Abstract
In this paper a set of mathematical tools are developed and assembled
together to assess and 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. Results show that the proposed
reconciliation methodology based on the definition of the identity
matrix, data curation, the estimation of missing fluxes and the
calculation of Lagrange multipliers allowed to close flow and COD, N, P,
S and multiple metals (Na, K, Ca, Mg and Al) mass balances. Plant-wide
overall mass balance reveals that that: 1) 32% of the incoming COD is
recovered mostly as methane, 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 and leave the plant via
effluent. Plant measurements were allocated into the model states
describing soluble/particulate and organic/inorganic loads arriving to
the WTS under study. The average deviation between computer simulations
and the result of the measuring campaign is 10.5%. 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 correctly predicts
organics transformation into biogas 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). A
scenario analysis is included showing the potential use of the presented
tools under dynamic conditions. This is the first study where both
tracking and prediction of multiple compounds in large industrial sites
has been done at this level of detail. The tool resulting from this
study can serve as starting point for a variety of applications, for
instance: holistic evaluation of retrofitting scenarios, advanced
plant-wide control strategie and environmental assessment.
| Original language | English |
|---|---|
| Article number | 136774 |
| Journal | Chemical Engineering Journal |
| Volume | 445 |
| Number of pages | 15 |
| ISSN | 1385-8947 |
| DOIs | |
| Publication status | Published - 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Data reconciliation
- Mass balancing
- Model simulation
- Process systems engineering
- Scenario analysis
- Waste treatment
Fingerprint
Dive into the research topics of 'Prediction of mass and volumetric flows in a full-scale industrial waste treatment plant'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver