Characterization of particulate matter and its related metal toxicity in an urban location in South West India

This study reports the quantification of the toxicity of particulate matter (PM)-bound metals and their possible associated risks to human health. For assessment of PM, 24-h samples of PM₁₀ and PM_2.5 were collected by Mini Vol-TAS sampler at an urban site of Pune. Samples were sequentially extracted with ultrapure water and concentrated HNO₃ and analyzed for “soluble” and “total” metals. Factor analysis identified the resuspension of road dust due to traffic, biomass burning, construction activities, and wind-blown dust as possible sources that played an important role for overall pollution throughout the year. Water-soluble proportion was found to be ≤20 % for Cr, Co, Fe, and Al; ≥50 % for Sr, Cd, Ca, and Zn; and a substantial proportion (～25–45 %) for Mn, Ba, K, Na, Ni, Mg, Cu, and Pb metals in PM₁₀. For PM_2.5, the water-soluble proportion was ≤20 % for Fe, Co, Ni, Cr, and Al, while Sr, K, and Cd were mostly soluble (>50 %) and Cu, Ba, Mn, Ca, Zn, Pb, Na, and Mg were substantially soluble (～25–45 %). In the present study, among the toxic metals, Cd and Pb show higher concentration in the soluble fraction and thus represent the higher bioavailability index and especially are harmful to the environment and exposed person. Risk calculations with a simple exposure assessment method showed that the cancer risks of the bioavailable fractions of Cr, Cd and Ni were greater than the standard goal.     

Adjusting the effect of seasonal variability in the bioassessment of streams

Bioassessment tools should distinguish between the effects of anthropogenic degradation in communities and natural temporal changes. The present study tests the influence of natural seasonal variability on macroinvertebrate stream communities assessed by a predictive model (PORTRIV) and a multimetric index (IPtI) calibrated for spring. The scores of PORTRIV decreased significantly between spring and autumn, and between spring and winter (ca. 37 to 53 %, respectively), while those of IPtI did not change significantly between seasons. For non-reference samples, the results of the predictive model also indicate no significant differences. A correction factor (CF) was calculated to adjust the existing differences in the model assessments between seasons, based on the percentage of variation of reference site scores from spring to autumn and winter. After the application of the CF to the OE50 scores of spring reference samples, the differences were no longer significant. Independent reference validation sites confirmed this tendency. This method has the advantage of avoiding large efforts required for the construction of databases from other seasons and the development of new models to allow the assessment of streams in seasons other than spring. Further tests with models developed in regions with more marked seasonal changes should be done to confirm its wider applicability.     

A spectrophotometric assay method for vanadium in biological and environmental samples using 2,4-dinitrophenylhydrazine with imipramine hydrochloride

A simple, rapid, and sensitive method involving the interaction of 2,4-dinitrophenylhydrazine with imipramine hydrochloride in presence of vanadium (V) in sulfuric acid medium has been proposed for the determination of vanadium. The purple-colored product developed showed an absorption maximum at 560 nm and was stable for 24 h. The working curve was linear over the concentration range of 0.1–2.8 μg ml^− 1, with sensitivity of detection of 0.0124 μg ml^− 1. Molar absorptivity and Sandell’s sensitivity were found to be 2.6 × 10⁴ l/mol cm and 0.0039 μg cm^− 1, respectively. The accuracy of the proposed method was assessed by Student’s t test and variance ratio F test, and the results were on par with the reported method. The method was successfully used in the determination of V in water, human urine, soil, and plant samples, and it was free from interference by various concomitant ions.     

Mixed response in bacterial and biochemical variables to simulated sand mining in placer-rich beach sediments,Ratnagiri, West coast of India

We investigated the influence on bacterial community and biochemical variables through mechanical disturbance of sediment-akin to small-scale mining in Kalbadevi beach, Ratnagiri, a placer-rich beach ecosystem which is a potential mining site. Changes were investigated by comparing three periods, namely phase I before disturbance, phase II just after disturbance, and phase III 24 h after disturbance as the bacterial generation time is ≤7 h. Cores from dune, berm, high-, mid-, and low-tide were examined for changes in distribution of total bacterial abundance, total direct viability (counts under aerobic and anaerobic conditions), culturability and biochemical parameters up to 40 cm depth. Results showed that bacterial abundance decreased by an order from 10⁶ cells g^− 1 sediment, while, viability reduced marginally. Culturability on different-strength nutrient broth increased by 155% during phase II. Changes in sedimentary proteins, carbohydrates, and lipids were marked at berm and dune and masked at other levels by tidal influence. Sedimentary ATP reduced drastically. During phase III, Pearson’s correlation between these variables evolved from non-significant to significant level. Thus, simulated disturbance had a mixed effect on bacterial and biochemical variables of the sediments. It had a negative impact on bacterial abundance, viability and ATP but positive impact on culturability. Viability, culturability, and ATP could act as important indicators reflecting the disturbance in the system at short time intervals. Culturability, which improved by an order, could perhaps be a fraction that contributes to restoration of the system at bacterial level. This baseline information about the potential mining site could help in developing rational approach towards sustainable harnessing of resources with minimum damage to the ecosystem.     

