EDO-2024-000052

2022 Monitoring
Activities at the
Utah Inland Port
P R E P A R E D B Y Utah Department of Environmental Quality
for the Utah Legislative Management Commiee
and Inland Port Authority Board
UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |2 of 24Introduction
Pursuant to Utah Code 19-1-201, the following report provides a summary of stormwater
and air quality monitoring data collected by the Utah Department of Environmental
Quality (DEQ) within the statutorily dened area of Utah Inland Port (UIP) Authority.
Data collected by DEQ through 2023 will be used to form the baseline conditions for the
UIP. Information presented in this report is intended as an overview of the monitoring
locations, methods used, and results of years one and two of monitoring. This rst and
second year data should not be used to dene or make inferences regarding the current
baseline conditions until more data and information can be collected. Multiple years of
quality data are needed to meaningfully assess any impact of the UIP on air and water
quality.
Section 1: Stormwater Monitoring
Background
This section of the report, prepared by the Division of Water Quality (DWQ), presents the
data collected during the rst two years of our investigation of the effects of stormwater
from the UIP on water quality. Building on the data collection in 2021, the additional
stormwater data enhances DWQ’s ability to discern patterns, compare sites undergoing
various stages of development, and draw conclusions regarding potential land-use
impacts. Furthermore, this report should inform future decision-making regarding the
effectiveness of best management practices (BMPs) toward mitigation of stormwater
pollution, as well as designing future stormwater monitoring plans.
Monitoring Locations and Associated Catchments
The objective of this report is to assess the condition of stormwater quality before, during
and after UIP development through the analysis of chemical data including nutrients,
metals and physical parameters,collected at six monitoring locations (Figure 1). Samples
were collected from storm drain channels in developing areas of the UIP to assess changes
in water quality over time in response to development. Monitoring locations are
strategically placed within areas that are currently under development, or may be in the
future.
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |3 of 24Figure 1. UIP boundary, study catchments and monitoring sites
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Table 1 summarizes the list of sampling sites and upstream catchments (areas where water is collected by the landscape),
their approximate drainage area within the UIP, and predominant land use within that area. All sites are open channels
with different characteristics depending on their drainage area and level of development.
Table 1. Summary of catchment areas, sampling frequency, and drainage area.
Site ID Monitoring
Location ID
Site Name Dates
Active
# Sampling
Events
Drainage
Area (ac)
Land Uses
REF 4991297 Storm Drain Channel at 8000 W North Temple 6/21 -
Present
1 144 Low intensity agriculture
AG1 4991299 Storm Drain Channel at 7200 W and 1300 N 4/21 -
Present
3 157 Developing Industrial/Low
Intensity Agriculture
NEWDEV1 4991302 Storm Drain Channel at 1100 N 6550 W 4/21 -
Present
9 204 Developing Industrial
NEWDEV2 4991303 Storm Drain Channel at 6000 W 700 N 4/21 -
Present
14 316 Developing Industrial
OLDDEV1 4991313 Storm Drain Channel at 150 S 5600 W 8/21-
Present
3 180 Developing Industrial
OLDDEV2 4991305 Storm Drain Channel at end of John Cannon Dr 6/21-
Present
15 109 Developing Industrial
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In the study area, there are existing land use characteristics within the upstream
catchments that are potentially affecting stormwater quality. Most of the upstream
drainage areas are inuenced by farming and stock grazing activities; however, the
relative intensity of these activities differs throughout the UIP study area. A retired landll
is also present and leaching from this area could inuence the water quality of the shallow
groundwater and subsequently stormwater sample results.
Sites were selected with differing land use characteristics to help differentiate water
quality impacts of the UIP development from those caused by other current and historical
land uses, particularly agriculture (AG). The drainage area for the site identied as REF
(4991297) in Table 1 is the site currently least inuenced by ongoing UIP development
(perhaps a small amount of stormwater from I-80 and low intensity agriculture) and can be
considered to reect reference conditions for purposes of this investigation. Finally, there
are areas where land development is largely complete (OLDDEV) and other areas where
development is ongoing (NEWDEV).
The sites selected for this study represent various stages of pre-development, active
development, and post-development and are intended to provide multiple opportunities to
compare stormwater quality between sites to discern potential impacts to water quality
and the potential for pollutants to enter more sensitive water bodies downstream of the
development.
Stormwater Catchment Descriptions
This section describes the catchment areas contributing stormwater ow to the
monitoring stations in relation to their current land uses. The descriptive titles are used for
the purposes of this study only and are subject to change in the future. The descriptions
also include the main sources of stormwater within the catchment area and receiving
water body.
