Impact of coagulation on SARS-CoV-2 and PMMoV viral signal in wastewater solids

Abstract

Wastewater surveillance (WWS) has received interest from researchers, scientists, and public health units for its application in monitoring active COVID-19 cases and detecting outbreaks. While WWS of SARS-CoV-2 has been widely applied worldwide, a knowledge gap exists concerning the effects of enhanced primary clarification, the application of coagulant to primary clarifiers, on SARS-CoV-2 and PMMoV quantification for reliable wastewater-based epidemiology. Ferric-based chemical coagulants are extensively used in enhanced clarification, particularly for phosphorus removal, in North America, and Europe. This study examines the effects of coagulation with ferric sulfate on the measurement of SARS-CoV-2 and PMMoV viral measurements in wastewater primary sludge and hence also settled solids. The addition of Fe ³⁺ to wastewater solids ranging from 0 to 60 mg/L caused no change in N1 and N2 gene region measurements in wastewater solids, where Fe ³⁺ concentrations in primary clarified sludge represent the conventional minimum and maximum concentrations of applied ferric-based coagulant. However, elevated Fe ³⁺ concentrations were shown to be associated with a statistically significant increase in PMMoV viral measurements in wastewater solids, which consequently resulted in the underestimation of PMMoV normalized SARS-CoV-2 viral signal measurements (N1 and N2 copies/copies of PMMoV). pH reduction from coagulant addition did not contribute to the increase in PMMoV measurements. Thus, this phenomenon is likely attributed to the partitioning of PMMoV particles to the solids of wastewater from the bulk liquid phase of wastewater.

Full text

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Impact of coagulation on SARS-CoV-2 and PMMoV
viral signal in wastewater solids
Nada Hegazy (  nhega051@uottawa.ca )
University of Ottawa Faculty of Engineering https://orcid.org/0000-0003-4277-076X
Xin Tian
University of Ottawa Faculty of Engineering
Patrick M. D'Aoust
University of Ottawa Faculty of Engineering
Lakshmi Pisharody
University of Ottawa Faculty of Engineering
Syeda Tasneem Towhid
University of Ottawa Faculty of Engineering
Élisabeth Mercier
University of Ottawa Faculty of Engineering
Zhihao Zhang
University of Ottawa Faculty of Engineering
Shen Wan
University of Ottawa Faculty of Engineering
Ocean Thakali
University of Ottawa Faculty of Engineering
Md Pervez Kabir
University of Ottawa Faculty of Engineering
Wanting Fang
University of Ottawa Faculty of Engineering
Tram B. Nguyen
University of Ottawa Faculty of Engineering
Nathan T. Ramsay
University of Ottawa Faculty of Engineering
Alex E. MacKenzie
Children's Hospital of Eastern Ontario Research Institute
Tyson E. Graber
Children's Hospital of Eastern Ontario Research Institute
Stéphanie Guilherme
University of Ottawa Faculty of Engineering
Robert Delatolla

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University of Ottawa
Research Article
Keywords: coagulation, normalization, partitioning, primary sludge, wastewater surveillance
Posted Date: July 7th, 2023
DOI: https://doi.org/10.21203/rs.3.rs-3001706/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full License

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Abstract
Wastewater surveillance (WWS) has received interest from researchers, scientists, and public health units
for its application in monitoring active COVID-19 cases and detecting outbreaks. While WWS of SARS-
CoV-2 has been widely applied worldwide, a knowledge gap exists concerning the effects of enhanced
primary clarication, the application of coagulant to primary clariers, on SARS-CoV-2 and PMMoV
quantication for reliable wastewater-based epidemiology. Ferric-based chemical coagulants are
extensively used in enhanced clarication, particularly for phosphorus removal, in North America, and
Europe. This study examines the effects of coagulation with ferric sulfate on the measurement of SARS-
CoV-2 and PMMoV viral measurements in wastewater primary sludge and hence also settled solids. The
addition of Fe3+ to wastewater solids ranging from 0 to 60 mg/L caused no change in N1 and N2 gene
region measurements in wastewater solids, where Fe3+ concentrations in primary claried sludge
represent the conventional minimum and maximum concentrations of applied ferric-based coagulant.
However, elevated Fe3+ concentrations were shown to be associated with a statistically signicant
increase in PMMoV viral measurements in wastewater solids, which consequently resulted in the
underestimation of PMMoV normalized SARS-CoV-2 viral signal measurements (N1 and N2
copies/copies of PMMoV). pH reduction from coagulant addition did not contribute to the increase in
PMMoV measurements. Thus, this phenomenon is likely attributed to the partitioning of PMMoV particles
to the solids of wastewater from the bulk liquid phase of wastewater.
Highlights
Effects of primary coagulation on SARS-CoV-2 and PMMoV measurements are unknown.
Fe3+ addition to 60 mg/L had no effect on SARS-CoV-2 N1 and N2 measurements.
Fe3+ addition to 60 mg/L elevated PMMoV measurements due to enhanced liquid-to-solid
partitioning
Fe3+ addition to 60 mg/L underrepresents PMMoV-normalized N1 and N2 measurements.
pH change associated with Fe3+ addition has no effect on PMMoV-normalized N1 and N2
measurements.
1 Introduction
Wastewater surveillance (WWS) efforts for monitoring active COVID-19-positive cases are ongoing
worldwide and are playing a major role in the early detection of community outbreaks (Ahmed et al.,
2020; Arora et al., 2020; Bivins et al., 2020; D’Aoust et al., 2021a; Gonzalez et al., 2020; La Rosa et al.,
2021; Mao et al., 2020; McClary-Gutierrez et al., 2021; Medema et al., 2020; Polo et al., 2020; Randazzo et
al., 2020a, 2020b; Sims and Kasprzyk-Hordern, 2020; Thompson et al., 2020; Wu et al., 2020). Solids-
based viral extraction protocols for measuring SARS-CoV-2 in wastewater have been shown to perform
well with samples rich in solids such as primary sludge, raw wastewater inuent, and municipal

