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Bioavailability and Safety Issues of Heavy Metals in Paddy Soil-Rice Continuum in Korea
Won-Il Kim1*, Jae E. Yang2, Goo-Bok Jung3, Byung-Jun Park1, Sang-Won Park1,
Jin-Kyoung Kim1, Oh-Kyung Kwon1, and Gab-Hee Ryu1
1National Institute of Agricultural Science and Technology,
RDA, Suwon 441-707, Korea
2Kangwon National University, Chuncheon 200-701, Korea
3Rural Development Administration, Suwon 441-707, Korea
*Corresponding author, 2009-04-07

Abstract

There is an increasing concern over heavy metal contamination of agricultural soils and the successive translocation of metals to rice in Korea. Rice is one of the most important crops in the country. Thus, it is very important to monitor the status and trend of heavy metal contamination in paddy soils and rice periodically. It is also important to verify the bioavailability of heavy metals in paddy soils released from mine tailings, which is a major source of contamination in Korea, and to make a prediction model of heavy metal uptake in rice. The average concentrations of As (arsenic), Cd (cadmium), Cu (copper), Ni (nickel), Pb (lead), and Zn (zinc) in paddy soils nationwide were 0.66, 0.08, 3.83, 0.59, 4.82 and 4.33 mg kg-1, respectively, which were within the threshold level for soil contamination designated by the Soil Environmental Conservation Act in Korea. However, heavy metal contents in paddy soils from 94 sites nearby the abandoned/closed mines and 43 sites nearby industrial complexes exceeded the Korean regulations. The respective average concentrations of As, Cd, Cu, Ni, Pb, and Zn in brown rice collected at the non-contaminated paddy fields in 1999 were 0.07, 0.035, 2.74, 0.29, 0.28 and 18.3 mg kg-1, respectively. Heavy metal phyto-availability in paddy soils near five abandoned mining areas was analyzed by sequential extraction method. Cd in soil consisted 25.1% of exchangeable form, 32.9% of oxide and carbonate form, 37.4% of sulfide and residual form, and 4.6% of organically bound form. The exchangeable forms of Cd were negatively correlated with soil pH. While oxide, carbonate, and sulfide forms of Cd was positively correlated with soil pH. All kinds of Cd fractionation except organically bound form were highly positively correlated with Cd content in brown rice. Two-year lysimeter experiments showed that Cd contents in the mine tailings were the limiting factor for Cd levels in rice, which were higher in the fine textured soil than in the coarse textured soils. Major species of Cd in leachate were Cd2+, CdCl+, and CdSO4 (aq), but these species were not positively correlated with Cd contents in rice. Rice variety was a more important factor regulating Cd translocation to grain than soil physico-chemical properties and agricultural management practices. Prediction of Cd uptake by rice was delineated by the model [log (Rice Cd) = -1.60 + 1.11 log (total soil Cd) - 0.014 (soil OM, %) + 0.18(pH) - 0.03 (soil clay, %) (R2=0.404***)] using 108 soils and rice grains collected from the closed mine areas. Key words: bioavailability, heavy metal contamination, paddy soils, rice, Cd uptake model

Key words: bioavailability, heavy metal contamination, paddy soils, rice, Cd uptake model

Introduction

Increase of contaminants in agricultural ecosystem has become a social issue worldwide as it is related with public health. International agencies, such as the Food and Agriculture Organization (FAO) and the World Health Organization (WHO), are currently advocating compliance to permission criteria of pollutants in agricultural products. In 2000, Korean Food and Drug Administration (KFDA) have set a safety criterion of 0.2 mg kg-1 for Cd concentration in polished rice. The maximum permitted concentration of Pb was also set at a level of 0.2 mg kg-1 in 2006. Accumulation of heavy metals in rice is one of the critical environmental issues in Korea.

Heavy metal contamination in paddy soils may have been caused by wastewater, dust, and sewage sludge originating from industries, mines, smelters, and metal processing industries (Jung et al., 2002; Lee et al., 2001; Oh, 1997). Generally, heavy metals such as Cu, Pb, Zn and As accumulated slowly but continuously in paddy fields may directly damage crops and through the food chain process, livestock and humans may indirectly be affected. Since application of municipal and industrial sewage sludge were prohibited in agricultural fields in Korea, the major sources of heavy metal contamination in paddy fields were mine and smelter industries through irrigation water, smoke, and suspended particles.

