Additional danger of arsenic exposure through inhalation from burning of cow dung cakes laced with arsenic as a fuel in arsenic affected villages in Ganga-Meghna-Brahmaputra plain

In arsenic contaminated areas of the Ganga-Meghna-Brahmaputra (GMB) plain (area 569,749 sq. km; population over 500 million) where traditionally cow dung cake is used as a fuel in unventilated ovens for cooking purposes, people are simply exposed to 1859.2 ng arsenic per day through direct inhalation, of which 464.8 ng could be absorbed in respiratory tract.     

Water-induced erosion potentiality and vulnerability assessment in Kangsabati river basin,eastern India

Environment, Development and Sustainability - The large-scale water-induced erosion is one of the most determining elements on land degradation in subtropical monsoon-dominated region. From this...     

Fresh water blue green algae from three agro-climatic zones of Uttar Pradesh, India: distribution pattern with seasonal variation

The paper deals with 45 species of 21 genera of fresh water blue green algae (BGA) from three different agro-climatic zones of Uttar Pradesh. Samples were collected from different habitats varying in physico-chemical properties. Out of 45 species, 13 species belonged to order Chroococcales, 31 to order Nostocales, while only 1 species belonged to order Stigonimatales i.e. Fischerella mucicola. The physico-chemical parameters like pH, temperature, dissolved oxygen, electrical conductivity, nitrate, nitrite and rainfall play an important role in the periodicity of BGA. A positive correlation was found between dissolved oxygen (DO) of different ponds and species diversity, except in the case of western region of Uttar Pradesh (Farukhabad and Mahoba districts) where a positive correlation was found in electrical conductivity and total dissolved solids.     

Physico-chemical characteristics and pollution level of Lake Nainital (U.P., India): role of macrophytes and phytoplankton in biomonitoring and phytoremediation of toxic metal ions

Lake Nainital is the sole source of drinking water for the local people and even to majority of tourists. In background of lake utility and its importance at national level, such study is essential which is focused on toxic metal pollution and current nutrient status of the lake and their magnification by algae and macrophytes. Study has shown that lake water is rich in nutrients which supports growth of many aquatic macrophytes and algal blooms. Besides, water is contaminated with metals like Cr, Cu, Fe, Mn, Ni, Pb and Zn. Concentration of some of them like Fe, Pb and Ni were higher than the recommended maximum permissible limits. Concentration of these metals were also found high in lake sediments. The level of metals amongst various components of lake varied considerably in different season. Plants and algae growing therein accumulated appreciable amount of metals and water roots of Salix being more efficient than others. High metal removing potential of these plants may be significant for biomonitoring studies and could be a useful phytoremediation technology to restore water quality by harvesting submerged and floating biomass inhabiting littoral zone of the lake.     

Removal of arsenic from drinking water by chemical precipitation--a modeling and simulation study of the physical-chemical processes.

A dynamic mathematical model was developed for removal of arsenic from drinking water by chemical coagulation-precipitation and was validated experimentally in a bench-scale set-up. While examining arsenic removal efficiency of the scheme under different operating conditions, coagulant dose, pH and degree of oxidation were found to have pronounced impact. Removal efficiency of 91-92% was achieved for synthetic feed water spiked with 1 mg/L arsenic and pre-oxidized by potassium permanganate at optimum pH and coagulant dose. Model predictions corroborated well with the experimental findings (the overall correlation coefficient being 0.9895) indicating the capability of the model in predicting performance of such a treatment plant under different operating conditions. Menu-driven, user-friendly Visual Basic software developed in the study will be very handy in quick performance analysis. The simulation is expected to be very useful in full-scale design and operation of the treatment plants for removal of arsenic from drinking water.     

Toxicity assessment of heavy metals with Nostoc muscorum L

Heavy metals in aquatic ecosystem (Mn, Ni, Zn, Cu) were tested for their toxicity against Nostoc muscorum L., a common fresh water phytoplankton, with respect to chlorophyll, protein, total carbohydrate and starch contents along with growth (OD). Mn showed stimulatory effect up to 1.5 ppm for all the observed parameters. However, Ni, Zn and Cu (0.1, 0.2, 0.3, 0.4 and 0.5 ppm) showed adverse effects even at 0.1 ppm. Chlorophyll was most sensitive parameter followed by carbohydrate, protein and starch. Ni was most toxic to N. muscorum followed by Cu and Zn. The IC50 for Ni was 0.1 ppm for growth, chlorophyll and protein, while total carbohydrate and starch showed IC50 at 0.3 and 0.4 ppm, respectively. The IC50 for Cu was recorded at 0.2 ppm for all the parameters. Zn showed IC50 at 0.3 ppm for growth, chlorophyll, protein and starch at 0.4 ppm for carbohydrate. This study can be applied as bioassay using cyanobacteria for toxicity assessment of various industrial wastes in aquatic ecosystem.     

Estimation of land surface temperature using different retrieval methods for studying the spatiotemporal variations of surface urban heat and cold islands in Indian Punjab

Spatial patterns of land surface temperature (LST), surface urban heat island (SUHI), surface urban cold island (SUCI), and their seasonal variations during January (winter) and September (summer) were analyzed over the three cities of Indian Punjab (Balachaur, Ludhiana and Bathinda) using Landsat 5, 7 and 8 satellite data of the years 1991, 2001, 2011, and 2018. Urban hot spots and Urban Thermal Field Variance Index (UTFVI) were used to measure the ecological environment of these cities. Land surface temperature was retrieved from Landsat satellite data using Plank equation, mono-window algorithm (MWA), single-channel algorithm (SCA), and radiative transfer equation. The LST derived using these algorithms was validated with MODIS-LST product. The relationship between LST derived from Landsat 5, 7 and 8 using the four methods and MODIS-LST product was higher with the SCA algorithm (R²?>?0.75). Land surface temperature was significantly positively correlated with built-up but significantly negatively correlated with vegetation. The surface urban heat intensity was higher during September than January, and it was higher in Ludhiana followed by Bathinda and Balachaur, irrespective of the season. Besides built-up area and population density, soil moisture availability in surrounding rural areas has significant impact on increasing surface urban heat intensity during September than January. The SUCIs were formed in the center of Bathinda city during January 1991, but these were in Ludhiana and Balachaur cities during January 2011. The most critical areas for ecological environment based on UTFVI were identified and the critical UTFVI values (>?0.020) were highest in Bathinda city followed by Balachaur and Ludhiana cities. These results suggest that SUHIs and SUCIs are influenced by seasons and the mitigating plans to counteract the overheating of urban areas should be formulated taking into account soil moisture availability in surrounding rural areas, landscape pattern, seasonal variations, local climatic conditions, urban growth, and development plan etc.