lines at 185 and 254 nm, low-pressure Hg lamps are widely used, such as in wastewater treatment,28 the detection of Hg in the air based on cold vapor atomic absorption spectrometry at 185 nm,29 simultaneous desulfurization and denitrification,30 ionization methods for analytical chemistry research,31 VOC emissions control,32 and generation of O3 and OH radicals in OFRs for atmospheric studies.17,33 Despite the wide application of OFRs based on low-pressure Hg lamps, the quantitative radical budget including the formation and destruction fluxes under various environmental and input conditions has not been studied quantitatively to our knowledge. The uncertainties in radical quantification can significantly affect the interpretation of experiments using such reactors. Existing atmospheric chemistry models do not include some of the chemistry relevant to the specific conditions in these reactors. In this work, a photochemical kinetic model has been developed and applied to simulate the formation and evolution of the key radicals and oxidants and quantify the radical budget for the OFR. These model results of OHexp are tested against laboratory measurements of OHexp estimated from trace gas removal under a variety of experimental conditions. To estimate OHexp during ambient measurements,

a OHexp estimation equation is also formulated and compared against several recent field measurements.

2. METHODS 2.1. Potential Aerosol Mass (PAM) OFR. Although the kinetics and photochemical mechanism developed here are applicable to a wide variety of reactor geometries and residence times, all of our simulations use the geometry and residence time of the PAM flow reactor, which has been used for all of the experiments reported here. The reactor was first introduced by Kang et al. (2007)17 and has been used in many field and laboratory studies on SOA formation.18,19,21,34−37 A user community has developed with regular user meetings (https://sites.google.com/site/pamwiki/). Briefly, the reactor is a 13 L cylindrical aluminum vessel with two or more low-pressure Hg lamps (model no. 82-9304-03, BHK Inc.) producing 185 and 254 nm light inside of the reactor in order to generate high concentrations of hydroxyl radicals (OH) under continuous flow conditions. The total OHexp in the reactor can be varied over a wide range (approximately 1010−1012 molecules cm−3 s) by changing the UV light intensity (via computer control of the voltage supplied to each Hg lamp), absolute humidity, and flow rate (i.e., residence time). OH oxidation of gas-phase precursors at different OHexp in the reactor may lead to new particle formation and/or particle growth by condensation. The Hg lamps are enclosed in sleeves through which N2 is flowed, which serves to minimize the heat generated by the lamps and prevent degradation of the lamp seals as well as surface oxidation of the lamps exterior. Two types of sleeves can be used. Teflon sleeves transmit both 185 and 254 nm light, and thus, we refer to reactors operated in this way as “OFR185” as the shorter wavelength allows the direct photolysis of O2 and H2O. When “ozone-free” quartz sleeves (GE 214) covered with Teflon heat-shrink tubing are used, only 254 nm light is transmitted, and we refer to this mode of operation as “OFR254”.17 While the photochemical model developed here can be applied to both types of operation, this paper focuses on OFR185 as it has some advantages for field deployments such as the ability to operate without an inlet and has been the primary OFR mode used by our group.19,36 An important parameter for the OFR185 modeling is the ratio of the photon intensities at 185−254 nm emitted by the lamps through the Teflon sleeves. In this study, the effective photon flux at 185 nm, f185, is determined from the observed O3 mixing ratio in the reactor, and the effective photon flux at 254 nm, f 254, is estimated from the flux ratio of f185/f 254. This ratio is estimated from measurements (see the Supporting Information) as a function of lamp power from 0.4 up to 1.2% at the maximum voltage supplied to the lamps. 2.2. OFR Model Description. To gain a better understanding of the detailed balance of radical/oxidant formation, 4420

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The Journal of Physical Chemistry A concentration, and destruction under various OFR input conditions, a photochemical model has been developed (Table 1). Briefly, OH radicals are primarily generated by photolysis of H2O (H2O + hν (185 nm) → OH + H) and photolysis of O3 formed from O2 photolysis hν(185 nm)

O2

hν(254 nm)

Table 2. List of Model Inputs with Typical Laboratory Conditions (Boulder, CO) and Zero External OHRa

H 2O

O2 ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ 2O(3P) → 2O3 ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ 2O(1D) ⎯⎯⎯→ nOH (1)

The number of OH formed (n) also depends on the H2O conditions. All reactions and rate coefficients are obtained from the most recent JPL evaluation.38 The attenuation of the UV light intensity due to absorption by O2 and H2O (for 185 nm) and O3 (for 254 nm) is calculated with the concentrations at each time step using a path length of 7 cm, which represents an average path length for different points in the reactor (see the notes in Table 1). Plug flow is assumed, and the model is integrated with respect to reaction time using the Runge−Kutta fourth-order method and implemented in Igor Pro 6 (Wavemetrics, Lake Oswego, OR). The time step, dt, is sufficiently small for direct integration of the concentration of most of the species listed in Table 1. A few radicals with very short lifetimes (i.e., O(1D) ≈ 10−9 s, HOSO2 and H ≈ 10−7 s, O(3P) ≈ 10−5 s) were assumed to be instantaneous in each time step. Different time steps were tested for stable results of OH exp, O3 concentration, and the HO2/OH radical ratio. A value of 0.005 s was retained for the time step, which resulted in less than 1% variation in all model outputs as the time step was halved. The total reaction time in the model was set to 180 s, which is a typical value for the residence time in the reactor. A distribution of residence times in the reactor has been published,18 and the average OH exposure calculated from the model using the residence time distribution (RTD) is not significantly different from that with the plug flow approximation (Figure S2, Supporting Information). For the typical conditions, the average OH exposure calculated with RTD is 10% higher than that with plug flow, which is smaller than the model uncertainty (a factor of 2). Therefore, the values of OH exposure from the plug flow model results are reported in this study. We note that most of our work has been conducted without an inlet plate to avoid losses of semivolatile species observed in a previous study, which is expected to lead to a substantially narrower distribution of residence times.19 For the purposes of this study, the actual distribution of reaction times, the heterogeneity of UV light intensities and radical/oxidant concentrations at different points in the reactor, and wall reactions were neglected because gradients caused by these effects are reduced by mixing within the chamber and as taking them into account directly would require much higher model complexity. The impact of these factors should be included in the focus of future studies. The input parameters in the model include environmental conditions (pressure, temperature, water vapor mixing ratio, and external OHR, which is the OH reactivity (OHR) of the added gases and not the OH/HO2/O3 chemistry itself) and reactor settings (photon fluxes at 185 and 254 nm, initial O3 mixing ratio, and residence time). The environmental conditions were set to be similar to typical laboratory and field experimental conditions (Table 2). Unlike other studies where external O3 was added to the sample air to produce OH when using the OFR254 mode,17,18 all of the cases in this study have no initial O3 input (other than inconsequentially low ambient O3 levels in some experiments). In the model outputs,

parameters

values

units

temperature pressure residence time H2O mixing ratiob flux @ 185 nmc flux @ 254 nmc SO2 initial CO initial

295 835 180 1 2.02 × 1013 2.53 × 1015 0 0

K mbar s % photons/cm2/s photons/cm2/s ppbv ppmv

Under these conditions, the model results are OHexp = 4.5 × 1012 molecules cm−3 s−1, O3 = 8032 ppbv, H2O2 = 66 ppbv, and HO2/OH = 4.1. bThe absolute water vapor content in the air sample, which is the ratio of the water vapor number density to the air number density in units of %. For the listed temperature and pressure, this H2O mixing ratio is equivalent to 50% RH. cThe photon fluxes at 40% power of one Hg lamp. a

