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Effects of Environmental Factors on the Disinfection Performance of a Wastewater Stabilization Pond Operated in a Temperate Climate Lei Liu, Geof Hall and Pascale Champagne * Received: 19 October 2015; Accepted: 14 December 2015; Published: 25 December 2015 Academic Editor: Robin Slawson Department of Civil Engineering, Queen’s University, 58 University Ave., Kingston, ON K7L 3N6, Canada; [email protected] (L.L.); [email protected] (G.H.) * Correspondence: [email protected]; Tel.: +1-613-533-3053
Abstract: Treatment in a wastewater stabilization pond (WSP) relies on natural purification processes, which can be sensitive to both location and climate. This study investigated the effects of three environmental factors, pH, dissolved oxygen (DO) and temperature, on disinfection efficiency in a WSP system consisting of three facultative cells, and operated in a temperate climate region, in Eastern Ontario, Canada. Indicator organism (Escherichia coli (E. coli)) removal in WSP systems is driven by a combination of different factors. Elevated pH and DO concentrations, which are attributed to the presence of algae, are important factors for effective disinfection. Therefore, the presence of algae in natural wastewater treatment systems can contribute appreciably to disinfection. Consequently, based on algal concentrations, removal efficiencies of pathogenic microorganisms during wastewater treatment over the course of a year can be highly variable, where higher removal efficiencies would be expected in summer and fall seasons. Keywords: disinfection; wastewater treatment; environmental factors; pH; dissolved oxygen; temperature; E. coli
1. Introduction Pressured by water scarcity and increases in water demand worldwide, treated wastewater has been reused for a variety of purposes over the last few decades, including agricultural irrigation and other industrial, environmental and municipal uses [1,2]. The potential for water reuse is dependent on effective pathogen removal. The disinfection process, generally the last step in wastewater treatment, aims to minimize the risk of pathogen exposure in receiving environments in order to protect public health [2]. However, the removal efficiency of pathogenic organisms can vary greatly and depends on the type of treatment process. Wastewater stabilization ponds (WSPs) are often considered to be the most environmentally and economically sustainable technology for small, rural or remote communities that require low-cost and low-maintenance wastewater treatment systems [3]. WSPs have the capability to effectively attenuate organic and nutrient concentrations, as well as bacteria and pathogen levels, present in municipal wastewater [4,5]. The removal of a wide range of pathogenic organisms, such as bacterial, viral, protozoan and helminthic pathogens, is commonly achieved in WSP systems. Conversely, disinfection methods (UV irradiation, chlorination and ozone) applied in conventional treatments often only target the removal of pathogenic bacteria and viruses, as helminth eggs and protozoan (oo)cysts are resistant to these disinfection methods [6–8]. Some studies have suggested that WSP systems may remove up to 6 log units of bacteria and practically all protozoan and helminth eggs, producing final effluents that meet World Health Organization (WHO) guidelines for the use of treated wastewater in unrestricted Water 2016, 8, 5; doi:10.3390/w8010005
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WSP systems is generally superior to that of conventional treatment processes, such as activated sludge or primary treatments, for whichperformance reductions of to 2 systems log unitsisfor bacteriasuperior and 70%–99% agricultural irrigation [3]. The reported of 1WSP generally to that for of protozoan and helminth eggs have been noted [9].sludge or primary treatments, for which reductions conventional treatment processes, such as activated organisms are often employed reflect pathogen levels in a particular of 1 toIndicator 2 log units for bacteria and 70%–99% fortoprotozoan and helminth eggs have beenwastewater noted [9]. or its effluent, asorganisms it would be time-consuming to monitor eachinpathogenic organism that Indicator arecostly often and employed to reflect pathogen levels a particular wastewater could be present the treated wastewater. It is expectedtothat indicator be detected or its effluent, as itinwould be costly and time-consuming monitor each organisms pathogeniccan organism that and quantified easily and cost-effectively. presence, behavior,organisms and population of indicator could be present in the treated wastewater. It isThe expected that indicator can be detected and organismseasily and other pathogens are The generally assumed to be correlated [10,11]. For theorganisms past few quantified and cost-effectively. presence, behavior, and population of indicator decades, bacterial indicator organisms, Escherichia coli (E. fecalfew coliforms total and other pathogens are generally assumedsuch to beascorrelated [10,11]. Forcoli), the past decades,and bacterial coliforms, have been commonly used for monitoring and regulating pathogen levels in treated indicator organisms, such as Escherichia coli (E. coli), fecal coliforms and total coliforms, have been wastewater. However, the limitations of bacterial indicator have been recognized in commonly used for monitoring and regulating pathogen levels organisms in treated wastewater. However, the recent publications. In some studies, E. coli populations were not found to be well correlated with limitations of bacterial indicator organisms have been recognized in recent publications. In some pathogenic including Vibrio cholera andwith Enterococcus (E.including faecalis). studies, E. colibacteria populations were not found to be (V. wellcholera) correlated pathogenicfaecalis bacteria Populations choleraand andEnterococcus E. faecalis increased with increasing pH andof temperature, while E. coli Vibrio cholera of (V.V. cholera) faecalis (E. faecalis). Populations V. cholera and E. faecalis populations decreased [12–14]. Burkhardt III et al. [15], and Len et al. [16], also challenged the increased with increasing pH and temperature, while E. coli populations decreased [12–14]. Burkhardt reliability of E. coliLen as et a pathogen indicator. Nascimento et al. [17], usingindicator. multiple III et al. [15], and al. [16], also challenged the reliability of E.recommended coli as a pathogen organisms as indictors, because the removal kinetics of various pathogens differ. A number of Nascimento et al. [17], recommended using multiple organisms as indictors, because the removal municipalities, such as the one in this study, continue to employ E. coli as indicator organisms kinetics of various pathogens differ. A number of municipalities, such as the one in this study, continue because wastewater treatment plants are required to meettreatment the effluent standards specified in to employthe E. coli as indicator organisms because the wastewater plants are required to meet their Certificate of Approval issued by the Ontario Ministry of the Environment, as well as the newer the effluent standards specified in their Certificate of Approval issued by the Ontario Ministry of Canadian Wastewater Effluent Regulation which Regulation stipulate minimum coli the Environment, as well as the newer Canadian Guidelines, Wastewater Effluent Guidelines, E. which concentrations. stipulate minimum E. coli concentrations. 2. Materials and and Methods Methods 2. Materials 2.1. 2.1. System System Overview Overview In In this this study, study, water water samples samples were were collected collected from from the the effluents effluents of of three three WSP WSP cells cells at at aa Water Water Pollution Control Plant (WPCP) located in Eastern Ontario (Canada), with a rated average Pollution Control Plant (WPCP) located in Eastern Ontario (Canada), with a rated average daily daily flow flow 3 3 capacity and rated The treatment treatment system capacity of of5700 5700m m3/day /day and rated peak peak capacity capacity of of 16,000 16,000m m3/day. /day. The system consists consists of of primary treatment, biological treatment via an extended aeration activated sludge process, secondary primary treatment, biological treatment via an extended aeration activated sludge process, secondary clarification, followed by by effluent effluent polishing The flow flow diagram diagram of clarification, followed polishing WSPs. WSPs. The of the the WPCP WPCP is is presented presented in in Figure Figure 1. 1.
