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BIOMONITORING OF OCCUPATIONAL EXPOSURE TO HEAVY METALS IN METALLURGICAL FACTORIES IN KHARTOUM STATE, SUDAN Abdelrazig M. Abdelbagi1,2, Wafa S. Abdelrahman3,4, Mohmaed A.H. Eltayeb5,6 and Abubakr M. Idris6,* 1

Physics Department, Science College, Shaqra University, Dawadami, Saudia Arabia 2 Faculty of Science, Omdurman Islamic University, Omdurman, Sudan 3 Department of Physics, Faculty of Science and Art, Qassim University, Buraidah, Saudi Arabia 4 Sudan University of Science and Technology, Khartoum, Sudan 5 Sudan Atomic Energy Commission, Khartoum, Sudan 6 Department of Chemistry, College of Science, King Khalid University, Abha, Saudi Arabia

ABSTRACT The main purpose of this work is to assess the occupational exposure to some heavy metals in two metallurgical factories in Khartoum State, Sudan using bioindicators. Urine and scalp hair samples were collected from workers in a mint factory and a foundry factory as well as from residents far from emission of metallurgical processes. Cr, Fe, Co, Ni, Cu, Zn and Pb were quantified in hair by X-ray fluorescence spectrometry while electrothermal atomic absorption spectrophotometry was used for urine analysis for the same metals. Hair samples recorded much higher concentrations of Cr, Fe and Zn for workers in both factories than residents in the control area, besides higher concentrations of Ni and Cu for workers in the mint factory than workers in the foundry factory and residents in the control area. This result indicates serious occupational exposure. In addition, urine samples recorded much higher concentrations of Fe in workers in the mint factory than workers in the foundry factory and the referents. Higher Ni and Cu contents in urine from workers in the both factories than the referents were recorded as well. A result that emphasizes an occupational exposure. KEYWORDS: Heavy metals, hair, urine, biomonitoring, occupational exposure

1 INTRODUCTION The presence of chemical pollutants in the environment can be examined by environmental monitoring. Usually, such environmental samples as water, soil, food, etc. are analyzed for chemical pollutants. However, this approach does not always reflect the effect of chemical pollu* Corresponding author

tion on human health. In this challenge, biomonitoring could be a complementary, or sometimes an alternative, approach because it can reflect more actual effect on human health [1]. The term “human biomonitoring” is defined as the direct measurement of people's exposure to environmental contaminants by measuring substances or their metabolites in blood, urine, or other specimens [2]. Biomonitoring is adopted in different situations such as identification and elimination of possible contamination sources [3]. Biomonitoring is also employed to observe time trends in chemical variations [4] and to prove the effectiveness of bans or restrictions [5]. The relationships between chemical exposure and diseases or development in abnormalities could be identified by biomonitoring as well [6]. In addition, biomonitoring is utilized to map the geographical distribution of contaminated regions [7] and to find relationships between chemical body burden and eating habits or workplace exposure [8]. In contrast, biomonitoring suffers from some limitations. For example, some chemicals are excreted rapidly and can only be monitored for a short period after exposure to pollutants. Moreover, biomonitoring does not reveal the sources or routes of pollutants [9]. Hence, the use of more than one type of biomonitor is more effective in environmental monitoring and assessment studies. In a more specific context, human hair sample offers numerous advantages for human biomonitoring including matrix stability, ease of collection, low cost, ease of transport and ease of storage [1, 10, 11]. In addition, hair samples have a special concern in occupational and environmental health surveys on heavy metals because metallic cations form bonds with the sulphur of the keratin matrix of the hair [12, 13]. Furthermore, hair grows approximately 10 mm per month and may serve as a long-term monitor of past and recent exposure and may usually reflect average concentrations for the previous two or three months exposure [13]. Furthermore, the levels of heavy metals in hair

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are up to 10-fold higher than the levels found in blood and urine. This phenomenon provides good detectable levels for analysis. In contrast, the main disadvantage of hair samples as a bioindicator is the difficulty in differentiating between external and internal exposure. This means that pollutants from exogenous sources, such as aerosol, water, detergents and cosmetics, can also adhere to the hair. Another limitation is the variations of hair characters, e.g. color, race, hair care, etc. [14]. In another context, urine is the preferred non-invasive matrix in biomonitoring especially for heavy metals. Many studies reported that urine-heavy metal is a suitable biomarker for general population and occupational exposure [1, 15]. Urine reflects recent exposure and has been taken as a surrogate when blood is not available because of various reasons [16]. Furthermore, the level of urinary heavy metals could be associated with the level of body burden at a certain time, and it is an important indicator in health risk analysis [17]. On the other hand, heavy metals are considered as one of the most serious pollutants in the environment. This opinion is due to the multipurpose usage of heavy metals, persistence in the environment, bioaccumulation and high toxicity [18-20]. Heavy metals are involved in various industrial processes, agricultural activity, domestic waste and vehicles emission [18-20]. The toxicity by heavy metals causes morphological abnormalities, nerurophysiological disturbances, genetic alteration of cell (mutation), teratogenesis and carcinogenesis. In addition, heavy metals effect on enzymatic and hormonal activities, reduces growth and increases mortality [18-20]. Therefore, there is a global increase of interest in the interaction of heavy metals with biological systems and the environment. The emission from industrial activities is one of the main sources of pollution by heavy metals. Thus, it is essential to study the level of heavy metals in biological specimens collected from workers. Unfortunately, direct assessment of the levels of heavy metals in biological samples is incorrect for many reasons. One of which is the difference in race and climate. Accordingly, this study aimed at determining the concentration of some heavy metals in hair and urine samples from workers in the largest metallurgical factories in Sudan, besides Sudanese residents in a control area. 2 MATERIALS AND METHODS 2.1 Study Area

The study area in the current work includes two metallurgical factories (mint and foundry), besides a control area that is expected to be free from industrial pollution. All sites are located in Khartoum State, which includes the major three cities in Sudan, i.e. Khartoum, KhartoumBahri and Omdurman. Khartoum is the capital and the largest city. Khartoum-Bahri is the heaviest industrial city. Omdurman is the most densely populated city in Sudan.

In the current study, the Mint Company, which is the single national factory in Sudan, was adopted. It is located at N 15º 58´, E 32 º 52´, Khartoum City. The other factory, which is called Mirghani Foundry, is located at N 15º 636´, E 32 º 437´, Omdurman City. The control area, which is located at N 15º 40´ and E 32º 31´, is Khartoum-Bahri City. 2.2 Sample collection

Scalp hair and urine samples were collected from thirty workers in the above mentioned factories and from thirty residents in the control area. All workers and referents were male and aged between 30 and 60 years. For hair sample collection, the protocol described by the International Atomic Energy Agency (IAEA) was considered [21]. The urine was collected on the last work day of the week and at the end of the shift because of the metal elimination rate [22]. Instructions were followed in order to avoid external contamination. The urine samples were collected in polyethylene flasks. 2.3 Sample treatment

For hair sample treatment, duplicate samples were firstly washed by acetone. Samples were washed again three times by distilled water for 10 minutes with shaking, and lastly with acetone. Hair samples were then dried at 80 oC. 3 mL of perchloric acid : nitric acid (1:5, v/v) was added to sample. The produced solution was diluted with bi-distilled water up to 60 mL. The pH was adjusted at the range of 3-4 using 0.1 mol/L NaOH. Thereafter, 2 mL of a freshly prepared filtered solution of 4% (w/v) Ammonium Pyrrolidine Dithocarbamate (APDC) were added to sample solution. The mixture was allowed to stand for 1 h with stirring. The mixture was then filtered and precipitated through a Nuclepore membrane [23-25]. The same procedure was applied to CRM-397 as a certified reference material. For urine sample treatment, also duplicate samples (0.5 mL), were dispensed into Teflon PTFE flasks. 2 mL of freshly prepared mixture of nitric acid : hydrogen peroxide (2:1, v/v) were added. The mixture was kept for 10 min at room temperature. Thereafter, the mixture was heated following a one-stage digestion program at 80% of total power (900 W) for 2–4 min. After cooling, the resulting solution was evaporated to semidried mass to remove excess acid. The retained material was diluted to 10 mL in volumetric flasks with 0.1 M nitric acid. Duplicate blanks were carried throughout the procedure [12]. For the confirmation of the adopted method, a certified reference material from NIES (No. 18 human urine) was analyzed in parallel with samples collected in the current study. 2.4 Instrumentation

A micro-computer-energy-depressive X-ray fluorescence spectrometer was used for hair analysis. The system was equipped with a molybdenum secondary target and a

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molybdenum filter. The system was also fitted with Cd109 excitation source, (t1/2 = 1.34 years, E = 22.2 keV and 88.0 keV) and coupled with a Si(Li) detector and multichannel analyzer. The concentrations of detectable elements were made from the measured intensity of the corresponding fluorescent X-rays combined with elemental sensitivity factor and coefficient of absorption in the residual matrix of the specimen through iteration procedure [24, 26, 27]. The method was applied to the certified reference material (BCR-143R). Urine samples were analyzed by AA-6800 atomic absorption spectrophotometer (AAS). The system was coupled with GFA-EX7 graphite furnace atomizer and ASC6100 auto-sampler from Shimadzu (Koyoto, Japan). Highdensity graphite tubes were used for atomization while

normal single hollow cathode lambs were used for irradiation. 3 RESULTS AND DISCUSSION The summary statistics of the concentrations of heavy metals in hair samples in the control area as well as the mint and foundry factories are compiled in Table 1. Fig. 2 compares the average concentrations of heavy metals in hair samples collected from both workers and referents. For the reliability of the obtained results, the analysis of the certified reference materials adopted in the current study recorded acceptable recovery. For hair analysis, the recovery values were in the range of 89.1-94.6% while for urine analysis the recovery values ranged from 91.0 to 105.1%.

TABLE 1 - Summary statistics of the concentrations (ng/mg) of heavy metals in hair samples collected from citizens in the control area as well as workers in the mint and foundry factories in Khartoum State, Sudan Metal Cr Fe Co Ni Cu Zn Pb

Control area Mean ± SD Min-Max 127.7 ± 38.0 93.9-188.7 223.0 ± 147.38 63.8-387.9 40.7 ± 0.37 40.1-41.0 50.1 ± 3.47 47.4-53.7 50.5 ± 6.12 38.9-55.3 67.3 ± 39.84 24.4-103.3 111.9 ± 10.48 97.4-122.3

Mint factory Mean ± SD Min-Max 235.3 ± 34.02 180.1-188.7 506.5 ± 126.90 410.2-387.9 43.1 ± 4.15 40.6-45.6 93.3 ± 2.11 91.7-53.8 126.8 ± 21.72 105.3-55.4 283.0 ± 242.77 34.7-10.4 240.9 ± 4.91 236.2–122.6

Foundry factory Mean ± SD Min-Max 196.2 ± 12.9 188.8-211.1 602.6 ± 325.5 296.6-944.7 43.2 ± 0.2 43.0-43.3 48.5 ± 0.2 48.3-48.6 54.1 ± 7.3 49.0-62.5 126.9 ± 121.2 46.0-266.3 109.4 ± 9.4 100.1-18.9

FIGURE 1 - Average concentrations of heavy metals in hair samples collected from citizines in the control area and workers in mint and foundry factories in Khartoum State, Sudan.

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For hair samples collected from citizens in the control area (Fig. 1), the average concentrations of heavy metals were in the rank order of Fe >> Cr > Pb > Zn > Ni ≈ Cu ≈ Co. Fig. 1 also shows that the concentrations in hair samples collected from workers in both foundries recorded different rank orders. For the mint factory, the rank order was Fe >> Zn > Pb ≈ Cr > Cu > Ni > Co while for the foundry factory the rank order was Fe >>> Cr > Zn > Pb > Cu ≈ Ni ≈ Co. In all hair samples, Fe was at the top of the rank order while Pb fluctuated from the third to the fourth ranks. Interestingly, various standard deviation values and different ranges of concentrations of all heavy metals were recorded in all hair samples. In this issue, wide ranges were recorded for the concentrations of Cr, Fe, Zn and to some extent for Pb in hair samples collected from citizens in the control area. Despite a narrow range was recorded for the concentrations of Fe in hair samples collected from workers in the mint factory, the average concentration of that metal in the same type of samples was five-fold that of hair samples collected from citizens in the control area. The same phenomenon was also observed for Cr and to some extent for Ni. Fig. 1 shows higher concentrations of Cr, Fe and Zn in hair samples from workers in both factories than those in hair samples from citizens in the control area. On the other hand, hair samples from workers in the mint factory only recorded higher concentrations of Ni, Cu and Pb than that in hair samples from workers in the foundry factory as well as in hair samples from citizens in the control area. Furthermore, Co recorded the same concentration in all hair samples. The World Bank Group [28] noted that foundries can emit airborne dust and discharge wastewater that can contribute in contamination by Zn, Pb, Cd, Cu, Cr

