Next Article in Journal
Potential of Fluid Dynamic Bowtie Filter for Dose Reduction and Image Quality Improvement of Cone-Beam CT
Next Article in Special Issue
The Tolerance, Absorption, and Transport Characteristics of Macleaya cordata in Relation to Lead, Zinc, Cadmium, and Copper under Hydroponic Conditions
Previous Article in Journal
A Ground Moving Target Detection Method for Seismic and Sound Sensor Based on Evolutionary Neural Networks
Previous Article in Special Issue
Remediation of Heavy Metal Contaminated Farmland Soil by Biodegradable Chelating Agent GLDA
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assessment of Soil Heavy Metal Pollution and Its Ecological Risk for City Parks, Vicinity of a Landfill, and an Industrial Area within Guangzhou, South China

1
School of Geography, South China Normal University, Guangzhou 510631, China
2
Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
3
Guangzhou Institute of Geological Survey, Guangzhou 510440, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(18), 9345; https://doi.org/10.3390/app12189345
Submission received: 19 August 2022 / Revised: 13 September 2022 / Accepted: 15 September 2022 / Published: 18 September 2022
(This article belongs to the Special Issue Ecology Impact of Heavy Metals)

Abstract

:
As a primary sink of pollutants, urban soil heavy metal pollution and its influence on urban residents and ecosystems has been becoming one of the most important environmental problems. In the present study, four indices, the Geoaccumulation index (Igeo), improved Nemerow index (IMN), degree of contamination (mCd), and contamination security index (CSI), as well as potential ecological risk (RI), were used to evaluate individual or integrated heavy metal pollution and its ecological risk for soil samples collected from city parks, the vicinity of a landfill, and an industrial area within the city of Guangzhou. The results indicated that the improved Nemerow index (IMN) calculated from the Geoaccumulation index was suitable for heavy metal pollution assessment of soils within landfills and industrial areas. As for soils collected from city parks, degree of contamination (mCd) was more suitable than IMN. Heavy metals Cd, Hg, Zn, and As were the main pollution elements in urban soils of Guangzhou. Potential ecological risks were mainly caused by Cd and Hg in urban soil of Guangzhou. Soil samples collected from city parks and the vicinity of the industrial area were moderately to highly and even extremely seriously polluted by heavy metals. Differing from the traditional cognition of the public, the ecological impact of heavy metal in soil in the vicinity of the landfill was similar to or even better than that within city parks.

1. Introduction

With the rapid urbanization and industrialization during the last decades, urban environments have been experiencing serious deterioration. Consequently, health and wellbeing of urban residents are affected by this deteriorated environment. As an attribute of urban activities, urban surface soil is the primary sink of all pollutants, including heavy metals. Previous studies indicated that heavy metals within urban surface soil are harmful to public health and the urban ecosystem [1,2,3,4]. Excessive enrichment of heavy metals in urban soils can lead to the destruction of soil ecosystems and other environmental problems, and in more severe cases can threaten human health [5]. Regular exposure to individual heavy metal or mixtures of heavy metals may cause cancer, liver problems, and neurological, hematological, endocrine, reproductive, and other health system disorders [6,7,8]. Many previous studies indicated different characteristics of soil heavy metal pollution in different urban function areas [9,10,11,12,13,14,15,16]. Yan et al. [17] revealed that metal enrichment in roadside soils was affected by the level of urbanization and road age. Obvious soil heavy metal pollution also appeared at public playgrounds [18,19]. Heavy metal pollution of soils collected from urban parks [20,21,22,23,24,25] and the vicinity of landfills [26,27,28] attracted the most attention during the last years. Meanwhile, heavy metals within urban soils were proved to originate from industrial areas, landfills, and public activity areas [29,30,31,32,33,34,35,36,37,38,39,40]. However, integration and comparison studies of soil heavy metal pollution for different function areas within a city are limited.
The study of soil heavy metal pollution for south China has been becoming a hotspot of environmental science due to the high geochemical background and the increasing human activities [41,42,43,44,45,46,47,48,49,50,51]. As the largest city in Southern China, many previous studies focused on heavy metal pollution of urban soil for different areas in Guangzhou. Compared to soil background values, heavy metals Cd, Cu, Hg, Mn, Pb, and Zn were significantly enriched in surface soil of Guangzhou due to a long history of urbanization and industrial activities [52,53,54,55,56,57,58,59,60,61]. However, few studies simultaneously concerned soil heavy metal pollution for different function areas in Guangzhou.
According to the conceptual FEP model proposed by Tatomir et al., the identification of pollution status which represents the “Feature” is an essential step for assessing the potential impact of heavy metal pollution [62]. As for the pollution assessment method, integrated pollution indices and the ecological risk index are useful tools that were widely used in previous studies. At least six indices were used for soil heavy metal pollution assessment by previous studies [21,63,64,65,66,67]. However, the assessed results using different methods were much different [11,14,43,55,68,69,70,71,72,73,74,75]. Therefore, selecting a proper index is a key for accurately acquiring the degree of contamination.
In the present study, heavy metal concentrations in surface soil samples collected from city parks, the vicinity of a landfill, and an industrial area within Guangzhou were simultaneously measured. Four pollution indices (Igeo, IMN, mCd, and CSI) and the potential ecological risk index (RI) were used to assess heavy metal pollution degree and its ecosystem risks, respectively. The main objective of this work is to enhance our understanding of the status of soil heavy metal pollution in Guangzhou, to reveal the differences in soil heavy metal pollution status and potential ecological risks for different urban function regions such as city parks, the vicinity of a landfill, and an industrial area, and to recommend more suitable assessment methods for evaluation of urban soil heavy metal pollution.

2. Materials and Methods

2.1. Study Area and Sampling

The study area, the city of Guangzhou, is the capital of Guangdong Province, located in South China (Figure 1). A subtropical monsoon climate characterized by being hot and humid with a mean annual temperature of 22 °C and mean annual rainfall of 1647 mm predominates the study area. Following to the guidelines of the Specification of Regional Ecogeochemistry Assessment and the Determination of Local Ecogeochemistry Assessment by the Ministry of Natural Resources of the People’s Republic of China, two hundred and twenty-nine surface soil (0–20 cm) samples were collected from city parks, landfills, and industrial areas within Guangzhou’s built-up area in 2015.
According to the distribution and developing history of city parks within Guangzhou, one hundred and thirty-two topsoil samples were collected from eleven parks within the city’s built-up area. Forty-one topsoil samples were collected from the vicinity of the Likeng landfill, which was put into use in 1992 and closed in April 2004. The Huangpu industrial zone with a state-owned large-scale enterprise Huangpu power plant at the southeast, a large oil storage of petrochemical plants at the northeast, and some other industries such as metal processing plants, concrete mixing plants, and fly ash plants within the area, was selected for the representative industrial area. Fifty-six topsoil samples were collected from the Huangpu industrial zone. The distribution of sampling sites is illustrated in the enlarged maps of Figure 1 for the three mentioned functional areas.

