Abstract

UV light-emitting diodes (UV-LEDs) offer various wavelength options, while microorganisms have spectral sensitivity, or so-called action spectra, which can be different among species. Accordingly, matching properly the emission spectra of UV-LEDs and the spectral sensitivity of microorganisms is a reasonable strategy to enhance inactivation. In this study, UV-LEDs with nominal peak emissions at 265, 280 and 300 nm were applied to pathogens including Legionella pneumophila, Pseudomonas aeruginosa, Vibrio parahaemolyticus and feline calicivirus, in comparison with indicator species including Escherichia coli, Bacillus subtilis spores, bacteriophage Qβ and MS2. The results indicated that, for all species tested, 265 nm UV-LED was highest in the fluence-based inactivation rate constant k, followed by 280 nm and 300 nm was much lower. The k value at 280 nm was close to that at 265 nm for feline calicivirus and MS2, suggesting that 280 nm UV-LED can be as good an option as 265 nm UV-LED to inactivate these viruses. Bacteria tended to show fluence-response curves with shoulder and tailing, while viruses followed log-linear profiles at all wavelengths tested. This study indicates the fluence-response profiles and the fluence required for a target inactivation of microorganisms, which would serve as reference data for future study and applications of UV-LEDs.

INTRODUCTION

The light-emitting diode (LED) with germicidal ultraviolet (UV) emissions, noted UV-LED hereafter, is an emerging source of UV radiation that can bring innovation to water treatment systems. For example, UV-LEDs are mercury-free, tiny in size, flexible in the reactor design, and quick to start without warming-up. UV-LEDs offer variety in emission wavelengths, thus, how to pick up the right one is a question. On the other hand, microorganisms are known to have spectral sensitivity, so-called action spectra, which greatly affects the inactivation efficiency at different wavelengths. Namely, matching properly the emission spectra of UV-LEDs and the spectral sensitivity of target microorganisms can enhance inactivation efficiency.

Health-related microorganisms in water include pathogens and indicators. Pathogens cause diseases in humans and animals through infection while indicators are ideally non-pathogenic but behave similar to or in a way indicative of pathogens, and are thus to be monitored in water treatment processes and in the water environment. As indicators, Escherichia coli and bacteriophages have been used commonly in general, while Bacillus subtilis spores are used as a challenge organism for validation of UV disinfection systems in Europe (ÖNORM 2001; DVGW 2006). Legionella spp. and Pseudomonas spp. are opportunistic pathogens which are important in public health due to concerns over susceptible populations and healthcare-associated infections (HAIs). Pseudomonas aeruginosa have been listed as a pathogen with critical priority (World Health Organization 2017), while L. pneumophila are known for the large-scale outbreak through the public water supply in Flint, Michigan (Zahran et al. 2018).

Vibrio parahaemolyticus is known to cause gastrointestinal disease through drinking water and food. As this species is ubiquitous in seawater, seafood-to-human is a common route of infection which is associated with water contamination. In aquaculture industries, mercury UV lamp systems are common in disinfecting water, thus V. parahaemolyticus is one of the key targets for UV disinfection. V. parahaemolyticus is also known to cause a fatal infectious disease in farmed shrimp, called Early Mortality Syndrome/Acute Hepatopancreatic Necrosis Disease, or EMS/AHPHD (Lightner et al. 2012) and thus the significance of this bacterium is not only for human health but for the farming industry and food security.

Among pathogenic viruses, adenovirus has already been tested with UV-LEDs as an important waterborne human pathogen (Oguma et al. 2016b), while feline calicivirus (FCV) is another key target to control in veterinary medicine as it causes respiratory infections in felids. Moreover, FCV is a single-strand RNA virus and phylogenetically related to human norovirus (HNV), and thus has been used as a surrogate for HNV historically. The appropriateness of FCV as a HNV surrogate is noted as ‘questionable’ nowadays (Bae & Schwab 2008; Park et al. 2011), but in general, it is worthwhile to diversify viral species in UV-LED studies.

It is needed to develop a dataset on fluence-responses of various microorganisms under UV-LED exposures at different wavelengths, which would serve as reference data for future research and development. A few reviews have made such efforts (Malayeri et al. 2016; Song et al. 2016), but comparing inactivation profiles reported in different studies can mislead the results because, while UV-LEDs offer variety in the emission wavelengths and high flexibility in the reactor design, no standardized protocol is available yet to test UV-LED apparatus. Namely, each study adopts a setup with a unique design concept and the way to determine the fluence in the systems is different among studies (for example, Bowker et al. 2011; Würtele et al. 2011; Oguma et al. 2013; Oguma et al. 2016a). Standardization of a UV-LED test protocol is inevitable to allow comparison among studies in a scientifically correct way. For now without such a protocol, it would be a reasonable and reliable option to compare the fluence-response profiles obtained using an identical exposure setup and the same method to determine the fluence.

Based on the background, the objective of this study is to summarize the fluence-response profiles of various microorganisms obtained using an identical UV-LED setup and the same protocol for fluence measurement. The target microbial species were the above-mentioned bacteria and viruses, and UV-LEDs emitting at 265, 280 and 300 nm were used for comparison. By doing so, we aim to offer reference data for future study and applications of UV-LEDs for disinfection.

MATERIALS AND METHODS

Cultivation and enumeration of microorganisms

Pure cultures of E. coli K12 (IFO 3301, Institute for Fermentation, Osaka, Japan), L. pneumophila (ATCC® 33152™, American Type Culture Collection, VA, USA), P. aeruginosa (ATCC® 10145™), B. subtilis spores (ATCC® 6633™) and bacteriophage Qβ (ATCC® 23631-B1™) were cultivated and enumerated as detailed in Rattanakul & Oguma (2018). Bacteriophage MS2 (ATCC® 15597-B1™) was tested as described earlier (Oguma et al. 2016b).

A pure culture of V. parahaemolyticus (NBRC 12711, Biological Resource Center in the National Institute of Technology and Evaluation, Chiba, Japan) was incubated at 37 °C for 16 h in a sterilized agar medium including 10 g of hipolypeptone, 2 g of yeast extract, 0.5 g of MgSO4·H2O and 15 g of bacteriological agar in 750 mL of artificial seawater and 250 mL of distilled water.

Feline calicivirus (ATCC® VR-782™) was propagated as detailed elsewhere (Oguma 2018). Briefly, the strain was propagated in Crandell Rees feline kidney cells (CRFK, ATCC® CCL-94™) which were cultured in complete Eagle's minimum essential medium (MEM) supplemented with 5% fetal bovine serum, 100 U/mL of penicillin and 0.1 mg/mL of streptomycin. FCV were cultivated and enumerated at Kitasato Research Center for Environmental Science, Kanagawa, Japan.

For UV-LED exposure, pre-cultured and purified microorganisms were suspended in phosphate-buffered solution at pH 7.2 at the initial concentration of 106 in colony-forming units (CFU) or plaque-forming units (PFU) per 1 mL of sample. The sample was placed in a Petri dish with a pre-sterilized magnetic spin bar and exposed to UV-LEDs as detailed below.

UV-LED setup and exposure

UV-LED exposure was conducted using a setup illustrated in Figure 1, and more details with dimensions are available in Rattanakul & Oguma (2018). The number of UV-LED packages mounted on one circuit board was eight for all species except V. parahaemolyticus, FCV and MS2, while these three species were tested using four UV-LED packages on a board as detailed elsewhere (Oguma 2018). The difference in the number of UV-LEDs (either four or eight packages), and therefore the difference in the fluence rate on the sample dish, was properly adjusted at the fluence rate determination as detailed below. UV-LEDs (Nikkiso Giken, Ishikawa, Japan) with nominal peak emissions at 265, 280 and 300 nm (full width at half maximum, FWHM, of about 10–12 nm) were used, and the emission spectra are depicted in Figure 2. The UV-LED packages mounted on one circuit board were identical in the emission, and the combination of different wavelengths was not tested.

Figure 1

UV-LED setup (modified from Rattanakul & Oguma 2018).

Figure 1

UV-LED setup (modified from Rattanakul & Oguma 2018).

Figure 2

Emission spectra of UV-LEDs with nominal peak emissions at 265, 280 and 300 nm.

Figure 2

Emission spectra of UV-LEDs with nominal peak emissions at 265, 280 and 300 nm.

The fluence rate was determined by ferrioxalate actinometry (Bolton et al. 2011) with correction using the Beer–Lambert Law or so-called Water Factor (Bolton & Linden 2003). The average fluence rate was multiplied by the exposure time to determine the fluence. Details are available in Rattanakul & Oguma (2018). Exposure time varied from about 2 to 2,000 seconds depending on the microbial species and emission wavelengths, and the microbial suspensions were mixed continuously throughout the experiment, including during sampling, at a constant temperature of 20 °C.

Inactivation kinetics and data analysis

The fluence-response profiles were fitted to a log-linear regression line by the least squares method, and the log10-based inactivation rate constant k (cm2/mJ) was defined as follows: 
formula
where N0 and Nt are the number of colonies (CFU/mL) or plaques (PFU/mL) at time 0 and t of UV-LED exposure, respectively, F (mJ/cm2) is the fluence, and b is the y-axis intercept of the regression line. Details are available in Hijnen et al. (2006). Data in shoulder and tailing regions were excluded in the log-linear fitting. The fluence required for a target level of inactivation was calculated based on the regression line.

RESULTS AND DISCUSSION

Fluence-response profiles for all species tested are shown in Figure 3. It is notable that bacteria, particularly bacterial spores, tended to show shoulder and tailing in the profile. Thus, for bacteria, shoulder was defined based on the apparent curve-shaped profile at low fluences while all data exceeding 4-log inactivation were defined in tailing, and the data in shoulder and tailing regions were eliminated in the log-linear fitting for the regression lines. For viruses, all data were used for the log-linear fitting because no apparent shoulder and tailing were observed with either virus. This is in accordance with the case when using conventional mercury lamps that viruses typically do not show apparent shoulder and tailing in UV disinfection (Hijnen et al. 2006). Many studies (for example, Severin et al. 1983; Pennell et al. 2008; Mbonimpa et al. 2018) have challenged the mechanistic explanation for the fact that some species (mostly bacteria and spores) show shoulder and/or tailing in UV inactivation kinetics while others (typically viruses) do not, and the most fundamental and widely accepted interpretation for shoulders is the multi-target model (Severin et al. 1983). The multi-target model assumes that photons must hit multiple critical targets in bacteria and spores to complete inactivation while a single hit is critical enough to inactivate viruses. Meanwhile, clumping or aggregation of microorganisms as well as the presence of sub-populations with higher resistance have been proposed as probable causes for tailing phenomena (Cerf 1977; Geeraerd et al. 2000; Mbonimpa et al. 2018). It would be scientifically reasonable to assume more targets in bacteria and spores than in simple viral particles. No apparent spectral effects were observed regarding the presence of shoulder and tailing, namely, species with shoulder and tailing showed such curves at all wavelengths tested.

Figure 3

Fluence-response profiles for microorganisms at 265, 280 and 300 nm UV-LED exposures. Figures on the right are the magnification at low fluences for bacteria.

Figure 3

Fluence-response profiles for microorganisms at 265, 280 and 300 nm UV-LED exposures. Figures on the right are the magnification at low fluences for bacteria.

Based on the regression lines for the inactivation profiles, the slope factor k and the intercept b were determined for all species as summarized in Table 1. As was partially reported earlier (Rattanakul & Oguma 2018), the 265 nm UV-LED was most efficient for all species tested in the fluence-based inactivation rate constant, followed by 280 nm, and the much lower 300 nm. This is in good agreement with the order of photon absorption efficiency of the pyrimidine base in the genome, the main target biomolecule for UV radiation (Harm 1980). Interestingly, the k value at 280 nm was close to that at 265 nm for FCV and MS2, although the values at 265 nm and 280 nm were still statistically different (p < 0.05, one-way analysis of variance (ANOVA)). In our previous study examining human adenovirus serotype 5, we found that the k value for a 285 nm UV-LED was higher than that for a 254 nm low-pressure mercury UV lamp (Oguma et al. 2016b). As such, it is suggested that some viruses tend to be sensitive to emissions at around 280 nm. It is known that while photon absorption of DNA and RNA shows a relative peak at 260 ± 5 nm, protein shows a relative peak at around 280 ± 5 nm (Harm 1980). A study demonstrated that UV-induced protein damage played an important role in virus inactivation using low- and medium-pressure mercury UV lamps (Eischeid & Linden 2011). Thinking that some viruses need specific proteins to get into the host cell to cause infection, it is implied that protein damage is critical for some viruses and that can be one of the reasons for the 280 nm UV-LED to be efficient in virus inactivation. More recently, Beck et al. (2018) has challenged the quantification of UV-induced protein damage in adenovirus and reported a significant reduction of protein quantities after UV exposure at wavelengths below 240 nm using deuterium lamps, encouraging a growing expectation for the development of short wavelength UV-LEDs in the future.

Table 1

Responses of bacteria and viruses under UV-LED exposures at different wavelengths

 na kb [cm2/mJ] ± SDc for k bb Fluence [mJ/cm2] for log inactivation of:
 
Bacteria 
 Legionella pneumophila 
  265 nm 14 1.039 0.122 −0.34 1.3 2.2 3.2 4.2 
  280 nm 15 0.458 0.048 −0.02 2.2 4.4 6.6 8.8 
  300 nm 15 0.051 0.006 −0.23 24.2 43.9 63.5 83.2 
Pseudomonas aeruginosa 
  265 nm 16 0.774 0.136 −0.91 2.5 3.8 5.1 6.3 
  280 nm 16 0.582 0.084 −0.49 2.6 4.3 6.0 7.7 
  300 nm 12 0.058 0.008 −1.12 36.3 53.4 70.5 87.6 
Vibrio parahaemolyticus 
  265 nm 0.359 0.079 −0.06 3.0 5.7 8.5 11.3 
  280 nm 11 0.281 0.035 −0.31 4.7 8.2 11.8 15.3 
  300 nm 0.017 0.005 0.08 54.4 113.3 172.2 231.1 
Escherichia coli 
  265 nm 13 0.878 0.116 −1.34 2.7 3.8 4.9 6.1 
  280 nm 15 0.562 0.063 −1.13 3.8 5.6 7.3 9.1 
  300 nm 16 0.067 0.010 −1.75 41.2 56.1 71.1 86.1 
Bacillus subtilis spores 
  265 nm 0.197 0.019 −1.25 11.4 16.5 21.6 26.7 
  280 nm 13 0.112 0.013 −1.05 18.3 27.3 36.3 45.2 
  300 nm 0.005 0.001 −2.17 671.4 882.8 1,094.3 1,305.8 
Viruses 
 Feline calicivirus 
  265 nm 0.113 0.008 0.24 6.7 15.6 24.5 33.4 
  280 nm 0.101 0.003 0.09 9.0 18.9 28.9 38.8 
  300 nm 0.007 0.0003 0.06 139.1 286.8 434.6 582.3 
 Bacteriophage Qβ 
  265 nm 17 0.091 0.015 0.19 8.9 19.9 31.0 42.0 
  280 nm 17 0.052 0.004 0.16 16.0 35.1 54.1 73.2 
  300 nm 17 0.005 0.002 0.51 100.0 304.8 509.7 714.5 
 Bacteriophage MS2 
  265 nm 0.034 0.007 0.38 18.1 47.1 76.1 105.2 
  280 nm 0.033 0.002 0.01 30.3 60.9 91.5 122.1 
  300 nm 0.003 0.0003 −0.18 412.8 763.4 1,114.1 1,464.7 
 na kb [cm2/mJ] ± SDc for k bb Fluence [mJ/cm2] for log inactivation of:
 