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wastewaters collected within sewered infrastructure (Balboa et al., 2020; D’Aoust et al., 2021b; Graham et
al., 2021; Peccia et al., 2020; Petala et al., 2021; Westhaus et al., 2021; Wu et al., 2020). Previous studies
suggest signicant and/or higher sensitivity of SARS-CoV-2 RNA detection from testing primary sludge
compared to testing inuent (D’Aoust et al., 2021b, 2021a; Graham et al., 2021; Peccia et al., 2020; Zulli et
al., 2021). Additionally, the estimation of COVID-19 disease incidence and clinical positive cases was
proven to be enhanced with the normalization of the SARS-CoV-2 RNA viral signal measurements with
pepper mild mottle virus (PMMoV) as a human-associated indicator that represents the fecal content of
wastewater samples (D’Aoust et al., 2021b; Graham et al., 2021; Kitamura et al., 2021; Wolfe et al., 2021;
Wu et al., 2021). Similar to SARS-CoV-2 RNA, PMMoV viral RNA is also consistently detected at
signicantly higher concentrations in the solids fraction of wastewaters (D’Aoust et al., 2021b; Jafferali et
al., 2021; Kitajima et al., 2018; Rosario et al., 2009; Wu et al., 2020).
The design and operation of primary sludge treatment processes may impact the sensitivity of SARS-
CoV-2 and PMMoV measurements in wastewater solids. One such design and operational consideration
is the addition of chemical coagulants in enhanced primary clarication treatment. Enhanced primary
sludge treatment is the process of adding coagulants to primary clarier units (Metcalf and Eddy, 2014;
Shewa and Dagnew, 2020), to enhance the removal of suspended solids and phosphorus from
wastewater (Cornel and Schaum, 2009; Metcalf and Eddy, 2014; Shewa and Dagnew, 2020). In Canada,
the United States, and Europe, 18.1%, 24%, and 48% of wastewater treatment plants apply primary
treatment which includes chemical precipitation/occulation (ECCC, 2011; EPA, 2022; European
Environment Agency, 2022). Chemical elimination of phosphorus and suspended solids during primary
clarication is commonly achieved with trivalent metal coagulants, mainly ferric-based salts (e.g. sulfate
or chloride) or dissolved aluminum (alum i.e., aluminum sulfate) (Crittenden et al., 2012; Metcalf and
Eddy, 2014). Ferric salts in particular are extensively used for removing phosphorus during primary
clarication across North America (Crittenden et al., 2012; Davis, 2010; ECCC, 2010; Mckinnon et al., 2018;
Toronto Water, 2009; U.S. EPA, 2000; Yeoman et al., 1988) and the UK (Carliell-Marquet et al., 2010).
Optimal ferric sulfate dosage (usually expressed as the concentration of Fe3+) in primary treatment range
between 5 and 250 mg/L as Fe3+ depending on inuent wastewater quality and treatment objectives
(Crittenden et al., 2012; Pal, 2017). In conventional enhanced primary clarication systems, the optimal
ferric sulfate dosage range between 5 and 60 mg/L as Fe3+ (Dong et al., 2019; Pal, 2017). Ferric and
aluminum coagulant ions may also be ultimately to added water resource recovery facilities (WRRFs)
through discharge of coagulant sludge in sewersheds from drinking water treatment plants that apply
ferric and aluminum ions during the treatment process.
Although the addition of Fe3+ coagulant is benecial for solids and phosphorous removal from
wastewaters, coagulants have been shown to effect viral particles within wastewater, which may be
problematic for the quantication of viral genomic measurements from wastewaters. In particular, earlier
wastewater-based epidemiology studies have applied an “aluminum hydroxide adsorption-precipitation”
method to concentrate for SARS-CoV-2 RNA measurements in wastewater with low solids (post-grit
wastewater) (Bar-Or et al., 2020; Barril et al., 2021; Randazzo et al., 2020b, a). Ferric-based precipitation

