HomeMy WebLinkAboutDWQ-2024-008825MEMO
To: ULWQS Science Panel
Cc: Scott Daly, Utah DEQ
From: Tetra Tech
Date: 2022-07-29
Subject: ULWQS Atmospheric Deposition Synthesis
1.0 INTRODUCTION AND BACKGROUND
A summary and chronology of efforts to quantify atmospheric deposition to Utah Lake is provided in “ULWQS
Science Panel Update to Steering Committee Regarding Engaging with All Potential Sources of Information to
Address Initial Charge Questions” (ULWQS Science Panel, 2020). Briefly, the Wasatch Front Water Quality
Council (WFWQC), led by Science Panelist Theron Miller, conducted an atmospheric deposition sampling
campaign in the areas immediately surrounding Utah Lake. The Science Panel (SP) reviewed the Sampling and
Analysis Plan written by WFWQC and additionally recommended a literature review be done to summarize
atmospheric deposition information relevant to Utah Lake. The latter effort was conducted by Science Panelist
Janice Brahney and underwent review by the SP. In the interim before the WFWQC Sampling and Analysis Plan
went into practice, the SP recommended to use the atmospheric deposition estimates presented in Brahney
(2019) be used for modeling until updated estimates became available. Differences in SP perspective on what
should be incorporated into the Sampling and Analysis Plan led to a third-party review by David Gay. The
recommendations put forth in the third-party review included:
● Updating sampler design to be more consistent with National Atmospheric Deposition (NADP) guidelines
and practices
● Sample screening to exclude insects
● Organized and repetitive quality assurance and quality control (QA/QC) plan (suggestions provided)
● Bird deterrents
● Meteorological measurements
● Triplicate samples at one sampling location
● Recommendation for wet/dry buckets rather than bulk collectors
In response to SP and third-party feedback, an updated Sampling and Analysis Plan by WFWQC was developed,
detailing:
● Sampler design
● Sample locations
● Sample handling
● Field log book
● Experiments to characterize insect contribution
● Equipment cleaning
● QA/QC
Following the implementation of the updated Sampling and Analysis Plan, WFWQC presented results from
atmospheric deposition samplers as well as estimates of atmospheric loading to Utah Lake. The SP is currently
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engaged in a review of the data and results generated from this effort. The current document synthesizes the
progress made in reviewing both new and existing atmospheric deposition data sources for Utah Lake.
Per ULWQS Uncertainty Guidance (Tetra Tech 2020), we comparatively evaluate sources of evidence relating to
atmospheric deposition of nitrogen (N) and phosphorus (P) onto the surface of Utah Lake and determine overall
confidence in final estimates (Figure 1). Evaluating evidence comprises four considerations:
● Type: derivation of evidence
● Amount: quantity of independent evidence types
● Quality: rigor with which the evidence was derived
● Agreement: how results or conclusions among lines of evidence differ or concur
Together, these four considerations can be combined to evaluate overall confidence.
2.0 OBJECTIVES
A single estimate of atmospheric deposition of N and P is needed as an input for the Utah Lake Nutrient Model.
Additional variability in atmospheric deposition can be explored in the model following calibration. Therefore, the
goal of this document is to recommend a single atmospheric loading estimate for both N and P, with a
narrow range that would account for interannual variability.
A recommendation for the atmospheric deposition estimate to Utah Lake incorporates several calculations, all of
which introduce potential uncertainty in observations as well as methodology. The objective of this synthesis
document is to review currently available information on atmospheric deposition to Utah Lake and develop
recommendations on how to determine:
1. Areal fluxes of nutrients (mass per unit area per unit time)
2. Attenuation of atmospheric deposition from the shoreline to the lake center
3. Loads, which combine areal fluxes and attenuation (mass per unit time)
4. Speciation of the chemical forms of N and P
Figure 1. Matrix that evaluates confidence from evidence and agreement (Tetra Tech 2020).
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3.0 SUMMARY AND CONFIDENCE EVALUATION OF FLUXES AND LOADS
All existing lines of evidence were reviewed and, where possible, summarized for areal fluxes (mg m-2 wk-1) as
well as estimated loads for Utah Lake (metric tons yr-1). In some instances, conversions were calculated to enable
comparisons among lines of evidence (e.g., imperial tons converted to metric tons, areal fluxes per year or per
day converted to per week). The type of evidence and any details about the derivation of the evidence were also
summarized. Five types of evidence were identified:
● Direct, unscreened: data collected by atmospheric deposition samplers near the lake, contamination
sources not removed by physical screening or by data QA/QC screening.
