Investigation of aerosol trace element concentrations nearby Algiers for environmental monitoring using instrumental neutron activation analysis

    Investigation of Aerosol Trace Element Concentrations nearby Algiers for Environmental Monitoring using Instrumental Neutron Activation Analysis Zohra Bouhila, Mohammed Mouzai, Tarek Azli, Arezki Nedjar, Choaib Mazouzi, Zineb Zergoug, Dallel Boukhadra, Salah Chegrouche, Hakim Lounici PII: DOI: Reference:

S0169-8095(15)00188-X doi: 10.1016/j.atmosres.2015.06.013 ATMOS 3435

To appear in:

Atmospheric Research

Received date: Revised date: Accepted date:

18 February 2015 13 June 2015 15 June 2015

Please cite this article as: Bouhila, Zohra, Mouzai, Mohammed, Azli, Tarek, Nedjar, Arezki, Mazouzi, Choaib, Zergoug, Zineb, Boukhadra, Dallel, Chegrouche, Salah, Lounici, Hakim, Investigation of Aerosol Trace Element Concentrations nearby Algiers for Environmental Monitoring using Instrumental Neutron Activation Analysis, Atmospheric Research (2015), doi: 10.1016/j.atmosres.2015.06.013

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ACCEPTED MANUSCRIPT Investigation of Aerosol Trace Element Concentrations nearby Algiers for Environmental Monitoring using Instrumental Neutron Activation Analysis Zohra Bouhilaa,b*, Mohammed Mouzaia, Tarek Azlia , Arezki Nedjara, Choaib Mazouzib, Zineb Zergouga, Dallel Boukhadraa, Salah Chegrouchea, Hakim Lounicib,c. a

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Nuclear Research Center of Draria (CRND/COMENA), Sebala, Draria PO Box 43, Algiers, Algeria b National Polytechnic School of Algiers (ENP), 10 Hassen Badi, PO Box 182, El Harrach, 16200, Algiers, Algeria c University of Bouira, Algeria

*

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Corresponding author. Tel.:+213 7 72 52 18 70; fax: +213 21 31 03 04 E-mail address: [email protected] . (Z. Bouhila). Present address: Nuclear Research Center of Draria (CRND) Commissariat à l’Energie Atomique (COMENA), Sebala, Draria PO Box 43, Algiers, Algeria. Abstract: The aim of this study was to enhance the use of instrumental neutron activation analysis (INAA) for long-term monitoring of air pollution and to identify critical sources of

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air pollution. For the collection of total suspended particulate matter (TSP), a filter unit low volume sampler (LVS) was employed. One hundred and seventeen samples were collected

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during 2010, 2011 and 2012, both on weekdays and weekends at a monitoring station located in Draria city, asuburban site near Algiers, Algeria. The concentrations of 25 trace elements (As, Br, Ca, Cd, Ce, Cl, Co, Cr, Cs, Eu, Fe, Gd, Hf, K, La, Mn, Mo, Na, Sb, Sc, Se, Sm, Sr, V, and Zn) were determined by INAA with using short and long neutron irradiation technique. Generally lower concentration values were observed during the weekends

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compared to the weekdays for almost all elements. The mean TSP concentration (34.8μg/m3) showed a seasonal pattern with higher levels during summer. The weekday/weekend ratio of TSP was 1.3 higher during summer than in winter. The concentrations of the elements Sb, Se and Cd are found to be highly enriched in atmospheric particulate matter. According to their, high enrichment factors (EF), it was possible to establish that these elements are of anthropogenic origin coming from automobile exhausts which is the main source of emission in this area. The typical suburban background TSP and trace element levels were compared with literature data from other regions around the world, and were lower than those reported in an urban site in Algiers in a previous study. Significant correlations between elements were found (Pearson’s coefficients >0.5) suggesting that the contaminant trace elements may be discharged from the same sources.

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ACCEPTED MANUSCRIPT Keywords: Total Suspended Particulate matter (TSP); Low Volume Sampler (LVS); Trace

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element; Instrumental Neutron Activation Analysis (INAA); Enrichment Factors (EF).

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1. Introduction

The abnormal levels of trace elements in atmosphere are potential health hazards and hence

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trace elements monitoring is an important aspect of atmospheric pollution studies (Almeida et al., 2011a). The distribution of trace elements in the environment at different geographical regions has been reported by many authors (i.e, Stortini et al. 2009; Jong-Myoung et al., 2010; Burt et al., 2011; Contini et al., 2012; Calvo et al., 2013; Feng Li et al., 2013). However, there is no recent information on trace element pollution in urban and suburban areas in Algiers.

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Limited data available shows that like all other major cities in the world, the capital city Algiers is also confronted with severe air pollution problems. Vehicle emissions are one of

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the major sources of air pollution in Algiers. Of special concerns are diesel-powered vehicles that emit a complex mixture of toxic gaseous pollutants and particulate matter (PM). Diesel vehicles contribute significantly to the particulate air pollution burden, especially in Algiers

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city (Oucher et al., 2012, Belamri, et al 2009). In other regions in North Africa, very little data for the study of the total suspended particulate (TSP) and any other particulate matter (PM) fractions are collected. In Morocco, some preliminary studies on air pollution are reported (El Khoukhi et al., 2004 and Bounouira et al., 2014); however, the data collected are insufficient to

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draw conclusion on the air quality in the study areas. Instrumental neutron activation analysis (INAA) is an established technique used for the measurement of trace elements levels in various matrices. INAA involves the neutron activation of the different trace elements in the sample and measuring the radioactivity of each radioisotope formed in order to measure the individual concentrations of the trace elements (Henderson and Pankhurst, 1984). INAA facilitates non-destructive analysis of trace elements in samples of different matrices (Tian, 2000 and Lei et al., 2002) especially of environmental origin (Gallorini et al., 1999). Certified reference materials (CRM) are used for estimation of the concentration of different trace elements in the samples. By simultaneous analysis of all the elements in a sample by a single experiment, the systematic errors are significantly reduced in INAA. In fact, the INAA is a powerful analytical technique (Avino et al., 2013) as it can do multi-element analysis of about 30 elements with high sensitivity enabling low levels of detection (LOD) with high accuracy (Avino et al., 2006) (Table 1). 2

ACCEPTED MANUSCRIPT In the present study, a monitoring campaign for about 14 months was undertaken to investigate the concentrations of trace elements in the air in a site in Draria city in the suburban Algiers. The sampling was designed to integrate different

seasons

and

social

events (i.e. winter, spring, winter and summer school vacation) that potentially influence the

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air dust composition in the environment. In most urban regions, the road traffic varies considerably between weekdays and weekends, with a strong increase on the weekdays. In

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different elements during all seasons is also done.

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this paper, a comparison between weekday and weekend variations in the concentrations of

The aims of this study are:

i. The determination of the TSP trace element concentrations in a suburban environment by INAA method; and

ii. The evaluation of the variation of the elemental composition in TSP, during weekdays and

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weekends in different seasons.

A comparison of the trace element levels estimated in the present study with the literature

2. Materials and methods

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data is also done.

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2.1 Site description and sample collection Sampling of TSP was carried out in the municipality of Draria (area: 20 km 2; population: 44141 in 2010) which is a residential area located in the suburb of Algiers, the capital city of Algeria. The sampling site (36 ° 43'32, 18'' North and 3 ° 00'29, 15'' East) is located on the

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roof of a three storied building approximately 15 m above the ground level and 10 m away from the nearest road having a traffic of ~ 30,000 vehicles/day. The sampling site is located at 200 m above sea level and about 10 km southwest from the centre of the heavy-traffic intersection as shown in Fig.1.

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ACCEPTED MANUSCRIPT Fig. 1. Map of Algeria showing the city and the sampling location for total particulate matter (TSP).

Draria city is densely populated with a high population growth rate and with increasing

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vehicular traffic. Traffic is a major source of metals related air pollution in this area, mainly due to abrasion of the brake linings and tires followed by the re-suspension of road dust

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generated by the strong winds that marks this region. The sampling site was characterized by

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good natural ventilation with absence of obstacles. The autumn and winter seasons of the site are dominated by strong northeasterly winds and moderate winds prevail for the rest of the year. There are no industries nearby emitting particles interfering with the air pollution due to road traffic except some surrounding construction sites. The closest domestic incinerator was 7 km east.

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Sampling was performed between December 2010 and January 2012 on weekdays and as well as weekends. TSP samples were collected continuously with a flow rate of 1m3/h using 0.8

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m pore size and 37 mm diameter Whatman cellulose nitrate filters (Whatman Inc., Maidstone, UK) using a low volume sampler (LVS) system (Millipore Bedford, USA). A

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detailed description of the sampling equipment is given by Hopke et al. (1997). The collection system was carefully cleaned with ethanol after each sampling was completed. In total, one hundred and seventeen samples were collected with an average sampling time of 50 hours, which corresponds to 50 m3 of filtered air per filter.

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2.2 TSP Analysis

The sampling filter papers were conditioned by exposure at constant temperature (20±5 °C) and humidity (50±2%) for about 24 hours. The filter papers were weighed before and after collection of aerosols using an analytical balance having precision of 0.01mg. Filter papers were stored at room temperature in desiccators at room. The TSP concentrations on loaded filters were determined in µg/m3 by gravimetric analysis (Zhang et al., 2010). The details of both sampling method and gravimetric analysis are given in Bouhila et al., (2012).

2.3 Trace element analysis by INAA 2.3.1 Preparation, arrangement of samples, standards and blanks for INAA: The trace element concentrations were determined by INAA according to the procedure fully detailed in Revel and Ayrault (2000). All reagents used in the experiment were at least of analytical grade. Samples CRM were weighted with the same precision level. Each filter was cut into 4

ACCEPTED MANUSCRIPT two parts with a clean ceramic scissors, half for the INAA and the other half as control. Due to the high cost of CRM, the accuracy of INAA applied to our air samples, was tested by using more common reference materials from environmental origin which are intensively used in our laboratory. Indeed, in each case and according to the element to be analysed,

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several standards are used in our laboratory, among which the IAEA-SL-1, IAEA-Soil-7 obtained from the International Atomic Energy Agency (IAEA) are frequently used. In each

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experiment, one standard was used as control and the other one as a comparator. The details concerning the criteria for qualification as recommended or an information value of elements

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can be found in the corresponding Reference sheets (Reference sheet, IAEA-Soil-7, 1999 and Reference sheet, IAEA-Soil-7, 2000)

For neutron irradiation, sample filters were wrapped in ultra-pure polyethylene films for short irradiations or high purity (99.999%) aluminum foils for longer irradiation. These two materials can be obtained in very pure form and the induced radioactivity of these materials is

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short lived and hence decreases rapidly after irradiation. Irradiated masses can vary from a few milligrams to a few grams and even more if the device for irradiation permits (Overwater

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et al., 1996).

2.3.2 Irradiations and activity measurements: In this study, samples were irradiated under a

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thermal neutron flux of 2x1013 n.cm-2.s-1, during 6 hours for long and medium half-life radioisotopes determination and 100 seconds for short half-life radioisotopes determination (Almeida et al., 2006) in NUR research reactor at Draria City in Algiers, which operate at a power of 1 MW.

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For determination of elements forming short half-life radioisotopes (Cl, Mn, and V), sample filters, standards and blanks (unexposed filters) were packed in high-density polyethylene (ethylene-butylene copolymer) material, which is virtually free of trace elements. The samples are irradiated for 100 seconds using a pneumatic transfer system followed by radioactivity measurement of 300 seconds. After a few days, the samples were repacked in aluminum foil for the determination of elements forming medium decay period having halflives of hours (Br, Sb, La, Na, Mo, As, K, Ca and Sm) and long half-life radioisotopes having half-lives of days and years (Eu, Hf, Sc, Ce, Cr, Sr, Zn, Co, Fe, Gd, Cs, Se, and Cd) (YliToumi et al., 2003 and Avino et al., 2013). The samples and standards were irradiated simultaneously for 6h, cooled for 4 days and radioactivity measured for 5000 seconds per sample for medium half life radionuclides. After measurement, the samples were cooled for 4 weeks and the measurement done again to estimate the activity associated with long lived radioisotopes formed. The cooling time is optimally chosen to allow decay of the 5

ACCEPTED MANUSCRIPT radioisotopes and manipulation of the sample at low dose, and to avoid the targeted radionuclide disappears into the background noise (Table 1). The radioactivity measurements were done using a gamma-ray spectrometer with an HPGe detector (from Canberra) and gamma Vision software, version 6.08 (from EG&G ORTEC). 60

Co with efficiency of ~ 30%. The

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The resolution is 1.90 keV on the 1332.5 keV line of

software takes into account decay losses and applies calibration factors to estimate the

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contents of the desired elements. While measuring by gamma spectrometry, it is possible that the count from the standard or sample is high, however, dead time losses were limited to 7%.

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Although the new measuring instruments and software allow automatic correction of the dead time, it is necessary to minimize acting on the measurement conditions such as the distance source / detector or the decay time (Greenberg et al., 2011).

Table 1

Ti

Td

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Counting # Neutron flux, n.cm-2s-1 1 1x1013 2 1x1013 3 1x1013

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A typical irradiation – counting scheme for trace elements analysis

300s 4d 20d

Elements determined

Cl, V, Mn Br, Sb, La, Na, Mo, As, K, Ca, Sm Eu, Hf, Sc, Ce, Cr, Sr, Zn, Co, Fe, Gd, Cs, Se, Cd Note: Ti , Td , Tc refer to irradiation time, decay time and counting time respectively.

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100s 6h 6h

Tc

300s 5000s 5000s

Gamma ray spectrometry is highly selective as it selects characteristic gamma rays for

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measurement of induced radioisotope of an element which have no overlap with gamma rays emitted by other radioisotopes. The activity corresponding to each radionuclide is measured, corrected for the decay during post irradiation. From the measured activity the concentrations of individual element are estimated. The equations used to calculate the concentration of an element in an unknown sample relative to a standard using Microsoft Excel are fully detailed in Bouhila et al., (2012).

2.4 Statistical data evaluation and calculation of enrichment factors The detection limit or the lowest concentration level statistically different from a blank was determined by selecting the concentration slightly higher than the lowest concentration of the standard line. Given detailed cross-sectional data found in a number of compiled information on the elements in the sample, a list of possible nuclear reactions, and detailed information on the 6

ACCEPTED MANUSCRIPT energy distribution of the gamma flux, the limits of detection for various elements can be calculated by Currie's quantitative definition (Currie, 1968) with a 10% allowable uncertainty. In our case, the lower detection limit (LD) for a radioactivity measurement, i.e. the minimal signal which can be detected above the background at 95% confidence level, given by the

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equation proposed by Currie, was used:

(1)

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LD= 2.71 + 4.65

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Where B: is the background value.

