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1 Atmospheric Environment xxx (2009) 1 9 Contents lists available at ScienceDirect Atmospheric Environment journal homepage: Simultaneous DOAS and mist-chamber IC measurements of HONO in Houston, TX Jochen Stutz a, *, Hoon-Ju Oh a, Sallie I. Whitlow b, Casey Anderson b, Jack E. Dibb b, James H. Flynn c, B. Rappenglück c, B. Lefer c a Department of Atmospheric Sciences, University of California, Los Angeles, CA , USA b Climate Change Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire, USA c Department of Earth and Atmospheric Science, University of Houston, USA article info abstract Article history: Received 10 September 2008 Received in revised form 20 January 2009 Accepted 2 February 2009 Keywords: Nitrous acid HONO Measurement techniques Nitrous acid is an important component of nighttime N-oxide chemistry, and provides a significant source of both OH and NO in polluted urban air masses shortly after sunrise. Several recent studies have called for new sources of HONO to account for daytime levels much higher than are consistent with current understanding. However, measurement of HONO is problematic, with most in-situ techniques reporting higher values than simultaneous optical measurements by long-path DOAS, especially during daytime. The discrepancy has been attributed to positive interference in the in-situ techniques, negative interference in DOAS retrievals, the difficulty of comparing the different air masses sampled by the methods, or combinations of these. During August and September 2006, HONO mixing ratios from collocated long-path DOAS and automated mist-chamber/ion chromatograph (MC/IC) systems ranged from several ppbv during morning rush hour to daytime minima near 100 pptv. Agreement between the two techniques was excellent across this entire range during many days, showing that both instruments accurately measured HONO during this campaign. A small bias towards higher LP-DOAS observations at night can be attributed to slow vertical mixing leading to pronounced HONO profiles. A positive daytime bias of the MC/IC instrument during several days in late August/early September was correlated with photochemically produced compounds such as ozone, HNO 3 and HCHO, but not with NO 2,NO x,ho 2 NO 2, or the NO 2 photolysis rate. While an interferant could not be identified organic nitrites appear a possible explanation for our observations. Ó 2009 Elsevier Ltd. All rights reserved. 1. Introduction Since the first identification of HONO in the Los Angeles atmosphere by Platt et al. (1980), the photolysis of HONO HONO D hn / OH D NO (R1) is known as the primary source of OH in the early morning, with diurnally averaged contributions to the OH budget of up to 34% (Alicke et al., 2002, 2003; Aumont et al., 2003; Kleffmann et al., 2005). Consequently, HONO formation and photolysis impacts ozone formation, the oxidation of various pollutants, as well as the formation of aerosol (Aumont et al., 2003; Harris et al., 1982; Jenkin et al., 1988). The discovery of HONO over sunlit snow surface showed that its photolysis is also important in polar regions (Dibb et al., 2004; Honrath et al., 2002; Liao et al., 2006). * Corresponding author. Tel.: þ ; fax: þ address: jochen@atmos.ucla.edu (J. Stutz). Despite its importance the details of HONO formation remain a mystery. Laboratory studies showed that HONO is formed through the heterogeneous reaction of NO 2 with surface adsorbed water. Because in the laboratory this process is first order in NO 2,andthe HONO and surface adsorbed HNO 3 yields are w50%, the following qualitative stoichiometry was proposed: NO 2 þ NO 2 þ H 2 O / HONO þ HNO 3 (Goodman et al., 1999; Finlayson-Pitts et al., 2003; Jenkin et al., 1988; Kleffmann et al., 1998). Other HONO formation mechanisms, for example involving NO (Calvert et al., 1994; Sjödin and Ferm, 1985), or soot particles (Gerecke et al., 1998; Kalberer et al., 1999), and the formation in various combustion processes (Kirchstetter et al., 1996; Kurtenbach et al., 2001) havebeen shownto be insufficient to explain urban HONO mixing ratios. To explain observations of daytime HONO levels above the photostationary supported by gas-phase formation, OH þ NO / HONO, and photolysis (Acker et al., 2006a,b; Kleffmann et al., 2006), new photo-enhanced reactions have been proposed (Kleffmann, 2007). The photolysis of surface adsorbed nitrate or nitric acid (Zhou et al., 2002) is believed to be the main source of HONO in polar regions. NO 2 reduction on surface adsorbed organic impurities, such as /$ see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi: /j.atmosenv

2 2 J. Stutz et al. / Atmospheric Environment xxx (2009) 1 9 photosensitized humic acid, has been shown to occur in the laboratory (Stemmler et al., 2007). Most recently Li et al. (2008a) showed that HONO can be formed upon the gas-phase reaction of photolytically excited NO 2 with water. Despite these new laboratory results our knowledge on the behavior of HONO in the atmosphere is still mostly based on field observations. A number of analytical methods have been used to detect HONO. Differential Optical Absorption Spectroscopy (DOAS) was used to first discover atmospheric HONO (Platt et al., 1980), and has subsequently been used in a large number of studies. DOAS is based on the unique, and artifact-free, identification and quantification of HONO through its narrow band UV absorptions in the open atmosphere with detection limits in the range of ppt (Platt and Stutz, 2008). The interpretation of DOAS measurements is often challenging due to the long absorption path-length required. Other spectroscopic methods, such as tunable diode laser spectroscopy (Li et al., 2008b), cavity enhanced absorption spectroscopy (Gherman et al., 2008) and photofragmentation/laser induced fluorescence (Liao et al., 2006) are not yet widely used. A number of chemical methods have been introduced over the years. Most of these methods are based on the detection of the nitrite ion after adsorption of HONO onto a solid surface (dry denuder) or water/aqueous solution (wet denuder, mist-chamber). The most widely used chemical methods have been annular denuders, which are based on the rapid gas-phase diffusion in a laminar flow between two surfaces (Febo et al., 1996; Acker et al., 2006a). A different way of sampling gas-phase HONO is the mistchamber sampler, wherein a cloud of small water droplets collects water soluble gases (Dibb et al., 2002, 2004). The aqueous sample can be analyzed by a variety of techniques to quantify different gases, such as HONO and HNO 3 (Talbot et al., 1990). Ion-chromatography is most commonly used for analysis, and provides quantification of HNO 3 and HONO (as NO 3 and NO 2 ) in a single chromatogram for each sample. It is well established that HNO 3 overwhelmingly dominates the NO 3 signal. However, in very cold and dry conditions like those at the South Pole and Summit, Greenland, HONO may account for less than half the measured NO 2. Kleffman and Wiesen (2008) describe problems with published HONO data from polar regions and suggest that various heterogeneous reactions of NO 2 on the wet surfaces of most chemical samplers for HONO create large artifacts (both HONO and other nitrites produced in the sampler) that must be corrected for. The latest chemical method introduced is the LOPAP technique which uses sulphanilamide in HCl to trap HONO in a short stripping coil. Quantification is achieved by optical absorption after addition of N-napthylendiamine-dihydrochloride (Kleffmann et al., 2002). Chemical methods often have detection limits which are superior to those of direct spectroscopic methods. However, they suffer from possible sampling artifacts and chemical interferences. While all methods have been extensively tested in the laboratory, the performance of these systems in the open atmosphere is difficult to assess (Appel et al., 1990; Febo et al., 1996; Kleffmann et al., 2006; Liao et al., 2006; Spindler et al., 2003). Typically chemical and spectroscopic methods agree well during the night but chemical techniques generally overestimate HONO during daytime. In most cases this has been attributed to unrecognized artifacts and interferants of the chemical method. Only the study by Kleffmann et al. (2006) showed good agreement between a LOPAP and a DOAS instrument during the day and night. Kleffman and Wiesen (2008) argue that the 2-coil LOPAP is less impacted by artifacts and chemical inferences, but that all other chemical methods fail to adequately account for them. Understanding possible artifacts of HONO measurements is crucial for our ability to accurately determine daytime HONO levels Table 1 Detected mixing ratio range and detection limits for trace gases measured by UCLA s LP-DOAS. and assess the impact of HONO photolysis on the OH budget. Here we present results from an intercomparison between UCLA s LP- DOAS instrument and UNH s mist-chamber IC system during the 2006 TRAMP experiment in Houston, TX. 2. Experimental The observations presented here were performed during the TexAQS Radical Measurement Program (TRAMP), a component of TexAQS-2006 field effort in Houston, TX, from August 15 to September 30, The TRAMP super-site was located on the roof of the North Moody tower (an 18-story dorm building) on the University of Houston campus. In-situ measurements by MC/IC were made with the sample inlet mounted at the top of a 10 m tower located near the northeast corner of the building. The LP- DOAS telescope was located in the northwest corner. Meteorological data on the roof of the Moody tower was acquired on a 12 m tower in between the two locations of the HONO measurements. Measurements of a number of other parameters (actinic flux, etc.) and chemical species (O 3, CO, NO, NO 2, HCHO, HNO 3, VOCs, etc.) were made either from the meteorological tower or the structure that hosted the MC/IC LP-DOAS Mixing ratio range (ppb) HONO (0.045) O (2.5) NO (0.12) HCHO (0.25) Detection limits a (average in parenthesis) (ppb) a Please note that DOAS calculates an error and detection limit for every absorption spectrum. Detection limits vary with visibility and instrument behavior. UCLA s LP-DOAS instrument consists of a 1.5 m double Newtonian telescope, which is used to send a parallel beam of light from a Xe-arc lamp onto an array of quartz corner-cube retroreflectors. The light returning from the retroreflectors is received by the same telescope and, through a fiber mode-mixer, fed into a 500 mm Czerny Turner Spectrometer (ACTON Spectra-Pro 500) with a photodiode array detector (Hoffmann Messtechnik). In Houston the LP-DOAS measured the atmospheric absorptions of O 3,NO 2, HCHO, and HONO (Table 1) between the telescope and three retroreflector arrays in downtown Houston at a distance of 4 5 km (Fig. 1). Measurements alternated between the retroreflectors at different heights. Here we concentrate on the lowest path which Fig. 1. Schematic drawing of the experimental setup during the TRAMP experiment 2006.

3 J. Stutz et al. / Atmospheric Environment xxx (2009) averaged over the m height interval. The middle light path ( m) will be used to investigate the impact of vertical trace gas profiles on the intercomparison. Because of the multiple light paths, DOAS measurements on the lowest light path were not continuous. The measurement interval varied from 7 to 30 min depending on visibility. LP-DOAS measurements of O 3,NO 2, HCHO, and HONO were made in the spectral range of nm with a spectral resolution of 0.5 nm (see details in Alicke et al., 2002). As discussed in Stutz and Platt (1996), errors of reported mixing ratios are calculated as 1s statistical uncertainties by the analysis procedure for each individual spectrum and trace gas. The systematic errors of the reported trace gas mixing ratios are dominated by the uncertainties of the absorption cross-sections of HONO, NO 2, and O 3,of5%, 3%, and 3%, respectively (Stutz et al., 2000; Vandaele et al., 2002; Bass and Paur, 1984). The systematic error of the DOAS spectrometer was <3% (Platt and Stutz, 2008) MC/IC A two-channel version of the UNH mist-chamber/ion chromatograph (MC/IC) system was used for TRAMP. Samples were collected for 5-min intervals, alternating between the two samplers. During collection of a sample in one MC, the previous sample collected in the other MC was automatically injected and analyzed in the IC. Data series are thus continuous, at 5-min resolution, for blocks of approximately 40 h duration between replenishment of IC eluents and the MilliQ ultrapure water used as the sampling solution in the MC. Each time eluent was refreshed the ICs were recalibrated using NIST certified aqueous solutions. Downtime for this routine maintenance was approximately 2 h every other day. Air was pulled into the MC samplers through a single (shared) 3-m long heated Teflon inlet tube (O.D. 0.5 inches), fitted with a 90 mm Zefluor Teflon filter at the end to prevent particles entering the inlet or MC. The heater and insulation around the inlet tubing excluded light, thus the short residence time (0.1 s) in the dark minimized heterogeneous and photolytic production of HONO in the inlet (a potential positive artifact suggested by Kleffman and Wiesen, 2008). Initially the inlet filter was replaced twice a day to minimize build up of particulates, especially NH 4 NO 3 (which might react with, or release, the acidic gases of interest). When no significant changes in signal were observed at filter replacement times during the first week, and AMS data indicated that particulate NO 3 was rarely observed at the sampling site (Ziemba et al., in this issue), the frequency of changes was reduced to once every 2 days, at the same time as other routine maintenance. Nitrite was well above detection limits by IC in all TRAMP samples (3 nmol l 1 in the aqueous sample, corresponding to an atmospheric mixing ratio of w5 ppt HONO for 5-min integration). Examination of the calibration curves throughout the campaign (n ¼ 22 for each of the IC channels) indicates our uncertainty in the quantification of nitrite concentrations in the aqueous sample solutions were on the order of 5%. Considering the precision of our determination of the sample volumes (both air sampled and water remaining in the MC for each sample) yields an overall uncertainty in the determination of the gas-phase mixing ratio of soluble nitrite of 10%. As will be shown below, most of the time HONO was the overwhelmingly dominant component of the NO 2 signal in the MC/IC system during TRAMP and the MC/IC NO 2 data is reported as HONO. Fig. 2. Overview of the TRAMP HONO data set as measured by mist-chamber/ionchromatography (black points) and the lower light path of the long-path DOAS instrument (red circles). Error bars are omitted to add clarity to this figure. Periods of north-easterly winds are identified by blue symbols at the top of the graphs. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Fig. 3. Hourly averaged HONO mixing ratios during the entire experiment for MC/IC and LP-DOAS. Error bars denote the standard deviation of the mixing ratios for each hourly interval.

4 4 J. Stutz et al. / Atmospheric Environment xxx (2009) Supplemental measurements Meteorological measurements were performed with a R.M. Young sensor for wind speed and wind direction, and a Vaisala, Inc. temperature/relative humidity HMP45C sensor. Carbon monoxide measurements were made using a TEI 48C Trace Level enhanced gas filter correlation wheel instrument. A trace level TEI 42C chemiluminescence instrument was used to provide measurements of NO. Photolysis rates were determined with a 2p steradian zenith viewing scanning actinic flux spectroradiometer (SAFS) (Shetter et al., 2003). Hydrocarbons were measured online using a Perkin Elmer gas-chromatographic system. 3. Results In general, the measurements by the two techniques track each other extremely well (Figs. 2 and 3) capturing the diurnal variation of HONO with mixing ratios over 2 ppb in the late night/early morning and daytime minimum mixing ratios on the order of, or below, 100 ppt. Variations due to meteorological conditions, indicated by the identification of NE winds in Fig. 2, clearly modulate the HONO mixing ratios in Houston. The contrast between the low- HONO period from 8/25 to 8/31 and periods with higher HONO levels will be discussed below. The average diurnal behavior of HONO, as observed by both instruments (Fig. 3), shows an increase throughout the night, from w100 ppt at 18:00 to maximum levels around 6:00, just before sunrise. The larger day-to-day variations of HONO observations (indicated by the bars in Fig. 3) during the night are caused by variations in the nocturnal vertical stability, the timing of the boundary layer breakup, and the strength of the morning rush hour (see also Ziemba et al., in this issue). HONO mixing ratios decrease in the morning reaching levels of ppt around noon. The average diurnal variation of HONO mixing ratios agrees with many previous observations of HONO in polluted urban areas (Acker et al, 2006a; Alicke et al, 2002, 2003; Appel et al, 1990; Febo et al., 1996; Kleffmann et al, 2006; Platt et al, 1980). To provide a more quantitative intercomparison of the instruments a linear regression analysis, weighed with errors of both Fig. 4. Correlation of MC/IC and LP-DOAS HONO observations. Red solid lines indicate a linear fit weighted by errors of both instruments. The results of the linear least squares analysis and the correlations can be found in Table 2. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Table 2 Correlations between HONO mixing ratios measured by LP-DOAS and MC/IC. To account for the influence of the different sampling strategies and to ensure a good quality, Q, of the regression, measurement uncertainties were multiplied by 2.5. HONO (measurement error 2.5) NO 2 # of points y-intercept Slope Q R 2 R 2 All data :00 5: :00 9: :00 15: :00 19: :00 24: Fig. 5. Comparison of MC/IC HONO mixing ratios with the observations made with the lower (black) and middle (blue) light paths of the LP-DOAS. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

5 J. Stutz et al. / Atmospheric Environment xxx (2009) instruments (Press et al., 1986), was performed. To account for the higher MC/IC sampling frequency, its HONO mixing ratios were integrated over the measurement period of one LP-DOAS observation. The comparison of all data and the results of the regression analysis (667 data points) are shown in Fig. 4a. The slope of this weighted regression is with a negligible y-axis intercept. However, the quality of the linear fit was poor, i.e. Q < (Press et al., 1986), indicating that the statistical instrument uncertainties did not fully capture the variability of the data. This is not surprising considering that the DOAS instrument averages over an extended light path while the MC/IC is an in-situ system. To achieve a regression of acceptable quality (Q ¼ 0.03) we increase the observational errors by 2.5 to take into account the difference in sampled air masses (Table 2). The slope of this regression remained the same but the error of the slope increased by a factor of w2.5. In the following we will use the data with higher errors to perform our analysis (Table 2). The correlation between the two instruments during the entire experiment was R 2 ¼ Comparing with the R 2 ¼ 0.81 for DOAS vs. in-situ NO 2 shows that much of the difference between the measurements is due to the different sampling strategies. Despite the difference in sampling strategy the two HONO instruments agree better than w15% throughout the entire experiment. The slightly higher values observed by the LP-DOAS can be explained by the nocturnal measurements. For the 19:00 24:00 time period (Fig. 4b) a slope of , close to that of the entire data set was found. The nocturnal data reveals a bias caused by the vertical distribution of HONO at night (Fig. 5). The lower LP-DOAS light path (20 70 m altitude) used for the intercomparisons in Figs. 2 4, showed higher HONO levels than the middle light path ( m altitude). The MC/IC mixing ratios generally fall between these two mixing ratios (Fig. 5). While it is not possible to quantitatively extract 70 m HONO mixing ratios from the LP-DOAS measurements, the MC/IC mixing ratios are always equal to or lower than those of the lower light path at night. Consequently the comparison of the two techniques will show a bias towards higher LP-DOAS mixing ratios at night, which explains the slopes above 1 in Fig. 4b and Table 2. Since the correlation analysis of all data (Fig. 4a) is strongly influenced by the larger nocturnal HONO levels, the overall data set will also show this bias. The linear regressions during other times of stable vertical stability, i.e. 0:00 5:00 and 5:00 9:00 in Table 2, show similar slopes and R 2 than those for the 19:00 24:00 period. The quality Fig. 6. Comparison of MC/IC and LP-DOAS HONO mixing ratios during a relatively unpolluted week in Houston from 8/24 to 8/31 and a polluted week 8/31 9/7. Error bars show the 1s error of each DOAS measurements. Please refer to the text for a discussion of the MC/IC errors. Fig. 7. Correlation of the difference of MC/IC/LP-DOAS HONO mixing ratios from 9:00 to 15:00, averaged for each day with meteorological parameters; wind speed, wind direction and relative humidity.