Pond #1
Pond #2
Pond #3
Figure 1. 1. The The configuration configuration of of the the wastewater wastewater treatment treatmentplant plant[18]. [18]. Figure
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The main wastewater treatment plant feeds into WSP Pond 1, flowed by Pond 2, and then Pond 3. The three facultative WSPs are operated in series, provide a total volume of 154,794 m3 and primarily facilitate disinfection prior to discharge. Table 1 summarizes the area, volume, and depth of the WSPs based on field measurements. The hydraulic retention time of the WSP system is approximately 27 days, which is anticipated to be sufficient for disinfection of secondary effluent. The discharge limit for this plant is 200 CFU/100 mL and the design objective is 100 CFU/100 mL. Table 1. Area, volume and depth of the wastewater stabilization ponds (WSPs) [19]. WSP
Surface Area (m2 )
Volume (m3 )
Depth (m)
1 2 3 Total
48,600 28,200 31,200 108,000
78,246 40,044 36,504 154,794
1.61 1.42 1.17 4.2
2.2. Field Monitoring and Sampling Eastern Ontario has a humid continental climate with four distinct seasons: winter, spring, summer and fall. Over the course of a year, the temperature typically varies from ´15 to 26 ˝ C and is rarely below ´24 ˝ C or above 31 ˝ C. The relative humidity typically ranges from 40% (comfortable) to 94% (very humid), rarely dropping below 22% (dry) and reaching as high as 100% (very humid). Monitoring was carried out from 10 May 2011 to 24 February 2015 and comprised of periods of cold climate (January–March), warm weather (April–June), the hottest season (July–September) and the return of cooler weather (October–December). pH, dissolved oxygen (DO) and temperature were measured at the effluent weirs of the three ponds between 10 am and 12 pm at weekly intervals. pH and temperature were recorded using a HQ40d (Hach, Loveland, CO), a portable pH, conductivity, DO, ORP and ISE multi-parameter meter, while DO was monitored using a Model 3100 portable dissolved oxygen analyzer (Insite IG, Slidell, LA, USA). At the same time, effluent samples were collected for E. coli analysis. The culture and enumeration of E. coli were carried out using the membrane filtration method according to Standard Methods for the Examination of Water and Wastewater [20]. 2.3. Statistical Analysis Because the data could not be assumed to be normally distributed, the non-parametric Spearman ρ correlation coefficient was evaluated. MATLAB codes were developed to calculate the correlation coefficient. Spearman’s rank correlation coefficient is a measure of statistical dependence between two variables. A Spearman correlation coefficient of 1 or ´1 results when the two variables being compared are monotonically related. If one variable tends to increase when the other variable increases, the Spearman correlation coefficient is positive. Conversely, if one variable tends to decrease when the other variable increases, the Spearman correlation coefficient is negative. The Spearman correlation increases in magnitudes as two variables become closer to being perfect monotone functions of each other. An absolute value of Spearman correlation coefficient larger than 0.5 suggests that the two variables are well correlated, a value between 0.25 and 0.5 indicates the two variables are moderately correlated, while a value below 0.1 suggests the two variables are not correlated. 3. Results and Discussion The influent to Pond 1 typically contains over 2000 CFU/100 mL of E. coli. The four-year average effluent E. coli of Pond 1, Pond 2 and Pond 3 were 84, 26, 28 CFU/100 mL respectively. More than 98.6% of disinfection efficiency was achieved throughout this WSP system. Spikes in E. coli concentrations were observed in the effluent of the first pond, some of which exceeded the dischargeable microbiological level of 200 CFU/100 mL of E. coli (Figure 2). Figure 3 shows the average, median, minimum and maximum value of E. coli concentrations in the effluents of the three WSP cells
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over theWSP monitoring The maximum coli concentration observed in Pond 1 was more than cells over period. the monitoring period. TheE. maximum E. coli concentration observed in Pond 1 was more than that of the discharge criteria. Most of the spikes were to noted to occur during seven times that seven of thetimes discharge criteria. Most of the spikes were noted occur during the colder the colder seasons (November–March). The next two ponds (Pond 2 and Pond 3) provided further seasons (November–March). The next two ponds (Pond 2 and Pond 3) provided further reduction in E. coli concentration to lower levels. E. coli concentrations above 200 CFU/100 mL were in E. colireduction concentration to lower levels. E. coli concentrations above 200 CFU/100 mL were rarely rarely observed, and at no time did the monthly geometric mean density of E. coli exceeded 200 observed, and at no time did the monthly geometric mean density of E. coli exceeded 200 CFU/100 mL. CFU/100 mL. 1600
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Figure 2. E. coli concentrations in the effluents of Pond 1, Pond 2 and Pond 3 of the Amherstview WPCP.
Figure 2. E. coli concentrations in the effluents of Pond 1, Pond 2 and Pond 3 of the Amherstview WPCP.
Figure 3. Average, median, minimum and maximum value of E. coli concentrations in the WSP effluents over a four year monitoring period.
Figure 3. Average, median, minimum and of E. coli concentrations in thepurification WSP effluents The treatment and disinfection of maximum wastewatervalue in WSPs mainly rely on natural over a four year monitoring period. processes. Hence, treatment and disinfection efficiency is expected to be influenced by environmental factors such as sunlight, temperature, pH and dissolved oxygen (DO). High pH (>9) and over-saturated DO concentrations often coincided with the occurrence of excessive Thelevels treatment and disinfection of wastewater in WSPs mainly rely on natural purification algal growth. The pH in the WSP cells ranged from 6.55 to 10.89, with an average of 8.90 during the processes. Hence, treatment and disinfection efficiency is expected to be influenced by environmental monitoring period (mid 2011 to beginning of 2015) as shown in Figure 4. The three WSP cells factors exhibited such as similar sunlight, temperature, pH and dissolved High pH levels (>9) and trends in annual pH fluctuations, where pHoxygen started to(DO). increase in January, reached
over-saturated DO concentrations often coincided with the occurrence of excessive algal growth. The 4 pH in the WSP cells ranged from 6.55 to 10.89, with an average of 8.90 during the monitoring period (mid 2011 to beginning of 2015) as shown in Figure 4. The three WSP cells exhibited similar trends in annual pH fluctuations, where pH started to increase in January, reached a maximum in May, dropped down to below 8 in July, increased again to above 10 in September and then started to decrease in September as ambient temperatures decreased and the daylight hours shortened. The influent pH was
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aWater maximum 2015, 8, 4 in May, dropped down to below 8 in July, increased again to above 10 in September and then toduring decreasemonitoring in September as ambient temperatures andfluctuation the daylightwithin hours WSPs between 6.5started and 7.5 period, which suggesteddecreased that the pH a maximumThe in May, dropped down to below 8 in7.5 July, increased again to abovewhich 10 in September and shortened. influent pH was between 6.5 and during monitoring period, suggested that were likely due to to algal activity.September as ambient temperatures decreased and the daylight hours thenpH started decrease the fluctuation withinin WSPs were likely due to algal activity. shortened. The influent pH was between 6.5 and 7.5 during monitoring period, which suggested that the pH fluctuation within WSPs were likely due to algal activity. 12 12 11
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Figure 4. pH fluctuation in the effluents of Pond 1, Pond 2 and Pond 3.
Figure 4. pH fluctuation in the effluents of Pond 1, Pond 2 and Pond 3.
Figure 5 displays the DOfluctuation concentrations in the effluents each of the three Figure 4. pH in the effluents of Pond 1,of Pond 2 and Pond 3. cells. DO levels fluctuated within the a range 0 to 25 mg/L. in Elevated DO concentrations be attributed to levels Figure 5 displays DO of concentrations the effluents of each ofcould the three cells. DO algalFigure growth.5 displays the DO concentrations in the effluents of each of the three cells. DO levels fluctuated within a range of 0 to 25 mg/L. Elevated DO concentrations could be attributed to fluctuated within a range of 0 to 25 mg/L. Elevated DO concentrations could be attributed to algal growth. algal growth. 30 30 25
DO, mg/L DO, mg/L
25 20 20 15
Pond 1 Pond 2 Pond 31 Pond
15 10
Pond 2 10 5
Figure 5. Changes in DO concentrations in the effluents of Pond 1, Pond 2 and four-year monitoring period. Figure 5. Changes in DO concentrations in the effluents of Pond 1, Pond 2 and Figure Elevated 5. Changes concentrations in the effluents of Pondis1,generally Pond 2 pH in andDO DO in WSPs resulting from algal growth four-year monitoring period.