Trace metals biogeochemistry of Kumaun Himalayan Lakes,Uttarakhand, India

The increasing urbanization, along with tourism, has posed a major threat to the Kumaun Himalayan Lakes, Uttarakhand, India. The total metal concentration in the water, interstitial water, and sediments along with the metal fractionation studies were carried out to understand the remobilization of the trace metals from the sediments of the lakes. The high concentration of the metals in the water column of the lakes generally decreases with depth and the metals release from the sediment is mainly due to the prevalence of anoxic condition at the sediment–water interface and sediment column. The sediment shows that metals Fe and Cr are derived from detrital source, whereas Co, Ni, and Zn are derived mainly from the organic matter dissolution. The sparse correlation of the trace metals with Ti shows most of the metals have chiefly re-precipitated from the water column. The metals speciation studies also supports that metals experience a high rate of anoxic dissolution and their precipitation onto the sediments are determined by the sediment composition and organic matter content. The high concentration of manganese in the interstitial water in the lakes indicates dissolution of organic matter. The released manganese is adsorbed/precipitated as carbonate phase (Nainital Lake) and oxide pahse (in other lakes). The study shows that the trace metals are regenerated from the sediments due to oxyhydroxide dissolution and organic matter decomposition.     

Occurrence of estrogen hormones in biosolids,animal manure and mushroom compost

The presence of natural estrogen hormones as trace concentrations in the environment has been reported by many researchers and is of growing concern due to its possible adverse effects on the ecosystem. In this study, municipal biosolids, poultry manure (PM) and cow manure (CM), and spent mushroom compost (SMC) were analyzed for the presence of seven estrogen hormones. 17α-estradiol, 17β-estradiol, 17α-dihydroequilin, and estrone were detected in the sampled biosolids and manures at concentrations ranging from 6 to 462 ng/g of dry solids. 17α-estradiol, 17β-estradiol, and estrone were also detected in SMC at concentrations ranging from 4 to 28 ng/g of dry solids. Desorption experiments were simulated in the laboratory using deionized water (milli-Q), and the aqueous phase was examined for the presence of estrogen hormones to determine their desorption potential. Very low desorption of 0.4% and 0.2% estrogen hormones was observed from municipal biosolids and SMC, respectively. An estimate of total estrogen contribution from different solid waste sources is reported. Animal manures (PM and CM) contribute to a significant load of estrogen hormones in the natural environment.     

Terrain Discontinuity Effects in the Regional Flow of a Complex Karstified Aquifer

Karst aquifers are characterized by spatial heterogeneity due to the presence of highly permeable channels and conduits in low-permeable fractured rocks (matrix block). Recent studies have reported a close relationship between surface and subsurface water in karstic regions due to the water flow through a complicated network of paths formed by fracture intersections. Subsurface flow in karstified aquifers ranges between conduit flow, in large passages with relatively high flow velocities, and diffuse flow, in the matrix block where Darcy’s law is still valid. In this paper, we present the simulation of a complex karstified aquifer system in Crete, Greece, where the presence of main faults drastically affects the regional flow. A discrete fracture approach in conjunction with an equivalent porous medium approach was adopted to simulate the mixed flow in the area of interest. The simulation results have shown that the length and the orientation of the dominant faults, primarily during the rainy season, affect the flow field.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Inexact Fuzzy-Stochastic Programming for Water Resources Management Under Multiple Uncertainties

In this study, an interval-parameter fuzzy-stochastic two-stage programming (IFSTP) approach is developed for irrigation planning within an agriculture system under multiple uncertainties. A concept of the distribution with fuzzy-interval probability (DFIP) is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets, and probability distributions. IFSTP integrates the interval programming, two-stage stochastic programming, and fuzzy-stochastic programming within a general optimization framework. IFSTP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised amounts are not delivered. IFSTP is applied to an irrigation planning in a water resources management system. Solutions from IFSTP provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results indicate that reasonable solutions are generated for objective function values and decision variables; thus, a number of decision alternatives can be generated under different levels of stream flows.