2.2. Heavy Metal Content Measurements

All samples were air dried at room temperature after sampling. After removing obvious gravel and roots, the samples were ground into a powder by sieving through a 74 μm mesh for element content measurements.
Heavy metal content measurements were performed at the ALS Minerals-ALS Chemex Laboratory, Guangzhou. An aliquot of a dry burning sample without organic matter was dissolved in aqua regia. Contents of heavy metals Copper (Cu), Nickel (Ni), and Cadmium (Cd) were determined using inductively coupled plasma mass spectrometry (ICP-MS, Agilent 7700x). Zinc (Zn), Lead (Pb), and Chromium (Cr) contents were measured by an X-ray fluorescence spectrometry. Arsenic (As) and Mercury (Hg) contents were analyzed using atomic fluorescence spectrometry. The detection limits were the following (as mg/kg): 0.2 Cu, 0.2 Ni, 0.001 Cd, 2.0 Zn, 0.5 Pb, 1.0 Cr, 0.2 As, and 0.004 Hg. During the measurements, quality controlling samples including standard samples, duplicate samples, and blank samples were added among the detected samples according to the regulations stated in ISO17025.

2.3. Pollution Indices

Pollution indices are widely used for comprehensive assessment of soil pollution degree [21,76,77,78,79]. Four pollution indices, Geoaccumulation index (Igeo), improved Nemerow index (IMN), degree of contamination (mCd), and contamination security index (CSI) were calculated for each sample to assess their heavy metal pollution degree. The calculating formulas and the pollution classification criteria used for each index are listed in Table 1. In order to reflect the differentiation of the specific area, the average values of A horizons in Guangdong Province (167 typical profiles, 33 main profiles) were used as the local natural background values.

2.4. Potential Ecological Risk Index

Potential ecological risk index (RI), introduced by Hakanson [84], is an indicator to assess degree of environmental risk caused by heavy metals in water and air, as well as in soil. RI is calculated for each sample according to the following equation.
R I = i = 1 n E r i = i = 1 n T r i C i C n i
where E r i is the potential ecological hazard coefficient of heavy metal i, T r i is the toxicity coefficient of heavy metal i, C i is the measured heavy metal content, and C n i is the background value of heavy metal content.
As suggested by Hakanson [84] and revised by Xu et al. [87], the values of T r i used in the present study are Zn = 1 < Cr = 2 < Pb = Cu = Ni = 5< As = 10 < Cd = 30 < Hg = 40. Again, the average values of layer A soils in Guangdong Province are used for C n i . Combined considering several references [78,84], the classification criteria of E r i and RI in this study are listed in Table 2.

3. Results

3.1. Heavy Metal Concentrations

A statistical summary of heavy metal content as well as the background value of surface soil (A horizon) in Guangdong is listed in Table 3.
Except the Cr content within surface soil around the landfill, average contents of all heavy metals within surface soil exceeded their background values. Even the minimum values of Zn, Pb, and Cd contents within surface soil exceeded their background values for the industrial area. According to the average contents listed in Table 3, contents of Cu, Zn, Ni, Cr, and Cd within surface soil increased from landfill, to city parks, to industrial area. Surface soil Pb content increased from city parks, to landfill, to industrial area. Surface soil As content increased from industrial area, to city parks, to landfill. Surface soil Hg content increased from landfill, to industrial area, to city parks.

3.2. Pollution Indices

The evaluated results of pollution indices listed in Table 1 are illustrated in Figure 2 for city parks, landfill, and industrial area.
The results of the Geoaccumulation index and IMN revealed that more than 70% of the measured 132 samples collected from city parks were moderately and moderately to highly polluted by heavy metals (Figure 2a). Samples showing slight or high to serious heavy metal pollution were about 10% of the total 132 samples. According to the results of the Geoaccumulation index for each heavy metal element illustrated in Figure 2a, almost all samples were unpolluted or slightly polluted by Ni and Cr. Most samples were slightly or moderately polluted by Cu, Zn, Pb, and As. However, most soil samples collected from city parks were moderately, moderately to highly, highly, seriously, or even extremely seriously polluted by Cd and Hg. Therefore, it can be concluded that the main pollution elements in urban city park soils in Guangzhou were Cd and Hg.
As for soil samples collected from the vicinity of the landfill, 73.2% of all samples were moderately to seriously polluted by heavy metals. All samples were clean or were slightly polluted by heavy metals Cr and Hg. More than ninety percent of the measured samples were unpolluted or slightly polluted by heavy metals Cu, Zn, Ni, and Pb. However, 56.1% and 48.8% of the measured samples collected from the vicinity of the landfill were moderately, moderately to highly, highly, and seriously polluted by Cd and As, respectively (Figure 2b).
As for the calculated results of IMN for soil samples collected from the industrial area, nearly 90% samples were moderately to seriously polluted by heavy metals. Furthermore, some samples collected from the industrial area were even extremely seriously polluted by HMs (Figure 2c). Fortunately, most surface soil samples collected from the industrial area showed no or only slight pollution by Ni (85.7%), Cr (87.5%), and As (69.6%). Of the measured soil samples collected from the industrial area, 32.1%, 35.7%, and 44.6% were unpolluted or slightly polluted by heavy metals Cu, Pb, and Hg. For all measured soil samples from the industrial area, percentages of moderate Cu, Pb, and Hg pollution were 46.4%, 37.5%, and 30.4%, respectively. More than half of the measured soil samples collected from the industrial area were moderately to highly, highly, seriously, and extremely seriously polluted by Zn. Concerning Cd in soil within the industrial area, all measured samples were polluted at different degrees. The percentages of measured samples under slight, moderate, moderate to high, high, serious, and extreme serious pollution degree were 5.4%, 19.6%, 7.1%, 42.9%, 14.3%, and 10.7%, respectively (Figure 2c). Therefore, it can be concluded that Cd and Zn are the main heavy metal pollution elements in surface soils of the industrial area in Guangzhou.

