WORKSHEET 11: DATA QUALITY OBJECTIVES
The USEPA has developed a seven-step process for establishing
Data Quality Objectives (DQOs) to help maximize the likelihood that
data collected in the field will be sufficient for the purposes
intended (EPA 2006). The following sections implement this
seven-step procedure for this study.
11.1Step 1: State the Problem
As discussed in Worksheet 10, one premise of the OU2 risk
investigation is that Cl2 and HCl are assumed to be acute
constituents of potential concern (COPC), and airborne
concentrations are known to occurair in the vicinity of the U.S.
Magnesium Plant. is known to be
impacted by releases of Cl2 and HCl. Concentrations of these
contaminants in air are expected to vary substantially as a
function of distance and direction from the Site, and also as a
function of time, depending on both short-term (minutes-hours) and
long-term (seasonal) variations in meteorological conditions, as
well as variations in release rates from normal plant operations,
maintenance activities, and equipment upsets. malfunctions.
Available data collected to date, summarized in Worksheet 10
[NOTE.this should include graphs that show C vs t from the original
DMA and/or from the gastronics DMA], support the concept that the
concentrations of these analytes over time are likely to be
characterized by intervals of zero or low concentration with a
series of intermittent “spikes” of varying concentration and
duration occurring at random times.
However, the available ambient air concentration information for
these two acute COPCs is too limited to support a risk assessment.
The data do not adequately characterize the spatial or temporal
patterns of concentration values in air, so additional data are
needed to support the characterization of human and ecological
exposures to Cl2 and HCl. In preceding RI activities, monitoring
systems have been demonstrated that can obtain continuous and
representative ambient air concentrations for these target
analytes. These systems are to be deployed in Phase 1B to obtain
data of sufficient quality and extent to support a risk assessment.
However, the existing data are too limited to reliably characterize
either the spatial or temporal patterns of concentration values in
air, so additional data are needed to support the characterization
of human and ecological exposures to Cl2 and HCl.
11.2Step 2: Identify the Goal of the Study
The goal of the study is to collect sufficient data on the
concentrations of Cl2 and HCl in air to reliably characterize the
pattern of short-term spikes and long-term average exposure
concentrations over space and time in order to support reliable
evaluation of human and ecological exposures and risks. In effect,
the goal of the Phase 1B monitoring program is to deliver
sufficient ambient air information with a relatively small number
of selected monitoring locations.
The focus for Phase 1B monitoring methodology is the acute
exposure timescale. Therefore, the monitoring program must be
designed to obtain a sequence of short-term ambient air
concentrations in candidate areas in which the presence of human
and ecological receptors is likely. Longer-term exposures may then
be quantified though analysis of the short-term concentration
data.
11.3Step 3: Identify Information Inputs
The environmental data that are need to be collected during this
project to support a reliable characterization of exposure and risk
from Cl2 and HCl in air consist of reliable measurements of
concentration values both over the short-term and long-term time
scales. Because long-term average values may be derived from an
adequate set of reliable and representative short-term values, only
short-term measurements are included in this study.
Such monitoring data are required at multiple locations around
the US Magnesium Plant, with special focus on locations and times
where different groups of humans or ecological receptors may tend
to be present.
Additional information inputs to the development of the DQO and
execution of the Phase 1B monitoring program are the data
validation and quality assurance measures that will be practiced
during and after the field portion of the monitoring program. These
methods, as developed in a subsequent Sampling and Analysis Plan
(SAP) will follow accepted practices to provide data of adequate
quality for risk assessment. Appropriate metrics of magnesium plant
production will also be recorded during Phase 1B, to verify that
operating levels during Phase 1B monitoring are representative of
normal production.
Because long-term average values may be calculated from an
adequate set of reliable and representative short-term values, only
the short-term samples require collection in the field.
In addition, data on plant production rates are needed to
determine if the time interval when sampling occurred is
representative of typical operating conditions.
11.4Step 4: Define the Boundaries of the Study
11.4.1Spatial Boundary
Based on the expectation that concentrations in air will tend to
be highest near the US Magnesium Plant and decrease as a function
of distance from the Plant, EPA identified an initial study area
described by a circle with a radius of 5 miles, centered on the
Plant (EPA 2013a). But within this study area, more detailed
spatial boundaries have been identified by USEPA as candidate areas
for monitoring to assess exposure risk (USEPA August 2014). Based
on qualitative considerations, these sites were viewed by USEPA as
representative of the likely locations of human and certain
ecological receptors, and that generally represented sufficient
spatial coverage within the OU2 overall boundary. Further analysis
using a combination of dispersion modeling simulations and ranking
tools has shown that five monitoring locations can provide
sufficient data for risk-based decisions (ERM May 2015). IIf data
collected during the Remedial Investigation indicate that exposures
in air may be of concern at distances beyond this initial study
area, the study area may be expanded.
11.4.2Temporal Boundaries
Concentrations of contaminants in air at any specified location
within the study area are expected to vary substantially as a
function of meteorological conditions, time and plant production
patternsrates and operational events, both over the short-term and
also seasonally.
and also seasonally. TTherefore, it is important that sampling
be of sufficient duration to capture the range of values that occur
over both the short-term (minutes-hours) and the long-term
(seasonally). For purposes of designing the Phase 1B monitoring
program, this DQO includes 1-minute instantaneous air concentration
readings as the short-term unit of the airborne dataset. This
monitoring interval can be reliably performed in field measurements
and is a suitable metric for assessing acute exposure. To capture
the effects of a full year of seasonal conditions and the potential
emission rate variability, it is proposed that the duration of the
Phase 1B sampling program be one year.
11.5Step 5: Develop the Analytic Approach
Risks from exposures to short-term spikes of Cl2 or HCl will be
characterized by estimating either the duration (minutes per year)
or the frequency (events per year) that a specified receptor will
experience. Repeated exposure to short-term spikes is also an
aspect of long-term potential risk. an exceedance of a specified
Risk-Based Concentration (RBC). Chronic risks will be evaluated by
comparing the long-term effective mean exposure concentration to an
appropriate chronic reference concentration. The detailsA summary
of how both acute and chronic exposure will be estimated from
1-minute instantaneous air concentration readings is provided
below. The specific methodologies of how these data will be used to
assess potential human or ecological risks will be described at a
later data in the baseline human health and ecological risk
assessment technical memoranda for OU 2. these evaluation processes
are described below, both for human and ecological receptors.
11.5.1Quantification of Hazard for Human Receptors
11.5.1.1Risk-Assessment Data for Short-Term ExposuresBased
Concentration Values for Humans
A number of studies have been performed to characterize the
nature and severity of adverse effects following both short-term
and long-term inhalation exposures to Cl2 and HCl, both in
humans and in animals. Attachment A summarizes the data and a
number of regulatory guidelines that have been established for
human exposure to Cl2, and Attachment B summarizes the data and
established regulatory guidelines for human exposure to HCl.
Available continuous monitoring data surrounding the Plant is
limited. But air data obtained during the DMA field work for OU2
does demonstrate the general pattern of concentration events. The
variability of local winds was found to result in substantial
periods with no measurable acute toxicants concentration present at
a monitor with relatively brief, well-spaced events of detectable
concentration. In effect, the acute toxicant concentrations pattern
at a typical location can be represented as a time-series of short
term concentration “spikes”. An example of this concentration data
pattern is illustrated in the time-series of 10-minute average
chlorine concentrations obtained during the Air Quality DMA in June
2013.
E
Figure 11.1 – Example DMA Field Data for Acute Toxicant Gas
Using the continuous contaminant data collected during the Phase
1B program at OU2 should support a risk assessment that assesses
exposure to repeated, infrequent, acute exposures. On this basis,
the monitoring data will support evaluation of concentration events
that exceed a recognized threshold for reversible acute effects.
Acute toxicity thresholds protective of human health and ecological
receptors will be presented in the baseline human health and
ecological risk assessment technical memoranda for OU 2.
11.5.1.25.1.3Characterization of Risks to Humans from Chronic
Exposure
To quantify the potential chronic exposure to human receptors,
longer-term average concentrations will be calculated using the
1-minute data collected during Phase 1B. The availability of a
full-year of 1-minute data at several locations will allow mean
average concentrations to be calculated for different timeframes
and locations of interest. In constructing this average, an
appropriate treatment of the prevalence of 1-minute data that are
effectively non-detects is necessary. The bounding cases would be
to either treat all non-detects as true zero concentrations, which
has some basis in the observation that the plume transport is the
only transient mechanism that conveys the gases to a given
receptor. A more conservative bounding case would be to assign a
level to the non-detects that reflects a background levels that are
below the detection limit. Assessment of the treatment of
non-detects and the comparison of long-term averages to toxicity
thresholds will be addressed in the Baseline Human Health Technical
Memorandum.
Non-cancer risks to humans from chronic exposures are
characterized using the Hazard Quotient
(HQ) approach:
HQ = EC / RfC
where:
EC = Long-term Exposure Concentration (ppm) RfC = Reference
Concentration (ppm)
An HQ value ≤ 1 indicates that risk of significant adverse
effects is not of concern, while an HQ value > 1 indicates that
adverse effects might occur, with the level of concern increasing
as the magnitude of the HQ increases.
RfC Values
EPA has not derived a chronic RfC for use in evaluating chronic
exposure to Cl2. However, EPA’s Regional Screening Level table
identifies the ATSDR chronic MRL (0.00005 ppm) as an appropriate
RfC. Consequently, the ATSDR Chronic MRL will be used to evaluate
hazard from chronic exposures to Cl2.
EPA has derived an RfC for HCl (0.014 ppm). This value will be
used in evaluating chronic exposures to HCl.
Uncertainties in the use of these toxicity values should be
discussed in the uncertainty section of the human health risk
assessment.
5.2Characterization of Hazard for Ecological Receptors
Risks to ecological receptors from inhalation exposures to Cl2
and HCl will be characterized using an approach that is generally
similar to that described above for humans. Details are provided
below.
5.2.1Risk-Based Concentration Values for Ecological
Receptors
A number of studies have been performed to characterize the
nature and severity of adverse effects following both short-term
and long-term inhalation exposures to Cl2 and HCl in mammals
(mainly rodents). Attachment A summarizes the data for Cl2, and
Attachment B summarizes the data for HCl. Quantitative
exposure-response data in birds are lacking.
September 17, 2015 As revised February 22, 2016
ENCLOSURE 2 – Revised Worksheet 11: Data Quality Objectives
(incl. Attachments A-D)
11-8
No existing risk-based concentration values (also referred to as
Toxicity Reference Values, or TRVs) were located for exposure of
ecological receptors to Cl2 or HCl. In the absence of such
established values, EPA is working in collaboration with
toxicologists from EPA, Agency partners, and U.S. Magnesium to
develop appropriate TRVs for both mammalian and avian receptors.
Attention will be focused on values appropriate for protection
against moderate (respiratory impairment) and severe (lethal)
adverse effects from single and repeated exposure to spikes, and
well as protection against effects of chronic (long-term) exposure
on growth, reproduction, and survival. After this development
process is completed, the resultant ecological TRVs will be
provided as part of the ecological risk assessment documents.
5.2.2Characterization of Risks to Ecological Receptors from
Short-Term Exposures
Characterization of risks to ecological receptors from exposure
to intermittent spikes of Cl2 or HCl will be evaluated by
estimating the frequency that exposures above each relevant
short-term TRV are likely to occur. For example if the frequency
(determined from the data) of the concentration exceeding a
10-minute ecological TRV is 0.00005 (0.005%), and assuming the
ecological receptor is present at the site for a total of 4 months
per year, the predicted exceedance frequency would be:
TRV exceedance frequency = (4 mo/yr x 30 days/mo x 24 hrs/day x
60 min/hr) x (0.00005) / (10 min/event)
= 0.5 events per year
5.2.3Characterization of Risks to Ecological Receptors from
Chronic Exposure
Risks to ecological receptors from chronic exposures will be
characterized using the Hazard
Quotient (HQ) approach:
HQ = EC / Chronic TRV
where:
EC = Long-tern exposure concentration (ppm)
TRV = Toxicity Reference Value for chronic exposure (ppm)
As was the case for humans, an HQ value ≤ 1 indicates that risk
of significant adverse effects is not of concern, while an HQ value
> 1 indicates that adverse effects might occur, with the level
of concern increasing as the magnitude of the HQ increases.
5.3Calculation of Effective Mean Exposure Concentration
(EMC)
5.3.1Short-term EMC Values
As noted above, it is expected that most exposures at the site
will be characterized by a series of intermittent spikes of varying
concentration and duration. In most cases when exposure
concentrations are not constant over time, it is assumed that risk
is proportional to the simple average of the concentration values.
This assumption is expressed as Haber’s Rule:
C x d = Constant effect where:
C = exposure concentration d = exposure duration
For example, if Haber’s Rule is true, then exposure to 10 ppm
for 10 minutes causes the same effect as exposure to 1 ppm for 100
minutes or exposure to 0.1 ppm for 1,000 minutes.
However, for some acute toxicants, Haber’s Rule may not be
reliable, and effects are observed to be proportional to the
product of time and concentration raised to some power “n” (ten
Berge et al. 1986):
Cn x d = Constant effect
In cases where C is not constant over the exposure duration d,
the metric of exposure is (ten
Berge et al. 1986):
∫ [C(t)n dt ] = Constant effect
Because C(t) is not a simple function of t, this integral may be
approximated as:
∑ (C(t)in x ti) = Constant effect
where ti is the width of sampling observation “i” that has
occurred within the time window d. The EMC is defined as a constant
concentration of exposure duration d that is toxicologically
equivalent to a non-constant exposure pattern that occurs over
the same exposure duration d:
That is:
∑ (C(t)in x ti) = EMCn ∙ d, where d = ∑ ti
Rearranging this expression to find EMC yields:
EMC = [∑ (Cin x ti ) / d ]1/n
Assuming that “t” is constant for all sample measurements within
a time window, this simplifies to:
EMC = [Average of Cn ]1/n
Both NAS (2004) and EPA (2013b) have reviewed the available
literature on the concentration- time relationship for Cl2, and
have determined that the effect of exposure is not well predicted
using Haber’s Rule. Although there is variability between studies,
both NAS (2004) and EPA (2013b) concluded that the most appropriate
value of the exponent “n” is 2. This value was also selected by
CalEPA (2014). Consequently, the EMC for Cl2 for any specified
exposure interval of duration d is calculated as:
EMCd (Cl2) = [Average of C2 over duration d]1/2
For HCl, both NAS (2004) and EPA (2009a) have reviewed the
available literature on the concentration-time relationship to
determine the value of the exponent “n”. Both NAS (2004) and EPA
(2009a) concluded that n = 1. This value was also selected by
CalEPA (2014). Consequently, the EMC for HCl for any specified
exposure interval of duration d is calculated as the simple average
of concentration:
EMCd (HCl) = Average of C over duration d
This approach for calculating the EMC for short-term exposures
to highly variable exposure concentrations has been reviewed and
endorsed by several experts (see Attachment C).
5.3.2Chronic EMC Values
The strategy for calculating the EMC for long-term or chronic
exposures will be to compute the EMC for each day that monitoring
has occurred, using the equation above, and then providing the
resultant set of one-day EMC values to EPA’s ProUCL software
application to compute the mean and the 95% UCL on the mean.
The value of long-term EC is calculated from the mean or UCL of
the mean EMC by adjusting for intermittent exposure frequency (EPA
2009b):
EC(best estimate) = EMC(mean) * ET/24 * EF /365
EC(upper bound) = EMC(UCL) * ET/24 * EF /365
5.4Counting the Number of RBC or TRV Exceedances
The probability that the concentration of Cl2 or HCl in air will
exceed the AEGL-1 value will be determined from the data simply by
counting the number of one-minute values that exceed the AEGL-1,
and dividing by the total number of observations. For example, if
reliable monitoring data have been obtained at a station once per
minute for a year (a total of 525,600 measurements), and the AEGL-1
value was exceeded in 894 of those measurements, the probability
would be 894/525,600 = 0.0017 (0.17%).
The probability that the EMC in air over a time window of
duration “d” will exceed the RBC or TRV for that duration will be
estimated by calculating the EMC for each sequential time window of
duration d, counting the number of events where the EMC exceeds the
RBC or TRV, and dividing by the number of observation windows of
duration d:
Probability of exceedance (events per time window) =
N(exceedance) / N(total)
where:
N(exceedance) = Number of exceedances counted in the data
set
N(total) = Total number of sequential time windows of duration d
in the data set
For example, assume that a data set of continuous one-minute
measurements has been obtained at some specified monitoring
station. Assuming that the goal is to calculate the probability
(frequency) that the EMC for a 10-minute time window exceeds a
10-minute RBC value, the calculation process is as follows:
Step 1. Divide the data into sequential 10-minute blocks.
Assuming the data span one full year, there are a total of 60 x 24
x 365 / 10 = 52,560 such time blocks
Step 2. Calculate the EMC for each time block, as described
above
Step 3: Count the number of time blocks where the EMC exceeded
the RBC. For this example, assume that there were 27 such
events.
Step 4: Calculate the probability of exceeding the RBC
In this example, the probability of exceeding the 10-minute RBC
is: Probability = 27 / 52,560 = 0.0005 (0.05%)
5.5Interpreting the Hazard of Short-Term RBC or TRV
Exceedances
EPA has not developed national guidelines that establish
acceptable limits on the duration or frequency that short-term
human RBCs or ecological TRVs may be exceeded. EPA is presently
consulting with EPA toxicologists and Agency partners to derive
appropriate values, and will also seek and consider input from US
Magnesium. When this process is complete, the EPA will establish
Exceedance Goals (EGs) for the site, and these will be provided as
part of the human health and ecological risk assessment documents.
In general, it is anticipated that EGs will become more stringent
as the severity of effect increases. In locations where the
estimated frequency or duration of exceedances is greater that the
relevant EG, action may be needed to reduce exposure and risk to
acceptable levels.
11.6Step 6: Specify Performance or Acceptance Criteria
11.6.1 Decision Error Goals
In evaluating exposures from Cl2 and HCl in air, two types of
decision errors are possible:
Type I error: In this case, it is concluded that exposure is
within acceptable limits, when in fact the true exposure exceeds
acceptable limits.
Type II error: In this case, it is concluded that exposure is
above acceptable limits, when in fact the true exposure is within
acceptable limits.
EPA is primarily concerned with minimization of the chances for
a Type I error, since an error of this type could result in a
failure to address exposures that are of potential human or
ecological health concern. In general, EPA has a goal that the
probability of making a Type I error should not exceed 5%.
Type II errors are of lesser concern, since a Type II error does
not result in unacceptable exposures. However, Type II errors may
result in the unnecessary expenditure of resources to address
exposures that are actually within acceptable limits. Consequently,
EPA typically seeks to limit the probability of Type II errors to
within a reasonable tolerance. Although there is no standard rule
for Type II errors, a value of 20-30% is often identified as a
goal.
11.6.2 Characterizing Uncertainty In Short-Term Exceedances
Observations
Using Phase 1B continuous data, Recall that both concentration
event exceedance duration and exceedance frequency are to be
calculated based on counts of the number of exceedances
concentrations above an accepted threshold that are observed during
some sampling duration. Type I and Type II errors may occur because
of random statistical variation in the observed counts of
concentration events. That is, the observed count may be either
higher or lower than the true long-term average count.
Sampling at the representative monitoring locations as informed
by air dispersion modeling provides reasonable assurance that Type
I errors will not occur. These locations can be shown by data
adequacy evaluations and possibly by additional modeling during the
execution of Phase 1B to show that the selected locations have
experienced concentrations that are representative of previous
levels as predicted by long-term modeling. Therefore, if during
Phase 1B the selected monitoring locations do not exhibit actual
concentrations above the Cl2 or HCl exposure risk thresholds, then
there is reduced probability that other locations could have
experienced such exposures.
In order to help minimize the probability of Type II errors, it
is desirable to sample for a sufficient duration such that if the
monitored frequency of elevated concentration events is below a
health-based threshold, then , in cases where the true exceedance
rate is below the EG, it can be concluded that the the upper bound
of the possible frequency of such events will also be below those
thresholds.n the exceedance rate will also meet the relevant EG.
Because uncertainty decreases as a function of the total number of
observations, longer sampling durations result in decreased
statistical uncertainty. Because suitable health-based thresholds
EGs are not yet established, quantitative estimates of sampling
duration needed to limit Type II errors are not possible. However,
once the data are collected,the probability of a Type I and Type II
decision error associated with a decision based on either the best
estimate or the upper bound may be calculated and presented as part
of the uncertainty discussion.
6.2Characterizing Uncertainty in Short-Term Exceedances
There are several different approaches that may be used to
estimate the uncertainty around a measured count. For this effort,
the Bayesian uncertainty interval described by Box and Tiao (1973)
is selected for use:
N(ub) = 0.5 x CHISQ.INV(0.95, 2*N+1)
where:
N(ub) = 95% Upper Confidence Bound on N
CHISQ.INV(p,df) = Inverse chisquare distribution with df degrees
of freedom evaluated for probability p
Given N(ub), the upper bound confidence limits on exceedance
duration and frequency are calculated as:
Upper bound on exceedance duration = N(ub) x (duration of the
RBC) Upper bound on exceedance frequency = N(ub) / N(total)
In order to help guard against Type I decision errors, EPA will
consider both the best estimate and upper bound values of
exceedance duration and frequency when assessing exposure to
spikes.
The equations are as follows:
•If the decision is that the exceedance rate based on the best
estimate and/or upper bound value of N does meet the EG, the
probability of a Type I error is:
Prob. of Type I error = CHISQ(EG / k, 2N + 1)
where:
CHISQ(x,df) = fraction of the cumulative chisquare distribution
function with df degrees of freedom that exceeds a value of x
k = (ET/24 * EF/365) / (2 * DUR)
•If the decision is that the exceedance rate based on the best
estimate and/or upper bound value of N does not meet the EG, the
probability of a Type II error is:
Prob. of Type II error = 1 – CHISQ(EG / k, 2N + 1)
6.3Characterizing Uncertainty in Long-Term Average Exposure
As noted above, the long-term average exposure concentration
will be derived by first calculating the mean averages EMC for each
day that monitoring has occurred, and then using that providing
that data set to ProUCL to derive estimates of the longer-term mean
and the UCL of the mean. Use of the UCL to estimate exposure
concentration automatically limits the probability of a Type I
error to 5%. Because the distributional pattern and variance of the
data are not known, it is not possible to perform a power
calculation to estimate the number of one-day values needed to
achieve target tolerances for Type II decision errors. However,
because each one-day concentration EMC is derived from many
short-term measurements (e.g., 1/minute * 60 min/hr * 24 hrs =
1440), it is expected that the high variance that is likely to be
present in the short-term measurements will be greatly reduced in
the set of one-day EMC values. Consequently, it is expected that
uncertainty in the estimate of long-term average exposure will be
small.
11.7. Step 7: Develop the Plan for Obtaining the Data
Several different types of continuous sensors that have the
ability to measure Cl2 and HCl in air have been evaluated at the
Site (ERM 2014, 2015a). Based on field trials of the instruments,
monitors available from Gastronics have been identified as the most
reliable, and these monitors will be used to collect data at
selected monitoring locations within the 5-mile study area.
Instantaneous values of both Cl2 and HCl will be measured and
recorded once per minute.
Details on instrument sensitivity, calibration, and maintenance
as well as protocols for data collection, storage and management
are provided in this section, and in the attached Gastronics
specifications and Operating Manual.
11.7.1Location of Sampling StationsSampling and Analysis
Methods
As noted above, the values and exceedance rates frequency of
observed concentrations of Cl2 and HCl are expected to vary as a
function of both direction and distance from the US Magnesium
Plant. In order to ensure the data are adequate to reliably
characterize spatial variability, an initial set of 12 candidate
sampling station locations were selected proposed by establishing
six equal pie-shaped sectors radiating outward from the plant. The
orientation of the sectors was selected so that the first sector
(designated “A”) lies with its center line oriented in the
predominant downwind direction (southeast) from the Plant. Two
monitoring locations were placed within each sector, focusing on
areas where human and/or ecological exposures are expected to occur
receptors are expected to be present. The 12 candidate locations
are shown in Figure 11-1 (Panels A and B).
The candidate sampling locations were then grouped into three
geographic zones, as follows in Table 11.1:
Table 11.1 Roster of Candidate Monitoring Locations by
Geographic Zone
Zone
Candidate Locations
Lakeshore
5, 6, 10, 11, 12
Central
1, 2, 3, 4, 9
Upland/Foothills
7, 8
Within each zone, AERMOD calculations were used to predict the
relative likelihood of high concentrations (one-hour values that
exceed the 95th percentile of the site-wide data set) occurring
within each candidate location, both long term (four year average)
and seasonally (by month). Calculations were performed both for
releases from the stack and for fugitive releases from the
production facility (ERM 2015e). Detailed results are presented in
Attachment D, and the results are summarized in Table 11-2. These
calculations were used to help select sampling locations within
each zone, as discussed below.
Lakeshore Zone
Because the Lakeshore Zone is relatively far from the production
facility, it is expected that the plant stack would be the dominant
source of Cl2 and HCl concentrations, and that contributions from
fugitive releases are likely to be minor. Because of this,
comparisons between candidate locations in this zone focused mainly
on the AERMOD calculations for stack releases.
Of the five candidate locations within the Lakeshore Zone, three
(11, 12, and 6) appear to be relatively similar, both with regard
to long-term average exceedance frequency predicted average high
concentration event frequency (4.0% to 4.6%) and with regard to
seasonal variability (a peak in the late winter with a second peak
in the late summer). Candidate locations 5 and 10 are also quite
similar to each other, but have a relatively lower exceedance
frequency of predicted high concentration events (1.7% to 1.9%)
than locations 11, 12, and 6, and have only a minor peak in late
winter.
Based on these results, candidate location 11 is selected to
characterize ambient air exposures in the Lakeshore Zone. Use of
this station is likely to provide representative data for locations
11, 12 and 6, although the data may tend to be biased somewhat high
for locations 5 and 10.
Central Zone
Because the Central Zone includes the area in close proximity
around the production facility (especially locations 1-4), it is
expected that both plant stack and fugitive sources may be
important contributors to measured concentrations of Cl2 and HCl in
this zone. Consequently, comparisons between candidate locations in
the Central Zone considered the AERMOD calculations for both stack
and fugitive releases.
When comparisons are based on AERMOD predictions of stack
releases, all five candidate locations within the Central Zone
(1-4, 9) appear to have similar seasonal patterns, with peaks in
the summer months. Three locations (1, 3, and 4) appear to be
relatively similar with regard to the long-term average frequency
of high concentration events (3.3% to 3.8%), while candidate
location 2 is predicted to have substantially higher stack-based
frequency of high concentration events (8.5%), and candidate
location 6 is intermediate (6%).
When comparisons are based on AERMOD predictions of fugitive
releases, the pattern is quite different, with peak exceedance
frequencies of high concentration events tending to occur in early
to late summer, and relatively large differences between expected
high concentration exceedances frequencies, with location1 being
higher (18%) than locations 2-4 (9-13%) or location 9 (3%).
Because the relative contributions of stack and fugitive
releases on measured concentrations in the Central Zone is not
known, and because each may be important, these AERMOD data do not
allow a reliable selection of any single sampling location to be a
reasonable representation forthe entire zone. Moreover, the
potential for human exposures is more likely in the Central Zone,
which makes the data especially important for reliable human health
risk characterization.
Based on these considerations, it is concluded that
characterization of worker exposure in the Central Zone requires
reliable measures of concentration at locations 1, 2, and 9. These
data will also be valuable in evaluation of potential ecological
exposures in the Central Zone, especially location 9.
Upland/Foothills Zone
Because the Upland/Foothills Zone is relatively far from the
production facility, it is expected that plant stack releases are
likely to be the dominant source of airborne Cl2 and HCl
concentrations, and that contributions from fugitive releases are
likely to be minor. Because of this, comparisons between candidate
locations in this zone focused mainly on the AERMOD calculations
for stack releases.
Of the two candidate locations within the Upland/Foothills Zone,
the long term average exceedance frequency of high concentration
events is expected to be somewhat higher at location 7 (4.8%) than
location 8 (2.6%). This suggests that location 7 is preferred as a
surrogate for this zone. Moreover, location 7 is located in the
foothills, in comparison to location 8, which is at the base of the
foothills. This is particularly important, because AERMOD
calculations suggest that there is are substantial differences
between the impact of stack releases on locations in the foothills
compared to the base of the foothills during winter months. This is
illustrated in Figure 11-2, which plots monthly average relative
concentrations along two transects near location 7 that begin in
the foothills (nodes a and b) and traverse northeastward onto the
uplands (nodes c and d). As shown, there is relatively little
difference between these locations in the summer (May – August),
but a large difference in other months, especially in January,
February, and March. This means that data collected at location 8
might substantially underestimate winter-time exposures to humans
and ecological receptors in the foothills.
Based on these results, candidate location 7 is selected to
characterize exposures in the Upland/Foothills Zone. Use of this
station is likely to provide representative data for human and
ecological exposures in the foothills, but may tend to overestimate
exposures that occur only at the base of the foothills, especially
in the winter months.
11.7.27.3 Temporal Requirements for Monitoring Stations
Available data on human land use patterns (ERM 2015b) were used
to determine time frames when various human receptors would likely
be exposed in each zone. The expected exposure patterns are
summarized below in Table 11.2.
Table 11.2. Summary of Human Receptor Occupancy of OU2 Zones
Zone
Receptor
Occupancy
Lakeshore
Shrimp harvesters
Land managers
Oct. - Feb.
Central
US Magnesium workers
ATI workers
Hill Bros workers Delivery persons BLM workers
Year round
Upland/Foothills
Ranchers
Hunters
Recreational visitors
Land managers
Oct. – Apr.
Sep. – Feb. Mar. – Nov. Year round
As indicated, human exposures in the Lakeshore Zone are expected
to occur mainly in October thru February, but are expected to occur
year round for one or more human receptor groups in the Central and
Upland/Foothills Zones.
Since data acquired during Phase 1B may also be used to assess
ecological receptor risk, it is noted that a wide range of avian
and mammalian receptors are present at the Site (ERM 2015c, 2015d).
The potential for ecological exposures is likely to vary somewhat
by species. Representative ecological receptors include the
following Table 11.3 (ERM 2015d):
Table 11.3. Representative Ecological Receptors in OU2
Group
Feeding Guild
Representative Species
Avian
Terrestrial Insectivore Aerial insectivore Carnivore
Herbivore
Aquatic insectivore
Horned lark
Tree swallow
Am. kestrel, Great horned owl
Mourning dove
Snowy plover, Avocet
Mammalian
Herbivore
Terrestrial Insectivore
Carnivore
Kangaroo rat Vagrant shrew Badger
For avian receptors, the potential for exposures in the spring
thru fall (breeding season and fall migration) are of interest,
although some avian species only occupy the site in winter, and
some are year-round residents. Mammalian receptors are also
year-round residents.
These occupancy patterns are summarized in Figure 11-3. As
shown, the presence of human and/or ecological receptors is
expected to occur in all months of the year in each sampling zone.
Because some receptors are only present part of the year, and
because seasonal exceedance rates may vary substantially in some
locations, it is necessary that sampling at each station span one
full year in order to capture the range of values that occur over
both the short- term (minutes-hours) and the long-term
(seasonally).
11.7.37.4Sampling Design for Phase 1B Monitoring Stations
As described in Section 11.7.12 of this worksheet, the Phase 1B
air monitoring program for OU2 will involve continuous monitoring
of acute target gases at five locations for one full year. Each
location will house a Gastronics electrochemical air monitor for
Cl2 and HCl. One selected location for the full year will also have
a co-located, identical Gastronics monitor to provide ongoing
assessment of precision. Table 11.4__ shows the manufacturer
performance specifications for the Cl2 and HCl sensors.
Table 11.4.__. Gastronics True Wireless® Performance
Specifications
Specification or Criteria
Cl2 Sensor
HCl Sensor
Measurement Range
0 - 50 ppm
0 - 30 ppm
Measurement Resolution
< 0.05 ppm
< 0.1 ppm
Oper. Temp. Range
- 20 to 40 °C
- 20 to 40 °C
Oper. Rel. Humidity Range
15 - 95%. non-condensing
15 - 95%. non-condensing
Long-Term Drift
< 10% per 6 months
< 3% per month
Linearity of Response
< 5% full scale
< 5% full scale
Response Time:
To 50% of final value
< 20 sec
< 30 sec
To 90% of final value
< 60 sec
< 70 sec
The operating principles for the Gastronics sensors are similar
to those for other electrochemical detectors; the reactive surface
of the electrochemical cell. The sensing element consists of a very
small “bead” made of an electrically heated platinum wire coil,
covered first with a ceramic base such as alumina and then with a
final outer coating of palladium or rhodium catalyst dispersed in a
substrate of thoria. This type of sensor operates on the principle
that when a given gas/air mixture passes over the hot catalyst
surface, oxidation/combustion reactions occur and the heat evolved
increases the temperature of the “bead”. This in turn alters the
resistance across the bead, which can be measured using a standard
electrical bridge circuit. The resistance change is then directly
related to the gas concentration in the surrounding atmosphere.
The Gastronics (dual gas) ambient electrochemical analyzer was
selected as the monitoring technology best-suited for long-term
continuous monitoring based on the following demonstrated
attributes:
· The response level for the concentration sensors is lower than
the lowest acute exposure chlorine and hydrogen chloride exposure
criteria;
· The monitoring system offers high data capture rates and has
demonstrated high dataset completeness during normal operation;
· Hardware is suitable for long term deployment, and will
withstand the range of conditions that occur at the locale;
· Field monitors operate reliably on solar-charged battery power
supplies;
· The time interval between sampled data points is sufficiently
short to capture brief concentration events (capable of sub-minute
readings);
· The sensor and monitoring unit accommodate accuracy audits and
field calibrations with reference gases to assure data quality;
and
· Data are transmitted wirelessly via radio signal to a
centralized base station where datasets can be downloaded to a PC
and in a convenient format (e.g., Excel spreadsheet) for review and
analysis.
The Gastronics field monitors transmit digital data in “packets”
that are sent from the monitoring stations by radio to a central
base unit every several minutes. This operation is controlled by
internal code in the base station software, and based on DMA
observations with two stations operating at fixed one-minute data
intervals, packets are transmitted and received from individual
stations every four to seven minutes. Each packet contains the
one-minute values for Cl2 and HCl concentration, and battery
voltage readings collected since the preceding transmission for
that station. Separate data packets are sent and received for each
field monitor, and are buffered by the base unit in separate files.
Each packet also includes a date/time stamp for the transmitting
station. The company indicates that over a dozen such field systems
can directly communicate to a single base station. The base station
software is configured with an internal data logging function that
buffers individual readings from each station in a separate buffer
file, so there is no ambiguity about which data is obtained from
which station.
The collected data is directly queried by a dedicated data
logging computer operating the vendor’s Scada software, to create
permanent data logs in the form of a .csv file for each individual
station. From this computer, data is downloaded periodically to a
USB memory device. Procedures for periodic downloading in the field
were validated during the Stage 3 DMA activities. These downloading
procedures allow verification of the proper capture of data in the
data logging computer files. Prior to Phase 1B, ERM will implement
phone-modem and communication software to support off-site queries
of monitoring status, and to allow data to be downloaded remotely
to an office computer.
The primary field activity for the US Magnesium monitoring
program is periodic quality assurance/quality control (QA/QC).
Gastronics recommends that the calibration procedures be performed
on a monthly basis. However, for the US Magnesium program the QA
audits, function checks, and if needed sensor calibration will be
conducted every 7 days of field operation, unless it is shown that
monitor performance warrants a longer or shorter QA interval.
QA field activities are initiated by challenging each sensor in
normal operating mode with certified, single component reference
gases (e.g, nominally 10 ppmv Cl2 in nitrogen). This audit provides
the “as found” sensor responses for a high concentration gas
(approximately 10 ppm Cl2/HCl), a low concentration (approximately
5 ppm Cl2/HCl), and zero air (0.0 ppm Cl2/HCl). ”As found” values
of the monitor response are manually recorded in the field, and the
reference gas flow will continue at least 2 minutes after than
point, to record th audit responses in the electronic record. The
primary field quality control (QC) procedure for the Gastronics
monitor operation is the zero and span reference gas calibration,
which readjusts the internal response curve of the sensor to match
zero and user-input span gas concentrations. If a sensor’s
“as-found” response was within 10% of the challenge gas
concentration, then the recalibration procedure are usually not
performed, unless other aspects of the sensor performance is
suspect.
REFERENCES
Box GEP and Tiao GC. 1973. Bayesian Inference in Statistical
Analysis. Wiley Online. Print
ISBN: 9780471574286. Online ISBN: 9781118033197. DOI:
10.1002/9781118033197
CalEPA. 2014. Air Toxicology and Epidemiology. All OEHHA Acute,
8-hour and Chronic Reference Exposure Levels (chRELs) as of January
2014. California Environmental Protection Agency, Office of
Environmental Health Hazard Assessment. Available online at:
http://www.oehha.org/air/allrels.html
EPA. 2009a. Provisional Advisory Levels (PALs) for Hydrogen
Chloride. Final Report. National Homeland Security Research Center,
Office of Research and Development, United States Environmental
Protection Agency, Cincinnati, Ohio. November, 2009.
EPA. 2009b. Risk Assessment Guidance for Superfund. Volume I:
Human Health Evaluation Manual (Part F, Supplemental Guidance for
Inhalation Risk Assessment). Final. Office of Superfund Remediation
and Technology Innovation, Environmental Protection Agency,
Washington, DC. EPA-540-R-070-002. OSWER 9285.7-82. January
2009.
EPA. 2013a. Phase 1A Remedial Investigation, Sampling and
Analysis Plan to Identify Chemicals of Potential Concern in Soils,
Sediment, Solid Waste, Water and Air, and Receptor Surveys.
Revision 0 for PRI Areas 2 and 8 through 17. US Magnesium NPL Site,
Tooele County, Utah. United States Environmental Protection Agency
Region VIII. September 2013
EPA. 2013b. Provisional Advisory Levels (PALs) for Chlorine
(Cl2) (CAS Reg. No. 7782-50-
5). Final Report. National Homeland Security Research Center,
Office of Research and
Development, United States Environmental Protection Agency,
Cincinnati, Ohio. November,
2013.
ERM. 2014. Phase 1A Remedial Investigation, Sampling and
Analysis Plan for Operable Unit 2
– Ambient Air. U.S. Magnesium RI/FS, Rowley, Utah. Prepared for
US Magnesium LLC
and USEPA Region 8 by ERM-West. Inc. Revision 1. July 2014.
ERM. 2015a. Draft Air Quality PRI (OU-2) Stage 3 Demonstration
of Method Applicability – Technical Memorandum, US Magnesium RI/FS,
Rowley, Utah. Prepared for US Magnesium LLC by ERM-West, Inc.
November 2015.
ERM. 2015b. Final Phase 1 Human Exposure Survey Report,
Remedial
Investigation/Feasibility Study, US Magnesium Site, Rowley,
Utah. Prepared for US Magnesium LLC by ERM-West. Inc. August
2015.
ERM. 2015c. Ecological Habitat Report
ERM. 2015d. Representative species tech memo
ERM. 2015e. Phase 1B Air Monitoring Site Selection for US
Magnesium OU2. Technical Memorandum to USEPA, Prepared for US
Magnesium LLC by ERM-West, Inc. August 2015
NAS. 2004. Acute Exposure Guideline Levels for Selected Airborne
Chemicals. Volume 4. Subcommittee on Acute Exposure Guideline
Levels, Committee on Toxicology, Board on Environmental Studies and
Toxicology, National Research Council of the National Academies.
The National Academies Press, Washington DC. www.nap.edu.
ten Berge WF, Zwart A, Appelman LM. 1986. Concentration-time
mortality response relationship of irritant and systemically acting
vapours and gases. J. Hazard. Mater. 13:301–309.
Table 11-2. AERMOD Modeling Results
Zone
Station
Stack
Fugative
EF
Peak
EF
Peak
Central
1
3.8%
May-Jun-Jul
17.6%
Nov-Dec-Jan
2
8.5%
Jun-Jul-Aug
12.0%
Jun-Jul-Aug
3
3.4%
Jul-Aug
12.5%
Nov-Dec-Jan-Feb
4
3.3%
Jun-Jul-Aug
9.1%
Oct-Nov-Dec
9
6.0%
Jul-Aug
2.7%
Nov-Dec-Jan
Lakeshore
11
4.6%
Feb-Mar, Jul-Aug
0.8%
-- (a)
12
4.1%
Feb-Mar, Jul-Oct
0.8%
-- (a)
5
1.7%
Feb
0.6%
-- (a)
10
1.9%
Feb-Mar
0.7%
-- (a)
6
4.0%
Mar-Apr
1.7%
-- (a)
Upland/ Foothills
7
4.8%
Sep-Oct-Nov
0.2%
-- (a)
8
2.6%
Jan-Feb
0.2%
-- (a)
EF = Long term average exceedance frequency of the 95th
percentile site-wide relative concentration
(a) FugativeFugitive emissions are likely of
reletivelyrelatively low importance at locations far from the
production plant
Figure 11-1.Panel A Candidate Air Sampling Locations
September,2015
A Sector Division
Candidate Sampling
Station Locations
0.5
Aerial Imagery:Google Earth 612712015
ENCLOSURE 2- Revised Worksheet 11: Data Quality Objectes (incl.
Attachments A-D)
September 17, 2015
11-22
Figure 11-1.PanelB Candidate Air Sampling Locations
September,2015
A Sector Division
Candidate Sampl ng
Station Locations
250500
I.OOOFHt A.
N
Aerial magery Google EarthJune 2015
ENCLOSURE 2 – Revised Worksheet 11: Data Quality Objectes (incl.
Attachments A-D)
September 17, 2015
Figure 11-2. Seasonal Variation Between Foothills and Upland
Locations
Monthly Average Relative Concentrations for Transect A
1.0
0.9
0.8
0.7
0.6
Mean Conc
0.5
0.4
0.3
0.2
0.1
0.0
02468101214
a b c d
Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
Monthly Average Relative Concentrations for Transect B
1.4
a
1.2
b
1.0c
0.8d
Mean Conc
0.6
0.4
0.2
0.0
02468101214
Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
11-23
ENCLOSURE 2 – Revised Worksheet 11: Data Quality Objectives
(incl. Attachments A-D)
September 17, 2015
Figure 11-3
Human and Ecological Occupancy Patterns
Zone Receptor Jan
Shrimper, Resource manager
Feb
Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Lakeshore
Birds
Mammals
Winter resident Breeding and migration
Winter resident
Central
Upland/ Foothills
Workers (US Mag, ATI, Hills Bros, BLM) Birds
Mammals
Rancher Rec visitor Hunter
BLM Worker Birds Mammals
Winter resident Breeding and migration Winter resident
Winter resident Breeding and migration Winter resident
11-24
ATTACHMENT A Toxicity Data for Chlorine
ATTACHMENT B
Toxicity Data for Hydrochloric Acid
ATTACHMENT C
Calculation of Effective Mean Concentration
ATTACHMENT DA
AERMOD Calculations of Relative Exceedance Frequency at
Candidate Monitoring Locations
