Further, the Cauchy-Kowalewski theorem (Courant & Hilbert (1989)) guarantees that the proposed solution is a valid solution of the discussed problem, since this problem is a special case of the afore mentioned theorem, so that existence and uniqueness are guaranteed. It remains to justify convergence of the decomposition method. In general convergence by the decomposition method is not guaranteed, so that the solution shall be tested by an appropriate criterion. Since standard convergence criteria do not apply in a straight forward manner for the present case, we resort to a method which is based on the reasoning of Lyapunov (Boichenko et al. (2005)). While Lyapunov introduced this conception in order to test the influence of variations of the initial condition on the solution, we use a similar procedure to test the stability of convergence while starting from an approximate (initial) solution **R**0 (the

Then strong convergence occurs if there exists an *n*0 such that the sign of *λ* is negative for all

the cut-off part of the spectrum is negligible, then the found solution is almost exact.

*m* and *m* an increasing integer number) variations

*r c dt dx d* ¯ *η* ∈ *L*2 (*η* = *y* or *z*) with spectrum {*λi*} which

. For the bounded spectrum and according to

*i*=*n*+1 **R***i*� be the maximum deviation of the

*i*=0 **R***i*, where �·� signifies the maximum norm.

we introduced a carbon-copy of the Cardinal theorem of interpolation theory.

along the bisector is to be expected.

may conclude that with decreasing length ( *�*

The square integrable function *χ* =

contain *n* + 1 terms, with *n* = int

seed of the recursive scheme). Let |*δZn*| = � ∑∞

 |*δZn*| |*δZ*0| .

correct from the approximate solution Γ*n* = ∑*n*

�Γ*n*� log

*n* ≥ *n*0. Here, *λ* = 1

vary significantly in length scales beyond the mentioned limit.

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**3**

*Spain*

**Monitoring Studies of**

Pilar Martín and Alberto Notario

*Castilla La Mancha University*

**Urban Air Quality in Central-Southern**

Florentina Villanueva, José Albaladejo, Beatriz Cabañas,

In urban areas, emissions of air pollutants by anthropogenic processes such as traffic, industry, power plants and domestic heating systems are the main sources of pollution (Fenger, 1999). The massive growth in road traffic and in the use of fossil fuels during the last decades has changed the composition of urban air, increasing the frequency of pollution episodes and the number of cities experiencing them. The main pollutants monitored in the atmosphere in these areas are ozone (O3), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), aromatic compounds and particulate matter. While CO, NO and aromatic compounds are mainly emitted by traffic, O3 and NO2 are originated by

The high levels of solar irradiation observed in the Mediterranean countries favour, in general, the enhanced photochemical production of secondary oxidising pollutants, including O3, nitrogen dioxide (NO2), and peroxyacetylnitrate (PAN). Amongst these, the O3 and the nitrogen dioxide (NO2) are capable of causing adverse impacts on human health and the environment (Lee et al., 1996; WHO, 2000a; Mazzeo and Venegas, 2002, 2004).

Nitrogen dioxide is considered to be an important atmospheric trace gas pollutant not only because of its effects on health but also because (a) it absorbs visible solar radiation and contributes to impaired atmospheric visibility, (b) as an absorber of visible radiation, it could play a potentially direct role in the change in the global climate if its concentrations were to become high enough (WHO, 2000a), (c) it is one of the major sources of acid rain (Tang and Lau, 1999), (d) it is, along with nitric oxide (NO), a chief regulator of the oxidising capacity of the free troposphere by controlling the build-up and fate of radical species, including hydroxyl radicals, and (e) it plays a critical role in determining concentrations of O3, nitric acid (HNO3), nitrous acid (HNO2), organic nitrates such as PAN (CH3C(O)O2NO2), nitrate aerosols and other species in the troposphere. In fact, the photolysis of nitrogen dioxide in the presence of volatile organic compounds is the only key initiator of the photochemical formation of ozone and photochemical smog, whether in polluted or unpolluted atmospheres (WHO, 2000a; Varshney and Singh, 2003). Therefore, ozone mainly

**1. Introduction**

photochemical reactions.

**Spain Using Different Techniques**

### **Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques**

Florentina Villanueva, José Albaladejo, Beatriz Cabañas, Pilar Martín and Alberto Notario *Castilla La Mancha University Spain*

#### **1. Introduction**

20 Will-be-set-by-IN-TECH

58 Air Pollution – Monitoring, Modelling and Health

Tirabassi T. & Rizza U. (1994). Applied dispersion modelling for ground-level concentrations from elevated sources. *Atmos. Environ.*, Vol. 28, page numbers (611-615). Tirabassi T. (2003). Operational advanced air pollution modeling. *PAGEOPH*, Vol. 160, No. 1-2,

Tirabassi, T.; Buske, D.; Moreira, D.M. & Vilhena, M.T. (2008). A two-dimensional solution of

Tirabassi, T.; Tiesi, A.; Buske, D.; Moreira, D.M. & Vilhena, M.T. (2009). Some characteristics

Torres, R.H. (1991). Spaces of sequences, sampling theorem, and functions of exponential type.

Valkó, P.P. & Abate, J. (2004). Comparison of sequence accelerators for the Gaver method of

van Ulden, A.P. (1978). Simple estimates for vertical diffusion from sources near the ground.

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*and Climatology*, Vol. 47, page numbers (2096-2104).

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the advection-diffusion equation with dry deposition to the ground. *J. Appl. Meteor.*

of a plume from a point source based on analytical solution of the two-dimensional advection-diffusion equation. *Atmos. Environ.*, Vol. 43, page numbers (2221-2227). Tirabassi, T.; Tiesi, A.; Vilhena, M.T.; Bodmann, B.E.J. & Buske, D. (2011). An analytical simple

formula for the ground level concentration from a point source. *Atmosphere*, Vol. 2,

numerical Laplace transform inversion. *Computers and Mathematics with Application*,

simulate the pollutant dispersion in the PBL. *Atmos. Environ.*, Vol. 39, page numbers

page numbers (05-16).

page numbers (21-35).

(2171-2178).

Vol. 48, page numbers (629-636).

In urban areas, emissions of air pollutants by anthropogenic processes such as traffic, industry, power plants and domestic heating systems are the main sources of pollution (Fenger, 1999). The massive growth in road traffic and in the use of fossil fuels during the last decades has changed the composition of urban air, increasing the frequency of pollution episodes and the number of cities experiencing them. The main pollutants monitored in the atmosphere in these areas are ozone (O3), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), aromatic compounds and particulate matter. While CO, NO and aromatic compounds are mainly emitted by traffic, O3 and NO2 are originated by photochemical reactions.

The high levels of solar irradiation observed in the Mediterranean countries favour, in general, the enhanced photochemical production of secondary oxidising pollutants, including O3, nitrogen dioxide (NO2), and peroxyacetylnitrate (PAN). Amongst these, the O3 and the nitrogen dioxide (NO2) are capable of causing adverse impacts on human health and the environment (Lee et al., 1996; WHO, 2000a; Mazzeo and Venegas, 2002, 2004).

Nitrogen dioxide is considered to be an important atmospheric trace gas pollutant not only because of its effects on health but also because (a) it absorbs visible solar radiation and contributes to impaired atmospheric visibility, (b) as an absorber of visible radiation, it could play a potentially direct role in the change in the global climate if its concentrations were to become high enough (WHO, 2000a), (c) it is one of the major sources of acid rain (Tang and Lau, 1999), (d) it is, along with nitric oxide (NO), a chief regulator of the oxidising capacity of the free troposphere by controlling the build-up and fate of radical species, including hydroxyl radicals, and (e) it plays a critical role in determining concentrations of O3, nitric acid (HNO3), nitrous acid (HNO2), organic nitrates such as PAN (CH3C(O)O2NO2), nitrate aerosols and other species in the troposphere. In fact, the photolysis of nitrogen dioxide in the presence of volatile organic compounds is the only key initiator of the photochemical formation of ozone and photochemical smog, whether in polluted or unpolluted atmospheres (WHO, 2000a; Varshney and Singh, 2003). Therefore, ozone mainly

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 61

of the city (also point 1). The mobile station (point MS) was also placed, at a fixed location located between the town centre and the ring road. This site represents well-mixed urban air

The measurements were carried out in different periods of time, the pollutants were monitored by means of DOAS from 21st July 2000 to 23rd March 2001, the passive sampling were carried out from January to December 2007 and the mobile station monitored the

Fig. 1. Situation map of Ciudad Real (Spain) and the sampling points of passive samplers. P1

**MS**

The DOAS principle and instrumentation have proven to be a powerful tool for simultaneously monitoring relevant atmospheric trace gases (Platt, 1994; Plane and Saiz-Lopez, 2005). The use of light paths which range from hundred of meters to several kilometres can avoid the problems of local influences and surface effects, as the measured concentrations are averaged over the light path and are barely influenced by small-scale perturbations. The technique is based on the fact that all trace gases absorb electromagnetic radiation in some part of the spectrum. If the radiation of the appropriate frequency is transmitted through the atmosphere, the absorption features of each molecule in that spectral region allow the identification and quantification of the gas concentration. A commercial DOAS system (OPSIS, model AR 500) was employed to simultaneously monitor

(DOAS and one passive sampler), MS (Mobile station).

**2.2 Description of experimental techniques**

**2.2.1 DOAS technique**

conditions near major anthropogenic sources of primary pollutants such as traffic.

pollutants from March to December 2008.

generated in the photochemical reaction mentioned above, is a secondary pollutant. Ozone is also produced by natural sources (trees and thunderstorms for example).

It has been found out that the photochemical ozone production in urban areas rises with the NOx emissions and is less sensitive to the VOC emissions (Sillman and Samson, 1995). In areas moderately contaminated, ozone sensitivity to emission of nitrogen oxides depends on the season and on the emission rates (Kleinman, 1991).

Hence, monitoring of air pollution is necessary, not only to comply with the environmental directives, but also to provide public information and to measure the effectiveness of emission control polices. It is also important to have a number of measurements from different cities to help understand the role of the different physicochemical processes in the troposphere. In addition to meteorological and irradiance conditions, traffic patterns, volatile organic compounds (VOC)/NO*x* emissions and industrial activities vary significantly between different locations.

Monitoring of urban air pollutants has been the subject of study in the city of Ciudad Real (in central-southern Spain) using passive and continuous techniques in order to identify, measure and study the daily, weekly and seasonal variation of the concentrations of important tropospheric constituents (Saiz-Lopez et al., 2006, Martín et al., 2010 and Villanueva et al., 2010). Therefore, a review of these studies has been presented in this chapter, where the evolution of air quality during three different periods (July 2000-March 2001; January-December 2007; March-December 2008) is shown and data of O3, NO2 and SO2 are compared.

#### **2. Material and methods: Experimental section**

#### **2.1 Area of study**

The study was carried out in the urban area of Ciudad Real (Spain). The city has around 65,000 inhabitants and is located in the heart of La Mancha region in central-southern Spain (38.59 N, 3.55 W, at approximately 628 m above sea level) in a fairly flat area, 200 km south of Madrid. With a low presence of industry, traffic is likely to be the most important source of air pollution in this city. Meteorologically, the zone is characterised by very hot and dry summer period with high insulation, variable direction winds and dry and cold winters, conditions that could play an important role in the evolution of the polluting agents.

A DOAS system, passive samplers and a mobile air pollution control station were used to sample, measure and identify the different pollutants. A map of the city is shown in Figure 1, where the situation of the all measurement points can be seen. The passive samplers were placed in town centre (total sampling area of 7.5 km2 approximately) with the exception of points 6, 7 and 10 that correspond to rural zones, but in the case of point 10 in the influence zone of a small airport under construction. Industry next to the city is especially scarce, and the zone is mainly surrounded by rural areas. There is a petrochemical complex located in Puertollano at 30 km from southwest of Ciudad Real. This complex would affect to increase the NO2 and O3 concentrations in the Ciudad Real atmosphere by transporting processes.

