Stream Sediment Research Articles

The applicability of G-BASE stream sediment geochemistry as a combined geological mapping, and prospective exploration tool for As-Co-Cu-Ni mineralisation across Cumbria, UK

Stream sediment geochemistry is a useful tool to analyse the geochemistry of the local geology within the source catchment area. This has significant applicability within the field of mineral exploration where understanding regional lithological geochemistry and how this is reflected in stream sediment geochemistry is needed, facilitating the identification of critical metal deposits. Successful identification of these deposits is essential to help tackle the deficit of these metals supply chains, especially for cobalt. This is in order to meet future carbon-neutral technological demand as part of global initiatives towards a more environmentally sustainable society.We make use of the UK Geochemical Baseline Survey of the Environment (G-BASE) dataset to demonstrate this stream sediment geochemical data has the potential to be used as a useful tool for isolating potential critical metals in host rocks across the UK Lake District. We reduced the dimensionality of the G-BASE stream sediment data, creating geochemical maps that identify a combination of volcanic, sedimentary, and plutonic lithologies lining up geological boundaries from established 50 k scale geological maps of the area. This was conducted through a combined statistical and mapping approach within QGIS and ioGAS.Furthermore, we derived average ore metal concentrations (Ag, As, Bi, Co, Cu, Mo, Ni, Sn, Zn) for the Skiddaw Group and the Borrowdale Volcanic Group, two established host lithologies for As-Co-Cu-Ni mineralisation. Average concentrations of Co in the Skiddaw have been modelled to be ~63 ppm, and ~ 28 ppm in the Borrowdale volcanics. These values, combined with As, Cu, and Ni modelled concentrations, and other available exploration-related data (structural maps, underlying batholith topography, mining history etc.) have allowed us to identify 10 prospective areas of interest for possible As-Co-Cu-Ni mineralisation. This workflow has strong applicability within critical metal exploration in the UK and other, prospective regions across the globe.

The Twannberg iron meteorite strewn field in the Swiss Jura mountains: insights for Quaternary environmental conditions

The ~ 10 km2 strewn field of the Twannberg type IIG iron meteorite is located in the Swiss Jura Mountains, 30 km northwest of Bern. The strewn field has been mapped by a group of citizen scientists since 2006, yielding more than 2000 meteorite fragments with a total mass of 152.7 kg until the end of 2022. With a terrestrial age of 176 ± 19 ka and a minimum pre-atmospheric mass of ~ 250 t, the Twannberg meteorite is a local time marker in an area with a poorly-known paleoenvironmental history. The Twannberg strewn field is located just outside of the maximum extent of ice during the Last Glacial Maximum (LGM). On the Mont Sujet, meteorites are size-sorted in a 6-km long section of the primary strewn field (altitude 945–1370 m a.s.l.), indicating a fall direction from east-northeast to west-southwest (azimuth approximately 250°). On the Twannberg plateau and in the Twannbach gorge, meteorites are not size-sorted and occur in a ~ 5.7-km long area associated with till and recent stream sediments (altitude 430–1075 m a.s.l.). The mass distribution of meteorites on the Twannberg plateau demonstrate that these meteorites were not found where they fell but that they must have been transported up to several km by glacier ice flow after the fall. The distribution of meteorites and of glacially transported Alpine clasts on the Mont Sujet and on the Chasseral chain indicates the presence of local ice caps and of an approximately 200-m higher Alpine ice surface with respect to the LGM at the time of fall. This high ice level during MIS 6 (Marine Isotopic Stage 6, 191–130 ka) indicated by the meteorite distribution is consistent with surface exposure ages of 50–144 ka from nearby resting erratic boulders at altitudes of up to 1290 m a.s.l., including the newly dated Jobert boulder (63 ka). These boulders indicate an ice level ~ 400 m higher than during LGM at a time not later than MIS 6. Post-LGM luminescence ages of loess-containing meteorites on the Mont Sujet and 14C ages of materials associated with meteorite finds indicate relatively young pedoturbation and increased oxidation of meteorites since ~ 7300 cal BP, possibly correlated with deforestation and enhanced erosion resulting from increased human activities since the Neolithic. This study shows that Twannberg meteorites in their palaeoenvironmental context provide valuable information about ice levels and transport directions during MIS 6 and about their interaction with the post-LGM environmental conditions. The unique Twannberg strewn field has the potential to reveal more valuable information.

Stable cerium isotope analysis of geological materials by MC-ICP-MS

We report stable cerium (Ce) isotopic compositions of terrestrial rocks and investigate Ce isotopic fractionation during column chemistry in this study. Cerium was separated from matrix elements by a single-stage extraction technique using Eichrom DGA resin. Ce isotope ratios were measured using a Thermo Scientific Neptune Plus MC-ICP-MS employing a sample–standard combined with a Sm-doping method. The data accuracy and precision of Ce isotope analyses were rigorously examined by two different laboratories. The δ142Ce values of mono-elemental Ce standards (JMC304 and CDUT-Ce) relative to NIST SRM 3110 solution were − 0.005 ± 0.042‰ (2SD, N = 9) and 0.118 ± 0.033‰ (2SD, N = 6), respectively. The δ142Ce of the manganese nodule (NOD-P-1) measured in two laboratories were 0.177 ± 0.035‰ (2SD, N = 7) and 0.172 ± 0.034‰ (2SD, N = 8), respectively; NOD-A-1 were 0.116 ± 0.028‰ (2SD, N = 8) and 0.104 ± 0.028‰ (2SD, N = 9), respectively. The offset between these two manganese nodules could be possibly related with their unique diagenetic environments. The δ142Ce of two USGS standards diabase W-2a was −0.036 ± 0.046‰ (2SD, N = 3), basalt BHVO-2 was −0.019 ± 0.036‰ (2SD, N = 4). Ce isotopic compositions of three Chinese reference standards granite gneiss GBW07121, diabase GBW07123, and stream sediment GBW07301a were 0.039 ± 0.033‰ (2SD, N = 5), 0.068 ± 0.027‰ (2SD, N = 5) and 0.046 ± 0.015‰ (2SD, N = 3), respectively. The reported data will be helpful for quality assurance and inter-laboratory comparison for high-precision Ce isotopic studies.Full recovery is important to achieve high precision and high accuracy data for metal isotopes. To understand Ce isotope behavior during column separation, an experiment with different Ce cuts was conducted. The δ142Ce of JMC304 and NIST SRM 3110 in five different Ce subcuts varied from 0.047 ± 0.020‰ (2SD, N = 3; 0–25% cut) to −0.029 ± 0.047‰ (2SD, N = 5; 45–100% cut), and 0.058 ± 0.047‰ (2SD, N = 4; 0–11% cut) to −0.022 ± 0.033‰ (2SD, N = 4; 32–100% cut), respectively. δ142Ce of these subcuts showed small ranges, but isotopic fractionation of Ce did occur during column chemistry and light isotopes are preferentially retained in the DGA resin.

Mercury occurrence and speciation in sediments from hard coal mining in Czechia

This study examines Hg distribution in stream sediments impacted by hard coal mining in the Upper Silesian Coal Basin (USCB), Czechia. By means of a comparative analysis, geological samples and samples from stream sediments were used to carry out a comprehensive assessment of the effects of anthropogenic activities on Hg distribution and speciation. Total Hg (THg), total organic and inorganic carbons (TOC and TIC), and total sulphur (TS) were measured in the samples to reveal a potential relationship. In addition, THg and TS species were discussed in order to elucidate their mobility pattern in the environment. The results have shown that there are no correlations between THg, TS, and TOC indicating overlapping Hg sources attributed to industrial processes. Geological samples, particularly coal and associated sedimentary rocks, contained lower Hg concentrations compared to a variety of stream sediments. The main Hg species identified in the samples was a stable β-HgS, which decreases its mobility in the riverine environment. It follows that Hg enrichment and speciation is linked to industrial processes, which are the main origin/cause for Hg enrichment and transformation. Minor proportions of HgO in some samples show Hg oxidation upon diagenesis, while HgCl2 is attributed to the chemical loads from the former coking plant.

