Nitrous acid (HONO) plays a significant role in the photochemistry of the troposphere, especially in the polluted urban atmosphere, due to its photolysis by solar UV radiation into the hydroxyl radical (OH), which is one of the most important oxidant in the atmosphere (Alicke et al., 2002). Some previous observations showed unexpected high HONO concentrations up to several ppb at urban or rural sites during the daytime or nighttime (Qin et al., 2009; Su et al., 2008a, 2008b; Yu et al., 2009) but gas-phase chemical models usually underestimated HONO observations, particularly in the daytime. HONO sources are thought to be direct emissions, homogeneous gas reactions, and heterogeneous reactions on aerosol surfaces. Sarwar et al. (2008) incorporated gas-phase reactions, direct emissions, a heterogeneous reaction, and a surface photolysis reaction into the CMAQ model, and simulations still indicated HONO underestimation by comparison with measurements, especially in the daytime. Li et al. (2008) suggested a reaction of electronically excited nitrogen dioxide (NO2*) with water vapor as follows,
The reaction rate for Reaction 2 given by Li et al. (2008) is 1.7×10-13cm3 molecule-1 s-1, which is an order of magnitude larger than that found by Crowley and Carl (1997). Although further experiments to reduce uncertainty in the rate constant need to be conducted, the HONO increase due to Reaction 2 may be potentially significant in some industrialized regions with elevated emission levels of NOx (= NO + NO2) and volatile organic compounds (VOCs). Wennberg and Dabdub (2008) implemented the NO2* chemistry into an air quality model and found that simulated ozone (O3) were enhanced by as much as 55 ppb in the southern California for a summer episode in 1987. However, Sarwar et al. (2009) did similar work and illustrated that the simulated increases were considerably smaller than those reported by Wennberg and Dabdub (2008) due primarily to the current low emissions of NOx and VOCs compared to the emission levels in 1987. Ensberg et al. (2010) then used the emissions in both 1987 and 2005 to assess impacts of the NO2* chemistry on air pollution in the south coast air basin of California showed that the NO2* chemistry increased the effectiveness in reducing O3 through NOx emissions reductions alone. Li et al. (2010) coupled the NO2* chemistry, four heterogeneous reactions on aerosol surfaces recommended by Jacob (2000), and secondary HONO formation from the NO2 heterogeneous reaction with semivolatile organics suggested by Gutzwiller et al. (2002) into the WRF-CHEM model version 3.2, and found that the additional HONO sources significantly improved HONO simulations by comparison with differential optical absorption spectroscopy (DOAS) observations (Zhu et al., 2009), especially in the daytime.
The purpose of this study is to use the state-of-the-art WRF-CHEM model version 3.2 to assess effects of the photoexcited NO2 chemistry and heterogeneous reactions on concentrations of O3 and NOy(total reactive N-containing compounds) in Beijing, Tianjin and Hebei Province of China (BTH region), where emissions of NOx and particulate matter (PM) are high (Zhang et al., 2009).
2. Model description
2.1. WRF-CHEM model
Used in this research is the Weather Research and Forecasting/Chemistry (WRF-CHEM) model version 3.2 (Fast et al., 2006; Grell et al., 2005). The WRF-CHEM model contains two components: a meteorological module and a chemistry module. The two modules use the same mass and scalar preserving flux scheme, the same horizontal and vertical resolutions, the same physics schemes for subgrid-scale transport, and the same time step (Grell et al., 2005). A detailed description of the WRF-CHEM model can be found on the website http://ruc.noaa.gov/wrf/WG11/ and http://www.wrf-model.org. In this study, the WRF-CHEM model employs the microphysics scheme of Lin et al. (1983), the Yonsei University (YSU) PBL scheme (Noh et al., 2001), the Noah land-surface model (Chen & Dudhia, 2001), the RRTM long wave radiation parameterization (Mlawer et al., 1997), and the Goddard short wave scheme (Chou & Suarez, 1994). For gas chemistry chosen is an updated lumped-structure photochemical mechanism CBM-Z (Zaveri & Peters, 1999). Photolysis rates are calculated by the TUV scheme (Madronich, 1987). The chosen aerosol module is MOSAIC (Fast et al., 2006; Zaveri et al., 2008) with an 8-size-bin representation and the biogenic module is based on the description of Guenther et al. (1993, 1994), Simpson et al. (1995), and Schoenemeyer et al. (1997).
