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Sustainable Management of Heavy Metals

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 69246

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Laboratory of Chemical Engineering and Engineering Sustainability, Faculty of Pure and Applied Sciences, Open University of Cyprus (OUC), Giannou Kranidioti 89, Latsia, Nicosia 2231, Cyprus
Interests: strategic planning development; zero waste approach; waste prevention; food waste; fashion waste; circular and bio-economy and industrial symbiosis; solid waste management and treatment (including hazardous and explosive); end of waste criteria; life cycle assessment (LCA); material flow analysis (MFA); waste to energy
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Department of Agrochemistry and Environment, University Miguel Hernandez of Elche, Av. de la Universidad s/n, 03206, Elche, Alicante, Spain
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Special Issue Information

Dear Colleagues,

Heavy metals, in general trace elements, are one of the major environmental problems. Nowadays, an increasing environmental and global public health concern related with environmental contamination by heavy metals are well known. Moreover, human exposure has risen dramatically because of an exponential increase of their use in several activities such as agricultural, industrial, technological and urban applications. They are presented in soils, water and atmosphere and they are a serious risk for the food chain.

United Nations through FAO and the European Union are concerned about the problem of heavy metal contamination and its impact on the food chain. Heavy metals, soil and water pollution, are in the target of the food security.

The main sources that heavy metals are produced include industrial, geogenic, agricultural, mining, wastewaters, domestic effluents, pharmaceutical and atmospheric causes. Heavy metals bioavailability is influenced by physical, chemical and biological factors. Temperature, adsorption and sequestration are consider as physical while complexation kinetics, leachability and mobility, lipid solubility and octanol/water partition coefficients are related with chemical factors. Biological factors such as species characteristics, trophic interactions, and biochemical/physiological adaptation, also play an important role.

Heavy metals are related also with health as are entering into our body through food chain. Also moreover illegal disposal of waste such as affected sewage sludge with heavy metals or household waste may affect soils and ground waters which may entering into human body through food chain and or breath or from humans skin

The studies of this special issue are expected to address:

  • The source and distribution of heavy metals in the environment (soil, water, air, living organisms, waste).
  • The mapping of areas at a global and regional scale where pollution is a high risk.
  • The consequences on the environment and food security of heavy metals.
  • The relation of trace elements with zero waste strategy and circular economy.
  • The sustainable strategies for the remediation of heavy metal pollution.
  • The impact of metals in the environmental policy
  • Methods to remove and or uptake heavy metals

Prof. Jose Navarro-Pedreño
Prof. Antonis A. Zorpas
Prof. I. Gómez Lucas
Guest Editors

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Keywords

  • Distribution
  • environmental health
  • food security
  • metal extractions
  • metals leachability
  • pollution
  • remediation
  • strategies on metal science

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Published Papers (18 papers)

