Traffic-related heavy metals uptake by wild plants ...

Environ Sci Pollut Res DOI 10.1007/s11356-016-6507-6

RESEARCH ARTICLE

Traffic-related heavy metals uptake by wild plants grow along two main highways in Hunan Province, China: effects of soil factors, accumulation ability, and biological indication potential Yunbo Zhai 1,2 & Qingyun Dai 1,2 & Kang Jiang 3 & Yun Zhu 4 & Bibo Xu 1,2 & Chuan Peng 1,2 & Tengfei Wang 1,2 & Guangming Zeng 1,2

Received: 26 January 2016 / Accepted: 17 March 2016 # Springer-Verlag Berlin Heidelberg 2016

Abstract This study was performed to investigate pollution of traffic-related heavy metals (HMs—Zn, Pb, Cu, Cr, and Cd) in roadside soils and their uptake by wild plants growing along highways in Hunan Province, China. For this, we analyzed the concentration and chemical fractionation of HMs in soils and plants. Soil samples were collected with different depths in the profile and different distances from highway edge. And leaves and barks of six high-frequency plants were collected. Results of the modified European Community Bureau of Reference (BCR) showed that the mobile fraction of these HMs was in the order of Cd > Pb > Zn > Cu > Cr. A high percentage of the mobile fraction indicates Cd, Pb, and Zn were labile and available for uptake by wild plants. The total concentration and values of risk assessment code (RAC) showed that Cd was the main risk factor, which were in the range high to very high risk. The accumulation ability of HMs in plants was evaluated by the biological accumulation factor Responsible editor: Elena Maestri * Yunbo Zhai [email protected] * Yun Zhu [email protected]

1

College of Environmental Science and Engineering, Hunan University, Changsha 410082, People’s Republic of China

2

Key Laboratory of Environmental Biology and Pollution Control (Hunan University), Ministry of Education, Changsha 410082, People’s Republic of China

3

Hunan Communications Research Institute, Changsha 410015, People’s Republic of China

4

Office of Scientific R& D, Hunan University, Changsha 410082, People’s Republic of China

(BAF) and the metal accumulation index (MAI), and the results showed that all those plant species have good phytoextraction ability, while accumulation capacity for most HMs plants tissues was bark > leaf. The highest MAI value (5.99) in Cinnamomum camphora (L) Presl indicates the potential for bio-monitoring and a good choice for planting along highways where there is contamination with HMs. Keywords Wild plants . Roadside soils . Traffic-related heavy metals . Accumulation ability . Bio-monitoring . Chemical fractions . Leaves and barks

Introduction The rapid development of highway transportation is driving the economic and social development, but the elevated inputs of heavy metals (HMs) through vehicular traffic bring many negative ecological impacts (Zhang et al. 2010). HMs, such as Pb, Zn, Cr, Cu, Cd, Ni, and Mn, are released from traffic vehicles in the form of vehicle exhaust as well as tear of automotive components (Rauret et al. 1999; Liu et al. 2007). They cannot be decomposed by micro-organisms and most of them persist for a long time in soil. The pollution of HMs in roadside soil has become the major problem in urban soil contamination (Obrador et al. 1997). In recent years, people pay increasing attention on the transfer of HMs between the soil-plant system (Liu et al. 2014; Zhan et al. 2014). Plants growing adjacent to road could directly take up these traffic-related HMs through root or other external tissues, such as leaf and bark. The ability of different plant species to accumulate HMs shows difference. Plant species can accumulate large quantities of HMs in their aboveground tissues and could be useful for phyto-extraction in soil contamination area. And species with high ability to reduce