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and Pond with 3 over associated thethe four-year monitoring period. extensive consumption of dissolved CO2 by algae. Through photosynthesis, algae utilize dissolved Elevated pH and DO in WSPs resulting from algal growth is generally associated with the extensive consumption of dissolved CO2 by algae. 5 Through photosynthesis, algae utilize dissolved
Elevated pH and DO in WSPs resulting from algal growth is generally associated with the extensive consumption of dissolved CO2 by algae. Through photosynthesis, algae utilize dissolved 5 inorganic carbon to produce organic matter, as shown in Equation (1). Oxygen is generated as a photosynthetic byproduct. 6CO2 ` 12H2 O
light, pigment receptor
Ñ
C6 H12 O6 ` 6H2 O ` 6O2
(1)
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inorganic carbon to produce organic matter, as shown in Equation (1). Oxygen is generated as a
When sufficientbyproduct. light is available and nutrients are not limiting, algae in WSPs remove CO2 from photosynthetic light , pigment receptor wastewater more rapidly than heterotrophic microorganisms can produce respiratory CO2 . The 6CO → C6 H12 O (1) uptake 2 + 12 H 2 O ⎯⎯⎯⎯⎯⎯⎯ 6 + 6 H 2 O + 6O2 of CO2 causes a shift in the equilibrium concentrations of dissolved CO2 , carbonic acid (H2 CO3 ), When sufficient light is available and nutrients are not limiting, algae in WSPs remove CO2 bicarbonate ion (HCO ´ ) and carbonate ion (CO3 2´ ),microorganisms the equilibrium relationships can be described from wastewater 3more rapidly than heterotrophic can produce respiratory CO2. by Equations (2)–(4) [21,22]. The uptake of CO2 causes a shift in the equilibrium concentrations of dissolved CO2, carbonic acid 2−),O H2 carbonate CO3 ˚ Ø ion CO(CO (2) (H2CO3), bicarbonate ion (HCO3−) and 2 ` 3H 2 the equilibrium relationships can be described by Equations (2)–(4) [21,22]. ´
HCO3 ` H2 O Ø H2 CO3 ˚ ` OH ´ ∗
↔
(3)
+
(2)
CO32´ ` H2 O Ø HCO∗3´ ` OH ´ +
↔
+
(3)
(4)
When CO2 is removed from the system, to maintain equilibrium, Equations (2)–(4) will shift to the (4) + ↔ + right to produce more CO2 . As a result, hydroxide ions will be released, increasing the pH. Therefore, When 2 is removed from the system, to maintain equilibrium, Equations (2)–(4) will shift to high pH and DOCO levels are often observed in WSPs containing algae. This effect is more pronounced the right to produce more CO2. As a result, hydroxide ions will be released, increasing the pH. during warmer weather and, particularly, during daylight hours [23]. Therefore, high pH and DO levels are often observed in WSPs containing algae. This effect is more Figure 6 displays relationship between E. coli concentrations and pH in Pond 1. As the pronounced duringthe warmer weather and, particularly, during daylight hours [23]. three WSP Figure cells exhibited similar trends in pH fluctuation, Pond 1 data was selected compare the 6 displays the relationship between E. coli concentrations and pH in Pond 1. Asto the three relationship between E. coli concentrations and pH, DO and temperature. As can be seen, the spikes in WSP cells exhibited similar trends in pH fluctuation, Pond 1 data was selected to compare the relationship between E. coli concentrations and pH, DO and temperature. As can be seen, the spikes E. coli concentrations tended to occur when the pH was below 8. As shown in Table 2, the statistical in indicated E. coli concentrations to occur when was below 8. As 2, the where analysis that E. colitended concentrations were the wellpH correlated with pHshown valuesin(ρTable = ´0.54), statistical analysis indicated that E. coli concentrations were well correlated with pH values elevated pH coincided with the decreases in E. coli concentrations. Hence, these observations would (ρ = −0.54), where elevated pH coincided with the decreases in E. coli concentrations. Hence, these suggest that pH levels higher than 8 could be considered effective in E. coli inactivation under these observations would suggest that pH levels higher than 8 could be considered effective in E. coli temperate climatic conditions. inactivation under these temperate climatic conditions. 1600
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Figure 6. The relationship between E. coli population and pH in the effluent of Pond 1.
Figure 6. The relationship between E. coli population and pH in the effluent of Pond 1. Table 2. Spearman rank correlation coefficients between E. coli population and pH, DO and
Table temperature. 2. Spearman rank correlation coefficients between E. coli population and pH, DO and temperature. E. coli pH −0.54 E. coli DO −0.11 pH Temperature ´0.54−0.5 DO Temperature
´0.11
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The observed correlation between E. coli removal and pH is consistent with other studies, which reported increased E. coli inactivation with increases in pH [24,25]. A neutral to slightly acidic pH has been reported as optimal for fecal bacteria growth [26], while pH levels higher than 9 have been
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The observed correlation between E. coli removal and pH is consistent with other studies, which7 of 11 reported increased E. coli inactivation with increases in pH [24,25]. A neutral to slightly acidic pH has been reported as optimal for fecal bacteria growth [26], while pH levels higher than 9 have been reported to be effective in pathogen removal [9,26–28]. Both the terms “removal” and “inactivation” reported to be effective in pathogen removal [9,26–28]. Both the terms “removal” and “inactivation” are intended to refer to the conditions where indicator organisms lose their ability to be cultured using are intended to refer to the conditions where indicator organisms lose their ability to be cultured Standard usingMethods. Standard Methods. A number of explanations forfor thethe effects ofofpH beenproposed. proposed.AA number of A number of explanations effects pHon ondisinfection disinfection have have been number studies have reported that light inactivation of E. coli is dependent on pH [24,25,29]. Under elevated of studies have reported that light inactivation of E. coli is dependent on pH [24,25,29]. Under elevated pH conditions 8.5), E.be coli would be inactivated by exogenous mechanisms, while pH conditions (pH > 8.5), E.(pH coli >would inactivated by exogenous mechanisms, while endogenous endogenous mechanisms would E. coliunder more slowly under morepH moderate pH conditions mechanisms would inactivate E. coliinactivate more slowly more moderate conditions [24,29]. These [24,29]. These could pH8levels 8 were to bein effective E. coli mechanisms couldmechanisms explain why pHexplain levelswhy above wereabove found to befound effective E. coli in inactivation. inactivation. The effects of pH on E. coli have also been attributed to conformational changes in the The effects of pH on E. coli have also been attributed to conformational changes in the membrane of membrane of the bacteria [30,31]. Bacterial inactivation can result from respiratory chain damage the bacteria [30,31]. Bacterial inactivation can result from respiratory chain damage due to a physical due to a physical breakdown in the membrane, which exposes nucleic acids to environmental breakdown the membrane, which exposes nucleic acids to environmental stresses [32]. stressesin [32]. Figure 7 shows thethe relationship between and DO levels. Light inactivation Figure 7 shows relationship betweenE. E. coli coli concentrations concentrations and DO levels. Light inactivation of E. coli and enterococci increased with increasing levels of DO [25]. As previously noted, oxygen is of E. coli and enterococci increased with increasing levels of DO [25]. As previously noted, oxygen is produced as a as by-product of of algal photosynthesis, whichisisalso alsoa source a source of oxygen in WSP systems. produced a by-product algal photosynthesis, which of oxygen in WSP systems. Elevated DO concentrations, highasas2323mg/L, mg/L, were 1. 1. Photo-oxidation, which Elevated DO concentrations, as as high were observed observedininPond Pond Photo-oxidation, which is a disinfection mechanism, requires the presence of oxygen. Photo-oxidation is a process where is a disinfection mechanism, requires the presence of oxygen. Photo-oxidation is a process where endogenous or exogenous sensitizers absorb transfer energy to other molecules endogenous or exogenous sensitizers absorb lightlight and and transfer this this energy to other molecules leading leading to the formation of reactive oxygen species (ROS), which can react with microorganisms and to the formation of reactive oxygen species (ROS), which can react with microorganisms and cause cause damage. Therefore, an increase in DO concentration would be expected to increase the effect damage. Therefore, an increase in DO concentration would be expected to increase the effect of of photo-oxidation. However, DO concentrations were not correlated with E. coli concentrations as photo-oxidation. However, DOisconcentrations were correlated with photo-oxidation E. coli concentrations the spearman’s coefficient low (ρ = −0.11). Thisnot might be because inducedas the spearman’s coefficient is low (ρ = ´0.11). This might be because induced disinfection disinfection is not only dependent on DO concentrations, but alsophoto-oxidation impacted significantly by sunlight is notintensity. only dependent on DO concentrations, but also impacted significantly by sunlight intensity. 1600
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Figure 7. The relationship between E. coli population and DO concentration in the effluent of Pond 1.
Figure 7. The relationship between E. coli population and DO concentration in the effluent of Pond 1.
