Appendix D. Microbiological Methods D. 1 General Recommendations The challenge microorganism used to validate UV reactors should be cultured and analyzed by a laboratory staffed by professional microbiologists and equipped to perform microbiological examinations as per Standard Methods for the Examination of Water and Wastewater ( APHA et al. 1998, sections 1020 1050). Protocols for culturing the challenge microorganism and measuring its concentration should be based on published and peer reviewed methods and should be clearly defined and followed. Measurement of the concentration of the challenge microorganism before and after exposure to UV light should be initiated within 24 hours of exposure. If the challenge microorganism has the ability to photorepair, exposure of samples to visible light should be kept to a minimum.

Because MS2 bacteriophage ( MS2) and B. subtilis spores are commonly being used as challenge microorganisms for UV reactor validation, the following sections describe procedures that can be used for preparing stock solutions of MS2 and B. subtilis spores and assaying the concentration of those microorganisms in water samples. Procedures for preparing stock solutions can be scaled to provide the volumes needed for UV reactor validation. Alternative procedures and challenge microorganisms can be used if they are acceptable to the State. Section F. 1 provides a rational for selecting challenge microorganisms.

D. 2 MS2 Bacteriophage Stock Preparation MS2 ( ATCC 15597 B1) can be propagated using a variety of host bacteria including Escherichia coli C3000 ( ATCC 15597), E. coli F amp ( ATCC 700891), and others ( Meng and Gerba 1996, Oppenheimer et al. 1993, NWRI/ AwwaRF 2000). The following propagation method was adapted from NWRI/ AwwaRF ( 2000):

1. Inoculate sterile tryptic soy broth ( TSB) ( DIFCO, Detroit, Michigan) with host bacterium transferred from a single colony grown on a nutrient agar plate. Incubate the culture with constant stirring at 35 to 37 ° C for 18 to 24 hours.

2. Transfer 0.5 mL of the host bacterium culture to 50 mL of fresh TSB and incubate at 35 to 37 ° C for 4 to 6 hours with continuous shaking at 100 Hz to obtain a culture in its log growth phase ( approx. 3x108 cfu/ mL) ( cfu = colony forming units).

3. Dilute stock MS2 using Tris buffered saline ( pH 7.3) to a concentration of approximately 108 pfu/ mL ( pfu = plaque forming units).

4. Add 1mL of diluted MS2 stock solution to the 50 mL volume of E. coli in TSB and incubate overnight at 35 to 37 ° C.

5. Centrifuge the MS2/ E. coli culture at 8000 × g ( g = 9.82 m/ s2) for 10 minutes at 4 ° C to remove cellular debris.

UV Disinfection Guidance Manual D 1 June 2003 Proposal Draft Appendix D. Microbiological Methods UV Disinfection Guidance Manual D 2 June 2003 6. Filter the supernatant by passing it through a 0.45 µ m low protein binding filter.

7. Assay the concentration of MS2 in the stock solution as per section D. 3.

8. Collect and refrigerate the filtrate at 4 ° C and use within a one month period.

Propagation should result in a highly concentrated stock solution of essentially monodispersed phage whose UV dose response follows first order kinetics with minimal tailing. Figure D. 1 presents the dose response of MS2 as reported in the literature. Over the range of REDs demonstrated during validation testing, the mean dose response of the MS2 stock solution should lie within the 90 percent prediction interval of the mean response in Figure D. 1. Over a dose range of 0 to 120 mJ/ cm2, the predictions intervals may be defined using the following equations:

Dose Dose on Inactivati Bound Lower × × + × ×   =     2 2 4 10 6 . 7 10 4 . 1 log: Dose Dose on Inactivati Bound Upper × × + × ×   =     2 2 5 10 5 . 4 10 6 . 9 log:

Figure D. 1 UV Dose Response of MS2 0 1 2 3 4 5 6 7 8 0 20 40 60 80 100 120 UV Dose ( mJ/ cm2) Log Inactivation Meng and Gerba, 1996 Oppenheimer et al, 1993 Sommer et al, 1998 Tree et al, 1997 Havelaar et al, 1990 Nieuwstad et al, 1994 Mean Mean Response 90% Prediction Interval Proposal Draft Appendix D. Microbiological Methods UV Disinfection Guidance Manual D 3 June 2003 D. 3 MS2 Assay The concentration of MS2 ( ATCC 15597 B1) in water samples can be assayed using the agar overlay technique with E coli ( ATCC 15597) as a host bacterium ( Adams 1959, Yahya et al. 1992, Oppenheimer et al. 1993, Meng and Gerba 1996). The following procedure can be used:

1. Inoculate TSB ( Difco, Detroit, MI) with the host bacterium and incubate at 35 to 37 ° C for 18 to 24 hours to obtain an approximate concentration of 108 CFU/ mL.

2. Transfer 1 mL of the culture to 50 mL of fresh TSB and incubate at 35 to 37 ° C for 4 to 6 hours with continuous shaking at 100 Hz to obtain a culture in its log growth phase.

3. Obtain serial dilutions of the MS2 sample using a 0.001 M phosphate saline buffer or TSB.

4. Combine and gently stir 1 mL of host cell solution, 0.1 mL of diluted MS2 sample, and 2 to 3 mL of molten tryptic soy agar ( TSA) ( 0.7 percent agar, 45  48 ° C) ( Difco, Detroit, MI).

5. Pour the mixture onto solidified TSA ( 1.5 percent agar) contained within Petri dishes. The time between the mixing the MS2 sample with the E. coli host and the plating of the top agar layer should not exceed 10 minutes. After plating, the agar should harden in 10 minutes.

6. After the top agar layer hardens, cover, invert the Petri dishes, and incubate 16 to 24 hours at 35 to 37 ° C.

7. Count the plaques with the aid of a colony counter. Plaques are identified as clear circular zones 1 to 10 mm in diameter in the lawn of host bacteria.

8. Record the number of plaques per dish, and the MS2 sample volume and dilution. If it is not possible to distinguish individual plaques because of confluent growth, record the plate counts as " TNTC" ( too numerous to count).

9. Calculate the MS2 concentration in the water samples:

=

i i V n ion Concentrat Equation D. 1 where ni = The number of counts on each plate Vi = The volume of undiluted sample used with each plate Example. A water sample containing MS2 was diluted 10, 100 and 1,000 fold using a 0.1 mL aliquot dilution of the sample for each. Each dilution was assayed in triplicate. Plaque Proposal Draft Appendix D. Microbiological Methods UV Disinfection Guidance Manual D 4 June 2003 forming units observed on the plates were 2, 5 and 6 for the 1,000 fold diluted sample and 32, 40, and 47 for the 100 fold diluted sample. With the 10 fold dilution, plate counts were too numerous to count. The concentration in the original sample is calculated as follows:

( ) mL pfu mL mL pfu ion Concentrat / 000 , 40 100 / 3 1 . 0 1000 / 3 * 1 . 0 47 40 32 6 5 2 = × + + + + + + =

D. 4 Bacillus Subtilis Spore Preparation Bacillus subtilis spores ( ATCC 6633) can be propagated using Schaeffer's media ( Munakata and Rupert 1972, Sommer et al. 1995, DVGW 1997). The following propagation method was adopted from DVGW ( 1997):

1. Prepare Columbia agar ( Oxoid CM 331) as a 1 L solution of 23.0 g special peptone ( Oxoid L 72), 1.0 g starch, 5.0 g NaCl, and 10.0 g agar ( Oxoid L 11) in distilled water. Adjust pH to 7.0 and autoclave 15 minutes at 121 º C.

2. Prepare the sporulation media as a 1 L solution of 280 mg MgSO4 · H2O, 1.11 g KCl, 3.1 mg FeSO4 · 7H2O, and 8.9 g nutrient broth ( Oxoid CM 67) in distilled water. Adjust the pH to 7.0 and autoclave it for 15 minutes at 121 º C.

3. Inoculate Columbia agar plates ( Oxoid CM 331) with three smears of B. subtilis and incubate 24 hours at 37 º C.

4. Inoculate 300 mL of sporulation media with three colonies collected from the agar plates.

5. Incubate the sporulation media 72 hours at 37 º C on a shaker operating at 2 Hz.

6. Sonicate the resulting culture for 10 minutes at 50 kHz and 10 º C.

7. Harvest the spores by centrifuging 80 mL aliquots at 5000 g for 10 minutes and 10 º C.

8. Wash the spores three times by resuspending in 20 mL of distilled water and centrifuging at 5000 × g for 10 minutes at 10 º C.

9. Resuspend the washed spores in 100 mL of 0.001 M phosphate saline buffer.

10. Inactivate the vegetative B. subtilis by heat treatment at 80 º C for 10 minutes.

11. Sonicate the resulting culture for 10 minutes at 50 kHz and 10 º C.

12. Collect the resulting stock solution and assay the B. subtilis spore concentration as per section D. 5.

13. Refrigerate the filtrate at 4 º C and use within a one month period. Sonicate for 10 minutes at 50 kHz and 10 º C before use.

Proposal Draft Appendix D. Microbiological Methods UV Disinfection Guidance Manual D 5 June 2003 Propagation should result in a highly concentrated stock solution of mono dispersed B. subtilis spores with a UV dose response that follows the dose response reported in the literature and presented in Figure D. 2. Over the range of reduction equivalent doses ( REDs) demonstrated during validation testing, the mean dose response of the B. subtilis stock solution should lie within the 90 percent prediction interval of the mean response provided in Figure D. 2. Over a dose range of 0 to 70 mJ/ cm2, the predictions intervals may be defined using the following equations:

Dose Dose Dose on Inactivati Bound Lower × ×   × × + × ×   =       2 2 3 3 5 10 3 . 5 10 7 . 2 10 0 . 2 log: Dose Dose on Inactivati Bound Upper × × + × × =     2 2 4 10 3 . 4 10 7 . 5 log:

Figure D. 2 UV Dose Response of Bacillus Subtilis Spores  1 0 1 2 3 4 5 6 7 0 50 100 150 UV Dose ( mJ/ cm2) Log Inactivation DVGW, 1997 Hoyer, 2002 Chang et al, 1985 Sommer et al, 1996 Sommer et al, 1995 Sommer et al, 1998 Sommer and Cabaj, 1993 Sommer and Cabaj, 1993 Mean 90% Prediction Interval of the Mean Response Proposal Draft Appendix D. Microbiological Methods UV Disinfection Guidance Manual D 6 June 2003 D. 5 Bacillus Subtilis Spore Assay The concentration of B. subtilis spores ( ATCC 6633) in water samples can be assayed by the plate method using plate count agar. The following procedure was adopted from Deutscher Verein des Gas und Wasserfaches ( DVGW) ( 1997):

1. Prepare plate count agar ( Oxoid CM 325) as a 1 L solution of 5.0 g casein peptone ( Oxoid L 42), 2.5 g yeast extract ( Oxoid L 21), 1.0 g glucose, and 9.0 g agar ( Oxoid L 11) in distilled water. Adjust pH to 6.8 ± 0.2 and autoclave for 15 minutes at 121 º C.

2. Obtain serial dilutions of the B. subtilis spore sample using 0.001 M phosphate saline buffer.

3. Vacuum filter 100 mL of diluted sample through a 47 mm x 0.45 µ m membrane filter ( Gelman Sciences, Ann Arbor, MI).

4. Place filter onto a Petri dish containing hardened agar and cover plates.

5. Incubate plates 24 ± 2 hours at 37 ± 1 º C.

6. Count the number of colonies formed with the aid of a colony counter.

7. Record the number of colonies per dish, and the B. subtilis spore sample volume and dilution. If it is not possible to distinguish individual colonies because of confluent growth, record the plate counts as " TNTC".

8. Calculate the B. subtilis spore concentration in the original samples as cfu/ mL using Equation D. 1.

D. 6 References Adams, M. H. 1959. Bacteriophage. New York: Interscience publication.

APHA/ AWWA/ WEF. 1998. Standard methods for the examination of water and wastewater, 20th edition. Washington DC: American Public Health Association, American Water Works Association, and Water Environment Federation.

DVGW. 1997. UV disinfection devices for drinking water supply     Requirements and testing. Bonn, Germany: German Gas and Water Management Union ( DVGW).

Havelaar, A. H., C. C. E. Meulemans, W. M. Pot Hogeboom, and J. Koster. 1990. Inactivation of bacteriophage MS2 in wastewater effluent with monochromatic and polychromatic ultraviolet light. Water Research 24, no. 2: 1387 1393.

Hoyer, O. 2002. Personal communication.

Proposal Draft Appendix D. Microbiological Methods UV Disinfection Guidance Manual D 7 June 2003 Meng, Q. S. and C. P. Gerba. 1996. Comparative inactivation of enteric adenovirus, poliovirus and coliphages by ultraviolet irradiation. Wat. Res. 30: 2665 2668.

Munakata, N. and C. S. Rupert. 1972. Genetically controlled removal of " spore photoproduct" from deoxyribonucleic acid of ultraviolet irradiated bacillus subtilis spores. J. Bacteriol. 111: 192 198.

Nieuwstad, T. J. and A. H. Havelaar. 1994. The kinetics of batch ultraviolet inactivation of bacteriophage MS2 and microbiological calibration of an ultraviolet pilot plant. J. Environ. Sci. Health A29, no. 5: 1993 2007.

NWRI/ AwwaRF. 2000. Ultraviolet disinfection guidelines for drinking water and water reuse. National Water Research Institute and AwwaRF Oppenheimer, J. A., J. E. Hoagland, J. M. Laine, J. G. Jacangelo, and A. Bhamrah. 1993. Microbial inactivation and characterization of toxicity and by products occurring in reclaimed wastewater disinfected with UV radiation. Water Environment Federation ( WEF) Specialty Conference: Planning, design & operation of effluent disinfection systems. Whippany, New Jersey.

Sommer, R. and A. Cabaj. 1993. Evaluation of the efficiency of a UV plant for drinking water disinfection. Water Science & Technology 27, no. 7 8: 357 362.