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has also been used in previous wastewater surveillance studies to effectively concentrates viruses from
municipal wastewaters (Farrah and Preston, 1985; John et al., 2011; Payment et al., 1984; Randazzo et
al., 2019; Sobsey et al., 1997). However, evidence that wastewater samples contaminated with ferric and
aluminum ions were found to interfere with qPCR amplication for the detection of viruses (Combs et al.,
2015; Dalecka and Mezule, 2018; Kuffel et al., 2021), and could cause false-negative results (Graham et
al., 2021; Kitajima et al., 2018; Rock et al., 2010; Schrader et al., 2012), which were not previously
considered in the earlier WWS studies. Hence, a knowledge gap regarding the effects of coagulation in
primary sludge clariers on SARS-CoV-2 and PMMoV wastewater measurements exists, and it is
necessary to further understand wastewater surveillance as a means of community prevalence of COVID-
19 or incidence in communities. An additional factor that may indirectly inuence SARS-CoV-2 and
PMMoV RNA detection sensitivity due to the addition of coagulants is the associated decrease in primary
sludge pH that occurs when a metal-based coagulant is added (Crittenden et al., 2012). Enteric viruses in
wastewater, including nonenveloped viruses, increase their propensity for binding to wastewater colloids
at lower pH due to associated changes in ionic strength and surface charges at low pH values (Walshe et
al., 2010; Ye et al., 2016). The effects of trivalent metal coagulants and associated pH changes on the
partitioning of SARS-CoV-2 and PMMoV viruses between the solids phase and the liquid phase have not
been previously explored.
The implications of coagulation in primary clariers on the measurement of SARS-CoV-2 and PMMoV
RNA in wastewaters remains unknown and needs to be understood to improve the ability of SARS-CoV-2
WWS to estimate the incidence of community COVID-19 disease. Further, by exploring the impact of ferric
sulfate (Fe3+) addition, a common primary sludge coagulant, on SARS-CoV-2 RNA and PMMoV RNA
targets in wastewaters will improve our understanding of the partitioning of these biological targets in
primary sludge wastewaters. The specic objectives of this study are to quantify the effects of Fe3+ and
the corresponding pH changes on N1 and N2 SARS-CoV-2 gene region measurements as well as PMMoV
measurements in primary sludge wastewaters and to use the results of Fe3+ addition on SARS-CoV-2 RNA
and PMMoV RNA measurements in primary sludge to advance the current understanding of the
partitioning of these targets in primary sludge wastewaters.
2 Materials and Methods
2.1 Wastewater source and collection
A total of 22.5 L of post-grit inuent wastewater was collected on Feb. 22nd, Mar. 23rd, and May 2nd,
2021, from the City of Ottawa’s (Ontario, Canada) WRRF, Robert O. Pickard Environmental Centre
(ROPEC). 24-hour composite samples were collected using an ISCO 6700 series sampler (Teledyne ISCO
Lincoln, NE, USA). The Ottawa WRRF treats wastewater collected from approximately 936,382 people and
has an average wastewater ow rate of 545million litres per day. Post-grit inuent samples were
collected in this study for various coagulant concentrations to be added to the harvested post-grit
wastewaters to produce primary sludge samples of various coagulant concentrations. Samples were

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immediately transported to the laboratory for storage following collection. During transportation, the
samples were kept cold on ice, and they were then stored at 4°C in a refrigerator for a maximum of 24
hours before processing.
The physico-chemical characteristics of the post-grit inuent samples were measured by the city of
Ottawa WRRF laboratory as per standard methods common to wastewaters (APHA American Public
Health Association, 2017). These characteristics include volatile suspended solids (VSS), total suspended
solids (TSS), carbonaceous biological oxygen demand (cBOD), chemical oxygen demand (COD), total
Kjeldahl nitrogen (TKN), and conductivity.
2.2 Jar tests
Jar testing of wastewaters is commonly performed to simulate primary clarication and coagulation
processes at a lab-scale(American Water Works Association, 2011; Xiao et al., 2008). Coagulation of post-
grit inuent was performed in a series of jar tests at ferric sulfate dosages of 0, 5, 15, 30, and 60 mg/L as
Fe3+, with each dosage replicated three times for data quality assurance. To ensure that each jar-test
replicate contained the same quantity of wastewater solids, the total solids (TS) was measured in each of
the jar test beakers. Prior to dosing the post-grit wastewater samples with ferric sulfate, a 10 mL pipettor
with a broad pipette tip was used to collect 20 mL of the homogenized post-grit wastewater sample from
each beaker into a separate 75 mL aluminum weighing dish (Fisher Scientic, PA, USA) that was massed
prior to use and labelled for each sample. The weighing dishes were then left in a furnace (VWR
International, PA, USA) at 133°C for at least 24 hrs so that only the total solids would remain in the
weighing dishes. An identical procedure was undertaken to measure the TS in the wastewater after the 30
min sedimentation period without resuspension of the settled solids. The weighting dishes were massed
once more after removing from the furnace and the TS concentration (mg/L) for each sample replicate,
before and after coagulation, was calculated by taking the difference in masses of the empty weighing
dishes and weighing dishes with TS.
2.2.1 Effect of ferric sulfate dosing on SARS-CoV-2 and
PMMoV viral measurements
Post-grit inuent wastewaters harvested from the Ottawa WRRF on Feb. 22nd, 2021, were dosed with
ferric sulfate (Fe2(SO4)3) solution and mixed within conventional jar test apparatus (Orbeco-Hellige six-
paddle stirrer, FL, USA) at distinct ve concentrations of 0, 5, 15, 30 and 60 mg/L of Fe3+ to produce
settled solids that simulate primary sludge and subsequently to be analyzed for SARS-CoV-2 and PMMoV
viral measurements. Each of these ve concentrations were prepared in triplicate, resulting in 15 samples
analyzed from the wastewater harvested on Feb. 22nd, 2021. This procedure was replicated once more
with the post-grit inuent wastewaters collected on Mar. 23rd, and May 2nd, 2021, and dosed with ferric
sulfate at 0 and 60 mg/L of Fe3+ and were run as complete test replicates to the Feb 22nd samples to
ensure that variations in wastewater samples did not alter the ndings of the study. Each jar test
consisted of a rapid mixing, slow mixing, and sedimentation step within the test apparatus to simulate
conventional primary clarication and coagulation processes (Fig.1). The post-grit samples were rst