4. Discussion

4.1. Comparison of Assessment Results Using Different Indices

Comparing the pollution evaluation results illustrated in Figure 2, it can be obviously seen that soil heavy metal pollution in both the comprehensive results and each element descended from the industrial area, to city parks, to the vicinity of the landfill. Except Cr and Ni in city park soils and Hg and Cr in soils in the vicinity of the landfill, other heavy metals appeared with different enrichment degrees in surface soils of different function areas within Guangzhou (Figure 2). Furthermore, the pollution degree of each element in soils of city parks, the vicinity of the landfill, and the industrial area were decreased following the order Cd, Hg, Zn, As, Pb, and Cu; Cd, As, Zn, Ni, Pb, and Cu; and Cd, Zn, Cu, Pb, Hg, As, Ni, and Cr, respectively. Despite Cd being the most important heavy metal pollutant in soils collected from the three function areas, the percentages of different Cd pollution degrees were much different (Figure 2). Heavy metals Hg, As, and Zn were also important heavy metal pollutants for soils of city parks, the vicinity of the landfill, and the industrial area, respectively.
A suitable method for analysis is the premise of regional soil pollution assessment. Compared the results of IMN, mCd, and CSI illustrated in Figure 2, it can be seen that comprehensive pollution degrees classified by IMN and mCd were similar for soil samples collected from city parks. However, pollution degrees classified by CSI were much weaker than those classified by IMN and mCd for the three function areas, indicating that heavy metal pollution assessed by CSI may be underestimated for urban surface soils. Results of IMN indicated that percentages of measured soil samples under clean and slight pollution were 26.8% and 7.2% for samples collected from the vicinity of the landfill and the industrial area, respectively. Meanwhile, these percentages classified by calculated results of mCd were 53.7% and 26.7% for the vicinity of the landfill and the industrial area, respectively (Figure 2b,c). Since obvious significant differences appeared between assessing the results of IMN and mCd (Figure 2), comprehensive assessment results by previous studies are summarized in Figure 3 to compare with the calculated results of IMN and mCd in the present study.
As illustrated in Figure 3a, previous studies indicated that no more than 35% (about 34.4%) of measured soil samples suffered high or serious pollution of heavy metals. The calculated results of mCd illustrated in Figure 2a are similar to the mentioned results of previous studies. However, the calculated IMN results of the present study illustrated in Figure 2a indicated nearly half of the measured samples (about 47.7%) were under high or serious pollution. These results indicated that heavy metal pollution might be overestimated for soils collected from city parks using IMN. As for soils collected from the vicinity of landfills, the percentage of slight and moderate pollution assessed by calculated results of IMN was almost consistent with these results of previous studies (Figure 2b and Figure 3b). Meanwhile, the percentages of unpolluted and moderately polluted samples assessed by the calculated mCd were twice as much as and half of the results of previous studies, respectively (Figure 2b and Figure 3b). From Figure 2c and Figure 3c, the percentages of seriously polluted samples assessed by results of IMN and mCd for soils collected from the industrial area were consistent with and much lower than the results reported in previous studies, respectively. The percentages of unpolluted and slightly polluted soil samples within the industrial area assessed by the IMN results were much lower than the results of previous studies (Figure 2c and Figure 3c). Furthermore, the percentages of highly polluted soil samples assessed by the calculated IMN and mCd results were much higher and lower than the results of previous studies, respectively (Figure 2c and Figure 3c). Since heavy metals are continuously accumulated in urban soils, it is reasonable that the pollution degree of the present study is a little bit more serious than previous studies. Therefore, compared to the results of IMN, the pollution situation may be underestimated by the results of mCd. Thus, it can be concluded that IMN is more suitable for heavy metal pollution assessment for soils within the vicinity of landfills and industrial areas of Guangzhou.

4.2. Ecological Impact of Heavy Metal Pollution

The calculated results of potential ecological risk for every element (E) as well as total potential ecological risks (RI) of the measured eight heavy metals are illustrated in Figure 4 for city parks, landfill, and industrial area.
Although some samples were under different degrees of pollution, potential ecological risks caused by heavy metals Cu, Zn, Ni, Pb, Cr, and As can be ignored for all surface soil samples collected from the three different function areas. However, surface soil samples collected from the city parks, landfill, and industrial area are suffering some ecological risks from Cd and Hg (Figure 4). Of the measured samples collected from city parks and the industrial area, 54.5% and 80.4% were subjected to high or very high ecological risks caused by Cd, respectively. The percentages of measured samples under high and very high ecological risks of Hg were 72.7% and 46.4% for city parks and the industrial area, respectively (Figure 4a,c). These results are consistent with previous studies on the ecological risk of soil heavy metals in urban parks, landfills, industrial areas, and urban areas in Guangzhou and urban soils in China [48,53,57,59,61,89]. Meanwhile, only 26.8% and none of the measured soil samples collected from the landfill vicinity were subjected to high or very high ecological risks caused by Cd and Hg, respectively. Totally, the percentages of measured soil samples collected from city parks, the vicinity of the landfill, and the industrial area under high or very high ecological risks caused by soil heavy metals were 44.7%, 12.2%, and 71.5%, respectively (Figure 4). These results indicated that the soil environment within the vicinity of the landfill was better than that within city parks, which was much different from the public’s traditional cognition.

5. Conclusions

The identification of pollution status is an essential step for assessing the potential impact of urban soil heavy metal pollution. However, assessed results were much different using different methods. Therefore, selecting a suitable method should be one of the most important aspects of heavy metal evaluation. Based on the mentioned results of the discussion, the following conclusions that can be used for further relevant research are acquired.
The improved Nemerow index (IMN) calculated based on the Geoaccumulation index is more suitable for heavy metal pollution assessment for soils within the vicinity of landfills and industrial areas of urban areas. Meanwhile, the degree of contamination (mCd) is more suitable than IMN for soil heavy metal pollution assessment for city parks.
The pollution degree of each element in soils of city parks, the vicinity of the landfill, and the industrial area were decreased following the order: Cd > Hg > Zn > As > Pb > Cu; Cd > As > Zn > Ni > Pb > Cu; and Cd > Zn > Cu > Pb > Hg > As > Ni > Cr, respectively. Heavy metals Cd, Hg, Zn, and As were the main pollution elements in urban soils of Guangzhou.
Considerable, high, to very high ecological risk was caused by heavy metal pollution of most samples collected from city parks and the industrial area. Meanwhile, low to moderate ecological risk was caused by heavy metal pollution of most samples collected from the vicinity of the landfill. Soil heavy metal potential ecological risks were mainly caused by Cd and Hg for the investigated three function areas. That the soil environment within the vicinity of the landfill was better than that within city parks differed from the public’s traditional cognition.

Author Contributions

Conceptualization, T.O. and Y.G.; methodology, H.Z. and C.H.; investigation, Y.G., S.P. and Z.Z.; data curation, T.O. and Y.G.; writing—original draft preparation, H.Z. and T.O.; writing—review and editing, H.Z. and T.O.; supervision, Z.Z.; project administration, Z.Z. and S.P.; funding acquisition, T.O. and Y.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Science Foundation of China (Grant No. 41977261) and the Guangzhou Land Resources and Planning Commission (Grant No. GSZB22C0025G).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All the data analyzed/generated are included and available in the manuscript.

