Soil contamination with persistent and potentially (eco)toxic heavy metal(loid)s is ubiquitous around the globe. Concentration of these heavy metal(loid)s in soil has increased drastically over the last three decades, thus posing risk to the environment and human health. Some technologies have long been in use to remediate the hazardous heavy metal(loid)s. Conventional remediation methods for heavy metal(loid)s are generally based on physical, chemical and biological approaches, which may be used in combination with one another to clean-up heavy metal(loid) contaminated soils to an acceptable and safe level. This review summarizes the soil contamination by heavy metal(loid)s at a global scale, accumulation of heavy metal(loid)s in vegetables to toxic levels and their regulatory guidelines in soil. In this review, we also elucidate and compare the pool of available technologies that are currently being applied for remediation of heavy metal(loid) contaminated soils, as well as the economic aspect of soil remediation for different techniques. This review article includes an assessment of the contemporary status of technology deployment and recommendations for future remediation research. Finally, the molecular and genetic basis of heavy metal(loid) (hyper)accumulation and tolerance in microbes and plants is also discussed. It is proposed that for effective and economic remediation of soil, a better understanding of remediation procedures and the various options available at the different stages of remediation is highly necessary.
Surface sediment (0–10 cm) samples were collected from 12 typical sites throughout the Dongting Lake. Samples were detected by inductively coupled plasma–mass spectrometry and atomic fluorescence spectrometry for Cr, Cu, Zn, Pb, Cd, As, and Hg, respectively. Based on geostatistics analyses, generally distributions of these heavy metal contents except that of Hg decreased in the order of the South Dongting Lake > the East Dongting Lake > the outlet of Dongting Lake ≈ the West Dongting Lake. Sediment quality guidelines (SQGs) and Hakanson's method were used to determine potential risk of heavy metal contamination. The results indicated that the mean contents of As and Cd exceeded the probable effect level (PEL), and there were 58% for Cd and 50% for As out of all sampling sites exceeding PEL. The calculated mean potential ecological risk degrees were in the descending order of Cd, Hg, As, Pb, Cu, Cr and Zn. Besides, multivariate statistical analyses revealed that Zn, Pb, Cd and As mainly originated from mining wastewater and industrial wastewater which were probably in the close relationship with characteristics about the Yueyang city and the Xiangjiang River. Cr and Cu mainly derived from natural erosion and nonpoint agricultural sources. However, Hg originated from both sources. Cluster analysis indicated that Cluster 1, S5, S6 and S10 included, were probably taken as the higher polluted sites, and Cluster 2, S7, S9 and S11 included, might be explained as the moderate pollution regions.
Raman spectroscopy is a versatile non-destructive technique for fluid inclusion analysis, with a wide field of applications ranging from qualitative detection of solid, liquid and gaseous components to identification of polyatomic ions in solution. Raman technique is commonly used to calculate the density of CO fluids, the chemistry of aqueous fluids, and the molar proportions of gaseous mixtures present as inclusions. Raman spectroscopy has been applied to measure the range and oxidation state of fluids. The main advantages of this technique are the minimal sample preparation and the high versatility. Present review summarizes the recent developments of Raman spectroscopy in fluid inclusions research to provide support for laboratory analyses.
Over the past several decades, a wide range of complex structures or phenomena of interest to geologists and geochemists has been quantitatively characterized using fractal/multifractal theory and models. With respect to the application of fractal/multifractal models to geochemical data, the focus has been on how to decompose geochemical populations or quantify the spatial distribution of geochemical data. A variety of fractal/multifractal models for this purpose have been proposed on the basis of the scaling characteristics of geochemical data. These include the concentration–area (C-A) fractal model, concentration–distance (C-D) fractal model, spectrum–area (S-A) multifractal model, multifractal singularity analysis, and the concentration–volume (C-V) fractal model. These fractal models have been widely demonstrated to be useful, as indicated by the increasing number of published papers. In this study, fractal/multifractal modeling of geochemical data including its theory, the way it works, its benefits and limitations, its applications, and the relationships between these models are reviewed. The comparison among of C-A, S-A, and multifractal singularity analysis based on simulated data suggested that mapping singularity technique can enhance and identify weak anomalies caused by buried sources. Future study should focus on how to distinguish the true anomalies associated to mineralization with the false anomalies from a fractal/multifractal perspective.
Human body may be directly exposed to heavy metals in urban soils through oral ingestion, dermal contact, and inhalation of soil particles. A total of 170 topsoil samples were collected from the urbanized area of Dongguan, China. Concentrations of As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, V, and Zn in soils were measured to calculate enrichment factors (EFs), pollution indexes (PIs), carcinogenic risks (CRs), and hazard indexes (HIs) of these elements. The mean concentrations of every element in urban soils of Dongguan are lower than both the soil environmental quality standards of China and the Canadian soil quality guidelines. However, concentrations of Cd, Cu, Ni, and Zn have increased slightly in the past 20 years. Slight contamination was observed in some samples for all heavy metals according to the Chinese soil quality standards, and the element of As may be the most important contaminant. Furthermore, the element of As may pose both carcinogenic and non-carcinogenic risks to human health. Oral ingestion and inhalation of soil particles are the main exposure pathways of As to the human body. This study may provide a scientific basis for strategies to protect human health in urban areas.
Due to the rapid urbanization and industrialization that has occurred in China over the last few decades, metals have been continuously emitted into the urban environment and now pose a serious threat to human health. Indeed, there is a growing concern over the potential for pollution of urban soils with heavy metals. Therefore, an extensive soil survey was conducted in urban areas of Changchun, China, to evaluate the current status of heavy metal contamination in soils and to evaluate its potential sources. A total of 352 samples of urban soils were collected from urban areas of Changchun using a systematic sampling strategy in which one sample per km was taken (0 ~ 20 cm). The levels of Cu, Pb, Zn and the major elements (Mn, Al O , CaO, Fe O , MgO, SiO , K O and NaO) were then determined by X-Ray fluorescence spectrometry (XRF), while the level of Cd was determined by graphite furnace atomic absorption spectrometry (GF-AAS), and the Hg and As concentrations were determined by atomic fluorescence spectroscopy (AFS). The results indicated that, when compared with the background values of topsoil in the Changchun region, the topsoil in urban areas were enriched with metals, particularly Cu, Cd, Zn, Pb and Hg. The results of correlation coefficient analysis showed that Hg, As, Cd, Cu, Pb and Zn were significantly positive correlated with each other, while Cr and Mn formed another group. Moreover, significantly positive correlations were observed between pH and Zn, Pb, Cu, Cd, As and Hg, indicating that pH influences the distributions of these metals in urban soils in Changchun. Principal component analysis (PCA) was conducted to identify sources of heavy metals and the results revealed distinctly different associations among the trace metals and the major elements in the urban soils. The concentration of Cr appeared to be controlled by the parent material (natural sources), while Cu, Pb and Zn were mainly from vehicle emissions, with Zn primarily coming from vehicle tires. Additionally, Hg and As primarily originated from coal combustion, while Cd was mainly associated with industrial sources. According to the pollution index (PI) of each metal, the overall levels of metal pollution were not especially high, but there were clearly contaminated sites concentrated in the central and northeast portion of the studied region. The Nemerow integrated pollution index (NIPI) of the seven metals also indicated that urban soils in Changchun city were classified as having low level of pollution. ► The article is an original contribution as a case study, as it is a study of the Changchun city (China) where the soils contamination situation has not been previously studied. ► The present study was conducted to: (1) determine the concentration of heavy metals in urban soil collected from Changchun; (2) identify their natural or anthropogenic sources by principal component analysis (PCA); and (3) assess the level of heavy metal contamination in the topsoil based on pollution index (PI) values and the Nemerow integrated pollution index (NIPI). This information will be helpful to urban planners and environmental risk managers who seek to encourage responsible, environmentally friendly economic development strategies. ► The methods followed in order to reach the aims of the study were basic statistical parameters calculation, binary correlations matrix, Principal Components Analysis, calculation of pollution index (PI) for each metallic element and finally an integrated pollution index (Nemerow Index). The main conclusions are that the core of Changchun city shows a low to middle level of pollution, which is mainly related to traffic and industrial sources.
