Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.     

DEFORMITIES IN CULTURED CHIRONOMUS TENTANS LARVAE AND THE INFLUENCE OF SUBSTRATE ON GROWTH, SURVIVAL AND MENTUM WEAR

Effects of four substrates (shredded papertowelling, coarse sand, fine sand, and silty clay)on growth, survival and mentum wear of Chironomustentans larvae were investigated in thelaboratory. Three categories of mentum wear were defined:minimal, moderate and substantial. Thenumber of larvae with worn mentum teeth did not differ in anyof the four substrates. However, thenumber of larvae with minimal wear of their teeth wassignificantly different among the substrates andwas in the order coarse sand > shredded paper towelling >clay/silt > fine sand. Mentumdeformities were observed in the cultured larvae, presumablybecause of inbreeding and not the effectof treatment. Differences in biomass and survival of larvaeamong the substrates were not significant(p<0.05), however, there was a trend for lower survival inthe sand substrates. These findingssuggest that shredded paper towelling is the most suitablereference substrate. The occurrence ofnatural abnormalities must be considered when using chironomidmouthpart deformities as an index of environmental degradation.     

Impact of bottom trawling on sediment characteristics—a study along inshore waters off Veraval coast, India

The present communication is a study on the impact of bottom trawling on the sediment characteristics along Veraval coast, which is the largest trawler port of India. Experimental bottom trawling was conducted from MFV Sagarkripa at five transects of water depths 15–20 m, 21–25 m, 26–30 m, 31–35 m and 36–40 m in commercial trawling grounds. Trawling was conducted for 12 months in a span of 15 months (September 2005–November 2006) excluding the trawl ban period (June to August). The sediment texture was analysed by pipette analysis and organic matter by wet oxidation method. The variations in organic matter and sediment texture were prominent between the stations selected at different depths. The sedimentary organic matter exhibited variations with different water depths and seasons. The organic matter content decreased with depth. Experimental trawling considerably reduced the organic matter content at all depths. Continued and incessant trawling operation can cause even more drastic reductions, where organic matter (OM) content is already very small. The sand proportion showed depth-wise variation; but seasonal and trawling effect was not significant showing highest values at 36–40 m depth. The silt proportion did not exhibit significant depth-wise variation. The seasonal variation of silt was significant whereas trawling effect imparted to silt was not evident. Trawling has no significant effect on clay concentration. But seasonal variation had great influence on the clay distribution and indicated significantly high depth–season interaction. The sediment of the study area was predominant in silt proportion. It was observed that the seasonal/natural variations were more prominent masking the trawling effect on silt.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Phosphorus speciation in the marine sediment of Kalpakkam coast,southeast coast of India

A study was carried out at Kalpakkam coast to find out the distribution of various fractions of phosphorus (P) in the marine sediment during pre-northeast monsoon period. Samples were collected from ten locations covering ~80 km² of the inner-shelf region. Sedimentary parameters such as sand, silt, clay, and organic carbon percentage were analyzed in order to find out their relation with various P fractions. The sediment was found to be predominantly sandy in nature with low silt and clay content. Among all the fractions (loosely bound (LoP), calcium bound (CaP), iron bound (FeP), aluminum bound (AlP), and organic (OP)), CaP fraction constituted the largest portion (68.7 %) followed by organic fraction (16.3 %). The bioavailable P fractions ranged from 5 to 44 % of the total P (TP) content. Relatively high LoP content was observed at the offshore locations with comparatively high mud percentage as compared with the near-shore locations. As FeP and AlP concentrations were directly proportional to the amount of fine-grain sediment, the low levels of these fractions found in this coastal area were therefore attributed to the sandy nature of the sediments. The order of abundance of the major forms of P in the surface sediments of Kalpakkam coast was as follows: CaP?>?OP?>?LoP?>?AlP?>?FeP.     

Predicting field capacity,wilting point,and the other physical properties of soils using hyperspectral reflectance spectroscopy: two different statistical approaches

In this study, we examined the ability of reflectance spectroscopy to predict some of the most important soil parameters for irrigation such as field capacity (FC), wilting point (WP), clay, sand, and silt content. FC and WP were determined for 305 soil samples. In addition to these soil analyses, clay, silt, and sand contents of 145 soil samples were detected. Raw spectral reflectance (raw) of these soil samples, between 350 and 2,500-nm wavelengths, was measured. In addition, first order derivatives of the reflectance (first) were calculated. Two different statistical approaches were used in detecting soil properties from hyperspectral data. Models were evaluated using the correlation of coefficient (r), coefficient of determination (R ²), root mean square error (RMSE), and residual prediction deviation (RPD). In the first method, two appropriate wavelengths were selected for raw reflectance and first derivative separately for each soil property. Selection of wavelengths was carried out based on the highest positive and negative correlations between soil property and raw reflectance or first order derivatives. By means of detected wavelengths, new combinations for each soil property were calculated using rationing, differencing, normalized differencing, and multiple regression techniques. Of these techniques, multiple regression provided the best correlation (P?<?0.01) for selected wavelengths and all soil properties. To estimate FC, WP, clay, sand, and silt, multiple regression equations based on first(2,310)-first(2,360), first(2,310)-first(2,360), first(2,240)-first(1,320), first(2,240)-first(1,330), and raw(2,260)-raw(360) were used. Partial least square regression (PLSR) was performed as the second method. Raw reflectance was a better predictor of WP and FC, whereas first order derivative was a better predictor of clay, sand, and silt content. According to RPD values, statistically excellent predictions were obtained for FC (2.18), and estimations for WP (2.0), clay (1.8), and silt (1.63) were acceptable. However, sand values were poorly predicted (RDP?=?0.63). In conclusion, both of the methods examined here offer quick and inexpensive means of predicting soil properties using spectral reflectance data.     

Polycyclic aromatic hydrocarbons in surface sediments from drinking water sources of Taihu Lake, China: sources, partitioning and toxicological risk

Sources, partitioning and toxicological risk of 15 priority polycyclic aromatic hydrocarbons (PAHs) in surface sediments from drinking water sources of Taihu Lake, with an area of 2428 km(2) located in the most developed and populated area of China, were studied, and the results were compared with those in other lakes of China and the USA. Concentrations of the 15 PAHs in sediments ranged from 436.6 to 1334.9 ng g(-1) (dw). Gasoline combustion, coal combustion, diesel combustion from shipping and spillage of petroleum were apportioned to be the main sources of PAHs in this area by principal component analysis, which contributed 35.19%, 26.43%, 25.41% and 12.97% to the PAH sources estimated by further multiple linear regression. Levels of PAHs in sediments were negatively correlated with contents of clay and fine silt (<16 μm), while positively with contents of medium silt, coarse silt and sand (>16 μm). Humin with size larger than 16 μm contained the largest part of the burden of PAHs in sediments, but the specific partitioning domain (bound humic acid, lipid or insoluble residue) depended on properties of organic matter reflected by optical absorbance at 465 and 665 nm. Total toxic benzo[a]pyrene equivalent (TEQ(carc)) of the carcinogenic PAHs in sediments varied from 31.8 to 209.3 ngTEQ(carc) g(-1). Benzo[a]pyrene and dibenzo[a,h]anthracene contributed 45.36 and 25.31% to total TEQ(carc), posing high toxicological risk to this area.     

The effects of land use changes on some soil properties in İndağı Mountain Pass – Çankırı, Turkey

Understanding spatial variability of dynamic soil attributes provides information for suitably using land and avoiding environmental degradation. In this paper, we examined five neighboring land use types in Indagi Mountain Pass - Cankiri, Turkey to spatially predict variability of the soil organic carbon (SOC), bulk density (BD), textural composition, and soil reaction (pH) as affected by land use changes. Plantation, recreational land, and cropland were the lands converted from the woodland and grassland which were original lands in the study area. Total of 578 disturbed and undisturbed soil samples were taken with irregular intervals from five sites and represented the depths of 0-10 and 10-20 cm. Soil pH and BD had the lower coefficient of variations (CV) while SOC had the highest value for topsoil. Clay content showed greater CV than silt and sand contents. The geostatistics indicated that the soil properties examined were spatially dependent to the different degrees and interpolations using kriging showed the dynamic relationships between soil properties and land use types. The topsoil spatial distribution of SOC highly reflected the changes in the land use types, and kriging anticipated significant decreases of SOC in the recreational land and cropland. Accordingly, BD varied depending on the land use types, and also, the topsoil spatial distribution of BD differed significantly from that of the subsoil. Generally, BD greatly decreased in places where the SOC was relatively higher except in the grassland where overgrazing was the more important factor than SOC to determine BD. The topsoil spatial distributions of clay, silt, and sand contents were rather similar to those of the subsoil. The cropland and grassland were located on the very fine textured soils whereas the woodland and plantation were on the coarse textured soils. Although it was observed a clear pattern for the spatial distributions of the clay and sand changing with land uses, this was not the case for the silt content, which was attributed to the differences of dynamic erosional processes in the area. The spatial distribution of the soil pH agreed with that of the clay content. Soils of the cropland and grassland with higher amounts of clay characteristically binding more cations and having higher buffering capacities had the greater pH values when compared to the soils of other land uses with higher amounts of sand naturally inclined to be washed from the base cations by the rainwater.     

The effectiveness of digital soil mapping to predict soil properties over low-relief areas

This study investigates the ability of different digital soil mapping (DSM) approaches to predict some of physical and chemical topsoil properties in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province, Iran. According to a semi-detailed soil survey, 120 soil samples were collected from 0 to 30 cm depth with approximate distance of 750 m. Particle size distribution, coarse fragments (CFs), electrical conductivity (EC), pH, organic carbon (OC), and calcium carbonate equivalent (CCE) were determined. Four machine learning techniques, namely, artificial neural networks (ANNs), boosted regression tree (BRT), generalized linear model (GLM), and multiple linear regression (MLR), were used to identify the relationship between soil properties and auxiliary information (terrain attributes, remote sensing indices, geology map, existing soil map, and geomorphology map). Root-mean-square error (RMSE) and mean error (ME) were considered to determine the performance of the models. Among the studied models, GLM showed the highest performance to predict pH, EC, clay, silt, sand, and CCE, whereas the best model is not necessarily able to make accurate estimation. According to RMSE%, DSM has a good efficiency to predict soil properties with low and moderate variabilities. Terrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas.     

Metals in water, sediments, and biota of an offshore oil exploration area in the Potiguar Basin, Northeastern Brazil

Metal concentrations were evaluated in water, bottom sediments, and biota in four field campaigns from 2002 to 2004 in the Potiguar Basin, northeastern Brazil, where offshore oil exploration occurs. Analyses were performed by inductively coupled plasma mass spectrometry and inductively coupled plasma optical emission spectrometry. Total metal concentrations in water (dissolved?+?particulate) and sediments were in the range expected for coastal and oceanic areas. Abnormally high concentrations in waters were only found for Ba (80 μg?l^?1) and Mn (12 μg?l^?1) at the releasing point of one of the outfalls, and for the other metals, concentrations in water were found in stations closer to shore, suggesting continental inputs. In bottom sediments, only Fe and Mn showed abnormal concentrations closer to the effluent releasing point. Metal spatial distribution in shelf sediments showed the influence of the silt–clay fraction distribution, with deeper stations at the edge of the continental shelf, which are much richer in silt–clay fraction showing higher concentrations than shallower sediments typically dominated by carbonates. Metal concentrations in estuarine (mollusks and crustaceans) and marine (fish) organisms showed highest concentrations in oysters (Crassostrea rhizophorae). Fish tissues metal concentrations were similar between the continental shelf influenced by the oil exploration area and a control site. The results were within the range of concentrations reported for pristine environments without metals contamination. The global results suggest small, if any, alteration in metal concentrations due to the oil exploration activity in the Potiguar Basin. For monitoring purposes, the continental inputs and the distribution of the clay–silt fraction need to be taken into consideration for interpreting environmental monitoring results.     

Identification of mangrove water quality by multivariate statistical analysis methods in Pondicherry coast,India

Different multivariate statistical analysis such as, cluster analysis, principal component analysis, and multidimensional scale plot were employed to evaluate the trophic status of water quality for four monitoring stations. The present study was carried out to determine the physicochemical parameters of water and sediment characteristics of Pondicherry mangroves—southeast coast of India, during September 2008–December 2010. Seasonal variations of different parameters investigated were as follows: salinity (10.26–35.20 psu), dissolved oxygen (3.71–5.33 mg/L), pH (7.05–8.36), electrical conductivity (26.41–41.33 ms⁻¹), sulfide (1.98–40.43 mg/L), sediment texture sand (39.54–87.31%), silt (9.89–32.97%), clay (3.06–31.20%), and organic matter (0.94–4.64%). pH, temperature, salinity, sand, silt, clay, and organic matter indicated a correlation at P < 0.01. CA grouped the four seasons in to four groups (pre-monsoon, monsoon, post-monsoon, summer) and the sampling sites in to three groups. PCA identified the spatial and temporal characteristics of trophic stations and showed that the water quality was worse in stations 3 and 4 in the Pondicherry mangroves.     

Some soil properties on coal mine spoils reclaimed with black locust (Robinia pceudoacacia L.) and umbrella pine (Pinus pinea L.) in Agacli-Istanbul

This study performed on randomly selected seven sample plots in leguminous black locust (Robinia pceudoacacia L.) plantations and five sample plots in umbrella pine (Pinus pinea L.) plantations on coal mine soil/spoils. Soil samples were taken from eight different soil depths (0–1, 1–3, 3–5, 5–10, 10–20, 20–30, 30–40, and 40–50 cm) into the soil profile. On soil samples, bulk density, fine soil fraction (Ø < 2 mm), sand, silt and clay rates, soil acidity (pH), organic carbon (C_org), and total nitrogen (N_t) contents were investigated. Also, some forest floor properties (unit mass, organic matter, and total nitrogen) were determined, and results were compared statistically between umbrella pine and black locust. As a result, 17 years after plantations, total forest floor accumulation determined as 6,107 kg ha^???1 under black locust compared to 13,700 kg ha^???1 under umbrella pine. The more rapid transformation of leguminous black locust forest floor creates organic carbon that migrates further into the mineral profile, and rapid accumulation of C and N in the soil profile was registered. Slower transformation processes of forest floor under umbrella pine result in lower soil N ratio and greater quantity of forest floor. Higher soil pH under leguminous black locust was determined significantly than umbrella pine. In conclusion, the composition of symbiotic nitrogen fixation of black locust appears to be a possible factor favoring carbon and nitrogen accumulation and, consequently, soil development. Clearly, both tree species have favorable impacts on initial soil formation. The umbrella pine generates the more forest floor layer; in contrast, black locust forest floor incorporates into the soil more rapidly and significantly increases soil nitrogen in upper soil layers.     

Distribution of mercury and organic matter in particle-size classes in sediments contaminated by a waste water treatment plant: Vidy Bay, Lake Geneva, Switzerland

In Lake Geneva, Switzerland, the most Hg-contaminated sediments have been found in the Vidy Bay where high Hg contents largely exceeds the background levels of Lake Geneva sediments. This contamination has been attributed to the discharge of a waste water treatment plant (WWTP). Total Hg (THg) and monomethylmercury (MMHg) were determined in bulk sediment and in three different grain size fractions (i: clay and silt, ii: fine-coarse sand, iii: and very coarse sand and gravel) collected close to the outlet pipe of a WWTP in order to verify whether the standardized procedures of sediment treatment is adequate for this setting and, by extension, for similar contaminated sites. THg was homogeneously distributed in the different grain size fractions and was correlated to organic matter content (R(2) = 0.6). MMHg was homogeneously distributed in the two finer grain fractions (Φ < 0.063 mm; 0.063 mm < Φ <1 mm). The results of this study suggested that the analysis of the bulk sediment seems to be more appropriate for the assessment of the content and spatial distribution of Hg in freshwater sediments contaminated by WWTPs.     