Acknowledgments

The authors are grateful to the anonymous reviewers for their constructive comments.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Galán, E.; Romero-Baena, A.J.; Aparicio, P.; González, I. A Methodological Approach for the Evaluation of Soil Pollution by Potentially Toxic Trace Elements. J. Geochem. Explor. 2019, 203, 96–107. [Google Scholar] [CrossRef]
  2. Modabberi, S.; Tashakor, M.; Sharifi Soltani, N.; Hursthouse, A.S. Potentially Toxic Elements in Urban Soils: Source Apportionment and Contamination Assessment. Environ. Monit. Assess. 2018, 190, 715. [Google Scholar] [CrossRef] [PubMed]
  3. Rastegari Mehr, M.; Keshavarzi, B.; Moore, F.; Sharifi, R.; Lahijanzadeh, A.; Kermani, M. Distribution, Source Identification and Health Risk Assessment of Soil Heavy Metals in Urban Areas of Isfahan Province, Iran. J. Afr. Earth Sci. 2017, 132, 16–26. [Google Scholar] [CrossRef]
  4. Wang, Z.; Guo, Y.; Zheng, X.; Zhou, X.; Shi, X. Environmental Geochemical Assessment and Health Risk Assessment of a Landfill in Guangzhou. J. Guizhou Univ. (Nat. Sci.) 2021, 38, 52-59+74. [Google Scholar]
  5. Wu, Y.; Li, X.; Yu, L.; Wang, T.; Wang, J.; Liu, T. Review of Soil Heavy Metal Pollution in China: Spatial Distribution, Primary Sources, and Remediation Alternatives. Resour. Conserv. Recycl. 2022, 181, 106261. [Google Scholar] [CrossRef]
  6. Wang, J.; Li, S.; Cui, X.; Li, H.; Qian, X.; Wang, C.; Sun, Y. Bioaccessibility, Sources and Health Risk Assessment of Trace Metals in Urban Park Dust in Nanjing, Southeast China. Ecotoxicol. Environ. Saf. 2016, 128, 161–170. [Google Scholar] [CrossRef]
  7. Zhang, M.; Li, X.; Yang, R.; Wang, J.; Ai, Y.; Gao, Y.; Zhang, Y.; Zhang, X.; Yan, X.; Liu, B.; et al. Multipotential Toxic Metals Accumulated in Urban Soil and Street Dust from Xining City, NW China: Spatial Occurrences, Sources, and Health Risks. Arch. Environ. Contam. Toxicol. 2019, 76, 308–330. [Google Scholar] [CrossRef]
  8. Tepanosyan, G.; Sahakyan, L.; Belyaeva, O.; Maghakyan, N.; Saghatelyan, A. Human Health Risk Assessment and Riskiest Heavy Metal Origin Identification in Urban Soils of Yerevan, Armenia. Chemosphere 2017, 184, 1230–1240. [Google Scholar] [CrossRef]
  9. Sun, Y.; Zhou, Q.; Xie, X.; Liu, R. Spatial, Sources and Risk Assessment of Heavy Metal Contamination of Urban Soils in Typical Regions of Shenyang, China. J. Hazard. Mater. 2010, 174, 455–462. [Google Scholar] [CrossRef]
  10. Zhang, Q.; Yu, R.; Fu, S.; Wu, Z.; Chen, H.Y.H.; Liu, H. Spatial Heterogeneity of Heavy Metal Contamination in Soils and Plants in Hefei, China. Sci. Rep. 2019, 9, 1049. [Google Scholar] [CrossRef]
  11. Han, Q.; Wang, M.; Cao, J.; Gui, C.; Liu, Y.; He, X.; He, Y.; Liu, Y. Health Risk Assessment and Bioaccessibilities of Heavy Metals for Children in Soil and Dust from Urban Parks and Schools of Jiaozuo, China. Ecotoxicol. Environ. Saf. 2020, 191, 110157. [Google Scholar] [CrossRef] [PubMed]
  12. Tepanosyan, G.; Maghakyan, N.; Sahakyan, L.; Saghatelyan, A. Heavy Metals Pollution Levels and Children Health Risk Assessment of Yerevan Kindergartens Soils. Ecotoxicol. Environ. Saf. 2017, 142, 257–265. [Google Scholar] [CrossRef] [PubMed]
  13. Lu, Y.; Yin, W.; Huang, L.; Zhang, G.; Zhao, Y. Assessment of Bioaccessibility and Exposure Risk of Arsenic and Lead in Urban Soils of Guangzhou City, China. Environ. Geochem. Health 2011, 33, 93–102. [Google Scholar] [CrossRef] [PubMed]
  14. Hu, Y.; Liu, X.; Bai, J.; Shih, K.; Zeng, E.Y.; Cheng, H. Assessing Heavy Metal Pollution in the Surface Soils of a Region That Had Undergone Three Decades of Intense Industrialization and Urbanization. Environ. Sci. Pollut. Res. 2013, 20, 6150–6159. [Google Scholar] [CrossRef]
  15. Famuyiwa, A.O.; Davidson, C.M.; Ande, S.; Oyeyiola, A.O. Potentially Toxic Elements in Urban Soils from Public-Access Areas in the Rapidly Growing Megacity of Lagos, Nigeria. Toxics 2022, 10, 154. [Google Scholar] [CrossRef]
  16. Chen, H.Z.; Gong, C.S.; Li, W.L.; Li, X.K.; Zhan, Q.J. Characteristic and Evaluation of Soil Pollution by Heavy Metal in Different Functional Zones of Guangzhou. J. Environ Health. 2010, 27, 700–703. [Google Scholar]
  17. Yan, G.; Mao, L.; Liu, S.; Mao, Y.; Ye, H.; Huang, T.; Li, F.; Chen, L. Enrichment and Sources of Trace Metals in Roadside Soils in Shanghai, China: A Case Study of Two Urban/Rural Roads. Sci. Total Environ. 2018, 631–632, 942–950. [Google Scholar] [CrossRef]
  18. Rodríguez-Oroz, D.; Vidal, R.; Fernandoy, F.; Lambert, F.; Quiero, F. Metal Concentrations and Source Identification in Chilean Public Children’s Playgrounds. Environ. Monit. Assess. 2018, 190, 703. [Google Scholar] [CrossRef]
  19. Peng, T.; O’Connor, D.; Zhao, B.; Jin, Y.; Zhang, Y.; Tian, L.; Zheng, N.; Li, X.; Hou, D. Spatial Distribution of Lead Contamination in Soil and Equipment Dust at Children’s Playgrounds in Beijing, China. Environ. Pollut. 2019, 245, 363–370. [Google Scholar] [CrossRef]
  20. Madrid, L.; Díaz-Barrientos, E.; Madrid, F. Distribution of Heavy Metal Contents of Urban Soils in Parks of Seville. Chemosphere 2002, 49, 1301–1308. [Google Scholar] [CrossRef]
  21. Gąsiorek, M.; Kowalska, J.; Mazurek, R.; Pająk, M. Comprehensive Assessment of Heavy Metal Pollution in Topsoil of Historical Urban Park on an Example of the Planty Park in Krakow (Poland). Chemosphere 2017, 179, 148–158. [Google Scholar] [CrossRef] [PubMed]
  22. Adedeji, O.H.; Olayinka, O.O.; Tope-Ajayi, O.O.; Adekoya, A.S. Assessing Spatial Distribution, Potential Ecological and Human Health Risks of Soil Heavy Metals Contamination around a Trailer Park in Nigeria. Sci. Afr. 2020, 10, e00650. [Google Scholar] [CrossRef]
  23. Wang, X.; Birch, G.F.; Liu, E. Traffic Emission Dominates the Spatial Variations of Metal Contamination and Ecological-Health Risks in Urban Park Soil. Chemosphere 2022, 297, 134155. [Google Scholar] [CrossRef] [PubMed]
  24. Gu, Y.-G.; Lin, Q.; Gao, Y.-P. Metals in Exposed-Lawn Soils from 18 Urban Parks and Its Human Health Implications in Southern China’s Largest City, Guangzhou. J. Clean. Prod. 2016, 115, 122–129. [Google Scholar] [CrossRef]
  25. Gu, Y.-G.; Gao, Y.-P. Bioaccessibilities and Health Implications of Heavy Metals in Exposed-Lawn Soils from 28 Urban Parks in the Megacity Guangzhou Inferred from an in Vitro Physiologically-Based Extraction Test. Ecotoxicol. Environ. Saf. 2018, 148, 747–753. [Google Scholar] [CrossRef]
  26. Nannoni, F.; Mazzeo, R.; Santolini, R.; Protano, G. Multi-Matrix Environmental Monitoring to Assess Heavy Element Distribution around a Municipal Solid Waste Landfill in Italy. Int. J. Environ. Sci. Technol. 2017, 14, 2591–2602. [Google Scholar] [CrossRef]
  27. Hölzle, I.; Somani, M.; Ramana, G.V.; Datta, M. Heavy Metals in Soil-like Material from Landfills—Resource or Contaminants? J. Clean. Prod. 2022, 133136. [Google Scholar] [CrossRef]
  28. Xie, W.; Chen, D.; Zhang, H.; Song, G.; Chang, X. An Investigation into Heavy Metals Pollution in a Landfill of Guangzhou. In Proceedings of the 2009 3rd International Conference on Bioinformatics and Biomedical Engineering, Beijing, China, 11–13 June 2009; IEEE: Beijing, China, 2009; pp. 1–4. [Google Scholar]
  29. Lv, J.; Liu, Y. An Integrated Approach to Identify Quantitative Sources and Hazardous Areas of Heavy Metals in Soils. Sci. Total Environ. 2019, 646, 19–28. [Google Scholar] [CrossRef]
  30. Tume, P.; González, E.; King, R.W.; Cuitiño, L.; Roca, N.; Bech, J. Distinguishing between Natural and Anthropogenic Sources for Potentially Toxic Elements in Urban Soils of Talcahuano, Chile. J. Soils Sediments 2018, 18, 2335–2349. [Google Scholar] [CrossRef]
  31. Jin, Z.; Lv, J. Integrated Receptor Models and Multivariate Geostatistical Simulation for Source Apportionment of Potentially Toxic Elements in Soils. CATENA 2020, 194, 104638. [Google Scholar] [CrossRef]
  32. Ou, C.; Zhu, X.; Hu, L.; Wu, X.; Yu, W.; Wu, Y. Source Apportionment of Soil Contamination Based on Multivariate Receptor and Robust Geostatistics in a Typical Rural–Urban Area, Wuhan City, Middle China. Open Chem. 2020, 18, 244–258. [Google Scholar] [CrossRef]
  33. Wang, Z.; Chen, X.; Yu, D.; Zhang, L.; Wang, J.; Lv, J. Source Apportionment and Spatial Distribution of Potentially Toxic Elements in Soils: A New Exploration on Receptor and Geostatistical Models. Sci. Total Environ. 2021, 759, 143428. [Google Scholar] [CrossRef] [PubMed]
  34. Yang, Z.; Li, X.; Wang, Y.; Chang, J.; Liu, X. Trace Element Contamination in Urban Topsoil in China during 2000–2009 and 2010–2019: Pollution Assessment and Spatiotemporal Analysis. Sci. Total Environ. 2021, 758, 143647. [Google Scholar] [CrossRef]
  35. Li, Y.; Dong, Z.; Feng, D.; Zhang, X.; Jia, Z.; Fan, Q.; Liu, K. Study on the Risk of Soil Heavy Metal Pollution in Typical Developed Cities in Eastern China. Sci. Rep. 2022, 12, 3855. [Google Scholar] [CrossRef] [PubMed]
  36. Pecina, V.; Brtnický, M.; Baltazár, T.; Juřička, D.; Kynický, J.; Galiová, M.V. Human health and ecological risk assessment of trace elements in urban soils of 101 cities in China: A meta-analysis. Chemosphere 2021, 267, 129215. [Google Scholar] [CrossRef]
  37. Tume, P.; González, E.; Reyes, F.; Fuentes, J.P.; Roca, N.; Bech, J.; Medina, G. Sources Analysis and Health Risk Assessment of Trace Elements in Urban Soils of Hualpen, Chile. CATENA 2019, 175, 304–316. [Google Scholar] [CrossRef]
  38. Nazarpour, A.; Watts, M.J.; Madhani, A.; Elahi, S. Source, Spatial Distribution and Pollution Assessment of Pb, Zn, Cu, and Pb, Isotopes in Urban Soils of Ahvaz City, a Semi-Arid Metropolis in Southwest Iran. Sci. Rep. 2019, 9, 5349. [Google Scholar] [CrossRef]
  39. Zhang, M.; Lu, X.; Shi, D.; Pan, H. Toxic Metal Enrichment Characteristics and Sources of Arid Urban Surface Soil in Yinchuan City, China. J. Arid Land 2018, 10, 653–662. [Google Scholar] [CrossRef]
  40. Horváth, A.; Kalicz, P.; Farsang, A.; Balázs, P.; Berki, I.; Bidló, A. Influence of Human Impacts on Trace Metal Accumulation in Soils of Two Hungarian Cities. Sci. Total Environ. 2018, 637–638, 1197–1208. [Google Scholar] [CrossRef]
  41. Cheng, H.; Li, M.; Zhao, C.; Li, K.; Peng, M.; Qin, A.; Cheng, X. Overview of Trace Metals in the Urban Soil of 31 Metropolises in China. J. Geochem. Explor. 2014, 139, 31–52. [Google Scholar] [CrossRef]
  42. Wang, S.; Cai, L.-M.; Wen, H.-H.; Luo, J.; Wang, Q.-S.; Liu, X. Spatial Distribution and Source Apportionment of Heavy Metals in Soil from a Typical County-Level City of Guangdong Province, China. Sci. Total Environ. 2019, 655, 92–101. [Google Scholar] [CrossRef] [PubMed]
  43. Chen, H.; Teng, Y.; Lu, S.; Wang, Y.; Wang, J. Contamination Features and Health Risk of Soil Heavy Metals in China. Sci. Total Environ. 2015, 512–513, 143–153. [Google Scholar] [CrossRef] [PubMed]
  44. Li, C.; Sanchez, G.M.; Wu, Z.; Cheng, J.; Zhang, S.; Wang, Q.; Li, F.; Sun, G.; Meentemeyer, R.K. Spatiotemporal Patterns and Drivers of Soil Contamination with Heavy Metals during an Intensive Urbanization Period (1989–2018) in Southern China. Environ. Pollut. 2020, 260, 114075. [Google Scholar] [CrossRef]
  45. Zhou, X.-Y.; Wang, X.-R. Impact of Industrial Activities on Heavy Metal Contamination in Soils in Three Major Urban Agglomerations of China. J. Clean. Prod. 2019, 230, 1–10. [Google Scholar] [CrossRef]
  46. Xiao, Y.; Guo, M.; Li, X.; Luo, X.; Pan, R.; Ouyang, T. Spatial Distribution, Pollution, and Health Risk Assessment of Heavy Metal in Agricultural Surface Soil for the Guangzhou-Foshan Urban Zone, South China. PLoS ONE 2020, 15, e0239563. [Google Scholar] [CrossRef] [PubMed]
  47. Li, T.; Jia, C.; Zhang, J.; Zheng, F.; Xian, Z. Heavy metal contamination of green space soils and its ecological risk assessment in industrial district of the pearl river delta. In Proceedings of the 2019 Annual Scientific and Technical Conference of the Chinese Society of Environmental Sciences—Environmental Engineering Technology Innovation and Application Sub-Forum (III), Xi’an, China, 23–25 August 2019; pp. 663–667+755. [Google Scholar]
  48. Cai, Y.M.; Zhang, Y.L.; Ren, L.L.; Li, C.X.; Wang, G.N.; Huang, H.S. Characteristics and Ecological Risk Assessment of Heavy Metal Pollution in Vegetable Soils of Guangzhou Urban Districts. Guangdong Agric. Sci. 2019, 46, 73–78. [Google Scholar]
  49. Lei, G.; Chen, Z.; Liu, Q.; Peng, X. The assessments of polluted degree and potential ecological hazards of heavy metals in suburban soil of Guangzhou city. China Environ. Sci. 2013, 33, 49–53. [Google Scholar]
  50. Zhao, H.; He, B.; Wang, T.Y.; Meng, J.; Xiao, R.B.; Liu, S.R.; Zhou, Y.Q.; Shi, B. Pollution characteristics of heavy metals and source-sink relationship in typical city of the South China. Acta Sci. 2019, 39, 2231–2239. [Google Scholar]
  51. Shang, S.; Zhong, W.; Wei, Z.; Zhu, C.; Ye, S.; Tang, X.; Chen, Y.; Tian, L.; Chen, B. Heavy Metals in Surface Sediments of Lakes in Guangzhou Public Parks in China and Their Relations with Anthropogenic Activities and Urbanization. Hum. Ecol. Risk Assess. Int. J. 2017, 23, 2002–2016. [Google Scholar] [CrossRef]
  52. Lu, Y.; Jia, C.; Zhang, G.; Zhao, Y.; Wilson, M.A. Spatial Distribution and Source of Potential Toxic Elements (PTEs) in Urban Soils of Guangzhou, China. Environ. Earth Sci. 2016, 75, 329. [Google Scholar] [CrossRef]
  53. Li, J.H.; Lu, Y.; Zhang, C.; Deng, X.L.; Lian, J. The status quo and potential ecological risks assessment of heavy metals in agricultural soils near a petrochemical complex in Guangzhou. Chinese J. Soil Sci. 2011, 42, 1242–1246. [Google Scholar]
  54. Zhuo, W.S.; Tang, J.F.; Guan, D.S. The Distributive Character and Pollution Assessment of Heavy Metals in Urban Soil of Guangzhou. Acta Sci. Nat. Univ. Sunyatseni 2009, 48, 47–51. [Google Scholar]
  55. Wang, C.M.; Gao, Y.H.; Zhang, D.W.; He, Q.J.; Lv, Y. Investigation and Assessment of Heavy Metals in Soil and Plants from a Sealed Landfill in Zengcheng, Guangzhou, China. J. Agro-Environ. Sci. 2013, 32, 714–720. [Google Scholar]
  56. Cai, Q.-Y.; Mo, C.-H.; Li, H.-Q.; Lü, H.; Zeng, Q.-Y.; Li, Y.-W.; Wu, X.-L. Heavy Metal Contamination of Urban Soils and Dusts in Guangzhou, South China. Environ. Monit. Assess. 2013, 185, 1095–1106. [Google Scholar] [CrossRef]
  57. Zhang, X.M. Heavy Metal Pollution and Ecological Risk Assessment of Soil in A Dictrict of Guangzhou. Guangzhou Chem. Ind. 2020, 48, 152–154+197. [Google Scholar]
  58. Li, C.; Sun, G.; Wu, Z.; Zhong, H.; Wang, R.; Liu, X.; Guo, Z.; Cheng, J. Soil Physiochemical Properties and Landscape Patterns Control Trace Metal Contamination at the Urban-Rural Interface in Southern China. Environ. Pollut. 2019, 250, 537–545. [Google Scholar] [CrossRef] [PubMed]
  59. Wang, Y.S.; Liu, C.J.; Chen, X.Y.; Chen, J.X.; Wu, S.S.; Yang, W.C.; Huang, D.J. Pollution Risk Assessment of Heavy Metals in Soils Around a Municipal Solid Waste Incinerator. J. S. China Norm. Univ. 2020, 52, 57–64. [Google Scholar]
  60. Lei, G.; Liu, Q.; Chen, Z.; Peng, X.; Zhang, Y.; Ding, C.; Zhao, S. Comparative Study on Characters of Soil Heavy Metal Pollution in Different Industries. Soils 2013, 45, 1023–1027. [Google Scholar]
  61. Liang, M.J.; Xiong, F.; Zeng, J.W.; Yu, W.D.; Zhang, Y.L.; Zhou, S.J. Heavy Metal Pollution and Ecological Risk Assessment of Farmland Soil Around Three Types of Industrial Enterprises in Guangzhou Suburb. Guangdong Agric. Sci. 2021, 48, 103–110. [Google Scholar]
  62. Tatomir, A.; McDermott, C.; Bensabat, J.; Class, H.; Edlmann, K.; Taherdangkoo, R.; Sauter, M. Conceptual Model Development Using a Generic Features, Events, and Processes (FEP) Database for Assessing the Potential Impact of Hydraulic Fracturing on Groundwater Aquifers. Adv. Geosci. 2018, 45, 185–192. [Google Scholar] [CrossRef]
  63. Vega, A.S.; Arce, G.; Rivera, J.I.; Acevedo, S.E.; Reyes-Paecke, S.; Bonilla, C.A.; Pastén, P. A Comparative Study of Soil Metal Concentrations in Chilean Urban Parks Using Four Pollution Indexes. Appl. Geochem. 2022, 141, 105230. [Google Scholar] [CrossRef]
  64. Kowalska, J.B.; Mazurek, R.; Gąsiorek, M.; Zaleski, T. Pollution Indices as Useful Tools for the Comprehensive Evaluation of the Degree of Soil Contamination–A Review. Environ. Geochem. Health 2018, 40, 2395–2420. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Obiri-Nyarko, F.; Duah, A.A.; Karikari, A.Y.; Agyekum, W.A.; Manu, E.; Tagoe, R. Assessment of Heavy Metal Contamination in Soils at the Kpone Landfill Site, Ghana: Implication for Ecological and Health Risk Assessment. Chemosphere 2021, 282, 131007. [Google Scholar] [CrossRef]
  66. Xie, Z.Y.; Zhang, Y.J.; Chen, D.Q.; Yang, J.J.; Liang, Y.J. Research on assessment methods for soil heavy metal pollution: A case study of Guangzhou. J. Agro-Environ. Sci. 2016, 35, 1329–1337. [Google Scholar]
  67. Wu, Q.; Tam, N.F.Y.; Leung, J.Y.S.; Zhou, X.; Fu, J.; Yao, B.; Huang, X.; Xia, L. Ecological Risk and Pollution History of Heavy Metals in Nansha Mangrove, South China. Ecotoxicol. Environ. Saf. 2014, 104, 143–151. [Google Scholar] [CrossRef] [PubMed]
  68. Wang, Z.; Guo, Y.; Shi, X.L. Assessment of Heavy Metal Pollution in Soil of an Industrial Zone in Guangzhou. Environ. Sci. Technol. 2021, 38, 52–59+74. [Google Scholar]
  69. Lin, M.; Li, S.; Sun, X.; Yang, S.; Li, J. Heavy Metal Contamination in Green Space Soils of Beijing, China. Acta Agric. Scand. Sect. B. Soil Plant Sci. 2018, 68, 291–300. [Google Scholar] [CrossRef]
  70. Xie, T.; Wang, M.; Chen, W.; Uwizeyimana, H. Impacts of Urbanization and Landscape Patterns on the Accumulation of Heavy Metals in Soils in Residential Areas in Beijing. J. Soils Sediments 2019, 19, 148–158. [Google Scholar] [CrossRef]
  71. Wang, M.; Han, Q.; Gui, C.; Cao, J.; Liu, Y.; He, X.; He, Y. Differences in the Risk Assessment of Soil Heavy Metals between Newly Built and Original Parks in Jiaozuo, Henan Province, China. Sci. Total Environ. 2019, 676, 1–10. [Google Scholar] [CrossRef]
  72. Guan, D.S.; Peart, M.R. Heavy metal concentrations in plants and soils at roadside locations and parks of urban Guangzhou. J. Environ. Sci. 2006, 18, 495–502. [Google Scholar]
  73. Lv, Y.; Cao, Y.J. Investigation and evaluation of landfill closure soil and plant heavy metals. China Sci. Technol. Overv. 2013, 32, 714–720. [Google Scholar]
  74. Gu, Y.-G.; Gao, Y.-P.; Lin, Q. Contamination, Bioaccessibility and Human Health Risk of Heavy Metals in Exposed-Lawn Soils from 28 Urban Parks in Southern China’s Largest City, Guangzhou. Appl. Geochem. 2016, 67, 52–58. [Google Scholar] [CrossRef]
  75. Li, Y.J.; Zhang, K.Y. Character of content and contamination evaluation for heavy metal in the soil of Guangzhou parks. China Gard. Digest. 2012, 28, 43–45. [Google Scholar]
  76. Mazurek, R.; Kowalska, J.B.; Gąsiorek, M.; Zadrożny, P.; Wieczorek, J. Pollution Indices as Comprehensive Tools for Evaluation of the Accumulation and Provenance of Potentially Toxic Elements in Soils in Ojców National Park. J. Geochem. Explor. 2019, 201, 13–30. [Google Scholar] [CrossRef]
  77. Santos-Francés, F.; Martínez-Graña, A.; Zarza, C.; Sánchez, A.; Rojo, P. Spatial Distribution of Heavy Metals and the Environmental Quality of Soil in the Northern Plateau of Spain by Geostatistical Methods. Int. J. Environ. Res. Public. Health 2017, 14, 568. [Google Scholar] [CrossRef]
  78. Pejman, A.; Nabi Bidhendi, G.; Ardestani, M.; Saeedi, M.; Baghvand, A. A New Index for Assessing Heavy Metals Contamination in Sediments: A Case Study. Ecol. Indic. 2015, 58, 365–373. [Google Scholar] [CrossRef]
  79. Kowalska, J.; Mazurek, R.; Gąsiorek, M.; Setlak, M.; Zaleski, T.; Waroszewski, J. Soil Pollution Indices Conditioned by Medieval Metallurgical Activity—A Case Study from Krakow (Poland). Environ. Pollut. 2016, 218, 1023–1036. [Google Scholar] [CrossRef]
  80. Müller, G. Index of geoaccumulation in sediments of the Rhine River. GeoJournal 1969, 2, 108–118. [Google Scholar]
  81. Förstner, U.; Ahlf, W.; Calmano, W.; Kersten, M. Sediment criteria development. In Sediments and Environmental Geochemistry; Heling, D., Rothe, P., Förstner, U., Stoffers, P., Eds.; Springer: Berlin/Heidelberg, Germany, 1990; pp. 311–338. ISBN 978-3-642-75099-1. [Google Scholar]
  82. Ghrefat, H.A.; Abu-Rukah, Y.; Rosen, M.A. Application of Geoaccumulation Index and Enrichment Factor for Assessing Metal Contamination in the Sediments of Kafrain Dam, Jordan. Environ. Monit. Assess. 2011, 178, 95–109. [Google Scholar] [CrossRef]
  83. Martínez, L.L.G.; Poleto, C. Assessment of Diffuse Pollution Associated with Metals in Urban Sediments Using the Geoaccumulation Index (Igeo). J. Soils Sediments 2014, 14, 1251–1257. [Google Scholar] [CrossRef]
  84. Hakanson, L. An Ecological Risk Index for Aquatic Pollution Control.a Sedimentological Approach. Water Res. 1980, 14, 975–1001. [Google Scholar] [CrossRef]
  85. Abrahim, G.M.S.; Parker, R.J. Assessment of Heavy Metal Enrichment Factors and the Degree of Contamination in Marine Sediments from Tamaki Estuary, Auckland, New Zealand. Environ. Monit. Assess. 2007, 136, 227–238. [Google Scholar] [CrossRef] [PubMed]
  86. Long, E.R.; Macdonald, D.D.; Smith, S.L.; Calder, F.D. Incidence of Adverse Biological Effects within Ranges of Chemical Concentrations in Marine and Estuarine Sediments. Environ. Manag. 1995, 19, 81–97. [Google Scholar] [CrossRef]
  87. Xu, Z.Q.; Ni, S.J.; Tuo, X.G.; Zhang, C.J. Calculation of heavy metals’ toxicity coefficient in the evaluation of potential ecological risk index. Environ. Sci. Technol. 2008, 31, 112–115. [Google Scholar]
  88. China National Environmental Monitoring Centre. The Background Values of Soil Elements in China; China Environmental Science Press: Beijing, China, 1990. [Google Scholar]
  89. Liu, Y.; Hu, L.S.; Zhang, C.X.; Xie, M.Y.; Xie, X.M.; Huang, C.S. Spatial Distribution and Risk Assessment of Heavy Metals in Contaminated Soil in Guangzhou. J. Wuhan Inst. Technol. 2018, 40, 127–131. [Google Scholar]
Figure 1. Location of the study area and distribution of sampling sites. Red dots represent sampling sites.
Figure 1. Location of the study area and distribution of sampling sites. Red dots represent sampling sites.
Applsci 12 09345 g001
Figure 2. Percentage composition of different pollution degree based on calculation results of Igeo for every element and IMN, mCd, and CSI for eight heavy metals (a) city parks, (b) landfill, and (c) industrial area.
Figure 2. Percentage composition of different pollution degree based on calculation results of Igeo for every element and IMN, mCd, and CSI for eight heavy metals (a) city parks, (b) landfill, and (c) industrial area.
Applsci 12 09345 g002aApplsci 12 09345 g002b
Figure 3. Soil heavy metal pollution assessment results by previous studies for the city of Guangzhou. (a) City parks (revised from [13,51,56,67,72]), (b) Landfills (revised from [14,55,59,73]), and (c) Industrial areas (revised from [13,14,47,49,53,57,60,61]).