Sommer, R., A. Cabaj, D. Schoenen, J. Gebel, A. Kolch, A. H. Havelaar, and F. M. Schets. 1995. Comparison of three laboratory devices for UV inactivation of microorganisms. Wat. Sci. Tech. 31: 147 156.

Sommer, R., A. Cabaj, and T. Haider. 1996. Microbiocidal effect of reflected UV radiation in devices for water disinfection. Water Science & Technology 34, no. 5 6: 173 177.

Sommer, R., T. Haider, A. Cabaj, W. Pribil, and M. Lhotsky. 1998. Time dose reciprocity in UV disinfection of water. IAWQ, Vancouver.

Tree, J. A., M. R. Adams, and D. N. Lees. 1997. Virus inactivation during disinfection of wastewater by chlorination and UV irradiation and the efficacy of f+ bacteriophage as a ' viral indicator'. Water Science & Technology 35: 227 232.

Yahya, M. T., T. M. Straub, and C. P. Gerba. 1992. Inactivation of coliphage MS 2 and poliovirus by copper, silver, and chlorine. Canadian Journal of Microbiology. 38, no. 6: 430 435.

Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response The challenge microorganism's UV dose response should be measured using a benchscale device referred to here as a " collimated beam apparatus" ( Figure E. 1). The apparatus delivers UV light to a microbial suspension usually contained within a completely mixed batch reactor. The UV light enters the suspension with a near zero degree angle of incidence and is relatively homogenous across the surface area. UV dose delivered to the suspension is calculated using measurements of incident UV intensity, exposure time, suspension depth, and the absorption coefficient of the suspension. By measuring microbial inactivation in the suspension as a function of UV dose, the microorganism's dose response is determined.

Figure E. 1 Collimated Beam Apparatus Low Pressure Mercury Arc Lamp Lamp Enclosure Petri Dish Containing Microbial Suspension Magnetic Stirrer UV Light @ 254 nm Collimating Tube UV Disinfection Guidance Manual E 1 June 2003 Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response UV Disinfection Guidance Manual E 2 June 2003 This appendix describes the following components of collimated beam testing:

  Collimated beam apparatus design and operation ( section E. 1)

  Procedure for irradiating samples using apparatus ( section E. 2)

  Calculation of UV dose delivered by the apparatus ( section E. 3)

  Quality Assurance / Quality Control ( QA/ QC) procedures ( section E. 4)

  Reporting results ( section E. 5)

E. 1 Apparatus Design and Operation Because UV dose requirements are based on the pathogen inactivation achieved using 253.7 nm light, the collimated beam apparatus must use a lamp that emits germicidal UV light only at 254 nm ( e. g., a low pressure lamp). To prevent ozone formation, lamps that emit 185 nm light should not be used. The output from the lamp measured using a radiometer or equivalent should not vary more than 5 percent over the exposure time. A stable lamp output can be obtained by driving the lamp with a constant power source and maintaining the lamp at a constant operating temperature. A voltage regulator may be used to obtain a stable power supply to the lamps if the line voltage is not sufficiently stable. A stable temperature can be obtained by controlling the airflow around the lamp.

The UV lamp should be located far enough above the surface of the microbial suspension that uniform irradiance is obtained across the sample's surface and UV light enters the suspension with a near zero degree angle of incidence ( Blatchley 1997). A recommended minimum distance from the lamp to the suspension is six times the longest distance across the suspension's surface. In order to vary the UV intensity incident on the suspension, the distance between the suspension and the lamp can be adjusted.

The uniformity of the intensity field across the sample's surface should be assessed by measuring the " Petri Factor," the ratio of the average irradiance across the suspension surface to the irradiance measured at the center ( Bolton and Linden 2003). The average irradiance is determined by averaging radiometer measurements taken at each point in a 5 mm spaced grid across an area defined by the suspension's surface. If the radiometer's sensing window is wider Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response UV Disinfection Guidance Manual E 3 June 2003 than 5 mm, it should be reduced using a cover slip with a small hole. In general, the collimated beam apparatus should have a Petri Factor greater than 0.9.

The lamp and the light path from the lamp to the suspension should be enclosed to protect the user from exposure to UV light. A box like enclosure made of aluminum is often used. A length of pipe is often used to enclose the light path from the lamp to the microbial suspension. The inside surface of the pipe should have a low UV reflectance and incorporate apertures to improve UV light collimation ( Blatchley 1997). A shutter mechanism is sometimes used to control the exposure of the suspension to UV light. The exposure times should be measured with an uncertainty of 5 percent or less. Exposure times less than 20 seconds are not recommended.

The microbial suspension should be irradiated in an open cylindrical container with a constant cross sectional area ( e. g., Petri dish). The diameter of the container should be smaller than the diameter of the light beam incident on the container. Sample depth should be 0.5 to 2 cm. The material of the container should not adsorb the challenge microorganism enough to impact its measured dose response.

Sample volumes irradiated in the container should be sufficient for measuring the challenge microorganism's concentration after irradiation. The microbial suspension should be mixed using a stir bar and a magnetic stirrer at a rate that does not induce vortices. The volume and diameter of the stir bar should be small relative to the volume and depth of the sample volume. The irradiance at the center of the suspension's surface before and after exposure to UV light should be measured using a radiometer calibrated at 254 nm. The radiometer calibration should be National Institute of Standards and Technology ( NIST) traceable or equivalent with a known measurement uncertainty. During measurement, the radiometer's calibration plane should match the height of the suspension's surface and be perpendicular to the incident UV light. The calibration plane of the radiometer should be specified in the radiometer's calibration certificate.

The depth of the suspension, including the stir bar volume, should be measured with an uncertainty of 10 percent or less. The UV absorption coefficient of the microbial suspension at 254 nm should be measured using a spectrophotometer with a measurement uncertainty of 10 percent or less. If scattering of light by the microorganisms and other particulate matter within the suspension is significant, the UV absorption coefficient should be measured using a spectrophotometer equipped with an integrating sphere ( Linden and Darby 1998). While 1 cm cuvettes are typically used for measuring UV absorption coefficients, cuvettes with longer pathlengths are recommended to reduce the measurement uncertainty with low UV absorbance samples.

E. 2 Procedure Personnel who perform bench scale UV irradiation should be experienced with the use and safety requirements of the equipment. Safety goggles and latex gloves should be worn. Skin should be shielded from exposure to UV light. The following procedure is recommended for irradiating a water sample using the collimated beam apparatus:

1. Define the target UV dose.

Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response UV Disinfection Guidance Manual E 4 June 2003 2. Measure the UV absorption coefficient of the water sample.

3. Place a known volume from the water sample into a container and add a stir bar.

4. Measure the water depth in the container.

5. Measure the UV irradiance delivered by the collimated beam.

6. Calculate the exposure time to deliver the target dose.

7. Block the light from the collimating tube using a shutter or equivalent.

8. Center the container containing the water sample under the collimating tube.

9. Unblock the light from the collimating tube and start the timer.

10. When the target exposure time has elapsed, block the light from the collimating tube.

11. Remove the container and collect the sample for measurement of the challenge microorganism concentration. If the sample is not assayed immediately, store in the dark at 4 º C. 12. Re measure the UV irradiance and calculate the average of the two measurements.

13. Using Equation E. 1, calculate the applied dose using the measured irradiance, UV absorption coefficient, sample depth, and exposure time.

14. Repeat the procedure for various target dose values. The UV dose response curve is a plot of the microorganism concentration as a function of the applied dose.

E. 3 Dose Calculation Dose delivered to the sample is calculated using Equation E. 1:

t ad L d L R P E D ad f s ) 10 ln( ) 10 1 ( ) ( ) 1 (   +   = Equation E. 1 where D = UV dose in mJ/ cm2 Es = UV irradiance at the center of the suspension's surface in mW/ cm2 Pf = Petri Factor R = Reflectance at the air water interface at 254 nm L = Distance from lamp centerline to suspension surface in cm d = Depth of the suspension in cm a = UV absorption coefficient ( Base 10) of the suspension at 254 nm in cm 1 t = Exposure time in seconds Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response UV Disinfection Guidance Manual E 5 June 2003 The term L/( d+ L) accounts for the divergence of the UV light from the collimated beam as it passes through the suspension. The reflectance at the air water interface estimated using Fresnel's Law is 0.025 given an index of refraction of 1.000 and 1.372 for air and water, respectively.

Alternatively, given a target dose, the exposure time may be calculated by re arranging Equation E. 1 to form Equation E. 2:

) 10 1 )( 1 ( ) )( 10 ln(

ad f s R L P E L d ad D t     + = Equation E. 2 where variables are defined as in Equation E. 1 The measurement uncertainty of the dose delivered by the collimated beam should be assessed at an 80 percent confidence interval with consideration of each term in Equation E. 1. The measurement uncertainty of each term in Equation E. 1 can be determined from the measurement uncertainty stated for the instrumentation used to measure those quantities and the standard deviation of repeated measurements made with that instrumentation ( Taylor 1997). If the uncertainty of the measurement of the suspension depth and the UV absorption coefficient is less than 10 percent at a 80 percent confidence level and the product ad is less than 0.1, the uncertainty of the term ( 1 10 ad)/ ad can be assumed as 4 percent. This assumption allows the use of the sum of variances approach to calculate the uncertainty of the dose delivered by the collimated beam.

Example. A pipette with an accuracy of 0.2 mL is used to place a 25 mL microbial sample in a Petri dish. The incident irradiance of 1.00 mW/ cm2 is measured using a radiometer. The uncertainty of the radiometer measurement indicated by the calibration certificate is 7 percent. The suspension is irradiated for 60 seconds. The irradiation time is monitored using a stopwatch with an uncertainty of ± 1 second. The Petri dish radius, measured using a ruler with 1 mm graduations, is 2.5 ± 0.1 cm. The stir bar volume is estimated as 1 ± 0.1 mL. The UV absorption coefficient of the microbial sample at 254 nm is 0.050 ± 0.005 cm 1. The Petri factor of 0.90 ± 0.02 is calculated for the collimated beam apparatus. The distance from the lamp to the surface of the suspension is determined using a ruler as 25 ± 1 cm.

The depth in the Petri dish is calculated as the sum of the suspension and stir bar volumes divided by the area of the Petri dish.

( ) ( ) ( ) l Volume Area 25 0.2 cm 1 0.1 cm p 2.5 0.1cm 1.32 0.07cm 3 3 2 = = ± + ± ± = ± The UV dose is calculated as:

Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response UV Disinfection Guidance Manual E 6 June 2003 ( )( )( )

[ ( ) ( ) ] ( )( ) ( ) ( )( ) ( ) ( ) D 1.00 mW/ cm 0.90 1 0.025 1 1.32cm 25cm 1 10 0.050cm 1.32 cm ln 10 60s 46 mJ/ cm 2 0.050 cm 1.32 cm 1 2 1 =

+   =

Because the uncertainty of the sample depth ( ± 0.07 cm) and the measured UV absorption coefficient ( ± 0.005 cm 1) is less than or equal to 10 percent of the sample depth and the product of the sample depth and UV absorption coefficient is less than 0.1, the uncertainty of the term ( 1 10 ad)/ ad is assumed as 4 percent. The uncertainties of the terms in the dose calculation are as follows:

  Incidence irradiance 7 percent   Petri factor 2 percent   L/( d+ L) 0.3 percent   Time 2 percent   ( 1 10 ad)/ ad 4 percent The uncertainty of the dose calculation is calculated using the sum of variances approach as:

Uncertainty ( ) % 5 . 8 4 2 3 . 0 2 7 2 / 1 2 2 2 2 2 = + + + + =

E. 4 Quality Assurance and Quality Control QA/ QC measures include:

  Designing the collimated beam apparatus with a Petri factor greater than 0.9   Selecting instrumentation and methods that minimize the measurement uncertainty of dose delivery by the collimated beam apparatus   Calibrating all radiometers at regular intervals as recommended by the manufacturer   Using a reference radiometer or equivalent method to regularly check the measurement accuracy of the radiometer used to measure incident irradiance   Ensuring irradiance measurements before and after exposure to UV light do not differ by more than 5 percent   Ensuring replicate UV inactivation curves do not differ significantly Proposal Draft Appendix E. Collimated Beam Apparatus: Measuring Challenge Microorganism UV Dose Response UV Disinfection Guidance Manual E 7 June 2003   Ensuring the UV dose response of the challenge microorganism lies within expected bounds as defined by published dose response data E. 5 Reporting The following information should be documented and included with the validation test report:

  Lamp type   Distance from the light source to the sample surface   Radiometer make and model   Measurement uncertainty of the radiometer and date of last calibration   Comparison of working and reference radiometers   Volume and depth of the microbial suspension   UV absorption coefficient of the microbial suspension measured at 254 nm   Irradiance measurement before and after each irradiation   Petri factor calculations and results   Method of dose determination   UV dose calculations   Uncertainty assessment E. 6 References Blatchley, E. R. 1997. Numerical modeling of UV intensity: Application to collimated beam reactors and continuous flow systems. Water Research 31: 2205 2218.

Bolton. J. and K. Linden. 2003. Standardization of methods for fluence ( UV Dose) determination in bench scale UV experiments. J. Environ. Eng. 129, no. 3: 209 216.

Linden, K. G. and J. L. Darby. 1998. UV Disinfection of Marginal Effluents: determining UV Absorbance and Subsequent Estimation of UV Intensity. Water Environment Research 70( 2).

Taylor, J. R. 1997. An introduction to error analysis: the study of uncertainties in physical measurements. Sausalito, CA: University Science Books.

Proposal Draft UV Disinfection Guidance Manual F 1 June 2003 Proposal Draft Appendix F. Background to the UV Reactor Validation Protocol This appendix provides background material for the validation protocol given in Appendix C. The background material is organized into the following six sections.

· Dose delivery by UV reactors. Section F. 1 describes how the RED of a challenge microorganism measured during UV reactor validation is related to the capacity of the UV reactor to inactivate a target pathogen. This section describes why correction factors should be applied to the reduction equivalent dose ( RED) of the challenge microorganism to account for systematic errors that arise if the challenge microorganism is more resistant to UV light as compared to the target pathogen. The section concludes by describing approaches for selecting one or more challenge microorganisms to minimize those errors.

