Monitoring of heavy metal levels in the major rivers ...

Environ Sci Pollut Res DOI 10.1007/s11356-016-6287-z

RESEARCH ARTICLE

Monitoring of heavy metal levels in the major rivers and in residents’ blood in Zhenjiang City, China, and assessment of heavy metal elimination via urine and sweat in humans Jianguo Sheng 1 & Wenhui Qiu 2,3 & Bentuo Xu 2 & Hui Xu 1 & Chong Tang 1

Received: 24 July 2015 / Accepted: 14 February 2016 # Springer-Verlag Berlin Heidelberg 2016

Electronic supplementary material The online version of this article (doi:10.1007/s11356-016-6287-z) contains supplementary material, which is available to authorized users.

Zhenjiang. The results suggest that the presence of heavy metals in the blood may threaten human health and the distribution appeared to correspond to most highly populated areas and/or areas with high traffic. We also found that the concentration of heavy metals in human blood showed an accumulation effect with increase in age. Moreover, the levels of most heavy metals were lower in participants who regularly exercised than in those who did not. We studied heavy metal levels in the urine and sweat of another 17 volunteers to monitor the elimination of bioaccumulated heavy metal. Heavy metals were found in the urine and sweat of all the 17 participants and were more concentrated in sweat. Induced micturition and sweating appear to be potential methods for the elimination of heavy metals from the human body.

* Wenhui Qiu [email protected]

Keywords Heavy metal . River . Human blood . Urine and sweat . Elimination

Abstract The coastal areas of China face great challenges, owing to heavy metal contamination caused by rapid industrialization and urbanization. To our knowledge, this study is the first report of the levels of heavy metals in the major rivers of Zhenjiang, one of the most important cities of the Yangtze River Delta in China. In addition, we measured heavy metal levels in the blood of 76 residents of

Responsible editor: Philippe Garrigues Jianguo Sheng and Wenhui Qiu contributed equally to this work.

Jianguo Sheng [email protected] Bentuo Xu [email protected] Hui Xu [email protected] Chong Tang [email protected]

1

Institute of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China

2

School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China

3

Department of Physiology, David Geffen School of Medicine at UCLA, 53-231 CHS, Physiology 650 Charles E Young DR S, Los Angeles, CA 90095, USA

Introduction Heavy metal pollution is one of the environmental crises that accompany the rapid economic development in many countries. Heavy metal contamination, especially in water environments, has been of great concern because of the inherent toxicity, persistence, and nondegradability (Wang et al. 2013). As reported, the concentration of heavy metals in water, sludge, and biological tissues of aquatic organisms has ranged from ng to μg/L (Karadede and Unlu 2000; Muhammad et al. 2011; Hosseini et al. 2012). With the increasing use of mining and smelting in the petrochemical industry, agriculture, aquaculture, printing, and the electronic industry, the types of heavy metal contamination have

