Environ Monit Assess (2016) 188:125 DOI 10.1007/s10661-016-5093-x
Ecological risk assessment of heavy metals in soils surrounding oil waste disposal areas Jianling Xu & Hanxi Wang & Yuanyuan Liu & Mengchao Ma & Tian Zhang & Xiaoxue Zheng & Meihan Zong
Received: 28 April 2015 / Accepted: 6 January 2016 # Springer International Publishing Switzerland 2016
Abstract More attention is being devoted to heavy metal pollution because heavy metals can concentrate in higher animals through the food chain, harm human health and threaten the stability of the ecological environment. In this study, the effects of heavy metals (Cu, Cr, Zn, Pb, Cd, Ni and Hg) emanating from oil waste disposal on surrounding soil in Jilin Province, China, were investigated. A potential ecological risk index was used to evaluate the damage of heavy metals and concluded that the degree of potential ecological damage of heavy metals can be ranked as follows: Hg > Cd > Pb > Cu > Ni > Cr > Zn. The average value of the potential ecological harm index (Ri) is 71.93, thereby indicating light pollution. In addition, this study researched the spatial distribution of soil heavy metals by means of ArcGIS (geographic information system) spatial analysis software. The results showed that the potential ecological risk index (R) of the large value was close to the distance from the oil waste disposal area; it is relatively between the degree of heavy metals in soil and the distance from the waste disposal area.
J. Xu (*) : H. Wang (*) : Y. Liu : M. Ma : T. Zhang : X. Zheng : M. Zong State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 130117 Changchun, People’s Republic of China e-mail: [email protected] e-mail: [email protected]
Keywords Heavy metals . Oil waste . Ecological risk assessment . ArcGIS . Spatial distribution
Introduction With the rapid development of industry and social progress, heavy metal pollution events are occurring frequently and receiving increased attention. Soil resources are scarce and deficient in China and heavy metals can easily concentrate throughout the food chain, thus seriously threatening human health (Mineev 1996; Mohammed et al. 2011). Chinese scholarly research on heavy metal pollution has mostly focused on the soil and water surrounding the tailings of mining areas, and results of this research show that a modified model of ecological risk assessment is a more effective evaluation (Dang et al. 2001). Heavy metal contents have been shown to be quite high in water systems and the pollution is very serious, with various heavy metal levels surpassing acceptable standards (Zhang et al. 2011; Meng et al. 2006). Foreign scholars began their research of heavy metal soil pollution earlier, primarily due to the inherent conflict between the benefits of industrialisation and protection of the environment. Foreign experts studied the evaporation behaviour of heavy metals in the soil primarily through the thermal desorption spectrum, as well as by examining vegetables growing in different types of soils to determine the influencing parameters of accumulated heavy metals. The results of these
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Environ Monit Assess (2016) 188:125
Page 2 of 10
Fig. 1 Plan layout of soil samples
studies showed that the concentrations of heavy metals in vegetables increased with increasing planting time (Ludwig et al. 2001; Golia et al. 2008; Pandey and Pandey 2009). To better understand the distribution of heavy metals in the soil, some foreign scholars began to use geographical spatial analysis software such as geographic information system (GIS) and ArcGIS to determine possible pollution sources and perform ecological risk assessments—with remarkable results. Purushotham et al. used GIS to analyse the soil in a region of southern India polluted by heavy metals. Their results showed that the heavy metal pollution in the region was primarily caused by human activities (Purushotham et al. 2013). Carr et al. analysed the pollution status of heavy metals in soil around an Irish stadium (converted from a dump) with a spatial analysis system; they determined that the content of heavy metals in the surface soil was high and recommended immediate action to repair the contaminated topsoil (Carr et al. 2008). Chinese scholars are gradually increasing their studies on the spatial distribution of heavy metals Table 1 Ecological risk index and classification standard of heavy metals
in soils. Fu et al. used GIS technology to study the content of heavy metals in the soil of a residential area in Hangzhou; the results showed that the soils of this area possessed differing degrees of heavy metal pollution (Fu et al. 2005). Ji et al. used GIS to analyse and evaluate the environmental quality agricultural soils in Guizhou; they found serious heavy metal pollution, with a comprehensive pollution index of 11.8 (Ji et al. 2006). A survey of present research on the content and ecological risk assessment of heavy metals in soil surrounding oil waste disposal areas shows relatively few studies. Foreign studies include the following: using composite plants such as Chromolaena odorata in pot experiments to study the bioremediation of soils suffering from the joint pollution of crude oil and heavy metals; using an equivalence-based fuzzy analysis method to establish a contaminant fate model and ecological risk assessment of heavy metals in drilling waste discharge in the Egyptian Red Sea; and using field investigation and evaluation methods to study the content of petroleum hydrocarbons and heavy metals in the soils of the Niger Delta, Nigeria (Atagana 2011; Agwa et al. 2013; Osuji and Onojake 2006). Domestic studies include using a single-factor index method to evaluate the heavy metal pollution state of soils in the Longdong oildom; using a single-factor enrichment index method to evaluate the state of heavy metal pollution by crude oil in soils at the Yanchang oilfield at three levels; using the geo-accumulation index method, based on a GIS tool, to analyse and evaluate the spatial distribution pattern and pollution levels of heavy metals in soil from a typical oil exploitation region; and using a principal-component analysis (PCA) and the Hakanson potential ecological risk index method to study the potential ecological risk level of heavy metals (Chen et al. 2011; Shan et al. 2014; Meng et al. 2012; Wang et al. 2013). Because petroleum engineering is typically a large-scale project, it is
Potential ecological risk parameter Er
Pollution ecological risk degree of single factor
Potential ecological risk index R
Degree of potential ecological risk
Er < 40
Low
R < 150
Low
40 ≤ Er < 80
Moderate
150 ≤ R < 300
Moderate
80 ≤ Er < 160
High
300 ≤ R < 600
Severe
160 ≤ Er Cd > Pb > Cu > Ni > Cr > Zn. Based on the potential ecological index, all 20 soil samples were in the low degree of contamination level for heavy metals – the average potential ecological risk index was 71.93, indicating light pollution. The experimental results showed that heavy metal contamination of soil samples 6 and 18 were higher than that of other samples; this may be because they were closer to the oilfield waste disposal area. Based on this analysis, the potential ecological risk index of soil samples that had the same distance from the contaminated areas had the same volatility.
Environ Monit Assess (2016) 188:125
Figure 9 shows the spatial distribution map of the content of heavy metals in the soil surrounding the petroleum waste disposal area. The changes in the content of heavy metals in the soil can be seen from the figure: the larger point of potential ecological risk index (R) is primarily concentrated in the upper area and the region away from oil waste disposal area was close; the smaller point of potential ecological risk index (R) is primarily distributed in the lower right and the middle right of the sampled area. The general trend of the R value was decreasing from top to bottom, thus indicating that there was some correlation between the degree of hazard of heavy metals in soil and the distance from the waste disposal area.
Conclusions 1. The measured average contents of Cu, Cr, Zn, Pb, Cd, Ni and Hg in the soil of a petroleum waste disposal area in Jilin Province were 11.51, 70.14, 52.98, 12.66, 0.06, 13.61 and 0.036 mg/kg respectively. Among these metals, the contents of Cu, Zn and Ni were no greater than the standard values of 72.34, 75.53 and 63.63 % respectively. While the levels of Cr, Pb, Cd and Hg were overweight to a certain degree, the exceeded rates of Cr and Pb were 1.23 and 1.21 times their own standard values respectively. The exceeded rates of Cd and Hg were 30 and 15 % respectively. 2. According to the potential ecological risk index of heavy metals in the soil and based on the perspective of the potential ecological risk parameters of the various metals, the Cd and Hg levels in the soil samples reached moderate pollution, whereas the levels of the other heavy metal elements were within a low degree of harm. From the perspective of total potential ecological risk index, the samples were all in the mild harm levels, with an average potential ecological risk index R of 71.93. 3. The chosen method of ecological risk assessment of heavy metals in the soil examined in this study was the potential ecological risk index; the method must determine the standard value of the soil with the soil background value as the basis and then calculate the total potential ecological risk index of heavy metals. Differences in soil background values will have an impact on the results.
Page 9 of 10 125 Acknowledgments This project was supported by the Scientific Development Program of Jilin Province (No. 20130102039JC) and the Key Scientific Research Programs of Jilin Province (No. 20140204041SF).
