Industrial effluent Management is one of the major environmental concerns, especially in developing countries under rapid industrialization. The grossly polluting industries recognized by Central Pollution Control Board (CPCB), such as Pulp and Paper Industries, poses even bigger environmental threats, owing to quantity and quality of effluent generated. This paper aimed at analyzing effluent management practices in pulp and paper industries in India, and asses the performance variability of a paper mill effluent treatment plant (ETP), as a Case Study. Majority of pulp and paper industries found to still employ conventional methods of effluent treatment. Although, most of the parameters of treated effluent are commonly reported within CPCB’s permissible discharge limits, the treatment is usually cost and energy intensive, and produce high amount of solid residuals as sludge. For the case study paper mill ETP, the treatment efficiencies of the ETP units were analyzed under variable inlet pH, TSS, TDS, BOD and COD loads. The pH variations in the range of 6.5 to 9 had little effect of COD or TSS removal, however removal efficiencies were higher for larger inlet COD or TSS loads. The results of the study could be helpful in optimizing operation of the existing ETPs, as well as, guiding on upgrading ETPs with more cost-effective and efficient units.
A deep learning-based approach for performance assessment and prediction: A case study of pulp and paper industries