Page 7/28
well homogenized (well-mixed samples to resuspend solids within the wastewater matrix) and then 500
mL of the samples were aliquoted into disinfected jar test B-KER2 laboratory 1000 mL beakers (Phipps &
Bird PN 7790630, VA, USA). The beakers and the paddle stirrers were disinfected with 5% bleach solution
(5 min contact time) and 70% ethanol (5 min contact) and then rinsed with tap water prior to use. Ferric
sulfate coagulant solution was prepared from acidied ferric sulfate stock coagulant (12% concentration
as Fe3+). The coagulation process of the post-grit samples was then initiated by undergoing rapid mixing
at 100 rotations per minute (RPM) for one minute immediately after the beakers with the 500 mL of
homogenized samples were dosed with ferric sulfate, followed by 15 min of slow mixing at 40 RPM.
Immediately thereafter, the mixing pedals were removed from the beakers for a 30 min sedimentation
period to allow large ocs to settle down. Finally, a 10 mL pipettor with a broad (disposable) pipette tip
was used to preferentially aspirate 40 mL of the settled solids fraction at the bottom of the beakers into a
40 mL disinfected centrifuge tube.
2.2.2 Effect of associated pH change on SARS-CoV-2 and
PMMoV viral measurements
An identical procedure to the jar test method described above (Fig.1) was also conducted in this study to
determine the indirect effects of pH changes associated with ferric sulfate coagulant dosing on SARS-
CoV-2 and PMMoV measurements in post-grit inuent wastewaters. Jar test beakers with the same
collected post-grit inuent wastewaters on Feb 22nd, 2021, were slowly dosed with 1M hydrochloric acid
(HCl) in place of ferric sulfate. These tests allowed for the effects of changes in the wastewater pH on
SARS-CoV-2 and PMMoV due to ferric sulfate dosing to be isolated from the effects of the addition of
ferric ion (Fe3+). Immediately after the rapid mixing, slow mixing, and the 30 min sedimentation of the
post-grit wastewater collected on Feb. 22nd with 0, 5, 15, 30, and 60 mg/L as Fe3+, the wastewater pH for
each sample replicate was measured using an HQ430d pH meter (Hach, CO, USA). As there was a
minimal change in pH between each ferric sulfate concentration, only the pH for wastewater without
coagulant (average pH of 7.6 ± 0.1) and wastewater with 60 mg/L as Fe3+ (average pH of 6.6 ± 0.2) were
quantied. Three beakers with 500 mL of homogenized post-grit samples collected on Feb 22nd were
dosed slowly with 1M HCl until a pH of 6.6 was reached (HQ430d pH meter, CO, USA), which was
equivalent to the average pH recorded during dosing to 60 mg/L as Fe3+, while an additional three post-
grit samples collected on Feb. 22nd remained untreated to maintain a pH of 7.6; equivalent to the 0 mg/L
as Fe3+ dosing. Following the 1 min rapid mixing at 100 rpm, 15 min slow mixing at 40 rpm, and 30 min
sedimentation period, 40 mL of the settled solids were aspirated in a 40 mL centrifuge tube and were
processed immediately for viral extraction and RT-qPCR quantication. The effect of pH change on SARS-
CoV-2 and PMMoV measurements was only conducted for the aliquoted post-grit samples from Feb.
22nd, 2021, as results show no notable effects on the PMMoV-normalized SARS-CoV-2 measurements
and were isolated from the effects of the coagulation process with ferric sulfate.
2.2.3 Effect of ferric sulfate dosing on SARS-CoV-2 and
PMMoV partitioning in wastewaters

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This study further investigates the inuence of ferric sulfate addition on the partitioning of SARS-CoV-2
and PMMoV RNA between the solids and liquid fractions of wastewaters. An identical jar-testing
procedure to the above-described experiments (Sections 2.2 and 2.2.1) was performed with post-grit
wastewater samples collected on Mar. 23rd and May 2nd, 2021 at a dosage of 0 and 60 mg/L as Fe3+
with each concentration being performed in triplicate, resulting in a total of 12 samples analysed for both
SARS-CoV-2 and PMMoV. The SARS-CoV-2 and PMMoV viral measurements in the wastewater from both
days were analyzed in both the settled solids fraction and the supernatant (liquid) fraction. After the 1
min rapid mixing, 15 min slow mixing, and the 30 min sedimentation period for all samples and prior to
aspiration of the settled solids, a 10 mL pipettor was used to collect 15 mL of the supernatant at different
depths of the beaker to homogenize the supernatant samples, but without resuspension of the settled
solids. Supernatant samples were collected before collecting the settled solids samples after the 30 min
sedimentation period to ensure no resuspension of solid wastewater particles into the supernatant
samples such that subsequent SARS-CoV-2 and PMMoV measurements are from the liquid phase of the
wastewater only. From the jar test conducted for the post-grit wastewater collected on Mar. 23rd, 2021,
supernatant samples were only collected from the beakers directly after the 30 min sedimentation period
(settled supernatant), resulting in 6 supernatant samples that were processed in parallel with the 6 settled
solids samples for viral extraction and RT-qPCR amplication, resulting in a total of 12 samples. As for
the jar test conducted for post-grit wastewater collected on May 2nd, 2021, the resulting supernatant from
the centrifugation (centrifuged supernatant) of the subsequent solids pellet was also collected in addition
to the settled supernatant to investigate whether SARS-CoV-2 and PMMoV viral particles are localized
within the supernatant post-centrifugation, resulting in 12 supernatant samples that were processed in
parallel with the 6 settled solids samples from May 2nd post-grit wastewater for a total of 18 samples
(Fig.2). The supernatant samples were processed for viral extraction and RT-qPCR quantication using
the same protocol that was applied for the solids pellet.
2.3 Enrichment, extraction and RT-qPCR quantication of
SARS-CoV-2 and PMMoV
The settled solids samples were concentrated by centrifuging the samples at 10,000 × g for 45 min at
4°C. The supernatant was decanted to isolate the settled solids fraction and the sample was centrifuged
once more at 10,000 × g for 5 min at 4°C to isolate the centrifuged solids pellet (also referred to as wet
solids). Sample pellets inside the 40 mL centrifuge were massed and the total pellet weight was recorded,
and then 0.250 ± 0.05 g of the sample pellets were immediately processed for viral extraction and RT-
qPCR quantication. RNA was extracted using a Qiagen RNeasy PowerMicrobiome extraction kit (PN
26000-50, MD, USA) on a QIAcube Connect automated extraction platform with a modied methodology
previously described using the RNeasy PowerMicrobiome Kit (Qiagen, Germantown, MD) (D’Aoust et al.,
2021b, c). RT-qPCR quantication was performed for the SARS-CoV-2 N1 and N2 gene regions, as well as
the replication-associated gene region of the pepper mild mottle virus (PMMoV), where measurements of
PMMoV involved 1/10 dilution of samples. Each PCR reaction well consisted of 1.5 µL of RNA template
and each sample was analyzed in triplicates; referred to as “biological replicates” throughout this study.
The primer and probe combinations that were used in this study are shown in Table1S (Supplementary