Environ Sci Pollut Res

translocation from roots to shoots could be considered as beneficial phyto-stabilizers. Many researchers have been launched on the accumulation of HMs in various plants to investigate the contamination of HMs in plants growing along highways and to identify useful plant species for phytoremediation (Zhang et al. 2010; Guillén et al. 2012). It has been well studied that the behavior and fate of HMs in soils are depended by their total concentration, chemical fractions, and ability to bind with soil component (Monterroso et al. 2014; Aziz et al. 2015). Therefore, these factors are of great concern when assessing the short- and long-term environmental impacts. Some studies turned out that the ability of plants to accumulate HMs into their tissues not only depends on plant factor but also associated with soil factors (heavy metal’s concentration in soil and their bioavailability) (PérezLópez et al. 2008). Concentrations of HMs in plants therefore can in turn be used to monitor soil pollution. There are some examples of plants used as bio-monitor for soil pollution: the leaves of Nerium oleander L. (oleander) (Zhang and Wang 2009), Platanus orientalis L. (Sager et al. 2007), leaf and bark of P. orientalis L., and Pinus nigra Arn (Lu et al. 2003). The main objectives of this study are (1) to investigate the pollution of traffic-related HMs in roadside soils and in wild plants growing along G4 highway and G60 highway, (2) to assess the mobility and bioavailability of traffic-related HMs according to their chemical fractions, (3) to evaluate the accumulation capability of HMs by different wild plant species, and (4) to identify wild plant species that could be useful for phytoremediation and bio-monitoring.

Materials and methods Sampling area In this study, concentrations of traffic-related HMs (Pb, Cd, Zn, Cu, and Cr) in G4 highway and G60 highway roadside soils were investigated. G4 highway and G60 highway are two main highways from north-south and east-west across Hunan Province. They are also belonging to the national trunk road and played an important role in supporting the national economy and social development. According to different service years and traffic volumes, three sampling sites were selected for our investigation along G4 highway and G60 highway (Fig. 1). Linchang (LC) and Changtan (CT) belong to G4 highway. Tanshao (TS) belongs to G60 highway. The specific characteristics of selected studied sites were presented in Table 1. Sampling and preparation Both soil samples and plant samples were collected from the roadside after a few days without rain in July to September,

2014. Soil samples were collected according to different depths in the profile (0–10 cm, 10–20 cm, and 20–30 cm) and different distances from the highway’s edge (5, 10, 15, 40, and 80 m) using a core extractor with a diameter of 2.5 cm. Five replicate samples (about 500 g) from each depth intervals were taken from the vertical profile of each sampling site. Those collected soil samples were placed in polyethylene bags and taken to the laboratory, air-dried at room temperature for a week. Then air-dried soil samples were ground with mortar and pestle and sieved through a 2-mm nylon sieve to remove coarse debris and kept in polyethylene bags for analysis. And a portion of the soil samples was sieved through LC > TS. Soils with high clay content kept more exchangeable cations than those with low clay content. The contents of the organic matter ranged from 9.28 to 32.04, 9.43 to 27.21, and 4.94 to 25.37 in LC, CT, and TS, respectively. And the organic matter decreased with the increase of distance from highways. Chemical fractionation of HMs in soils Chemical species of Cd, Cr, Cu, Pb, and Zn in roadside soils according to the modified BCR sequential extraction were shown in Fig. 2. The results were usually expressed as a percentage of chemical speciation of HMs in soils. It was reported that the distribution of HMs in soils can reflect some information of anthropogenic activity’s impact on soils (Aziz et al. 2015). According to Fig. 2, on the whole, the fractionation (relative percent) of these HMs in soils did not vary significantly with depth. And different HMs had different changing situation with the increasing of distance from highways. Owing to the previously mentioned difference in soil physicochemical properties and traffic volume, there were

