Analysis of some heavy metals in the riverine water, sediments and fish from river Ganges at Allahabad

The river Ganges has been one of the major recipients of industrial effluents in India. The present paper deals with the study related to occurrence and bioaccumulation of heavy metals (Cu, Cr, Cd, Pb, Zn) in the riverine water, sediment, and the muscles of two cat fish species, Channa punctatus (C. punctatus) and Aorichthys aor (A. aor) procured from the river Ganges at Allahabad. The data obtained after water analysis reflected the order of occurrence of heavy metals to be Zn > Pb > Cu > Cr > Cd, respectively. The analysis of heavy metals in sediment indicated that among the five heavy metals tested; Zn was maximally accumulated followed by Pb, Cr, Cu and Cd. The trend of heavy metals accumulation in fish muscles was found to be similar to that observed in sediment and water such as Zn > Pb > Cu > Cr > Cd. Data indicated that Zn accumulated maximally in the sediment as well as muscles of both of the fish species in comparison to other metals.     

An assessment of fluoride in the coastal aquifer of the Bara tract in Bharuch district, Gujarat (India)

The fluoride (F) concentration in the coastal aquifers of Bara tract in Bharuch district, Gujarat was determined by potentiometric method using an ion-selective electrode. The fluoride concentration in these aquifers varies between 0.060 to 3.51 mg/L. It was also found that F has a positive correlation with pH and HCO(3)(-) whereas negatively correlated with Ca(2+), indicating that high fluoride in ground water is associated with low calcium content. This suggests that the higher pH of water promotes the leaching of fluoride and thus affects the concentration of fluoride in the ground water. It was also found that there exists no relationship between F, EC, and ground water table from surface in the ground water.     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Development of tiger habitat suitability model using geospatial tools—a case study in Achankmar Wildlife Sanctuary (AMWLS), Chhattisgarh India

Geospatial tools supported by ancillary geo-database and extensive fieldwork regarding the distribution of tiger and its prey in Anchankmar Wildlife Sanctuary (AMWLS) were used to build a tiger habitat suitability model. This consists of a quantitative geographical information system (GIS) based approach using field parameters and spatial thematic information. The estimates of tiger sightings, its prey sighting and predicted distribution with the assistance of contextual environmental data including terrain, road network, settlement and drainage surfaces were used to develop the model. Eight variables in the dataset viz., forest cover type, forest cover density, slope, aspect, altitude, and distance from road, settlement and drainage were seen as suitable proxies and were used as independent variables in the analysis. Principal component analysis and binomial multiple logistic regression were used for statistical treatments of collected habitat parameters from field and independent variables respectively. The assessment showed a strong expert agreement between the predicted and observed suitable areas. A combination of the generated information and published literature was also used while building a habitat suitability map for the tiger. The modeling approach has taken the habitat preference parameters of the tiger and potential distribution of prey species into account. For assessing the potential distribution of prey species, independent suitability models were developed and validated with the ground truth. It is envisaged that inclusion of the prey distribution probability strengthens the model when a key species is under question. The results of the analysis indicate that tiger occur throughout the sanctuary. The results have been found to be an important input as baseline information for population modeling and natural resource management in the wildlife sanctuary. The development and application of similar models can help in better management of the protected areas of national interest.     

Assessing impact of industrialization in terms of LULC in a dry tropical region (Chhattisgarh), India using remote sensing data and GIS over a period of 30 years

The main focus of the paper is to assess the land use/ land cover (LULC) change in northern Chhattisgarh due to industrialization using remote sensing and Geographical Information System (GIS). The impact was assessed using an information extraction method applied to temporal satellite data (LANDSAT and IRS scenes) in GIS domain. For assessing the impact on natural resources, the classification scheme was restricted to (1) Forest patches ((a) completely cleared, (b) partially cleared, (c) least affected), (2) Non-Forest ((d) completely changed, (e) least changed), (3) Industrial/Mining area, and (4) River. Over the three decades 22.22% of forests have been completely cleared and converted to industrial setup. Another 25% is completely cleared and 10% is degraded. Around 4% of agricultural area is totally affected due to industrial activity. Random assessment of plant distribution (Trees, Shrubs and Herbs) indicates significant changes in the herb distribution directly related to distance gradient form the industrial/mining setup. Visual recording, socio-economic survey and satellite data also helped in delineation of extent of environmental pollution in forest and non-forest areas. The paper presents methodology for the environmental impact assessment.     

Attitudinal response towards road traffic noise in the industrial town of Asansol, India

The major objective of the investigation was to evaluate the road traffic noise and its likely impacts on the local community of Asansol city (West Bengal, India) by monitoring and modeling. The attitudinal response of local population due to existing vehicular noise is presented in the paper. Noise and Attitudinal Survey was conducted at 25 locations. A total of 869 individuals were surveyed. The relationship between traffic noise levels and annoyance was studied using correlation, linear and multiple linear regressions analysis. The average L(dn) value was 73.28 +/- 8.51 dB(A) (55.1-87.3); The Traffic Noise Index (TNI) was 80.62 +/- 15.88 dB(A) (49.4-115.8). The mean value of percent of population Highly Annoyed (%HA) due to road traffic noise was 26.50 +/- 3.37 (19.44-33.2), whereas the mean dissatisfaction score (MDS) was 2.96 +/- 0.90 (1.04-4.45). Annoyance modeling was also performed based on field data. It can be said that Noise values gives desirable annoyance predicting values in comparison to vehicular data.     

Distribution of vehicular pollutants in street canyons of Varanasi, India: a different case

In present study horizontal and vertical distribution of traffic-related pollutants (CO and SO(2)) within the street canyons in (CO and SO(2)) Varanasi, India was monitored. The results showed that average horizontal profiles of traffic-related pollutant concentrations within street canyon at leeward side were approximately same as that of windward side. However, the vertical concentration of both the pollutants decreases with height above the ground and study indicated that CO and SO(2) concentrations at different heights below the roof showed clear vertical self-gradient. CO and SO(2) concentration decreased with height and the minimum value occurred at the roof. It was concluded from the observed results that pollutants from vehicular exhaust emissions in the street canyon of Varanasi were evenly distributed. This result may be due to the fact that wind vortices are not formed. Therefore, urban planners can use this type of streets so that there is proper ventilation and dispersal of pollutants.     

Assessment and significance of phytoplankton species composition within Chesapeake Bay and Virginia tributaries through a long-term monitoring program

Phytoplankton and water quality long term trends are presented from a 20-year monitoring program of Chesapeake Bay and several of its major tributaries. Increasing phytoplankton biomass and abundance are ongoing within this estuarine complex, with diatoms the dominant component, along with chlorophytes and cyanobacteria as sub-dominant contributors in the tidal freshwater and oligohaline regions. Diatoms, dinoflagellates, and cryptomonads are among the major flora downstream in the tributaries and within the Chesapeake Bay. Water quality conditions within the three tributaries have remained rather stable over this time period; while there are long term trends of reduced nutrients, increasing bottom oxygen, and decreasing water clarity for the lower Chesapeake Bay. Of note is an increasing trend of cyanobacteria biomass at 12 of the 13 stations monitored at tributary and Chesapeake Bay stations, plus the presence of 37 potentially harmful taxa reported for these waters. However, the overall status of the phytoplankton populations is presently favorable, in that it is mainly represented and dominated by taxa suitable as a major food and oxygen source within this ecosystem. Although potentially harmful taxa are present, they have not at this time exerted profound impact to the region, or replaced the diatom populations in overall dominance.     

Bioaccumulation of heavy metals in fish tissues of a freshwater lake of Bhopal

Contamination of heavy metals, namely, lead, cadmium, zinc, nickel, copper, chromium and mercury was evaluated in the samples of water and tissues of Labeo rohita and Ctenopharyngodon idella of Upper Lake of Bhopal collected during summer, rainy and winter seasons of 2005–2006. Different organs of the fishes accumulated varying quantities of different heavy metals. In L. rohita, accumulation of heavy metals was in the sequence liver > kidney > gills > muscles, and in C. idella, it was gills > liver > kidney > muscles. Zn was the highest accumulating metal in fish, whilst Hg was the lowest and was well corroborated with those of water. The values of heavy metals were so far well within the maximum permissible standard value of heavy metals for drinking water and for fish culture as prescribed by various national and international agencies.     

Monsoon-induced changes in the size-fractionated phytoplankton biomass and production rate in the estuarine and coastal waters of southwest coast of India

Changes in the autotrophic pico- (0.2–2 μm), nano- (2–20 μm), and microplankton (>20 μm) biomass (chlorophyll a) and primary production were measured in the estuarine and coastal waters off Cochin, southwest coast of India during the onset and establishment of a monsoon. During this period, the estuary was dominated by nutrient-rich freshwater, whereas the coastal waters were characterized with higher salinity values (>30 psu) and less nutrients. The average surface chlorophyll a concentrations and primary production rates were higher in the estuary (average 13.7 mg m^???3 and 432 mgC m^???3 day^???1) as compared to the coastal waters (5.3 mg m^???3 and 224 mgC m^???3 day^???1). The nanoplankton community formed the major fraction of chlorophyll a and primary production, both in the estuary (average 85 ± SD 8.3% and 81.2 ± SD 3.2%) and the coastal waters (average 73.2 ± SD 17.2% and 81.9 ± 15.7%). Nanoplankton had the maximum photosynthetic efficiency in the coastal waters (average 4.8 ± SD 3.9 mgC mgChl a m^???3 h^???1), whereas in the estuary, the microplankton had higher photosynthetic efficiency (average 7.4 ± 7 mgC mgChl a m^???3 h^???1). The heavy cloud cover and increased water column turbidity not only limit the growth of large-sized phytoplankton in the Cochin estuary and coastal waters but also support the proliferation of nanoplankton community during the monsoon season, even though large variation in nanoplankton chlorophyll a and production exists between these two areas.