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Research

14 pages, 2938 KiB  
Article
The Ecological Risk Assessment and the Chemical Speciation of Heavy Metals in Ash after the Incineration of Municipal Sewage Sludge
by Jolanta Latosińska and Przemysław Czapik
Sustainability 2020, 12(16), 6517; https://doi.org/10.3390/su12166517 - 12 Aug 2020
Cited by 19 | Viewed by 2648
Abstract
Popular incineration of sewage sludge results in the increase in heavy metals content in ash. The knowledge of the total content of heavy metals in sewage sludge ash does not demonstrate a potential hazard. The toxicity of heavy metals in great measure depends [...] Read more.
Popular incineration of sewage sludge results in the increase in heavy metals content in ash. The knowledge of the total content of heavy metals in sewage sludge ash does not demonstrate a potential hazard. The toxicity of heavy metals in great measure depends on the form of their occurrence. The prevailing norms do not require the ecological risk assessment of the environmental burden with heavy metals for the choice of the method of the utilization of sewage sludge ash. The paper presents the research results on the mobility of heavy metals in sewage sludge ash after its incineration. The geo-accumulation index (IGAI), the potential ecological risk index (PERI) and the risk assessment code (RAC) were used for the evaluation of the potential soil contamination with heavy metals. The authors also suggested a new formula, which took into consideration more factors influencing the risk of the contamination of a water-soil environment with heavy metals—the water and soil environment risk index (WSERI). The calculated indices for sewage sludge ash indicate the risk of soil contamination with heavy metals. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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26 pages, 11900 KiB  
Article
Environmentally Degraded Mining Areas of Eastern Slovakia As a Potential Object of Geotourism
by Vladimír Čech, Bohuslava Gregorová, Juliana Krokusová, Vladislava Košová, Pavel Hronček, Mário Molokáč and Jana Hlaváčová
Sustainability 2020, 12(15), 6029; https://doi.org/10.3390/su12156029 - 27 Jul 2020
Cited by 8 | Viewed by 3126
Abstract
The paper deals with the possibilities of further use of environmentally degraded and polluted areas on the example of (mining and industrial) activities residues in the Central Spiš region in eastern Slovakia. On the example of the Slovinky mining tailing pond, the Markušovce [...] Read more.
The paper deals with the possibilities of further use of environmentally degraded and polluted areas on the example of (mining and industrial) activities residues in the Central Spiš region in eastern Slovakia. On the example of the Slovinky mining tailing pond, the Markušovce mining tailing pond, and two mining dumps in Rudňany, we deal with the analysis of their condition in terms of heavy metal content, as well as the real and potential alternative use of these sites. Data were collected using field trips and field research in sediment sampling in all localities and by preparing a questionnaire for opinion polls. The content of heavy metals from all four places, the results of field trips, and the questionnaire were analyzed. The article points out the current state of these objects in terms of their load with heavy metals and considers their possible alternative uses, especially in terms of geotourism or education. The implementation of geotourism in the studied sites brings along benefits, not only for visitors and students, but also has a positive impact on sites themselves and on the local community. The results of such analyses should also serve as a basis (starting point) in planning the renewal and further development of such areas. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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19 pages, 966 KiB  
Article
Assessing the Effects of Biochar on the Immobilization of Trace Elements and Plant Development in a Naturally Contaminated Soil
by Paloma Campos and José María De la Rosa
Sustainability 2020, 12(15), 6025; https://doi.org/10.3390/su12156025 - 27 Jul 2020
Cited by 24 | Viewed by 3955
Abstract
Soil contamination with trace elements is an important and global environmental concern. This study examined the potential of biochars derived from rice husk (RHB), olive pit (OPB), and a certified biochar produced from wood chips (CWB) to immobilize copper (Cu2+) and [...] Read more.
Soil contamination with trace elements is an important and global environmental concern. This study examined the potential of biochars derived from rice husk (RHB), olive pit (OPB), and a certified biochar produced from wood chips (CWB) to immobilize copper (Cu2+) and lead (Pb2+) in aqueous solution to avoid its leaching and in a pot experiment with acidic Xerofluvent soils multicontaminated with trace elements. After assessing the adsorption potential of Cu2+ and Pb2+ from an aqueous solution of the three studied biochars, the development of Brassica rapa pekinensis plants was monitored on polluted soils amended with the same biochars, to determine their capability to boost plant growth in a soil contaminated with several trace elements. RHB and CWB removed the maximum amounts of Cu2+ and Pb2+ from aqueous solution in the adsorption experiment. The adsorption capacity increased with initial metal concentrations for all biochars. The efficiency in the adsorption of cationic metals by biochars was clearly affected by biochar chemical properties, whereas total specific surface area seemed to not correlate with the adsorption capacity. Among the isotherm models, the Langmuir model was in the best agreement with the experimental data for both cations for CWB and RHB. The maximum adsorption capacity of Cu2+ was 30.77 and 58.82 mg g−1 for RHB and CWB, respectively, and of Pb2+ was 19.34 and 77.52 mg g−1 for RHB and CWB, respectively. The application of 5% of RHB and CWB to the acidic polluted soils improved soil physico-chemical properties, which permitted the development of Brassica rapa pekinensis plants. RHB and CWB have been shown to be effective for the removal of Cu2+ and Pb2+, and the results obtained regarding plant development in the soils contaminated with trace elements indicated that the soil amendments have promising potential for the recovery of land polluted with heavy metals. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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15 pages, 799 KiB  