● Direct, screened: data collected by atmospheric deposition samplers near the lake, contamination
sources removed by physical screening or by data QA/QC screening.
● Local & regional dust: estimates derived from mathematical conversions from local and regional dust
deposition measurements with assumptions about nutrient content of the dust. Considered a
“constraining analysis.”
● Mass balance: estimates derived by difference from a nutrient mass balance of Utah Lake. Considered a
“constraining analysis.”
● Global review: literature-derived fluxes from ecosystems worldwide, intended as a tool for comparison.
3.1 AREAL FLUXES
Comparisons among areal fluxes of TP among studies and types of evidence are presented in Figure 2. Note that
areal fluxes of N were not calculated because N fluxes were collected separately as ammonium and nitrate,
precluding direct comparisons across constituents. Note the quality of these lines of evidence differs (Table 1).
Figure 2. Summary of areal fluxes of TP derived from direct measurement, global and regional dust
measurements, and a global review. Points represent mean estimates, and lines represent ranges.
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3.2 ATTENUATION
Nutrient loads may be reduced moving from a shoreline sampling location to mid-lake, a process referred to as
attenuation. Attenuation of nutrient loads across Utah Lake, or lack thereof, can be quantified using several
different methods. Given an estimate of areal flux at or near the lake shoreline, an areal flux at any given location
in the lake can be estimated through:
Mathematical averaging across monitored locations with no attenuation. This approach is simplest and assumes
no attenuation moving from the shoreline to the mid-lake. It can be assumed that this approach would represent
an upper bound on the maximum atmospheric deposition to Utah Lake. This approach is presented as a
simplified conversion from areal flux to load by Science Panelist Mitch Hogsett (2022), although this approach is
not recommended over a more spatially explicit approach in the document but rather as an upper bound.
Similarly, Science Panelist Greg Carling (2022) calculated a conversion from local dust measurements that
assumes no attenuation over the lake, representing an upper estimate of possible loading. Analysis by Wood
Miller (2021) also averaged fluxes across sites to compute loads.
Use kriging to spatially interpolate between locations (assumes no attenuation). This approach, while spatially
explicit, does not assume any attenuation moving from shoreline to mid-lake but rather computes a spatial
interpolation between shoreline sites across the lake. This approach was used by Olsen et al. (2018) with an
exponential variogram and a range of 1000 m as well as Barrus et al. (2021) with a standard variogram.
Assume local fluxes at the edge of the lake, which attenuate to low values at a given distance moving toward mid-
lake. In addition, regional background fluxes may be assumed for in-lake locations where local fluxes are minimal.
This approach was used by Brahney (2019) with a first order decay equation with the zone of influence
decreasing to 10% at ranges of 200, 400, and 600 m and regional loading rates applied to the remainder of the
lake area. This approach was also used by Reidhead (2019) with a simple kriging approach with a linear
decrease toward a single point of zero deposition in the center of the lake.
A potential advancement to more accurately quantify attenuation of atmospheric nutrient fluxes to the lake would
be to physically measure fluxes at an in-lake location. This approach comes with challenges, including the
physical placement of a sampler in the middle of a lake and ensuring the sampler captures atmospheric nutrient
sources rather than other sources such as lake-derived spray and aerosols and other sources of contamination.
To pursue this approach, a sampler located in the main basin of Utah Lake on Bird Island was used by Barrus et
al. (2021). The study observed higher areal fluxes at the Bird Island site compared to shoreline sampling sites.
This result was unexpected and indicates a nutrient source to the Bird Island sampler beyond the flux at shoreline
samplers. Third party review by David Gay (Miller 2022) indicated that validation of these results would involve (a)
sampling at an additional shoreline location hypothesized to be the local source of atmospheric nutrients to the
Bird Island location (from the northwest shore which has not been sampled), and (b) QA/QC documentation and
continued sampling to validate that the fluxes observed at the Bird Island samplers are from atmospheric sources
rather than in-lake or bird sources.
3.3 LOADING
Comparisons among atmospheric loads of TP, TN or dissolved inorganic N (DIN) to Utah Lake are presented in
Figures 3 and 4. Note that the direct estimates of load encompass differences in methodology for measuring
fluxes as well as differences in methodology in converting fluxes to load, namely estimation of attenuation from
shoreline to mid-lake. Note the quality of these lines of evidence differs (Table 1).