For each element and at the energy in keV used for the calculation, this formula gives us the detection limit of the background in terms of signal. Then, the results obtained are introduced in the usual concentration calculation process to obtain the respective values on ng/m3 for

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each element. The analytical data were treated statistically using Microsoft Excel. For the evaluation of the performance of the assay and the meaning of the results, the z-score, is most often used. The evaluation using Z-score includes the uncertainty of the assigned

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value. For our study, the Z score is calculated according to the following equation:

Z-score = (XLab – Xref)/Uref

(2)

Where XLab, Xref and Uref are the laboratory result, the

reference value

and

reference

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uncertainty, respectively.

In addition, enrichment factors (EF) from measured elemental concentrations in our samples were also calculated as follows: EF = (Ce/CR) Sample/(Ce/CR) crust

(3)

An EF is given by the calculation of the double ratio of the element of interest in the sample to a reference element in the sample divided by the ratio of the same element found in the reference material. Where Ce is the concentration of the selected element e, and CR is the concentration of the reference element. The (Ce/CR) Sample is calculated on the basis of the sample and (Ce/CR)crust ratio used here is calculated on the basis of earth crust mean abundance of the elements given in the upper continental crust CRC handbook (Lide, 2005). The EF was calculated for each detected element using Sc and Fe as reference elements, assuming that all iron and scandium determined in the air dust are of soil origin. 7

ACCEPTED MANUSCRIPT Statistical analysis of the collected data sets was performed in the present study in the form of correlation analysis, using IBMSPSS Statistics for Windows, version 19 (IBM Corp.,

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Armonk, NY, USA).

3. Results and discussion

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3.1 Meteorological conditions

Since meteorological information including sampling period, may have influence in the TSP and associated trace elements, daily average values of relative humidity, wind speed, cumulative precipitation and temperature collected from national meteorological observatory of Ben-Aknoun in Algiers are presented in figure 2. Autumn/winter seasons were

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characterized by low temperatures (average in winter = 11°C and average in summer = 25°C), higher relative humidity (average in winter =82% and average summer = 71%) and higher

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precipitation in winter (sum in winter = 2601 mm and sum in summer = 199 mm).

Fig. 2. Daily average (a) Relative humidity (%), (b) Wind speed (ms-1), (c) cumulative precipitation (mm) and (d) Temperature (°C) registered in sampling area in all 2011 days.

3.2 Performance of the analytical method 8

ACCEPTED MANUSCRIPT The quality assessment of our study was made by means of the results from Z-score and certified reference materials were used as analytical quality controls. The laboratory performance is evaluated as satisfactory if Z score ≤ 2, questionable for 2
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with a recommended value for two reference materials SL-1-IAEA and Soil-7-IAEA are

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displayed in Tables 2-3.

Table 2

Certified value 27.6±2.9 0.26±0.05 117±17 19.8±1.5 104±9* 7.0±0.9* 1.6±0.5* 67400±1700 4.2±0.6* 14500±2100* 52.6±3.1 3460±160 1700±100* 1.31±0.12* 17.3±1.1* 2.85±1.53* 9.25±0.51* 80±43* 170±15 223±10

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This study 25.3±2.0 0.25±0.03 100.3±10 21.3±0.9 110±5 7.86±0.5 1.62±0.3 68200±2500 5.2±0.5 14200±1100 50.5±5.3 3400±200 1710±95 1.51±0.13 18.3±1.56 3.2±1.33 10.05±0.66 85±32 161±20 230±17

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Table 3

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Element As Cd Ce Co Cr Cs Eu Fe Hf K La Mn Na Sb Sc Se Sm Sr V Zn *Information values.

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Elemental concentrations (mg kg-1) in SL-1-IAEA and Soil-7-IAEA

Z-score -0.8 -0.2 -1 1 0.67 0.96 0.04 0.47 1.67 -0.1 -0.7 -0.4 0.1 1.67 0.91 0.23 1.57 0.12 -0.6 0.7

Elemental concentrations (mg kg-1) in Soil-7-IAEA Element As Br Ca Cd Ce Co Cr Cs Eu Fe Hf K La Mn Mo Na Sb Sc Se

This study 14.2±2 6.75±4.6 164500±10000 2±1.1 65.0±7.8 9.2±0.99 61.5±10.9 6.20±0.91 1.3±0.25 25500±752 5.6±0.45 12230±756 27.3±1.26 596±42 2.56±2.25 2530±99 1.86±0.16 9.6±2.03 0.46±0.29

Certified value 13.4±0.85 7±3.5* 163000±8500* 1.3±0.8* 61.0±6.5 8.9±0.85 60±12.5 5.40±0.75 1.0±0.2 25700±550* 5.1±0.35 12100±700* 28±1 631±23 2.5±2.1* 2400±100* 1.7±0.2 8.3±1.05 0.4±0.3*

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Z-score 0.94 -0.07 0.18 0.88 0.62 0.35 0.12 1.07 1.5 -0.36 1.43 0.19 -0.7 -1.52 0.03 1.3 0.8 1.24 0.2

ACCEPTED MANUSCRIPT Sm Sr V Zn *Information values.

5.6±0.53 106±7.36 71±6.3 105±7.9

5.1±0.35 108±5.5 66±7 104±6

1.43 -0.36 0.71 0.17

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The Z-score values for most of the elements in both the materials were within  1. The results are in good agreement with the recommended value of CRM standards. This evaluation shows

3.3 TSP investigation

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an excellent quality of the results obtained in this investigation.

TSP concentrations are quantified in our samples by gravimetric method and significant variation in the concentrations was observed (Fig.3). The minimum daily concentration of 3.8 g/m3 is obtained the Sunday 18/08/2011; whereas the highest concentration, which is of 81.1

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g/m3, is observed the Tuesday 30/11/2011.

Fig. 3. Variation of the monthly mean value of TSP (µg/m3) in Draria city nearby Algiers (n=117 samples) with the associated error bars. Compared to the levels recorded in another site in Algiers center (with a annual average value of 80 g/m3 ) where human density and the traffic are higher (Belamri et al., 2009), our values of TSP (with an annual average value of 34.8 g/m3 ) are much lower. In fact, in our case, 88% of the samples had lower TSP compared to the Algerian daily mean limit value (50 g/m3); and 99.3% of the samples did not exceed the limit value (80 g/m3) of the World health organization (WHO). Total suspended particulates are a very heterogeneous group 10

ACCEPTED MANUSCRIPT whose quality on the physical, chemical and / or biological plane is variable depending on the emission sources either local distant and the weather conditions (Masclet, 2005) especially the power and direction of the wind, which scatters the pollutants resulting in variations of TSP values each day (Cloquet et al., 2006). For example, strong winds characterizing the days: 18/08/2011 and 04/10/2011 led to the dispersion of the pollutants that explain the very low

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corresponding content of TSP (3.8 and 4.3 g/m3) these days. Indeed, it is well known that

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low wind speeds are affiliated with large increases in the concentration of particulate matters as cited in Ezaz Ahmed et al., (2015). In addition, it is clearly demonstrated from figure 3,

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that mean TSP levels are higher in the summer season when compared to the values obtained in the other seasons; the weekly ratio of TSP was 1.3 higher during summer than in the winter season (Table 6). The distribution of TSP is affected by the large number of variables, including geographical locations, meteorological conditions, and anthropogenic sources (e.g.