This overview provides an up-to-date assessment of the trace metal contamination (As, Cd, Cr, Cu. Hg, Ni, Pb, Sb, Se, and Zn) in urban soils of 31 metropolises in China. This systematic soil geochemical survey summarizes the characteristics of trace metals in Chinese urban soils, including concentration, accumulation, spatial distribution, and major sources. Mercury was ranked first followed by Cd and Se in geo-accumulation among all of the contaminant metals in urban soils in China; this finding is likely due to the Hg and Se emissions from fossil fuels. However, the lack of studies on Se contamination in urban soils, not only in China but also in the rest of the world, implies that Se contamination may have been unobserved for a long time. Shanghai, Kunming, Shenyang, and Changsha may be some of the most heavily contaminated Chinese cities based on the concentrations, spatial dimensions, and associations among the contaminant metals. Numerous hotspots with high concentrations of metals were found in Changsha, Shanghai, and Shenyang, clearly indicating a significant contribution from both the metallurgical industry and smelt mining to the contamination of urban soils. Conversely, the levels of Sb, Cu, and Cd in Kunming originated from their naturally high geochemical background in soils. Heavy Se contamination was found in Guiyang and Taiyuan. The natural source of Se may be important in defining the pattern of pollution in Guiyang, whereas anthropogenic sources are likely more accurate than is the natural background in Taiyuan city. We review the existing limits and types of pollutants in the current soil guidelines and find that an international agreement on the range of the limits and the types of pollutants contained in the soil guidelines is urgently needed.
Environmental geochemical mapping with high-density soil sampling was conducted to determine the spatial distribution, possible sources and potential ecological risk of heavy metals at a former chemical industry area in Beijing. A total of 550 surface soil samples were collected and the concentrations of heavy metals, such as Ni, Cr, V, As, Cu, Pb, Cd, Zn and Hg, were analyzed. The spatial distribution characteristics of these metals were demonstrated by environmental geochemical mapping. Enrichment factors show that the soil concentrations of Cu, Pb, Cd, Zn and especially Hg were higher than the background values. Multivariate geostatistical analyses suggested that Cu, Pb, Cd, Zn and Hg in the topsoil were strongly influenced by anthropogenic or chemical industry activities while Ni, As, V and Cr mainly originated from the natural parent materials of the soils. The potential ecological risk was quantitatively estimated for each site and the risk map was plotted for assessment. Among the metals, Cd and Hg showed a higher potential ecological risk than the others.
Mining and milling operations, including grinding, concentrating ores and disposal of tailings, along with mine and mill waste water, provide obvious sources of contamination in the surface environment. Climatic effects such as heavy rainfall events, have a great impact in the dispersion of metals in semi-arid areas, since soils are typically scarcely vegetated. The dispersion and influence of soluble and particulate metals present in the materials from an abandoned mine, Cabezo Rajao, in SE Spain, was evaluated. Tailings and soils were sampled and analysed for pH, EC, CaCO , grainsize, mineralogical composition and heavy metal content, while water samples were collected and analysed for pH, EC, soluble metals and salts. The mean concentrations of Pb, Zn, Cd, Cu and As in solid samples were 8.3 g kg , 12.5 g kg , 40.9 mg kg , 332.1 mg kg , 314.7 mg kg respectively, and 1.5 mg l , 50.3 mg l , 13.6 g l , 17.2 mg l , 1.7 mg l in water samples respectively. These metals can be dispersed downstream and downslope from the tailings by water after rainfall. Soil samples collected in the surroundings of Mar Menor Lagoon were analysed, reflecting the influence of the transport of soluble and particulate materials from Cabezo Rajao, especially of Pb and Zn. However, the presence of high amounts of carbonate in the soils around the mine area revealed the stabilization of all the metals studied.
