Studying the Effect of Different Gas-Phase Chemical Kinetic Mechanisms on the Formation of Oxidants, Nitrogen Compounds and Ozone in Arid Regions

CMAQ was implemented in the central region of Saudi Arabia and the effect of simulating models using various chemical mechanisms on selected oxidants, nitrogen species, and O3 was investigated. CB05TUCL predicted OH, MEPX, and NOz about 7%, 7.7%, and 8% more than CB05E51 respectively; however, there was no observable difference in the O3 predictions. The differences in variations of SAPRC07 mechanism (SAPRC07TB, SAPRC07TC, and SAPRC07TIC) for all parameters were less than 1%. RACM2 produced the highest OH and H2O2 concentrations. RACM2 enhanced OH production in the range of 24% 32% and H2O2 by 9% over other mechanisms; these are comparatively less than the findings of other studies. Similarly, CB05 produced over 40% more PAN concentration than CB05. Moreover, PAN concentrations produced by all mechanisms were very high compared to other studies. SAPRC07 produced approximately 3% more mean surface O3 concentration than RACM2 and approximately 10% more than CB05. RACM2 O3 predictions were higher than CB05 by 7%. The predicted O3 concentrations by CB05, RACM2, and SAPRC07 were 6%, 11%, and 15% more than the average observed concentrations, which indicate that closest predictions to the observed values were by CB05. This study concludes that there is a wide variation of mechanisms with respect to the predictions of oxidants and nitrogen compounds; however, less variation is noticed in predictions of O3. For any air pollution control strategies and photochemical modeling studies in the current region or in any other arid regions, the CB05 mechanism is recommended. How to cite this paper: Shareef, M.M., Husain, T. and Alharbi, B. (2019) Studying the Effect of Different Gas-Phase Chemical Kinetic Mechanisms on the Formation of Oxidants, Nitrogen Compounds and Ozone in Arid Regions. Journal of Environmental Protection, 10, 1006-1031. https://doi.org/10.4236/jep.2019.108060 Received: June 2, 2019 Accepted: August 17, 2019 Published: August 20, 2019 Copyright © 2019 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access M. M. Shareef et al. DOI: 10.4236/jep.2019.10806


Introduction
Ozone (O 3 ) is a secondary pollutant formed because of the reactions of its precursors: nitrogen oxides (NO + NO 2 = NO x ) and Volatile Organic Compounds gap. ACTM can also estimate many chemical species that are not easily measured. Several chemical mechanisms were developed for ACTM to address the issues associated with urban and rural O 3 formation. Three of the more widely used mechanisms are the Carbon Bond (CB) [1], Regional Atmospheric Chemistry Mechanism (RACM) [2], and State Air Pollution Research Center (SAPRC) [3].
The original CB mechanism, CB04, was based on the simple Arrhenius law rate constant forms that were derived from more complex temperature and pressure-dependent rate constants. It is a lumped structure type and is the fourth in a series of CB mechanisms and includes 36 species and 96 reactions of which 12 are photolytic. Subsequent changes were made by adding rate constants for the formation and decomposition of peroxyacetyl nitrates (PAN) and a termination reaction between the XO 2 and XO 2 N operator and the HO 2 radical. Carter and Atkinson in 1996 enhanced the mechanism by updating the isoprene chemistry [4]. Yarwood et al. in 2005 proposed a major kinetic and photolysis update to CB04 and extended the inorganic reaction set [5].
The new CB05 mechanism was shown to enhance the model performance for O 3 and organic carbons in rural areas and high altitude conditions [6]. CB05 was further improved to include toluene chemistry (CB05TU), and it was proved that CB05TU enhances the prediction of O 3 formation rate [7]. The CB mechanism has been widely used in several studies, to develop reduced form models [8] [9] [10] and to study O 3 and meteorological sensitivities [11] [12] [13]. Dunker et al. in 2002 used CB05 to study the oxidation of reactive VOCs and other processes [14]. Community Multiscale Air Quality (CMAQ) implements two enhanced versions of the CB05 mechanisms, namely cb05e51 and cb05tucl.
The enhancements include the updates in molecular hydrolysis and rate constants based on the recent International Union of Pure and Applied Chemistry [15]. Cb05e51 consists of 148 species and 343 reactions, and cb05tucl includes 107 species and 238 reactions, as shown in Table 1 and Table 2.
The regional acid deposition model (RADM2) is a lumped species mechanism that uses a reactivity-based weighting scheme to account for lumping chemical  [16]. The photo-oxidation of isoprene was further improved in RADM2 by Zimmermann and Poppe in 1996 [17]. The base mechanism includes 57 model species and 158 reactions, 21 of which are photolytic. RADM2 was later updated to the Regional Atmospheric Chemistry Mechanism RACM [16] and recently to RACM2 [18]. The updated version, RACM2, implemented in CMAQ consists of about 400 chemical reactions and 156 chemical species, as shown in Table 2. The kinetic data used in the reactions include the recent suggestions of IUPAC [15] and NASA/JPL [19]. This mechanism was used to study heterogeneous chemistry [20] and sensitivity analysis with respect to the microphysics scheme in WRF-Chem [21].
The original version of SAPRC99 is a detailed mechanism for gas-phase atmospheric reactions of VOCs and NO x in urban and regional atmospheres, the details of which are documented by Carter in 2000 [3]. SAPRC99 was later updated to SAPRC07 to reflect the new kinetic and mechanistic data and to incorporate new data on several types of VOCs. The versions available in CMAQ are saprc07tb and saprc07tc; both consist of 186 species and 741 chemical reactions.
In another SAPRC version in CMAQ, saprc07tic, the number of species has been increased to 231, as shown in Table 1.
The three chemical mechanisms discussed above share the common concept of reaction rates and products; however, they differ in terms of rate constants, photolysis (due to change in pressure and temperature), and treatment of or-  [22]. A comparison between RADM2 and its updated version RACM2 under urban and rural conditions showed large species and process differences in organic speciation [23]. Tonnesen [13].
The problem of O 3 is generally of concern in large cities due to its role in the formation of photochemical smog, and the city of Riyadh in Saudi Arabia is no exception. Recent studies show the declining trend of air quality [29] [30] [31], and Riyadh is reported to be one of the top 10 cities in the world with urban smog problems. In Riyadh, ACTM can be implemented to evaluate various air pollution strategies to control O 3 and its precursors and to improve air quality in Riyadh and its vicinity. Applying the correct chemical mechanism in ACTM is fundamental in formulating the appropriate mitigation measures.
Atmospheric chemical mechanisms have not been studied in arid regions such as Saudi Arabia before. Therefore, the aim of this paper is to identify the impacts of using various chemical mechanisms on the formation of O 3 , selected oxidants (OH and H 2 O 2 ), and nitrogen species (PAN and NO z ) in the central region of Saudi Arabia. This will provide insight into the formation of O 3 and assist regulatory agencies in designing effective O 3 control strategies. Moreover, it will also serve as a benchmark for any future implementations of ACTM in this region as well as similar regions.

Methodology
All simulations were performed using CMAQ which is a 3D grid-based air qual-  [36], and health impact [37]; however, to the knowledge of authors no published study has implemented CMAQ in Saudi Arabia.
The meteorological fields for the study were generated by the Weather Research and Forecasting (WRF) version 3.4.1; it is a next-generation mesoscale model that uses an updated four-dimensional data assimilation approach [38].
The physics options selected for the WRF simulations are summarized in Table   3. The WRF meteorological data was applied to a Meteorology Chemistry Inter- The chemical mechanisms included variations of cb05 (CB05E51 and CB05TUCL), racm (racm2), and saprc07 (saprc07tb, saprc07tc, and saprc07tic) totalling six simulations as summarized in Table 1. The Rosenbrock third order numerical solver [39] was used to solve the system of differential equations for gas-phase chemistry. Clean air was assumed as the initial and boundary conditions. In most studies, spin-up periods are used to minimize the effect of initial conditions in the model, so 50 hours of simulation time was used as a spin-up period    [40].
Biogenic emissions were calculated based on Model of Emissions of Gases and Aerosols from Nature (MEGAN), and anthropogenic emissions were estimated by a combination of direct sources of inventories and indirect calculations from the source data. MEGAN v2.1 [41] [42] was configured to generate these emissions biogenic emissions. MEGAN is a modeling system for estimating terrestrial emissions of gases and aerosols. To generate the atmospheric emissions, MEGAN requires information related to land-cover, weather, and atmospheric chemical composition. Land-cover variables include emission factors, leaf area index, and plant functional types; this data was downloaded from MEGAN's global distributions and processed for the area using the ESRI ArcGIS tools [43].
The appropriate mapping of emissions of real organic species to the emissions of mechanism species is vital for the effective use of condensed mechanisms in air quality models. Carter, W. P. L in 2015 [44] documented the mapping for different mechanisms; however, in MEGAN v2.1, the assignments for the mechanisms are built into the code. Subsequently, MEGAN tools were run and the emission files were merged using Sparse Matrix Operator Kernel Emissions (SMOKE v3.65) system [32] to generate hourly gridded and speciated model-ready emissions files. Two main sources were considered for anthropogenic emissions, the mobile source such as emissions from automobiles and static sources such as emissions from power plants and factories.
This paper presents the results of the comparison between various chemical mechanisms on the formation of the selected HOX, nitrogen compounds, and O 3 . The surface O 3 concentrations were also compared with the observed data. Table 5 presents the domain-wide mean concentrations of various species simulated with six different chemical mechanisms including the variations of CB (CB05E51 and CB05TUCL). The differences in the mean concentrations between the two CB mechanisms were less than 1% except for OH, NO z , and MEPEX which had differences of 7%, 7.7% and 8% more than CB05TUCL respectively.