Two nested domains shown in Fig. 1. are employed in the simulation. Domain 1, 2, and 3, consists of 83×65, 58×55 and 55×55 horizontal grid cells with 81 km, 27 km and 9 km, primarily covering East Asia, North China, and the BTH region, respectively. The stretched vertical coordinate in the model that extends up to approximately 50 mb uses 28 vertical model layers with nonuniform thickness and a 28 m first layer above the ground. Meteorological initial and boundary conditions are from NCEP reanalysis data, which are also used for nudging every 6 h. The chemical initial and lateral boundary conditions are constrained by the output of a global chemical transport model MOZART-4 (Emmons et al., 2009) every 6 h. The detailed description of mapping species concentrations from the MOZART to the WRF-CHEM can be found on the website http://www.acd.ucar.edu/wrf-chem/. Monthly anthropogenic emissions of SO2, NOx, CO, VOCs, PM10, PM2.5, BC, and OC in 2006/2007 were obtained from (Zhang et al., 2009) and those of NH3 from Streets et al. (2003) and monthly emissions of other species were derived from Zhang et al. (2009). Model simulations were performed in August 1-31, 2007 with a spin-up period of 7 days (July 25-31).
Four different model simulations, i.e., Cases R, S, T and E, were conducted to assess impacts of the NO2* chemistry and heterogeneous reactions on O3 and NOy in the BTH region. Case R is a reference, using the standard CBMZ mechanism and the MOSAIC module. Case S contains Case R with Reactions 1-3. Case T is the same as Case S besides inclusion of 3.1% emissions of HONO/ NOx (See Section 2.2). Case E includes Case T with Reactions 4-7 (See Section 2.2).
2.2. Parameterization of HONO sources
The NO2* chemistry (Reactions 1-3) (Li et al., 2008) is added to the CBM-Z mechanism. The rate of photoexcitation is simplified as 3.5 times the photolysis of NO2 because the former is 3~4 times higher than the latter (Ensberg et al., 2010). The quenching rate constants for Reaction (3) are 2.7×10−11, 3.0×10−11, and 1.7×10−10 cm3 molecule−1 s−1 for N2, O2, and H2O, respectively (Li et al., 2008). The uncertainty in the rate constant for Reaction (2) is ±50% (Li et al., 2008), so the rate constant (2) is chosen as 9.1×10-14 cm3 molecule-1 s-1, which is the mean value of 1.7×10-13 cm3 molecule-1 s-1 from Li et al. (2008) and 1.2×10-14 cm3 molecule-1 s-1 from Crowley and Carl (1997).
For heterogeneous reactions on aerosol surfaces we follow Jacob (2000) recommendations as below,
The reactive uptake of HO2, NO3, NO2, and N2O5 by aerosols is depicted by using a simple reaction probability parameterization (Jacob, 2000),
where k is the first-order rate constant, a, the aerosol equivalent radius (m), Dg, the gas-phase molecular diffusion coefficient being 10-5 m2s-1 (Dentener & Crutzen, 1993), ν, the mean molecular speed (ms-1), A, the aerosol surface area per unit volume of air, and γ, the uptake coefficient of reactive species. Considered aerosols are sulfate, nitrate, organic carbon, and black carbon. Taken from Chin et al. (2002) are parameters for aerosol density, size distributions, and hygroscopic growth rates at ambient relative humidity. A fraction of 2.3% of the NOx emitted in diesel exhaust is assumed to be heterogeneously converted to HONO (Gutzwiller et al., 2002). Additionally, direct HONO emissions are estimated by 0.8% emissions of NOx (Kurtenbacha et al., 2001), which is also adopted in other studies (Aumont et al., 2003; Sarwar et al., 2008). Thus, 3.1% (= 2.3% + 0.8%) of NOx emissions is used to reflect HONO direct emissions and secondary HONO formation from the NO2 heterogeneous reaction with semivolatile organics in diesel exhaust.
3. Results and discussion
3.1. Impacts of the NO2* chemistry and heterogeneous reactions on O3 and NOy
Shown in Fig. 2. are the largest differences in simulated daily maximum 1-h O3 concentrations between Cases S and R. Typically 10~20 ppb increases in daily maximum 1-h O3 concentrations are found in suburban areas and 30~50 ppb enhancements in major cities, i.e., Beijing, Tianjin, Shijiazhuang, and Baoding, over the BTH region. The values are much higher than the results (1~13 ppb) given by Sarwar et al. (2009). This demonstrates that the NO2* chemistry can play a key role in some industrialized regions with elevated emissions of NOx and VOCs. The conclusion is consistent with the suggestion of Sarwar et al. (2009). Monthly mean daily maximum 8-h O3 concentrations near the surface are enhanced in the range of 8~18 ppb in most areas of the BTH region due to the NO2* chemistry and the largest increase is located close to Shijiazhuang (Fig. 3.). The enhanced concentration range in the BTH region is much higher than that of 1~6 ppb in some urban areas and in the vicinity of isolated large NOx sources in the United States of America (Sarwar et al., 2009).
For monthly mean daytime surface NOy concentrations the NO2* chemistry causes 4~15 ppb increases in the BTH region and the largest enhancement is found near the Bohai Bay (Fig. 4.) due to much lower heights of the planetary boundary layer (PBL) and much higher values of relative humidity around the Bohai Bay than those in the other areas of the BTH (Figures are not shown here). This agrees with the results of Sarwar et al. (2009).
Elevated PM concentrations in Beijing, Tianjin, and Shijiazhuang lead to 5~15 ppb decreases in monthly mean daytime NOy concentrations near the surface when heterogeneous reactions on aerosol surfaces are considered (Fig. 5.). Comparatively, during the nighttime high relative humidity, low heights of the PBL, and stable atmospheric conditions are favorable for enhancements in PM concentrations and PM hygroscopic growth rates and finally result in 10~29 ppb decreases in the nighttime NOy concentrations in Beijing, Tianjin, and Shijiazhuang cities and increases in areas with the reduced nighttime NOy concentrations being larger than 10 ppb over the BTH region (Fig. 6.).
3.2. Comparison of simulations and observations
3.2.1. Observed data used for model comparison
HONO observations in Beijing in August 13-25 of 2007 were from Zhu et al. (2009). HONO concentrations were measured by the differential optical absorption spectroscopy (DOAS), which was described in detail by Zhu et al. (2009) and Qin et al. (2006). The specific detection limits are 0.41 ppb for HONO, 2.17 ppb for O3, and 0.63 ppb for NO2, respectively (Zhu et al., 2009). O3 and NOx were also simultaneously monitored at seven sites across Beijing, Tianjin, and Hebei Province (BTH region), partially as the Beijing Atmospheric Environmental Monitoring Action conducted by Chinese Academy of Sciences. The detection limit of a Thermo Environmental Instrument (TEI) model 49 analyzer is 2 ppb for O3, and that of a conventional chemiluminescent gas analyzer (TEI Model 42C) is 0.05 ppb for NO2. Li et al. (2010) find that there is a nice agreement between O3 and NO2 measurements from DOAS and Chemiluminescence in Beijing. The correlation coefficient is 0.97 for O3 and that is 0.83 for NO2. The intercept of 0.75 for NO2 is much better than that of 12.0 given by An et al. (2009). This is due to inclusion of heavy emissions from the Badaling expressway for DOAS measurements, and also confirms the suggestions of An et al. (2009).
3.2.2. Comparison of simulated and observed HONO concentrations
For Case R simulated hourly HONO concentrations are always considerably underestimated by comparison with observations in the period of August 13-25, 2007 (Fig. 7a). Diurnal averages in 13 days (August 13-25, 2007) are approximately 25 times lower than observations (Fig. 7b). The mean bias (MB), the normal mean bias (NMB), the root mean square error (RMSE), the normal mean error (NME), and the correlation coefficient (RC) is -0.98 ppb, -97%, 1.10 ppb, 97%, -0.56, respectively. When the four HONO sources are included (Case E), the WRF-CHEM model well simulates observed HONO daily variations within the studied period (Fig. 7a) and simulated daytime HONO concentrations are also considerably improved (Fig. 7b). This leads to significant improvements in diurnal averaged HONO levels, and the corresponding MB, NMB, RMSE, NME, and RC is improved to -0.28 ppb, -28%, 0.37 ppb, 29%, 0.91, respectively.