References Agwa, A., Leheta, H., Salem, A., & Sadiq, R. (2013). Fate of drilling waste discharges and ecological risk assessment in the Egyptian Red Sea: an aquivalence-based fuzzy analysis. Stochastic Environmental Research and Risk Assessment, 27, 169–181. Atagana, H. I. (2011). Bioremediation of co-contamination of crude oil and heavy metals in soil by phytoremediation using Chromolaena odorata (L) King & H.E. Robinson. Water, Air, and Soil Pollution, 215, 261–271. Carr, R., Zhang, C., Moles, N., & Harder, M. (2008). Identification and mapping of heavy metal pollution in soils of a sports ground in Galway City, Ireland, using a portable XRF analyser and GIS. Environmental Geochemistry and Health, 30, 45–52. Chen, L. H., Luo, X. H., & Hasi, Q. M. G. (2011). Pollute situation and correlation analysis of soil heavy metals in oil field. Journal of North University of China (Natural Science Edition), 32, 189–194 (in Chinese). Dang, Z., Liu, C. Q., & Shang, A. A. (2001). Review of the mobility and bioavailability of heavy metals in the soil contaminated by mining. Advances in Earth Sciences, 16, 86–92 (in Chinese). Fu, J. L., Zhang, M. K., & Li, R. A. (2005). GIS-assisted assessment and spatial variation of heavy metal pollution in soils of residential areas of Hangzhou city. Chinese Journal of Soil Science, 36, 575–578 (in Chinese). Golia, E. E., Dimirkou, A., & Mitsios, I. K. (2008). Levels of heavy metals pollution in different types of soil of central Greece. Bulletin of Environmental Contamination and Toxicology, 80, 206–210. Hakanson, L. (1980). An ecological risk index for aquatic pollution control: a sedimentological approach. Water Research, 14, 975–1001. Ji, Y. B., Xie, F., Tan, H., He, J. L., Wang, D. X., & Shen, C. Y. (2006). Evaluation of environment quality of agricultural soils by GIS in Guizhou. Guizhou Agricultural Sciences, 34, 15–17 (in Chinese). Jia, Z. B., Liang, T., Kinche, L. A. M., & Lv, F. W. (1997). Study on heavy metals contamination and potential ecological risk in Hong Kong rivers. Acta Scientiarum Naturalium Universitatis Pekinensis, 33, 485–492 (in Chinese). Ludwig, C., Lutz, H., Wochele, J., & Stucki, S. (2001). Studying the evaporation behavior of heavy metals by thermodesorption spectrometry. Fresenius Journal of Analytical Chemistry, 371, 1057–1062. Meng, X. X., She, Z. S., Liu, G. Q., Kang, S. L., Yu, M. Q., Wang, S. Z., Wang, Q. C., & Qi, S. H. (1985). Background values of certain metal elements in main agricultural soil of middle northeastern in China. Acta Ecologica Sinica, 5, 114–126 (in Chinese).
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Meng, D., Zhou, L. D., & Yu, C. W. (2006). Heavy metal pollution of water body and treatment. Liaoning Chemical Industry, 35, 534–536 (in Chinese). Meng, C., Li, D. F., Du, X. Y., Li, X. C., & Li, Y. (2012). Distribution rules of heavy metals in the soil of a typical oilfield based on GIS. Journal of Anhui Agricultural Sciences, 40, 9306–9310 (in Chinese). Mineev, V. G. (1996). Accumulation and transformation of heavy metals (HM) within the ‘soil-plants’ system in prolonged agrochemical trials. In C. RodriguezBarrueco (Ed.), Fertilizers and environment: proceedings of the international symposium ‘fertilizers and environment’, held in Salamanca, Spain, 26–29, September, 1994 (pp. 539–540). New York: Springer Netherlands. Mohammed, A. S., Kapri, A., & Goel, R. (2011). Heavy metal pollution: source, impact, and remedies. In M. S. Khan, A. Zaidi, R. Goel, & J. Musarrat (Eds.), Biomanagement of metal-contaminated soils (pp. 1–28). New York: Springer. Moore, J. W., & Ramamoorthy, S. (1984). Monitoring and impact assessment approaches. In J. W. Moore & S. Ramamoorthy (Eds.), Heavy metals in natural waters: applied monitoring and impact assessment (pp. 234– 246). New York: Springer. Osuji, L. C., & Onojake, C. M. (2006). Field reconnaissance and estimation of petroleum hydrocarbon and heavy metal contents of soils affected by the Ebocha-8 oil spillage in Niger Delta, Nigeria. Journal of Environmental Management, 79, 133–139.
Environ Monit Assess (2016) 188:125 Pandey, J., & Pandey, U. (2009). Accumulation of heavy metals in dietary vegetables and cultivated soil horizon in organic farming system in relation to atmospheric deposition in a seasonally dry tropical region of India. Environmental Monitoring and Assessment, 148, 61–74. Purushotham, D., Rashid, M., Lone, M. A., Rao, A. N., Ahmed, S., Nagaiah, E., & Dar, F. A. (2013). Environmental impact assessment of air and heavy metal concentration in groundwater of Maheshwaram watershed, ranga reddy district, Andhra Pradesh. Journal of the Geological Society of India, 81, 385–396. Shan, B. Q., Zhang, Y. T., Cao, Q. L., Kang, Z. Y., & Li, S. Y. (2014). Content and distribution characteristics of heavy metals in different soil layers of petroleum polluted soil in Northern Shaanxi. Environmental Pollution and Control, 36, 20–25 (in Chinese). Wang, D. Z., Hu, Y., & Li, Y. (2013). Potential ecological risk assessment of heavy metals in an onshore oilfield. Environmental Chemistry, 32, 1723–1729. Xu, S. J., Wei, S. Q., & Xie, D. T. (2003). Characteristics of heavy metals distribution in cultivated soil in Three Gorge Reservoir Area (TGRA). Journal of Soil and Water Conservation, 17, 64–66. Xu, Z. Q., Ni, S. J., Tuo, X. G., & Zhang, C. J. (2008). Calculation of heavy metals’ toxicity coefficient in the evaluation of potential ecological risk index. Environmental Science and Technology, 31, 112–115. Zhang, J. J., Jia, J. M., & Ma, Y. H. (2011). Pollution of toxic heavy metals in important water system in China. Occupation and Health, 27, 89–91 (in Chinese).
Ecological risk assessment of heavy metals in soils surrounding oil waste disposal areas Jianling Xu & Hanxi Wang & Yuanyuan Liu & Mengchao Ma & Tian Zhang & Xiaoxue Zheng & Meihan Zong
Received: 28 April 2015 / Accepted: 6 January 2016 # Springer International Publishing Switzerland 2016
Abstract More attention is being devoted to heavy metal pollution because heavy metals can concentrate in higher animals through the food chain, harm human health and threaten the stability of the ecological environment. In this study, the effects of heavy metals (Cu, Cr, Zn, Pb, Cd, Ni and Hg) emanating from oil waste disposal on surrounding soil in Jilin Province, China, were investigated. A potential ecological risk index was used to evaluate the damage of heavy metals and concluded that the degree of potential ecological damage of heavy metals can be ranked as follows: Hg > Cd > Pb > Cu > Ni > Cr > Zn. The average value of the potential ecological harm index (Ri) is 71.93, thereby indicating light pollution. In addition, this study researched the spatial distribution of soil heavy metals by means of ArcGIS (geographic information system) spatial analysis software. The results showed that the potential ecological risk index (R) of the large value was close to the distance from the oil waste disposal area; it is relatively between the degree of heavy metals in soil and the distance from the waste disposal area.