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population and traffic density). Note that the meteorological conditions are also key factor determining the status of the TSP pollution (Titos et al., 2014). It is well known that enhanced concentrations of atmospheric aerosol are commonly found at low wind speed (Choi, et al.,

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2008), as reported previously from Chillan, Chile (Celis et al., 2004). PM10 concentrations measured in Athens, Greece were also seen to be inversely proportional to wind speed

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(Chaloulakou et al., 2003). The correlation analysis revealed a significant association (r = 0.5, p < 0.05) between the TSP concentration and the wind speed. To evaluate the differences between weekdays and weekends, figure 4 demonstrates that there is a peak in TSP concentrations during weekdays except for three periods: March, August and December. In fact, theses three periods correspond to the spring, winter and summer school

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vacations. The daily traffic in Algiers is higher because of the unavailability of public transport and also is a tradition in Algeria that the children are accompanied by their parents in private vehicles to the schools. During school holidays transit decreases on weekdays which is shown by the arrows in figure 4.

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Fig. 4. Weekdays/weekends differences for TSP (µg/m3) in Draria city nearby Algiers (n=117 samples) with the associated error bars. The arrows highlight the periods in which the average

3.4 Trace elements in the TSP

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weekend concentrations exceeded the weekday’s ones.

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Elemental concentrations in the air samples as estimated by the INAA method are shown as follows in Table 4. Table 4

Synoptic table (mean value, min-max values and standard deviation) of elements

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concentrations (ng/m3) INAA determined in the TSP fractions in Draria city nearby Algiers (n=117 samples). SD: standard deviation (1). Element As Br Ca Cd Ce Cl Co Cr Cs Eu Fe Gd Hf

Mean 0.19 2.39 270 0.03 1.30 650 0.71 1.43 0.03 0.02 540 0.22 0.04

Min
Max 1.24 4.05 450 0.09 2.28 2292 3.27 3.29 0.19 0.05 1272 1.57 0.08

SD 0.10 0.59 40 0.02 0.07 1057 0.12 0.09 0.01 0.003 21.5 0.03 0.009

Element K La Mn Mo Na Sb Sc Se Sm Sr V Zn

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Mean 0.37 0.66 4.25 0.08 106 0.71 0.15 0.15 0.07 12.0 4.36 10.0

Min
Max 4.80 2.00 10.1 0.30 331 1.09 0.29 0.43 0.09 24.4 6.06 26.9

SD 0.11 0.06 4.98 0.03 18.3 1.90 0.007 0.04 0.03 8.94 3.63 0.57

ACCEPTED MANUSCRIPT The sector "transport" is not just for road transport, which contribute largely to the ambient particulate pollution (Alleman et al., 2010), but also includes rail, air, and sea transport. Draria city is a sub urbanized area, so high levels of certain elements are mainly related to heavy traffic avenues (cars, buses and trucks) and may be associated with the presence of anthropogenic emission sources (Hjortenkrans et al., 2007). Congestion on our roads noticed

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in recent years, largely contributes to increased emissions. However, all the observed values

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are lower than the safe level for inhalation exposure guidelines (WHO, 2000). In order to evaluate the contribution of the different sources (anthropogenic or marine), it was

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assumed that all Na is of marine origin, and the mass ratio Cl/Na and K/Na in the samples and in seawater are compared. High concentrations of Cl were observed and the ratio Cl/Na was 6.13 in Draria atmosphere compared to 1.8 in sea water (contini et al., 2014) suggesting anthropogenic sources for Cl (e.g. combustion processes).

The presence of Se and Ce can be related to its applications in the surrounding construction

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sites which generate high levels of dust (typically from concrete, cement, wood and stone). The presence of Br is mainly due to traffic (Sternbeck et al., 2002). Indeed, the dibromo

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ethane (C2H4Br2) is an additive that turns lead derivatives in bromide and chloride of lead, used in the fuel to prevent the formation of deposits of lead (Pb) in the combustion chambers and of systems exhaust (Bonnard et al., 2006). The Sb/As ratio, which is an indication of a

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possible traffic influence, in the upper continental crust (UCC) composition (Reimann and De Caritat, 1998) was 0.13, this ratio was 3.74 in Draria city compared to 6.3 in Saclay in France near a dense road network (Ayrault et al., 2010). The road traffic noticed every day in this region can be the cause of the high value of the Sb/As ratio. The low SD noticed, especially

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for Sc, Cr, Gd, La and Zn have indicated that their concentrations were fairly uniform around the sampling station and indicate a temporal stability of the 50 hours averages.

3.4.1 Comparison with other results: Because of the unavailability of guide and limit values for some of the trace elements, we compared our results to those found by other published studies illustrating the elemental mean concentration levels in the air particulate matter in other regions of some prominent cities of Europe, North America, China and India at various sampling years. The results are presented in Table 5. Overall, Cl, Fe and Na are the most dominant trace elements, but the ranks in concentration of other trace elements are different from one country to the next.

Table 5

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ACCEPTED MANUSCRIPT Trace elemental concentrations (ng/m3) in air particulate matter in the study area (n=117 samples) and other world regions by INAA determination

Seville, Spain, 2002 b

0.19 2.39 270 1.30 0.03 650 0.71 1.43 0.03 0.02 540 0,04 0.37 0.66 4.25 0.08 106 0.71 0.15 0.15 0.065 4.36 10.0

8.2 8.3 9281

1.0

3.6 162 6.0 11

0.3

Algiers city, Algeria, 2008c

Copenhagen, Denmark, 2005d

1726

0.64 35.4

1112

1380 0.067

19 0.8

6.6 1.7

2.0 0.6

4.7 42

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49

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500

2.17 0.74

6.0 63

0 .69

Turin, Italy, 1967-2001 f

15 2400

8.6 4644

1270

628

20.8 645

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0.4 5.0 0.1

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8.6 4.5

Mumbai, India, 1996e

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Pristina, Cosovo, 2002a

312

1780

931

400

1861

198

80

40 36.8

428 4.5

170

356

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As Br Ca Ce Cd Cl Co Cr Cs Eu Fe Hf K La Mn Mo Na Sb Se Sc Sm V Zn

Present study, 2011

a

Arditsoglou and Samara., 2005 b Enamorado-Báez et al., 2015 c Belamri et al., 2009 d Anoop et al., 2007 e Bandhu et al., 2000 f Malandrino et al., 2013

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It is clear from the results provided in Table 5 that concentrations levels in Draria city are lower than those measured in other regions; the exception being the values of Zn and Fe at Copenhagen (Denmark) (Anoop et al., 2007). The mean value of Fe is more than 780 times higher than in Copenhagen, but 3 times lower than in Mombay (India), Algiers (Algeria) (Belamri et al., 2009), Seville (Spain) (Enamorado-Báez et al., 2015) and Pristina (Cosovo) (Arditsoglou and Samara., 2005) and 2 times lower than in Turin (Italy) (Malandrino et al., 2013). For Cr, the mean value was found to be similar to that measured at Seville (Spain) (Enamorado-Báez et al., 2015) but 451 times lower than in Copenhagen and 25 lower than in Algiers in a previous study. The reason for this may be due to well-mixed atmosphere in Draria station (winds which continuously occur strongly in this region), where the meaning of its name (Draria) in the autochthon language given to this region. This inverse relationship between atmospheric compounds and wind speed was also observed in other studies (Tiwari et al., 2013). 14

ACCEPTED MANUSCRIPT 3.4.2 Seasonal, weekdays and weekends variations of elemental concentrations: To learn more about the temporal variations of TSP and associated trace elements, the data were compared after being sorted into monthly and seasonal data groups. For the grouping of data

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on a seasonal basis, we divided each season as follows: spring (March to May), summer (June to August), autumn (September to November), and winter (December to February). The

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seasonal variation of the different elements in TSP of Draria station for the entire study period is shown in Table 6. The average weekends and weekdays concentrations were calculated

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from the data collected within the same period for each trace element. The seasonal mean concentrations (µg/m3) of TSP showed the maximum in summer (39.6 ± 5.38) followed by spring and autumn (34.8 ± 5.38 and 34.8 ± 2.93), and winter (31.3.3 ± 2.48). This can be interpreted most probably as a result of more effective, low winds in the drier months of the year, leading to higher concentrations of TSP (Harrison et al., 2001). As shown in Table 7,

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due to low winds and low mixing height, we notice that, except for Gd, the concentrations of the majority of the elements during the summer season are superior to those of the winter

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season by a factor which varied from 3 to 4 for Mo, Se, Cs, Hf and by a factor of 2 for Ca, Cd, Ce, La, and Cr. In case of Cr and Co, we noticed the same ratios in another study done in Nanjing, China (Sun et al., 2014) and in Budapest, Hungary (Szigeti et al., 2015). The

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summer / winter concentrations ratio for Zn in this study is similar to that observed in PM2.5 fraction of Nanjing, China; but it is twice higher than that calculated in TSP fraction one (Sun et al., 2014). The Br, Eu, Mo and Se are undetectable (
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fact, during the rainy period, elemental levels decreased due to lower source intensity and dilution by the marine air mass (Jeongwon et al., 2013). It is clearly observed that there is a seasonal effect, with higher averages in summer seasons and during weekdays for almost all the elements. For all seasons, increased average concentrations during weekdays compared to those of the weekends are noticed, especially for Br, Ca, Cd, Cr, Cs, Mo, Sc, Sm and Zn except for Co, Hf, Gd and La, where the average levels are quite high during weekends in the winter season, in addition, the same was true for Sb and K in the summer season. In addition to these observations, the weekdays/weekends ratio of the investigated elements for almost all elements is higher in the summer season than in the winter season, except for Na, Fe, Sc and Zn. Relative higher values are observed in weekdays than in weekends, due to the influence of the anthropogenic activities, but the most probable source of antropogenically emitted dust is the re-suspension of the road traffic. In fact, in Draria city area, road traffic is strongly reduced during weekends in all seasons. 15

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16

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Table 6 Average concentration and standard deviation of TSP (µg/m3) and investigated elements concentrations (ng/m3), INAA determined in the TSP fractions,

SD

34.8

2.93

As


Br

2.61

1.27

Ca

381

170

Cd


Ce

1.3

Co

Weekend Weekday Average

SD

Weekend Weekday Average

33

35.3

31.3

2.48

30.4

29.9

34.8



0.3

0.11

0.36

0.17



2.74





401

143

95

121

154

0.03

0.04

0.02

0.06

0.04

0.44

1.18

1.4

0.88

0.45

1.06

0.9

0.5

0.8


0.79

0.5

0.94

0.92


Cr

2.22

2.99

Cs


Eu

0.02

Fe

664

Gd


Hf

0.06

K


La

0.49

Mo


Na

66.8

91.9

Sb

0.96

Sc

2.29

0.81

0.59

0.6


0.03

0.04


0.01

0.02

0.02


316

590

721

495

722



1.19

2.32

0.05

0.06

0.02




0.42

0.55

0.35




98.9

54.1

128

277

0.64

0.86

1.05

0.6

0.17

0.06

0.16

0.19

0.13

Se

0.37

0.22

0.41

0.33


Sm

0.07

0.03

0.05

0.09

0.05

0.03

Sr

3.5

9.21

0.02

6.11

10.9

Zn




15.3

0.25

Weekend Weekday Average

SD

Summer /Winter concentration Weekend Weekday ratio

31.5

37.1

39.6

5.38

36

40

1.27

0.54

0.48

0.42

0.13

0.41

0.42

1.40



3.58

1.31

3.11

3.93

>6.5

346

301

381

327

347

270

351

2.29

0.02

0.04

0.06

0.09

0.02

0.08

0.1

2.25

1.77

1.23

1.19

1.9

1.83

1.23

1.25

2.02

2.07






<1


0.03


1.2

2.01

2.35

2.04

1.2

1.62

2.29

2.51



0.14

0.08

0.13

0.14

4.66



0.03

0.02

0.04

0.03

0.03

0.02

0.02

0.03

>1.5

360

546

912

476

1064

808

818

476

763

843

1.65

4.68






<0.16

0.05

0.05

0.07

0.03

0.06

0.07

3.50



0.27

5.77

0.5


>1.17

1.2

1.24

0.73

1.65

0.48

0.85

2.09



0.03

0.02

0.05




0.45

0.3

1.24

1.65



0.26

0.09

0.3

0.27

0.3

0.09

0.28

0.85

>6

35.5

173

80.9

51.2

49.4

78.7

125

51.2

114

168

0.98

0.49

0.57

0.62

0.48

0.26

0.6

0.56

0.86

0.26

0.92

0.83

1.43

0.11

0.1

0.14

0.13

0.06

0.13

0.12

0.16

0.06

0.15

0.17

1.23

0.08





0.32

0.12

0.32

0.32

>3,2

0.05

0.06

0.07

0.04

0.07

0.08

0.08

0.04

0.07

0.09

1.60

4.64

12.1

9.79

18.1

0.46

17.8

18.5

16.7

0.46

15.1

17.8

1.53

19.8

10.1

17.4

20.7

14.3

18.5

22.4

19

14.3

16.9

20

1.24

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0.02

Summer

0.05

0.92

EP T

1.96
212

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350
SD 5.38

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Average

Spring

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TSP

Winter

SC

Autumn

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T

separated for all seasons, weekend and weekdays in Draria city nearby Algiers (n=117 samples). SD: standard deviation (1)

0.02

0.29

17

0.03

ACCEPTED MANUSCRIPT 3.4.3 Enrichment factor and elemental correlation: In order to have an initial indication on the extent of the contribution of anthropogenic emissions to atmospheric elemental levels, the EF was calculated for each detected element using Sc and Fe as reference elements. The results obtained by the two methods and the respective EFSc and EFFe are quite similar (Fig.

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5). This means that the anthropogenic Fe is negligible compared to natural sources (Avino et

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al., 2008 and Avino et al., 2006).

Fig. 5. Enrichment factors of the trace element concentrations in TSP fractions in Draria city nearby Algiers (Algeria) in 2011 (n=117 samples).

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In general, when EF approaches unity, the dominant source for that element is treated as crustal; if EF >10, a significant fraction of the element is considered to be from anthropogenic sources (Zhang et al., 2014). In accordance with the results of urban dust studies (i.e Bogen, 1973), the EF value of Sb is the most higher, this relates to the replacement of asbestos in brake linings by Sb-containing compounds (Shotyk et al., 2004). As shown in Fig. 5, the Sb, Se and Cd showed high EF values (230, 196 and 23, respectively). According to their high EF, it was possible to establish that these elements are of traffic origin. Low EF values (in general < 5) were found for other elements, signifying a negligible contribution from anthropogenic emissions to the ambient levels. These results are in accordance with those found by other authors when elements are associated with coarse particles (Reimann and De Caritat, 1998). Since data on elemental concentrations suggested that the relationship between elements may exist, they were tested for Pearson’s correlations. The correlation matrix performed for the 18

ACCEPTED MANUSCRIPT samples from Draria City atmosphere is presented in.Table A (supplementary data), where the possible correlations are highlighted in bold. Pearson's linear (r) correlation coefficients with a two-tailed test of significance (p) were produced to show linear relationship between different investigated trace elements. The significance of the correlation coefficient increases with the sample size. In our case the size of the sample is sufficiently large to give a good

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significance for Pearson’s correlations.

