Spatial Distribution Of As Research Articles

Bayesian multivariate receptor model and convolutional neural network to identify quantitative sources and spatial distributions of potentially toxic elements in soils: A case study in Qingzhou City, China

Determining sources and spatial distributions of potentially toxic elements (PTEs) is a crucial issue of soil pollution survey. However, uncertainty estimation for source contributions remains lack, and accurate spatial prediction is still challenging. Robust Bayesian multivariate receptor model (RBMRM) was applied to the soil dataset of Qingzhou City (8 PTEs in 429 samples), to calculate source contributions with uncertainties. Multi-task convolutional neural network (MTCNN) was proposed to predict spatial distributions of soil PTEs. RBMRM afforded three sources, consistent with US-EPA positive matrix factorization. Natural source dominated As, Cr, Cu, and Ni contents (78.5 %∼86.1 %), and contributed 37.1 %, 61.0 %, and 65.9 % of Cd, Pb, and Zn, exhibiting low uncertainties with uncertainty index (UI) < 26.7 %. Industrial, traffic, and agricultural sources had significant influences on Cd, Pb, and Zn (30.2 %∼61.9 %), with UI < 39.3 %. Hg originated dominantly from atmosphere deposition (99.1 %), with relatively high uncertainties (UI=87.7 %). MTCNN acquired satisfactory accuracies, with R2 of 0.357–0.896 and nRMSE of 0.092–0.366. Spatial distributions of As, Cd, Cr, Cu, Ni, Pb, and Zn were influenced by parent materials. Cd, Hg, Pb, and Zn showed significant hotspot in urban area. This work conducted a new approach exploration, and practical implications for soil pollution regulation were proposed.

Quantitative analysis of the contribution of sources, diffusion pathways, and receptor attributes for the spatial distribution of soil heavy metals and their nested structure analysis in China

Investigation of heavy metal pollution degree, pollution sources, and spatial distribution structure is crucial for the country's soil pollution prevention, but relevant research is lacking. In this study, As, Cd, Cr, Cu, Pb and Zn in the national scope are taken as research objects. Among them, Cd has the highest pollution level. Four sources were quantitatively allocated as soil type, mining and dressing industry, GDP, and NDVI, which accounted for 92.93, 97.81, 99.30 and 96.24 % of Cr, Cd, Zn and As contamination, respectively. In addition, according to the geographical detector, the spatial distribution of As was affected by three diffusion pathways, whose influence degree were 0.822–0.947, especially the slope. Cadmium was primarily affected by both receptor attributes and diffusion pathways, with an influence degree of 0.010–0.175, especially soil water content and slope; Cr and Pb were affected by receptor attributes, with an influence degree of 0.886–0.986 and 0.007–0.288, respectively, especially for soil water content and soil organic carbon; Cu and Zn were affected by receptor attributes, with an influence degree of 0.182–0.823 and 0.002–0.150, respectively, especially for soil texture. There are two spatial distribution structures with nested scales in east–west and north–south directions. The large spatial structure has a more significant impact on the spatial distribution of heavy metals, especially in the east–west direction. Overall, the mining and dressing industry is the main source in Hunan, Yunnan, and Liaoning, where many mines exist and mining activities are frequent. GDP was the main source in Shanghai and Zhejiang areas, where the economy is developed. NDVI was the main source in Guangdong and Anhui areas, where agriculture is relatively developed. These results provide a basis for determining remediation and prevention objectives in soil pollution remediation and prevention in the national scope.

Research on Risk Assessment and Contamination Monitoring of Potential Toxic Elements in Mining Soils.

Potentially toxic element (PTE) contamination in soils has serious impacts on ecosystems. However, there is no consensus in the field of assessment and monitoring of contaminated sites in China. In this paper, a risk assessment and pollution monitoring method for PTEs was proposed and applied to a mining site containing As, Cd, Sb, Pb, Hg, Ni, Cr, V, Zn, Tl, and Cu. The comprehensive scoring method and analytical hierarchical process were used to screen the priority PTEs for monitoring. The potential ecological risk index method was used to calculate the risk index of monitoring point. The spatial distribution characteristics were determined using semi-variance analysis. The spatial distribution of PTEs was predicted using ordinary kriging (OK) and radial basis function (RBF). The results showed that the spatial distribution of As, Pd, and Cd are mainly influenced by natural factors, while Sb and RI are influenced by both natural and human factors. OK has higher spatial prediction accuracy for Sb and Pb, and RBF has higher prediction accuracy for As, Cd, and RI. The areas with high ecological risk and above are mainly distributed on both sides of the creek and road. The optimized long-term monitoring sites can achieve the monitoring of multiple PTEs.

Spatial distribution and ecological risk assessment of heavy metals in alpine grasslands of the Zoige Basin, China

Heavy metals elements are not only related to the functions of ecosystems but also affect human health. To understand the characteristics of heavy metals in the topsoil of the Zoige alpine basin, a total of 252 grass and topsoil samples were collected in May and September 2014. The results showed that only Cd and Pb highly exceeded their background values (BV); in May and September, Cd was 2.02- and 1.55-fold higher than its BV, respectively, and Pb was 2.35- and 2.17-fold above its BV, respectively. The sources of Cd and Pb were homologous. In addition, the comprehensive potential ecological risk index was less than 150, indicating that heavy metal pollution in the study area is currently low. The spatial interpolation indicated that Cd and Pb pollution might be related to tourism and transportation, but the low biological absorption coefficient for all heavy metals showed that heavy metal absorption ability of forage was low and would not impact yak breeding. Finally, the soil was lightly contaminated by Cd and Pb due to the rapid development of the animal husbandry and tourism. The spatial variation of heavy metal in the basin is dominated by structural factors, and the random factors also have an effect on spatial distribution of As, Cd, Cu and Ni. The random factors such as overgrazing can exert an influence on physical structure and the circulation of nutrient substances of meadow soil through livestock grazing and trampling, ultimately affecting the content and distribution of soil heavy metals.

Analysis of driving factors of spatial distribution of heavy metals in soil of non-ferrous metal smelting sites: Screening the geodetector calculation results combined with correlation analysis

Heavy metals (HMs) discharged from smelting production may pose a major threat to human health and soil ecosystems. In this study, the spatial distribution characteristics of HMs in the soil of a non-ferrous metal smelting site were assessed. This study employed the geodetector (GD) by optimizing the classification condition and supplementing the correlation analysis (CA). The contribution of driving factors, such as production workshop distributions, hydrogeological conditions, and soil physicochemical properties, to the distribution of HMs in soil in the horizontal and vertical dimensions was assessed. The results showed that the main factors underlying the spatial distribution of As, Cd, Hg, Pb, Sb, and Zn in the horizontal direction were the distance from the sintering workshop (the maximum q value of that factor, q=0.28), raw material yard (q=0.14), and electrolyzer (q=0.29), while those in the vertical direction were the soil moisture content (q=0.17), formation lithology (q=0.12), and soil pH (q=0.06). The findings revealed that the CA is a simple and effective method to supplement the GD analysis underlying the spatial distribution characteristics of HMs at site scale. This study provides useful suggestions for environmental management to prevent HMs pollution and control HMs in the soil of non-ferrous metal smelting sites.

Influence of hydrostratigraphy on the distribution of groundwater arsenic in the transboundary Ganges River delta aquifer system, India and Bangladesh

Abstract The Ganges River delta complex contains a transboundary aquifer system shared between India and Bangladesh. Although it serves as the main freshwater source for the population inhabiting the delta, the aquifer system is severely contaminated with arsenic (As). This study aimed to determine the control of the delta hydrostratigraphy on the regional-scale depth distribution of As within the aquifer system. We developed the first high-resolution, regional-scale, transboundary hydrostratigraphic model of the Ganges River delta and analyzed the patterns of As distribution as a function of the hydrostratigraphy. Model results indicate that, despite the presence of a single aquifer system across the delta, the hydrostratigraphy is spatially variable and can be architecturally divided into three distinct aquifer subsystems from northwest to southeast: a single, thick continuous aquifer (type I); a vertically segregated, semi-confined aquifer subsystem (type II); and a multilayered, nearly confined aquifer subsystem (type III). Results indicate that the spatial distribution of As is characteristically different in each subsystem. In the type I aquifer, As concentrations tend to be homogeneous at all depths, while in type II and type III aquifers, As concentrations sharply decrease with depth. The intervening aquitards in the type II and type III aquifer subsystems appear to act as natural barriers to infiltration of surficial As or organic matter–rich water to the deeper aquifer zones. This delineation of the regional-scale hydrostratigraphic architecture and resulting understanding of its plausible controls on the depth-distribution of As within the delta should significantly aid in the systematic framing of sustainable management plans for the As-safe aquifers within the Ganges River delta aquifer system.

Regional-scale hydrogeochemical evolution across the arsenic-enriched transboundary aquifers of the Ganges River Delta system, India and Bangladesh

Arsenic (As) dynamics within the extensively contaminated aquifers of the Ganges River delta have been widely studied over the past few decades, but the hydrogeochemical signatures across the delta aquifers remain to be characterized. Here, we characterize the varied geochemical and isotopic (δ18O, δ2H) signatures of groundwater across the delta and interpret the hydrogeochemical evolution pathways and the driving processes on a regional-scale as a function of the delta hydrostratigraphy. Our hydrostratigraphic model identifies three major aquifer sub-systems across the delta from north-west to south-east: a single continuous unconfined aquifer (Type I); a semiconfined vertically-segregated aquifer sub-system (Type II); and a nearly confined multilayered aquifer sub-system (Type III). The Type I aquifer is dominated by Ca-Mg-HCO3-rich waters, while the aquifers to the south (Type II and Type III) exhibits increasing dominance of Na-Cl hydrogeochemical facies at shallow and intermediate depths and Na-HCO3 hydrogeochemical facies in the deep aquifers. The spatial distribution of As is also found to be heavily dictated by hydrostratigraphy, wherein the Type I aquifer sub-system yields similar concentrations across depths, while the Type II and Type III aquifer sub-systems exhibit a sharp increase in As-safe aquifers with depth. Although dominant reducing conditions occur within the delta groundwater, co-occurrence of redox-sensitive solutes from varying redox stability fields indicates to the development of overlapping redox zones. Stable isotopic signatures of groundwater exhibit a progressive depletion away from the Bay of Bengal. The Type I aquifer exhibits relatively homogenous hydrogeochemical signatures, possibly suggesting deeper infiltration of recharge under higher vertical hydraulic gradients, while the Type II and Type III aquifers exhibit variability across depth, which is possibly a reflection of horizontally stratified groundwater flows, dictated by the spatial geometry of the intervening aquitard layers.

Identification of spatial patterns and sources of heavy metals in greenhouse soils using geostatistical and positive matrix factorization (PMF) methods

AbstractGreenhouse vegetable products are important dietary sources. Heavy metals in greenhouse soils are associated with food safety and public health. Therefore, heavy metals in greenhouse soils are of significant concern. This study used positive matrix factorization (PMF) and geostatistical analyses to assess possible sources and spatial distribution patterns of heavy metals in 248 greenhouse soil samples obtained from southern Hebei Province, China. The results showed that the mean arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) concentrations in the greenhouse soil samples were 13.5, 0.16, 74.3, 31.4, 0.03, 26.0, 156, and 98.0 mg/kg, respectively. Approximately 97.18%, 32.26%, 25.81%, 22.98%, 8.06%, 6.45%, 2.02%, and 0.40% of sample sites were contaminated with Cd, Cu, Hg, Zn, Cr, As, Pb, and Ni, respectively. The PMF indicated that Cd and Pb was mainly influenced by metal smelting activity; Cu and Zn accumulation in greenhouse soils was mainly from manure and chemical fertilizer application, while Ni, Cr, and As were strongly derived from natural sources. The spatial distribution patterns varied among metals, with Ni and Pb mainly controlled by natural factors, whereas Cd, Cu, Cr, and Zn were moderately to strongly influenced by fertilizer application. However, Pb is also affected by atmospheric deposition caused by industrial emissions. The spatial distribution of As is controlled by both natural and anthropogenic factors.

An Integrated Approach for Source Apportionment and Health Risk Assessment of Heavy Metals in Subtropical Agricultural Soils, Eastern China

Unreasonable human activities may cause the accumulation of heavy metals (HMs) in the agricultural soil, which will ultimately threaten the quality of soil environment, the safety of agricultural products, and human health. Therefore, the accumulation characteristics, potential sources, and health risks of HMs in agricultural soils in China’s subtropical regions were investigated. The mean Hg, Cu, Zn, Pb, and Cd concentrations of agricultural soil in Jinhua City have exceeded the corresponding background values of Zhejiang Province, while the mean concentrations of determined 8 HMs were less than their corresponding risk-screening values for soil contamination of agricultural land in China. The spatial distribution of As, Cr, Ni, Cu, and Pb were generally distributed in large patches, and Hg, Zn, and Cd were generally sporadically distributed. A positive definite matrix factor analysis (PMF) model had better performance than an absolute principal component–multiple linear regression (APCS-MLR) model in the identification of major sources of soil HMs, as it revealed higher R2 value (0.81–0.99) and lower prediction error (−0.93–0.25%). The noncarcinogenic risks (HI) of the 8 HMs to adults and children were within the acceptable range, while the carcinogenic risk (RI) of children has exceeded the safety threshold, which needs to be addressed by relevant departments. The PMF based human health risk assessment model indicated that industrial sources contributed the highest risk to HI (32.92% and 30.47%) and RI (60.74% and 61.5%) for adults and children, followed by agricultural sources (21.34%, 29.31% and 32.94% 33.19%). Therefore, integrated environmental management should be implemented to control and reduce the accumulation of soil HMs from agricultural and industrial sources.

Distribution Characteristics and Seasonal Variations of Arsenic in Atmospheric Aerosols over the Yellow Sea and Bohai Sea

Marine aerosol samples of total suspended particulates (TSP) were collected in winter (2017) and spring and summer (2018) over the Yellow Sea and Bohai Sea. These samples were analyzed for total arsenic (As), As(Ⅴ) and As(Ⅲ), and water soluble ions to investigate the distribution and seasonal variation of As in atmospheric aerosols, as well as the dry deposition flux. Results showed that As concentrations in winter, spring, and summer were 6.6, 5.5, and 4.4 ng·m-3, respectively. The highest As concentrations occurred in the winter. Obvious differences in the spatial distribution of As were observed in different seasons. The highest concentrations of As were observed over the Bohai Sea in winter and the northern Yellow Sea in spring, with an average of 8.8 and 11.3 ng·m-3, respectively. As concentrations exhibited a relatively uniform spatial pattern in summer over the Yellow Sea and Bohai Sea, which may have been affected by the different sources of As. As(Ⅴ) was the main species of As, while As(Ⅴ)/As(Ⅲ) ratios were 0.41 in winter and 0.21 in summer, respectively. Average As/TSP ratios in the winter, spring, and autumn were 95.4, 83.9, and 81.4 μg·g-1, respectively. Obviously higher As/TSP ratios, indicating higher intensity, occurred in winter. Air masses carry pollutants released over the Bohai Rim Region by the winter monsoon, resulting in higher As concentrations in winter. In summer, As concentrations are also higher, because air masses bring pollutants to the southeast coastal economic zone via the northeast monsoon. In spring, most air masses arriving in this region originate from Siberia and the southeast ocean with high rate, resulting in lower As concentrations. The significant correlation between K+/TSP and As/TSP (r=0.78, P<0.05) in winter indicates that As is affected by the combustion of land biomass. No significant correlation in summer reveals the difference in As sources between winter and summer. The dry deposition flux of As over the Yellow Sea and Bohai Sea was 1.15 μg·(m2·d)-1 in winter, 0.77 μg·(m2·d)-1 in spring, and 0.97 μg·(m2·d)-1 in summer, with an annual mean value of 0.95 μg·(m2·d)-1.

