**1. Introduction**

Atmospheric pollution is considered a severe problem, especially in large urban areas where anthropogenic emissions (e.g., emissions from domestic, industrial, and transportation activities, as well as from other productive sectors) mix with biogenic emissions (i.e., emissions with natural origins). Anthropogenic emissions include gas-phase primary air pollutants such as nitric oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), volatile organic com‐ pounds (VOCs), and sulfur dioxide (SO2). Although these pollutants can produce harmful health effects, their ability to react as precursors of secondary air pollutants is one of their most relevant characteristics.

Ozone (O3) is produced as a secondary pollutant by photochemical reactions occurring between nitrogen oxides (NOx, where NOx = NO + NO2) and VOCs in the presence of sunlight [1, 2]. For a long time, interest in O3 focused on its direct health effects as a major constituent of photochemical air pollution [3, 4] and its impacts on vegetation [5, 6]. However, O3 also affects the energy budget of the atmosphere; thus, it has become part of a family of species referred to as short-lived climate pollutants (SLCP) [7].

Photochemical activity occurs in both natural and human-altered environments. Theoretically, in the presence of only NOx in the troposphere, O3 generation could be described by a simple mechanism known as the NOx-O3 photostationary state, summarized by the following reactions:

$$\mathsf{NO}\_{2} + \mathsf{h}\mathsf{V} \to \mathsf{NO} + \mathsf{O}\_{3} \tag{1}$$

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$$\bullet \bullet + \bullet\_{\bf 2} + \bullet \bullet \rightarrow \bullet\_{\bf 3} + \bullet \bullet \tag{2}$$

$$\text{NO}\_3 + \text{NO} \rightarrow \text{NO}\_2 + \text{O}\_2,\tag{3}$$

where *hv* represents a photon (sunlight energy), O• denotes an oxygen free radical (an oxygen atom with an unpaired electron), and *M* is known as a third body (molecule) that acts as an energy sink. In the atmosphere, this third body is typically N2 or O2. Under this chemical reaction scheme, the net O3 production is zero, and according to the photostationary state equation, the concentration of O3 can be determined based on the concentration of NOx and the amount of solar radiation:

$$
\begin{bmatrix} \mathbf{O}\_{\text{e}} \end{bmatrix}\_{\text{pos}} = \begin{pmatrix} \boldsymbol{f}\_{\text{NO}\_{\text{e}}} \\ \boldsymbol{\kappa}\_{\text{g}\text{s}} \end{bmatrix} \begin{bmatrix} \mathbf{NO}\_{\text{e}} \\ \hline \begin{bmatrix} \mathbf{NO} \end{bmatrix} \end{bmatrix}, \tag{4}
$$

where *kR3* is the kinetic reaction rate constant for reaction (3) and *jNO2* is the photolysis rate of NO2. As a demonstration, if a 10 parts per billion (ppb) value is considered for the term *jNO2/ kR3*, the O3 concentration would be 27 ppb, with an initial value of 100 ppb of NO [8]. An O3 concentration ranging between 10–40 ppb is typical of rural areas around the globe [9].

When VOCs are added to the mixture of species present in the troposphere, the observed O3 levels are higher than those predicted by the photostationary state formulation. In this case, interactions in the O3-NOx-VOC system are initialized by the hydroxyl (HO•) radical, through the photolysis of O3:

$$\bullet \bullet\_{\mathfrak{z}} + \mathsf{h}\mathsf{v} \to \mathsf{O}\_{\mathfrak{z}} + \mathsf{O}\left(\mathsf{'D}\right) \tag{5}$$

$$\mathbf{O} \begin{pmatrix} \mathbf{D} \end{pmatrix} + \mathsf{H}\_{\mathrm{z}} \mathbf{O} \to \mathbf{2} \mathsf{HO}^{\cdot},\tag{6}$$

where O(1 *D*) represents an excited singlet oxygen atom. The oxidation of the VOCs (repre‐ sented here as RH, where R is an organic functional group, e.g., an alkyl group) continues in the presence of HO• and NOx to produce more O3 and a variety of nitrogen-containing species. The process can be represented by the following generalized reactions [8]:

$$\mathsf{RH} + \mathsf{HO}^{\cdot} + \mathsf{O}\_{\mathrm{z}} \rightarrow \mathsf{RO}\_{\mathrm{z}}^{\cdot \cdot} + \mathsf{H}\_{\mathrm{z}}\mathsf{O}.\tag{7}$$

The alkyl peroxide radical (RO2 •) reacts with NO to form aldehydes (R'CHO) and peroxide radicals (HO2 •):

Ambient Level of NOx and NOy as Indicators of Photochemical Activity in an Urban Center http://dx.doi.org/10.5772/59752 287

$$\mathsf{RO}\_{2}^{\cdot \cdot} + \mathsf{NO}^{\cdot} + \mathsf{O}\_{2} \rightarrow \mathsf{NO}\_{2} + \mathsf{RIC}\mathsf{HO}^{\cdot} + \mathsf{HO}\_{2}^{\cdot \cdot} \tag{8}$$

Reaction 8 is a relevant process because it represents an alternate route for the production of NO2 from NO, but without destroying O3 (in contrast to reaction [3]). A similar process occurs when the aldehydes continue reacting to eventually form acyl peroxy radicals (R´C(O)O2 •) that undergo a similar fate as the RO2 • radicals in reaction (8). Thus, O3 starts to accumulate in the system, as it is no longer destroyed by reaction (3). It continues to be produced by reactions (1) and (2) as NO2 and NO cycle through this set of reactions. In addition, the RO2 • radicals can produce nitrates when they react with NO2:

+ +® + <sup>g</sup>

+® +

 NO

*M*

 O

2

where *hv* represents a photon (sunlight energy), O• denotes an oxygen free radical (an oxygen atom with an unpaired electron), and *M* is known as a third body (molecule) that acts as an energy sink. In the atmosphere, this third body is typically N2 or O2. Under this chemical reaction scheme, the net O3 production is zero, and according to the photostationary state equation, the concentration of O3 can be determined based on the concentration of NOx and

æ ö é ù

 *M* 3

> O

 2,

2

,

(4)

(5)

(6)

(7)

NO

NO

> 1

> > ,

 H O.

 2

•) reacts with NO to form aldehydes (R'CHO) and peroxide

(2)

(3)

O

O

the amount of solar radiation:

286 Current Air Quality Issues

the photolysis of O3:

where O(1

radicals (HO2

3  O

> NO

> > =

3 ps

O

O

O D

RH HO

The alkyl peroxide radical (RO2

•):

3

1

*hv*

The process can be represented by the following generalized reactions [8]:

ë û é ù ç ÷ ë û ç ÷ é ù è ø ë û 2

*k*

*j*

*NO*

*R*

3

where *kR3* is the kinetic reaction rate constant for reaction (3) and *jNO2* is the photolysis rate of NO2. As a demonstration, if a 10 parts per billion (ppb) value is considered for the term *jNO2/ kR3*, the O3 concentration would be 27 ppb, with an initial value of 100 ppb of NO [8]. An O3 concentration ranging between 10–40 ppb is typical of rural areas around the globe [9].

When VOCs are added to the mixture of species present in the troposphere, the observed O3 levels are higher than those predicted by the photostationary state formulation. In this case, interactions in the O3-NOx-VOC system are initialized by the hydroxyl (HO•) radical, through

+®+ ( )

g

sented here as RH, where R is an organic functional group, e.g., an alkyl group) continues in the presence of HO• and NOx to produce more O3 and a variety of nitrogen-containing species.

