Kamal Uddin Ahamad

Water turbidity sensing using a smartphone

This paper demonstrates a rapid, cost-effective and field-portable smartphone based turbidimeter that measures turbidity of water samples collected from different natural water resources and in drinking water. The working of the designed sensor is based on a Mie-scattering principle where suspended micro (μ-) particles in water medium scatter a strong light signal along the normal direction of the incoming light signal, which can be detected by an infra-red (IR) proximity sensor embedded in the smartphone. Two freely available android applications were used to measure the irradiance of the scattered flux and analyse the turbidity of the medium. With the designed sensor, water turbidity variation as low as 0.1 NTU can be measured accurately in the turbidity value ranging from 0 to 400 NTU. The sensor responses for these ranges of turbid media are found to be linear. A high repeatability in the sensor characteristics is also been observed. The optics design involved for the development of the proposed smartphone turbidimeter is simple and is robust in operation. The designed sensing technique could emerge as a truly portable, user-friendly and inexpensive turbidity sensing tool that would be useful for different in-field applications.

Surface Water Quality Modeling by Regression Analysis and Artificial Neural Network

The major objective of the present study is to develop water quality prediction models after evaluation of water quality to predict water pollution of two lakes situated inside Tezpur University. The water quality parameters were analyzed using linear regression analysis and artificial neural network to predict the water quality. Correlation studies suggested a highly positive correlation between TS with turbidity and EC for both lakes. Modeling of TS and BOD by regression analysis suggests a good correlation between actual and predicted TS but a very poor correlation between actual and predicted BOD. Modeling of TS and BOD by ANN shows a very good correlation between the actual and predicted values for both TS and BOD for both the lakes studied. The error between the experimental and estimated ANN model is less than regression model, suggesting suitability of ANN model for prediction of studied parameters.

Removal of Fluoride from Groundwater by Adsorption onto Brick Powder–Alum–Calcium-Infused Adsorbent

Removal of fluoride from groundwater onto BAC—an adsorbent made by infusing brick powder, alum, and calcium chloride has been investigated in the present study. Individually, the three materials can take up fluoride, but in very low concentration and therefore these have been selected and fused together to enhance the overall fluoride removal capacity. The three materials were taken in the ratio of 1:1:1, fused together with 20% conc. HCl, oven dried at 105 °C for 24 h. The material was then crushed and powder and was kept in airtight container. For initial fluoride concentration of 4 mg/L, an equilibrium time of 120 min. was observed at dose of 7.5 g/L of BAC at 280 rpm shaking speed. Pseudo-second-order kinetic model fits experimental data very well suggested the applicability of the same. The results of the isotherm studies showed that fluoride removal by BAC followed the Freundlich isotherm model.

Water Quality Evaluation in a Rural Stretch of Tezpur, Assam (India) Using Water Quality Index and Correlation Matrix

Groundwater resources have a major role in ensuring livelihood security across the world, especially in economies that depends on agriculture. In India it is the major source of drinking water in both urban and rural and its importance cannot be over emphasized. It accounts for more than 85 % of the rural domestic water needs, and 50 % of the urban water needs (Ganeshkumar and Jaideep 2011). With an estimated use of 230 km3 of groundwater every year, i.e. more than a quarter of the global level, India is the largest user of groundwater in the world. At present apart from depletion of groundwater level, India is also facing problems regarding the increments of pollutant concentration present in it. In the North Eastern region of India, natural springs and dug wells are the only cost effective viable means of fulfilling the domestic needs for present population. Information on groundwater quality of northeast India is scanty (Suryawanshi et al. 2004). It has been reported that the concentration of fluoride (F−), and iron [Fe(II)] in the groundwater is much higher than the permissible limits of drinking water at different areas of Assam (Sushella 2001). Fluoride in the groundwater of Assam has been reported in the range of 5–23 mg/L (Meenakshi and Maheshwari 2006) and iron in the range of 1–25 mg/L (Das et al. 2003; Mahanta et al. 2004). The permissible limit in drinking water is 1–1.5 mg/L for fluoride and 0.3 mg/L for iron (IS 10500 1991; WHO 1993). The iron present in the groundwater causes visible colouration to the water, but fluoride doesn’t impart any colour to the water. Therefore the quality of drinking water is of vital importance for human being, though most consumers are unaware of the various pollutants present in the groundwater.

Breakthrough studies with mono-, binary- and ternary-ion systems comprised of Fe(II), F− and As(III) using river sand packed columns for groundwater treatment

Groundwater in Assam, India, contains excessive amounts of arsenic (As(III)), fluoride (F(-)) and iron (Fe(II)). The rural and semi-urban population of Assam uses indigenous iron filters fabricated using processed sand (PS) as one of the chief constituents to reduce Fe(II) concentration; however, no efforts have been made to reduce As(III) or F(-) concentrations before use. The present work is directed towards assessing the potential of PS for removal of these ions from mono-, binary- and ternary-ion systems through continuous mode column studies. Synthetic water samples containing fixed concentration of ions were prepared using deionized water. The observed order of breakthrough of ions was: As(III) followed by Fe(II) and F(-) followed by Fe(II) in the case of the binary ion systems of Fe(II) + As(III) and Fe(II) + F(-). The throughput volume for As(III) in the (Fe(II) + As(III)) system and for F(-) in the (Fe(II) + F(-)) system is termed the critical breakthrough throughput volume. In the ternary ion system (Fe(II) + As(III) + F(-)), the order of breakthrough of ions observed was F(-), then As(III) and then Fe(II) and hence the throughput volume F(-) is termed the critical breakthrough throughput volume. Results of column studies also indicate the impact on the uptake of the selected ion by the presence of the other ion present in the binary- and ternary-ion systems.