The bioavailability and toxicity of heavy metals to plant are strongly correlated by both biotic factors and soil characteristics. The bioavailability of heavy metals, their biological uptake, and their ecotoxicological effects on the soil biota can be better understood in terms of their chemical speciation. Computer models have been developed to predict chemical speciation, which is crucial in the assessment of bioavailability. Computer software named MINTEQ has facilitated a new approach to calculate the chemical speciation and following the evaluation of plant uptake of heavy metals. Furthermore, several soil factors, such as soil pH, Eh, clay contents, Mn oxide and oxidized Fe, organic matter as well as cation exchange capacity, were involved with distribution of heavy metals and their availability to plant in soils (de Matos et al., 2000; Martinez and Motto, 2000; Mench et al., 1997; Miner et al., 1997; Sterckeman et al., 2000).

Therefore, the objectives of this study were: 1) to evaluate the state and trend of heavy metal contamination in relevant paddy soils and rice; 2) to assess the release characteristics of heavy metals from the mine tailings and to get the prediction of heavy metals load potential from mine tailing to soil and rice, and finally; 3) to develop the countermeasure techniques to conserve the contaminated paddy soils.

Materials and Methods

Monitoring of Heavy Metal Contents in Paddy Soils and Polished Rice

To monitor the status and trend of heavy metal contamination in non-contaminated paddy soils, 4,047 sites in 1999 and 2,010 sites in 2003 of paddy soils were collected nationwide. For the vulnerable agricultural paddy soils, 2,400 soil samples at a 15 cm of top layer were also collected near closed mines and industrial zones. The contents of As, Cd, Cu, Ni, Pb, and Zn in the collected soils were measured by ICP after HCl dilution extraction for soils (MOE, Soil Environmental Conservation Act). The concentration of heavy metals in polished rice was analyzed using ICP or ICP-MS after acid digestion.

Distribution of Heavy Metals and Its Availability in Paddy Soils near Closed Mines

Soil samples were collected at paddy fields near five-abandoned mines within 5 km for distribution of Cd and their availability to rice plants. This research considered mining activities with distance from mines and gathered in 0. 15 cm depth of 30 sites (6 sites for each mine) before the growing season. The Cd content in brown rice collected at the same paddy fields was analyzed. The sequential extraction procedure was used to fractionate the heavy metals in soils. These heavy metals were designated into: water soluble, exchangeable, organically bound, oxide/carbonate, and sulfide/residual (Sims and Kline, 1991; Ryu et al., 1995).

Transition of heavy metals released from the mine tailings to rice plants

Two-year lysimeter experiments were done to identify the speciation and transition characteristics of heavy metals released from mine tailings. Lysimeters were filled with sandy loam (SL) and silt loam soils (SiL), which are representative of paddy soils in Korea. Each plot was made with 0, 2, 4, 8 mg kg-1, respectively of Cd basis by adding two different mine tailings collected near closed mines located at the eastern part of Korea. Rice was grown in the lysimeters (900 mm X 900 mm X 1000 mm) and harvested. Leachate was also collected periodically at the bottom of the lysimeter during the growing season and water pH, EC, anions and cations in the leachate were analyzed with pH meter, ion chromatography and ICP. The concentrations of heavy metals in soil and polished rice were analyzed using ICP-OES. To estimate the speciation of heavy metals in leachate, MINTEQ program (1991) was used.

Prediction of CD Uptake by Rice in Paddy Soils near Closed Mine Areas

To develop a prediction model for Cd uptake by rice on the basis of soil physico-chemical properties, 108 soil and rice grain samples were collected and analyzed from seven closed mine areas in 2001 and 2002. Soil organic matter and clay content were also measured, as well as the contents of heavy metals in soils and rice. Correlation coefficients were determined for Cd in rice versus selected soil physical and chemical properties. Multivariate regression was used to derive best-fit models of Cd concentration in rice to soil's physical and chemical properties including extractable and total Cd in soils.

Results and Discussion

Monitoring of Heavy Metal Contents in Paddy Soils and Polished Rice

Since rice is one of the most important crops in Korea, it is necessary to monitor the status and long-term trend of heavy metal contamination in paddy soils and rice periodically. Paddy soils were collected from March to April before rice cultivation nationwide and the contents of As, Cd, Cr, Cu, Pb, Ni, and Zn in soils were measured by ICP after a dilute HCl extraction. This procedure was conducted in 1999 and 2003.