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Figure 3. Summary of TP load estimates to Utah Lake derived from direct measurements, local and regional dust
measurements, and mass balance analysis. Points represent mean estimates, and lines represent ranges.
*Loads from Miller 2021 are not attenuated.
Figure 4. Summary of TN load estimates to Utah Lake derived from direct measurements, and local and regional
dust measurements. Points represent mean estimates, and lines represent ranges. *Loads from Miller 2021 are
not attenuated. +Loads from Brahney 2019 are attenuated.
*
*
*
*
*
+
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3.4 SPECIATION
Total loads of N and P are comprised of different chemical forms, which differ in their reactivity and bioavailability.
The bioavailable fraction of the TP load, soluble reactive phosphorus (SRP), has been approximated in several
studies. For example, Brahney (2019) estimates 75% of the P in urban dust and 34% of the P in regional dust is
bioavailable. Direct measurements from Reidhead (2019) found 37% of TP was comprised of SRP, and Miller
(2021) found 32% of TP was comprised of SRP. SRP was measured during the effort by Barrus et al. (2021),
however it was indicated that the quality assurance of these samples was not sufficient to evaluate bioavailability
from the results of that study. Loads of ammonium and nitrate could be calculated from previous direct estimates
of DIN fluxes. Atmospheric deposition inputs to the Utah Lake Nutrient Model will include organic N, ammonium,
nitrate, organic P, and SRP, so any additional parsing of chemical species will be helpful to inform model
development and calibration.
3.5 CONFIDENCE EVALUATION
A summary of evidence types, quality, amount, and agreement is provided in Table 1. This evaluation is intended
to be overarching and encompass both flux and load estimates. Differences within each line of evidence are
attributed to (a) differences in methodology from sampler design to QA/QC to assumptions about attenuation, and
(b) environmental variability in fluxes.
Table 1. Confidence evaluation of atmospheric deposition evidence for Utah Lake.
Study Evidence Type Quality Amount Agreement
Hogsett 2022
Barrus et al. 2021
Miller W. 2021
Olsen et al. 2018
Direct, screened
and/or contaminated
samples removed
Hogsett 2022:
2020 measurements are
based on SP-recommended
sampler design and data QA
Barrus et al. 2021:
2020 measurements are
based on SP-recommended
sampler design but include
unscreened samples
January-May.
Miller W. 2021.
Uses an unscreened
sampler, though outlier
removal was tested. Raw
data were not available for
the SP to evaluate.
Olsen et al. 2018.
Uses an unscreened
sampler, though
contaminated sample
removal was tested. Raw
data were not available for
the SP to evaluate.
4 Spans the range of
other estimates (except
direct, unscreened)
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Study Evidence Type Quality Amount Agreement
Brahney 2022
Brett 2022
Mass balance Medium
(conversion from Utah Lake-
specific data)
2 Consistent with direct,
screened estimates
Brahney 2019
Brahney 2022
Carling 2022
Dust measurements Medium
(conversion from direct local
& regional data)
3 Consistent with direct,
screened estimates
Brahney 2019
Brahney 2022
Global review Limited
(Globally comprehensive but
not Utah Lake-specific)
2 Consistent with direct,
screened estimates
Olsen et al. 2018
Reidhead 2019
Barrus et al. 2021
Miller W. 2021
Hogsett 2022
Direct, unscreened Limited
(recommended that
contaminated samples be
left out of estimates, per SP
discussion and David Gay
review)
5 Higher than other lines
of evidence
4.0 RECOMMENDATION
Overall, estimates of atmospheric deposition fluxes and loads are variable within and across lines of evidence.
The variability can be attributed to temporal variability in deposition rates as well as methodological differences
among studies including sampling and mathematical assumptions about temporal and spatial variability.
Statistical comparisons of directly sampled data, apart from areal flux and load point estimates and ranges, are
not possible given the lack of raw data availability among studies. However, there are areas of overlap in
atmospheric deposition estimates, both within and across evidence types. This agreement may lead to higher
confidence in atmospheric loading estimates. Specifically, there is consistency in the range of atmospheric fluxes
and loading between direct, screened measurements and constraining analyses (local & regional dust and mass
balance). Therefore, there is high confidence that the true rate of atmospheric deposition to Utah Lake
falls within the range estimated by these evidence types.
The recommendation for areal flux is to calculate estimates based on direct measurements of screened samples
that explicitly exclude sources of contamination. It is recommended that estimates generated from the most recent
Sampling and Analysis Plan (i.e., those generated in 2020) be prioritized because they incorporate the
recommendations from the SP and the third-party review.
