Le et al.
Data validation and gross error detection in monitoring wastewater treatment process – application to a SHARON reactor Quan H. Le1*, Peter J.T. Verheijen2, Mark C.M. van Loosdrecht2 and Eveline I.P. Volcke1 1Department
of Biosystems Engineering, Ghent University, Belgium of Biotechnology, Delft University of Technology, The Netherlands *Corresponding author:
[email protected] 2Department
Abstract: Data reconciliation and gross error detection were applied on data of a SHARON reactor. This technique provides an internal check on the validity of the data or point at significant errors either in measurement or in mass balancing. The estimation of parameters of the processes will be easily determined than from the raw data. Keywords: data reconciliation, data validation, mass balances, big data, gross error
INTRODUCTION Data reconciliation offers an opportunity to find better estimates for measured data by applying conservation laws such as mass balances as constraints (Crowe, 1996). This procedure is always accompanied by statistical tests for gross error detection, which verify whether the necessary adjustments are acceptable compared to the measurement error. Even though data reconciliation has been widely applied in chemical engineering for decades, this concept so far has received relatively little attention in wastewater treatment process engineering (Meijer et al., 2002, Puig et al., 2008, Meijer et al., 2015). In this contribution, data reconciliation and gross error detection were applied to a SHARON process for biological nitrogen removal from wastewater.
MATERIALS AND METHODS Steady-state data In a SHARON reactor, ammonium, the dominant form in wastewater, is biologically oxidized to nitrite while preventing further oxidation to nitrate. The reactor effluent contains ammonium and nitrite in about equimolar amounts, which is ideally suited to feed the subsequent anammox process (van Dongen et al., 2001). Data from a 3-weeks measurement campaign on SHARON reactor at the WWTP Dokhaven (Rotterdam) was used on the full-scale (Mampaey et al., 2016); an overview of the measured variables from liquid and gas phase monitoring is given in Figure 1.
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off-gas Qoff O2off , CO2off , NOoff , N2Ooff
influent Qin NHin , TIC
effluent Qeff NHeff , NO2eff , NO3eff
SHARON
aeration air Qaer O2aer , CO2aer
Figure 1. Overview of measurements at the full-scale SHARON partial nitritation reactor. Gas phase measurement: off-gas and aeration air; liquid phase measurement: influent and effluent Setup constraint The nitrogen balance over the reactor expresses that the total incoming nitrogen in the form of ammonium (NHin) in the liquid phase equals the sum of the outgoing nitrogen in form of nitrite (NO2eff) and nitrate (NO3eff) in the effluent (liquid phase) and nitric oxide (NOoff) and nitrous oxide (N2Ooff) in the off gas. It was assumed that no dinitrogen gas (N2) was formed. Nitrogen incorporation into biomass was neglected, a reasonable assumption given the short biomass retention time. The COD balance was formed by take into account supplied oxygen from aeration (O2aer) while the outgoing of oxygen are the ones left reactor in off gas (O2off) and the consumed oxygen, which were based on oxygen equivalent of nitrite (3/2×NO2eff) and nitrate (2×NO3eff), nitric oxide (5/4×NO) and nitrous oxide (N2O). A gas flow balance was set up in terms of dinitrogen, which is present in air. This balance expresses the dinitrogen balance in the gas phase with assumption was that there was no or negligible formed dinitrogen in the reactor. Table 1 summarized three mass balances served as constraints. Table 1. Mass balances of nitrogen, COD and gas flow without infiltration air. Variable notations are explained in Table 2. Balance Unit Expression -1 Nitrogen mole N.h Qin × NHin = Qin × (NHeff + NO2eff + NO3eff) + Qoff × (N2Ooff + NOoff) -1 COD mole O2.h Qaer × O2aer = Qin × (3/2NO2eff + 2NO3eff) + Qoff× (N2Ooff + 5/4NOoff + O2off) 3 -1 Gas flow m .h Qaer × (100 - nO2aer -nCO2aer)/(273.15 + Taer) = Qoff ×(100 - nO2off-nCO2off)/(273.15 + Toff) Data reconciliation and gross error detection procedure Data reconciliation and gross error detection were based on the method of Verheijen (2010). Particularly, three tests were used for gross error detection namely global test and measurement test. The detailed procedure is the subject of an upcoming article. The procedure was implemented using MATLAB 2013b (The MathWorks, Inc., Natick, Massachusetts, United States). 210
Le et al. RESULT AND DISCUSSION Detection and estimation of air infiltration Data reconciliation and gross error detection procedure were performed using constraints in Table 1. The result indicated that all measured variables could be balanced (or improved). The off gas flow rate (Qoff), being an unmeasured variable, was estimated. However, gross error detection indicated that all measurements concerning the concentration and flow rate of gas phase measurements and influent flow rate (Qin) contained gross errors (Table 2, without Qinf); global test also show that there was gross error in data set (Table 3, without Qinf). Table 2. Result of measurement test (critical value =1.9, significant level = 0.05); Values in bold indicate gross error in corresponding variables. All measured variables were balanced otherwise indicated. Test statistic # Variable Description Without Qinf With Qinf 1 N2Ooff N2O concentration in the off gas 0.78 0.35 + 2 NHeff NH4 concentration in the effluent 0.76 0.35 + 3 NHin NH4 concentration in the influent 0.76 0.35 4 NO2eff NO2 concentration in the effluent 1.5 0.35 5 NO3eff NO3- concentration in the effluent 2.1 0.35 6 NOoff NO concentration in the off-gas 0 0 7 O2aer O2 concentration in the aeration air 0.35 5 8 O2off O2 concentration in the off-gas 0.35 5 9 Qaer Aeration air flow rate 0 5 10 Qin Influent flow rate 0 5 11 Taer Aeration air temperature 0.35 5 12 Toff Off-gas temperature 0.35 5 13 nCO2aer Fraction of CO2 in aeration air 0 5 14 nCO2off Fraction of CO2 in offgas 0.35 5 15 nO2aer Fraction of O2 in aeration air 0.35 5 16 nO2off Fraction of O2 in offgas 0.35 5 Table 3. Result of global tests (significant level = 0.05) Without Qinf Test statistic 25 Critical value 6
With Qinf 0.12 3.8
These gross errors could be explained by two reasons. First, measurement outliers could be caused by apparatus malfunctioning. Second, it could be that the applied constraints were not valid. As it is most unlikely that the multiple apparatus measuring many different variables were all malfunctioning at the same time, the latter scenario seemed the most likely. Furthermore, some under pressure was observed in the headspace of the reactor during the monitoring campaign. Therefore, even though the reactor was considered completely covered, air infiltration into reactor might happen in case it was not completely airtight.
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In order to test this hypothesis an additional unmeasured variable, the infiltration airflow rate (Qinf) was introduced into the system of mass balances (Table 4). Data reconciliation and gross error detection were repeated on the same data set but applying these new constraints. The results were satisfying compared to the measurement accuracy: no gross errors remained (Table 3 and 4 with Qinf). The infiltration airflow rate was estimated at Qinf = 667 ± 166 m3.h-1, which equalled to 40% of aeration air supplied into reactor (Qaer = 1633 ± 107 m3.h-1). Off gas flow rate (Qoff) was also be estimated to be 2411 ± 180 m3.h-1. Table 4. Mass balances nitrogen, COD and gas flow. Infiltration air is unmeasured variable (Qinf) Balance Unit Expression Nitrogen
mole N.h-1
COD
mole O2.h-1
Gas flow
m3.h-1
Qin × NHin = Qin × (NHeff + NO2eff + NO3eff) + Qoff×(N2Ooff + NOoff) (Qaer + Qinf) ×O2aer = Qin × (3/2NO2eff+ 2NO3eff) + Qoff× (N2Ooff + 5/4NOoff + O2off) (Qaer + Qinf)×(100-nO2aer-nCO2aer)/(273.15 + Taer) = Qoff ×(100 - nO2off - nCO2off)/(273.15+Toff)
Estimation of total inorganic in the influent The CO2 mass balance was formulated based on the assumption that all CO2 in the off gas were result of CO2 stripping as result of biological oxidation of ammonium and CO2 from aeration air. By introducing this CO2 constraint into the system of mass balances in Table 4, also the total inorganic carbon in the influent (TICin) could be estimated (TICin = 112 ± 8 mole C.m-3, details not shown). The ratio of total inorganic carbon and total ammonium in the influent (TIC:TAN) was then calculated to be 1.20 ± 0.09, which then agreed with typical range of 1-1.4 for this type of influent. CO2 mass balance (mole C.h-1): Qin×TICin + (Qaer + Qinf)×CO2aer = Qoff×CO2off
CONCLUSION Data reconciliation and gross error detection provides an internal check on the validity of the data or point at significant errors either in measurement or in mass balancing. Therefore, any knowledge that one looks for in processes will be made clearer and estimation of parameters of the studied processes will be easily determined than from the raw data. REFERENCES Crowe, C. M. 1996. Data reconciliation - Progress and challenges. Journal of Process Control, 6, 8998. Mampaey, K. E., De Kreuk, M. K., van Dongen, U. G. J. M., van Loosdrecht, M. C. M. & Volcke, E. I. P. 2016. Identifying N2O formation and emissions from a full-scale partial nitritation reactor. Water Research, 88, 575-585. Meijer, S. C. F., van der Spoel, H., Susanti, S., Heijnen, J. J. & van Loosdrecht, M. C. M. 2002. Error diagnostics and data reconciliation for activated sludge modelling using mass balances. Water Science and Technology, 45, 145-156. Meijer, S. C. F., van Kempen, R. N. A. & Appeldoorn, K. J. 2015. Plant upgrade using big-data and reconciliation techniques. Applications of Activated Sludge Models. IWA publishing. Puig, S., van Loosdrecht, M. C. M., Colprim, J. & Meijer, S. C. F. 2008. Data evaluation of full-scale wastewater treatment plants by mass balance. Water Research, 42, 4645-4655.
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Le et al. van Dongen, U., Jetten, M. S. M. & van Loosdrecht, M. C. M. 2001. The SHARON((R))Anammox((R)) process for treatment of ammonium rich wastewater. Water Science and Technology, 44, 153-160. Verheijen, P. J. T. 2010. Data reconciliation and error detection. The metabolic pathway engineering handbook : fundamentals. Boca Raton: CRC Press/Taylor & Francis.
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