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Energy and Earth Science 
Vol. 1, No. 1, 2018 

www.scholink.org/ojs/index.php/ees 
ISSN 2578-1359 (Print)   ISSN 2578-1367 (Online) 

1 
 

Original Paper 

Ambient Air Quality Assessment in the Grand Casablanca Area 

(Morocco): Impact of Road Traffic Emissions for the 2013-2016 

Period 

Manal Inchaouh1*, Kenza Khomsi2& Pr. Mohamed Tahiri1 
1 Department of chemistry, Faculty of Science Ain Chock, University Hassan ΙΙ of Casablanca, 

Morocco  
2 Direction de Météorologie Nationale, Casablanca, Morocco 
* Manal INCHAOUH, E-mail: inchaouhmanal@gmail.com 

 

Received: July 31, 2018   Accepted: September 5, 2018   Online Published: September 27, 2018 

doi:10.22158/ees.v1n1p1         URL: http://dx.doi.org/10.22158/ees.v1n1p1 

 

Abstract 

Air Pollution is a serious hazard worldwide especially in urban areas. Road traffic is the main cause of 

pollution in agglomerations that are confronted to an excess of pollutants due to traffic intensity and 

the dominance of diesel cars. This paper presents the assessment of road traffic pollution in the Grand 

Casablanca area. Data used are the result of simultaneous measurements at thirteen sites located in the 

Grand Casablanca. Available data cover 4 years period (2013-2016). Traffic-related air pollutants are 

reviewed in order to assess their impact on the local air quality. It include nitrogen dioxide (NO2), 

particulate matter (PM10), carbon monoxide (CO) and Benzene (C6H6). Annual evolutions are 

presented and compared to national air quality standards; NO2 annual trends are also evaluated. The 

[NO]/[NO2] emissions ratio calculation allows then to characterize the measurement sites against road 

traffic. The paper focuses on determining the contribution of road traffic emissions on air quality 

modifying; we found spatial variability in traffic pollutants. The results pointed out that road traffic and 

conditions are the main causes of air pollution in the area and the analysis provide a quick view of the 

relatively critical areas that need more action to reduce this pollution. 

Keywords 

Air quality monitoring, measurements, urban air pollution, traffic intensity, road traffic pollution 

 

1. Introduction 

The urban environment has nowadays the wider population; this generates a perpetual growth of 



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activities that adversely affect environment, public health, well-being, and quality of life. Population 

increase is accompanied with proportional increase in emissions while higher urbanization rate and lower 

average household size increase emissions as well (Cole & Neumayer, 2004). The ever-changing 

transport sector is exacerbating the phenomenon of pollution and contributing to the overall balance of 

gas emissions. The transition from massively industrial pollution to a pollution where transports have a 

predominant share has gradually been accompanied by a major transformation of monitoring systems, 

while industrial pollution has significantly declined in recent years, transport pollution has been steadily 

increasing, with the main cause being the increase of cars traffic and the vehicles fleet. Air pollution 

parameters demonstrates a strong correlation with the traffic intensity. The highest correlation indicators 

established are from CO and NO2 pollution (Zariņš, 2014). Moreover, it is in cities that the situation is 

most sensitive, because while the pollution depends on topography and weather conditions, the 

consumption of a car in the city is four times higher than on the highway, and the highest pollution levels 

globally occurs in winter and summer (Cichowicz, Wielgosiński, & Fetter, 2017; Dadhich, Goyal, & 

Dadhich, 2017). A study on the urban population exposure to air pollution during their travels in the 

Paris agglomeration highlighted that the highest exposure levels are obtained in the passenger cars 

(Delaunay, Goupil, Ravelomanantsoa, & Person, 2012). Air pollutants are known or suspected to cause 

harmful effects on human health, traffic-related pollution proved to be significantly associated with 

respiratory symptoms in children (Kim et al., 2004), moreover, many studies showed that pollution 

increases mortality and pointed out the causal link between short-term exposure to air pollution and 

mortality (L. Pascal, 2009), (Dab et al., 2001). The Grand Casablanca , Morocco’s biggest agglomeration 

and economic capital, is currently affected by year-round air pollution (Khatami, Ponche, Jabry, & 

Mirabel, 1998).  

This study has made the first attempt to define the possible influence of road traffic emissions in 

ambient air quality over a large urban agglomeration from Morocco: the coastal area of the Grand 

Casablanca. The work carried out in this study focuses on: 

- Presenting the main indicators of air pollution originating from road traffic (NOx, PM10, CO and 

C6H6), in particular through their effects on health and the environment;  

- Present the main associated air quality standards.  

- Investigating the temporal trends of NO2 concentrations for the period 2013-2016 

- drawing up a temporal average profiles of sites with the highest levels of pollutants 

- Identifying the most affected areas by road traffic pollution by the calculation of [NO]/[NO2] 

emissions ratio of each measurement site. 

- Analyzing and exploiting data through the Boxplots representation of the average cycles  

- Determining how meteorological parameters (wind direction and speed) affects the dispersion of 

pollutants  

This study can be used in a more general reflection on atmospheric pollution during the implementation 

of Urban Travel Plan for example. 



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2. Materials and Methods 

2.1 Study Area 

The Grand Casablanca area (Figure 1) is located on the Atlantic coast in the north-west of the country, 

with an area of 1 615 km² and a population of about 4 million inhabitants (RGPH 2014). The Grand 

Casablanca hosts different activities, a large industrial environment (the thermal power station, 

Mohammedia refinery and Ain Sebaa-Bernoussi industrial zone) characterizes the North-East part, the 

urbanized part is bordered by the Bouskoura forest in the south and rural agricultural lands in the 

South-East and South-West, the southern parts are less urbanized. It is also a major transport hub for the 

whole country; railway lines and several major roads and highways connecting the city with the rest of 

the country cross it: the N1 and N11 National Roads, South Ring Road, Coastal Road, Expressway, R315 

Regional Road and the A7, A3 and A5 Highways.  

 

 
Figure 1. Location of Morocco in Africa (right map) and Location of the Grand Casablanca in 

Morocco 

Source: haut-commissariat au plan; Google maps 2018 

 

2.2 Studied Parameters and Their Health Impact 

Air pollution parameters considered here (NO2, PM10, CO and C6H6) are the main indicators of road 

traffic pollution especially in urban areas. The exhaust (fuel combustion), evaporation, abrasion of 

vehicle equipment (brakes, tires, etc.) as well as road wear and the resuspension emit these pollutants. 

Nitrogen dioxide (NO2) is a motor traffic tracer (L. Smith et al., 2015), it forms during the combustion of 

fossil fuels from the reaction of Nitrogen monoxide (NO) with oxygen or ozone in the air. NO2 causes a 

range of harmful health effects, a short-term exposure to NO2 is associated with adverse health effects 

and increases hospital admissions and mortality especially for susceptible populations (children, elderly, 

and asthmatics) and long-term exposure is associated with adverse health effects (respiratory 

symptoms/diseases, hospital admissions, mortality, etc.) (Latza, Gerdes, & Baur, 2009). Particulate 

matter 10 micron or less (PM10) comes from iron and steel industry, cement factory, wastes incineration 



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and automobile traffic and the smaller they are, the more dangerous they are (Ropeik & Gray, 2002). 

According to a public health study in France, fine particles pollution causes 48,000 deaths per year, 

which is as much as alcohol, and reduces life expectancy by up to two years (M. Pascal et al., 2016). 

Ultra-fine particles provoke alveolar inflammations, with release of mediators capable, in susceptible 

individuals (elderly, diabetics, or those with known coronary artery disease) of causing exacerbations of 

lung disease and increasing blood coagulability, thus also explaining the increases in cardiovascular 

deaths associated with urban pollution episodes (Martinelli, Olivieri, & Girelli, 2013; Seaton, MacNee, 

Donaldson, & Godden, 1995). Carbon monoxide (CO), an odorless, colorless and flammable gas, results 

from the incomplete combustion and motor vehicles is the absolutely dominant source (Fenger, 1999). 

Numerous studies showed that prolonged exposure to CO has health consequences: headaches and 

dizziness (Raaschou-Nielsen, Nielsen, & Gehl, 1995) and elderly hospitalizations for cardiovascular 

disease (Hoek, Brunekreef, Goldbohm, Fischer, & Van Den Brandt, 2002). Benzene (C6H6) is a volatile 

organic compound belonging to the family of hydrocarbons that mainly comes from the residential and 

tertiary sector, in particular from woods combustion, and road transport. Benzene has effects on the 

nervous system, blood cells and platelets that can cause loss of consciousness and the major health risk 

associated with exposure to low concentrations has been shown to be cancers risk and leukemia 

(Duarte-Davidson, 2001; M. T. Smith, 2010; WHO, 2000). 

2.3 Data Collection  

Hourly data were obtained from the air quality monitoring network of the Grand Casablanca (13 

stations) (see Figure 2) from January of 2013 to December of 2016, except for the PM10 that are daily 

data. The fixed stations are generally located in public places and measures continuously and in real 

time the concentrations of a number of ambient air pollutants including those quoted above, as well as 

the meteorological parameters allowing the transformation and dispersion of the pollutants (wind speed 

and direction, ambient temperature, atmospheric pressure and relative humidity). Air pollution 

parameters studied here are subject to specific regulations in Morocco (Table 1). In order to perform a 

relevant statistical analysis, basic data are analyzed according to the requirements of the ADEME 

Guide: “Rules and Recommendations on: Data Validation, Aggregation Criteria and Statistical 

Parameters” (2003), and the “Guide of Air Quality Data Aggregation for the Application of the 

European Directives 2004/107/EC and 2008/50/CE on ambient air quality” (2015). Only sites that meet 

the criteria mentioned in these guides are evaluated here.  

 

 

 

 

 

 

 



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Figure 2. Location of the Air Quality Stations and Road Infrastructures of the Grand Casablanca 

 

Table 1. National Ambient Air Quality Standards 

Pollutant Nature of the threshold Limit values 

NO2 (μg/m3) 
Limit values for health protection 

50; Annual Average 
200; Percentile 98 of Hourly Averages 

Limit value for the protection of 
vegetation 

30; Annual Average 

SO2 (μg/m3) 
Limit values for health protection 

125; Percentile 99.2 of the Daily 
Averages 

Limit value for the protection of 
ecosystems 

20; Annual Average 

CO (mg/m3) Limit values for health protection 
10; Daily Maximum of 8-hour running 
average 

PM10 (μg/m3) Limit values for health protection 50; Percentile 90.4 of the Daily Averages

C6H6 (μg/m3) Limit values for health protection 10; Annual Average 

 

2.4 Data Analysis 

For each site of the monitoring network, the mean annual of the traffic pollution indicators: NO2, PM10, 

CO and C6H6 were calculated and compared to the Moroccan legislated air quality standards, for the 

entire period 2013–2016. Temporal trends of NO2 concentrations were then evaluated for stations with 

a minimum data coverage of 75% of valid data per year for at least three out of the 4-years period. The 

non–parametric method proposed by Thiel (1950) and Sen (1968) for estimating the slope of a linear 

trend was used. This approach involves computing slopes for all the pairs of ordinal time points and 

then using the median of these slopes as an estimate of the overall slope. Since Sen’s slope is robust 

against outliers, it is widely used for the estimation of trending magnitudes of climate series (Deo, 



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McAlpine, Syktus, McGowan, & Phinn, 2007; Guentchev & Winkler, 2010; Hidalgo-Muñoz, Argüeso, 

Gámiz-Fortis, Esteban-Parra, & Castro-Díez, 2011; Tramblay, El Adlouni, & Servat, 2013). The 

statistical significance of the obtained trends is then tested using the modified Mann–Kendall test 

proposed by Hamed and Rao (Hamed & Ramachandra Rao, 1998), for testing the presence of a 

monotonic increasing or decreasing trend. EPA’s ProUCL5.1.002 software (US EPA Statistical 

Software for Environmental Applications for Data Sets with and without Non detect Observations) was 

used here and the test is performed at significance level of 5 %. 

