Prediction of Mass and Volumetric Flows in a Full-Scale Industrial Waste Treatment Plant

Abstract

In this paper a set of mathematical tools are developed to predict mass and volumetric flows in waste treatment systems (WTS). The proposed approach is constructed upon a set of data reconciliation methods, influent fractionation routines and process simulations models (and model interfaces) to balance, analyze, reproduce and forecast the behavior of different compounds within treatment facilities. The proposed approach is tested on full-scale data collected after two five-week measuring campaigns at the largest industrial WTS in Northern Europe. Plant-wide overall mass balance reveals that that: 1) 32% of the incoming COD is recovered as biogas, 2) 23% and 65% of COD and N are biologically removed and leave the system via the gas phase, 3) 32 % and 33% of COD and N are stored in the activated sludge  4) > 70% of P, Ca, Mg and Al are accumulated in the bio-solids stream as precipitates and 5) > 70% of Na, K and S remain soluble in the effluent. This study also shows that the proposed approach is capable to reproduce main streams neutralization, volatile fatty acid production, particulate removal and nitrate denitrification in the anaerobic water line (buffer tank, primary clarifier, pre-acidification tank). It also predicts organics transformation into methane in the anaerobic granular sludge reactor. Lastly, it is possible to describe biological and chemical N and P removal processes in the activated sludge and the quality of bio-solids after inactivation/dewatering (reject water /cake). The average deviation between measurements and simulations is 10.5%. This is the first study where both tracking and prediction of multiple compounds in a large industrial site is done at this level of detail.

Keywords: Data reconciliation, Mass balancing, Model simulation, Process systems engineering, Scenario analysis, waste treatment