Trace metal geochemistry sediments from the Dibamba River, SW Cameroon: Implication for heavy metal assessment and origin

Sediment quality and trace metal accumulation are two of the most pressing issues facing the aquatic ecosystem around the world. Twenty-four (24) samples of stream sediments were collected along the Dibamba River, in the economic and industrial capital of Cameroon, to judge the trace metal levels in this river flowing near the city of Douala. Trace metal concentrations were disclosed with an ICP-MS on two different grain size fractions (very fine-grained sand and clay). The sediments indicate possible adverse effects of trace metals on surrounding biota as elements like Cr, Cu, Ni, Zn, Pb, and Hg show positive enrichment of greater than 1 when compared to background values from the upper continental crust (UCC) and sediment quality factors such as TEL (threshold effects level), PEL (probable effects level), ERL (effects range low), and ERM (effects range medium) values. The sediments show values of Degree of contamination (DC = 2–4), Pollution load index (PI = 1–2), and individual potential risk (EI = 92–219) indicating moderate pollution and ecological risk. Statistical and multivariate analyses point to both anthropogenic and geogenic sources for the heavy metals in the Dibamba stream sediments. The geogenic origin of the heavy metals is linked to the weathering of gneiss and migmatite found in the river banks. This study found low to mild levels of metal pollution and toxicity in the sediment, but it also warned that the continued development of nearby industries and businesses, the provision of transportation services, and waste disposal activities could result in a gradual outflow and accumulation of metals in the sediment, endangering the aquatic ecosystem.

Tracking Sediment Provenance Applying a Linear Mixing Model Approach Using R’s FingerPro Package, in the Mining-Influenced Ocoña Watershed, Southern Peru

Stream sediments record water–rock interactions in tributaries followed by fluid mixing in larger downstream catchments, but it can be difficult to determine the relative contributions of each tributary. A good way to analyze this problem is sediment fingerprinting, which allows researchers to identify the source of sediments within a basin and to estimate the contribution of each source to the watershed. Herein, we developed a workflow using the frequentist model FingerPro v1.3 to quantify the sediment source contribution in a semiarid watershed. We applied an unmixing model algorithm to an ICP-MS geochemical database containing information on 32 elements in 362 stream sediment samples. By modeling the source contributions to these mixed samples, we infer that the main sediment contribution comes from the upper portion of the catchment (61–70%), followed by the middle (21–29%) and lower (8–10%) parts, with geochemical anomalies (As and Cu) being closely related to mining sites. Results from this study can be helpful for future management decisions to ensure a better environment in this semiarid watershed.

Is the pathway length of sediments relevant to assess the background value in stream sediment geochemical exploration?

The sample catchment basin approach (SCBA) is one of the methods mainly used to assess the expected chemical composition of a stream sediment sample considering the geolithological variability of the catchment basin upstream of its collection point. In the original SCBA, the catchment surface considered for the purpose is limited to the area between two subsequent collected samples; in the true sample catchment basin approach (TSCBA), the catchment area of each collected sample is limited upstream only by the actual watershed. In both approaches, the dilution is generally assessed in relation to the extension of the single geolithological units falling within the sample catchment area used.However, it makes sense to think that when multiple geolithological units are outcropping upstream of a sampling location, the sediments originating from the ones closer to the collection point (which have traveled a shorter distance) could have a major influence on the geochemical composition of the samples. It is plausible that the degree of dilution occurring during the transport from the source to a given point could also be a function of the distance traveled by the sediments along the fluvial pattern. This also holds in the case of mineralization occurring within the catchment: the farther a mineralization is from a sampling point, the more its geochemical signal should be diluted at the sampling site.In the present study, using the TSCBA, a modification of the existing algorithm is proposed to include both the extension of the geological units and their position relative to the catchment outlet (represented by the sampling point).The territory around Feshark village (Isfahan, central Iran), where stream sediment and rock samples have been collected and analyzed, has been used as the study area. The geochemical background values (corresponding to the expected geochemical values following dilution) for each stream sediment sample were determined using the modified algorithm. The results were compared with those obtained by applying the original equation to the same dataset. The results demonstrated that the new equation could more accurately estimate background (expected) concentrations at the basin outlet, showing a better performance of the new method compared to the original one.