some discrepancies apparent on the fractions of HMs among LC, CT, and TS, especially in TS. It was well studied that the sum of the quantity in the acid soluble/exchangeable fraction (F1), reducible fraction (F2), and oxidizable fraction (F3) reflected the potential mobility and bioavailability of HMs in soil (Pérez-López et al. 2008; Zhang and Wang 2009; Guillén et al. 2012). The mobile fraction of these HMs were in the order of Cd > Pb > Zn > Cu > Cr. The high proportion of Cd (38–85 %) in the mobile fraction in the soil was of note. It was almost four to five times higher than Cr (7–35 %), while the order of the total concentrations of Cd and Cr is just the opposite. On the whole, the mobile fraction proportions of Cd were first decreasing and then increasing with the increasing of the distance from the highway’s edge. In LC and CT, Cd was extracted in large quantities during the first extraction step, in which the heavy metal was associated with carbonated phases. But surface samples taken in TS had the highest percentage of oxide-bound fraction and the lowest carbonate-bound fraction, which suggested that Cd had a preference for Fe-Mn oxides at the expense of the carbonate fractions. As we discussed above, the increase of pH was responsible for this phenomenon, owing to the high proportion in the mobile fraction, indicating Cd was labile and available for uptake by wild plants. The predominant fraction for Pb was the Fe-Mn oxide phase (12–50 %), followed by residual fraction and oxidizable fraction in TS, while in LC and CT, Pb was amply referentially associated with the residual fraction, followed by the Fe-Mn oxide phase and oxidizable fraction. Obviously, the mobile fraction proportion of Pb in TS was higher than that of LC and CT. The mobile fraction proportions of Pb in TS were decreasing with the distance from the highways’ edge. Numerous researchers turn out that the exchangeable and reducible fraction should be liable to be absorbed by plants’ root (Lu et al. 2003; Sager et al. 2007). Pb in roadside soils was principally distributed between the exchangeable and reducible fraction (almost 25–58 %), which showed a high degree of bioavailability. With the exception of Cd and Pb, the other three studied HMs (Zn, Cu, and Cr) were primarily associated with the residual fraction. Correlation analysis showed that the reducible fraction and the exchangeable fraction were significantly positively correlated with pH and CEC (Table 3). A significant negative correlation was observed between the HM content (Zn, Pb, and Cd) in exchangeable fraction and the content of clay. Presenting a percentage significant in the reducible fraction, Zn could pose a potential environmental risk if changes occur in the soils parameters (pH, CEC). Low relative percent of Cr and Cu observed in the mobile fraction (almost recovered in the residual fraction), which confirmed the low potential of ecological risk from these elements. In this study, relatively, the total concentration and the mobile fraction of Cu


Fig. 2 Heavy metals fractionation (relative percent) in three studied sites with different distance and depth

were lower than reported by other researchers (Li et al. 2001; Pagotto et al. 2001), while the low relative percent of Cr in the mobile fraction is in agreement with previous findings (Lee et al. 2005; Malandrino et al. 2011). A significant negative correlation was observed between the content of clay and Cr

bound with organic matter and sulfide, while a significant positive correlation was observed between the content of clay and Cr bound with silicate (Table 3). Owing to the low content of clay in TS, relatively high percent of the oxidizable fraction was observed in Fig. 2.

Environ Sci Pollut Res Table 3 Correlation coefficient matrix among different heavy metal fractions and soil properties in the three studied sites TC

RAC

F1

F2

F3

F4

pH

–

–

–

–

.633*

−.563*

Clay Cu

–

–

–

–

−.773**

.712**

TOM

–

–

–

–

.678**

-

Zn pH

.813**

.644**

–

.952**

–

−.609*

CEC Clay

– −.569*

.539* –

.723** –

– −.863**

– –

−.545* –

pH

–

.526*

–

.771**

–

−.719**

CEC Clay Cd

.575* –

– −.647**

– –

– −.781**

– –

– .669**

pH

–

.556*

–

.568*

–

–

CEC Clay TOM

– – −.536*

– −.589* –

– .536* –

– −.748** –

.569* – –

– – –

percent in exchangeable fraction, and reducible fraction, Cu did not show potential hazard to around environment. With the exception of the soil sample in CT at the distance of 80 m, Cr showed a low risk.

Cr

Pb

TC the total concentration, TOM the organic matter, F1 exchangeable fraction, F2 reducible fraction, F3 oxidizable fraction, F4 residual fraction *Correlation is significant at the 0.05 level (2-tailed); ** Correlation is significant at the 0.01 level (2-tailed); we only provided the correlation coefficients which were significant (*and **)

Ecological risk assessment of HMs using the risk assessment code RAC was evaluated by the percentage of the total heavy metal content that was present in the first two fractions (% F1 + F2), where binding was weak and the HMs posed a greater risk to around environment (Passos et al. 2010). The obtained RAC values of Cd, Cu, Zn, Cr, and Pb in three sampling sites with different depths and distances were sequentially presented in Fig. 3. The relative percent of HMs in the first two fractions demonstrated the potential ecological risk in the order of Cd > Pb > Zn > Cu > Cr in the three studied areas. Depending on Fig. 3, different HMs had different changing situation with the increasing of distance from highways. But, in general, values of RAC were decreasing with the increasing of depth. Pb, Zn, and Cd were the main risk factors, which were in the range from high to very high risk. However, the total concentrations of Pb and Zn in three studied sites were low, indicating that currently, the Pb and Zn concentration that could be released was low. Therefore, Pb and Zn were under the safe line. With high total concentrations and high values of RAC, Cd showed heavily contaminated in soils. A significant negative correlation was observed between RAC of Pb and the content of clay (Table 3). Low total concentration, low relative

The concentrations of HMs in wild plants HM concentrations in the studied six different species of wild plants were given in Fig. 4. The concentrations of the six studied HMs (Zn, Pb, Cu, Cr, and Cd) in wild plants varied with studied sites, plant species, and tissues. In general, the mean concentrations of HMs in bark are higher than that in leaf, indicating that the accumulation capacity for most heavy metals in selected wild plant tissues were bark > leaf. Pollutants deposited on the leaves can be washed away by rain or can be dispersed by the wind, while the structural porosity of bark retains the pollutants longer (Sawidis et al. 2011). As shown in Fig. 4, the mean concentrations of HMs in Cinnamomum camphora (L) Presl and Pinus massoniana Lamb were in order of Zn > Pb > Cu > Cr > Cd. There were small difference in the other four studied wild plants with the order of Zn > Cr > Pb > Cu > Cd. Compared with other HMs, the concentrations of Zn in those studied wild plants were higher. And Zn is an essential element for plants. The peak concentrations of Zn were present in the bark of C. camphora (L) Presl in CT (386.47 mg/kg), which was almost three times of the concentration in soil. Concentrations of Zn in normal plants are in the range of 10–150 mg/kg (Hu et al. 2014). However, the concentration of Zn in Populus euramevicana in LC (leaf, 156.39 mg/kg; bark, 229.61 mg/kg), bark of P. massoniana Lamb in CT (245.16 mg/kg), and Broussonetia papyrifera in TS (leaf, 211.73 mg/kg, 177.69 mg/kg; bark, 163.89 mg/kg, 196.34 mg/kg) exceeded 150 mg/kg and their corresponding concentration in soil, indicting that Zn, to some extent, can be accumulated by all of those wild plants. The highest mean concentration of Pb and Cd was also observed in the bark of C. camphora (L) Presl (Pb, 151.61 mg/kg; Cd, 5.90 mg/kg), followed by P. massoniana Lamb (Pb, 73.60 mg/kg; Cd, 4.5 mg/kg). Pb and Cd were neither essential nor beneficial in plants’ nutrition. And the normal concentration of Pb and Cd in plants was in the range of 0.1–41.7 mg/kg and 0.2–0.8 mg/kg, respectively (Hu et al. 2014). As for metal Pb, mean concentration in the bark of P. massoniana Lamb, C. camphora (L) Presl, and B. papyrifera were outside the normal range. It is likely that traffic emissions are responsible for increased Pb concentration in wild plant along highways. According to the discussion in chemical fractionation of HMs in soil, Cd showed very high bioavailability. Therefore, mean concentrations of Cd in most wild plants along highways exceeded the normal range. Especially in the bark of C. camphora (L) Presl, the mean concentration was almost seven times of the normal value.