J. Xu (*) : H. Wang (*) : Y. Liu : M. Ma : T. Zhang : X. Zheng : M. Zong State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, School of Environment, Northeast Normal University, 130117 Changchun, People’s Republic of China e-mail: [email protected] e-mail: [email protected]
Keywords Heavy metals . Oil waste . Ecological risk assessment . ArcGIS . Spatial distribution
Introduction With the rapid development of industry and social progress, heavy metal pollution events are occurring frequently and receiving increased attention. Soil resources are scarce and deficient in China and heavy metals can easily concentrate throughout the food chain, thus seriously threatening human health (Mineev 1996; Mohammed et al. 2011). Chinese scholarly research on heavy metal pollution has mostly focused on the soil and water surrounding the tailings of mining areas, and results of this research show that a modified model of ecological risk assessment is a more effective evaluation (Dang et al. 2001). Heavy metal contents have been shown to be quite high in water systems and the pollution is very serious, with various heavy metal levels surpassing acceptable standards (Zhang et al. 2011; Meng et al. 2006). Foreign scholars began their research of heavy metal soil pollution earlier, primarily due to the inherent conflict between the benefits of industrialisation and protection of the environment. Foreign experts studied the evaporation behaviour of heavy metals in the soil primarily through the thermal desorption spectrum, as well as by examining vegetables growing in different types of soils to determine the influencing parameters of accumulated heavy metals. The results of these
125
Environ Monit Assess (2016) 188:125
Page 2 of 10
Fig. 1 Plan layout of soil samples
studies showed that the concentrations of heavy metals in vegetables increased with increasing planting time (Ludwig et al. 2001; Golia et al. 2008; Pandey and Pandey 2009). To better understand the distribution of heavy metals in the soil, some foreign scholars began to use geographical spatial analysis software such as geographic information system (GIS) and ArcGIS to determine possible pollution sources and perform ecological risk assessments—with remarkable results. Purushotham et al. used GIS to analyse the soil in a region of southern India polluted by heavy metals. Their results showed that the heavy metal pollution in the region was primarily caused by human activities (Purushotham et al. 2013). Carr et al. analysed the pollution status of heavy metals in soil around an Irish stadium (converted from a dump) with a spatial analysis system; they determined that the content of heavy metals in the surface soil was high and recommended immediate action to repair the contaminated topsoil (Carr et al. 2008). Chinese scholars are gradually increasing their studies on the spatial distribution of heavy metals Table 1 Ecological risk index and classification standard of heavy metals
in soils. Fu et al. used GIS technology to study the content of heavy metals in the soil of a residential area in Hangzhou; the results showed that the soils of this area possessed differing degrees of heavy metal pollution (Fu et al. 2005). Ji et al. used GIS to analyse and evaluate the environmental quality agricultural soils in Guizhou; they found serious heavy metal pollution, with a comprehensive pollution index of 11.8 (Ji et al. 2006). A survey of present research on the content and ecological risk assessment of heavy metals in soil surrounding oil waste disposal areas shows relatively few studies. Foreign studies include the following: using composite plants such as Chromolaena odorata in pot experiments to study the bioremediation of soils suffering from the joint pollution of crude oil and heavy metals; using an equivalence-based fuzzy analysis method to establish a contaminant fate model and ecological risk assessment of heavy metals in drilling waste discharge in the Egyptian Red Sea; and using field investigation and evaluation methods to study the content of petroleum hydrocarbons and heavy metals in the soils of the Niger Delta, Nigeria (Atagana 2011; Agwa et al. 2013; Osuji and Onojake 2006). Domestic studies include using a single-factor index method to evaluate the heavy metal pollution state of soils in the Longdong oildom; using a single-factor enrichment index method to evaluate the state of heavy metal pollution by crude oil in soils at the Yanchang oilfield at three levels; using the geo-accumulation index method, based on a GIS tool, to analyse and evaluate the spatial distribution pattern and pollution levels of heavy metals in soil from a typical oil exploitation region; and using a principal-component analysis (PCA) and the Hakanson potential ecological risk index method to study the potential ecological risk level of heavy metals (Chen et al. 2011; Shan et al. 2014; Meng et al. 2012; Wang et al. 2013). Because petroleum engineering is typically a large-scale project, it is
Potential ecological risk parameter Er
Pollution ecological risk degree of single factor
Potential ecological risk index R
Degree of potential ecological risk
Er < 40
Low
R < 150
Low
40 ≤ Er < 80
Moderate
150 ≤ R < 300
Moderate
80 ≤ Er < 160
High
300 ≤ R < 600
Severe
160 ≤ Er Cd > Pb > Cu > Ni > Cr > Zn. Based on the potential ecological index, all 20 soil samples were in the low degree of contamination level for heavy metals – the average potential ecological risk index was 71.93, indicating light pollution. The experimental results showed that heavy metal contamination of soil samples 6 and 18 were higher than that of other samples; this may be because they were closer to the oilfield waste disposal area. Based on this analysis, the potential ecological risk index of soil samples that had the same distance from the contaminated areas had the same volatility.