· Dose monitoring. Section F. 2 describes three approaches whereby measurements of flowrate, UV intensity, and water UV transmittance ( UVT) are used by UV reactors to indicate dose delivery. This section discusses the importance of UV intensity sensor placement within a UV reactor and provides a rationale for defining test conditions to validate UV reactors using a given dose monitoring approach.

· UV intensity sensors. Section F. 3 describes the properties of UV intensity sensors, how those properties impact the sensor's measurement uncertainty, and how that measurement uncertainty is used to define rejection criteria for using reference sensors to check the accuracy of duty sensors. The section also discusses how nonuniform lamp aging and fouling and the variability in lamp output affects the use of UV intensity sensors.

· Polychromatic considerations. Section F. 4 describes systematic errors that can occur with the validation of UV reactors equipped with medium pressure UV lamps. This section provides approaches for assessing those errors and for defining correction factors that should be applied to validation data.

· Uncertainty of monitoring and dose factors. Section F. 5 provides a rationale for defining a safety factor that accounts for the random uncertainty associated with UV reactor validation and monitoring.

· Re validation. Section F. 6 discusses how some changes to a UV reactor design made by a manufacturer would trigger a need to re validate the UV reactor.

F. 1 Dose Delivery by UV Reactors Dose delivered to an individual microorganism passing through a UV reactor is defined as the integral of UV intensity over time: Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 2 June 2003   = r t Idt D 0 Equation F. 1 where D = Dose delivered to the microorganism by the UV reactor I = UV intensity incident on the microorganism as it travels through the UV reactor t = time tr = Residence time of the microorganism within the UV reactor Because each microorganism passing through the UV reactor follows a unique trajectory, each microorganism is exposed to a unique dose. For example, microorganisms passing through the UV reactor close to the lamps are exposed to higher UV intensities as compared to microorganisms traveling near the reactor walls or between lamps. Microorganisms caught in eddies or dead zones spend more time within the UV reactor as compared to microorganisms that pass through the reactor quickly due to hydraulic short circuiting. Because each microorganism is exposed to a different UV dose, dose delivery by the UV reactor is best described using a dose distribution, as opposed to a single dose value. A dose distribution describes the probability that a microorganism passing through a UV reactor will receive a given dose. Figure F. 1 presents an example of a dose distribution for a UV reactor.

Model based and experimental approaches have been identified to determine the dose distribution of a UV reactor. Model based approaches use computational fluid dynamics ( CFD) to predict microorganism trajectories through a UV reactor and hence the dose delivered to each microorganism. Experimental approaches use microspheres that undergo a chemical reaction when exposed to UV light. The microspheres are injected upstream of the UV reactor and are collected downstream. The extent of the UV induced chemical reaction within each sphere is measured and used to calculate the dose delivered to that sphere as it traveled through the reactor. While promising, both model and experimental based approaches are subjects of current research. Further effort is necessary to prove these approaches as practical and accurate predictors of UV reactor performance.

Dose delivery by UV reactors is currently measured using biodosimetry ( Qualls and Johnson 1983). With biodosimetry, inactivation of a challenge microorganism passed through the UV reactor is measured and related to a single dose value based on the known UV dose response of that microorganism. This dose value is termed the RED.

Proposal Draft Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 3 June 2003 Proposal Draft Figure F. 1 Dose Distribution Delivered by a UV Reactor1 1( Adapted from Chiu et al. 1999)

F. 1.1 Relationship Between RED and the Dose Distribution The RED of a given microorganism depends on the dose distribution delivered by the reactor and the UV inactivation kinetics ( dose response) of the challenge microorganism ( Cabaj et al. 1996). A general equation describing this dependence is Equation F. 2:

( ) ( )

 = = j 1 i i i D f p RED f Equation F. 2 where RED = RED measured using biodosimetry f = Mathematical function describing the inactivation kinetics of the microorganism j = Number of dose values in the dose distribution Di = ith dose in the dose distribution pi = Probability of occurrence of dose Di For example, if the microorganism has first order inactivation kinetics, the function f is shown in Equation F. 3:

( ) ( ) kD. exp N D f N 0  = = Equation F. 3 where N = Microorganism concentration after exposure to dose D N0 = Microorganism concentration with zero UV dose D. = Applied UV dose k = Microorganism's first order inactivation coefficient Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 4 June 2003 Proposal Draft Substituting Equation F. 3 into F. 2 gives the following equation for the RED of a microorganism with first order inactivation kinetics:

( )

          =

 = j i i i kD p k RED 1 exp ln 1 Equation F. 4 In equation F. 4, the RED depends on the dose distribution of the UV reactor and the first order inactivation coefficient of the microorganism.

Figure F. 2 presents the dependence of the RED on the first order inactivation coefficient of the challenge microorganism for the dose distribution shown in Figure F. 1. The relation was calculated using Equation F. 4. As shown, the RED of a microorganism with a small first order inactivation coefficient is greater than the RED of a microorganism with a large first order inactivation coefficient. Because the RED depends on the microorganism's UV inactivation kinetics, the RED of the challenge microorganism is an exact measure of the RED delivered to a pathogen of interest only when the challenge microorganism has the same inactivation kinetics as the pathogen ( Wright and Lawryshyn 2000).

Example 1. A UV reactor delivers a dose distribution represented by Figure F. 1. The UV reactor is evaluated using biodosimetry. The challenge microorganisms are MS2 bacteriophage ( MS2) with a first order coefficient of 0.13 cm2/ mJ and  X174 phage with a first order coefficient of 1.2 cm2/ mJ. As shown in Figure F. 2, MS2 would have experienced 1.1 log inactivation, corresponding to an RED of 19 mJ/ cm2. fX174 would have experienced 3.6 log inactivation, corresponding to an RED of 7.3 mJ/ cm2. If the pathogen of interest has the same inactivation kinetics as  X174, the RED of MS2 would be 2.5 times greater than the RED delivered to the pathogen, while the RED of  X174 would be an exact measure of the RED delivered to the pathogen. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 5 June 2003 Proposal Draft Figure F. 2 Microorganism Log Inactivation and RED as a Function of the Microorganism's First Order Inactivation Coefficient for the UV Reactor Represented in Figure F. 1 F. 1.2 Using RED to Demonstrate Target Pathogen Inactivation If the UV dose response of the challenge microorganism differs from that of the target pathogen and the dose distribution of the UV reactor is not known, the results of biodosimetry can only be used to estimate the target pathogen inactivation within a range bounded by the inactivation expected assuming ideal and worst case hydraulics. Figure F. 3 provides a comparison of the dose distribution of reactors with ideal and worst case hydraulics to a dose distribution that might be seen with a real reactor.

Figure F. 3 Comparison of the Dose Distributions of Ideal, Realistic, and Worst Case UV Reactors A reactor with ideal hydraulics delivers the same dose to all the microorganisms passing through the reactor. Its dose distribution is represented by a single dose. Examples of a UV reactor with ideal hydraulics include the stirred suspension irradiated during the measurement of UV dose response by a collimated beam device and a plug flowrate reactor with complete lateral mixing. In both cases, the UV dose delivered is the product of the average UV intensity within 0 50 100 UV Dose ( mJ/ cm 2) Probability Ideal 0 50 100 UV Dose ( mJ/ cm 2) Probability Reality 0 80 UV Dose ( mJ/ cm 2) Probability Worst Case 0 Infinity Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 6 June 2003 Proposal Draft the reactor and the residence time. With an ideal reactor, Equation F. 5 shows the net microbial inactivation achieved by the reactor:

( ) ( ) D f D f p N N j 1 i i i 0 = =

 = Equation F. 5 Accordingly, with an ideal reactor, the RED measured with a challenge microorganism is a measure of the RED delivered to all microorganisms that pass through the reactor. If both the challenge microorganism and the pathogen have first order inactivation kinetics, the log inactivation of the pathogen is calculated using Equation F. 6:

( ) ( ) P p p D RED RED k N N 10 0 exp log log =   =

        Equation F. 6 where log ( N/ N0) p = Log inactivation of the pathogen kp = First order inactivation coefficient of the pathogen RED = RED observed with the pathogen D10 p = UV sensitivity of the pathogen expressed as mJ/ cm2 per log The UV sensitivity of the pathogen is related to the first order inactivation coefficient using Equation F. 7:

( ) k k D 30 . 2 10 ln 10 = = Equation F. 7 A UV reactor with worst case hydraulics delivers a UV dose of zero to all microorganisms passing through the reactor. However, in the case of a reactor with a measurable RED, worst case hydraulics is defined as infinite dose delivered to one fraction of the flowrate and zero dose delivered to the other fraction. Under these conditions, the net microbial inactivation achieved by the reactor is calculated according to Equation F. 8:

( ) ( ) ( ) 1 2 1 j 1 i i i 0 p f p 0 f p D f p N N = ° + = =

 = Equation F. 8 As shown, the net inactivation achieved by the worst case UV reactor with a measurable RED is constant and independent of the inactivation kinetics of the microorganism. With a worst case UV reactor, the measured inactivation is a measure of the inactivation that would occur with all microorganisms regardless of their UV sensitivity. In other words, the log inactivation of the pathogen is calculated according to Equation F. 9: Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 7 June 2003 Proposal Draft c p N N N N         =

        0 0 log log Equation F. 9 where log ( N/ N0) c = log inactivation of the challenge microorganism Using the above definitions of an ideal and a worst case reactor, the log inactivation of a pathogen estimated from biodosmetry results will have a value between log( N/ No) c and RED/ Dp. If the inactivation of the pathogen must be known with absolute confidence, the lower bound of that range should be used. If the challenge microorganism is more resistant to UV light than the pathogen, the lower bound is log( N/ No) c. If the challenge microorganism is less resistant to UV light than the pathogen, the lower bound is RED/ Dp.

Example 2. A UV reactor is challenged using MS2 with a UV sensitivity of 18 mJ/ cm2 per log inactivation. Four log inactivation of the MS2 is observed corresponding to an MS2 RED of 4 ¥ 18 = 72 mJ/ cm2. The MS2 results are used to estimate the log inactivation of two pathogens, one with a UV sensitivity of 10 mJ/ cm2 per log inactivation and the other with a UV sensitivity of 25 mJ/ cm2 per log inactivation. The log inactivation of the first pathogen is estimated between 4.0 and 72/ 10 = 7.2 log and the log inactivation of the second pathogen is estimated between 72/ 25 = 2.9 and 4.0 log. The biodosimetry results can be used to state with absolute confidence that the inactivation of the first pathogen was at least 4.0 log and the inactivation of the second pathogen was at least 2.9 log.

Example 3. A UV reactor is designed for 3.0 log Cryptosporidium inactivation. MS2 is used to measure the performance of the UV reactor. Because MS2 is more resistant to UV light than Cryptosporidium, 3.0 log MS2 inactivation must be measured to state with absolute confidence that the reactor achieves 3.0 log Cryptosporidium inactivation.

Example 4. A UV reactor is designed for two log adenovirus inactivation. Two log adenovirus inactivation occurs using a UV dose of 100 mJ/ cm2. The UV reactor is validated using MS2. Because adenovirus is more resistant to UV light than MS2, a RED of 100 mJ/ cm2 must be measured with MS2 to state with absolute confidence that the UV reactor achieves 2 log adenovirus inactivation.

Because UV manufacturers strive to optimize the hydraulic design of their UV reactors, using the worst case dose distribution represented in Figure F. 3 to define the lower bound of pathogen inactivation is overly conservative. An alternative approach is to use the dose distribution of a commercial UV reactor that is representative of worst case reactor hydraulics. However, defining a worst case commercial UV reactor is difficult because little data are available in the peer reviewed UV disinfection literature on dose distributions. Chiu et al. ( 1999) used measured velocity fields and a random walk model to predict the dose distribution delivered by a wastewater reactor equipped with low pressure ( LP) lamps oriented perpendicular to flowrate. The dose distribution was bimodal due to a short circuiting path along the reactor walls. Wright and Lawryshyn ( 2000) compared the dose distribution of four reactor designs using CFD based dose modeling including the reactor modeled by Chiu et al. Based on this comparison, the dose distribution developed by Chiu et al. is believed to represent a worst case commercial UV reactor. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 8 June 2003 Proposal Draft Figure F. 1 presents a dose distribution adapted from Chiu et al.' s data. For that dose distribution, Figure F. 2 presents log inactivation and RED as a function of the microorganism's UV sensitivity expressed as a first order inactivation coefficient. Figure F. 4 presents the same relationship, but with UV sensitivity expressed as dose per log inactivation. Using these figures, the RED delivered to a pathogen by a given UV reactor can be estimated from the measured RED of the challenge microorganism using Equation F. 10:

* *

c p c p RED RED RED RED ¥ = Equation F. 10 where REDP = RED of the pathogen estimated for the UV reactor of interest REDc = RED of the challenge microorganism measured during biodosimetry REDp = RED of the pathogen estimated from Figure F. 2 or F. 4 REDc = RED of the challenge microorganism estimated from Figures F. 2 or F. 4 The RED determined using Equation F. 10 represents the RED that would be delivered if the reactor under consideration had a dose distribution representative of a worst case commercial reactor.

Figure F. 4 Microorganism Inactivation and RED as a Function of Microorganism UV Sensitivity for the UV Reactor Represented in Figure F. 1 Example 5. A UV reactor is challenged using MS2 with a UV sensitivity of 18 mJ/ cm2 per log inactivation. Four log inactivation of the MS2 is observed corresponding to an MS2 RED of 4 ¥ 18 = 72 mJ/ cm2. The MS2 results are used to estimate the log inactivation of two pathogens, one with a UV sensitivity of 10 / cm2 per log inactivation and the other with a UV sensitivity of 25 mJ/ cm2 per log inactivation. In Figure F. 4, the RED delivered to the microorganisms with a UV sensitivity of 10, 18, and 25 mJ/ cm2 per log inactivation is 15, 19, Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 9 June 2003 Proposal Draft and 21 mJ/ cm2, respectively. Assuming the UV reactor's performance is bounded by a worst case represented by Figure F. 4, the RED delivered to the first pathogen is estimated between 72 mJ/ cm2 and ( 72 ¥ 15)/ 19 = 57 mJ/ cm2 and the RED delivered to the second pathogen is estimated between 72 and ( 72 ¥ 21)/ 19 = 80 mJ/ cm2. Inactivation of the first pathogen is estimated between 5.7 ( 57/ 10) and 7.2 ( 72/ 10) log and inactivation of the second pathogen is estimated between 2.9 ( 72/ 25) and 3.2 ( 80/ 25) log inactivation. This range of inactivation estimated using the worst case represented in Figure F. 4 is notably less than the range estimated in Example 3 using the worst case represented in Figure F. 3.

For regulatory purposes, the lower bound of the range of inactivation and RED estimated for the pathogen should be used when relating challenge microorganism inactivation to target pathogen inactivation. If the challenge microorganism is more sensitive to UV light than the pathogen or if both have the same sensitivity, the RED delivered to the pathogen should be estimated using the RED of the challenge microorganism. If the challenge microorganism is more resistant to UV light than the pathogen, the RED delivered to the pathogen should be estimated using Equation F. 10.

Example 6. A UV reactor is designed for three log Cryptosporidium inactivation. The dose needed for 3 log Cryptosporidium taken from Chapter 1 ( Table 1.4) is 12 mJ/ cm2. Accordingly, the UV sensitivity of Cryptosporidium is defined as 12/ 3 = 4 mJ/ cm2 per log inactivation. MS2 with a UV sensitivity of 18 mJ/ cm2 per log inactivation is used to measure the performance of the UV reactor. Because MS2 is more resistant to UV light than Cryptosporidium, Equation F. 10 is used to relate the RED measured using MS2 to the dose delivered to Cryptosporidium. From Figure F. 4, the RED delivered to the microorganisms with a UV sensitivity of 3.9 and 18 mJ/ cm2 per log inactivation is 9.8 and 19, respectively. Thus an MS2 RED of 12 ¥ 19/ 9.8 = 23 mJ/ cm2 should be demonstrated to show 3 log Cryptosporidium inactivation.

Example 7. A UV reactor is designed for one log adenovirus inactivation. The dose needed for 1 log adenovirus taken from Chapter 1 ( Table 1.4) is 58 mJ/ cm2. MS2 with a UV sensitivity of 18 mJ/ cm2 is used to measure the performance of the UV reactor. Because MS2 is less resistant to UV light than adenovirus, an MS2 RED of 58 mJ/ cm2 should be demonstrated to show 1 log adenovirus inactivation.

The RED of microorganisms with shoulders and tailing within the dose response curve depends on the overlap of the dose distribution with those regions ( Cabaj et al. 1996, Wright and Lawryshyn 2000). To use Figure F. 2 to define safety factors, the inactivation of the challenge microorganism should demonstrate an exponential inactivation as a function of dose over the range of doses in the dose distribution. This creates a dilemma if the dose distribution is not known. To avoid this issue, the dose response of an appropriate challenge microorganism should not demonstrate a shoulder at a dose beyond 50 percent of the demonstrated RED and should not demonstrate tailing until one log inactivation beyond the demonstrated inactivation. In the case of a challenge microorganism with a shoulder and tailing in the dose response, the UV sensitivity will be defined as the sensitivity over the region of exponential inactivation that occurs between the shoulder and the onset of tailing. The shoulder of the dose response is defined by the intersect of the exponential region with the dose axis ( see Figure F. 5). Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 10 June 2003 Proposal Draft Example 8. Figure F. 5 presents the measured UV dose response of B. subtilis spores. Because the measured dose response has a shoulder of 16.5 mJ/ cm2, the B. subtilis spores should only be used to demonstrate RED values greater than or equal to 2 ¥ 16.5 = 33 mJ/ cm2.

Figure F. 5. UV Dose Response of B. subtilis Spores ( Adapted from Sommer et al. 1998)

The RED safety factor provides an incentive to select a challenge microorganism whose UV sensitivity matches that of the target pathogen and a disincentive for overrating UV reactor performance by using challenge microorganisms whose UV sensitivity is much greater than the target pathogen.

F .1.3 Biodosimetry Using Two Challenge Microorganisms In order to provide a better estimate of the target pathogen's log inactivation and RED, two microorganisms with different UV sensitivities can be used to validate UV reactors. The target pathogen's log inactivation should be estimated by interpolating the log inactivation of the two microorganisms as a function of the UV sensitivity defined on a linear scale as a first order inactivation coefficient. Alternatively, the target pathogen's RED should be estimated by interpolating the RED of the two microorganisms as a function of the UV sensitivity defined on a linear scale as dose per log inactivation. If interpolation does not meet these provisions, the inactivation of the pathogen will be overestimated.

Example 9. A UV reactor with a dose distribution represented in Figure F. 4 is tested using MS2 and fX174. The MS2 and fX174 have a UV sensitivity of 18 and 2 mJ/ cm2 per log inactivation. Using biodosimetry, 1.1 and 3.6 log inactivation of MS2 and fX174 are measured. These log inactivations correspond to RED values of 20 and 7.2 mJ/ cm2, respectively. The RED measured with MS2 and fX174 is fit as a function of UV sensitivity resulting in the following equation: Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 11 June 2003 Proposal Draft 83 . 5 731 . 0 + ¥ = y Sensitivit UV RED This equation predicts that the RED delivered to Cryptosporidium, defined with a UV sensitivity of 3.9 mJ/ cm2 per log inactivation, is 8.7 mJ/ cm2.

If the inactivation of the more UV sensitive of the two challenge microorganisms is greater than the detection limit of the assay, interpolation should be based on the level indicated by the limitation. Because the inactivation of the UV sensitive microorganism is underestimated, the interpolation will be conservative and two microorganism validation may not offer an advantage over single microorganism validation.

Example 10. A UV reactor is evaluated using MS2 and fX174 phage. MS2 and fX174 are injected into the flowrate upstream of the reactor. Influent and effluent samples are collected and assayed. The assay has a detection limit of 1 pfu/ mL. The concentrations of MS2 and fX174 in the influent is determined as 1,000,000 and 10,000 pfu/ mL, respectively. The concentrations of MS2 and fX174 in the effluent samples are 10,000 and 0 pfu/ mL, respectively. The results indicate that the concentration of fX174 is below the detection limit of the assay. Accordingly, the log inactivation of MS2 and fX174 is 2 log and > 4 log, respectively. If the UV sensitivity of MS2 and fX174 are determined to be 20 and 2 mJ/ cm2 per log, the MS2 RED is 40 mJ/ cm2 and the fX174 RED is > 8 mJ/ cm2. The following equation fits the measured RED as a function of UV sensitivity:

44 . 4 77 . 1 + ¥ = y Sensitivit UV RED This equation predicts that the RED delivered to Cryptosporidium defined with a UV sensitivity of 3.9 mJ/ cm2 per log is 11.3 mJ/ cm2. This compares to an RED of 20 mJ/ cm2 that would have been predicted by Equation F. 10 using the MS2 data alone. In this case, twomicroorganism biodosimetry estimated lower dose delivery to Cryptosporidium than single microorganism biodosimetry.

In the past, it has been assumed that the RED measured with a UV resistant challenge microorganism can be used to demonstrate compliance with a dose target while the log inactivation demonstrated with a UV sensitive challenge microorganism can be used to demonstrate compliance to a log inactivation target. This approach is not recommended. It is not possible to demonstrate compliance to a 3 log Cryptosporidium inactivation by using UVresistant MS2 to show an RED of 11.7 mJ/ cm2 and using UV sensitive fX174 to show 3 log inactivation.

E xample 11. In Example 9, even though the RED measured with MS2 was 18 mJ/ cm2 and the log inactivation measured with fX174 was 3.6 log, Figure F. 4 shows that Cryptosporidium, defined with a UV sensitivity of 3.9 mJ/ cm2 per log, experienced a log inactivation of 2.5 corresponding to an RED of 9.8 mJ/ cm2. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 12 June 2003 Proposal Draft F. 1.4 Challenge Microorganism Selection Ideally, UV reactor performance should be validated with a microorganism whose UV sensitivity matches that of the target pathogen. In this guidance document, the UV sensitivity of the target microorganisms is given by the dose requirements given in Chapter 1 for Cryptosporidium, Giardia, and virus. Challenge microorganisms currently used to validate UV reactors do not have a UV sensitivity that matches the UV sensitivity of the target pathogens as defined in Chapter 1. The UV resistance of MS2 and B. subtilis spores is notably greater than that of Cryptosporidium and Giardia, and notably less than that of adenovirus. Furthermore, demonstrating 3 or 4 log virus inactivation with these challenge microorganisms necessitates demonstrating REDs greater than 150 mJ/ cm2. These REDs correspond to greater than 6 log inactivation of MS2 and B. subtilis spores. Currently, culturing titers of challenge microorganisms needed to demonstrate greater than 6 log inactivation are not practical.

A challenge microorganism should have reproducible UV inactivation kinetics over the dose range of interest. The challenge microorganism should be easily prepared in high titers, easily enumerated by an assay based on microorganism replication, non pathogenic to humans, and not harmful to the environment. If the challenge microorganism is a phage, the host bacteria used to assay the phage concentration should not be pathogenic to humans. MS 2 phage, non pathogenic Escherichia coli, B. subtilis spores, and Saccharomyces cerevisae have been used to bioassay UV reactors designed to treat drinking water. Table F. 1 summarizes the UV sensitivity of commonly used and candidate bioassay microorganisms.

Table F. 1 UV Sensitivity of Bioassay Microorganisms and Candidates Dose ( mJ/ cm2) Reported to Achieve Microorganism 1 log 2 log 3 log 4 log Reference MS 2 phage 16 34 52 71 Wilson et al. 1992 E. Coli 3.0 4.8 6.7 8.4 Chang et al. 1985 B. subtilis spores 28 39 50 62 Sommer et al. 1998 fx174 phage 2.2 5.3 7.3 11 Sommer et al. 1998 B40 8 phage 12 18 23 28 Sommer et al. 1998 PRD 1 phage 9.9 17 24 30 Meng and Gerba 1996 F. 2 Dose Monitoring There are three approaches currently used to monitor dose delivery. In this guidance document, the terms used are as follows:

· UV intensity setpoint approach · UV intensity and UVT setpoint approach · Calculated dose approach Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 13 June 2003 Proposal Draft With the UV intensity setpoint approach, dose delivery is indicated by measured flowrate and UV intensity. The UV reactor complies with a required dose delivery when the measured UV intensity is above an alarm setpoint value defined as a function of flowrate through the reactor. With this approach, the UV intensity sensor should be positioned far enough from the lamp that it provides measurable responses to changing water UV absorbance ( and corresponding UVT) as well as lamp output. With the UV intensity and UVT setpoint approach, dose delivery is indicated by measured flowrate, UV intensity, and UVT. The UV reactor complies with a required dose delivery when the measured UV intensity and UVT are above alarm setpoint values, both defined as a function of flowrate through the reactor. With this approach, the UV intensity sensor should be positioned relatively close to the lamp so that it responds primarily to changing lamp output. With the calculated dose approach, dose delivery is indicated by a dose value calculated from measured flowrate, UV intensity, and UVT. The UV reactor complies with a required dose delivery when the calculated dose is above an alarm setpoint value. With this approach, there are no requirements for sensor positioning.

To illustrate the UV intensity setpoint approach and the UV intensity and UVT setpoint approach, Figures F. 6, F. 7, and F. 8 present the relationship between UV dose and measured UV intensity for an annular reactor containing a single LP lamp. UV intensity was calculated using a radial UV intensity model and UV dose was calculated assuming ideal hydraulics ( Haas and Sakellaropoulos 1979). UV intensity and dose were calculated for a fixed flowrate of 400 gpm, water UVT ranging from 60 to 98 percent, and lamp output ranging from 20 to 100 percent. In each figure, data are presented as plots of dose versus UV intensity sensor reading for values of UVT specified in the legend. For each of those plots, each point at a given UVT represents, in order of increasing dose, operation at 20, 40, 60, 80, and 100 percent lamp power. The differences between these figures are due to sensor placement.

Figure F. 6 Relationship between UV Dose and Intensity for a UV Intensity Sensor Located to Give Dose Proportional to Measured Irradiance 0 10 20 30 40 50 60 70 0 20 40 60 Sensor ( mW/ cm2) Dose ( mJ/ cm2)

60%

70%

80%

85%

90%

94%

98% S UVT 254 nm 400 GPM Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 14 June 2003 Proposal Draft Figure F. 7 Relationship between UV Dose and Intensity for a UV Intensity Sensor Located Close to the Lamp Figure F. 8 Relationship between UV Dose and Intensity for a UV Intensity Sensor Located Far from the Lamp F. 2.1 UV Intensity Setpoint Approach Figure F. 6 presents the relationship obtained when the UV intensity sensor is located at a distance from the lamps where UV dose is proportional to measured UV intensity regardless of the UVT and lamp output. With an ideal reactor, this sensor location occurs where the measured intensity equals the average intensity within the reactor. Because of the proportional relationship between dose delivery and measured intensity, a given intensity can be related to a specific level of dose delivery.

Example 12. The UV reactor characterized in Figure F. 6 is used in a disinfection application needing a UV dose of 20 mJ/ cm2. At a flowrate of 400 gpm, a UV intensity value S 0 10 20 30 40 50 60 70 0 5 10 15 20 Sensor ( mW/ cm2) Dose ( mJ/ cm2)

60% 70% 80% 85% 90% 94% 98% S UVT 254 nm 400 GPM S' 0 10 20 30 40 50 60 70 0 20 40 60 80 100 120 140 160 Sensor ( mW/ cm2) Dose ( mJ/ cm2)

60%

70%

80%

85%

90%

94%

98% S UVT 254 nm 400 GPM S' Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 15 June 2003 Proposal Draft of 18 mW/ cm2 is used as an alarm setpoint to indicate the UV reactor delivers a dose of 20 mJ/ cm2. This alarm setpoint value will indicate a dose of 20 mJ/ cm2 regardless of the UVT of the water and the output of the lamps.

Figure F. 7 presents the relationship between dose delivery and measured UV intensity when the UV intensity sensor is placed closer to the lamp than the sensor in Figure F. 6. Because the sensor views the lamp through a relatively thin water layer, the sensor response to changing UVT is small compared to that in Figure F. 6. Accordingly, the relationship between dose delivery and measured intensity for different values of UVT cannot be described by a single proportional relationship. Unlike Figure F. 6, a given UV intensity is not related to a specific level of dose delivery but is related to a range of delivered doses. Accordingly, the measured UV intensity should only be used to indicate dose delivery at the lower end of that range, which occurs under conditions of maximum lamp power and reduced UVT.

Example 13. The UV reactor characterized in Figure F. 7 is used in an application needing a UV dose of 20 mJ/ cm2. The UV manufacturer states that a UV intensity value S of 80 mW/ cm2 will indicate a dose of 20 mJ/ cm2 under design conditions of 85 percent UVT and 60 percent lamp output. However, as shown in Figure F. 7, an intensity of 80 mW/ cm2 corresponds to a dose ranging from 5 to 37 mJ/ cm2. The lower end of this range occurs with lamp powers higher that 60 percent and water UVT lower than 85 percent. For a UV intensity alarm setpoint to ensure a dose of 20 mJ/ cm2 under all possible conditions of the water UVT and lamp output, a setpoint value S' of 134 mW/ cm2 should be chosen.

Figure F. 8 presents the relationship between dose delivery and measured UV intensity when the UV intensity sensor is located further from the lamps than the sensor in Figure F. 6. Because the sensor views the lamp through a relatively thick water layer, the sensor response to changing water transmittance is large compared to that in Figure F. 6. Like Figure F. 7, the relationship between dose delivery and measured intensity for different values of UVT cannot be described by a single proportional relationship. As such, a given intensity value is related to a range of dose values as opposed to a single value. Again, the measured UV intensity should only be used to indicate dose delivery at the lower end of that range. However, unlike Figure F. 7, the lower end of the range occurs under conditions of reduced lamp power and maximum UVT.

Example 14. The UV reactor characterized in Figure F. 8 is used in an application needing a UV dose of 20 mJ/ cm2. The UV reactor uses the UV intensity setpoint approach to monitor dose delivery. A UV intensity alarm setpoint value S of 4 mW/ cm2 is proposed based on the UV intensity measured under design conditions of 85 percent UVT and 60 percent lamp output. However, an intensity of 4 mW/ cm2 indicates a dose ranging from 9 to 26 mJ/ cm2. To indicate a dose of 20 mJ/ cm2 using the UV intensity setpoint approach, a setpoint value S' of 8 mW/ cm2 should be chosen.

The location of the UV intensity sensor within a UV reactor is selected by the manufacturer of the UV reactor. If the UV reactor uses the UV intensity setpoint approach for dose monitoring, the UV manufacturer should optimize the UV intensity sensor's location to give a proportional relationship between dose delivery and measured UV intensity similar to the example given in Figure F. 6. If the UV manufacturer does not optimize the UV intensity sensor's location, a given UV intensity will correspond to a range of UV doses values as opposed to a single value. While this does not prevent the UV reactor from using the UV intensity Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 16 June 2003 Proposal Draft setpoint approach, the monitoring approach will not be as efficient as with an optimally located sensor because the UV reactor will be overdosing at many combinations of UVT and lamp power that given rise to operation at the setpoint.

F. 2.2 UV Intensity and UVT Setpoint Approach If the UV intensity sensor is not at a location optimal for the UV intensity setpoint approach, measurements of UVT can be used to provide more efficient dose monitoring. UVT alarm setpoints combined with UV intensity alarm setpoints can be used to indicate dose delivery providing the UV intensity sensor is placed relatively close to the lamp. With the sensor located relatively close to the lamp, dose delivery at a given intensity and flowrate decreases with decreasing UVT ( Figure F. 7). Accordingly, a UVT alarm setpoint combined with a UV intensity alarm setpoint provides a meaningful indicator of dose delivery.

Example 15. The UV reactor characterized in Figure F. 7 is used in an application needing a UV dose of 20 mJ/ cm2. If the UV reactor used the UV intensity setpoint approach to monitor dose delivery, an alarm setpoint S' of 134 mW/ cm2 would be used to indicate a dose delivery of 20 mJ/ cm2. This approach is not efficient because a UV intensity of 134 mW/ cm2 is associated with a UV dose ranging from 20 to 60 mJ/ cm2. An alternative approach for dose monitoring is to use the UV intensity and UVT setpoint approach. Under this approach, a UV intensity alarm setpoint S of 80 mW/ cm2 combined with a UVT alarm setpoint of 85 percent will indicate a dose delivery of 20 mJ/ cm2. However, the approach is still inefficient because UV dose may range from 20 to 38 mJ/ cm2 with operation of the reactor at the setpoint conditions.

If the UV intensity sensor is located at the optimal position for the UV intensity setpoint approach ( Figure F. 6), the UVT reading does not provide any additional information on dose delivery that is not provided by the measured UV intensity. However, the measured UVT could be used to indicate whether a UV intensity alarm condition arises from low UVT.

If the UV intensity sensor is located too far from the lamp, dose delivery at a given UV intensity and flowrate increases with decreasing UVT ( Figure F. 8). As such, the UVT reading cannot be used as an alarm setpoint to indicate dose delivery.

E xample 16. The UV reactor characterized in Figure F. 8 uses the UV intensity and UVT setpoint approach to show the UV reactor delivers a dose of 20 mJ/ cm2. The intensity alarm setpoint is set to 5 mW/ cm2 and the UVT alarm setpoint is set to 90 percent. If the reactor was operating with a measured UVT and UV intensity of 85 percent and 5 mW/ cm2, the delivered dose would be 28 mJ/ cm2. If the reactor was operating with a UVT and UV intensity of 98 percent and 5 mW/ cm2, respectively, the delivered dose would be 12 mJ/ cm2. Thus the two alarm setpoint values are not ensuring the UV reactor complies with a dose of 20 mJ/ cm2. To remedy this problem, the UV manufacturer should either uses the UV intensity setpoint approach, move the UV intensity sensor closer to the lamps, or use the calculated dose approach to monitor dose delivery. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 17 June 2003 Proposal Draft F. 2.3 Calculated Dose Approach Measurements of flowrate, UV intensity, and UVT can be incorporated into theoretical, empirical, or semi empirical calculations of dose delivery. For example, the relationships represented in Figures F. 6 to F. 8 could be defined experimentally and used in an empirical manner to calculate dose. Relationships could also be defined using advanced modeling approaches and used to relate measured intensity to dose delivery for a given flowrate and UVT. In theory, the dose calculation does not necessitate that the sensor be placed at any one location within the reactor. However, if the sensor placed at a location that gives dose delivery proportional to the sensor reading, the dose calculation does not require UVT as an input parameter.

F. 2.4 Validating Dose Monitoring The test conditions used to validate a UV reactor should depend on the approach used to monitor dose delivery.

If the UV reactor uses the UV intensity setpoint approach, the UV reactor is validated by measuring the dose delivery with the UV intensity adjusted to the UV intensity alarm setpoint value. The combination of lamp power and UVT used to achieve operation at the alarm setpoint should be selected to capture the lower end of the dose range associated with the setpoint. If the UV intensity sensor is located closer to the lamp than the optimal location, the UV reactor should be validated at peak lamp power and lowered UVT. If the UV intensity sensor is located further from the lamp than the optimal location, the UV reactor should be validated at peak UVT and lowered lamp power. If the positioning of the UV intensity sensor relative to the optimal location is not known prior to validation testing, the UV reactor should be validated using both test conditions. If the dose values measured with both test conditions are the same, the UV intensity sensor is at the optimal location.

If the UV reactor uses the UV intensity and UVT setpoint approach, the UV reactor is validated by measuring dose delivery with the UV intensity and UVT adjusted to the alarm setpoint values. Validation should also confirm that the UV intensity sensor is located close enough to the lamp that UVT alarm setpoint values provide a meaningful indicator of dose delivery. This is accomplished by showing that dose delivery decreases with decreasing UVT while the UV intensity is held constant at the intensity alarm setpoint value. If dose delivery increases with decreased UVT, the UV intensity sensor is located too far from the lamp and this monitoring approach will not work.

If the reactor uses dose calculations, validation testing confirms that dose delivery is greater than or equal to the calculated dose. Validation testing is conducted at various combinations of flowrate, lamp output, and UVT that result in performance at a target dose. This proves the dose calculation is robust over the range of those variables expected with operation of the reactor at a water treatment plant ( WTP). Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 18 June 2003 Proposal Draft F. 3 UV Intensity Sensors UV reactors should be equipped with at least one on line UV intensity sensor that measures the UV intensity at some point within the UV reactor. Measurements made by the on line UV sensors are used to indicate dose delivery by the UV reactor. Reference sensors are used to check that the measurements made by the on line sensors are valid.

F. 3.1 UV Sensor Properties The UV sensor may or may not measure the UV light through a monitoring window that is separate from the sensor body. The monitoring windows should have a high UVT over the spectral response range of the UV sensors.

The UV intensity sensor should detect germicidal UV radiation and produce a standardized output signal ( e. g., 4 to 20 mA) proportional to the UV irradiance incident on the sensor. UV intensity sensors should be calibrated to an absolute irradiance standard and have a suitable measurement range, angular response, spectral response, linearity, and stability for monitoring and controlling UV dose delivery by the UV reactor. An ideal UV intensity sensor has a linear response to incident UV irradiance that is independent of water temperature and does not degrade with time. Furthermore, the ideal sensor has a fixed angular response and a wavelength response that mimics the germicidal response of microorganisms.

UV intensity sensors provided by the manufacturer should be individually calibrated. UV intensity sensors used to monitor LP lamps are often calibrated using the substitution method ( Larason et al. 1998). With this approach, the intensity of a collimated beam of UV light at 254 nm is measured using the UV sensor and compared to that made using a standard measurement, such as a National Institute of Standards and Technology ( NIST) traceable sensor or chemical actinometer. The ratio of the standard measurement to the sensor output is the calibration factor. With sensors designed to measure the output of medium pressure ( MP) lamps, the sensor can be either calibrated at 254 nm, calibrated as a function of wavelength, or calibrated using polychromatic light from a MP lamp with a known spectral output. Regardless of the approach used, the calibration should be traceable to some absolute measurement standard and have a quantified measurement uncertainty.

Sensor linearity is determined by comparing the sensor output as a function of incident irradiance to standard measurements of that irradiance. Sensor temperature response is determined by measuring the dependence of sensor output on the sensor's operating temperature with the sensor measuring a constant irradiance. Both linearity and temperature response should be determined over the range of irradiance and temperature expected with the operation of the UV reactor at the WTP. Angular response of a sensor is determined by measuring the dependence of the sensor output on the incident angle of collimated UV light of fixed intensity.

The spectral response of a sensor is determined by measuring the dependence of the sensor output on the wavelength of monochromatic light of known irradiance incident on the sensor. Spectral response is typically presented as a plot of the ratio of sensor output to incident irradiance as a function of the wavelength of light. Because it may be affected by infrared Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 19 June 2003 Proposal Draft transmission of glass filters and fluorescence of diffusers that are part of the sensor ( Larason and Cromer 2001), UV intensity sensor spectral response should be evaluated from 200 to 1000 nm.

The long term stability of a UV sensor is best determined using field data but may be estimated using accelerated life cycle testing. The measurement accuracy of UV sensors can change over time with operation and environmental exposure. Temperature cycling, exposure to UV light, mechanical vibration, and other factors will impact the linear, spectral, angular, and temperature response of a sensor.

The UV sensor manufacturer should conduct regular testing on manufactured UV sensors to develop a database on sensor properties. While some sensor properties may be measured with each sensor, other properties, such as long term stability, can only be measured on a representative lot size. The sensor manufacturer should have available for inspection the following information:

· Description of the properties measured · Description of the measurement system used to measure each property · Description of the measurement standards used · Documented uncertainty of each measurement · Description of QA/ QC procedures used to ensure the measurements are traceable · Data collected over time that demonstrates that the properties of the manufactured sensors meet specifications F .3.2 UV Intensity Sensor Measurement Uncertainty The measurement uncertainty of a UV intensity sensor quantifies how the measurement of UV intensity made by the sensor when mounted on the UV reactor compares with the true value. For the purposes of this guidance document, UV intensity sensor uncertainty should be determined at a 90 percent confidence level by summing the uncertainty that arises from the calibration, linearity, angular and spectral response, temperature response, and long term stability.

The uncertainty of sensor calibration depends on the uncertainty of the standards and instrumentation used to calibrate the sensor, such as voltmeters and amplifiers. Uncertainty arises from linearity and temperature response because sensor calibration factors, determined at a given temperature and UV irradiance, are used over a range of temperatures and irradiances with operation of the sensor with the UV reactor. Uncertainty arises with sensor degradation because calibration factors are determined on new sensors.

Uncertainty arises with angular response because sensors, calibrated using collimated UV light, are used in UV reactors to measure UV light impacting from different directions. Uncertainty arises with spectral response because sensors, calibrated at a fixed wavelength, are Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 20 June 2003 used in UV reactors equipped with MP lamps. Variability in spectral and angular response from sensor to sensor will result in a measurement uncertainty not accounted for in calibration. The impact of spectral and angular response variability on sensor measurement uncertainty can be determined either by calculation or by measurement. In the first approach, the sensor spectral and angular response measured on a representative lot size is used as an input to a model that predicts sensor readings in a UV reactor. The variability in the sensor readings predicted by the model is used to define an uncertainty term that is included in the calculation of sensor uncertainty. In the second approach, the variability in measurements made by a representative number of sensors mounted on the UV reactor is used to define the uncertainty.

Example 17. A UV sensor manufacturer calibrates each manufactured UV intensity sensor at 20 ° C with an uncertainty of 5 percent. UV intensity sensor linearity, temperature response, angular response, and spectral response is evaluated on every tenth sensor manufactured. Linearity ranges from 1 to 3 percent over the measurement range of the sensor. Temperature response ranges from 0.1 to 0.2 percent per C ° , or an uncertainty of 4 percent from 0 to 40 ° C. Models predict that the variability in angular and spectral response from sensor to sensor will cause uncertainties of 8 and 4 percent, respectively. An evaluation of sensors returned from the field indicates that the long term drift over a one year period is 10 percent. The measurement uncertainty of the sensors is calculated as the square root of the sum of the squares of the individual uncertainties as per:

percent 15 10 4 8 4 3 5 M 2 2 2 2 2 2 = + + + + + = ty uncertain easurement F. 3.3 On line and Reference UV Intensity Sensors Degradation in UV intensity sensor performance can lead to significant under or overestimations of dose delivery by the UV reactor's on line monitoring system. To prevent underdosing, the measurement uncertainty of the UV intensity sensors should be incorporated as a safety factor into the sizing and operation of a UV installation and the performance of the online sensor should be regularly checked by use of a reference sensor. Measurements made by the on line and reference sensor should meet the following equation:

[ ] 2 / 1 2 Duty 2 Ref Ref Duty     100 1 I I +   ×

       Equation F. 11 where IRef = Intensity measured with the reference sensor ( W/ m2) IDuty = Intensity measured with the duty sensor ( W/ m2)  Ref = Measurement Uncertainty of the reference UV intensity sensor (%)  Duty = Measurement Uncertainty of the duty UV intensity sensor (%)

If this condition is not met, the cause for the discrepancy should be determined and resolved. Typically, the discrepancy indicates degradation of the on line sensor that necessitates recalibration or replacement.

Proposal Draft Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 21 June 2003 Proposal Draft Example 18. A UV reactor uses on line sensors with an uncertainty of 15 percent. A reference sensor with an uncertainty of 5 percent is used to check the on line sensors when the UV reactor is operating at the WTP. Measurements made by the on line sensors are considered out of spec when:

[ ] % 16 5 15 100 1 I I 1/ 2 2 2 Ref Duty = + £ ¥

F. 3.4 Positioning of UV Intensity Sensors While the UV output along the length and around the circumference of a new UV lamp will be relatively uniform, this may not be true with aged or fouled lamps. Sputtering of electrode material leads to deposits on the inside of the lamp sleeve within 2 or 3 inches from the electrode. Discoloration of the lamp sleeve with lamp aging varies along the length of the lamp. Sleeve fouling varies spatially both along the length and circumference of the lamp sleeve ( Lin et al. 1999).

If lamps experience non uniform aging along their length, the UV intensity sensor should be located to monitor the section along the lamp that experienced the greatest decrease in UV output with aging. The sensor should not be located to monitor the section that experiences the least decrease in UV output.

F. 3.5 Number of UV Intensity Sensors Variability in UV output from lamp to lamp impacts both dose delivery and monitoring. A lamp with a lower output will deliver lower doses to microorganisms passing in its vicinity, thereby shifting the dose distribution to lower values and reducing the net performance of the reactor. The shift in the dose distribution will be more pronounced with a reactor with fewer lamps. Because the dose distribution is affected, the impact on net performance will be greater with a more UV sensitive microorganism. If the number of UV intensity sensors is less than the number of lamps and the sensors monitor those lamps with the highest output, the monitoring system will overestimate dose delivery by the UV reactor.

The monitoring strategy used to ensure that UV dose delivery meets regulatory targets should account for the variability of UV output from lamp to lamp. If each lamp in the reactor is monitored by a UV intensity sensor, dose delivery compliance should be based on the lowest lamp output, unless an accepted and validated dose calculation methodology can account for lamp to lamp variability. If the number of sensors used is less than the number of lamps, either the lamp with the lowest output should be monitored and used for dose compliance, or the setpoint used for dose delivery compliance should include a safety factor to account for lamp tolamp variability.

E xample 19. A UV reactor installed at a WTP is equipped with four lamps and two UV intensity sensors. Because of variability in lamp output, the UV intensity 5 cm from each lamp is 15, 10, 8, and 20 mW/ cm2, respectively. If one sensor monitors the first lamp and the second Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 22 June 2003 Proposal Draft monitors the forth lamp, the monitoring system will over estimate the dose delivery by the UV reactor because microorganisms passing by the second and third lamps will receive lower doses than the microorganisms passing by the first and fourth lamps.

During UV reactor validation, variability in UV output from lamp to lamp should not cause the UV reactor to be overrated. If the number of sensors is less than the number of lamps, the sensors should be monitoring the lamps with the lowest output. If UV intensity sensors record different values during validation, intensity setpoints and calculations should be based on the lowest values recorded.

Example 20. A UV reactor undergoing validation is equipped with four lamps and two sensors. Dose delivery is monitored using the UV intensity setpoint approach. Because of variability in lamp output, the UV intensity 5 cm from each lamp is 10, 15, 8, and 12 mW/ cm2, respectively. To ensure validation results are meaningful, the sensors should be monitoring the first and third lamps.

F. 4 Polychromatic Considerations With UV reactors equipped with LP or low pressure high output ( LPHO) lamps, dose delivery and monitoring occurs at a single wavelength of 254 nm. With UV reactors equipped with MP lamps, dose delivery and monitoring involves a response to multiple wavelengths. Dose delivery is an integrated response to UV light from 200 to 320 nm. The output from the UV intensity sensor is an integrated response to UV light over wavelengths spanning the sensor's spectral response. UV absorbance monitors typically measure UV absorbance at a single wavelength of 254 nm. If the spectral properties of the UV reactor that influence dose delivery and monitoring during operation of the UV installation at a WTP are the same as the spectral properties during validation, then the same dose delivery and monitoring characterized during validation will occur at the WTP. However, if the spectral properties are different, dose delivery and monitoring at the WTP will differ from dose delivery and monitoring measured during validation. The following spectral properties may differ:

· Action spectra of the challenge microorganism used during validation and the target pathogen · Spectral UV absorbance of the water during validation and at the WTP · UV output of the lamps during validation and at the WTP · UVT of the lamp sleeves during validation and at the WTP Safety factors should be applied to the validation data for polychromatic UV reactors if spectral differences will lead to under dosing at the WTP. This section describes approaches for assessing the impact of differences in spectral properties and deriving those safety factors. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 23 June 2003 Proposal Draft F. 4.1 Action Spectra The dependence of microorganism inactivation kinetics on UV wavelength may be described using an action spectrum  the UV inactivation sensitivity as a function of wavelength ( Figure F. 9). Ideally, the action spectrum of the challenge microorganism used to validate a polychromatic UV reactor would either match that of the target microorganism or provide a conservative estimate of inactivation.

Figure F. 9 Action Spectra for Various Microorganisms1 1 ( Adapted from Rauth 1965)

The impact of various action spectra on UV dose delivery may be estimated by calculating the germicidal lamp output using Equation F. 12:

( ) ( )

 = D = 320 200 l l l l G P P G Equation F. 12 where PG = Germicidal output of the MP lamp ( W/ cm)  = Wavelength ( nm) P(  ) = Lamp output ( W/ nm) measured over 1 nm increments at wavelength  G(  ) = Relative UV sensitivity of the microorganism at wavelength  Dl = 1 nm increment Using the action spectra published for fourteen microorganisms ( Rauth 1965, Cabaj et al. 2002, Linden 2001), Table F. 2 presents the germicidal lamp output calculated for a MP lamp and the ratio of that output to that of Cryptosporidium. A ratio greater than one indicates that the action spectra of the microorganism favors greater inactivation than the action spectra of Cryptosporidium. If a challenge microorganism with a ratio greater than one is used to validate a 0.0 0.5 1.0 1.5 2.0 2.5 225 235 245 255 265 275 285 295 305 Wavelength ( nm) Action relative to 254 nm Herpes simplex MS2, R 17, fr, 7 S oX 174 T2 Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 24 June 2003 Proposal Draft MP reactor for Cryptosporidium inactivation, the ratio should be used as a correction factor to account for the greater inactivation of the challenge that arises from the differences in action spectra. In the case of MS2 and B. subtilis, the ratio is close to one and the correction is small. However, based on the data in Table F. 2, a correction factor of 1.16 would be needed with UV reactors equipped with MP lamps if fX174 was used to show Cryptosporidium inactivation.

Table F. 2 Germicidal Output Delivered to 14 Microorganisms by a MP Lamp Microorganism Type / Nucleic acid ( SS = Single Strand, DS = Double Strand) Germicidal Output ( W/ cm) Germicidal Output Relative to Cryptosporidium Cryptosporidium oocysts DS DNA 5.64 1.00 MS 2, R 17, fr, 7 S Phage / SS RNA 5.78 1.04 B. subtilis spores DS DNA 5.58 0.99  X174 Phage / DS DNA 6.53 1.16 Reovirus 3 Animal virus / DS RNA 7.46 1.32 Polyoma Animal virus / DS DNA 6.74 1.18 T2 Phage / DS DNA 6.05 1.07 VSV Animal virus / RNA 5.53 0.99 Vaccinia Animal virus / DS DNA 5.46 0.98 EMC Animal virus / SS RNA 5.98 1.07 Herpes simplex Human virus / DS DNA 7.00 1.26 The germicidal output of the MP lamp calculated using the action spectra of B. subtilis spores and MS2 is equal to or less than that of most of the 14 microorganisms listed in Table F. 2. It is thus reasonable to assume that these microorganisms are acceptable as challenge microorganisms for many pathogens whose action spectrum is not known, like adenovirus and Giardia. However, if an alternative challenge microorganism is to be used, its action spectra should be assessed for suitability.

As an alternate approach to measuring the action spectrum and using Equation F. 12, the correction factor can also be estimated by comparing the dose response of the challenge microorganism to that of MS2 measured with a LP and MP lamp. The correction factor would be defined as:

MS2 MP LP Challenge LP MP k k k k 1.04 r Facto Safety                 = Equation F. 13 where kMP = Slope of the dose response measure with the MP collimated beam ( cm2/ mJ) kLP = Slope of the dose response measure with the LP collimated beam ( cm2/ mJ) 1.04 = Germicidal output of MS2 relative to Cryptosporidium, from Table F. 2 Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 25 June 2003 Proposal Draft The correction factor that accounts for differences in the action spectra is not the same correction factor that accounts for differences in the UV sensitivity described in section F. 1.2. The correction factor described in section F. 1.2 applies to all UV reactors regardless of lamp type. The correction factor described in this section is applicable to MP reactors. It should be used in addition to the correction factor described in section F. 1.2.

F .4.2 Water Absorption During UV reactor validation, a UV absorbing chemical is added to the water passing through the reactor in order to simulate high UV absorbance events that could occur at the WTP. UV absorbing chemicals that have been used to validate UV reactors include sodium thiosulfate, fluorescein, coffee, tea, and parahydroxybenzoic acid. Ideally, the spectral absorption of the water used to validate UV reactors equipped with MP lamps should match the spectral absorption of the water at the WTP over the wavelength range associated with dose delivery and monitoring ( Figure F. 10).

Figure F. 11 compares the UV absorbance spectra of coffee and lignin sulphonate to that of two drinking water sources ( Water A and Water B). For a given UVT at 254 nm, the UV absorption at wavelengths above and below 254 nm is greater with coffee, tea, and lignin sulphonate than with the drinking water sources. If those chemicals are used during validation of a MP reactor, the RED and UV intensity measured at a given flowrate, lamp output, and water UVT will be lower during validation than at the WTP.

Figure F. 10 Spectral UV Absorption of Water at Various WTPs Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 26 June 2003 Proposal Draft Figure F. 11 Comparison of the UV Absorbance Spectrum of Additives used during UV Reactor Validation to the UV Absorbance of Two Finished Waters The impact of the difference in the UV absorbance spectra on the measured intensity will depend on sensor placement relative to the lamps. If the sensor is located close to the lamps, the sensor reading during validation will be only slightly lower than the reading at the WTP. Accordingly, for a given sensor reading, flowrate, and water UVT, the RED delivered at the WTP will be greater than the RED measured during validation. However, if the sensor is placed far enough from the lamp, the UV intensity measured during validation will be much lower than the reading at the WTP. As such, for a given sensor reading, flowrate, and water UVT, the RED delivered at the WTP will be less than the RED measured during validation. If the UV intensity sensor's spectral response mimics the microorganism's action spectra and the sensor is located at a position where the dose delivery is proportional to the sensor reading, the RED delivered at the WTP will equal the RED measured during validation, even with the differences in the UV absorbance spectra shown in Figure F. 11 ( Wright et al. 2002). However, this relationship will not hold true if the sensor's spectral response deviates sufficiently from the microorganism's action spectra.

Modeling approaches can be used to predict and compare the RED and UV intensity sensor readings obtained during validation to those expected at a WTP. The modeling approach can be used to define correction factors applicable to validation results to ensure dose monitoring provides valid measurements at the WTP. UV intensity readings should be predicted using polychromatic intensity models that factor in the spectral and angular response of the sensor. While RED predictions could be obtained using CFD based dose modeling approaches, ideal dose delivery models should be used to provide conservative correction factors. The ideal dose delivery model is conservative because the sensor location within a reactor where the dose delivery is proportional to sensor reading is predicted to occur closer to the lamp with the ideal model than with a CFD based dose delivery model ( Wright et al. 2002). As such, the transition to a correction factor greater than one occurs with closer sensor to lamp distance with the ideal dose delivery model than with the CFD based dose delivery model. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 27 June 2003 Proposal Draft Table F. 3 provides predictions of dose delivery and sensor measurements for an ideal annular reactor. The reactor consists of a cylinder with an 18.81 cm radius and a length greater than the arc length of the lamp. The reactor is equipped with a single MP lamp oriented along the central axis of the cylinder ( i. e., at a radius of 0 cm). The lamp is housed in a lamp sleeve with a radius of 3.81 cm. The spectral output of the lamp is given in Figure F. 12. The spectral UV absorbances used in the model are provided in Figure F. 11. UV intensity was modeled using a polychromatic radial intensity model and the dose was calculated as the product of the average germicidal intensity and the hydraulic residence time as per the following equation:

( ) ( ) ( ) ( ) ( ) ( )  =            = 320 200 1 exp l l a l a l l l e wl e q arc Q r T G L P D Equation F. 14 where D = Dose delivered by the reactor ( mJ/ cm2) Larc = Arc length of the lamp ( cm) Tq( l) = Lamp sleeve UVT ae( l) = Naperian UV absorbance rwl = Reactor water layer, defined as the radial distance from the sleeve to the reactor wall ( cm) Q = Flowrate through the reactor ( cm3/ s)

UV intensity sensor measurements were modeled at different lamp to sensor distances for sensors with the spectral response shown in Figure F. 13 as per Equation F. 15:

( ) ( ) ( ) ( )( ) ( )

 =   = 400 200 2 exp l p l a l l l r r r T S P I S e q Equation F. 15 where I = Intensity measured by the sensor S( l) = Sensor spectral response normalized to unity at 254 nm r = Distance from the sensor to the lamp ( cm) rS = Lamp sleeve outer radius ( cm) Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 28 June 2003 Proposal Draft Table F. 3 Dose and UV Intensity Sensor Measurements Modeled for a MP Annular Reactor Performance Parameters Water A Water B Coffee Lignin Sulphonate MS2 RED ( mJ/ cm2) 72 67 60 61 Sensor Water Layer ( cm) 1 Measured UV Intensity ( 254 nm equivalent mW/ cm2) 2.0 269 256 238 245 5.0 136 122 101 110 10 59.7 48.7 31.6 40.4 15 31.9 23.6 11.7 18.2 SiC 20 19.2 13.0 4.77 9.34 2.0 112 107 103 104 5.0 48.0 44.8 10.9 11.8 10 15.3 13.7 3.46 4.06 15 5.02 4.97 1.18 1.51 Filtered SiC 20 2.42 1.95 0.410 0.593 1 Water layer is defined as the distance between the lamp sleeve and the UV intensity sensor.

Figure F. 12 UV Output of a MP Lamp Table F. 3 presents the MS2 RED and sensor measurements predicted for the annular reactor operating at a flowrate of 200 gpm, a water UVT of 85 percent at 254 nm, and 100 percent lamp power. As expected, the dose delivered with coffee and lignin sulphonate for a given flowrate, water UVT, and lamp power was less than the dose delivered with both WTP waters.

For a given sensor reading, flowrate, and UVT, Table F. 4 presents the ratio of the dose measured during validation to the dose delivered at the WTP calculated using the data from Table F. 3. A ratio greater than one indicates that the dose measured during validation will be greater than the dose delivered at the WTP. As expected, the ratio is less than one with the UV Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 29 June 2003 Proposal Draft intensity sensor located close to the lamps and greater than one with the UV intensity sensor located far from the lamps. For a given sensor position, the ratio with lignin sulphonate is closer to one than the ratio with coffee indicated that lignin sulphonate better matches the UV absorption spectra of WTP waters. The ratio is also closer to one with a germicidal sensor spectral response compared to the non germicidal response. This indicates that validation results with a germicidal sensor are more representative of performance at a WTP than validation results with a non germicidal sensor.

Table F. 4 Impact of Water UV Absorbance on the UV Intensity Sensor Value Associated with a Given UV Dose Delivery Ratio of Dose Delivered During Validation to Dose Delivered at the WTP for a Given Sensor Reading UV Sensor Water Layer ( cm) Coffee to Water A Coffee to Water B Lignin Sulphonate to Water A Lignin Sulphonate to Water B 2 0.93 0.96 0.93 0.95 5 1.12 1.09 1.04 1.01 10 1.56 1.37 1.25 1.10 15 2.25 1.80 1.48 1.19 SiC 20 3.34 2.44 1.74 1.27 2 0.89 0.93 0.91 0.94 5 0.98 0.99 0.98 0.99 10 1.16 1.12 1.09 1.06 15 1.39 1.29 1.21 1.12 Filtered SiC 20 1.70 1.48 1.35 1.18 For the germicidal sensor, Figure F. 13 presents the ratio of the dose expected with coffee to the dose expected with finished Water A as a function of sensor position and water UVT. With the sensor located close to the lamp, the ratio is less than one over a wide range of water UVT values. However, the ratio increases above one with increased sensor to lamp water layer and, for the most part, increases with decreased UVT. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 30 June 2003 Figure F. 13 Comparison of Dose Expected with Coffee as a UV Absorber to Dose Expected with WTP Water for a MP Reactor Equipped with a Germicidal Sensor For a given UV reactor equipped with MP lamps, the impact of differences in the spectral UV absorbance between validation and operation at a WTP should be evaluated and used to establish correction factors. The correction factor is calculated for a given flowrate, sensor reading, and UVT, as the ratio of the dose expected during validation to the dose expected at the WTP. If the ratio is less than one, no correction factor is needed.

F. 4.3 Spectral Shifts Spectral shifts in the UV output of MP lamps may occur as MP lamps age. Spectral shifts in the UVT of light through lamp sleeves may occur as sleeves age and undergo internal and external fouling. Spectral shifts in the UVT of sensor windows may occur with window fouling. Spectral shifts associated with the lamp sleeve assembly will impact both dose delivery and monitoring, while spectral shifts associated with window fouling will impact monitoring only.

Figure F. 14 presents reported data on the spectral shift in MP lamp output and lamp sleeve UVT experienced with aging. Figure F. 15 presents data comparing the UVT of clean and fouled lamp sleeves. In both cases, aging and fouling have reduced the output of lowwavelength UV light from the lamp/ sleeve assembly more than the output of higher wavelength UV light. The impact of lamp and sleeve aging and sleeve fouling can be assessed by validation testing. Alternatively, the impact can be modeled and used to define a correction factor applicable to validation results generated using new lamps.

Proposal Draft Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 31 June 2003 Figure F. 14 Spectral Shifts in the MP Lamp Output and Lamp Sleeve UVT Reported with Aging1 1 Adapted from Phillips 1983 and Kawar et al. 1998.

Figure F. 15 Comparison of the UVT of New and Fouled Lamp Sleeves For a measured flowrate, water UVT, and UV intensity, Figures F. 16, F. 17, and F. 18 provide the ratio of the dose delivered with new lamps and sleeves to the dose delivered with aged lamps, aged sleeves, and fouled sleeves, respectively. In each figure, the dose ratio is presented as a function of water UVT and sensor to lamp water layer for two different sensors. One sensor had a SiC spectral response while the other had a germicidal response. Dose and UV Proposal Draft Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 32 June 2003 Proposal Draft response. Dose and UV intensity values were predicted using Equations F. 14 and F. 15 applied to the annular reactor described in section F. 4.2.

Figure F. 16 Comparison of Dose Delivered by a MP Reactor with New and Aged Type 214 Lamp Sleeves Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 33 June 2003 Proposal Draft Figure F. 17 Comparison of Dose Delivered by a MP Reactor with New and Aged Lamps Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 34 June 2003 Proposal Draft Figure F. 18 Comparison of Dose Delivered by a MP Reactor with New Type 214 Lamp Sleeves to Fouled Sleeves In each figure ( Figures F. 16 to F. 18), the dose ratio increases with decreased water UVT and increased sensor to lamp distance. The ratio is closer to one with germicidal sensors compared with sensors with a SiC spectral response.

For a given UV reactor equipped with MP lamps, the impact of spectral shifts in lamp output and sleeve UVT should be evaluated and used to establish correction factors. The correction factor is calculated, for a given flowrate, sensor reading, and UVT, as the ratio of the dose expected with and without the spectral shift expected with operation of the UV reactor at the WTP. If the ratio is less than one, no correction factor is needed. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 35 June 2003 Proposal Draft Spectral shifts associated with lamp and sleeve aging can be avoided by regular replacement of those components. Spectral shifts arising from fouling on external surfaces of lamp sleeves and sensor windows can be minimized with good cleaning practices. However, fouling can also occur on internal surfaces of lamp sleeves and sensor windows.

F. 5 Uncertainty of Dose Monitoring and Safety Factors UV installations should be sized and operated in a manner that accounts for the measurement uncertainty associated with dose delivery monitoring. The objective of dose delivery monitoring is to indicate the level of inactivation of the target pathogen. Safety factors applied to UV installations that account for measurement uncertainty should be chosen to ensure that UV reactors meet inactivation targets at a 90 percent confidence level. A 90 percent confidence level is consistent with the confidence level used to define dose values for Cryptosporidium, Giardia, and virus in Chapter 1.

F. 5.1 Analytical Foundation for Defining Uncertainty This section derives a measurement equation for UV dose monitoring. This equation is used in this guidance document as the analytical foundation for defining the uncertainty of dose monitoring.

Consider a UV installation operating at a WTP. Assuming first order kinetics, the log inactivation of a target pathogen achieved by the UV reactor at some point in time can be expressed using Equation F. 16:

log N RED D p p p = 10 Equation F. 16 where log Np = Log inactivation of the pathogen REDp = RED of the pathogen ( mJ/ cm2) D10p = UV sensitivity of the pathogen ( mJ/ cm2 per log inactivation)

If the UV reactor delivers a dose distribution, the log inactivation of the pathogen is related to the inactivation of a challenge microorganism using Equation F. 17:

p c RED p D RED B N 10 log = Equation F. 17 where REDc = RED of the challenge microorganism ( mJ/ cm2) BRED = Ratio of the RED of the pathogen to that of the challenge microorganism Assuming the challenge microorganism RED is proportional to the measured UV intensity, log inactivation of the pathogen can be expressed according to Equation F. 18: Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 36 June 2003 Proposal Draft p RED p D I B N 10 log a = Equation F. 18 where I = UV intensity measured at the WTP ( mW/ cm2) a = Constant relating challenge microorganism inactivation to measured intensity ( J/ W)

The constant k is determined during validation as the ratio of the measured RED of the challenge microorganism to the measured intensity. Assuming that inactivation is proportional to flowrate, Equation F. 19 can be used:

Q Q I I D RED B N v v p cv RED p 10 log = Equation F. 19 where REDcv = RED of the challenge microorganism measured during validation Iv = UV intensity measured during validation Qv = Flowrate measured during validation ( mgd) Q = Flowrate measured at the WTP ( mgd)

If spectral properties such as lamp output, sleeve UVT, and water UV absorbance during validation differ from those during operation of the UV installation at the WTP, Equation F. 19 is expressed as Equation F. 21:

Poly v v p cv REF p B Q Q I I D RED B N 10 log = Equation F. 20 where variables are defined as in Equation F. 19 The term BPoly is the ratio of challenge microorganism RED expected at the WTP to the challenge microorganism RED expected during validation for the same conditions of flowrate, water UVT, and UV intensity.

Assuming the dose response of the challenge microorganism follows first order kinetics, the challenge microorganism RED during validation is calculated using the log inactivation of the challenge microorganism measured through the reactor as per Equation F. 21:

cv ef in c cv N N D RED       = log 10 Equation F. 21 where D10c = UV sensitivity of the challenge microorganism ( mJ/ cm2 per log inactivation) Nin = Challenge microorganism concentration measured at the reactor influent Nef = Challenge microorganism concentration measured at the reactor effluent Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 37 June 2003 Proposal Draft The UV sensitivity of the challenge microorganism can be calculated according to Equation F. 22 from the UV dose response measured using the collimated beam apparatus:

i D D CB c log 10 = Equation F. 22 where DCB = Dose delivered by the collimated beam apparatus log i = Log inactivation of the challenge microorganism observed with dose DCB The dose delivered by the collimated beam apparatus is defined by Equation E. 1 ( section E. 3). Substituting Equations F. 21 and F. 22, and E. 1 into Equation F. 20 gives the measurement equation for dose monitoring using the UV intensity setpoint approach:

) 10 ln( ) 1 1 ( log ) 10 1 )( 1 ( log log 10 al L i D R P E Q Q I I N N B B N p al f s v v cv ef in Poly RED p +

        =

Equation F. 23 F. 5.2 Calculating Total Uncertainty Errors in dose monitoring can be classified as either biases or random uncertainties.

Biases are systematic errors that favor either an over or under estimation of dose delivery. A bias error will occur with dose monitoring if the monitoring approach does not account for differences in the RED measured with the challenge microorganism and the RED delivered to the target pathogen. A bias error will also occur if the monitoring approach does not account for differences between the spectral properties of the UV reactor that impact dose delivery and monitoring during validation and those properties during operation of the UV reactor at the WTP. A bias error will occur if the radiometer, UV intensity sensor, flowmeter, or UVT monitor used during validation always reads either high or low. Bias errors should be accounted for using correction factors. The approaches for defining correction factors to account for bias errors represented by the terms BRED and BPoly in the measurement equation are provided in Sections F. 1 and F. 4, respectively.

Random uncertainty is associated with every term in the measurement equation ( Equation F. 23). If the measurement equation consists of linear relationships of independent variables whose random uncertainty is normally distributed, standard approaches can be used to calculate the uncertainty of the measured variable from the uncertainty of each term in the measurement equation. For example, if the measurement equation is y = x1 + x2 or y = x1  x2, the uncertainty of y due to the uncertainty of x1 and x2 is calculated using Equation F. 24: Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 38 June 2003 Proposal Draft ( ) 2 1 2 2 2 1 s s s + = Equation F. 24 where s = Uncertainty of y in absolute units s1 = Uncertainty of x1 in absolute units s2 = Uncertainty of x2 in absolute units On the other hand, if the measurement equation is y = x1 ¥ x2 or y = x1 / x2, the uncertainty of y due to the uncertainty of x1 and x2 is calculated using Equation F. 25:

( ) 2 1 2 2 2 1 s s s + = Equation F. 25 where s = Uncertainty of y in percent s1 = Uncertainty of x1 in percent s2 = Uncertainty of x2 in percent If the measurement equation involves non linear relations like y= x1 exp( x2), Monte Carlo approaches should be used to define the uncertainty of y.

Determining the random uncertainty of a measured quantity requires making assumptions about the statistical distribution of measurements. If the distribution is normal, the uncertainty is calculated as the product of the sample standard deviation and the t statistic. If the number of samples is high, the t statistic can be approximated by the z statistic. If the standard deviation of the population is known, the uncertainty is calculated as the product of the population standard deviation and the z statistic. T and z statistics are often given in the appendices of statistics texts. The NIST provides recommendations for specifying the uncertainty for quantities that are not normally distributed.

Table F. 5 defines an approach for estimating the uncertainties of each term in the measurement Equation F. 23. The total random uncertainty of dose monitoring can be estimated by summing the uncertainties associated with each term in Equation F. 23 using the above stated rules. Assuming the terms BRED and BPoly are the only bias terms, a safety factor for dose monitoring can be defined according to Equation F. 26:

( ) e B B SF Poly RED + ¥ ¥ = 1 Equation F. 26 where e = Total random uncertainty associated with the measurement equation. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 39 June 2003 Proposal Draft Table F. 5 Terms Used to Define the Uncertainty of Dose Monitoring Term Assumption BRED and Babs No term used if values are selected as safety factors as described in Sections F. 1 and F. 4. If terms are calculated, use uncertainty of model predictions to define uncertainty of these terms.

I and Iv UV intensity measurement uncertainty is often defined by the UV intensity sensor manufacturer. If a reference sensor is used to check the uncertainty of a duty sensor, the uncertainty of the duty sensor should be defined as the rejection criteria used to determine if the on line sensor is out of tolerance. See Equation F. 11. Q and Qv Use measurement uncertainty defined by flowmeter manufacturer D10p Accounted for in dose targets provided in Chapter 1 Log( Nin/ Nef) Calculated as a confidence interval using standard deviation and Student's t statistic associated with samples collected during validation. See Equation C. 7 DCB Calculated as a confidence interval using the measurement uncertainties of the terms in Equation C. 2. See Appendix E and Equation C. 8. Log( i) Use confidence interval of challenge dose response. See sections C. 4.9.7 and C. 4.9.8 The safety factor defines the relationship between the dose targets provided in Chapter 1 and the RED that should be delivered by the UV reactor at the WTP.

F. 6 Re validation If the design of a validated UV reactor changes, the UV reactor should be re validated if the design change significantly impacts dose delivery or monitoring. Dose delivery and sensor modeling can be used to assess the impact of the design change and justify the need, or lack of need, for re validation. This section discusses UV reactor modifications and provides guidance on the need for re validation.

F. 6.1 Lamp Assembly Design changes to the lamp assembly include changes made by the lamp manufacturer to the lamp, selection of a new lamp type by the UV manufacturer, and changes made by the UV manufacturer to the components associated with the lamp assembly. The relationship between dose delivery and monitoring may be impacted by any design change involving modifications to the following components:

· Lamp arc length · Any reflectors, connectors, and spacers used at the lamp ends · Lamp envelope diameter · Lamp envelope UVT from 185 nm to 400 nm Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 40 June 2003 Proposal Draft · Mercury content of the lamp · Argon content of the lamp The lamp's arc length and the use of components at the ends of the lamps ( like reflectors, spacers, and connectors) impact the UV intensity field in the region near the lamp ends. Design changes to these components could impact dose delivery, especially if the lamps are oriented perpendicular to flowrate. Design changes could also impact UV intensity sensor measurements if the lamp ends are within the viewing angle of the sensors. Dose delivery and UV intensity sensor modeling can be used to assess the impacts on changing the lamp arc length or components used at the lamp ends. If the impacts are considered significant, the reactor should be re validated.

With LP lamps, the UV emitting plasma occupies the space within the lamp envelope. With MP lamps, the plasma forms a narrow arc that occupies a portion of the space within the lamp envelope. In the presence of electromagnetic fields, the plasma within a MP lamp can be displaced off center within the lamp. The diameter of a plasma centered within the lamp envelope should have a small impact on the UV intensity field and dose delivery ( Bolton 2000). However, displacement of the plasma off center within the envelope could impact the intensity field and dose delivery. The reactor should be re validated if design changes to the lamp diameter significantly impact the intensity field.

The UVT of the lamp envelope will impact the UV output of both LP and MP lamps. With LP lamps, envelope material can be selected to allow or prevent LP lamps from emitting UV light at 185 nm. While UV light at 185 nm has a negligible impact on dose delivery and UV intensity sensor measurements because of the high UV absorbance of water at this wavelength, 185 nm light may promote the formation of ozone within the lamp sleeve. Ozone will absorb UV light at 254 nm and lower the output from the lamp. Ozone could degrade components within the lamp assembly leading to internal sleeve fouling. Typically, LP lamps are selected with envelopes that prevent output at 185 nm.

With MP lamps, the envelope material has a significant impact on the intensity of UV light emitted below 260 nm. Lamp envelope material can be selected to eliminate or maximize UV output at lower wavelengths. Since envelope transmittance decreases with increased temperature, the UVT of the envelope of a MP lamp should be assessed at the operating temperature of the lamp. Dose delivery and UV intensity sensor modeling can be used to assess the impacts of changing lamp material and justify the need for re validation.

LP lamps typically operate near 40 º C with a relatively low mercury vapor pressure that promotes UV output at 254 nm. Because the amount of mercury added to the lamp is well in excess of the amount that enters the vapor state during lamp operation, the UV output of a LP lamp is independent of the mercury dose added to the lamp during lamp manufacture. On the other hand, MP lamps operate at a high temperature, near 600 º C, with all of the added mercury in the vapor phase. As such, the mercury vapor pressure is dependent on the mercury dose and the lamp operating temperature. The vapor pressure influences the fraction of mercury that is ionized or excited to higher energy states, and hence the spectral output of the MP lamp. Table F. 6 presents the calculated impact of mercury dose on the germicidal output and measured intensity from a MP lamp operating with an electrical input of 70 W/ cm. The results suggest that Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 41 June 2003 Proposal Draft a change in mercury dose has no impact on the relationship between dose delivery and monitoring with germicidal sensors and a small impact on the relationship with SiC sensors.

Table F. 6 Impact of the Mercury Dose on the Relationship Between Germicidal Output and Measured Output of a MP Lamp1 UV Output ( W/ cm) Weighted by Ratios Mercury Dose ( mg/ cm) MS2 Action SiC Sensor Filtered SiC Sensor SiC: MS2 Filtered SiC: MS2 4.8 6.88 11.4 6.82 1.65 0.990 8 6.53 10.3 6.46 1.58 0.989 10.1 7.10 10.8 7.06 1.52 0.993 1 Adapted from lamp output data from 248 to 400 nm provided by Phillips ( 1983).

F. 6.2 Ballasts Modifications to lamp ballasts include changing the operating voltage, current, frequency, and waveform. With LP lamps, modifications will impact the amount of UV generated by the lamp, but will not impact the relationship between dose delivery and UV intensity measurements. With MP lamps and some LPHO lamps, changes in lamp operating temperature and mercury pressure caused by changes in ballast power will impact the spectral distribution of emitted light. Table F. 7 presents the impact of changing the input power from 48 to 92 W/ cm on the germicidal output and measured intensity from a MP lamp dosed with 4.8 mg/ cm of mercury. The results suggest a change in lamp operating power has no impact on the relationship between dose delivery and monitoring with germicidal sensors and a small impact with SiC sensors.

Table F. 7 Impact of Operating Power on the Relationship Between Germicidal Output and Measured Output of a MP Lamp1 UV Output ( W/ cm) Weighted by Ratios Lamp Input Power ( W/ cm) MS2 Action SiC Sensor Filtered SiC Sensor SiC: MS2 Filtered SiC: MS2 48 4.13 7.01 4.08 1.70 0.99 70 6.86 11.3 6.78 1.66 0.99 92 9.29 15.2 9.14 1.65 0.98 1 Adapted from lamp output data from 248 to 400 nm provided by Phillips ( 1983) for a MP lamp dosed with 4.8 mg/ cm Hg.

F. 6.3 Lamp Sleeves Design changes to the lamp sleeves include changing the sleeve diameter, thickness, and material. Changing the sleeve diameter may impact the hydraulics through the reactor, the measurement of UV intensity, and the optimal placement of UV intensity sensors relative to the lamp. Changing the thickness and material of the lamp sleeve will impact the spectral UVT, thereby impacting both dose delivery and UV intensity measurements. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 42 June 2003 Proposal Draft Dose delivery and UV intensity sensor modeling may be used to assess the impact of lamp sleeve design changes. Figure F. 19 provides the ratio of dose delivered with a standard sleeve to dose delivered with an " ozone free" sleeve for a given sensor reading as a function of water UVT, sensor to lamp distance, and sensor spectral response. Dose and UV intensity values were predicted using Equations F. 14 and F. 15 applied to the annular reactor described in section F. 4.2. Sleeve UVT is provided in Figure F. 20. The results show that a design change from a regular sleeve to an ozone free sleeve described in Figure F. 20 would have a small impact on the relationship between dose delivery and UV intensity sensor readings with a SiC sensor and a negligible impact with a germicidal sensor. Modeling can also be used to show that the dose delivery at a given lamp output, water UVT, and flowrate would be approximately 10 percent greater with the standard sleeve than with the ozone free sleeve. If models indicate the sleeve design change causes a significant impact on dose delivery and monitoring, the UV reactor should be re validated.

Figure F. 19 Ratios of Dose Delivered with Standard Sleeve to Dose Delivered with " Ozone Free" Sleeves by an Annular Reactor Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 43 June 2003 Proposal Draft Figure F. 20 UVT of Standard and " Ozone Free" Quartz Assuming Air Quartz and Quartz Water Interfaces F. 6.4 Reactor and Component Dimensions Modifications to the wetted dimensions and positioning of the components within the reactor will impact the reactor hydraulics and dose delivery. Modifications could also impact the intensity field within the reactor and the measurement of UV intensity. Modifications include changes to the dimensions of the reactor, inlet piping, exit piping, baffles, lamp sleeves, wipers, and UV intensity sensors. The impact of such modifications on dose delivery and UV intensity measurements can be insignificant or large. Addition of a baffle plate will likely have a large impact on dose delivery and a small impact on measured UV intensity, while changing the position of a UV intensity sensor will likely have a small impact on dose and a large impact on measured UV intensity. Dose delivery and UV intensity modeling may be used to assess the impacts of these modifications. If the impacts are significant, the reactor should be re validated.

F. 6.5 UV Intensity Sensors Modifications to the UV intensity sensors include changes made by the sensor manufacturer to the sensor, changes by the UV manufacturer to the sensor housing and associated optical components, and changes by the UV manufacturer to the number and positioning of the sensors within the reactor.

Changes to the semi conductor and optical components within the UV intensity sensor could impact the sensor's spectral response, linearity, angular response, and temperature stability. Changes to those properties could impact the sensor's measurement uncertainty. If the new measurement uncertainty is quantified, it should be used to define a new safety factor for the UV reactor. If the angular response or spectral response of the sensor changes, measurements supported by calculations should be used to evaluate the impact of the change on dose delivery monitoring. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 44 June 2003 Proposal Draft Changes to the measuring window of the UV intensity sensor include dimensional and material changes. Changes may impact the UVT of the window and the detection angle. Measurements supported by calculations should be used to evaluate the impact of the change on dose delivery monitoring.

Modifications to the positioning of the UV intensity sensor within the reactor could disturb the flowrate and impact dose delivery. If the impact on dose delivery is negligible, measurements supported by calculations may be used to compare measured UV intensity at the two positions and modify the dose monitoring approach without the need for re validation.

Addition of UV intensity sensors to the reactor could disturb the flowrate through the UV reactor and impact dose delivery. If sensors are added, they should be positioned relative to the lamps in a similar manner as the other sensors. For example, if one sensor is positioned to view two lamps through a 5 cm water layer, then all added sensor should view two lamps through a 5 cm water layer.

F. 7 References Bolton, J. R. 2000. Calculation of ultraviolet fluence rate distributions in an annular reactor: significance of refraction and reflection. Water Research 34: 3315 3324.

Cabaj, A., R. Sommer, and D. Schoenen. 1996. Biodosimetry: model calculations for U. V. water disinfection devices with regard to dose distributions. Water Research. 30, no. 4: 1003 1009.

Cabaj, A., R. Sommer, W. Pribil, and T. Haider. 2002. The spectral UV sensitivity of microorgnisms used in biodosimetry. Water Science and Technology: Water Supply, 2( 3): 175 181.

Chang, J. C. H., S. F. Osoff, D. C. Lobe, M. H. Dorfman, C. M. Dumais, R. G. Qualls, and J. D. Johnson. 1985. UV inactivation of pathogenic and indicator microorganisms. Applied and Environmental Microbiology 49( 6): 1361 1365.

Chiu, K. P., D. A. Lyn, P. Savoye, and E. R. Blatchley. 1999. Effect of UV system modifications on disinfection performance. Journal of Environmental Engineering 125( 5): 459 469.

Haas, C. N. and G. P. Sakellaropoulos. 1979. Rational analysis of ultraviolet disinfection. National Conference on Environmental Engineering, Proc. ASCE Specialty Conf., San Francisco, CA, July 9 11.

Kawar, K., J. Jenkins, B. Srikanth, and A. Shurtleff. 1998. Ultraviolet light deterioration of the light transmittance of quartz sleeves due to continuous exposure to UV radiation. Ultrapure Water October, 67 71.

Larason, T. C., S. S. Bruce, and A. C. Parr. 1998. Spectroradiometric Detector Measurements. NIST Special Publication 250 41. U. S. Government Printing Office, Washington. Appendix F. Background to the UV Reactor Validation Protocol UV Disinfection Guidance Manual F 45 June 2003 Proposal Draft Larason T. C. and C. L. Cromer. 2001. Source of error in UV radiation measurements. Journal of Research of the National Institute of Standards and Technology 106, no. 4: 649 656.