Article
Environmental Risk Evaluation and Source Identification of Heavy Metal(loid)s in Agricultural Soil of Shangdan Valley, Northwest China
by Sukai Zhuang and Xinwei Lu
Sustainability 2020, 12(14), 5806; https://doi.org/10.3390/su12145806 - 19 Jul 2020
Cited by 23 | Viewed by 2713
Abstract
To understand the environmental quality and heavy metal(loid) pollution of farmlands in Shangdan Valley, the contents of macroelements (Na, K, Si, Mg, Ca, Al, Fe, Ti, P, S, Cl, Br) and heavy metal(loid)s (Cu, Pb, Zn, Mn, Ni, V, Co, Cr, As) were [...] Read more.
To understand the environmental quality and heavy metal(loid) pollution of farmlands in Shangdan Valley, the contents of macroelements (Na, K, Si, Mg, Ca, Al, Fe, Ti, P, S, Cl, Br) and heavy metal(loid)s (Cu, Pb, Zn, Mn, Ni, V, Co, Cr, As) were surveyed by the X-ray fluorescence method. The pollution degree and ecological risk of the heavy metal(loid)s were judged by the Nemerow synthetic pollution index, geo-accumulation index, and potential ecological risk index, and their sources were identified by the multivariate statistic method. The mean contents of nine heavy metal(loid)s in Shangdan Valley farmland soil exceeded their corresponding reference values. Soils were not contaminated with As, Cr, Mn, and Ni but were slightly contaminated with Co, Cu, Pb, V, and Zn. Their comprehensive pollution levels were moderate to serious. The ecological risk index of single heavy metal(loid) decreased in the sequence As > Pb > Co > Cu > Ni > V > Zn > Cr > Mn. The source analysis results indicated that Cu, Pb, Zn, and As were highly affected by anthropogenic inputs, e.g., metal smelting and agricultural activities, while Mn, Ni, Cr, and V were principally derived from a natural source. As for Co, it was affected by a mixture source of nature, fossil fuel combustion, and fertilizer. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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15 pages, 2274 KiB  
Article
Contamination Identification of Trace Metals in Roadway Dust of a Typical Mountainous County in the Three Gorges Reservoir Region, China, and its Relationships with Socio-Economic Factors
by Huiyun Pan, Xinwei Lu and Kai Lei
Sustainability 2020, 12(14), 5624; https://doi.org/10.3390/su12145624 - 13 Jul 2020
Cited by 4 | Viewed by 2055
Abstract
Trace metal contamination in urban road dust has attracted global concern due to its potential risk to the urban environment and human health. Compared to big cities, relative studies in counties and small towns have not been well quantified. This research identified the [...] Read more.
Trace metal contamination in urban road dust has attracted global concern due to its potential risk to the urban environment and human health. Compared to big cities, relative studies in counties and small towns have not been well quantified. This research identified the trace metal contamination characteristics and possible sources in the road dust of a typical mountainous county and a town in the Three Gorges Reservoir region, southwest China, and their associations with major regional socio-economic factors. The trace metal concentrations were determined, and the contamination levels were assessed. Concentrations of Zn, Pb, and Cu were relatively high in both locations, and a significant accumulation of them was confirmed by the geo-accumulation method. Multivariate analysis and geographic information system (GIS) mapping were combined to explore the sources of trace metals in the investigated area. Anthropogenic activities predominantly affected the contamination levels of Zn, Pb, Cu, and Co, and traffic emission, agricultural activities, and fossil fuel combustion were their main sources. The significant accumulation of Zn should attract special concern for its wide use in industrial and agricultural activities. Population and vehicle density were the main factors that controlled the trace metal contamination levels in the roadway dust. Rapid urbanizing promoted trace metal accumulation in counties and towns. Therefore, it is urgent to make appropriate strategies for trace metal pollution mitigation in the process of urbanization. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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10 pages, 2319 KiB  
Article
Magnetic Fe3O4-Ag0 Nanocomposites for Effective Mercury Removal from Water
by Vassilis J. Inglezakis, Aliya Kurbanova, Anara Molkenova, Antonis A. Zorpas and Timur Sh. Atabaev
Sustainability 2020, 12(13), 5489; https://doi.org/10.3390/su12135489 - 7 Jul 2020
Cited by 20 | Viewed by 4175
Abstract
In this study, magnetic Fe3O4 particles and Fe3O4-Ag0 nanocomposites were prepared by a facile and green method, fully characterized and used for the removal of Hg2+ from water. Characterizations showed that the Fe3 [...] Read more.
In this study, magnetic Fe3O4 particles and Fe3O4-Ag0 nanocomposites were prepared by a facile and green method, fully characterized and used for the removal of Hg2+ from water. Characterizations showed that the Fe3O4 particles are quasi-spherical with an average diameter of 217 nm and metallic silver nanoparticles formed on the surface with a size of 23–41 nm. The initial Hg2+ removal rate was very fast followed by a slow increase and the maximum solid phase loading was 71.3 mg/g for the Fe3O4-Ag0 and 28 mg/g for the bare Fe3O4. The removal mechanism is complex, involving Hg2+ adsorption and reduction, Fe2+ and Ag0 oxidation accompanied with reactions of Cl with Hg+ and Ag+. The facile and green synthesis process, the fast kinetics and high removal capacity and the possibility of magnetic separation make Fe3O4-Ag0 nanocomposites attractive materials for the removal of Hg2+ from water. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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21 pages, 3676 KiB  
