TY - JOUR
T1 - Data evaluation for wastewater treatment plants
T2 - Linear vs bilinear mass balances
AU - Le, Q. H.
AU - Carrera, P.
AU - van Loosdrecht, M. C.M.
AU - Volcke, E. I.P.
N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2025
Y1 - 2025
N2 - While nowadays a lot of measurements are conducted at wastewater treatment plants, data reliability could further be improved, e.g., through data reconciliation. This study demonstrated the added value of data reconciliation to improve data quality in a full-scale wastewater treatment plant. Also, the effect of the mass balance setting (linear and bilinear mass balances) was quantitatively evaluated, considering data sets with missing measurements and with gross errors. The improvement in the precision of the key variables was higher with bilinear mass balances (40–80 %) compared to the linear setting (0–70 %). Besides, it delivered a higher number of improved key variables, especially when flow measurements were limited (minimum improved variables of 15 and 0, respectively). Bilinear mass balances were also more efficient in gross error detection and played a crucial role in cross-validation based on flow measurements, resulting in lower incorrectly-identified gross errors. Overall, it is recommended to use bilinear mass balances.
AB - While nowadays a lot of measurements are conducted at wastewater treatment plants, data reliability could further be improved, e.g., through data reconciliation. This study demonstrated the added value of data reconciliation to improve data quality in a full-scale wastewater treatment plant. Also, the effect of the mass balance setting (linear and bilinear mass balances) was quantitatively evaluated, considering data sets with missing measurements and with gross errors. The improvement in the precision of the key variables was higher with bilinear mass balances (40–80 %) compared to the linear setting (0–70 %). Besides, it delivered a higher number of improved key variables, especially when flow measurements were limited (minimum improved variables of 15 and 0, respectively). Bilinear mass balances were also more efficient in gross error detection and played a crucial role in cross-validation based on flow measurements, resulting in lower incorrectly-identified gross errors. Overall, it is recommended to use bilinear mass balances.
KW - Data reconciliation
KW - Gross error detection
KW - Mass balances
KW - Wastewater treatment
UR - http://www.scopus.com/inward/record.url?scp=85216215455&partnerID=8YFLogxK
U2 - 10.1016/j.compchemeng.2025.109012
DO - 10.1016/j.compchemeng.2025.109012
M3 - Article
AN - SCOPUS:85216215455
SN - 0098-1354
VL - 195
JO - Computers and Chemical Engineering
JF - Computers and Chemical Engineering
M1 - 109012
ER -