Cryptosporidium Oocysts in Drinking Water Supply of Chennai City,Southern India

Cryptosporidium is an enteric parasitic protozoan capable of causing chronic diarrhea. One of the most common modes of transmission is through faeces‐contaminated water. This study determines the distribution of Cryptosporidium oocysts for the first time in Chennai City's drinking water supply. 199 drinking water samples were collected from ten zones of the city. In the water samples Cryptosporidium, a common pathogenic protozoan of the gastrointestinal tract, has been analyzed physico chemically as well as microbiologically for heterotrophic organisms and total coliforms (TC). The studies revealed that three zones of the city were highly contaminated with coliforms and parasitic protozoa. A statistical analysis was done to find any correlation between heterotrophic organisms, total coliforms, and oocysts. Even though a positive correlation exists between oocysts and bacteriological parameters, a regression equation shows that heterotrophic plate count (HPC) and total coliforms were only 20% responsible for the presence of oocysts. The level of Cryptosporidium oocysts isolated from the water samples may present a public health hazard although no major outbreaks have so far been reported in Chennai City. Routine surveillance of water quality throughout the city is needed to curb the pollutants.     

Groundwater quality and its suitability for drinking and agricultural use in Chithar River Basin, Tamil Nadu, India

Hydrochemistry of groundwater in Chithar Basin, Tamil Nadu, India was used to assess the quality of groundwater for determining its suitability for drinking and agricultural purposes. Physical and chemical parameters of groundwater such as electrical conductivity, pH, total dissolved solids (TDS), Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^–, HCO₃^–, CO₃^2–, SO₄^2–, NO^–₃, F^–, B^– and SiO₂ were determined. Concentrations of the chemical constituents in groundwater vary spatially and temporarily. Interpretation of analytical data shows that mixed Ca–Mg–Cl, Ca–Cl and Na–Cl are the dominant hydrochemical facies in the study area. Alkali earths (Ca²⁺, Mg²⁺) and strong acids (Cl^–, SO₄^2–) are slightly dominating over alkalis (Na⁺, K⁺) and weak acids (HCO₃^–, CO₃^2–). The abundance of the major ions is as follows: Na⁺ Ca²⁺ Mg²⁺ > K⁺ = Cl^– > HCO₃^–> SO₄^2– > NO₃^– > CO₃^2– . Groundwater in the area is generally hard, fresh to brackish, high to very high saline and low alkaline in nature. High total hardness and TDS in a few places identify the unsuitability of groundwater for drinking and irrigation. Such areas require special care to provide adequate drainage and introduce alternative salt tolerance cropping. Fluoride and boron are within the permissible limits for human consumption and crops as per the international standards.     

Controlling NOx Emission of Crude Rice Bran Oil Blend for Sustainable Environment

The main objective of this work is to investigate the factors influencing the NOx control of a stationary diesel engine fuelled with crude rice bran oil blend with lesser effect on smoke density and brake thermal efficiency (BTE). Fuel injection timing, percentage of EGR, and fuel injection pressure are chosen as the factors for the objective and NOx emission, smoke density, and BTE are considered as the response variables. To critically analyze the effects of the chosen factors on the objective three levels were chosen in each factor and the experiments were designed by following the design of experiments method. Taguchi's L₉ orthogonal array was used to conduct the tests with different combination of factor levels. Through analysis of variance (ANOVA) method, the most influencing factors and also the significance of each factor affecting each response variable were found out. Response graph was drawn for each response variable to determine the optimum combination of factor levels in achieving the objective and the obtained combination was confirmed experimentally.     

Decision of threshold values for extraction of turbidity for inland wetland using IRS P6 LISS III data

Wetland is a kind of natural resource with fast dynamic changes. Around 50% of the earth’s wetlands are estimated to have already disappeared worldwide over the last hundred years through conversion to industrial, agricultural, and residential developments. It is important for wetland protection and management to accurately map the wetland distribution by remote sensing and GIS. A study of the water turbidity and water quality of the wetland is essential to assess the fitness of the water for various purposes—irrigation, drinking, other domestic use, and industry. In the present study, an attempt has been made to know the inland wetland of Salem taluk of Salem district and to monitor changes in turbidity conditions for post-monsoon and pre-monsoon seasons. With the IRS P6 LISS III satellite image, indices images were generated for the extraction of water spread boundary. An automatic determination method of the threshold was examined to produce masks for the extraction of turbidity, and a turbidity map was generated which classifies turbidity into high, medium, and low. From the analysis, it has been observed that the inland wetlands of post-monsoon constitute 489 ha of the study area, of which 21.3% is subjected to high turbidity. Pre-monsoon spread constitutes 362.81 ha, of which 15.7% is subjected to high turbidity in pre-monsoon. Thus, this study highlights the usefulness of remotely sensed data for wetland mapping, seasonal monitoring, and characterization. The result indicates that turbidity conditions are moderate and low in pre-monsoon and moderate in post-monsoon seasons.     

Remote Sensing and GIS Tool to Detect Hydrocarbon Prospect in Nagapattinam Sub Basin, India

Cauvery Basin is one of the pericratonic rift basins located in the east coast of Tamilnadu. The rifting has resulted in a series of horsts and grabens. The present study uses a new technique which was devised with the help of GIS by analyzing the surface lineaments and subsurface linearities effectively. In this present study, a satellite image based analysis was conducted for extracting surface lineaments, and for the subsurface linearities, the basement linearities were extracted from seismic, magnetic, and gravity data. An orientation analysis of these surface and subsurface linear features was performed to detect the basic structural grains of the study area. The correlation between these structural grains and subsurface oil and gas traps was performed to understand the connectivity to the reservoirs. This article discusses in detail about the same and the importance of using surface and subsurface lineament analyses for delineating hydrocarbon reservoirs in the Nagapattinam Sub-Basin of Cauvery Basin.     

Risk of Fluoride-Rich Groundwater on Human Health: Remediation Through Managed Aquifer Recharge in a Hard Rock Terrain,South India

The main objective of the present research was to examine the risk of fluoride-rich groundwater in the Shanmuganadhi River basin, south India on human health. The non-carcinogenic risks were estimated into two classes: (1) risks associated with oral intake of water and (2) risks associated with dermal contact. Hazard Quotient for oral intake and dermal contact was separately calculated for adult men, adult women and children from the geochemical results of 61 representative samples collected from the wells constructed in hard rock aquifers during the post- (January-2018) and pre-monsoon (May-2018) seasons. The collected samples were analyzed immediately after the field work for all the major ions and fluoride. Finally, total hazard index was calculated for adults (men and women) and children to evaluate the risk. It directed that 41%, 49% and 74% of post-monsoon samples and 30%, 43% and 62% of pre-monsoon samples possessed a non-carcinogenic risk for men, women and children, respectively. Because the basin falls in the drought-prone region, the water supply for drinking and cultivation are commonly based on groundwater resources. The study revealed that the minerals such as apatite, fluorite, biotite and pyroxene in the hornblende–biotite gneiss formation contribute fluoride ions to the groundwater system due to water–rock interaction mechanism. The Durov diagram depicted that dissolution of silicate minerals and cation exchange are the foremost hydrogeochemical activities, which decide the overall chemical composition of groundwater in this region. The ionic concentrations including fluoride increased with respect to depth of occurrence of groundwater. Escalation of the water table due to monsoon recharge and artificial recharge through a check dam decreased the total dissolved solids and fluoride ion concentration. The investigation conducted around the existing check dam at Kaldurai village highlighted that the fluoride concentration is below the allowable limit of 1.5 mg/l (WHO in World health statistics 2017: monitoring health for the SDGs, Sustainable Development Goals. World Health Organization, Geneva, 2017) in the wells closer to the check dam toward the downstream side. The concentration increased with distance, which lead the groundwater unsuitable for consumption. Therefore, it is recommended to implement the managed aquifer recharge using check dams in the other parts of the basin to enrich the quantity and applicability of groundwater.

     

Microbial status in seawater and coastal sediments during pre- and post-tsunami periods in the Bay of Bengal, India

Tsunami, the natural disaster, which occurred on December 26, 2004 in the Indian Ocean, caused severe damage to mankind in the coastal areas. Total loss of life and economic loss because of this disaster have been estimated by various agencies but its effect on microbial density has not been probed. With our previous results on microbial populations in four locations of the Chennai coast of the Bay of Bengal, India in the pre‐tsunami period, the change in microbial populations was studied after the tsunami at regular intervals in the same locations. Coastal sediment and seawater samples were collected from four different locations after 5–10 h and thereafter at intervals of every 7 days up to 28 days post‐tsunami. Bacteria, fungi and actinomycetes were isolated from the marine samples by serial dilution on respective media. Before the tsunami, the bacterial population was higher in seawater samples than the sediments, whereas fungi and actinomycetes were recorded only in the sediments. The microbial population remarkably increased 5–10 h post‐tsunami in all the marine samples irrespective of the location. However, it slowly declined in the subsequent days and became similar to that of the population recorded before the tsunami. The population of gram‐positive bacteria increased whereas the gram‐negative bacterial population decreased after the tsunami. Further, populations of pathogenic bacteria such as coliform and vibrios did not increase after the tsunami. It has been observed that the increase in populations of bacteria and actinomycetes even after 28 days of tsunami may be due to the introduction of foreign microorganisms that developed the ability to survive in the extreme environment by exhibiting special characteristics such as pigmentation and production of exopolysaccharides.     

Biosorption of Cr (VI), Cr (III), Pb (II) and Cd (II) from aqueous solutions by Sargassum wightii and Caulerpa racemosa algal biomass

Heavy metal pollution is one of the most important environmental problems today.Biosorption is an innovative tech-nology that employs biological materials to accumulate heavy metals from waste water through metabolic process or physicochemi-cal pathways of uptake.Even though several physical and chemical methods are available for removal of heavy metals,currently many biological materials such as bacteria,algae,yeasts and fungi have been widely used due to their good performance,low cost and large quantity of availability.The aim of the present study is to explore the biosorption of toxic heavy metals,Cr(VI),Cr(III),Pb(II) and Cd(II) by algal biomass obtained from algae Sargassum wightii(brown) and Caulerpa racemosa(green).Biosorption of algal biomass was found to be biomass concentration-and pH-dependent,while the maximal biosorption was found at pH 5.0 and with the metal concentration of 100 mg L-1.S.wightii showed the maximal metal biosorption at the biomass concentration of 25 g L-1,followed by C.racemosa with the maximal biosorption at 30 g L-1.S.wightii showed 78% biosorption of Cr(VI),Cr(III),Pb(II) and Cd(II) ions.C.racemosa exhibited 85% biosorption of Cd(II) and Cr(VI),and 50% biosorption of Cr(III) and Pb(II).The results of our study suggest that seaweed biomass can be used efficiently for     

Prioritization of subwatersheds based on quantitative morphometric analysis in lower Bhavani basin,Tamil Nadu,India using DEM and GIS techniques

Watershed prioritization is one of the most important processes in natural resource management system especially in areas of sustainable watershed development and planning. Morphometric characteristics are the viable entity to understand the hydrological behavior of the subwatershed. For prioritization of subwatershed, morphometric analysis was utilized by using the linear, areal, and relief aspects of the drainage basin. In this context, remote sensing and GIS has been proved to be an efficient tool to identify the morphological features. The Survey of India (SOI) topographical maps, satellite data IRS-LISS III, and Cartosat DEM data were utilized to understand the drainage pattern and also for prioritization of subwatershed areas. The prioritization of subwatershed has been attempted using novel and quantitative approaches based on compound parameter ranking for soil erosion. Lower compound factors were chosen as the most feasible for soil erosion. Based on the observation, eight subwatersheds with a higher degree of the slope were severely prone to soil erosion and remaining 21 subwatersheds occur in low-lying areas that can be developed as sustainable watersheds. The identified subwatershed requires immediate soil remediation and water conservation measures for efficient watershed planning and management. The proposed study might be helpful for resource planners, government agencies, private sectors, and other stake holders to take up soil conservation measures and fixation of water-harvesting structures for better decision making.     

A new ensemble-based data assimilation algorithm to improve track prediction of tropical cyclones

This paper proposes a new ensemble-based algorithm that assimilates the vertical rain structure retrieved from microwave radiometer and radar measurements in a regional weather forecast model, by employing a Bayesian framework. The goal of the study is to evaluate the capability of the proposed technique to improve track prediction of tropical cyclones that originate in the North Indian Ocean. For this purpose, the tropical cyclone Jal has been analyzed by the community mesoscale weather model, weather research and forecasting (WRF). The ensembles of prognostic variables such as perturbation potential temperature (θ, k), perturbation geopotential (?, m²/s²), meridional (U) and zonal velocities (V) and water vapor mixing ratio (q _v , kg/kg) are generated by the empirical orthogonal function technique. An over pass of the tropical rainfall-measuring mission (TRMM) satellite occurred on 06th NOV 0730 UTC over the system, and the observations from the radiometer and radar on board the satellite(1B11 data products) are inverted using a combined in-home radiometer-radar retrieval technique to estimate the vertical rain structure, namely the cloud liquid water, cloud ice, precipitation water and precipitation ice. Each ensemble is input as a possible set of initial conditions to the WRF model from 00 UTC which was marched in time till 06th NOV 0730 UTC. The above-mentioned hydrometeors from the cloud water and rain water mixing ratios are then estimated for all the ensembles. The Bayesian filter framework technique is then used to determine the conditional probabilities of all the candidates in the ensemble by comparing the retrieved hydrometeors through measured TRMM radiances with the model simulated hydrometeors. Based on the posterior probability density function, the initial conditions at 06 00 UTC are then corrected using a linear weighted average of initial ensembles for the all prognostic variables. With these weighted average initial conditions, the WRF model has been run up to 08th Nov 06 UTC and the predictions are then compared with observations and the control run. An ensemble independence study was conducted on the basis of which, an optimum of 25 ensembles is arrived at. With the optimum ensemble size, the sensitivity of prognostic variables was also analyzed. The model simulated track when compared with that obtained with the corrected set of initial conditions gives better results than the control run. The algorithm can improve track prediction up to 35 % for a 24 h forecast and up to 12 % for a 54 h forecast.