Figure 8 illustrates the relationship between E. coli concentration and temperature, while
Figure illustrates the relationship between E. coli andoftemperature, while Figure 9 Figure 98 indicates the average, median, minimum and concentration maximum values E. coli concentration for the four different seasons. statistical analysis indicated thatof E.E. coli concentrations were indicates the average, median,The minimum and maximum values coli concentration forwell the four correlated withThe temperature = −0.50),indicated where thethat negative suggested that at correlated lower different seasons. statistical(ρanalysis E. colicorrelation concentrations were well with temperature (ρ = ´0.50), where the negative correlation suggested that at lower temperatures, 7 E. coli concentrations were higher than during the warmer seasons. Notably lower concentrations of E. coli were observed during the warm seasons. The E. coli concentrations during the warmer seasons (April–September) were found to be significantly different from the E. coli concentrations in the colder seasons (October–March) (p < 0.05). These findings suggest that temperature may play a role in the survival of E. coli. E. coli survived better in cold weather (T < 5 ˝ C), possibly because algae growth
temperatures, E. coli concentrations were higher than during the warmer seasons. Notably lower temperatures, E. coli concentrations were higher than during the warmer seasons. Notably lower concentrations of E. coli were observed during the warm seasons. The E. coli concentrations during concentrations of E. coli were observed during the warm seasons. The E. coli concentrations during the warmer seasons (April–September) were found to be significantly different from the E. coli the warmer seasons (April–September) were found to be significantly different from the E. coli concentrations in the colder seasons (October–March) (p < 0.05). These findings suggest that Water 2016, 8, 5 11 concentrations in the colder seasons (October–March) (p < 0.05). These findings suggest8 of that temperature may play a role in the survival of E. coli. E. coli survived better in cold weather (T < 5 temperature may play a role in the survival of E. coli. E. coli survived better in cold weather (T < 5 °C), possibly because algae growth was inhibited due to reduced sunlight intensity, shorter daylight °C), possibly because algae growth was inhibited due to reduced sunlight intensity, shorter daylight period and lower temperature [33]. Reduced algal activity resulted in and a pHlower decrease to ≤8, and a was inhibited due to reduced sunlight intensity, shorter daylight period temperature [33]. period and lower temperature [33]. Reduced algal activity resulted in a pH decrease to ≤8, and a consequently disinfection in the system. On the other hand, efficiency although Reduced algal lower activity resulted in efficiency a pH decrease to studied ď8, and WSP a consequently lower disinfection consequently lower disinfection efficiency in the studied WSP system. On the other hand, although optimal bacterial typically restrictedoptimal to small temperature ranges, bacterial in the studied WSPgrowth system. rates On theare other hand, although bacterial growth rates are typically optimal bacterial growth rates are typically restricted to small temperature ranges, bacterial organismstoare generally ableranges, to survive within broader In within this four-year restricted small temperature bacterial organisms aretemperature generally ableranges. to survive broader organisms are generally able to survive within broader temperature ranges. In this four-year full-scale WSP study,In thethis removal efficiencies E. coli may the increase withefficiencies increasingof temperature. temperature ranges. four-year full-scaleofWSP study, removal E. coli may full-scale WSP study, the removal efficiencies of E. coli may increase with increasing temperature. This observation is consistent with a This number of studies that havewith reported increased removal increase with increasing temperature. observation is consistent a number of studies that This observation is consistent with a number of studies that have reported increased removal efficiencies of fecal coliforms withefficiencies increasingoftemperature [25,34–38]. have reported increased removal fecal coliforms with increasing temperature [25,34–38]. efficiencies of fecal coliforms with increasing temperature [25,34–38]. 1600 1600
30 30
1400 1400
25 25 20 20
1000 1000 800 800
15 15
600 600
10 10
Temperature, oCoC Temperature,
E. E. coli,cfu/100ml coli,cfu/100ml
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0 0
2011-05-17 2011-05-17
200 200
0 0
Figure 8. The relationship between E. coli population and temperature in the the effluent of of Pond 1. 1. Figure 8. 8. The The relationship relationship between between E. E. coli coli population population and and temperature temperature in in Figure the effluent effluent of Pond Pond 1.
Figure 9. Seasonal (Spring: April–June; Summer: July–September; Fall: October–December; Winter: Figure 9. Seasonal (Spring: April–June; Summer: July–September; Fall: October–December; Winter: Figure 9. Seasonal April–June; July–September; Fall:period. October–December; Winter: January–March) E. (Spring: coli concentrations inSummer: Pond 1 during the monitoring January–March) E. coli concentrations in Pond 1 during the monitoring period. January–March) E. coli concentrations in Pond 1 during the monitoring period.
It should be noted that effects of hydraulic retention [39,40], hydraulic efficiency [39,40], It should be noted that effects of hydraulic retention [39,40], hydraulic efficiency [39,40], sunlight [3], attachment/sedimentation [9],hydraulic predation and nutrient availability may all contribute to It should be noted that effects of[9], [39,40], hydraulic [39,40], sunlight [3], attachment/sedimentation predationretention and nutrient availability mayefficiency all contribute to sunlight [3], attachment/sedimentation [9], predation and nutrient availability may all contribute 8 8 to disinfection in WSPs. This study was focused on the environmental factors associated with algae growth, which is commonly present in facultative and maturation ponds due to their long hydraulic retention time.
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4. Conclusions Pathogen removal in WSP systems is driven by a combination of mechanisms and factors. Environmental factors, such as pH, DO and temperature, all play a role in the inactivation of indicator organisms. Elevated pH, due to the presence of algae, and temperature are considered important factors because they were statistically correlated well with E. coli concentrations. pH values higher than 8 in this study were noted to be effective in disinfection. Temperatures lower than 5 ˝ C seemed to inhibit algal activity, but E. coli were able to remain active under the same temperature conditions. Inhibited algal activity may lead to a decrease in pH to below 8, which is not considered to be effective to achieve disinfection. DO concentration was not well correlated with E. coli removal, possibly due to the influence of other factors, such as sunlight penetration and intensity. Pathogen removal efficiencies can be highly variable in WSPs, and exhibit seasonal patterns, such as observations of lower E. coli concentration during the warm season. This would imply that WSPs performance is sensitive to location and climate, making wastewater treatment using natural systems more challenging. The last two WSP cells at the WPCP were noted to further reduce E. coli populations, suggesting that multiple WSP cells in series could provide a more reliable indicator organism (E. coli) removal performance than a single WSP system. Acknowledgments: The authors wish to acknowledge the staff at Amherstview WPCP for their assistance in sample collection and analysis; Marie-Josée Merritt, Jenna Campbell, and Lorie McFarland at Loyalist Township for their assistance with technical background, and site information. The authors would also like to acknowledge the financial support of the Natural Sciences and Engineering Research Council (NSERC), Collaborative Research and Training Experience Program (CREATE) program in civil engineering STEWARD—System Training and Education in Water Assets Research and Development, NSERC Collaborative Research and Development (CRD) and the Canada Research Chairs program. Author Contributions: Amherstview WPCP staff collected and analyzed the samples; Lei Liu analyzed the data; and Lei Liu, Pascale Champagne, and Geoff Hall wrote the paper. Conflicts of Interest: The authors declare no conflict of interest.