The Gangdese Belt is now recognized as an important Cu polymetallic mineralization belt. Recent studies suggest that apart from porphyry copper deposits, polymetallic skarn deposits are another significant deposit type in this belt. In this paper, principal component analysis (PCA) and spectrum–area ( – ) fractal modeling are used to identify geochemical anomalies associated with Cu and Pb–Zn skarn mineralization based on Cu, Pb, Zn and Ag stream sediment data. Firstly, the raster maps of Cu, Pb, Zn and Ag were obtained by multifractal inverse distance weighted (MIDW). Secondly, PCA was used to combine the Cu, Pb, Zn and Ag concentration values. Finally, – analysis was used to decompose the first component pattern obtained by the PCA. The results show that major anomalies of Cu, Pb, Zn and Ag are mostly located around mapped intrusions, and along E–W trending faults, where Cu and Pb–Zn skarn deposits favorably occur. These results indicate that: (1) the Gangdese Belt potentially hosts undiscovered Cu and Pb–Zn skarn deposits, and the integrated anomalies for Cu, Pb, Zn and Ag occurring around the intrusions and in the vicinity of faults in the center part of the Gangdese Belt should be further investigated in the next step of mineral resource exploration; and (2) the hybrid method combining PCA and – modeling is an effective tool to identify geochemical anomalies. ► Geochemical mapping plays an important role in mineral resource exploration. ► Spectrum–area fractal model is an effective tool to decompose mixed geochemical pattern. ► Gangdese Belt potentially hosts undiscovered skarn deposits.
In this paper, it is shown that recently developed nonlinear singularity theory and methods can be used to recognize weak but complex geo-anomalies for the prediction of the presence of mineral deposits in areas covered by deserts, regolith or vegetation. The theory and models of singularity and generalized self-similarity developed in the context of multifractals are proposed for analyzing weak anomalies caused by buried mineralization. These anomalies can be extracted from geochemical stream sediment data and can be used for the prediction of the Fe and Sn mineral deposits of skarn and hydrothermal types in Gejiu, Yunnan and Eastern Tianshan, Xinjiang, China. Significant portions of these areas are covered by vegetation, desert or regolith. The concepts and models of local singularity and generalized self-similarity are utilized to demonstrate that the singularity index, which is the exponent of the power-law associating density with scale (area or volume) of geochemical anomaly, determines an essential dimensional property of geochemical anomaly that is independent of its geometrical scale. Singularity values calculated by means of the local singularity analysis method are capable of enhancing weak geochemical anomalies caused by deeply buried sources. The principles and methodologies proposed in this paper are demonstrated by a case study of predicting the presence of Fe mineral deposits in Eastern Tianshan, China. The singularity analysis methods, in conjunction with combined low-pass and high-pass filtering methods, were successfully applied to process regional stream sediment geochemical maps, gravity map and aeromagnetic map with the aim of extracting weak anomalies revealing locations of mafic volcanic rocks, felsic to intermediate intrusions, skarn and hydrothermal alterations in the study areas. These geological features are genetically associated with skarn and other hydrothermal iron deposits in the area. A modified fuzzy weights-of-evidence method with a correction for conditional independence of evidence was applied to integrate the evidence and to create a posterior probability map. The results show that weak geochemical anomalies caused by buried mineral deposits in the considered areas are significantly enhanced and extracted from variable backgrounds. Approximately 30% of significant target areas delineated by the integrated geo-anomalies in the study areas had been previously ignored. ► Proposed new methods for prediction of mineral deposits in covered areas. ► Proved singularity is applicable for mapping anomalies caused by buried sources. ► Mapped target areas for finding Fe mineral deposits in covered areas. ► Demonstrated integrated approach effective for mineral exploration in covered areas.
The combination of revegetation and application of stabilizing soil amendments on heavy metal-contaminated soils is generally considered to be a promising alternative to expensive classical remediation techniques. Here, we simultaneously investigated the effects of six cost-effective amendments (CaCO , iron grit, fly ash, manure, bentonite and bone meal) on Cd, Zn and Pb leaching and phytoavailability (assessed using white lupin, L.). The Cd and Zn leaching was reduced by all amendments mainly due to alkalinity increase. The Pb leaching was strongly affected by the dissolved organic carbon (DOC) release. Therefore, bone meal and manure treatments, which highly increased DOC concentrations in leachates, increased the flow-weighted mean Pb concentrations by 2.3 and 16 times, respectively. Surprisingly, while iron grit induced strong Cd and Pb leaching reductions, this amendment doubled Cd and Pb concentrations in shoots of white lupin. Conversely, the addition of bone meal reduced Pb concentrations in shoots by 74%, probably because organo-Pb complexes (predicted using Visual MINTEQ) were largely dominant in solution. Overall, the addition of CaCO offered the best compromise as it successfully reduced both the leaching and the phytoavailability of the three considered metals. Our results demonstrate the efficacy of several amendments while stressing the need to measure simultaneously the leaching and the phytoavailability of metals induced by each amendment. ► We study the effects of amendments on Cd, Zn and Pb leaching and phytoavailability. ► pH controls Cd and Zn leaching while DOC controls Pb leaching. ► Iron grit highly lowers metal leaching but doubles Cd and Pb phytoavailability. ► Bone meal and manure lower metal phytoavailability but strongly increase Pb leaching. ► CaCO appears to be the most effective amendment.