The DOAS instrument was placed at a fixed location inside the campus of the University of Castilla-La Mancha, situated in the Eastern part of the city and downwind of the main traffic of the city (also point 1). The mobile station (point MS) was also placed, at a fixed location located between the town centre and the ring road. This site represents well-mixed urban air conditions near major anthropogenic sources of primary pollutants such as traffic.

The measurements were carried out in different periods of time, the pollutants were monitored by means of DOAS from 21st July 2000 to 23rd March 2001, the passive sampling were carried out from January to December 2007 and the mobile station monitored the pollutants from March to December 2008.

Fig. 1. Situation map of Ciudad Real (Spain) and the sampling points of passive samplers. P1 (DOAS and one passive sampler), MS (Mobile station).

#### **2.2 Description of experimental techniques**

#### **2.2.1 DOAS technique**

60 Air Pollution – Monitoring, Modelling and Health

generated in the photochemical reaction mentioned above, is a secondary pollutant. Ozone

It has been found out that the photochemical ozone production in urban areas rises with the NOx emissions and is less sensitive to the VOC emissions (Sillman and Samson, 1995). In areas moderately contaminated, ozone sensitivity to emission of nitrogen oxides depends on

Hence, monitoring of air pollution is necessary, not only to comply with the environmental directives, but also to provide public information and to measure the effectiveness of emission control polices. It is also important to have a number of measurements from different cities to help understand the role of the different physicochemical processes in the troposphere. In addition to meteorological and irradiance conditions, traffic patterns, volatile organic compounds (VOC)/NO*x* emissions and industrial activities vary

Monitoring of urban air pollutants has been the subject of study in the city of Ciudad Real (in central-southern Spain) using passive and continuous techniques in order to identify, measure and study the daily, weekly and seasonal variation of the concentrations of important tropospheric constituents (Saiz-Lopez et al., 2006, Martín et al., 2010 and Villanueva et al., 2010). Therefore, a review of these studies has been presented in this chapter, where the evolution of air quality during three different periods (July 2000-March 2001; January-December 2007; March-December 2008) is shown and data of O3, NO2 and SO2

The study was carried out in the urban area of Ciudad Real (Spain). The city has around 65,000 inhabitants and is located in the heart of La Mancha region in central-southern Spain (38.59 N, 3.55 W, at approximately 628 m above sea level) in a fairly flat area, 200 km south of Madrid. With a low presence of industry, traffic is likely to be the most important source of air pollution in this city. Meteorologically, the zone is characterised by very hot and dry summer period with high insulation, variable direction winds and dry and cold winters,

A DOAS system, passive samplers and a mobile air pollution control station were used to sample, measure and identify the different pollutants. A map of the city is shown in Figure 1, where the situation of the all measurement points can be seen. The passive samplers were placed in town centre (total sampling area of 7.5 km2 approximately) with the exception of points 6, 7 and 10 that correspond to rural zones, but in the case of point 10 in the influence zone of a small airport under construction. Industry next to the city is especially scarce, and the zone is mainly surrounded by rural areas. There is a petrochemical complex located in Puertollano at 30 km from southwest of Ciudad Real. This complex would affect to increase the NO2 and O3 concentrations in the Ciudad Real atmosphere by transporting processes.

The DOAS instrument was placed at a fixed location inside the campus of the University of Castilla-La Mancha, situated in the Eastern part of the city and downwind of the main traffic

conditions that could play an important role in the evolution of the polluting agents.

is also produced by natural sources (trees and thunderstorms for example).

the season and on the emission rates (Kleinman, 1991).

**2. Material and methods: Experimental section**

significantly between different locations.

are compared.

**2.1 Area of study**

The DOAS principle and instrumentation have proven to be a powerful tool for simultaneously monitoring relevant atmospheric trace gases (Platt, 1994; Plane and Saiz-Lopez, 2005). The use of light paths which range from hundred of meters to several kilometres can avoid the problems of local influences and surface effects, as the measured concentrations are averaged over the light path and are barely influenced by small-scale perturbations. The technique is based on the fact that all trace gases absorb electromagnetic radiation in some part of the spectrum. If the radiation of the appropriate frequency is transmitted through the atmosphere, the absorption features of each molecule in that spectral region allow the identification and quantification of the gas concentration. A commercial DOAS system (OPSIS, model AR 500) was employed to simultaneously monitor

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 63

C represents the ambient air NO2 or O3 concentration measured by the passive sampler (micrograms per cubic metre), m is the quantity of NO2 or O3 captured in the sampler (micrograms) and z, A, t and D denote the diffusion length (centimetres), cross-sectional area (square centimetres), sampling time (minutes) and diffusion coefficient (square centimetres per second), respectively. Exposure time to sample NO2 and O3 was in all points 7 days. Details of the extraction and analysis procedure of the samples are given in Martín et al., 2010 according with R&P-Co 2001. In all cases, three unused cartridges belonging to the same lot were treated in the same manner as the samples. Then, it was subtracted by the

A Mercedes Sprinter van was selected as rolling platform for the measuring equipment. The mobile air pollution control station is equipped with a vertical manifold that distributes the sample to all the analyzers, a multipoint calibrator (API, model 700) with an internal ozone calibrator and photometer, a zero air generator (API, model 701) and a meteorological station. Table 1 presents a list of the characteristics of the instruments and measured parameters including meteorological parameters. The methods used to analyze the different air pollutants are those used by the Air-Quality Networks and therefore, defined by the

The particulate matter analyzer is based on beta radiation absorption technique and has been designated by the American Environmental Protection Agency (EPA) as equivalent method for measuring the PM10 fraction of suspended matter (EQPM-0798-122). The calibration of the photometer and flows of the calibrator and analyzers was made at the beginning of the measurement period by the accredited calibration laboratory of the

BTX Syntech spectras GC 955 15 min 0.05 ppb for benzene

1 h 10 s 10 s 10 s 10 s --

manufacturer. More experimental details are described in Villanueva et al., 2010.

 Monitoring instruments employed in the mobile monitoring platform.

*z*

(2)

resolution Detection limit

1 g/m3 -40ºC / 0% 0 mbar 0.5 m/s 0 W/m2 --

1 ( min ) 60 *k A Q mL xDx*

average blank value from the absorbance values of the samples.

European Directive (2008/50/CE), as reference methods.

Parameter Instrument Time

PM10

Rain

Pressure

Solar radiation

Temperature and humidity

Wind direction and speed

**2.2.3 Mobile air pollution control station**

the gas concentration of O3, NO2, NO, and SO2 integrated along a light path of 391 m. More experimental details are described in Saiz-Lopez et al., 2006 and only a brief description is made. The system used in this study consists of an emitter (EM 150) and receiver (RE 150) in combination with the AR 500 analyzer. The emitter was located on the roof of the School of Agricultural Studies about 16m above the ground, and the receiver system was installed 12m above street level, on a terrace on the School of Computing Science.

The average altitude of the optical path was 14m above ground level. The 391m light beam crosses over a small parking area and is nearby two interior city roads containing the heaviest traffic in the city. Also, a monitoring station of the National Meteorological Institute was located in the middle of the light path and provided surface meteorological data for the interpretation of the measurements in this study. In the evaluation procedure (Platt, 1994; Plane and Saiz-Lopez, 2005), the wavelength region of the strongest absorption was used for each gas: 200–250 nm (NO), 250–300 nm (O3), 360–440 nm (NO2) and 260–340 nm (SO2). The calibration of the DOAS system was made using the cell reference system provided by the manufacturer (an OPSISCB100 calibration bench with cells of various lengths, a calibration lamp CA 150 and an OPSIS OC 500 ozone calibrator unit). For the pollutants monitored, the manufacturer specifies a detection limit of the order of 1 *μ*g m−3 and an accuracy of 2% for NO2, SO2 and O3 and 3%–15% for NO.

#### **2.2.2 Passive sampling technique**

Passive samplers are based on free flow (according to the Fick's first law of diffusion) of pollutant molecules from the sampled medium to a collecting medium. These devices can be deployed virtually anywhere, being them useful for mean concentrations determinations. Radiello® samplers (Fondazione Salvatore Maugeri, Padova, Italy) have been employed to measure ambient NO2 and ozone concentrations. Radiello passive samplers are different from the axial ones because the diffusion process is radial through a microporous cylinder in which a cartridge with adsorbent material is positioned. Consequently, there is a greater diffusion area, which facilitates the reaction between the gas and the collection cartridge (Cocheo et al., 1999), giving an uptake rate of at least two times higher.

Radiello passive samplers were used to describe the evolution of NO2 and O3 levels in the urban air of Ciudad Real throughout the four seasonal periods during 2007. The Radiello sampler for measuring nitrogen dioxide and O3 is based on the principle that NO2 and O3 diffuse across the diffusive body towards the absorbing material on the inner cartridge. NO2 and O3 in the atmosphere are captured in the sampler as nitrite (NO2−) and 4 pyridylaldehyde, respectively. According to the Fick's first law, the quantity of NO2 − and 4 pyridylaldehyde in the sampler is proportional to the concentration outside the sampler, the diffusion coefficient, the dimensions of the sampler and the sampling time. Concentrations are calculated from the quantity of nitrite or 4-pyridylaldehyde captured in the sampler by means of Eq. 1:

$$\text{C(}\mu\text{g}\text{m}^{-3}\text{)}=\frac{m\times z}{A\times t\times D}10^6=\frac{m}{Q\_kt}10^6\tag{1}$$

Where the sampling rate Qk is constant:

$$Q\_k(mL\,\text{min}^{-1}) = 60xDx\frac{A}{z} \tag{2}$$

C represents the ambient air NO2 or O3 concentration measured by the passive sampler (micrograms per cubic metre), m is the quantity of NO2 or O3 captured in the sampler (micrograms) and z, A, t and D denote the diffusion length (centimetres), cross-sectional area (square centimetres), sampling time (minutes) and diffusion coefficient (square centimetres per second), respectively. Exposure time to sample NO2 and O3 was in all points 7 days. Details of the extraction and analysis procedure of the samples are given in Martín et al., 2010 according with R&P-Co 2001. In all cases, three unused cartridges belonging to the same lot were treated in the same manner as the samples. Then, it was subtracted by the average blank value from the absorbance values of the samples.

#### **2.2.3 Mobile air pollution control station**

62 Air Pollution – Monitoring, Modelling and Health

the gas concentration of O3, NO2, NO, and SO2 integrated along a light path of 391 m. More experimental details are described in Saiz-Lopez et al., 2006 and only a brief description is made. The system used in this study consists of an emitter (EM 150) and receiver (RE 150) in combination with the AR 500 analyzer. The emitter was located on the roof of the School of Agricultural Studies about 16m above the ground, and the receiver system was installed

The average altitude of the optical path was 14m above ground level. The 391m light beam crosses over a small parking area and is nearby two interior city roads containing the heaviest traffic in the city. Also, a monitoring station of the National Meteorological Institute was located in the middle of the light path and provided surface meteorological data for the interpretation of the measurements in this study. In the evaluation procedure (Platt, 1994; Plane and Saiz-Lopez, 2005), the wavelength region of the strongest absorption was used for each gas: 200–250 nm (NO), 250–300 nm (O3), 360–440 nm (NO2) and 260–340 nm (SO2). The calibration of the DOAS system was made using the cell reference system provided by the manufacturer (an OPSISCB100 calibration bench with cells of various lengths, a calibration lamp CA 150 and an OPSIS OC 500 ozone calibrator unit). For the pollutants monitored, the manufacturer specifies a detection limit of the order of 1 *μ*g m−3 and an accuracy of 2% for

Passive samplers are based on free flow (according to the Fick's first law of diffusion) of pollutant molecules from the sampled medium to a collecting medium. These devices can be deployed virtually anywhere, being them useful for mean concentrations determinations. Radiello® samplers (Fondazione Salvatore Maugeri, Padova, Italy) have been employed to measure ambient NO2 and ozone concentrations. Radiello passive samplers are different from the axial ones because the diffusion process is radial through a microporous cylinder in which a cartridge with adsorbent material is positioned. Consequently, there is a greater diffusion area, which facilitates the reaction between the gas and the collection cartridge

Radiello passive samplers were used to describe the evolution of NO2 and O3 levels in the urban air of Ciudad Real throughout the four seasonal periods during 2007. The Radiello sampler for measuring nitrogen dioxide and O3 is based on the principle that NO2 and O3 diffuse across the diffusive body towards the absorbing material on the inner cartridge. NO2 and O3 in the atmosphere are captured in the sampler as nitrite (NO2−) and 4 pyridylaldehyde, respectively. According to the Fick's first law, the quantity of NO2− and 4 pyridylaldehyde in the sampler is proportional to the concentration outside the sampler, the diffusion coefficient, the dimensions of the sampler and the sampling time. Concentrations are calculated from the quantity of nitrite or 4-pyridylaldehyde captured in the sampler by

3 66 ( ) 10 10

*mz m C gm A t D Qt*

*k*

(1)

12m above street level, on a terrace on the School of Computing Science.

(Cocheo et al., 1999), giving an uptake rate of at least two times higher.

Where the sampling rate Qk is constant:

NO2, SO2 and O3 and 3%–15% for NO.

**2.2.2 Passive sampling technique**

means of Eq. 1:

A Mercedes Sprinter van was selected as rolling platform for the measuring equipment. The mobile air pollution control station is equipped with a vertical manifold that distributes the sample to all the analyzers, a multipoint calibrator (API, model 700) with an internal ozone calibrator and photometer, a zero air generator (API, model 701) and a meteorological station. Table 1 presents a list of the characteristics of the instruments and measured parameters including meteorological parameters. The methods used to analyze the different air pollutants are those used by the Air-Quality Networks and therefore, defined by the European Directive (2008/50/CE), as reference methods.

The particulate matter analyzer is based on beta radiation absorption technique and has been designated by the American Environmental Protection Agency (EPA) as equivalent method for measuring the PM10 fraction of suspended matter (EQPM-0798-122). The calibration of the photometer and flows of the calibrator and analyzers was made at the beginning of the measurement period by the accredited calibration laboratory of the manufacturer. More experimental details are described in Villanueva et al., 2010.

Table 1. Monitoring instruments employed in the mobile monitoring platform.

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 65

decrease in NO and NO2. After sunset, the cease in solar activity decreases the O3 concentrations. The diurnal cycles registered in both studies (Saiz-Lopez et al., 2006 and Villanueva et al., 2010) show that the urban atmosphere of Ciudad Real is mainly influenced by road traffic and photochemistry. This behavior was observed in other urban areas of

Figure 3 shows the evolution of NO, NO2 and O3 concentrations observed for an autumn day with the analyzers of the mobile station. It can be seen a negative correlation between O3 and NO2 as it occurred in summer-time and also an additional peak for NO2 and NO after sunset which is related to a second rush hour in the traffic circulation. In this case the drop in O3 concentration must be mainly due to the reaction with NO because of the absence of solar radiation. The same behavior was observed in 2001 with the DOAS system (Saiz-Lopez

NO2 O3 NO

1 3 5 7 9 11 13 15 17 19 21 23 **CET (hours)**

Fig. 3. Example of the evolution of O3, NO and NO2 concentrations for an autumn day (12nd December 2008) in Ciudad Real. Time scale is given in CET (Central European Time), being

Figure 4 shows the daily averaged mixing ratio of NO2 and O3 measured by the DOAS technique (Saiz-Lopez et al., 2006) and figure 5 the weekly variation of O3 and NO2 using passive sampling (Martin et al., 2010). Finally, monthly averaged concentrations for NO, NO2 and O3 obtained from mobile station (Villanueva et al., 2010) are represented in figure 6 (in all cases during the whole measurements period). As it can be seen, the annual cycle for these trace gases show the largest values of O3 during summer while NO2 exhibit maximum value in winter or autumn months. On average, the production of O3 is reduced in autumn-winter by up to 60% compared to the summer months. Maximum monthly averages of O3, (in summer) and NO2 (in autumn-winter) were: with DOAS, 65 and 35 *μ*g m−3, with passive samplers 48 and 24 *μ*g m−3 and 82 and 18,6 *μ*g m−3 with the

The increase of ozone concentration in spring observed in the case of passive samplers, where several sampler points were located outside of downtown, could be due to emitted volatile organic compounds of biogenic origin (BVOCs), which reach the maximum levels in the spring period as a result of the intense activity of plant species and the photochemical associated. In the presence of nitrogen oxides (NOx) and under particular weather

Spain and Europe (Palacios et al., 2002 and Kourtidis et al., 2002).

**g/m3**

et al., 2006).

UTC+1 in autumn.

analyzers of the mobile station.

#### **3. Results and discussion**

#### **3.1 Measurements of O3, NO and NO2**

The evolution of NO, NO2 and O3 concentration measured using the continuous techniques DOAS (Saiz-Lopez et al., 2006) and the mobile station (Villanueva et al., 2010) for a typical summer day are shown in Figure 2a and 2b, respectively.

Fig. 2. Evolution of O3, NO and NO2, concentrations for a typical summer day in Ciudad Real measured (**a)** with DOAS (12th August 2000) and **(b)** with the mobile station (30th July 2008). Time scale is given in CET (Central European Time). CET=UTC+2 in summer; UTC (Universal time coordinated).

It can be seen a typical profile for the three pollutants that is similar in both cases during the time period from 10:00 to 14:00. The maximum of NO concentrations in the early morning (see figure 2b) corresponds with the minimum of O3. This morning O3 loss has been previously studied by Zhang et al., 2004. Their results suggested that O3 concentrations are depressed by the reaction of NO + O3 NO2. During daytime, NO2, can be quickly photodisassociated (in a few minutes) and yield O3. Therefore, as the day progresses, solar radiation levels favour the increase in the O3 concentrations, having as consequence a

The evolution of NO, NO2 and O3 concentration measured using the continuous techniques DOAS (Saiz-Lopez et al., 2006) and the mobile station (Villanueva et al., 2010) for a typical

> 1 3 5 7 9 11 13 15 17 19 21 23 **CET (hours)**

> > b)

Fig. 2. Evolution of O3, NO and NO2, concentrations for a typical summer day in Ciudad Real measured (**a)** with DOAS (12th August 2000) and **(b)** with the mobile station (30th July 2008). Time scale is given in CET (Central European Time). CET=UTC+2 in summer; UTC

It can be seen a typical profile for the three pollutants that is similar in both cases during the time period from 10:00 to 14:00. The maximum of NO concentrations in the early morning (see figure 2b) corresponds with the minimum of O3. This morning O3 loss has been previously studied by Zhang et al., 2004. Their results suggested that O3 concentrations are depressed by the reaction of NO + O3 NO2. During daytime, NO2, can be quickly photodisassociated (in a few minutes) and yield O3. Therefore, as the day progresses, solar radiation levels favour the increase in the O3 concentrations, having as consequence a

O3 NO NO2

a)

**3. Results and discussion**

(Universal time coordinated).

**g/m3**

**3.1 Measurements of O3, NO and NO2**

summer day are shown in Figure 2a and 2b, respectively.

decrease in NO and NO2. After sunset, the cease in solar activity decreases the O3 concentrations. The diurnal cycles registered in both studies (Saiz-Lopez et al., 2006 and Villanueva et al., 2010) show that the urban atmosphere of Ciudad Real is mainly influenced by road traffic and photochemistry. This behavior was observed in other urban areas of Spain and Europe (Palacios et al., 2002 and Kourtidis et al., 2002).

Figure 3 shows the evolution of NO, NO2 and O3 concentrations observed for an autumn day with the analyzers of the mobile station. It can be seen a negative correlation between O3 and NO2 as it occurred in summer-time and also an additional peak for NO2 and NO after sunset which is related to a second rush hour in the traffic circulation. In this case the drop in O3 concentration must be mainly due to the reaction with NO because of the absence of solar radiation. The same behavior was observed in 2001 with the DOAS system (Saiz-Lopez et al., 2006).

Fig. 3. Example of the evolution of O3, NO and NO2 concentrations for an autumn day (12nd December 2008) in Ciudad Real. Time scale is given in CET (Central European Time), being UTC+1 in autumn.

Figure 4 shows the daily averaged mixing ratio of NO2 and O3 measured by the DOAS technique (Saiz-Lopez et al., 2006) and figure 5 the weekly variation of O3 and NO2 using passive sampling (Martin et al., 2010). Finally, monthly averaged concentrations for NO, NO2 and O3 obtained from mobile station (Villanueva et al., 2010) are represented in figure 6 (in all cases during the whole measurements period). As it can be seen, the annual cycle for these trace gases show the largest values of O3 during summer while NO2 exhibit maximum value in winter or autumn months. On average, the production of O3 is reduced in autumn-winter by up to 60% compared to the summer months. Maximum monthly averages of O3, (in summer) and NO2 (in autumn-winter) were: with DOAS, 65 and 35 *μ*g m−3, with passive samplers 48 and 24 *μ*g m−3 and 82 and 18,6 *μ*g m−3 with the analyzers of the mobile station.

The increase of ozone concentration in spring observed in the case of passive samplers, where several sampler points were located outside of downtown, could be due to emitted volatile organic compounds of biogenic origin (BVOCs), which reach the maximum levels in the spring period as a result of the intense activity of plant species and the photochemical associated. In the presence of nitrogen oxides (NOx) and under particular weather

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 67

Fig. 5. Evolution of temperature, humidity, NO2 and O3 average concentrations of the 11 measured points during the full period (January-December 2007) using passive samplers.

O3 NO2 NO Solar radiation

Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mean annual levels for O3 and NO2 were 50 and 27 *μ*g m−3 with DOAS, 38 and 20.8 *μ*g m−3 with passive samplers and 63 and 13 *μ*g m−3 for the mobile station. Mean annual levels for O3 and NO2 at P1, the point nearest to DOAS and mobile station was 42.5 and 16 *μ*g m−3. The values reported here are generally lower than those observed in previous studies in large urban areas in Spain, such as Madrid (Pujadas et al., 2000; Palacios et al., 2002) and Barcelona (Toll and Baldasano, 2000), where traffic emissions are considerably higher.

Fig. 6. Monthly means of O3, NO2 and NO pollutants measured from daily data (March-December 2008) with the analyzers of the mobile station. Solar radiation has also been

**W/m2**

Winter (I-V), Spring (VI-XVI), Summer (XVII-XXX) and Autumn (XXXI-XLII).

**g/m3**

plotted.

conditions (supporting photochemistry), BVOC contribute to the formation in the troposphere of secondary pollutants such as ozone (Atkinson, 2000 and Fuentes et al., 2000). Nevertheless, in rural areas with high levels of BVOCs the formation of ozone may be NOxlimited. In this sense, meteorological conditions and the dominating trajectories of air masses can constitute a source of NOx. Thus, there are several meteorological conditions that may enhance the rise on surface ozone during the spring season. In these months the heating of the ground favors the formation of higher mixing layers, mostly in continental areas such as the studied region, and therefore the photochemical activity inside them is elevated. This increase in O3 concentration in spring is also observed for the points in which DOAS and the mobile station are located in the urban area.

Regarding NOx, the highest values found in winter and autumn months must be related with the lesser solar radiation and lower temperature which reduce the photochemical activity. Therefore, the oxidation of NO from motor traffic and central heating systems will increase the concentration of NO2 and it will tend to accumulate due to the less photochemical activity in this period. Also, the reduction of the photochemical production of O3 will favour the removal of this molecule by reaction with NO to form NO2 and O2, which in turn will contribute of the enhancement of the NO2 values.

Fig. 4. Daily mean concentration data for O3 and NO2 obtained from the DOAS dataset for the whole period of measurements (August 2000–March 2001).

conditions (supporting photochemistry), BVOC contribute to the formation in the troposphere of secondary pollutants such as ozone (Atkinson, 2000 and Fuentes et al., 2000). Nevertheless, in rural areas with high levels of BVOCs the formation of ozone may be NOxlimited. In this sense, meteorological conditions and the dominating trajectories of air masses can constitute a source of NOx. Thus, there are several meteorological conditions that may enhance the rise on surface ozone during the spring season. In these months the heating of the ground favors the formation of higher mixing layers, mostly in continental areas such as the studied region, and therefore the photochemical activity inside them is elevated. This increase in O3 concentration in spring is also observed for the points in which

Regarding NOx, the highest values found in winter and autumn months must be related with the lesser solar radiation and lower temperature which reduce the photochemical activity. Therefore, the oxidation of NO from motor traffic and central heating systems will increase the concentration of NO2 and it will tend to accumulate due to the less photochemical activity in this period. Also, the reduction of the photochemical production of O3 will favour the removal of this molecule by reaction with NO to form NO2 and O2,

Fig. 4. Daily mean concentration data for O3 and NO2 obtained from the DOAS dataset for

the whole period of measurements (August 2000–March 2001).