CB05E51 and CB05TUCL
The differences in the mean concentration of O 3 (shown in Figure 2) were less than 0.5%; this implies that there is no significant difference between the mechanisms when producing O 3 . In order to compare with the other mechanisms, the concentrations for the various parameters for CB05E51 and CB05TUCL were averaged and referred to as CB05.

SAPRC07TB, SAPRC07TC and SAPRC07TIC
The three variations of SAPRC07 (saprc07tb, saprc07tc and saprc07tic) produced similar concentrations for various species. The differences between the species as presented in Table 5 are less than 1% implying that no significant dif-   [28] states that additional reactions in RACM2 with olefins and methacrolein may be another reason for higher OH production. However, this does not seem to be the case, as the reactions with acrolein exist in all the three mechanisms at similar rates. The CMAQ model species name for methacrolein in CB05 is MAPAN and the species name in SAPRC07 and RACM2 is MACR.
In the study's US domain, Sarwar et al. in 2013 [28] observed that OH enhancement by RACM2 was in the range of 36% -60%. Comparing these results, the enhancements in this study were mostly in the range of 24% -32%, which is significantly lower than the US domain. This could be due to the shortage of H 2 O in Saudi Arabia as it is dry and arid. OH measurements were not performed in the study area; hence, the model predictions could not be compared with field    Table 6. RACM2 has the highest H 2 O 2 formation potentially due to these reactions unlike other findings [28].
This implies that organic compounds have a significant role in the formation and destruction of O 3 .

Selected Nitrogen Species 1) Effect on Peroxyacyl Nitrates (PAN)
PAN is one of the components of photochemical smog and forms with the reaction of aldehydes and NO 2 as shown in Table 8. Although the reaction rates differ (RACM2 reaction rate being the highest), the formation mechanisms of the three mechanisms are similar. The reverses of the same mechanisms destroy PAN; additionally, it is also destroyed with the formation of NO 2 , NO 3 and other compounds. In RACM2, PAN reacts with OH to form NO 3 and other organic compounds. Figure 5 shows the spatial distribution of the mean PAN concentration and percent differences predicted by the three mechanisms. In most of the domain, all three mechanisms produced concentrations in the range 0 -8 ppbv, but there were few patches of concentrations in the north ranging from 48 to 64 ppbv. CB05 produced the maximum concentration followed by RACM2 and SAPRC07. Due to large differences in the concentrations at certain locations, the percent differences showed a wide variation. The concentrations of PAN predicted by all mechanisms, when compared with another study [28], are high. This indicates that there is high formation of photochemical smog in certain areas in the domain. The reason for this high concentration and its formation requires further analysis.
2) Effect on Secondary nitrogen species (NO z ) NO z was calculated based on equations presented in Table 9 for the three mechanisms. Figure 6 shows the variation of the mean concentration of NO z Journal of Environmental Protection       Figure 6. Spatial distribution of predicted mean NO z concentrations obtained with chemical mechanisms (a) CB05 (b) SAPRC07 (c) RACM2 and percent differences between the mechanisms (d) SAPRC07 and CB05 (e) RACM2 and CB05 (f) RACM2 and SAPRC07. Journal of Environmental Protection predicted by the mechanisms along with percent differences. RACM2 predicts the highest concentration followed by SAPRC07 and CB05. For all the three mechanisms, the lowest concentration was in the southeast area of the domain and the highest was towards the northwest. RACM2 produced about 60% and 35% more NO z than CB05 and SAPRC07 respectively. The major components of NO z are organic nitrate (NTR) and PAN which were about 78% in CB05, 81% in SAPRC07, and 86% in RACM2.

3) Formation of O 3 4) Effect on Surface O 3
As shown in Figure 2 and NO. This reaction has a lower reaction rate in RACM2 when compared to CB05 and SAPRC07, and this lower reaction rate keeps the concentration of O 3 high. • NO 2 is the primary source for producing O, if it reacts with another molecule such as OH, the O 3 concentrations will be lower. In RACM2 the reaction rate of NO 2 + OH is lower, thus more NO 2 is available for photolysis, subsequently producing more O 3 .
• NO 2 can also be produced through organic compounds (RO2) by the conversion of NO; these conversions are higher in RACM2, especially by aromatic compounds.
• The organic nitrates recycling reactions are higher in RACM2.  [48], and Sarwar et al in 2013 [28] for higher O 3 production by RACM2 over CB05. In the current scenario as well, RACM2 produced higher than CB05, however, the percent differences are larger. In addition to faster photolysis due to high temperature, the reaction NO 2 + OH is further slowed down, likely due to the shortage of OH radical in the atmosphere, as the region is arid. Kim  This observed value is about 6%, 11%, and 15% more than the predicted values by CB05, RACM2 and SAPRC07 respectively. there was no effect of the chemical mechanisms as O 3 concentrations were the same.
Immediately after sunrise CB05 started producing more O 3 than the others did, and as the day progressed all variations of SAPRC07 (SAPRC07TB, SAPRC07TC, and   increase is clearly due to daytime activities most likely the automobile traffic.