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Material). To check for inhibition, the samples were diluted by a factor of four and then a factor of ten
and were compared with undiluted samples for corresponding decreases in PMMoV measurements. The
assay limit of detection (ALOD, ≥ 95% detection) was determined to be approximately 2 copies/reaction
(D’Aoust et al., 2021b). To avoid contamination, RNA extraction and RT-qPCR were performed in separate
laboratories in Class 2 biosafety cabinets. The resulting SARS-CoV-2 N1 and N2 viral measurements, as
well as PMMoV viral measurements in this study, are represented as N1, N2, and PMMoV genomic copies
(or copies) per gram of extracted wastewater concentrated solids (0.250 ± 0.05 g) and N1, N2 and
PMMoV copies per sample-volume basis (500 mL). The PMMoV-normalized SARS-CoV-2 viral
measurements measured in wastewater during this study are expressed as N1 and N2 copies/copies of
PMMoV.
2.4 Statistical analysis
To test for statistically signicant changes between SARS-CoV-2 N1 and N2 measurements, as well as
PMMoV measurements of the differing ve ferric sulfate dosed concentrations in the resulting settled
solids fraction and the supernatant fractions, a one-way analysis of variance (ANOVA) was performed
with a
p
-value of 0.05 or lower indicating statistical signicance. ANOVA was also used to determine the
statistical signicance of SARS-CoV-2 and PMMoV RNA viral detection due to a change in pH.
Throughout this study, the linear association (R2) between the SARS-CoV-2 N1 and N2 and PMMoV viral
signal measurements, and the ferric sulfate dosed concentrations, were determined cumulatively with
respect to all individual resulting data.
3 Results and Discussion
3.1 Characteristics of Ottawa post-grit inuent wastewater
The physico-chemical characteristics of the post-grit inuent wastewater samples collected from the
Ottawa WRRF exhibited low variations across the three distinct sampling dates (Table1). It is noted that
wastewater parameters are measured every second day at the Ottawa WRRF, and the parameters
corresponding to the sampling date of Feb. 22nd were measured on that day, while the parameters
corresponding to the additional sampling dates of Mar. 23rd and May 2nd of this study were calculated
by averaging the wastewater measurements performed on the day prior and following those sampling
dates As such, the wastewater characteristics shown for Feb. 22nd in Table1 are a single date
measurement and do not show standard deviations, while the wastewater characteristics shown for Mar.
23rd and May 2nd are the average of two measurements and hence show standard deviations.

Page 10/28
Table 1
Physico-chemical characteristics of post-grit inuent samples collected at the Ottawa (Ontario, Canada)
WRRF on the sampling dates during this study.
Wastewater
characteristics Feb.
22nd Mar. 22nd – 24th (avg. ±
standard dev.) May 1st – 3rd (avg ±
standard dev.)
VSS (mg/L) 270 219 ± 52 353 ± 152
cBOD (mg/L) 201 164 ± 7 243 ± 79
COD (mg/L) 660 488 ± 77 693 ± 302
TSS (mg/L) 323 289 ± 72 348 ± 53
TKN (mg/L) 53.7 36.6 ± 0.9 44.3 ± 4.5
Conductivity (µS/cm) 1,234 1,606 ± 143 1,392 ± 51

The daily COVID-19 positive cases (ve-day midpoint average in brackets) reported by Ottawa Public
Health (OPH) on Feb. 22nd was 31 (46.0 ± 12.3) (Table2), and on Mar. 23rd, and May 2nd, 2021 were 95
(88.6 ± 22.8), and 118 (121.2 ± 21.8), respectively (Table2S in Supplemental Material). The daily COVID-
19 positive cases (ve-day midpoint average in brackets) between June 1st, 2020, through May 4th, 2021,
ranged from 0 to 682 (62.2 ± 82). The daily percentage test positivity (ve-day midpoint average) reported
by the Ontario Laboratories Information System (OLIS) on Feb. 22nd, Mar. 23rd, and May 2nd, 2021, were
1.4% (2.1%), 3.3% (4.0%), and 6.9% (8.2%), respectively (Table2). The daily percentage test positivity (ve-
day midpoint average in brackets) from Jun. 1st, 2020, through May 2nd, 2021, ranged from 0.0–16.8%
(2.6% ± 2.9%).

Page 11/28
Table 2
Viral signal measurements (average ± standard deviation of
biological replicates) from post-grit inuent wastewater samples
collected on Feb. 22nd, 2021, from this study at Ottawa (Ontario,
Canada) WRRF with no coagulant.
Copies/g N1 3.0 x 103 ± 8.7 x 102
N2 3.0 x 103 ± 7.2 x 102
PMMoV 1.0 x 107 ± 1.1 x 106
Copies/L N1 4.3 x 103 ± 1.3 x 103
N2 4.3 x 103 ± 1.1 x 103
PMMoV 1.5 x 107 ± 2.5 x 106
Copies/copies PMMoV N1 2.9 x 10− 4 ± 7.9 x 10− 5
N2 2.9 x 10− 4 ± 7.6 x 10− 5
Daily COVID-19 positive cases 31
Daily COVID-19 percent positivity 1.4%