Environ Monit Assess (2016) 188:125
Figure 9 shows the spatial distribution map of the content of heavy metals in the soil surrounding the petroleum waste disposal area. The changes in the content of heavy metals in the soil can be seen from the figure: the larger point of potential ecological risk index (R) is primarily concentrated in the upper area and the region away from oil waste disposal area was close; the smaller point of potential ecological risk index (R) is primarily distributed in the lower right and the middle right of the sampled area. The general trend of the R value was decreasing from top to bottom, thus indicating that there was some correlation between the degree of hazard of heavy metals in soil and the distance from the waste disposal area.
Conclusions 1. The measured average contents of Cu, Cr, Zn, Pb, Cd, Ni and Hg in the soil of a petroleum waste disposal area in Jilin Province were 11.51, 70.14, 52.98, 12.66, 0.06, 13.61 and 0.036 mg/kg respectively. Among these metals, the contents of Cu, Zn and Ni were no greater than the standard values of 72.34, 75.53 and 63.63 % respectively. While the levels of Cr, Pb, Cd and Hg were overweight to a certain degree, the exceeded rates of Cr and Pb were 1.23 and 1.21 times their own standard values respectively. The exceeded rates of Cd and Hg were 30 and 15 % respectively. 2. According to the potential ecological risk index of heavy metals in the soil and based on the perspective of the potential ecological risk parameters of the various metals, the Cd and Hg levels in the soil samples reached moderate pollution, whereas the levels of the other heavy metal elements were within a low degree of harm. From the perspective of total potential ecological risk index, the samples were all in the mild harm levels, with an average potential ecological risk index R of 71.93. 3. The chosen method of ecological risk assessment of heavy metals in the soil examined in this study was the potential ecological risk index; the method must determine the standard value of the soil with the soil background value as the basis and then calculate the total potential ecological risk index of heavy metals. Differences in soil background values will have an impact on the results.
Page 9 of 10 125 Acknowledgments This project was supported by the Scientific Development Program of Jilin Province (No. 20130102039JC) and the Key Scientific Research Programs of Jilin Province (No. 20140204041SF).
References Agwa, A., Leheta, H., Salem, A., & Sadiq, R. (2013). Fate of drilling waste discharges and ecological risk assessment in the Egyptian Red Sea: an aquivalence-based fuzzy analysis. Stochastic Environmental Research and Risk Assessment, 27, 169–181. Atagana, H. I. (2011). Bioremediation of co-contamination of crude oil and heavy metals in soil by phytoremediation using Chromolaena odorata (L) King & H.E. Robinson. Water, Air, and Soil Pollution, 215, 261–271. Carr, R., Zhang, C., Moles, N., & Harder, M. (2008). Identification and mapping of heavy metal pollution in soils of a sports ground in Galway City, Ireland, using a portable XRF analyser and GIS. Environmental Geochemistry and Health, 30, 45–52. Chen, L. H., Luo, X. H., & Hasi, Q. M. G. (2011). Pollute situation and correlation analysis of soil heavy metals in oil field. Journal of North University of China (Natural Science Edition), 32, 189–194 (in Chinese). Dang, Z., Liu, C. Q., & Shang, A. A. (2001). Review of the mobility and bioavailability of heavy metals in the soil contaminated by mining. Advances in Earth Sciences, 16, 86–92 (in Chinese). Fu, J. L., Zhang, M. K., & Li, R. A. (2005). GIS-assisted assessment and spatial variation of heavy metal pollution in soils of residential areas of Hangzhou city. Chinese Journal of Soil Science, 36, 575–578 (in Chinese). Golia, E. E., Dimirkou, A., & Mitsios, I. K. (2008). Levels of heavy metals pollution in different types of soil of central Greece. Bulletin of Environmental Contamination and Toxicology, 80, 206–210. Hakanson, L. (1980). An ecological risk index for aquatic pollution control: a sedimentological approach. Water Research, 14, 975–1001. Ji, Y. B., Xie, F., Tan, H., He, J. L., Wang, D. X., & Shen, C. Y. (2006). Evaluation of environment quality of agricultural soils by GIS in Guizhou. Guizhou Agricultural Sciences, 34, 15–17 (in Chinese). Jia, Z. B., Liang, T., Kinche, L. A. M., & Lv, F. W. (1997). Study on heavy metals contamination and potential ecological risk in Hong Kong rivers. Acta Scientiarum Naturalium Universitatis Pekinensis, 33, 485–492 (in Chinese). Ludwig, C., Lutz, H., Wochele, J., & Stucki, S. (2001). Studying the evaporation behavior of heavy metals by thermodesorption spectrometry. Fresenius Journal of Analytical Chemistry, 371, 1057–1062. Meng, X. X., She, Z. S., Liu, G. Q., Kang, S. L., Yu, M. Q., Wang, S. Z., Wang, Q. C., & Qi, S. H. (1985). Background values of certain metal elements in main agricultural soil of middle northeastern in China. Acta Ecologica Sinica, 5, 114–126 (in Chinese).
