DWQ-2024-004890

1

Utah Lake Sediment Phosphorus Binding
Findings Report

Joshua J. LeMonte, Forrest Jarvis, Abidemi Aremu, Audrey Hughes, Kara Hunter, Kate
Hales, Mardell Overson, Stephen T. Nelson, Kevin A. Rey, Gregory T. Carling

Department of Geological Sciences, Brigham Young University

Final Report
Submitted to Utah Division of Water Quality

First Version Submitted August 2023
Final Version Submitted March 2024

2
1 Table of Contents
2 DEFINITION OF TERMS .......................................................................................................... 4
3 FINDINGS ................................................................................................................................. 5
4 CHARACTERIZE THE CHEMICAL SPECIATION OF P IN THE SEDIMENT AND WATER
COLUMN, INCLUDING FREE FORMS, SOLUBLE COMPLEXES, PRECIPITATES, AND
SORBED SPECIES UNDER A SERIES OF SPECIFIED WATER QUALITY CONDITIONS
REPRESENTING EXISTING AND POTENTIAL FUTURE CONDITIONS IN UTAH LAKE. ....... 8
4.1 SEDIMENT CHARACTERIZATION ................................................................................................ 8
4.1.1 SEDIMENT PARTICLE SIZE AND BULK DENSITY ...................................................................... 8
4.1.2 TOTAL SEDIMENT ELEMENTAL CONCENTRATIONS ............................................................... 11
4.1.3 SEDIMENT PHOSPHORUS SPECIATION DETERMINED BY SEQUENTIAL EXTRACTION ............. 13
4.1.4 IN-SITU SEDIMENT PHOSPHORUS SPECIATION VIA XANES ................................................. 13
4.1.5 SEDIMENT MINERALOGY ...................................................................................................... 16
4.1.6 SEDIMENT CARBONATE AND ORGANIC MATTER .................................................................. 17
4.1.7 SEDIMENT MICROBIOME ...................................................................................................... 18
4.2 WATER COLUMN PHOSPHORUS SPECIATION .......................................................................... 19
4.2.1 WATER COLUMN PHOSPHORUS .......................................................................................... 21
4.2.2 COLLOIDAL PHOSPHORUS IN THE WATER COLUMN ............................................................. 22
5 CREATE A REACTION NETWORK OF PROCESSES INVOLVING THE CHEMICAL
SPECIES OF P IN UTAH LAKE. ................................................................................................. 24
6 CHARACTERIZE P SCAVENGING AND RELEASE FROM THE WATER COLUMN AND
SEDIMENTS UNDER A SERIES OF SPECIFIED CONDITIONS (E.G., PH, REDOX, ETC.) TO
IDENTIFY CONTRIBUTING MECHANISMS SUCH AS PRECIPITATION AND SORPTION AND
ESTIMATE OF THE EXPECTED FRACTIONAL DISTRIBUTION OF P IN EACH FORM. ...... 25
6.1 POREWATER GEOCHEMISTRY ................................................................................................ 25
6.1.1 POREWATER REDOX POTENTIAL ......................................................................................... 25
6.1.2 IN-SITU SEDIMENT REDOX POTENTIAL ................................................................................ 27
6.1.3 POREWATER PH ................................................................................................................. 29
6.1.4 POREWATER CONDUCTIVITY ............................................................................................... 32
6.1.5 POREWATER PHOSPHORUS ................................................................................................ 32
7 EVALUATE PREDICTIVE RELATIONSHIPS TO CHARACTERIZE BINDING OF P ONTO
SORBING SURFACES IN THE WATER COLUMN AND SEDIMENTS SUCH AS USING
SORPTION ISOTHERMS AND/OR PARTITION COEFFICIENTS OVER A RANGE OF
SPECIFIED CONDITIONS (E.G., PH, REDOX, ETC.) ................................................................ 36
7.1 PARTITIONING OF PHOSPHORUS BETWEEN UTAH LAKE SEDIMENTS AND WATERS ................ 36
7.1.1 SORPTION EXPERIMENTAL AND MODELING APPROACH ....................................................... 36
7.1.2 SORPTION/DESORPTION THRESHOLDS: INTERPRETING Y- AND X-INTERCEPTS .................... 38
3
7.1.3 PARTITIONING COEFFICIENTS ............................................................................................. 41
7.1.4 SORPTION MAXIMA AND FREUNDLICH CORRECTION FACTORS ............................................ 43
7.1.5 IMPACTS OF UV-TREATMENT ON PARTITIONING .................................................................. 44
8 EVALUATE THE KINETICS OF P SORPTION AND DESORPTION OF P ONTO SORBING
SURFACES (E.G., CALCITE, FE, MN, ORGANICS) AND EVALUATE DESORPTION
HYSTERESIS (E.G., SPEED OR IRREVERSIBILITY OF DESORPTION AND UNDER WHAT
CONDITIONS) FOR A SERIES OF RELEVANT CONDITION FOR UTAH LAKE. ................... 47
8.1 KINETICS EXPERIMENTAL AND MODELING APPROACH ........................................................... 47
8.2 KINETICS OF DISSOLVED PHOSPHORUS RETENTION .............................................................. 48
9 REFERENCES ....................................................................................................................... 51
10 APPENDIX A. PHOSPHORUS REACTION NETWORK .................................................... 54
11 APPENDIX B. TABLES AND SUPPLEMENTAL DATA .................................................... 67
12 APPENDIX C. SAMPLING ANALYSIS PLAN FOR PHOSPHORUS BINDING IN UTAH
LAKE............................................................................................................................................. 72

4
2 Definition of Terms

Abbreviation Meaning
bd below detection
BI East of Bird Island
cmbs centimeters below the surface
Fe iron
GB Goshen Bay
Kd partitioning coefficient
 micro
P phosphorus
PB Provo Bay
PO43- phosphate
PP East of Pelican Point
PV West of Provo Marina
SAP sampling and analysis plan
SS Saratoga Springs
TDP total dissolved phosphorus
USEPA United States Environmental Protection Agency
VY West of Vineyard
XANES x-ray absorption near edge spectroscopy
XFM x-ray fluorescence microprobe
XRD X-ray diffraction
XRF x-ray fluorescence

5
3 FINDINGS

The research presented in this report supports the Utah Lake Science Panel: Utah Lake
Water Quality Study charge question 2: What is the current state of the lake with respect
to nutrients and ecology? More specifically, this research addresses charge question
2.3.5: What is the role of calcite “scavenging” (i.e., binding) in the phosphorus cycle? The
approach to address these questions follows what was laid out in the Sampling and
Analysis Plan. Addressing these charge questions was further broken down into five
distinct objectives, and the results within this report are divided into the following sections:

1) Characterize the chemical speciation of P in the water column and sediment,
including free forms, soluble complexes, precipitates, and sorbed species under a
series of specified water quality conditions representing existing and potential
future conditions in Utah Lake;
2) Create a reaction network of processes involving the chemical species of P in Utah
Lake;
3) Characterize P scavenging and release from the water column and sediments
under a series of specified conditions (e.g., pH, redox, etc.) in order to identify
contributing mechanisms such as precipitation and sorption and estimate of the
expected fractional distribution of P in each form;
4) Evaluate predictive relationships to characterize binding of P onto sorbing surfaces
in the water column and sediments such as using sorption isotherms and/or
partition coefficients over a range of specified conditions (e.g., pH, redox, etc.);
and
5) Evaluate the kinetics of P sorption and desorption of P onto sorbing surfaces (e.g.,
calcite, Fe, Mn, organics) and evaluate desorption hysteresis (e.g., speed or
irreversibility of desorption and under what conditions) for a series of relevant
conditions for Utah Lake.

It is of note that several of the findings presented herein also address additional charge
questions, including questions 1.2: “What were the historic phosphorus, nitrogen, and
silicon concentrations as depicted by sediment cores?”, 2.4: “How do sediments affect
nutrient cycling in Utah Lake?”, and 2.4.1: “What are current sediment equilibrium P
concentrations (EPC) throughout the lake? What effect will reducing inputs have on water
column concentrations? If so, what is the expected lag time for lake recovery after nutrient
inputs have been reduced?” The data presented in this report also provides insights on
the geochemical context for other charge questions.

This investigation followed a systematic design that includes field observations and
sample collection; physical, geochemical, and mineralogical analyses; field-informed
laboratory experiments; modeling for parameter determination; and data sharing (Fig. 1).
Water column, porewater, and sediment samples were collected from seven locations
Utah Lake in summer of 2021 for analysis and experimentation. In an effort to capture the
geochemical heterogeneity that exists within the sediments of Utah Lake, the seven
selected sites were: Saratoga Springs (SS), West of Vineyard (VY), West of Provo Marina
(Provo or PV), Provo Bay (PB), East of Pelican Point (PP), East of Bird Island (BI), and
6
Goshen Bay (GB, Fig. 2, Table 1). Multi-level sediment redox sensors and porewater
samplers were installed at 5 of these locales for continued monitoring for the duration of
the study. Secondary sites, proposed in the Sampling and analysis plan (SAP, Appendix
C), were not sampled due to time constraints. These field observations and existing
datasets were used to inform laboratory experiments as to the environmental conditions
of the lake. Laboratory sorption isotherm and kinetics experiments replicated these
environmental conditions and controlled for factors that may influence P sorption and
desorption within Utah Lake, particularly pH. Redox experiments detailed in the SAP were
not conducted due to limited instrumentation availability. Experimentally derived data was
modeled to parameterize P sorption behavior to inform Utah Lake water quality model
development. Statistical comparisons made throughout the document were done using a
t-test with a p = 0.05 and degrees of freedom equal to n-1, unless otherwise noted. More
detailed information regarding the methods of analysis used to obtain the data presented
herein can be found in Appendix B: Scope of Work.

Within this report many results are presented. To aid the reader, a succinct selection of
key findings includes:
• Redox potential of sediment and porewater become reducing within top 8 cm of
lakebed,
• Reduced oxidation states of iron (Fe2+) are present in lakebed sediments,
Figure 1. Project flow diagram including field sampling, analyses, laboratory
experiments, and data sharing.
7
• Most phosphorus (63%) in Utah Lake sediments is relatively stable due to its
association with carbonate minerals (e.g. calcite),
• Colloidal P (< 0.45 µm in size) in the water column was quantified for the first time,
which has implications on P bioavailability in Utah Lake,
• For most sites in the lake, P partitioning coefficients (Kd) increase with increasing
pH, suggesting that P partitioning to the sediment is more pronounced at pH > 8.0,
• Lakebed sediment is usually a P sink, as indicated by equilibrium phosphorus
concentrations (0.3 – 1.07 mg-P L-1) above the average P loading in the water
column but near porewater P concentrations, and sorption capacities (Smax)
greater than current sediment P concentrations, and
• Phosphorus reacts rapidly with Utah Lake sediments (max sorption by 100 min).

Figure 2. A map of Utah Lake showing the location of seven
sampling sites: PB (Provo Bay), PV (Provo), VY (Vineyard), BI
(Bird Island), GB (Goshen Bay), SS (Saratoga Springs), and PP
(Pelican Point). Blue lines represent half-meter incremented
bathymetric contour lines (in meters above sea-level).
8
4 Characterize the chemical speciation of P in the sediment and water column,
including free forms, soluble complexes, precipitates, and sorbed species
under a series of specified water quality conditions representing existing and
potential future conditions in Utah Lake.

4.1 Sediment characterization

In order to determine the speciation, or form, of P in the sediment, a series of analyses
were conducted. These included a sediment digestion to determine the total P in the
sediment. Once the total P concentration was determined, the sediment P speciation was
determined via sequential extraction. In addition to this chemical extraction method of
speciating P, in-situ X-Ray Absorption Near Edge Spectroscopic (XANES) data was
collected. Sediment mineralogy was also determined via X-Ray Diffraction (XRD). A
particular focus is given to the sediment at the sediment-water interface. These interfacial
sediments were collected via Eckman dredge to a depth of 10 centimeters below the
surface (cmbs). Additionally, sediment cores were collected at each of the 7 sites to
provide additional insight into geochemical trends with increasing sediment depths.

4.1.1 Sediment Particle Size and Bulk Density

Sediment particle size and particularly clay content often affect sorption by influencing
mineral surface area and substrate availability.1 Thus, variations in particle size amongst
differing locations could explain trends in P scavenging or sorption. In the case of Utah
Lake, particle size distributions are similar across the various locations (Fig. 3). Each site
has comparable amounts of silt and clay, averaging 69.7% and 28.6% respectively.
Deviations in size fractions are only apparent in PB and PP where the sand fraction is 3.5
times greater than the rest of the lake. The average at PB and PP is 3.54%-Sand, while
the rest of the lake averages of 1.02%-Sand. The divergent sand fractions in PB are easily
explained when considering the bay’s shallow water depth and the fact that it is a major
inlet for the lake, creating ideal conditions for sand particles to settle out and be deposited
before entering the lake proper. Sand fractions in PP are explained by longshore drift,
which creates a shallow northward propagating shelf protruding into the lake and is unlike
other locations. As the fetch of Utah Lake delivers sand into the shallow point, current
velocities increase and filter clay sized particles and OM from the area.2 Ultimately, PP
receives a less mature influx of sediment compared to other main lake sites, leaving it
with the lowest clay sized fraction (25.9%) and OM content (6.59%).

9
Seven soft sediment cores were collected from the designated research sites across Utah
Lake. Collecting sediment cores using the freeze coring technique ensures a careful
recovery of soft sediments by in situ freezing, resulting in well-preserved samples without
compaction or distortion of sedimentary structures, porewater recovery, and in situ
porosity. These cores provide additional insight as to the geochemical trends in the
sediments of Utah Lake. Following collection, each freeze-core was stored in the dark at
-20C. The cores were cut into 1 cm increment sections at the same sub-zero
temperatures to limit potential geochemical changes due to freezing and thawing the
sediment. These 1 cm incremental subsamples of sediment core samples were then
analyzed. One of the analyses conducted on the freeze core samples was dry bulk density
determination to prepare for geochronology determination. However, the geochronology
was not pursued to avoid duplication of efforts with other simultaneous studies conducted
as part of the Utah Lake Water Quality Study, namely the study conducted by Brahney et
al.3 Additionally, a study by Williams et al (2023) dated Utah Lake sediment freeze cores.4
Figure 3. Particle size distribution as sand, silt, or clay fractions in top 10 cm of Utah Lake sediments.
10
Rather than redo what these teams did, we opted to refer to their studies for the age of
Utah Lake sediments, using some measures such as dry bulk density and elemental
distributions to correlate our cores with theirs. In order to do this effectively, we
determined dry bulk density by two separate methods as the two teams mentioned above
used different methods to determine bulk density, one working with frozen core
Figure 4. Sediment dry bulk densities as determined by two methods: cuboid and syringe. The
cuboid method is represented by the lighter lines on each of the subfigures.
11
subsections (“cuboid method”) and the other using graduated syringes to determine the
initial wet volume of a core subsection (“syringe method”). Both methods have been used
successfully in the past. Our objective in using both methods was to validate comparison
of data collected via either method.

Both dry bulk density methods provided similar insights into the trends of bulk density of
the sediments in Utah Lake: generally, bulk density increased with increasing depth (Fig.
4). Both methods also show site-specific deviations from the general trend: decreases in
PV sediment density at ~35 cmbs, decreases in GB sediment density at ~45 cmbs, and
decreases in PB sediment density at ~25 cmbs.

4.1.2 Total Sediment Elemental Concentrations

Total elemental concentrations in the sediment was determined on sediment samples
collected in August 2021 via Eckman dredge to a depth of 10 cmbs, then air-dried,
disaggregated, and analyzed via USEPA Method 3051a.5 To statistically differentiate
between elemental concentrations, 95% Total sediment phosphorus (TP) ranged from
599 – 791 mg kg-1 P, averaging 674 ± 44 mg kg-1 P dry mass (Fig. 6). Whereas sediment
TP concentrations were similar at most sites, PP sediment had significantly less TP (612
Figure 5. Elemental concentrations in Utah Lake sediments in to top 10 cm of the sediment with their
respective 95% confidence intervals
12
mg-P kg-1), when compared with GB, BI, and SS, which averaged 689 mg-TP kg-1. Total
P concentrations at the PB location were lower than others have reported in PB likely
because this study’s sampling location for PB was near the mouth of PB to the main body
of the lake and the inflow of the Spanish Fork River into Utah Lake. This location was
selected because the low water levels limited navigation by boat in PB when this study
was started in summer 2021. Sampling sites within PB used in other studies were further
into the bay and closer to wastewater effluent locations.6,7
Concentrations of other elements that commonly influence P cycling within Utah Lake are
included in Figure 4. Though we analyzed sediments for 30 elements via ICP-OES
following acid digestion of the sediments, we will be focusing on Ca, Fe, Al, Mn, and P for
their major roles in P-cycling within lakes.8,9 For Fe, Al, Mn, and P most sites do not
statistically differ (95% confidence interval, p < 0.05) from PV with few exceptions: 1) ,
average Fe and Mn concentrations were lower (by 20.3% and 41.6%, respectively) in PB
compared to PV; 2) total Al was higher (41.5% more) at BI compared to PV; 3) Ca content
in most sites had similar concentrations to GB, excluding PB and SS. Provo Bay was less
(by 35.5%) than GB, which had less (by 18.9%) than SS. Supplemental Data on other
elements analyzed for but not discussed here can be found in Appendix C.

Figure 6. Sequential extraction of phosphorus from Utah Lake Sediments before (A) and after (B)
sorption isotherm experiments.
13
4.1.3 Sediment Phosphorus Speciation Determined by Sequential Extraction

Sequential extraction of sediment P was performed following the protocol used by others
previously.6,9,10 For all sites, there was no significant difference in P fractionation in the
sediment as determined by sequential extraction. In accordance with previously published
research, most P is associated with carbonate minerals.7 Sediment P concentrations
found in the lake (avg. total = 677 mg-P kg-1) are divided among (in order from largest P
fraction to smallest P fraction) 1) carbonate minerals (HCl; avg. 424 mg-P kg-1 or 62.6%),
2) redox-sensitive Fe and Mn compounds (BD; avg. 94.1 mg-P kg-1 or 13.9%), 3) non-
extractable minerals and refractory OM (residual; avg. 88.0 mg-P kg-1 or 13.0%), 4) OM
and OH- exchangeable compounds (NaOH; avg. 53.5 mg-P kg-1 or 7.87%), and 5) loosely
binding compounds (NH4Cl; avg. 17.7 mg-P kg-1 or 2.61%).

Although the P fractionation remained relatively consistent across the sites measured,
there were some differences between select fractions between certain sites. Despite PB
having less elemental Fe and Mn (Fig. 6, see also Appendix B Table 1), the relative
proportion of P bound in this redox-sensitive fraction is similar to or greater than other
sites (Fig. 7). Redox-sensitive associated P is significantly higher in VY (15.4%-Total P)
and PB (16.5%-Total P) when compared to GB (12.22%-Total P) and PP (12.39%-Total
P). Organic matter and OH- exchangeable associated P is significantly higher in PB
(9.44%-Total P) when compared to VY (5.92%-Total P) and BI (6.77%-Total P). Also, OM
and OH- exchangeable associated P is significantly less in VY (5.92%-Total P) when
compared to PP (7.95%-Total P). Non-extractable minerals and refractory OM associated
P is statically lower in PB (8.75%-Total P) when compared with GB, SS, PP, and VY (avg.
13.9%-Total P). Higher percentages of P associated with OM and OH- exchangeable
compounds found in PB are attributed to higher percentages of organic matter found in
PB sediment (Fig. 7).

4.1.4 In-situ Sediment Phosphorus Speciation via XANES

In-situ Fe and P speciation determinations in select Utah Lake sediments were conducted
at the National Synchrotron Light Source II at Brookhaven National Laboratory, Upton,
NY. The Fe speciation was performed on beamline 4-BM, X-ray Fluorescence Microprobe
(XFM). The P speciation was performed on beamline 8-BM, TES (Tender Energy X-ray
Absorption Spectroscopy). Due to limited beam time, only sediments from Provo Bay and
west of Provo Marina were able to be analyzed.

Micro X-ray fluorescence (-XRF) maps show heterogeneous distribution of Fe, Ca, and
other elements in Provo Marina and Provo Bay sediments (Fig. 9A, 9B, 9D, and 9E).
These results are consistent with the bulk elemental data. Micro-X-ray absorption near-
edge spectroscopy (-XANES) show reduced and oxidized Fe phases present in Provo
and Provo Bay sediments (Figs. 9C and 9F, respectively). This is determined by a shift in
the “white line” (peak) energy of the spectra. In the case of Fe, the white line shift to a
lower energy indicates that the Fe forms in the sediment are heterogeneous and suggests
potential differences in oxidation state stability of those Fe phases (Figs. 9C and 9F).
Additionally, this whiteline shift shows that the existence of reduced Fe forms in the
14
sediment due to the whiteline and spectral shoulder at 7123 eV for PB and PV,
respectively. Reduced Fe (Fe2+) is less able than its oxidized counterpart, Fe3+ to bind
oxyanions such as PO3-4 . However, the presence of Fe3+ shows that there are Fe mineral
phases in the sediment that could readily sorb PO3-4 . However, these samples may have
Provo Marina Provo Bay
A
B
C
D
E
F
Figure 7. Speciation of Fe in Provo Marina and Provo Bay sediments. Tricolor uXRF maps (A and D)
show distribution of Fe (red), Ca (blue), and Mn (green). Bicolor maps (B and E) show distribution of Fe
(green) and Ca (red) on the same sample. Iron speciation (oxidation state) can be determined using the
micro-X-ray absorption near edge spectroscopy data in C and F
15
undergone oxidation between the time of sampling and point of analysis. The samples
analyzed were collected as surface sediment bulk samples via Eckman dredge. Upon
collection, the saturated sediment was placed in an HDPE bucket and then left to settle.
The water was then decanted and the sediment air-dried. Once dried and powdered, a
dusting of the sediment was sealed between two layers of Kapton tape for -XANES
analysis. At any point following sampling, reduced phases (particularly Fe2+) in the sample
may have been oxidized due to exposure to the atmosphere. These samples were used
to collect “scoping data” at the beamline to strengthen future proposals for more analytical
beamtime and increase the likelihood of having beamtime allocated. Unfortunately, no
beamtime was allocated for this project during the span of this project, despite several
proposal submissions by the research team. Future molecular-level analyses such as
these are needed to definitively identify speciation and bonding environments of the Fe
in Utah Lake sediments.

Phosphorus -XANES data were also collected as speciation “scoping data” (Fig 10).
Phosphorus speciation using -XANES is more difficult to interpret than Fe without data
of appropriate known standards collected at the same time as the unknown environmental
samples. There are, however, some diagnostic spectral features in P -XANES spectra,
including post-edge features, or resonances, for Ca-P phases that occur between 2161
and 2182 eV. These spectral features are present in the PB and PV samples, indicating
that the P measured at these spots in the sediment is predominantly associated with Ca
(Fig. 10).

Figure 8. Speciation of sediment P via synchrotron based micro-XANES (right) in Provo (depicted as
Marina, but samples were collected 1 mi W of Marina in main body of Utah Lake) and Provo Bay (depicted
as Bay).
16

4.1.5 Sediment mineralogy

Sediment mineral fractions to a depth of 10 cmbs across Utah Lake proper appear to be
spatially consistent (Figure 9), excluding a significant enrichment of quartz found in PP.
Provo Bay also significantly diverges from Utah Lake proper in terms of quartz and calcite
content, being enriched with quartz but depleted of calcite. Quartz percentages in PB
average 53.0%-Mineral Mass (MM), while Utah Lake proper averages 12.1%-MM,
excluding PP where the average is 19.7%-MM. Quartz enters the lake via stream flow
carrying eroded sands from the surrounding mountains. Calcite percentages in PB
average 25.6%-MM, however percentages in the main body of the lake average 58.7%-
MM. Though calcite percentages show in little statistical variation from site-to-site inside
Utah Lake proper, PP does have the lowest average at 49.7%-MM. Given the lake’s high
alkalinity, most calcite found in the lakebed should originate from authigenic precipitation
(Randall et al. 2019). However, without C and O isotope measurements from the
sediment a specific amount of authigenic vs. allogenic calcite cannot be estimated.
Other detectable minerals, including dolomite, oligoclase, and clay, do not statistically
vary from site-to-site for the entirety of the lake and are detrital in origin. Dolomite
averages around 3.62%-MM and is eroded into the lake from the surrounding mountains,
which are rich in carbonate strata like the Oquirrh Group (Konopka & Dott 1982). Feldspar
Figure 9. Mineralogy of sediments across Utah Lake identified via XRD
17
percentages, identified as oligoclase, are highly variable but do not significantly differ
across sites, averaging 7.23%-MM for the whole of the lake. Feldspar, or oligoclase, is
delivered into Utah Lake through intermittent stream flow and the American Fork River.
The oligoclase found in these flows is sourced from silicic and plutonic igneous rocks
found in the Tintic, Oquirrh, and Traverse Mountains, as well as the Little Cottonwood
Stock (Moore 1973, Harbor et al. 2009, and Jensen et al. 2022). Total clay content (avg.
16.2%-MM) is also highly variable but does not statistically vary across the lake, including
at PB. Like quartz, clays are delivered into the lake via stream flow containing weathered
sediments from the surrounding mountain ranges. Additionally, Utah Lake sediment might
contain authigenic metal hydroxides, however low concentrations yield the secondary
minerals imperceptible using XRD.

Trends found in mineral fractions identified by XRD follow the trends identified by particle
size distributions and carbonate/OM digestions. In fact, carbonate percentages
determined by HCl digestion and calcite percentages determined by XRD were within
3.8% of each other when averaging across all locations. The uncertainty of oligoclase
and clay percentages is likely due to variable grain size and orientation associated with
sample prep. Furthermore, specific species of clays are difficult to distinguish without
glycolating samples just prior to XRD analysis (Schultz 1964). Thus, clays here are
identified into two broad categories: 2:1 clays that have relatively more sorption sites, and
1:1 clays with relatively fewer sorption sites. Again, PB is a shallow inlet for Utah Lake,
creating an ideal location for allochthonous sediment (quartz) and detritus (OM)
deposition before it has a chance to enter the main lake. Longshore drift forms PP, leading
to deposition of less mature sediment enriched with quartz but slightly depleted of finer
particulates (calcite, clay, and OM).

4.1.6 Sediment Carbonate and Organic Matter

Sediment organic matter across most sites is low, excluding PB. Focusing on results from
the NaOCl method, we can see that 4 sites do not statistically differ from BI, which has
about 9% SOM. Provo Bay has significantly higher SOM than BI at 11% (Fig. 10).
Saratoga Springs and PP have significantly lower SOM than BI at 8% and 7%,
respectively. Note, PP does have significantly lower SOM when compared to SS,
although the values are quite similar which means that functionally this difference may be
nominal.

Carbonate abundance in the sediment is high across all sites. However, carbonate
percentages as determined by HCl digestion show PB to be significantly (p < 0.05)
carbonate-depleted when compared to all other locations (Table 1; Figure 10). Provo Bay
averages 24.9% carbonate and the rest of the lake ranges from 54.5-57.3% carbonate.
Organic matter (OM) percentages as determined by NaOCl digestion show PP to be
significantly depleted when compared to all other locations (Table 1; Figure 4). Pelican
Point averages 6.59% OM while the rest of the lake ranges from 7.67-9.63% OM,
excluding PB. Provo Bay has the highest average amount of OM at 11.4%. As supported
by Figures 5 and 6, the low percentage of carbonate and relatively high percentage of
OM in PB are likely products of to the bay’s shallow nature as a major inlet into the lake,
18
making it an ideal location for early deposition of allochthonous detritus and quartz grains.
Low organic matter percentages in PP are likely due to the absence of an inlet or outlet
in the area and longshore drift, reducing the amount of allochthonous OM received into
the area. Despite the role of allochthonous OM in P-sorption, the majority of OM found in
Utah Lake is authigenic and produced from algae.4
Figure 10. Carbonate and organic matter abundance in sediments of Utah Lake with their respective 95%
confidence intervals.

4.1.7 Sediment microbiome

Sequences obtained from DNA extractions from lakebed sediments collected near 4 of
the 7 sites (VY, PB, BI, and PP) reveal the microbiome of Utah Lake sediment to be
taxonomically diverse as determined by a principal component analysis (Fig. 11). The
microbiome of Utah Lake sediment is dominated by bacterial species in the
proteobacteria, actinobacteria, chloroflexi, and firmicutes kingdoms. Despite the diversity
of species housed within Utah Lake sediment, community analysis using EMPeror
suggests statistical microbiome uniformity across the lake as indicated by the lack of
clustering in the principal component analysis (Fig. 11).11 This microbial community
similarity across Utah Lake suggests that differences in microbially mediated sediment
biogeochemical processes are likely not predominantly controlled by the presence or
19
absence of specific taxonomies, but are more likely controlled by other environmental
parameters (e.g. nutrient availability, temperature, pH, redox, etc.).

4.2 Water column phosphorus speciation

To determine the speciation of P in the water column, a series of analyses were
conducted, including determining total P and PO3-
4 concentrations in water column
samples. These concentrations have been reported several times previously and are
regularly monitored by the state of Utah’s Division of Water Quality. In addition to these
observations, select samples were analyzed to determine the concentration of P in the
colloidal fraction found in the water column of Utah Lake. These measured lake water
samples were collected across all seven sites at the water surface (0-5 cm), middle (50%
of the depth), and bottom (5-10 cm above the sediment) on a single day when the water
was placid. Phosphorus in the water column was highest in Provo Bay and Provo Marina
samples at all depths and in the bottom samples of Goshen Bay. The total water column
concentrations of P at Bird Island, Pelican Point, Saratoga Springs, and Vineyard were
Figure 11. Principal component analysis of sediment microbial community DNA extracted from sediments
across Utah Lake (left). The lack of clustering by the sites indicates no spatial patterns across Utah Lake
related to microbial communities.
20
similar across the three measured depths at these sites. It is important to note that these
data only represent a snapshot of the lake water geochemistry.

Geochemical equilibria of species in natural waters and sediments are functions of the
solution composition, including the concentration of the element(s) of interest, as well as
the pH and Eh (or, redox potential, or pε). Applying the rules of thermodynamics and
geochemical stabilities, a pourbaix diagram, or Eh-pH diagram can be constructed to aid
in predicting molecular speciation in aqueous systems, such as Utah Lake (Fig. 12). Using
these thermodynamic predictions, it is expected that orthophosphate (HPO42-) is the
dominant P species under modern conditions of the Earth’s surface and therefore in Utah
Lake. Phosphorus does occur in several oxidation states: phosphides (–3), diphosphides,
elemental phosphorus (0), hypophosphite (+1), phosphite (+3), and phosphate (+5), but
phosphate is the only commonly stable form of phosphorus.12 The reduction of phosphate
(PO3-
4 ) to phosphite [HPO3]2- occurs only at very low redox potentials. In fact, no reduced
oxidation state P are stable on the surface of the Earth, though they may occur under
extreme conditions such as hydrothermal vents or volcanism, making this transition of P
irrelevant to the Utah Lake system.13 The primary equilibrium constants that control the
ionization of PO3-
4 ions are12:
Figure 12. Relative abundances of phosphorus aqueous species in environmental conditions
(above, adapted from Reddy et al. 1999) and thermodynamic Eh-pH stability diagram for
phosphorus species adapted from Pasek (2008, below).
21
4.2.1 Water Column Phosphorus

Concentrations of P and other elements found in the column water of an individual site
did not significantly differ across depth in almost all instances, suggesting Utah Lake
sediments to be well mixed vertically.14 A notable exception to this rule is PB, which has
poor vertical mixing. Furthermore, most sites share similar water-column P-
concentrations, excluding PV and PB. Water-column P-concentrations in PB and PV were
more like each other (avg. 61.9 µg-P L-1) than to other sites in the lake (avg. 18.5 µg-P L-
1, Fig. 13). Elevated P-concentrations found in the column water of PB are tied to
increased sediment P-concentrations and enhanced P-mobility in the area due to
microbial activity (Fig. 13).

Concentrations of nutrients and organic compounds found in the water column of Utah
Lake appear to be horizontally consistent across the lake from site-to-site (Fig. 14).
However, the mean concentration of total nitrogen (N), total ammonia, organic carbon
(Corg), orthophosphate (PO43-), chlorophyll-a, and pheophytin-a is clearly greatest in PB
(Table 3). Elevated mean concentrations of organics, chlorophyll-a, and pheophytin-a in
PB suggest enhanced microbial activity in the area. Increased microbial activity could
engender increased organic matter percentages in PB. Vice versa, increased organic
Figure 13. Total dissolved P across Utah Lake at 3 relative depths
22
matter percentages found in the sediment of PB could engender increased microbial
activity in the water column.

4.2.2 Colloidal Phosphorus in the Water Column

In response to inquiries regarding the P content of colloidal fraction within the water
column from members of the Utah Lake Water Quality Study Science Panel, exploratory
samples were collected from the Provo site (PV) located 1 mi west of Provo Marina, and
colloids were separated. The colloids were separated using centrifugation.15 Determining
centrifugation time and speed was done using the following equations:
Eq. 1. 𝜔=2𝜋
60 𝑘𝑘𝑘
Eq. 2. 𝑡= 18𝜂 𝑘𝑘(𝑅
𝑅)
(𝜔2𝑑2𝛥𝜋)
Where ω = angular velocity of the centrifuge (rad s-1), rpm = the rotations per minute used
during centrifugation, η = viscosity of the suspension medium (g cm.s-1) , 0.01005 poise
at 20 0°C; 0.00894 poise at 25 0°C (water), R = distance (cm) from the axis of rotation to
the level from where the supernatant is decanted from the tube, S = the distance (cm)
Figure 14. Aqeuous nutrient concentrations including total nitrogen (nitrogen)), total ammonia
(ammonia), organic carbon (Carbonorg), and orthophosphate (PO43-) in the water column at seven sites
across Utah Lake.
23
from the axis of rotation to the surface of the suspension in the tube, d = particle diameter
(cm), and Δρ = the density difference between the particles and the suspension medium
(g cm-3), particle density (assume): 2.65 g cm-3, density of water= 0.997 g cm-3. Ultra-
filtration is another potential technique that may be considered in the future for a more in-
depth investigation regarding colloidal chemistry in Utah Lake.

Four colloid size fractions were used: >1.00 μm, 0.45-1.00 μm, 0.10-0.45 μm, and 0.05-
0.10 μm. Following this particle size separation, the separated solid colloidal fractions
were washed three times with deionized water to release free and loosely-bound P
phases. Using this method, the concentrations of total P in colloidal phases ranged from
52.4 to 87.0 μg kg-1 and PO3-
4 concentrations ranged from 10.6 – 47.6 μg kg-1 based on
the dry colloidal mass. Total P The key observation in this data is that there are
comparable levels of total P and PO3-4 in the colloidal phases that are typically removed
from samples by filtration and therefore the total concentrations of these forms of P may
be underrepresented in many reports, depending on site conditions and analytical
methods. For instance, when taking water samples, it is common practice to use 0.45 μm
or 0.20 μm filtration to operationally define dissolved species. These data show that there
are colloidal (solid) phases smaller than these filtration methods, as well as colloidal
phases that are larger than these phases that have potentially bioavailable P. Future
colloidal P determination and speciation in Utah Lake should include colloidal separation
via centrifugation or ultrafiltration and in combination with digestion of the separated
colloids and/or filtered samples via EPA Method 3015.16

A typical ratio of soluble PO4-P:total P in natural waters is 1:10. This study shows that in
Utah Lake, the PO4-P:total P ratio is higher than typical natural waters (Table 1). This is
to say that relatively more P is likely to be bioavailable in Utah Lake than in other natural
waters. The fraction smaller than 0.45 um is of particular interest as this fraction is
operationally defined as “dissolved”. Within the < 0.45 um colloidal fraction, the PO4-
P:total P ratio is 1:8.2. Another way to look at this is that after filtration with a 0.45 um filter
12 % of the total P is PO4-P.

Table 1. Phosphorus concentrations from Utah Lake in various colloidal size ranges.
*Colloidal total P = 295.8 μg kg-1
*Total phosphate = 133.8 μg kg-1
*Total PO4-P = 43.6 μg kg-1
*Summative PO4-P:total P ratio = 1:6.8

Colloid Size
Range (μm) Total P*, μg kg-1 Phosphate*, μg kg-1 PO4-P*, μg kg-1 PO4-P:total P*
1.00 + 52.4 35.3 11.5 1 : 4.6
0.45 – 1.00 87.0 40.3 13.1 1 : 6.6
0.10 – 0.45 86.4 47.6 15.5 1 : 5.6
0.05 – 0.10 70.0 10.6 3.5 1 : 20.2
24

5 Create a reaction network of processes involving the chemical species of P in
Utah Lake.

To understand which geochemical reactions occur in Utah Lake and directly impact the
P speciation and bioavailability, a comprehensive list of reactions was derived from
multiple geochemical modeling software databases. These databases are called upon in
popular geochemical modeling software programs such as Geochemist’s Workbench,
Visual MINTEQ, and PHREEQC. The geochemical databases from which the
Phosphorus Reaction Network in Utah Lake was derived were the Lawrence Livermore
National Laboratory (LLNL), Visual MINTEQ (MINTEQ version 4;
https://vminteq.lwr.kth.se/), the United States Geological Survey (USGS) database for
chemical modeling of acid waters (WATEQ4F;
https://wwwbrr.cr.usgs.gov/projects/GWC_chemtherm/software.htm), and PHREEQC
and PHREEQD from the USGS (https://www.usgs.gov/software/phreeqc-version-3/).
Several of the reactions within the Utah Lake’s P reaction network were included in more
than one database. Rather than remove duplicate reactions, these were kept in the
reaction network because there may be slight differences in how the reactions are
denoted or the thermodynamic data associated with the reaction. For example, the
dissolution of the hydroxyapatite/hydroxylapatite mineral (see Reaction 1 below) is a
common reaction that was included in all of the databases, but the thermodynamic data
varies between the databases, based on where those databases acquired the
thermodynamic data. This comprehensive approach provided redundancy and minimized
the likelihood that any geochemical reactions pertinent to the Utah Lake system would be
overlooked.

Reaction 1. 𝐶𝑍5(𝑀𝐻)(𝑀𝑀4)3 +4𝐻+=𝐻2𝑀+3𝐻𝑀𝑀42−+5𝐶𝑍2+

Once all phosphorus reactions were identified across the selected geochemical
databases, a phosphorus reaction network for Utah Lake was created by selecting only
those reactions that are possible in the Utah Lake system from the comprehensive
geochemical database. For a reaction to be deemed “possible”, all elements in the
reaction must be present in Utah Lake. The reactions deemed possible include
decomposition (i.e. dissolution), synthesis (i.e. precipitation), and replacement (i.e.
sorption). It should not be assumed that all the reactions within the proposed reaction
network may be always happening across Utah Lake. It should also not be assumed that
any given reaction is occurring in isolation across Utah Lake. Rather, it is safe to assume
that several of these reactions are occurring at any given time as the lake system moves
toward equilibrium or adjusts to shifting environmental conditions. Many of the reactions
listed are pH-dependent, or otherwise controlled by environmental conditions. To provide
insight regarding the likelihood of each reaction taking place, thermodynamic data
including enthalpy (∆𝐻 in kJ mol-1) and enthalpy of formation (∆𝐻𝑓 in kJ mol-1) are included
for those reactions that included this metadata within at least one of the parent databases.
The full Phosphorus Reaction Network can be found in Appendix A.

25
6 Characterize P scavenging and release from the water column and sediments
under a series of specified conditions (e.g., pH, redox, etc.) to identify
contributing mechanisms such as precipitation and sorption and estimate of
the expected fractional distribution of P in each form.

6.1 Porewater geochemistry

In order to understand how P is distributed across the water column – sediment interface,
porewater was collected using a modified Hesslein peeper design.17 This pore water
equilibration dialysis device was selected to capture the full geochemical transition zone
from surface water to interfacial sediment pore water (within the active zone of mixing
and sedimentation) to “deep” sediment pore water (below the active mixing zone).
Additionally, this method collects a larger sample volume, which limits the amount of
sample dilution and complicated sample preservation methods. The peepers were
installed into the sediment at each of the seven sampling locations during the summer of
2022. Each peeper was given at least 3 weeks to equilibrate following installation and
before sample collection. It is of note that early sampling periods (May 2022) were shorter
(~21 days) and that this may not have been enough time for the sampling cell to reach
equilibration and therefore the later sampling periods were deployed longer (~35+ days)
to allow the cell to equilibrate. Data from both deployment periods is included in this report
and in the averaged values and figures below. This is part of the reason, in addition to
the latent lake heterogeneity, for some of the larger ranges of reported values below. In-
situ multi-level redox probes were also deployed to measure redox potential conditions
and variability across time and depth.

Due to the large number of porewater samples that were collected, it was not feasible to
perform analyses for unstable redox-sensitive aqueous compounds (e.g. Fe2+ and sulfide)
as originally outlines in the Sampling and Analysis Plan (Appendix C). These analyses
would have been too time-consuming in combination with the rest of the analyses that
were performed on the samples. However, the porewater chemistry presented here
provides direct observation of redox potential rather than inferred redox potential as is
commonly done when measuring for reduced-phase aqueous compounds.

6.1.1 Porewater Redox Potential

From the bottom of the water column to the shallow porewater, the redox potential shifts
rapidly from oxidizing to reducing. Averaged across all sites within the lake, the porewater
redox potential (Eh) decreased with increasing depth, with a clear shift at the water
column-porewater interface (Fig. 14). The redox potential values from the peeper data go
from oxidizing (~ +200 mV) in the bottom water column (4-8 cm above the sediment-water
interface) to reducing (~ -100 mV) in the porewater at shallow depths (4-8 cm below the
sediment-water interface). Prior to this work, there was no clear data that showed at what
depth the sediments of Utah Lake became reducing. These findings show that there is,
indeed, a redox potential shift and that this redox shift occurs very close to the sediment
surface. When the redox potential drops below +150 mV, reductive dissolution of iron
26
oxide minerals begins. If there are phosphorus-bearing Fe oxides, then the reductive
dissolution of those mineral oxides will result in phosphorus releasing into solution and
becoming potentially bioavailable. It has been shown previously that under reducing
conditions, P release from lake sediments is favorable.18

There are some site-specific porewater redox potential trends. For instance, the Provo
Bay porewater Eh between 8-36 cmbs remained above -100 mV, then dropped rapidly at
40 cmbs to -300 mV. Goshen Bay porewaters was also unique in that it’s redox potential
exhibited the typical decrease from the interface sediments to 8 cmbs, but then increases
to nearly +100 mV at 16 cmbs. This is likely an example of the influence of subsurface
hydrologic flow on Utah Lake sediments. The peeper installed at Bird Island was installed
deeper than anticipated due to the soft nature of the sediment, therefore no water column
samples were collected. The redox potential of the porewater at Bird Island was
measured between 0 cmbs and 60 cmbs and all Eh levels were reducing. There was,
however, a noticeable increase in Eh beginning at 44 cmbs and continuing to its terminal
depth at 60 cmbs where the Eh reached -80 mV. Similar to the shifts toward more positive
redox potential mentioned above, it is hypothesized that this data is further evidence of
subsurface hydrologic flow influencing porewater chemistry, which is a logical conclusion
for the tufa-rich Bird Island & Lincoln Point regions of the lake.19
Figure 15. Average porewater redox potential values across all sampling sites and collection periods
longer than the minimum 35-day equilibration time indicated by the solid black line. Standard deviation
for the average across all sites is indicated by the blue “cloud”. Each sampling unique site and collection
is indicated by a different color: SS7 = Saratoga Springs 7/2022; WV6, 7,9,10, 9_23, 11_23 = West of
Vineyard 6/2022, 7/2022, 9/2022, 10/2022, 9/2023, and 11/2023; BI9 = Bird Island 9/2022; GB10 =
Goshen Bay 10/2022; PP6,9,10 = Pelican Point 6/2022, 9/2022, and 10/2022.
27

6.1.2 In-situ Sediment Redox Potential

To provide additional insight regarding the redox conditions within the saturated
sediments of Utah Lake, particularly with respect to variability of redox potential across
depth and time, in-situ multi-level redox probes (hereafter redox probes) were installed at
5 of the 7 sites: BI, GB, PB, PV, and VY. These probes were custom fabricated by SWAP
Instruments (Castricum, Netherlands). At each redox probe site, the sediment-water
interface was determined by lowering a steel rod into the sediment, letting it settle, then
removing the rod and measuring the distance from the water surface to the sediment
surface, as noted by sediment stuck on the steel rod and repeating this at least 3 times.
Once the depth of the sediment-water interface was determined, the redox probes were
pushed into the soft sediment. Sensors were located every 2 cm from 2 – 16 cmbs and
every 5 cm from 20 – 50 cmbs. Once deployed, Eh data from these redox probes were
collected every 15 minutes and stored on a datalogger (Campbell Scientific, Logan UT)
supplied with solar power using a NexSens data buoy for continuous power (NexSens
Figure 16. Utah Lake sediment redox potential (mV) across time and depth at 4 sites in Utah Lake: Bird
Island (upper left), Vineyard (upper right), Provo (bottom left), and Provo Bay (bottom right). An
additional representation of Provo Bay is provided in the far bottom right to show its redox shifts.
28
Technology, Fairborn OH). The data buoy was moored to the lakebed sediment with 200
lb. concrete mooring sinkers. Redox probes were deployed at Provo Bay from July to
October and Bird Island, Vineyard, and Provo from July to November, 2022. A limitation
of this design was that the redox probes could be impacted by wind and wave action at
the water surface because their cables were connected to the data buoys. As the buoys
faced fierce winds, this likely placed enough strain on the redox probe cables that they
pulled on the probes and created preferential flowpaths for the surface water to mix with
porewater and sediment. This complication resulted in noise within the redox probe data
at those sites with considerable wind and wave action, namely BI, PV, and VY. However,
there are stretches of time in the data at each site where the redox potential at the redox
probes was not impacted by wave action and the Eh values are more consistent, providing
a detailed view into how redox potential changes in the sediments of Utah Lake.

Figure 17. Schematic of redox potential monitoring instrumentation (left) and average Utah Lake sediment
redox potential (mV) at the four sites with continuous redox potential monitoring (right).

The sites from the main body of Utah Lake had more heterogeneous sediment redox,
with Eh values shifting from reducing to oxidizing periodically (Fig. 16). This is likely due
to wave action in the water column and potential resultant movement of the sensors as
discussed above. The redox probe data shows that it is all sites are reducing much of the
time, which is agreement with the porewater Eh data. The redox potential in the sediment
of the main body of the lake averaged around 0 mV, at which point reductive dissolution
of mineral oxides (particularly FeIII reducing to FeII) can occur and minimize the ability of
mineral oxides to bind oxyanions such as PO3-
4 .20 Below -200 mV, sulfur becomes the
terminal electron acceptor and (as sulfate, SO42- with SVI) is reduced to form sulfide (S-
II).21 Consequently, these lower redox potential conditions can lead to the formation of
29
some metal sulfides and effectively stabilize metals under reducing conditions. It is
important to note that these are general thresholds, and actual speciation may deviate
depending on the amount of organic C in the system and the microbial community, as
redox reactions are often microbially mediated. Nonetheless, the influence of reducing
conditions on oxidation state and subsequent sorption potential on mineral oxides within
the sediment is an important finding related to PO3-
4 retention in the sediment of Utah
Lake. The abundance of reducing conditions in the sediment, even at shallow depths,
suggests that the redox-sensitive minerals and metals (particularly Fe) are not a stable
sink for phosphorus in the sediment.

Recently published work used redox proxies (V/Cr and Ni/Co ratios) from sediment cores
collected at Provo Bay, Goshen Bay, and west of Provo Marina in the main body of the
lake.4 The authors concluded that all sediment conditions at the time of deposition,
regardless of age, are oxic.4,22 The data of this report are in agreement – they show
oxidizing depositional conditions. The data within this report adds the important insight
that the redox conditions change to reducing within 5-10 cmbs. While the implementation
of this paleoredox method provided insight into the lake’s history regarding its well-mixed
status, one cannot accurately deduce Utah Lake’s dynamic redox conditions from this
data. Our in-situ and porewater data demonstrate that the the redox state of the sediments
is dynamic, with the redox conditions of the sediment impacted by resuspension events
and changing from oxidizing to reducing within 5-10 cmbs.

6.1.3 Porewater pH

The average porewater pH was consistent across all sampling sites and peeper
deployments (Fig. 18). The porewater pH was less (~ 6.5) than that of the lake water near
the top of the water column (~ 8.5). Some sites showed very little change in porewater
pH with depth (i.e. PV, Fig. 19). However, there is significant shifts in porewater pH with
depth at several sites, where the pH increased from the sediment water interface down
the sediment column (BI, GB, PB, SS, VY, Fig. 19). There were also variations in
porewater pH based on the time of year. Goshen Bay consistently increased in pH by 1
pH unit from the sediment water interface to 40 cmbs. The lower porewater pH values
near the sediment-water interface may be a result of organic matter decomposition. The
increase in pH as one moves down the sediment profile is likely influenced by Eh, and as
the Eh decreases, the pH increases due to the increasing abundance of hydrogen ions
under reducing conditions.

While the porewater pH at many sites was consistent between shorter and longer
equilibration times, it is possible that this low pH level may be a sampling artifact due to
the method of collection and the equilibration time of the peepers. Other studies have
shown that a longer period of equilibration for the peepers (> 32 d) may be necessary to
allow cell equilibration with sediment porewaters.17 Most of the pore water sampler
equilibration times met this 32 d minimum. For those samples that were not equilibrated
in the sediment for at least 32 d, the pH was compared to equilibration times >32 d at the
same site as an indicator as to whether the collection cells established equilibration.
30
Figure 18. Average porewater pH across all sampling sites and collection periods longer than the minimum
35-day equilibration time are indicated by the solid black line. Standard deviation for the average across all
sites is indicated by the blue “cloud”. Each sampling unique site and collection is indicated by a different
color: SS7 = Saratoga Springs 7/2022; WV6, 7,9,10, 9_23, 11_23 = West of Vineyard 6/2022, 7/2022,
9/2022, 10/2022, 9/2023, and 11/2023; BI9 = Bird Island 9/2022; GB10 = Goshen Bay 10/2022; PP6,9,10
= Pelican Point 6/2022, 9/2022, and 10/2022.

31

Figure 19. Porewater pH as a function of depth at all sites across Utah Lake. Different
line patterns show different sampling dates.
32
6.1.4 Porewater conductivity

Averaged across all sites within the lake the porewater conductivity decreased with
increasing depth, with a defined shift at the water column-sediment porewater interface
(Fig. 20). While the Provo Bay pore water samplers were not deployed for the minimum
35 days, a 28 day deployment showed Provo Bay porewater conductivity decreased
rapidly from the sediment surface to 12 cmbs. A distinct shift then occurred and Provo
Bay porewater conductivity increased with depth to its terminal depth of 40 cmbs, with the
porewater conductivity reaching values higher than that in its water column. It is
hypothesized that this is either due to the shorter deployment time or is another instance
of subsurface hydrologic flow influencing porewater chemistry.

6.1.5 Porewater Phosphorus

Phosphate concentrations in the porewater are higher than PO 3-
4 concentrations in the
water column by 10-100x (Fig. 21). Earlier studies have demonstrated the potentially
large role internal P cycling plays in Utah Lake, including determining sediment nutrient
fluxes.6,7 The current work discovered elevated PO3-
4 concentrations in the sediment
porewater compared to the water column, a likely source of PO3-
4 flux from the sediment
to the water column. Provo Bay and Goshen Bay had the highest levels of PO4-P in the
porewater, with concentrations reaching 2.4 and 1.8 mg L-1, respectively. The relative
Figure 20. Average porewater conductivity across all sampling sites and collection periods longer than
the minimum 35-day equilibration time indicated by the solid black line. Standard deviation for the
average across all sites is indicated by the blue “cloud”. Each sampling unique site and collection is
indicated by a different color: SS7 = Saratoga Springs 7/2022; WV6, 7,9,10, 9_23, 11_23 = West of
Vineyard 6/2022, 7/2022, 9/2022, 10/2022, 9/2023, and 11/2023; BI9 = Bird Island 9/2022; GB10 =
Goshen Bay 10/2022; PP6,9,10 = Pelican Point 6/2022, 9/2022, and 10/2022.
33
high primary productivity of these areas leads to more organic matter in the sediment,
which then decomposes and results in high porewater PO4 concentrations.

There is also a seasonal change in the porewaters, with PO3-4 concentrations increasing
between May, June, July, and August (Fig. 21). This increase in porewater PO3-4
correlates to the primary production and algal bloom occurrence pattern in Utah Lake –
warmer summer months result in more algal blooms and primary production.23 There also
appears to be a large spike in PO3-4 at ~50 cmbs for BI. This is likely due to
contamination of the porewater sample with the sediment on the filter at the point of
extraction from the lakebed.

Similar seasonal patterns in total dissolved P are present at BI, GB, and at certain depths
for SS and PP (Fig. 22). Several locations see slight decreases in porewater total P with
depth. Provo Bay is an exception to this trend. Total P in PB porewaters increases with
depth to 16 cmbs where it reaches 14 mg-P L-1. This is considerably more than the PO3-4
-phase in PB porewaters, suggesting other forms of P are prevalent – likely organic forms
of P due to PB’s primary productivity. Below 16 cmbs total P decreases by nearly 70%, a
shift that is similar to the change in PO3-4 concentrations.
34

Figure 21. Porewater phosphate (PO3-
4 ) concentrations across sites.
35
Figure 22. Total dissolved phosphorus in Utah Lake sediment porewater across depth and time.
36
7 Evaluate predictive relationships to characterize binding of P onto sorbing
surfaces in the water column and sediments such as using sorption isotherms
and/or partition coefficients over a range of specified conditions (e.g., pH,
redox, etc.)

7.1 Partitioning of Phosphorus between Utah Lake Sediments and Waters

7.1.1 Sorption Experimental and Modeling Approach

P-sorption is dependent upon a myriad of factors, including sediment composition, water
composition, microbiome, pH, temperature, and redox. Sorption experiments allow us to
observe the effects of a single factor affecting P-sorption in a system by keeping all other
factors constant. Batch sorption isotherm (BSI) experiments are ideal for determining
sorption in saturated sediment-water systems. For P-sorption across the sediment-water
interface of Utah Lake, we wanted to observe the effect of four individual factors: sediment
composition, pH, aqueous P-concentration, and biological activity. To achieve this goal,
we performed five major batch sorption isotherm (BSI) experiments: (1) at pH 7.5, we
reacted interface sediments collected from PB and PV with water collected from SS
spiked with various amounts of P (0, 50, 100, 250, and 500 mg-P L-1-water); (2-3) at pH
8.0 and 9.0, we reacted interface sediments collected from each site with water collected
from SS spiked with various amounts of P (0, 50, 100, 250, and 500 mg-P L-1-water); (4)
at pH 8.5, we reacted interface sediments collected from each site with water collected
from SS spiked with various amounts of P (0, 0.5, 1, 3, 10, 50, 76, 100, 152, 250, 381,
500, and 762 mg-P L-1-water); and (5) at pH 8.5, we utilized UV-treated interface
sediments collected from each site to react with UV-treated water collected from SS
spiked with various amounts of P (0, 50, 100, 250, and 500 mg-P L-1-water). This UV
treatment killed all microbial communities in the sediment and water in order to conduct
the experiment abiotically. All BSI experiments were performed for 24 hours at 25oC, the
temperature of Utah Lake water in the summer when algal blooms are most likely to occur
(Søndergaard et al. 2013).

BSI experiments are performed by mixing water and sediment until equilibrium and
measuring the change in aqueous P. For each P-spiking level, we weighed 4 g of
sediment from each site into 50 mL centrifuge tubes in triplicate. After weighing, we added
4 mL of 0.5 M HEPPS or CHES (zwitterionic buffers; buffered to the desired pH using 10
M NaOH), 0-1 mL of 20,000 ppm-P or 400 ppm-P stock (made from dissolved KH2PO4
and buffered to the desired pH using 10 M NaOH), and 35-36 mL of lake water (collected
from SS on May 6, 2022 and buffered to the desired pH using 10 M NaOH) depending on
the required volume of P-stock (Total water volume = 40 mL). After the reagents were
added, the pH, conductivity, ORP, and temperature of the sediment-water mixture inside
each tube was measured using a Mettler Toledo probe. The tubes were then placed onto
a shaker table set to 100 rpm for 24 hours. After shaking, the tubes were measured for
pH, conductivity, ORP and temperature again. After measuring, the tubes were
centrifuged at 3000 rpm for 15 minutes and the supernatant decanted into a separate
tube. The remaining sediment was immediately stored in a walk-in freezer at -25oC and
37
the supernatant was filtered through a PES 0.45-micron syringe filter. The filtered
supernatant from each tube was prepared for ICP-OES and IC analysis as previously
described. Post-reaction or post-sorption sediments from BSI experiments performed at
pH 8.5 (spike-level: 1 mg-P L-1) were sent to SIRFER for isotopes of C, N, and O. Post-
sorption sediments from BSI experiments performed at pH 8.5 (spike-level: 3 mg-P L-1)
were analyzed using sequential extractions for changes in P-fractionation.

The isotherms derived from sorption experiments were fitted for Linear, Freundlich, and
Langmuir models using MATLAB 2022b. Values of R2 for fitted models across all batch
sorption experiments performed were greater than 0.73 with the mean value being 0.98.
Five different P loading levels performed in triplicate at pH values 7.0, 8.0, and 9.0,
representing 15 data points for each pH level. Because Utah Lake’s average pH is 8.5,
more P loading levels were used (13 total) at this pH, also performed in triplicate, totaling
39 data points for this pH level. Batch sorption isotherms only apply to systems operating
under the same environmental conditions as the experiment. BSI experiments do not
account for advective flow in systems and, therefore, cannot quantify sorption rates.24
Since Utah Lake sediment has clearly been exposed to P-contamination before
experimentation we have decided to include a y-intercept, bd,f,l, into our sorption models.25
The amount of P-sorption/desorption occurring in each tube of the sorption experiment
was calculated using the following equation:

𝑀= 𝐶0(𝑈0)−𝐶𝑓(𝑈𝑓)
𝑀

where Q is the amount of P that sorbed to or desorbed from the sediment in mg kg-1. M
is the mass of sediment contained within the 50 mL centrifuge tube in kg (M = ~0.004 kg).
C0 is the initial concentration of aqueous P in mg L-1 (C0 = ~0.25-762 mg-P L-1). Cf is the
final concentration of aqueous P after shaking in mg L-1. V0 is the initial volume of water
contained within the tube in L (V0 = ~0.04 L). Vf is the final volume of water contained
within the tube after shaking in L (Vf = ~0.04 L).

Linear models help to quantify P-partitioning at lower, more environmentally relevant,
aqueous P-concentrations for a given system. The Linear fit employed to model P-
sorption for a given site within an experiment is as follows:

𝑀= 𝐾𝑑(𝐶𝑓)+𝑍𝑑

where Q is the amount of P that sorbed to or desorbed from the sediment in mg kg-1. Cf
is the final concentration of aqueous P after shaking in mg L-1. Kd is the Linear P-
partitioning coefficient for the system in L kg-1. bd is the y-intercept, a shifting factor for
the model used to find the true x-intercept for the system, in mg L-1, and bd,f,l is relevant
when utilizing sediments previously exposed to P. Though bd,f,l by itself is more theoretical
in nature, the x-intercept or sorption origin it provides for the system has real-world
applications, representing the predicted aqueous-P concentration at which sorption
phenomena in the system switches from sediment P-sequestration to sediment P-
release.
38

Freundlich models help to quantify P-partitioning across low and high aqueous P-
concentrations for a given system. The Freundlich fit employed to model P-sorption for a
given site within an experiment is as follows:

𝑀=(𝐾𝑓)𝐶𝑓
(1/𝑘)+𝑍𝑓

where Q is the amount of P that sorbed to or desorbed from the sediment in mg kg-1. Cf
is the final concentration of aqueous P after shaking in mg L-1. Kf is the Freundlich P-
partitioning coefficient for the system in L kg-1. n is the Freundlich correction factor and is
unitless, and bf is the y-intercept, a shifting factor for the model used to find the true x-
intercept for the system, in mg L-1.

Langmuir models define the maximum amount and relative affinity of P-binding in a
system. The Langmuir fit employed to model P-sorption for a given site within an
experiment is as follows:

𝑀= 𝐾𝑘(𝐶𝑓)𝑆𝑘𝑎𝑤
1 +𝐾𝑘(𝐶𝑓)+𝑍𝑘

where Q is the amount of P that sorbed to or desorbed from the sediment in mg kg-1. Cf
is the final concentration of aqueous P after shaking in mg L-1. Kl is the Langmuir relative
binding strength for the system and is unitless. Smax is the P-sorption limit or maximum
for the sediment in the system in mg kg-1. bl is the y-intercept, a shifting factor for the
model used to find the true x-intercept for the system, in mg L-1. Others have used a
modified Langmuir approach to derive a value similar to this x-intercept which represents
dynamic equilibrium between the sediment and the water column, referred to as the
equilibrium phosphate concentration (EPC0).26

7.1.2 Sorption/Desorption Thresholds: Interpreting Y- and X-intercepts

The application of a y-intercept into Linear (bd), Freundlich (bf), and Langmuir (bl) models
(Fig. 23) only has precedence if the soil or sediment considered has been previously
exposed to the contaminant of study.25 For Utah Lake, we know without question that the
sediment of the lake has been heavily exposed to P contamination prior to examination.
Most sorption reactions are biphasic, with an initial reaction eventually changing to a
different reaction mechanism. Whereas the Freundlich (bf), and Langmuir (bl) models do
an acceptable job at fitting the biphasic nature of sorption, the Linear (bd) model fails to
capture more than the initial reaction behavior. Therefore, the Linear (bd) model was only
applied to data within the linear range (Cf < 50 mg P L-1). However, a potential downside
of using bd,f,l in models comparing sorption trends from different locations is that if bd,f,l
greatly differs from location-to-location one cannot make meaningful comparisons of
contaminant partition coefficients (Kd,f,l). Luckily, bd,f,l values for Utah Lake sorption
models do not significantly vary across sites for a given pH (Figure 19). There is only one
exception, which exists for bd at pH 8.5 between PB with VY and GB, however at 97.2%
confidence the intervals of these locations do overlap. Additionally, bd values do
39
significantly vary across pH for a given location and exceptions to this are negligible
(Figure 20). Values of bl do not significantly vary across pH for a given site. Values of bf
across pH do not significantly vary from bf values observed at pH 8.5 for a given site,
excluding for PB at pH 7.5 and for VY at pH 8.

Considering all these trends exhibited by bd,f,l, it is interesting to take an average of all
bd,f,l values: Linear (avg. bd = -24.2 mg-P kg-1), Freundlich (avg. bf = -400 mg-P kg-1), and
Langmuir (avg. bl = -7.57 mg-P kg-1). These singular values of bd,f,l could be applied to
every site in the lake for all pH scenarios. Using these constant bd,f,l values, one could
Figure 23. A representative plot of Q (P-sorption; mg-P kg-1) vs. Cf (Total Dissolved Equilibrium P;
mg-P L-1) obtained from a sorption isotherm experiment which reacted surface lakebed sediments
from the Vineyard site and surface waters.
40
recalculate Kd,f,l values for each site and pH scenario. Given the wide 95% confidence
bounds of current Kd,f,l values, most changes in calculated partitioning coefficients would
not be significant and should not severely reduce R2 fitting values. However, the
incorporation of a single constant y-intercept value for the lake would further solidify our
claims for using bd,f,l in our Linear, Freundlich, and Langmuir models and enhance our
ability to make meaningful mathematical comparisons of contaminant partitioning
coefficients across sites and pH.

