Spatial Variation Of Heavy Metals Research Articles

Sedimentary contamination study in the Great Chao Phraya River watershed, Thailand, using geographically weighted regression

ABSTRACT This research investigated the spatial variations of heavy metals and nutrients in the sediment of the Great Chao Phraya River network of Thailand using geographically weighted regression (GWR). The performance of GWR in explaining the spatiality of selected contaminants using single and multiple predictors was compared and discussed, and a suitable approach was recommended for sediment study. Extensive explanatory variables, including land use type and topographic, socio-economic, and meteorological indicators were utilized in the geospatial regressions of river sediment contaminants at the sub-catchment scale. In the case of simple regression, GWR outperformed the ordinary least square (OLS) regressions with global R 2 (range 0.34–0.72 for GWR and 0–0.24 for OLS, respectively), over 2-fold of which was derived by OLS. Similar observations were obtained in multiple regressions, where GWR offered global R 2 values between 0.27 and 0.6, higher than those that were provided by OLS (i.e. 0.12–0.44). Furthermore, multiple GWR model presented higher local explanatory power and performance with significantly increased local R 2 (up to 51%) compared with simple GWRs (p ≤ 0.05). It is recommended to combine the applications of simple and multiple GWR models to understand the effects of selected explanatory predictors on sediment contaminations from different perspectives.

Surface water-groundwater interactions drive the spatial variability of dissolved heavy metals and interfacial fluxes in mangrove intertidal zones

The intertidal aquifer is a crucial area that significantly influences the transport of heavy metals and the health of coastal environment. In this study, we used a 3-dimensional sampling method to analyze the spatial variability of heavy metals in the groundwater of the mangrove intertidal zone in China. The pollution level of heavy metals and their release processes into coastal waters through groundwater discharge were also explored. Our findings revealed high spatial heterogeneity of heavy metals occurred along the cross-shore, parallel-shore, and depth directions. Specifically, heavy metals exhibited inconsistent variation trends between the seawater infiltrated zone and groundwater discharge zone along the cross-shore direction. Fe, Cr, Cu, Zn, and Pb exhibited a similar variation trend along the cross-shore direction, but were opposite to that of Hg and As. In addition, most heavy metals showed higher concentrations in mangrove groundwater compared to inland pond water and coastal seawater, indicating that mangrove intertidal zone played a crucial role in sequestering heavy metals. The spatial variability of heavy metals can be attributed to different exchange types and magnitudes between the surface water and groundwater, as well as the complex biogeochemical reactions. Our study also identified a slight pollution level of Zn and Hg, and high groundwater discharge-derived fluxes of Hg and As compared with other study sites in the world. In addition, this study highlights the importance of considering different groundwater end-member, especially for redox sensitive heavy metals, when determining groundwater discharge-derived fluxes into the surface water in mangrove intertidal zone.

Spatial variability of heavy metals in soils and vegetation and associated risk to grazing animals in the abandoned gold mine in Francistown, Botswana

ABSTRACT The environmental impact of the abandoned Monarch Gold Mine in Botswana was analysed based on the concentrations of As, Mn, Cu, Cr and Zr in tailings and its vicinity, and the plants growing in the area. Results showed that the soil in the tailings dam (TD) and in the vicinity of the tailings dam (VTD), and the river sediments (RS) were severely contaminated with pollution load index (PLI) ranging from 1.89 to 2.86 in decreasing magnitude from TD>VTD> RS. The main contaminant is As but Cu, Cr and Zr are all also slightly above the critical values for soil. The TD has fewer plant species than VTD and accumulated elevated levels of these heavy metals (HM). The livestock grazing on these plants also consume the soil which could result to HM bioaccumulation. Therefore, proper management of the site is recommended to prevent the spread of pollutants and exposure to HM by animals and humans.