In order to study temporal behaviors of pollutants, temporal profiles are presented in different time 

steps (monthly, weekly &daily) for sites recording the highest levels of NO2, PM10 and CO. 

The most affected sites by road traffic emissions are determined by the method of the NO/NO2 ratio 

calculation for characterizing the measurement sites against traffic intensity. A hierarchical 

classification is carried out and the monitoring sites are grouped according to their profiles. 

Statistical data analysis of pollutants for the site representing the highest [NO]/[NO2]ratio was 

performed using the Boxplot presentation method for different temporal cycles. Boxplot graphic is 

good for showing trends in the distributions of data (Mintz, Fitz-Simons, & Wayland, 1997). We 

represent the evolution of the minimum, 25th percentile (P25), median, mean, 75th percentile (P75) and 

the maximum. 

Meteorological data are used for the interpretation of the pollutant concentrations observed at the 

urban-traffic station representing a traffic pollution hot-spot. Meteorological parameters analyzed here 

include wind direction (°) and wind speed (m/s). 

 

3. Results 

3.1 Annual Mean Concentrations Compared to the Annual Guideline 

3.1.1 Nitrogen Dioxide NO2 

The evolution of NO2 annual averages (Figure 3 (a)) allows the differentiation of the thirteen study sites; 

it shows that the NO2 levels respect relatively the sanitary standard. A prioritization seems to be in place 

with three sites recording the highest values and exceedances of the limit value for the protection of 

vegetation (30 μg/m³): Ain Harrouda, Ain Sebaa and Bouskoura sites. The 98 Percentile evolution 

(Figure 3(b)) allows the estimation of peak levels, the measured values are all below the health 

protection limit value (200μg/m³) except for the Ain Harrouda site that exceeded this value in 2013. 

 

 

 



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Figure 3. Evolution of: (a) Annual Average Concentrations & (b) 98% Annual Percentile of Nitrogen 

Dioxide regarding the Moroccan Standards in the Thirteen Monitored Sites (2013-2016) 

 

3.1.2 Particulate Matter PM10 

For the Particulate pollution, figure 4 illustrates the annual evolution of the 90.4 daily percentiles of PM10; 

most of the represented sites experienced exceedances of the daily PM10 standard. Table2 represent the 

number of days where the PM10 standard was exceeded for the sites presenting exceedances of the health 

protection. The results shows exceedances of the sanitary standard, and a largest number of overruns 

recorded in 2014. 

 

 

Figure 4. Evolution of the 90.4 Percentile of Daily Averages of PM10 regarding the Moroccan 

Standards over 2013-2016 Period 

 

 

 

 

 



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Table 2. Number of Days Exceeding the Limit Value for Health Protection of the PM10 (90.4 

Percentile) 
 St C. 

Ain 
Chock 

St C. 

Ain 
Harrouda 

St C. 

Ain Sebaa 

St C. 
Bernoussi 

St C. 
Bouskoura

St C. 

Hay 
Hassani

St C. 
Chu

St C. 
Oncf

St C.

Wilaya

St C.

Sidi 
Othman

St C. 