An extensive survey was conducted in the study to determine the spatial distribution and possible sources of As and heavy metals in the agricultural soils in the Shunde, a representative area in the Pearl River Delta, China. A total of 238 topsoil samples were collected (0–20 cm) from the study area. The levels of Cd, Co and Ni were then analyzed by inductively coupled plasma mass spectrometry, while the content of Cr was determined by inductively coupled plasma optical emission spectrometry, and As and Hg concentrations were analyzed by atomic fluorescence spectrophotometry. The results showed that the mean concentrations of As, Cd, Co, Cr, Hg and Ni are 16.08, 0.60, 16.76, 78.87, 0.38 and 33.45 mg/kg, respectively. The concentrations of Cd and Hg were far higher than their background values of Pearl River Delta topsoil, and in the study area, 2.10%, 90.86%, 43.27% and 18.07% samples for As, Cd, Hg and Ni were higher than the guideline values of the Chinese Environmental Quality Standard for Soils, especially for Cd and Hg, which are 2.00 and 1.27 times the guide values, respectively. Multivariate and geostatistical analyses suggested that soil Cr, Ni, and Zn had a lithogenic origin. Whereas, soil contamination of Cd and As was mainly related to industrial and agronomic practices, and the main sources of Hg were coal burning exhausts, industrial fumes, domestic waste, and vehicle exhausts. The origin identification of As and heavy metals in agricultural soils is a basis for undertaking appropriate action to reduce their inputs.
The purpose of this study was to identify the various mineralization zones especially supergene enrichment and hypogene in two different Iranian porphyry Cu deposits, based on subsurface data and by using the proposed concentration–volume (C–V) fractal method. The Sungun and Chah-Firuzeh porphyry Cu deposits, which are situated in NW and SE Iran, respectively, were selected for this study. Straight lines fitted through log–log plots showing C–V relations for Cu were employed to separate supergene enrichment and hypogene zones from oxidation zones and barren host rocks in the two deposits and to distinguish a skarn mineralized zone from the hypogene zone in Sungun deposit. In the proposed C–V fractal method, the identification of mineralization zones is based on power–law relationships between Cu concentrations and the volume of rocks hosting porphyry Cu mineralization. Separate subsurface data from the two deposits were analyzed by C–V fractal method and the results have been compared with geological models which included alteration and mineralogical models. The comparison shows that the interpreted zones based on the C–V fractal method are consistent with the geological models. The proposed C–V method is a new approach to defining zones in a mineral deposit and there was no commercial software available to perform the relevant calculations; therefore, a fractal concentration–volume (FCV) software was designed by the authors to achieve this goal. ► Determination of concentration-volume (C-V) method for identification of mineralization zones in porphyry deposits. ► Separation of supergene and hypogene zones in Sungun and Chah-Firuzeh Iranian porphyry deposits by C–V method. ► Separation skarn zone from porphyry stock in Sungun porphyry deposit by using of C–V method. ► Construction of FCV software. ► Correlation between results from C–V method and geological characteristics.
As a tributary of Le'an River in Jiangxi Province of China, Jishui River has been seriously polluted by non-ferrous heavy metal mining activities, and long-term irrigation using Jishui River water has caused severe heavy metal pollution of soil. We collected samples of agricultural soils along the river and determined the contents of As, Cd, Cr, Cu, Mn, Ni, Pb and Zn. The results showed that Cd and Cu were two primary pollutants in the soils with concentrations of 0.52–2.55 mg·kg and 27.87–426.15 mg·kg , respectively. The mean concentrations of As, Mn, Pb and Zn in the soils were 33.99 mg·kg , 468.70 mg·kg , 125.32 mg·kg and 171.48 mg·kg , respectively. Moreover, higher heavy metal concentrations were found in the agricultural soils closer to mines and metal smelters. The metal speciation analysis showed that Cd was mainly in the exchangeable and carbonate fraction, and the reducible fraction of Mn and Pb was a significant proportion in most soils. However, Cu and Zn were mainly in the residual fraction in all samples. Assessments of pollution levels revealed that (1) heavy metals that were mainly from anthropogenic sources, such as Cd, Cu, Pb and Zn, were much higher than their background value, (2) heavy metal pollution in the agricultural soils closer to the mines and smelters was often more severe, and (3) the environmental risk of Cd was highest and should be of special concern.