Figure 3. Soil heavy metal pollution assessment results by previous studies for the city of Guangzhou. (a) City parks (revised from [13,51,56,67,72]), (b) Landfills (revised from [14,55,59,73]), and (c) Industrial areas (revised from [13,14,47,49,53,57,60,61]).
Applsci 12 09345 g003
Figure 4. Percentage composition of different potential ecological risks caused by soil heavy metal based on calculation results of E for every element and RI for eight heavy metals: (a) city parks, (b) landfill, and (c) industrial area.
Figure 4. Percentage composition of different potential ecological risks caused by soil heavy metal based on calculation results of E for every element and RI for eight heavy metals: (a) city parks, (b) landfill, and (c) industrial area.
Applsci 12 09345 g004aApplsci 12 09345 g004b
Table 1. Indices of pollution used in this study.
Table 1. Indices of pollution used in this study.
IndexDescription and Aim of UseFormulaClassifications of Contamination Situation
Geoaccumulation index (Igeo)Igeo determines metal contamination in soil with respect to natural background level as a reference [80]. Classification criteria according to Förstner et al. [81]. I g e o = l o g 2 [ C k B n ]
C —measured heavy metal content, B n —background value of heavy metal content, k —the petrogenesis effect, usually set to 1.5 [82,83]
≤0: unpolluted; 0–1: slightly polluted; 1–2: moderately polluted; 2–3: moderately to highly polluted; 3–4: highly polluted; 4–5: seriously polluted; ≥5: extremely seriously polluted.
Improved Nemerow index (IMN)IMN allows the assessment of the overall degree of soil pollution and includes the contents of all analyzed elements. The contamination factor is substituted by the Igeo [76,77]. I M N = ( I g e o m a x 2 + I g e o a v e 2 ) 2
I g e o m a x —the maximum value of the Igeo of all metals in a sample,
I g e o a v e —the arithmetic mean of the Igeo of all metals in a sample
<0.5: uncontaminated; 0.5–1: slightly contaminated; 1–2: moderately contaminated; 2–3: moderately to heavily contaminated; 3–4: heavily contaminated; 4–5: heavily to extremely contaminated; ≥5: extremely contaminated.
Degree of contamination (mCd)mCd assesses the degree of contamination in soil [84,85]. m C d = i = 1 n C s i C n i n
C s i —measured heavy metal content, C n i —background value of heavy metal content
<1.5: nil to very low degree of contamination; 1.5–2: low degree of contamination; 2–4: moderate degree of contamination; 4–8: high degree of contamination; 8–16: very high degree of contamination; 16–32: extremely high degree of contamination; ≥32: ultra-high degree of contamination.
Contamination security index (CSI)CSI, introduced by Pejman et al. [78], is informative about the heavy metal pollution intensity in soil. C S I = i = 1 n w i [ ( C E R L ) 1 2 + ( C E R M ) 2 ]
w i —weight for each heavy metal, calculated according to Pejman et al. [78], C —measured heavy metal content, effects range low ( E R L ) , and effects range median ( E R M ) , given by Long et al. [86]
<0.5: uncontaminated; 0.5–1.5: low severity of contamination; 1.5–2.5: moderate severity of contamination; 2.5–3: moderate to high severity of contamination; 3–4: high severity of contamination; 4–5: very high severity of contamination; ≥5: ultra-high severity of contamination.
Table 2. Classification criteria of potential ecological risk index.
Table 2. Classification criteria of potential ecological risk index.
E r i   Values RI ValuesRisk Intensity
<40<150Low ecological risk
40–80150–300Moderate ecological risk
80–160300–600Considerable ecological risk
160–320600–1200High ecological risk
≥320≥1200Very high ecological risk
Table 3. Statistical summary of heavy metal contents (unit: mg/kg).
Table 3. Statistical summary of heavy metal contents (unit: mg/kg).
AreaCuZnNiPbCrAsCdHg
City parksMin8.218.06.422.213.06.30.0120.006
Max240.03660.065.1564.0145.0305.015.80011.950
Ave44.0203.019.9105.051.734.70.5990.804
Std.32.0351.79.277.118.135.71.5021.329
CV (%)73.0173.246.473.435.0103.2251.8165.4
Landfill Min8.313.04.814.812.05.30.0100.006
Max160.0268.0127.55420.0145.0604.03.1500.217
Ave24.483.219.3177.744.656.40.3100.105
Std.28.255.422.8839.627.6109.20.5150.059
CV (%)115.666.6118.4472.561.9193.8165.859.2
Industrial areaMin9.656.08.046.021.05.10.1010.043
Max2365.05640.0136.8942.01120.078.517.6501.570
Ave170.4601.130.8204.6107.019.31.4150.353
Std.407.21080.628.9200.4162.214.02.4520.312
CV (%)239.0179.893.797.9151.672.5173.388.5
Background value of surface soil (A horizon) in Guangdong) *17.047.314.436.050.58.90.0560.078
* Data taken from The Background Values of Soil Elements in China [88].
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Zhou, H.; Ouyang, T.; Guo, Y.; Peng, S.; He, C.; Zhu, Z. Assessment of Soil Heavy Metal Pollution and Its Ecological Risk for City Parks, Vicinity of a Landfill, and an Industrial Area within Guangzhou, South China. Appl. Sci. 2022, 12, 9345. https://doi.org/10.3390/app12189345

AMA Style

Zhou H, Ouyang T, Guo Y, Peng S, He C, Zhu Z. Assessment of Soil Heavy Metal Pollution and Its Ecological Risk for City Parks, Vicinity of a Landfill, and an Industrial Area within Guangzhou, South China. Applied Sciences. 2022; 12(18):9345. https://doi.org/10.3390/app12189345

Chicago/Turabian Style

Zhou, Huimin, Tingping Ouyang, Yu Guo, Shasha Peng, Chenjian He, and Zhaoyu Zhu. 2022. "Assessment of Soil Heavy Metal Pollution and Its Ecological Risk for City Parks, Vicinity of a Landfill, and an Industrial Area within Guangzhou, South China" Applied Sciences 12, no. 18: 9345. https://doi.org/10.3390/app12189345

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop