assessment of ro membrane fouling by nom size analysis
TRANSCRIPT
Fredrick W. Gerringer, D.Env., P.E. (Trussell Technologies*)
Alex D. Revchuk (Water Quality & Technology Solutions*)
Mel Suffet, Ph.D. (UCLA, Env. Science & Eng. Program)
13th Water Reuse and DesalinatIon Research Conference May 19, 2009
* Current employer
Assessment of RO Membrane Fouling by NOM Size Analysis Using Ultrafiltration
Membranes and Polarity Analysis
Create an empirical model of organic fouling by comparing NOM characteristics to RO metrics NOM characteristics in RO feed ○ Polarity ○ Molecular weight (MW) distribution ○ Average MW ○ Charge/size ratio
RO performance metrics ○ Specific flux ○ Salt rejection
Research Objective
RO Fouling Mechanisms
Degrade quality of RO permeate Increase operating costs
Reduce membrane longevity
Inorganic Colloidal Biological Organic
RO Fouling Mechanisms
Focus on organic fouling Characterize NOM
Polarity MW distribution Charge/size ratio
RO Pretreatment without Ozone
RO Membrane Permeate
Brine
Memcor Unit
Colorado River Water
NOM Sample
Permeate
Brine
Dual-Media Filters
RO Membrane
Microfiltration
Conventional Filtration
NOM Sample
Coagulant Polymer
Solids Contact Reactor
Chlorine
Ammonia
Sulfuric Acid (if used)
Ammonia
Sulfuric Acid (if used)
RO Pretreatment with Ozone
Sulfuric Acid (if used)
RO Membrane Permeate
Brine
MF Unit
Colorado River Water
NOM Sample
Permeate
Brine
Biofiltration
RO Membrane
MF with pre-O3
CF-O3/BF
Coagulant Polymer NOM
Sample
Ozonation 1 mg/L for
5 min
Solids Contact Reactor
Sulfuric Acid (if used)
NOM Characterization - Polarity
Polarity rapid assessment method (PRAM) (Rosario-Ortiz et al., 2007)
Non-polar resins: C-18 and C-2 Polar resins: Cyanide (CN), Silica and
Glycol (Diol) Anion exchange resins ○ Strong anion exchanger (SAX) ○ Weak anion exchanger (NH-2)
UV254 (A)
Volume
A/A0
0
1 RC
Water Sample
(A0)
Increasing polarity
Retention Coefficient (RC) = 1 – A/A0
Silica
C-18
C-2
CN
Diol
NH-2
SAX
1 sample – 40 minutes
100 mL total volume
PRAM Analysis
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
C18 C2 CN Silica Diol NH2 SAX
Ret
entio
n C
oeffi
cien
t
SPE Sorbent
Polarity
Non-Polar
Polar
Anion Exchange RC= 1-A/A0
RCnon-polar + RCpolar + RCanion ex. ≠ 1
PRAM Analysis
NOM Characterization – MW Distribution (Gerringer et al., 2009)
Water Sample (A0)
Size Fractions
1-5 kDa 5-10 kDa > 10 kDa < 1 kDa
1 kDa 5 kDa 10 kDa UF
Membrane (Polyethersulfone)
NOM Charge/Size Ratio Relationship between polarity and MW Calculate energy of interaction in joules:
ΔEi = RC x δ 2 x Vm RC: retention coefficient from PRAM δ : Hansen’s solubility parameter (J-½•mol-½•cm-3/2) Vm : molar volume of the SPE sorbent (cm3•mol-1)
Use non-polar (C-18) & polar (Diol) resins Divide by average MW (Da)
Correlations – RO and NOM Polarity
Correlations – RO and NOM Size
Charge/size ratios Non-polar Polar
<1 kDa 1-5 kDa 5-10 kDa
(>10 kDa)-1
Average MW
Best Fit Specific Flux Models
Best Fit Salt Rejection Model
Conclusions NOM size correlated poorly with fouling Hydrophobic interactions (C-18) were
important for specific flux Weak anion exchange capacity (NH-2)
was associated with salt rejection RO fouling could be modeled using
NOM characteristics
Acknowledgements Funding Agencies Metropolitan Water District of Southern California California Department of Water Resources US Environmental Protection Agency
Project Development Dr. Christopher Gabelich – MWD of Southern California Dr. Fernando Rosario-Ortiz – U. of Colorado at Boulder Alexander Modifi – AECOM
Acknowledgements Pilot Plant Operation and Sample Collection Mike Norris and Angela Adams – USBR Bruce Garrett – Beach Global Robert Northrup, Wayne Johnson and Brent
Corbett – Burns & Roe
NOM Characterization – UCLA Students Hakam Al-Samarrai Po Fung Susan Givens
THANK YOU !! ANY QUESTIONS ??
Development of Empirical Model Describe changes to RO performance
caused by organic fouling Assess normality of each data set Evaluate correlations between NOM and RO ○ Correlation coefficients ≥ 0.5
Linear regression with forward selection procedure ○ F-value ≥ 4.0 ○ Exclude NOM parameters that were
statistically significant with each other
Future Research
Improve UF fractionation method Evaluate effect of ozone on RO fouling Perform bench-scale RO fouling
studies with NOM characterization Maximize statistical power Consider more experimental conditions