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Effects of Environmental Factors on the Disinfection Performance of a Wastewater Stabilization Pond Operated in a Temperate Climate Lei Liu, Geof Hall and Pascale Champagne * Received: 19 October 2015; Accepted: 14 December 2015; Published: 25 December 2015 Academic Editor: Robin Slawson Department of Civil Engineering, Queen’s University, 58 University Ave., Kingston, ON K7L 3N6, Canada; [email protected] (L.L.); [email protected] (G.H.) * Correspondence: [email protected]; Tel.: +1-613-533-3053
Abstract: Treatment in a wastewater stabilization pond (WSP) relies on natural purification processes, which can be sensitive to both location and climate. This study investigated the effects of three environmental factors, pH, dissolved oxygen (DO) and temperature, on disinfection efficiency in a WSP system consisting of three facultative cells, and operated in a temperate climate region, in Eastern Ontario, Canada. Indicator organism (Escherichia coli (E. coli)) removal in WSP systems is driven by a combination of different factors. Elevated pH and DO concentrations, which are attributed to the presence of algae, are important factors for effective disinfection. Therefore, the presence of algae in natural wastewater treatment systems can contribute appreciably to disinfection. Consequently, based on algal concentrations, removal efficiencies of pathogenic microorganisms during wastewater treatment over the course of a year can be highly variable, where higher removal efficiencies would be expected in summer and fall seasons. Keywords: disinfection; wastewater treatment; environmental factors; pH; dissolved oxygen; temperature; E. coli
1. Introduction Pressured by water scarcity and increases in water demand worldwide, treated wastewater has been reused for a variety of purposes over the last few decades, including agricultural irrigation and other industrial, environmental and municipal uses [1,2]. The potential for water reuse is dependent on effective pathogen removal. The disinfection process, generally the last step in wastewater treatment, aims to minimize the risk of pathogen exposure in receiving environments in order to protect public health [2]. However, the removal efficiency of pathogenic organisms can vary greatly and depends on the type of treatment process. Wastewater stabilization ponds (WSPs) are often considered to be the most environmentally and economically sustainable technology for small, rural or remote communities that require low-cost and low-maintenance wastewater treatment systems [3]. WSPs have the capability to effectively attenuate organic and nutrient concentrations, as well as bacteria and pathogen levels, present in municipal wastewater [4,5]. The removal of a wide range of pathogenic organisms, such as bacterial, viral, protozoan and helminthic pathogens, is commonly achieved in WSP systems. Conversely, disinfection methods (UV irradiation, chlorination and ozone) applied in conventional treatments often only target the removal of pathogenic bacteria and viruses, as helminth eggs and protozoan (oo)cysts are resistant to these disinfection methods [6–8]. Some studies have suggested that WSP systems may remove up to 6 log units of bacteria and practically all protozoan and helminth eggs, producing final effluents that meet World Health Organization (WHO) guidelines for the use of treated wastewater in unrestricted Water 2016, 8, 5; doi:10.3390/w8010005
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WSP systems is generally superior to that of conventional treatment processes, such as activated sludge or primary treatments, for whichperformance reductions of to 2 systems log unitsisfor bacteriasuperior and 70%–99% agricultural irrigation [3]. The reported of 1WSP generally to that for of protozoan and helminth eggs have been noted [9].sludge or primary treatments, for which reductions conventional treatment processes, such as activated organisms are often employed reflect pathogen levels in a particular of 1 toIndicator 2 log units for bacteria and 70%–99% fortoprotozoan and helminth eggs have beenwastewater noted [9]. or its effluent, asorganisms it would be time-consuming to monitor eachinpathogenic organism that Indicator arecostly often and employed to reflect pathogen levels a particular wastewater could be present the treated wastewater. It is expectedtothat indicator be detected or its effluent, as itinwould be costly and time-consuming monitor each organisms pathogeniccan organism that and quantified easily and cost-effectively. presence, behavior,organisms and population of indicator could be present in the treated wastewater. It isThe expected that indicator can be detected and organismseasily and other pathogens are The generally assumed to be correlated [10,11]. For theorganisms past few quantified and cost-effectively. presence, behavior, and population of indicator decades, bacterial indicator organisms, Escherichia coli (E. fecalfew coliforms total and other pathogens are generally assumedsuch to beascorrelated [10,11]. Forcoli), the past decades,and bacterial coliforms, have been commonly used for monitoring and regulating pathogen levels in treated indicator organisms, such as Escherichia coli (E. coli), fecal coliforms and total coliforms, have been wastewater. However, the limitations of bacterial indicator have been recognized in commonly used for monitoring and regulating pathogen levels organisms in treated wastewater. However, the recent publications. In some studies, E. coli populations were not found to be well correlated with limitations of bacterial indicator organisms have been recognized in recent publications. In some pathogenic including Vibrio cholera andwith Enterococcus (E.including faecalis). studies, E. colibacteria populations were not found to be (V. wellcholera) correlated pathogenicfaecalis bacteria Populations choleraand andEnterococcus E. faecalis increased with increasing pH andof temperature, while E. coli Vibrio cholera of (V.V. cholera) faecalis (E. faecalis). Populations V. cholera and E. faecalis populations decreased [12–14]. Burkhardt III et al. [15], and Len et al. [16], also challenged the increased with increasing pH and temperature, while E. coli populations decreased [12–14]. Burkhardt reliability of E. coliLen as et a pathogen indicator. Nascimento et al. [17], usingindicator. multiple III et al. [15], and al. [16], also challenged the reliability of E.recommended coli as a pathogen organisms as indictors, because the removal kinetics of various pathogens differ. A number of Nascimento et al. [17], recommended using multiple organisms as indictors, because the removal municipalities, such as the one in this study, continue to employ E. coli as indicator organisms kinetics of various pathogens differ. A number of municipalities, such as the one in this study, continue because wastewater treatment plants are required to meettreatment the effluent standards specified in to employthe E. coli as indicator organisms because the wastewater plants are required to meet their Certificate of Approval issued by the Ontario Ministry of the Environment, as well as the newer the effluent standards specified in their Certificate of Approval issued by the Ontario Ministry of Canadian Wastewater Effluent Regulation which Regulation stipulate minimum coli the Environment, as well as the newer Canadian Guidelines, Wastewater Effluent Guidelines, E. which concentrations. stipulate minimum E. coli concentrations. 2. Materials and and Methods Methods 2. Materials 2.1. 2.1. System System Overview Overview In In this this study, study, water water samples samples were were collected collected from from the the effluents effluents of of three three WSP WSP cells cells at at aa Water Water Pollution Control Plant (WPCP) located in Eastern Ontario (Canada), with a rated average Pollution Control Plant (WPCP) located in Eastern Ontario (Canada), with a rated average daily daily flow flow 3 3 capacity and rated The treatment treatment system capacity of of5700 5700m m3/day /day and rated peak peak capacity capacity of of 16,000 16,000m m3/day. /day. The system consists consists of of primary treatment, biological treatment via an extended aeration activated sludge process, secondary primary treatment, biological treatment via an extended aeration activated sludge process, secondary clarification, followed by by effluent effluent polishing The flow flow diagram diagram of clarification, followed polishing WSPs. WSPs. The of the the WPCP WPCP is is presented presented in in Figure Figure 1. 1.