3.2.3. Comparison of simulations and observations of O3 and NO2
Daily O3 peaks are substantially improved in most cases when the four HONO sources are included (Case E) although Cases R and E show similar daily O3 variations (Fig. 8.). This further indicates the importance of the NO2* chemistry, heterogeneous reactions on aerosol surfaces, secondary HONO formation from the NO2 heterogeneous reaction with semivolatile organics, and direct emissions in the industrialized region with high emissions of NOx, VOCs and PM. Daily NOx simulations also demonstrate certain improvements at some sites, e.g., Sites Baoding and Shijiazhuang, in different days (Fig. 9.). For diurnal averages in 13 days (August 13-25, 2007) the O3 peak is improved (Case E, Fig. 10a), with an increase of 25.5 ppb (= 64.2 - 38.7 ppb). NO variations are excellently reproduced both in the day and at night (Fig. 10c). NO2 levels are well simulated in the nighttime whereas those are underestimated in the daytime (Fig. 10b).
Incorporated into the state-of-the-art WRF-CHEM model were four sources of HONO, i.e., photoexcited NO2 (NO2*) chemistry, heterogeneous reactions on aerosol surfaces, secondary HONO formation from the NO2 heterogeneous reaction with semivolatile organics, and direct emissions, and simulations were conducted in Beijing, Tianjin, and Hebei Province (BTH region) in August of 2007. Results indicate that the NO2* chemistry and heterogeneous reactions on aerosol surfaces have considerable impacts on concentrations of O3 and NOy (total reactive N-containing compounds) in the BTH region. The NO2* chemistry produces 30~50 ppb enhancements in daily maximum 1-h surface O3 concentrations in major cities, 8~18 ppb enhancements in monthly mean daily maximum 8-h surface O3 concentrations, and 4~15 ppb increases in monthly mean daytime surface NOy concentrations over the BTH region. Heterogeneous reactions on aerosol surfaces lead to 5~15 ppb decreases in monthly mean daytime NOy concentrations and further substantial decreases in monthly mean nighttime NOy concentrations, with a maximum decrease of nearly 29 ppb in major cities over the BTH region. This suggests that inclusion of the four HONO sources could aggravate acid deposition in industrialized areas with high emissions of NOx (NO + NO2), volatile organic compounds, and particulate matter. Comparison with observations indicates that HONO simulations are significantly improved and O3 concentrations are well simulated in most cases when the four sources of HONO are included in the WRF-CHEM model.
The research was partly supported by Knowledge Innovation Key Projects of Chinese Academy of Sciences (kzcx1-yw-06-04, KZCX2-YW-Q02-03, and kzcx1-yw-06-06) and the National Natural Science Foundation of China (Grant No. 40905055). Special thanks are given to Prof. Yuesi Wang from CERN, LAPC, Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences for offering NOx and O3 observed data at seven sites of Hebei Province, and INTECH for providing the opportunity to publish the paper in time.
Alicke B. Platt U. Stutz J. 2002Impact of nitrous acid photolysis on the total hydroxyl radical budget during the Limitation of Oxidant Production/Pianura Padana Produzione di Ozono study in Milan. , 107 D228196, (November 2002), 0148-0227
An J. Zhang W. Qu Y. 2009Impacts of a strong cold front on concentrations of HONO, HCHO, O3, and 2in the heavy traffic urban area of Beijing. 43No.22-23, (July 2009), 3454 3459, 1352-2310
Aumont B. Chervier F. Laval S. 2003Contribution of HONO sources to the NOx/HOx/O3 chemistry in the polluted boundary layer. , 37 4(Feburary 2003), 487 498, 1352-2310
Chen F. Dudia J. 2001Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model description and implementation. , 129 4(April 2001), 569 585, 0027-0644
Chin M. Ginoux P. Kinne S. Torres O. Holben B. N. Duncan B. N. Martin R. V. Logan J. A. Higurashi A. Nakajima T. 2002Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. , 59 3(February 2002), 461 483, 0022-4928
Chou M. D. Suarez M. J. 1994An efficient thermal infrared radiation parameterization for use in general circulation models. , 104606 3 85
Crowley J. N. Carl S. A. 1997OH formation in the photoexcitation of 2beyond the dissociation threshold in the presence of water vapor. , 101No.3, (June 1997), 4178 4184, 1089-5639
Dentener F. J. Crutzen P. J. 1993Reaction of N2O5 on Tropospheric Aerosols’ Impact on the Global Distributions of NOx, O3, and OH. , 98 D4(April 1993), 7149 7163, 0148-0227
Emmons L. K. Walters S. Hess P. G. Lamarque J. F. Pfister G. G. Fillmore D. Granier C. Guenther A. Kinnison D. Laepple T. Orlando J. Tie X. Tyndall G. Wiedinmyer C. Baughcum S. L. Kloster S. 2009Description and evaluation of the Model for Ozone and Related chemical Tracers,version 4 (MOZART-4). 2(August 2009), 1157 1213, 1991-9611
Ensberg J. J. Carreras-Sospedra M. Dabdub D. 2010Impacts of electronically photo-excited 2on air pollution in the South Coast Air Basin of California. , 10No.3, (Februrary 2010), 1171 1181, 1680-7316
Fast J. D. Jr W. I. G. Easter R. C. Zaveri R. A. Barnard J. C. Chapman E. G. Grell G. A. Peckham S. E. 2006Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model. , 111 D21305(November 2006), 0148-0227
Grell G. A. Peckham S. E. Schmitz R. Mc Keen S. A. Frost G. Skamarock W. C. Eder B. 2005Fully coupled “online” chemistry within the WRF model. 39 37(December 2005), 6957 6975, 1352-2310
Guenther A. Zimmerman P. Harley P. C. Monson R. K. Fall R. 1993Isoprene and monoterpene emission rate variability: model evaluations and sensitivity analyses. , 98 D7 12609 12617, 0148-0227
Guenther A. Zimmerman P. Wildermuth M. 1994Natural volatile organic compound emission rate estimates for US woodland landscapes. 28 6(April 1994), 1197 1210, 1352-2310
Gutzwiller L. Arens F. Baltensperger U. Gaggeler H. W. Ammann M. 2002Significance of semivolatile diesel exhaust organics for secondary HONO formation.Environmental Science and Technology, 36 4(January 2002), 677 682, 0001-3936X
Jacob D. J. 2000Heterogeneous chemistry and tropospheric ozone. 34 12-24, 2131 2159, 1352-2310
Kurtenbacha R. Beckera K. H. Gomesa J. A. G. Kleffmanna J. Lorzera J. C. Spittler M. Wiesen P. Ackermann R. Geyer A. Platt U. 2001Investigations of emissions and heterogeneous formation of HONO in a road traffic tunnel. 35 20(July 2001), 3385 3394, 1352-2310
Li S. Matthews J. Sinha A. 2008Atmospheric hydroxyl radical production from electronically excited 2and H2O. , 319No.5870, (March 2008), 1657 1660, 0036-8075
Li Y. An J. Min M. Zhang W. Wang F. Xie P. 2010Impacts of HONO sources on the air quality in Beijing, Tianjin and Hebei Province of China. (in press)
Lin Y. L. Farley R. D. Orville H. D. 1983Bulk parameterization of the snow field in a cloud model, , 22(June 1983), 1065 1092, 0894-8763
Madronich S. 1987Photodissociation in the atmosphere 1. actinic flux and the effects of ground reflections and clouds., 92 D8 9740 9752, 0148-0227
Mlawer E. J. Taubman S. J. Brown P. D. Iacono M. J. Clough S. A. 1997Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. , 102 D14(July 1997), 16663 16682, 0148-0227
Noh Y. Cheon W. G. Raasch S. 2001The improvement of the K-profile model for the PBL using LES. Preprints, , Seoul, South Korea, Laboratory for Atmospheric Modeling Research, 65 66.