6 6 J. Stutz et al. / Atmospheric Environment xxx (2009) 1 9 of the 00:00 05:00 regression is low (Table 2) due to the impact of the vertical HONO gradients, which are strongest in this time period. The R 2 of HONO and NO 2 during this time period are similar, confirming the variability of the data due to vertical gradients. The comparison of the two HONO instruments during daytime periods, i.e. 9:00 15:00 and 15:00 19:00, reveals much smaller slopes and R 2 than those during the night (Fig. 3, Table 2). In particularly during the 9:00 15:00 period the linear regression yields a slope of only and a R 2 of This is not reflected in the NO 2 data, which shows larger R 2 of 0.95 during this period than during the night (Table 2), indicating that the difference in sampled air masses is much less pronounced when the atmosphere is better mixed. Fig. 3 and Table 2 seem to indicate that the MC/IC instrument is systematically higher during the daytime hours, when HONO levels are lowest. However, data from the unpolluted week of 8/25 8/31 (Fig. 6a) reveals that the agreement between the two instruments is quite good during these low-hono days. A regression for the week of 8/25 8/31 results in a slope of , a y-intercept of ppt and a R 2 of 0.78, supporting the conclusion that both instruments agree very well even at the low HONO mixing ratios during this week. A systematic deviation of the two instruments at low HONO levels can therefore be excluded. The difference in daytime HONO mixing ratios that are displayed in Fig. 3 were apparent solely during nine days of the experiment. These days all showed the characteristics of heavy pollution episodes (Fig. 6b). The discrepancy is above the detection limits of both instruments, which, as discussed above, agreed quite well during other low HONO periods. 4. Discussion The comparison between the MC/IC and the LP-DOAS was quite excellent during most of the TRAMP experiment, with an agreement of 15% or better, even during periods of low HONO mixing ratios (Fig. 6). A previous intercomparison with a PF-LIF system in a polar environment implied possible problems with the accuracy of the MC/IC system (Liao et al., 2006). While the polar environment is quite different from the more complex conditions in Houston, our results showed that the NO 2 data from the MC/IC instrument indeed represented HONO during most of the experiment, in particular during relatively clean periods. The results also seem to rule out a negative bias in the DOAS data which has been suggested previously. The relationships between the magnitude of the MC/IC vs. DOAS midday difference and a variety of meteorological and chemical parameters provide clues about the source of the daytime bias. By averaging this difference from 9:00 to 15:00 for each day of the experiment, the relationship between various meteorological and chemical parameters can be illustrated (Figs. 7 and 8). All of the days with particularly large enhancements of MC/IC compared to DOAS HONO were under the influence of winds from the northeast ( ). However, several other days with midday winds from this sector had small, or even no, discrepancy between the HONO measurements. It should be noted that over the duration of the experiment winds were from this north to east sector 39% of the time (see the blue diamonds in Fig. 2) and most of that time the agreement between the two techniques was within the combined uncertainties. The 9 days when average midday HONO discrepancies were >140 ppt represent just 6% of all sampling times and Fig. 8. Comparison of the difference of MC/IC/LP-DOAS HONO mixing ratios from 9:00 to 15:00 for each day of the experiment with average ozone (panel a) and HNO 3 (panel b) mixing ratios. Panels c and d show the same data as a correlation plot. The results for the linear regression analysis are DHONO ¼ ( 91 32) ppt þ ( ) (O 3 ); R 2 ¼ 0.62 and DHONO ¼ ( 10 17) ppt þ ( ) (HNO 3 ); R ¼ 0.72.