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Significant positive correlations between the analyzed trace elements were found for Br vs Na (r= 0.511). Another significant correlation is observed between Hf–Sc (r= 0.509) and Hf–Mn

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(r=0.571), which proves that these trace elements may be discharged from the same sources, probably from the many surrounding construction sites. Sc is found to be positively correlated with Cr (r=0.540) and Fe (r=0.569), again a case of a common source, also Ce vs Mn (r=0.565). This correlation also depends on the secondary characteristic of these pollutants which are more dependent on meteorological conditions than on common anthropogenic

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sources, like atmospheric stability and wind speed. The low EF for Mn, Hf, Sc, Cr, and Ce, together with its significant Pearson’s correlation suggests that soil re-suspension is the

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unique or the main source of these elements. It is worth noting that (Sb and Cd), generally considered good traffic tracers (Wang et al., 2003) coming generally from brake powder resuspension (Iijima et al., 2009; Belzile et al., 2011) show a slightly different behavior with

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lower correlation with the above group (Pearson’s coefficients <0.5). The high EF values for Sb, Se and Cd, on the other hand, with low Pearson’s correlation could support the hypothesis that soil re-suspension by buses circulation is also an important source for both elements in the sampling site.

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The EF of Zn is around 10 (9.9), furthermore, the very low correlation between Zn which has multiple anthropogenic sources (as a component of tire rubber debris) (Almeida et al., 2011b), and other trace elements like Gd, Mn, Cl, Sm, Br, La, Sb and Ca suggests yet other sources for them, noticed previously by Sternbeck et al. (2002). The reliability of these inter-element interactions and their exact meaning requires further evaluation.

19

ACCEPTED MANUSCRIPT 4. Conclusions In Algiers, the air pollution has become a great topic of debate at all levels because of the enhanced anthropogenic activities related to vehicular emissions. Exposure to air pollutants

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can overload or break down natural defense mechanisms in the body, causing or contributing to respiratory diseases such as asthma, lung cancer, chronic bronchitis and emphysema. Air

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pollution can also have adverse impacts on other important systems such as the cardiovascular system and central nervous system. This study provides the first long-term information on

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TSP continuous TSP and associated trace elements in the sampling by continuous TSP sampling and measurement for more than one year. Trace element concentrations between weekends, weekdays and seasons were studied and seasonal variations in TSP and element concentrations are pronounced. The focal objective of this study was to assess the level as well as seasonal, weekends and weekdays variations of air pollution in Draria city. Higher

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concentrations of TSP were found in the summer than in the other seasons. This finding may be explained by the fact that, in this season, calm winds, occurring almost daily, favour the increase

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of air pollutants in the Draria city atmosphere. The results showed a strong seasonal variation in

TSP levels and the associated elements investigated. This was especially pronounced during summer time and weekdays. In fact, the comparison of the mean concentrations of a high

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sample number (n=117 samples), showed that high traffic density during weekdays caused higher amounts of TSP and associated trace elements especially in summer time. In order to gain a better understanding of the sources of the trace analyzed, enrichment factors were calculated using Sc and Fe as references and the results reflected the possible origins of

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the elements: crustal or anthropogenic. Indeed, high enrichment factors (greater than 10) for Sb, Se and Cd are noticed in sampling area atmosphere and it indicates their partly anthropogenic contributions. Relative higher values are observed in weekdays than in weekends, resulting surely from the influence of the anthropogenic activities, but the most probable source of antropogenically emitted dust is the re-suspension of the road traffic dust. The information obtained from correlation between the elemental concentrations and the enrichment factors should be considered only as a first step in a more detailed evaluation of the aerosol composition in Draria sampling site. The reliability of these inter-element interactions and their exact meaning requires further evaluation.

Acknowledgments The authors wish to thank the staff of Draria NUR research reactor for their support in irradiation procedures. The first author is also indebted to the NAA research team of the 20

ACCEPTED MANUSCRIPT nuclear research centre of Algiers (CRNA) in particular Dr. M. Belamri for assistance provided in the start up of this monitoring study.

References Almeida, S. M., Pio, C. A., Freitas, M. C., Reis, M. A., Trancoso, M. A., 2006. Source apportionment

suspended dust contribution. Atmos. Environ. 40, 2058–2067.

PT

of atmospheric urban aerosol based on weekdays/weekend variability: evaluation of road re-

RI

Almeida, S. M., Canha, N., Silva, A., Fritas, M. D.C., Pegas, P., Alves, C., Evlyugina, M., Adria, P.c., 2011a. Children exposure to atmospheric particles in indoor of Lisbon primary schools. Atmos.

NU SC

Environ. 45, 7594–7599.

Almeida, S. M., Canha, N., Freitas, M.C., Dung, H.M., Dionisio, I., 2011b. Air pollution at an urban traffic tunnel in Lisbon, Portugal–an INAA study. Appl. Radiation and Isotope 69, 1586–1591. Arditsoglou, A., Samara, C., 2005. Levels of total suspended particulate matter and major trace

MA

elements in Kosovo: a source identification and apportionment study. Chemosphere 59, 669–678. Anoop, K. S., Keld, A. J., Jette, R., Paul, A. White, Staffan, L., Remi, G., Nicklas,R., Jacobsen, Jesper, K., Ulla, V., Hakan, W., 2007. Genotoxicity, Inflammation and Physicochemical Properties of Fne Particle Samples from an Incineration Energy Plant and Urban Air. Mut. Res. 633, 95–111.

ED

Avino, P., Capannesi, G., Rosada, A., 2006. Characterization and distribution of mineral content in 214.

CE PT

fine and coarse airborne particle fractions by neutron activation analysis. Toxicological 92, 206–

Avino, P., Capannesi, G., Rosada, A., 2008. Heavy metal determination in atmospheric matter by Instrumental Neutron activation Analysis. Microchemical Journal 88, 97–106. Avino, P., Capannesi, G., Renzi, L., Rosada, A., 2013. Instrumental neutron activation and statistical approach for determining baseline values of essential and toxic elements in hairs of high school

AC

students. Ecotox. Environ. Safety 92, 206–214. Avino, P., Capannesi, G., Rosada, A., 2011. Ultra-trace nutritional and toxicological elements in Rome and Florence drinking waters determined by Instrumental Neutron Activation Analysis. Microchemical Journal 97, 144–153. Ayrault, S., Senhou, A., Moskura, M., Gaudre, A., 2010. Atmospheric trace element concentrations in total suspended particles near Paris, France. Atmos. Environ. 44, 3700–3707. Bandhu, H.K., Sanjiv, P., Garg, M.L., Singh, B., Shahi, J.S , Mehta, D.E., Swietlicki, E., Dhawan, D.K., Mangal, P.C., Nirmal, S., 2000. Elemental composition and sources of air pollution in the city of Chandigarh, India, using EDXRF and PIXE techniques. Nucl. Instruments and Methods in Phys. Res. B 160, 126–138. Belamri, M., Bouhila, Z., Omari, L., Lakhdar Chaouche, C., Azbouche, A., Mouhouche, F., 2009. Evaluation de la dégradation de la qualité de l’air par le dosage des métaux lourds. Proc. of the Int. Conf. On Environment Deterioration; what Solutions? Skikda, Algeria, 1–26.

21

ACCEPTED MANUSCRIPT Belzile, N., Chen, Y.-W., Filella, M., 2011. Human exposure to antimony: I. Sources and intake. Crit. Rev. Environ. Sci. Technol. 41 (14), 1309–1373. Bogen, J., 1973. Trace elements in atmospheric aerosol in the Heidelberg area, measured by instrumental neutron activation analysis. Atmos. Environ. 7, 1117–1125. Bonnard, N., Clavel, T., Falcy, M., Jargot, D., Hesburt, A., Protois, J.C., Schneider, O., 2006. Fiche

PT

toxicologique du sodium. s.l. : INRS.