Sources and spatial variations of heavy metals in offshore sediments of the western Pearl River Estuary

The concentrations of six heavy metals (Cd, Cr, Cu, Pb, Zn, and As) in offshore surface sediments of western Pearl River Estuary were analyzed to investigate their sources and spatial variations using factorial kriging analysis. Three-scale spatial variations in heavy metal concentrations were identified and separated: nugget, local, and regional scale, which indicated sample errors, anthropogenic pollution and natural variation, respectively. Anthropogenic heavy metals varied sharply and heterogeneous at range of 60 km. Maoming Port, Hailing Bay and coastal area northeastern Hainan Island were potential polluted areas of Cd, Cr, Cu, Pb, Zn and As, also the Nandu River, Baoling River and Wanquan River estuaries were potential polluted areas of As. These polluted areas ranged up to 60 km in size and tended to extend with currents. The natural heavy metals varied continuously and relatively homogeneous at range of 180 km, which was dominated by riverine input and paleo-sea-level changes.

Spatial variation of heavy metals and their ecological risk and health risks to local residents in a typical e-waste dismantling area of southeastern China.

There is an increasing concern that soils in e-waste recycling regions are severely contaminated by unregulated e-waste dismantling activities. Hence, it is urgent to reveal the spatial variation of hazardous elements in arable lands close to e-waste stacking and dismantling areas and their potential risks to human beings. We collected 349 topsoil samples based on an intensive grid of 100m × 100m in southeastern China. The average concentrations of heavy metals were 1.25 (Cd), 35.44 (Ni), 77.68 (Cr), 77.38 (Pb), 122.14 (Cu), 203.39 (Zn), 0.21 (Hg), and 4.74 (As) mg kg-1, respectively. Compared to the risk screening values of hazardous elements in Chinese agricultural land, Cd and Cu were severely accumulated in the soils. The results of ecological risk analysis revealed that Cd posed the crucial risk among the studied elements. However, the levels of non-carcinogenic and carcinogenic risk were still within the acceptable quantity for adults. Spatial distribution by kriging interpolation displayed that the heavy metals were mainly distributed close to e-waste dismantling sites.

Using multispectral variables to estimate heavy metals content in agricultural soils: A case of suburban area in Tianjin, China

Efficient estimation and mapping of soil heavy metal concentrations based on rapid and environmentally friendly multispectral data can provide a reference for the prevention and control of non-point source pollution and safety in ecosystems. In this study, the spatial variation of soil heavy metals (As, Cd, Cr, Cu, Ni, and Zn) in Wuqing was analyzed with 394 and 57 soil samples gathered in 2005 and 2019. Based on these samples, as well as multispectral variables (raw bands and their respective vegetation index and derivative transformation), random forest-ordinary kriging (RFOK) and artificial neural network-ordinary kriging (ANNOK) were combined to predict spatial variations of heavy metal content. Results indicated that the mean values of soil As, Cd, Cr, Cu, and Zn in 2019 exceeded their respective concentrations in 2005 by 1.40, 1.36, 1.12, 1.12, and 1.35 times, and exceeded the standard rate of background values (BGV) in 2019 for all soil heavy metals (except for Ni). Compared to RF, ANN, and RFOK, the ANNOK method exhibited the best estimation performance for As (R20052= 69.47% andR20192= 65.03%), Cd (R20052= 64.48% andR20192= 64.20%), Cr (R20052= 72.02% andR20192= 70.65%), Cu (R20052= 72.05% andR20192= 70.53%), Ni (R20052= 69.37% andR20192= 66.03%), and Zn (R20052= 71.16% andR20192= 67.11%) in the validation dataset. Mapping of heavy metals derived from ANNOK revealed a similar distribution in 2005 and 2019, where the high concentrations of all soil heavy metals were in the southern part of the study area. The effects of multispectral bands as indicated by vegetation index and derivative transformation exhibited sensitivity for predicting soil heavy metals based on hybrid geostatistical methods. Overall, greater efficiency of spatial estimation for the content of soil heavy metals is important for the prevention and control of non-point source pollution.

Identification of the sources and influencing factors of the spatial variation of heavy metals in surface sediments along the northern Jiangsu coast

Determining the sources and factors influencing the spatial variation of heavy metals in the surface sediments of tidal flats is important for controlling and reducing heavy metal pollution. We used principal component analysis and partial least square regression to analyse the distribution characteristics, sources, and factors influencing the spatial variation of nine heavy metals (As, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn) in the surface sediments of tidal flats along four sites located on the northern Jiangsu coast. Our results indicate that the northern three sampling areas had a high heavy metal content, whereas the southern sampling area had a low heavy metal content. The heavy metals Mn and Pb are related to both natural and anthropogenic sources, whereas V and Cr are primarily derivatives of human activities, and As, Co, Cu, Ni, and Zn are primarily a result of natural processes. The spatial variation of Mn and Pb was primarily affected by the total inorganic carbon and clay content (positive affect) as well as the sand and silt content (negative affect). The spatial variation of V and Cr was primarily related to silt, clay, and total phosphorus content (positive influence) as well as sand (negative influence). In addition, the spatial variation of As, Co, Cu, Ni, and Zn was primarily influenced by the total organic carbon and clay content (positive effect) as well as sand and pH (negative effect). The grain size of sediments plays an important role in the spatial variation of heavy metals in the surface sediments of tidal flats, with fine-grained clay materials being related to the enrichment of heavy metals. The results of our study are important for the control and reduction of heavy metal pollution in coastal sediments, protecting both the ecological environment and human health.

Spatial variability of heavy metals in the coastal area of Monastir and origin of pollution

Spatial variability of heavy metals in the coastal area of Monastir and origin of pollution

Assessment of Spatial Variability of Heavy Metals (Pb and Al) in Alluvial Soil around Delta State University of Science and Technology, Ozoro, Southern Nigeria

Soil heavy metals pollution is a major global threat, because of its impact to plants, animals, and the soil geotechnical properties. Geostatistical method was used to investigate the spatial distributions of aluminum and lead within a section of the Delta State University of Science and Technology, Ozoro, Nigeria. A total area of 1 km2 (100 hectares) was covered within the school environment. Twenty -five (25) topsoil samples were collected, at the end of the dry season (March 2021); when the water table in the study area was very low. The lead and aluminum concentrations of the 25 samples were measured by using the Association of Official Analytical Chemists (AOAC) approved methods. Using a geostatistical tool, the lead and aluminum concentrations and distribution in the soil were plotted on predication maps. The maps revealed irregular spatial distributions of lead and aluminum ions within the study area. The lead concentration was highest at the North-central region of the study area; while lead concentration was lowest at the Eastern region of the study area. In terms of the aluminum metal, the highest aluminum concentration was observed in the North eastern region; while aluminum concentration was lowest at the South western region. Data obtained from this study will be useful for agricultural and civil engineering purposes, mainly in the area of decision-making.

The spatial-temporal evolution of heavy metal accumulation in the offshore sediments along the Shandong Peninsula over the last 100 years: Anthropogenic and natural impacts

The anthropogenic and natural impacts on the temporal and spatial variations of heavy metals in sediments under the Shandong Peninsula coastal current are still unclear. Here, the concentrations\\burial fluxes of Cr, Cu, Zn, As, and Pb in three sediment cores retrieved from the Bohai Sea and the Yellow Sea along the Shandong Peninsula were analyzed to study the spatial-temporal variability of heavy metal accumulation over the last century. The results showed that the buried heavy metal fluxes were relatively low at the end of the Shandong Peninsula coastal current. The enrichment factor (EF) and geoaccumulation index (Igeo) indicated that those metals did not severely pollute the sediments except As that reached a moderate enrichment. Principal component analysis (PCA) revealed that Cr, Cu, Zn, and Pb were mainly derived from natural weathering and As was determined by anthropogenic contamination. The strength of the Shandong Peninsula coastal current, the Yellow River estuary location, and sediment discharge load significantly influenced the concentrations of natural-origin heavy metals by affecting sediment grain size and the source-sink process. The emission of pollutants from agricultural and industrial activities in the Shandong Peninsula region resulted in As enrichment since the 1950s. Moreover, the EF values of heavy metals in sediment cores from China's coastal seas showed apparent spatial variations of heavy metal pollution but had coherent temporal variability with China's economic development process. Heavy metals pollution has weakened in most coastal seas since the 2000s, likely due to the extensive industrial upgrading and the implementation of pollution control. These results have a reference significance for studying the evolution and source-sink process of the heavy metals in offshore sediments and tracing anthropogenic impacts in different periods.