Article
Silicon Alleviates Copper Toxicity in Flax Plants by Up-Regulating Antioxidant Defense and Secondary Metabolites and Decreasing Oxidative Damage
by Hossam S. El-Beltagi, Mahmoud R. Sofy, Mohammed I. Aldaej and Heba I. Mohamed
Sustainability 2020, 12(11), 4732; https://doi.org/10.3390/su12114732 - 10 Jun 2020
Cited by 82 | Viewed by 4424
Abstract
In recent years, nutrient management has gained much attention as a way to mitigate heavy metal stress. Silicon (Si) promotes plant defense responses against toxic metal stresses. In this study, we evaluated the effects of silicon (Si) on copper (Cu) toxicity in two [...] Read more.
In recent years, nutrient management has gained much attention as a way to mitigate heavy metal stress. Silicon (Si) promotes plant defense responses against toxic metal stresses. In this study, we evaluated the effects of silicon (Si) on copper (Cu) toxicity in two flax genotypes (Sakha 1 and Sakha 2) as it relates to plant growth, yield attributes, total chlorophyll, nucleic acid content, enzymatic and non-enzymatic antioxidants, oxidative damage, lipid peroxidation, copper and silicon content, and fatty acid composition. The results showed that Cu (100 and 200 µM) inhibited plant growth and increased Cu accumulation in soil, roots, and shoots. Cu significantly decreased the yield attributes, total chlorophyll by 9.5% and 22% in Sakha 1 and by 22.5% and 29% in Sakha 2, and enhanced the accumulation of non-enzymatic (tocopherol), enzymatic antioxidants such as superoxide dismnutase, peroxidase, ascorbate peroxidase and catalase) and secondary metabolites (phenol and flavonoids). The DNA content significantly decreased in stressed plants with 100 and 200 µM Cu about 22% and 44%, respectively, in Sakha 1 and about 21.6% and 34.7% in Sakha 2, and RNA content also decreased by about 20% and 29%, respectively, in Sakha 1 and by about 2% and 13% in Sakha 2 compared to the control plant. Furthermore, Cu stress accelerated the generation of reactive oxygen species (ROS), such as hydrogen peroxide (H2O2) and induced cellular oxidative injury caused by lipid peroxidation. In parallel, Cu induced a change in the composition of fatty acids, resulting in lower unsaturated fatty acid levels and increased saturated fatty acids (increased saturation/unsaturation ratio for both genotypes). Treating the flax plants with irrigation three times with Si protected the plants from Cu toxicity. Si treatment decreased the uptake and the transport of Cu to the shoots and harvested seeds and promoted plant growth, yield attributes, and antioxidant defense systems by reducing Cu accumulation, lipid peroxidation, and the generation of H2O2. In addition, the alleviation of Cu toxicity correlated with increased Si accumulation in the roots and shoots. In conclusion, Si can be used to improve the resistance of flax plants to Cu toxicity by up-regulating the antioxidant defense system such as superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX) and catalase (CAT) and decreasing the oxidative damage caused by reactive oxygen species (ROS). Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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16 pages, 10214 KiB  
Article
Hyperspectral Inversion of Chromium Content in Soil Using Support Vector Machine Combined with Lab and Field Spectra
by Yun Xue, Bin Zou, Yimin Wen, Yulong Tu and Liwei Xiong
Sustainability 2020, 12(11), 4441; https://doi.org/10.3390/su12114441 - 29 May 2020
Cited by 18 | Viewed by 3024
Abstract
Chromium is not only an essential trace element for the growth and development of living organisms; it is also a heavy metal pollutant. Excessive chromium in farmland soil will not only cause harm to crops, but could also constitute a serious threat to [...] Read more.
Chromium is not only an essential trace element for the growth and development of living organisms; it is also a heavy metal pollutant. Excessive chromium in farmland soil will not only cause harm to crops, but could also constitute a serious threat to human health through the cumulative effect of the food chain. The determination of heavy metals in tailings of farmland soil is an essential means of soil environmental protection and sustainable development. Hyperspectral remote sensing technology has good characteristics, e.g., high speed, macro, and high resolution, etc., and has gradually become a focus of research to determine heavy metal content in soil. However, due to the spectral variation caused by different environmental conditions, the direct application of the indoor spectrum to conduct field surveys is not effective. Soil components are complex, and the effect of linear regression of heavy metal content is not satisfactory. This study builds indoor and outdoor spectral conversion models to eliminate soil spectral differences caused by environmental conditions. Considering the complex effects of soil composition, we introduce a support vector machine model to retrieve chromium content that has advantages in solving problems such as small samples, non-linearity, and a large number of dimensions. Taking a mining area in Hunan, China as a test area, this study retrieved the chromium content in the soil using 12 combination models of three types of spectra (field spectrum, lab spectrum, and direct standardization (DS) spectrum), two regression methods (stepwise regression and support vector machine regression), and two factors (strong correlation factor and principal component factor). The results show that: (1) As far as the spectral types are concerned, the inversion accuracy of each combination of the field spectrum is generally lower than the accuracy of the corresponding combination of other spectral types, indicating that field environmental interference affects the modeling accuracy. Each combination of DS spectra has higher inversion accuracy than the corresponding