REF MLID-4991297: Storm Drain Channel at 8000 W North Temple:This site is intended to
capture conditions minimally impacted by development. With the exception of local roads
and roadside conveyances, the catchment does not include extensive industrial or
agricultural development. Due to low-density impervious surfaces, stormwater in this
catchment is primarily from overland ow. Runoff drains into a ditch which ows west to
Lee Creek.
AG1 MLID-4991299: Storm Drain Channel at 7200 W and 1300 NThis site is in early stages
of development and is largely low intensity agriculture uses. In addition, a major
transportation artery of the UIP to the northwest dominates the borders of the drainage
area. As with the REF catchment, a large proportion of the stormwater likely originates as
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overland ow, although runoff from roads likely has a larger contribution here. Discharge
from this area ows north into the Goggin Drain.
NEWDEV1 MLID-4991302: Storm Drain Channel at 1100 N 6550 WCurrently, this site
captures the most active construction and development activities in the UIP study area. It
is located in an area of a large warehouse and road development with multiple retention
basins and drainage ditches feeding into the sampling location. Discharge from the
catchment ows northward into the Goggin Drain.
NEWDEV2 - 4991303 Storm Drain Channel at 6000 W 700 NThis location is under active
development located just south of NEWDEV1 (4991302), and includes a major road, 700
North, bisecting the drainage east to west. In addition, the area includes a portion of the
historic North Temple Landll that is slated for phased re-development under the
Voluntary Cleanup Program. Discharge from the catchment ows northward into the
Goggin Drain.
OLDDEV1 - 4991313 Storm Drain Channel at 150 S 5600 WThis catchment encompasses the
area east of 56th West and its stormwater ows west through ditches and ultimately to Lee
Creek. It is representative of a fully developed industrial/commercial land use, so the
stormwater characteristics may be similar to those that can be expected once UIP
development is complete. For the duration of the study, this site will be used to represent a
more fully developed industrial/commercial site for comparison with newly developed
sites over time.
OLDDEV2 - 4991305 Storm Drain Channel at end of John Cannon Dr:This site also represents
a more fully developed area within the UIP and includes a small portion of pre-existing
industrial use outside the UIP. There is some potential for future development at a parcel
directly south, adjacent to the Fedex facility. This area discharges to the east via open
canals and ultimately into the Goggin Drain.
Stormwater Quality Evaluations
Methods
For each of the six sites listed above, composite samples were collected after a qualifying
storm event. Samples were collected as a composite throughout the duration of the runoff
event on a ow-weighted basis. Sampling was performed by DWQ in accordance with the
UIP Sampling and Analysis Plan (SAP)and DWQ Standard Operating Procedures. Samples
were analyzed by the Utah Public Health Laboratory (UPHL).
Water quality monitoring activities were designed to understand the temporal and spatial
condition of stormwater within the UIP area. Stormwater samples are characterized by a
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suite of select parameters that are responsive to environmental conditions within their
contributing area. Parameters were established to assist managers understand the
temporal and spatial condition of stormwater before, during, and after UIP development.
Stormwater Chemistry
A review of scientic literature was conducted to identify important water chemistry
constituents. The selected chemical constituents are intended to characterize different
sources of stormwater contamination and potential threats to downstream uses.
●Solids:Total solids (total suspended solids (TSS),total dissolved solids (TDS) and
total volatile solids (TVS)) were selected to quantify the mass of material suspended
in the water column. The type and amount of material in stormwater is dependent
on the substances contacted as the water ows downstream. Even at the same
location, materials are likely to differ from one storm event to the next due to recent
human activity and the intensity and duration of a particular storm event.
Stormwater solids were evaluated to broadly characterize the total amount of
material suspended in the water column during each storm event.
Among the measures of solids, TSS quanties the overall abundance of
non-dissolved materials suspended in the water column, which can include soils,
organic matter and other similar materials. TVS is the subset of solids that indicates
organic materials suspended in the stormwater, which can contribute to low
dissolved oxygen (DO) in downstream waters. TDS is the measure of the dissolved
components of solids, and is composed of many different potential contaminants,
nutrients and metals, which were further evaluated.
●Metals:Metals are a common stormwater contaminant that can be toxic to humans
and wildlife. Metals in stormwater can come from natural sources, but human
industrial activity can also introduce them to the environment, particularly at higher
concentrations. For this study, metals were evaluated to be an indicator of
industry-related stormwater contaminants. Given the presence of a historic landll,
legacy mining and ongoing industrial activities throughout the UIP study area, it is
important to understand whether stormwater serves as a primary conduit to
transport these contaminants to more sensitive waters downstream. The metals
evaluated in this study include: arsenic (As), zinc (Zn), copper (Cu), lead (Pb),
cadmium (Cd), selenium (Se), and mercury (Hg).