Bacteria 
 Legionella pneumophila 
  265 nm 14 1.039 0.122 −0.34 1.3 2.2 3.2 4.2 
  280 nm 15 0.458 0.048 −0.02 2.2 4.4 6.6 8.8 
  300 nm 15 0.051 0.006 −0.23 24.2 43.9 63.5 83.2 
Pseudomonas aeruginosa 
  265 nm 16 0.774 0.136 −0.91 2.5 3.8 5.1 6.3 
  280 nm 16 0.582 0.084 −0.49 2.6 4.3 6.0 7.7 
  300 nm 12 0.058 0.008 −1.12 36.3 53.4 70.5 87.6 
Vibrio parahaemolyticus 
  265 nm 0.359 0.079 −0.06 3.0 5.7 8.5 11.3 
  280 nm 11 0.281 0.035 −0.31 4.7 8.2 11.8 15.3 
  300 nm 0.017 0.005 0.08 54.4 113.3 172.2 231.1 
Escherichia coli 
  265 nm 13 0.878 0.116 −1.34 2.7 3.8 4.9 6.1 
  280 nm 15 0.562 0.063 −1.13 3.8 5.6 7.3 9.1 
  300 nm 16 0.067 0.010 −1.75 41.2 56.1 71.1 86.1 
Bacillus subtilis spores 
  265 nm 0.197 0.019 −1.25 11.4 16.5 21.6 26.7 
  280 nm 13 0.112 0.013 −1.05 18.3 27.3 36.3 45.2 
  300 nm 0.005 0.001 −2.17 671.4 882.8 1,094.3 1,305.8 
Viruses 
 Feline calicivirus 
  265 nm 0.113 0.008 0.24 6.7 15.6 24.5 33.4 
  280 nm 0.101 0.003 0.09 9.0 18.9 28.9 38.8 
  300 nm 0.007 0.0003 0.06 139.1 286.8 434.6 582.3 
 Bacteriophage Qβ 
  265 nm 17 0.091 0.015 0.19 8.9 19.9 31.0 42.0 
  280 nm 17 0.052 0.004 0.16 16.0 35.1 54.1 73.2 
  300 nm 17 0.005 0.002 0.51 100.0 304.8 509.7 714.5 
 Bacteriophage MS2 
  265 nm 0.034 0.007 0.38 18.1 47.1 76.1 105.2 
  280 nm 0.033 0.002 0.01 30.3 60.9 91.5 122.1 
  300 nm 0.003 0.0003 −0.18 412.8 763.4 1,114.1 1,464.7 

an: number of data for regression analysis, exclusive of data in shoulder and tailing regions.

bk, b: slope and intercept for log-linear regression, log inactivation = k × fluence + b.

cSD: standard deviation.

Viruses were generally more resistant to UV than bacteria, as is the case with conventional mercury UV lamps (Hijnen et al. 2006). V. parahaemolyticus was less sensitive to UV compared with other bacterial species except B. subtilis spore. This is to be taken into account when UV-LEDs are applied to aquaculture and food industries where V. parahaemolyticus is an important target to inactivate. The k value of B. subtilis spores dropped significantly from 280 nm to 300 nm, suggesting the drastic change in action spectra of this species at this wavelength band. This is supported by a previous study showing action spectra of B. subtilis spores (Mamane-Gravetz et al. 2005). The b value is the y-axis intercept, thus showing a negative value if the regression line crosses the x-axis (fluence) where the log-linear relationship starts. This was true in most cases with bacteria, and positive b values for viruses at some wavelengths may be partially due to experimental errors in culture assays. A high absolute value for b suggests significant shoulder in the response profile, which was particularly the case with E. coli and B. subtilis spores. P. aeruginosa, E. coli and B. subtilis spores showed increased absolute value for b at 300 nm, suggesting more apparent shoulder at this wavelength. Namely, more ‘lag’ is to be expected if a 300 nm UV-LED is used to inactivate these species.

Action spectra have been reported for some species of microorganisms. For example, Mamane-Gravetz et al. (2005) examined the action spectra of MS2 and B. subtilis spores using a xenon lamp with a monochromator (FWHM of about 10 nm), and reported the action spectra of MS2, relative to the efficiency at 254 nm, as 0.96, 0.62 and 0.27 at 265 nm, 280 nm and 293 nm, respectively, while the value for B. subtilis spores was 1.05, 0.99 and 0.20 at 265 nm, 280 nm and 293 nm, respectively. Another outstanding study on action spectra was conducted by Beck et al. (2015) using a tunable laser with an extremely sharp monochromatic emission (FWHM less than 1 nm). They reported MS2 action spectra, relative to the efficiency at 254 nm, of 1.20, 0.77 and 0.01 at 265 nm, 280 nm and 300 nm, respectively, while the value for Qβ was 1.22, 0.71 and 0.04 at 265 nm, 280 nm and 300 nm, respectively. In comparison with the current study, our data for B. subtilis spores and Qβ are acceptably similar to those reported earlier while the MS2 data in this study, showing relatively high efficiency at 280 nm, are not in good agreement with either studies. The discrepancy may arise from multiple factors including the difference in spectral patterns for different UV radiation sources, difference in the fluence determination methods, and the difference in the statistical analyses for data fitting. As such, it is not that simple to compare data among independent studies particularly when different UV sources are adopted.

Although the fluence-based inactivation efficiency was highest for the 265 nm UV-LED with all species tested, the electrical energy consumption required for 3-log inactivation, EE,3 (kWh/m3), was lowest for the 280 nm UV-LED with E. coli, P. aeruginosa, L. pneumophila, B. subtilis spores and bacteriophage Qβ, due to the higher wall-plug efficiency of the 280 nm UV-LED than the 265 nm UV-LED (Rattanakul & Oguma 2018). Based on this fact, it is recommended that, with the currently available UV-LED devices that still suffer from relatively low wall-plug efficiency, not only 265 nm but 280 nm UV-LEDs would be a good option for practical applications in industries. Namely, at selecting a particular UV-LED out from many spectral options, not only the action spectra of the target microorganisms but also the integrity of the UV-LED products are to be considered. Therefore, it would be important to keep updating the technology trend of UV-LEDs while conducting fundamental research for ‘robust’ data on the inactivation kinetics of diverse microorganisms.

CONCLUSIONS

This study summarizes fluence-response profiles for various microorganisms and indicates the fluence required for a target value of inactivation using UV-LEDs at 265, 280 and 300 nm. Results of this study would be practically useful as reference data for future study and development of UV-LED disinfection apparatus.

ACKNOWLEDGEMENTS

This study has been supported by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research 17H03329, Japan Science and Technology Agency, and Ministry of Health, Labour and Welfare. The author is grateful to Nikkiso Giken Co. Ltd for providing the UV-LED apparatus and technical support.

REFERENCES

REFERENCES
Beck
S. E.
,
Wright
H. B.
,
Hargy
T. M.
,
Larason
T. C.
&
Linden
K. G.
2015
Action spectra for validation of pathogen disinfection in medium-pressure ultraviolet (UV) systems
.
Water Research
70
,
27
37
.
Beck
S. E.
,
Hull
N. M.
,
Poepping
C.
&
Linden
K. G.
2018
Wavelength-dependent damage to adenoviral proteins across the germicidal UV spectrum
.
Environmental Science and Technology
52
,
223
229
.
Bolton
J. R.
&
Linden
K. G.
2003
Standardization of methods for fluence (UV dose) determination in bench-scale UV experiments
.
Journal of Environmental Engineering, ASCE
129
(
3
),
209
215
.
Bolton
J. R.
,
Stefan
M. I.
,
Shaw
P. S.
&
Lykke
K. R.
2011
Determination of the quantum yields of the potassium ferrioxalate and potassium iodide–iodate actinometers and a method for the calibration of radiometer detectors
.
Journal of Photochemistry and Photobiology A: Chemistry
222
(
1
),
166
169
.
Bowker
C.
,
Sain
A.
,
Shatalov
M.
&
Ducoste
J.
2011
Microbial UV fluence-response assessment using a novel UV-LED collimated beam system
.
Water Research
45
,
2011
2019
.
Cerf
O.
1977
Tailing of survival curves of bacterial spores
.
Journal of Applied Bacteriology
42
,
1
19
.
DVGW
2006
DVGW W 294-1. UV Disinfection Devices for Water Supply – Part 1: Requirements for Quality, Function and Operation
.
Deutscher Verein des Gas und Wasserfaches (German Technical and Scientific Association for Gas and Water)
,
Bonn
,
Germany
.
Eischeid
A. C.
&
Linden
K. G.
2011
Molecular indication of protein damage in adenoviruses after UV disinfection
.
Applied and Environmental Microbiology
77
(
3
),
1145
1147
.
Geeraerd
A. H.
,
Herremans
C. H.
&
Van Impe
J. F.
2000
Structural model requirements to describe microbial inactivation during a mild heat treatment
.
International Journal of Food Microbiology
59
(
3
),
185
209
.
Harm
W.
1980
Biological Effects of Ultraviolet Radiation
.
IUPAB Biophysics Series, Cambridge University Press
,
Cambridge, UK
.
Lightner
D. V.
,
Redman
R. M.
,
Pantoja
C. R.
,
Noble
B. L.
&
Tran
L.
2012
Early mortality syndrome affects shrimp in Asia
.
The Global Aquaculture Advocate
15
(
1
),
40
.
Malayeri
A. H.
,
Mohseni
M.
,
Cairns
B.
&
Bolton
J. R.
2016
Fluence (UV dose) required to achieve incremental log inactivation of bacteria, protozoa, viruses and algae
.
IUVA News
18
(
3
),
4–6
.
Mamane-Gravetz
H.
,
Linden
K. G.
,
Cabaj
A.
&
Sommer
R.
2005
Spectral sensitivity of Bacillus subtilis spores and MS2 coliphage for validation testing of ultraviolet reactors for water disinfection
.
Environmental Science and Technology
39
,
7845
7852
.
Mbonimpa
E. G.
,
Blatchley
E. R.
III
,
Applegate
B.
&
Harper
W. F.
Jr.
2018
Ultraviolet A and B wavelength-dependent inactivation of viruses and bacteria in the water
.
Journal of Water and Health
16
(
5
),
796
806
. http://dx.doi.org/10.2166/wh.2018.071
Oguma
K.
,
Kita
R.
,
Sakai
H.
,
Murakami
M.
&
Takizawa
S.
2013
Application of UV light emitting diodes to batch and flow-through water disinfection systems
.
Desalination
328
,
24
30
.
Oguma
K.
,
Rattanakul
S.
&
Bolton
J. R.
2016b
Application of UV light emitting diodes to adenovirus in water
.
Journal of Environmental Engineering, ASCE
142
(
3
),
04015082
.
ÖNORM
2001
Austrian National Standard: ÖNORM M5873-1. Plants for Disinfection of Water Using Ultraviolet Radiation: Requirements and Testing – Low-Pressure Mercury Lamp Plants
.
Austrian Standards Institute
,
Vienna
,
Austria
.
Pennell
K. G.
,
Aronson
A. I.
&
Blatchley
E. R.
III
2008
Phenotypic persistence and external shielding ultraviolet radiation inactivation kinetic model
.
Journal of Applied Microbiology
104
,
1192
1202
.
Severin
B. F.
,
Suidan
M. T.
&
Engelbrecht
R. S.
1983
Kinetic modeling of UV disinfection of water
.
Water Research
17
,
1669
1678
.
World Health Organization (WHO)
2017
Global Priority List of Antibiotic-Resistant Bacteria to Guide Research, Discovery, and Development of New Antibiotics
.
WHO, Geneva
,
Switzerland
.
Würtele
M. A.
,
Kolbe
T.
,
Lipsz
M.
,
Külberg
A.
,
Weyers
M.
,
Kneissl
M.
&
Jekel
M.
2011
Application of GaN-based ultraviolet-C light emitting diodes – UV LEDs – for water disinfection
.
Water Research
45
,
1481
1489
.
Zahran
S.
,
McElmurry
S. P.
,
Kilgore
P. E.
,
Mushinski
D.
,
Press
J.
,
Love
N. G.
,
Sadler
R. C.
&
Swanson
M. S.
2018
Assessment of the Legionnaires’ disease outbreak in Flint, Michigan
.
Proceedings of the National Academy of Sciences (PNAS)
115
(
8
),
E1730
E1739
.