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Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China
International Biodeterioration & Biodegradation xxx (2017) 1e7
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Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China Kuangjia Li a, Yansheng Gu b, c, *, Manzhou Li d, Lin Zhao a, Junjie Ding c, Zijian Lun c, Wen Tian c a
School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, PR China State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, PR China School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China d Department of Land and Resources of Henan Province, Zhengzhou 450000, PR China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 13 June 2016 Received in revised form 28 March 2017 Accepted 29 March 2017 Available online xxx
The purpose of this study is to investigate the heavy metal (HM) concentration of the gangue and HM pollution of the soil in a coal mining area. On the basis of determination of the concentrations of cadmium (Cd), lead (Pb), copper (Cu), zinc (Zn) and chromium (Cr) in the samples from the gangue and surface soils, the spatial distribution of toxic metals, contamination sources, potential ecological risks, potential health risks were studied. The content of Cd, Pb, Cu and Zn in the surface soils exceeded China National Standard (CNS, GB15618-1995). The spatial distributions of Cd, Pb, Cu and Zn are similar, exhibiting a declining trend from the gangue dump to the surrounding farmland. Results of Pearson correlation matrix and principal component analysis indicate that the origin of Cd, Pb, Cu and Zn elements is the gangue dump. The potential ecological risk index ranges from 97.2 to 619.5, and its spatial distribution is similar to those of Cd, Pb, Cu and Zn. Our results indicate that the HMs exceeded the corresponding CNS and posed noticeable ecological risks, which suggest that monitor and remediation measures should be taken in order to protect the health of the residents and the safety of the crops. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Coal gangue waste Heavy metals Multivariable analysis Potential ecological risk Potential health risk Spatial analysis
1. Introduction Coal mining industry generates a large volume of gangue wastes, from which a considerable amount of toxic HMs could be released during weathering of the waste under the joint effects of water, microorganisms, vegetation, sunlight radiation and heat (Larocque and Rasmussen, 2011). These hazardous substances enter the ecosystem by a variety of pathways where they could be detrimental to crops and animals, and might be taken up by human through direct contact (ingestion, dermal absorption and inhalation) or food chains (Sun et al., 2013). Even at low concentrations, these contaminations are toxic to human health (Arora et al., 2008; €der, 2009), especially to children's health (Ljung Memon and Schro et al., 2006; Poggio et al., 2009; Chabukdhara and Nema, 2013), by causing gastrointestinal disorders, diarrhea, stomatitis, and neurological system malfunctions like tremor and ataxia (USEPA,
* Corresponding author. 388 Lumo Road, China University of Geosciences, Wuhan 430074, PR China. E-mail address: [email protected] (Y. Gu).
1986; Singh et al., 2010). Environmental studies of coal mining areas were conducted by many researchers from USA (Finkelman, 1999; Finkelman and Gross, 1999), Europe (Szczepanska and Twardowska, 1987; Panov et al., 1999) and China (Ding et al., 2001). However, HM contamination in the soil around coal gangue dumps has not drawn enough attention than it deserves. The HM pollution has multiple sources, such as parent material, industrial emission, application of fertilization and pesticides (Fulekar et al., 2009; Wuana and Okieimen, 2011; Nanos and Martín, 2012). Natural and anthropogenic sources of soil HMs could be identified by employing multivariate analysis, including correlation analysis and principal component analysis (PCA) (Lu et al., 2012; Fu and Wei, 2012; Shan et al., 2013). In addition, some spatial analysis techniques could map distributions of HM and identify the possible hotspots in soils. Therefore, the combination of the above methods could be more reliable to differentiate the sources in soil environment (Lv et al., 2014). Yanma coal mine is a large state-owned mine in Henan and has more than 50 years of mining history. The gangue dump with a weight of 3 105 t might be a great threat to at least 3000
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Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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residents, 2 km2 farmland and 6 farms by releasing toxic metals. However, few investigations have been performed about the impacts of HMs on the local environment in this particular area. Therefore, it is essential to investigate the source and distribution of the contaminants. Moreover, analysis of different HM contents in contaminated soils could evaluate their potential ecological and health risks. The scientific basis of targeted contamination management, residents’ health protection, crop production safety and environmental remediation in this area remains unclear until the problems mentioned above are solved. 2. Materials and methods 2.1. Sampling and analysis The study area (N35160 2.100,E113 2108.200 ) is located at Yanmazhuang, Jiaozuo coal mining area, Henan (Fig. 1). The terrain gradually declines from northwest to southeast; groundwater flow direction is SE/130 . The area belongs to the front Taihang piedmont alluvial-pluvial fan, which is under control of a temperate continental monsoon climate. The groundwater depth is between 1 m and 3 m. Prevailing wind directions are northeastward and southwestward. Annual average temperature, precipitation and average evaporation are 14 C, 610 mm and 2039 mm, respectively. Three sampling profiles (L1-L3) were conducted based on the prevailing wind direction, non-prevailing wind direction and groundwater flow direction: L1 was to the southeast (groundwater flow direction and nonprevailing wind direction, SE/130 ) of the gangue dump, the distance between the gangue dump and the south easternmost sampling site was approximately 2000 m; L2 was to the northeast (the prevailing wind direction, NE/35 ) of the gangue dump, the north easternmost sampling site is about
2500 m from the dump; L3 was located within a distance of 300 m from the southwest of the gangue dump, including the top, hillside, foot. All sampling sites were chosen cautiously to avoid main roads, railways and other major human activities. Twenty-five surface soil/gangue and three groundwater samples were collected along three sampling profiles. The closer to the gangue dump, the more sampling sites were selected. Each sample contained four subsamples randomly collected in order to form a representative sample (Li et al., 2008b). Three water samples were collected from wells that recharged by shallow groundwater at L1 profile. GPS coordinates of all sampling sites were documented. Soil pH was measured by IQ150 portable pH-conductivity meter. All the samples were ground, dried and sieved through 100 mesh sieve. An H2O2-HClO4-HF-HNO3 digestion method was employed. A Chinese national standard sample (GBW07427), as well as a blank sample was used as references to control the quality of the entire determination. The total concentrations of cadmium (Cd), lead (Pb), copper (Cu), chromium (Cr), and zinc (Zn) in soil and gangue were measured by inductively coupled plasma-atomic emission spectroscopy (ICP-AES, IRIS Intrepid II XSP). The total concentrations of Cd, Pb, Cu, and Zn in groundwater were measured by ICP-AES (PE Optima 2100DV). The total concentration of Cr in groundwater was determined by ultraviolet visible spectrophotometer (UV, Hitachi U-2900). 2.2. Spatial analysis The inverse distance weighted method of Geostatistic module in ArcGIS was employed to interpolate the surface of each HM element and to calculate the potential ecological risk index. The values of the surface were estimated by weighting sampling points in accordance with their vicinity in the whole sampling area.