In 2003, the average contents of As, Cd, Cu, Ni, Pb, and Zn in soils were 0.66, 0.079, 3.83, 0.59, 4.82 and 4.33 mg kg-1, respectively. It was found out that heavy metal content did not exceed the threshold level for soil contamination described in the Soil Environmental Conservation Act in 1999 survey. However, one of the 2,010 samples exceeded the mg kg-1 of concern level for As in 2003. A wide range of overall heavy metals was found in paddy soils. Considering the distribution characteristics of heavy metal contents in paddy soils, median value was less than mean value because a few sites (over 95 %) percentile had high concentrations of heavy metals while lots of sites were under the detection limit ( Table 1(1241)). There was no clear difference between 1999 and 2003 in terms of distribution characteristics of all surveyed heavy metals in paddy soils ( Fig. 1(1246)).

However, heavy metal contents were relatively higher in the vulnerable paddy soils and rice for environmental contamination near closed mines and industrial area than those in non-contaminated soils ( Table 2(1240)). This maybe attributed to the major sources of heavy metal contamination in the vulnerable paddy fields such as mines, smelter industries through irrigation water, smoke, and suspended particles. It was indicated that heavy metal contents in soils exceeded the Korean regulation at 94 sites near closed mines in 2004 and at 33 sites near industrial area in 2005. In terms of the distribution characteristics of heavy metal contents in vulnerable paddy soils, median value were also less than mean value because a few sites (over 95 % percentile) were of high concentrations of heavy metals and many of the sites were detected under the detection limit ( Table 2(1240)). Overall, the heavy metal contamination in vulnerable paddy soils near closed metal mines was higher than those near industrial areas Compared with the previous survey for the same sampling sites in 2000 and 2001, heavy metal contents were significantly decreased in 2004 and 2005 due to the continuous soil reclamation for the contaminated paddy soils.

The mean concentrations of As, Cd, Cu, Ni, Pb, and Zn in brown rice collected at the non-contaminated paddy fields in 1999 were 0.07, 0.035, 2.74, 0.29, 0.28 and 18.3 mg kg-1, respectively. However, heavy metal concentrations in brown rice collected at paddy fields in flowing municipal wastewater were much higher. Cd concentrations in brown rice ranged between 0 and 0.95 mg kg-1 and were below the 1.0 mg kg-1 maximum permitted concentrations (MPC) for Cd set by KFDA ( Table 3(1240)).

Distribution of Heavy Metals and Its Availability in Paddy Soils near Closed Mines

Total content of Cd in soils and brown rice digested by ternary solution near closed mines was described in Table 4(1175). It was observed that the higher Cd concentration in soils, the higher Cd content was there in brown rice. The Cd concentration was 4.08 mg kg-1 in paddy soil at D closed mine with high soil pH. It was two-fold higher than those of C and E mine, but lower by 0.145 and 0.076 mg kg-1 compared with C and E mines, and in brown rice it had 0.051 mg kg-1. The uptake of Cd in crop was proportioned with Cd concentration in soils, but it was affected by soil pH. It could be possible to assess the total concentration of extractable content of heavy metal ratio by considering the soil characteristics.

After dry acid digestion and evaluation of the chemical speciation of heavy metal in soil through sequential extraction procedure were done, Cd contents in brown rice cultivated at the same fields were also analyzed. Cd fractionations in 30 paddy soils (0-15 cm) near the closed mines were also analyzed by sequential extraction method to assess availability to rice plant ( Table 5(1177)).

Cd content at the same fields was also analyzed after acid digestion. Average total content in all chemical forms of Cd was 3.24. Available chemical forms of heavy metals to rice plant, such as water soluble and exchangeable form were relatively low. Soil Cd consisted of 25.1% exchangeable form, 32.9% oxide and carbonate form, 37.4% sulfide and residual form, and 4.6% organically bound form. These values were relatively lower than the exchangeable portion of Cd. Lee and Touray (1998) and Ullrich et al. (2000) reported that the ratio of exchangeable form was high in the following order : Cd>Zn>Pb. However, organically bound form extracted with 0.5M-NaOH was 47.3% for Cu but 0.4-4.6% for other metals. Martinez and Motto (2000) reported that solubility of Cu, Pb, and Zn following to mobility in soil and availability and toxicity to plants increases as soil pH decreases.

Table 6(1078) shows the relationship between soil pH and chemical forms of Cd in paddy soils collected near closed mines. Soil pH was negatively correlated with water soluble and exchangeable forms of Cd, which were easily absorbed by the plant. Among these, Cd had the highest correlation coefficient with soil pH. In addition, oxide, carbonate, sulfide, and residual forms of Cd were positively correlated with soil pH. Therefore, exchangeable Cd was reduced and non-exchangeable Cd, such as organically bound, carbonate, and sulfide form, were increased as soil pH was increased. In case of Cu and Pb, non-exchangeable form increased with decreasing organically bound form as soil pH increased (Krebs et al., 1998).