The objective of this study is, firstly, to investigate the contamination levels and dispersion patterns of As and heavy metals, secondly, to estimate the bioaccessible fraction of the metals in soil and crop plant and, finally, to assess the risk of health effects on the residence in the vicinity of the abandoned Songcheon Au–Ag mine, Korea. Samples of tailing, soil, crop plant and water were collected around the mine site. After appropriate preparation, all samples were analyzed for As, Cd, Cu, Pb and Zn by ICP-AES and ICP-MS. Elevated levels of As and heavy metals were found in tailing. Mean concentrations of As in agricultural soil were higher than the permissible level. Especially, maximum levels of As and Hg in farmland soil were up to 626 mg/kg and 4.9 mg/kg, respectively. The highest levels in crop plant were 33 mg As/kg and 3.8 mg Pb/kg (in green onion root), 0.87 mg Cd/kg and 226 mg Zn/kg (in lettuce root), 16.3 mg Cu/kg (in sesame leaves). The concentration of heavy metals in leaves is much higher than those in grains and stalk. Vegetables grown on the contaminated soil were rich in As and heavy metals. Concentrations of As, Cd, and Zn in most stream waters which are used for drinking water around the mine area were higher than the permissible levels regulated in Korea. Maximum levels of As, Cd and Zn in stream waters were 0.71 mg/L, 0.19 mg/L and 5.4 mg/L, respectively. These results indicate that mine tailings can be the main contamination sources of As and heavy metals in the soil–water system of the mine site. The average of estimated human-bioaccessible fraction in soil in simulated stomach was 3% As, 40% Cd, 15% Cu, 31% Pb and 21% Zn, and that in simulated small intestine 12% As, 2.2% Cd, 5.6% Cu, 0.5% Pb and 1.2% Zn. The highest value of human-bioaccessible fraction of metal in farmland soil was 85% for Cd. The estimated human-bioaccessible fraction of plant was up to 97% for Cd in simulated stomach, and to 51% for Pb in simulated small intestine. The highest human-bioaccessible fractions were found in Chinese cabbage (in stomach) and potato leaves (in small intestine). The average human-bioaccessible fraction in plants were 47% As, 70% Cd, 62% Cu, 0% Pb and 62% Zn in simulated stomach and 22% As, 7% Cd, 27% Cu, 9% Pb and 23% Zn in simulated small intestine. The HQ (hazard quotient) value of the mine site was 16, and especially, the HI (hazard index) value of only As was 15. The carcinogenic risk of the mine site was 2.7E−03. This value means the probable possibility that about 3 cancer patients among 1000 people happen. Carcinogenic risk exceeded in the generally accepted range of E−04 to E−06.
There is lack of research and documentation of actual (as opposed to theoretical) benefits (e.g., mineral deposit discovery) of developments in compositional data analysis and imputation of censored values to mineral exploration geochemistry. In the present study, analyses of logratio- and -transformed stream sediment geochemical data containing ca. 30% of samples with censored values of a pathfinder element for the mineral deposit-type of interest yielded the following findings. Exclusion of those samples supports interpretation of multi-element anomalies reflecting the presence of mineralization. However, the multi-element anomaly maps obtained by exclusion of those samples are barely better than the multi-element anomaly maps derived by inclusion of those samples after replacing the censored values with 1/2 of detection limit or with imputed values. Logratio (i.e., , , or ) transformation, compared to -transformation, of stream sediment geochemical data does not improve mapping of pathfinder element anomalies reflecting the presence of mineralization. However, stream sediment geochemical data, excluding or including censored values (replaced with 1/2 of detection limit or with imputed values), should be - or -transformed to enhance recognition of anomalous multi-element associations reflecting the presence of mineralization. The anomaly maps of multi-element associations derived from -transformed data are better, albeit slightly, than the anomaly maps of multi-element associations derived from -transformed data. In the present study, the main benefit of either - or -transformation, compared to either - or -transformation, of stream sediment geochemical data is the enhancement of anomalous multi-element associations reflecting the presence of mineralization. This is an important benefit because variations in trace element concentrations in regional-scale stream sediment geochemical data are mostly due to lithology and other factors (or processes) unrelated to mineralization. Further investigations of various exploration geochemical data are needed to demonstrate and document the actual (as opposed to theoretical) benefits of developments in compositional data analysis and imputation of censored values to mineral exploration. ► This study examines and documents actual (as opposed to theoretical) benefits compositional data analysis and imputation of censored values to exploration geochemistry. ► Geochemical data used contain ~30% of samples with censored values of a pathfinder element for deposit-type of interest. ► Logratio compared to -transformation of geochemical data does not improve mapping of pathfinder element anomalies. ► Geochemical data should be - or -transformed to enhance recognition of anomalous multi-element associations.