> RO

2  O D

 2HO

*D*) represents an excited singlet oxygen atom. The oxidation of the VOCs (repre‐

2

 O

( ) + ®

2

+ +® + g g

2

 O

 H O

2

$$\mathsf{RO}\_{2}^{\cdot \cdot} + \mathsf{NO}^{\cdot} + \ \mathsf{M} \to \mathsf{RONO}\_{2} + \ \mathsf{M} \tag{9}$$

$$\mathsf{H}\mathsf{O}^{\cdot} + \mathsf{NO}\_{2} + \mathsf{M} \to \mathsf{HNO}\_{3} + \mathsf{M}.\tag{10}$$

This description is not exhaustive, as we have focused our attention on the main reactions of O3 production by NOx and VOCs. As indicated, NOx acts as catalyst in these reactions, while the VOCs continue to undergo oxidation until they are converted to CO2. In parallel, a variety of different inorganic (e.g., HNO3) and organic (e.g., RONO2) nitrogen-containing species are also produced. Some of these substances act as reservoirs of NOx which are released to the reacting mixture upon decomposition (e.g., peroxy acetyl nitrate or PAN, an organic nitrate), and others act as sinks (most notably, HNO3). The sum of NOx and these additional inorganic and organic nitrates is referred to as total reactive nitrogen or total odd nitrogen oxides (NOy).

In general, the O3-NOx-VOC system increases the NOx available to react through reactions (1)- (2) (increasing O3), thereby producing a complex mixture of partially oxidized VOCs that mixes with freshly emitted VOCs and different oxidized nitrogen species (HNO3, HNO2, NO3, PAN, etc.). The study of the dynamics of O3 production can be quite challenging, given the com‐ plexity of the chemical mixtures and their nonlinear response to emission changes and meteorological conditions. For this reason, comprehensive air quality models have been devised to study the complex physical and chemical processes that participate in gas-phase production of O3 and other air pollutants [10].

Observational-based approaches have proven to be valuable for describing the conditions and regimes that foster air pollution. Some observational approaches use considerable amounts of data that can be obtained through networks of routine air quality and meteorological moni‐ toring stations, and conclusions are then inferred based on the statistical analysis of these data [11-17]. The analyses of these databases can be enhanced if information is also available for additional indicator species that are typically not routinely monitored, such as NOy.

In this study, we have analyzed data gathered by the routine air quality monitoring stations of the Monterrey Metropolitan Area (MMA; 25° 40´ N, 100° 18´ W). Monterrey is the third most populated urban center in Mexico (4.1 million inhabitants), second in size in the country in terms of industrial infrastructure, and one of the cities with the worst air quality problems in Mexico [18]. The MMA (see Figure 1) has been in violation of the 1-hr Mexican Air Quality Standard for O3 (0.11 ppm) since the establishment of its routine air quality monitoring system in 1993. For example, the 1-hr O3 standard was exceeded on 48 different days in 2011 [19]. Peak O3 concentrations can reach 170 ppb and typically occur at the downtown or western air quality stations [20]. Some studies report that the MMA is the fifth most polluted Latin American city in terms of O3 [21]. In addition to the large number of industrial facilities located inside or nearby the metropolitan area that contribute to the poor air quality, emissions from several gas-fired electric utilities and one of the six refineries that operate in the country (located less than 40 km to the east of downtown Monterrey) add to the anthropogenic burden imposed on the airshed. Despite the importance of the contribution of area and point sources to the total emissions inventory, the mobile sources represent approximately 75% of the total anthropo‐ genic emissions released in the MMA [20]. This is a result of a relatively high proportion of vehicles per inhabitant registered in this urban center (approximately one vehicle for every two inhabitants).

#### **2. Methods: Database and analysis tools**

The study used data collected by the *Sistema Integral de Monitoreo Ambiental* (SIMA; Integrated Environmental Monitoring System) of the MMA. At the time of the study, valid data from six operational routine air quality stations were available: Downtown, Southeast, Southwest, Northeast, Northwest, and North (see Figure 1). Data archived for the period of August 2012 to August 2013 were retrieved. The database contained hourly-average concentrations of CO, NO, NO2, and O3, as well as meteorological parameters (relative humidity, atmospheric pressure, dry bulb temperature, solar radiation [SR], wind speed [WS], and wind direction [WD]). These data go through a quality assurance/quality control process defined by SIMA in compliance with international standards. Additional air quality parameters monitored by the stations (mainly, SO2 and particulate matter with aerodynamic diameter less than or equal to 10 microns [PM10] and less than or equal to 2.5 microns [PM2.5]) were not used in this study, as the focus was on the relationship between O3 and NOx.

In addition to the above chemical parameters, NOy was monitored in the Downtown station from August 2012 to August 2013, using a NO-NOy (Thermo Scientific, Model 42i-Y) chemilu‐ minescence continuous sampling device. NOy is a chemical parameter that is not routinely measuredbyMexicanairqualitystations,as itisnot considereda criteriapollutant.Thedecision to deploy the NO-NOy instrument atthe location ofthe Downtown station was based on spatial homogeneity studies performed in the past for the MMA [22], which indicate that pollutant levels observed in the Downtown station are representative of the MMA, with the exception of the Southeast region. The data collected by the NO-NOy device went through a validation process similar to that routinely conducted by SIMA on its own collected data. The main conditions to reject data included the following red flags: obstructed capillary tubing, low flow in the inlet, and concentrations outside the measurement range (i.e., above 200 ppbv). The data were thenconsolidatedandanalyzedonadaily basis, amonthly basis, andby seasons (Summer and Fall 2012, and Winter, Spring, and Summer 2013). Summer 2012 included only data from August and September of 2012; Summer 2013 did not include data for September 2013. monthly basis, and by seasons (Summer and Fall 2012, and Winter, Spring, and Summer 2013). Summer 2012 included only data from August and September of 2012; Summer 2013 did not include data for September 2013.

(i.e., above 200 ppbv). The data were then consolidated and analyzed on a daily basis, a

concentrations of CO, NO, NO2, and O3, as well as meteorological parameters (relative humidity, atmospheric pressure, dry bulb temperature, solar radiation [SR], wind speed [WS], and wind direction [WD]). These data go through a quality assurance/quality control process defined by SIMA in compliance with international standards. Additional air quality parameters monitored by the stations (mainly, SO2 and particulate matter with aerodynamic diameter less than or equal to 10 microns [PM10] and less than or equal to 2.5 microns [PM2.5]) were not used in this study, as the focus was on the relationship between O3 and

In addition to the above chemical parameters, NOy was monitored in the Downtown station from August 2012 to August 2013, using a NO-NOy (Thermo Scientific, Model 42i-Y) chemiluminescence continuous sampling device. NOy is a chemical parameter that is not routinely measured by Mexican air quality stations, as it is not considered a criteria pollutant. The decision to deploy the NO-NOy instrument at the location of the Downtown station was based on spatial homogeneity studies performed in the past for the MMA [22], which indicate that pollutant levels observed in the Downtown station are representative of the MMA, with the exception of the Southeast region. The data collected by the NO-NOy device went through a validation process similar to that routinely conducted by SIMA on its own

Figure 1. Municipalities that comprise the Monterrey Metropolitan Area (left panel) and location of the air quality stations monitoring stations used in this study (right panel): 1 Southeast, 2 Northeast, 3 Downtown, 4 Northwest, 5 Southwest; data from the North station was not used **Figure 1.** Municipalities that comprise the Monterrey Metropolitan Area (left panel) and location of the air quality sta‐ tions monitoring stations used in this study (right panel): 1 Southeast, 2 Northeast, 3 Downtown, 4 Northwest, 5 South‐ west; data from the North station was not used

Once the data were consolidated, an exploratory analysis of the data set was conducted to derive descriptive statistics. In addition, correlation analysis was conducted to explore relations between the chemical and meteorological parameters, with emphasis on the rela‐ tionships among O3, NOx, and NOy. This analysis was complemented by the use of polar plots and wind roses to determine the relationship between high pollutant levels and transport conditions (wind speed and direction).

Grouping techniques were then applied for further exploration of the data. Two methods were used: Principal Components Analysis (PCA) and Analysis of Variance (ANOVA). PCA is helpful in reducing the dimensionality of the dataset, and ANOVA can identify differences among data groups. Thus, PCA was used to identify the most important variables in the dataset which in turn merit further exploration. With the ANOVA, we attempted to determine differences in the weekday and weekend conditions that resulted in high O3 levels. All statistical analyses were conducted using Minitab® 16, and plots were constructed using the R programming language.