Fig. 1. Map showing the field routes and sampling sites.
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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2.3. Statistical analysis The mean value, maximum value, minimum value, standard deviation (sd) and coefficient of variation (CV %) were calculated in Microsoft Excel. Relationships and sources of all HM elements could be unveiled by Pearson correlation matrix and principle component analysis (PCA) by using R Commander Pack of R language. 2.4. Potential ecological risk assessment Potential ecological risk assessment (RI) was widely utilized in soil and sediment HM studies. The calculation formulas are as follows:
. Cfi ¼ CDi CRi
(1)
Eri ¼ Tri Cfi
(2)
RI ¼
m X
Eri
(3)
i¼1
RI is the sum of all indexes of five HMs, Cfi is the pollution factor, is the measured concentration, CRi is a reference value, Eri is the monomial potential ecological risk index, and Tri is the toxic factor for HM which is 30, 5, 5, 2 and 1 for Cd, Pb, Cu, Cr and Zn. Five categories of monomial risk are low potential ecological risk (Eri < 40), moderate potential ecological risk (40 Eri < 80), considerable potential ecological risk (80 Eri < 160), high potential ecological risk (160 Eri < 320) and very high ecological risk (Eri 320). Four categories of RI values correspond to low ecological risk (RI < 150), moderate ecological risk (150 RI < 300), considerable ecological risk (300 RI < 600) and very high ecological risk (RI 600) (Hakanson, 1980). CDi
2.5. Potential health risk assessment The potential chronic effects were measured by hazard quotient (HQ), which was a ratio of an exposure (oral soil ingestion) level over a specified time period with a reference dose (RfD) for a similar exposure period (USEPA, 2002). In order to assess the overall potential chronic effects posed by multiple pollutants, a hazard index (HI) approach that equals to the sum of all HQs has been introduced (USEPA, 1992, 2003). The equations for the average daily dose (ADD), HQ, and HI are as follows:
ADD ¼
C IR EF ED BW AT
ADD HQi ¼ RfDi HI ¼
n X
HQi
(4)
3
Adverse health effects should be considered cautiously if HQ or HI > 1, whereas HQ or HI 1 suggested that no severe adverse effects to human health (USEPA, 1989; Leung et al., 2008). 3. Results and discussion 3.1. HM in gangue, soil and groundwater The total concentrations of HM in all samples are shown in Table 1. Among all samples, there was an obvious variation in the measured concentrations of HMs, varying between 29.55 mg kg1 and 117.28 mg kg1 (mean ± sd ¼ 70.10 ± 17.89 mg kg1) for Pb, 28.48 mg kg1 and 70.95 mg kg1 1 1 (mean ± sd ¼ 50.97 ± 12.09 mg kg ) for Cr, 13.09 mg kg and 53.85 mg kg1 (mean ± sd ¼ 26.97 ± 8.15 mg kg1) for Cu, 43.85 mg kg1 and 188.80 mg kg1 (mean ± sd ¼ 109.63 ± 39.76 mg kg1) for Zn, 0.20 mg kg1 and 1.44 mg kg1 (mean ± sd ¼ 0.61 ± 0.35 mg kg1) for Cd. Compared with CNS for soils (GB 15618-1995), the following metals exceeded level 1 CNS were 24 samples (i.e., 96% of total) for Pb, 3 samples (12.0%) for Cr, 11 samples (44.0%) for Zn and none for Cr. For Cd, all the samples exceeded level 1. And 7 samples even exceeded level 2. The concentrations of all HMs measured were higher than the soil background values in Henan except Cr. Collectively, these results indicate the contaminations of Cd, Cu, Pb and Zn in the gangue dump and the adjacent land. Among these four heavy metals, Cu and Zn are essential elements for living organisms (Obuekwe and Semple, 2013). However, the high Cu or Zn content exceeding certain threshold might pose considerable threats. Cd and Pb were not essential for human health, and low concentrations of Cd and Pb might also produce severe health problems (Damodaran et al., 2013). As shown in Tables 2 and 3, except that of NO 3 , the concentrations of other chemicals in groundwater samples were within the WHO standard (WHO, 2001). Previous results (Atapour, 2012; Bhagure and Mirgane, 2011) suggested that the HM concentrations of the groundwater samples near the contaminated area were higher than those at distances due to the HM migration in groundwater. Other studies conducted with microscopic approaches (Erakhrumen, 2007; Li et al., 2013; Wu et al., 2010) suggested that certain plants or bacteria could reduce the mobility of HMs by converting their speciation to more insoluble form to prevent their migration with groundwater. In this study, neither the specific trend of HM concentrations nor the correlation between the distance to the gangue dump and the concentrations of HMs was found. Hence, the groundwater transportation is not likely the dominant contamination pathway. 3.2. Spatial analysis and source identification of HMs
(5)
(6)
i¼1
where C is the measured concentration of HM in soil. IR is the soil ingestion rate, which is recommended to be 100 mg d1 for adults (USEPA, 2011), and 200 mg d1 for children (USEPA, 2011). BW represents the average body weight which is assumed to be 70 kg for adults (Lee et al., 1994; Leung et al., 2008) and 15 kg for children. The exposure frequency (EF), exposure duration (ED), and average time (AT) are recommended to be 350 d a1, 6 a and 2190 d. RfD is 0.001, 0.003, 0.04, 0.0035 and 0.3 mg (d kg1) for Cd, Cr, Cu, Pb and Zn (Leung et al., 2008; USEPA, 2014).
The surface “hotspots” and potential sources of contamination could be identified by a spatial distribution map of the HM concentration (Karbassi, 2005; Viguri et al., 2007). As shown in Fig. 2, 71.29% of the area exceeded level 1 CNS of Cd and 28.71% for level 2. An uneven distribution of Cd was found throughout most of the study area. That is, the gangue dump was identified as the only “hotspot” with the highest concentration; the greater distance to the dump, the lower concentration of Cd was found in the adjacent soil; the decrease in concentrations of Cd along the L2 soils sampled was much higher than that in the L1 soils. There were 99.99%, 0.16% and 49.30% of the study area exceeded level 1 CNS for Pb, Cu, and Zn, respectively. They shared the similar distribution pattern with Cd. The distribution pattern of Cr, however, did not show any noticeable “hotspot”. Complicated relationships were commonly found among soil
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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Table 1 Total concentrations of HMs, HQ and HI in soil and gangue (n ¼ 25).
Min mg kg1 Max mg kg1 Mean ± sd mg kg1 CV% Background in Henan (China EPA, 1990) mg kg1 GB15618-1995 mg kg1 HI Children Min Max Mean sd HI Adult Min Max Mean sd
Pb
Cr
Cu
Zn
Cd
29.55 117.28 70.10 ± 17.89 25.52% 19.60 ± 4.62
28.48 70.95 50.97 ± 12.09 23.72% 63.80 ± 13.25
13.09 53.85 26.97 ± 8.15 30.22% 19.70 ± 4.80
43.85 188.80 109.63 ± 39.76 36.27% 60.10 ± 15.30
0.20 1.44 0.61 ± 0.35 57.61% 0.07 ± 0.02
HI
35Ⅰ,300Ⅱ
90Ⅰ
35Ⅰ,100Ⅱ
100Ⅰ
0.20Ⅰ,0.60Ⅱ
1.13 4.47 2.67 6.82
101 101 101 102
1.27 3.15 2.27 5.37
101 101 101 102
4.36 1.80 8.99 2.72
103 102 103 103
1.95 8.39 4.87 1.77
103 103 103 103
2.68 1.92 8.09 4.66
103 102 103 103
2.48 101 8.08 101 5.16 101
1.21 4.79 2.86 7.30
102 102 102 103
1.36 3.38 2.43 5.76
102 102 102 103
1.56 6.41 3.21 9.70
107 107 107 108
9.28 4.00 2.32 8.41
109 108 108 109
3.83 2.75 1.16 6.66
106 105 105 106
2.56 102 8.17 102 5.29 102
I: level 1 CNS, II: level 2 CNS (6.5 < pH < 7.5).
Table 2 Water quality parameters of groundwater samples. Samples
Naþ
Ca2þ
Mg2þ
Cl
SO24
NO 3
TDS
pH
Pond. Middle of the gangue dump and GZG Shallow well. North of GZG Shallow well. Southeast of GZG WHO HDL WHO MPL
13.85 20.31 155.8 e 200
65.61 116.4 158.07 75 200
27.96 35.53 28.13 30 150
22.33 26.23 48.57 200 600
42.27 97.5 49.47 200 400
13.7 30.9 3.69 0 0.45
340.46 552.88 629.33 500 1000
8.1 7.65 7.9 7e8.5 6.5e9.5
Except pH, all values are in mg kg1. TDS: total dissolved solids. HDL: highest desirable limit. MPL: maximum permissible limit.
Table 3 Concentrations of HMs in groundwater samples. Samples
Fe
Zn
Cu
Pb
Cd
Cr
Pond. Middle of the gangue dump and GZG Shallow well. North of GZG Shallow well. Southeast of GZG WHO
nd 0.02 0.21 e
nd nd nd 3
nd nd nd 2
nd nd nd 10
nd nd nd 3
nd nd nd 50
HMs. It was reported that HMs were controlled by quite a few factors, such as original contents in parent materials and rocks, numerous pedogenic process and anthropogenic factors (Li et al., 2008b). Correlation analysis was an effective way to explore the relationships among multivariate data so that the factors and sources of chemical components could be identified (Shine et al., 1995; Al-Khashman and Shawabkeh, 2006). Pearson correlation coefficient matrix of 5 HMs is demonstrated in Table 4. The correlation coefficients between Cd and Cu, Cd and Zn, Cr and Pb, Zn and Cu, Zn and Pb and Cu and Pb were 0.66, 0.81, 0.63, 0.85, 0.76 and 0.64, respectively, with high significance correlation (P < 0.01). Significance correlations (P < 0.05) were found between Cd and Pb (r ¼ 0.51), Cr and Cu (r ¼ 0.72) and Cr and Zn (r ¼ 0.53). The correlation coefficient between Cd and Cr was 0.23, indicating minor significance. The high correlations between HM concentrations suggest that corresponding metals shared similarity of contamination level and pollution sources (Li et al., 2009). Overall, Cd, Pb, Zn and Cu were grouped together and the gangue dump was identified as their source. The result was similar to those of the earlier studies in other coal mining areas (Yongming et al., 2006; Li et al., 2009, 2012; Sun et al., 2010). PCA is widely applied to reduce data dimensions (Loska and Wiechuła, 2003) by extracting a much less number of latent
factors (principal components, PCs) for analyzing the relationships among the observations. Specifically, it could reveal the degrees of contamination by HMs from different sources (Chen et al., 2005; Zhou et al., 2007; Rodríguez et al., 2008). As shown in Table 5 and Fig. 3, two PCs were produced, which performed 88.2% of the total variation. The first principal component PC1 explaining the highest variance (71.5%) included all 5 HMs. Based on the contribution to PC1, the metals were arranged in the following order: Pb > Cu > Zn > Cd > Cr. The second principal component PC2 contributed 16.7% of the total variance, including Cd and Cr. Little loading was found on PC2 for Pb, Cu and Zn, while Cd and Cr contributed to PC2 in opposite directions. Our results imply that the contamination of Cd, Cu, Pb and Zn originated from the gangue dump. Accordingly, PC1 could be defined as “origin of gangue dump”. Based on the fact that Cr concentration was lower than the background values of both Henan Province and entire China, PC2 could be defined as “origin of natural sources”. The outcome of the principal component analysis is consistent with those of early studies (Chen et al., 2005; Yongming et al., 2006; Sun et al., 2010; Liu et al., 2013; Hossain et al., 2014). The results of soil HM spatial analysis, source analysis and the uncontaminated groundwater samples, along with the southwestward prevailing wind direction, suggest that the gangue dump was the source of Cd, Pb, Cu and Zn contamination. The fugitive dust translocation of weathered gangue by prevailing wind direction was likely the contamination pathway and the gangue dump was unlikely the source of Cr. These results are consistent with previous studies which indicated that HMs from point source might have been intensively retained in the surface near the source (Facchinelli et al., 2001; Vince et al., 2014), while metals from nonpoint source were more uniformly distributed throughout most of the study area (Shine et al., 1995; Li et al., 2012).
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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5
Fig. 2. Spatial distribution pattern of 5 heavy metal concentrations (mg kg1) and RI.
3.3. Potential ecological risk assessment
Table 4 Correlation coefficient matrix of 5 heavy metals.
Cd Cr Cu Pb Zn
Cd
Cr
Cu
Pb
Zn
1.00 0.23 0.66** 0.51* 0.81**
1.00 0.72* 0.63** 0.53*
1.00 0.64** 0.85**
1.00 0.76**
1.00
Pearson correlations, n ¼ 25, level of significance: *P < 0.05, **P < 0.01.
Table 5 Proportion of variance and cumulative proportion.
SD Proportion of variance Cumulative proportion
PC1
PC2
PC3
PC4
PC5
1.89 71.5% 71.5%
0.91 16.7% 88.2%
0.62 7.7% 95.9%
0.37 2.8% 98.6%
0.26 1.4% 100.0%
Potential ecological risk index has been generally considered as a metrics that could reflect overall potential ecological risk due to co-contamination quantitatively. There was an uneven distribution of RI (Fig. 2-f): the highest, mean and lowest RI were 619.5, 244.4 and 97.2; all four categories of RI value were included throughout the whole study area; RI decreased as the distance increased, similar to the concentration distributions of Cd, Pb, Cu and Zn. The area ratio was 5.53% for low ecological risk (RI < 150), 75.63% for moderate ecological risk (150 RI < 300), 18.84% for considerable ecological risk (300 RI < 600) and 0.01% for very high ecological risk (RI > 600). Cd contributed the greatest to the RI, the percentage ranging from 81.5% to 94.4%, which was consistent with another research conducted in Yangcaogou coal gangue dump (Jiang et al., 2014). All of Cd monomial risks were considerable potential ecological risk (80Eir <160) or above it. The contribution of the
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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those of Cd, Pb, Cu and Zn. These heavy metals posed noticeable potential ecological risks, varying from 97.2 to 619.5. Cd contributed the greatest to the risk index. Overall, intensive monitor, vegetation restoration and soil remediation would be necessary to block the contamination pathway and protect the residents, since the metals exceeded CNS and pose noticeable potential ecological risk. Acknowledgments This study was financially supported by Department of Land and Resources of Henan Province (2011-622-38). The authors would like to thank Prof. Tian-Chyi Yeh of the University of Arizona, Prof. Khan M. G. Mostofa, Dr. Ruochun Zhang and Dr. Kai Zhang of Tianjing University for their valuable comments on the earlier version of the manuscript. References
Fig. 3. Biplot of 5 heavy metal elements on PC1 and PC2 (n ¼ 25).
other metals was significantly lower, and their monomial RI values were below low ecological risk (RI < 150). Our results indicate that HMs posed noticeable potential ecological risks and Cd contributed the greatest to the RI. 3.4. Potential health risk assessment Early study suggested that health risks caused by dermal contact and inhalation were relatively less than those triggered by direct oral ingestion of polluted soil (Chabukdhara and Nema, 2013). Hence, the potential risks to children and adult were assessed by considering oral ingestion of contaminated soil (Table 1). The maximum hazard quotient (HQ) for children was 4.47 101 for Pb, 3.15 101 for Cr, 1.80 102 for Cu, 8.39 103 for Zn and 1.92 102 for Cd Overall hazard index (HI) for children was 8.08 101. The maximum HQ of Pb, Cr, Cu, Zn and Cd for adults was 4.79 102, 3.38 102, 6.41 107, 4.00 108 and 2.75 105. The HI was 8.17 102. The potential health risks for children were greater than those for adults. None of these indices were greater than 1, which indicates that there were no severe potential health risks posed by direct ingestion. However, humankind was exposed through other pathways such as consumption of contaminated grains (Shimbo et al., 2001; Zhang and Zi-Xia, 2004; Cheng et al., 2006), vegetables (Li et al., 2006) and fruits. Consequently, health risk assessment of multiple contamination pathways needs to be conducted in the future. 4. Conclusions Among 25 gangue and soil samples collected in the study area, the concentrations of Cd in seven samples exceeded level 2 CNS. The concentrations of Pb, Cu and Zn in all samples exceeded level 1 CNS, while Cr concentrations remained lower than both level 1 CNS and Henan background concentration. The HM concentrations in 3 groundwater samples were within the WHO standard. The Cd, Pb, Cu and Zn concentrations reduced as the distance to the gangue dump increased; the concentration reduction gradient of L2 was higher than that of L1. The fugitive dust was the migration pathway. The contamination source of Cd, Pb, Cu and Zn was the gangue dump. The general spatial distribution of RI value was similar to
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Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China Kuangjia Li a, Yansheng Gu b, c, *, Manzhou Li d, Lin Zhao a, Junjie Ding c, Zijian Lun c, Wen Tian c a
School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, PR China State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, PR China School of Environmental Studies, China University of Geosciences, Wuhan 430074, PR China d Department of Land and Resources of Henan Province, Zhengzhou 450000, PR China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 13 June 2016 Received in revised form 28 March 2017 Accepted 29 March 2017 Available online xxx
The purpose of this study is to investigate the heavy metal (HM) concentration of the gangue and HM pollution of the soil in a coal mining area. On the basis of determination of the concentrations of cadmium (Cd), lead (Pb), copper (Cu), zinc (Zn) and chromium (Cr) in the samples from the gangue and surface soils, the spatial distribution of toxic metals, contamination sources, potential ecological risks, potential health risks were studied. The content of Cd, Pb, Cu and Zn in the surface soils exceeded China National Standard (CNS, GB15618-1995). The spatial distributions of Cd, Pb, Cu and Zn are similar, exhibiting a declining trend from the gangue dump to the surrounding farmland. Results of Pearson correlation matrix and principal component analysis indicate that the origin of Cd, Pb, Cu and Zn elements is the gangue dump. The potential ecological risk index ranges from 97.2 to 619.5, and its spatial distribution is similar to those of Cd, Pb, Cu and Zn. Our results indicate that the HMs exceeded the corresponding CNS and posed noticeable ecological risks, which suggest that monitor and remediation measures should be taken in order to protect the health of the residents and the safety of the crops. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Coal gangue waste Heavy metals Multivariable analysis Potential ecological risk Potential health risk Spatial analysis
1. Introduction Coal mining industry generates a large volume of gangue wastes, from which a considerable amount of toxic HMs could be released during weathering of the waste under the joint effects of water, microorganisms, vegetation, sunlight radiation and heat (Larocque and Rasmussen, 2011). These hazardous substances enter the ecosystem by a variety of pathways where they could be detrimental to crops and animals, and might be taken up by human through direct contact (ingestion, dermal absorption and inhalation) or food chains (Sun et al., 2013). Even at low concentrations, these contaminations are toxic to human health (Arora et al., 2008; €der, 2009), especially to children's health (Ljung Memon and Schro et al., 2006; Poggio et al., 2009; Chabukdhara and Nema, 2013), by causing gastrointestinal disorders, diarrhea, stomatitis, and neurological system malfunctions like tremor and ataxia (USEPA,
* Corresponding author. 388 Lumo Road, China University of Geosciences, Wuhan 430074, PR China. E-mail address: [email protected] (Y. Gu).
1986; Singh et al., 2010). Environmental studies of coal mining areas were conducted by many researchers from USA (Finkelman, 1999; Finkelman and Gross, 1999), Europe (Szczepanska and Twardowska, 1987; Panov et al., 1999) and China (Ding et al., 2001). However, HM contamination in the soil around coal gangue dumps has not drawn enough attention than it deserves. The HM pollution has multiple sources, such as parent material, industrial emission, application of fertilization and pesticides (Fulekar et al., 2009; Wuana and Okieimen, 2011; Nanos and Martín, 2012). Natural and anthropogenic sources of soil HMs could be identified by employing multivariate analysis, including correlation analysis and principal component analysis (PCA) (Lu et al., 2012; Fu and Wei, 2012; Shan et al., 2013). In addition, some spatial analysis techniques could map distributions of HM and identify the possible hotspots in soils. Therefore, the combination of the above methods could be more reliable to differentiate the sources in soil environment (Lv et al., 2014). Yanma coal mine is a large state-owned mine in Henan and has more than 50 years of mining history. The gangue dump with a weight of 3 105 t might be a great threat to at least 3000
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residents, 2 km2 farmland and 6 farms by releasing toxic metals. However, few investigations have been performed about the impacts of HMs on the local environment in this particular area. Therefore, it is essential to investigate the source and distribution of the contaminants. Moreover, analysis of different HM contents in contaminated soils could evaluate their potential ecological and health risks. The scientific basis of targeted contamination management, residents’ health protection, crop production safety and environmental remediation in this area remains unclear until the problems mentioned above are solved. 2. Materials and methods 2.1. Sampling and analysis The study area (N35160 2.100,E113 2108.200 ) is located at Yanmazhuang, Jiaozuo coal mining area, Henan (Fig. 1). The terrain gradually declines from northwest to southeast; groundwater flow direction is SE/130 . The area belongs to the front Taihang piedmont alluvial-pluvial fan, which is under control of a temperate continental monsoon climate. The groundwater depth is between 1 m and 3 m. Prevailing wind directions are northeastward and southwestward. Annual average temperature, precipitation and average evaporation are 14 C, 610 mm and 2039 mm, respectively. Three sampling profiles (L1-L3) were conducted based on the prevailing wind direction, non-prevailing wind direction and groundwater flow direction: L1 was to the southeast (groundwater flow direction and nonprevailing wind direction, SE/130 ) of the gangue dump, the distance between the gangue dump and the south easternmost sampling site was approximately 2000 m; L2 was to the northeast (the prevailing wind direction, NE/35 ) of the gangue dump, the north easternmost sampling site is about
2500 m from the dump; L3 was located within a distance of 300 m from the southwest of the gangue dump, including the top, hillside, foot. All sampling sites were chosen cautiously to avoid main roads, railways and other major human activities. Twenty-five surface soil/gangue and three groundwater samples were collected along three sampling profiles. The closer to the gangue dump, the more sampling sites were selected. Each sample contained four subsamples randomly collected in order to form a representative sample (Li et al., 2008b). Three water samples were collected from wells that recharged by shallow groundwater at L1 profile. GPS coordinates of all sampling sites were documented. Soil pH was measured by IQ150 portable pH-conductivity meter. All the samples were ground, dried and sieved through 100 mesh sieve. An H2O2-HClO4-HF-HNO3 digestion method was employed. A Chinese national standard sample (GBW07427), as well as a blank sample was used as references to control the quality of the entire determination. The total concentrations of cadmium (Cd), lead (Pb), copper (Cu), chromium (Cr), and zinc (Zn) in soil and gangue were measured by inductively coupled plasma-atomic emission spectroscopy (ICP-AES, IRIS Intrepid II XSP). The total concentrations of Cd, Pb, Cu, and Zn in groundwater were measured by ICP-AES (PE Optima 2100DV). The total concentration of Cr in groundwater was determined by ultraviolet visible spectrophotometer (UV, Hitachi U-2900). 2.2. Spatial analysis The inverse distance weighted method of Geostatistic module in ArcGIS was employed to interpolate the surface of each HM element and to calculate the potential ecological risk index. The values of the surface were estimated by weighting sampling points in accordance with their vicinity in the whole sampling area.
Fig. 1. Map showing the field routes and sampling sites.
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
K. Li et al. / International Biodeterioration & Biodegradation xxx (2017) 1e7
2.3. Statistical analysis The mean value, maximum value, minimum value, standard deviation (sd) and coefficient of variation (CV %) were calculated in Microsoft Excel. Relationships and sources of all HM elements could be unveiled by Pearson correlation matrix and principle component analysis (PCA) by using R Commander Pack of R language. 2.4. Potential ecological risk assessment Potential ecological risk assessment (RI) was widely utilized in soil and sediment HM studies. The calculation formulas are as follows:
. Cfi ¼ CDi CRi
(1)
Eri ¼ Tri Cfi
(2)
RI ¼
m X
Eri
(3)
i¼1
RI is the sum of all indexes of five HMs, Cfi is the pollution factor, is the measured concentration, CRi is a reference value, Eri is the monomial potential ecological risk index, and Tri is the toxic factor for HM which is 30, 5, 5, 2 and 1 for Cd, Pb, Cu, Cr and Zn. Five categories of monomial risk are low potential ecological risk (Eri < 40), moderate potential ecological risk (40 Eri < 80), considerable potential ecological risk (80 Eri < 160), high potential ecological risk (160 Eri < 320) and very high ecological risk (Eri 320). Four categories of RI values correspond to low ecological risk (RI < 150), moderate ecological risk (150 RI < 300), considerable ecological risk (300 RI < 600) and very high ecological risk (RI 600) (Hakanson, 1980). CDi
2.5. Potential health risk assessment The potential chronic effects were measured by hazard quotient (HQ), which was a ratio of an exposure (oral soil ingestion) level over a specified time period with a reference dose (RfD) for a similar exposure period (USEPA, 2002). In order to assess the overall potential chronic effects posed by multiple pollutants, a hazard index (HI) approach that equals to the sum of all HQs has been introduced (USEPA, 1992, 2003). The equations for the average daily dose (ADD), HQ, and HI are as follows:
ADD ¼
C IR EF ED BW AT
ADD HQi ¼ RfDi HI ¼
n X
HQi
(4)
3
Adverse health effects should be considered cautiously if HQ or HI > 1, whereas HQ or HI 1 suggested that no severe adverse effects to human health (USEPA, 1989; Leung et al., 2008). 3. Results and discussion 3.1. HM in gangue, soil and groundwater The total concentrations of HM in all samples are shown in Table 1. Among all samples, there was an obvious variation in the measured concentrations of HMs, varying between 29.55 mg kg1 and 117.28 mg kg1 (mean ± sd ¼ 70.10 ± 17.89 mg kg1) for Pb, 28.48 mg kg1 and 70.95 mg kg1 1 1 (mean ± sd ¼ 50.97 ± 12.09 mg kg ) for Cr, 13.09 mg kg and 53.85 mg kg1 (mean ± sd ¼ 26.97 ± 8.15 mg kg1) for Cu, 43.85 mg kg1 and 188.80 mg kg1 (mean ± sd ¼ 109.63 ± 39.76 mg kg1) for Zn, 0.20 mg kg1 and 1.44 mg kg1 (mean ± sd ¼ 0.61 ± 0.35 mg kg1) for Cd. Compared with CNS for soils (GB 15618-1995), the following metals exceeded level 1 CNS were 24 samples (i.e., 96% of total) for Pb, 3 samples (12.0%) for Cr, 11 samples (44.0%) for Zn and none for Cr. For Cd, all the samples exceeded level 1. And 7 samples even exceeded level 2. The concentrations of all HMs measured were higher than the soil background values in Henan except Cr. Collectively, these results indicate the contaminations of Cd, Cu, Pb and Zn in the gangue dump and the adjacent land. Among these four heavy metals, Cu and Zn are essential elements for living organisms (Obuekwe and Semple, 2013). However, the high Cu or Zn content exceeding certain threshold might pose considerable threats. Cd and Pb were not essential for human health, and low concentrations of Cd and Pb might also produce severe health problems (Damodaran et al., 2013). As shown in Tables 2 and 3, except that of NO 3 , the concentrations of other chemicals in groundwater samples were within the WHO standard (WHO, 2001). Previous results (Atapour, 2012; Bhagure and Mirgane, 2011) suggested that the HM concentrations of the groundwater samples near the contaminated area were higher than those at distances due to the HM migration in groundwater. Other studies conducted with microscopic approaches (Erakhrumen, 2007; Li et al., 2013; Wu et al., 2010) suggested that certain plants or bacteria could reduce the mobility of HMs by converting their speciation to more insoluble form to prevent their migration with groundwater. In this study, neither the specific trend of HM concentrations nor the correlation between the distance to the gangue dump and the concentrations of HMs was found. Hence, the groundwater transportation is not likely the dominant contamination pathway. 3.2. Spatial analysis and source identification of HMs
(5)
(6)
i¼1
where C is the measured concentration of HM in soil. IR is the soil ingestion rate, which is recommended to be 100 mg d1 for adults (USEPA, 2011), and 200 mg d1 for children (USEPA, 2011). BW represents the average body weight which is assumed to be 70 kg for adults (Lee et al., 1994; Leung et al., 2008) and 15 kg for children. The exposure frequency (EF), exposure duration (ED), and average time (AT) are recommended to be 350 d a1, 6 a and 2190 d. RfD is 0.001, 0.003, 0.04, 0.0035 and 0.3 mg (d kg1) for Cd, Cr, Cu, Pb and Zn (Leung et al., 2008; USEPA, 2014).
The surface “hotspots” and potential sources of contamination could be identified by a spatial distribution map of the HM concentration (Karbassi, 2005; Viguri et al., 2007). As shown in Fig. 2, 71.29% of the area exceeded level 1 CNS of Cd and 28.71% for level 2. An uneven distribution of Cd was found throughout most of the study area. That is, the gangue dump was identified as the only “hotspot” with the highest concentration; the greater distance to the dump, the lower concentration of Cd was found in the adjacent soil; the decrease in concentrations of Cd along the L2 soils sampled was much higher than that in the L1 soils. There were 99.99%, 0.16% and 49.30% of the study area exceeded level 1 CNS for Pb, Cu, and Zn, respectively. They shared the similar distribution pattern with Cd. The distribution pattern of Cr, however, did not show any noticeable “hotspot”. Complicated relationships were commonly found among soil
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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Table 1 Total concentrations of HMs, HQ and HI in soil and gangue (n ¼ 25).
Min mg kg1 Max mg kg1 Mean ± sd mg kg1 CV% Background in Henan (China EPA, 1990) mg kg1 GB15618-1995 mg kg1 HI Children Min Max Mean sd HI Adult Min Max Mean sd
Pb
Cr
Cu
Zn
Cd
29.55 117.28 70.10 ± 17.89 25.52% 19.60 ± 4.62
28.48 70.95 50.97 ± 12.09 23.72% 63.80 ± 13.25
13.09 53.85 26.97 ± 8.15 30.22% 19.70 ± 4.80
43.85 188.80 109.63 ± 39.76 36.27% 60.10 ± 15.30
0.20 1.44 0.61 ± 0.35 57.61% 0.07 ± 0.02
HI
35Ⅰ,300Ⅱ
90Ⅰ
35Ⅰ,100Ⅱ
100Ⅰ
0.20Ⅰ,0.60Ⅱ
1.13 4.47 2.67 6.82
101 101 101 102
1.27 3.15 2.27 5.37
101 101 101 102
4.36 1.80 8.99 2.72
103 102 103 103
1.95 8.39 4.87 1.77
103 103 103 103
2.68 1.92 8.09 4.66
103 102 103 103
2.48 101 8.08 101 5.16 101
1.21 4.79 2.86 7.30
102 102 102 103
1.36 3.38 2.43 5.76
102 102 102 103
1.56 6.41 3.21 9.70
107 107 107 108
9.28 4.00 2.32 8.41
109 108 108 109
3.83 2.75 1.16 6.66
106 105 105 106
2.56 102 8.17 102 5.29 102
I: level 1 CNS, II: level 2 CNS (6.5 < pH < 7.5).
Table 2 Water quality parameters of groundwater samples. Samples
Naþ
Ca2þ
Mg2þ
Cl
SO24
NO 3
TDS
pH
Pond. Middle of the gangue dump and GZG Shallow well. North of GZG Shallow well. Southeast of GZG WHO HDL WHO MPL
13.85 20.31 155.8 e 200
65.61 116.4 158.07 75 200
27.96 35.53 28.13 30 150
22.33 26.23 48.57 200 600
42.27 97.5 49.47 200 400
13.7 30.9 3.69 0 0.45
340.46 552.88 629.33 500 1000
8.1 7.65 7.9 7e8.5 6.5e9.5
Except pH, all values are in mg kg1. TDS: total dissolved solids. HDL: highest desirable limit. MPL: maximum permissible limit.
Table 3 Concentrations of HMs in groundwater samples. Samples
Fe
Zn
Cu
Pb
Cd
Cr
Pond. Middle of the gangue dump and GZG Shallow well. North of GZG Shallow well. Southeast of GZG WHO
nd 0.02 0.21 e
nd nd nd 3
nd nd nd 2
nd nd nd 10
nd nd nd 3
nd nd nd 50
HMs. It was reported that HMs were controlled by quite a few factors, such as original contents in parent materials and rocks, numerous pedogenic process and anthropogenic factors (Li et al., 2008b). Correlation analysis was an effective way to explore the relationships among multivariate data so that the factors and sources of chemical components could be identified (Shine et al., 1995; Al-Khashman and Shawabkeh, 2006). Pearson correlation coefficient matrix of 5 HMs is demonstrated in Table 4. The correlation coefficients between Cd and Cu, Cd and Zn, Cr and Pb, Zn and Cu, Zn and Pb and Cu and Pb were 0.66, 0.81, 0.63, 0.85, 0.76 and 0.64, respectively, with high significance correlation (P < 0.01). Significance correlations (P < 0.05) were found between Cd and Pb (r ¼ 0.51), Cr and Cu (r ¼ 0.72) and Cr and Zn (r ¼ 0.53). The correlation coefficient between Cd and Cr was 0.23, indicating minor significance. The high correlations between HM concentrations suggest that corresponding metals shared similarity of contamination level and pollution sources (Li et al., 2009). Overall, Cd, Pb, Zn and Cu were grouped together and the gangue dump was identified as their source. The result was similar to those of the earlier studies in other coal mining areas (Yongming et al., 2006; Li et al., 2009, 2012; Sun et al., 2010). PCA is widely applied to reduce data dimensions (Loska and Wiechuła, 2003) by extracting a much less number of latent
factors (principal components, PCs) for analyzing the relationships among the observations. Specifically, it could reveal the degrees of contamination by HMs from different sources (Chen et al., 2005; Zhou et al., 2007; Rodríguez et al., 2008). As shown in Table 5 and Fig. 3, two PCs were produced, which performed 88.2% of the total variation. The first principal component PC1 explaining the highest variance (71.5%) included all 5 HMs. Based on the contribution to PC1, the metals were arranged in the following order: Pb > Cu > Zn > Cd > Cr. The second principal component PC2 contributed 16.7% of the total variance, including Cd and Cr. Little loading was found on PC2 for Pb, Cu and Zn, while Cd and Cr contributed to PC2 in opposite directions. Our results imply that the contamination of Cd, Cu, Pb and Zn originated from the gangue dump. Accordingly, PC1 could be defined as “origin of gangue dump”. Based on the fact that Cr concentration was lower than the background values of both Henan Province and entire China, PC2 could be defined as “origin of natural sources”. The outcome of the principal component analysis is consistent with those of early studies (Chen et al., 2005; Yongming et al., 2006; Sun et al., 2010; Liu et al., 2013; Hossain et al., 2014). The results of soil HM spatial analysis, source analysis and the uncontaminated groundwater samples, along with the southwestward prevailing wind direction, suggest that the gangue dump was the source of Cd, Pb, Cu and Zn contamination. The fugitive dust translocation of weathered gangue by prevailing wind direction was likely the contamination pathway and the gangue dump was unlikely the source of Cr. These results are consistent with previous studies which indicated that HMs from point source might have been intensively retained in the surface near the source (Facchinelli et al., 2001; Vince et al., 2014), while metals from nonpoint source were more uniformly distributed throughout most of the study area (Shine et al., 1995; Li et al., 2012).
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5
Fig. 2. Spatial distribution pattern of 5 heavy metal concentrations (mg kg1) and RI.
3.3. Potential ecological risk assessment
Table 4 Correlation coefficient matrix of 5 heavy metals.
Cd Cr Cu Pb Zn
Cd
Cr
Cu
Pb
Zn
1.00 0.23 0.66** 0.51* 0.81**
1.00 0.72* 0.63** 0.53*
1.00 0.64** 0.85**
1.00 0.76**
1.00
Pearson correlations, n ¼ 25, level of significance: *P < 0.05, **P < 0.01.
Table 5 Proportion of variance and cumulative proportion.
SD Proportion of variance Cumulative proportion
PC1
PC2
PC3
PC4
PC5
1.89 71.5% 71.5%
0.91 16.7% 88.2%
0.62 7.7% 95.9%
0.37 2.8% 98.6%
0.26 1.4% 100.0%
Potential ecological risk index has been generally considered as a metrics that could reflect overall potential ecological risk due to co-contamination quantitatively. There was an uneven distribution of RI (Fig. 2-f): the highest, mean and lowest RI were 619.5, 244.4 and 97.2; all four categories of RI value were included throughout the whole study area; RI decreased as the distance increased, similar to the concentration distributions of Cd, Pb, Cu and Zn. The area ratio was 5.53% for low ecological risk (RI < 150), 75.63% for moderate ecological risk (150 RI < 300), 18.84% for considerable ecological risk (300 RI < 600) and 0.01% for very high ecological risk (RI > 600). Cd contributed the greatest to the RI, the percentage ranging from 81.5% to 94.4%, which was consistent with another research conducted in Yangcaogou coal gangue dump (Jiang et al., 2014). All of Cd monomial risks were considerable potential ecological risk (80Eir <160) or above it. The contribution of the
Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026
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K. Li et al. / International Biodeterioration & Biodegradation xxx (2017) 1e7
those of Cd, Pb, Cu and Zn. These heavy metals posed noticeable potential ecological risks, varying from 97.2 to 619.5. Cd contributed the greatest to the risk index. Overall, intensive monitor, vegetation restoration and soil remediation would be necessary to block the contamination pathway and protect the residents, since the metals exceeded CNS and pose noticeable potential ecological risk. Acknowledgments This study was financially supported by Department of Land and Resources of Henan Province (2011-622-38). The authors would like to thank Prof. Tian-Chyi Yeh of the University of Arizona, Prof. Khan M. G. Mostofa, Dr. Ruochun Zhang and Dr. Kai Zhang of Tianjing University for their valuable comments on the earlier version of the manuscript. References
Fig. 3. Biplot of 5 heavy metal elements on PC1 and PC2 (n ¼ 25).
other metals was significantly lower, and their monomial RI values were below low ecological risk (RI < 150). Our results indicate that HMs posed noticeable potential ecological risks and Cd contributed the greatest to the RI. 3.4. Potential health risk assessment Early study suggested that health risks caused by dermal contact and inhalation were relatively less than those triggered by direct oral ingestion of polluted soil (Chabukdhara and Nema, 2013). Hence, the potential risks to children and adult were assessed by considering oral ingestion of contaminated soil (Table 1). The maximum hazard quotient (HQ) for children was 4.47 101 for Pb, 3.15 101 for Cr, 1.80 102 for Cu, 8.39 103 for Zn and 1.92 102 for Cd Overall hazard index (HI) for children was 8.08 101. The maximum HQ of Pb, Cr, Cu, Zn and Cd for adults was 4.79 102, 3.38 102, 6.41 107, 4.00 108 and 2.75 105. The HI was 8.17 102. The potential health risks for children were greater than those for adults. None of these indices were greater than 1, which indicates that there were no severe potential health risks posed by direct ingestion. However, humankind was exposed through other pathways such as consumption of contaminated grains (Shimbo et al., 2001; Zhang and Zi-Xia, 2004; Cheng et al., 2006), vegetables (Li et al., 2006) and fruits. Consequently, health risk assessment of multiple contamination pathways needs to be conducted in the future. 4. Conclusions Among 25 gangue and soil samples collected in the study area, the concentrations of Cd in seven samples exceeded level 2 CNS. The concentrations of Pb, Cu and Zn in all samples exceeded level 1 CNS, while Cr concentrations remained lower than both level 1 CNS and Henan background concentration. The HM concentrations in 3 groundwater samples were within the WHO standard. The Cd, Pb, Cu and Zn concentrations reduced as the distance to the gangue dump increased; the concentration reduction gradient of L2 was higher than that of L1. The fugitive dust was the migration pathway. The contamination source of Cd, Pb, Cu and Zn was the gangue dump. The general spatial distribution of RI value was similar to
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Please cite this article in press as: Li, K., et al., Spatial analysis, source identification and risk assessment of heavy metals in a coal mining area in Henan, Central China, International Biodeterioration & Biodegradation (2017), http://dx.doi.org/10.1016/j.ibiod.2017.03.026