Environ Sci Pollut Res Fig. 3 RAC value of the five studied heavy metals in three sampling sites with different distance and depth

Mean concentrations of Cu and Cr were in the range of 5– 58.75 mg/kg and 9.09–81.33 mg/kg, respectively. The highest concentrations of Cu and Cr were both observed in the bark of B. papyrifera, while the minimum concentrations of Cu and Cr were presented in leaf of P. massoniana Lamb in CT and LC, respectively. With low concentration in soils and low bioavailability, Cu and Cr were shown to have a low concentration in those six wild plants. The accumulation capability of HMs from soil to the wild plants The values of biological accumulation factor (BAF) and the metal accumulation index (MAI) of each wild plant species in

three studied sites are shown in Table 4. BAF refers to the ratio of HMs concentration in aerial parts of wild plants to that in soil, which can reflect the uptake ability of plants to a single heavy metal. The mean BAFs for Cd, Zn, Cu, Cr, and Pb were ranged from 0.14 to 5.84, 0.37 to 3.93, 0.30 to 2.23, 0.07 to 0.91, and 0.20 to 2.35, respectively. According to the values of BAF, the accumulation capability for wild plants along the G4 highway and G60 highway changed in the order of Cd > Zn > Pb > Cu > Cr, which was in accordance with some previous research (Zhan et al. 2014). Bark showed higher accumulation ability than leaf, which indicated bark was more suitable for applying to monitoring the contamination of HMs than leaf. As shown in Table 4, the values of MAI were in the range of 2.43–5.99, which was a little higher than Youning Hu


Fig. 4 Mean values (and standard deviation) of heavy metals concentrations (mg/kg) in the wild plants samples collected from the three studied sites

reported in Yan’an (Hu et al. 2014) but lower than Liu reported in Beijing (Liu et al. 2007). The highest MAI value presented in the bark of C. camphora (L) Presl in CT (5.99), followed in the bark of P. massoniana Lamb in LC (5.39), while the minimum MAI value was displayed in the leaf of Dalbergia hupeana Hance (2.43), indicating the former two plants have well accumulation properties in HMs. And those two plants were widespread around the world and can apparently survive under different environments. Thus, these two plants should be used more frequently as barriers between polluted and vulnerable areas, especially highways. Owing to accumulate HM efficiently, they can be used in the bioindication of HM pollution.

Conclusions The total concentrations of Cd, Cu, Pb, Cr, and Zn in roadside soils confirmed that long-term exposure to traffic caused the Table 4

contamination of the roadside soils. The modified BCR showed that Cd, Pb, and Zn were labile and available for uptake by wild plants. And in combination with the total concentration and values of RACs of the five studied HMs, Cd turning out to be the major pollution factor, which was in the range of high to very high risk. The four chemical species of the studied five HMs had different changing situation with the increasing of distance from highways. But, in general, values of RAC were decreasing with the increasing of depth. Being affected by the traffic activity, concentrations of HMs in wild plants along G4 highway and G60 highway exceeded the normal range of organisms. According to the values of BAF and MAI, all selected six wild plants showed good accumulation capacity. And the accumulation ability of wild plant tissue was bark > leaf. The highest value of MAI was present in the bark of C. camphora (L) in CT (5.99). And the values of BAF showed those C. camphora (L) have high accumulation ability for Cd. Being seriously polluted with Cd along the G4 highway and G60 highway, C. camphora (L)

Biological accumulation factor (BAF) and the metal accumulation index (MAI) of the six wild plants

Sampling sites

Linchang (LC)

Wild plants

PTLC

Tissue

Leaf Bark Leaf Bark Leaf Bark Leaf Bark Leaf Bark Leaf Bark Leaf Bark Leaf Bark Leaf Bark

Biological accumulation factor (BAF)

MAI

Cd Zn Cr Pb Cu

1.85 0.8 0.07 0.26 0.3 3.52

Changtan (CT)

PMLC

6.43 1.23 0.11 1.45 1.26 5.39

0.14 1.19 0.27 0.37 1.1 3.41

1 0.94 0.65 0.41 2.23 4.63

ALC

1.14 1.53 0.23 0.3 0.38 4.34

PTCT

3.86 2.25 0.14 0.36 0.71 5.29

2.37 0.87 0.21 0.2 0.2 3.71

Tanshao (TS)

