ORIGINAL PAPER

Contribution of atmospheric processes to the degradation of airquality: case study (Sohar Industrial Area, Oman)

Abdullah Al-Khadouri & Sultan Al-Yahyai &Yassine Charabi

Received: 17 June 2013 /Accepted: 22 January 2014# Saudi Society for Geosciences 2014

Abstract The impact of the air pollution generated by anyindustrial activities may be further aggravated if the locationof the industrial area is exposed to certain atmospheric char-acteristics. Under such conditions, the likelihood of accumu-lation of local air pollution is high. This paper uses twoapproaches (statistical and numerical simulation) to investi-gate the contribution of atmospheric processes towards deg-radation of air quality. A case study of the two approaches wasconducted over Sohar Industrial Area in the Sultanate ofOman. Measured wind data were used to account for specificatmospheric characteristics such as stagnation, ventilation,and recirculation using the statistical approach. In the secondapproach, numerical weather prediction model was used tosimulate mesoscale circulation phenomena such as sea breezeand its contribution to the processes affecting the air quality.The study demonstrates that the atmospheric processes appearto contribute substantially to the degradation of air quality inthe Sohar Industrial Area. The statistical analysis shows thatthe atmospheric dilution potential of Sohar Industrial Area isprone to stagnation and recirculation, rather than ventilation.Moreover, model simulation shows that there is a seasonalvariation in the contribution of atmospheric processes to thedegradation of the air quality at Sohar Industrial Area.

Keywords Air quality . Stagnation . Recirculation .

Ventilation . Sea breeze . Sohar Industrial Area

Acronym/abbreviationsU Observed wind speedθ Observed wind directionN Number of observationsui Wind vector into east–west direction of the ith

observationvi Wind vector into north–south direction of the ith

observationXi Transportation distance on east–west directionYi Transportation distance on north–south directionτ Sampling intervals of the wind observationLi Horizontal straight line distance of the ith observationSi Wind run of the ith observationRi Recirculation factor of the ith observation

Introduction

The issue of air quality is of a great concern to many people.Different studies have been conducted to investigate air qual-ity problem and proposed methods to improve quality of theair, especially in rapidly developing industrial areas. In orderto determine the effect of air quality on humans, deeperknowledge about the atmospheric processes that control thetransport and dispersion of the air and its pollutants is needed.In many countries, studies of the local atmospheric transportand dispersion conditions are now mandatory prior to thedevelopment and construction of any new industrial area.

The effect of atmospheric processes on air quality has beendiscussed and analyzed statistically in studies such as Allwine

A. Al-Khadouri : S. Al-Yahyai (*)Public Authority for Civil Aviation, Oman National MeteorologicalService, P.O. 1, Postal Code 111 Muscat, Omane-mail: s.alyahyai@gmail.com

A. Al-Khadourie-mail: a.alkhadouri@gmail.com

Y. CharabiDepartment of Geography, Sultan Qaboos University, P.O. 42,Al-Khodh, Muscat 123, Omane-mail: yassine@squ.edu.om

Arab J GeosciDOI 10.1007/s12517-014-1295-0

andWhiteman (1994), Kim et al. (2007), Nankar et al. (2009),Venegas and Mazzeo (1999), and Charabi and Al-Yahyai(2010). Numerical simulations were also used to analyze theair quality. Simulation results were presented at Crescenti(1997), Liu and Chan (2002), Bornstein and Thompson(1981), Kassomenos et al. (1998), Gangoiti et al. (2002),Bastin et al. (2005), and Bouchlaghem et al. (2007).

Several types of air pollutants were investigated at differentregions. Ghrefat and Howari (2011) investigated dust trans-port and deposition over UAE. Similarly, dust particles loadanalysis was conducted over Iraq (Al-Dabbas et al. 2010).Phosphate particles, which may cause several diseases such ascancer, respiratory, and allergies, were also investigated overthe mining area in Tunisia (Mokadem et al. 2013). Khelfaouiet al. (2012) used discriminant statistical analysis to determinethe origin of industrial pollution type in the aquiferous systemof the area of Berrahal in Algeria. Recently, Sönmez et al.(2013) monitored and analyzed air pollutants generated fromfires using the Meteosat second-generation products.

Statistical approach analyzes the observed wind data at onesite and calculates different air quality indices. On the otherhand, mumerical modeling methods are used to simulate theair quality through trajectory calculation and dispersion.However, this research paper combines both statistical andnumerical approaches. Combining both approaches is usefulto investigate the air quality at single site by calculatingseveral air quality indices (statistical approach) and then toinvestigate the effect of the air pollutions over the surroundareas (numerical approach). Numerical simulation is also use-ful to investigate the vertical extent of the pollutants. A casestudy using both approaches was conducted over SoharIndustrial Area in the north of Sultanate of Oman. First,statistical analysis was used to explain specific atmosphericcharacteristics such as stagnation, ventilation, and recircula-tion using hourly wind data covering a 5-year-period (2005–2009). Then, numerical weather model was used to simulatemesoscale circulation (sea breeze) and its contribution to thedegradation of the processes air quality. Consortium forSmall-Scale Modeling (COSMO) model at 2.8-km resolutionwas used in this study.

The rest of the paper is organized as follows: The casestudy area is presented in “Area of study.” “Methodology”presents the methodology employed in this study. “Resultsand discussion discusses the results, and finally, the paper isconcluded in “Conclusions.”

Area of study

Sohar is located in the northeastern part of Oman. Heavyindustrial plants such as those involving petrochemicals andmetals are located close to the city. Because of these heavyindustries, air quality in Sohar is threatened with degradation;

this is becoming one of the primary environmental issues inthe country. Geographically, Sohar lies between two naturalbarriers, which are the Al-Hajar Mountains to the west and theSea of Oman to the east. Figure 1 shows the topography of thearea.

Climatology, Sohar is characterized by arid to semi aridclimate. There are mainly two seasons in Sohar, which aresummer and winter. Summer extends fromMay to Septemberand the winter extends from November to February. The restof the months are considered as transitional period betweenthe main seasons. Summer in Sohar is characterized by hotand humid air mass, and average temperature varies between30s and 40s. On the other hand, winter is characterized by coldand dry continental air mass where the temperature rangesbetween 10s and 20s. In general, the wind in Sohar is domi-nated by the mesoscale circulation through the sea and landbreeze. Finally, there are two main sources of rain that affectSohar: topographic rainfall that sometime affects Sohar duringthe summer days and westerly frontal systems that affectSohar during winter days Kwarteng et al. (2009).

Methodology

Statistical approach

Allwine and Whiteman (1994) proposed a way to study atmo-spheric transport and dispersion conditions by identifying thefactors affecting the occurrence of stagnation, recirculation, andventilation of the air above any site. The representative integralquantities for stagnation and recirculation are calculated on thebasis of observed wind speed (U) and direction (θ). Thismethod considers a time series of N data pairs (U, θ), and itproposes to resolve the wind vector into east–west (positivetowards the east) and north–south (positive towards the north)components, respectively, in the following way:

ui ¼ UisinX

θi−180� �

ð1Þ

vi ¼ UicosX

θi−180� �

ð2Þ

where i=1, 2…NBy summing Eqs. (1) and (2) over a period of 24 h, the

transportation distance of the effluents is calculated in thedirection of east–west and north–south, respectively.

X i ¼ τXiþp

j¼1

uj ð3Þ

Y i ¼ τXiþp

j¼1

v j ð4Þ

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where τ is the sampling intervals and P=24H/τ.The horizontal straight line distance (Li) from the release

point is calculated using Eq. (5):

Li ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiX 2

i þ Y 2i

qð5Þ

The real transport distance (Si), which is also known aswind run (Si), is calculated using Eq. (6):

Si ¼ τXiþp

j¼1

U j ð6Þ

The recirculation factor (Ri) is calculated at each time step tiusing Eq. (7):

Ri ¼ 1−

XLi

Si

!ð7Þ

According to Allwine and Whiteman (1994), the wind runSi is used as an indication of stagnation and can be defined asthe total distance a parcel of air would travel regardless ofdirection over the transport time τ. Total stagnation existswhen Si is equal to 0. This occurs when winds are calm (orwith very low speed), and thus, the result is no net transport.

The recirculation factor (Ri) indicates the occurrence oflocal recirculation on time scales comparable with τ. WhenR is equal to 0, straight line transport will occur. When R isequal to 1, zero net transports will occur over a time interval τ.As a result, there will be a complete recirculation.

Ventilation is characterized by high values of wind run S andlow values of recirculation factor R. In this way, the concept ofgood ventilation should be interpreted as the atmospheric ca-pacity to replace polluted air by sweeping in fresh air.

Allwine and Whiteman (1994) proposed an approach forclassifying the atmosphere of different sites by comparing the

Fig. 1 Topographical map of thearea of study

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mean values of the wind run (S) and the recirculation factor(R) with predetermined critical values. If the mean value of Sis lower than the critical value, the local atmosphere shows atendency towards stagnation of the air. On the other hand, ifthe mean value of R is greater than the corresponding criticalvalue, the local air flow has a tendency towards recirculation.For a site prone to ventilation, the mean value of S is greaterthan a critical value of S for ventilation and the mean value ofR is lower than critical value of R for ventilation.

A second procedure for classifying stagnation, recircula-tion, and ventilation potential is based on the computation ofpercent occurrence of Si≤Sc (stagnation), of Ri≥Rc

(recirculation), and simultaneously Si≥Scv and Ri≤Rcv

(ventilation), where Sc, Rc, Scv, and Rcv are the respectivecritical values. Allwine and Whiteman (1994) have pointedout that the sum of the observed percent occurrence of stag-nation, recirculation, and ventilation for any site will notnecessarily add up to 100 %. The reason is that some flowconditions might not show any of these features or stagnationand recirculation could occur simultaneously.

Numerical simulation

Mesoscale circulation such as sea breeze is a very importantphenomenon which plays a major role in exacerbating theconcentration of air pollutants in any industrial region. Anonhydrostatic numerical weather model COSMO, as de-scribed in Doms and Schattler (2012), at 2.8-km resolution,is used to simulate the sea breeze. Table 1 summarizes themain configurations used in COSMO model.

This simulation is used to identify different aspects relatingto sea breeze such as extent of inland penetration, verticalextent, and the depth of PBL, which in turn will explain thetransport and dispersion of air pollution. Typical summer andwinter cases are used to analyze the seasonal variation of seabreeze characteristics. Simulation results are validated bymeans of wind observation.

Results and discussion

Statistical analysis

Variation of straight line distance (Li) from the release point

The straight line distance (Li) as described in Eq. (5) showshow far a parcel of air can travel depending on both its speedand direction. The straight line distance from the release pointduring the period of 2005–2009 for Sohar weather station isgiven in Table 2. The straight line distance from the releasepoint was found to vary from 0.82 to 130 km with an averagevalue of 26.43 km. The daily average Li distance from therelease point was observed to be at a minimum (0.82 km) on13/08/2006 and was observed to be at a maximum (130 km)on 02/07/2006. On the day on which Liwas the minimum, thehourly average wind speed was fluctuating from 0.1 to 2.3 m/swith a daily average wind speed of 2.3 m/s, and the maximumfluctuation of wind direction was 311°. As a result of lowwind speeds and large variation in the wind direction, the windparcel had traveled less than the straight line distance from therelease point. On the other hand, on the day where Li wasmaximum, the hourly average wind speed was fluctuatingfrom 0.5 to 9.4 m/s with a daily average wind speed of4.5 m/s. The maximum fluctuation of wind direction was174°. As a result of the relatively high average wind speedand low variations of wind direction, the wind parcel hadtraveled a maximum Li distance from the release point.Therefore, the daily average straight line distance dependson both wind speed and direction.

It can be concluded that the daily average straight linedistance that a parcel of air can travel is only 26.43 km, whichis a very short distance compared with the average wind speedof 2.0 m/s.

Table 1 CSOMO model configuration

Details Configuration

Model equations Nonhydrostatic, full compressible hydro-thermodynamical equations in advection form.Subtraction of a hydrostatic base state at rest

Model resolution 2.8 km nested from 7 km; 50 vertical layers;lowest model layer at 10 m above the ground

Prognostic variables Horizontal and vertical Cartesian windcomponents, pressure perturbation,temperature, specific humidity, cloud watercontent. Optionally: cloud ice content, turbulentkinetic energy, specific water content of rain,snow and graupel

Coordinate system Generalized terrain-following height coordinatewith rotated geographical coordinates and userdefined grid stretching in the vertical

Initial conditions Global German Model analysis at 00 UTC

Boundary conditions Global German Model (20 km); 40 vertical layers

Surface layerparameterization

Turbulent kinetic energy

Convectionparameterization

Tiedtke mass-flux convection

Table 2 Variation of straight line distance (Li) from the release pointduring 2005–2009

2005 2006 2007 2008 2009

Number of pints 365 365 365 365 365

Min 2.08 (km) 0.82 1.82 0.94 1.73

Max 80.18 130.35 91.20 95.97 77.32

Average 25.47 27.23 26.15 26.63 24.99

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Variation of wind run (Si)

The wind run Si is used as a measure of stagnation and it isdefined as the total distance traveled by a parcel of air. In thisstudy, the wind run is found to vary from 69.1 to 319.2 kmwith an average value of 126.3 km. The daily average windrun was observed to be a minimum of 69.1 km on 12/10/2005and a maximum of 319.2 km on 01/02/2008. During the dayon which minimum wind run was observed, the hourly aver-age wind speed was fluctuating from 0.4 to 2.25 m/s, with adaily average wind speed of 1.4 m/s. It can be concluded thatthere is a large variation between the minimum and maximumwind run during the year.

Figure 2 shows seasonal variation of average wind run (Si)during 2005–2009 for the Sohar weather station. In this con-text, summer is (May, June, July, August, and September), fallis (October and November), winter is (December, January,and February), and spring is (March and April). It can be seenthat the average wind run was the highest during summerand the lowest during fall with 132 and 111.68 km, re-spectively. Higher values of wind run during summerseason can be explained by the meteorological situationof the synoptic and mesoscale circulation that occurs inthe area. During summer, a major heat difference betweenland and sea occurs, and this enhances the mesoscalecirculation by producing a significant sea breeze duringthe day and a land breeze during the night. According tothese results, an air parcel will typically travel furtherduring the summer season compared to the distance cov-ered in the fall season. In terms of air quality, a parcel ofpolluted air would travel further in summer than it wouldin the fall or other seasons.

Variation of the recirculation factor (Ri)

Recirculation is a process where the air parcel is returned backto its releasing point. The recirculation factor (Ri) indicates theoccurrence of local recirculation on time scales comparablewith τ. When Ri is equal to 0, straight line transport will occur.

On the other hand, when Ri is equal to 1, zero net transportswill occur over a time interval τ. The daily average recircula-tion factor was found to vary from 0.327 to 0.994 with anaverage value of 0.790.

Figure 3 shows the variation of seasonal recirculationfactor (Ri) during 2005–2009. It can be seen that theaverage seasonal recirculation factor (Ri) is higher inwinter and summer than in the other seasons. This resultcan also be explained by the synoptic and mesoscalecirculation in the study area. As mentioned earlier, duringsummer and winter, the mesoscale circulation is moredefined than in the transitional seasons. Therefore, bothsea and land breeze can be noticed clearly throughout dayand night during summer and winter.

Atmospheric stagnation, recirculation, and ventilation

Following Allwine and Whiteman’ (1994) method, the occur-rence of stagnation (Si≤Sc) was estimated assuming Sc=170 km. On the other hand, Rc=0.4 was assumed for theestimating the recirculation (Ri≥Rc). Finally, ventilation (Si≥Scv and Ri≤Rcv) was estimated assuming Scv=250 km andRcv=0.2.

Based on these assumptions, there are two conditionsrequired for ventilation to take place. First, the wind runshould be more than 250 km. Second, the recirculationfactor should be lower than 0.2. It was found that theoverall occurrences of stagnation, recirculation, and ven-tilation characteristics in the Sohar Industrial Area during2005–2009 are present for 91.6 % of the time, 99.3 % ofthe time, and 0.0 % of the time, respectively. The sum ofthe observed percentages for occurrence of stagnation,recirculation, and ventilation is not equal to 100 % be-cause, in most of the cases, stagnation and recirculationwere observed to occur simultaneously.

Based on the obtained results, recirculation has the mostfrequent occurrence. In fact, out of a total of 1,826 days, only9 days were observed without recirculation of air masses. Thishigh percentage of recirculation is supported by the

Fig. 2 Variation of seasonal windrun (Si) during 2005–2009

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geographical orientation of the mountains and meteoro-logical conditions of the synoptic and mesoscale circu-lation. Geographically, the city of Sohar is situatedbetween two natural barriers formed by a chain ofmountains (Alhajar Al-Gharbi)) to the west and theSea of Oman to the east. Therefore, Sohar City is aperfect place for the recirculation factor to play a role.