7 J. Stutz et al. / Atmospheric Environment xxx (2009) only 16% of the time that winds from the northeast impacted the tower site. The Houston ship channel and associated petrochemical facilities are just a few km northeast of Moody tower. Highly reactive volatile organic compounds (HRVOCs) from this region often contribute to O 3 events in the greater Houston area (Karl et al., 2003). We examined time series of several reactive alkenes, and the ratios of these alkenes to ethyne, to see if the HONO discrepancy could be linked to enhanced releases of these O 3 precursors. No significant relationships were found. The HONO discrepancies had a weak inverse relation with wind speed (Fig. 7). Lighter winds might simply allow more time for photochemical production of species suspected to interfere with the instruments between the suspected source(s) near the ship channel and Moody tower. Alternatively reduced vertical mixing during low wind periods could lead to a larger build up of these possible interferants. The possibility that light winds could allow HONO produced on the surfaces of Moody tower to build up and influence our measurements was investigated with model calculation, which showed a negligible impact on our observations. Smaller differences between the two methods were found for higher relative humidities, but it seems this mainly reflects the dependence on wind direction. Cleaner air masses coming from the Gulf were moister than the polluted air masses arriving at the sampling site from the north and east. The strongest correlations were found between the HONO difference and pollution tracers, but especially strong with secondary pollutants formed photochemically (O 3, HNO 3, HCHO). This is particularly clear in the comparison of the daily averaged 9:00 15:00 HONO differences and the O 3 and HNO 3 mixing ratios measured by the DOAS and the MC/IC, respectively (Fig. 8). The correlation coefficients, R 2, of the daily averaged daytime HONO difference were 0.62 and 0.72 for ozone and HNO 3 respectively. To provide further evidence of the correlation we applied linear regressions to a number of other parameters using the difference between the two instruments for all LP-DOAS measurements taken from 9:00 to 15:00 during the experiment (Fig. 9 and Table 3). The R 2 for O 3 and HNO 3 were somewhat lower than those of the daily averaged values, but still significant (Fig. 9). Similar correlations were also found for HCHO, another photochemically produced pollution tracer. The somewhat weaker correlation with CO seems to be indicative of higher pollution levels, most likely from Fig. 9. Correlation of the difference of MC/IC/LP-DOAS HONO mixing ratios for all data points during the 9:00 15:00 time period throughout the experiment. Red lines indicate a linear regression weighted by errors of both instruments. Correlation coefficients are given in Table 3. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

8 8 J. Stutz et al. / Atmospheric Environment xxx (2009) 1 9 Table 3 Correlations between HONO LP-DOAS/MC/IC difference and other parameters measured during the experiment for the period from 9:00 to 15:00. Parameter R 2 (141 data points) O HNO HCHO 0.52 CO 0.34 NO NO x 0.05 J(NO 2 ) 0.10 HO 2 NO OH 0.01 Wind speed 0.18 R.H combustion sources, during times of larger HONO discrepancies. No significant correlation was found for NO 2,NO x, and J(NO 2 ), ruling out formation processes that directly involve the conversion of these species to HONO, i.e. inlet effects. HO 2 NO 2 was investigated as a possible interferant in the MC/IC instrument that would be formed preferentially at higher pollution levels. At the high daytime temperatures in Houston of around 30 C the mixing ratios of HO 2 NO 2 are predominantly determined by its equilibrium with HO 2 and NO 2 :HO 2 þ NO 2 4 HO 2 NO 2, i.e. the thermal decay of HO 2 NO 2 is much faster than the loss rates due to photolysis and reaction with OH. Equilibrium HO 2 NO 2 mixing ratios are thus an upper estimate and a very good approximation of its true levels in Houston. While HO 2 NO 2 mixing ratios reach up to 150 ppt during pollution episodes, the correlation with the HONO discrepancy is insignificant (Fig. 9), with a R 2 of Considering, in addition, that the collection efficiency of HO 2 NO 2 in the mistchamber is below 100% and that the inlet is heated to 40 C it is very unlikely that HO 2 NO 2 is the main source of the discrepancy, although it may explain a small portion of MC-DOAS difference. Another class of possible interferants is organic nitrites. However, little is known about their ambient concentration and their atmospheric chemistry, and we can only speculate about their potential significance. Laboratory studies (Akimoto and Takagi, 1986; Takagi et al., 1986) indicate that methyl nitrite can be formed heterogeneously from the methanol þ NO 2 reaction, with a 3000 times faster rate than the analogous