HRCT

4.05 2.49 0.48 1.87 1.62 4.02

0.99 1.48 0.24 0.23 0.41 2.43

1.68 1.07 0.5 0.67 0.46 2.62

NTCT

1.98 1.33 0.19 0.45 0.62 3.07

1.68 1 0.4 0.46 0.49 2.75

CTCT

0.59 0.37 0.5 0.46 0.62 4.22

5.84 3.93 0.55 2.35 1.8 5.99

PMTS 1

0.17 1.45 0.37 1.06 0.48 3.04

0.33 1.13 0.91 0.61 1.01 3.68

PMTS 2

0.83 1.22 0.28 0.84 0.46 4.06

1.33 1.35 0.73 1.27 0.6 4.29


should be planted more frequently as an ecological barrier. Their high accumulation capacity also indicated their potential use in bio-monitoring. Acknowledgments This work was supported by Program for New Century Excellent Talents in University (NCET-12-0169), the progress of science and technology innovation plan launched by Department of Transportation of Hunan province (No.2014318), and the Ministry of Education Scientific Research Foundation for Returned overseas scholar (No.757210011)

References Aziz RA, Rahim SA, Sahid I, Idris WMR (2015) Speciation and availability of heavy metals on serpentinized paddy soil and paddy tissue. Procedia - Social and Behavioral Sciences 195:1658–1665. doi:10. 1016/j.sbspro.2015.06.235 Guillén MT, Delgado J, Albanese S, Nieto JM, Lima A, De Vivo B (2012) Heavy metals fractionation and multivariate statistical techniques to evaluate the environmental risk in soils of Huelva Township (SW Iberian Peninsula). J Geochem Explor 119–120: 32–43. doi:10.1016/j.gexplo.2012.06.009 Hao Q, Jiang C (2015) Heavy metal concentrations in soils and plants in Rongxi Manganese Mine of Chongqing, Southwest of China. Acta Ecologica Sinica 35:46–51. doi:10.1016/j.chnaes.2015.01.002 Hu Y, Wang D, Wei L, Zhang X, Song B (2014) Bioaccumulation of heavy metals in plant leaves from Yan an city of the Loess Plateau, China. Ecotox Environ Safe 110:82–88. doi:10.1016/j. ecoenv.2014.08.021 Lee PK, Yu YH, Yun ST, Bernhard M (2005) Metal contamination and solid phase partitioning of metals in urban roadside sediments. Chemosphere 60:672–689. doi:10.1016/j.chemosphere.2005.01. 048 Li XD, Poon CS, Liu PS (2001) Heavy metal contamination of urban soils and street dusts in Hong Kong. Appl Geochem 16:1361–1368. doi:10.1016/S0883-2927(01)00045-2 Liu Y-J, Zhu Y-G, Ding H (2007) Lead and cadmium in leaves of deciduous trees in Beijing, China: development of a metal accumulation index (MAI). Environ Pollut 145:387–390. doi:10.1016/j.envpol. 2006.05.010 Liu J, Zhang X-h, Li T-y, Wu Q-x, Jin Z-j (2014) Soil characteristics and heavy metal accumulation by native plants in a Mn mining area of Guangxi, South China. Environ Monit Assess 186:2269–2279. doi: 10.1007/s10661-013-3535-2 Lu Y, Gong Z, Zhang G, Burghardt W (2003) Concentrations and chemical speciations of Cu, Zn, Pb and Cr of urban soils in Nanjing, China. Geoderma 115:101–111. doi:10.1016/S0016-7061(03) 00079-X Malandrino M, Abollino O, Buoso S, Giacomino A, La Gioia C, Mentasti E (2011) Accumulation of heavy metals from contaminated soil to plants and evaluation of soil remediation by vermiculite. Chemosphere 82:169–178. doi:10.1016/j.chemosphere.2010.10. 028 Monterroso C, Rodríguez F, Chaves R, Diez J, Becerra-Castro C, Kidd PS, Macías F (2014) Heavy metal distribution in mine-soils and plants growing in a Pb/Zn-mining area in NW Spain. Appl Geochem 44:3–11. doi:10.1016/j.apgeochem.2013.09.001 Nemati K, Bakar NKA, Abas MR, Sobhanzadeh E (2011) Speciation of heavy metals by modified BCR sequential extraction procedure in

different depths of sediments from Sungai Buloh, Selangor, Malaysia. J Hazard Mater 192:402–410. doi:10.1016/j.jhazmat. 2011.05.039 Obrador A, Rico MI, Mingot JI, Alvarez JM (1997) Metal mobility and potential bioavailability in organic matter-rich soil-sludge mixtures: effect of soil type and contact time. Sci Total Environ 206:117–126. doi:10.1016/S0048-9697(97)80003-4 Okedeyi O, Dube S, Awofolu O, Nindi M (2014) Assessing the enrichment of heavy metals in surface soil and plant (Digitaria eriantha) around coal-fired power plants in South Africa. Environ Sci Pollut R 21:4686–4696. doi:10.1007/s11356-013-2432-0 Pagotto C, Rémy N, Legret M, Le Cloirec P (2001) Heavy metal pollution of road dust and roadside soil near a major rural highway. Environ Technol 22:307–319. doi:10.1080/09593332208618280 Passos EA, Alves JC, dos Santos IS, Alves JPH, Garcia CAB, Spinola Costa AC (2010) Assessment of trace metals contamination in estuarine sediments using a sequential extraction technique and principal component analysis. Microchem J 96:50–57. doi:10.1016/j.microc. 2010.01.018 Pérez-López R, Álvarez-Valero AM, Nieto JM, Sáez R, Matos JX (2008) Use of sequential extraction procedure for assessing the environmental impact at regional scale of the São Domingos Mine (Iberian Pyrite Belt). Appl Geochem 23:3452–3463. doi:10.1016/j. apgeochem.2008.08.005 Rauret GF, Lopez-Sanchez J, Sahuquillo A, Rubio R, Davidson CU A, Quevauviller P (1999) Improvement of the BCR three step sequential extraction procedure prior to the certification of new sediment and soil reference materials. J Environ Monitor 1:57–61. doi:10. 1039/A807854H Sager M, Park J, Chon H (2007) The effect of soil bacteria and perlite on plant growth and soil properties in metal contaminated samples. Water Air Soil Pollut 179:265–281. doi:10.1007/s11270-0069230-y Sawidis T, Breuste J, Mitrovic M, Pavlovic P, Tsigaridas K (2011) Trees as bioindicator of heavy metal pollution in three European cities. Environ Pollut 159:3560–3570. doi:10.1016/j.envpol.2011.08.008 Xiao R, Bai J, Lu Q, Zhao Q, Gao Z, Wen X, Liu X (2015) Fractionation, transfer, and ecological risks of heavy metals in riparian and ditch wetlands across a 100-year chronosequence of reclamation in an estuary of China. Sci Total Environ 517:66–75. doi:10.1016/j. scitotenv.2015.02.052 Zhai YB, Chen HM, Xu BB, Xiang BB, Chen Z, Li CT, Zeng GM (2014) Influence of sewage sludge-based activated carbon and temperature on the liquefaction of sewage sludge: yield and composition of biooil, immobilization and risk assessment of heavy metals. Bioresource Technol 159:72–79. doi:10.1016/j.biortech.2014.02. 049 Zhan H, Jiang Y, Yuan J, Hu X, Nartey OD, Wang B (2014) Trace metal pollution in soil and wild plants from lead–zinc smelting areas in Huixian County, Northwest China. J Geochem Explor 147(Part B): 182–188. doi:10.1016/j.gexplo.2014.10.007 Zhang GL, Gong ZT (2012) Laboratory analysis method for Soil investigation. Science press, Beijing Zhang M, Wang H (2009) Concentrations and chemical forms of potentially toxic metals in road-deposited sediments from different zones of Hangzhou, China. J Environ Sci 21:625–631. doi:10.1016/ S1001-0742(08)62317-7 Zhang Y, Li D, Zhang Z, Liao K (2010) A comparison study of two methods for mensuration of soil cation exchange capacity. Guizhou Forestry Science and Technology 38:45–49