The distribution rate of Cd forms in paddy soils near each closed mine was presented in Fig. 2(1168). It appeared that the distribution rate of Cd forms in the soils had significant differences among the location, especially for D closed mine that had soil pH 7.59. The distribution percent of soluble and exchangeable Cd forms was 1.06% at D closed mine. This percent was so low as compared to the average value (30.31%) in the other mines because it was mainly consisted of sulfide bound and residual form.

It may be contributed to the high soil pH 8.0 as location of limestone and the huge application of lime and silicate for reclamation of heavy metal contamination at D closed mine. Also, it was observed that the concentration rate of soluble and exchangeable heavy metals was extremely low and the rate of sulfide bound and residual form was high in this type of soil. Heavy metal forms were mainly existed with an oxide, carbonate, sulfide bound and residual form, but the rate of soluble and exchangeable form was low in soil as increment of soil pH with application of lime in paddy near Zn closed mine (Lyu et al., 1995).

Relationships between Cd contents in brown rice and soil fractionation are shown in Table 7(1252). All kinds of Cd fractionation in soils had high positive correlation with Cd content in brown rice. It can be concluded that all kinds of Cd fractionations were dependent on the cadmium uptake in brown rice. Yoo et al. (1995) reported that organically bound chemicals, carbonate and sulfide form of Cd, and water soluble and exchangeable form of Zn were highly positively correlated with these metals in brown rice, whereas, Pb did not shown any correlation.

Therefore, it was also concluded that relationship between heavy metal speciation in soil and their contents in plants were different in terms of source and degree of heavy metal contamination, chemical composition of soil, and fractionation method of heavy metals (Andreu and Gimeno-Garcia, 1999; Jung, 2000). Furthermore, it was suggested that countermeasure research and proper assessment methodology at different location with contamination characteristics be conducted in order to recover the greatly contaminated site of heavy metals.

Transition of Heavy Metals Released from the Mine Tailings to Rice Plants

Two-year lysimeter experiments packing with SL and SiL soil types were done to identify the speciation and transition characteristics of Cd released from the two types of mine tailings. Chemical properties of soil used were presented in Table 8(1425). Total contents of heavy metals in each soil and in treated mine tailings were also shown ( Table 8(1425) and Table 9(1143)). Each plot was made with 0 (control), 2 (DG1 and WD1), 4 (DG2 and WD2), 8 (DG3 and WD3) mg kg-1 of Cd basis by adding two different mine tailings (DG and WD) collected near closed mines located at the eastern part of Korea.

Leachate pH was not significantly different with soil type and treated amount of mine tailing. However, ECs in laechate from SL plot were much higher than those from SiL ( Fig. 3(1093)). NO2-N, NO3-N, NH4N, PO4-P, SO4, F, Cl, K, Na, Cr, Cd, Fe, Zn, Pb, Al, Mg, Ni, Cu, Ca, and Mn concentrations in effluent were measured. With this dataset, MINTEQ output showed 16 different Cd speciations. Table 10(1304) shows one example for sandy loam control plot. Major compositions in laechate were Cd2+, CdCl+, and CdSO4 (aq), which consist of more than 99% ( Table 11(1209)). Compared with soil types, rice harvested on the SiL plot contained more Cd than that on the SL plot ( Fig. 4(1327)). The concentrations of Cd in polished rice were increased as treatment of both mine tailings increased. However, these major speciations were not positively correlated with Cd contents in rice at all ( Fig. 5(1231)).

Chemical forms of heavy metals in soil and soil solution were closely related to the bioavailability and toxicity. Many studies have shown that both metal speciation and ion activity were more effective than total concentrations of heavy metals in soils (McBride, 2002; Nolan et al., 2003; Sauve, 2000; Weng et al., 2004). Lorenz et al. (1997) concluded that Cd concentrations in leaves and tubers were more closely correlated with their total and free ionic concentrations in rhizosphere solution than with their concentrations in soils.