The Application of Portable X-ray Fluorescence (pXRF) for Elemental Analysis of Sediment Samples in the Laboratory and Its Influencing Factors

Several techniques, such as chemical methods and inductively coupled plasma mass spectrometry (ICP-MS), are available to accurately determine element content. However, they are time-consuming, labor-intensive, or expensive. Portable X-ray fluorescence spectrometry (pXRF) can be applied in various scenarios, with significantly higher efficiency and cost-effectiveness than laboratory methods. However, it also has limitations such as lower detection capability, relatively high detection limits, and lower accuracy than laboratory methods. In this study, we focused on applying pXRF to determine the elemental content of sediment samples and investigate its use in mineral exploration. A variety of factors influencing the results of pXRF analysis were analyzed. Our results showed that pXRF could detect more than 30 elements in stream sediments. The reliability of pXRF’s measurements was affected by factors such as the kind of element, sediment particle size, sample grinding treatment, count time, averaged element content, standard deviation of content, and range of content variation. The combination of pXRF analysis and laboratory analysis of partial samples is adequate for establishing a multi-element content inference equation. With this equation, it is possible to effectively infer the content gradient of elements, which will provide valuable support for mineral resource exploration.

The effect of Paenibacillus on IDEXX Enterolert results from freshwater stream environments.

Enterolert, a fluorogenic substrate test, is used as a quantitative method for determining freshwater concentrations of Enterococcus for water quality indicators. However, there is some evidence from recent studies suggesting that Enterolert may not suppress false positives due to pollution sources in waterbodies. In this study, we evaluated this method by analyzing field water and sediment samples from four freshwater streams. We also performed a laboratory microcosm study from two of the stream sediments. The Enterolert method was investigated by phenotypic and genomic analyses for accuracy of isolating and quantifying Enterococcus and/or Streptococcus. Additionally, we tested isolates from Enterolert panels for antibiotic resistance. Results from the field and microcosm studies from initial to final time points indicated that false positives were predominantly Paenibacillus spp. and other non-fecal indicator bacteria. Furthermore, the microcosm study indicated shifts from lactic acid to non-lactic acid bacteria between initial to final time points, but Enterococcus concentrations from Enterolert panels remained stable for the duration of the study for both stream sediments. Antibiotic resistance indicated no distinct pattern of resistance or susceptibility to a suite of antibiotics. However, all isolates tested were resistant to bacitracin and nalidixic acid. In conclusion, we found that Enterolert was not exclusively selective for Enterococcus from freshwater environments and that sediment and polluted waterbodies have the potential to skew the presumed concentrations. More research is needed to evaluate the effectiveness and selectivity of the medium used for the fluorogenic substrate test for Enterococcus enumeration.

Elevated sediment radionuclide concentrations downstream of facilities treating leachate from landfills accepting oil and gas waste

Management of oil and gas (O&G) waste streams from extraction of unconventional reservoirs challenges the sustainable development of these reservoirs. Landfilling of waste materials is an emerging strategy for unconventional O&G waste disposal. However, the effectiveness of effluent management systems designed for historical landfill waste streams in treating O&G waste is not established. This creates the potential for contamination associated with landfills accepting O&G waste. Yet, tracers of O&G waste are not necessarily included in routine effluent monitoring and environmental surveillance monitoring is too sparse to reliably detect this contamination. This study reviewed administrative records and analyzed grab samples of surface waters and stream sediments near effluent outfalls from facilities accepting O&G waste to evaluate this potential contamination. Administrative records are conflicting and inadequate, with only one landfill out of twenty-five agreeing within a factor of two between waste delivery and receipt volume reporting in 2019. Moreover, total radium was enriched in sediments downstream of effluent discharges, up to 4x relative to upstream values, magnitudes consistent with sediment accumulations downstream of known O&G waste inputs. Water chemistry measurements indicate that the largest upstream to downstream changes are consistent with O&G waste chemistry. These findings suggest landfill effluent influenced by O&G waste should be carefully scrutinized to avoid potential contamination of surface waters.