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Meng, D., Zhou, L. D., & Yu, C. W. (2006). Heavy metal pollution of water body and treatment. Liaoning Chemical Industry, 35, 534–536 (in Chinese). Meng, C., Li, D. F., Du, X. Y., Li, X. C., & Li, Y. (2012). Distribution rules of heavy metals in the soil of a typical oilfield based on GIS. Journal of Anhui Agricultural Sciences, 40, 9306–9310 (in Chinese). Mineev, V. G. (1996). Accumulation and transformation of heavy metals (HM) within the ‘soil-plants’ system in prolonged agrochemical trials. In C. RodriguezBarrueco (Ed.), Fertilizers and environment: proceedings of the international symposium ‘fertilizers and environment’, held in Salamanca, Spain, 26–29, September, 1994 (pp. 539–540). New York: Springer Netherlands. Mohammed, A. S., Kapri, A., & Goel, R. (2011). Heavy metal pollution: source, impact, and remedies. In M. S. Khan, A. Zaidi, R. Goel, & J. Musarrat (Eds.), Biomanagement of metal-contaminated soils (pp. 1–28). New York: Springer. Moore, J. W., & Ramamoorthy, S. (1984). Monitoring and impact assessment approaches. In J. W. Moore & S. Ramamoorthy (Eds.), Heavy metals in natural waters: applied monitoring and impact assessment (pp. 234– 246). New York: Springer. Osuji, L. C., & Onojake, C. M. (2006). Field reconnaissance and estimation of petroleum hydrocarbon and heavy metal contents of soils affected by the Ebocha-8 oil spillage in Niger Delta, Nigeria. Journal of Environmental Management, 79, 133–139.
Environ Monit Assess (2016) 188:125 Pandey, J., & Pandey, U. (2009). Accumulation of heavy metals in dietary vegetables and cultivated soil horizon in organic farming system in relation to atmospheric deposition in a seasonally dry tropical region of India. Environmental Monitoring and Assessment, 148, 61–74. Purushotham, D., Rashid, M., Lone, M. A., Rao, A. N., Ahmed, S., Nagaiah, E., & Dar, F. A. (2013). Environmental impact assessment of air and heavy metal concentration in groundwater of Maheshwaram watershed, ranga reddy district, Andhra Pradesh. Journal of the Geological Society of India, 81, 385–396. Shan, B. Q., Zhang, Y. T., Cao, Q. L., Kang, Z. Y., & Li, S. Y. (2014). Content and distribution characteristics of heavy metals in different soil layers of petroleum polluted soil in Northern Shaanxi. Environmental Pollution and Control, 36, 20–25 (in Chinese). Wang, D. Z., Hu, Y., & Li, Y. (2013). Potential ecological risk assessment of heavy metals in an onshore oilfield. Environmental Chemistry, 32, 1723–1729. Xu, S. J., Wei, S. Q., & Xie, D. T. (2003). Characteristics of heavy metals distribution in cultivated soil in Three Gorge Reservoir Area (TGRA). Journal of Soil and Water Conservation, 17, 64–66. Xu, Z. Q., Ni, S. J., Tuo, X. G., & Zhang, C. J. (2008). Calculation of heavy metals’ toxicity coefficient in the evaluation of potential ecological risk index. Environmental Science and Technology, 31, 112–115. Zhang, J. J., Jia, J. M., & Ma, Y. H. (2011). Pollution of toxic heavy metals in important water system in China. Occupation and Health, 27, 89–91 (in Chinese).