Indonesia (Sulawesi and Halmahera Islands) has some of the largest surface exposures of ultramafic bedrock in the world, and these are the sites of productive lateritic nickel mining operations. The proven and potential use of native plant species of ultramafic outcrops in mine rehabilitation can help drive conservation efforts, and nickel hyperaccumulators in particular can potentially be used in phytomining. The phytomining operation uses hyperaccumulators to extract residual nickel from stripped land. As such, in the foreseeable future, implementation of this technology is likely to be seen as a part of a progressive rehabilitation strategy of lateritic nickel mining in Indonesia. This approach ensures effective erosion control (e.g. ‘re-greening’) while at the same time generating income by gaining residual nickel. ► Indonesia has some of the world's largest nickel laterite occurrences. ► Nickel extraction results in significant adverse environmental impacts. ► Native nickel hyperaccumulators can be used for phytomining technology. ► Nickel phytomining offers to gain income from mine site rehabilitation.
Acid rock drainage (ARD) prediction is a very important issue in order to predict and prevent environmental pollution associated with mining activities. Nowadays, simple tests are widely applied and established in the mining and consulting business for ARD prediction. These tests have many known errors and problems, as that they do not account for the complexity of the mineral assemblage of an ore deposit, and therefore are not able to predict the geochemical behavior accurately. This critical review has the aim of first, highlighting the geochemical processes associated to the problems of ARD prediction. Secondly, the errors and limitations of the standard static and kinetic tests are highlighted. The currently applied calculation factor of 31.25 for sulfide acid potential calculation overestimates the carbonate neutralization potential by 100% in its geochemical assumptions. Thus, the calculation factor 62.5, based on the effective carbonate speciation at neutral pH, is recommended. Additionally, standard ABA procedure ignore the acid potential of Fe(III) hydroxides and/or sulfates and do not distinguish between different carbonate minerals. This can be critical, as for example siderite can be a net acid producing carbonate. Therefore, it is crucial to count on accurate quantitative mineral data in order to be able to accurately predict ARD formation and potential liberation of hazardous trace elements to the environment. In many modern mining operations, quantitative mineral data is nowadays produced in order to enhance the recovery of the extraction process by the incorporation of geometallurgical information (e.g. quantitative mineralogy, mineral liberation, textural information, grain size distribution). Thus, the use of this very same existing data for ARD prediction can increase importantly the precision of ARD prediction, often without additional costs and testing. The only requirement is the interdisciplinary collaboration between the different divisions and data exchange in a modern mining operation.
The Heqing area, located in the Sanjiang ore belt, China, consists of the Beiya gold orefield related to the alkaline porphyry, the Emeishan volcanic mafic rocks and a series of sedimentary rocks. Thirty-nine elements of stream sediment samples taken in the 1:200,000 geochemical survey in the Heqing area can be classified into four groups using principal component analysis. Two fractal models, i.e., the concentration–area model and the number–size model, are applied in determination of the thresholds for the representative elements in the four groups. The thresholds obtained from the two models are similar. According to the thresholds, the element concentration distribution can be divided into 3 segments, each of them is mainly correlated to one type of rocks, including the alkaline porphyry related to gold-mineralized rocks, mafic rocks and sedimentary rocks. This paper reveals that the various geological events can be characterized by the different fractal models of element distribution.