Prediction of CD Uptake by Rice in Paddy Soils near Closed Mine Areas

In 2001 and 2002, 108 soils and rice grains were collected and analyzed from seven closed mine areas in order to develop a prediction model for Cd uptake by rice on the basis of soil physico-chemical properties. Soil pH, organic matter content, and clay content were major components of the model as main factors controlling Cd availability in paddy soils. They ranged from 4.2-7.9, 4.82-57.20 mg kg-1, and 4.5-25.9%, respectively. Soil 0.1M HCl-extractable and total Cd concentrations for the field studies ranged from 0.04-14.3, and 0.94-18.6 mg kg-1, respectively ( Table 12(1232)). Dilute HCl extractable Cd in soils was not closely correlated with Cd concentrations in brown rice ( Fig. 6(1143)). Extractable Cd was negatively correlated with soil pH and clay content, whereas, it was positively correlated with soil organic matter content and Cd contents in rice ( Table 13(1027)). Rice Cd concentrations in the paddy studies ranged from 0.01-2.13 mg kg-1 FW. The model was developed using a stepwise multiple regression equation: Rice Cd = 0.939 + 0.0616 soil HCl-extractable Cd - 0.0066 % soil OM - 0.0912 pH - 0.0065 % soil clay (R2=0.182***). However, this model was more effective by adding total Cd in soil and using the logarithm in the equation, as: log Rice Cd = -1.600 + 1.11 log total soil Cd - 0.014 % soil OM + 0.180 pH - 0.032 % soil clay (R2=0.404***) ( Table 14(1241) and Fig. 7(1606)).

Conclusion

Generally, heavy metal contamination in agricultural soils has steadily and slowly increased in the past few decades. Therefore, long-term monitoring study on the heavy metal contamination in paddy soils and rice has to be continued periodically. Specially, a more detailed study is needed in vulnerable paddy soils and rice for environmental contamination near closed mines and industrial area. Heavy metals in paddy soils are loaded by parent materials and anthropogenic inputs. Mining activity and smelter industry are major sources of heavy metal contamination in a localized area. It is important to understand the evaluation of released kinetics from the mine tailing next to loading capacity on paddy soils and the assessment of transition mechanism to edible crops.

A prediction model for Cd uptake by rice was developed on the basis of soil physico-chemical properties, such as soil pH, organic matter content, clay content and Cd concentrations, using stepwise multiple regression. Even though the prediction model was significant, R2 value was relatively low. On the other hand, large differences in Cd accumulation among cultivars were observed especially in the grain. The lowest Cd accumulator (DT 637) of durum wheat variety had ca. 20-fold less Cd compared to the highest one (Kyle) (Cieslinski et al, 1996). Compared with Cd uptake capability and transfer to grain in rice varieties, Japonica types could be divided as the lower accumulators whereas, Indica types and Indica X Japonica hybrid belonged to the higher accumulators (unpublished data). Therefore, it could be concluded that rice variety difference was more affected by heavy metal transition to grain than other physico-chemical soil properties and agricultural management. It means the more accurate prediction model can be made when some biotic factors such as varietals characteristics and environmental conditions were added. It can be used for establishing the countermeasure technique for soil conservation and optimal farm management of paddy fields and to contribute the production of safe agricultural products.

References

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Index of Images

Figure 2 The Distribution of Cadmium Forms Extracted by Sequential Extraction Procedure in Paddy Soils near Each Mine (Adopted from Jung Et Al., 2000B). the Values of Y-Axis Are the Percent Distribution of Chemical Forms of Cadmium. H2o+Kno3 Is Water-Soluble Plus Exchangeable, Naoh Is Organically Bound, Edta Is Oxide and Carbonate, and Hno3 Is Sulfide Bound Plus Residual Form of Heavy Metals in Soils.

Figure 2 The Distribution of Cadmium Forms Extracted by Sequential Extraction Procedure in Paddy Soils near Each Mine (Adopted from Jung Et Al., 2000B). the Values of Y-Axis Are the Percent Distribution of Chemical Forms of Cadmium. H2o+Kno3 Is Water-Soluble Plus Exchangeable, Naoh Is Organically Bound, Edta Is Oxide and Carbonate, and Hno3 Is Sulfide Bound Plus Residual Form of Heavy Metals in Soils.

Figure 3 Leachate PH and Ec with Different Rates of Mine Tailing

Figure 3 Leachate PH and Ec with Different Rates of Mine Tailing

Figure 4 CD Concentration in Rice Grown on the Lysimeter with Different Rates of Mine Tailings.

Figure 4 CD Concentration in Rice Grown on the Lysimeter with Different Rates of Mine Tailings.

Figure 5 Relationship between CD Content in Rice and Activity of CD Speciation in Effluent.