DOAS and the mobile station are located in the urban area.

which in turn will contribute of the enhancement of the NO2 values.

Fig. 5. Evolution of temperature, humidity, NO2 and O3 average concentrations of the 11 measured points during the full period (January-December 2007) using passive samplers. Winter (I-V), Spring (VI-XVI), Summer (XVII-XXX) and Autumn (XXXI-XLII).

Fig. 6. Monthly means of O3, NO2 and NO pollutants measured from daily data (March-December 2008) with the analyzers of the mobile station. Solar radiation has also been plotted.

Mean annual levels for O3 and NO2 were 50 and 27 *μ*g m−3 with DOAS, 38 and 20.8 *μ*g m−3 with passive samplers and 63 and 13 *μ*g m−3 for the mobile station. Mean annual levels for O3 and NO2 at P1, the point nearest to DOAS and mobile station was 42.5 and 16 *μ*g m−3. The values reported here are generally lower than those observed in previous studies in large urban areas in Spain, such as Madrid (Pujadas et al., 2000; Palacios et al., 2002) and Barcelona (Toll and Baldasano, 2000), where traffic emissions are considerably higher.

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 69

threshold limit value (40 *μ*g m−3 calendar year) which implies damage to materials. The values obtained for NO2 in points P2 and P11 slightly exceeded the annual limit value for

The levels of SO2 in the urban atmosphere of Ciudad Real during August 2000 to March 2001 and March to December 2008 were monitored using the continuous remote-sensing technique DOAS and the SO2 analyzer placed at mobile station. The data obtained are

SO2

SO2

Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 8. (a) Daily mean concentration data for SO2 obtained from the DOAS dataset for the

The daily mean concentration profile obtained with DOAS system shows clearly an increase in the concentration of SO2 during winter being the maximum monthly average of 10 *μ*g m−3 in December 2000. SO2 mean values were two times higher in winter than in summer. In the case of mobile station there is not a clear difference throughout the months, the maximum monthly average was 2.7 *μ*g m−3 in November 2008 what means a 73% less than the maximum value found in 2000. Mean annual levels were 7 *μ*g m−3 measured with DOAS

entire period of measurements (August 2000–March 2001) and **(b)** monthly mean concentration data obtained from mobile station (March –December 2008).

the protection of vegetation (30 *μ*g m−3) and human health (40 *μ*g m−3).

**3.2 Measurements of SO2**

a)

b)

0 0,5 1 1,5 2 2,5 3

system and 1.8 *μ*g m−3 measured with the mobile station.

**g/m3**

shown in Figure 8 (a) and 8 (b) respectively.

One advantage of using passive samplers is the ability to develop a spatial distribution map. In this sense, the O3 and NO2 average values obtained in the points P1, P2, P3, P4, P5, P6, P8, P9 and P11 have been used to create the spatial distribution map of these pollutants (Fig. 7) using SurGe Project Manager ver 1.4. As it can be seen, higher values of O3 correspond to lower values of NO2 and vice versa. This behaviour is expected considering the interconversion of both species according to photochemical cycle of tropospheric O3 production (Finlayson-Pitts and Pitts, 2000). This same behaviour was also observed in the case of analysis by DOAS and conventional analyzers.

Fig. 7. Maps of O3 and NO2 spatial distribution. Units are in *μ*g m−3.

As commented above, meteorological conditions can affect the pollutant transport and distribution. Ozone concentration (in *μ*g m−3) from data obtained by passive samplers, showed a slight negative correlation with relative humidity (RH in %) ([O3]=−0.62RH + 88.66) and a positive correlation with temperature (T in degree Celsius; [O3]=0.37T + 2.52). Periods with higher temperatures and lower humidity usually correspond to higher values of ozone (Martin et al., 2010). In the case of DOAS analysis, the wind speed does not significantly influence the NO2 observations in winter, by contrast, in summer, higher influence of the wind speed in the NO2 concentrations is observed with a decreasing trend on NO2 as the wind speed increases. The higher thermal convection (associated with larger eddy diffusion coefficients) and the faster winds in summer will contribute to a more efficient mixing leading to a higher dependence of the NO2 values with wind speed as observed by the DOAS (Saiz-Lopez et al., 2006).

Regarding limit and threshold environmental levels values, the European Directive 2008/50/EC for O3 establishes a population information threshold defined as an hourly average of 180 *μ*g m−3. Results obtained from DOAS in summer of 2000 and from mobile station in summer of 2008, showed that this value was exceeded only one time during summer season in 2008, with a concentration of 191 *μ*g m−3. In addition, the annual mean values of 50, 47 (point P6) and 63 *μ*gm-3 measured in 2000, 2007 and 2008 exceeded the threshold limit value (40 *μ*g m−3 calendar year) which implies damage to materials. The values obtained for NO2 in points P2 and P11 slightly exceeded the annual limit value for the protection of vegetation (30 *μ*g m−3) and human health (40 *μ*g m−3).

#### **3.2 Measurements of SO2**

68 Air Pollution – Monitoring, Modelling and Health

One advantage of using passive samplers is the ability to develop a spatial distribution map. In this sense, the O3 and NO2 average values obtained in the points P1, P2, P3, P4, P5, P6, P8, P9 and P11 have been used to create the spatial distribution map of these pollutants (Fig. 7) using SurGe Project Manager ver 1.4. As it can be seen, higher values of O3 correspond to lower values of NO2 and vice versa. This behaviour is expected considering the interconversion of both species according to photochemical cycle of tropospheric O3 production (Finlayson-Pitts and Pitts, 2000). This same behaviour was also observed in the case of

analysis by DOAS and conventional analyzers.

Fig. 7. Maps of O3 and NO2 spatial distribution. Units are in *μ*g m−3.

observed by the DOAS (Saiz-Lopez et al., 2006).

As commented above, meteorological conditions can affect the pollutant transport and distribution. Ozone concentration (in *μ*g m−3) from data obtained by passive samplers, showed a slight negative correlation with relative humidity (RH in %) ([O3]=−0.62RH + 88.66) and a positive correlation with temperature (T in degree Celsius; [O3]=0.37T + 2.52). Periods with higher temperatures and lower humidity usually correspond to higher values of ozone (Martin et al., 2010). In the case of DOAS analysis, the wind speed does not significantly influence the NO2 observations in winter, by contrast, in summer, higher influence of the wind speed in the NO2 concentrations is observed with a decreasing trend on NO2 as the wind speed increases. The higher thermal convection (associated with larger eddy diffusion coefficients) and the faster winds in summer will contribute to a more efficient mixing leading to a higher dependence of the NO2 values with wind speed as

Regarding limit and threshold environmental levels values, the European Directive 2008/50/EC for O3 establishes a population information threshold defined as an hourly average of 180 *μ*g m−3. Results obtained from DOAS in summer of 2000 and from mobile station in summer of 2008, showed that this value was exceeded only one time during summer season in 2008, with a concentration of 191 *μ*g m−3. In addition, the annual mean values of 50, 47 (point P6) and 63 *μ*gm-3 measured in 2000, 2007 and 2008 exceeded the The levels of SO2 in the urban atmosphere of Ciudad Real during August 2000 to March 2001 and March to December 2008 were monitored using the continuous remote-sensing technique DOAS and the SO2 analyzer placed at mobile station. The data obtained are shown in Figure 8 (a) and 8 (b) respectively.

Fig. 8. (a) Daily mean concentration data for SO2 obtained from the DOAS dataset for the entire period of measurements (August 2000–March 2001) and **(b)** monthly mean concentration data obtained from mobile station (March –December 2008).

The daily mean concentration profile obtained with DOAS system shows clearly an increase in the concentration of SO2 during winter being the maximum monthly average of 10 *μ*g m−3 in December 2000. SO2 mean values were two times higher in winter than in summer. In the case of mobile station there is not a clear difference throughout the months, the maximum monthly average was 2.7 *μ*g m−3 in November 2008 what means a 73% less than the maximum value found in 2000. Mean annual levels were 7 *μ*g m−3 measured with DOAS system and 1.8 *μ*g m−3 measured with the mobile station.

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 71

benzene toluene m,p-xylene

1 3 5 7 9 11 13 15 17 19 21 23 **CET (hours)**

PM10 CO

1 3 5 7 9 11 13 15 17 19 21 23 **CET (hours)**

Fig. 10. Example of the evolution of BTX, CO and PM10 concentrations for an autumn day (12nd December 2008) in Ciudad Real. Time scale is given in CET (Central European Time),

Figure 11 shows the monthly averaged concentrations for CO, PM10 and BTX during the whole period of measurement. For PM10, there is not a clear trend throughout the months, while for CO the highest values are registered in spring, 0.19 mg m−3 and autumn, 0.21 mg m−3 while the lowest values are measured during summer, 0.12 mg m−3. For BTX, the highest values are registered in spring (benzene 1.5, toluene 10.8, and m,p-xylene 3.6 *μ*g m−3) and the levels decrease up to reach the minimum values in August (benzene 0.4, toluene 2.6, and m,p-xylene 1 *μ*g m−3). Maximum monthly averages were in g m−3: 31 (PM10) in August, 2 (benzene) in November, 12 (toluene) in March, 4 (m,p-xylene) in May and 0.3 mg m−3 (CO) in November. The mean values of CO, PM10, benzene, toluene and m,p-xylene during the whole measurements period were: 0.2 mg m−3, 20.7 *μ*g m−3, 1.2 *μ*g m−3, 6.4 *μ*g

Regarding BTX, the average level of benzene found in this study during the whole period was 1.2 *μ*g m−3 as mentioned above, with the highest concentration reaching 2 *μ*g m−3. This is comparable with the results published by Fernandez-Villarrenaga et al., 2004 concerning benzene levels in Coruña (Spain); the annual mean was 3.4 *μ*g m−3 while Cocheo et al., 2000 reported urban concentrations in a few European cities as a mean annual average of 4.4 *μ*g m−3 for Antwerp, 3.1 *μ*g m−3 for Copenhagen and much higher for the South European cities.

0 0,1 0,2 0,3 0,4 0,5 0,6

**CO mg/m3**

 **PM10 g/m3**

being UTC+1 in autumn.

m−3and 2.4 *μ*g m−3 respectively.

**g/m3**

A diurnal profile of SO2 for summer and winter time, hourly averaged, is illustrated in Figure 9. The higher SO2 concentrations in winter were mainly related to house heating and only at a small extent with road traffic. The main difference between them arises in the later part of the day (i.e. 16 h to 22 h). In the case of the January data, the concentration of SO2 increases up to three times in the early evening hours, when central heating systems (widely employed in this city during the cold winter months) are in greater use. The diurnal variation of SO2 is also characterised by a secondary small peak observed in the morning, at the rush hour of traffic. In the warm season, only this small peak at the rush hour is observed. This small peak is broader in August indicating a change in the traffic pattern in this vacational month and/or another source of SO2.

Fig. 9. Mean diurnal variation of the hourly averaged concentration during August 2000 and January 2001. Time scale is given in CET (Central European Time), being UTC+1 in winter and UTC + 2 in summer.

Generally, the levels of SO2 registered in Ciudad Real during 2000/2001 and 2008 were found to be lower than those encountered in similar studies on other European cities (Gobiet et al., 2000; Vandaele et al., 2002; Kourtidis et al., 2002).

#### **3.3 Measurements of CO, BTX and PM10**

The concentrations of CO, PM10 and benzene, toluene and m,p-xylene (BTX) were reported for the first time in Ciudad Real (Villanueva et al., 2010) using the mobile station.

Figure 10 shows the evolution of BTX, CO and PM10 concentrations observed for an autumn day. As above mentioned, the daily evolution of air pollutants reveals a marked daily cycle as in the cases of O3 and NO2. The daily evolution of O3, and NO and their relation with BTX is due to common NO and BTX sources and the photochemical mechanism involving these species (NO, NO2, BTX, among others) that leads to O3 formation (Finalyson-Pitts and Pitts, 2000). Two peaks are observed during the day, one in the early morning hours when the emissions from road traffic increase and other after sunset which is related to a second rush hour in the traffic circulation. During summer, only the first peak corresponding to the early morning hours appears as in the cases of NO and NO2.

A diurnal profile of SO2 for summer and winter time, hourly averaged, is illustrated in Figure 9. The higher SO2 concentrations in winter were mainly related to house heating and only at a small extent with road traffic. The main difference between them arises in the later part of the day (i.e. 16 h to 22 h). In the case of the January data, the concentration of SO2 increases up to three times in the early evening hours, when central heating systems (widely employed in this city during the cold winter months) are in greater use. The diurnal variation of SO2 is also characterised by a secondary small peak observed in the morning, at the rush hour of traffic. In the warm season, only this small peak at the rush hour is observed. This small peak is broader in August indicating a change in the traffic pattern in

Fig. 9. Mean diurnal variation of the hourly averaged concentration during August 2000 and January 2001. Time scale is given in CET (Central European Time), being UTC+1 in winter

Generally, the levels of SO2 registered in Ciudad Real during 2000/2001 and 2008 were found to be lower than those encountered in similar studies on other European cities (Gobiet

The concentrations of CO, PM10 and benzene, toluene and m,p-xylene (BTX) were reported

Figure 10 shows the evolution of BTX, CO and PM10 concentrations observed for an autumn day. As above mentioned, the daily evolution of air pollutants reveals a marked daily cycle as in the cases of O3 and NO2. The daily evolution of O3, and NO and their relation with BTX is due to common NO and BTX sources and the photochemical mechanism involving these species (NO, NO2, BTX, among others) that leads to O3 formation (Finalyson-Pitts and Pitts, 2000). Two peaks are observed during the day, one in the early morning hours when the emissions from road traffic increase and other after sunset which is related to a second rush hour in the traffic circulation. During summer, only the first peak corresponding to the early

for the first time in Ciudad Real (Villanueva et al., 2010) using the mobile station.

this vacational month and/or another source of SO2.

et al., 2000; Vandaele et al., 2002; Kourtidis et al., 2002).

morning hours appears as in the cases of NO and NO2.

**3.3 Measurements of CO, BTX and PM10**

and UTC + 2 in summer.

Fig. 10. Example of the evolution of BTX, CO and PM10 concentrations for an autumn day (12nd December 2008) in Ciudad Real. Time scale is given in CET (Central European Time), being UTC+1 in autumn.

Figure 11 shows the monthly averaged concentrations for CO, PM10 and BTX during the whole period of measurement. For PM10, there is not a clear trend throughout the months, while for CO the highest values are registered in spring, 0.19 mg m−3 and autumn, 0.21 mg m−3 while the lowest values are measured during summer, 0.12 mg m−3. For BTX, the highest values are registered in spring (benzene 1.5, toluene 10.8, and m,p-xylene 3.6 *μ*g m−3) and the levels decrease up to reach the minimum values in August (benzene 0.4, toluene 2.6, and m,p-xylene 1 *μ*g m−3). Maximum monthly averages were in g m−3: 31 (PM10) in August, 2 (benzene) in November, 12 (toluene) in March, 4 (m,p-xylene) in May and 0.3 mg m−3 (CO) in November. The mean values of CO, PM10, benzene, toluene and m,p-xylene during the whole measurements period were: 0.2 mg m−3, 20.7 *μ*g m−3, 1.2 *μ*g m−3, 6.4 *μ*g m−3and 2.4 *μ*g m−3 respectively.

Regarding BTX, the average level of benzene found in this study during the whole period was 1.2 *μ*g m−3 as mentioned above, with the highest concentration reaching 2 *μ*g m−3. This is comparable with the results published by Fernandez-Villarrenaga et al., 2004 concerning benzene levels in Coruña (Spain); the annual mean was 3.4 *μ*g m−3 while Cocheo et al., 2000 reported urban concentrations in a few European cities as a mean annual average of 4.4 *μ*g m−3 for Antwerp, 3.1 *μ*g m−3 for Copenhagen and much higher for the South European cities.

Monitoring Studies of Urban Air Quality in Central-Southern Spain Using Different Techniques 73

The variation in the particulate matter concentration throughout the study, as mentioned above, has not a clear trend and there is not a clear relation to meteorological parameters such as wind speed that is below 2 m s−1 (in the whole period), temperature or humidity (Figure 11). This correlation was observed in the study carried out by Kulshrestha et al., 2009. PM10 concentrations in Ciudad Real must be conditioned for natural processes of the pollutants such as dust intrusion from Sahara desert, fires, etc., together with road activities and re-suspension of road dust. The mean value obtained in this study was 20.7 *μ*g m−3. This value is lower than those reported in other urban areas in Spain (Querol et

Regarding limit and threshold environmental levels values, the European Directive 2008/50/EC defines the threshold to protect the human health as a daily value of 50 *μ*g m−3. This value was exceeded 4 times during the period of study, in all cases during the warm season. The highest daily concentration was 56 *μ*g m−3. On the other hand, since EU has not guide value for toluene and xylenes, we compare our measurements with WHO, 2000b, recommended air guideline for toluene (9-10 ppb for 24 h). The values measured in Ciudad

We analyse in this study, the air quality of an urban atmosphere, Ciudad Real (in centralsouthern Spain) through different monitoring techniques. We perform a comparison study on four trace gases (O3, NO, NO2 and SO2) using three different measurement techniques: a commercial DOAS system (Opsis, Sweden), conventional analyzers (API-Teledyne, USA) placed at a mobile station and passive samplers (Radiello, Italy). The results showed a fairly good agreement between the monitoring methods considering the differences in the techniques, the different time period and meteorological situations found during the different years and also the altitude and location of the instruments. In this study, measurement of BTX, CO and PM10 carried out with the mobile station for first time in

Based on the results of the studies made during the three campaigns (July 2000-March 2001, January-December 2007 and March-December 2008) using different techniques it can be concluded that Ciudad Real has high air quality with no significant changes during the three years monitored and where the pollution mainly comes from road traffic and it is influenced by photochemistry. There are not signs that indicate that the pollution from the petrochemical complex located 30 km southwest can significantly affect the air quality of

Atkinson, R. (2000). *Atmospheric chemistry of VOCs and NOx.* Atmospheric Environment 34,

Cocheo, V.; Boaretto, C.; Cocheo, L. & Sacco, P.; (1999). *Radial path in diffusion: The idea to*

*improve the passive sampler performances.* In V. Cocheo, E. De Saeger, D. Kotzias

al., 2008).

Real are below these limits.

Ciudad Real have also been included.

(12–14), 2063–2101.

**4. Conclusion**

Ciudad Real.

**5. References**

In the present study, the obtained mean concentration was lower, due to the fact that Ciudad Real is not a big city. Toluene and m,p-xylene had concentrations either in the same range or lower than the ones reported for other urban areas, especially North European cities (Derwent et al., 2000).

Fig. 11. Monthly means of CO, PM10 and BTX measured from daily data. The meteorological parameters are also presented.

The variation in the particulate matter concentration throughout the study, as mentioned above, has not a clear trend and there is not a clear relation to meteorological parameters such as wind speed that is below 2 m s−1 (in the whole period), temperature or humidity (Figure 11). This correlation was observed in the study carried out by Kulshrestha et al., 2009. PM10 concentrations in Ciudad Real must be conditioned for natural processes of the pollutants such as dust intrusion from Sahara desert, fires, etc., together with road activities and re-suspension of road dust. The mean value obtained in this study was 20.7 *μ*g m−3. This value is lower than those reported in other urban areas in Spain (Querol et al., 2008).

Regarding limit and threshold environmental levels values, the European Directive 2008/50/EC defines the threshold to protect the human health as a daily value of 50 *μ*g m−3. This value was exceeded 4 times during the period of study, in all cases during the warm season. The highest daily concentration was 56 *μ*g m−3. On the other hand, since EU has not guide value for toluene and xylenes, we compare our measurements with WHO, 2000b, recommended air guideline for toluene (9-10 ppb for 24 h). The values measured in Ciudad Real are below these limits.

#### **4. Conclusion**

72 Air Pollution – Monitoring, Modelling and Health

In the present study, the obtained mean concentration was lower, due to the fact that Ciudad Real is not a big city. Toluene and m,p-xylene had concentrations either in the same range or lower than the ones reported for other urban areas, especially North European

PM10 CO (x0,1)

Mar Apr May Jun Jul Aug Sep Oct Nov Dec

BEN TOL XYL

Mar Apr May Jun Jul Aug Sep Oct Nov Dec

temperature (ºC) Humidity (%)

wind speed (m/s)

Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 11. Monthly means of CO, PM10 and BTX measured from daily data. The

0

0,5

1

1,5

**Wind speed**

2

2,5

cities (Derwent et al., 2000).

meteorological parameters are also presented.

**Humidity, Temperature**

**g/m3**

**g/m3**

We analyse in this study, the air quality of an urban atmosphere, Ciudad Real (in centralsouthern Spain) through different monitoring techniques. We perform a comparison study on four trace gases (O3, NO, NO2 and SO2) using three different measurement techniques: a commercial DOAS system (Opsis, Sweden), conventional analyzers (API-Teledyne, USA) placed at a mobile station and passive samplers (Radiello, Italy). The results showed a fairly good agreement between the monitoring methods considering the differences in the techniques, the different time period and meteorological situations found during the different years and also the altitude and location of the instruments. In this study, measurement of BTX, CO and PM10 carried out with the mobile station for first time in Ciudad Real have also been included.

Based on the results of the studies made during the three campaigns (July 2000-March 2001, January-December 2007 and March-December 2008) using different techniques it can be concluded that Ciudad Real has high air quality with no significant changes during the three years monitored and where the pollution mainly comes from road traffic and it is influenced by photochemistry. There are not signs that indicate that the pollution from the petrochemical complex located 30 km southwest can significantly affect the air quality of Ciudad Real.

#### **5. References**

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Cocheo, V.; Boaretto, C.; Cocheo, L. & Sacco, P.; (1999). *Radial path in diffusion: The idea to improve the passive sampler performances.* In V. Cocheo, E. De Saeger, D. Kotzias

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R&P-Co. (2001). Radiello® Model 3310 passive sampling system. Passive gas sampling

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**4**

*1Turkey 2Greece*

**Air Pollution in Mega Cities:**

*Processes Laboratory (ECPL) Voutes, Heraklion, Crete*

*1Istanbul Technical University, Department of Meteorology, Maslak, Istanbul 2University of Crete Department of Chemistry, Environmental Chemical*

A megacity is defined by the United Nations as a metropolitan area with a total population of more than 10 million people. This chapter provides a brief introduction to the air pollution in megacities worldwide. This is an extensive topic and brings together recent comprehensive reviews from particular megacities. We have here highlighted the air quality

The main objective of this chapter is to enhance our understanding of the polluted atmosphere in megacities, with respect to the emission characteristics, climate, population and specific meteorological conditions that are leading to episodes. Therefore, the chapter will provide state-of-the-art reviews of air pollution sources and air quality in some selected megacities, particularly Beijing, Cairo, Delhi and Istanbul. Furthermore, a detailed analysis of emission sources, air quality, mesoscale atmospheric systems and local meteorology

The world population is expected to rise by 2.3 billion, passing from 6.8 billion to 9.1 billion in between 2009 and 2050 (UN Report, 2010). Additionally, population living in urban areas is projected to gain 2.9 billion from 3.4 to 6.3 billion in this period. However, during the industrial revolution years, only about 10% of the total population lived in the cities. As an example, in 1820, which is the beginning times of the United States (US) transformation from rural to urban, the great majority of the population lived in rural areas of US (about 96%) (Kim, 2007). Today, according to UN Report the world population in urban areas has reached to 50.5%. In other words, half of the world's population are concentrated in the cities. However, distribution of urban population in the world is not evenly. A significant diversity in the urbanization levels can be seen in different regions of the world. About 75% of the inhabitants of the more developed regions lived in urban areas in 2010, whereas this ratio was 45% in the less developed regions. It is expected that urbanization will continue to rise in both more developed and less developed regions by 2050 with about 86% and 69%, respectively. These developments have created new physical, social and economic processes in the cities. For example, uncontrolled urban sprawl has leaded the rising of environmental

in megacities that are of particular relevance to health effects.

leading to air pollution episodes in Istanbul will be extensively presented.

**1. Introduction**

**A Case Study of Istanbul**

Selahattin Incecik and Ulaş Im

Zhang, R.W.; Lei, X. & TieHess, P. (2004) *Industrial emissions cause extreme diurnal urban ozone variability.* Proceedings of the National Academy of Sciences, USA, 101, 6346-6350.

### **Air Pollution in Mega Cities: A Case Study of Istanbul**

Selahattin Incecik and Ulaş Im

*1Istanbul Technical University, Department of Meteorology, Maslak, Istanbul 2University of Crete Department of Chemistry, Environmental Chemical Processes Laboratory (ECPL) Voutes, Heraklion, Crete 1Turkey 2Greece*

#### **1. Introduction**

76 Air Pollution – Monitoring, Modelling and Health

Zhang, R.W.; Lei, X. & TieHess, P. (2004) *Industrial emissions cause extreme diurnal urban*

6346-6350.

*ozone variability.* Proceedings of the National Academy of Sciences, USA, 101,

A megacity is defined by the United Nations as a metropolitan area with a total population of more than 10 million people. This chapter provides a brief introduction to the air pollution in megacities worldwide. This is an extensive topic and brings together recent comprehensive reviews from particular megacities. We have here highlighted the air quality in megacities that are of particular relevance to health effects.

The main objective of this chapter is to enhance our understanding of the polluted atmosphere in megacities, with respect to the emission characteristics, climate, population and specific meteorological conditions that are leading to episodes. Therefore, the chapter will provide state-of-the-art reviews of air pollution sources and air quality in some selected megacities, particularly Beijing, Cairo, Delhi and Istanbul. Furthermore, a detailed analysis of emission sources, air quality, mesoscale atmospheric systems and local meteorology leading to air pollution episodes in Istanbul will be extensively presented.

The world population is expected to rise by 2.3 billion, passing from 6.8 billion to 9.1 billion in between 2009 and 2050 (UN Report, 2010). Additionally, population living in urban areas is projected to gain 2.9 billion from 3.4 to 6.3 billion in this period. However, during the industrial revolution years, only about 10% of the total population lived in the cities. As an example, in 1820, which is the beginning times of the United States (US) transformation from rural to urban, the great majority of the population lived in rural areas of US (about 96%) (Kim, 2007). Today, according to UN Report the world population in urban areas has reached to 50.5%. In other words, half of the world's population are concentrated in the cities. However, distribution of urban population in the world is not evenly. A significant diversity in the urbanization levels can be seen in different regions of the world. About 75% of the inhabitants of the more developed regions lived in urban areas in 2010, whereas this ratio was 45% in the less developed regions. It is expected that urbanization will continue to rise in both more developed and less developed regions by 2050 with about 86% and 69%, respectively. These developments have created new physical, social and economic processes in the cities. For example, uncontrolled urban sprawl has leaded the rising of environmental

Air Pollution in Mega Cities: A Case Study of Istanbul 79

which exceeds 20 million. Fig. 1 presents the population in megacities world-wide with their continents. The four of the megacities are located at the South Hemisphere. Fifteen megacities are located at the tropical and humids-subtropical regions. This characteristic is important due to the growing evidence of the climate–health relationships posing increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world (Patz, et al., 2005). A total of 14 megacities, corresponding to more than of 50% of the total megacities, are located at the Asia continent, particularly in south and east parts. In this very dynamic region of the world, there are significant increases in industrialization and urbanization enhanced the urban population growth and economic development. This also leads to drastic increases in energy consumption and pollutant emissions in these regions. As an example, China is a rapid developing country with an urban population rate that increased from 19.6% to 46% within the last

Fig. 1. Populations of the megacities with respect to their continents.

According to "China's blue paper", urban population ratio will reach 65% by 2030 in China. In recent years, a remarkable increase in the number of studies for air quality in China has been conducted (Kai et al., 2007; Chan and Yao, 2008; Wu et al., 2008; Fang et al., 2009; Wang et al, 2010;Zhu et al., 2011; Jahn et al., 2011). As an example, Chan and Yao (2008) extensively discussed the urbanization and air quality characteristics in Beijing, Shanghai and cities in Pearl River Delta (PRD) which is the mainland of China's leading commercial and manufacturing region covering Guangzhou, Shenzhen and Hong Kong. They noticed that in spite of the much attention to reduce emissions through effective control measures, particulate pollution is still severe in megacities of China. Among them, Guangzhou, which is the fourth largest city in China, is the main manufacturing hub of the PRD. In this city, the major industries are located in this industrial zone. In an earlier study by Kai et al. (2007) Air Pollution Index (API) values of Guangzhou were compared with the values of Shanghai and Beijing. The API for Guangzhou is higher than those of Beijing and Shanghai indicating that TSP was the prominent pollutant accounting for 62% of the major share in Guangzhou

three decades.

problems due to high traffic volume, irregular industry, and low quality housing, etc. Massive urbanization in the cities due to the better job opportunities and challenges in the urban areas began first in Europe and then in other regions of the world, particularly in Asia. At this point, urbanization levels have led to a new classification and a concept- megacitywhich is usually defined as a metropolitan area with a total population in excess of 10 million inhabitants. Megacities are highly diverse in the world, spanning from Paris (France), Los Angeles, New York City (USA) in developed countries to Delhi (India), Dhaka (Bengladesh) and Lagos (Nigeria) in developing countries. In today's developing countries, megacities exhibit the highest levels of pollution and therefore, in the studies of the anthropogenic impact on atmospheric composition, have become of primary importance, particularly those having high traffic volumes, industrial activities and domestic heating emissions.

The United Nations Environment Programme Urban Environment (UNEP-UE) unit expressed that more than 1 billion people are exposed to outdoor air pollution annually and the urban air pollution is linked to up to 1 million premature deaths and 1 million pre-native deaths each year. Additionally, UNEP presented the cost of urban air pollution with approximately 2% of GDP in developed countries and 5% in developing countries, respectively. In addition, the UNEP/Global Environmental Monitoring System (GEMS) reported that rapid industrialization, burgeoning cities, and greater dependency on fossil fuels have caused increasing production of harmful pollutants, creating significant health problems in most urban cities. The serious air quality problems, specifically inverse health effects, have been experienced in megacities of both developing and developed countries. due to the exposure to high concentrations of particular matter (PM), nitrogen oxides (NOx), ozone (O3), carbon monoxide (CO), hydrocarbons (HC) and sulfur dioxide (SO2) depending on country's technology level. Especially, exposure to eleveted levels of particular matter and surface ozone causes loss of life-expectancy, acute and chronic respiratory and cardiovascular effects. Furthermore, damage to the ecosystem biodiversity by excess nitrogen nutrient is an important consequence of pollution.

In the beginning of the 2011, The European Commusion released a paper about the current policy efforts and the expected results to maintain a hard line against countries that are yet to comply with EU air quality legistlation limiting fine particulate matter (PM2.5) concentrations. WHO (2009) concluded that megacities have faced particularly health impact by transportation, governance, water and sanitation, safety, food security, water and sanitation, emergency preparedness, and environmental issues. Furthermore, Baklanov (2011) recently shared results of the EU MEGAPOLI project (Megacities: Emissions, Impact on Air Quality and Climate, and Improved Tools for Mitigation and Assessment), which focuses on the multiple spatial and temporal scales from street to global levels and vice versa. The project addresses megacities with air quality and climate having complex effects on each other. Another EU-funded project CityZen (Megacities: Zoom for the Environment) also focused on impact of megacities on their environment and climate and vice versa from local to global aspects using long-term ground and satellite observations as well as regional and global modeling.

#### **2. Megacities and air quality**

As of 2011, there are 26 megacities in the world such as Tokyo, Guangzhou, Seoul, Delhi, Mumbai, Mexico City, New York City, Sao Paulo, Istanbul and other sixteen , eight of

problems due to high traffic volume, irregular industry, and low quality housing, etc. Massive urbanization in the cities due to the better job opportunities and challenges in the urban areas began first in Europe and then in other regions of the world, particularly in Asia. At this point, urbanization levels have led to a new classification and a concept- megacitywhich is usually defined as a metropolitan area with a total population in excess of 10 million inhabitants. Megacities are highly diverse in the world, spanning from Paris (France), Los Angeles, New York City (USA) in developed countries to Delhi (India), Dhaka (Bengladesh) and Lagos (Nigeria) in developing countries. In today's developing countries, megacities exhibit the highest levels of pollution and therefore, in the studies of the anthropogenic impact on atmospheric composition, have become of primary importance, particularly those having

The United Nations Environment Programme Urban Environment (UNEP-UE) unit expressed that more than 1 billion people are exposed to outdoor air pollution annually and the urban air pollution is linked to up to 1 million premature deaths and 1 million pre-native deaths each year. Additionally, UNEP presented the cost of urban air pollution with approximately 2% of GDP in developed countries and 5% in developing countries, respectively. In addition, the UNEP/Global Environmental Monitoring System (GEMS) reported that rapid industrialization, burgeoning cities, and greater dependency on fossil fuels have caused increasing production of harmful pollutants, creating significant health problems in most urban cities. The serious air quality problems, specifically inverse health effects, have been experienced in megacities of both developing and developed countries. due to the exposure to high concentrations of particular matter (PM), nitrogen oxides (NOx), ozone (O3), carbon monoxide (CO), hydrocarbons (HC) and sulfur dioxide (SO2) depending on country's technology level. Especially, exposure to eleveted levels of particular matter and surface ozone causes loss of life-expectancy, acute and chronic respiratory and cardiovascular effects. Furthermore, damage to the ecosystem biodiversity by excess

In the beginning of the 2011, The European Commusion released a paper about the current policy efforts and the expected results to maintain a hard line against countries that are yet to comply with EU air quality legistlation limiting fine particulate matter (PM2.5) concentrations. WHO (2009) concluded that megacities have faced particularly health impact by transportation, governance, water and sanitation, safety, food security, water and sanitation, emergency preparedness, and environmental issues. Furthermore, Baklanov (2011) recently shared results of the EU MEGAPOLI project (Megacities: Emissions, Impact on Air Quality and Climate, and Improved Tools for Mitigation and Assessment), which focuses on the multiple spatial and temporal scales from street to global levels and vice versa. The project addresses megacities with air quality and climate having complex effects on each other. Another EU-funded project CityZen (Megacities: Zoom for the Environment) also focused on impact of megacities on their environment and climate and vice versa from local to global aspects using long-term ground and satellite observations as well as regional

As of 2011, there are 26 megacities in the world such as Tokyo, Guangzhou, Seoul, Delhi, Mumbai, Mexico City, New York City, Sao Paulo, Istanbul and other sixteen , eight of

high traffic volumes, industrial activities and domestic heating emissions.

nitrogen nutrient is an important consequence of pollution.

and global modeling.

**2. Megacities and air quality**

which exceeds 20 million. Fig. 1 presents the population in megacities world-wide with their continents. The four of the megacities are located at the South Hemisphere. Fifteen megacities are located at the tropical and humids-subtropical regions. This characteristic is important due to the growing evidence of the climate–health relationships posing increasing health risks under future projections of climate change and that the warming trend over recent decades has already contributed to increased morbidity and mortality in many regions of the world (Patz, et al., 2005). A total of 14 megacities, corresponding to more than of 50% of the total megacities, are located at the Asia continent, particularly in south and east parts. In this very dynamic region of the world, there are significant increases in industrialization and urbanization enhanced the urban population growth and economic development. This also leads to drastic increases in energy consumption and pollutant emissions in these regions. As an example, China is a rapid developing country with an urban population rate that increased from 19.6% to 46% within the last three decades.

Fig. 1. Populations of the megacities with respect to their continents.

According to "China's blue paper", urban population ratio will reach 65% by 2030 in China. In recent years, a remarkable increase in the number of studies for air quality in China has been conducted (Kai et al., 2007; Chan and Yao, 2008; Wu et al., 2008; Fang et al., 2009; Wang et al, 2010;Zhu et al., 2011; Jahn et al., 2011). As an example, Chan and Yao (2008) extensively discussed the urbanization and air quality characteristics in Beijing, Shanghai and cities in Pearl River Delta (PRD) which is the mainland of China's leading commercial and manufacturing region covering Guangzhou, Shenzhen and Hong Kong. They noticed that in spite of the much attention to reduce emissions through effective control measures, particulate pollution is still severe in megacities of China. Among them, Guangzhou, which is the fourth largest city in China, is the main manufacturing hub of the PRD. In this city, the major industries are located in this industrial zone. In an earlier study by Kai et al. (2007) Air Pollution Index (API) values of Guangzhou were compared with the values of Shanghai and Beijing. The API for Guangzhou is higher than those of Beijing and Shanghai indicating that TSP was the prominent pollutant accounting for 62% of the major share in Guangzhou

Air Pollution in Mega Cities: A Case Study of Istanbul 81

Gurjar et al. (2008) examined the emissions and air quality pertaining to the megacities. He and his colleagues ranked megacities in terms of their trace gas and particle emissions and ambient air quality, based on the newly proposed multi-pollutant index (MPI) which considers the combined level of the three criterion pollutants (TSP, SO2 and NO2) in view of the World Health Organization (WHO) guidelines for air quality. Simulations of the export of air pollution from megacities to downwind locations via long-range transport (LRT) have shown different transport patterns depending on the megacity location: in the tropics export is occurring mostly via the free troposphere, whereas at mid and high latitudes it occurs within the lowest troposphere (Lawrence et al., 2007). Butler & Lawrence (2009) simulated small impacts of megacities on the oxidizing capacity of the atmosphere and larger on reactive nitrogen species on global scale. They also pointed out the need of parameterization of the subgrid effects of megacities. Butler et al. (2008) analyzed different emission inventories and found substantial differences in emission's geographical distribution within countries even if the country total emissions are the same. They also reported large differences in the contribution

Table 1 presents the megacities with their location, climate type, major emissions and critical air quality parameters. As seen in Table 1, there is a significant geographical variation in domestic heating emissions. Specifically, particulate matter is a major problem in almost all of Asian and Latin cities. In all of the megacities, emissions from the motor vehicles are a major contributor of harmful pollutants such as nitrogen oxides and particulate matter. The most important source for the classical pollutants such as particular matter, sulfur dioxide, nitrogen oxides, carbon monoxide, and volatile organic

Beijing (39°54′N; 116°23′E), the capital of China, has completed its third decade of economic development known as the Economic Reform and Open Policy starting in 1978, and is a rapidly developing megacity with a 16 million population (Fang et al., 2009). As it's the capital city, Beijing continues to experience substantial growth in population, economic activity, business, travel and tourism. The city is situated at the northern tip of the roughly triangular North China Plain, which opens to the south and east of the city. Mountains to the north, northwest and west shield the city and northern China's agricultural areas from the desert steppes. Beijing has been experiencing severe anthropogenic air pollution problems since 1980s due to the significant energy consumption depending on developments of the city. Furthermore, natural sources have a significant impact on the city environment such as dust transport from the northern parts of the city. This leads to polluted smog covering the city as a thick blanket under specific

Beijing is in a warm temperate zone and has a typical monsoon–influenced humid continental climate with four distinct seasons. It is usually characterized by hot and humid

of various sectors to the total emissions from each city.

compounds are combustion of fossil fuels.

**3. Megacity of Beijing**

meteorological conditions.

summers and dry winters.

**3.1 Climate**

(Zhou et al., 2007). In order to improve the air quality in Guangzhou, several new strategic efforts have been planned and established in industry and transportation sectors. Examples of the new control measures in transportation are; the metro line, which was opened in 1997, bus rapid transit system, hybrid buses, and design of low-emission zones in busy traffic areas. In a very recent study, Zhu et al. (2011) investigated the transport pathways and potential sources of PM10 in Beijing.

On the contrary to the classical air pollution events in megacities that are above mentioned, Los Angeles, USA (34o03' N; 118o15'W) which is in a large basin surrounded by the Pacific Ocean to the west and several mountain peaks to the east and south, and having a population of over 18 million, remains the most ozone-polluted region in the country. The Los Angeles region, which has a subtropical Mediterranean climate, enjoys plenty of sunshine throughout the year. The frequent sunny days and low rainfall contribute to ozone formation and accumulation as well as high levels of fine particles and dust in Los Angeles. The city area has the highest levels of ozone nationwide, violating federal health standards with an average of 137 days a year. The population growth, dependence on private motor vehicles, and adverse natural meteorological conditions can lead the episodic air quality levels in this area.

#### **2.1 The general characteristics of air pollution and emission sources in megacities**

Air pollution in urban areas comes from a wide variety of sources. The sources responsable for high emission loads are grouped into several sectors such as transport, domestic commercial and industrial activities for anthropogenic sources and NMVOCs from biogenic sources. Transport sector includes mainly motor vehicles, trains, aircraft, ship and boats while **i**ndustry and domestic activities include fuel combustion including wood, coal, and gas for heating and production. Besides, biogenic (natural) emissions include NOx and VOC emissions from vegetation and soils (Guenther et al., 2006). Today, urban air quality is a major concern throughout the world. Molina (2002) indicated that the quality of the air we breathe is fundamental to the quality of life for the growing millions of people living in the world's burgeoning megacities and deteriorating urban air quality threatens the public health. Furthermore, airborne emissions from major urban and industrial areas influence both air quality and climate change. This challenge is particularly acute in the developing world where the rapid growth of megacities is producing atmospheric pollution of unprecedented severity and extent. Mage et al. (1996) reviewed the difficulties in finding solutions to the air pollution in the megacities. Baldasano et al. (2003) examined the air quality for the principal cities in developed and developing countries. According to the study, the current state of air quality worldwide indicates that SO2 maintains a downward tendency throughout the world, with the exception of some Central American and Asian cities, whereas NO2 maintains levels very close to the WHO guideline value in many cities. However, in certain cities such as Kiev, Beijing and Guangzhou, the figures are approximately three times higher than the WHO guideline value. In the Asian databases consulted, only Japan showed really low figures. Surface ozone levels presents average values that exceed the selected guideline values in all of the analysis by regions, income level and number of inhabitants, demonstrating that this is a global problem with consequences for rich and poor countries, large and medium cities and all the regions.

(Zhou et al., 2007). In order to improve the air quality in Guangzhou, several new strategic efforts have been planned and established in industry and transportation sectors. Examples of the new control measures in transportation are; the metro line, which was opened in 1997, bus rapid transit system, hybrid buses, and design of low-emission zones in busy traffic areas. In a very recent study, Zhu et al. (2011) investigated the transport pathways and potential

On the contrary to the classical air pollution events in megacities that are above mentioned,

Ocean to the west and several mountain peaks to the east and south, and having a population of over 18 million, remains the most ozone-polluted region in the country. The Los Angeles region, which has a subtropical Mediterranean climate, enjoys plenty of sunshine throughout the year. The frequent sunny days and low rainfall contribute to ozone formation and accumulation as well as high levels of fine particles and dust in Los Angeles. The city area has the highest levels of ozone nationwide, violating federal health standards with an average of 137 days a year. The population growth, dependence on private motor vehicles, and adverse natural meteorological conditions can lead the episodic air quality

**2.1 The general characteristics of air pollution and emission sources in megacities**

Air pollution in urban areas comes from a wide variety of sources. The sources responsable for high emission loads are grouped into several sectors such as transport, domestic commercial and industrial activities for anthropogenic sources and NMVOCs from biogenic sources. Transport sector includes mainly motor vehicles, trains, aircraft, ship and boats while **i**ndustry and domestic activities include fuel combustion including wood, coal, and gas for heating and production. Besides, biogenic (natural) emissions include NOx and VOC emissions from vegetation and soils (Guenther et al., 2006). Today, urban air quality is a major concern throughout the world. Molina (2002) indicated that the quality of the air we breathe is fundamental to the quality of life for the growing millions of people living in the world's burgeoning megacities and deteriorating urban air quality threatens the public health. Furthermore, airborne emissions from major urban and industrial areas influence both air quality and climate change. This challenge is particularly acute in the developing world where the rapid growth of megacities is producing atmospheric pollution of unprecedented severity and extent. Mage et al. (1996) reviewed the difficulties in finding solutions to the air pollution in the megacities. Baldasano et al. (2003) examined the air quality for the principal cities in developed and developing countries. According to the study, the current state of air quality worldwide indicates that SO2 maintains a downward tendency throughout the world, with the exception of some Central American and Asian cities, whereas NO2 maintains levels very close to the WHO guideline value in many cities. However, in certain cities such as Kiev, Beijing and Guangzhou, the figures are approximately three times higher than the WHO guideline value. In the Asian databases consulted, only Japan showed really low figures. Surface ozone levels presents average values that exceed the selected guideline values in all of the analysis by regions, income level and number of inhabitants, demonstrating that this is a global problem with consequences for rich and poor countries, large and medium cities and all the regions.

N; 118o15'W) which is in a large basin surrounded by the Pacific

sources of PM10 in Beijing.

Los Angeles, USA (34o03'

levels in this area.

Gurjar et al. (2008) examined the emissions and air quality pertaining to the megacities. He and his colleagues ranked megacities in terms of their trace gas and particle emissions and ambient air quality, based on the newly proposed multi-pollutant index (MPI) which considers the combined level of the three criterion pollutants (TSP, SO2 and NO2) in view of the World Health Organization (WHO) guidelines for air quality. Simulations of the export of air pollution from megacities to downwind locations via long-range transport (LRT) have shown different transport patterns depending on the megacity location: in the tropics export is occurring mostly via the free troposphere, whereas at mid and high latitudes it occurs within the lowest troposphere (Lawrence et al., 2007). Butler & Lawrence (2009) simulated small impacts of megacities on the oxidizing capacity of the atmosphere and larger on reactive nitrogen species on global scale. They also pointed out the need of parameterization of the subgrid effects of megacities. Butler et al. (2008) analyzed different emission inventories and found substantial differences in emission's geographical distribution within countries even if the country total emissions are the same. They also reported large differences in the contribution of various sectors to the total emissions from each city.

Table 1 presents the megacities with their location, climate type, major emissions and critical air quality parameters. As seen in Table 1, there is a significant geographical variation in domestic heating emissions. Specifically, particulate matter is a major problem in almost all of Asian and Latin cities. In all of the megacities, emissions from the motor vehicles are a major contributor of harmful pollutants such as nitrogen oxides and particulate matter. The most important source for the classical pollutants such as particular matter, sulfur dioxide, nitrogen oxides, carbon monoxide, and volatile organic compounds are combustion of fossil fuels.

#### **3. Megacity of Beijing**

Beijing (39°54′N; 116°23′E), the capital of China, has completed its third decade of economic development known as the Economic Reform and Open Policy starting in 1978, and is a rapidly developing megacity with a 16 million population (Fang et al., 2009). As it's the capital city, Beijing continues to experience substantial growth in population, economic activity, business, travel and tourism. The city is situated at the northern tip of the roughly triangular North China Plain, which opens to the south and east of the city. Mountains to the north, northwest and west shield the city and northern China's agricultural areas from the desert steppes. Beijing has been experiencing severe anthropogenic air pollution problems since 1980s due to the significant energy consumption depending on developments of the city. Furthermore, natural sources have a significant impact on the city environment such as dust transport from the northern parts of the city. This leads to polluted smog covering the city as a thick blanket under specific meteorological conditions.

#### **3.1 Climate**

Beijing is in a warm temperate zone and has a typical monsoon–influenced humid continental climate with four distinct seasons. It is usually characterized by hot and humid summers and dry winters.

