TY - JOUR
T1 - Digital twinning to advance effluent water treatment for pulp and paper mills: A data-driven approach for process optimization
AU - Iqbal, Fatima
AU - Naeijian, Fatemeh
AU - Page, Christopher
AU - Fu, George Yuzhu
AU - Cubas, Francisco
AU - Rowles, Lewis S.
PY - 2026/1/15
Y1 - 2026/1/15
N2 - The pulp and paper industry is the third largest freshwater consumer and faces pressure to minimize water usage and environmental impact. Aerated stabilization basins (ASBs) play a crucial role in treating their wastewater, yet existing open-source models often fail to accurately predict treatment efficiency across varying conditions. This study addresses this gap by advancing ASB modeling for ultimate oxygen demand prediction. Specifically, we improved accuracy with variable temperature corrections and incorporating uncertainty to capture the variability in outputs. The models demonstrated strong predictive performance for ultimate oxygen demand (mainly carbonaceous and nitrogenous biochemical oxygen demand) with R2 values ranging from 0.75 to 0.83 across various temperature range. The estimation of total suspended solids showed greater variability, highlighting a key area for model improvement. Overall, integrating variable temperature correction significantly enhanced model performance, particularly for microbial activity and organic matter degradation. The study also effectively modeled phosphorus dynamics (R2 = 0.741), including benthal feedback effects. A digital twin was developed by embedding the calibrated process models within an interactive simulation environment to support operator-guided evaluation of operational trade-offs under uncertainty. Analysis of hydraulic retention time and aeration rates revealed their critical roles in treatment efficiency, with performance improving above ∼2.5 d HRT and ≥4 Wm-3 aeration at 22 °C, while similar efficiency at 12 °C required >3 d HRT and ∼5 Wm-3, informing seasonal operational strategies. This research offers a validated framework for enhancing wastewater treatment efficiency, supporting regulatory compliance and environmental sustainability efforts. The study also presents valuable outcomes for managing industrial wastewater that meets current challenges and future regulations.
AB - The pulp and paper industry is the third largest freshwater consumer and faces pressure to minimize water usage and environmental impact. Aerated stabilization basins (ASBs) play a crucial role in treating their wastewater, yet existing open-source models often fail to accurately predict treatment efficiency across varying conditions. This study addresses this gap by advancing ASB modeling for ultimate oxygen demand prediction. Specifically, we improved accuracy with variable temperature corrections and incorporating uncertainty to capture the variability in outputs. The models demonstrated strong predictive performance for ultimate oxygen demand (mainly carbonaceous and nitrogenous biochemical oxygen demand) with R2 values ranging from 0.75 to 0.83 across various temperature range. The estimation of total suspended solids showed greater variability, highlighting a key area for model improvement. Overall, integrating variable temperature correction significantly enhanced model performance, particularly for microbial activity and organic matter degradation. The study also effectively modeled phosphorus dynamics (R2 = 0.741), including benthal feedback effects. A digital twin was developed by embedding the calibrated process models within an interactive simulation environment to support operator-guided evaluation of operational trade-offs under uncertainty. Analysis of hydraulic retention time and aeration rates revealed their critical roles in treatment efficiency, with performance improving above ∼2.5 d HRT and ≥4 Wm-3 aeration at 22 °C, while similar efficiency at 12 °C required >3 d HRT and ∼5 Wm-3, informing seasonal operational strategies. This research offers a validated framework for enhancing wastewater treatment efficiency, supporting regulatory compliance and environmental sustainability efforts. The study also presents valuable outcomes for managing industrial wastewater that meets current challenges and future regulations.
UR - https://doi.org/10.1016/j.jenvman.2025.128409
U2 - 10.1016/j.jenvman.2025.128409
DO - 10.1016/j.jenvman.2025.128409
M3 - Article
SN - 0301-4797
VL - 398
JO - Journal of Environmental Management
JF - Journal of Environmental Management
ER -