OHexp represents the integrated exposure over the reaction time. The output for HO2/OH is the ratio of HO2 exposure to OH exposure over the reaction time. For all other species (e.g., O3, H2O2, SO2, and CO), the model output is the final concentration at the end of reaction time (outflow of reactor). In the highly oxidizing conditions in the reactor, NO is rapidly reacted with high O3 (∼1014 molecules cm−3 for the base case) to form NO2 (given kO3−NO = 1.9 × 10−14 cm3 molecules−1 s−1 and NO lifetime ≈ 0.5 s),4 with NO2 subsequently reacting with OH (∼2.5 × 1010 molecules cm−3 for the base case) and forming HNO3 (given kOH−NO2 = 2.8 × 10−11 cm3 molecules−1 s−1 and NO2 lifetime ≈ 1.5 s),4 whereas the photolysis of HNO3 under our UV lights is slow (J = 10−5 s−1)5 (Figure S3, Supporting Information). Therefore, NOx chemistry is not thought to play an important role in the reactor chemistry under ambient conditions and has not been included. 2.3. Experiment Description. To evaluate the model results, calibration experiments using SO2 and CO as the sources of external OHR were performed in the laboratory under various conditions. A schematic diagram of the experimental setup is shown in Figure 1. Clean dry air (or zero air, defined as ambient air that has been processed with a purification system to contain less than 0.1 ppm of total hydrocarbons) from a zero air generator (1160 zero air supply, Thermo Scientific Inc.) was introduced into the reactor. SO2 or CO was added so that the integrated OHexp can be calculated from their relative decay. Part of the zero air flowed through a glass water bubbler (HPLC water) and the fraction flowing through versus bypassing the bubbler were adjusted to control the relative humidity (RH) in the sample air. A minor fraction of the input flow was exhausted through a rotameter before the entrance of the reactor to ensure ambient pressure in the reactor because the output from the zero air generator can be pressurized. At the exit of the reactor, 10% of the flow was sampled from the center of the reactor (for particle measurements), and 90% of total flow was sampled from an internal perforated Teflon ring for the gas-phase species (O3, SO2, and CO). A similar sampling design was used in previous studies18 but at different flow ratios. SO2 (Thermo Scientific Model 43i-TLE) and CO (Picarro Inc. Model G2401) monitors alternated measurements before and after the reactor for OHexp estimation. O3 in the reactor output was constantly measured by an O3 monitor (2B Technologies, Model 202). To 4421

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Figure 1. Diagram of the reactor calibration experiment setup. Each group of experiments was set to step through six UV light intensity settings (lamp off; one lamp at 10, 20, 40, and 60% power; and two lamps at 100% power) every 30 min while all other conditions remained constant. During each light setting, trace gases were sampled before the reactor for 10 min (gray dash) and after the reactor for 20 min (black dash) to ensure stable concentrations. Only the periods (last 5 min) with stable measurements were used for the model evaluation.

keep constant flow in the reactor, a makeup flow was alternated before and after the reactor depending on the sampling configuration of a given experiment (Figure 1). Table S1 (Supporting Information) lists all of the calibration experiment results used in this study. Figure S4 (Supporting Information) illustrates the time series of measurements of one set of experiments using CO. CO before the reactor is at a constant mixing ratio and decays to various levels after oxidation, from which the OHexp is calculated (see the Supporting Information for details). The range of measurable OHexp is trace-gasdependent, which will be discussed in detail in section 3.5.

water vapor concentration and UV light intensity (as OH formation from O3 is second-order in UV intensity while formation from H2O is first-order). HOx destruction is dominated by HOx self-reactions to form more stable products (H2O, O2, H2O2). Because OH and HO2 concentrations are comparable (HO2/OH ≈ 4), the dominant reactions for HOx loss are determined by the reaction rate coefficients. As shown in Table 1, the reaction rate coefficient of OH + HO2 is an order of magnitude higher than that of other HOx self-reactions (OH + OH and HO2 + HO2). Figure 2A shows that indeed HOx loss is dominated by OH + HO2, with a minor contribution of HO2 + HO2 and a negligible contribution of OH + OH. Figure 2B provides additional insight on OH formation and destruction due to the fast HOx cycling reactions. Aside from the primary formation channels from stable species, the reaction of HO2 + O3 is a non-negligible contributor to OH formation. For OH destruction, OH + O3 and OH + H2O2 (both of which form HO2) play an important role, in addition to the terminating HOx self-reactions. These different species reacting with OH can be quantified as an “internal OHR” of the system (in contrast to “external OHR” from species in the sample air such as SO2 and CO). Their relative contributions to OH destruction for the base case are shown in Figure 3A. OH + HO2 and OH + O3 are the main OH destruction pathways (58 and 33%, respectively), while OH + H2O2 and OH + OH have minor contributions (7 and 2%, respectively). The HOx destruction reactions dominate the internal OHR. The total internal OHR for the base case is 19 s−1 (i.e., a OH lifetime of 53 ms). 3.2. Species Time Evolution. To gain further insight into the photochemical regime under OFR185 operation and on the effect of varying residence time, Figure 4 shows the model results versus time in the reactor for concentration, production, and destruction rates for key species in the base case. As the fate of H radicals is dominated (>99%) by H + O2, it is not presented in this figure. The net production of these species (the sum of production and destruction), indicating the species concentration growth rate, is shown in Figure S5 (Supporting Information). After an initial transient period, OH quickly approaches a relatively constant concentration, whereas O(1D), O(3P), O3, HO2, and H2O2 all increase with reaction time. The

3. RESULTS AND DISCUSSION 3.1. Photochemistry and Reaction Fluxes. The model results for the base case under typical experimental conditions (Table 2) will be discussed in this section. Figure 2 shows a schematic representation of the key reaction fluxes and species concentrations for the base case. Figure 2A shows the total radical formation for HOx (HOx  OH + HO2), whereas Figure 2B shows the same results separating OH and HO2. Only the reactions with significant reaction fluxes are shown (i.e., >1 × 1010 molecules cm−3 s−1). The reactions are grouped depending on the fate of OH and HO2 radicals: radical production, destruction, and propagation (i.e., radical cycling between OH and HO2 and no net radical formation or loss). Because HOx is grouped in Figure 2A, the propagation reactions do not appear on the graph, allowing a clearer representation of radical formation and destruction. The following pathways dominate the photochemistry under these conditions. A very high rate for the O2 photolysis with 185 nm light forms O(3P) radicals, which immediately react with O2 to form substantial O3 concentrations. O3 photolyzes upon absorption of 254 nm light to form O(1D), about 10% of which reacts with H2O and forms two OH radicals. The majority of O(1D) (∼90%) collides with N2 and O2 to form O(3P), which re-forms O3 and completes a null cycle. H2O also photolyzes at 185 nm to OH and H radicals, and almost all H (99.93%) reacts with O2, forming HO2. The contribution of H2O2 photolysis to OH formation is negligible for the base case. Under these conditions, O3 and H2O photolysis make similar contributions to HOx formation, but the relative importance of both pathways is highly dependent on the 4422

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Figure 2. Reaction fluxes for HOx and concentrations for the key species for the base case of operation of OFR185, with one UV lamp at 40% power and 50% RH, as shown in Table 2. (A) HOx are shown together. (B) The same as in (A), but OH and HO2 are shown separately. The highlighted values next to each species are their average number concentration over the reaction time. The arrows between each species represent different reactions, and the arrow thickness is proportional to the average reaction flux, shown as the number (in units of 1010 molecules cm−3 s−1) on each arrow, except for the arrow thickness of the photolysis O2 + hν, which is scaled down by a factor of 5. The average concentrations of O(1D) and O(3P) radicals are also shown on the graph.