Mexico City (MEX)

Moscow

Mumbai

New York City (USA)

Osaka

Rio de Janeiro (BR)

Sao Paulo

Seoul

Shanghai

Tehran

**(million)**

(RUS) 55°45′N 37°37′E 16.0 1,081 Humid

(IND) 18°58′N; 72°49′E 23.0 603 Tropical wet

40°43′N;74°00′W 19.0 1,214 Humid

(JPN) 34°41′N; 135°30′E 16.6 222 Humid

22°54′S; 43°11′W 14.4 4,557

Paris (F) 48° 51′ N;02° 21′ E 11.8 14,518

(BR) 23°33′S;46°38′W 22.0 7,944

(KR) 37°34′N;126°58′E 25.0 605

(CN) 31°12′N; 121°30′E 24.7 6,340 Humid

(IRN) 35°41′N ;51°25′E 13.4 1,274 Semiarid

Table 1.  The recent measurements of PM10 indicates lower levels such as 123μg/m3 in 2008; 120μg/m3 in 2009, respectively. One of the reasons of the high level of PM10 is residential coal-combustion in Beijing. SO2 emissions from residential coalcombustion in Beijing were increased from 68,800 tons in 2003 to 85,100 tons in 2005. The expansion of the urban areas and the increase in SO2 emissions led to increased particulate sulfate concentrations, which resulted in higher PM10 levels. However, SO2 levels in the city are decreasing (Fang et al., 2009). Furthermore, Beijing experiences high PM10 pollution during spring dust storms. Zhu et al. (2011) showed that the typical wind speed of such dust storms is approximately 7 m/s or more, and the sand and dust sources are located about 1000-2000 km northwest of Beijing. According to Zhu et al. (2011), dust storms can reach to

PM10 SO2 NO2 CO

2000 2002 2004 2006

Fig. 2. Variations of annual-mean PM10, SO2, NO2 (µgm-3) and CO (mgm-3) levels in Beijing (2000-2008) \*Air quality standard for PM10 is 100 µg/m3 and WHO guideliness is 20µg/m3.

Recently, heavy industries have been gradually replaced by less polluting industries in Beijing. Besides, several possible activities are planned on major polluting industries such as the closure of cookery units at coke and chemical plants as well as closure of cement, lime and brick plants. The, transport sector is also a major contributor to Beijing's air quality. In this sector, stringent vehicle emission standards have been established. The Beijing municipal government will also implement traffic control measures such as the improvement of fuel quality to meet the new emission standards and to ease the city's traffic

Greater Cairo (30o3'N; 31o13'E), which is the capital of Egypt, is the largest city in Africa and located in northern Egypt, to the south of the delta in the Nile basin. The Greater Cairo

0.0

0.5

1.0

1.5

CO (mgm-3)

2.0

2.5

3.0

Beijing within 3 days.

PM10, SO2, NO2 (

congestion.

**4. Megacity of Cairo**

gm-3)

#### **3.2 Air pollution sources**

The major anthropogenic emission sources in Beijing are domestic heating, traffic and industry. Coal dominated energy structure is also one of the major causes of air pollution in Beijing (Hao, et al., 2007). As an example to the total emissions from energy production sector of 16.0 GWh/y, Hao et al. (2007) calculated a 102,497 t/y of SO2, 60,567 t/y of NOx and 11,633 t/y of PM10. Domestic heating in Beijing usually starts in mid-November and ends in the following March and it is the major source for SO2 in the winter season (Chan and Yao, 2008; Hao et al., 2005). Furthermore, industrial emissions emitted from Shijingshan region, located west of Beijing, are significant sources of particulate matter in Beijing. Beijing experiences a serious urban sprawl which has been claimed to be a major factor leading to the need for long-distance travel, congestion in the city centre and private vehicle usage problem (Zhao, et al., 2010; Deng & Huang, 2004). The number of cars in Beijing has grown rapidly and reached to 4.76 million vehicles in 2011, up from 1.5 million in 2000 and 2.6 million in 2005, according to official statistics provided by the municipal transportation authorities. Particulate matter emitted from motor vehicles and re-suspension of road dust are also likely contributors to PM10 pollution in the city (Song et al., 2006). Last but not least, natural dust originating from the erosion of deserts in northern and northwestern China results in seasonal dust storms that plague the city.

#### **3.3 Air quality in Beijing**

Beijing is party to the Standard Ambient Air Quality Standards (GB 3095-1996), which sets limits for SO2, CO, PM10 and nitrogen dioxide (NO2). The Chinese air quality standards set separate limits for different types of areas such as Class I, II and III based on physical characteristics of the region such as natural conservation areas and special industrial areas. Beijing is designated as a Class II area, which applies to residential, mixed commercial/ residential, cultural, industrial, and rural areas.

TSP and SO2 have been the major pollutants in China for a long time due to the fossil fuel burning from power plants, industry and domestic heating. However, in recent years, the Chinese Government have planned to reveal a major environmental plan to help managing air pollution and is expected to include efforts to reduce pollution through new regulations and strategies including taxes and investments in this field. As an example, energy-related measures include fuel substitution and flue gas desulfurization facilities, which were built at the coal fired power plants, control measures such as energy efficiency and fuel use and dust control improvements (Hao et al. 2007). Initiatives have also been implemented in Beijing. The use of natural gas has been increased four-fold from 2000 as a result of efforts made to replace coal fired boilers and family stoves to use natural gas, and coal heating with electrical heating. As a result of these initiatives, from 1990 to 1999, the annual average TSP concentration in 100 major cities decreased by 30% to 256 μg/m3 and it remained almost constant from 1999 to 2003 (Sinton et al., 2004), despite an overall decrease of 30% in total energy consumption from 1997 to 2002. Fang et al. (2009) examined the air quality management in China and the changing air quality levels with their reasons. The results of the new strategies in Beijing are seen in Fig.2. In 1998, Beijing started its phased intensive control program to fight air pollution. PM10 concentrations increased by around 10% from 2003 to 2006 because of the increase in coal-fired boiler emissions, construction activities and dust storms (United Nations Environment Program, 2007). The annual PM10 concentrations

The major anthropogenic emission sources in Beijing are domestic heating, traffic and industry. Coal dominated energy structure is also one of the major causes of air pollution in Beijing (Hao, et al., 2007). As an example to the total emissions from energy production sector of 16.0 GWh/y, Hao et al. (2007) calculated a 102,497 t/y of SO2, 60,567 t/y of NOx and 11,633 t/y of PM10. Domestic heating in Beijing usually starts in mid-November and ends in the following March and it is the major source for SO2 in the winter season (Chan and Yao, 2008; Hao et al., 2005). Furthermore, industrial emissions emitted from Shijingshan region, located west of Beijing, are significant sources of particulate matter in Beijing. Beijing experiences a serious urban sprawl which has been claimed to be a major factor leading to the need for long-distance travel, congestion in the city centre and private vehicle usage problem (Zhao, et al., 2010; Deng & Huang, 2004). The number of cars in Beijing has grown rapidly and reached to 4.76 million vehicles in 2011, up from 1.5 million in 2000 and 2.6 million in 2005, according to official statistics provided by the municipal transportation authorities. Particulate matter emitted from motor vehicles and re-suspension of road dust are also likely contributors to PM10 pollution in the city (Song et al., 2006). Last but not least, natural dust originating from the erosion of deserts in northern and northwestern China

Beijing is party to the Standard Ambient Air Quality Standards (GB 3095-1996), which sets limits for SO2, CO, PM10 and nitrogen dioxide (NO2). The Chinese air quality standards set separate limits for different types of areas such as Class I, II and III based on physical characteristics of the region such as natural conservation areas and special industrial areas. Beijing is designated as a Class II area, which applies to residential, mixed commercial/

TSP and SO2 have been the major pollutants in China for a long time due to the fossil fuel burning from power plants, industry and domestic heating. However, in recent years, the Chinese Government have planned to reveal a major environmental plan to help managing air pollution and is expected to include efforts to reduce pollution through new regulations and strategies including taxes and investments in this field. As an example, energy-related measures include fuel substitution and flue gas desulfurization facilities, which were built at the coal fired power plants, control measures such as energy efficiency and fuel use and dust control improvements (Hao et al. 2007). Initiatives have also been implemented in Beijing. The use of natural gas has been increased four-fold from 2000 as a result of efforts made to replace coal fired boilers and family stoves to use natural gas, and coal heating with electrical heating. As a result of these initiatives, from 1990 to 1999, the annual average TSP concentration in 100 major cities decreased by 30% to 256 μg/m3 and it remained almost constant from 1999 to 2003 (Sinton et al., 2004), despite an overall decrease of 30% in total energy consumption from 1997 to 2002. Fang et al. (2009) examined the air quality management in China and the changing air quality levels with their reasons. The results of the new strategies in Beijing are seen in Fig.2. In 1998, Beijing started its phased intensive control program to fight air pollution. PM10 concentrations increased by around 10% from 2003 to 2006 because of the increase in coal-fired boiler emissions, construction activities and dust storms (United Nations Environment Program, 2007). The annual PM10 concentrations

**3.2 Air pollution sources**

**3.3 Air quality in Beijing**

results in seasonal dust storms that plague the city.

residential, cultural, industrial, and rural areas.

in Beijing decreased from 162μg/m3 in 2006 to 141μg/m3 in 2007 despite an increase in energy consumption. The recent measurements of PM10 indicates lower levels such as 123μg/m3 in 2008; 120μg/m3 in 2009, respectively. One of the reasons of the high level of PM10 is residential coal-combustion in Beijing. SO2 emissions from residential coalcombustion in Beijing were increased from 68,800 tons in 2003 to 85,100 tons in 2005. The expansion of the urban areas and the increase in SO2 emissions led to increased particulate sulfate concentrations, which resulted in higher PM10 levels. However, SO2 levels in the city are decreasing (Fang et al., 2009). Furthermore, Beijing experiences high PM10 pollution during spring dust storms. Zhu et al. (2011) showed that the typical wind speed of such dust storms is approximately 7 m/s or more, and the sand and dust sources are located about 1000-2000 km northwest of Beijing. According to Zhu et al. (2011), dust storms can reach to Beijing within 3 days.

Fig. 2. Variations of annual-mean PM10, SO2, NO2 (µgm-3) and CO (mgm-3) levels in Beijing (2000-2008) \*Air quality standard for PM10 is 100 µg/m3 and WHO guideliness is 20µg/m3.

Recently, heavy industries have been gradually replaced by less polluting industries in Beijing. Besides, several possible activities are planned on major polluting industries such as the closure of cookery units at coke and chemical plants as well as closure of cement, lime and brick plants. The, transport sector is also a major contributor to Beijing's air quality. In this sector, stringent vehicle emission standards have been established. The Beijing municipal government will also implement traffic control measures such as the improvement of fuel quality to meet the new emission standards and to ease the city's traffic congestion.

#### **4. Megacity of Cairo**

Greater Cairo (30o3'N; 31o13'E), which is the capital of Egypt, is the largest city in Africa and located in northern Egypt, to the south of the delta in the Nile basin. The Greater Cairo

Air Pollution in Mega Cities: A Case Study of Istanbul 87

(%) 30 26 23 9 6 Table 2. Relative contributions to particulate pollution from different economic activities in

Air quality in Greater Cairo is a major concern to the Government of Egypt, particularly with regard to adverse health impacts. According to Country Cooperation Strategy (CCS) for WHO and the Egypt Report (2010), particulate matter and lead pollution have been recognized as the most significant pollutants threatening health in Cairo causing at least about 6,000 premature deaths annually and about 5,000 excess cancer cases over the lifetimes of current Cairo residents. Under this framework, PM10 is the most critical air quality problem in Egypt. Windblown dusts particles were significantly contributed the PM levels in Cairo and surrounding areas (EEPP-Air, 2004). A comprehensive national air quality monitoring system has been recently established in Egypt as part of Environmental Information and Monitoring Program and implemented with support from the Danish Government. The monitoring system has been operational for the measurements of common air pollutants such as SO2, NO2, CO, O3 and PM10. This is carried out by 42 monitoring stations throughout the country with one-third of them