Pond #1
Pond #2
Pond #3
Figure 1. 1. The The configuration configuration of of the the wastewater wastewater treatment treatmentplant plant[18]. [18]. Figure
2
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The main wastewater treatment plant feeds into WSP Pond 1, flowed by Pond 2, and then Pond 3. The three facultative WSPs are operated in series, provide a total volume of 154,794 m3 and primarily facilitate disinfection prior to discharge. Table 1 summarizes the area, volume, and depth of the WSPs based on field measurements. The hydraulic retention time of the WSP system is approximately 27 days, which is anticipated to be sufficient for disinfection of secondary effluent. The discharge limit for this plant is 200 CFU/100 mL and the design objective is 100 CFU/100 mL. Table 1. Area, volume and depth of the wastewater stabilization ponds (WSPs) [19]. WSP
Surface Area (m2 )
Volume (m3 )
Depth (m)
1 2 3 Total
48,600 28,200 31,200 108,000
78,246 40,044 36,504 154,794
1.61 1.42 1.17 4.2
2.2. Field Monitoring and Sampling Eastern Ontario has a humid continental climate with four distinct seasons: winter, spring, summer and fall. Over the course of a year, the temperature typically varies from ´15 to 26 ˝ C and is rarely below ´24 ˝ C or above 31 ˝ C. The relative humidity typically ranges from 40% (comfortable) to 94% (very humid), rarely dropping below 22% (dry) and reaching as high as 100% (very humid). Monitoring was carried out from 10 May 2011 to 24 February 2015 and comprised of periods of cold climate (January–March), warm weather (April–June), the hottest season (July–September) and the return of cooler weather (October–December). pH, dissolved oxygen (DO) and temperature were measured at the effluent weirs of the three ponds between 10 am and 12 pm at weekly intervals. pH and temperature were recorded using a HQ40d (Hach, Loveland, CO), a portable pH, conductivity, DO, ORP and ISE multi-parameter meter, while DO was monitored using a Model 3100 portable dissolved oxygen analyzer (Insite IG, Slidell, LA, USA). At the same time, effluent samples were collected for E. coli analysis. The culture and enumeration of E. coli were carried out using the membrane filtration method according to Standard Methods for the Examination of Water and Wastewater [20]. 2.3. Statistical Analysis Because the data could not be assumed to be normally distributed, the non-parametric Spearman ρ correlation coefficient was evaluated. MATLAB codes were developed to calculate the correlation coefficient. Spearman’s rank correlation coefficient is a measure of statistical dependence between two variables. A Spearman correlation coefficient of 1 or ´1 results when the two variables being compared are monotonically related. If one variable tends to increase when the other variable increases, the Spearman correlation coefficient is positive. Conversely, if one variable tends to decrease when the other variable increases, the Spearman correlation coefficient is negative. The Spearman correlation increases in magnitudes as two variables become closer to being perfect monotone functions of each other. An absolute value of Spearman correlation coefficient larger than 0.5 suggests that the two variables are well correlated, a value between 0.25 and 0.5 indicates the two variables are moderately correlated, while a value below 0.1 suggests the two variables are not correlated. 3. Results and Discussion The influent to Pond 1 typically contains over 2000 CFU/100 mL of E. coli. The four-year average effluent E. coli of Pond 1, Pond 2 and Pond 3 were 84, 26, 28 CFU/100 mL respectively. More than 98.6% of disinfection efficiency was achieved throughout this WSP system. Spikes in E. coli concentrations were observed in the effluent of the first pond, some of which exceeded the dischargeable microbiological level of 200 CFU/100 mL of E. coli (Figure 2). Figure 3 shows the average, median, minimum and maximum value of E. coli concentrations in the effluents of the three WSP cells
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over theWSP monitoring The maximum coli concentration observed in Pond 1 was more than cells over period. the monitoring period. TheE. maximum E. coli concentration observed in Pond 1 was more than that of the discharge criteria. Most of the spikes were to noted to occur during seven times that seven of thetimes discharge criteria. Most of the spikes were noted occur during the colder the colder seasons (November–March). The next two ponds (Pond 2 and Pond 3) provided further seasons (November–March). The next two ponds (Pond 2 and Pond 3) provided further reduction in E. coli concentration to lower levels. E. coli concentrations above 200 CFU/100 mL were in E. colireduction concentration to lower levels. E. coli concentrations above 200 CFU/100 mL were rarely rarely observed, and at no time did the monthly geometric mean density of E. coli exceeded 200 observed, and at no time did the monthly geometric mean density of E. coli exceeded 200 CFU/100 mL. CFU/100 mL. 1600
1400
E. coli CFU/100ml
1200
1000
800
Pond 1 Pond 2 Pond 3
600
400
200
20
20
20
11 -
05
11 10 -0 711 10 -0 2 0 9 -1 0 11 -1 2 0 1 -1 0 12 -0 2 0 1 -1 0 12 -0 2 0 3 -1 0 12 -0 2 0 5 -1 0 12 -0 2 0 7 -1 0 12 -0 2 0 9 -1 0 12 -1 2 0 1 -1 0 13 -0 2 0 1 -1 0 13 -0 2 0 3 -1 0 13 -0 2 0 5 -1 0 13 -0 2 0 7 -1 0 13 -0 2 0 9 -1 0 13 -1 2 0 1 -1 0 14 -0 2 0 1 -1 0 14 -0 2 0 3 -1 0 14 -0 2 0 5 -1 0 14 -0 2 0 7 -1 0 14 -0 2 0 9 -1 0 14 -1 2 0 1 -1 0 15 -0 110
0
Figure 2. E. coli concentrations in the effluents of Pond 1, Pond 2 and Pond 3 of the Amherstview WPCP.
Figure 2. E. coli concentrations in the effluents of Pond 1, Pond 2 and Pond 3 of the Amherstview WPCP.
Figure 3. Average, median, minimum and maximum value of E. coli concentrations in the WSP effluents over a four year monitoring period.
Figure 3. Average, median, minimum and of E. coli concentrations in thepurification WSP effluents The treatment and disinfection of maximum wastewatervalue in WSPs mainly rely on natural over a four year monitoring period. processes. Hence, treatment and disinfection efficiency is expected to be influenced by environmental factors such as sunlight, temperature, pH and dissolved oxygen (DO). High pH (>9) and over-saturated DO concentrations often coincided with the occurrence of excessive Thelevels treatment and disinfection of wastewater in WSPs mainly rely on natural purification algal growth. The pH in the WSP cells ranged from 6.55 to 10.89, with an average of 8.90 during the processes. Hence, treatment and disinfection efficiency is expected to be influenced by environmental monitoring period (mid 2011 to beginning of 2015) as shown in Figure 4. The three WSP cells factors exhibited such as similar sunlight, temperature, pH and dissolved High pH levels (>9) and trends in annual pH fluctuations, where pHoxygen started to(DO). increase in January, reached
over-saturated DO concentrations often coincided with the occurrence of excessive algal growth. The 4 pH in the WSP cells ranged from 6.55 to 10.89, with an average of 8.90 during the monitoring period (mid 2011 to beginning of 2015) as shown in Figure 4. The three WSP cells exhibited similar trends in annual pH fluctuations, where pH started to increase in January, reached a maximum in May, dropped down to below 8 in July, increased again to above 10 in September and then started to decrease in September as ambient temperatures decreased and the daylight hours shortened. The influent pH was
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aWater maximum 2015, 8, 4 in May, dropped down to below 8 in July, increased again to above 10 in September and then toduring decreasemonitoring in September as ambient temperatures andfluctuation the daylightwithin hours WSPs between 6.5started and 7.5 period, which suggesteddecreased that the pH a maximumThe in May, dropped down to below 8 in7.5 July, increased again to abovewhich 10 in September and shortened. influent pH was between 6.5 and during monitoring period, suggested that were likely due to to algal activity.September as ambient temperatures decreased and the daylight hours thenpH started decrease the fluctuation withinin WSPs were likely due to algal activity. shortened. The influent pH was between 6.5 and 7.5 during monitoring period, which suggested that the pH fluctuation within WSPs were likely due to algal activity. 12 12 11
pH
pH
11 10 10 9
Pond 1 Pond 2
9 8
Pond 31 Pond Pond 2
8 7
Pond 3
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2011-11-10 2011-11-10
2011-09-10 2011-09-10
2011-07-10 2011-07-10
6
2011-05-10 2011-05-10
7 6
Figure 4. pH fluctuation in the effluents of Pond 1, Pond 2 and Pond 3.
Figure 4. pH fluctuation in the effluents of Pond 1, Pond 2 and Pond 3.
Figure 5 displays the DOfluctuation concentrations in the effluents each of the three Figure 4. pH in the effluents of Pond 1,of Pond 2 and Pond 3. cells. DO levels fluctuated within the a range 0 to 25 mg/L. in Elevated DO concentrations be attributed to levels Figure 5 displays DO of concentrations the effluents of each ofcould the three cells. DO algalFigure growth.5 displays the DO concentrations in the effluents of each of the three cells. DO levels fluctuated within a range of 0 to 25 mg/L. Elevated DO concentrations could be attributed to fluctuated within a range of 0 to 25 mg/L. Elevated DO concentrations could be attributed to algal growth. algal growth. 30 30 25
DO, mg/L DO, mg/L
25 20 20 15
Pond 1 Pond 2 Pond 31 Pond
15 10
Pond 2 10 5
Figure 5. Changes in DO concentrations in the effluents of Pond 1, Pond 2 and four-year monitoring period. Figure 5. Changes in DO concentrations in the effluents of Pond 1, Pond 2 and Figure Elevated 5. Changes concentrations in the effluents of Pondis1,generally Pond 2 pH in andDO DO in WSPs resulting from algal growth four-year monitoring period.
2015-01-10 2015-01-10
2014-11-10 2014-11-10
2014-09-10 2014-09-10
2014-07-10 2014-07-10
2014-05-10 2014-05-10
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0
2011-05-10 2011-05-10
5 0
Pond 3
Pond 3 over the Pond 3 over the
and Pond with 3 over associated thethe four-year monitoring period. extensive consumption of dissolved CO2 by algae. Through photosynthesis, algae utilize dissolved Elevated pH and DO in WSPs resulting from algal growth is generally associated with the extensive consumption of dissolved CO2 by algae. 5 Through photosynthesis, algae utilize dissolved
Elevated pH and DO in WSPs resulting from algal growth is generally associated with the extensive consumption of dissolved CO2 by algae. Through photosynthesis, algae utilize dissolved 5 inorganic carbon to produce organic matter, as shown in Equation (1). Oxygen is generated as a photosynthetic byproduct. 6CO2 ` 12H2 O
light, pigment receptor
Ñ
C6 H12 O6 ` 6H2 O ` 6O2
(1)
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inorganic carbon to produce organic matter, as shown in Equation (1). Oxygen is generated as a
When sufficientbyproduct. light is available and nutrients are not limiting, algae in WSPs remove CO2 from photosynthetic light , pigment receptor wastewater more rapidly than heterotrophic microorganisms can produce respiratory CO2 . The 6CO → C6 H12 O (1) uptake 2 + 12 H 2 O ⎯⎯⎯⎯⎯⎯⎯ 6 + 6 H 2 O + 6O2 of CO2 causes a shift in the equilibrium concentrations of dissolved CO2 , carbonic acid (H2 CO3 ), When sufficient light is available and nutrients are not limiting, algae in WSPs remove CO2 bicarbonate ion (HCO ´ ) and carbonate ion (CO3 2´ ),microorganisms the equilibrium relationships can be described from wastewater 3more rapidly than heterotrophic can produce respiratory CO2. by Equations (2)–(4) [21,22]. The uptake of CO2 causes a shift in the equilibrium concentrations of dissolved CO2, carbonic acid 2−),O H2 carbonate CO3 ˚ Ø ion CO(CO (2) (H2CO3), bicarbonate ion (HCO3−) and 2 ` 3H 2 the equilibrium relationships can be described by Equations (2)–(4) [21,22]. ´
HCO3 ` H2 O Ø H2 CO3 ˚ ` OH ´ ∗
↔
(3)
+
(2)
CO32´ ` H2 O Ø HCO∗3´ ` OH ´ +
↔
+
(3)
(4)
When CO2 is removed from the system, to maintain equilibrium, Equations (2)–(4) will shift to the (4) + ↔ + right to produce more CO2 . As a result, hydroxide ions will be released, increasing the pH. Therefore, When 2 is removed from the system, to maintain equilibrium, Equations (2)–(4) will shift to high pH and DOCO levels are often observed in WSPs containing algae. This effect is more pronounced the right to produce more CO2. As a result, hydroxide ions will be released, increasing the pH. during warmer weather and, particularly, during daylight hours [23]. Therefore, high pH and DO levels are often observed in WSPs containing algae. This effect is more Figure 6 displays relationship between E. coli concentrations and pH in Pond 1. As the pronounced duringthe warmer weather and, particularly, during daylight hours [23]. three WSP Figure cells exhibited similar trends in pH fluctuation, Pond 1 data was selected compare the 6 displays the relationship between E. coli concentrations and pH in Pond 1. Asto the three relationship between E. coli concentrations and pH, DO and temperature. As can be seen, the spikes in WSP cells exhibited similar trends in pH fluctuation, Pond 1 data was selected to compare the relationship between E. coli concentrations and pH, DO and temperature. As can be seen, the spikes E. coli concentrations tended to occur when the pH was below 8. As shown in Table 2, the statistical in indicated E. coli concentrations to occur when was below 8. As 2, the where analysis that E. colitended concentrations were the wellpH correlated with pHshown valuesin(ρTable = ´0.54), statistical analysis indicated that E. coli concentrations were well correlated with pH values elevated pH coincided with the decreases in E. coli concentrations. Hence, these observations would (ρ = −0.54), where elevated pH coincided with the decreases in E. coli concentrations. Hence, these suggest that pH levels higher than 8 could be considered effective in E. coli inactivation under these observations would suggest that pH levels higher than 8 could be considered effective in E. coli temperate climatic conditions. inactivation under these temperate climatic conditions. 1600
11
1400
10
1200
1000 8 pH
E. coli CFU/100ml
9
800 7
E. coli pH
600 6 400 5
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0
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200
4
Figure 6. The relationship between E. coli population and pH in the effluent of Pond 1.
Figure 6. The relationship between E. coli population and pH in the effluent of Pond 1. Table 2. Spearman rank correlation coefficients between E. coli population and pH, DO and
Table temperature. 2. Spearman rank correlation coefficients between E. coli population and pH, DO and temperature. E. coli pH −0.54 E. coli DO −0.11 pH Temperature ´0.54−0.5 DO Temperature
´0.11
6 ´0.5
The observed correlation between E. coli removal and pH is consistent with other studies, which reported increased E. coli inactivation with increases in pH [24,25]. A neutral to slightly acidic pH has been reported as optimal for fecal bacteria growth [26], while pH levels higher than 9 have been
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The observed correlation between E. coli removal and pH is consistent with other studies, which7 of 11 reported increased E. coli inactivation with increases in pH [24,25]. A neutral to slightly acidic pH has been reported as optimal for fecal bacteria growth [26], while pH levels higher than 9 have been reported to be effective in pathogen removal [9,26–28]. Both the terms “removal” and “inactivation” reported to be effective in pathogen removal [9,26–28]. Both the terms “removal” and “inactivation” are intended to refer to the conditions where indicator organisms lose their ability to be cultured using are intended to refer to the conditions where indicator organisms lose their ability to be cultured Standard usingMethods. Standard Methods. A number of explanations forfor thethe effects ofofpH beenproposed. proposed.AA number of A number of explanations effects pHon ondisinfection disinfection have have been number studies have reported that light inactivation of E. coli is dependent on pH [24,25,29]. Under elevated of studies have reported that light inactivation of E. coli is dependent on pH [24,25,29]. Under elevated pH conditions 8.5), E.be coli would be inactivated by exogenous mechanisms, while pH conditions (pH > 8.5), E.(pH coli >would inactivated by exogenous mechanisms, while endogenous endogenous mechanisms would E. coliunder more slowly under morepH moderate pH conditions mechanisms would inactivate E. coliinactivate more slowly more moderate conditions [24,29]. These [24,29]. These could pH8levels 8 were to bein effective E. coli mechanisms couldmechanisms explain why pHexplain levelswhy above wereabove found to befound effective E. coli in inactivation. inactivation. The effects of pH on E. coli have also been attributed to conformational changes in the The effects of pH on E. coli have also been attributed to conformational changes in the membrane of membrane of the bacteria [30,31]. Bacterial inactivation can result from respiratory chain damage the bacteria [30,31]. Bacterial inactivation can result from respiratory chain damage due to a physical due to a physical breakdown in the membrane, which exposes nucleic acids to environmental breakdown the membrane, which exposes nucleic acids to environmental stresses [32]. stressesin [32]. Figure 7 shows thethe relationship between and DO levels. Light inactivation Figure 7 shows relationship betweenE. E. coli coli concentrations concentrations and DO levels. Light inactivation of E. coli and enterococci increased with increasing levels of DO [25]. As previously noted, oxygen is of E. coli and enterococci increased with increasing levels of DO [25]. As previously noted, oxygen is produced as a as by-product of of algal photosynthesis, whichisisalso alsoa source a source of oxygen in WSP systems. produced a by-product algal photosynthesis, which of oxygen in WSP systems. Elevated DO concentrations, highasas2323mg/L, mg/L, were 1. 1. Photo-oxidation, which Elevated DO concentrations, as as high were observed observedininPond Pond Photo-oxidation, which is a disinfection mechanism, requires the presence of oxygen. Photo-oxidation is a process where is a disinfection mechanism, requires the presence of oxygen. Photo-oxidation is a process where endogenous or exogenous sensitizers absorb transfer energy to other molecules endogenous or exogenous sensitizers absorb lightlight and and transfer this this energy to other molecules leading leading to the formation of reactive oxygen species (ROS), which can react with microorganisms and to the formation of reactive oxygen species (ROS), which can react with microorganisms and cause cause damage. Therefore, an increase in DO concentration would be expected to increase the effect damage. Therefore, an increase in DO concentration would be expected to increase the effect of of photo-oxidation. However, DO concentrations were not correlated with E. coli concentrations as photo-oxidation. However, DOisconcentrations were correlated with photo-oxidation E. coli concentrations the spearman’s coefficient low (ρ = −0.11). Thisnot might be because inducedas the spearman’s coefficient is low (ρ = ´0.11). This might be because induced disinfection disinfection is not only dependent on DO concentrations, but alsophoto-oxidation impacted significantly by sunlight is notintensity. only dependent on DO concentrations, but also impacted significantly by sunlight intensity. 1600
25
1400 20
1000
15 DO, mg/L
E. coli, CFU/100ml
1200
800 10
600
E. coli DO
400 5 200
2015-01-17
2014-11-17
2014-09-17
2014-07-17
2014-05-17
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2012-07-17
2012-05-17
2012-03-17
2012-01-17
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2011-09-17
2011-07-17
0 2011-05-17
0
Figure 7. The relationship between E. coli population and DO concentration in the effluent of Pond 1.
Figure 7. The relationship between E. coli population and DO concentration in the effluent of Pond 1.
Figure 8 illustrates the relationship between E. coli concentration and temperature, while
Figure illustrates the relationship between E. coli andoftemperature, while Figure 9 Figure 98 indicates the average, median, minimum and concentration maximum values E. coli concentration for the four different seasons. statistical analysis indicated thatof E.E. coli concentrations were indicates the average, median,The minimum and maximum values coli concentration forwell the four correlated withThe temperature = −0.50),indicated where thethat negative suggested that at correlated lower different seasons. statistical(ρanalysis E. colicorrelation concentrations were well with temperature (ρ = ´0.50), where the negative correlation suggested that at lower temperatures, 7 E. coli concentrations were higher than during the warmer seasons. Notably lower concentrations of E. coli were observed during the warm seasons. The E. coli concentrations during the warmer seasons (April–September) were found to be significantly different from the E. coli concentrations in the colder seasons (October–March) (p < 0.05). These findings suggest that temperature may play a role in the survival of E. coli. E. coli survived better in cold weather (T < 5 ˝ C), possibly because algae growth
temperatures, E. coli concentrations were higher than during the warmer seasons. Notably lower temperatures, E. coli concentrations were higher than during the warmer seasons. Notably lower concentrations of E. coli were observed during the warm seasons. The E. coli concentrations during concentrations of E. coli were observed during the warm seasons. The E. coli concentrations during the warmer seasons (April–September) were found to be significantly different from the E. coli the warmer seasons (April–September) were found to be significantly different from the E. coli concentrations in the colder seasons (October–March) (p < 0.05). These findings suggest that Water 2016, 8, 5 11 concentrations in the colder seasons (October–March) (p < 0.05). These findings suggest8 of that temperature may play a role in the survival of E. coli. E. coli survived better in cold weather (T < 5 temperature may play a role in the survival of E. coli. E. coli survived better in cold weather (T < 5 °C), possibly because algae growth was inhibited due to reduced sunlight intensity, shorter daylight °C), possibly because algae growth was inhibited due to reduced sunlight intensity, shorter daylight period and lower temperature [33]. Reduced algal activity resulted in and a pHlower decrease to ≤8, and a was inhibited due to reduced sunlight intensity, shorter daylight period temperature [33]. period and lower temperature [33]. Reduced algal activity resulted in a pH decrease to ≤8, and a consequently disinfection in the system. On the other hand, efficiency although Reduced algal lower activity resulted in efficiency a pH decrease to studied ď8, and WSP a consequently lower disinfection consequently lower disinfection efficiency in the studied WSP system. On the other hand, although optimal bacterial typically restrictedoptimal to small temperature ranges, bacterial in the studied WSPgrowth system. rates On theare other hand, although bacterial growth rates are typically optimal bacterial growth rates are typically restricted to small temperature ranges, bacterial organismstoare generally ableranges, to survive within broader In within this four-year restricted small temperature bacterial organisms aretemperature generally ableranges. to survive broader organisms are generally able to survive within broader temperature ranges. In this four-year full-scale WSP study,In thethis removal efficiencies E. coli may the increase withefficiencies increasingof temperature. temperature ranges. four-year full-scaleofWSP study, removal E. coli may full-scale WSP study, the removal efficiencies of E. coli may increase with increasing temperature. This observation is consistent with a This number of studies that havewith reported increased removal increase with increasing temperature. observation is consistent a number of studies that This observation is consistent with a number of studies that have reported increased removal efficiencies of fecal coliforms withefficiencies increasingoftemperature [25,34–38]. have reported increased removal fecal coliforms with increasing temperature [25,34–38]. efficiencies of fecal coliforms with increasing temperature [25,34–38]. 1600 1600
30 30
1400 1400
25 25 20 20
1000 1000 800 800
15 15
600 600
10 10
Temperature, oCoC Temperature,
E. E. coli,cfu/100ml coli,cfu/100ml
1200 1200
E. coli E. coli T T
400 400 5 5
2015-01-17 2015-01-17
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0 0
2011-05-17 2011-05-17
200 200
0 0
Figure 8. The relationship between E. coli population and temperature in the the effluent of of Pond 1. 1. Figure 8. 8. The The relationship relationship between between E. E. coli coli population population and and temperature temperature in in Figure the effluent effluent of Pond Pond 1.
Figure 9. Seasonal (Spring: April–June; Summer: July–September; Fall: October–December; Winter: Figure 9. Seasonal (Spring: April–June; Summer: July–September; Fall: October–December; Winter: Figure 9. Seasonal April–June; July–September; Fall:period. October–December; Winter: January–March) E. (Spring: coli concentrations inSummer: Pond 1 during the monitoring January–March) E. coli concentrations in Pond 1 during the monitoring period. January–March) E. coli concentrations in Pond 1 during the monitoring period.
It should be noted that effects of hydraulic retention [39,40], hydraulic efficiency [39,40], It should be noted that effects of hydraulic retention [39,40], hydraulic efficiency [39,40], sunlight [3], attachment/sedimentation [9],hydraulic predation and nutrient availability may all contribute to It should be noted that effects of[9], [39,40], hydraulic [39,40], sunlight [3], attachment/sedimentation predationretention and nutrient availability mayefficiency all contribute to sunlight [3], attachment/sedimentation [9], predation and nutrient availability may all contribute 8 8 to disinfection in WSPs. This study was focused on the environmental factors associated with algae growth, which is commonly present in facultative and maturation ponds due to their long hydraulic retention time.
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4. Conclusions Pathogen removal in WSP systems is driven by a combination of mechanisms and factors. Environmental factors, such as pH, DO and temperature, all play a role in the inactivation of indicator organisms. Elevated pH, due to the presence of algae, and temperature are considered important factors because they were statistically correlated well with E. coli concentrations. pH values higher than 8 in this study were noted to be effective in disinfection. Temperatures lower than 5 ˝ C seemed to inhibit algal activity, but E. coli were able to remain active under the same temperature conditions. Inhibited algal activity may lead to a decrease in pH to below 8, which is not considered to be effective to achieve disinfection. DO concentration was not well correlated with E. coli removal, possibly due to the influence of other factors, such as sunlight penetration and intensity. Pathogen removal efficiencies can be highly variable in WSPs, and exhibit seasonal patterns, such as observations of lower E. coli concentration during the warm season. This would imply that WSPs performance is sensitive to location and climate, making wastewater treatment using natural systems more challenging. The last two WSP cells at the WPCP were noted to further reduce E. coli populations, suggesting that multiple WSP cells in series could provide a more reliable indicator organism (E. coli) removal performance than a single WSP system. Acknowledgments: The authors wish to acknowledge the staff at Amherstview WPCP for their assistance in sample collection and analysis; Marie-Josée Merritt, Jenna Campbell, and Lorie McFarland at Loyalist Township for their assistance with technical background, and site information. The authors would also like to acknowledge the financial support of the Natural Sciences and Engineering Research Council (NSERC), Collaborative Research and Training Experience Program (CREATE) program in civil engineering STEWARD—System Training and Education in Water Assets Research and Development, NSERC Collaborative Research and Development (CRD) and the Canada Research Chairs program. Author Contributions: Amherstview WPCP staff collected and analyzed the samples; Lei Liu analyzed the data; and Lei Liu, Pascale Champagne, and Geoff Hall wrote the paper. Conflicts of Interest: The authors declare no conflict of interest.
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