case, the average O(1D) concentration is about 3.3 × 103 molecules cm−3. 3.2.2. O(3P). Three reactions dominate O(3P) radical production. In the first 40 s of residence time in OFR, O(3P) is mainly produced by the constant photolysis rate of O2 at 185 nm. With the increase in O(1D) concentration with reaction time, the quenching of O(1D) from O3 photolysis by N2 and O2 becomes larger after the initial 40 s period. The only primary destruction of O(3P) is from the reaction of O(3P) + O2 + M, which is the primary O3 production pathway. The lifetime of O(3P) is about 10−5 s, and the concentration of O(3P) increases with time. The average concentration of O(3P) in the reactor is about 6.4 × 107 molecules cm−3. 3.2.3. OH. A constant OH production flux from the photolysis of H2O at 185 nm is the dominant primary OH source in the first 60 s. As O3 accumulates over time, OH formation from the O(1D) formed from O3 photolysis becomes

reasons for this time evolution of these species are discussed below. 3.2.1. O(1D). A large number of O(1D) radicals (production rate on the order of 1012 molecules cm−3s−1) is produced by the photolysis of O3 at 254 nm, which increases with reaction time as the O3 concentration increases (nearly linearly). Most O(1D) are very rapidly converted to O(3P) by reacting with N2 (∼70%) and O2 (∼24%). Only ∼6% of O(1D) radicals contribute to OH formation by reacting with H2O. The O(1D) lifetime is (estimated as the concentration divided by the production flux in the middle of the reactor) about 10−9 s; therefore, O(1D) radicals do not “accumulate”, but rather, their steady-state concentration increases with time as the ratio of total production to destruction rates increases with time. The increase in O(1D) concentration results in an increase in OH formation with reaction time from O(1D) + H2O. For this base 4423

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species reach high concentrations very quickly due to photolytic production and then gradually increases with time as HO2 increases. OH + O3 becomes comparable later as O3 grows more slowly than HO2. OH + H2O2 is a minor contributor, again growing on a similar time scale as OH + O3. The behavior of production and destruction leads to a short spike in OH concentration that returns to a lower level and then a slow increase. After the initial 30 s transient, production and destruction are closer to balance, leading to a OH concentration around 2.5 × 1010 molecules cm−3. Compared to the typical atmospheric OH concentration (1.5 × 10 6 molecules cm−3), the OH chemistry is sped up by 3−4 orders of magnitude in the reactor. 3.2.4. HO2. The only primary production of HO2 is from photolysis of H2O. Similarly to OH, HO2 production from this source is constant and dominates in the first ∼100 s, while recycling from OH + O 3 becomes larger later as O 3 accumulates. OH + H2O2 also plays a minor role and slowly increases with time as H2O2 accumulates. The main destruction pathways are OH + HO 2 , which become important immediately as discussed above, while HO2 + HO2 and HO2 + O3 become appreciable later as HO2 and O3 increase. Overall, the production is always higher than destruction, resulting in an increase in HO2 with time. This behavior is consistent with the net HO2 production (Figure S5, Supporting Information), which stays positive (indicating higher production rate than destruction) throughout the residence time in the reactor. The HO2 lifetime is about 250 ms. For this base case, HO2 ≈ 1011 molecules cm−3, with HO2/OH ≈ 4. 3.2.5. O3. As mentioned earlier, O3 is only produced by the reaction of O2 + O(3P) + M. As the O(3P) concentration

Figure 3. (A) Fraction of total OHR for the base case (Table 2). (B) Fraction of total OHR when 46 s−1 of external OHR is added to the base case (via a 10 ppmv initial CO mixing ratio).

larger after this initial 60 s period. Recycling via HO2 + O3 also increases over time because both HO2 and O3 increase with time. The three dominant destruction paths all increase with time due to the increase of partner reactant concentrations. OH + HO2 dominates, and it quickly jumps to a high value as these

Figure 4. Time evolution of production and destruction rates (left axes) and concentrations (right axes) of O(1D), O(3P), OH, HO2, O3, and H2O2 for the base case model results (Table 2). 4424

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Figure 5. Comparison between model results (y-axes) and measurements from calibration experiments (x-axes) for OHexp (A,C) and O3 mixing ratios (B,D) under various UV flux and humidity conditions. The data in each panel are fit with orthogonal distance linear regression. Panels A and B show the comparisons using SO2 as the reactant trace gas (initial concentrations of 500 and 100 ppbv, i.e., 10 and 2 s−1 OHR) with different UV fluxes at 3.5% RH. Panels C and D show the comparisons using CO (initial concentration of 10 ppmv, i.e., 50 s−1 external OHR) at different UV fluxes and relative humidities (color coded). In all comparisons, the data are size-coded with lamp power settings, ranging from one lamp at 10% to two lamps at 100%. In CO experiments (C,D), the data are also color-coded with four different relative humidities, ranging from 3.5 to 60%.

Figure 6. Sensitivity study on the dependence of OHexp, O3, HO2/OH, and H2O2 of the model results on UV photon fluxes, pressure, temperature, residence time, H2O, and external OHR. The left axis shows the absolute values of the model outputs. The right axis represents the percent of the base case (=100%) for each variable, that is, the relative change versus the default conditions.

OH. Other O3 destruction reactions are negligible contributors under these conditions, and interestingly, O3 + HO2 is an appreciable reaction for OH and HO2 but not for O3. Production is ∼3 times higher than destruction, resulting in an accumulation of O3 in the reactor, with an O3 lifetime of ∼30 s for this case. The O3 net production profile in Figure S5 (Supporting Information) decreases with time, indicating that

increases with time (due primarily to the increase in O3 and subsequent photolysis), the O3 production rate also increases. Its dominant destruction pathway is photolysis at 254 nm. In net terms, O3 photolysis represents a sink of 6% of its production rate because 94% of the O(1D) is quenched and reforms O3, but about 6% forms OH that does not re-form O3 through subsequent reactions. A minor destruction path is O3 + 4425

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density M, altering the reaction rate coefficients of termolecular reactions listed in Table 1 and the concentration of O2 and, thus, the source of O3 (and downstream source of OH) from its photolysis, while the water vapor number concentration is kept constant. The main reaction differences due to pressure change are shown in Figure S6 (Supporting Information), which compares the reaction fluxes between lower-pressure (0.6 atm) and higher-pressure (1 atm) conditions. As pressure increases (by a factor of 1.67), higher O2 concentrations lead to an increased photolysis rate and higher O3 (by a factor of 1.54), less than linearly due to the increased absorption of 185 nm light discussed above. These changes result in a large decrease in O(3P) by 45% due to a larger increase in the O(3P) destruction reaction (O(3P) + O2 + M → O3 + M) than production. O(1D) also decreases with pressure (by 5%) due to the increase in destruction reactions with the increased N2 and O2, resulting in a decrease in OH production by the reaction with H2O. The OH production from H2O photolysis decreases by 15% as the 185 nm flux is reduced by O2 absorption at the higher pressure. The total net OH production decreases by 8%, which results in a decrease in OH with pressure. The increase in O3 formation results in a higher OH-to-HO2 conversion rate (O3 + OH → HO2 + O2) and thus a higher HO2/OH ratio. The decrease of the other important sink for HO2 (OH + HO2 → H2O + O2) also contributes to the increase in HO2 (by a factor of 1.17) and thus an increase in H2O2 (by a factor of 2). It should be noted that although the absolute number concentrations of O3 and H2O2 increase by factors of 1.54 and 2, respectively, the air number density, M, also increases by a factor of 1.67, which results in little change in the O3 mixing ratio (within 2%) and an increase for H2O2 by only 40%, as shown in Figure 6. 3.4.3. Temperature. Temperature variation in OFR185 depends on the experiment setup and conditions. Typical of ground-based field operations, OFR185 is deployed without temperature control; hence, temperature change is subject to the ambient temperature variation and a small heating effect (∼2 °C) from the lamps. In this work, the laboratory temperature of the gas sample was relatively constant at 22 ± 1 °C, and no temperature control was used. The heating effect was not included in the model. The temperature dependence of the model results was studied under two constant water vapor mixing ratios (0.215 and 1%). Drier conditions allow a wider range in temperature variation without reaching water vapor saturation. The increase of temperature reduces OHexp, increases the HO2/OH ratio and H2O2 mixing ratio, but has little impact on the O3 mixing ratio. These effects can be explained by the reaction flux change comparing the high- and low-temperature cases, as shown in Figure S7 (Supporting Information). The increase in temperature (at constant pressure) leads to a decrease in air number density M, which decreases both O2 and H2O number densities and thus decreases O3 and OH production by photolysis of O2 and H2O. The O3 decrease also leads to less OH production. The reaction rate coefficient of the OH sink reaction (OH + O3 → HO2 + O2) has positive temperature dependence (listed in Table 1), resulting in an increase in OH destruction and OH-to-HO2 conversion with the increase of temperature. Therefore, OHexp decreases due to the decrease of OH production and the increase of destruction, and consequently, the HO2/OH ratio increases with temperature. Similarly to the pressure effects on species mixing ratios, although the number concentration of O3 decreases by 7% and

total destruction rates increase faster than production rates, resulting in the O3 accumulation slowing with time (Figure 4). 3.2.6. H2O2. The main production reaction for H2O2 is HO2 + HO2, which is also an appreciable loss for HO2 (30%). Because H2O2 production and HO2 destruction by this reaction have a quadratic dependence on HO2, this pathway can become more important under conditions with higher UV light. OH + OH + M is the only other H2O2 formation reaction and is a minor contributor for this case. The main destruction pathway is OH + H2O2. H2O2 photolysis at both 185 and 254 nm plays a very small role in H2O2 removal and is a negligible OH source under these conditions. All of these reaction rates increase with time as reactant concentrations increase, except OH + OH due to the different temporal profile of OH. As shown in the net production profile for H2O2 (Figure S5, Supporting Information), production exceeds destruction by ∼15%; therefore, H2O2 concentration increases with time and is on the order of 1012 molecules cm−3, with a lifetime of ∼25 s. The net production quickly increases to a peak value in the beginning due to HO2 production initiated by UV flux and slowly decreases as the destruction rate increases with time. 3.3. Model Results Evaluation. The model results of OHexp and O3 output concentration at different H2O and external OHR input conditions are compared with experimental results (experiments #2−12 in Table S1, Supporting Information) in Figure 5. Overall the model reproduces the experimental trends within a factor of 2 in most cases. Considering all the simplifications in the model (e.g., plug flow, lack of wall loss, lack of heterogeneity in UV fluxes and residence time), this level of agreement over a wide range of conditions strongly suggests that the model captures the major photochemical pathways that control OHexp in the OFR185. 3.4. Sensitivity studies. The previous model results focused on the base case under typical conditions and without external OHR. A detailed sensitivity analysis of the model results to its input parameters is discussed here to provide insights on the impact of key parameters on the photochemistry (Figure 6), to help guide experimental design, and to enable the development of a OHexp estimation equation (discussed below). Four model outputs (OHexp, HO2/OH, O3 mixing ratio, and H2O2 mixing ratio) are examined as the input parameters of UV flux, pressure, temperature, residence time, humidity, and external OHR are changed. While one of the parameters was varied, all other parameters were set at the base case values (Table 2). 3.4.1. UV Photon Fluxes. The variation of the photon fluxes enables a wide range of OHexp for gas- and particle-phase oxidation. In this work, six different voltage settings of the lamp power supplies were studied, and their corresponding photon fluxes at 185 and 254 nm are listed in Table S2 (Supporting Informaiton). As expected, OHexp, O3, and H2O2 all increase strongly with UV fluxes as higher UV leads to stronger photochemistry and more O(1D), O(3P), OH, and HO2 formation. The output dynamic ranges are factors of 15, 50, and 30 for OHexp, O3, and H2O2, respectively, for an input 185 nm flux dynamic range of 110. HO2/OH stays relatively constant at around ∼4, in part due to fast HO2 to OH cycling. 3.4.2. Pressure. The pressure in OFR185 during most experiments and field campaigns remains approximately constant, but it has been deployed at different ground-site elevations with different ambient pressures, and deployment on aircraft platforms may be of interest for future studies. We explore the range 0.6−1 atm, which changes the air number 4426

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Information) shows the same reaction flux diagram for the base case shown in Figure 2B (zero OHR) except with 46 s−1 external OHR (10 ppmv CO) added. OHexp decreases substantially (by 75%) with OHR, primarily due to the reaction of OH with, for example, CO that converts OH to HO2 radicals. This increased conversion leads to a large increase in HO2/OH. Compared to the case with zero OHR, this change leads to an increase in HO2 + HO2 and decrease in OH + O3. Because HO2 + HO2 is the main pathway for H2O2 formation, the large increase in HO2 radicals leads to a large enhancement in H2O2 (by a factor of 8.8) and also an increase in OH destruction by H2O2 (H2O2 + OH by a factor of 2.7). In contrast, O3 changes little with external OHR as its main formation and destruction pathways are photolytic. The slight increase is primarily due to the overall decrease of O3 sinks (OH + O3 decreases by a factor of 3, and HO2 + O3 increases by a factor of 2). The contribution of different pathways to OHR (destruction) is illustrated in Figure 3B for the base case modified by an added external OHR of 46 s−1 (CO in this case). The source of the external OHR does not change the radical chemistry if OH is converted to HO2, as is the case for SO2, CO, or VOCs (but not NO2). In the model, we use CO as the OH reactant for simplicity. We note that reactions with some VOCs may not lead to the production of HO2. To estimate this effect, the base case was run with external OHR = 10 s−1 and with/without HO2 generation from the CO reaction. OHexp only changed 12%, indicating that the impact of HO2 regeneration is small compared to other uncertainties in the model. Compared to the case without external OHR (Figure 3A), the dominant loss of OH becomes OH + CO. The other key reactants with OH in the case without CO are HO2, H2O2, O3, and OH itself. Because adding external OHR strongly increases HO2 and H2O2, leaves O3 relatively unchanged, and strongly reduces OH, the changes in the relative importance of the destruction reactions follows those trends. For instance, the HO x destruction is dominated by HO2 + HO2, and OH + HO2 becomes less important compared to the base case with zero external OHR, as shown in Figure S9 (Supporting Information). It also results in a large increase in the propagation reactions, which become the dominant OHR. It is worth noting that with higher external OHR, the total internal OHR also increases (from 19 to 43 s−1 in Figure 3) due to increases in HO2 and H2O2. The increase in the internal OHR also contributes to reducing the OH concentration. Because the photochemistry and radicals are influenced by the VOCs and inorganic precursors of interest for these OFR studies, it is important to understand their impact quantitatively. We define OH suppression as the OHexp decrease as external OHR is added, compared to an identical case except with no external OHR. The higher the value of external OHR, the larger the reduction in OHexp (suppression = 1 for no external OHR). Figure 7 shows the OH exposure suppression at different combinations of H2O and UV photon fluxes, with all other input conditions the same as the base case (Table 2). OH suppression is very sensitive to UV fluxes and less so to H2O. At lower UV fluxes, OH suppression is the largest and can reach a factor of 10 under rural OHR conditions and up to ∼100 under very polluted conditions. Conceptually, this is due to the lower internal OHR at low UV fluxes, making the radical balance more sensitive to chemical forcing by external reactivity. There is also a larger impact from water vapor at low photon flux conditions than at high conditions, primarily

