n. caradot , h. sonnenberg, m. riechel, a. matzinger and p. rouault kompetenzzentrum wasser berlin
DESCRIPTION
The influence of local calibration on the quality of UV-VIS spectrometer measurements in urban stormwater monitoring. N. Caradot , H. Sonnenberg, M. Riechel, A. Matzinger and P. Rouault Kompetenzzentrum Wasser Berlin. Online CSO monitoring in Berlin. Separate sewer system. 10 km. - PowerPoint PPT PresentationTRANSCRIPT
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The influence of local calibration on the quality of UV-VIS spectrometer measurements in urban
stormwater monitoring
N. Caradot, H. Sonnenberg, M. Riechel, A. Matzinger and P. RouaultKompetenzzentrum Wasser Berlin
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Combined sewer system
Separate sewer system
CSO monitoring station N
Online CSO monitoring in Berlin
10 km
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Online CSO monitoring in Berlin
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Manufacturerglobal calibration
• default manufacturer configuration• for typical municipal waste or river
More than 50% error (Austrian study, Gamerith et al., 2011)
Online probes need to be calibrated to local conditions !!!
Absorbance measurement
ConcentrationsTSS, COD, etc.
LocalconcentrationsTSS, COD, etc.
Userlocal calibration
Spectrometer calibration and uncertainties
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Spectrometer calibration and uncertainties (COD)
• error spectro us=3%
• error from lab ul=10%
• Calculation using Monte-Carlo analysis
10,000 regressions
• Mean a and b
SD a and b
Y=a1.x+b1
Y=a2.x+b2
…Y=a.x+b
± u(y)
Calibration error:Error from calibration curve (confidence interval)Error from new prediction
RMSE1
)²()(
nRMSEu i
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CSO COD load: sources of uncertainty
Source of uncertainty
Estimation Contribution to load uncertainty
Concentration
Calibration curve ± Confidence interval 10 %
New prediction ± RMSE 70 %
Field installation ± 10% (Assumption) 10 %
Flow
Cross section ± 1 cm10 %
Velocity ± 0,05 m / s
• RMSE contributes to > 70% of load uncertainty underlines the importance of the collection of samples to build reliable
local calibration function
… what is the optimal sampling effort to calibrate the probes ?
1
)²()(
nRMSEu i
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• Sampling during CSO events parallel to online measurements– Flow trigger (> 0.3 m³/s)– Grab sampling each 5 minutes
• 15 CSO events with a minimum of 5 samples (75 samples) between 2010 and 2012
Data available for spectrometer calibration in Berlin
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Calibration parameter + uncertainty All events
Using all 75 samples (i.e. 15 events)total COD load is 29 t
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Calibration parameter + uncertainty Chronology of events
At least 20 samples (i.e. 4 events) :stable coefficients and uncertaintystable load
The effort to gain more than 20 samples is less effective and not necessary !!!
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Calibration parameter + uncertainty Berlin and Graz
Same results in Graz and Berlin !!!
At least 20 samples (i.e. 4 events) :stable coefficients and uncertaintystable load
The effort to gain more than 20 samples is less effective and not necessary !!!
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Calibration parameter + uncertainty Combination of events
Same results using combination of events:
At least 20 samples (i.e. 4 events) :stable load: 29 t stable uncertainty: 20 %
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Calibration parameter + uncertainty Combination of events
Using Global calibration from the manufacturer:total COD load is 19 t
high underestimation of about 30%
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UV-VIS probes need to be calibrated to local conditions !!! • e.g. Berlin: global calibration 30% underestimation for COD load
Even with local calibration : significant uncertainties ~ 20% (conc. and load)
Good estimation of calibration parameters with more than 20 grab samples (4 events)
Effort and sampling costs to gain more than 20 samples less effective • Parameters and loads stable with an increasing number of samples !!!
Results representative of the local Berlin case study : no general rule !!!
validation of results on other case studies in progress! Berlin Graz Lyon Bogota
Conclusion
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• Input data : samples = pairs (spectrometer probe values; related lab values) • Each sample belongs to an event (CSO or river impact)• Within one event : chronology of samples maintained to avoid unrealistic combinations
Generation of subsets of samples for all possible combinations of events
1. Subset creation
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2. Local calibration
For each subset : calibration function (linear regression) between probe and lab values.
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Calculation of calibrated COD concentrations + total load over all the events (CSO)
3. Concentration and load calculation
COD = a1 . x + b1
COD = a14 . x + b14
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Calculation of calibrated COD concentrations + total load over all the events (CSO)
3. Concentration and load calculation
COD = a1 . x + b1
Annual CSO Load MUncertainty U(M)
Generation of 50 random M values (Monte Carlo)- normal distribution- SD = u(M) = RMSE