The recommendation for attenuation is to exclude Bird Island data for the time being while the SP awaits
validation data from shoreline samplers and/or extensive QA/QC of sampler data to support increased deposition
rates in the mid-lake beyond rates observed at current shoreline samplers. In the meantime, a spatial interpolation
or decay equation approach is recommended to use while hypothesis testing for Bird Island data continues. An
option would be to assume zero attenuation of areal fluxes as the upper bound of potential load, and an
attenuation approaching regional background levels at the mid-lake as a lower bound.
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The recommendation for load is to use the combined recommendations of areal flux and attenuation over the
area of Utah Lake. For an upper bound, non-attenuated loads calculated from the recommended areal fluxes may
be considered alongside the upper bounds of constraining analyses. For a lower bound, attenuated loads
calculated by Brahney (2019) may be considered. For a middle estimate, an estimate between the lower and
upper bounds may be chosen, or a new attenuation factor calculated from areal fluxes (Table 2).
Table 2. Recommended loads to be considered in determining the upper, lower, and middle bound atmospheric
deposition estimates to Utah Lake.
Constituent Load (tons/yr) Context Source
TP
42
Direct measurement
SP-recommended sampling design
No attenuation
Hogsett 2022, calculated
from Barrus 2021
60 Mass balance
Constraining analysis Brett 2022
57.5 Local & regional dust conversion
No attenuation Carling 2022
33 Mass balance
Constraining analysis Brahney 2022
20 Local & regional dust conversion
Constraining analysis Brahney 2022
5 Local & regional dust conversion
Attenuation Brahney 2019
TN
251
Direct measurement
SP-recommended sampling design
No attenuation
Hogsett 2022, calculated
from Barrus 2021
153-288 Community Multiscale Air Quality Model Brahney 2019
Finally, to estimate speciation of nutrient loads, it is recommended to apply a proportional factor to total loads to
calculate SRP (approximately 1/3; see section 3.4) and to calculate ammonium and nitrate loads from directly
sampled data.
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5.0 NEXT STEPS
It is recognized that atmospheric deposition work on Utah Lake is an ongoing process, with improvements and
hypothesis testing continually underway. From previous reports and SP discussions, the following items are noted
as areas of continued study based on previous SP and third party recommendations:
● Dust: what is the magnitude of areal dust fluxes to Utah Lake, and what is the N and P content of this
dust?
● Bioavailability: What are the total and relative magnitudes of bioavailable N and P fluxes compared to
total fluxes?
● Discriminating between local and regional sources of nutrient deposition
● Validation of the Bird Island hypothesis via source characterization. Given higher nutrient fluxes at the
Bird Island site than the shoreline sites, it is hypothesized that either (a) shoreline fluxes at the northwest
side of the lake are higher than other observed fluxes, or (b) there are non-atmospheric sources of
nutrients making their way into the samplers at Bird Island. Additional sampling and QA/QC efforts have
been suggested to explore one or both of these hypotheses.
● Additional atmospheric deposition modeling through models such as AERMOD and AERSCREEN
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6.0 APPENDIX: EVIDENCE REVIEW AND SUMMARIES
AD Chronology and comments (SP 2020)
Note: summary of SP history on estimating AD to Utah Lake
Correspondence with Gus Williams
Note: email chain between SP subgroup and Gus Williams
AD 2021 Summary V8_DAG (Miller T 2022)
Content summary
● Summary of Miller, Reidhead, Barrus, and Olsen studies. No new data presented
● Includes review from David Gay. Unclear whether the comments included are the entire review (includes
comments such as “see note 6” which are not traceable)
Relevant methodological details
● Comments from David Gay:
o Precipitation weighted averaging: “I guess my approach would have been to use the data as
measured for every week that you have both precipitation and concentration over the three years.
Then, for the weeks where there are no concentration measurements but you know how much it
rained, i would calculate the PWM concentration for that season, and multiply that seasonal
PWMC times the actual rain value. This is think, would give you the best “record” of deposition,
and then flux over three years.”
o Bird Island samples having higher AD than shoreline sites: “One way you might be able to show
that this is a real signal goes something like this. The Lakeshore sampling site is not capturing the
urban “plume” moving over the lake (plume is to the north). So put another shore line sampler
north of Lakeshore where it would capture these high samples. Not certain that will work, but if
you can show these high samples on land, then you have it” “As you know, this could be a game
changer. So I would again recommend beefing up the QA information for the Bird Island sampler.