Spatial distribution and health risk assessment of As and Pb contamination in the groundwater of Rayong Province, Thailand

This study investigates the presence of arsenic (As) and lead (Pb) in groundwater and their spatial distribution in Ban Khai District, Rayong Province, Thailand. Forty groundwater samples were collected at different locations in the dry and wet seasons during March and August of 2019, respectively. The hydrochemical facies illustrate that the major groundwater types in both seasons mainly consisted of Ca–Na–HCO3, Ca–HCO3–Cl and Na–HCO3 types. The concentration of As ranged from <0.300 to 183.00 μg/L, accounting for 22% (18 of 80 samples), exceeding the WHO guidelines of 10 μg/L. The spatial distribution of As was distinctly predominant as a hot spot in some areas during the wet season. The wells may have been contaminated from human activity and thus constituted a point source in the adjacent area. For Pb, its concentration in all the wells were not exceeded 10 μg/L of the WHO guidelines, appearing as a background concentration in this area. Most of the wells were shown to be in an oxidation state, supporting AsV mobility. Moreover, the area also had a nearly neutral pH that promoted AsV desorption, while the presence of undissolved Pb in the aquifers tended to increase. Furthermore, chemical applications to agricultural processes could release the As composition into the groundwater. The health risk resulting from oral consumption was at a higher risk level than dermal contact. The non-carcinogenic risk affecting the adult population exceeded the threshold level by approximately 27.5% of the wells, while for the children group, the risk level was within the limit. Total cancer risk (TCR) of adult residents exceeded the acceptable risk level (1 × 10−6) in all wells, causing carcinogenic health effects. Therefore, health surveillance is important in monitoring the toxic effects on the local residents who use groundwater from these contaminated wells. Furthermore, a sanitation service and an alternative treatment of the water supply will be needed, especially in wells with high As levels.

Spatial trace element bioaccumulation along with consumer risk simulations of Mediterranean mussels in coastal waters of Turkey.

Turkey borders three seas and the most populous locations are squeezed into the coastal territories. Thus, organisms living in these aquatic territories are under longstanding anthropogenic pressure. Hence, this study investigated the consumption outcomes leading to potential child and adult health risks along with the spatial distribution of As, Cd, Cr, Cu, Ni, Pb, V, and Zn in the Mediterranean mussels (Mytilus galloprovincialis) sampled at 23 different stations from the Black Sea, the Sea of Marmara, and the Aegean Sea coastal waters of Turkey. The mean concentrations of trace elements found in the Mediterranean mussels followed Zn (39.75 mg kg-1) > Cu (1.95 mg kg-1) > As (1.84 mg kg-1) > Pb (0.99 mg kg-1) > Ni (0.65 mg kg-1) > Cr (0.62 mg kg-1) > V (0.47 mg kg-1) > Cd (0.08 mg kg-1). Factor analysis revealed that trace elements were mostly derived from anthropogenic sources. Pb values were found to be above the permissible European Union limits at 10 sampling stations. While the estimated weekly intake did not exceed the Joint FAO/WHO Expert Committee on Food Additives limits, the target hazard quotient for As was found >1 for children. The lifetime cancer risk (CR) for adults and children was unacceptable (>10-4) at high consumption rates for As according to US Environmental Protection Agency. Monte Carlo simulation confirmed a CR to adult (62.98%) and children (97.24%) mussel consumers caused by As.

The key roles of Fe-bearing minerals on arsenic capture and speciation transformation during high-As bituminous coal combustion: Experimental and theoretical investigations

The conversion of As vapor released from coal combustion to less hazardous solids is an important process to alleviate As pollution especially for high-As coal burning, but the roles of key ash components are still in debate. Here, we used multiple analytical methods across the micro to bulk scale and density functional theory to provide quantitative information on As speciation in fly ash and clarify the roles of ash components on As retention. Fly ash samples derived from the high-As bituminous coal-fired power plants showed a chemical composition of typical Class F fly ash. In-situ electron probe microanalysis (EPMA) was for the first time used to quantify and distinguish the inter-particle As distribution difference within coal fly ash. The spatial distribution of As was consistent with Fe, O, and sometimes with Ca. Grain-scale distribution of As in coal fly ash was quantified and As concentrations in single ash particles followed the order of Fe-oxides > aluminosilicates > unburned carbon > quartz. Sequential extraction and Wagner chemical plot of As confirmed that Fe minerals rather than Al-/Ca-bearing minerals played a vital role in capturing and oxidizing As3+ into solid phase (As5+). Magnetite content in fly ash well-correlated with the increase ratio of As before and after magnetic separation, suggesting magnetite enhanced As enrichment in fly ash. Density functional theory (DFT) indicated that the bridges O sites of octahedral structure on Fe3O4 (111) surface were likely strong active sites for As2O3 adsorption. This study highlights the importance of magnetite on As transformation during bituminous or high-rank coal combustion in power plants and has great implications for developing effective techniques for As removal.