that of H2O2 increases by 10% for the case with 1% water mixing ratio, the increase in temperature reduces the air number density, M, by 10%, which results in a slight increase in the O3 mixing ratio (by 2%) and amplifies the H2O2 mixing ratio increase to 20%, as shown in Figure 6. 3.4.4. Residence Time. The residence time depends on the experiment setup, that is, the flow rate of the sampling lines and sometimes makeup flow on the output of OFR185. Understanding the radical dependence on the residence time allows users to optimize the experimental setup. OHexp increases linearly with residence time in the range of 90−300 s because the OH concentration stays approximately constant. O3 and H2O2 concentrations increase continuously during this period as their production rates are higher than destruction rates, as shown in Figure S5 (Supporting Information). Because their net production decreases with time, the rates of increase of their concentrations are lower for higher residence times, as shown in Figure 4. HO2/OH increases with time as HO2 increases, while OH stays approximately constant (Figure 4). 3.4.5. H2O. Humidity conditions for most ambient measurements are not constant and need to be accounted for for the radical change in the reactor as H2O is needed for both primary OH sources. The H2O dependence was studied at 20 and 40 °C. A higher temperature allows a wider range of H2O mixing ratios without saturation. The water vapor impacts photochemistry in OFR185 in several ways, as shown in Figure S8 (Supporting Information), which compares the reaction fluxes at low (3.5% RH) and high (90% RH) humidities for the case at 20 °C (i.e., the water vapor number concentration increases by a factor of 26 from low-humidity to high-humidity conditions). First, the higher water vapor content in the air sample increases the absorption at 185 nm, increasing the OH production by H2O photolysis and by O(1D) + H2O by factors of 31 and 16, respectively, and results in strongly increasing OHexp with increasing H2O. The absorption by the higher H2O results in less photon flux at 185 nm, leading to a lower O2 photolysis rate and O3 production. The destruction of O3 by reaction with OH increases strongly with H2O as OH increases. These changes lead to a substantial O3 concentration decrease (by 51%) as H2O increases. Although OH destruction reactions also increase notably with increasing H2O, the overall OHexp still increases by a factor of 10. Because the increase in OH production as H2O increases (by a factor of 16) is much higher than the increase in OH-to-HO2 conversion (O3 + OH → HO2 + O2, by a factor of 6.7), OH increases faster with H2O than HO2 does, and thus, the HO2/OH ratio decreases with H2O. Finally, H2O2 is not a monotonic function of H2O (Figure 6). The main production of H2O2 scales with the square of HO2, and its main destruction scales with OH. Under dry conditions, the H2O2 destruction rate is much lower than production (Figure S8(top), Supporting Information), and the H2O2 concentration depends more on its production reaction (i.e., on HO2 concentration), which increases with H2O. As H2O increases, OH increases, HO2/OH decreases, and the H2O2 destruction rate becomes larger and leads to a decrease in H2O2 to a relatively stable level as H2O increases. 3.4.6. External OHR. The external OHR in this test ranges from 0 to 200 s−1 (Figure 6), which represents the range of ambient OH reactivities observed in different areas. For instance, the OHR in marine and rural areas ranges over 2− 10 s−1,39−41 whereas in urban areas and megacities, it varies over a much wider range, from 6 to 25 to 100−200 s−1 for different locations and times.42−47 Figure S9 (Supporting 4427

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been used to study biogenic SOA formation in different forest sites, that is, a mountain ponderosa pine forest during BEACHON-RoMBAS in Colorado,49 a mixed forest with impacts by regional pollution during SOA in Alabama (http:// wiki.envsci.rutgers.edu), and in the Amazon Basin at a site periodically affected by a large urban plume during GOAMAZON. A OHexp estimation equation for OFR185 as a function of easily measurable parameters (O3 and H2O) was proposed in previous studies.19 However, the equation was not found to perform well in comparison with experimental measurements. Also, that formulation cannot account for the OH suppression that occurs as external OHR increases because O3 changes little with increasing OHR (Figure 6). For this reason, during these campaigns, the OHexp in the reactor under different lamp settings and meteorological conditions was calibrated by measuring the decay in the reactor of either added SO2 or CO or of ambient species such as monoterpenes. However, there are a number of limitations of performing OHexp calibration experiments during field studies. First, experimental complexity is added, necessitating additional measurements and data analyses, which may not always be available, operational, or reliable in a given study. Second, a given calibration tracer cannot be used to measure the full range of OHexp produced in the reactor. This problem occurs because a given tracer needs to decay a measurable amount (typically several percent of its concentration) but not be completely destroyed (i.e., at least ∼10% of its concentration remaining) in order to allow reliable quantification of the OHexp despite experimental noise and background issues. For example, assuming a 10−90% fraction remaining, CO (kOH+CO = 2.13 × 10−13 cm3 molecules−1 s−1) can only be used for estimating OHexp between 5 × 1011 and 1 × 1013 molecules cm−3 s and SO2 (kOH+SO2 = 9.49 × 10−13 cm3 molecules−1 s−1) for OHexp between 1 × 1011 and ∼2 × 1012 molecules cm−3 s. Some ambient species such as terpenes (α-pinene kOH = 5.3 × 10−11 cm3 molecules−1 s−1) allow quantification of smaller exposures but not of high exposures (∼2 × 109−4 × 1010 molecules cm−3 s). Therefore, an improved OHexp estimation equation that uses measured quantities (H2O input, O3 output as a surrogate for

Figure 7. OH exposure suppression (OHexp normalized to the OHexp at zero external OHR) versus external OHR for five different UV flux and H2O conditions (shown in the inset).

due to different dominant OH production channels. In the high-flux case when f185 = 1014 photons cm−2 s−1 in Figure 7, the O3 contribution dominates OH production, and the suppression has less water dependence, whereas in the lowflux case, OH is mainly produced by H2O photolysis, and the suppression has higher water dependence, as illustrated in Figure S10 (Supporting Information). As expected, the case with moderate water and photon flux settings shows intermediate OH suppression. 3.5. OH Exposure Estimation Equation. OFR185 reactors have been deployed in a number of field campaigns for characterizing the potential SOA formation and aging in ambient air. For instance, this reactor was used in the CalNex campaign in the Los Angeles Basin to investigate SOA formation from anthropogenic sources.48 Additionally, it has

Figure 8. (A) Model results for OHexp versus O3 for a range of UV photon fluxes, external OH reactivities, and H2O. The results are color-coded with OH reactivities and size-coded with water vapor mixing ratios (3.5−90% RH at T = 22 °C). (B) Comparison of OHexp calculated from the new estimation equation versus the model results. 4428

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The Journal of Physical Chemistry A UV flux, and external OHR) as input parameters would be very useful for estimating OHexp in field and laboratory studies. In this work, a OHexp estimation equation is developed based on fitting the model results under a wide range of conditions. Figure 8A shows model results for OHexp versus O3 output at different H2O, UV flux levels, and external OH reactivities. A wide range of these three parameters is used (i.e., 5 × 1012−1 × 1015 molecules cm−3 for O3, 3.5−85% RH at T = 22 °C, and 3− 200 s−1 external OHR). The analysis of the model output indicates that OHexp increases as a power function of UV flux and linearly with H2O but decreases with OHR in a complex way at different UV and H2O conditions. Therefore, the OHexp is expressed as OHexp = A ·O3 p1 ·H 2O

(2)

where A is a fitting coefficient, O3 is the ozone output concentration (molecules cm−3), H2O is the water vapor mixing ratio (%), and the exponent p1 is a function of OHR and O3 p1 = b + c·OHRd + e· log O3 · OHR f

Figure 9. OHexp estimated from the estimation equation (see text) versus OHexp calculated from added/ambient tracer decay for different field studies. The uncertainty of OHexp obtained from the estimation equation (vertical bars) is estimated as a factor of 2. The uncertainty of OHexp calculated from trace species decay in the field measurements (horizontal bars) was estimated for each case (see detailed calculation in the Supporting Information). On average, the uncertainties for OHexp estimated from SO2, CO, and monoterpenes are 34, 30, and 29%.