Figure 5 Relationship between CD Content in Rice and Activity of CD Speciation in Effluent.

Figure 6 Relationship between CD in Paddy Soils and in Rice Harvested from the Same Fields.

Figure 6 Relationship between CD in Paddy Soils and in Rice Harvested from the Same Fields.

Figure 7 Relationship between Measured and Predicted CD in Rice by the Regression Model.

Figure 7 Relationship between Measured and Predicted CD in Rice by the Regression Model.

Table 1 Mean Contents (and Their Ranges) of 0.1N HCL Extractable CD, Cu, Ni, PB, ZN and 1N HCL Extractable As in Non-Contaminated Paddy Soils

Table 1 Mean Contents (and Their Ranges) of 0.1N HCL Extractable CD, Cu, Ni, PB, ZN and 1N HCL Extractable As in Non-Contaminated Paddy Soils

Table 2 Mean Contents (and Their Ranges) of As, CD, Cu, Ni, PB, and ZN in Paddy Soils Collected near Closed Mines and Industrial Complex Zones

Table 2 Mean Contents (and Their Ranges) of As, CD, Cu, Ni, PB, and ZN in Paddy Soils Collected near Closed Mines and Industrial Complex Zones

Table 4 Total Content of CD in Soils and Brown Rice Collected near Closed Mines (Adopted from Jung Et Al., 2000a)

Table 4 Total Content of CD in Soils and Brown Rice Collected near Closed Mines (Adopted from Jung Et Al., 2000a)

Table 5 The Relative Distribution of Each Fraction of CD in Thirty Paddy Soils near Five Closed Mines

Table 5 The Relative Distribution of Each Fraction of CD in Thirty Paddy Soils near Five Closed Mines

Table 6 Relationships between Percentage Ratios of the CD Content of Each Fraction to the Sum of All Fractionation and PH in Paddy Soils (N=30) near Closed Mines

Table 6 Relationships between Percentage Ratios of the CD Content of Each Fraction to the Sum of All Fractionation and PH in Paddy Soils (N=30) near Closed Mines

Table 7 Relationships between CD Content in Brown Rice and Soil Fractions in Thirty Paddy Soils near Five Closed Mines

Table 7 Relationships between CD Content in Brown Rice and Soil Fractions in Thirty Paddy Soils near Five Closed Mines

Table 8 Chemical Properties of Paddy Soils in the Lysimeter before Mine Tailings Treatment

Table 8 Chemical Properties of Paddy Soils in the Lysimeter before Mine Tailings Treatment

Figure 1 Distribution of Dilute HCL Extractable As, CD, Cu, Ni, PB, and ZN Concentration in Paddy Soils Collected Nationwide in 1999 and 2003.

Figure 1 Distribution of Dilute HCL Extractable As, CD, Cu, Ni, PB, and ZN Concentration in Paddy Soils Collected Nationwide in 1999 and 2003.

Table 3 Mean Contents (and Their Ranges) of As, CD, Cu, Ni, PB, ZN in Rice

Table 3 Mean Contents (and Their Ranges) of As, CD, Cu, Ni, PB, ZN in Rice

Table 9 Heavy Metal Concentrations in Mine Tailings Treated in the Lysimeter

Table 9 Heavy Metal Concentrations in Mine Tailings Treated in the Lysimeter

Table 10 Ratio of CD Speciation Concentration and Activity in Effluent of Sandy Loam Control Plot Calculated by Minteq

Table 10 Ratio of CD Speciation Concentration and Activity in Effluent of Sandy Loam Control Plot Calculated by Minteq

Table 11 Ratio (%) of Major CD Speciation Activity in Effluent from Mine Tailing Treated Plots

Table 11 Ratio (%) of Major CD Speciation Activity in Effluent from Mine Tailing Treated Plots

Table 12 Physico-Chemical Properties of Paddy Soils and Rice Collected near Closed Mines

Table 12 Physico-Chemical Properties of Paddy Soils and Rice Collected near Closed Mines

Table 13 Correlation between Physico-Chemical Properties of Paddy Soils near Closed Mines and CD in Brown Rice Harvested from the Same Fields

Table 13 Correlation between Physico-Chemical Properties of Paddy Soils near Closed Mines and CD in Brown Rice Harvested from the Same Fields

Table 14 Stepwise Multiple Regression Models Relating CD in Rice to Soil Parameters

Table 14 Stepwise Multiple Regression Models Relating CD in Rice to Soil Parameters

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