3.2 Effect of ferric sulfate coagulant on SARS-CoV-2 and
PMMoV viral signal measurements
The effects ferric sulfate dosing at 0, 5, 15, 30, and 60 mg/L as Fe3+ on the detection of SARS-CoV-2 N1
and N2 and PMMoV viral measurements in settled solids were investigated, with RT-qPCR analysis of the
resulting solids pellets for each biological replicate displayed oscillations between 1460 and 6700 N1 and
N2 copies/g without a signicant change in trend across all ve Fe3+ concentrations (
p =
0.200 and
p
=
0.313) with a very weak linear relation (R2 = 0.008 and R2 = 0.031) (Fig.3A and B, respectively). As such,
ndings suggest no signicant effects of ferric sulfate coagulant dosage on N1 copies/g measurements
(Fig.3A) and in N2 copies/g measurements, except for the N2 copies/g measurements at 5 mg/L Fe3+
which is a likely outlier (Fig.3B). The N1 and N2 copies/L measurements for each biological replicate
ranged between 2.1 x 103 and 1.4 x 104 N1 and N2 copies/L and exhibited a statistically signicant
change across the ve Fe3+ (
p < 0.05
) and a very weak linear relation (R2 = 0.216 and R2 = 0.038) remains
between the increasing Fe3+ concentrations and the SARS-CoV-2 N1 and N2 copies/L (Fig.3D and E,
respectively). This weak linear relation is likely attributed to the differing pellet weights obtained
throughout all the ve Fe3+ concentrations (Table3S in Supplementary Material). An experimental
replicate with ferric sulfate dosages of 0 and 60 mg/L as Fe3+ similarly displayed no signicant change
in the N1 and N2 copies/g trend (
p
= 0.557 and
p
= 0.519) with a very weak linear relation (R2 = 0.090 and

Page 12/28
R2 = 0.033) (Fig.1S A and B in Supplementary Material). Hence, ferric sulfate dosages exhibited no
signicant effect on the SARS-CoV-2 RNA viral measurements in settled solids.
PMMoV viral measurements in settled solids from the post-grit wastewater that was collected from the
Ottawa WRRF on Feb. 22nd, 2021, were detected at all ve Fe3+ concentrations. Unlike the observations
for the N1 and N2 gene region measurements, coagulation with ferric sulfate signicantly affected the
PMMoV viral signal measurements in the settled solids (Fig.3C and F). Measurements represented in
PMMoV copies/g and PMMoV copies/L ranged from 8.8 x 106 to 4.0 x 107 and 1.2 x 107 to 8.2 x 107,
respectively, displayed a statistically signicant increase with increasing Fe3+ concentrations (
p < 0.05
)
along with a strong linear dependence (R2 = 0.843 and R2 = 0.873, respectively) (Fig.3C and F). Higher
PMMoV measurements in wastewater were previously associated with higher fractions of solids in
wastewater (Kitamura et al., 2021). However, in this study, the PMMoV copies/g and copies/L
measurements have a stronger linear dependence on Fe3+ concentrations (R2 = 0.843 and R2 = 0.873)
(Fig.3C and F, respectively)) compared to the resulting settled solids pellet at all ve Fe3+ concentrations
(R2 = 0.377 and R2 = 0.638) (Fig.2S A and B, respectively, in Supplemental Material). An additional
experimental replicate with ferric sulfate dosage of 0 and 60 mg/L as Fe3+ similarly displayed a
statistically signicant increase with increasing Fe3+ concentrations (
p < 0.05
) along with a strong linear
association (R2 = 0.940 and R2 = 0.915) (Fig.1S C and F in Supplemental Material). Hence, the signicant
elevations of PMMoV viral measurements in the settled solids are more strongly associated with the
increased coagulant concentration in the post-grit wastewater samples collected on Feb. 22nd, 2021.
Consequently, the increased Fe3+ dosages were shown to signicantly reduce the SARS-CoV-2 copies of
N1 and N2 per copies of PMMoV-normalized measurements in the settled solids samples (
p < 0.05
)
(Fig.3G and H); this signicant reduction in the PMMoV-normalized measurements (
p < 0.05
) was
similarly observed the consecutive experimental replicate (Fig.1S G and H). This suggests that
coagulation with ferric sulfate could cause a signicant under-representation of PMMoV-normalized
SARS-CoV-2 viral measurements in settled solids in WWS applications.
It has been previously identied that the virus interactions with various solid surfaces is primarily
governed by long range hydrophobic and electrostatic interactions between the viral capsid and the
surfaces. Although short ranged Vander Wall’s forces and stearic interactions affect the virus-solid
interactions, they are, however, of secondary importance (Lee et al., 2016; Xagoraraki et al., 2014; Ye et al.,
2016). Enveloped viruses, such as SARS-CoV-2 virion particles, have been shown to have a higher
propensity to adsorb to wastewater solids compared to non-enveloped viruses, such as PMMoV virion
particles, due to presence of the hydrophobic lipid bilayer membrane and S spike protein on the virus
surface (Duan et al., 2020; Kampf et al., 2020; Kumar et al., 2021; Wang et al., 2022; Ye et al., 2016). Since
PMMoV RNA was previously measured in both the wastewater solids fraction and the supernatant
fraction (Kim et al., 2021; Kitamura et al., 2021), it is hypothesized that the observed change in PMMoV
viral measurements associated with the increasing Fe3+ concentrations is likely attributed to alterations
in electrostatic interactions between PMMoV virion particles and the settled wastewater solids. Change in