Bouhila, Z., Lounici, H., Mouzai, M., Nedjar, A., Azli, A., Zergoug, Z., Chegrouche, S., 2012. The

RI

Nuclear Power in the Service of the Environment: Atmospheric Trace Element Determination Using Neutron Activation Analysis. (Proc. Of the 2nd Int. Sym. on Environment-Friendly

NU SC

Energies and Applications EFEA 2012, Northumbria University UK) 523–528. Bounouira, H., Embarch, K., Amsil, H., Bounakhla, M., Blaaun, M., 2014. Neutron flux characterization of the

Moroccan Triga Mark II research reactor and validation of the ko

standardization method of NAA using ko-IAEA program. J. Radioanal Nucl.Chem. 300, 465– 471.

MA

Burt, R., Weber, T., Park, S., Yochum, S., Ferguson, R., 2011. Trace Element Concentration and Speciation in Selected Mining-Contaminated Soils and Water in Willow Creek Floodplain, Colorado. Appl. Environ. Soil Sci. 201, 1–20.

ED

Calvo, A.I., Alves, C., Castro, A. Pont, V., Vicente, A.M., Fraile, R., 2013. Research on aerosol sources and chemical composition: Past, current and emerging issues. Atmos. Res. 120–121, 1–

CE PT

28.

Celis, J.E., Morales, J.R., Zaror, C.A., Inzunza, J.C., 2004. A study of the particulate matter PM10 composition in the atmosphere of Chill_an, Chile. Chemosphere 54, 541–550. Chaloulakou, A., Kassomenos, P., Spyrellis, N., Demokritou, P., Koutrakis, P., 2003. Measurements of PM10 and PM10 particle concentrations in Athens, Greece. Atmos. Environ. 37, 649–660.

AC

Choi, H., Zhang, Y., Kim, K., 2008. Sudden high concentration of TSP affected by atmospheric boundary layer in Seoul metropolitan area during dust storm period. Environ. Int. 34, 635–647. Cloquet, C., Carignan, J., Libourel, G., 2006. Atmospheric pollutant dispersion around an urban area using trace metal concentrations and Pb isotopic compositions in epiphytic lichens. Atmos. Environ. 40, 574–587. Contini, D., Belosi, F., Gambaro, A., Cesari, D., Stortini, A.M., Bove, M.C., 2012. Comparison of PM10 càncentrations and metal content in three different sites of the Venice Lagoon of possible aerosol sources. J. Environ. Sci. 24, 1954–1965. Contini, D., Cesari, D., Genga, A., Siciliano, M., Ielpo, P., Guascito, M.R., Conte, M., 2014. Source apportionment of size-segregated atmospheric particles based on the major water-soluble components in Lecce (Italy). Sci. Total Environ. 472, 248–261. Currie, L., A., 1968. Limits for qualitative detection and quantitative determination. Application to radiochemistry. Anal. Chem. 40, 586–593.

22

ACCEPTED MANUSCRIPT El Khoukhi, T., Cherkaoui, R.M., Gaudry, A., Ayrault, S., Senhou, A., Chouak, A., Moutia, Z., E., Chakir, 2004. Air pollution biomonitoring survey in Morocco using k0-INAA Nucl. Instruments and Methods in Phys. Res. B 213, 770–774. Enamorado-Báez, S.M., Gómez-Guzmán, J.M., Chamizo, E., AbrilLevels, J.M., 2015. Levels of 25 trace elements in high-volume air filter samples from Seville (2001–2002): Sources, enrichment factors and

PT

temporal variations Atmospheric Research 155, 118–129.

Ezaz, A., Ki-Hyun, K., Zang-Ho, S., Sang-Keun, S., 2015. Long-term trend of airborne particulate

RI

matter in Seoul, Korea from 2004 to 2013. Atmos. Environ. 101, 125 –133.

Feng, L., Xiang-yun, Z., Chang-hua, W., Zhi-peng, D., Yan-mao, W., Guo-ru, H., Xiao-lin, L., Min-

NU SC

Jian, L., Man-Jie, L., and Jiang-Yu, X., 2013. Ecological Risks Assessment and Pollution Source Identification of Trace Elements in Contaminated Sediments from the Pearl River Delta, China. Biol. Trace Element Res. 155, 301–313.

Gallorini, M., Rizzio, E., Birattari, C., Bonardi, M., Groppi, F., 1999. Biol. Trace Element Res. 71. Greenberg, R. R., Bode, P., De Nadal Fernandes, E. A., 2011. Neutron activation analysis: A primary

MA

method of measurement. Spectrochimica Acta Part B: Atomic Spectroscopy 66, 193–241. Harrison, R.M., Yin, J., Mark, D., Stedman, J., Appleby, R.S., Booker, J., Moorcroft, S., 2001. Studies of the coarse particle (2.5e10 mm) component in UK urban atmospheres. Atmos. Environ. 35,

ED

3667–3679.

Henderson, P., Pankhurst J., 1984. Anal. Chem., in: P. Henderson Ed., Rare Earth Element

CE PT

Geochemistry 13, Elsevier, and Amsterdam. 467–499. Hjortenkrans, D.S.T., Bergbäck, B.G., Häggerud, A.V., 2007. Metal emissions from brake linings and tires: case studies of Stockholm, Sweden 1995/1998 and 2005. Environ. Sci. and Technol. 41, 5224–5230.

Hopke, P.K. Xien, Y., Raunemaa, T., Biegalski, S., Landsberger, S., Maenhaut, W., Artaxo, P., Cohen,

AC

D., 1997. Characterization of the gent stacked filter unit PM10 sampler. Aerosol Sci. and Technol. 27, 726–735. Iijima, A., Sato, K., Fujitani, Y., Fujimori, E., Saito, Y., Tanabe, K., Ohara, T., Kozawa, K., Furuta, N., 2009. Clarification of the predominant emission sources of antimony in airborne particulate matter and estimation of their effects on the atmosphere of Japan. Environ. Chem. 6, 122–132. Jeongwon, K., Man-Sik, C., Hi-Il, Y., Kap-Sik, J., Jung-Sun, C., Chang-Sik, C., 2013. Elemental composition of different air masses over Jeju Island, South Korea. Atmos. Res. 122, 150–164. Jong-Myoung, L., Jin-Hong, L., Jong-Hwa, M., Yong-Sam, C., Ki-Hyun, K., 2010. Airborne PM10 and metals from multifarious sources in an industrial complex area. Atmos. Res. 96, 53–64. Lei, C., Weizhi, T., Bangfa, N., Yangmei, Z., Pingheng, W., 2002. Preliminary study of airborne particulate matter in a Beijing sampling station by Instrumental Neutron Activation Analysis. Atmos. Environ. 36, 1951–1956. Lide, D.R., 2005. CRC Handbook of Chemistry and Physics, Section 14: Geophysics, Astronomy and Acoustics; Abundance of Elements in the Earth's Crust and in the Sea85th ed. CRC Press, Boca Raton, Florida.

23

ACCEPTED MANUSCRIPT Masclet, P., 2005. Pollution atmosphérique : causes, conséquences, solutions, perspectives. Ed. Ellipes. 137, 29–30. Malandrino, M., Di Martino., M. Giacomino, A., Geobaldo, F., Berto, S., Grosa, M. M., Abollino, O., 2013. Temporal trends of elements in Turin (Italy) atmospheric particulate matter from 1976 to 2001. Chemosphere. 90, 2578–2588.

