FIELD MINIATURE STUDY ON HEAVY METAL DETECTION USING ELECTRICAL RESISTIVITY IMAGING (ERI) Z. A. M. Hazreek and A. T. S. Azhar Faculty of Civil and Environmental Engineering Universiti Tun Hussein Onn Malaysia, Batu Pahat Johor S. Rosli School of Physics Universiti Sains Malaysia, Penang, MALAYSIA ABSTRACT Electrical resistivity imaging (ERI) has widely used in subsurface characterization thru surface investigation related to geotechnical and environmental studies. In the past, soil contamination detection experienced some limitation such as determination of the affected zone accurately. Hence, this study performed an electrical resistivity imaging to investigate the efficiency of geophysical tools in heavy metal detection in soil. The survey was performed on field miniature scale using ABEM Terramater SAS (4000) equipment set based on single spread line via Wenner and Schlumberger configurations before and after heavy metal injection. Electrical resistivity raw data was processed using RES2DINV software to produce electrical resistivity tomography (ERT). It was found that the electrical resistivity of soil changed before and after the heavy metal injection. Lower electrical resistivity value was founds (<10 Ωm) at the area that being infiltrated by heavy metal. The decreasing of the resistivity value was influenced by increment quantity of ions derived from composition of heavy metal. Hence, the study demonstrates that ERI was applicable for heavy metal detection in soil due to its economic, fast, large data coverage and sustainable to our environment. Keywords: Electrical Resistivity Imaging, Heavy Metal, Electrical Resistivity Tomography. Cite this Article: Z. A. M. Hazreek, A. T. S. Azhar and S. Rosli, Field Miniature Study on Heavy Metal Detection using Electrical Resistivity Imaging (ERI), International Journal of Civil Engineering and Technology, 9(5), 2018, pp. 284–292. http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=9&IType=5
1. INTRODUCTION Soil contamination is one of the pollution that affects the earth this century. One of the major factors that influence soil pollution is heavy metals. Heavy metals such as Cu, Ni, Mg, Zn and Pb are some common type of metals that able to polluted soils. The properties of soil such as clay contents, pH and organic matter have major impacts on the expanse of the effects of the heavy metals on biological and biochemical properties (Singh et al. 2011) . In order to obtain the engineering and chemical properties of the soil, site investigation were performed to collect the soil contaminated samples for further testing purposes. Generally, conventional method for subsurface profile exploration was based on drilling of vertical holes in ground. This approach is known as borings or exploratory borings. In addition, shallow investigation such as exploratory trenches (test pits) provide more information than a boring of comparable depth and can be necessary to supplement a program of exploratory boring. Rotary drilling is one of boring exploration techniques which applicable for sand, clay and rock (Coduto et al. 2011) . Wash boring is another method of advancing boreholes and is effective for cohesion soil and may consider low cost to be performed (Das, 2014) . All those classical method has similar aimed which to obtain the representative soil and rock samples. Current soil exploration techniques has demand some alternative technique to reduce the limitation of conventional methods in term of cost, labors and time, data coverage and sustainability. Hence, geophysical method with particular reference to electrical resistivity method (ERM) was introduced. ERM is one of the geophysical surveying techniques that investigate the variations of electrical resistance by thru difficulty of electrical current to flow within the subsurface geomaterials. It utilizes direct currents or low frequency alternating currents to exploit the electrical properties (resistivity) of the subsurface geomaterials. During resistivity surveys, current is injected into the earth through a pair of current electrodes, and the potential difference is measured between a pair of potential electrodes to produces electrical resistivity value. Common application of electrical resistivity survey is to discover the resistivity distribution of the ground subsurface by making the measurement on the ground surface (Loke, 1999) . From past experienced, ERM has successful demonstrated its ability in subsurface mapping in engineering, environmental and archaeology studies (Abidin et al. 2013) . Contamination zone due to heavy metals can easily being mapped based on geophysical characteristics (Porsani et al. 2013) . Hence, this study performed ERM for soil heavy metal detection via field miniature studies using wenner and schlumberger configuration.