Analysis of the Spatial Distribution of Heavy Metals in Soil from a Coking Plant and Its Driving Factors

Coking plants are typical industrial pollution sites and may release heavy metals into the environment, posing a threat to human health. Scholars have discovered that different types of heavy metals are released during different coking production processes and lead to spatial differences in heavy metals. Research on the spatial distribution and driving factors of pollutants in the soil inside and outside coking plants is important for sampling design, risk assessment, pollution prevention and control, etc.. Inverse distance weight was used to analyze the spatial distribution of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn inside and outside of the coking plant. A geo-detector was used to find out the difference in the driving factors for the spatial distribution of heavy metals between soil from inside and outside the coking plant. The results showed that except As, Ni, and Zn, the overall background value rate of other heavy metals was above 50%, and the continuity of the spatial distribution of heavy metals in the soil was poor. The coefficient of variation (CV) exceeded 30%, representing a moderate variation. The average degree of CV inside the coking plant was Hg > Cd > As > Cu > Zn > Cr > Pb > Ni, and the external average degree of CV was Hg > Cu > Cd > As > Zn > Pb > Cr > Ni. An analysis of heavy metal content showed that the content of As, Cd, Cr, Pb, and Zn outside the coking plant was bigger than inside. According to geo-detector results, the physicochemical properties factors with a large contribution rate to the spatial distribution of heavy metals inside and outside the coking plant was the soil's total nitrogen, organic matter, and available medium-micro element content. Pollution source factors that contributed the most to the spatial distribution of heavy metals inside were the crude benzol and cold drum section, while the coke oven and quench section determined the outside spatial distribution of heavy metals. The q value of the strongest factor inside the coking plant was more than 0.5 while outside the coking plant it was less than 0.5. According to the interaction detector result, the interaction factors values of pollution sources and soil physicochemical properties to the inside spatial distribution of heavy metals was higher than outside. According to the distribution and geo-detector results, the strongest physicochemical properties driving factors that determined the inside and outside spatial distribution of heavy metals were relatively consistent. These factors were soil nutrient factors, which mainly influenced the availability of heavy metals. The differences in the production processes led to the difference between the inside and outside spatial distribution of heavy metals. The content of heavy metals outside the coking plant was higher than inside because the heavy metals came from various pollution sources. The driving forces for the distribution of heavy metals inside the plant were higher than outside and showed that the heavy metals inside of the plant were mainly from the coking plant. Heavy metal distribution inside the coking plant was mainly driven by the pollution source factor of the coking refining process and coking water, while heavy metal distribution outside the coking plant was mainly driven by the coking gas production process and other emission pollution source factors.

Human health risk assessment of arsenic in a region influenced by a large coal-fired power plant

Previous studies in the largest coal mining region of Brazil showed the strong influence of the coal-fired power plant in spatial distribution of As, especially in prevailing wind direction. However, it was not evaluated the risk of As on the local population. Thus, this study aims to assess the human health risk of As in a region under influence of atmospheric deposition of As from the coal-fired power plant. The human health risk assessment model was based on established by the U.S. Environmental Protection Agency (USEPA). It estimate the average daily dose (ADD), non-carcinogenic (HQ) and carcinogenic risk by in oral, dermal and inhalation exposure routes, as well as, the contribution of each via to ADD, HQ and carcinogenic risk to soil and air. Separately, both air and soil exposure pathways show HQ and HI below the risk threshold (< 1). However, when considerate the sum of both exposure pathways in the worst scenario of As contamination in air (maximum concentrations) there are a carcinogenic risk in the most of evaluated areas, including in a control area. The maximum values of As in PM10 contribute to health risk by air inhalation pathway (1.45 µg/m3). Inhalation pathway presents the major contribution to ADDair and ADDtotal. However, oral and dermal routes were more important to ADDsoil. The study reveals that there is a carcinogenic risk for exposure to As at a distance of almost 10 km from the coal-fired power plant.