Prove to the reader that you have QA info that shows these samples are valid. And I would also
recommend that you say you will continue these measures out into the future, for further proof
these are real.”
AD Report Addendum (Miller T 2022)
Content summary
● N:P ratios in deposition (by mass)
● Summary of precipitation weighting
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● Updated table of AD estimates across studies
Findings
● N:P ratios across sites: 9.2-21.9 (avg 12.95) from Wood Miller data
● N:P wet ratios across sites: 6.3-14.8 (avg 8.6) from Olsen data
● N:P dry ratios across sites: 0.4-4.2 (avg 2.3) from Olsen data
● Re-calculation of Olsen and Reidhead data to calculate up to 12 months of data:
o 10-430 metric tons TP (Olsen)
o 57-570 metric tons TIN (Olsen)
o 193 metric tons TP (Reidhead)
o 637 tons TIN (Reidhead)
Relevant methodological details
● Wood Miller precipitation weighting approach is detailed: weekly precipitation/avg precipitation by week
across the year = weighting factor. Appears to be different than a traditional precipitation weighting which
is a volume-weighted concentration (e.g., Grimshaw and Dolske 1999). Confirmed by David Gay review:
“I guess my approach would have been to use the data as measured for every week that you have both
precipitation and concentration over the three years. Then, for the weeks where there are no
concentration measurements but you know how much it rained, i would calculate the PWM concentration
for that season, and multiply that seasonal PWMC times the actual rain value. This is think, would give
you the best “record” of deposition, and then flux over three years.”
● Details distance of Saratoga Spring site to gravel pit, which is farther away than gravel pit to lake
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AD Review, Mitch DRAFT 7-11-2022 (Hogsett 2022)
Content summary
● Re-analysis of Barrus data
Findings
● Samplers sometimes left out for 2+ weeks at a time
● Data QA issues, where SRP>TP (6-17% of observations 2017-2020 across sites)
● Concerned about QA/QC if wet/dry sampling mechanism was broken
● Large events dominate monthly flux estimates, particularly for NH4, SRP, TP, and PP 🡪 points to organic
matter signal
● Bird Island sampler has four months of data to approximate spatial distribution across the lake.
Deposition at Bird Island is higher than at the lakeshore.
● AD TIN load:
o Baseline 2019 (unscreened): 608 metric tons/yr
o Event 2019 (unscreened): 808 metric tons/yr
o Total 2019 (unscreened): 1415 metric tons/yr
o Baseline 2020 (screened): 251 metric tons/yr
o Event 2020 (screened): 142 metric tons/yr
o Total 2020 (screened): 393 metric tons/yr
● AD TP load:
o Baseline 2019 (unscreened): 89 metric tons/yr
o Event 2019 (unscreened): 250 metric tons/yr
o Total 2019 (unscreened): 339 metric tons/yr
o Baseline 2020 (screened): 42 metric tons/yr
o Event 2020 (screened): 51 metric tons/yr
o Total 2020 (screened): 93 metric tons/yr
Relevant methodological details
● AD loads calculated only by averaging four sites, assuming uniform fluxes across lake and not using
Kriging. Noted that this is not the appropriate calculation but simply a comparison
● Used cumulative summing to calculate fluxes and loads
● Assumed TP was correct when SRP>TP
● Unknown when screens were installed in 2020. Current estimates do not incorporate specific date of
screening
● Noted dates and locations of “events” and the constituents with spikes
Barrus 2020_Thesis (Barrus 2021)
Note: same content as Barrus et al. 2021
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Barrus 2021_Nutrient AD on Utah Lake (Barrus et al. 2021)
Content summary
● Tested differences between previously published methods which had received criticism and new methods
● Collection table height
● Screened buckets
● AD spatial patterns, attenuation across lakes
Findings
● No attenuation moving from offshore to mid-lake
● No difference from table height