2. MATERIAL & METHODS Field miniature scale was setup at Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat, Johor. This study was conducted on a flat ground surface in the UTHM sites. A single line of resistivity spread line (SL) with length of 3.2 m was performed at UTHM site. Electrical resistivity survey was carried out using ABEM Terrameter SAS4000 equipment set. Two resistivity land cables with total 42 take out was setup in a straight line. The end of cable 1 and initial of cable 2 was connected with electrode switcher. 41 numbers of mini electrodes (6 inch of length with 3 mm of diameter) was pluck into the spread line based on 80 mm of electrode equal spacing via 42 numbers of jumper cables. ABEM Terrameter SAS4000 and electrode selector switcher were set up at the centre of the resistivity land cables. 12 volt of battery was used to generate the source of current into the ground alternately between electrodes. Then, the equipment will calculate the resistance value of the subsurface soil and the data was recorded automatically in Terrameter SAS4000. Electrical resistivity imaging and setup was shown in Figure 1 and 2. The survey performed in
Field Miniature Study on Heavy Metal Detection using Electrical Resistivity Imaging (ERI)
two different conditions which are before and after injection of heavy metal (chemical). The chemical was injected between electrode numbers 20 to electrode number 27. This study used a liquid of magnesium for heavy metal simulation. This study decides a magnesium as a chemical agent due to its less hazardous (safety purposes) compared to other chemical agent. 1 liter of magnesium was poured and left for 20 minutes around the electrode numbers of 2027 to ensure that the chemical was infiltrate into the soil. Raw data obtained from data acquisition was analyzed using commercialize RES2DINV software to replicate the subsurface soil before and after the heavy metal agent being injected. RES2DINV inversion algorithm was used to analyze the data, as recommended by (Loke and Barker, 1996)  in order to obtain the electrical resistivity tomography (ERT). Commercialize RES2DINV software has widely being used by previous and current researcher worldwide in many studies (Loke and Barke, 1996; Hazreek et al. 2017; Abidin et al. 2017; Ganiyu et al. 2016; Cinar et al. 2015; Nordiana et al. 2014; Rosales et al. 2012; Hazreek et al. 2015; Baharuddin et al. 2013) [7 – 15].
Figure 1 Electrical resistivity imaging and its field arrangement
Figure 2 Location of magnesium injection and field arrangement of ERI
3. RESULTS AND DISCUSSIONS All results were discussed based on electrical resistivity tomography (ERT) as given in subsection 3.1 – 3.2.
3.1. Electrical resistivity tomography 1 Figure 3 shows the electrical resistivity tomography (ERT) for wenner array before the injection of magnesium. According to Figure 9, it was found that resistivity tomography composed of materials which having electrical resistivity value (ERV) ranging at 6.1 – 301.6 Ωm. According to Figure 2, ERT anomaly contrast was generally similar representing its homogenous condition. ERT founds that the ERV of the subsurface profile mostly was ranged at 15 – 100 Ωm which interpreted as a mixture of sandy, silty and clayey soils. According to (Lee, 2012) , ERV for soil form clayey, silty and sand may ranged at 100 – 250 Ωm. During field observation, soil type was identified physically as sand and silt due to its transported fill soil. Figure 4 shows the electrical resistivity tomography (ERT) for wenner array after the injection of magnesium. As referred to Figure 4, ERV founds at 5.6 Ωm – 300.8 Ωm. There is no significant change between the previous ERT (Figure 3) due to the fast infiltration of magnesium which penetrated deeper into the soil. As a result, ERT at Figure 4 was unable to detect the magnesium within its section due to the influence of small electrode spacing adopted during the survey which produced shallow ERT section. Table 1 and Figure 5 highlight the variation of ERV from the injection of magnesium between electrode numbers 20 – 27. Moreover, wenner array only provide 71 number of datum point to produce the ERT thus unable to image the ERV changes obviously.
