GEHP – same as GEH, but with addition of photo-induced HONO production; \end{itemize} \begin{figure*}[t] \includegraphics[width=13cm]{acp-2012-40-f01.pdf} \caption{Comparison of measured vs. simulated HONO time series at the UH Moody Tower for the time period 25 August–20 September 2006. Dots represent measured values, the solid lines represent CMAQ predicted concentration from G, GEH, and GEHP cases (explanation see text). Dashed vertical lines indicate midnight times. (a): Comparison with data measured in-situ by a MC/IC system at the top of the Moody Tower, at 60 m a.g.l. (b–d): Time series comparison of HONO measured from the Moody Tower by DOAS low light-path (b), middle light path (c), and upper path (d).} \end{figure*} \section{Results and discussion} \subsection{Evaluation of HONO modeling} Simulated HONO concentrations were compared with values measured in-situ by a mist-chamber/ion chromatograph (MC/IC) system at the top of the Moody Tower (60 m a.g.l.) on the University of Houston (UH) campus (Stutz et al., 2010) and are shown in Fig. 1a for simulation cases G, GEH, and GEHP. The highest HONO mixing ratios up to 2 ppbv were measured during nighttimes and in the early mornings while daytime concentrations are much lower, but still appreciable. HONO values simulated with only gas-phase chemistry (case G) persistently show significant under prediction of HONO concentrations. HONO mixing ratios from GEH and GEHP cases are much closer to the observed values (e.g. 31 August, 12 and 20 September). The advantage of including photochemical HONO sources can nicely be seen on 30 August, 7, 9, and 13 September (and others) when daytime HONO values from the GEHP case are higher and closer to measurements than HONO values from the GEH case. In some cases a mismatch between observed and simulated HONO values occurs (e.g. 1 and 6 September). This is mostly related to mismatch in NO₂ concentrations as discussed further below. In order to evaluate HONO modeling for different altitudes in the urban boundary layer observational HONO data detected by Differential Optical Absorption Spectroscopy (DOAS) were utilized. These measurements were taken along different paths between the Moody Tower super site and Downtown Houston (Stutz et al., 2010). The low light-path detected mixing ratios between 20–70 m height which corresponds to the first and second CMAQ model layer, the middle light-path between 70–130 m corresponding to the second and third layer, and the upper light-path between 130–300 m, which falls into model layers three to five. Figures 1b–d shows comparisons of measured and simulated HONO values. While daytime measurements show only slight dependence on altitude, HONO mixing ratios at night and early morning decrease with altitude, with maximum values reaching about 2 ppbv at the low level and only about 0.5 ppbv at the upper level. Contrary to the measured values, HONO mixing ratios from the G case do not show variation with height. HONO values obtained from GEH and GEHP cases correctly capture the trend towards lower nighttime and early morning mixing ratios at higher altitudes. In addition, including photolytic HONO sources in the GEHP case resulted in average 100 ppt higher daytime HONO concentrations at the low DOAS level and an average daytime increase of 50 and 30 ppt at the middle and upper DOAS levels, respectively. Since most of the photolytic HONO production occurs by NO₂ reaction at the surface, stronger increase was obtained at the lower altitudes and changes in HONO mixing ratios at higher altitudes can be explained by upward transport of HONO (see discussion in Sect. 3.2 and bottom graph in Fig. 9). Figure 2 shows an average diurnal variation of HONO and NO₂ based on the same data set (25 August–20 September 2006) for all simulated cases as well as MC/IC observed values. This presentation summarizes clearly the general differences in HONO model simulations. It can be seen that higher daytime values were obtained from the GEHP case, which includes photolytic HONO formation, in comparison with the GEH case, in which heterogeneous HONO production dominates HONO sources. The model tends to overpredict NO₂ during nighttime and early morning which causes overprediction of simulated HONO at those times. \begin{figure}[t] \includegraphics[width=8.3cm]{acp-2012-40-f02.pdf} \caption{Average diurnal variation of HONO (top) and NO₂ (bottom) based on data for 25 August–20 September 2006 at the top of the Moody Tower, at 60 m a.g.l. Measured data obtained by MC/IC.} \end{figure} Figure 3 shows a time series comparison of NO₂ measured by DOAS with the values simulated with the GEH case. Too high NO₂ concentrations on 1 and 4 September resulted in over prediction of HONO concentrations at those times. In contrast, NO₂ under prediction on 2, 7, and 8 September leads to under predictions of HONO. There may be several reasons for NO₂ mismatches, such as uncertainties in emission inventory or mixing layer height, in some cases these mismatches can be related to predictions of meteorological parameters. For example, on the night of 1 September the measurements indicate calm conditions, while the model predicts strong southerly winds, causing lower modeled concentrations at the location of measurements. On 6 September the model fails to predict precipitation correctly which in turn directly affects the concentration of pollutants. The correlation coefficient between HONO values measured at the DOAS low path and those simulated with GEH case is 0.68. However, when data points with wrong NO₂ prediction were ignored and only NO₂ values simulated within 70 more OH from the GEHP case as compared to GEH case during morning hours (50 more OH around noon. Therefore, HONO produced in a photochemical way has much more impact on OH than HONO formed in a heterogeneous process. A closer look at OH sources from particular reactions is presented in Fig. 5. For this purpose the IRR analysis was employed. This analysis was based on data which were averaged in a box consisting of 25 horizontal cells with the middle cell corresponding to the location of the Moody Tower. The gray line in Fig. 5 shows IRR results for the GEHP case for the sum of reactions HONO + $h\nu$ → OH + NO and NO₂$^{\ast}$ + H₂O → OH + HONO that can be interpreted as the amount of OH produced from these two reactions. For the GEH case the black line represents OH produced only from the first reaction which is photolysis of HONO. Therefore, the difference between these two cases is the amount of OH formed from HONO that was photo-chemically produced on surfaces. To further distinguish between the impact of NO₂$^{\ast}$ on OH formation an additional simulation was performed in which photochemical HONO formation on surfaces covered with organic materials was not included; this simulation is indicated in the graph as "GEHP (no surface phot)". During morning hours OH production from the GEHP case was 2–3 times higher than production from the case without photochemical HONO formation (the GEH case) indicating that HONO produced in a photochemical way on surfaces is a significant source of OH in the morning. Reactions involving NO₂$^{\ast}$ contributed only about 30 , which is low in comparison to other studies. For example, Mao et al. (2010) demonstrated that in the Houston area HONO is the major contributor to HO_x in the morning. In our model analysis the morning contribution of HONO to HO_x formation rates in Houston became dominant (81 to HO_x formation and NO₂$^{\ast}$ contributes 7 (20 of produced HONO is consumed by means of photolysis and reaction with OH during daytime (indicated in the graph as CHEM{_}LOSS{_}HONO), about 20 removed by transport processes. In the GEH case, 71 . During daytime contribution from emissions increases to 50 and 19 to nighttime and 65 and 12 of daytime HONO reacts to form OH. Although dry deposition and vertical transport are significant HONO removal processes during nighttime, the production of HONO is higher leading to a net increase of HONO concentration that result in the morning peak. After sunrise photochemical reactions add to the removal of HONO resulting in a decrease of HONO concentration. There are two additional pathways of photochemical HONO production in the GEHP case, these are photochemical formation on surfaces covered with organic material ($h\nu${_}SF{_}HONO) and formation from excited NO₂ ($h\nu${_}NO2$^{\ast}${_}HONO). Although we used the largest reaction coefficient for HONO formation from excited NO₂ it resulted in small amount of HONO produced by this pathway, which is even less than that from gas phase chemistry, being negligible compared with other HONO production mechanisms. The photochemical formation on the surfaces has a major contribution of 61 of the measured value were considered. Heterogeneous HONO production is a major source of HONO during nighttime leading to HONO accumulation and early morning peak concentration of up to 2 ppbv. Since HONO dissociation at that time is less important than deposition and vertical transport, heterogeneous HONO production only slightly increases concentrations of OH and O₃ (up to 3 ppbv ozone increase). The implementation of additional photo-dependent HONO sources, in particular HONO formation from the photo-induced reaction of NO₂ on surfaces covered with humic acid and similar organic materials, only resulted in an increase in HONO mixing ratios of at most 0.5 ppbv. However, process analysis shows that actually much more HONO was produced, but was quickly transported upward and dissociated, which resulted in doubled morning production of hydroxyl radical and an ozone increase of up to 11 ppbv. In contrast to heterogeneous HONO formation that mainly accelerates morning ozone formation, inclusion of HONO photochemical sources influences ozone throughout the day, affecting its peak concentration. Although daytime HONO formation mechanisms may not be understood in all details and the implementation of it to the model is based on many assumptions and simplifications, for example the estimation of urban surfaces or uncertainties in the uptake coefficient, this paper demonstrates that photochemical HONO formation can be a strong source of daytime HONO that directly impacts OH mixing ratios and peak ozone concentrations while nighttime and early morning HONO production by means of NO₂ hydrolysis greatly affects the HONO morning peak concentration but only slightly increases hydroxyl radical and ozone concentrations. \begin{acknowledgements} The authors would like to thank the Houston Advanced Research Center (HARC) for support. Observational DOAS data provided by Jochen Stutz, UCLA and MC/IC data provided by Jack Dibb, UNH. OH data provided by Bill Brune, Penn State University.\\ \\ Edited by: A. Hofzumahaus \end{acknowledgements} \begin{thebibliography}{}

Alicke, B., Platt, U., and Stutz, J.: Impact of nitrous acid photolysis on the total hydroxyl radical budget during the limitation of oxidant production/Pianura Padana Produzione di Ozono study I Milan, J. Geophys. Res., 107, 8196, https://doi.org/10.1029/2000JD000075, 2002.

Alicke, B., Geyer, A., Hofzumahaus, A., Holland, F., Konrad, S., Pätz, H. W., Schäfer, J., Stutz, J., Volz-Thomas, A., and Platt, U.: OH formation by HONO photolysis during the BERLIOZ experiment, J. Geophys. Res., 108, 8247, https://doi.org/10.1029/2001JD000579, 2003.

Amedro, D., Parker, A. E., Schoemaecker, C., and Fittschen, C.: Direct observation of OH radicals after 565 nm multi-photon excitation of NO₂ in the presence of H₂O, Chem. Phys. Lett., 513, 12–16, https://doi.org/10.1016/j.cplett.2011.07.062, 2011.

Berkowitz, C. M., Jobson, T., Jiang, G., Spicer, C. W., and Doskey, P. V.: Chemical and meteorological characteristic associated with rapid increases of O₃ in Houston, Texas, J. Geophys. Res., 109, D10307, https://doi.org/10.1029/2003JD004141, 2004.