(3)

where b−f are fitting coefficients. By substituting eq 3 into eq 2 and taking the logarithm log OHexp = a + (b + c· OHRd + e·log O3 ·OHR f ) ·log O3 + log H 2O

(4)

where a = log(A). All of the parameters (a−f) are obtained by fitting eq 4 to the model-calculated OHexp in Figure 8A. The resulting fit coefficients are listed in Table 3. The OHexp

time (in min) (i.e., scaling factor = actual residence time t/3 min) log OHexp = [a + (b + c· OHRd + e· log O3 · OHR f ) ·log O3

Table 3. Fit Parameters and One Standard Deviation (SD) for the OHexp Estimation Equation Based on Model Results

a

parameters

values

SD

a b c d e fa

26.89 −1.76 −1.29 0.077 0.14 0.046

0.93 0.094 0.068 0.0024 0.0042

⎛t ⎞ + log H 2O] + log⎜ ⎟ ⎝3⎠

(5)

Online standard addition of CO was used in SOA, while ambient SO2 decay was used in CalNex to calibrate high OHexp (>1011 molecules cm−3 s). Ambient measurement of monoterpenes by high-resolution PTR-MS in BEACHON-RoMBAS and SOA was used to estimate OHexp at lower exposures, as discussed above. It should be noted that the decay of monoterpenes (α-pinene, β-pinene, isoprene, and limonene) due to their reactions with O3 was less than 2% compared to their OH reactions under the typical conditions in the OFR185. Therefore, the ozonolysis of monoterpenes and the OH produced from those reactions have been neglected in the OHexp calculation. Figure 9 shows the comparison of OHexp between the estimation equation results and trace decay measurements. The level of agreement varies depending on the OHexp range. For the high level of OHexp (1011−1013 molecules cm−3 s using CO for OHexp calibration), the results agree well with the estimation equation (slope = 1.2, R2 = 0.95). For a medium OHexp level (1011−1012 molecules cm−3 s using SO2), 90% of the OHexp at higher UV flux (40% power setting, blue dots) agrees with calibration equation results within a factor of 3, but only about 60% of the OHexp at lower UV flux (orange dots) agrees within a factor of 3. The reduced agreement at lower UV flux is at least partially due to the increased uncertainty in the measurements. The OHexp estimated from trace decay measurement at a lower lamp power setting has higher uncertainty because the uncertainty is inversely proportional to the trace species

This parameter was constrained to this value in the fit.

calculated from the estimation equation (eq 4) are compared with the model results in Figure 8B. Overall, all of the points line up closely to the 1:1 line with an average absolute value of the relative errors of 10%. Therefore, the OHexp estimated from the estimation equation is representative of the model results under a wide range of conditions. The OHexp calculated from the estimation equation is evaluated against ambient measurements taken during several field studies. Figure 9 compares the OHexp estimated from the estimation equation to that calculated from the ambient or added tracer decay during CalNex, BEACHON-RoMBAS, and SOA. It should be noted that the estimation equation was derived for a 3 min residence time, but the exact residence time varied in different campaigns (4.1, 2.1, and 3.2 min for CalNex, BEACHON, and SOA, respectively). The sensitivity study (Figure 6) showed that OHexp linearly increased with residence time. Therefore, in the comparison with field studies, the OHexp from the estimation equation (eq 4) was scaled for residence 4429

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The Journal of Physical Chemistry A removal at low removal fractions (as shown in eq S6 in the Supporting Information). For comparison with OHexp calculated from monoterpenes during SOA, the estimation equation overestimates by a factor of 2−10. For the lowest OHexp calculated from the monoterpenes during BEACHON, 90% of the estimation equation results agree within a factor of 3. Considering all of the simplifications in the model assumptions and the uncertainties in quantifying OHexp in the field, the new estimation equation provides estimates for most levels of OHexp in the reactor that are valuable in the interpretation of SOA formation and processing in the reactor.

experiments, time evolution of the net production rates of key species, and flux diagram comparisons at different pressure, temperature, humidity, and OH reactivity. This material is available free of charge via the Internet at http://pubs.acs.org.

4. CONCLUSIONS A box model was developed to study the photochemistry in an oxidation reactor under OH oxidation initiated by low-pressure Hg lamps. The model simulates the formation and evolution of the key radicals and oxidants. The characterization of each species sheds light on its dominant reaction pathways and budget under various environmental and input conditions. The photolysis of O3 and H2O is dominant for HOx production, while HOx loss is dominated by OH + HO2, with a minor contribution of HO2 + HO2 under typical conditions. The fast HOx cycling reactions of HO2 + O3, OH + O3, and OH + H2O2 are also non-negligible contributors to the HOx budget. The relative importance of these pathways for both production and destruction may vary depending on the photon fluxes, H2O, and OH reactivities. A sensitivity study was performed to characterize the dependence of key parameters on UV flux, humidity, temperature, pressure, residence time, and external OHR in the reactor. OHexp is mainly dependent on UV light flux, H2O, external OHR, and residence time. OHexp is suppressed to various degrees by external OHR that converts OH to HO2 and H2O2, especially at low UV light fluxes and with a weaker dependence on H2O. This OH suppression can reach factors of 10−100 and needs to be taken into account in the operation and interpretation of OFR185. OHexp from the model output agrees well with that calculated from the tracer decay in laboratory experiments (slope = 0.96 ± 0.05), except that at low humidity conditions, the model underestimates OHexp by a factor of 2. To enable a more accurate estimation of OHexp from more easily quantifiable parameters in field and laboratory studies, a new OHexp estimation equation was derived over a wide range of O3, H2O, and external OHR. The OHexp calculated with the new estimation equation shows good agreement with the model results (average 11% error). This estimation equation is also compared with OHexp quantification using trace gas decays for several field campaigns. The comparison shows reasonable agreement with most data within a factor of 3. The simplifications in the model assumptions compared to the reactor operating conditions and the difficulty in accurately quantifying OHexp in the field are thought to lead to the differences between the equation and the measurements. The improved understanding of the OFR185 technique and quantification of OHexp resulting from this work further establishes the viability of such tools for aerosol formation and aging research.

Notes





AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Present Address ∇

C.N.: Meteorologisches Institut, Ludwig-Maximilian-Universität, München, Germany.

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The Abstract graphic background photo was taken by Rui Li. We thank the PAM user community for many useful discussions. This research was partially supported by CARB 11-305, DOE (BER/ASR program) DE-SC0006711 and DESC0011105, NSF AGS-0919079, NSF AGS-1243354 and AGS1360834, and NOAA NA13OAR4310063. A.O. acknowledges fellowships from DOE and the CU Graduate School. B.P. acknowledges fellowships from EPA STAR and CIRES. R.L. acknowledges a CIRES Graduate Student fellowship. We thank our collaborators from the CalNex (Barry Lefer’s group at the University of Houston for SO2 measurements and Philip Steven’s group at Indiana University for OHR measurements), BEACHON-RoMBAS (Lisa Kaser, Armin Hansel, Thomas Karl, Luca Cappellin), and SOA field studies (Lina Hacker, Astrid Kiendler-Scharr) for providing the SO2 and monoterpene measurements that were used in the calculation of OHexp used for the estimation equation comparisons.



REFERENCES

(1) Odum, J. R.; Hoffmann, T.; Bowman, F.; Collins, D.; Flagan, R. C.; Seinfeld, J. H. Gas/Particle Partitioning and Secondary Organic Aerosol Yields. Environ. Sci. Technol. 1996, 30, 2580−2585. (2) Griffin, R. J.; Cocker, D. R.; Seinfeld, J. H.; Dabdub, D. Estimate of Global Atmospheric Organic Aerosol from Oxidation of Biogenic Hydrocarbons. Geophys. Res. Lett. 1999, 26, 2721−2724. (3) Ng, N. L.; Kroll, J. H.; Keywood, M. D.; Bahreini, R.; Varutbangkul, V.; Flagan, R. C.; Seinfeld, J. H.; Lee, A.; Goldstein, A. H. Contribution of First- versus Second-Generation Products to Secondary Organic Aerosols Formed in the Oxidation of Biogenic Hydrocarbons. Environ. Sci. Technol. 2006, 40, 2283−2297. (4) Hennigan, C. J.; Miracolo, M. A.; Engelhart, G. J.; May, A. A.; Presto, A. A.; Lee, T.; Sullivan, A. P.; McMeeking, G. R.; Coe, H.; Wold, C. E.; et al. Chemical and Physical Transformations of Organic Aerosol from the Photo-Oxidation of Open Biomass Burning Emissions in an Environmental Chamber. Atmos. Chem. Phys. 2011, 11, 7669−7686. (5) Jathar, S. H.; Miracolo, M. A.; Tkacik, D. S.; Donahue, N. M.; Adams, P. J.; Robinson, A. L. Secondary Organic Aerosol Formation from Photo-Oxidation of Unburned Fuel: Experimental Results and Implications for Aerosol Formation from Combustion Emissions. Environ. Sci. Technol. 2013, 47, 12886−12893. (6) Duplissy, J.; DeCarlo, P. F.; Dommen, J.; Alfarra, M. R.; Metzger, A.; Barmpadimos, I.; Prevot, A. S. H.; Weingartner, E.; Tritscher, T.; Gysel, M.; et al. Relating Hygroscopicity and Composition of Organic Aerosol Particulate Matter. Atmos. Chem. Phys. 2011, 11, 1155−1165. (7) Andersen, M. P. S.; Nilsson, E. J. K.; Nielsen, O. J.; Johnson, M. S.; Hurley, M. D.; Wallington, T. J. Atmospheric Chemistry of transCF3CHCHCl: Kinetics of the Gas-Phase Reactions with Cl Atoms, OH Radicals, and O3. J. Photochem. Photobiol., A 2008, 199, 92−97.