Soil phosphorus forms and their variations in selected paddy soils of Iran

Fractionation of soil phosphorus (P) can provide useful information for assessing the risk of soil P as the potential sources of eutrophication in aquatic systems. Little information exists on P forms in paddy soils of Isfahan Province in central Iran, where P fertilizers have been continuously applied for at least 45 years. The objectives of this study were to investigate concentrations and proportions of P forms in paddy soils and correlate the content of P forms with basic soil properties. Soil samples from three paddy sites were obtained, and soil P forms were determined by a modified Hedley fraction method. Results show that the total P concentrations ranged from 288 to 850 mg kg^?1 and were enriched in site 1. In all sites, the rank order of P fractions was HCl-P (CARB-P)?>?residual-P (RES-P)?>?NaOH-P (Fe-Al-P)?>?KCl-P (EXCH-P), indicating that Ca compounds are the main soil components contributing to P retention in these calcareous paddy soils. The EXCH-P represented on average?<?1 % of the total P, while the Fe-Al-P ranged 3.3–18 %. The CARB-P showed considerable contribution (63.6–85.6 %) to the total P. The Pearson correlation matrix indicated that Fe-Al-P only was positively correlated with total P, but did not show any significant correlations with other soil geochemical properties. Calcium-bound P fraction was significantly correlated with the clay, silt, cation exchange capacity, and total P.     

Comparative study based on sediment characteristics and macrobenthic communities in two Italian lagoons

The aims of this study were to analyse sediment characteristics and macrobenthic assemblages in two very close Italian coastal lagoons (Lesina and Varano) and to assess the different behaviour between the two basins and the relationship between sediment matrix and benthic organisms within and between the two lagoons. The comparative study was performed in July 2007 at 13 sampling sites in Lesina lagoon and 15 sites in Varano basin for sediment grain size, total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP) and macrobenthic structure analyses. Both lagoons were generally dominated by fine-grained sediments (clay and silt components). The average contents of TOC and TN measured in Lesina was higher than in Varano (3.31% vs 2.52% for TOC and 5,200 μg·g^???1 vs 3,713 μg·g^???1 for TN); in contrast, the TP was lower (540 μg·g^???1 vs 620 μg·g^???1). Based on macrobenthic community patterns, the central zone in Varano lagoon and the eastern area in Lesina lagoon were characterised by the lowest abundance (168.7 ind·m^???2 and 503.2 ind·m^???2, respectively) and by the lowest number of species, as highlighted by the diversity indices (Shannon–Wiener, H ^′ range was 0.47–1.45 for Lesina and 0.00–1.68 for Varano; Margalef species richness, d range was 0.00–1.67 for Lesina lagoon and 0.00–2.38 for Varano basin). Ordination diagrams suggested an influence of marine and freshwater inputs on the sediment distribution in Varano lagoon and on macrobenthic assemblages in Lesina lagoon.     

Improving Estimation of Specific Surface Area by Artificial Neural Network Ensembles Using Fractal and Particle Size Distribution Curve Parameters as Predictors

Specific surface area (SSA) is one of the principal soil properties used in modeling soil processes. In this study, artificial neural network (ANN) ensembles were evaluated to predict SSA. Complete soil particle-size distribution was estimated from sand, silt, and clay fractions using the model by Skaggs et al. and then the particle-size distribution curve parameters (PSDCPs) and fractal parameters were calculated. The PSDCPs were used to predict 20 particle-size classes for a soil sample’s particle size distribution. Fractal parameters were calculated by the model of Bird et al. In addition, total soil-specific surface area (TSS) was calculated using the above 20 size classes. Pedotransfer functions were developed for SSA and TSS using ANN ensembles from 63 pieces of SSA data taken from the literature. Fractal parameters, PSDCPs, and some other soil properties were used to predict SSA and TSS. Introducing fractal parameters and PSDCPs improved the SSA estimations by 12.5 and 11.1 %, respectively. The improvements were even better for TSS estimations (27.7 and 27.0 %, respectively). The use of fractal parameters as estimators described 44 and 92.8 % of the variation in SSA and TSS, respectively, while PSDCPs explained 42 and 6.6 % of the variation in SSA and TSS, respectively. The results suggested that fractal parameters and PSDCPs could be successfully used as predictors in ANN ensembles to predict SSA and TSS.     

Assessment of inceptisols soil quality following long-term cropping in a calcareous environment

The combination of morphological, clay mineralogy, physicochemical, and fertilitical properties of inceptisols were compared for monitoring soil quality response following long-term agricultural activities. For this target, fifty-nine paired surface soils belonging to five subgroups of inceptisols from the major sugar beet growing area and the adjoining virgin lands were described, sampled, and analyzed. The soils were alkaline and calcareous as characterized by high pH, ranging from 7.2 to 8, and calcium carbonate equivalent, ranging from 60 to 300 g kg^− 1. Following long-term sugar beet cultivation, morphological properties modifications were reflected as weakening of structure, hardening of consistency, and brightening of soil color. Although, the quantity of clay minerals did not significantly change through long-term cropping, some modifications in the XRD pattern of illite and smectite were observed in the cultivated soils compared to the adjoining virgin lands mainly as a result of potassium depletion. Without significant variation, sand content decreased by 4–55% and silt and clay increased by 3–22% and 2–15%, respectively, in the cultivated soils than to that of the virgin lands. Both negative and positive aspects of soil quality were reflected regarding soil chemical and fertilitical properties and the role of negative effects far exceeded the role of positive effects. Typic calcixerepts was known to be more degraded through a significant decrease (P ≤ 0.001) in mean value of soil organic carbon (a drop of 24%), total N (a drop of 23%), available K (a drop of 42%), exchangeable K (a drop of 45%), potassium adsorption ratio and potassium saturation ratio (a drop of 44% and 42%, respectively) and a significant increase (P ≤ 0.001) in EC (a rise of 53%). Soil quality index, calculated based on nine soil properties [coarse fragments, pH, SOC, total N, ESP, exchangeable cations (Ca, Mg, and K), and available phosphorus], indicated that 60% of the all soil types studied had negative changes, 20% had positive changes, and 20% produced no changes in soil heath.     

Vertical distribution of heavy metals in soil profile in a seasonally waterlogging agriculture field in Eastern Ganges Basin

The accumulation of heavy metals in soil and water is a serious concern due to their persistence and toxicity. This study investigated the vertical distribution of heavy metals, possible sources and their relation with soil texture in a soil profile from seasonally waterlogged agriculture fields of Eastern Ganges basin. Fifteen samples were collected at ～0.90-m interval during drilling of 13.11 mbgl and analysed for physical parameters (moisture content and grain size parameters: sand, silt, clay ratio) and heavy metals (Fe, Mn, Cr, Cu, Pb, Zn, Co, Ni and Cd). The average metal content was in the decreasing order of Fe?>?Mn?>?Cr?>?Zn?>?Ni?>?Cu?>?Co?>?Pb?>?Cd. Vertical distribution of Fe, Mn, Zn and Ni shows more or less similar trends, and clay zone records high concentration of heavy metals. The enrichment of heavy metals in clay zone with alkaline pH strongly implies that the heavy metal distributions in the study site are effectively regulated by soil texture and reductive dissolution of Fe and Mn oxy-hydroxides. Correlation coefficient analysis indicates that most of the metals correlate with Fe, Mn and soil texture (clay and silt). Soil quality assessment was carried out using geoaccumulation index (I _geo), enrichment factor (EF) and contamination factor (CF). The enrichment factor values were ranged between 0.66 (Mn) and 2.34 (Co) for the studied metals, and the contamination factor values varied between 0.79 (Mn) and 2.55 (Co). Results suggest that the elements such as Cu and Co are categorized as moderate to moderately severe contamination, which are further confirmed by I _geo values (0.69 for Cu and 0.78 for Co). The concentration of Ni exceeded the effects-range median values, and the biological adverse effect of this metal is 87 %. The average concentration of heavy metals was compared with published data such as concentration of heavy metals in Ganga River sediments, Ganga Delta sediments and upper continental crust (UCC), which apparently revealed that heavy metals such as Fe, Mn, Cr, Pb, Zn and Cd are influenced by the dynamic nature of flood plain deposits. Agricultural practice and domestic sewage are also influenced on the heavy metal content in the study area.     