Determination of Elemental Composition and Content in Stream Sediments by Laser-Induced Breakdown Spectroscopy

Determination of Elemental Composition and Content in Stream Sediments by Laser-Induced Breakdown Spectroscopy

Graph inference algorithms as high-performance tools for detecting geochemical anomalies related to mineralization from geochemical exploration data

Geochemical exploration data usually consists of a small number of labeled data (cells containing known deposits) and a large number of unlabeled data (cells containing none of known deposits). How to make full use of a small number of labeled data and a large number of unlabeled data to build a high-performance anomaly detection model for identifying mineralization anomalies from geochemical exploration data is a challenge faced by geochemical exploration practitioners. The graph inference algorithms including label propagation and label spreading can efficiently build high-performance semi-supervised classification models by learning from sparse labeled and abundant unlabeled data in machine learning. For this reason, the two graph inference algorithms were used to build the semi-supervised classification models to detect Fe-mineralization anomalies from stream sediment survey data of 1: 50,000 scale in the Chengde area (Hebei Province, China). The label propagation model and label spreading model were compared with the Gaussian mixture model and logistic regression model in detecting Fe-mineralization anomalies. The data processing time of the label propagation algorithm and label spreading algorithm is 64.26 s and 28.21 s, respectively; and the data processing time of the Gaussian mixture model and logistic regression algorithm is 37.79 s and 18.98 s, respectively. The area under the receiver operating characteristic curves (AUCs) of the label propagation model and label spreading model are 0.979 and 0.999, respectively; and the AUCs of the Gaussian mixture model and logistic regression model are 0.800 and 0.817, respectively. Therefore, the data modeling efficiency of the label propagation model and label spreading model is comparable to that of the Gaussian mixture model and logistic regression model in detecting Fe-mineralization anomalies. However, the performance of the label propagation model and label spreading model are significantly better than that of the Gaussian mixture model and logistic regression model. It can be concluded that the two graph inference algorithms are potentially useful high-performance tools for detecting mineralization anomalies from geochemical exploration data.

Geochemical evaluation and environmental risk assessment of heavy metals: A case study from Ireland using Tellus stream sediment data (2011–2017)

A comprehensive assessment of the distribution, spatial mapping and ecological risk of heavy metals in stream sediments of 17 counties of Ireland based on the Tellus geochemical survey programme in Ireland was carried out. Average trace metal concentrations of chromium (Cr), nickel (Ni), copper (Cu), lead (Pb), zinc (Zn), vanadium (V), cobalt (Co), arsenic (As), and major and minor oxides iron oxide (Fe2O3), manganese oxide (MnO) in the stream sediments were above the background values, but lower than Irish sediment quality guidelines for livestock and Canadian sediment quality guidelines (ISQG); threshold effect level (TEL) and probable effect level (PEL). 69.65% of Ni, 22.13% of Zn, and 96.7% of Pb samples exceeded the low-effect-range (ERL) values, whereas only 21%, 1.80% and 0.69% of the same elements exceeded the median effect range (ERM) values. Hotspots of Zn (>12000 mg kg−1), Pb (>10,000 mg kg−1), Fe2O3 (61.38%), MnO (26%), Cr (>2300 mg kg−1) and Ni (874.2 mg kg−1) were observed at Wicklow, Dublin, Mayo, Galway and Cavan counties. Catchment geochemistry was identified for the presence of heavy metals in the stream sediments. The geo-accumulation index (Igeo) indicated Kildare to be the least contaminated county with Igeo < 0 for Cr, Ni, Cu, Zn, Pb and As for 50% of the samples. The enrichment factor (EF) indicated that some sites located in Mayo and Donegal were highly contaminated. PInemerow followed the trend, Tipperary > Dublin > Waterford > Monaghan > Donegal > Wexford > Galway > Wicklow > Cavan > Meath > Kilkenny > Leitrim > Mayo > Louth > Sligo > Kildare > Carlow. Based on potential ecological risk index (PERI), 83.1% of the sites posed low ecological risk (PERI <150), 11.9% sites posed moderate risk (150 < RI < 300) and high ecological risk was posed by 0.3% (PERI >1200) of the sites. Lithology, topography and anthropogenic factors influenced the distribution and ecological risks of heavy metals. Non-carcinogenic and carcinogenic risk for adults and children were above the recommended value.