combination of field spectra, indicating that DS spectra have a certain effect in eliminating soil spectral differences caused by environmental conditions. (2) The inversion accuracy of each spectrum type of SVR_SC (Support Vector Regression_Strong Correlation) is the highest for the combination of regression method and inversion factor. This indicates the feasibility and superiority of inversion of heavy metals in soil by a support vector machine. However, the inversion accuracy of each spectrum type of SVR_PC (Support Vector Regression_Principal Component) is generally lower than that of other combinations, which indicates that, to obtain superior inversion performance of SVR, the selection of characteristic factors is very important. (3) Through principal component regression analysis, it is found that the pre-processed spectrum is more stable for the inversion of Cr concentration. The regression coefficients of the three types of differential spectra are roughly the same. The five statistically significant characteristic bands are mostly around 384–458 nm, 959–993 nm, 1373–1448 nm, 1970–2014 nm, and 2325–2400 nm. The research results provide a useful reference for the large-scale normalization monitoring of chromium-contaminated soil. They also provide theoretical and technical support for soil environmental protection and sustainable development. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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13 pages, 2035 KiB  
Article
Heavy Metal Accumulation and Anti-Oxidative Feedback as a Biomarker in Seagrass Cymodocea serrulata
by Mohammed Othman Aljahdali and Abdullahi Bala Alhassan
Sustainability 2020, 12(7), 2841; https://doi.org/10.3390/su12072841 - 2 Apr 2020
Cited by 18 | Viewed by 2916
Abstract
The pursuit of a good candidate to biomonitor environmental pollutants has been on the increase. In this study, the concentrations of Fe, Mn, Cu, Zn, Cd, Cr, Pb and Ni in sediment, seawater and seagrass Cymodocea serrulata compartments and antioxidant enzymes activities in [...] Read more.
The pursuit of a good candidate to biomonitor environmental pollutants has been on the increase. In this study, the concentrations of Fe, Mn, Cu, Zn, Cd, Cr, Pb and Ni in sediment, seawater and seagrass Cymodocea serrulata compartments and antioxidant enzymes activities in C. serrulata were determined. Our results revealed that bioconcentration factors for all the metals were less than 1 (BCF < 1) and concentrations in seagrass compartments were in the order root > leaf > rhizome for Fe and Mn, leaf > root > rhizome for Cu, Zn, Pb and Ni, and root > rhizome > leaf for Cd and Cr. Effect range low concentrations (ER-L) revealed that Cu, Zn, Cd, Pb and Ni concentrations were above ER-L values and Cr concentration was below ER-L values while concentrations in seawater for all the heavy metals were above the estimate average element concentrations in seawater (ECS). Significant variation (p < 0.05) was recorded for heavy metals in sediment, seawater, seagrass compartments and heavy metal concentrations across stations. Influence of heavy metals on antioxidant enzymes activities; catalase (CAT), superoxide dismutase (SOD), glutathione S-transferase (GST) and acetylcholinesterase (AChE) were recorded, and high activities of the antioxidants were recorded in station S8 corresponding to high concentrations of heavy metals in the same station. There is a need for the promotion of biomonitoring networks across the marine environment using C. serrulata and antioxidant enzymes as biomarkers of oxidative stress caused by environmental pollutants. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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13 pages, 2069 KiB  
Article
Trace Elements in Soils of a Typical Industrial District in Ningxia, Northwest China: Pollution, Source, and Risk Evaluation
by Songlin Zhang, Yuan Liu, Yujing Yang, Xilu Ni, Muhammad Arif, Wokadala Charles and Changxiao Li
Sustainability 2020, 12(5), 1868; https://doi.org/10.3390/su12051868 - 2 Mar 2020
Cited by 15 | Viewed by 3058
Abstract
Intense industrial activities could result in massive accumulations of trace elements in the soil and risk the terrestrial ecosystems and human health. A total of 119 topsoil samples from a typical industrial area, Huinong District, Ningxia, Northwest China, were collected, and the contents [...] Read more.
Intense industrial activities could result in massive accumulations of trace elements in the soil and risk the terrestrial ecosystems and human health. A total of 119 topsoil samples from a typical industrial area, Huinong District, Ningxia, Northwest China, were collected, and the contents of six trace elements (As, Cd, Cr, Cu, Pb, and Zn) were determined. The results indicated that the mean concentrations of Cr, Cu, Pb, and Zn were lower than the national standard values of class II, while As and Cd were 2.77 and 3.92 times the corresponding threshold values. Multivariate analyses revealed six metals can be categorized into three principal components (PC). PC1 was As, Cd, and Pb, which originated from anthropogenic inputs. PC2 consisted of Cr and Cu, which originated from the natural geological background. PC3 only included Zn and was mainly due to agricultural impacts. The spatial distribution of six metals greatly varied from local anthropic inputs. For As and Cd, the most heavily polluted area was located in the north and southwest parts of the study area, whereas most Zn was enriched in the southern part, which was mainly agricultural land. The topsoil in this area displayed a moderate environmental risk with the metal pollution order of Cd > As > Zn ≈ Cr ≈ Pb ≈ Cu. Moreover, the contents of trace elements in the industrial land and water were relatively higher than those in other land-use types, indicating a considerable risk of metal migration and accumulation to rivers and the groundwater. It is suggested that effective remediation measures for Cd and As, in particular, should be properly employed for the sustainable development of the soil and groundwater, while reducing the risk of elements to the local residents in Huinong District. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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21 pages, 5449 KiB  
Article
Hyperspectral Prediction Model of Metal Content in Soil Based on the Genetic Ant Colony Algorithm
by Shiqi Tian, Shijie Wang, Xiaoyong Bai, Dequan Zhou, Guangjie Luo, Jinfeng Wang, Mingming Wang, Qian Lu, Yujie Yang, Zeyin Hu, Chaojun Li and Yuanhong Deng
Sustainability 2019, 11(11), 3197; https://doi.org/10.3390/su11113197 - 7 Jun 2019
Cited by 19 | Viewed by 4138
Abstract
The accumulation of metals in soil harms human health through different channels. Therefore, it is very important to conduct fast and effective non-destructive prediction of metals in the soil. In this study, we investigate the characteristics of four metal contents, namely, Sb, Pb, [...] Read more.
The accumulation of metals in soil harms human health through different channels. Therefore, it is very important to conduct fast and effective non-destructive prediction of metals in the soil. In this study, we investigate the characteristics of four metal contents, namely, Sb, Pb, Cr, and Co, in the soil of the Houzhai River Watershed in Guizhou Province, China, and establish the content prediction back propagation (BP) neural network and genetic-ant colony algorithm BP (GAACA-BP) neural network models based on hyperspectral data. Results reveal that the four metals in the soil have different degrees of accumulation in the study area, and the correlation between them is significant, indicating that their sources may be similar. The fitting effect and accuracy of the GAACA-BP model are greatly improved compared with those of the BP model. The R values are above 0.7, the MRE is reduced to between 6% and 15%, and the validation accuracy is increased by 12–64%. The prediction ability of the model of the four metals is Cr > Co > Sb > Pb. These results indicate the possibility of using hyperspectral techniques to predict metal content. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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19 pages, 2158 KiB  
Article
Application of Time-Lapse Ion Exchange Resin Sachets (TIERS) for Detecting Illegal Effluent Discharge in Mixed Industrial and Agricultural Areas, Taiwan
by Po-Kang Shih, Li-Chi Chiang, Sheng-Chi Lin, Tsun-Kuo Chang and Wei-Chan Hsu
Sustainability 2019, 11(11), 3129; https://doi.org/10.3390/su11113129 - 3 Jun 2019
Cited by 6 | Viewed by 4632
Abstract
Many factories were built and scattered around the farmlands in Taiwan due to inappropriate land use planning. Illegal effluent discharge of high concentration of metals from the nearby factories has been threatening the farmlands, causing damages to agricultural production, food safety, and human [...] Read more.
Many factories were built and scattered around the farmlands in Taiwan due to inappropriate land use planning. Illegal effluent discharge of high concentration of metals from the nearby factories has been threatening the farmlands, causing damages to agricultural production, food safety, and human health. Sampling was mostly responsible for monitoring the water quality of the agricultural environment; however, the analysis is of high cost and time consuming. Due to uneasy controlled environmental factors (i.e., illegal effluents) and time-consuming and expensive traditional analysis techniques (i.e., atomic absorption spectrometry (AAS), atomic fluorescence spectrometry (AFS), inductively coupled plasma atomic emission spectrometry (ICP-AES), inductively coupled plasma optical emission spectrometry (ICP-OES), and inductively coupled plasma mass spectrometry (ICP-MS)), we develop a fast-screening method, which is the combination of ion exchange resins and the portable X-ray fluorescence (XRF) spectroscopy to identify the source of contaminants in a mixed industrial and agricultural area in Taoyuan County, Taiwan. The time-lapse ion exchange resin sachet (TIERS) is a non-woven bag that is filled with resins and placed in the irrigation channels for continuously absorbing the metal and trace elements in water. The standardization ratios of Cu/Sr and Zn/Sr were calculated as the pollutant indicators for fast-screening the highly polluted sites of exceedance probability of 2.27% in the monitoring area. The TIERS is verified to detect the metal and trace element concentration in an efficient and sufficient way. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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16 pages, 1111 KiB  
Article
Impact of Non-Agricultural Employment and Environmental Awareness on Farmers’ Willingness to Govern the Heavy Metal Pollution of Farmland: A Case Study of China
by Hua Lu
Sustainability 2019, 11(7), 2068; https://doi.org/10.3390/su11072068 - 8 Apr 2019
Cited by 10 | Viewed by 3430
Abstract
Heavy metal pollution of farmland is a significant issue affecting the quality of agricultural products and human health. Farmers’ behaviors can have a direct impact on the level of heavy metal pollution affecting farmland in China. Whether the heavy metal pollution of farmland [...] Read more.
Heavy metal pollution of farmland is a significant issue affecting the quality of agricultural products and human health. Farmers’ behaviors can have a direct impact on the level of heavy metal pollution affecting farmland in China. Whether the heavy metal pollution of farmland can be effectively governed at a low cost depends on the farmers. This paper analyzes the mechanism by which the extent of non-agricultural employment and environmental awareness influences farmers’ willingness to govern the heavy metal pollution of farmland using microdata for farmers in China and conducts an empirical analysis via a logit model. The results show that farmers in China display low willingness to govern the heavy metal pollution of farmland and that the increase in non-agricultural income will not significantly improve this willingness. Environmental awareness and farmers’ willingness to govern the heavy metal pollution of farmland are closely related: the higher the environmental awareness of farmers is, the stronger their willingness to govern heavy metal pollution, and the higher the probability of their participating in fallow land treatment. The government can introduce incentives to improve farmers’ environmental awareness of the heavy metal pollution of farmland. In addition, the government should strengthen publicity about the positive effects of fallow land treatment and encourage farmers to participate in the governance of heavy metal pollution of farmland. Given increasing non-agricultural employment opportunities and the transformation of agricultural production modes, agricultural technical training provided by governmental departments can enable them to be more scientific and rational in their agrochemical selection and application, thus reducing or avoiding the heavy metal pollution of farmland at the source. Attention should be paid to the differences between farmers to ultimately reduce the cost and improve the efficiency of treatment. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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13 pages, 790 KiB  
Article
Effects of Vegetation Pattern and Spontaneous Succession on Remediation of Potential Toxic Metal-Polluted Soil in Mine Dumps
by Fuyao Chen, Yongjun Yang, Jiaxin Mi, Run Liu, Huping Hou and Shaoliang Zhang
Sustainability 2019, 11(2), 397; https://doi.org/10.3390/su11020397 - 14 Jan 2019
Cited by 19 | Viewed by 5043
Abstract
The ecological rehabilitation of potential toxic metal-contaminated soils in sites disturbed by mining has been a great challenge in recent decades. Phytoremediation is one of the most widely promoted renovation methods due to its environmental friendliness and low cost. However, there is a [...] Read more.
The ecological rehabilitation of potential toxic metal-contaminated soils in sites disturbed by mining has been a great challenge in recent decades. Phytoremediation is one of the most widely promoted renovation methods due to its environmental friendliness and low cost. However, there is a lack of in situ investigation on the influence of vegetation pattern and spontaneous succession on the rehabilitation of potential toxic metal-polluted soil. To clarify how the vegetation pattern in the early stage of restoration and the spontaneous succession influence the remediation of the soil, we investigated a metal mining dump in Sichuan, China, by field investigation and laboratory analysis. We determined the plant growth, soil fertility, and the capacity of potential toxic metals (PTMs) in metal mining soil under different initial vegetation patterns for different years to understand the role of vegetation pattern and spontaneous succession in PTM pollution phytoremediation projects. The results show that: (1) Phytoremediation with a simple initial vegetation pattern (RP rehabilitative plant pattern) which involves two rehabilitation plants, Agave sisalana and Neyraudia reynaudiana, achieves a PTM pollution index that is 9.28% lower than that obtained with the complex vegetation pattern (RP&LP rehabilitation plants mixed with local plants pattern), 21.86% lower in the soil fertility index, and 73.69% lower in the biodiversity index; (2) The phytoremediation with the 10-year RP&LP pattern was associated with a PTM pollution index that was 4.04% higher than that for the 17-year RP&LP pattern, a soil fertility index that was 4.48% lower, and a biodiversity index that was 12.49% lower. During the process of vegetation succession, if accumulator plants face inhibition of growth or retreat, the reclamation rate will decrease. The vegetation patterns influence the effect of phytoremediation. Spontaneous vegetation succession will cause the phytoremediation process to deviate from the intended target. Therefore, according to the goal of vegetation restoration, choosing a suitable vegetation pattern is the main premise to ensure the effect of phytoremediation. The indispensable manipulation of succession is significant during the succession series, and more attention should be paid to the rehabilitative plants to ensure the stable effect of reclamation. The results obtained in this study could provide a guideline for the in situ remediation of PTM-polluted soil in China. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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11 pages, 7484 KiB  
Article
Trace Metal Content and Availability of Essential Metals in Agricultural Soils of Alicante (Spain)
by Jose Navarro-Pedreño, María Belén Almendro-Candel, Ignacio Gómez Lucas, Manuel M. Jordán Vidal, Jaume Bech Borras and Antonis A. Zorpas
Sustainability 2018, 10(12), 4534; https://doi.org/10.3390/su10124534 - 1 Dec 2018
Cited by 37 | Viewed by 3658
Abstract
This article analysed the presence of trace metals (essential elements and pollutants) and soil properties in rural abandoned soils of a Mediterranean region. The soil properties determined were texture, pH, equivalent calcium carbonate, soil organic matter, availability of micronutrients (Fe, Mn, Cu, and [...] Read more.
This article analysed the presence of trace metals (essential elements and pollutants) and soil properties in rural abandoned soils of a Mediterranean region. The soil properties determined were texture, pH, equivalent calcium carbonate, soil organic matter, availability of micronutrients (Fe, Mn, Cu, and Zn), and acid microwave digestion extraction to measure the trace metals considered as main pollutants (Cu, Zn, Cd, Cr, Ni, and Pb). Descriptive statistics and correlations were used to determine the relations among these parameters. pH, soil organic carbon (SOC), and clay were the main properties that controlled the availability of essential metals. pH was the main factor related to these metals in these calcareous soils. However, SOC, which can be incremented by adding organic fertilizers for soil rehabilitation as a sustainable practice, played an important role. Mean values of the metal composition in soils (Cu, Zn, Cd, Cr, Ni, and Pb) obtained in this study were similar to values reported for other areas in the Mediterranean basin. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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18 pages, 1998 KiB  
Article
Pollution Assessment of Trace Elements in Agricultural Soils around Copper Mining Area
by Xianfeng Cheng, Jarmila Drozdova, Tomas Danek, Qianrui Huang, Wufu Qi, Shuran Yang, Liling Zou, Yungang Xiang and Xinliang Zhao
Sustainability 2018, 10(12), 4533; https://doi.org/10.3390/su10124533 - 1 Dec 2018
Cited by 32 | Viewed by 4253
Abstract
Agricultural soils from Dongchuan copper mining area were sampled and analyzed to determine the concentrations of selected trace elements, namely As, Cd, Cr, Cu, Hg, Ni, Pb and Zn. The main objectives of this study were: (1) To determine the levels of trace [...] Read more.
Agricultural soils from Dongchuan copper mining area were sampled and analyzed to determine the concentrations of selected trace elements, namely As, Cd, Cr, Cu, Hg, Ni, Pb and Zn. The main objectives of this study were: (1) To determine the levels of trace elements and their spatial distribution in soils; (2) to evaluate the potential ecological risk; and (3) to identify the main sources of risk element pollution. The environmental risks were assessed using five different contamination and pollution indexes. Descriptive and exploratory statistical analyses were performed to identify the relations among the trace elements in soils and possible sources of pollution. Although the values of As, Cu and Zn in the soils were significantly higher than Yunnan background values and exceeded the limits of the Chinese national standards in several sampling points, the most serious threat for the ecosystem and human health was represented by Cd. The main sources of Cu and As were identified mining activities, airborne particulates from smelters and the weathering of tailings, and partly also agricultural fertilizers. The major source of Cd was agricultural fertilizers and partly sources associated with mining and smelting activities. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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14 pages, 3165 KiB  
Article
Assessment of Heavy Metals and Color as Indicators of Contamination in Street Dust of a City in SE Spain: Influence of Traffic Intensity and Sampling Location
by Pura Marín Sanleandro, Antonio Sánchez Navarro, Elvira Díaz-Pereira, Francisco Bautista Zuñiga, Miriam Romero Muñoz and María José Delgado Iniesta
Sustainability 2018, 10(11), 4105; https://doi.org/10.3390/su10114105 - 8 Nov 2018
Cited by 27 | Viewed by 4792
Abstract
In the present work, a sampling grid of the urban core of the city of Murcia (South East Spain) was designed in order to analyze street dust, focusing on the contents of the heavy metals Cd, Cr, Cu, Ni, Pb, and Zn and [...] Read more.
In the present work, a sampling grid of the urban core of the city of Murcia (South East Spain) was designed in order to analyze street dust, focusing on the contents of the heavy metals Cd, Cr, Cu, Ni, Pb, and Zn and their relationships with the color of the sample, the traffic pattern, and the location where they were sampled (sidewalks, ledges, and roads). The characterization of the samples was carried out by X-ray diffraction and scanning electron microscopy, whereas the heavy metals were extracted by acid digestion and determined by inductively coupled plasma mass spectrometry. The concentration (mg/kg) in urban dust of the city of Murcia was highest for Zn (653), followed by Cu (201) > Pb (177) > Cr (117) > Ni (51) >> Cd (0.5). The color expounded statistically significant differences with regard to the heavy metals, including the pollutant load. The same pattern was found when the classification variable was the traffic intensity, except in the case of Ni. The areas with a higher risk of contamination by heavy metals in the urban dust are the ledges of narrow city center streets with moderate traffic, where Zn and Pb seem to accumulate most greatly. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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14 pages, 4519 KiB  
Article
Estimation Methods for Soil Mercury Content Using Hyperspectral Remote Sensing
by Li Zhao, Yue-Ming Hu, Wu Zhou, Zhen-Hua Liu, Yu-Chun Pan, Zhou Shi, Lu Wang and Guang-Xing Wang
Sustainability 2018, 10(7), 2474; https://doi.org/10.3390/su10072474 - 15 Jul 2018
Cited by 59 | Viewed by 4906
Abstract
Mercury is one of the five most toxic heavy metals to the human body. In order to select a high-precision method for predicting the mercury content in soil using hyperspectral techniques, 75 soil samples were collected in Guangdong Province to obtain the soil [...] Read more.
Mercury is one of the five most toxic heavy metals to the human body. In order to select a high-precision method for predicting the mercury content in soil using hyperspectral techniques, 75 soil samples were collected in Guangdong Province to obtain the soil mercury content by chemical analysis and hyperspectral data based on an indoor hyperspectral experiment. A multiple linear regression (MLR), a back-propagation neural network (BPNN), and a genetic algorithm optimization of the BPNN (GA-BPNN) were used to establish a relationship between the hyperspectral data and the soil mercury content and to predict the soil mercury content. In addition, the feasibility and modeling effects of the three modeling methods were compared and discussed. The results show that the GA-BPNN provided the best soil mercury prediction model. The modeling R2 is 0.842, the root mean square error (RMSE) is 0.052, and the mean absolute error (MAE) is 0.037; the testing R2 is 0.923, the RMSE is 0.042, and the MAE is 0.033. Thus, the GA-BPNN method is the optimum method to predict soil mercury content and the results provide a scientific basis and technical support for the hyperspectral inversion of the soil mercury content. Full article
(This article belongs to the Special Issue Sustainable Management of Heavy Metals)
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