Figure 3 ERT for wenner array before magnesium injection
Figure 4 ERT for wenner array before magnesium injection
Field Miniature Study on Heavy Metal Detection using Electrical Resistivity Imaging (ERI) Table 1 ERV variations for wenner array before and after magnesium injection Depth (m)
Electrical resistivity value (Ωm) Before magnesium injection
After magnesium injection
37.35 34.58 36.29 209.4
14.29 23.16 30.55 31.40
0.06 0.10 0.15 0.20
Variations (%) 62.0 33.0 15.8 85.0
Electrical Resistivity Value (Ω.m)
Resistivity Value (Wenner Array) 300 200 100 0 1
Figure 5 ERV variation for wenner array before and after magnesium injection
3.1. Electrical resistivity tomography 1 Figure 6 shows ERT for schlumberger array before the magnesium injection. Electrical resistivity value (ERV) was founds in the range of 5.6 – 1970.6 Ωm. According to the Figure 6, maximum depth of ERT was 0.56 m thus give more data coverage of the subsurface profile. Schlumberger array able to produce deeper ERT compared to wenner array due to its different geometry factor, k. It was found that ERT of Figure 6 consists of homogenous soil due to insignificant contrast of anomaly which ranged at 15 – 150 Ωm thus indicate as silty sand (McCarthy, 2007) [17 According to Figure 7, ERV found to be in the range of 2.97 – 679.34 Ωm. As shown in Table 2 and Figure 8, ERV decrease significantly (ERV variation = 86.8 % and above) due to the injection of magnesium. According to (Hamzah et al. 2014) , leachate contaminant which is the other form of magnesium in the soil experienced ERV at 5 – 9 Ωm thus demonstrate that soil contaminated with chemical agent will decreased the ERV. The reduction of ERV was due to the present of magnesium ion (Mg+) which ease the current propagation in soil medium. When an electric field is applied, electrical current flows in materials due to the motion of charged particles (Karato and Wang, 2013) . High quantity of ion in soil will ease the current propagation thus reduce the ERV and vice-versa. Basically, ERV was highly influenced by pore fluid and grain matrix of geomaterials (Griffith and King, 1981) . ERV of earth materials may varies due to the influence of soil properties such as moisture content, grain size, degree of denseness and stiffness, void and porosity concentration (Hazreek et al. 2016; Hazreek et al. 2015; Hazreek et al. 2014; Hazreek et al. 2014; Abidin et al. 2014; Abidin et al. 2013; Abidin et al. 2013) [21 – 27]. Furthermore, resistivity array (Abidin et al. 2013; Abidin et al. 2013) [5 and 28], metal ion or inorganic
Field Miniature Study on Heavy Metal Detection using Electrical Resistivity Imaging (ERI)
4. CONCLUSION The subsurface profile evaluation with particular reference to soil heavy metal contamination was successfully being performed using electrical resistivity method thru wenner and schlumberger array. Contamination zone of subsurface profile has been determined by analyzing electrical resistivity data obtained along the resistivity spread line and the results has shown a good agreement compared to the previous researcher ERV. This finding has proved that the technique was applicable to detect and predict soil contamination zone thus able to compliment the classical drilling method. Generally, contamination zone due to heavy metal can be easily recognized based on lower ERV. Consequently, the determination of shape and depth of the heavy metal contamination material are easier and cheaper than with conservative borehole method. The information obtained from ERM was useful for decision making regarding the soil improvement afterward. ERM is suitable for our sustainable ground investigation due to its efficiency in term of cost, time and data coverage. Furthermore, ERM was performed using surface techniques (non-destructive test) thus able to avoid site destruction which contribute to the environmental sustainability. Finally, the study has demonstrated that ERV was applicable as an alternative tool in soil heavy metal detection.
ACKNOWLEDGMENT The authors would like to express their deepest appreciation to the Ministry of Higher Education and Universiti Tun Hussein Onn Malaysia for supporting this research under Incentive Grant Scheme for Publication (IGSP) Vot U258. Many thank are due to all research members for their tremendous work and cooperation.
   
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