Spatial variation and source identification of heavy metals in sediments in Shaanxi section of Weihe River, Northwest China.

In order to understand the spatial variation of heavy metals in Shaanxi section of Weihe River, the contents and sources of Cd, Co, Cu, Pb, Sb, As, Ni, Cr, Zn, Mn in sediments at 17 sampling sites in Shaanxi section of Weihe River and its tributaries were analyzed. The results showed that the average contents of Cd, Co, Cu, Pb, Sb, As, Ni, Cr, Zn, Mn were 0.10, 1.24, 11.73, 11.95, 24.90, 24.91, 29.31, 54.18, 72.74, 626.85 mg·kg-1, respectively. Except for that of Cd being greater than 1, the coefficient of variation for each of other heavy metals was less than 0.5. The peak contents of Cd, Pb and Cr were found at the sampling site of Bahe River, of Co and Mn at Heihe River, of Cu and Zn at Qingjiang River, and of Sb, As and Ni at Shawang Ferry, Xianyang Railway Bridge and Linjia Village, respectively. According to the results of correlation analysis, principal component analysis and cluster analysis, the elements of Cd, Co, Cu, Pb, Ni, Cr, Zn and Mn mainly originated from industrial and domestic sources, but Sb and As mainly originated from agricultural and geochemical sources.

Temporal and spatial variability of heavy metals in bottom sediments and the aquatic macrophyte Paspalum repens of the Orinoco River floodplain lagoons impacted by industrial activities.

This study investigated the water parameters and the levels of several heavy metals in leaves and roots of the aquatic macrophyte Paspalum repens and in bed sediments of one unpolluted lagoon and two polluted lagoons of the Orinoco River floodplain to know the impact of the alumina refining wastes on these ecosystems. The sampling was performed during four hydrological periods, covering one hydrological year. Chemical parameters in water (pH, conductivity, and total dissolved solids) and the levels of Al, Pb, Cr, and Cu in sediments were the highest in Macanillal (LMaca) lagoon, whereas sediments of Punta Cuchillo (LPC) lagoon also had elevated concentrations of Al and Fe in comparison with Las Aruhacas (LArh) lagoon (unpolluted lagoon). Chemical parameters in waters returned almost to natural values during high water stage because of the huge inundation of the Orinoco River during the high discharge periods. The solid/liquid discharges of industrial effluents over these systems also affected the grain size distribution of sediments in the lagoons. In all the studied lagoons, the distribution of elements in leaves of P. repens was in the order K ≥ Cr > Ca > Mg > Al > Fe > Mn > Cu > Pb, whereas Al was found to be the more abundant element in roots. The high abundance of Cr in P. repens was related with the high Cr accumulation potential shown by aquatic macrophytes. Despite this, the concentration of elements in P. repens did not show differences between the plants collected in the polluted lagoons versus the plants collected in the unpolluted lagoon. This suggests that P. repens is unsuitable for bio-monitoring studies of heavy metals in these aquatic environments impacted by alkaline residues.