Sorption origin, or X, represents the x-intercept of Linear, Freundlich, and Langmuir
models. It is the minimum concentration of TDP required in the water column above a
given lakebed sediment before P-sorption behavior can be observed (Figure 24).
Aqueous TDP-concentrations below X tend to cause desorption behavior instead of
sorption behavior for a given sediment. Sorption origin values calculated for each site
using bd,f,l are constant across pH, thus the X values in Figure 24 represent the average
X from all models for a given location. Average X values do not significantly differ from
site-to-site except between PV (0.81 mg-P L-1) and PP (0.30 mg-P L-1). Pelican Point has
the lowest average X of any site as well as the lowest average sediment P-content (612
mg-P kg-1). Lower concentrations of P found in the sediment of PP may assist P-sorption
at lower concentrations of aqueous-P by increasing the number of sites available for P-
binding (i.e., less P currently bound to sediment = more vacant P-binding sites).

Figure 24. Sorption/desorption thresholds (equilibrium phosphorus concentrations) as determined using the
x-intercept of sorption isotherm models for Utah Lake sediments.
41

7.1.3 Partitioning Coefficients

The partitioning coefficients Kd, Kf, and Kl, from Linear, Freundlich, and Langmuir models,
respectively, all significantly increase from pH 8 to 9 for all locations taken from Utah Lake
(Figure 25). Partitioning is consistent at each site, as evidenced by the tight confidence
intervals of Kd data (Figure 25). However, differences do exist between sites and at
different pH levels. Therefore, when using Kd in models, it is advisable to use site-specific
Kd values for most cases. However, groups may be formed to simplify the lake’s
geochemical behavior when the 95% confidence intervals of Kd overlap between sites
(Appendix B, Table 4). Kf values differ from Kd values in that they are statistically more
uniform across sites. When compared to Linear models, Freundlich models cover a
broader range of concentrations in a sorption system for a given pH, redox, and
temperature. Consequently, it may not be so that odd Kf appears more generalized for
sediments of similar composition like Utah Lake. However, at pH 8.5 we do observe that
Figure 25. Phosphorus partitioning coefficients for Utah Lake water and sediment as a function of
pH. Where Kd = Linear partition coefficient; Kf = Freundlich partition coefficient; Kl = Langmuir
relative binding strength.
42
VY exhibits significantly increased sorption when compared directly with GB, SS, and PP
(see Appendix B, Table 4). Looking at Tables 1 and 3, we can see that there are no
apparent differences in composition between these sites. Therefore, the deviation of
partitioning of VY to these sites at pH 8.5 may be related to optimal binding conditions for
differing redox species, including Fe (II, III) and Mn (II, III, IV).

The variability of the Langmuir relative binding strength (Kl) falls between that of the Kf
and Kd across sites. At pH 7.5, PB and PV have similar sorption trends. At pH 8.0, all
sites exhibit similar sorption partitioning to PB. At pH 8.5, all sites exhibit similar sorption
behavior to each other except for VY, which shows increased sorption to all other sites.
At pH 9.0, all sites exhibit similar sorption partitioning to PV.

Overall, it is advisable to use partition values (Kd,f,l) in accordance with the pH from which
they were obtained. However, exceptions may apply where adjacent pH values may not
show significant differences in Kd,f,l, like when transitioning from pH 8.0 to 8.5 or 8.5 to 9.
Nevertheless, it is best to exercise caution as some sites still exhibit significant variations
at those pH jumps. Therefore, when using Kd it is recommended to utilize individual values
for corresponding sites and pH. When using Kf, most sites can be treated as uniform,
Figure 26. Changes in phosphorus partitioning coefficients across pH levels
commonly found in Utah Lake. Lines indicate polynomial line of best fit to
illustrate trends in partitioning across pH.
43
except for VY at pH 8.5. As for Kl, one can either average values for most situations or
compare them to specific references, such as PB at pH 8 and PV at pH 9.

7.1.4 Sorption Maxima and Freundlich Correction Factors

Values of n calculated from Freundlich models highlight two important trends: 1) like Kf,
n values significantly increase for an individual site from pH 8 to 9 (Fig. 27) and 2) also
like Kf, n values do not statistically vary from site-to-site for a given pH, excluding VY
which has a higher n (5.92) at pH 8.5 (Table 4; Figure 27). Higher values of n for VY at
pH 8.5 can be explained by the same reason Kf values are higher for VY at pH 8.5.
The values of Smax calculated from Langmuir models also highlight two interesting trends
for Utah Lake sediment (Fig. 28). One, Smax values decrease with increasing pH for BI
and PB. Two, the minimum Smax at VY occurs at pH = 8.5, whereas this same pH level
represents the maximum Smax for SS, PP, GB, and PV. Variations in Smax across pH and
sites are difficult to explain. It could be the case that slight variations in composition
between sites might require varying conditions for maximal P-sorption. In general, lower
pH generates higher values of Smax for each location.

Figure 27. Freundlich values of n—with their respective 95% confidence
intervals and Langmuir values of Smax—with their respective 95% confidence
intervals across pH values for Utah Lake water and sediment.
44

7.1.5 Impacts of UV-treatment on Partitioning

UV-treatment of Utah Lake sediments significantly decreases Kd for every site (Figure
21). Despite this, Kf and Kl do not statistically decrease for a given location following UV-
treatment (excluding Kl for VY). For UV-treated sediments, Kd for VY averages 32.4 L kg-
1 while the rest of the lake averages 18.2 L kg-1. For UV-treated sediments, Kf does not
significantly differ across sites, including VY, creating an average of 199 L kg-1. For UV-
treated sediments, Kl for VY averages 0.016 L kg-1 while the rest of the lake averages
0.009 L kg-1. Given these trends, UV-treatment of Utah Lake sediments tends to
homogenize sediment compositions or characteristics which contribute to P-sorption
between sites. Originally performed to control microbial activity among different sites, UV-
treatment of sediments could easily degrade organic matter (Li et al. 2015).
Consequently, the removal of organic matter from Utah Lake sediments could
homogenize sorption trends from site-to-site, as seen in PB (11.4%-SOM) and PP
(6.59%-SOM) which significantly differed in Kd before treatment. Again, the elevated
values of Kd,f,l in VY sediments following UV-treatment can be attributed to something
other than organic matter. Redox-sensitive Fe and Mn compounds in VY could maintain
elevated partitioning the area, which seems probable given that VY reported the highest
Figure 28. Changes in sorption maxima across pH levels commonly found in Utah Lake. Lines
indicate polynomial line of best fit to illustrate trends in sorption maxima with respect to pH.
45
percentage of BD associated P following batch experimentation. These redox-sensitive
Fe and Mn compounds could have been deposited during the time of Geneva Steel, a
company which heavily contaminated the area with iron production by-products and was
immediately east of the VY site (Hogsett et al. 2019).

UV-treatment of Utah Lake sediments does not appear to significantly change values of
n or Smax for most locations (Figure 22). For VY, UV-treated sediments yielded a
significant decrease in n (2.90UV vs. 5.92pH8.5) and a significant increase in Smax (2628UV
vs. 1976 mg-P kg-1 pH8.5) compared to…. For PP, UV-treated sediments yielded a
significant decrease in Smax (1921UV vs. 2586 mg-P kg-1 pH8.5) compared to…. Values of n
do not significantly differ from site-to-site following UV-treatment. Meanwhile, Smax does
not differ from site-to-site following UV-treatment, except PP (1921 mg-P kg-1) is
significantly less than PV, VY, and BI (avg. 2577 mg-P kg-1). Trends in n and Smax
following UV-treatment of Utah Lake sediments uphold previously made assertions.
Exposure to UV can degrade SOM, which can homogenize sediment compositions or
characteristics which contribute to P-sorption (Li et al. 2015). PP reports the lowest
percentage of SOM (6.59%-SOM) of any site in Utah Lake, which might mean PP suffers
greater losses of SOM during UV exposure. PP might suffer greater losses of SOM
following UV-treatment precisely because it has less, which is an issue for some
sediments where loss on ignition (LOI) is performed (Heiri et al. 2001). However, the
changes in Smax for VY following treatment may complicate this assertion. If UV exposure
degrades SOM, a major component of P-retention in sediment, why does Smax
significantly increase for VY following treatment? The answer might have to do with VY’s
suspected unique composition of redox-sensitive compounds. Perhaps, the loss of SOM
in VY decreases competition for redox-sensitive P-binding sites which are inherently more
stable than loosely binding sites associated with SOM, leading to more effective P-
sequestration.
46

Figure 29. Influence of UV treatment on sorption maxima (Smax) and Freundlich correction factors
(n) in Utah Lake sediments.
47

8 Evaluate the kinetics of P sorption and desorption of P onto sorbing surfaces
(e.g., calcite, Fe, Mn, organics) and evaluate desorption hysteresis (e.g., speed
or irreversibility of desorption and under what conditions) for a series of
relevant conditions for Utah Lake.

8.1 Kinetics Experimental and Modeling Approach

Kinetics experiments control pH, temperature, redox, flow, time, sediment composition,
and water composition to determine kinetic P-retention rates. The stirred-flow (SF)
method is particularly useful because the sorbent is exposed to a greater number of ions
than in a static batch system (Sparks 2003). Also, the flowing solution removes any
desorbed/unsorbed species, helping prevent secondary precipitation and quantify the
advective flow of P through the system. The enhanced temporal resolution associated
with SF is more representative of natural system evolution.

Kinetics experiments were performed in triplicate for each site using three SF reactors
(schematic of experimental setup in SAP). For the reaction we flowed lake water
containing 1.1 mg-P L-1, pH 8.5, into each reactor holding 0.32 g of sediment, creating a
1:50 ratio of sediment to water inside the reaction chamber.27 Water flowed through the
reactor at 1 mL min-1, entering from the side of the reactor and exiting out the top via a
0.45-micron filter. Two main kinetics experiments were conducted, one using sediment
from site PB and the other using sediment from site PV. These two experiments were
performed for 16 hours, despite it only taking 120 minutes for the systems to reach
apparent equilibrium. Effluent from the reactor was collected every 10 minutes using a
Teledyne ISCO Foxy R2 autosampler. The solution extracted from the SF reactor was
analyzed for total dissolved P using ICP-OES (stored at 4oC and analyzed within 90 days)
and IC (stored at -25oC and analyzed within 28 days).

Sorbed concentrations of TDP were calculated via mass balance from the following
equation:

𝑆𝑘= 𝑘[∑∆𝑡𝑘(𝐶0 −𝐶𝑘)𝑘𝑘=1 ]−𝑈(𝐶𝑘)
𝑀

where q is the volumetric flow rate in L min-1 (q = 1 mL min-1).28 Δtk is the time interval
between measurements k-1 and k in min (Δtk = 10 min). C0 is the input or influent
concentration in mg-P L-1 (C0 ≈ 1.1 mg-P L-1). Ck is the measured effluent concentration
at sampling interval k in mg-P L-1. Cn is the measured concentration at the present
sampling interval in mg-P L-1. V is the effective reactor volume in L (V ≈ 16 mL), and M is
the mass of soil or sediment contained within the reactor in g or kg (M ≈ 0.32 g).

Sediment P-retention kinetic rates were calculated using the following nonlinear kinetic
equation:

48
𝜔𝑆
𝜔𝑡=𝑘𝑓(𝜃
𝜌)𝐶𝑎−𝑘𝑎(𝑆)

where b is dimensionless and represents the order of the retention reaction, illustrating
the heterogeneity of sorption processes.29 𝜔𝑆
𝜔𝑠 is the change in P-sorbed over time in mg-
P kg-1 min-1. kf and kb are the forward and backward rates of reactions for the retention
mechanism, respectively, in min-1. C is the change in effluent concentration in mg-P L-1.
S is the change in P-sorbed in mg-P kg-1. θ is the volumetric water content of the soil or
sediment in L L-1, and ρ is the bulk density of the soil or sediment in kg L-1.

8.2 Kinetics of Dissolved Phosphorus Retention

Figure 30. Change in the rate of sorption as a function of effluent concentration (top), phosphorus
sorbed to the sediment as a function of time (middle), and changes in output solution relative to input
solution with respect to time (bottom), all using PV and PB sediment.
49
Changes in the rate of sorption indicate that as experimental effluent P-concentrations
trend toward influent P-concentrations the rate of P-sorption slows for PV and PB
sediments (Figure 30). This slowing indicates saturation of P-binding sites. P-sorption
increases with time for both locations, reaching peak sorption between 80-100 min.
Averages for peak sorption are 37.8 mg-P kg-1 for PV and 30.3 mg-P kg-1 for PB. After
reaching peak sorption, P seems to exchange evenly between sediment and solution
phases. Effluent P-concentrations (C) reach influent concentrations (C0) at about 80-100
min and with comparable paces between PV and PB. It is understood that P sorption onto
calcite typically reaches equilibrium within 3 hours.30,31 These results indicate that
equilibrium between dissolved P and Utah Lake sediments occurs within 2 hours under
constant mixing conditions.

Kinetics experiments highlight nonlinear retention kinetics of P-sorption for PV and PB
sediments (Figure 31). For PV (b = -4.52), b suggests more heterogeneity of sorption
processes than PB (b = -2.96). Forward (kf; PV0.78 min-1 vs. PB0.48 min-1) and backward
(kb; PV0.003 min-1 vs. PB0.003 min-1) retention rates suggest that PV experiences faster
initial P-retention than PB, however as time progresses the retention maintained at both
sites is comparable. Initially faster rates of P-retention in PV might be explained by the
differences in sediment P-concentrations found between PB and PV. With initially lower
sediment P-concentration, PV has more sites available for P-binding relative to PB.
However, these vacant sites quickly fill and ultimately PV and PB retain the same amount
of P.

50
Figure 31. Nonlinear retention behavior of SF experiments showcasing nonlinear kinetics of P-sorption for
PV and PB sediments. Raw trends in dS/dt (P-sorption over time) vs. C, S were fitted to a single-reaction
nonlinear kinetic model in MATLAB using a least squares regression.

51
9 References

(1) Schweizer, S. A.; Mueller, C. W.; Höschen, C.; Ivanov, P.; Kögel-Knabner, I. The
Role of Clay Content and Mineral Surface Area for Soil Organic Carbon Storage in
an Arable Toposequence. Biogeochemistry 2021, 156 (3), 401–420.
https://doi.org/10.1007/s10533-021-00850-3.
(2) Miller, S. A.; Crowl, T. A. Effects of Common Carp (Cyprinus Carpio) on Macrophytes
and Invertebrate Communities in a Shallow Lake. Freshw. Biol. 2006, 51 (1), 85–94.
https://doi.org/10.1111/j.1365-2427.2005.01477.x.
(3) Devey, M. Comparing Multiple Approaches to Reconstructing the Phosphorus
History of Marl Lakes: A Utah Lake Case Study. Grad. Theses Diss. 2022.
https://doi.org/10.26076/104b-7ba6.
(4) Williams, R.; Nelson, S.; Rushforth, S.; Rey, K.; Carling, G.; Bickmore, B.; Heathcote,
A.; Miller, T.; Meyers, L. Human-Driven Trophic Changes in a Large, Shallow Urban
Lake: Changes in Utah Lake, Utah from Pre-European Settlement to the Present.
Water. Air. Soil Pollut. 2023, 234 (4), 218. https://doi.org/10.1007/s11270-023-
06228-5.
(5) US Environmental Protection Agency. Method 3051A (SW-846): Microwave Assisted
Acid Digestion of Sediments, Sludges, Soils, and Oils; Washington, D.C., USA,
2007; pp 1–30.
(6) Randall, M. C.; Carling, G. T.; Dastrup, D. B.; Miller, T.; Nelson, S. T.; Rey, K. A.;
Hansen, N. C.; Bickmore, B. R.; Aanderud, Z. T. Sediment Potentially Controls In-
Lake Phosphorus Cycling and Harmful Cyanobacteria in Shallow, Eutrophic Utah
Lake. PLOS ONE 2019, 14 (2), e0212238.
https://doi.org/10.1371/journal.pone.0212238.
(7) Hogsett, M.; Li, H.; Goel, R. The Role of Internal Nutrient Cycling in a Freshwater
Shallow Alkaline Lake. Environ. Eng. Sci. 2019, 36 (5), 551–563.
https://doi.org/10.1089/ees.2018.0422.
(8) Sondergaard, M.; Jensen, P. J.; Jeppesen, E. Retention and Internal Loading of
Phosphorus in Shallow, Eutrophic Lakes. ScientificWorldJournal 2001, 1, 427–442.
https://doi.org/10.1100/tsw.2001.72.
(9) Hupfer, M.; Zak, D.; Roßberg, R.; Herzog, C.; Pöthig, R. Evaluation of a Well-
Established Sequential Phosphorus Fractionation Technique for Use in Calcite-Rich
Lake Sediments: Identification and Prevention of Artifacts Due to Apatite Formation.
Limnol. Oceanogr. Methods 2009, 7 (JUN.), 399–410.
https://doi.org/10.4319/lom.2009.7.399.
(10) Gu, C.; Dam, T.; Hart, S. C.; Turner, B. L.; Chadwick, O. A.; Berhe, A. A.; Hu, Y.;
Zhu, M. Quantifying Uncertainties in Sequential Chemical Extraction of Soil
Phosphorus Using XANES Spectroscopy. Environ. Sci. Technol. 2020, 54 (4), 2257–
2267. https://doi.org/10.1021/acs.est.9b05278.
(11) Vázquez-Baeza, Y.; Pirrung, M.; Gonzalez, A.; Knight, R. EMPeror: A Tool for
Visualizing High-Throughput Microbial Community Data. GigaScience 2013, 2, 16.
https://doi.org/10.1186/2047-217X-2-16.
(12) Reddy, R.; Delaune, R. D. Biogeochemistry of Wetlands: Science and Applications;
CRC Press: Boca Raton, FL, 2008.
52
(13) Pasek, M. A. Rethinking Early Earth Phosphorus Geochemistry. Proc. Natl. Acad.
Sci. 2008, 105 (3), 853–858. https://doi.org/10.1073/pnas.0708205105.
(14) Zanazzi, A.; Wang, W.; Peterson, H.; Emerman, S. H. Using Stable Isotopes to
Determine the Water Balance of Utah Lake (Utah, USA). Hydrology 2020, 7 (4), 88.
https://doi.org/10.3390/hydrology7040088.
(15) Gimbert, L. J.; Haygarth, P. M.; Beckett, R.; Worsfold, P. J. Comparison of
Centrifugation and Filtration Techniques for the Size Fractionation of Colloidal
Material in Soil Suspensions Using Sedimentation Field-Flow Fractionation. Environ.
Sci. Technol. 2005, 39 (6), 1731–1735. https://doi.org/10.1021/es049230u.
(16) US Environmental Protection Agency, O. EPA Method 3015A: Microwave Assisted
Acid Digestion of Aqueous Samples and Extracts. https://www.epa.gov/esam/epa-
method-3015a-microwave-assisted-acid-digestion-aqueous-samples-and-extracts
(accessed 2023-08-19).
(17) Johnston, S. G.; Burton, E. D.; Keene, A. F.; Bush, R. T.; Sullivan, L. A.; Isaacson,
L. Pore Water Sampling in Acid Sulfate Soils: A New Peeper Method. J. Environ.
Qual. 2009, 38 (6), 2474–2477. https://doi.org/10.2134/jeq2009.0135.
(18) Christophoridis, C.; Fytianos, K. Conditions Affecting the Release of Phosphorus
from Surface Lake Sediments. J. Environ. Qual. 2006, 35 (4), 1181–1192.
https://doi.org/10.2134/JEQ2005.0213.
(19) Dustin, Jacob B.; Merritt, LaVere B. Hydrogeology of Utah Lake with Emphasis on
Goshen Bay; Water Resources Bulletin 23; Utah Geological and Mineral Survey,
1980; pp 1–50.
(20) Delaune, R.; Pezeshki, S. Plant Functions in Wetland and Aquatic Systems:
Influence of Intensity and Capacity of Soil Reduction. ScientificWorldJournal 2001,
1, 636–649. https://doi.org/10.1100/tsw.2001.257.
(21) Stumm, W.; Morgan, J. J. Aquatic Chemistry: Chemical Equilibria and Rates in
Natural Waters; Wiley, 1996.
(22) Williams, R. R. R. Determining the Anthropogenic Effects on Eutrophication of Utah
Lake Since European Settlement Using Multiple Geochemical Approaches. Master
of Science, Brigham Young University, 2021. http://hdl.lib.byu.edu/1877/etd12570.
(23) King, L.; Brahney, J.; Daly, S.; Paul, M. J.; Salk, K. R.; Brothers, S. Primary
Production Modeling Identifies Restoration Targets for Shifting Shallow, Eutrophic
Lakes to Clear-Water Regimes. Freshw. Sci. 2023, 42 (1), 44–57.
https://doi.org/10.1086/723892.
(24) Sparks, D. L.; Singh, B.; Siebecker, M. G. Environmental Soil Chemistry, 3rd ed.;
Academic Press, 2023.
(25) Chappell, M. A.; Seiter, J. M.; West, H. M.; Miller, L. F.; Negrete, M. E.; LeMonte, J.
J.; Porter, B. E.; Price, C. L.; Middleton, M. A. Organic Contaminant Sorption
Parameters Should Only Be Compared across a Consistent System of Linear
Functions. Heliyon 2020, 6 (3), e03511.
https://doi.org/10.1016/j.heliyon.2020.e03511.
(26) Zhou, A.; Tang, H.; Wang, D. Phosphorus Adsorption on Natural Sediments:
Modeling and Effects of pH and Sediment Composition. Water Res. 2005, 39 (7),
1245–1254. https://doi.org/10.1016/j.watres.2005.01.026.
53
(27) Shimizu, M.; Arai, Y.; Sparks, D. L. Multiscale Assessment of Methylarsenic
Reactivity in Soil. 1. Sorption and Desorption on Soils. Environ. Sci. Technol. 2011,
45 (10), 4293–4299. https://doi.org/10.1021/es103576p.
(28) Padilla, J. T.; Selim, H. M. Modeling the Kinetics of Competitive Sorption and
Desorption of Zn(II), Ni(II), and Pb(II) in an Acidic Soil: Stirred-Flow Experiments.
Soil Sci. Soc. Am. J. 2021, 85 (3), 560–573. https://doi.org/10.1002/saj2.20220.
(29) Selim, H. M. Transport and Fate of Chemicals in Soils: Principles and Applications;
Taylor & Francis Group: Baton Rouge, UNITED STATES, 2014.
(30) Sø, H. U.; Postma, D.; Jakobsen, R.; Larsen, F. Sorption of Phosphate onto Calcite;
Results from Batch Experiments and Surface Complexation Modeling. Geochim.
Cosmochim. Acta 2011, 75 (10), 2911–2923.
https://doi.org/10.1016/j.gca.2011.02.031.
(31) Taggart, J. B. Inorganic Phosphorus Chemistry of Utah Lake’s Effluent Mixing Zones.
Master of Science, Colorado School of Mines, 2021.

54
10 Appendix A. Phosphorus Reaction Network

LeMonte et al, 2023.
Utah Lake Water Quality Study
Utah Lake Sediment Phosphorus Binding

Data presented were extracted from multiple geochemical modeling software databases. Databases are listed in the table;
LLNL = Lawrence Livermore National Laboratory, MINTEQ = Visual MINTEQ (https://vminteq.lwr.kth.se/), WATEQ4F =
United States Geological Survey (USGS) database for chemical modeling of acid waters
(https://wwwbrr.cr.usgs.gov/projects/GWC_chemtherm/software.htm), PHREEQC = USGS
(https://www.usgs.gov/software/phreeqc-version-3/), PHREEQD = USGS (https://water.usgs.gov/water-
resources/software/PHREEQC/Phreeqc_ReleaseNotes.txt), MINTEQ.v4 = database derived from MINTEQA2 version 4.

Based on data presented in this report and by others regarding chemical abundances in the sediment and waters of Utah
Lake and thermodynamic data contained in the above mentioned geochemical databases, the following reactions are
assumed to be the most likely to occur in the Utah Lake system. As a refresher on thermodynamic values, log K indicates
the equilibrium constant where more positive values indicate more product species exist at equilibrium, and if log K is
negative (particularly less than -3) then mostly reactant species exist at equilibrium.

Reaction Mineral name
(if applicable) -Gamma
Equilibrium
Constant,
log K
Enthalpy, ∆𝐻,
(kJ/mol)
Enthalpy of
Formation, ∆𝑓𝐻°,
(kJ/mol)
𝐻𝑀𝑀42−+𝐻++𝐴𝑘3+=𝐴𝑘𝐻2𝑀𝑀42+ 4.5 +3.100
𝐻𝑀𝑀42−+𝐴𝑘3+=𝐴𝑘𝐻𝑀𝑀4+ 4.0 +7.4
𝐻𝑀𝑀42−+𝐻++𝐶𝑍2+=𝐶𝑍𝐻2𝑀𝑀4+ 4.0 +1.400
𝐻𝑀𝑀42++𝐶𝑍2+=𝐶𝑍𝐻𝑀𝑀4 3.0 +2.7400
2𝐻𝑀𝑀42− +𝐶𝑍2+=𝐶𝑍𝑀2𝑀72−+𝐻2𝑀 4.0 +3.0537
𝐻𝑀𝑀42−+𝐶𝑍2+=𝐶𝑍𝑀𝑀4−+𝐻+ 4.0 -5.8618
HPO42−+𝐻++𝐹𝑑2+=𝐹𝑑𝐻2𝑀𝑀4+ 4.0 +2.7000
𝐻𝑀𝑀42−+𝐻++𝐹𝑑3+ =𝐹𝑑𝐻2𝑀𝑀42+ 4.5 +4.1700
𝐻𝑀𝑀42−+𝐹𝑑2+=𝐹𝑑𝐻𝑀𝑀4 3.0 +3.6000
𝐻𝑀𝑀42−+𝐹𝑑3+=𝐹𝑑𝐻𝑀𝑀4+ 4.0 +10.1800
55

A comprehensive list of potential P reactions in natural waters is listed below.

𝐻𝑀𝑀42−+𝐹𝑑2+=𝐹𝑑𝑀𝑀4−+𝐻+ 4.0 -4.3918
𝐶𝑍5(𝑀𝐻)(𝑀𝑀4)3 +4𝐻+
=𝐻2𝑀+3𝐻𝑀𝑀42−+5𝐶𝑍2+ Hydroxylapatite -3.0746 -191.982
𝐹𝑑𝑀𝑀4:2𝐻2𝑀+𝐻+
=+𝐹𝑑3++𝐻𝑀𝑀42−+2𝐻2𝑀

Strengite -11.3429 -37.107 -1876.23
𝐹𝑑3(𝑀𝑀4)2:8𝐻2𝑀
=3𝐹𝑑+2 +2𝑀𝑀4−3 +8𝐻2𝑀 Vivianite -36
Database Reaction Mineral name
(if applicable) -Gamma Log K
∆𝐻
(kJ/mol,
unless
otherwis
e noted)
Enthalpy
of
Formati
on
(kcal/mo
l)
Log K
Sourc
e
∆𝐻
Sourc
e
LLNL 𝐻𝑀𝑀42−+𝐻++𝐴𝑘3+=𝐴𝑘𝐻2𝑀𝑀42+ 4.5 +3.100
LLNL 𝐻𝑀𝑀42−+𝐴𝑘3+=𝐴𝑘𝐻𝑀𝑀4+ 4.0 +7.4
LLNL 𝐻𝑀𝑀42−+𝐻++𝐶𝑍2+=𝐶𝑍𝐻2𝑀𝑀4+ 4.0 +1.400
LLNL 𝐻𝑀𝑀42++𝐶𝑍2+=𝐶𝑍𝐻𝑀𝑀4 3.0 +2.7400
LLNL 2𝐻𝑀𝑀42− +𝐶𝑍2+=𝐶𝑍𝑀2𝑀72−+𝐻2𝑀 4.0 +3.0537
LLNL 𝐻𝑀𝑀42−+𝐶𝑍2+=𝐶𝑍𝑀𝑀4−+𝐻+ 4.0 -5.8618
LLNL 2𝐻𝑀𝑀42−+𝐶𝑑2+ =𝐶𝑑𝑀2𝑀72−+𝐻2𝑀 4.0 +4.8094
LLNL 𝐻𝑀𝑀42−+𝐻++𝐶𝑡2+=𝐶𝑡𝐻2𝑀𝑀4+ 4.0 +8.9654
LLNL 𝐻𝑀𝑀42−+𝐶𝑡2+=𝐶𝑡𝐻𝑀𝑀4 3.0 +4.0600
LLNL 𝐻𝑀𝑀42−+𝐶𝑡2+=𝐶𝑡𝑀𝑀4−+𝐻+ 4.0 -2.4718
LLNL HPO42−+𝐻++𝐹𝑑2+=𝐹𝑑𝐻2𝑀𝑀4+ 4.0 +2.7000
LLNL 𝐻𝑀𝑀42−+𝐻++𝐹𝑑3+ =𝐹𝑑𝐻2𝑀𝑀42+ 4.5 +4.1700
LLNL 𝐻𝑀𝑀42−+𝐹𝑑2+=𝐹𝑑𝐻𝑀𝑀4 3.0 +3.6000
LLNL 𝐻𝑀𝑀42−+𝐹𝑑3+=𝐹𝑑𝐻𝑀𝑀4+ 4.0 +10.1800
LLNL 𝐻𝑀𝑀42−+𝐹𝑑2+=𝐹𝑑𝑀𝑀4−+𝐻+ 4.0 -4.3918
56
LLNL 2𝐻𝑀𝑀42−+2𝐻+=𝐻2𝑀2𝑀7−+𝐻2𝑀 4.0 +12.0709 19.7192 -544.6
LLNL 3𝐻++𝐻𝑀𝑀42−+𝐹−=𝐻2𝑀𝑀3𝐹+𝐻2𝑀 3.0 +12.1047
LLNL 𝐻𝑀𝑀42−+𝐻+=𝐻2𝑀𝑀4− 4.0 +7.2054 -4.20492 -309.82
LLNL 3𝐻++2𝐻𝑀𝑀42−=𝐻3𝑀2𝑀7−+𝐻2𝑀 4.0 +14.4165 21.8112 -544.1
LLNL 2𝐻++𝐻𝑀𝑀42−=𝐻3𝑀𝑀4 3.0 +9.3751 3.74468 -307.92
LLNL 4𝐻++2𝐻𝑀𝑀42−=𝐻4𝑀2𝑀7 +𝐻2𝑀 3.0 +15.9263 29.7226 -2268.6
LLNL 2𝐻𝑀𝑀42−+𝐻+=𝐻𝑀2𝑀73−+𝐻2𝑀 4.0 +5.4498 23.3326 -
2274.99
LLNL 2𝐻++𝐻𝑀𝑀42−+𝐹−=𝐻𝑀𝑀3𝐹−+𝐻2𝑀 4.0 +11.2988
LLNL 𝐾++𝐻𝑀𝑀42−=𝐾𝐻𝑀𝑀4− 4.0 +0.7800
LLNL 2𝐻𝑀𝑀42−+𝐾+=𝐾𝑀2𝑀73−+𝐻2𝑀 4.0 -1.4286 34.1393 -
2516.36
LLNL 𝑀𝑑2++𝐻𝑀𝑀42−+𝐻+=𝑀𝑑𝐻2𝑀𝑀4+ 4.0 +1.6600
LLNL 𝑀𝑑2++𝐻𝑀𝑀42−=𝑀𝑑𝐻𝑀𝑀4 3.0 +2.9100
LLNL 2𝐻𝑀𝑀42−+𝑀𝑑2+=𝑀𝑑𝑀2𝑀72−+𝐻2𝑀 4.0 +3.4727 38.5451 -
2725.74
LLNL 𝑀𝑑2++𝐻𝑀𝑀42−=𝑀𝑑𝑀𝑀4−+𝐻+ 4.0 -5.7328
LLNL 𝑀𝑘2++𝐻𝑀𝑀42−+𝐻+=𝑀𝑘𝐻2𝑀𝑀4+ 4.0 +8.554
LLNL 𝑀𝑘2++𝐻𝑀𝑀42−=𝑀𝑘𝐻𝑀𝑀4 3.0 +3.5800
LLNL 𝑀𝑘2++𝐻𝑀𝑀42−=𝑀𝑘𝑀𝑀4−+𝐻+ 4.0 -5.1318
LLNL 2𝑀𝑍++2𝐻𝑀𝑀42−=𝑀𝑍2𝑀2𝑀72−+𝐻2𝑀 4.0 +0.4437
LLNL 2𝐻𝑀𝑀42−+𝑀𝑍++𝐻+
=𝑀𝑍𝐻𝑀2𝑀72−+𝐻2𝑀 4.0 +6.8498
LLNL 𝑀𝑍++𝐻𝑀𝑀42−=𝑀𝑍𝐻𝑀𝑀4− 4.0 +0.9200
LLNL 𝐻𝑀𝑀42−+𝑀𝑍+=𝑀𝑍𝑀2𝑀73−+𝐻2𝑀 4.0 -1.4563
LLNL 2𝐻𝑀𝑀42−+𝑀𝑖2++𝐻+
=𝑀𝑖𝐻𝑀𝑀2𝑀7−+𝐻2𝑀 4.0 +9.2680
LLNL 2𝐻𝑀𝑀42−=𝑀2𝑀74−+𝐻2𝑀 4.0 -3.7463 27.2256 -2271.1
LLNL 3𝐻++𝐻𝑀𝑀42−=𝑀𝐻4++2𝑀2 4.0 -212.7409
LLNL 𝐻𝑀𝑀42−=𝑀𝑀42−=𝑀𝑀43−+𝐻+ 4.0 -12.3218 14.7068 -305.3
LLNL 𝑀𝑍2++𝐻𝑀𝑀42−+𝐻+=𝑀𝑍𝐻2𝑀𝑀4+ 4.0 +1.5000
LLNL 𝑀𝑍2++𝐻𝑀𝑀42−=𝑀𝑍𝐻𝑀𝑀4 3.0 +3.1000
LLNL 2𝐻𝑀𝑀42−+𝑀𝑍2+=𝑀𝑍𝑀2𝑀72−+𝐻2𝑀 4.0 +7.4136
57
LLNL 𝑆𝑘2++𝐻𝑀𝑀42−+𝐻+=𝑆𝑘𝐻2𝑀𝑀4+ 4.0 +0.7300
LLNL 𝑆𝑘2++𝐻𝑀𝑀42−=𝑆𝑘𝐻𝑀𝑀4 3.0 +2.0600
LLNL 2𝐻𝑀𝑀42−+𝑆𝑘2+=𝑆𝑘𝑀2𝑀72−+𝐻2𝑀 4.0 +1.6537
LLNL 𝑍𝑘2+𝐻𝑀𝑀42−+𝐻+=𝑍𝑘𝐻2𝑀𝑀4+ 4.0 +0.4300
LLNL 𝑍𝑘2++𝐻𝑀𝑀42−=𝑍𝑘𝐻𝑀𝑀4 3.0 +3.2600
LLNL 𝑍𝑘2++𝐻𝑀𝑀42−=𝑍𝑘𝑀𝑀4−+𝐻+ 4.0 -4.3018
LLNL 𝐶𝑍𝐻𝑀𝑀4:2𝐻2𝑀=𝐶𝑍2++𝐻𝑀𝑀42−
+2𝐻2𝑀 Brushite 6.5500
LLNL 𝐶𝑘3(𝑀𝑀4)2 +2𝐻+=2𝐻𝑀𝑀42−+3𝐶𝑘2+ -10.0123
LLNL 𝐶𝑘𝐻𝑀𝑀4 =𝐶𝑘2++𝐻𝑀𝑀42− -6.7223
LLNL 𝑀𝑍𝐹𝑑3(𝑀𝑀4)(𝑆𝑀4)(𝑀𝐻)6 +7𝐻+
=𝐻𝑀𝑀42−+𝑀𝑍2+
+𝑆𝑀42−+3𝐹𝑑3+
+6𝐻2𝑀
Corkite -9.7951
LLNL 𝐶𝑡3(𝑀𝑀4)2 +2𝐻+=2𝐻𝑀𝑀42−+3𝐶𝑡2+ -12.2247
LLNL 𝐶𝑡3(𝑀𝑀4)2:3𝐻2𝑀+2𝐻+
=2𝐻𝑀𝑀42−+3𝐶𝑡2+
+3𝐻2𝑀
-10.4763
LLNL 𝐶𝑍5(𝑀𝑀4)3𝐹+3𝐻+
=𝐹−+3𝐻𝑀𝑀42−
+5𝐶𝑍2+
Fluorapatite -24.9940 -90.8915 -
6836.12
LLNL 𝐴𝑘3𝑀𝑀𝑍𝑆𝑀8(𝑀𝐻)6 +7𝐻+
=𝐻𝑀𝑀42−+𝑀𝑍2+
+𝑆𝑀42−+3𝐴𝑘3+
+6𝐻2𝑀
Hinsdalite 9.8218
LLNL 𝐻𝑘𝑀𝑀4:10𝐻2𝑀+𝐻+
=𝐻𝑀𝑀42−+𝐻𝑘3+
+10𝐻2𝑀
-11.8782
LLNL 𝑍𝑘3(𝑀𝑀4)2:4𝐻2𝑀+2𝐻+
=2𝐻𝑀𝑀42−+3𝑍𝑘2+
+4𝐻2𝑀
Hopeite -10.6563
58
LLNL 𝐶𝑍5(𝑀𝐻)(𝑀𝑀4)3 +4𝐻+
=𝐻2𝑀+3𝐻𝑀𝑀42−
+5𝐶𝑍2+
Hydroxylapati
te -3.0746 -191.982
LLNL 𝑀𝑘3(𝑀𝑀4)2 +2𝐻+
=2𝐻𝑀𝑀42−+3𝑀𝑘2+ 0.8167
LLNL 𝑀𝑘𝐻𝑀𝑀4 =+𝐻𝑀𝑀42−+𝑀𝑘2+ -12.9470
LLNL 𝑀𝑖2𝑀2𝑀7 +𝐻2𝑀=+2𝐻𝑀𝑀42−+2𝑀𝑖2+ -8.8991
LLNL 𝑀𝑖3(𝑀𝑀4)2 +2𝐻+
=+2𝐻𝑀𝑀42−+3𝑀𝑖2+ -6.6414
LLNL
𝑀+1.5𝐻2𝑀+1.25𝑀2
=+𝐻𝑀𝑀42−+2𝐻+

132.1032 -848.157
LLNL
𝑀𝑍𝐴𝑘3(𝑀𝑀4)2(𝑀𝐻)5:𝐻2𝑀+7𝐻+
=+𝑀𝑍2++2𝐻𝑀𝑀42−
+3𝐴𝑘3++6𝐻2𝑀
Plumbogumm
ite

-8.1463
LLNL
𝑀𝑍5(𝑀𝑀4)3𝐶𝑘+3𝐻+
=+𝐶𝑘−+3𝐻𝑀𝑀42−
+5𝑀𝑍2+
Pyromorphite
-47.8954
LLNL
𝑀𝑍5(𝑀𝐻)(𝑀𝑀4)3 +4𝐻+
=+𝐻2𝑀+3𝐻𝑀𝑀42−
+5𝑀𝑍2+
Pyromorphite
-OH

-26.2653
LLNL
𝑀𝑑(𝑈𝑀2)2(𝑀𝑀4)2 +2𝐻+
=+𝑀𝑑2++2𝐻𝑀𝑀42−
+2𝑈𝑀22+
Saleeite
-19.4575 -110.816 -
1189.61
LLNL 𝑆𝑘𝐻𝑀𝑀4 =+𝐻𝑀𝑀42−+𝑆𝑘2+
-6.2416 -19.7942
-
1823.19
kJ/mol

LLNL
𝐹𝑑𝑀𝑀4:2𝐻2𝑀+𝐻+
=+𝐹𝑑3++𝐻𝑀𝑀42−
+2𝐻2𝑀

Strengite -11.3429 -37.107
-
1876.23
kJ/mol

59
MINTEQ
𝐶𝑍5(𝑀𝑀4)3𝑀𝐻+𝐻+
=5𝐶𝑍+2 +3𝑀𝑀4−3
+𝐻2𝑀
Hydroxyapatit
e -44.199
MINTEQ
9.496Ca+2 + 0.36Na+ + 0.144Mg+2
+ 4.8PO4−3 + 1.2CO3−2 + 2.48F−
=Ca9.316Na0.36Mg0.144(𝑀𝑀4)4.8 (CO3)1.2F2.48
FCO3Apatite -114.4 +39.39
kcal
MINTEQ 𝐹𝑑𝑀𝑀4:2𝐻2𝑀=𝐹𝑑+3 +𝑀𝑀4−3 +2𝐻2𝑀 Strengite -26.4 -2.03
kcal
MINTEQ
𝐹𝑑3(𝑀𝑀4)2:8𝐻2𝑀
=3𝐹𝑑+2 +2𝑀𝑀4−3
+8𝐻2𝑀
Vivianite -36 0 kcal
MINTEQ 𝑀𝑘3(𝑀𝑀4)2 =3𝑀𝑘+2 +2𝑀𝑀4−3 -23.827 2.12 kcal
MINTEQ 𝐶𝑡3(𝑀𝑀4)2 =3𝐶𝑡+2 +2𝑀𝑀4−3 -36.85 0 kcal
MINTEQ
𝐶𝑡3(𝑀𝑀4)2:3𝐻2𝑀
=3𝐶𝑡+2 +2𝑀𝑀4−3
+3𝐻2𝑀
-35.12 0 kcal
MINTEQ
𝑍𝑘3(𝑀𝑀4)2:4𝐻2𝑀
=3𝑍𝑘+2 +2𝑀𝑀4−3
+4𝐻2𝑀
-32.04 0 kcal
MINTEQ 𝐶𝑑3(𝑀𝑀4)2 =3𝐶𝑑+2 +2𝑀𝑀4−3 -32.6
MINTEQ 𝑀𝑍5(𝑀𝑀4)3𝐶𝑘=5𝑀𝑍+2 +3𝑀𝑀4−3 +𝐶𝑘− Cl-
Pyromorphite -84.43
MINTEQ 𝑀𝑍5(𝑀𝑀4)3𝑀𝐻=5𝑀𝑍+2 +3𝑀𝑀4−3
+𝐻2𝑀
Hxypyromorp
hite -62.79
MINTEQ 𝑀𝑘𝐻𝑀𝑀4 =𝑀𝑘+2 +𝑀𝑀4−3 +𝐻+ -25.4
MINTEQ 𝑀𝑍𝐻𝑀𝑀4 =𝑀𝑍+2 +𝑀𝑀4−3 +𝐻+ -23.9
MINTE Q 𝑀𝑍3(𝑀𝑀4)2 =3𝑀𝑍+2 +2𝑀𝑀4−3 -44.5
MINTEQ 𝐻𝑑2𝐻𝑀𝑀4 =𝐻𝑑2+2 +𝐻++𝑀𝑀4−3 -25.9795
WATEQ4f 𝐻++𝑀𝑀4−3 =𝐻𝑀𝑀4−2 12.346 -3.53
kcal
WATEQ4f 2𝐻++𝑀𝑀4−3 =𝐻2𝑀𝑀4− 19.553 -4.52
kcal
WATEQ4f 𝑀𝑍++𝐻𝑀𝑀4−2 =𝑀𝑍𝐻𝑀𝑀4− 0.29
WATEQ4f 𝐾++𝐻𝑀𝑀4−2 =𝐾𝐻𝑀𝑀4− 0.29
WATEQ4f 𝑀𝑑+2 +𝐻𝑀𝑀4−2 =𝑀𝑑𝐻𝑀𝑀4 2.87 3.3 kcal
60
WATEQ4f 𝐶𝑍+2 +𝐻𝑀𝑀4−2 =𝐶𝑍𝐻𝑀𝑀4 2.739 3.3 kcal
WATEQ4f 𝐹𝑑+2 +𝐻2𝑀𝑀4−=𝐹𝑑𝐻2𝑀𝑀4+ 2.7
WATEQ4f 𝐶𝑍+2 +𝑀𝑀4−3 =𝐶𝑍𝑀𝑀4− 6.459 3.1 kcal
WATEQ4f 𝐶𝑍+2 +𝐻2𝑀𝑀4−=𝐶𝑍𝐻2𝑀𝑀4+ 1.408 3.4 kcal
WATEQ4f 𝑀𝑑+2 +𝑀𝑀4−3 =𝑀𝑑𝑀𝑀4− 6.589 3.1 kcal
WATEQ4f 𝑀𝑑+2 +𝐻2𝑀𝑀4−=𝑀𝑑𝐻2𝑀𝑀4+ 1.513 3.4 kcal
WATEQ4f 𝐹𝑑+2 +𝐻𝑀𝑀4−2 =𝐹𝑑𝐻𝑀𝑀4 3.6
WATEQ4f 𝐹𝑑+3 +𝐻𝑀𝑀4−2 =𝐹𝑑𝐻𝑀𝑀4+ 5.43 5.76 kcal
WATEQ4f 𝐹𝑑+3 +𝐻2𝑀𝑀4−=𝐹𝑑𝐻2𝑀𝑀4+2 5.43
WATEQ4f
𝐶𝑍5(𝑀𝑀4)3𝑀𝐻+4𝐻+
=5𝐶𝑍+2 +3𝐻𝑀𝑀4−2
+𝐻2𝑀
-3.421 -36.155
kcal
WATEQ4f
𝐹𝑑5(𝑀𝑀4)2𝐹:8𝐻2𝑀
=3𝐹𝑑+2 +2𝑀𝑀4−3
+8𝐻2𝑀
-36.0
WATEQ4f 𝐹𝑑𝑀𝑀4:2𝐻2𝑀=𝐹𝑑+3 +𝑀𝑀4−3 +2𝐻2𝑀 -26.4 -2.030
kcal
PHREEQ
D
𝑀𝑀43−+𝐻+=𝐻𝑀𝑀42−

-dw = 0.69e-9
4.0 12.346 -3.530
kcal
PHREEQ
D
𝑀𝑀43−+2𝐻+=𝐻𝑀𝑀42−

-dw = 0.846e-9
4.5 19.553 -4.520
kcal
PHREEQ
D 𝐶𝑍2++𝐻𝑀𝑀43−=𝐶𝑍𝑀𝑀4− 6.459 3.10 kcal
PHREEQ
D 𝐶𝑍2++𝐻𝑀𝑀42−=𝐶𝑍𝐻𝑀𝑀4 2.739 3.3 kcal
PHREEQ
D 𝐶𝑍2++𝐻2𝑀𝑀4−=𝐶𝑍𝐻2𝑀𝑀4+ 1.408 3.4 kcal
PHREEQ
D 𝑀𝑑2++𝑀𝑀43−=𝑀𝑑𝑀𝑀4− 6.589 3.10 kcal
PHREEQ
D 𝑀𝑑2++𝐻𝑀𝑀42−=𝑀𝑑𝐻𝑀𝑀4 2.87 3.3 kcal
61
PHREEQ
D 𝑀𝑑2++𝐻2𝑀𝑀4−=𝑀𝑑𝐻2𝑀𝑀4+ 1.513 3.4 kcal
PHREEQ
D 𝑀𝑍++𝐻𝑀𝑀42−=𝑀𝑍𝐻𝑀𝑀4− 0.29
PHREEQ
D 𝐾++𝐻𝑀𝑀42−=𝐾𝐻𝑀𝑀4− 0.29
PHREEQ
D
𝐹𝑑2++𝐻𝑀𝑀42−=𝐹𝑑𝐻𝑀𝑀4
3.6
PHREEQ
D 𝐹𝑑2++𝐻2𝑀𝑀42−=𝐹𝑑𝐻2𝑀𝑀4+ 2.7
PHREEQ
D 𝐹𝑑3++𝐻𝑀𝑀42−=𝐹𝑑𝐻𝑀𝑀4+ 5.43 5.76 kcal
PHREEQ
D 𝐹𝑑3++𝐻2𝑀𝑀4−=𝐹𝑑𝐻2𝑀𝑀42+ 5.43
PHREEQ
D
𝐶𝑍5(𝑀𝑀4)3𝑀𝐻+4𝐻+
=𝐻2𝑀+3𝐻𝑀𝑀42−
+5𝐶𝑍2+
Hydroxyapatit
e

-3.421 -36.155
kcal
PHREEQ
D
𝐹𝑑3(𝑀𝑀4)2:8𝐻2𝑀
=3𝐹𝑑2++2𝑀𝑀43−
+8𝐻2𝑀
Vivianite
-36.0
PHREEQ
D
𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀43−+3𝐻+
=𝐻𝑑𝑘𝑤𝐻2𝑂𝑂4 +𝐻2𝑀 Phosphate 31.29
PHREEQ
D
𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀43−+2𝐻+
=𝐻𝑑𝑘𝑤𝐻𝑂𝑂4 +𝐻2𝑀 25.39
PHREEQ
D
𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀43−+𝐻+
=𝐻𝑑𝑘𝑤𝑂𝑂42−+𝐻2𝑀 17.72
PHREEQ
C 𝑀𝑀4−3 +𝐻+=𝐻𝑀𝑀4−2 4.0 12.346 -3.530
PHREEQ
C 𝑀𝑀4−3 +2𝐻+=𝐻2𝑀𝑀4− 4.5 19.553 -4.520
PHREEQ
C 𝐶𝑍+2 +𝑀𝑀4−3 =𝐶𝑍𝑀𝑀4− 6.459 3.10
PHREEQ
C 𝐶𝑍+2 +𝐻𝑀𝑀4−2 =𝐶𝑍𝐻𝑀𝑀4 2.739 3.3
62
PHREEQ
C 𝐶𝑍+2 +𝐻2𝑀𝑀4−=𝐶𝑍𝐻2𝑀𝑀4+ 1.408 3.4
PHREEQ
C 𝑀𝑑+2 +𝑀𝑀4−3 =𝑀𝑑𝑀𝑀4− 6.589 3.1
PHREEQ
C 𝑀𝑑+2 +𝐻𝑀𝑀4−2 =𝑀𝑑𝐻𝑀𝑀4 2.87 3.3
PHREEQ
C 𝑀𝑑+2 +𝐻2𝑀𝑀4−=𝑀𝑑𝐻2𝑀𝑀4+ 1.513 3.4
PHREEQ
C 𝑀𝑍++𝐻𝑀𝑀4−2 =𝑀𝑍𝐻𝑀𝑀4− 0.29
PHREEQ
C 𝐾++𝐻𝑀𝑀4−2 =𝐾𝐻𝑀𝑀4− 0.29
PHREEQ
C 𝐹𝑑+2 +𝐻𝑀𝑀4−2 =𝐹𝑑𝐻𝑀𝑀4 3.6
PHREEQ
C 𝐹𝑑+2 +𝐻2𝑀𝑀4−=𝐹𝑑𝐻2𝑀𝑀4+ 2.7
PHREEQ
C 𝐹𝑑+3 +𝐻𝑀𝑀4−2 =𝐹𝑑𝐻𝑀𝑀4+ 5.43 5.76
PHREEQ
C 𝐹𝑑+3 +𝐻2𝑀𝑀4−=𝐹𝑑𝐻2𝑀𝑀4+2 5.43
PHREEQ
C
𝐶𝑍5(𝑀𝑀4)3𝑀𝐻+4𝐻+
=𝐻2𝑀+3𝐻𝑀𝑀4−2
+5 𝐶𝑍+2

Hydroxyapatit
e -3.421 -36.155
PHREEQ
C
𝐹𝑑3(𝑀𝑀4)2:8𝐻2𝑀
=3𝐹𝑑+2 +2𝑀𝑀4−3
+8𝐻2𝑀

Vivianite -36.0
PHREEQ
C
𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀4−3 +3𝐻+
=𝐻𝑑𝑘𝑤𝐻2𝑂𝑂4 +𝐻2𝑀

Phosphate 31.29
PHREEQ
C
𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀4−3 +2𝐻+
=𝐻𝑑𝑘𝑤𝐻𝑂𝑂4−+𝐻2𝑀

25.39
63
PHREEQ
C
𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀4−3 +𝐻+
=𝐻𝑑0𝑤𝑂𝑂4−2 +𝐻2𝑀

17.72
MINTEQ.
V4 𝐻++𝑀𝑀4−3 =𝐻𝑀𝑀4−2 5.0 12.375 -15 kJ NIST4
6.3
NIST
46.3
MINTEQ.
V4

2𝐻++𝑀𝑀4−3 =𝐻𝑀𝑀4− 5.4 19.573 -18 kJ NIST4
6.3
NIST
46.3
MINTEQ.
V4

3𝐻++𝑀𝑀4−3 =𝐻3𝑀𝑀4 21.721 -10.1 NIST4
6.3
NIST
46.3
MINTEQ.
V4

𝐶𝑘+2 +𝐻++𝑀𝑀4−3 =𝐶𝑘𝐻𝑀𝑀4 15.4128 NIST4
6.4
MTQ
3.11
MINTEQ.
V4

𝐹𝑑=22𝐻++𝑀𝑀4−3 =𝐹𝑑𝐻2𝑀𝑀4+ 5.4 22.273 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝐹𝑑+2 +𝐻++𝑀𝑀4−3 =𝐹𝑑𝐻𝑀𝑀4 15.975 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝐹𝑑+3 +2𝐻++𝑀𝑀4−3 =𝐹𝑑𝐻2𝑀𝑀4+2 5.4 23.8515 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝐹𝑑+3 +𝐻++𝑀𝑀4−3 =𝐹𝑑𝐻𝑀𝑀4+ 5.4 22.292 -30.5432 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝑀𝑑+2 +2𝑀𝑀4−3 =𝑀𝑑𝑀𝑀4− 5.4 4.654 12.9704
SCD3.
02
(1993
GMa)
MTQ
3.11
MINTEQ.
V4

𝑀𝑑+2 +2𝐻++𝑀𝑀4−3 =𝑀𝑑𝐻2𝑀𝑀4+ 5.4 21.2561 -4.6861 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝑀𝑑+2 +𝐻++𝑀𝑀4−3 =𝑀𝑑𝐻𝑀𝑀4 15.175 -3 NIST4
6.3
NIST
46.3
64
MINTEQ.
V4

𝐶𝑍+2 +𝐻++𝑀𝑀4−3 =𝐶𝑍𝐻𝑀𝑀4 15.035 -3 NIST4
6.3
NIST
46.3
MINTEQ.
V4

𝐶𝑍+2 +𝑀𝑀4−3 =𝐶𝑍𝑀𝑀4− 5.4 6.46 12.9704
SCD3.
02
(1993
GMa)
MTQ
3.11
MINTEQ.
V4

𝐶𝑍+2 +2𝐻++𝑀𝑀4−3 =𝐶𝑍𝐻2𝑀𝑀4+ 5.4 20.923 -6 NIST4
6.3
NIST
46.3
MINTEQ.
V4

𝑀𝑍++𝐻++𝑀𝑀4−3 =𝑀𝑍𝐻𝑀𝑀4−
5.4 13.445 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝐾+𝐻+𝑀𝑀4−3 =𝐾𝐻𝑀𝑀4− 5.4 13.255 NIST4
6.3
MTQ
3.11
MINTEQ.
V4

𝐶𝑡3(𝑀𝑀4)2 =3𝐶𝑡+2 +2𝑀𝑀4−3 -36.85
MINTEQ.
V4

𝐶𝑡3(𝑀𝑀4)2:3𝐻2𝑀
=3𝐶𝑡+2 +2𝑀𝑀4−3
+3𝐻2𝑀
-35.12
MINTEQ.
V4

𝐹𝑑3(𝑀𝑀4)2:8𝐻2𝑀
=3𝐹𝑑+2 +2𝑀𝑀4−3
+8𝐻2𝑀
Vivianite
-36
MINTEQ.
V4

𝐹𝑑𝑀𝑀4:2𝐻2𝑀=𝐹𝑑+3 +𝑀𝑀4−3 +2𝐻2𝑀 Strengite
-26.4 -9.3601
MINTEQ.
V4

𝑀𝑘3(𝑀𝑀4)2 =3𝑀𝑀+2 +2𝑀𝑀4−3 -23.827 8.8701
MINTEQ.
V4

𝑀𝑘𝐻𝑀𝑀4 =𝑀𝑘+2 +𝑀𝑀4−3 +𝐻+ -25.4
MINTEQ.
V4 𝑀𝑑3(𝑀𝑀4)2 =3𝑀𝑑+2 +2(𝑀𝑀4)−3 -23.28
65

MINTEQ.
V4

𝑀𝑑𝐻𝑀𝑀4:3𝐻2𝑀
=𝑀𝑑+2 +𝐻++𝑀𝑀4−3
+3𝐻2𝑀
-18.175
MINTEQ.
V4

𝐶𝑍9.316 𝑀𝑍0.36𝑀𝑑0.144 (𝑀𝑀4)4.8
(𝐶𝑘3)1.2 𝐹2.48=9.316𝐶𝑍+2 +0.36𝑀𝑍+
+𝑀.144𝑀𝑑+2
+4.8𝑀𝑀4−3 +1.2𝐶𝑀3−2
+2.48𝐹−
FCO3Apatite -114.4 164.808
MINTEQ.
V4

𝐶𝑍5(𝑀𝑀4)3𝑀𝐻+𝐻+
=5𝐶𝑍+2 +3𝑀𝑀4−3
+𝐻2𝑀
Hydroxylapati
te

-44.333
MINTEQ.
V4

𝐶𝑍𝐻𝑀𝑀4:2𝐻2𝑀=𝐶𝑍+2 +𝐻++𝑀𝑀4−3
+2𝐻2𝑀 -18.995
MINTEQ.
V4

𝐶𝑍𝐻𝑀𝑀4 =𝐶𝑍+2 +𝐻++𝑀𝑀4−3 -19.275 31,23
MINTEQ.
V4

𝐶𝑍3(𝑀𝑀4)2 =3𝐶𝑍+2 +2𝑀𝑀4−3 -28.92 54
MINTEQ.
V4

𝐶𝑍4𝐻(𝑀𝑀4)3:3𝐻2𝑀
=4𝐶𝑍+2 +𝐻++3𝑀𝑀4−3
+3𝐻2𝑀
-47.08
MINTEQ.
V4

𝐻𝑑𝑘𝑠𝑂𝐻+𝑀𝑀4−3 +3𝐻+
=𝐻𝑑𝑘𝑠𝐻2𝑂𝑂4 +𝐻2𝑀 31.29
MINTEQ.
V4

𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀4−3 +3𝐻+
=𝐻𝑑𝑘𝑤𝐻2𝑂𝑂4 +𝐻2𝑀 31.29
MINTEQ.
V4

𝐻𝑑𝑘𝑠𝑂𝐻+𝑀𝑀4−3 +2𝐻+
=𝐻𝑑𝑘𝑠𝐻𝑂𝑂4−+𝐻2𝑀 25.39
MINTEQ.
V4

𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀4−3 +@𝐻+
=𝐻𝑑𝑘𝑤𝐻𝑂𝑂4−+𝐻2𝑀 25.39
66

MINTEQ.
V4

𝐻𝑑𝑘𝑠𝑂𝐻+𝑀𝑀4−3 +𝐻+
=𝐻𝑑𝑘𝑠𝐻𝑂𝑂4−2 +𝐻2𝑀 17.72
MINTEQ.
V4

𝐻𝑑𝑘𝑤𝑂𝐻+𝑀𝑀4−3 +𝐻+
=𝐻𝑑𝑘𝑤𝐻𝑂𝑂4−2 +𝐻2𝑀

17.72
67
11 Appendix B. Tables and Supplemental Data

LeMonte et al, 2023.
Utah Lake Water Quality Study
Utah Lake Sediment Phosphorus Binding

Supplemental data, as well as raw data for this study can be found online at PhosBinding_Supplemental Data.