Environ Sci Pollut Res

increased, and the resulting pollution has become more serious. More importantly, human health is ultimately affected by heavy metal pollution (Kampa and Castanas 2008; Rainbow and Luoma 2011). As shown in a previous study, the concentration of heavy metals in human blood samples collected from individuals in the polluted areas was significantly higher than in samples from the unpolluted area (Jan et al. 2011). Therefore, better understanding of the current pollution status of heavy metals is significant for public health and the sustainable development of ecosystems. Many studies have shown that human body could metabolize parts of heavy metals after intake and eliminate them in feces, urine, sweat, and saliva to protect from the harmful effects of heavy metals (Omokhodion and Crockford 1991; Gil et al. 2011). Studies about arsenic and modulation of arsenic species have shown that the increasing chronic exposure to inorganic arsenic via drinking water could result in increased urinary excretion of arsenic, which suggested that arsenic would be partly excreted in human urine (Aposhian et al. 2000). Genuis et al. (2011b) also pointed out that many toxic elements including heavy metal appeared to be preferentially excreted through sweat and also suggested that induced sweating appears to be a potential method for elimination. Thus, drinking more water and exercising can increase excretion of heavy metals through sweat and urine. Owing to the rapid development of the economy and industry in the past decades, China is expected to become a large heavy metal manufacturer and consumer, thereby becoming one of the countries most affected by heavy metal pollution (Li et al. 2014; Deng et al. 2010; Abdel-Baki et al. 2013). Zhenjiang, Jiangsu province is one of the most important cities of the Yangtze River Delta economic circle in east China. The present study was carried out to determine the levels of some heavy metals including lead (Pb), zinc (Zn), cadmium (Cd), cobalt (Co), nickel (Ni), and copper (Cu) in the major rivers of Zhenjiang City. In addition, the concentrations of heavy metals in the blood of 76 residents in Zhenjiang have also been studied. We analyzed the blood data according to participants’ settlement, age, and physical status (active or inactive) to determine the probable reasons for high level of heavy metals in human blood. In addition, another 17 volunteers’ urine and sweat were analyzed to monitor the elimination of bioaccumulated heavy metal elements. Our results, hereby, present the preliminary data on heavy metal concentration in the river and the blood of residents of Zhenjiang City. This will help us understand the state of heavy metal pollution in Zhenjiang and the threats that it imposes to human health.

Materials and methods Sample collection Water samples Water samples from three major rivers of Zhenjiang, Jiangsu, were collected in polyethylene bottles at 14 sites in March 2014 (Yunliang River, 5 sites; Ancient Canal, 7 sites; Hongqiao Harbor, 2 sites). Locations from which the samples were obtained and other information about the samples have been shown in Fig. 1. Water samples were collected according to the standard procedure described by Dwaf (1992). The samples were collected from a depth of 1 ft below the surface by using a Nansen-type water sampler and were kept cooled en route to the laboratory. Then, the samples were filtered through 0.45-mm millipore filter paper and stored at 4 °C until analyzed. Treatment and analysis of samples usually happened within 24 h of collection. Blood samples A total of 76 healthy people were selected at random (age range, 10 to 57 years; mean age, 37 years) based on data of a physical examination conducted at the hospital affiliated to Jiangsu University. Heavy metal concentration data was directly provided by the laboratory department of the hospital, which was approved by the ethics committee of the hospital (see the Supplementary Material). The heavy metal concentration in blood was measured following the standard protocols of the hospital (Shi et al. 2010). Briefly, all blood samples were collected at the hospital in single-use containers coated with heparin (Shanghai Medical Equipment Works Co. Ltd., Shanghai, China). Whole blood (200 μL) was digested with 400 μL of HNO3 (65 %) using a microwave digestion system for 60 min and diluted to 5 ml with deionized water. Then, the concentration of heavy metals in samples was determined by inductively coupled plasma mass spectrometry (ICP-MS, Agilent Technologies, Tokyo, Japan). All participants provided informed consent to participate in the study under the specified conditions. We analyzed the blood data according to the participants’ settlement, age, and physical activity status. The participants were divided into 16 area categories according to their place of residence in Zhenjiang (from N1W1 to N4W4), as shown in Fig. 1, to better analyze the distribution of heavy metals. Then, we analyzed the blood data according to the participants’ age groups: 10–19 years (10s, n = 8), 20–29 years (20s, n = 15), 30–39 years (30s, n = 21), 40–49 years (40s, n = 18), and 50–59 years (50s, n = 14). The data were also analyzed according to participants’ physical


Fig. 1 Sampling location in major rivers of Zhenjiang City and heavy metal concentrations in blood of residents from different regions of Zhenjiang City. Zhenjiang City area is divided into 16 regions from N1W1 to N4W4 and all participants fall into 16 areas according to their

residence. N represents the number of participants in a region. Scale bar = 1 km. Data are presented as means of participants’ level in a region (μg/L). All participants have resided in the study areas for at least 5 years

activity status, i.e., active (n = 34) or inactive (n = 42), on the basis of weekly exercise hours: active = exercise for at least 10 h per week; inactive = exercise for less than 10 h per week. All participants had lived in the study areas for at least 5 years.

Reagents

Urine and sweat samples Urine and sweat samples were collected according to the procedure described by Genuis et al. (2011b). A total of 17 participants were instructed to collect the first voided urine sample directly into a provided 200-mL glass jar. Urine samples were delivered by the participants directly to our laboratory. Urine samples were transferred to 10-mL glass vials with a lid and stored in a freezer at −20 °C until analyzed. For sweat collection, the participants were instructed to collect sweat samples on the same day as that on which the urine samples were collected. The participants collected perspiration from any site on their body directly into the provided glass bottle with a cover during and immediately after exercising. All participants provided more than 20 ml of sweat. No specific instruction was given regarding the type or location of exercise. Sweat samples were transferred to 50-mL glass vials with a lid and stored in a freezer at −20 °C until analyzed.

All chemicals used in this study were of analytical grade from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). All solutions are prepared using double-distilled water (DDW). All the glassware were soaked in nitric acid for 15 min and rinsed with deionized water before use. Measurement of the environmental parameters The water samples were assessed for the following environmental parameters according to the method described by Akcay et al. (2003): total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), biochemical oxygen demand (BOD5), and total organic carbon (TOC). Sample preparation Water, urine, and sweat samples were prepared by modifying the method described by Tüzen (2003) and Zhang et al. (2013). All the samples were dried at 105 °C for 24 h in the oven until a constant weight was achieved. Then, the samples were placed in muffle furnace (Shanghai Linpin Instrument


Stock Co., LTD, Shanghai, China) to remove organic matter with a slow increase in temperature from room temperature to 500 °C. The samples were ashed for approximately 24 h until a white or gray ash residue was obtained. After being cooled to room temperature in the dryer, the residue was added to 5 ml of HNO3 (25 % v/v) and heated slowly to dissolve the residue. The solution was transferred to a 25-ml volumetric flask and made up to volume. The supernatant was used to detect the concentration of heavy metals.

Table 2 The comparison of our method, wet ashing, and microwave digestion methods on the recovery of heavy metals Recovery in our method (%)

Recovery in the method of wet ashing (%)

Recovery in the method of microwave digestion (%)

Pb

90–105

72–113

87–127

Zn Cd

82–115 81–120

79–107 81–113

89–134 78–115

Co Ni

85–118 93–123

79–99 81–131

88–135 75–125

Instrumental analysis Determinations of the samples were carried out using a flame atomic absorption spectrophotometer (AA370MC AAS, INESA) according to the method described in a previous study (Tokalioǧlu et al. 2000). The airflow rate was 5.5 L min−1 and the acetylene flow was 1.5 L min−1. The instrument settings for the analysis of trace elements are described in Table 1.

Quality assurance/quality control The blank solution was DDW and was prepared in the same manner as the experimental samples. All experiments were performed in triplicate. Good linearity was obtained from the calibration curves prepared from each metal standard. The limit of detection (LOD) for individual heavy metals was in the range of 0.01–2.86 μg/L, as shown in Table 1. Also, the recovery in our method ranged from 81 to 23 %, as shown in Table 2, indicating that the method was satisfactory and reproducible for analysis of the present samples. Moreover, we evaluated the other two methods including wet ashing and microwave digestion as reported by Tüzen (2003) in our laboratory. As shown in Table 2, the comparison of our method, wet ashing, and microwave digestion methods showed no statistically significant differences in results and recovery (these were consistent with the results of Tüzen 2003).

Table 1

Instrument test parameters

Parameters

Co

Pb

Cd

Cu

Ni

Zn

Wavelength (nm) Lamp current (mA) Slit (nm) Air Compressor (MPa) Acetylene bottle (MPa) Determination of delay (s) limit of detection (μg/L)

240.7 6.0 0.4 0.3 1.6 2 0.015

283.3 12 0.7 0.3 1.6 2 0.123

228.8 2.0 0.2 0.3 1.6 2 0.04

324.8 5.0 0.7 0.3 1.6 2 2.1

232.0 3.0 0.2 0.3 1.6 2 0.01

213.9 6.5 1.3 0.3 1.6 2 2.86

Statistical analysis Data are presented as mean values for triplicate experiments. The mean, median, SD, and skewness were analyzed using Microsoft Excel 2010 (Microsoft Corp., Redmond, WA, USA). The correlations between the measured parameters were analyzed using Spearman’s test and the level for statistical significance was set at p < 0.05, indicated by an asterisk. Statistical analyses were performed using SPSS 18.0 software (SPSS, Inc., Chicago, IL, USA).

Results and discussion Concentration levels of heavy metals in the river The spatial distribution of heavy metal in the major rivers of Zhenjiang, Jiangsu, China is shown in Fig. 1 and Table 3. Heavy metals including Pb, Zn, Cd, Co, Ni, and Cu were detected in all water samples. There was an obvious difference in the concentration of different kinds of heavy metal. The levels of Pb ranged from 4.23 to 12.68 μg/L, and its average concentration in all samples was around 7.97 μg/L. The level of Zn and Cu ranged from 13.70 to 84.36 μg/L and from 22.08 to 61.11 μg/L, respectively, which were relatively higher than that of the other heavy metals detected in this river. Moreover, the average concentrations of Cd, Co, and Ni were 4.26, 1.69, and 1.16 μg/L, respectively. According to Drinking Water Contaminants in the US Environmental Protection Agency (USEPA), the concentrations of Pb and Cu were within the safe limit for both drinking as well as farming purposes but the concentrations of Cd exceeded the maximum contaminant level described by the USEPA for drinking water (0.005 mg/ L for Cd). To the best of our knowledge, this is the first report on heavy metals in the river water in Zhenjiang City. We also evaluated the heavy metal content of rainwater and found the concentration of Pb, Zn, Cd, Co, Ni, and Cu to be 2.23,

83.21 32.46 30.57

75.27

5.53 6.43

4.23 12.68 11.75

12.34 6.78 8.25

12.65

7.16 7.97

6.97 3.05 0.72

A5 A6

A7 Y1 Y2

Y3 Y4 Y5

H1

H2 Mean

Median SD Skewness

4.05 0.91 0.84

3.36 4.26

4.79

5.96 4.12 3.52

3.19 5.73 5.54

3.44 4.15

3.94 4.31 3.97

3.62

Cd (μg/L)

1.73 0.15 −1.74

1.77 1.69

1.89

1.68 1.74 1.72

1.26 1.76 1.73

1.65 1.78

1.62 1.85 1.66

1.55

Co (μg/L)

0.90 0.40 0.70

0.85 1.16

1.69

1.71 0.85 0.82

N.D. 1.76 1.68

0.87 0.89

0.93 1.24 0.91

0.87

Ni (μg/L)

27.85 14.19 0.90

25.36 35.32

61.11

51.68 27.58 28.12

24.12 56.77 53.86

22.08 26.43

30.92 38.58 23.92

23.92

Cu (μg/L)

208.50 194.92 2.82

241 263.00

284

167 125 208

187 198 209

204 143

329 915 236

236

TSS (mg/L)

3.05 1.65 0.02

3.174 3.29

2.874

4.892 1.084 2.628

3.875 2.980 3.012

3.082 5.878

0.643 1.192 5.372

5.372

TN (mg/L)

2.05 0.58 −0.05

2.140 1.87

2.109

2.145 1.498 1.876

2.847 2.681 1.981

1.133 1.043

1.193 1.145 2.178

2.178

TP (mg/L)

122.30 31.53 0.32

120.6 124.83

142.7

89.7 92.1 113.0

103.9 115.8 132.0

72.8 168.0

180.3 168.7 124.0

124.0

COD (mg/L)

44.92 23.56 0.61

30.74 49.01

52.82

49.01 67.91 78.24

40.82 24.20 29.83

24.6 91.61

57.08 83.94 27.67

27.67

BOD5 (mg/L)

N.D. not determined, TSS total suspended solids, TN total nitrogen, TP total phosphorus, COD chemical oxygen demand, BOD biochemical oxygen demand, TOC total organic carbon

31.25 25.25 0.80

27.42 42.66

31.92 84.36 73.15

28.87 49.32

23.18 13.70 21.92

5.57 7.19 5.76

21.92

5.22

Zn (μg/L)

A2 A3 A4

Pb (μg/L)

The concentration of heavy mental and the environmental parameters in river samples

A1

Table 3

15.22 9.96 1.17

14.11 19.55

26.74

35.24 16.72 18.34

13.24 15.21 32.73

11.27 40.46

11.34 15.23 11.50

11.50

TOC (mg/L)



18.55, ND (no detection), 0.13, ND, and 8.67 μg/L, respectively. Almost all the samples of river water had higher levels of heavy metals than rainwater, which shows that heavy metals are ubiquitous environmental contaminants in this area. Overall, the highest mean concentration of heavy metals was observed in the Yunliang River, followed by Hongqiao Harbor and Ancient Canal. Distribution of heavy metals appears to correspond to Zhangjiang’s industrialized areas and location of garbage treatment station. Moreover, the flow of the Yangtze River might transfer the pollutants in the Ancient Canal, resulting in lower heavy metal content in the Ancient Canal than in the other two rivers. We also analyzed the content of total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), biochemical oxygen demand (BOD), and total organic carb (TOC) in the water samples at the same time (as shown in Table 3). The correlation between measured parameters and heavy metal content in river was analyzed using the Spearman’s test (Table 4). Significantly positive correlations were observed between most heavy metals and TOC contents (p < 0.05), suggesting that TOC played an important role in the transport and distribution of heavy metals in water, which was consistent with a previous study on surface sediments (Bai et al. 2011). Interestingly, as shown in Table 4, significantly positive correlations were reported among the concentration of heavy metal elements. It is possible that there is a close correlation between pollution due to each heavy metal. In particular, a high correlation was reported in the present study between Cu and Pb levels (correlation coefficient of 0.862) in the river environment. Although there is variability in analytic methods, sample sizes, and geographical position, the levels of heavy metal

Table 4

Pb Zn Cd Co Ni Cu TSS TN TP COD BOD5 TOC

(including Pb, Zn, Cd, Co, Ni, and Cu) in river water samples used in this study do not differ significantly from those reported in other studies (Table 5). When these sites in Zhenjiang were compared with other regions worldwide, it was found that the levels of heavy metal in our study were lower than those in India and South Africa (Kar et al. 2008; Begum et al. 2009) and were similar to those found in Menderes River in Turkey between 2000 and 2002 (Turgut 2003). However, the levels of some heavy metal, such as Cu, were higher than those reported in West Bengal (Kar et al. 2008). The levels of Zn, Pb, and Cd reported in our study were lower than those in the Lanzhou section of the Yellow River (Wang et al. 2010) and the water of subsidence pools in Huainan coal field, China (Wang et al. 2015), but slightly higher than the levels in Tianjin Bohai Bay, China in 2008 (Wei et al. 2008). In general, a relatively low heavy metal level was reported in our study compared to that reported worldwide. Moreover, the heavy metal contents in river or lake water were generally low worldwide, generally in ng/L and μg/L (Begum et al. 2009). Reports on heavy metal content in the river water are fewer than those for sediment and soil. However, the research on heavy metals content in the river water is important because of the direct intake by animals and humans and use in agriculture and various industries. Further studies are required to evaluate heavy metal pollution of the river water. Concentration levels of heavy metal in human blood The levels of heavy metals in the blood from 76 residents in Zhenjiang have been examined and classified according to their settlement, as shown in Fig. 1 and Table 6. The concentrations of Pb in every area varied from 43.21 to 77.26 μg/L

Correlation analysis of measured parameters in rivers Pb

Zn

Cd

Co

Ni

Cu

TSS

TN

TP

COD

BOD5

TOC

1.000 0.648* 0.758* 0.697* 0.579* 0.862* 0.026 −0.295 0.053 0.053 0.079 0.656*

1.000 0.574* 0.290 0.481 0.608* −0.581* 0.220 0.176 −0.304 −0.066 0.634*

1.000 0.495 0.860* 0.777* −0.099 −0.090 −0.015 0.213 0.068 0.627*

1.000 0.220 0.568* 0.136 −0.224 −0.343 0.352 0.405 0.612*

1.000 0.730* 0.114 −0.007 0.316 0.261 −0.241 0.266

1.000 0.137 −0.485 0.013 0.308 0.238 0.608*

1.000 −0.313 −0.053 0.648* −0.013 −0.361

1.000 0.330 −0.150 −0.313 0.070

1.000 −0.278 −0.577* −0.163

1.000 0.374 0.093

1.000 0.524*

1.000

TSS total suspended solids, TN total nitrogen, TP total phosphorus, COD chemical oxygen demand, BOD5 biochemical oxygen demand, TOC total organic carbon *p < 0.05 according to Spearman’s test

0.08–0.19

N.D.–1.76 22.08–61.11 1.6–4.10

3.19–5.96 1.26–1.89

4.23–12.68 3.63–12.65 13.70–84.36 3.0–55.0

50–5250 30–1120

N.D.–2230

80–9950 N.D.–10700

Range

5–53 2–8

N.D.–84

3–97 4–111

Range

Begum et al. (2009) Kar et al. (2008) Ganga river in West Cauvery River in Bengal India

11–15.4 25–220

N.D. N.D.

N.D. 64–197

Range

Awofolu et al.(2005) Tyume River in South Africa.

0.209–1.265

N.D.–1.77 212.5–285.85

In 2002

NS NS NS

NS NS NS

Pb Zn Cd

Co Ni Cu

0.17 1.96 1216

60.35 4357 0.04

N1W2

NS NS NS

NS NS NS

N1W3

0.29 0.73 1420

51.22 3425 0.02

N1W4

0.08 1.71 1043

57.29 3456 0.03

N2W1

0.18 1.80 1119

77.26 6424 0.04

N2W2

0.19 1.85 957

72.32 3478 0.03

N2W3

0.31 1.21 1598

61.28 5563 0.03

N2W4

0.20 1.12 881

53.36 3537 0.03

N3W1

0.21 1.88 1583

65.29 7425 0.03

N3W2

0.18 2.03 1689

66.23 4418 0.02

N3W3

0.06 1.75 878

57.27 3407 0.02

N3W4

0.18 1.69 1093

43.21 4489 0.04

N4W1

0.36 2.15 1594

50.31 3501 0.03

N4W2

3.51–4.62 1.49–2.7 10.12–15.18 10.63–14.37

N.D.–10

1.13–1.73 N.D.

In 2000

Turgut (2003) Kucuk Menderes River in Turkey

The concentration of heavy metal in the blood of residents, the space was divided 16 regions according to the people’s living positions (μg/L)

N1W1

Table 6

Ni 1.16 0.90 Cu 35.32 39.52

4.05 1.73

7.97 6.97 42.66 31.25

Range

Mean Median Range

Cd 4.26 Co 1.69

Pb Zn

Wei et al.(2008) Tianjin Bohai Bay, China

Heavy metals concentrations (μg/L) in river water: Comparison with recently published data

This study The main rivers of Zhengjiang city in China

Table 5

0.17 0.76 895

57.32 4464 0.02

N4W3

0.28 1.73 884

44.26 6486 0.04

N4W4

11–15.4 25–220

N.D. N.D.

N.D. 64–197

0.20 1.60 1204

58.36 4602 0.03

Mean

Karadede and Unlu.(2000) Ataturk Dam Lake water in Turkey Range



(mean 58.36 μg/L), and the highest level was detected in the area of N2W2. In our study, the levels of Pb in the blood were much higher than that reported by Genuis et al. (ranged from 0.44 to 0.98 μg/L) (2011b), but similar to the study by Institut National de Santé Publique du Québec on 2004 (the mean concentration of Pb in 471 healthy adults was 20.7 μg/L) (LeBlanc 2004). Zinc concentrations in the blood ranged from 3407 to 7425 μg/L (mean 4602 μg/L), more than 1000-fold higher than that reported in Pakistani (Pasha et al. 2010) but still within the normal range of China (Wang et al. 2012). The levels of Cd ranged from 0.02 to 0.04 μg/L (mean 0.03 μg/L) and were similar to the other results reported worldwide (Genuis et al. 2011b) but were much lower than the levels in the critically polluted industrial areas in China. The mean level of Cd found in children’s blood was 8.51 μg/L around the largest coking area in China (the south of Shanxi Province) (Cao et al. 2014). We also evaluated the toxic heavy metals Co (ranged from 0.08 to 0.31 μg/L), Ni (ranged from 0.73 to 2.15 μg/L), and Cu (ranged from 878 to 1689 μg/L) and the means were 0.2, 1.6, and 1204 μg/L, respectively. The results obtained in our study were in agreement with previous data that presented the levels of heavy metals in the blood of individuals residing in France (Goulle et al. 2005), Switzerland (Forrer et al. 2001), South Africa (Rollin et al. 2009), and Alberta Canada (Gabos et al. 2008). Moreover, compared with the heavy metal concentration in human blood in our country (Wang et al. 2012), the levels of Cu reported in our study were 2-fold higher than that in the blood of healthy males from the regions

Fig. 2 The content of heavy metals including lead (Pb), zinc (Zn), cadmium (Cd), cobalt (Co), nickel (Ni), and copper (Cu) in the blood of participants according to age division. The participants’ age was divided into 5 groups including 10–19 years (10s, n = 8), 20–29 years (20s, n = 15), 30–39 years (30s, n = 21), 40– 49 years (40s, n = 18), and 50– 59 years (50s, n = 14). n represents the number of participants in a group. Data are presented as means of participants’ level in a group

of Beijing, China; however, the levels of Cd were much lower in our study. These results suggested that the content of heavy metals in the human body has a great correlation with the geographical location. In Zhenjiang, the area comprising N2W2, N2W3, N3W2, and N3W3 is the downtown of the city, has the most developed transportation, and is densely populated. As shown in Fig. 1 and Table 6, individuals residing in several regions of N2W2, N2W3, N2W3, and N3W3 had high levels of heavy metals, and the mean value was (Pb, 70.275 μg/L; Zn, 5436.25 μg/L; Cd, 0.03 μg/L; Co, 0.19 μg/L; Ni, 1.89 μg/L; Cu, 1337 μg/L) obviously higher than that reported in the other regions; in particular, accumulation of Pb, the main ingredient in automobile exhaust is a cause of great concern. Distribution appears to correspond to Zhangjiang’s most highly populated and/or traffic areas, indicating that one of the reasons of high levels of heavy metals in human blood is the emissions from automobile exhaust. The hypothesis is very similar to previous research (Fergusson 1986). We also classified the sampling population (n = 76) according to age (10–19 years (10s), n = 8; 20–29 years (20s), n = 15; 30–39 years (30s), n = 21; 40–49 years (40s), n = 18; and 50– 59 years (50s), n = 14 and found that the concentration of heavy metals in human blood has a cumulative effect at increasing age, as shown in Fig. 2. Consistent with our results, a significant increase in heavy metal concentration with age was found in the kidneys of European moles by Gunter and Komarnicki (2000), and another study found that individuals aged