●Nutrients:Stormwater is often thought of as originating from water owing over
impervious surfaces such as concrete or asphalt. While this is an important aspect of
stormwater, contaminants can also be introduced as precipitation moves over or
through more pervious or disturbed surfaces. The macronutrients nitrogen (N) and
phosphorus (P) were selected as indicators of contaminants introduced through
non-industrial activities. These contaminants can also potentially threaten
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downstream waters by contributing to excessive richness of nutrients and
associated problems such as low dissolved oxygen (DO)). The nutrients evaluated in
this study include total phosphorus (TP) and total nitrogen (TN)--along with its
constituents ammonia and nitrate/nitrite.
Chemistry Evaluation and Interpretation
The evaluation and interpretation of stormwater chemistry is notoriously challenging.
Different contaminants are introduced into the environment by human activity, and those
contaminants may accumulate in the drainage area until there is a storm of sufficient
intensity for the contaminant to be suspended and ushed out. While some stormwater
contaminants are more commonly associated with different types of land use, they may be
introduced inconsistently from place-to-place, which means that chemical stormwater
quality can vary at each location from one storm event to the next. For this evaluation,
several additional steps were taken to better understand how chemical stormwater
constituents are related to ongoing UIP development.
Another challenge is pollutant concentrations also differ considerably among parameters,
sometimes by an order of magnitude or more. By its nature stormwater is not natural and
does not have designated uses or associated numeric water quality criteria, so it is difficult
to know what constitutes high or low concentrations for many important water quantity
parameters.
To address these challenges, key water quality parameters were normalized among all
samples collected for the project so that the lowest concentration (best water quality) was
scored as 100 and the highest concentration observed was scored as one. This
normalization allows the magnitude of different chemical contaminants to be directly
compared because they are measured on the same scale and relative to all UIP water
chemistry observations.
Normalized water chemistry values were used to understand whether or not there were
consistent stormwater contaminant observations at each collection location. Similarly, the
data were also used to nd patterns of stormwater contamination, if any, associated with
the type and extent of development in the upstream catchment of each sample location.
It is also possible that the storm intensity alters the contaminants observed in UIP
stormwater. To evaluate this, the relative magnitude of 24-hour precipitation was used to
quantify the magnitude of the associated storm as follows:
●LOW:Low storm intensity events were the bottom quartile of all collection event
storms (≤0.27 inches).
●MOD:Moderate storm intensity events were those with 24-hour rainfall between the
25th and 75th percentile of all storms (0.28-0.54 inches).
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●HIGH:High storm intensity events were those between the 75th and 95th percentile
(0.54-0.78 inches).
●V HIGH:Very high storm intensity events were those above the 95th percentile (>0.78
inches).
Storm intensities were then compared with the normalized stormwater contaminants to
see if certain types of contaminants were more likely to occur during storms of varying
intensity.
Results
Weather/Precipitation
Precipitation and air temperature associated with each collection event were obtained
from the Salt Lake International Airport weather station (KSLC). On average, collection
events were characterized by 0.42±0.26 inches of precipitation. The minimum amount of
24-hour precipitation associated with a collection event was 0.04 inches and the maximum
was 1.14 inches.
The sample locations were all affected differently by storms of varying intensity. Because
the same sample collection criteria were applied to all sites, this resulted in unequal
sample sizes among all sites depending on how strongly the location was inuenced by
stormwater. For example, REF was only sampled on one occasion, which was the largest
storm event observed over the study period. In contrast, NEWDEV2 and OLDDEV2 were
often the only sites sampled because the storm effects were too small at other locations.
Chemistry Data
TOTAL SOLIDS
Average TSS among all samples (159±177 milligrams per liter (mg/L)) reects a high
variability among sites and sampled events, with a low of 2.8 mg/L and a high of 990
mg/L. As expected, TSS concentrations were inversely proportional to the amount of
impervious surface area among land development categories, with highest concentrations
in the agricultural stormwater catchment, followed by old and then newly developed
catchments (TABLE 2). It is possible that the lower TSS values at the newly developed
locations is reective of the Best Management Practices (BMPs) being put into place as UIP
develops, which will be further evaluated as additional samples are collected.
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Table 2.Total solids observed in stormwater samples collected in 2021 and 2022 from catchments with
dierent densities of impervious surfaces/industrial development.
