Kinetics of sorption of lead on bed sediments of River Hindon, India

A number of low cost waste sorbent have been used for removal of heavy metals, however, few studies have been carried out on the sorption process on riverbed sediments in their natural state of occurrence. Stream sediments adsorb certain solutes from streams, thereby significantly changing the solute composition, but little is known about quantitatively describing sorption phenomena and rates of these processes. In the present investigation, sorption of lead ions on river bed sediments of river Hindon, a tributary of river Yamuna, India has been studied to demonstrate the role of bed sediments in controlling metal pollution. The effect of various operating variables, viz., initial concentration, solution pH, sediment dose, contact time and particle size has been studied. The sorption of lead ions increased with respect to pH and sorbent dose and decreased with sorbent particle size. Two important geochemical phases, iron and manganese oxide, also play important role in the sorption process. The sorption data were analysed using Langmuir and Freundlich isotherm models to determine the mechanistic parameters related to the sorption process. Further, although lead ions have more affinity for the fine fraction of the sediment, but the overall contribution of coarser fraction to sorption is more as compared to clay and silt fraction. The kinetic data suggest that the sorption of lead on bed sediments is an endothermic process, which is spontaneous at low temperature. The uptake of lead is controlled by both bulk and intraparticle diffusion mechanism.     

Cover estimation versus density counting in species-rich pasture under different grazing intensities

Two methods for monitoring of grassland vegetation were compared: visual estimation of plant cover (C) and plant densities counting (D). C and D were performed in monthly intervals for three vegetation growing seasons after imposing different grazing regimes on abandoned grassland in 1998. Species scores obtained from paired redundancy analyses (RDA) of C and D data were compared and Spearman's rank correlations were used to show if the two methods give comparable results. Results of C and D were highly correlated in the first two growing seasons only. In the third season, correlation was substantially lower as the sward structure was more heterogeneous due to creation of differently defoliated patches especially under extensive grazing. Presence of the same plant species with different habit in frequently and in infrequently grazed patches, reduced significance of Spearman's rank correlations. Cover estimation can fully substitute plant density counting in grassland with lower proportion of frequently and infrequently grazed patches only, but caution should be used when comparing different management regimes in long term analyses.     

Multivariate statistical study of seasonal variation of BTEX in the surface water of Savitri River

Volatile organic compounds (VOCs) analysis was carried out for the surface water of the Savitri river during the period of June 2005 to June 2007. BTEX compounds (Benzene, Toluene, Xylene & Ethyl benzene) were analyzed by using micro extraction technique (Purge & Trap). Concentrations of these BTEX compounds were ranging from 0.1 to 1.5 ppm during sampling period. Higher concentrations of BTEX were found at sampling location VI. Concentration of ethyl benzene was very low as compare to other compounds. However, the concentration of benzene was very high. Seasonal variations in conc. of BTEX compounds were observed and higher concentration was detected during the summer season. Salting-out effect had given higher quantification values. In PCA and PFA, the component loading for all the variables are positively correlated. Death of fishes was observed in the river that is indication of severe pollution problem.     

Identification and quantification of microcystins from a Nostoc muscorum bloom occurring in Oukaïmeden River (High-Atlas mountains of Marrakech, Morocco)

Atmospheric BTEX [benzene, toluene, ethylbenzene, o-xylene and (m + p)-xylene] concentrations have been determined in the Naples metropolitan area (NMA) and in two suburban areas located on the north within about 25 km, during 2006. The pollutants were collected by passive samplers (24-h samplings), and analysed by GC-MS. In all the areas analysed the average atmospheric benzene concentrations were higher than the limit value fixed by the European Union for 2010 and in NMA the average concentration (9.8 microg m(-3)) also exceeded the limit fixed for 2006. High linear correlation coefficients between the average daily concentrations of the different BTEX are indicative of a single major source, most likely the vehicular traffic. The temporal and spatial distribution of BTEX relative concentrations suggest that massive emissions in NMA negatively affect the quality of the air in northern suburban areas, prevalently during the hottest months of the year, probably due to transport by local seasonal winds. The ratios between BTEX daily concentrations showed a clear dependence on the intensity of solar actinic flow, indicating a major role of photochemical processes in the air cleaning from these volatile organic pollutants.     