PT

Moreno-Grau, S., Pérez-Tornell, A., Bayo, J., Moreno, J., Angosto, J.M., Moreno-Clavel, J., 2000. Particulate matter and heavy metals in the atmospheric aerosol from Cartagena, Spain. Atmos.

RI

Environ. 34, 5161–5167.

Oucher, N., Kerbachi, R., 2012. Evaluation of Air Pollution by Aerosol Particles Due to Road Traffic:

NU SC

A Case Study from Algeria. Procedia Engineering 33, 415 – 423.

Overwater, R.M.W., Jeroen, P.B., De Goeij, J.M., Hoogenboom, J.E., 1996. Feasibility of elemental analysis of kilogram size samples by instrumental neutron activation analysis. Anal. Chem. 68, 341–348. sheet,

IAEA-SL-1,

date

Documents/rs_iaea-sl-1.pdf. Reference

sheet,

IAEA-Soil-7,

date

Documents/rs_iaea-soil-7.pdf.

issue

of

issue

September

January

1999, http://nucleus.iaea.org/rpst/

2000,

http://nucleus.iaea.org/rpst/

Chemical Elements in the Environment Factsheets for the

ED

Reimann, C., De Caritat, P., 1998.

of

MA

Reference

Geochemist and Environmental Scientist. Springer-Verlag, Berlin, Germany.

CE PT

Revel, G., Ayrault, S., 2000. Comparative use of INAA and ICP-MS methods for environmental studies. Radioanal. Nucl. Chem. 244,73–80. Sabin, L.S., Lim, J.H., Stolzenbach, K.D., Schiff, K.C., 2006. Atmospheric dry deposition of trace metals in the coastal region of Los Angeles, California, USA. Environ. Toxicol. Chem. 25, 2334– 2341.

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Shotyk, W., Krachler, M., Chen, B., 2004. Antimony in recent, ombrotrophic peat from Switzerland and Scotland: Comparison with natural background values (5,320 to 8,020 14C yr BP) and implications for the global atmospheric Sb cycle. Global Biogeochemical Cycles 18 (13), GB1016. doi:10.1029/2003GB002113. Sun, Y., Hu, X., Wu, J., Lian, H., Chen, Y., 2014. Fractionation and health risks of atmospheric particle-bound As and heavy metals in summer and winter. Sci. Total Environ. 493, 487–494 Szigeti, T., Óvári, M., Dunster, C., Kelly, F.J., Lucarelli, F., Záray, G., 2015. Changes in chemical composition and oxidative potential of urban PM2.5 between 2010 and 2013 in Hungary. Sci. Total Environ. 518–519, 534–544. Sternbeck, J., Sjödin, Å., Andréasson, K., 2002. Metal emissions from road traffic and the in fluence of resuspension-results from two tunnel studies. Atmos. Environ. 36, 4735–4744. Stortini, A.M., Freda ,A., Cesari, D., Cairns,W.R.L., Contini, D., Barbante, C., Prodi, F., Cescon, P., Gambaro, A., 2009. An evaluation of the PM2.5 trace elemental composition in the Venice Lagoon area and an analysis of the possible sources. Atmos. Environ. 43, 6296–6304.

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ACCEPTED MANUSCRIPT Tian, W., 2000. Reactor Neutron Activation Analysis of airborne particulate matter, NAHRES-53. IAEA, Vienna. Titos, G., Lyamani, H., Pandolfi, M., Alastuey, A., Alados-Arboledas, L., 2014. Identification of fine (PM1) and coarse (PM10-1) sources of particulate matter in an urban environment. Atmos. Environ. 89, 593–602.

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Tiwari, S., Srivastava, A.K., Bisht, D.S., Parmita, P., Manoj, K. S., Attri, S.D., 2013. Diurnal and seasonal variations of black carbon and PM2.5 over New Delhi, India: Influence of meteorology.

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Atmos. Res. 125–126, 50–62.

Wang, Y.F., Huang, K.L., Li, C.T., Mi, H.H., Luo, J.H., Tsai, P.J., 2003. Emissions of fuel metals

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content from a diesel vehicle engine. Atmos. Environ. 37, 4637–4643.

WHO, 2000. Air Qualirty Guidelines for Europe. WHO Regional Publications Eur. Ser. No. 91, Regional Office for Europe, Copenhagen, Denmark.

Yli-Tuomi, T., Venditte, L., Hopke, P.K., Basunia, M. S., Landsberger, S., Viisanen, Y., Paatero, J.,

Atmos. Environ. 37, 2355–2364.

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2003. Composition of the finnish arctic aerosol: Collection and analysis of historic filter samples.

Zhang, W., Zhang, G., Guo, J., Xu, D., Wang, W., Baumgardner, D., Wu Z., Yang W., 2010. Sources

Res. 95 , 197–209.

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of aerosol as determined from elemental composition and size distributions in Beijing. Atmos.

Zhang, N., Cao, J., Liu, S., Zhao, Z., Xu, H., Xiao, S., 2014. Chemical composition and sources of

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PM2.5 and TSP collected at Qinghai Lake during summertime. Atmos. Res. 138, 213–222.

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ACCEPTED MANUSCRIPT Figures captions: Fig. 1. Map of Algeria showing the city and the sampling location for total particulate matter (TSP).

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Fig. 2. Daily average (a) Relative humidity (%), (b) Wind speed (ms-1), (c) cumulative

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precipitation (mm) and (d) Temperature (°C) registered in sampling area in all 2011 days.

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Fig. 3. Variation of the monthly mean value of TSP (µg/m3) in Draria city nearby Algiers (n=117 samples) with the associated error bars.

Fig. 4. Weekdays/weekends differences for TSP (µg/m3) in Draria city nearby Algiers (n=117 samples) with the associated error bars. The arrows highlight the periods in which the average

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weekend concentrations exceeded the weekday’s ones.

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Fig. 5. Enrichment factors of the trace element concentrations in TSP fractions in Draria city

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nearby Algiers (Algeria) in 2011 (n=117 samples).

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ACCEPTED MANUSCRIPT List of tables:

Table 1

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A typical irradiation – counting scheme for trace elements analysis

Table 2

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Elemental concentrations (mg kg-1) in SL-1-IAEA and Soil-7-IAEA

Table 3

Elemental concentrations (mg kg-1) in Soil-7-IAEA Table 4

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Synoptic table (mean value, min-max values and standard deviation) of elements concentrations (ng/m3) INAA determined in the TSP fractions in Draria city nearby Algiers

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(n=117 samples). SD: standard deviation (1).

Table 5

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Trace elemental concentrations (ng/m3) in air particulate matter in the study area (n=117 samples) and other world regions by INAA determination Table 6

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Average concentration and standard deviation of TSP (µg/m3) and investigated elements concentrations (ng/m3), INAA determined in the TSP fractions, separated for all seasons, weekend and weekdays in Draria city nearby Algiers (n=117 samples). SD: standard deviation (1)

Appendix A. Supplementary data Table A Pearson correlation between investigated elements present in TSP (n=101)

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ACCEPTED MANUSCRIPT

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Highlights: - Samples of air filters were analyzed for TSP and trace element composition, in a suburban area in Algiers (Algeria), from December 2010 to January 2012. - Using the INAA, Multi-trace determination of 25 elements is carried out in 117 samples. - Significant variation in the concentrations of TSP and trace elements in our samples was observed. - Results revealed that most of trace elements are of road traffic origin and show the characteristic seasonal variation in Draria city. - High enrichment factors (greater than 10) for Sb, Se and Cd are noticed in sampling area

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atmosphere and it indicates their partly anthropogenic contributions.

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