Jahid 

St 

Med. 
Khansaa 

St 

Med. 
Prefecture

2013 - - - - - - - - - - - - - 

2014 - - 40 - - 35 - - - 95 - 37 - 

2015 - - - - - - - - - 43 - 14 - 

2016 - 13 - - 6 16 - - - - - - - 

 

3.1.3 Carbone Monoxide CO 

Table 3 record the exceedances of the standard for stations with carbon monoxide analyzers. In 

2013-2016 period, the measuring stations showed no exceedances of the 8-hour sanitary standard: 10 

mg/m³ (Daily maximum of the running average over 8 hours), but in 2016 the station of Ain Harrouda 

exceeded the above-mentioned value 17 days. 

 

Table 3. Number of Days Exceeding the 8-Hour CO Standard (Limit Value for Health Protection) 

 
St C.Ain 

Chock 

St C.Ain 

Harrouda 

St C.Ain 

Sebaa 

St C. 

Bernoussi 

St C. 

Bouskoura

St C.Hay 

Hassani 

St 

C.ONCF 

St C.Sidi 

Othman 

2013 0 0 0 0 0 0 0 0 

2014 0 0 0 0 0 0 0 0 

2015 0 0 0 0 0 0 0 0 

2016 0 17 0 0 0 0 0 0 

 

 

Figure 5. Annual Average Concentrations of Benzene regarding the Sanitary Standard 

 

3.1.4 Benzene C6H6 

Figure 5 shows the evolution of the annual averages of benzene for sites with benzene analyzers. A lack 

of data probably due to equipment failures for some sites, did not allow to compare the measurement 



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results or to study the evolution of annual concentrations. However, we found that the recorded levels are 

all below 10 μg/m3, the annual limit value.  

3.2 Trends in Annual NO2 Concentrations Average  

Trends in data for nitrogen dioxide (NO2) were investigated over the period 2013 to 2016 at the Grand 

Casablanca monitoring stations. Table 4 summarizes the coefficients of variation of Theil and Sen of the 

average annual NO2 concentrations. The record for six monitoring stations (Casa.Ain Saba; Casa.CHU; 

Casa.ONCF; Casa.Wilaya; Casa.Jahid; Media Prefect; and Media Khansaa) was less than three. This 

period is considered too short to offer a meaningful understanding about concentration trends. Therefore, 

results for these stations are not presented in table 4. Results indicates statistically significant increasing 

trends of annual concentrations of NO2 at the Casa.Ain Chock; Casa.Bernoussi; Casa.Bouskoura; 

Casa.Hay Hassani and Casa.Sidi Othman stations.Trends in Casa.Ain Harrouda station are not 

statistically significant. 

 

Table 4. Annual Trends in Nitrogen Dioxide (NO2) in the Studied Area; Significance Level=0.05 

Station 
Trends 

Average Nitrogen dioxide (NO2) 

ST C.Ain Chock 0.215 

ST C.Ain Harrouda 0.405 

ST C.Bernoussi 0.0595 

ST C.Bouskoura 0.247 

ST C.Hay Hassani 0.202 

ST C.Sidi Othman 0.381 

 

3.3 Intercycles Analysis: Average Profiles of Sites with the Highest Levels of Pollutants 

Figure 6 provide the evolution of automobile pollution indicators studied here, at various time scales 

(seasonal/monthly, weekly and daily) for sites recording the highest levels of pollution (Ain Harrouda, 

Ain Sebaa and Bouskoura). This allows evaluating the temporal evolutions and highlight the 

occurrence of exceptional air pollution events (pollution peaks, weekend effect, seasonality, etc.) as 

well as the specificities of this pollution according to the typologies of the measurement sites. Temporal 

profiles enable to differentiate the selected sites and globally shows homogeneous behavior for all 

pollutants. Seasonal/monthly profiles are marked by a maximum in winter (december-february) and 

minimum values at the end of summer (august-September). Weekly profiles shows higher 

concentrations on workdays and a decline on weekend with peaks in the middle of the week. As for the 

daily profiles, hourly evolution shows, for NO2, the presence of two peaks corresponding to the hours 

of intensification of car traffic during the day. NO2 level increases in the morning from 07:00 to 09:00, 

a second peak is formed in the late afternoon (19:00-22:00), beyond these hours, levels are stable and 



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the lowest values are observed at night (23:00-06:00). CO daily profile follows the same trend as for 

NO2 but with less intense peaks. For all temporal profiles, the Bouskoura site seems to be intermediate 

to the other sites for all the studied pollutants. 

 

 
Figure 6. Average Cycles (Monthly, Weekly, Daily) of Road Traffic Indicators for Sites with the 

Highest Levels 

 

3.4 Identification of Typical Traffic Sites: [NO]/ [NO2] Ratio 

Considering the results, the[NO]/[NO2]ratio differs greatly from one site to another (Table 5). The 

resulting values allows to draw a distinction between the sites and to group them in three categories: 

• Ain Chock, Bernoussi, Hay Hassani, CHU, Med Khansaa and Med prefecture sites are the least 

influenced by traffic vicinity with an [NO]/[NO2]ratio lower than 1. These sites could be defined as 

urban background sites, with an NO concentrations mainly lower than NO2 and less characteristic of 

road transport effect.  

• Ain Sebaa and ONCF sites appears intermediate (moderately affected by road traffic), with an 

NO/NO2 ratio of between 1 and 1,5. However, those of Ain Harrouda, Wilaya and Sidi Othman have 

more scattered ratios. Indeed, in 2013-2014, the sites had ratios lower than 1, then as of 2015, the 

influence of road traffic emissions seems to have increased to values beyond 1. 

• Finally, Bouskoura site stands out as the most affected site by road traffic emissions with an [NO]/ 

[NO2] ratio higher than 1.5 for most of the time. 

 



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3.5 Analysis of the Cycle Structure: Boxplots Representation 

 

Table 5. [NO]/ [NO2] Ratio during the Study Period (2013-2016) 

 

Ain 

Chock 

Ain 

Harrouda 

Ain 

Sebaa 

Bernoussi Bouskoura Hay 

Hassani

CHU ONCF Wilaya Sidi 

Othman 

Jahid Med. 

Khansaa 

Med.

Prefect

2013 0.83 0.25 -- 0.56 1.35 0.67 -- 1.13 -- 0.61 -- 0.60 -- 

2014 0.63 0.86 1.11 0.54 1.94 0.50 -- 1.01 1.08 0.59 -- 0.75 0.65

2015 0.55 1.16 0.98 0.56 2.03 0.65 0,63 1.41 1.69 1.06 -- 0.70 0.78

2016 0.50 1.39 1.11 0.63 2.02 0.49 -- 1.42 -- -- -- 0.86 -- 

 

The box-plot representation of the average cycles allow analyzing the dispersion of the concentration 

data against the average. It is therefore necessary to analyze the representativity of the average cycles 

over the considered period. For the Bouskoura site, which represents the highest NO/NO2 ratio, 

considering the figure, the data are more dispersed in winter than in summer, during the weekly peak 

(midweek) and peak hours (09:00 and 20:00). The dispersion of the NO2 data seems to be better than 

the CO and PM10 data. This observation is illustrated, in part, by the difference between the median and 

the mean of the extracted cycles (represented by the curve in Figure 7). Indeed, for the NO2 data these 

are relatively close, whereas for the CO and PM10 data the means are sometimes below the median 

values. The CO and PM10 means appear accordingly smoothed by the low extreme values and the 

NO2extreme values are higher than the high border. A specificity is noted with regard to NO2 data for 

the daily cycle, the interquartile gap is larger for hours from 7am to 10am. This can be explained quite 

simply by the alternation of the road attendance that can vary according to peak hours. 

 



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Figure 7. Average Cycles (at Monthly, Weekly, Hourly Intervals) for the Traffic Indicator 

Pollutants (NO2, CO and PM10) of the BOUSKOURA Site over the 2013-2016 Period 

 

3.6 Wind Roses  

Figure 8 present the wind roses for the Bouskoura site. The wind roses have been created using the hourly 

data from the four years 2013-2016. The results of this station located in the background of the Grand 

Casablanca suggest that the predominant winds come from the northern sector with a velocity mostly 

between 0 and 2 m/s, followed by the westerly winds; this situation is favorable to the accumulation and 

stagnation of pollution plumes loaded with air pollutants. The site was therefore influenced by the 

emissions of pollutants from the center of the agglomeration and the neighboring road network. 



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Figure 8. Wind Roses of Bouskoura Site from 2013 to 2016 

 

4. Discussions  

The purpose of this study is to examine the role of road traffic in modifying air quality in a large urban 

agglomeration, the Grand Casablanca. Over all measurement sites, the measured concentrations result 

from different contributions: background pollution, transregional contribution (imported via air mass 

flows), urban contribution mainly related to traffic and meteorological factors impact. NO2 Annual 

means showed a significant increase for some monitoring sites. The absence of statistical significant 

tendencies in time series for some monitoring sites is due to the shortness of the period used for this 

study. The high annual value of NO2 in Ain Harrouda (67.51 μg / m³) can be explained by the exposure 

of the site to the prevailing winds of the SAMIR oil refinery of Mohammedia, and the decrease is 

probably due to the significant decline of refining activities and their definitive cut by the end of 2014. 

As for PM10, the majority of sites experienced limit values exceedances most of the time; a large 

proportion of the particulate pollution can result from road dust resuspension (Amato et al., 2009) , and 

rise with the vehicles speed (Nicholson, Branson, Giess, & Cannell, 1989). The benzene and CO 

respects the recommended thresholds except for the station of Ain Harrouda that exceeds the sanitary 

standard 17 times in 2016. In order to determine the most affected sites by road traffic emissions, we 

studied the temporal evolutions of the sites with the highest values of road traffic pollutants, including 

NO2, the analysis of temporal profiles (monthly, weekly and daily) has enabled to understand the 

evolution of these pollutants over time and highlight the periods with the highest emissions. The 

NO/NO2 ratio allowed to set up a hierarchical classification and to determine the most affected sites by 

the road traffic emissions. The results revealed that the Bouskoura site have the highest values and 

turned out to be the most impacted site by the NO2 emissions. This finding may reflects the direct 

influence of road traffic emissions on the air quality in this site. However, several other factors may be 

behind these results; in addition to emission levels, meteorological parameters also highly influence the 



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pollution levels by their transport or transmission (Mayer, 2015), a low wind speed (less than 3 m/s) 

favors the accumulation of the pollutants (Latini, Grifoni, & Passerini, 2002). The analysis of the wind 

roses in the Bouskoura site reveals that the site is mainly subject to the prevailing northern winds, 

which turns the pollution plumes formed downtown to this site. That can explain the strong values 

recorded. 

 

5. Conclusion 

Urban air quality is getting worse; road traffic in the Grand Casablanca is largely responsible for the 

local emissions of nitrogen oxides and particles, and thus contributing to the degradation of its air 

quality. Some air pollutants are present in high concentrations, often above the recommended 

guidelines. In addition to emissions, air pollution levels also depend on weather conditions. This study 

allowed us to understand the spatio-temporal distribution of pollutants, particularly those emitted by 

road traffic in the Grand Casablanca and to identify the most affected areas by this type of pollution. 

This work suggests that road traffic plays an important role in the air quality modification, especially in 

areas with heavy road traffic or close to major traffic routes. The Improvement of local air quality 

requires therefore additional controls and the application of reduction strategies for the vehicular 

emissions to reduce the alarming pollution levels. 

 

Declaration of interest 

The authors report no conflicts of interest. The authors alone are responsible for the content and writing 

of this article. 

 

Acknowledgements  

We want to express our gratitude to the Direction de Météorologie Nationale of Casablanca for kindly 

providing the necessary data.  

 

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