Identification of air pollutant sampling period using horizontal dilution potential

A new model is proposed for estimating horizontal dilution potential of an area using wind data. The mean wind speed and wind direction variation are used as a measure of linear and angular spread of pollutant in the atmosphere. The methodology is applied to monitored hourly wind data for each month of 1 year for wind data collected at Vadodara, Gujarat and monthly dilution potential is estimated. It is found that there is a gradual variation of horizontal dilution potential over a year with limited dilution during post monsoon period i.e., October and November and a high dilution in pre monsoon period i.e., May and June. This information can be used to design air quality sampling network and duration of sampling for source apportionment study. Air pollutant sampling during high dilution period can be carried out for identifying urban and rural dust and wind blown dust from mining activity. Air pollutant sampling during low dilution period can be carried out for capturing large amount of particulate matter from anthropogenic sources like elevated stack of furnace.     

Assessing benthic community condition in Chesapeake Bay: does the use of different benthic indices matter?

Federal and state environmental agencies conduct several programs to characterize the environmental condition of Chesapeake Bay. These programs use different benthic indices and survey designs, and have produced assessments that differ in the estimate of the extent of benthic community degradation in Chesapeake Bay. Provided that the survey designs are unbiased, differences may exist in the ability of these indices to identify environmental degradation. In this study we compared the results of three indices calculated on the same data, and the assessments of two programs: the Chesapeake Bay Program and the Mid-Atlantic Integrated Assessment (MAIA). We examined the level of agreement of index results using site-based measures of agreement, evaluated sampling designs and statistical estimation methods, and tested for significant differences in assessments. Comparison of ratings of individual sites was done within separate categories of water and sediment quality to identify which indices summarize best pollution problems in Chesapeake Bay. The use of different benthic indices by these programs produced assessments that differed significantly in the estimate of degradation. A larger fraction of poor sites was classified as good by the Environmental Monitoring and Assessment Program’s Virginian Province and MAIA benthic indices compared to the Chesapeake Bay benthic index of biotic integrity, although overall classification efficiencies were similar for all indices. Differences in survey design also contributed to differences in assessments. The relative difference between the indices remained the same when they were applied to an independent dataset, suggesting that the indices can be calibrated to produce consistent results.     

Modelling Water Blending—Sensitivity of Optimal Policies

Water blending is modelled as a combination of a linear program and a stochastic dynamic program. Optimal policies are found for linear and integer-linear formulations using both an expected monetary value and conditional value-at-risk criterion. The sensitivity of these solutions to the discretisation over volume and over time is investigated.     

The seasonal status of chemical parameters in shallow coastal aquifers of Rameswaram Island, India

The study area Rameswaram, a holy island, is famous for the sacred Ramanathaswamy temple, which cements people of the country regardless of their place, residence, or their religion or creed. This coastal tract is experiencing a chronic fresh water shortage, despite a few spring sources. The study area is selected for the characterization of physico-chemical parameters viz., pH, EC, TDS, salinity, TA, TH, CH, MH, chloride, and fluoride for 150 groundwater samples and the impact of pre- and post-monsoons on the groundwater quality is studied. The water quality index advocates the transfer of groundwater quality from unacceptable status in the pre-monsoon into an acceptable status in the post-monsoon. The Langelier saturation index reflects the scaling tendency of groundwater in the study area. The Karl Pearson correlation matrix has approved the maximum influence of calcium and chloride on the total dissolved solids. It is interesting to conclude that the groundwater in the study area has very had nature, especially of non-carbonate type.     

Fire risk evaluation using multicriteria analysis—a case study

Forest fires are one of the major causes of ecological disturbance and environmental concerns in tropical deciduous forests of south India. In this study, we use fuzzy set theory integrated with decision-making algorithm in a Geographic Information Systems (GIS) framework to map forest fire risk. Fuzzy set theory implements classes or groupings of data with boundaries that are not sharply defined (i.e., fuzzy) and consists of a rule base, membership functions, and an inference procedure. We used satellite remote sensing datasets in conjunction with topographic, vegetation, climate, and socioeconomic datasets to infer the causative factors of fires. Spatial-level data on these biophysical and socioeconomic parameters have been aggregated at the district level and have been organized in a GIS framework. A participatory multicriteria decision-making approach involving Analytical Hierarchy Process has been designed to arrive at a decision matrix that identified the important causative factors of fires. These expert judgments were then integrated using spatial fuzzy decision-making algorithm to map the forest fire risk. Results from this study were quite useful in identifying potential “hotspots” of fire risk, where forest fire protection measures can be taken in advance. Further, this study also demonstrates the potential of multicriteria analysis integrated with GIS as an effective tool in assessing “where and when” forest fires will most likely occur.     

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.