● Unscreened AD had up to 3-fold higher nutrient concentrations than screened AD
● TP deposition: 262 tons (2019), 133 tons (2020)
● DIN deposition: 1052 tons (2019), 482 tons (2020)
● Note: 2019 results include unscreened samplers that included insects
● Areal TP deposition: 1.66-102.4 mg/m2/wk unscreened, 3.09-11.25 mg/m2/wk screened
● Areal DIN deposition: 5.72-414.19 mg/m2/wk unscreened, 4.28-35.44 mg/m2/wk screened
Relevant methodological details
● Samplers filled with 3 L water, similar to
o Jassby et al. 1994: Lake Tahoe: buckets filled with 4 L distilled water, left for one week or until
precipitation occurs. If the latter, collected within 24 h
o Anderson and Downing 2006: Iowa: tested dry deposition samplers with and without 3 L of
distilled, deionized water. Contaminated samples included samples collected longer than a week
and samples with contaminants such as insects and bird droppings. NH4 was higher in buckets
filled with water by two orders of magnitude w/ hypothesized mechanism of NH4 sources passing
rapidly into water from atmospheric gaseous phase
● Screens added to samplers in 2020, previous years outliers were removed to account for insects. Outliers
defined as 1 mg/L for TP of 8 mg/L for DIN
Carling_UtahLakePdeposition (Carling 2022-03-21)
Content summary
● Comparison of Miller 2022 and Brahney 2019 AD rates to Goodman et al. 2019
● Justification for why Miller loads may be overestimated
Findings
● AD TP load to Utah Lake based on urban dust deposition rate (Goodman et al. 2019): 57.5 tons TP/yr
● Dust deposition fluxes 0.5-3.8 g/m2/month
● Reidhead (2019) and Barrus (2020) seem unrealistically high
● Brahney (2019) may underestimate AD due to decay equation
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Relevant methodological details
● Used published dust flux data from Goodman et al. 2019 from Wasatch Front
o Provo, Salt Lake City, Ogden, Logan
o 2-month deployments 2015-2018
● Conversion to P deposition: measurements of P in dust from local, playa, and urban sources. Used high
end of concentration at 5000 mg/kg
● Compared against Brahney estimates, there’s debate about the best decay equation which may have
biased these estimates low
● Includes review from Gus Williams
Comparison with NADP nitrogen (Carling 2022)
Content summary
● Comparison of Barrus DIN loading data with nationwide NADP data
Findings
● Nationwide, N deposition at NADP sites ranged from 0-8 kg/ha per year.
● Closest NADP site is an agricultural site in Cache Valley with deposition of 2.3 kg/ha
● Conversion of Barrus tons to Utah Lake to kg/ha: 13.8 kg/ha per year, 6x nearest NADP site
Methodological details
● Per Stensland et al. (https://www3.epa.gov/ttnchie1/conference/ei10/ammonia/stensland.pdf), NADP sites
in Logan and Green River (Cache Valley) are located near livestock areas and municipal waste treatment
lagoons, with potential stagnation of air around sites due to placement in basin
Constraints on AD deposition 2022 (Brahney 2022)
Content summary
● Comparison of AD rates to Utah Lake with global rates of AD
● Constraining AD estimates with local dust deposition rates and dust P content
● Constraining AD estimates with sediment accumulation rates
● Constraining AD estimates with mass balance
Findings
● 164 TP rates collected worldwide: 49 mg/m2/yr
● Estimate of AD to Utah Lake based on bounds of dust P content and dust deposition rates: 20 tons P/yr
● Estimate of AD to Utah Lake based on sediment accumulation rate and sediment P content: 22 tons P/yr
Relevant methodological details
● Converted tons P per year to the lake to mg P/m2/yr
● 350 tons P/yr equates to 1000 mg P/m2/yr, 9.5x SD above the global mean
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● Converted between P deposition and dust deposition using 0.1-0.3% as a conversion. Compared output
across AD tons estimates and dust percentages to average dust deposition rate of 40.5 g/m2/yr.
● Using sedimentation rates and sediment dry density from cores, determine plausible AD deposition rates
Estimating total and bioavailable nutrient loading… (Brahney 2019)
Content summary
● Summary of the state of knowledge on dust deposition, composition, and effects on aquatic systems,
specifically for Utah Lake
● Literature review on dust, aerosol, and wet atmospheric deposition of N and P
Findings
● TP deposition 2-9 metric tons/yr (80% of bootstrapped estimates), 5.0 ± 3.1 metric tons/yr
● Bioavailable P deposition 0.5-7.9 metric tons/yr, probable range 2-2.5 metric tons/yr
● TN deposition 153-288 metric tons/yr
● Literature evidence: local AD sources attenuate quickly because they do not emit high into the
atmosphere
● Literature findings
o Dust deposition rates in northern Utah: 24.7-57.7 g/m2/yr, avg 40.5
o Dust deposition rates in desert California and Nevada: 3.92-20.98 g/m2/yr
o Largest recorded urban deposition rates 600 g/m2/yr (Kuwait City)
o Global mean TP, TDP, and SRP deposition rates of 27, 19, and 14 mg P m-2 yr-1
o Mixed urban-forested catchment SRP and PO4 deposition rates of 19.6 and 25.6 mg P/m2/yr
● Bioavailability of TP deposition estimated as 75% of urban dust, 34% of regional dust
Relevant methodological details
● First order decay equation applied according to Lake Tahoe study: zone of influence decreased to 10% at
200, 400, and 600 m, and regional loading rates applied to the remainder of the lake area
● Bootstrap method for regional and local P deposition 🡪 frequency diagram of deposition rates
● Regional data used:
o Regional dust deposition in northern Utah (n = 12) 1.4-15.6 g/m2/yr, avg 6.2
o Regional TP concentrations in dust (n = 19) 0.56-5.08 mg/g, avg 1.56
o Urban/local dust deposition in northern Utah (n = 7)
o Urban/local P concentrations (n = 3)
● Mean urban dust TP deposition from northern Utah: 152.3 mg TP/m2/yr
● Mean urban dust from multiple regions: 93.6 mg TP/m2/yr
● N deposition rates estimated from Community Multiscale Air Quality Model
`
GlobalPb-combined
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Note: appendix to Constraints on AD deposition 2022 (table of global estimates)
Miller 2021_Atmospheric Bulk Nutrient Deposition Report (Miller W 2021)
Content summary
● 4 sections
o Interim report on nutrients in precipitation on Utah Lake, Wood Miller
o Updated report review, David Gay
o Revised report responding to comments, Wood Miller
o Revised report comments, David Gay
Findings
● Note: all rates are imperial tons, need to be converted to metric tons
● 2017-2019 AD loading rates for TP
o Non-weighted all TP data 74-83 tons/yr
o Precipitation-weighted all TP data 73-115 tons/yr
o Number of samples-weighted all TP data 75-82 tons/yr
o Non-weighted TP <5 mg/L removed 46-53 tons/yr
o Precipitation-weighted TP <5 mg/L removed 49-76 tons/yr
o Number of samples-weighted TP <5 mg/L removed 49-52 tons/yr
o Non-weighted TP <1 mg/L removed 23-27 tons/yr
o Precipitation-weighted TP <1 mg/L removed 29-41 tons/yr
o Number of samples-weighted TP <1 mg/L removed 26-29 tons/yr
● 2017-2019 AD loading rates for TN
o Non-weighted all TN data 283-310 tons/yr
o Precipitation-weighted all TN data 320-451 tons/yr
o Number of samples-weighted all TN data 314-345 tons/yr
o Non-weighted TN <10 mg/L removed 212-232 tons/yr
o Precipitation-weighted TN <10 mg/L removed 269-344 tons/yr
o Number of samples-weighted TN <10 mg/L removed 242-288 tons/yr
Relevant methodological details
● Raw data provided as mg/L
● TP censored at 1 and 5 mg/L, TN censored at 10 mg/L. Unclear why these thresholds were chosen
● Precipitation weighting was not used for individual samples. 3 years were combined by week and the
average, then precipitation-weighted value calculated by weekly precip/avg weekly precip. Also calculated
a “number of samples” weighted average
● Years were combined by week
● David Gay review
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o Precipitation collectors are not the best collectors for wet, dry, or bulk collection
o Assumes chemical analyses was done with proper QA
o Samplers could be prone to evaporation and contamination
o QA between sample collection is unclear (cleaning?). Miller states NWS cleans out samplers
“now and then” and collection tubes and funnels are cleaned “quite well” when samples are
collected
o Unclear if funnels are removed during winter
o Arithmetic averages was used to estimate deposition flux, should be precipitation-weighted
o Best fit trend lines are not recommended for 3 years of data
o OP/TP ratio and TN are high in Mosida – could be something other than dust storms
o TN deposition is in line with NADP rates
o Suggest comparing outlier samples with regional independent dust measures
Miller 2021_Comparing bulk deposition… (Miller W 2021)
Note: 6 months of raw data presented in tables and figures. Assume this is a subset of the data presented in the
Miller 2021 full report
Olsen 2018_Measuring and calculating current atmospheric… (Olsen et al. 2018)
Content summary
● AD estimates generated from data collected in NADP-style samplers
Findings
● TP deposition: 8-350 metric tons/8 months, 1.26-31.38 mg TP/m2/d (avg 8.10)
● DIN deposition: 46-460 metric tons/8 months, 1.59-36.06 mg N/m2/d (avg 10.23)
● High end of results includes contaminated samples, low end excludes contaminated samples
● Sites had differences in timing and magnitude of AD spikes
Relevant methodological details
● Some sites not NADP-compliant
o 3 sites have irrigated fields within 20 m
o 1 site has a gravel driveway within 25 m
o 1 sites has a parking lot within 60 m
● Samples considered contaminated if dry/wet overlapped, sampler malfunction, samples with bird
droppings, insects, algal growth, and samples >1 week
● Spatial interpolation: simple kriging with exponential variogram with range of 1000 m
Olsen 2018_Thesis (Olsen 2018)
Note: same content as Olsen et al. 2018
18
Reidhead 2019_Thesis (Reidhead 2019)
Content summary
● Soil samples taken around Utah Lake
● AD samples taken w/ same methodology as Olsen
Findings
● AD of SRP: 57.9-58.9 tons/7.5 months, 1.26-12.90 mg/m2/week
● AD of TP: 153-163 tons/7.5 months, 3.31-46.97 mg/m2/week
● AD of NO3: 118.3-123.6 tons/7.5 months, 9.92-19.38 mg/m2/week
● AD of NH4: 386.9-382.5 tons/7.5 months, 24.20-72.20 mg/m2/week
Relevant methodological details
● Sampling occurred once per week except in colder months (decrease to once every two weeks)
● 5 sampling sites
● Insects were removed from samplers, but those samples were included in analysis. Contaminated
samples were significantly different than uncontaminated samples
● Spatial interpolation: simple kriging with linear decrease toward a single point of zero deposition in the
center of the lake
Sediment P constraints on external phosphorus inputs ot Utah Lake (Brett 2022)
Content summary
● Mass balance of P for Utah Lake
● Uncertainty in TP AD, so can use observed Utah Lake sediment accumulation to back-calculate
reasonable AD
Findings
● Sediment accrual rate estimated at 226 metric tons P/yr (225 ± 110 from bootstrapping)
● To match sediment accrual, which balances watershed + WWTP + AD inputs – Jordan River output, AD
would be 60 metric tons/yr (0-160 metric tons from mean ± SD)
Relevant methodological details
● Estimating sediment P accrual
o Sedimentation rate: 1.0, 1.7 and 2.6 mm/yr from 3 cores
o Sediment dry weight conversion (n = 17): 0.580 ± 0.110 g/cm3
o Surface area of lake: 340 km2
o Used mean value for each constituent
UL_sediment_P_Accrual_w_uncertainty
Note: excel workbook to accompany Brett 2022
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Utah Lake TP and Dust Fluxes (Hogsett 2022)
Content summary
● Exploration/review of results from Miller 2022
● Discussion of methodological review of Barrus study
Findings
● If TP loading was all dust, at 300 tonnes/yr TP there would be 0.4-1.1 kg dust/m2/yr
● Assuming a sedimentation rate of 1-1.25 mm/yr in Utah Lake, large dust loads may contribute up to 100%
of sediment flux
Relevant methodological details
● Converted tonnes/yr back to mg TP/m2/yr
● Converted TP to dust using Carling et al. 2017 concentrations of local dust: 700-1800 mg TP/dry kg
● Estimated annual sediment depth flux
● Barrus review
o Organic debris should be removed from samples as in Olsen
o Solids should be characterized via TSS and VSS analysis
o Screened samples have lower concentrations than unscreened
Williams 20221_Utah Lake atmospheric deposition… (Williams et al. 2021)
Content summary
● Summary of Barrus et al 2021 and Olsen et al. 2018
● Appendix A: statistical analysis by David Richards
● Appendix B: detailed description of geostatistical methods
Findings
● Appendix A
o TP and DIN in high and low samplers was not significantly different
o Screened samplers had higher TP, SRP, and DIN than unscreened
o SRP was higher in high table than low table
o TP mg/m2/week 2.94-10.36 (95% CI 2.06-14.19) May-October
o SRP mg/m2/week 0.72-5.80 (95% CI 0.50-10.08) May-October
o DIN mg/m2/week 3.45-29.56 (95% CI 2.14-45.53) May-October
o Bird Island deposition rates for TP, SRP, DIN were higher than shore sampling sites
o Recommended using both Utah Lake and Great Salt Lake TP and DIN data to estimate AD in
Utah Lake due to non-significant difference among concentrations
o Alternate spatial approaches
● Appendix B
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o Alternate methodologies of kriging and variogram approaches for spatial modeling (no results
presented)