ASSOCIATED CONTENT

* Supporting Information S

The laboratory calibration experiments’ settings, results and the corresponding model results, the determination of photo fluxes at 185 and 254 nm, the small NOx impact on OHexp in the OFR, an example of the measurement results of calibration 4430

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The Journal of Physical Chemistry A (8) Nilsson, E. J. K.; Eskebjerg, C.; Johnson, M. S. A Photochemical Reactor for Studies of Atmospheric Chemistry. Atmos. Environ. 2009, 43, 3029−3033. (9) Leone, J. A.; Flagan, R. C.; Grosjean, D.; Seinfeld, J. H. An Outdoor Smog Chamber and Modeling Study of Toluene−NOx Photooxidation. Int. J. Chem. Kinet. 1985, 17, 177−216. (10) Brockmann, K. J.; Kriesche, V.; Etzkorn, T.; Volkamer, R.; Wirtz, K. The European Photoreactor Euphore: A Technical Description; Computational Mechanics Publications Ltd: Southampton, U.K., 1997; pp 457−461. (11) Rohrer, F.; Bohn, B.; Brauers, T.; Brüning, D.; Johnen, F. J.; Wahner, A.; Kleffmann, J. Characterisation of the Photolytic HONOSource in the Atmosphere Simulation Chamber Saphir. Atmos. Chem. Phys. 2005, 5, 2189−2201. (12) Wang, J.; Doussin, J. F.; Perrier, S.; Perraudin, E.; Katrib, Y.; Pangui, E.; Picquet-Varrault, B. Design of a New Multi-Phase Experimental Simulation Chamber for Atmospheric Photosmog, Aerosol and Cloud Chemistry Research. Atmos. Meas. Tech. 2011, 4, 2465−2494. (13) Presto, A. A.; Huff Hartz, K. E.; Donahue, N. M. Secondary Organic Aerosol Production from Terpene Ozonolysis. 1. Effect of UV Radiation. Environ. Sci. Technol. 2005, 39, 7036−7045. (14) Carter, W. P. L.; Cocker, D. R.; Fitz, D. R.; Malkina, I. L.; Bumiller, K.; Sauer, C. G.; Pisano, J. T.; Bufalino, C.; Song, C. A New Environmental Chamber for Evaluation of Gas-Phase Chemical Mechanisms and Secondary Aerosol Formation. Atmos. Environ. 2005, 39, 7768−7788. (15) Platt, S. M.; El Haddad, I.; Zardini, A. A.; Clairotte, M.; Astorga, C.; Wolf, R.; Slowik, J. G.; Temime-Roussel, B.; Marchand, N.; Ježek, I.; et al. Secondary Organic Aerosol Formation from Gasoline Vehicle Emissions in a New Mobile Environmental Reaction Chamber. Atmos. Chem. Phys. 2013, 13, 9141−9158. (16) Lambe, A. T.; Zhang, J.; Sage, A. M.; Donahue, N. M. Controlled OH Radical Production via Ozone-Alkene Reactions for Use in Aerosol Aging Studies. Environ. Sci. Technol. 2007, 41, 2357− 2363. (17) Kang, E.; Root, M. J.; Toohey, D. W.; Brune, W. H. Introducing the Concept of Potential Aerosol Mass (PAM). Atmos. Chem. Phys. 2007, 7, 5727−5744. (18) Lambe, A. T.; Ahern, A. T.; Williams, L. R.; Slowik, J. G.; Wong, J. P. S.; Abbatt, J. P. D.; Brune, W. H.; Ng, N. L.; Wright, J. P.; Croasdale, D. R.; et al. Characterization of Aerosol Photooxidation Flow Reactors: Heterogeneous Oxidation, Secondary Organic Aerosol Formation and Cloud Condensation Nuclei Activity Measurements. Atmos. Meas. Tech. 2011, 4, 445−461. (19) Ortega, A. M.; Day, D. A.; Cubison, M. J.; Brune, W. H.; Bon, D.; de Gouw, J. A.; Jimenez, J. L. Secondary Organic Aerosol Formation and Primary Organic Aerosol Oxidation from BiomassBurning Smoke in a Flow Reactor During Flame-3. Atmos. Chem. Phys. 2013, 13, 11551−11571. (20) Jimenez, J. L.; Canagaratna, M. R.; Donahue, N. M.; Prevot, A. S. H.; Zhang, Q.; Kroll, J. H.; DeCarlo, P. F.; Allan, J. D.; Coe, H.; Ng, N. L.; et al. Evolution of Organic Aerosols in the Atmosphere. Science 2009, 326, 1525−1529. (21) Kang, E.; Toohey, D. W.; Brune, W. H. Dependence of SOA Oxidation on Organic Aerosol Mass Concentration and OH Exposure: Experimental PAM Chamber Studies. Atmos. Chem. Phys. 2011, 11, 1837−1852. (22) Donahue, N. M.; Henry, K. M.; Mentel, T. F.; Kiendler-Scharr, A.; Spindler, C.; Bohn, B.; Brauers, T.; Dorn, H. P.; Fuchs, H.; Tillmann, R.; et al. Aging of Biogenic Secondary Organic Aerosol via Gas-Phase OH Radical Reactions. Proc. Natl. Acad. Sci. U.S.A. 2012, 109, 13503−13508. (23) Kroll, J. H.; Chan, A. W. H.; Ng, N. L.; Flagan, R. C.; Seinfeld, J. H. Reactions of Semivolatile Organics and Their Effects on Secondary Organic Aerosol Formation. Environ. Sci. Technol. 2007, 41, 3545− 3550. (24) de Gouw, J. A.; Middlebrook, A. M.; Warneke, C.; Ahmadov, R.; Atlas, E. L.; Bahreini, R.; Blake, D. R.; Brock, C. A.; Brioude, J.; Fahey,