and Ni. Krystek and Ritsema [29] also reported that a foundry factory emitted significant amounts of a wide range of heavy metals, including Co, Cu, Fe, Ni, Pb and Zn, to the environment. The ranges of the concentrations of heavy metals obtained in the current study were compared with the corresponding ranges reported in some previous studies in the world (Table 2). Cr, Fe Co and Pb contents in residents’ hair in the control area in Sudan were significantly higher than the corresponding contents in residents’ hair in control areas in Malaysia [30], India [31] and China [32]. Showing the opposite trend, Ni and Cu contents in residents’ hair in the control area in Sudan were significantly lower than the corresponding contents in a control area in Malaysia [30]. Different contents of heavy metals in hair samples from non-occupationally exposed residents in different areas in the world could be attributed to the different in race, care, climate, nutrition, etc. For occupationally exposed workers, the same trend was found for the same sets of elements, i.e. Cr, Fe Co and Pb contents in Sudanese’ hair were much higher than those in Malaysian’ [30], Indian’ [31] and Chinese’ [32] hair and vice versa for Ni and Cu. For urine samples, the summary statistics of heavy metal contents obtained from the current study are shown in Table 3. In addition, for the comparison study purpose, Fig. 2 depicts the urinary heavy metal contents from citizens in the control area and workers in the two factories. Citizens in the control area recorded heavy metal concentrations in the rank order of Cr ≈ Pb > Co > Cu > Ni > Fe. It was found that while Fe concentration ranked in the top in hair samples, Fe concentration ranked in the

TABLE 2 - Comparison of the concentration of heavy metals (ng/mg) in hair samples from Khartoum State, Sudan with that other hair samples from other areas Current study Malaysia1 Control Industrial Control Industrial Cr 127.7 215.75 NR NR Fe 223.0 554.7 36 58 Co 40.7 43.15 NR NR Ni 50.1 70.9 417 388 Cu 50.5 90.45 514 817 Zn 67.3 204.95 458 751 Pb 111.9 175.15 0 38 1: Khudzari et al. 2013 [30]; 2: Wang et al. 2009 [32]; Ha et al. 2009 [31]; Metal

China2 Control 0.4-7.2 NR NR 0.0-9.4 10.9-537 NR 1.9-730.0

India3 Industrial 0.7-2.5 NR NR 0.4-3.0 5.3-14.0 NR 1.1-15.9

Control 0.3-1.3 NR 0.0-0.5 NR 5.6-9.6 60.2-150 NR

Industrial 0.2-0.7 NR 0.0-0.6 NR 8.9-163 98-186 NR

TABLE 3 - Summary statistics of the concentrations (µg/L) of heavy metals in urine samples collected from citizens in control area as well as workers in the mint and foundry factories in Khartoum State, Sudan Metal Cr Fe Co Ni Cu Pb

Control area Mean ± SD Min-Max 5.41 ± 2.56 3.85-10.45 0.45 ± 0.04 0.00-0.89 3.01 ± 0.90 2.22-4.16 1.88 ± 0.81 1.06-2.18 2.01 ± 0.89 1.05-2.91 5.1 ± 2.63 2.33-10.5

Mint factory Mean ± SD Min-Max 4.93 ± 0.59 4.59-5.64 3.58 ± 1.94 2.25-5.81 2.37 ± 0.18 2.26-2.58 2.35 ± 0.05 2.30-2.38 2.48 ± 0.21 2.35-2.73 5.59 ± 0.15 5.44-5.74

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Foundry factory Mean ± SD Min-Max 2.22 ± 0.01 2.21-2.23 0.48 ± 0.27 0.29-0.67 3.14 ± 0.05 3.10-3.17 3.33 ± 0.54 2.95-3.71 -

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FIGURE 2 - Average concentrations of heavy metals in urine samples collected from citizines in the control area and workers in mint and foundry factories in Khartoum State, Sudan.

TABLE 4 - Comparison of the concentrations of heavy metals (µg/L) in human urine samples from Khartoum State, Sudan with that of other urine samples from other areas Current study Ghana1 Control Industrial Control Industrial Cr 3.85-10.45 2.21-4.64 < 0.01-26.0 0.18-29.0 Fe 0.00-0.89 0.29-5.81 13.0-260.0 19.0-540.0 Co 2.22-4.16 2.26-2.58 0.13-2.1 0.041-8.7 Ni 1.06-2.18 2.30-3.17 NR NR Cu 1.05-2.91 2.35-3.71 5.25-481.0 7.12-490.0 Pb 2.33-10.5 5.44-5.74 0.31-33.7 0.86-18.3 1: Asante et al. 2012 [34]; 2: Wang et al. 2011[17];; 3: Aguilera et al. 2008 [33] Metal

last in urine samples. On the other side, other heavy metal concentrations were almost in the same sequence in both types of samples of hair and urine. However, the levels of heavy metals in hair samples were much higher than those in urine samples. It is worth noting that the increase of heavy metal concentrations between workers and referents in hair samples was much higher than those in urine samples. This phenomenon may reflect that hair is more effective bioindicator than urine. On the other side, urinary heavy metal concentrations obtained from the current study were compared with the corresponding data obtained from previous studies in other different areas in the world (Table 4). For urinary Cr content in control areas, the Sudanese samples were comparable with Ghani samples [34] and higher than Spanish

China2 Control NR NR NR NR 6.20±9.33 5.82±8.64

Industrial NR NR NR NR 6.81±10.20 4.09±16.02

Spain3 Control 0.65 NR NR 2.52 11.65 NR

Industrial 0.52 NR NR 2.03 11.38 NR

samples [33]. In addition, Fe urinary contents in the Sudanese control samples were lower than Ghani samples [34] and vice versa for Co. In another context, Cu urinary levels in Sudanese referents were lower than the corresponding Ghani [34], Chinese and Spanish [33] referents. For occupationally exposed workers, urinary Cr, Fe, Co, Cu and Pb contents for Sudanese workers are concordant with Ghani workers and to some extent with Chinese workers while higher than Spanish workers (Table 3). 4 CONCLUSIONS The current manuscript reports the first study on the levels of some heavy metals in hair and urine samples from occupationally and non-occupationally inhabitants

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in Sudan. The largest metallurgical factories, namely mint and foundry, in Khartoum State, Sudan were adopted in the current study. Another residential area, which is far from industrial activity, was adopted as a control area.

[6]

Jensen, T. K., Grandjean, P., Jorgensen, E. B., White, R. F., Debes, F., Weihe, P. (2005). Effects of breast feeding on neuropsychological development in a community with methylmercury exposure from seafood. J. Exposure Anal. Environ. Epid. 15, 423-430.

Significant difference in exposure to heavy metals between samples from workers and referents was observed indicating serious contamination.

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Campbell, L., Dixon, D. G., Hecky, R. E. (2003). A review of mercury in Lake Victoria, east Africa: implications for human and ecosystem health. J. Toxicol. Environ. Health Part B 6, 325-356.

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It is highly desirable to increase public awareness about the effects of exposure to metallurgical industries and more effective processes would be taken to minimize its risk. The comparative study between results obtained in the current control area with other worldwide control areas exhibited significant variation, which is due to variation in climate and race. This finding emphasizes that the inclusion of a control area, in the same region of the study area, is essential to assess properly occupational exposure to heavy metals. Since there are no specific reference values for the levels of heavy metals in biological samples for unexposed Sudanese residents, the current study establishes a baseline data for Khartoum State as the most densely populated state in Sudan. Specifically in the same area, it is recommended in the future studies in Khartoum State to consider factors effecting on the use of bioindicators such as age, gender, health status, lifestyle (smoking, Sudanese drug (Tombak) users) etc. Generally, it is also recommended to examine the environment of additional metallurgical heavy factories in Khartoum State. In addition, further research has to be carried out on evaluating the correlation between the exposure level and exposure pathways. The authors have declared no conflict of interest.

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Received: December 10, 2012 Accepted: January 30, 2013

CORRESPONDING AUTHOR Dr. Abubakr M. Idris King Khalid University College of Science Department of Chemistry Abha SAUDI ARABIA E-mail: [email protected] FEB/ Vol 22/ No 12a/ 2013 – pages 3625 - 3631

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