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.     

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.     

Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in North-East India during 1972–1999

Deforestation is recognized as one of the most significant component in LULC and global changes scenario. It is imperative to assess its trend and the rates at which it is occurring. The changes will have long-lasting impact on regional climate and in turn on biodiversity. In North-East India, one of the recognized global biodiversity hotspots, approximately 30% of total forest cover is under pressure of rapid land use changes. This region harbors variety of rare and endemic species of flora and fauna. It also has a strong bearing on regional climatic conditions. Extensive shifting cultivation, compounded by increasing population pressure and demands for agriculture land are the prime drivers in addition to other proximate drivers of deforestation. It is therefore of prime concern to analyse forest cover changes in the region, assess rate of change and extent and to identify the areas, which show repetitive changes. We analyzed forest cover maps from six temporal datasets based on satellite data interpretation, converted to geospatial database since 1972 till 1999. The states of Meghalaya, Nagaland and Tripura show highest changes in forest cover. Arunachal Pradesh shows least dynamic areas and maintains a good forest cover owing to its topographical inaccessibility in some areas. The present study reports the forest cover changes in the region using geospatial analysis and analyse them to devise proper management strategies.     

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.     

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.     

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.     

Acid soil indicators in forest soils of the Cherry River Watershed, West Virginia

Declining forest health has been observed during the past several decades in several areas of the eastern USA, and some of this decline is attributed to acid deposition. Decreases in soil pH and increases in soil acidity are indicators of potential impacts on tree growth due to acid inputs and Al toxicity. The Cherry River watershed, which lies within the Monongahela National Forest in West Virginia, has some of the highest rates of acid deposition in Appalachia. East and West areas within the watershed, which showed differences in precipitation, stream chemistry, and vegetation composition, were compared to evaluate soil acidity conditions and to assess their degree of risk on tree growth. Thirty-one soil pits in the West area and 36 pits in the East area were dug and described, and soil samples from each horizon were analyzed for chemical parameters. In A horizons, East area soils averaged 3.7 pH with 9.4 cmol_c kg^???1 of acidity compared to pH 4.0 and 6.2 cmol_c kg^???1 of acidity in West area soils. Extractable cations (Ca, Mg, and Al) were significantly higher in the A, transition, and upper B horizons of East versus West soils. However, even with differences in cation concentrations, Ca/Al molar ratios were similar for East and West soils. For both sites using the Ca/Al ratio, a 50% risk of impaired tree growth was found for A horizons, while a 75% risk was found for deeper horizons. Low concentrations of base cations and high extractable Al in these soils translate into a high degree of risk for forest regeneration and tree growth after conventional tree harvesting.     

Risk assessment and distribution of soil Pb in Guangdong, China

In this study, the spatial distributions of soil lead (Pb) concentration in three horizontal soils in Guangdong, China, were surveyed and analyzed using geostatistics and geography information systems (GIS). Findings indicated that the Pb geometric mean concentration of 23.3 mg/kg in surface soils was found to be higher than those in global soils, which ranged from 2.3–235 mg/kg. In addition, the Pb geometric mean concentrations from A- to C-horizon were found to be 23.3, 27.2, and 28.6 mg/kg, respectively. The classification of a soil Pb environmental risk in an area was likewise presented based on the different levels of environmental quality of Pb and was done by GIS technology. Accordingly, there is a higher local concentration of Pb in the surrounding areas of Guangzhou where there is higher population density and in the north of Guangdong, which is a historic mining area. The results obtained by the environmental risk assessment reveal that about 46% of total surveyed area was above the background value, that is, 2.7% of the total area was at risk of pollution.