D. W.; et al. Organic Aerosol Formation Downwind from the Deepwater Horizon Oil Spill. Science 2011, 331, 1295−1299. (25) Heering, W. UV SourcesBasics, Properties and Applications. IUVA News 2004, 6, 7−13. (26) Vasilyak, L. M.; Drozdov, L. A.; Kostyuchenko, S. V.; Kudryavtsev, N. N.; Sokolov, D. V. Main Factors of Life Time of Bactericidal Mercury Low Pressure Lamps. Light Eng. 2009, 17, 86− 89. (27) Zhang, H.; Han, Q.; Zhang, S. 254 nm Radiant Efficiency of High Output Low Pressure Mercury Discharge Lamps with Neon− Argon Buffer Gas. Appl. Mech. Mater. 2013, 325−326, 409−12. (28) Zoschke, K.; Boernick, H.; Worch, E. Vacuum-UV Radiation at 185 nm in Water Treatment  A Review. Water Res. 2014, 52, 131− 145. (29) Danet, A. F.; Bratu, M.-C.; Radulescu, M.-C.; Bratuc, A. Portable Minianalyzer Based on Cold Vapor Atomic Absorption Spectrometry at 184.9 nm for Atmospheric Mercury Determination. Sens. Actuators, B 2009, 137, 12−16. (30) Ye, J.; Shang, J.; Li, Q.; Xu, W.; Liu, J.; Feng, X.; Zhu, T. The Use of Vacuum Ultraviolet Irradiation to Oxidize SO2 and NOx for Simultaneous Desulfurization and Denitrification. J. Hazard. Mater. 2014, 271, 89−97. (31) Stinson, C.; Xia, Y. Reactions of Hydroxyalkyl Radicals with Cysteinyl Peptides in a NanoESI Plume. J. Am. Soc. Mass Spectrom. 2014, 25, 1192−1201. (32) Johnson, M. S.; Nilsson, E. J. K.; Svensson, E. A.; Langer, S. GasPhase Advanced Oxidation for Effective, Efficient in Situ Control of Pollution. Environ. Sci. Technol. 2014, 48, 8768−8776. (33) George, I. J.; Vlasenko, A.; Slowik, J. G.; Broekhuizen, K.; Abbatt, J. P. D. Heterogeneous Oxidation of Saturated Organic Aerosols by Hydroxyl Radicals: Uptake Kinetics, Condensed-Phase Products, and Particle Size Change. Atmos. Chem. Phys. 2007, 7, 4187−4201. (34) Bahreini, R.; Middlebrook, A. M.; Brock, C. A.; de Gouw, J. A.; McKeen, S. A.; Williams, L. R.; Daumit, K. E.; Lambe, A. T.; Massoli, P.; Canagaratna, M. R.; et al. Mass Spectral Analysis of Organic Aerosol Formed Downwind of the Deepwater Horizon Oil Spill: Field Studies and Laboratory Confirmations. Environ. Sci. Technol. 2012, 46, 8025−8034. (35) Lambe, A. T.; Onasch, T. B.; Croasdale, D. R.; Wright, J. P.; Martin, A. T.; Franklin, J. P.; Massoli, P.; Kroll, J. H.; Canagaratna, M. R.; Brune, W. H.; et al. Transitions from Functionalization to Fragmentation Reactions of Laboratory Secondary Organic Aerosol (SOA) Generated from the OH Oxidation of Alkane Precursors. Environ. Sci. Technol. 2012, 46, 5430−5437. (36) Li, R.; Palm, B. B.; Borbon, A.; Graus, M.; Warneke, C.; Ortega, A. M.; Day, D. A.; Brune, W. H.; Jimenez, J. L.; de Gouw, J. A. Laboratory Studies on Secondary Organic Aerosol Formation from Crude Oil Vapors. Environ. Sci. Technol. 2013, 47, 12566−12574. (37) Lambe, A. T.; Cappa, C. D.; Massoli, P.; Onasch, T. B.; Forestieri, S. D.; Martin, A. T.; Cummings, M. J.; Croasdale, D. R.; Brune, W. H.; Worsnop, D. R.; et al. Relationship between Oxidation Level and Optical Properties of Secondary Organic Aerosol. Environ. Sci. Technol. 2013, 47, 6349−6357. (38) Sander, S. P.; Friedl, R. R.; Barker, J. R.; Golden, D. M.; Kurylo, M. J.; Wine, P. H.; Abbatt, J.; Burkholder, J. B.; Kolb, C. E.; Moortgat, G. K.; et al. Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies Evaluation Number 17, JPL Publication 10-6; Jet Propulsion Laboratory, National Aeronautics and Space Administration; Pasadena, CA, 2011. (39) Ingham, T.; Goddard, A.; Whalley, L. K.; Furneaux, K. L.; Edwards, P. M.; Seal, C. P.; Self, D. E.; Johnson, G. P.; Read, K. A.; Lee, J. D.; et al. A Flow-Tube Based Laser-Induced Fluorescence Instrument to Measure OH Reactivity in the Troposphere. Atmos. Meas. Tech. 2009, 2, 465−477. (40) Lou, S.; Holland, F.; Rohrer, F.; Lu, K.; Bohn, B.; Brauers, T.; Chang, C. C.; Fuchs, H.; Häseler, R.; Kita, K.; et al. Atmospheric OH Reactivities in the Pearl River Delta  China in Summer 2006: 4431

DOI: 10.1021/jp509534k J. Phys. Chem. A 2015, 119, 4418−4432

Article

The Journal of Physical Chemistry A Measurement and Model Results. Atmos. Chem. Phys. 2010, 10, 11243−11260. (41) Ren, X.; Brune, W.; Cantrell, C.; Edwards, G.; Shirley, T.; Metcalf, A.; Lesher, R. Hydroxyl and Peroxy Radical Chemistry in a Rural Area of Central Pennsylvania: Observations and Model Comparisons. J. Atmos. Chem. 2005, 52, 231−257. (42) Sinha, V.; Williams, J.; Crowley, J. N.; Lelieveld, J. The Comparative Reactivity MethodA New Tool to Measure Total OH Reactivity in Ambient Air. Atmos. Chem. Phys. 2008, 8, 2213−2227. (43) Ren, X.; Harder, H.; Martinez, M.; Lesher, R. L.; Oliger, A.; Shirley, T.; Adams, J.; Simpas, J. B.; Brune, W. H. HOx Concentrations and OH Reactivity Observations in New York City During PMTACSNY2001. Atmos. Environ. 2003, 37, 3627−3637. (44) Ren, X.; Brune, W. H.; Mao, J.; Mitchell, M. J.; Lesher, R. L.; Simpas, J. B.; Metcalf, A. R.; Schwab, J. J.; Cai, C.; Li, Y.; et al. Behavior of OH and HO2 in the Winter Atmosphere in New York City. Atmos. Environ. 2006, 40 (Supplement 2), 252−263. (45) Yoshino, A.; Sadanaga, Y.; Watanabe, K.; Kato, S.; Miyakawa, Y.; Matsumoto, J.; Kajii, Y. Measurement of Total OH Reactivity by Laser-Induced Pump and Probe TechniqueComprehensive Observations in the Urban Atmosphere of Tokyo. Atmos. Environ. 2006, 40, 7869−7881. (46) Shirley, T. R.; Brune, W. H.; Ren, X.; Mao, J.; Lesher, R.; Cardenas, B.; Volkamer, R.; Molina, L. T.; Molina, M. J.; Lamb, B.; et al. Atmospheric Oxidation in the Mexico City Metropolitan Area (MCMA) during April 2003. Atmos. Chem. Phys. 2006, 6, 2753−2765. (47) Lu, K. D.; Rohrer, F.; Holland, F.; Fuchs, H.; Brauers, T.; Oebel, A.; Dlugi, R.; Hu, M.; Li, X.; Lou, S. R.; et al. Nighttime Observation and Chemistry of HOx in the Pearl River Delta and Beijing in Summer 2006. Atmos. Chem. Phys. 2014, 14, 4979−4999. (48) Ryerson, T. B.; Andrews, A. E.; Angevine, W. M.; Bates, T. S.; Brock, C. A.; Cairns, B.; Cohen, R. C.; Cooper, O. R.; de Gouw, J. A.; Fehsenfeld, F. C.; et al. The 2010 California Research at the Nexus of Air Quality and Climate Change (CALNEX) Field Study. J. Geophys. Res.: Atmos. 2013, 118, 5830−5866. (49) Ortega, J.; Turnipseed, A.; Guenther, A. B.; Karl, T. G.; Day, D. A.; Gochis, D.; Huffman, J. A.; Prenni, A. J.; Levin, E. J. T.; Kreidenweis, S. M.; et al. Overview of the Manitou Experimental Forest Observatory: Site Description and Selected Science Results from 2008 to 2013. Atmos. Chem. Phys. 2014, 14, 6345−6367.

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