reaction of NO 2 þ H 2 O. A photoenhancement of these reactions (Akimoto and Takagi, 1986) was observed, similar to recent reports on HONO formation (Kleffmann, 2007). The photolytic lifetime of methyl nitrite, on the other hand, appears to be w3 min (Taylor et al., 1980), shorter than that of HONO. One can speculate that with the high methanol levels in Houston (Karl et al., 2003) the formation of methyl nitrite could at times contribute to the nitrite signal in the MC/IC, despite the faster photolysis. Other organic nitrites could potentially also contribute, but even less is known about their chemistry. It is interesting to speculate about the potential impact of the presence of 100 ppt levels of methyl nitrite, which could explain the MC/IC DOAS discrepancy. Methyl nitrite photolysis ultimately forms HO 2 and HCHO, which, in the high NO environment of Houston, will be rapidly converted to OH. Using a noontime methyl nitrite photolysis rate of s 1 and a unity quantum yield (Taylor et al., 1980) one derives an OH formation rate of w molec. cm 3 s 1, compared to w molec. cm 3 s 1, w molec. cm 3 s 1, and ws molec. cm 3 s 1 for O 3, HCHO, and HONO photolysis, as observed at noon on 9/1/06, respectively. The impact of methyl nitrite could thus be substantial, even at levels below 100 ppt. In order to assess the possible error introduced by interpreting the MC/IC data during the 9 days of disagreement as HONO we performed model calculations using the LaRC 0-D photochemical box model, which is based on a modified version of the condensed scheme in Lurmann et al. (1986). Model runs were performed in the photostationary steady-state mode, constrained by the observations during TRAMP. Using the MC/IC data compared to the LP-DOAS data leads to an increase of the OH concentration of up to 20% around noon during polluted days. Interpretation of the discrepancy as methyl nitrite could lead to an even larger impact. 5. Conclusions Throughout the 5 weeks of the TRAMP experiment HONO observations made by the UCLA LP-DOAS and UNH MC/IC were in excellent agreement. Dramatic morning rush hour peaks (see also Ziemba et al., in this issue) with mixing ratios near 2 ppb, and low mixing ratios below 100 ppt during clean days, were equally well measured to within 15% by both instruments. Differences during periods of vertical stability at night can be explained by the distinct vertical profile of HONO. Neither method seemed to suffer from noticeable artifacts and the soluble gas-phase nitrite measured by the MC/IC instrument can be interpreted as HONO, except during daytime periods of the most polluted days of the experiment. On about 1/4 of the sampling days 6 h around solar noon the MC/IC technique appears to suffer a positive bias. Strong correlations between the timing and magnitude of the MC/IC HONO bias and mixing ratios of O 3, HNO 3 and HCHO suggest that the interfering compound(s) are photochemically produced. We excluded a number of possible interferants, such as NO 2, and HO 2 NO 2, which did not show sufficient correlation with the MC/IC bias. However, we were not able to clearly identify the interferant(s), and we propose that organic nitrites, which could lead to a soluble nitrite signal in the MC, deserve more attention. It should be noted that in previous campaigns at South Pole (summertime) and central Greenland (springtime) HONO mixing ratios in the ppt range from the MC/IC were suggested to be too high (compared to NO x and OH) due to unknown interferants. The results from Houston suggest that the polar interferants either do not scale with NO x in urban air, or are thermally labile, hence too-short lived in Houston to be significant most of the time. It is unlikely that the unknown, but strongly pollution-related, interferant(s) observed during TRAMP are also the source of apparent artifacts in polar regions. Our observations in combination with box model calculations demonstrate that the accurate measurement of daytime HONO, as well as the identification of the possible MC/IC HONO interferant, is important for a better understanding of daytime radical chemistry. Consequently, further intercomparisons of HONO measurement techniques together with observations targeted to identify daytime interferants spanning a variety of environments are needed. Acknowledgements This study was supported by a Career Award from the National Science Foundation Atmospheric Chemistry Program (ATM ), the Texas Environmental Research Consortium, and the Houston Advanced Research Center (Grants H78, H86, and H104C). References Acker, K., et al., 2006a. Nitrous acid in the urban area of Rome. Atmos. Environ. 40 (17), Acker, K., Möller, D., Wieprecht, W., Meixner, F.X., Bohn, B., Gilge, S., Plass- Dülmer, C., Berresheim, H., 2006b. Strong daytime production of OH from HNO 2 at a rural mountain site. Geophys. Res. Lett. 33 (2).

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