SITE ID Rel. Imp
Surface1
Number of
Observations
TSS
mg/L
TDS
mg/L
TVS
mg/L
REF2 Low
High
1 48 310 13.3
AG1 3 106±151 396±69 14±17
(N=23
NEWDEV1 10 292±303 663±619 25±24
(N=83
NEWDEV2 14 132±103 949±832 19±15
(N=113
OLDDEV1 3 84±73 1683±1062 21±7
(N=23
OLDDEV2 15 153±104 728±791 22±11
(N=103
Notes:
1. Sites are ordered with respect to the relative amount of impervious surface area. The NEWDEV and OLDDEV sites also have
dierent industrial uses, which are more diicult to broadly characterize at the catchment scale.
2. Confidence estimates (±X, 1 SD not provided due to a single observation at this location.
3. Calculations do not include observations N below the method detection limit MDL.
METALS
As with other contaminants, there is considerable variation in the metal concentration
observed at any given location among collection events. With the exception of arsenic (As),
the condence estimates are often nearly as large as the average concentration. Beyond
this general observation, it is best to evaluate the relative concentration of each metal
among the various collection locations because the concentration–and toxicity–of metals
varies considerably from one metal to another.
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Table 3.Dissolved metals observed in stormwater samples collected in 2021 and 2022 from catchments with dierent densities of impervious
surfaces/industrial development.
SITE ID Rel. Imp
Surface1
# of
Observation
s
Arsenic
(As)
µg/L
Zinc
(Zn)
µg/L
Lead
(Pb)
µg/L
Copper
(Cu)
µg/L
Cadmium2
(Cd)
µg/L
Selenium2
(Se)
µg/L
Mercury2
(Hg)
µg/L
REF3 Low
High
1 7.42 137 1.9 12.7 0.11 1.09
(N=05
AG1 3 34.3±10.4 12.3±12.6 3.9±4.1 9.4±8.1 0.16±0.09
(N=24
0.64
(N=13,4

(N=05
NEWDEV
1
10 15.4±6.5 60.3±36.6 15.7±11.1 26.8±14.1 0.31±0.25
(N=94
0.77±0.11
(N=34
0.13
(N=13,4
NEWDEV
2
14 21.0±8.5 43.8±37.4 8.6±6.4 24.2±13.7 0.18±0.12
(N=134
0.71±0.25
(N=7

(N=05
OLDDEV1 3 4.1±1.4 53.3±41.5 5.7±5.1 15.2±10.9 0.18±0.11
(N=24

(N=05

(N=05
OLDDEV2 15 8.4±3.7 146.3±79.8 11.2±11.1 28.3±18.3 0.45±0.46
(N=124
0.73±0.12
(N=54

(N=05
Notes:
1. Sites are ordered with respect to the relative amount of impervious surface area. The NEWDEV and OLDDEV sites also have dierent industrial uses, which are more diicult to broadly
characterize at the catchment scale.
2. Metals with a relatively large number of observations below method reporting limits MRLs); not included in the generalized metal gradient.
3. Confidence estimates (±X, 1 SD not provided due to a single observation (N=1.
4. Calculations do not include observations N below method detection limits MDLs).
5. All observations were below method detection limits MDLs).
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Arsenic (As) concentrations were highest at AG1 and lowest at the two older development
locations (OLDDEV1 and OLDDEV2) (see Table 3). This contaminant is sometimes
associated with soil disturbance, so it is possible that the higher concentrations at the
agricultural locations is due to water inltration through the soils at AG1.
Zinc (Zn), copper (Cu) and lead (Pb) showed the opposite pattern, with average
concentrations being generally higher at developed locations than the agriculture
catchment. For Zn, the most striking observation was at OLDDEV2, where the average Zn
concentration was about 3X greater than the other locations. Average lead concentrations
were highest at NEWDEV1, followed closely by OLDDEV2. Cu was also highest at
OLDDEV2, followed closely by the two newly developing catchments (NEWDEV1 and
NEWDEV2). Taken together, the data suggest that something within the OLDDEV2
catchment is contributing to metal contamination. While this may not be directly related
to new UIP developments, it should be further evaluated to see if these sources of pollution
can be reduced.
Cadmium (Cd), selenium (Se) and mercury (Hg) were more difficult to evaluate due to the
large number of observations below method reporting limits (MRLs). This means the
concentrations of these metals are often very low, with some exceptions. Among the
measurable values, these metal concentrations also suggest that the OLDDEV2 and
possibly NEWDEV1 catchments are sources of stormwater metal contamination.
NUTRIENTS
Total phosphorus (TP) among all sample locations averaged 0.37±0.22 mg/L with a low of
0.07 (OLDDEV1) and a high of 1.04 mg/L (NEWDEV1) (Table 4). On average, TP
concentrations were highest at NEWDEV1 and lowest at the AG1 location. At each sample
location, the variance in TN concentrations among collection events was considerable, as
evidenced by the condence estimates against the location average.
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Table 4.Macronutrients observed in stormwater samples collected in 2021 and 2022 from catchments with dierent densities of impervious
surfaces/industrial development.
SITE ID Rel. Imp Surface1 Number of
Observations
Total Phosphorus
mg/L
Total Nitrogen
mg/L Ammonia2
mg/L
Nitrate/Nitrite2
mg/L
REF3 Low
High
1 0.51 3.00 0.05 0.40
AG1 3 0.18±0.12 1.56±1.26 0.11±0.08 0.80±1.11
NEWDEV1 10 0.47±0.28 1.32±0.64 0.23±0.12 0.56±0.45
NEWDEV2 14 0.33±0.19 1.87±0.68 0.18±0.13 0.80±0.59
OLDDEV1 3 0.21±0.12 1.41±0.77 0.17±0.20 0.39±0.11
OLDDEV2 15 0.35±0.14 1.60±0.65 0.21±0.14 0.38±0.23
Notes:
1.Sites are ordered with respect to the relative amount of impervious surface area. The NEWDEV and OLDDEV sites also have dierent industrial uses, which are more
diicult to broadly characterize at the catchment scale.
2.Ammonia and Nitrate/Nitrite and components of total nitrogen.
3.Confidence estimates (±X, 1 SD not provided dueto a single observation at this location.
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Among all stormwater samples, total nitrogen (TN) averaged 1.71±0.92 mg/L, but varied
considerably from a low of 0.54 (NEWDEV1) to a high of 3.09 mg/L (OLDEV2) (Table 4). The
REF site had the highest TN concentration, but this site was only sampled at a single
event, so it is impossible to know if this is reective of the site itself or the fact that this
sample took place following the largest storm events over the two collection years. The
average TN among the other sites was roughly comparable. As with TP, the variance in TN
among different collection events was considerable.
Potential Sources of Variation among Contaminants: Further Evaluation
Normalized water chemistry allows us to directly compare different types of contaminants
(Table 5). Several patterns can be observed, but the most telling observation is that it is
difficult to generalize about the nature of stormwater contamination within the UIP study
area.
Table 5.Normalized and color-coded1scores for dierent stormwater contaminants 20212022 relative
to development intensity (impervious surface) in the contributing catchments.
Catchment Rel. Imp
Surface
2
N Solids Nutrients Metals
TSS TDS Comb.TN TP Comb.As Zn Pb Cu
REF3 Low
High
1 98 95 34 13 55 82 89 56 96 86
AG1 3 91 55 76 64 88 77 28 98 90 90
NEWDEV1 10 75 83 66 72 60 69 71 82 57 66
NEWDEV2 14 90 73 64 53 74 62 58 87 77 24
OLDDEV1 3 94 46 78 69 86 87 97 84 85 82
OLDDEV2 15 87 73 67 62 72 69 87 53 70 64
Notes:
1.Color coding represents the pollutant “grade”,with higher scores reflecting lower relative concentrations, as follows: dark
green = 90100, light green = 8089, yellow = 7079, light red = 6069, dark red < 60.
2.Sites are listed relative to each other fromlow to high impervious surface area, but sites with higher impervious surface
also have higher levels of industrial activity.
3.The only reference site sample collected was during the largest storm event sampled, so the values may not be reflective
of more common storms.
Data from the REF site are included in these tables; however, with a single sample it is
difficult to conclude anything from water chemistry at this location. The fact that this site
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was only sampled once between 2021 and 2022 means that a single storm event
contributed measurable stormwater (within autosampler specications). Furthermore, this
suggests that the potential for stormwater runoff and contamination can be expected to
increase as the UIP is developed. This reference site can provide useful background data,
as intended, provided that autosampler specications can be modied to collect additional
samples.
STORMWATER CONTAMINANTS AND INTENSITY OF DEVELOPMENT
Normalized solids data do not reveal any strong patterns with respect to development
intensity. With the exception of NEWDEV1, TSS values among all sites were generally low
among all sampled storms with a couple of atypically higher concentrations, perhaps
because solids only become strained during the largest storms. The relatively higher
stormwater TDS concentrations at AG1 may reect water picking up TDS sources such as
fertilizer during soil inltration. It is not clear why OLDDEV1 had relatively high TDS, but it
is of note that this was the only contaminant that was relatively high at this location in
comparison with the other sample locations.
The normalized metal concentrations show a couple of interesting patterns. With respect
to arsenic, contamination is probably a lesser concern with regard to stormwater because
it was only high at the agricultural catchment (AG1) where impervious surfaces were
relatively low. Metal stormwater contamination may not be a concern for the OLDDEV1
catchment where relative concentrations were low for all metals, although additional
observations are needed to conrm this observation. To varying degrees, all other
developed watersheds have relatively high metal concentrations for at least some
contaminants. The type and intensity of development may play a role in explaining
differences in metal concentrations among catchments, but consistent patterns are not
easily explained by this qualitative impervious surface gradient. Future contaminant data
collection data or quantication of catchment impervious surface areas may reveal more
consistent relationships.
STORMWATER CONTAMINANTS AND RELATIVE STORM INTENSITY
To evaluate the role that storm intensity played in the differences in pollutants among the
study catchments, the normalized data were also compared with the relative intensity of
storms associated with each collection event (Table 6). As expected, the concentration of
most pollutants increased with storm intensity. However, this trend reversed for samples
collected following the highest intensity storms, likely as a result of dilution.
Table 6.Normalized and color-coded1 scores for dierent stormwater contaminants relative to the
intensity of the storm that preceded the collection event 20212022.
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Relative
Precip.
Intensity2
N Solids Nutrients Metals
TSS TDS Comb.TN TP Comb.As Zn Pb Cu
LOW 8 90 82 73 72 73 76 81 71 78 74
MODERATE 21 86 65 62 53 71 72 57 80 78 74
HIGH 11 82 88 60 59 60 65 71 74 56 60
VERY HIGH 4 93 95 74 70 78 85 85 85 87 84
Notes:
1.Color coding represents the pollutant “grade”,with higher scores reflecting lower relative concentrations, as follows: dark
green = 90100, light green = 8089, yellow = 7079, light red = 6069, dark red < 60.
2.Storm intensity categories were determined using the 24-hour total precipitation prior to each collection event. LOW =
boom quartile, MODERATE = 25th – 50th percentile,HIGH = 75th – 95th percentile, VERY HIGH = >95thpercentile.
Unexpectedly, there was not an obvious relationship between TSS and storm intensity.
This suggests that the atypically high TSS concentrations in some samples cannot be
solely explained by differing amounts of stormwater runoff. It is possible that
precipitation-related TSS patterns are obscured by the fact that some sites were only
sampled during larger storm events because the autosamplers were not triggered during
smaller storms. In contrast, TDS did increase appreciably from low to moderate storm
intensity, but the concentrations then declined at higher—high and very high—storm
events, presumably as a result of sample dilution.
Normalized nutrients and metal concentrations responded more predictably, increasing as
storm intensity increased. Among metals, Pb and Cu are most strongly associated with
industrial activities, and these pollutants remained fairly consistent except during high
intensity storms. Normalized TP concentrations revealed a similar pattern, which is
notable as stormwater inputs of phosphorus to aquatic ecosystems are typically associated
with particulates. It is possible that storms need to be of sufficient intensity to suspend
phosphorus-associated material, but if this is true it is unclear why a similar pattern was
not observed with the normalized TSS data.
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |17 of 24
Discussion
The ongoing UIP stormwater study continues to provide insight into the impact of
development on water quality. The data collected so far indicates that the development of
these areas may alter the type and amount of contaminants, however, the variation of
stormwater contaminants from place-to-place and storm-to-storm makes understanding
what specic changes can be expected challenging. Stormwater does not have designated
uses, which means there are no applicable water quality standards for any pollutant until
the water reaches downstream water bodies. It remains unclear the extent to which UIP
stormwater pollutants evaluated in this investigation will impact the designated uses of
downstream waters.
Understanding the impact of UIP stormwater pollutants to downstream waters is not
possible without more extensive hydrological investigations, which is beyond the scope of
this work. The areas around UIP developments contain numerous drainage ditches, and
the residence time, or length of time water remains within these ditches, varies from place
to place and storm to storm. Many new UIP developments include holding ponds and other
BMPs to retain as much stormwater ow as possible. Inltration of stormwater throughout
the drainage network is dependent on soil saturation and the overall volume of stormwater
that moves through these systems during storm events. This complicated hydrology
means that there are no easy answers when it comes to understanding the extent to which
pollutants are transported to more sensitive ecosystems downstream, such as Great Salt
Lake wetlands.
If and when pollutants reach more sensitive waters, deleterious impacts to aquatic
organisms can potentially be mitigated due to the nature of stormwater pollutants.
Stormwater pollutants are intrinsically transitory because they only happen during storm
events, and pollutants that make it downstream during events arrive when waters are most
diluted due to the increase in ows. That said, these pollutants can still potentially
degrade downstream ecosystems, particularly if the contaminants increase from one storm
to the next, but the role that UIP stormwater would play relative to all other sources is
difficult to quantify.
Given these challenges, perhaps the most important insight from this and future
investigations is how UIP stormwater contaminants change over time. To date, these data
have only been collected for two seasons, so year-to-year changes in stormwater
pollutants associated with development cannot be interpreted with condence. This data
gap will likely narrow with the collection of additional stormwater samples as this
monitoring effort continues. Further examination of the differences among developed
catchments could provide insight into BMPs that could be implemented in the future to
minimize pollutants associated with industrial activity. When this occurs, lessons learned
might also be applied to other stormwater reduction efforts statewide.
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |18 of 24
Next Steps
Sampling and Analysis Plan Improvements
Since traditional measures of water chemistry may not be sufficient to document changes
in water delivery or water quality due to stormwater runoff, looking at additional measures
and techniques may provide signicant improvements to our understanding of impacts in
the UIP. For instance, where pollutant concentrations may be diluted during high runoff,
measures of discharge may greatly improve estimates of overall pollutant loading at each
of these sites.
Therefore, in the spring of 2022, DWQ updated the UIP Sampling Analysis Plan (SAP)to
include several improvements to assist with evaluating the impacts of development on
stormwater runoff. These proposed changes include adding an estimation of discharge
during storm events at autosampler locations, augmenting the water sampling effort with
the addition of passive samplers which can integrate measurements of pollutants over
time, adding sampling locations on the receiving waters of Lee Creek and Goggin Drain,
and mapping the changes in areas of impervious cover over time to assist with data
interpretation.
Due to limited resources, most of these proposed elements are on hold, with the exception
of discharge measurements and mapping of impervious cover. Data from these elements
will be integrated into the 2023 annual report. Future improvements and additional
monitoring will be contingent on funding allocated over the full period of the UIP
development.
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |19 of 24
Section 2: Air Quality Monitoring
The Division of Air Quality (DAQ) established monitoring facilities at the UIP site to track
pre-development or early development baseline. This monitoring includes: a sensor system
consisting of monitors to measure levels of research-grade particulate matter, ozone, and
oxides of nitrogen, and data logging equipment with internal data storage that are
interconnected at all times to capture air quality readings and store data.
Monitoring Locations
UIP air quality monitoring sites are known as the Lake Park (LP) site and the Prison site
(currently named IP). The LP site monitors for continuous and ltered PM2.5, PM10, sulfur
dioxide, ozone, and nitrogen dioxide. East of the UIP and Salt Lake International Airport is
the Air Monitoring Center (AMC) site that monitors for all parameters. Supporting these
measurements are weather measurements for temperature, wind speed and wind
direction. The IP site monitors continuous PM2.5, ozone, and nitrogen dioxide with
supporting weather measurements for wind speed, direction, temperature, and ambient
pressure.
All instruments/data, with the exception of PM2.5 lter measurements, are connected to
the air monitoring network and report data in near real time, hourly, to the network data
collection system. This data is then posted to DAQ web pages, the UtahAir mobile
application, and EPA’s AirNow site on an hourly basis.All data is reported to federal
databases at least quarterly as required by EPA.
UIP Air Monitoring Locations and Parameters
County EPA AIRS
Code
Station
Name
(Code)
Station
Address
Latitude Longitude Elevation
(Meters)
Monitored Parameters
Salt Lake 490353011 Air
Monitoring
Center UT
240 N 1950
West, Salt
Lake City
40.7769 -111.9461 1286 PM2.5, PM10, O3, NOx,
SO2, CO, NH3,
Meteorology
Salt Lake 490351007 Inland Port
IP
1480 N 8000
W, Salt Lake
City
40.8079 -112.0877 1285 PM2.5, BC, O3, NOx,
Meteorology
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |20 of 24
Salt Lake 490353005 Lake Park
LP
2782 S.
Corporate
Park Dr.,
West Valley
City
40.7098 -112.0086 1295 PM2.5, PM10, BC, O3,
NOx,CO, Meteorology
Monitors that were partially funded through a legislative appropriation are noted in bold.
A summary of the monitors found at all sites, including UIP sites, can be found on page 15
of the “Division of Air Quality Annual Monitoring Network Report 2022.” Site specic
information related to instrument type and other related information can be found on
pages 47 and 63. Please note that IP is referred to as “ZZ” in this document.
Air Monitoring Data Collection and Certification
Air monitoring data is collected annually and is certied at the end of the year once
comprehensive quality control checks have been completed. The data is then certied
with EPA, and can be used for regulatory purposes to demonstrate compliance with federal
air quality standards. The due date for data certication is May 1 of each year.
Requirements for data certication can be found in 40 CFR part 58. All data certication is
reviewed by EPA and they either concur, or not, to the states’ assertion of data
completeness. Analyzing site data before the end of the year or on a daily, monthly, or
quarterly basis when collecting baseline data is of limited value as all standards and
parameters are based on the data of an entire year, January 1 - December 31. Data
completeness and efficiency is also based on the data collected for the entire year.
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |21 of 24
Monitoring began at the LP site in September 2020 and at the IP site in March of 2021. To
date, the IP and LP sites have reported 96.7% of data during the period of operation, as of
November 4, 2022. Most parameters report an hourly value and it is these sampling
opportunities that are used to determine data reporting. Some data values will be
eliminated due to quality control checks, instrument malfunction, routine maintenance,
power outages etc. The nal numbers for 2022 will not be determined until the data
certication process, which will be conducted by April 2023.
UIP Baseline Air Quality Data Limitations
The two current UIP air monitoring locations, LP and IP, have been in operation for less
than three years, limiting the conclusions that can be drawn from the available
measurements. Additionally, the information collected during operations are dominated by
non-normal monitoring years. The year 2020 saw reduced emissions levels due to the
global pandemic, and the summers of 2021 and 2022 were impacted by wildre smoke.
The IP site is located at the new prison site, which is under construction. Given the
ongoing construction activity, the frequent power outages that are impacting data
collection should be considered normal baseline activity. Please also note that 2022
2022 MONITORING ACTIVITIES AT THE UTAH INLAND PORT • UTAH DEPT. of ENVIRONMENTAL QUALITY 21 of 24
UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |22 of 24
measurements are not fully quality certied, and the Design Value calculation, the
statistic that describes the air quality status of a given location relative to the level of the
National Ambient Air Quality Standards (NAAQS), cannot be made on partial years of data.
We can see that monitored air quality for the spring and summer of 2022 at the established
UIP monitoring sites correlates very well with the air quality monitors within the Salt Lake
region, indicating that regional air quality is impacted by the combination of all emissions
sources.Emissions sources within the geographical IP area are predominantly from
transportation, manufacturing and warehousing. The baseline daily emissions are
represented by the 2017 statewide air emissions inventory.
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UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |23 of 24
In the gure above, PM2.5 (top) and ozone (bottom) concentrations are shown between
May and October of 2022. Pollution concentrations were measured at UIP sites (IP, LP) and
further away in the urban Salt Lake Valley (HW, UT) for comparison. IP PM2.5
concentrations are noted by the gray dotted line in the top panel, while IP ozone is
represented by the orange dotted line in the bottom panel. Similarly, LP PM2.5
concentrations are represented by the green line in the top panel, while LP ozone is
depicted by the gray dotted line in the bottom panel.
Temperature (dashed blue lines) is displayed to indicate how pollution concentrations
change during warmer and cooler periods. Solid horizontal red lines indicate federal air
quality standards for 24-hour PM2.5 (35 µg/m3) and 8-hour daily maximum ozone (70 ppb).
Color bars on the left-hand side depict good (green), moderate (yellow), unhealthy for
sensitive groups (orange), and generally unhealthy (red) levels for both pollutants.
2022 MONITORING ACTIVITIES AT THE UTAH INLAND PORT • UTAH DEPT. of ENVIRONMENTAL QUALITY 23 of 24
UTAH DEPARTMENT of ENVIRONMENTAL QUALITY |24 of 24Salt Lake International Airport SLIA Air Quality Data
Air quality monitoring data is not being collected within the SLIA. The SLIA is bracketed
by the Department of Environmental Quality Technical Support Center AMC monitor to
the east, the IP site to the west, the LP site to the southwest and the Bountiful Viewmont
site to the northeast.
Air quality compliance inspections are routinely performed at the permitted sources that
are within or supporting the SLIA to determine compliance with air emissions and control
requirements. Emissions trends will be tracked through the air emissions inventory
process along with projections for emissions increases through the development of State
Implementation Plans that will occur during future reporting periods.
2022 MONITORING ACTIVITIES AT THE UTAH INLAND PORT • UTAH DEPT. of ENVIRONMENTAL QUALITY 24 of 24