Environmental Engineering Research

  • 제19권1호
  • /
  • Pages.31-36
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  • 2014
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  • 1226-1025(pISSN)
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  • 2005-968X(eISSN)
대한환경공학회 (Korean Society of Environmental Engineers)
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A Study on the Influence of a Sewage Treatment Plant's Operational Parameters using the Multiple Regression Analysis Model

  • Lee, Seung-Pil (Environmental Technology Institute, Samchully Enbio Co., Ltd.) ;
  • Min, Sang-Yun (Environmental Technology Institute, Samchully Enbio Co., Ltd.) ;
  • Kim, Jin-Sik (Environmental Technology Institute, Samchully Enbio Co., Ltd.) ;
  • Park, Jong-Un (Environmental Technology Institute, Samchully Enbio Co., Ltd.) ;
  • Kim, Man-Soo (Environmental Technology Institute, Samchully Enbio Co., Ltd.)
  • 투고 : 2013.06.03
  • 심사 : 2013.10.23
  • 발행 : 2014.03.30
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초록

In this study, the influence of the control and operational parameters within a sewage treatment plant were reviewed by performing multiple regression analysis on the effluent quality of the sewage treatment. The data used for this review are based on the actual data from a sewage treatment plant using the media process within the year 2012. The prediction models of chemical oxygen demand ($COD_{Mn}$) and total nitrogen (T-N) within the effluent of the 2nd settling tank based on the multiple regression analysis yielded the prediction accuracy measurements of 0.93 and 0.84, respectively; and it was concluded that the model was accurately predicting the variances of the actual observed values. If the data on the energy spent on each operating condition can be collected, then the operating parameter that conserves energy without violating the effluent quality standards of COD and T-N can be determined using the regression model and the standardized regression coefficients. These results can provide appropriate operation guidelines to conserve energy to the operators at sewage treatment plants that consume a lot of energy.

키워드

참고문헌

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피인용 문헌

  1. Development of multiple linear regression model for biochemical oxygen demand (BOD) removal efficiency of different sewage treatment technologies in Delhi, India vol.6, pp.2, 2014, https://doi.org/10.1007/s40899-020-00377-9
  2. Study of energy consumption in a wastewater treatment plant using logistic regression vol.664, pp.1, 2014, https://doi.org/10.1088/1755-1315/664/1/012054