Pleistocene sands of the Mississippi River Alluvial Aquifer produce the highest groundwater arsenic concentrations in southern Louisiana, USA

Geostatistical and geospatial analysis techniques were employed to evaluate relationships between high arsenic (As), iron (Fe), and manganese (Mn) concentrations in groundwaters from the Pleistocene Mississippi River Alluvial Aquifer (MRAA) in south-central Louisiana. The MRAA is recharged by the Mississippi River, and its groundwater contains Fe concentrations that range from 0.43 to 179 µmol kg−1 (n = 40) and As concentrations that range from 26 nmol kg−1 up to 8500 nmol kg−1 (i.e., 637 µg kg−1). Arsenic speciation analysis reveals a mix of redox states with As(V) accounting for between ca. 18% and ca. 84% of the total dissolved As (mean ± 1σ = 61.6 ± 24.4%, n = 6). Spatial distributions of As, Fe, and Mn concentrations suggest that the reductive dissolution of Fe/Mn oxides/oxyhydroxides is the likely source of As to the MRAA groundwaters. Geostatistical and geospatial analyses were employed to produce interpolation maps that show concentrations of As, Fe, and Mn decrease with distance from the Mississippi River. Spatial correlations are stronger between groundwater As and Fe concentrations (r = 0.710, PAs*Fe < 0.0005) than those between the As and Mn concentrations (r = 0.404, PAs*Mn < 0.0005). More specifically, regions of the MRAA characterized by high dissolved As concentrations spatially correlate with regions of high dissolved Fe concentrations, and to a lesser degree, high dissolved Mn concentrations. We hypothesize that recharge of the MRAA by Mississippi River water introduces labile organic carbon into the MRAA that subsequently fuels microbial respiration, which reduces Fe/Mn oxides/oxyhydroxides, and mobilizes adsorbed and/or co-precipitated As into MRAA groundwaters. Once mobilized, As is transported away from the riverbank by flowing groundwaters but is rapidly removed from solution by re-adsorption onto Fe/Mn oxides/oxyhydroxides within the regionally oxidized aquifer sediments. Our investigation indicates that oxidized Pleistocene sand aquifers in large river delta plains can also produce groundwater with dangerously high As concentrations if redox conditions shift to suboxic/ferruginous conditions.

Spatial Distribution of As and Cd in Co-contaminated Soils Within the Rice Root Microzone.

Soil samples were collected from the As and Cd co-contaminated demonstration area to analyze the spatial distributions of As and Cd in soils within the rice root microzone using the treatment of soil cubes (50mm × 50mm × 50mm). The results indicated that there was no significant difference in the spatial distributions of total As or Cd in the microzone with the percentage of root weight, horizontal distances (HD), and vertical depths (VD). Interestingly, available As or Cd increased with the increasing HD, and both of them showed a significant difference (p < 0.05) between < 75mm and ≥ 120mm. The availability of As or Cd increased from the center to the edge of the rice root microzone. Moreover, the risk assessment code (RAC) showed that the site with a high potential risk of As or Cd was located on the edge of the rice root microzone. This phenomenon implied that cultivating paddy rice in the low potential risk microzone might have a low accumulative risk.

Hydrogeochemical contrasts in the shallow aquifer systems of the Lower Katari Basin and Southern Poopó Basin, Bolivian Altiplano

Drinking water sources in the southeastern part of Lake Titicaca (Lower Katari Basin: LKB) and the southern part of Lake Poopó (Southern Poopó Basin: SPB) have high concentrations of arsenic (As), >10 μg/L compared to the WHO and NB-512 guideline value. These regions belong to the Bolivian Altiplano and are characterized by a semiarid climate, slow hydrological flow, with geological formations of volcanic origin, in addition to brines and other mineral deposits. The present study is focused on comparing the geochemical processes of As in relation to the sources and mobilization in groundwater (GW) in LKB and SPB. Groundwater (GW), surface water (SW) and sediment samples were collected from both basins. The As (LKB: 0.8–288 μg/L and SPB: 2.6–207 μg/L), boron (B) (LKB: 96–2473 μg/L and SPB: 507–4359 μg/L), manganese (Mn) (LKB: 0.6–7259 μg/L) and salinity (LKB: 125–11740 μS/cm) were found to be higher than the WHO guideline values, which is a serious concern about the GW quality for human consumption. The dissolution and exchange of bases are the processes that govern the mineralization of GW. Load of solids and liquids of anthropogenic origin in surface water (LKB) represents an environmental problem for communities on river banks. The spatial distribution of As was attributed to the geology of both the basins and the heterogeneously distributed evaporites in the sediments. The highest As concentrations are found in alluvial sediments of the northern region of LKB and “PACK belt” (an approximately 25 km long belt stretching along the southern shores of the Lake Poopó, between the villages of Pampa Aullagas and Condo K) in SPB. Sequential extraction of sediment and mineral saturation indices indicate that iron (Fe) and aluminum (Al) oxides as well as hydroxides are the most predominant mineral phases as potential sorbents of As.

Identifying quantitative sources and spatial distributions of potentially toxic elements in soils by using three receptor models and sequential indicator simulation.

Determining the reliable source contribution and spatial distribution of potentially toxic elements (PTEs) is a focal issue for soil regulation and remediation. For this purpose, three receptor models, US-EPA positive matrix factorization (EPAPMF), weighted alternating least squares positive matrix factorization (WALSPMF), and non-negative constrained absolutely principle analysis (NCAPCA), were used to a dataset consisting of ten PTEs (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, and Zn) for source apportionment. Hazardous areas of ten PTEs were delineated using sequential indicator simulation (SIS) and uncertainty analysis. Three factors for ten PTEs were derived by three receptor models with a one-to-one correspondence between the factors. To obtain more appropriate results, the three receptor models were combined to calculate the ensemble-average source contributions. As, Co, Cr, Cu, Mn, and Ni were derived from a natural source with ensemble-average contributions higher than 85.72%. Cd, Hg, Pb, and Zn were contributed by both parent material and anthropogenic influence. More than half of Hg concentrations were associated with atmospheric deposition caused by human emissions. The concentrations of 28.04% for Cd, 20.74% for Hg, 43.49% for Pb, and 23.71% for Zn were associated with human inputs including agriculture practice, industrial activities, and vehicle emissions. The maps of spatial distribution generated by the SIS indicated that parent materials controlled the spatial distributions of As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn. 27.1% and 32.1% of the total area for Cd and Hg were identified as hazardous areas exceeding 1.5 times background values of Shandong province.

The influence of the industrial area on the pollution outside its borders: a case study from Quintero and Puchuncavi districts, Chile.

The specific objectives of this study were: (1) to establish background content levels of potentially harmful elements in topsoil of Quintero and Puchuncavi districts; (2) to assess the degree of topsoil pollution and identify the local sources of pollution; and (3) to assess the health risk of metal exposure to population. Data from a Chilean Environmental Ministry report were analyzed. Multivariate analysis suggests that the potentially harmful elements are split into two main groups, which can be explained by controlling geogenic (Ni, V and Zn) and anthropogenic (As, Cd, Cu and Pb) factors. The spatial distribution of As, Cd, Cu and Pb displays a spatial pattern around the Puchuncavi-Ventanas industrial park. The background values determined with MAD (median absolute deviation) method include As 31.6mgkg-1, Cd 0.7mgkg-1, Cu 296mgkg-1, Ni 16.9mgkg-1, Pb 48.6mgkg-1, V 199mgkg-1 and Zn 192mgkg-1. The pollution indices reported considerable contamination to very high contamination in some soil samples. Hazard quotient values were higher for children than for adults, due to the ingestion and dermal absorption, while the cancer risk index values were in the acceptable range.