Qin M. Xie P. H. Liu W. Q. Li A. Dou K. Fang W. Liu H. G. Zhang W. J. 2006Observation of atmospheric nitrous acid with DOAS in Beijing, China. , 18 1(July 2006), 69 75, 1001-0742
Qin M. Xie P. Su H. Gu J. Peng F. Li S. Zeng L. Liu J. Liu W. Zhang Y. 2009An observational study of the HONO- 2coupling at an urban site in Guangzhou City, South China. 43No.36, (November 2009), 5731 5742, 1352-2310
Sarwar G. Roselle S. J. Mathur R. Appel W. Dennis R. L. Vogel B. 2008A comparison of CMAQ HONO predictions with observations from the Northeast Oxidant and Particle Study. 42 23(July 2008), 5760 5770, 1352-2310
Sarwar G. Robert W. Appel K. Mathur R. Carlton A. 2009Examination of the impact of photoexcited 2chemistry on regional air quality, 43No.40, (December 2009), 6383 6387, 1352-2310
Schoenemeyer T. Richter K. Smiatek G. 1997Vorstudie uber ein raumlich und zeitlich aufgelostes Kataster anthropogener und biogener Emissionen fuer Bayern mit Entwicklung eines Prototyps und Anwendung fur Immissionsprognosen. Abschluss bericht an das Bayerische Landesamt fur Umweltschutz. Fraunhofer-Institut fuer Atmosphaerische Umweltforschung, Garmisch-Partenkirchen
Simpson D. Guenther A. Hewitt C. N. Steinbrecher R. 1995Biogenic emissions in Europe 1. estimates and uncertainties. , 100 D11 22875 22890, 0148-0227
Streets D. G. Bond T. C. Carmichael G. R. Fernandes S. D. Fu Q. He D. Klimont Z. Nelson S. M. Tsai N. Y. Wang M. Q. Woo J. H. Yarber K. F. 2003An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. , 108 D218809, (November 2003), 0148-0227
Su H. Cheng Y. F. Cheng P. Zhang Y. H. Dong S. F. Zeng L. M. Wang X. S. Slanina J. Shao M. Wiedensohler A. 2008aObservation of nighttime nitrous acid (HONO) formation at a non-urban site during PRIDE-PRD2004 in China. 42 25(August 2008), 6219 6232, 1352-2310
Su H. Cheng Y. F. Shao M. Gao D. F. Yu Z. Y. Zeng L. M. Slanina J. Zhang Y. H. Wiedensohler A. 2008bNitrous acid (HONO) and its daytime sources at a rural site during the 2004 PRIDE-PRD experiment in China. , 113 D14312(July 2008), 0148-0227
Wennberg P. O. Dabdub D. 2008Rethinking ozone production. , 319 5870(March 2008), 1624 1625, 0036-8075
Yu Y. Galle B. Panday A. Hodson E. Prinn R. Wang S. 2009Observations of high rates of 2-HONOconversion in the nocturnal atmospheric boundary layer in Kathmandu, Nepal. , 9No.17, (September 2009), 6401 6415, 1680-7316
Zaveri R. A. Peters L. K. 1999A new lumped structure photochemical mechanism for large-scale applications. , 104 D23(December 1999), 30387 30330,415, 0148-0227
Zaveri R. A. Easter R. C. Fast J. D. Peters L. K. 2008Model for Simulating Aerosol Interactions and Chemistry (MOSAIC), , 113 D13(July 2008), 0148-0227
Zhang Q. Streets D. G. Carmichael G. R. He K. B. Huo H. Kannari A. Klimont Z. Park I. S. Reddy S. Fu J. S. Chen D. Duan L. Lei Y. Wang L. T. Yao Z. L. 2009Asian emissions in 2006 for the NASA INTEX-B mission. , 9 14(January 2009), 5131 5153, 1680-7316
Zhu Y. . Liu W. . Xie P. . Dou K. . Liu S. Si F. . Li S. Qin M. 2009Observations of atmospheric HONO in summer of Beijing. , 30 6(June 2009), 1567 1573. 0250-3301(in Chinese)