Title: Multivariate statistical analysis between COD and BOD of sugar mill effluent
Abstract:Sugar industry is an agro based seasonal industry. India is the second largest producer of sugar in the world. The effluents generated from this industry contain considerable amounts of organic and in...Sugar industry is an agro based seasonal industry. India is the second largest producer of sugar in the world. The effluents generated from this industry contain considerable amounts of organic and inorganic chemical components such as fibers, cellulosic wastes, wood dust, chlorine compounds, carbonates and bicarbonates. Direct discharge of untreated effluents from this industry may have profound effect on water and makes the environment unfit for aquatic life. In the present study, waste water samples from sugar industry were collected and analyzed for biological oxygen demand (BOD) and chemical oxygen demand (COD). The wastes generated from sugar mill are highly organic in nature due to high COD and BOD. Correlation between COD and BOD of industrial effluent would be highly advantageous because chemical composition (COD and BOD) is very important deciding factor for the treatment process. Therefore for this investigation, the correlation between COD and BOD was chosen. COD and BOD do not follow a linear relationship. Polynomial equations were formulated using graphical and Newton’s divided difference methods. The errors estimated were very low in the case of fourth order polynomial as compared to the value calculated from Newton’s divided difference method. The range of COD and BOD were 189 mg/l and 123 mg/l respectively. The variance and standard deviation values for COD were 556.96 and 23.6. The corresponding values for BOD were 2798.41 and 52.9 respectively. The standard errors for COD and BOD were 9.63 and 21.59 respectively. The correlation coefficient (r = - 0.940) show negative relation which indicates that the increase in COD will lead to decrease in BOD. The linear and exponential regression equations were found out.Read More
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 6
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot