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|contributor.author||Mishra, P C||-|
|contributor.author||Patel, R K (Guide)||-|
|identifier.citation||Some Aspects of the Quality of Water in and around Rourkela, Thesis submitted in partial fulfillment of the requirements for the award of the Doctor of Philosophy in Chemistry, Submitted to National Institute of Technology, Rourkela||en|
|description||Copyright for the thesis belongs to NIT Rourkela||en|
|description.abstract||In recent years the newer environmental issues regarding hazardous waste,global climate change, stratospheric ozone depletion, groundwater contamination,disaster mitigation and removal of pollutant have become the focus of environmental
attention. Though all the segments of environment are being polluted in various ways,
the study of water pollution is selected as it is not an ordinary liquid but is the elixir of
life. Moreover, water is the most common liquid but it is also one of the most unusual because of its few unique property. Rourkela is one of the most important industrial complex in the state of Orissa which has Integrated Rourkela Steel Plant, a number of sponge iron industries, cement manufacturing unit, chemicals,explosives, ceramics and distillery units and large number of small and medium industries.
Keeping the above in view, the study area has rightly been selected. The study area experiences a seasonal climate and broadly divided into three seasons as Winter (November to February), Summer (March to June) and Rainy (July to October). The minimum and maximum air temperature was 6.00C and 470C in December and May respectively. The rainfall in the monsoon period (Rainy season) accounts for more
than 70 % of the total annual rainfall of the area. The average relative humidity
ranged from 35 % (January) to 85 % (July).
The analytical data of various physico-chemical parameters indicates that some parameters like pH, Hardness, Calcium, Magnesium, Electrical Conductivity,DO, Chloride, Total Alkalinity, Iron are found to be excess than the prescribed limit in some groundwater samples of the study areas. The WQI value indicates that water
samples of some areas are quite unfit for drinking purpose because of high concentration of Iron. The water samples of down stream of river Brahmani were found to be more polluted than the up stream. The WQI value of both down stream and up stream indicate that the water is not fit for drinking without any treatment and
disinfection. However, the samples of tap water were found to be good for drinking purpose. Hence the Water Treatment Plants are efficient. The physico-chemical parameters of periphery area are also analyzed. From the data it is observed that except some areas of Sundergarh Town, the water quality of other areas are better
than the water quality of Rourkela.
The pesticide contamination is becoming a great problem in water bodies especially in the underground water. It is reported by several agencies that the underground water of those areas, which are developed in agriculture, contains pesticides. The adsorption effectiveness of two different low cost adsorbent Sal wood (Shorea robusta, family- Diptero carpaceae) charcoal and sand along with activated charcoal to remove the pesticides from water has been investigated. It was observed
that the efficiency for removal of pesticide is more in activated charcoal with 94.6%
followed by silica 90%. The efficiency of wood charcoal is moderately high with 87.6 %, which can be regenerated after the treatment with dilute HNO3 which decomposes the pesticide.
The menace of pollution is necessary day by day. In some places the problem of water pollution is very high and in some places it is approaching towards the permissible limit. To assess the load on the water quality in future based on the
current trend, forecasting is highly required. Fixed techniques are used for prediction
of future time series data but subsequently adoptive techniques are used to forecast
improved future data. These techniques are essentially based on ANN and fuzzy logic
techniques. The limitation of these techniques are that it perform poorly when the
input data set available is less and when there is abrupt change in the input data set.
The different models of ANN were proposed for the prediction of Water Quality
Index of the groundwater of different areas of Rourkela. Out of these model Data
Farming Linked Artificial Neural Network (DFL-ANN) model was found to be most efficient in predicting the quality of water in future.||en|
|publisher||National Institute of Technology, Rourkela||en|
|subject||Potable surface water||en|
|subject||Volatile Organic Compounds||en|
|title||Some Aspects of the Quality of Water in and around Rourkela||en|
|Appears in Collections:||Thesis (Doctor of Philosophy)|
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