The occurrence of stagnation is also high with a percentageof 91.6 %. This high percentage of stagnation can be ex-plained by the weak values of the wind run compared to thecritical value, which is 170 km. However, there is no casesatisfying both of the conditions necessary for ventilation andtherefore ventilation did not occur.

In terms of air quality, these results showing frequentoccurrence of stagnation and recirculation and zero occur-rence of ventilation suggest that a serious air pollution riskmay be present due to the existence of the industrial factoriesin the Sohar area.

The seasonal variations of stagnation, recirculation, andventilation during 2005–2009 are given in Fig. 4. It can beobserved that the instances of stagnation are high during falland winter and low during spring and summer with percent-ages of 97.0, 95.4, 88.1, and 86.2 %, respectively. This highpercentage of stagnation during fall is supported by the aver-age low values of wind run that are recorded during thatseason. Because of high values of average wind run during

summer, summer season had the lowest percentage of stagna-tion with 86.2 %. Stable weather with stagnant air mass isexpected over the area during fall and winter. Stable weatherconditions are known to enhance stagnation in the atmosphereof any area (Moran and Morgan 1986).

Recirculation is comparatively higher in summer and win-ter seasons with 99.7 and 100 %, respectively. This resultis also related to the meteorological conditions prevailingin the Sohar Industrial Area during summer and winter.Finally, it can also be seen that the occurrence of ventila-tion across all seasons is 0 %. This result indicates thatthere was no single case satisfying both conditions forventilation to occur. Therefore, it can be seen that thetransport conditions in the Sohar Industrial Area werevery weak during the study period.

Numerical simulation

Two case studies were conducted over the study area.COSMO model at 2.8-km resolution was used to simulatesea breeze circulation. These case studies were conducted on atypical winter day (January 1) and a typical summer day (1stAugust). These 2 days were selected after detailed analysis ofsynoptic situation and satellite images (Charabi and Al-Yahyai2010). The output results of this simulation were verified byobservations recorded on those days

Fig. 3 Variation of seasonalrecirculation factor (Ri) during2005–2009

Fig. 4 Seasonal and annualvariation of air quality indicesduring 2005–2009

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Winter case

After analyzing the satellite images and surface maps of thatday (Charabi and Al-Yahyai 2010), it can be confirmed thatthere was no synoptic weather situation affecting the studyarea. Therefore, January 1st was a suitable day to simulate thesea breeze (Fig. 5 and LST).

Figure 5 and 6 shows simulated wind speed and direction at1000 hPa at different time of the day. It can be seen that theonset of sea breeze in Sohar started between 12 to1PM (localstandard time) and ended at 6PM; between 6 and 7PM, it startedto shift from the northeast (sea breeze) to the southwest (land

breeze). The duration of the sea breeze winds during that daywas approximately 6–7 h.

Figure 7 shows the observed measurements of the winddirection on January 1, 2009 at the Sohar weather station. Itshows good agreement with the simulated model output.However, it can be seen from Fig. 5 that the peak of the seabreeze strength occurred around 3 and 4PM and penetratedinland to the east side of the Al-Hajar Mountains. Therefore,any existing “polluted air mass” generated by the industrialSohar area would be carried over the land along with the seabreeze and would affect the residential areas.Moreover, due tothe stagnation of the air which occurs naturally during late

(a) 0400 LST (b) 0700 LST

(c) 1000 LST (d) 1300 LSTFig. 5 Simulated winds over the northern part of Oman (04–13 LST): a 0400 LST, b 0700 LST, c 1000 LST, and d 1300 LST

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night and early morning, most of the smoke and air pollutantswill accumulate in the very lowest level of the atmosphere.Therefore, the blowing sea breeze will move this “polluted airmass” into the residential areas during the daytime hours

where it may cause very serious problems to human healthas well as to the agricultural sector. Figure 8 shows verticalcross section for wind barbs, temperature (shaded), and hu-midity (contours). Calm wind and low temperature during the

(a) 1600 LST (b) 1900 LST

(c) 2200 LST (d) 0100 LSTFig. 6 Simulated winds over the northern part of Oman (16–01 LST): a 1600 LST, b 1900 LST, c 2200 LST, and d 0100 LST

Fig. 7 Observation of winddirection during January 1 inSohar meteorological station

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late night and earlymorning clearly indicate the stagnation of theair. In addition, the onset of the sea breeze wind (northeasterlywind) between 12 and 13PM and its ending at 6PM are clearlysimulated. Due to the weak thermal difference between land andsea during winter, wind speed during sea breeze is relatively lighttomoderate, with amaximumwind speed of 15 knots (26 km/h).

Summer case

Table 3 summarizes the simulation results of the summer casestudy as compared with the results of the winter case study.The comparison shows that the sea breeze during summer ischaracterized by longer duration, higher strength, and deepervertical depth than is the case during the winter. For example,the duration of the sea breeze during summer is 9 h, whereasthe sea breeze during winter lasts only 4 h. Therefore, in termsof air quality, a typical summer day in the Sohar area isexpected to experience less degradation of the air quality thanany typical winter day. This is due to the fact that air pollutants

will be mixed into a larger layer and dispersed over a widerarea during summer as compared to winter.

Depth of the boundary layer

NCEPGADS simulation is used to analyze the boundary layerdepth. Figure 9a shows that the depth of the boundary layerduring the winter case reached about 1,400 m. It also showsthat the atmosphere is extremely stable (G) throughout the dayand night except from 13 to 16 LST when the atmosphere isslightly unstable (C) due to the weak heating. Furthermore,vertical mixing coefficient (VMC) in the figure indicates thatthe turbulent mixing layer is located below 450 m. In terms ofthe air quality, the air pollution will be trapped below the450 m level of the atmosphere. On the other hand, Fig. 9bshows that the depth of the boundary layer during the summercase reached to approximately 3,500 m. It also shows that theatmosphere is extremely unstable (A) in the middle of the dayand in the afternoon and slightly unstable during the morning

Fig. 8 Time cross-section over the meteorological station in Sohar region, wind barbs, temperature (shaded) and humidity (contours)

Table 3 Winter and summercase comparison results Sea breeze Summer Winter

Start time Around 10 LST Around 13 LST

End time Around 19 LST Around 17 LST

Duration (h) 9 h 4 h

Strength (km/h) 38 km/h 26 km/h

Inland penetration East of Hajr Mountains (∼90 km) West of Hajr Mountains (∼30 km)

Vertical extent (hPa) Below 900 hPa, ∼3,500 m 950 hPa, ∼1,800 m

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and the early part of the night. The indication of VMC showsthat the turbulent mixing layer is found below 1,400 m.

It can be concluded from those figures that the depth ofthe boundary layer in the summer is more than the doublethat observed in the winter. In addition, the mixing layerduring the summer is higher than in the winter. Thisindicates that any air pollutants can accumulate morefrequently in the winter than summer because of theshallower boundary and mixing layer that exist at thistime. However, during summer, the air pollutants will bemixed into a more extensive layer, and hence, their con-centration is reduced. It can be seen that there is a directrelation between the vertical extents of the sea breezeduring both cases and the simulated depth of boundarylayer.

Conclusions

Two approaches (statistical and simulation) were used in acase study to investigate the contribution of atmospheric pro-cesses to the degradation of the air quality in the SoharIndustrial Area. With the statistical approach, atmosphericcharacteristics such as stagnation, ventilation, and recircula-tion factors were analyzed using wind measurements.Numerical simulation was then used to analyze the strength

and depth of air circulation and its role in the degradation ofthe air quality in this area.

The statistical approach showed that the atmospheric dilu-tion potential of the Sohar Industrial Area is affected more bystagnation and recirculation than by ventilation. In fact, therewas no single case during the period of the study showing anyventilation in the Sohar Industrial Area. However, the stagna-tion and recirculation processes were observed to be moreactive during fall and winter than over the rest of the year. Thestudy showed that the overall occurrence percentages of stag-nation, recirculation, and ventilation are 91.6, 99.3, and 0% ofthe time, respectively.

The simulation results showed that the sea breeze dur-ing winter is characterized by short duration, weakstrength, and shallow vertical depth. On the other hand,the sea breeze during summer has longer duration, stron-ger inland penetration, and deeper vertical extent. In termsof air quality, a typical winter day in the Sohar area isexpected to experience more degradation of the air qualitythan any typical summer day. This is due to the fact that airpollutants will bemixed into a more extensive layer and over awider area during summer as compared to winter. This casestudy and its findings suggest that the Sohar Industrial Area byvirtue of its geographic location is prone to atmosphericconditions likely to exacerbate the impact of atmosphericpollution generated by factories in the area.

Fig. 9 NCEP-GADS simulationof the PBL and vertical coefficientfor winter (a) and summer (b)

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