Location Provo Bay Provo Vineyard Bird Island Goshen Bay Saratoga Springs Pelican Point
Site ID PB PV VY BI GB SS PP
Latitude,WGS-84 °N 40.1846 40.2357 40.3002 40.1654 40.0906 40.337 40.2703
Longitude,WGS-84 °W -111.7162 -111.7668 -111.8020 -111.7788 -111.8915 -111.8687 -111.8364
ρ,a g cm-3 0.69 ( 0.53 , 0.85 ) 0.78 ( 0.74 , 0.82 ) 0.79 ( 0.76 , 0.82 ) 0.61 ( 0.57 , 0.64 ) 0.56 ( 0.51 , 0.62 ) 0.45 ( 0.42 , 0.49 ) 0.48 ( 0.45 , 0.52 )
θ,a L L-1 0.74 ( 0.68 , 0.80 ) 0.72 ( 0.70 , 0.74 ) 0.71 ( 0.69 , 0.74 ) 0.83 ( 0.79 , 0.87 ) 0.79 ( 0.75 , 0.83 ) 0.89 ( 0.82 , 0.96 ) 0.83 ( 0.80 , 0.85 )
pH 7.69 7.89 7.94 7.94 7.99 8.02 8.04
ORP, rel. mV 131 132 131 133 126 128 127
Conductivity, µS cm-1 1589 2476 2273 2640 2438 2186 1876
Sediment Composition, %
_Organic Matterb 11.4 ( 8.80 , 14.0 ) 9.63 ( 8.59 , 10.7 ) 8.49 ( 8.05 , 8.93 ) 9.14 ( 8.26 , 10.0 ) 9.28 ( 8.40 , 10.2 ) 7.67 ( 7.09 , 8.26 ) 6.59 ( 6.47 , 6.70 )
_Carbonatesc 24.9 ( 20.1 , 29.7 ) 57.3 ( 56.1 , 58.5 ) 57.3 ( 56.3 , 58.2 ) 57.0 ( 55.3 , 58.7 ) 56.6 ( 50.4 , 62.8 ) 55.7 ( 48.1 , 63.3 ) 54.5 ( 52.3 , 56.7 )
Particle Size Distribution,d %
_Sand 3.23 1.60 0.62 1.45 1.01 0.40 3.85
__Coarse Sand> 0.5mm, % of Sand 1.04 0.15 8.25 6.46 0.03 3.09 0.38
__Fine Sand> 0.053mm, % of Sand 93.3 93.0 81.0 87.1 90.6 89.7 95.6
__POM, % of Sand 5.63 6.89 10.8 6.48 9.37 7.19 3.99
_Silt 66.2 69.8 71.6 68.7 71.9 69.5 70.2
_Clay 30.6 28.6 27.8 29.9 27.1 30.1 25.9
Mineralogy,e % of mineral mass
_Quartz 53.0 ( 32.6 , 73.4 ) 12.9 ( 10.9 , 14.8 ) 11.7 ( 10.2 , 13.3 ) 11.6 ( 9.23 , 14.0 ) 15.5 ( 11.4 , 19.7 ) 8.66 ( 5.72 , 11.6 ) 19.7 ( 18.8 , 20.5 )
_Calcite 25.6 ( 15.6 , 35.6 ) 62.4 ( 56.5 , 68.4 ) 59.5 ( 53.2 , 65.9 ) 58.6 ( 48.1 , 69.1 ) 55.3 ( 45.7 , 64.9 ) 66.7 ( 49.7 , 83.8 ) 49.7 ( 48.0 , 51.3 )
_Dolomite 2.56 ( 1.57 , 3.54 ) 3.73 ( 3.11 , 4.36 ) 3.28 ( 2.29 , 4.27 ) 3.57 ( 1.08 , 6.06 ) 4.63 ( 2.70 , 6.56 ) 3.44 ( 2.51 , 4.36 ) 4.15 ( 3.44 , 4.86 )
_Oligoclase 11.6 ( 0.00 , 28.4 ) 6.30 ( 3.07 , 9.53 ) 8.02 ( 3.82 , 12.2 ) 3.80 ( 0.00 , 9.51 ) 6.23 ( 0.00 , 14.5 ) 3.97 ( 2.10 , 5.83 ) 10.7 ( 5.07 , 16.3 )
_2:1 Claysf 5.29 ( 0.00 , 11.5 ) 10.6 ( 0.00 , 23.6 ) 14.2 ( 8.52 , 19.8 ) 18.2 ( 1.22 , 35.2 ) 12.3 ( 0.00 , 26.6 ) 13.1 ( 0.00 , 28.9 ) 12.1 ( 4.23 , 19.9 )
_1:1 Claysf 2.10 ( 0.00 , 5.35 ) 3.90 ( 0.00 , 9.35 ) 3.20 ( 0.94 , 5.46 ) 4.37 ( 2.68 , 6.06 ) 6.00 ( 5.01 , 6.99 ) 4.13 ( 0.00 , 9.04 ) 3.72 ( 1.42 , 6.03 )
Chemical Composition,g mg kg-1
_Ca, 105 1.18 ( 1.07 , 1.29 ) 1.88 ( 1.61 , 2.15 ) 1.94 ( 1.82 , 2.05 ) 1.91 ( 1.84 , 1.98 ) 1.83 ( 1.62 , 2.04 ) 2.18 ( 2.14 , 2.21 ) 1.65 ( 1.45 , 1.85 )
_Al, 103 6.55 ( 5.27 , 7.83 ) 7.07 ( 6.62 , 7.51 ) 7.98 ( 6.73 , 9.24 ) 10.0 ( 8.86 , 11.1 ) 7.40 ( 4.54 , 10.3 ) 7.04 ( 5.64 , 8.44 ) 7.35 ( 4.69 , 10.0 )
_Fe, 103 7.81 ( 6.41 , 9.20 ) 9.80 ( 8.83 , 10.8 ) 9.33 ( 8.83 , 9.84 ) 10.8 ( 10.2 , 11.5 ) 10.3 ( 8.30 , 12.4 ) 8.84 ( 8.36 , 9.31 ) 8.89 ( 8.23 , 9.55 )
_Mn 190 ( 162 , 217 ) 324 ( 280 , 369 ) 304 ( 288 , 320 ) 333 ( 318 , 348 ) 323 ( 288 , 359 ) 330 ( 324 , 336 ) 264 ( 236 , 292 )
Sequential P-fractions,h mg-P kg-1
_NH4Cl 22.5 ( 6.4 , 45.0 ) 15.3 ( 12.1 , 18.7 ) 19.3 ( 14.5 , 24.5 ) 15.2 ( 12.3 , 18.3 ) 16.5 ( 14.2 , 18.9 ) 17.8 ( 14.5 , 21.1 ) 17.3 ( 13.6 , 21.4 )
BS 44.2 ( 36.3 , 52.8 ) 34.8 ( 22.8 , 48.8 ) 35.9 ( 24.2 , 49.5 ) 36.9 ( 32.0 , 42.0 ) 33.9 ( 25.1 , 43.5 ) 39.5 ( 32.3 , 47.3 ) 37.2 ( 23.7 , 53.5 )
_BD 119 ( 77.6 , 169 ) 88.0 ( 76.2 , 101 ) 100 ( 88.9 , 112 ) 86.4 ( 62.3 , 113 ) 87.1 ( 70.1 , 106 ) 92.4 ( 84.5 , 100 ) 86.8 ( 70.3 , 103 )
BS 174 ( 138 , 213 ) 115 ( 84.4 , 150 ) 121 ( 81.0 , 168 ) 127 ( 114 , 142 ) 126 ( 91.4 , 164 ) 134 ( 113 , 156 ) 137 ( 34.9 , 287 )
_NaOH 68.2 ( 43.5 , 98.4 ) 49.9 ( 39.9 , 60.7 ) 38.4 ( 28.3 , 49.3 ) 46.1 ( 39.2 , 53.6 ) 63.5 ( 44.9 , 84.6 ) 53.2 ( 46.4 , 59.9 ) 55.1 ( 45.5 , 65.5 )
BS 65.4 ( 44.8 , 89.3 ) 58.7 ( 37.6 , 83.5 ) 48.3 ( 28.6 , 73.2 ) 64.0 ( 47.8 , 82.2 ) 67.4 ( 51.8 , 83.5 ) 54.8 ( 30.4 , 83.7 ) 40.7 ( 6.00 , 92.8 )
_HCl 450 ( 319 , 598 ) 374 ( 317 , 436 ) 407 ( 384 , 431 ) 444 ( 400 , 490 ) 445 ( 371 , 526 ) 406 ( 375 , 438 ) 441 ( 376 , 510 )
BS 579 ( 479 , 689 ) 463 ( 346 , 598 ) 476 ( 331 , 639 ) 492 ( 430 , 558 ) 510 ( 384 , 644 ) 486 ( 413 , 564 ) 509 ( 331 , 719 )
_Residual 63.2 ( 36.2 , 97.6 ) 84.9 ( 56.4 , 116 ) 83.8 ( 76.2 , 91.8 ) 90.1 ( 62.7 , 120 ) 100 ( 75.9 , 128 ) 101 ( 87.2 , 114 ) 92.8 ( 74.4 , 113 )
BS 73.1 ( 43.6 , 108 ) 102 ( 64.7 , 145 ) 108 ( 73.8 , 147 ) 116 ( 98.0 , 136 ) 112 ( 79.7 , 149 ) 116 ( 91.3 , 143 ) 99.2 ( 64.7 , 140 )
_Total 723 ( 558 , 887 ) 692 ( 613 , 772 ) 649 ( 621 , 677 ) 682 ( 648 , 715 ) 713 ( 651 , 774 ) 671 ( 668 , 673 ) 612 ( 577 , 648 )
BS 935 ( 832 , 1038 ) 824 ( 606 , 1042 ) 789 ( 593 , 985 ) 837 ( 755 , 918 ) 849 ( 665 , 1033 ) 830 ( 740 , 919 ) 773 ( 686 , 861 )
Notes: () = 95% Confidence Interval; WGS-84 = World Geodetic System 1984 datum; ρ = Bulk density; θ = Volumetric Water Content; ORP = Oxidation-Reduction Potential; POM = Particulate
Organic Matter; > 0.5mm = Sand particles larger than 0.5 mm; > 0.053mm = sand particles larger than 0.053 mm but smaller than 0.5 mm; Ca = Calcium; Al = Aluminum; Fe = Iron; Mn =
Manganese; P = Phosphorus; NH4Cl = Ammonium Chloride extracted P, loosely adsorbed P; BD = Bicarbonate/Dithionite extracted P, redox-sensitive P bound to Fe and Mn compounds; NaOH =
Sodium Hydroxide extracted P, P exchangeable against OH- ions and bound in organic matter; HCl = Hydrochloric-aid extracted P, carbonate bound P; Residual = Acid-Digestion extracted P,
refractory organic P and hyper-stable mineral P; Total = Sum total of P collected from each sequential fraction; BS = Rows are sediment values following a batch sorption isotherm experiment
conducted at pH 8.5, 25°C, and an initial aqueous concentration of 3 mg-P L-1; a Syringe method determined Bulk Density or VWC, average of top 10 cm of lakebed (Richwine et al. 2015); b
Sodium-Hypochlorite removal of organic matter (Anderson 1961); c Hydrochloric-Acid removal of carbonates (Dhillon et al. 2015); d Particle-Size Determination of soil/sediment (Kettler et al.
2001); e Mineralogy by X-ray Diffraction and Rietveld fitting method (Bish & Post, 1993); f Non-glycolated clays by X-ray Diffraction, percentages represent relative abundances (Schultz 1964); g
Chemical Composition by Acid-Digestion of Sediments using dry mass (EPA 2007); h Sequential P-fractionation in sediments using dry mass (Hupfer et al. 2009 and Gu et al. 2020)

Table 2. Physiochemical properties of Utah Lake sediment gathered using an Ekman dredge from the top 10 cm of the lakebed. Sediments were collected from 7 locations across the lake in August 2021.
68
Table

Location Provo Bay Provo Vineyard Bird Island Goshen Bay Saratoga Springs Pelican Point
Site ID PB PV VY BI GB SS PP
Latitude,WGS-84 °N 40.1846 40.2357 40.3002 40.1654 40.0906 40.337 40.2703
Longitude,WGS-84 °W -111.7162 -111.7668 -111.8020 -111.7788 -111.8915 -111.8687 -111.8364
Sequential P-fractions,a %
_NH4Cl 3.11 ( 1.15 , 5.07 ) 2.49 ( 2.10 , 2.89 ) 2.98 ( 2.34 , 3.62 ) 2.23 ( 1.90 , 2.56 ) 2.32 ( 2.19 , 2.45 ) 2.65 ( 2.18 , 3.13 ) 2.50 ( 2.23 , 2.77 )
BS 4.72 ( 4.36 , 5.08 ) 4.50 ( 3.33 , 5.67 ) 4.55 ( 4.07 , 5.03 ) 4.40 ( 4.24 , 4.57 ) 3.99 ( 3.77 , 4.21 ) 4.76 ( 4.37 , 5.15 ) 4.52 ( 3.91 , 5.13 )
_BD 16.5 ( 13.9 , 19.0 ) 14.4 ( 13.2 , 15.5 ) 15.4 ( 14.3 , 16.5 ) 12.7 ( 9.61 , 15.7 ) 12.2 ( 10.8 , 13.7 ) 13.8 ( 12.7 , 14.9 ) 12.4 ( 11.5 , 13.3 )
BS 18.5 ( 16.6 , 20.5 ) 14.8 ( 12.3 , 17.4 ) 15.4 ( 13.7 , 17.1 ) 15.2 ( 15.0 , 15.4 ) 14.8 ( 13.7 , 15.9 ) 16.1 ( 15.2 , 17.0 ) 16.7 ( 5.76 , 27.6 )
_NaOH 9.44 ( 7.79 , 11.1 ) 8.14 ( 6.91 , 9.38 ) 5.92 ( 4.56 , 7.28 ) 6.77 ( 6.04 , 7.49 ) 8.91 ( 6.89 , 10.9 ) 7.93 ( 6.95 , 8.90 ) 7.95 ( 7.42 , 8.49 )
BS 6.99 ( 5.39 , 8.60 ) 7.59 ( 5.49 , 9.70 ) 6.13 ( 4.82 , 7.43 ) 7.64 ( 6.33 , 8.95 ) 7.94 ( 7.79 , 8.09 ) 6.61 ( 4.11 , 9.11 ) 4.95 ( 0.98 , 8.91 )
_HCl 62.2 ( 57.1 , 67.4 ) 61.1 ( 55.0 , 67.3 ) 62.8 ( 61.9 , 63.7 ) 65.1 ( 61.7 , 68.5 ) 62.5 ( 56.9 , 68.0 ) 60.6 ( 56.1 , 65.1 ) 63.8 ( 61.5 , 66.1 )
BS 61.9 ( 57.5 , 66.3 ) 59.9 ( 50.4 , 69.4 ) 60.3 ( 55.7 , 64.9 ) 58.8 ( 57.0 , 60.7 ) 60.1 ( 57.8 , 62.4 ) 58.6 ( 55.8 , 61.4 ) 61.8 ( 54.6 , 69.0 )
_Residual 8.75 ( 6.49 , 11.0 ) 13.9 ( 9.76 , 18.0 ) 12.9 ( 12.3 , 13.6 ) 13.2 ( 9.68 , 16.8 ) 14.1 ( 11.7 , 16.5 ) 15.0 ( 13.1 , 17.0 ) 13.4 ( 12.2 , 14.7 )
BS 7.81 ( 5.23 , 10.4 ) 13.1 ( 9.43 , 16.9 ) 13.7 ( 12.4 , 14.9 ) 13.9 ( 13.0 , 14.8 ) 13.2 ( 12.0 , 14.4 ) 13.9 ( 12.3 , 15.5 ) 12.0 ( 10.7 , 13.4 )
Notes: () = 95% Confidence Interval; WGS-84 = World Geodetic System 1984 datum; P = Phosphorus; NH4Cl = Ammonium Chloride extracted P, loosely adsorbed P; BD =
Bicarbonate/Dithionite extracted P, redox-sensitive P bound to Fe and Mn compounds; NaOH = Sodium Hydroxide extracted P, P exchangeable against OH- ions and bound in organic matter;
HCl = Hydrochloric-aid extracted P, carbonate bound P; Residual = Acid-Digestion extracted P, refractory organic P and hyper-stable mineral P; a Sequential P-fractionation in sediments (Hupfer
et al. 2009 and Gu et al. 2020)

Table 3. Sequential P-fractionation percentages for sediment collected using an Ekman dredge from the top 10 cm of the lakebed. Sediments were collected from 7 locations across the lake in August 2021. Rows
labeled with BS are percentages obtained from sediments following a BSI experiment conducted at pH 8.5, 25°C, and an initial aqueous concentration of 3 mg-P L-1.

69

Location Provo Bay Provo Vineyard Bird Island Goshen Bay Saratoga Springs Pelican Point
Site ID PB PV VY BI GB SS PP
Latitude,WGS-84 °N 40.1846 40.2357 40.3002 40.1654 40.0906 40.337 40.2703
Longitude,WGS-84 °W -111.7162 -111.7668 -111.8020 -111.7788 -111.8915 -111.8687 -111.8364
Temperature,DWQ °C 23.0 ( 20.6 , 25.5 ) 24.6 ( 24.5 , 24.7 ) 24.1 ( 24.1 , 24.2 ) 26.5 ( 26.4 , 26.7 ) 20.9 ( 20.9 , 21.0 ) 25.1 ( 25.1 , 25.1 ) 25.2 ( 25.0 , 25.4 )
Conductivity,DWQ µS cm-1 1442 ( 982 , 1902 ) 2418 ( 2405 , 2431 ) 2399 ( 2395 , 2402 ) 2380 ( 2373 , 2387 ) 2746 ( 2741 , 2751 ) 2424 ( 2422 , 2425 ) 2342 ( 2318 , 2365 )
pHDWQ 8.48 ( 6.39 , 10.58 ) 8.88 ( 8.87 , 8.88 ) 8.85 ( 8.84 , 8.86 ) 8.89 ( 8.89 , 8.90 ) 8.21 ( 8.15 , 8.28 ) 8.74 ( 8.73 , 8.75 ) 8.75 ( 8.73 , 8.77 )
ORP, rel. mV 201 ( 154 , 248 ) 250 ( 213 , 288 ) 255 ( 231 , 279 ) 245 ( 124 , 365 ) 212 ( 187 , 238 ) 287 ( 268 , 306 ) 132 ( 108 , 155 )
Alkalinity,DWQ mg L-1 176 182 172 169 195 170 175
Turbidity,DWQ NTU 56.2 39.8 27.1 21.6 38.2 24.6 33.3
Solids, mg L-1
_Total Dissolved Solids DWQ 914 1420 1410 1430 1730 1450 1370
_Total Suspended Solids DWQ 132 53 55 42 93 69 53
_Total Volatile Solids DWQ 36 17 17 15 20 23 17
Isotopes,a ‰
_δ2HVSMOW -117 ( -119 , -114 ) -50.5 ( -54.5 , -46.6 ) -49.7 ( -50.5 , -48.9 ) -51.7 ( -52.1 , -51.3 )
_δ18OVSMOW -15.0 ( -15.3 , -14.7 ) -4.27 ( -5.05 , -3.50 ) -4.33 ( -4.40 , -4.26 ) -4.90 ( -5.21 , -4.59 )
Nutrients & Organics, mg L-1
_NDWQ 2.41 ( 0.00 , 4.94 ) 0.78 ( 0.18 , 1.38 ) 0.85 ( 0.70 , 1.00 ) 0.89 ( 0.00 , 2.04 ) 1.29 ( 0.21 , 2.38 ) 0.79 ( 0.78 , 0.80 ) 0.75 ( 0.29 , 1.20 )
_NH3DWQ 0.0379 0.0085 0.0085 0.0085 0.0085 0.0085 0.0085
_Organic-CDWQ 23.1 ( 0.34 , 45.8 ) 8.90 ( 7.50 , 10.3 ) 10.6 ( 6.53 , 14.6 ) 10.9 ( 0.00 , 38.8 ) 14.1 ( 0.00 , 53.5 ) 8.84 ( 5.72 , 12.0 ) 8.46 ( 8.27 , 8.66 )
_Dissolved-ODWQ 7.15 ( 0.00 , 24.8 ) 7.90 ( 7.74 , 8.06 ) 7.88 ( 7.77 , 7.98 ) 8.77 ( 8.70 , 8.84 ) 5.66 ( 5.59 , 5.72 ) 9.49 ( 9.47 , 9.52 ) 7.63 ( 7.35 , 7.90 )
_Dissolved-O Saturation, DWQ % 98.0 ( 0.00 , 321 ) 113 ( 111 , 115 ) 111 ( 110 , 113 ) 130 ( 129 , 130 ) 75.8 ( 74.3 , 77.2 ) 137 ( 137 , 137 ) 110 ( 106 , 114 )
_Chlorophyll-a,DWQ µg L-1 183 ( 0.00 , 385 ) 51.6 ( 0.00 , 118 ) 59.7 ( 0.00 , 125 ) 54.4 ( 0.00 , 121 ) 72.5 ( 0.00 , 171 ) 84.2 ( 0.00 , 189 ) 52.6 ( 0.00 , 121 )
_Pheophytin-a,DWQ µg L-1 8.25 1.98 4.44 1.98 4.61 2.47 2.47
Cations,b mg L-1
_Ca sur 47.9 ( 45.9 , 49.8 ) 54.1 ( 46.0 , 62.1 ) 15.6 ( 12.7 , 18.4 ) 19.5 ( 15.1 , 23.9 ) 9.42 ( 5.47 , 13.4 ) 15.9 ( 3.06 , 28.7 ) 21.1 ( 19.8 , 22.3 )
mid 51.4 ( 49.3 , 53.5 ) 53.2 ( 50.5 , 55.9 ) 19.1 ( 10.6 , 27.7 ) 22.1 ( 15.6 , 28.5 ) 10.7 ( 6.16 , 15.2 ) 14.8 ( 3.17 , 26.4 ) 16.9 ( 15.4 , 18.3 )
bot 55.8 ( 50.1 , 61.5 ) 49.2 ( 31.8 , 66.6 ) 13.5 ( 1.48 , 25.4 ) 16.7 ( 16.3 , 17.1 ) 17.0 ( 14.0 , 19.9 ) 16.3 ( 7.13 , 25.4 ) 24.8 ( 22.4 , 27.1 )
_K sur 14.4 ( 14.1 , 14.7 ) 27.1 ( 23.7 , 30.4 ) 12.9 ( 11.7 , 14.0 ) 14.7 ( 12.4 , 17.0 ) 10.7 ( 7.53 , 13.9 ) 12.6 ( 6.17 , 19.0 ) 17.1 ( 16.1 , 18.1 )
mid 15.6 ( 15.0 , 16.2 ) 28.2 ( 27.0 , 29.4 ) 14.1 ( 10.5 , 17.8 ) 16.0 ( 13.0 , 19.1 ) 11.0 ( 8.30 , 13.7 ) 11.8 ( 5.84 , 17.7 ) 13.2 ( 12.6 , 13.9 )
bot 16.8 ( 15.6 , 17.9 ) 25.4 ( 19.1 , 31.7 ) 11.6 ( 5.84 , 17.3 ) 13.5 ( 13.0 , 14.0 ) 10.9 ( 9.37 , 12.3 ) 12.4 ( 7.40 , 17.5 ) 15.1 ( 14.0 , 16.3 )
_Mg sur 49.3 ( 47.4 , 51.2 ) 80.5 ( 71.6 , 89.4 ) 27.8 ( 22.6 , 33.1 ) 32.9 ( 25.1 , 40.6 ) 16.5 ( 9.24 , 23.7 ) 27.7 ( 4.74 , 50.7 ) 44.2 ( 39.4 , 49.0 )
mid 56.1 ( 54.1 , 58.2 ) 83.7 ( 80.4 , 87.0 ) 33.3 ( 18.0 , 48.7 ) 36.9 ( 25.7 , 48.1 ) 16.9 ( 9.40 , 24.5 ) 26.1 ( 5.02 , 47.1 ) 29.6 ( 26.8 , 32.4 )
bot 58.1 ( 51.8 , 64.5 ) 72.5 ( 48.1 , 97.0 ) 21.4 ( 1.42 , 41.4 ) 27.4 ( 26.6 , 28.2 ) 16.4 ( 13.8 , 18.9 ) 28.7 ( 12.7 , 44.7 ) 37.3 ( 35.0 , 39.5 )
_Na sur 139 ( 135 , 144 ) 290 ( 268 , 311 ) 127 ( 111 , 144 ) 150 ( 122 , 179 ) 104 ( 69.4 , 139 ) 126 ( 49.2 , 204 ) 179 ( 171 , 186 )
mid 161 ( 154 , 168 ) 294 ( 274 , 315 ) 144 ( 99.5 , 189 ) 164 ( 129 , 199 ) 108 ( 76.1 , 139 ) 118 ( 48.4 , 189 ) 133 ( 124 , 143 )
bot 172 ( 160 , 184 ) 264 ( 213 , 315 ) 111 ( 43.3 , 179 ) 135 ( 131 , 138 ) 104 ( 87.9 , 120 ) 127 ( 69.8 , 183 ) 156 ( 144 , 167 )
_Fe, 10-3 sur 60.3 ( 56.5 , 64.1 ) 68.3 ( 60.3 , 76.3 ) 19.7 ( 0.00 , 82.8 ) 9.00 ( 0.00 , 26.2 ) 5.00 ( 0.00 , 11.6 ) 6.00 ( 0.00 , 19.1 ) 11.3 ( 0.00 , 32.2 )
mid 30.3 ( 18.1 , 42.6 ) 65.0 ( 62.5 , 67.5 ) 13.7 ( 7.41 , 19.9 ) 18.0 ( 0.00 , 65.4 ) 28.0 ( 0.00 , 61.4 ) 7.33 ( 0.00 , 26.1 ) 8.33 ( 6.90 , 9.77 )
bot 99.3 ( 83.2 , 116 ) 86.0 ( 42.9 , 129 ) 15.3 ( 0.99 , 29.7 ) 89.7 ( 0.00 , 347 ) 151 ( 0.00 , 351 ) 4.00 ( 0.00 , 10.6 ) 10.7 ( 0.00 , 22.9 )
_P, 10-3 sur 65.3 ( 62.5 , 68.2 ) 54.3 ( 41.8 , 66.8 ) 14.0 ( 9.03 , 19.0 ) 13.0 ( 12.9 , 13.2 ) 10.3 ( 7.46 , 13.2 ) 11.7 ( 2.94 , 20.4 ) 15.3 ( 12.5 , 18.2 )
mid 40.3 ( 36.5 , 44.1 ) 47.3 ( 41.1 , 53.6 ) 19.7 ( 5.98 , 33.3 ) 13.0 ( 8.70 , 17.3 ) 21.3 ( 11.0 , 31.7 ) 10.7 ( 2.68 , 18.7 ) 11.7 ( 10.2 , 13.1 )
bot 107 ( 95.5 , 118 ) 57.3 ( 42.8 , 71.9 ) 17.0 ( 6.17 , 27.8 ) 10.7 ( 6.87 , 14.5 ) 55.7 ( 49.4 , 61.9 ) 12.0 ( 9.52 , 14.5 ) 19.3 ( 13.6 , 25.1 )
Anions, mg L-1
_Cl- DWQ 236 453 435 433 545 458 442
_NO3- + NO2- DWQ 0.0115 0.0115 0.0115 0.0115 0.0115 0.0115 0.0115
_SO42- DWQ 281 367 365 369 434 373 355
_PO43- DWQ 0.0823 0.0682 0.0648 0.0651 0.0658 0.0618 0.0691
Notes: () = 95% Confidence Interval; WGS-84 = World Geodetic System 1984 datum; DWQ = Data derived using the Utah Department of Water Quality (DWQ) Utah Lake Data Explorer (ULDE) for
August 2021; ORP = Oxidation-Reduction Potential; VSMOW = Vienna Standard Mean Ocean Water; sur = Waters in row collected from ~4 cm below water surface; mid = Waters in row collected from
~1-2 m below water surface; bot = Waters in row collected from ~3-4 m below water surface; C = Carbon; Ca = Calcium; Cl- = Chloride; Fe = Iron; H = Hydrogen; K = Potassium; O = Oxygen; Mg =
Magnesium; N = Nitrogen; Na = Sodium; NH3 = Ammonia; NO3- + NO2- = Nitrate and Nitrite; SO42- = Sulfate; P = Phosphorus; PO43- = Orthophosphate; a Waters collected on November 15, 2021 and
analyzed using a Los Gatos Research cavity ring-down Liquid Water Isotope Analyzer; b Waters collected on August 20, 2021, filtered (0.45 microns), acidified, and analyzed using Inductively Coupled
Plasma Optical Emission spectroscopy