Geochemical Speciation, Ecological Risk and Assessment of Main Sources of Potentially Toxic Elements (PTEs) in Stream Sediments from Nile River in Egypt

Studying and understanding the complexity and interactions of different factors influencing stream sediment quality is necessary for the development of successful water quality management strategies. This study aims to evaluate the level of contamination by potentially toxic elements (PTEs) (As, Co, Cr, Cu, Mn, Ni, Pb, V, Zn) of the stream sediments of the Nile River. During the spring of 2019, river sediments were sampled at 23 sites along the Nile River. For each sample, one aliquot was digested in aqua regia and analyzed by ICP-MS for pseudo-total concentration, while for another aliquot, sequential extraction procedures were applied to determine chemical speciation. Compositional data analysis (CoDa) and k-means were applied to recognize the contribution of natural and anthropogenic sources, while pollution indices (EF, RAC) and sediment quality guidelines (SQGs) were applied to assess the ecological risk to biotic species. The results reveal that elements such as Cr, Mn, V and Fe, found in high concentrations in almost all samples (Cr up to 739 mg/kg, Mn up to 1942 mg/kg, V up to 507 mg/kg, Fe up to 98,519 mg/kg), have a natural origin, while the concentrations of Cu (up to 69 mg/kg), Ni (up to 88 mg/kg), Co (up to 42 mg/kg) and As (up to 9.8 mg/kg) are linked to both natural and anthropogenic processes. Sequential extraction shows that Mn, Co, Ni and, in some sites, Cu and Zn, are the most bioavailable elements. These elements present a high risk of toxicity, while the remaining elements imply a low-to-moderate risk.

Investigation of textural attributes of sediment in Ifelodun County, Nigeria

Stream sediments were collected from different areas in Ifelodun county within latitude 8°451N to 8°51N and longitude 4°461E to 5°61E. 13 samples of sediments were obtained from each of the eight locations totaling 108. A German standard sieve set of mesh with shaker was used for grain size analysis. The results of grain size analysis range from medium to very coarse sand as the majority of sediment composition before investigation of textural parameters. The result of textural parameters was obtained and used to differentiate the depositional environment of the sediments. The mean, sorting, skewness and kurtosis defined the sediment as very coarse, poorly sorted, vary from very fine skewed to near symmetrical with mesokurtic environment, although the other extreme tails also exist. Positively skewed and poorly sorted sediments characterized low energy environment.

Optimizing Rotation Forest-Based Decision Tree Algorithms for Groundwater Potential Mapping

Groundwater potential mapping is an important prerequisite for evaluating the exploitation, utilization, and recharge of groundwater. The study uses BFT (best-first decision tree classifier), CART (classification and regression tree), FT (functional trees), EBF (evidential belief function) benchmark models, and RF-BFTree, RF-CART, and RF-FT ensemble models to map the groundwater potential of Wuqi County, China. Firstly, select sixteen groundwater spring-related variables, such as altitude, plan curvature, profile curvature, curvature, slope angle, slope aspect, stream power index, topographic wetness index, stream sediment transport index, normalized difference vegetation index, land use, soil, lithology, distance to roads, distance to rivers, and rainfall, and make a correlation analysis of these sixteen groundwater spring-related variables. Secondly, optimize the parameters of the seven models and select the optimal parameters for groundwater modeling in Wuqi County. The predictive performance of each model was evaluated by estimating the area under the receiver operating characteristic (ROC) curve (AUC) and statistical index (accuracy, sensitivity, and specificity). The results show that the seven models have good predictive capabilities, and the ensemble model has a larger AUC value. Among them, the RF-BFT model has the highest success rate (AUC = 0.911), followed by RF-FT (0.898), RF-CART (0.894), FT (0.852), EBF (0.824), CART (0.801), and BFtree (0.784), respectively. Groundwater potential maps of these 7 models were obtained, and four different classification methods (geometric interval, natural breaks, quantile, and equal interval) were used to reclassify the obtained GPM into 5 categories: very low (VLC), low (LC), moderate (MC), high (HC), and very high (VHC). The results show that the natural breaks method has the best classification performance, and the RF-BFT model is the most reliable. The study highlights that the proposed ensemble model has more efficient and accurate performance for groundwater potential mapping.