Spatial Variability of Heavy Metals in Native Oysters From an Anthropogenically Impacted Estuary in Northeastern Brazil

This brief research compares the bioconcentration of heavy metals (Cd, Cr, Cu, Pb, Ni, and Zn) in the soft tissues of native oysters Crassostrea rhizophorae (Guilding, 1828) from two areas in the Potengi estuary, northeastern coast of Brazil. The purpose was to test the hypotheses of relevant differences in bioaccumulation while the environmental conditions change upstream. The downstream station showed higher concentrations for cadmium and nickel, while the upstream one, revealed increased values for body weight, condition index, chromium, lead, and zinc (p < 0.05). The cooper variation between sites was negligible, but, as for zinc and chromium, the metal content observed was above guidance levels. Results revealed two aspects that were mainly influencing the bioavailability and bioaccumulation of metals in oysters. Firstly, the predominance of marine or riverine characteristics of each site, and secondly, the relative proximity to the point of introduction of the pollutant, even though stations were not quite far apart. Crassostrea rhizophorae accumulated heavy metals in significant concentrations, endorsing its efficiency as a biomonitor.

Biomagnetic monitoring of atmospheric heavy metal pollution using pine needles: the case study of Isfahan, Iran.

Atmospheric deposition particles are fine-sized having a high adsorption capacity. Therefore, they can easily transfer the contamination to other areas. Plants can absorb certain pollutants using their leaves and then accumulate them in their biomass. In this study, the spatial and temporal variability of air pollution was assessed using pine needles as the bioindicators of atmospheric pollution. The magnetic susceptibility (MS) at low and high frequencies (χlf, χhf) and the concentration of selected heavy metals of pine needles (Pinus mugo) were estimated in order to address the possible relationships between needles' MS and the heavy metal concentration in the city of Isfahan, central Iran. In addition, the relationship between the heavy metal concentration of pine needles and that of the atmospheric dust was examined using the published data. Tree pine needles were monthly sampled, from April to December 2015 (T1-T9), during 9 months, from 30 different sites in the Isfahan city. There were two treatments including washed + unwashed (WU) and washed + washed (WW). The heavy metal total concentrations including Zn, Fe, Cu, Co, Pb, and Ni were measured. The mean concentrations of Fe, Zn, Pb, Cu, Ni, and Co were 80.4, 3.9, 1.8, 1.4, 0.6, and 0.3 mg kg-1, respectively. The results revealed that the concentration of heavy metals and MS in the pine needles followed the order Fe > Zn > Pb > Cu > Ni > Co. Also, the heavy metal concentration in the pine needles with different treatments had the following trend: WU > WW. It was shown that there was a significant correlation (p < 0.01) between the heavy metal concentrations and the leaf MS values of the pine needles and the concentration of heavy metals in atmospheric dust. Besides, similar trends were detected for the spatial variability of heavy metals and the pine needles' MS. In general, it could be concluded that the biomagnetic approach could serve as a comparatively fast and low-cost method to detect highly polluted urban areas with selected heavy metals, particularly the areas which are under the influence of anthropogenic and other traffic-related sources.

Identifying the influencing factors controlling the spatial variation of heavy metals in suburban soil using spatial regression models

Determining the factors that control the spatial variation of heavy metals in suburban soil is important in identifying and preventing pollution sources. Soil intrinsic factors combined with environmental variables can effectively explain the spatial distribution of heavy metals. Compared with classical statistical methods, such as multiple linear regression (MLR) models, spatial regression models that can cope with the spatial dependence of heavy metals have greater potential in establishing an accurate relationship between influencing factors and heavy metals. This study aims to identify the factors that influence the spatial variation of lead (Pb) and cadmium (Cd) in 138 topsoil samples from the suburbs of Wuhan City, China, by using spatial regression models with MLR as the reference. Moran's I values reveal the spatial autocorrelation of Pb and Cd. The spatial lag model (SLM) outperforms MLR and has higher R2 and lower spatial dependence of residuals. The significant coefficients of the spatial lag term in SLMs indicate that the spatial variation of Pb and Cd depends on their surrounding observations. SLM results show that Pb content depends on the distance from the nearest industrial enterprises and suggest that industrial pollution is the main source of Pb. Cd content depends on pH, soil organic matter, and the topographic wetness index, indicating that intrinsic and topographical factors contribute to the spatial variation of Cd. Parent materials and application of phosphorus fertilizer are the most likely sources of Cd. The findings highlight the spatial autocorrelation of heavy metals and the effects of intrinsic factors and environmental variables on the spatial variation of such metals. Moreover, this study reveals the effectiveness of spatial regression models in identifying the influencing factors of heavy metals.

Seasonal and spatial variations of heavy metals in water and sediments from mainland and maritime areas of Ebrie lagoon (Côte d’Ivoire, Western Africa)

This study has been conducted to assessment the contamination level of the water and sediment by heavy metals of the both mainland and maritime areas in western part of Ebrie lagoon. Water and sediments samples were collected in eleven stations in mainland and maritime areas from February 2014 to January 2015. Water quality parameters such as temperature, pH, conductivity, transparency, salinity and dissolved oxygen were measured in situ and suspended matter in a laboratory. The concentration levels of mercury (Hg), lead (Pb), Cadmium (Cd) and Arsenic (As) in water and sediments were determined using Atomic Absorption Spectrophotometer. The results showed that seasonal mean values of heavy metals varied slightly during the dry, rainy and swelling seasons in both the maritime and mainland areas. The highest average values of heavy metals were recorded in the mainland area. Seasonal concentration levels of mercury and cadmium in the both maritime and mainland areas were above the safe limit for human consumption. The Pearson correlation between heavy metals and physico-chemical parameters showed a relationship between these parameters. The contamination factor (CF) in mainland and maritime areas showed that the sediments were moderately contaminated for Hg, Pb, and Cd and As during all seasons, except Cd in maritime area. Maritime sediment is low contamination for Cd. The PLI value (PLI˃1) indicates polluted sediment from mainland and maritime areas. However, generally, the mainland area is more polluted.© 2019 International Formulae Group. All rights reserved.Keywords: Physico-chemical parameters, exchange factor, contamination factor, pollution load index

Assessment of seasonal and spatial variations of heavy metals in the muscles of Oreochromis niloticus and Clarias gariepinus at Sharkia province, Egypt: Biochemistry and Histology Evaluation

The most significant pollutants are the heavy metals in the aquatic network due to their toxicity, accumulation, and bio-magnification. In an attempt to characterize the physical-chemical and demonstrate the potential water impact of the heavy metal content of wastes in two lakes in Sharkia province, Egypt, this study was developed to determine their toxicity and the potential waste impacts in biochemistry and histology of fish muscle. Samples of water and fish muscles were collected and analyzed for heavy metals using atomic absorption of two different fish species (Oreochromis niloticus and Clarias gariepinus) along two canals in Sharkia province in Egypt during the four seasons in 2018. The water samples were also analyzed for the physicochemical parameters. The impact of heavy metal on the enzymatic antioxidant (superoxide dismutase and catalase) as well as the reduced glutathione content, besides the oxidative stress marker presented by lipid peroxidation levels in fish muscles, were evaluated. Results showed the largest amount of chloride (Cl-) and iron (Fe) in the Sharkia water sample, while Faquas water sample had the highest level of HCO3 and iron (Fe). The manganese concentration in the fish muscle was the highest in Sharkia water and the highest level of Fe was detected in the fish muscles collected from Faquas area. These high levels of some of the physicochemical parameters and heavy metals in the two lakes with two different wastes as seen in this study may be a source of water pollution. The highest accumulation of metals in the muscle of the two fish species, suggesting risk for human consumption. There were seasonal variations in the level of LPO in muscle tissue of two types of fishes with a reverse relationship with antioxidant parameters. This accumulation varied seasonal and spatial as well as according to the species of fish. Increasing the level of heavy metals effect on the biochemistry and histology of fish. Keywords: Heavy metals; Muscle; Oxidative/Antioxidant, Histology, Clarias gariepinus; Oreochromis niloticus

Distribution and transport of heavy metals in surface sediments of the Zhejiang nearshore area, East China Sea: Sedimentary environmental effects

Surface sediment and vibrocore samples were collected in the Zhejiang nearshore area to study the distribution and transportation of heavy metals on the basis of grain size, elements, and 210Pb dating analyses. The results indicated that the spatial patterns of heavy metal (Zn, Cr, Pb, Ni, Cu, and Co) were closely related to the sediment types. Heavy metal concentrations in the clayey silt were the highest, the second for silt and the least for fine sand. Moreover, Heavy metal concentrations were positively correlated with the mean diameter of sediment, silt, and clay contents. And there were conspicuous positive correlations between Al2O3 and heavy metal, suggesting that terrigenous sediment from the Yangtze River was a dominating factor controlling the spatial variations of heavy metals. Sedimentary environment, including hydrodynamics, sediment transport, and sedimentary rates, would dominate the distribution and transport of heavy metal pollutants through controlling the transport pathway of surface sediment.

Spatial variation of heavy metals and uptake potential by Typha domingensis in a tropical reservoir in the midlands region, Zimbabwe.

Pollution of aquatic ecosystems with heavy metals is now of global concern due to their dangers to human health and persistence in the environment. An investigation on the spatial distribution of heavy metals in water and sediments and the bioaccumulation potential of heavy metals by plant parts (i.e. roots, stems and leaves) of aquatic macrophyte Typha domingensis (Pers.) Steud in a tropical reservoir was carried out. The results showed no difference in spatial distribution of heavy metals (Fe, Cu, Cd, Cr, Pb, Zn, Mn) in water and sediments from the riverine to the dam wall. The concentration of heavy metals Fe, Cu, Cr and Zn in T. domingensis was of the order root > stem > leaves, but for Pb, Cd and Mn, it followed the order root > leaf > stem. The metal transfer between roots and shoots of T. domingensis followed the order Zn > Pb > Fe > Cu > Cd > Cr. The bio-concentration factor (BCF) was low (BCF < 1) for all the selected metals while the transfer factor (TF) varied among metals suggesting that T. domingensis is not an accumulator of the studied metals. The high concentration of heavy metals found in the water (0.7-16.14mgL-1) and sediments (43.6-569.18mgkg-1) present a potential risk to both ecological health and human health for the population living in the area. The results of metal concentration in water and sediments from this study are important as a baseline for future monitoring studies. Further studies on bioavailability of metals to other macrophytes and aquatic organisms are recommended.

Seasonal and spatial contamination statuses and ecological risk of sediment cores highly contaminated by heavy metals and metalloids in the Xiangjiang River.

To reveal seasonal and spatial variations of heavy metals and metalloids (HMMs) in sediment of the Xiangjiang River, a total of 24 water and 649 sediment samples were collected from six sampling stations in the Songbai section of the river which had been polluted by HMMs for 100years. Their contamination statuses and ecological risk were determined by enrichment factor (EF), geo-accumulation index (Igeo), pollution load index (PLI), and mean probable effect concentration quotients (mPECQs) analyses. The results revealed a unique seasonal distribution of metals in the sampling stations: The highest concentrations were revealed in the dry seasons (autumn and winter) and the lowest during the wet seasons (spring and summer). It exhibited a greater seasonal variation in the estuary sediment cores (sites ME and MW) than in the cores of other sites. Moreover, the highest concentrations of the tested metals were also found in the estuary sediment cores in the dry seasons (autumn and winter). The highest vertical concentrations of Pb, Zn, Cu, Ni, As, Fe, and Mn were observed at the depths of 16-36cm in all of the sampled sediment cores. The EF, Igeo, PLI, and mPECQs values of all samples in autumn were higher than in summer. Cd posed the highest ecological risk in all seasons, although its concentrations were lower compared to other studied elements. Our results will benefit to develop feasible sediment quality guidelines for government monitor and remediate the local sediments in the Xiangjiang River.