Table 4. Physiochemical properties of Utah Lake column waters gathered using a peristaltic pump attached to a hand drill. Waters were collected from 7 locations across the lake in Fall 2021.
70

Location Provo Bay Provo Vineyard Bird Island Goshen Bay Saratoga Springs Pelican Point
Site ID PB PV VY BI GB SS PP
Latitude,WGS-84 °N 40.1846 40.2357 40.3002 40.1654 40.0906 40.337 40.2703
Longitude,WGS-84 °W -111.7162 -111.7668 -111.8020 -111.7788 -111.8915 -111.8687 -111.8364
X,a mg-P L-1 1.07 ( 0.42 , 1.72 ) 0.81 ( 0.51 , 1.11 ) 0.40 ( 0.18 , 0.62 ) 0.70 ( 0.28 , 1.13 ) 0.50 ( 0.25 , 0.75 ) 0.36 ( 0.15 , 0.56 ) 0.30 ( 0.16 , 0.44 )
Linear: Q = Kd·(Cf) + bd
_Kd, L kg-1 pH 7.5 11.7 ( 10.8 , 12.5 ) 15.2 ( 13.2 , 17.1 )
pH 8.0 14.0 ( 6.47 , 21.5 ) 18.5 ( 17.5 , 19.5 ) 18.7 ( 17.9 , 19.5 ) 19.0 ( 17.5 , 20.4 ) 16.2 ( 15.2 , 17.3 ) 18.8 ( 17.6 , 20.1 ) 13.9 ( 13.4 , 14.5 )
pH 8.5-A 18.8 ( 15.2 , 22.4 ) 17.9 ( 15.9 , 19.9 ) 32.4 ( 24.6 , 40.2 ) 19.6 ( 16.4 , 22.8 ) 18.1 ( 16.4 , 19.7 ) 17.2 ( 14.3 , 20.1 ) 17.4 ( 15.6 , 19.2 )
pH 8.5 41.7 ( 37.1 , 46.3 ) 34.2 ( 31.5 , 37.0 ) 56.7 ( 52.7 , 60.7 ) 38.0 ( 34.2 , 41.7 ) 33.3 ( 31.0 , 35.6 ) 33.1 ( 30.6 , 35.6 ) 32.6 ( 30.2 , 34.9 )
pH 9.0 145 ( 126 , 165 ) 63.5 ( 60.6 , 66.4 ) 74.3 ( 56.8 , 91.7 ) 74.3 ( 69.6 , 79.1 ) 58.9 ( 55.1 , 62.7 ) 50.8 ( 49.4 , 52.2 ) 73.5 ( 69.4 , 77.6 )
_bd, mg-P kg-1 pH 7.5 -8.72 ( -23.4 , 0.00 ) -10.3 ( -38.5 , 0.00 )
pH 8.0 -51.7 ( -268 , 0.00 ) -16.8 ( -29.8 , -3.87 ) -6.67 ( -17.3 , 0.00 ) -14.0 ( -32.8 , 0.00 ) -13.3 ( -28.3 , 0.00 ) -12.7 ( -28.9 , 0.00 ) -6.35 ( -14.4 , 0.00 )
pH 8.5-A -13.8 ( -60.0 , 0.00 ) -18.7 ( -66.8 , 0.00 ) -10.7 ( -132.3 , 0.00 ) -24.0 ( -97.8 , 0.00 ) -10.7 ( -32.7 , 0.00 ) -3.98 ( -74.7 , 0.00 ) -5.46 ( -29.3 , 0.00 )
pH 8.5 -63.9 ( -101 , -26.8 ) -16.2 ( -38.6 , 0.00 ) -1.57 ( -24.0 , 0.00 ) -19.8 ( -48.1 , 0.00 ) -3.84 ( -26.5 , 0.00 ) -7.30 ( -28.2 , 0.00 ) -10.0 ( -29.9 , 0.00 )
pH 9.0 -58.7 ( -109 , -8.44 ) -49.5 ( -65.2 , -33.8 ) -79.0 ( -165.1 , 0.00 ) -15.7 ( -36.4 , 0.00 ) -45.0 ( -66.4 , -23.6 ) -26.4 ( -35.0 , -17.8 ) -19.5 ( -37.7 , -1.30 )
_R2 pH 7.5 0.9972 0.9918
pH 8.0 0.7345 0.9985 0.9990 0.9969 0.9978 0.9977 0.9993
pH 8.5-A 0.9815 0.9850 0.9323 0.9676 0.9956 0.9660 0.9946
pH 8.5 0.9591 0.9728 0.9803 0.9592 0.9865 0.9753 0.9773
pH 9.0 0.9907 0.9989 0.9722 0.9979 0.9979 0.9996 0.9984
Freundlich: Q = Kf·(Cf)(1/n) + bf
_Kf, L kg-1 pH 7.5 56.5 ( 37.9 , 75.1 ) 69.5 ( 48.0 , 90.9 )
pH 8.0 99.1 ( -19.1 , 217 ) 214 ( 105 , 323 ) 118 ( 76.8 , 160 ) 113 ( 33.4 , 192 ) 133 ( 75.0 , 190 ) 169 ( 97.2 , 241 ) 91.1 ( 61.0 , 121 )
pH 8.5-A 165 ( 77.5 , 252 ) 272 ( 71.2 , 474 ) 354 ( 87.5 , 620 ) 240 ( 31.2 , 449 ) 157 ( 68.4 , 246 ) 128 ( 54.9 , 201 ) 165 ( -15.2 , 346 )
pH 8.5 379 ( 202 , 555 ) 331 ( 86.8 , 574 ) 1000 ( 511 , 1489 ) 380 ( 173 , 586 ) 298 ( 142 , 453 ) 267 ( 123 , 410 ) 276 ( 169 , 384 )
pH 9.0 1000 ( 307 , 1693 ) 1000 ( 395 , 1605 ) 1000 ( 432 , 1568 ) 965 ( 370 , 1560 ) 712 ( 520 , 904 ) 702 ( 424 , 979 ) 1000 ( 148 , 1852 )
_bf, mg-P kg-1 pH 7.5 -57.4 ( -116 , 0.00 ) -66.2 ( -128 , -4.26 )
pH 8.0 -145. ( -440 , 0.00 ) -219 ( -386 , -51.7 ) -90.2 ( -175 , -4.98 ) -109 ( -283 , 0.00 ) -136 ( -249 , -23.7 ) -157 ( -279 , -36.0 ) -72.0 ( -140 , -4.40 )
pH 8.5-A -155 ( -305 , -4.07 ) -343 ( -652 , -33.2 ) -305 ( -671 , 0.00 ) -302 ( -649 , 0.00 ) -150 ( -310 , 0.00 ) -110 ( -258 , 0.00 ) -132 ( -423 , 0.00 )
pH 8.5 -403 ( -640 , -165 ) -289 ( -602 , 0.00 ) -855 ( -1346 , -364 ) -339 ( -596 , -81.7 ) -258 ( -486 , -30.8 ) -207 ( -399 , -14.9 ) -223 ( -366 , -79.6 )
pH 9.0 -766 ( -1499 , -33.5 ) -952 ( -1607 , -297 ) -981 ( -1606 , -356 ) -769 ( -1386 , -152 ) -678 ( -897 , -458 ) -621 ( -926 , -315 ) -802 ( -1682 , 0.00 )
_n pH 7.5 1.69 ( 1.53 , 1.84 ) 1.74 ( 1.58 , 1.89 )
pH 8.0 1.92 ( 1.22 , 2.62 ) 2.72 ( 2.16 , 3.27 ) 2.09 ( 1.84 , 2.33 ) 2.00 ( 1.55 , 2.44 ) 2.20 ( 1.87 , 2.53 ) 2.45 ( 2.06 , 2.84 ) 2.00 ( 1.79 , 2.20 )
pH 8.5-A 2.40 ( 1.94 , 2.87 ) 2.77 ( 1.94 , 3.61 ) 2.90 ( 1.95 , 3.85 ) 2.52 ( 1.69 , 3.36 ) 2.33 ( 1.85 , 2.80 ) 2.11 ( 1.71 , 2.51 ) 2.54 ( 1.47 , 3.60 )
pH 8.5 3.11 ( 2.48 , 3.73 ) 3.00 ( 2.04 , 3.96 ) 5.92 ( 4.04 , 7.81 ) 3.14 ( 2.38 , 3.91 ) 2.82 ( 2.22 , 3.42 ) 2.74 ( 2.14 , 3.35 ) 2.79 ( 2.34 , 3.23 )
pH 9.0 5.07 ( 2.93 , 7.22 ) 5.32 ( 3.34 , 7.29 ) 5.12 ( 3.39 , 6.85 ) 5.59 ( 3.37 , 7.81 ) 4.29 ( 3.66 , 4.92 ) 4.72 ( 3.64 , 5.80 ) 6.12 ( 2.67 , 9.57 )
_R2 pH 7.5 0.9970 0.9973
pH 8.0 0.9544 0.9899 0.9950 0.9835 0.9930 0.9928 0.9959
pH 8.5-A 0.9902 0.9822 0.9746 0.9744 0.9877 0.9879 0.9500
pH 8.5 0.9796 0.9349 0.9820 0.9633 0.9731 0.9615 0.9790
pH 9.0 0.9872 0.9907 0.9920 0.9852 0.9978 0.9946 0.9764
Langmuir: Q = (Smax·Kl·Cf)·(1 + Kl·Cf)-1 + bl
_Kl, 10-3 L kg-1 pH 7.5 3.89 ( 3.06 , 4.71 ) 4.36 ( 3.46 , 5.26 )
pH 8.0 6.00 ( 2.40 , 9.70 ) 10.8 ( 9.73 , 11.8 ) 7.37 ( 6.55 , 8.19 ) 6.27 ( 4.18 , 8.35 ) 7.45 ( 6.80 , 8.09 ) 9.00 ( 8.07 , 10.5 ) 6.31 ( 5.19 , 7.43 )
pH 8.5-A 9.26 ( 6.26 , 12.3 ) 10.7 ( 8.70 , 12.7 ) 20.0 ( 10.8 , 21.1 ) 10.2 ( 6.78 , 13.6 ) 8.49 ( 6.81 , 10.2 ) 7.51 ( 5.39 , 9.64 ) 10.3 ( 5.20 , 15.4 )
pH 8.5 11.2 ( 7.83 , 14.6 ) 13.4 ( 7.72 , 19.1 ) 30.0 ( 24.7 , 41.0 ) 14.0 ( 9.32 , 18.6 ) 10.0 ( 7.56 , 14.7 ) 11.7 ( 7.55 , 15.8 ) 11.2 ( 8.10 , 14.2 )
pH 9.0 71.2 ( 38.1 , 104 ) 36.1 ( 27.1 , 45.1 ) 29.8 ( 19.9 , 39.7 ) 46.5 ( 36.2 , 56.8 ) 24.1 ( 16.3 , 32.0 ) 28.8 ( 23.1 , 34.6 ) 55.6 ( 43.3 , 67.8 )
_bl, mg-P kg-1 pH 7.5 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 )
pH 8.0 -58.7 ( -221 , 0.00 ) -13.0 ( -38.1 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) -5.13 ( -26.8 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 )
pH 8.5-A 0.00 ( 0.00 , 0.00 ) -46.9 ( -105 , 0.00 ) -13.8 ( -129 , 0.00 ) -52.3 ( -161 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 )
pH 8.5 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 ) 0.00 ( 0.00 , 0.00 )
pH 9.0 -22.0 ( -212 , 0.00 ) -35.4 ( -125 , 0.00 ) -11.6 ( -131 , 0.00 ) -5.76 ( -86.2 , 0.00 ) 0.00 ( -110 , 0.00 ) 0.00 ( 0.00 , 0.00 ) -22.6 ( -102 , 0.00 )
_Smax, mg-P kg-1 pH 7.5 3019 ( 2681 , 3356 ) 3176 ( 2840 , 3511 )
pH 8.0 2886 ( 2264 , 3507 ) 2034 ( 1980 , 2088 ) 2525 ( 2407 , 2643 ) 2839 ( 2415 , 3264 ) 2399 ( 2331 , 2467 ) 2164 ( 2057 , 2271 ) 2342 ( 2160 , 2523 )
pH 8.5-A 2191 ( 1923 , 2460 ) 2406 ( 2279 , 2533 ) 2628 ( 2408 , 2847 ) 2696 ( 2433 , 2958 ) 2342 ( 2159 , 2525 ) 2600 ( 2000 , 2902 ) 1921 ( 1577 , 2265 )
pH 8.5 2643 ( 2382 , 2904 ) 2470 ( 2147 , 2793 ) 1976 ( 1873 , 2079 ) 2542 ( 2283 , 2802 ) 2700 ( 2402 , 2969 ) 2555 ( 2262 , 2848 ) 2586 ( 2353 , 2819 )
pH 9.0 2200 ( 2000 , 2444 ) 2072 ( 1951 , 2194 ) 2218 ( 2061 , 2376 ) 1973 ( 1870 , 2076 ) 2220 ( 2057 , 2382 ) 1881 ( 1780 , 1983 ) 1797 ( 1699 , 1895 )
_R2 pH 7.5 0.9951 0.9951
pH 8.0 0.9693 0.9990 0.9980 0.9842 0.9993 0.9968 0.9951
pH 8.5-A 0.9813 0.9961 0.9882 0.9884 0.9930 0.9870 0.9529
pH 8.5 0.9576 0.9137 0.9796 0.9451 0.9511 0.9416 0.9637
pH 9.0 0.9757 0.9925 0.9881 0.9932 0.9883 0.9904 0.9925
Notes: () = 95% Confidence Intervals; WGS-84 = World Geodetic System 1984 datum; R2 = R-squared; P = Phosphorus; X = Sorption Origin or x-intercept of models, minimum aqueous P-concentration required for
sediment P-sequestration; Kd = Linear partition coefficient; Kf = Freundlich partition coefficient; n = Freundlich correction factor; Kl = Langmuir relative binding strength; Smax = Sorption maximum of sorbent; bd,f,l = y-
intercept of Linear, Freundlich, or Langmuir models; pH 7.5 = Values in row correspond to batch experiment for sediment performed at pH 7.5 and ≈ 25°C; pH 8.0 = Values in row correspond to batch experiment for
sediment was performed at pH 8.0 and ≈ 25°C ; pH 8.5-A = Values in row correspond to batch experiment for UV-treated sediment was performed at pH 8.5 and ≈ 25°C ; pH 8.5 = Values in row correspond to batch
experiment for sediment was performed at pH 8.5 and ≈ 25°C; pH 9.0 = Values in row correspond to batch experiment for sediment was performed at pH 9.0 and ≈ 25°C; a X represents an average of all calculated X
values for a specific location; BSI = Batch sorption isotherm
Table 5. Coefficient values from Linear, Freundlich, and Langmuir sorption models fitted to Q (sediment sorbed P, mg-P kg-1) vs. Cf (equilibrium aqueous-P concentration, mg-P L-1) trends. Data obtained from BSI experiments which reacted
Utah Lake sediment and water collected from 7 locations across the lake. Experiments were performed at approximately 25°C with pH intervals at 7.5, 8.0, 8.5, and 9.0 for 24 hours. Initial aqueous-P concentrations for batch experiments
ranged from 0 to 760 mg-P L-1.
71

Location Provo Bay Provo
Site ID PB PV
Latitude,WGS-84 °N 40.1846 40.2357
Longitude,WGS-84
°W -111.7162 -111.7668
pH 8.46 8.46
Temperature, °C 24.4 24.4
ORP, rel. mV 221.4 221.4
Conductivity, µS
cm-1 2435 2435
C0, mg-P L-1 1.091 1.091
θ, L L-1 0.74 0.72
ρ, kg L-1 0.69 0.78
q, mL min-1 1.00 1.00
Nonlinear Kinetic Model: dS / dt = kf*(θ / ρ)*Cb - kb*S
b -2.96 ( -3.59 , -2.32 ) -4.52 ( -5.49 , -3.54 )
kf, min-1 0.482 ( 0.378 , 0.587 ) 0.779 ( 0.514 , 1.044 )
kb, min-1 0.003 ( -0.001 , 0.007 ) 0.003 ( -0.003 , 0.009 )
R2 0.7996 0.9640 Reactor
1 2 1 2
VR, mL 16.28 16.04 16.28 16.04
M, g 0.322 0.320 0.321 0.320
Notes: () = 95% Confidence Interval; WGS-84 = World Geodetic System 1984
datum; ρ = Bulk density; θ = Volumetric Water Content; ORP = Oxidation-
Reduction Potential; C0 = Influent P-concentration to stirred-flow reactor; q =
rate of flow; b = order of retention; kf = Forward retention rate; kb = Backward
retention rate; VR = volume of stirred-flow reaction chamber; M = mass of
sediment in reaction chamber; dS/dt = P-sorption over time; C = Effluent P-
concentration from reactor; S = P sorbed to sediment in reactor

Table 6. Parameters and coefficients for kinetics experiments using Provo (PV) and Provo
Bay (PB) sediment. For experiments, an input solution with a phosphorus (P)
concentration of ~1.1 mg L-1 in a lake water (pH 8.5, 24°C) background solution was
pumped into a reaction chamber (~16 mL) agitated with a triangular stir-bar (100 rpm) at
1 mL min-1 for 120 min. A 4.0 cm diameter filter membrane with a 0.45-μm pore size was
used to retain the sediment in the chamber. A fraction collector was used to collect effluent
samples at a 10 min interval. Sorption experiments were not followed by desorption
experiments, which is not standard for kinetic adsorption testing (Sun & Selim 2019).
Therefore, the results outlined here should be classified as scope or initial observations
of kinetic behaviors between PV and PB sediment.
72

12 Appendix C. Sampling Analysis Plan for Phosphorus Binding in Utah Lake

Joshua J. LeMonte1*, Gregory T. Carling1, Kevin Rey1, Stephen T. Nelson1

1Department of Geological Sciences, Brigham Young University, Provo, UT, USA.
*Lead PI, Corresponding author, [e-mail], 801-422-7037.

Updated 26 May 2021

*Add full text here prior to publishing final report. For now, it is best to reference the SAP
document separately to keep MS Word happy.
73