Analysis of Toxic Metal-Induced Ecological Risk in Kepez Stream, Çanakkale, Türkiye

Ecological risk in the mouth of Kepez Stream has recently increased notably due to waste from the Kepez settlement, agricultural activity in the Kepez delta, maritime traffic in the Çanakkale Strait, and summer houses in the coastal area. This study analyzed the ecological risk of 10 sediment samples along the bed in the mouth of Kepez Stream to shed light on anthropogenically induced pollution. The pollution proxies such as chlorophyll degradation products, heavy metal concentrations and organic carbon of the sediment samples were determined. Enrichment Factor (EF), Contamination Factor (CF), Geoaccumulation Index (Igeo) and Potential Ecological Risk Index (PER) were calculated from the results obtained. Spearman's correlation analysis and factor analysis were also performed. The obtained data show that there is moderate enrichment of Zn, As and Co, a significant level of Pb, and very high level of Cr in the sediments of Kepez Stream. Ni enrichment was determined to be excessive and poses a high potential ecological risk. Cleaning and rehabilitation need to be carried out urgently in the mouth of Kepez Stream. It should be determined whether metals are being transmitted to aquatic organisms, and measures should be taken to reduce the sources of pollution.

Solid–Water Partitioning and Speciation of Trace Metal Micronutrients in Wetland Soils and Stream Sediments

Solid–Water Partitioning and Speciation of Trace Metal Micronutrients in Wetland Soils and Stream Sediments

Identifying geochemical anomalies using a new method of Yang Chizhong-spatial scan statistic

Identifying anomalies from geochemical data by modeling of the background and statistical evaluation of anomalies is a major concern in geochemical exploration. This study developed a novel method (namely YangScan) for extracting geochemical anomalies by using Yang Chizhong filtering and a spatial scan statistic. The Yang Chizhong filtering, a progressive filtering method on the principle of weighted moving mean of binomial coefficient, was used to construct the background whose concavity and convexity are consistent with the original data. After removing the background from the original data, a spatial scan statistic based on multidirectional optimization was developed to identify arbitrary shaped and statistically significant anomalies from the residuals. YangScan was tested on both simulated datasets and a stream sediment geochemical dataset collected in the Northwestern Jiaodong Peninsula, Eastern China. The experimental results evaluated by geology consistency, recall, and weights of evidence contrast show that YangScan outperforms the two comparision methods (i.e., the trend surface analysis method and k-nearest neighbor anomaly detector) in identifying weak and irregularly-shaped geochemical anomalies. The distribution of geochemical anomalies linked to Au mineralization identified by YangScan is highly correlated with the trending of known Au deposits and ore-controlling structures. Therefore, YangScan is a powerful tool for identifying geochemical anomalies and can provide a useful reference for mineral exploration.

Seasonal dynamics of sediment organic carbon storage for the upper streams of the Yangtze River

IntroductionForest streams reserve more than 90% of the organic carbon (OC) in sediments, thus playing crucial roles in the global carbon cycle. Although forest streams are widely distributed across various forest regions, seasonal dynamics of OC in forest sediments have not been fully investigated.MethodsHere, we sampled soils (0–5 cm) in 15 representative forest stream sediments for 5 critical periods (snowmelt season, early growing season, growing season, late growing season, and seasonal snow cover season) during a one-year investigation in a geologically fragile subalpine coniferous forest catchment in the upper reaches of the Yangtze River in Sichuan province and the OC concentrations were measured by potassium dichromate external heating method.ResultsThe OC concentration of stream sediments ranged from 6.39 to 458.93 g kg−1, and the average was 84.56 g kg−1 for 15 streams in 5 critical periods during a 1-year investigation. Correspondingly, their stocks ranged from 2.05 to 310.56 kg m−2, and the average was 46.03 kg m−2. The maximum and minimum OC stocks were consistently observed during the late growing season and the snowmelt season, respectively. Otherwise, the OC stocks ranged from 1.31 to 218.05, 1.29 to 182.64, and 0.99 to 190.38 kg m−2 for the upstream, midstream, and downstream sediments, and the average was 39.36, 36.58, and 37.93 kg m−2, respectively. The average ratios of the OC stocks of the upstream and downstream ranged from 0.10–6.31, with an average of 1.43, during 5 critical periods, which indicated that the forest stream sediments may play crucial roles as carbon sources.DiscussionFurthermore, based on regression analysis, we found that the seasonal dynamics of OC concentrations and stocks were mainly regulated by precipitation, temperature, sediment depth, and litter carbon input to the streams together. These findings demonstrate that forest stream sediments may play crucial roles in the carbon biogeochemical cycle of subalpine forests and adjoining streams.