Page 13/28
the virus’ surface charge was also reported to affect their propensity for binding to wastewater colloids
from the liquid phase (Walshe et al., 2010; Ye et al., 2016). Virus’ surface charges are inuenced either by:
i) change in the virion particle isoelectric point (pH at which the viral particles have zero net electrical
potential) due to pH change (Walshe et al., 2010) or ii) by the neutralization of wastewater colloids during
the coagulation process (Crittenden et al., 2012), which is hypothesized to increase electrostatic
interactions between the PMMoV virion particles in the liquid phase and wastewater colloids. In this
study, those two hypotheses are explored by i) testing the effects of the consecutive pH decrease
associated with the increased Fe3+ dosages in the post-grit samples, and ii) by measuring the SARS-CoV-
2 and PMMoV RNA in the supernatant fractions of the wastewater at increasing Fe3+ concentrations.
3.3 Effect of pH change on SARS-CoV-2 and PMMoV viral
signal measurements
This study further explored whether the pH decrease associated with the increased Fe3+ dosages affects
SARS-CoV-2 and PMMoV copies independent of direct Fe3+ effects. All ve of the post-grit wastewaters
demonstrated that pH values decreased after Fe3+ addition from 7.6 ± 0.1 (at 0 mg/L Fe3+) to 6.6 ± 0.2 (at
60 mg/L Fe3+), which lie within the optimal operating pH range of 5.0–8.5 for ferric precipitation during
enhanced primary clarication (Crittenden et al., 2012). Measurements of N1 and N2 copies/g oscillating
between 1500 and 4880 copies/g showed no statistically signicant change between the two pH
conditions (
p
= 0.173 and
p
= 0.536) (Fig.4A and B, respectively). However, measurements of PMMoV
copies/g showed a statistically signicant decrease in the samples from 9.0 x 106 ± 3.2 x 106 at pH 6.6 to
5.5 x 106 ± 1.7 x 106 at pH 7.6 (
p <
0.05) (Fig.4C). This nding runs contrary to the original hypothesis
that reducing the sample pH would result in a higher PMMoV viral signal in solids since viral particles
reportedly bind better to wastewater colloids at lower pH due to a reduction in the negative charge of the
virus (Walshe et al., 2010). PMMoV viral particles are negatively charged at an environmental pH above
3.8 (Charles P. Gerba, 1984; Kitajima et al., 2018; Michen and Graule, 2010; Shirasaki et al., 2017; Vega,
2006; Wetter et al., 1984); thus, PMMoV surface charge at the sample with pH 7.6 would likely be more
negatively charged than at sample with pH 6.6. Since wastewater solids are usually negatively charged
as well, it would be expected that PMMoV RNA in samples with pH 6.6 (less negative surface charge) to
have better binding to wastewater solids. However, it was found in previous studies that wastewater
acidication could reduce adsorption of nonenveloped viruses (similar to PMMoV) in wastewater solids
due to possible degradation or alteration in the integrity of the virus or wastewater ocs (Yang et al.,
2022). Despite these changes in the PMMoV RNA measurements, the PMMoV-normalized SARS-CoV-2
N1 and N2 gene regions associated with these measurements are shown to not be signicantly affected
by this change in the measured PMMoV in the solids (Fig.4D and E). Therefore, the pH decrease
associated with the Fe3+ addition, isolated from the effects of Fe3+ itself, shows no statistical change in
the PMMoV-normalized SARS-CoV-2 measurements in the wastewater solids.
3.4 Effect of ferric sulfate dosing on partitioning of PMMoV
measurements between wastewater solids and supernatant

Page 14/28
In post-grit wastewater inuent collected on March 23rd and May 3rd, the SARS-CoV-2 RNA was
exclusively detected in the wet solids fraction of the partitioning experiments with negligible detection of
the signal in the settled supernatant and centrifuged supernatant fractions in both the untreated and
treated samples by the coagulant (Fig.5A). PMMoV RNA was similarly found to be enriched in the wet
solids fraction of the post-grit wastewater (Fig.5B); this is consistent with the previous nding that
measured signicantly higher PMMoV RNA in wastewater solids fraction compared to the liquid fraction
(Kim et al., 2021). Solids from post-grit samples that were not treated by coagulant were shown to
contain 96.35% ± 0.67% of the total PMMoV copies (Fig.5B). Partitioning of PMMoV viral particles could
still be observed in the samples treated with 60 mg/L Fe3+ for which an additional 3.48% ± 0.48% of total
PMMoV viral copies transferred from the unsettled and settled supernatant fractions to the solids
fraction; as such, when treated with 60 mg/L as Fe3+ dosage, the solids fraction contained 99.83% ±
0.11% of the total PMMoV biomass (Fig.5B). With PMMoV being largely localized in the solids phase,
this makes it an effective normalizing biomarker for the SARS-CoV-2 N1 and N2 gene regions in WWS.
Normalization against PMMoV in WWS applications is particularly important as it better reects the
community prevalence of COVID-19 infections by accounting for variations in wastewater physico-
chemical properties, fecal mass ux, and PCR amplication (D’Aoust et al., 2021b; Graham et al., 2021;
Kitamura et al., 2021; Wolfe et al., 2021; Wu et al., 2021). Conclusion and Recommendations
Over the past 41 months since the detection of the rst COVID-19 cases in December 2019, WWS has
emerged as an effective disease surveillance tool for monitoring active COVID-19 cases (Ahmed et al.,
2020; Arora et al., 2020; Bivins et al., 2020; D’Aoust et al., 2021a; Gonzalez et al., 2020; La Rosa et al.,
2021; Mao et al., 2020; McClary-Gutierrez et al., 2021; Medema et al., 2020; Polo et al., 2020; Randazzo et
al., 2020a, 2020b; Sims and Kasprzyk-Hordern, 2020; Thompson et al., 2020; Wu et al., 2020). In this
investigation, the effect of the commonly used metal coagulant Fe3+ on SARS-CoV-2 and PMMoV viral
measurements of primary sludge wastewaters was examined for potential implications on the
effectiveness of WWS using primary sludge samples. Coagulation via the addition of Fe3+ did not
signicantly inuence the average measurements of SARS-CoV-2 N1 and N2 viral copies per gram of wet
wastewater solids or per liter of wastewater. However, the PMMoV measurement per wet wastewater
solids showed a signicantly higher measurement at elevated and with increasing concentrations of
Fe3+. Indirect pH reduction associated with adding ferric sulfate was not associated with trends observed
for PMMoV copies and had no signicant impact on PMMoV-normalized viral N1 and N2 copies. This
observation is more likely attributed to possible changes in electrostatic interactions between PMMoV
RNA particles and the settled wastewater solids associated with ferric sulfate addition. Ultimately, this
change in PMMoV copies may signicantly affect the normalization of SARS-CoV-2 viral copies in
wastewater using PMMoV at elevated concentrations of Fe3+ and hence may result in an underestimation
of the community prevalence of COVID-19 through WWS of the disease.
4 Conclusion and Recommendations

Page 15/28
Over the past 41 months since the detection of the rst COVID-19 cases in December 2019, WWS has
emerged as an effective disease surveillance tool for monitoring active COVID-19 cases (Ahmed et al.,
2020; Arora et al., 2020; Bivins et al., 2020; D’Aoust et al., 2021a; Gonzalez et al., 2020; La Rosa et al.,
2021; Mao et al., 2020; McClary-Gutierrez et al., 2021; Medema et al., 2020; Polo et al., 2020; Randazzo et
al., 2020a, 2020b; Sims and Kasprzyk-Hordern, 2020; Thompson et al., 2020; Wu et al., 2020). In this
investigation, the effect of the commonly used metal coagulant Fe3+ on SARS-CoV-2 and PMMoV viral
measurements of primary sludge wastewaters was examined for potential implications on the
effectiveness of WWS using primary sludge samples. Coagulation via the addition of Fe3+ did not
signicantly inuence the average measurements of SARS-CoV-2 N1 and N2 viral copies per gram of wet
wastewater solids or per liter of wastewater. However, the PMMoV measurement per wet wastewater
solids showed a signicantly higher measurement at elevated and with increasing concentrations of
Fe3+. Indirect pH reduction associated with adding ferric sulfate was not associated with trends observed
for PMMoV copies and had no signicant impact on PMMoV-normalized viral N1 and N2 copies. This
observation is more likely attributed to possible changes in electrostatic interactions between PMMoV
RNA particles and the settled wastewater solids associated with ferric sulfate addition. Ultimately, this
change in PMMoV copies may signicantly affect the normalization of SARS-CoV-2 viral copies in
wastewater using PMMoV at elevated concentrations of Fe3+ and hence may result in an
underestimation of the community prevalence of COVID-19 through WWS of the disease.
Declarations
Acknowledgements
The authors wish to acknowledge the help and assistance of the University of Ottawa, the Ottawa
Hospital, the Children’s Hospital of Eastern Ontario, the Children’s Hospital of Eastern Ontario’s Research
Institute, Public Health Ontario and all of their employees who were involved in this project. Their time,
facilities, resources, and feedback are greatly appreciated.
Author Contributions
All authors contributed to the study conception and design as described below. The rst draft of the
manuscript was written by Nada Hegazy and all authors commented on previous versions of the
manuscript. All authors read and approved the nal manuscript.
Nada Hegazy: experimental work, investigation, formal analysis, writing, review and editing.
Xin Tian:experimental work, review and editing
Patrick M. D’Aoust: experimental work, review and editing
Lakshmi Pisharody: investigation, review and editing

Page 16/28
Syeda Tasneem Towhid: experimental work, review and editing
Élisabeth Mercier: review and editing
Zhihao Zhang: experimental work, review and editing
Shen Wan: review and editing
Ocean Thakali: review and editing
Md Pervez Kabir: review and editing
Wanting Fang: review and editing
Tram B. Nguyen: review and editing
Nathan T. Ramsay: review and editing
Alex E. MacKenzie: methodology, validation, review and editing, funding acquisition
Tyson E. Graber: review and editing
Stéphanie Guilherme:validation, supervision, review and editing
Robert Delatolla: methodology, validation, supervision, writing – review and editing, funding acquisition
Funding
This research was supported by the Province of Ontario’s Wastewater Surveillance Initiative (WSI). It was
also supported by a CHEO (Children’s Hospital of Eastern Ontario) CHAMO (Children’s Hospital Academic
Medical Organization) grant, which was awarded to Dr. Alex E. MacKenzie.
Availability of Data and Materials
All data and materials analyzed during this study are included in this published article.
Ethical Approval
Not applicable.
Consent to Participate
Not applicable.

Page 17/28
Consent to Publish
Not applicable.
Declaration of Competing Interests
The authors declare that no competing nancial interests or personal relationships inuenced the work
reported in this manuscript.
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Figures

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Figure 1
Jar test method used in this study

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Figure 2
Wastewater sample fractions post-sedimentation and post-centrifugation analyzed in this study

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Figure 3
Effect of increasing coagulant concentrations on: (A) N1 copies/g extracted mass, (B) N2 copies/g
extracted mass, (C) PMMoV copies/g of extracted mass, (D) N1 copies/L of total sample volume, (E) N2
copies/L of total sample volume, (F) PMMoV copies/L total sample volume, (G) N1 copies/copies
PMMoV, and (H) N2 copies/copies PMMoV.

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Figure 4
Effect of pH change on (A) N1 copies/g of extracted mass, (B) N2 copies/g of extracted mass, (C)
PMMoV copies/g of extracted mass, (D) N1 copies/copies PMMoV, and (E) N2 copies/copies PMMoV.

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Figure 5
Comparison of the partitioning of (A) SARS-CoV-2 and (B) PMMoV genomic copies. The bars represent
the standard deviation (SD) of each measurement and the number on top of each bar is the mean
percentage for the measurements.
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