Screening and identification of early warning algal species for metal contamination in fresh water bodies polluted from point and non-point sources

The water bodies of Lucknow, Unnao and Kanpur (U.P.), India polluted through various point and non point sources were found to be either eutrophic or oligotrophic in nature. These water bodies supported a great number of algal diversity, which varied seasonally depending upon the physico-chemical properties of water. Further, the water bodies polluted through non point sources supports diverse algal species, while the water bodies polluted through point sources supports growth of tolerant blue green algae. High biomass producing algal species growing in these water bodies have accumulated significant amount of metals in their tissues. Maximum amount of Fe was found accumulated by species of Oedogonium sp. II (20,523.00 mug g(-1) dw) and Spirogyra sp. I (4,520.00 mug g(-1) dw), while maximum Chromium (Cr) was found accumulated in Phormedium bohneri (2,109.00 mug g(-1) dw) followed by Oscillatoria nigra (1,957.88 mug g(-1) dw) and Oedogonium sp. I (156.00 mug g(-1) dw) and Ni in Ulothrix sp. (495.00 mug g(-1) dw). Results showed that some of these forms growing in polluted environment and accumulating high amounts of toxic metals may be used as bioindicator species, however, their performance in metal contaminated water under different ecological niche is to be ascertained.     

Biophysical and socioeconomic characterization of a water-stressed area and simulating agri-production estimates and land use planning under normal and extreme climatic events: a case study

This study aims in linking the biophysical and socioeconomic data base layers with the technical coefficients or simulation models for agri-production estimates and land use planning under normal and extreme climatic events, and exploring the resource and inputs management options in village Shikohpur, Gurgaon district located in the northwest part of India. The socioeconomic profile of Shikohpur is highly skewed with mostly small and marginal farmers. Though the areas under wheat in Shikohpur are increasing, the productivity is declining or remaining stagnant over the years. Most of the area during kharif season (June-September) remains fallow. Pearl millet based cropping systems (pearl millet-mustard and pearl millet-wheat) are predominant. Soils are mostly loamy sand to sandy loam with average of 70-80% sand content. Organic C content in soil is less than 0.3%, due to high prevailing temperature with little rainfall and also intensive agriculture followed in this region. Though the annual average seasonal rainfall in Gurgaon did not have much variation over the years, occurrence of extreme climate events has increased in the last two decades. The crop intensity is low and the water table is declining. Water and nitrogen production functions were developed for the important crops of the region, for their subsequent use in scheduling of the inputs. InfoCrop, WTGROWS and technical coefficients were used for crop planning and resource management under climate change and its variability, extreme events, limited resource availability and crop intensification. These will help in disseminating necessary agro-advisories to the farmers so that they will be able to manipulate the inputs and agronomic management practices for sustained agricultural production under normal as well as extreme climatic conditions.     

Effect of Trivalent and Hexavalent Chromium on Carbohydrate Metabolism of a Freshwater Field Crab, Barytelphusa guerini

The in vivo toxic impact of chromium in its two forms(trivalent and hexavalent) on glycogen metabolism in the tissuesof freshwater field crab Barytelphusa guerini was studied.In a sublethal long-term exposure of 30, 60 and 90 days, thedepletion of glycogen and glucose levels reflected in theactivity of glycogenphosphorylases `a' and `ab'. A tissuespecific and time-dependent variation in tissue glucose reservesparelleled the progressive accumulation of haemolymph sugars.Trivalent and hexavalent chromium induced alterations in metabolite levels and in enzyme activities in the tissues. Themagnitude of responses were found more in the hexavalent formthan in trivalent form.     

Migratory crustaceans as biomonitors of metal pollution in their nursery areas. The Lesina lagoon (SE Italy) as a case study

Lichens collected in an unpolluted forest (background) in November 2004, transplanted at 41 sampling sites along the Madina-Tetteh Quarshie road, retrieved in February 2005 and analysed were found to contain higher concentrations of Manganese (Mn), Vanadium (V), lead, Cadmium (Cd), Chromium (Cr) and Nickel (Ni) than in the background area. Observations showed that of all the heavy metals studied, Manganese concentrations were highest at all sampling points with maximum values around a traffic light, an intersection and car fitting/mechanic workshops. Significant correlations were found between Ni and Mn, Mn and Cr and Mn and V. Statistical analysis also revealed a relatively even dispersion of the studied elements on the eastern side of the road than on the western side.     

Biomonitoring of heavy metals by pollen in urban environment

Abstract Industrial development and consumption of petroleum products leads to increase air pollution levels especially in urban and industrial areas. Heavy metal components associated with air pollutants have far reaching effects with respect to economic and ecological importance of pollens. The pollens are male reproductive organs of the plant and travel through air from flower to flower for pollination purpose. During this period they are exposed to air pollutants. Present investigation thus pertains to study of effect of air pollutants on pollens especially biosorption and bioaccumulation of heavy metals. The pollens of three commonly occurring plants namely Cassia siamea, Cyperus rotundus, Kigelia pinnata have been studied from the NH-6 of Nagpur city, India. The pollens exposed to polluted air showed the presence of higher concentrations of Ca, Al and Fe as compared to unexposed pollens. Higher concentration of these metals was observed in Cyperus rotundus followed by Cassia siamea and Kigelia pinnata. These results indicate that pollens act as good indicator of air pollution giving results in short time of exposure of 5–10 h. Apart from this, it is also reported that some of these metals play crucial role in the metabolic activity in pollens for example Calcium is necessary for growth of pollen tube and other metabolic activities in pollens. The presence of these metals in pollens may also enhance the allergenicity of the pollens. Similarly accumulation of heavy metals may also deteriorate the quality of pollen for their economical use. The viability of pollen is also affected by these pollutants in sensitive species leading to impairment of their fertility.     

Whole body vibration exposure in heavy earth moving machinery operators of metalliferrous mines

As mining operations get mechanized, the rate of profit generation increases and so do the rate of occupational hazards. This study deals with one such hazard - occupational vibration. The present study was carried out to determine the whole body vibration (WBV) exposure of the heavy earth moving machinery (HEMM) operators in two types of metalliferous mines in India, when they were engaged in the mining activity. Cross-comparison was done of the vibration dose value (VDV) for HEMM operators as well as each type of mine. The VDV for the shovel operator in bauxite mine was observed to be 13.53 +/- 5.63 m/s(7/4) with 25% of the readings higher than the prescribed limit whereas in iron ore mine VDV for dumper operator was 10.81 +/- 3.44 m/s(7/4) with 14.62% readings on the higher side. Cross-comparison of the VDV values for bauxite and iron ore mines revealed that it was 9.57 +/- 4.93 and 8.21 +/- 5.12 m/s(7/4) with 21.28 and 14.95% of the readings on the higher side respectively. The Student's t test level was found to be insignificant for both type of mines, indicating that the WBV exposure is not dependent on the type of mine but is dependent on the working condition and type of HEMM in operation.     

Precipitation composition and wet deposition temporal pattern in Central Serbia for the period from 1998 to 2004

Bulk samples collected on a daily basis at three principal meteorological stations in central Serbia were analyzed on chloride (Cl(-)), nitrate [Formula: see text], sulfate [Formula: see text], sodium (Na(+)), ammonium [Formula: see text], potassium (K(+)), calcium (Ca(2+)), and magnesium (Mg(2+)) in addition to precipitation amount, pH and conductivity measurements over the period 1998-2004. The data were subjected to variety of analyses (linear regression, principal component analysis, time series analysis) to characterize precipitation chemistry in the study area. The most abundant ion was [Formula: see text] with annual volume weighted mean concentration of 242 microeq L(-1). Neutralization of precipitation acidity occurs both as a result of the dissolution of alkaline compounds containing Ca(2+), Mg(2+), and K(+) as well as the absorption of ammonia. The ratio of [Formula: see text] was above 5, which indicated that the combustion process of low-grade domestic lignite for electricity generation from coal-fired thermal power plants was the main source of pollution in the investigated area. A considerable mean annual bulk wet deposition of SO(4)-S determined by precipitation amount and concentrations of sulfate in the precipitation was calculated to be 12-35 kg ha(-1).     

Indoor and outdoor PM mass and number concentrations at schools in the Athens area

Simultaneous indoor and outdoor PM₁₀ and PM_2.5 concentration measurements were conducted in seven primary schools in the Athens area. Both gravimetric samplers and continuous monitors were used. Filters were subsequently analyzed for anion species. Moreover ultrafine particles number concentration was monitored continuously indoors and outdoors. Mean 8-hr PM₁₀ concentration was measured equal to 229 ± 182 μg/m³ indoors and 166 ± 133 μg/m³ outdoors. The respective PM_2.5 concentrations were 82 ± 56 μg/m³ indoors and 56 ± 26 μg/m³ outdoors. Ultrafine particles 8-h mean number concentration was measured equal to 24,000 ± 17,900 particles/cm³ indoors and 32,000 ± 14,200 particles/cm³ outdoors. PM₁₀ outdoor concentrations exhibited a greater spatial variability than the corresponding PM_2.5 ones. I/O ratios were close or above 1.00 for PM₁₀ and PM_2.5 and smaller than 1.00 for ultrafine particles. Very high I/O ratios were observed when intense activities took place. The initial results of the chemical analysis showed that accounts for the 6.6 ± 3.5% of the PM₁₀ and for the 3.1 ± 1.4%.The corresponding results for PM_2.5 are 12.0 ± 7.7% for and 3.1 ± 1.9% for . PM_2.5 indoor concentrations were highly correlated with outdoor ones and the regression line had the largest slope and a very low intercept, indicative of no indoor sources of fine particulate . The results of the statistical analysis of indoor and outdoor concentration data support the use of as a proper surrogate for indoor PM of outdoor origin.     

Prediction models of CO, SPM and SO2 concentrations in the Campo de Gibraltar Region, Spain: a multiple comparison strategy

The 'Campo de Gibraltar' region is a very industrialized area where very few air pollution studies have been carried out. Up to date, no model has been developed in order to predict air pollutant levels in the different towns spread in the region. Carbon monoxide (CO), Sulphur dioxide (SO(2)) and suspended particulate matter (SPM) series have been investigated (years 1999-2000-2001). Multilayer perceptron models (MLPs) with backpropagation learning rule have been used. A resampling strategy with two-fold crossvalidation allowed the statistical comparison of the different models considered in this study. Artificial neural networks (ANN) models were compared with Persistence and ARIMA models and also with models based on standard Multiple Linear Regression (MLR) over test sets with data that had not been used in the training stage. The models based on ANNs showed better capability of generalization than those based on MLR. The designed procedure of random resampling permits an adequate and robust multiple comparison of the tested models. Principal component analysis (PCA) is used to reduce the dimensionality of data and to transform exogenous variables into significant and independent components. Short-term predictions were better than medium-term predictions in the case of CO and SO(2) series. Conversely, medium-term predictions were better in the case of SPM concentrations. The predictions are significantly promising (e.g., d (SPM 24-ahead) = 0.906, d (CO 1-ahead) = 0.891, d (SO2 1-ahead) = 0.851).