Occurrence and sorption properties of arsenicals in marine sediments

The content of total arsenic, the inorganic forms: arsenite (As(III)) and arsenate (As(V)), the methylated forms: monomethylarsonic acid and dimethylarsinic acid (DMA), trimethylarsenic oxide, tetramethylarsenonium ion and arsenobetaine was measured in 95 sediment samples and 11 pore water samples from the Baltic Sea near the island of Bornholm at depths of up to 100 m. As(III+V) and DMA were detected in the sediment and As(III+V) was detected in the sediment pore water. Average total As concentration of 10.6?±?7.4 mg/kg dry matter (DM) in the sediment corresponds to previously reported values in the Baltic Sea and other parts of the world. Existing data for on-site measurements of sorption coefficients (Kd) of arsenicals in marine and freshwater sediments show large variability from <1 to >1,000 L/kg. In this work, calculated sorption coefficients (Kd and Koc) for As(III+V) showed significant correlation with depth, dissolved oxygen (DO), salinity and sediment classification; for depths <70 m, salinity <11 %, DO >9 mg/L and sand/silt/clay sediments the Kd was 118?±?76 L/kg DM and for depths >70 m, salinity >11 %, DO?<?9 mg/L and muddy sediments the Kd was 513?±?233 L/kg DM. The authors recommend using the found Kd value for arsenic in marine sediments when conditions are similar to the Baltic Sea. At locations with significant anthropogenic point sources or where the local geology contains volcanic rock and sulphide mineral deposits, there may be significantly elevated arsenic concentrations, and it is recommended to determine on-site Kd values.     

Assessment of the Heavy Metal Pollution Effects on the Soil Respiration in the Baix Llobregat (Catalonia, NE Spain)

A main goal of investigations is to determine could a soilrespiration be an indicator of the soil pollution. In this case a measured levelof the soil oxygen consumption depends of its pollution. It alsomeans that the pollution reduces biological processes in edaphon.Investigated soil samples were taken from polluted andnon-polluted places in the Baix Llobregat near Barcelona (Catalonia, NE Spain). Soil samples were taken from the top ofsoil (0–5 cm) without a litter. Soil analysis were done, determining percentage shares of coarsefragments, coarse sand, fine sand, coarse silt, fine silt, clay,CaCO₃, organic matter as well as water pH and conductivityCE (1:5 [mS cm^-1]). Also were determined (in mg kg^-1)quantities of heavy metals, as Fe, Al, Mn, Zn, Cr, Ni, V, Cu, Cd, Pb.The soil respiration was investigated in temperatures15 and 30 °C and with controlled humidity.The respiration in 30 °C is number of times greater thenin 15 °C both for polluted and non-polluted soils.Particularly high coefficients of correlation between the soilrespiration and soil pollution in polluted soils were obtainedfor Pb: r = 0.75 in 15 °C and r = 0.98 in30 °C; for Ba: 0.90 and 0.57; for V: 0.99 and 0.81. In non-polluted soils highest correlation coefficients are for Pb: r = 0.70 in 15 °C; Fe: 0.60 and 0.72; Al: 0.68 and0.64; Mn: 0.51 and 0.66; Ba: 0.63 and 0.61; Cr: 0.94 and0.70; Ni: 0.64 and 0.65; Cu: 0.69 and 0.48; as well as V: 0.62in 15 °C; and Cd: 0.69 in 15 °C.This way the soil respiration could be a good indicator of the soil pollution.