Heavy metal contamination of agricultural soils affected by mining activities around the Ganxi River in Chenzhou, Southern China

Ma, Li; Sun, Jing; Yang, Zhaoguang; Wang, Lin

doi:10.1007/s10661-015-4966-8

Cited by 122 publications

(40 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mining and subsequent ore-processing activities are always associated with very high levels of heavy metal contamination of the environment (Alloway 2010;Ma et al 2015). The descriptive statistics of the heavy metal concentrations in soils of the Central Spiš area in two year horizons are listed in Table 2.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of soil heavy metal pollution in a former mining area - before and after the end of mining activities

Demková¹,

Jezný²,

Bobuľská³

2017

Soil Water Res.

View full text Add to dashboard Cite

Demková L., Jezný T., Bobuľská L. (2017): Assessment of soil heavy metal pollution in a former mining area -before and after the end of mining activities. Soil & Water Res., 12: 229−236.Toxicity and persistence of heavy metals, which are accumulated in the environment as the result of diverse industrial activities, represent serious environmental problem worldwide. The intense mineral extraction in mining areas has produced a large amount of waste material and tailings, which release toxic elements to the environment. The aim of the study was to determine in two time horizons (1997, 2015) the heavy metal contents of samples derived from ten sampling sites located in the former mining area of Central Spiš (Slovakia). In order to compare the level of contamination, the contamination factor (C i f ), degree of contamination (C d ), and pollution load index (PLI) were computed. Spearman's correlation coefficient was used in order to detect the relationships among heavy metals. A serious situation was found for Hg, Zn, and Cd, which exceeded limit values at all sampling sites within both studied years. In 1997, the average values of contamination factor have shown very high contamination with all studied heavy metals, and moderate contamination with Co. In 2015, the study area was classified as very highly contaminated with As, Hg, Zn, Cu, considerably contaminated with Ni, Cr, Pb, and Cd, while Co contamination was not detected. Since 1997 till 2015 the pollution load index decreased by about 38%, nevertheless even then almost all sampling sites were classified as heavily polluted. Despite the fact that mining activities were stopped or limited at the beginning of the 21 st century, the presence of heavy metals in soils remains at a serious level. The high level of contamination is a result of heavy metal persistence and non-biodegradability.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The intense mineral extraction has produced a large amount of waste material accumulated on the heaps or tailings (Ma et al 2015). Without proper management, abandoned mines and tailings are the source of heavy metals, which are washed out by precipitation and can contaminate all environmental components (Liakopoulos et al 2010;Li et al 2014).…”

mentioning

confidence: 99%

Assessment of soil heavy metal pollution in a former mining area - before and after the end of mining activities

Demková¹,

Jezný²,

Bobuľská³

2017

Soil Water Res.

View full text Add to dashboard Cite

show abstract

“…The principal components (PCs) were transferred from the original variables using eigenanalysis (Lee et al 2006). Varimax rotation with Kaiser normalization was applied to extract PCs according to the eigenvalue with the variance >10 % and cumulative variances >70 % (Ma et al 2015). The validity of the PCA was confirmed by Kaiser-Meyer-Olkin (KMO) measure and Bartlett's test.…”

Section: Discussionmentioning

confidence: 99%

“…The P s is classified into five groups (Ma et al 2015): P s <1: uncontaminated; 1≤P s <2: slightly contaminated; 2≤P s <3: moderately contaminated; 3≤P s <5: strongly contaminated; and P s ≥5: seriously contaminated.…”

Section: Risk Assessmentmentioning

confidence: 99%

“…Long-term exposure to heavy metals may cause damage to certain organs and induce cancers (Jarup 2003). In order to assess the potential risk of heavy metals in urban soils to the ecosystem, evaluation models, such as potential ecological risk index and Nemerow comprehensive index, have been employed to quantify the pollution levels (Ma et al 2015, Zhou et al 2014.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Source identification and risk assessment of heavy metal contaminations in urban soils of Changsha, a mine-impacted city in Southern China

Yang

et al. 2016

Environ Sci Pollut Res

Self Cite

102

View full text Add to dashboard Cite

The urban soils suffered seriously from heavy metal pollutions with rapid industrialization and urbanization in China. In this study, 54 urban soil samples were collected from Changsha, a mine-impacted city located in Southern China. The concentrations of heavy metals (As, Cd, Co, Cu, Mn, Ni, Pb, and Zn) were determined by ICP-MS. The pollution sources of heavy metals were discriminated and identified by the combination of multivariate statistical and geostatistical methods. Four main sources were identified according to the results of hierarchical cluster analysis (HCA), principal component analysis (PCA), and spatial distribution patterns. Co and Mn were primarily derived from soil parent material. Cu, Pb, and Zn with significant positive relationships were associated with mining activities and traffic emissions. Cd and Ni might be affected by commercial activities and industrial discharges. As isolated into a single group was considered to have correlation with coal combustion and waste incineration. Risk assessment of heavy metals in urban soils indicated an overall moderate potential ecological risk in the urban region of Changsha.

show abstract

Simultaneous separation and determination of six arsenic species in rice by anion‐exchange chromatography with inductively coupled plasma mass spectrometry

Yang

Tang

et al. 2016

J of Separation Science

Self Cite

View full text Add to dashboard Cite

The simultaneous separation and determination of arsenite As(III), arsenate As(V), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), arsenobetaine (AsB), and arsenocholine (AsC) in rice samples have been carried out in one single anion-exchange column run by high-performance liquid chromatography with inductively coupled plasma mass spectrometry. To estimate the effect of variables on arsenic (As) speciation, the chromatographic conditions including type of competing anion, ionic strength, pH of elution buffer, and flow rate of mobile phase have been investigated by a univariate approach. Under the optimum chromatographic conditions, baseline separation of six As species has been achieved within 10 min by gradient elution program using 4 mM NH4 HCO3 at pH 8.6 as mobile phase A and 4 mM NH4 HCO3 , 40 mM NH4 NO3 at pH 8.6 as mobile phase B. The method detection limits for As(III), As(V), MMA, DMA, AsB, and AsC were 0.4, 0.9, 0.2, 0.4, 0.5, and 0.3 μg/kg, respectively. The proposed method has been applied to separation and quantification of As species in real rice samples collected from Hunan Province, China. The main As species detected in all samples were As(III), As(V) and DMA, with inorganic As accounting for over 80% of total As in these samples.

show abstract

Heavy metal contamination of agricultural soils affected by mining activities around the Ganxi River in Chenzhou, Southern China

Cited by 122 publications

References 35 publications

Assessment of soil heavy metal pollution in a former mining area - before and after the end of mining activities

Assessment of soil heavy metal pollution in a former mining area - before and after the end of mining activities

Source identification and risk assessment of heavy metal contaminations in urban soils of Changsha, a mine-impacted city in Southern China

Simultaneous separation and determination of six arsenic species in rice by anion‐exchange chromatography with inductively coupled plasma mass spectrometry

Contact Info

Product

Resources

About