Study on the Effect of Variation of Flow in Sequencing Batch Reactor Using PCA and ANOVA
Govindasamy Vijayan, R. Saravanane, T. Sundararajan
Abstract
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Govindasamy Vijayan, R. Saravanane, T. Sundararajan
Abstract
Open-access reader
Wastewater treatment using Sequencing Batch Reactor (SBR) technology is one of the state-of-the art wastewater management systems.In this technology equalization, biological treatment and secondary clarification are performed in a single reactor in a time control sequence.SBR system is idler for the areas where the available land is limited, since it operates in less space and very cost effective even on small scales.The control of the operational parameters during the process of biological wastewater treatment is often complicated due to the dynamic change in the composition and characteristics of the raw wastewater, flow rates and other parameters influencing the complex nature of the treatment process and the process in SBR has a unique cyclic batch operation.The performance of the SBR was studied using pilot and real plant at Puducherry.The parameters considered in this study are flow, Mixed Liquor Suspended Solids (MLSS), pH, temperature, influent and effluent of Total Suspended Solids (TSS), Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD).As a part of the study, the effect of constant flow and varying flow on the organic loading of the influent TSS, BOD and COD and their influence on the organic load of the effluent parameters were examined to identify the level of significance of the parameters in relation to the flow.The impact of flow on other parameters was also examined.The experimental data obtained from pilot and real plants were analyzed using multi variate statistical analyses like correlation analysis, Principal Component Analysis (PCA) and Analysis of variance (ANOVA).The statistical analysis revealed that constant flow had no significant role and the influent parameters alone had the critical role, whereas varying flow as well as the influent parameters had the significant role on the performance of SBR.
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Wastewater treatment using Sequencing Batch Reactor (SBR) technology is one of the state-of-the art wastewater management systems.In this technology equalization, biological treatment and secondary clarification are performed in a single reactor in a time control sequence.SBR system is idler for the areas where the available land is limited, since it operates in less space and very cost effective even on small scales.The control of the operational parameters during the process of biological wastewater treatment is often complicated due to the dynamic change in the composition and characteristics of the raw wastewater, flow rates and other parameters influencing the complex nature of the treatment process and the process in SBR has a unique cyclic batch operation.The performance of the SBR was studied using pilot and real plant at Puducherry.The parameters considered in this study are flow, Mixed Liquor Suspended Solids (MLSS), pH, temperature, influent and effluent of Total Suspended Solids (TSS), Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD).As a part of the study, the effect of constant flow and varying flow on the organic loading of the influent TSS, BOD and COD and their influence on the organic load of the effluent parameters were examined to identify the level of significance of the parameters in relation to the flow.The impact of flow on other parameters was also examined.The experimental data obtained from pilot and real plants were analyzed using multi variate statistical analyses like correlation analysis, Principal Component Analysis (PCA) and Analysis of variance (ANOVA).The statistical analysis revealed that constant flow had no significant role and the influent parameters alone had the critical role, whereas varying flow as well as the influent parameters had the significant role on the performance of SBR.
Key concepts: Analysis of variance, Variation (astronomy), Repeated measures design, Sequencing batch reactor, Statistics, Flow (mathematics), Mathematics, Environmental science