Draft Ambient Water Quality
Guidelines for Sulfate
In British Columbia
Water Protection & Sustainability Branch
October 13th, 2011
1
Overview
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Review process
Background concentrations
WQGs vs. WQOs
Data requirements
Process for Sulfate guideline
Maximum likelihood estimates
Model Averaging
Questions sent from MABC
2
Guidelines Development & Review
WQG
Development
Priority Setting
MoE
Document
Drafting
Draft
Internal Gov’t
Review
Draft External
Review (peer,
public)
Final for
Approval
Posted
3
Table 1. Summary of ambient dissolved sulfate concentrations in BC freshwaters.
Sulfate background concentrations
in BC
10th
percentile
1.2
Mean
value
6.8
90th
percentile
9.3
883
Lower Mainland
1.0
12.8
18.5
185
Southern Interior
1.0
5.6
19.0
253
Okanagan
2.4
21.6
59.6
1370
West Kootenays
4.7
10.8
14.0
394
East Kootenays
2.3
28.4
64.3
728
Cariboo
1.0
12.5
17.7
1551
Skeena
0.9
12.2
21.8
822
Omineca-Peace
1.0
26.1
61.9
272
Region
Vancouver Island
n
4
Water Quality Guidelines
• Science-based and intended for generic provincial
application
• Protect most sensitive species and life stage during
indefinite exposure
• All higher components of the aquatic ecosystem (e.g.
algae, macrophytes, invertebrates, amphibians, fish) are
considered if the data are available.
• Maximum – protect against lethal effects
• 30-day average – protect against sub-lethal effects
5
Water Quality Objectives
• Refinement of BC-approved & working WQGs
• Developed to protect the most sensitive water use,
at a specific location, taking local circumstances into
account
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What are WQGs and WQOs used for?
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Input to permits, licenses, orders and regulations
As benchmarks
To report to the public on water quality
To determine if remedial action is necessary
To promote water stewardship
7
Data Requirements
 Acute (max) & chronic (30-d avg)
 Fish
– ≥ 3 freshwater species resident in BC, ≥ 2 cold-water (e.g.
trout)
 Invertebrates
– ≥ 2 invertebrates from different classes, 1 planktonic species
resident in BC (e.g. daphnid)
 Plants
– ≥ 1 freshwater vascular plant or algal species resident in BC
• Amphibians
– Highly desirable
8
Preferred endpoints
•
Most appropriate ECx/ICx representing a low-effects
threshold > EC15-25/IC15-25 > LOEC > MATC > EC26-49/IC26-49
Uncertainty factors (typically between 2-10)
•
Decided on case-by-case basis based on data quality and
quantity, toxicity of the contaminant, severity of toxic
effects, bioaccumulation potential and scientific judgement.
9
Sulfate WQG development
• Literature review
• Conduct chronic toxicity tests (PESC)
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Rainbow trout
Chinook salmon
Fathead minnow
algae
Hyalella
Freshwater mussel
Bullfrog
– *note all species were tested at 50, 100, and 250 hardness
10
Sulfate WQG development
• Later we received Elphick et al. (2011) data
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Rainbow trout
Coho salmon
Ceriodaphnia
Rotifer
Hyalella
Fathead minnow
Tree frog
– Algae
– Moss
(15 hardness)
(15 hardness)
(40, 80, 160, 320 hardness)
(40, 80, 160, 320 hardness)
(80 hardness)
(40, 80, 160, 320 hardness)
(15, 80 hardness)
(10, 80, 320 hardness)
(15 hardness)
11
Sulfate WQG development
• Statistical analysis (MLE) of toxicity data from PESC and
Elphick et al. (2011)
– Reviewed hardness and sulfate toxicity data with
species and endpoints tested
– No consistent relationship between water hardness
and sulfate toxicity (similar results reported in Elphick
et al. 2011).
• MLE results sent to MABC for review – concern with
model choices and sensitivity of model choice at loweffect concentrations – model averaging
12
Maximum Likelihood Estimates
• Method to fit curves to data (e.g. dose-response of
sulfate vs. mortality)
• Quantal responses (mortality) - use Probit model
• Continuous responses (e.g. growth) - Isotonic regression
(ICPIN), or 3-p log-logistic
• After fitting model, assess goodness-of-fit (residual plots,
etc)
• Use fitted curve to estimate LCxx values. Caution advised
if extrapolating to very low effect LCxx endpoints, e.g.
LC01 or LC001 values.
• MLE extracts all information from data but must choose
appropriate models
13
Model Averaging
• Problem
– Different models can lead to (greatly) different estimates of
LCxx
– Relying on a single model's estimates can be misleading.
• Solution:
– Fit several models
– Find relative support for fit of models to data using AIC =
trade-off of fit and complexity
– Weighted average of model estimates of LCxx incorporates
model uncertainty
14
BC Draft Sulfate WQG
• New chronic guideline 65 mg/L - based on 28-day LC10 of
rainbow trout of 127 (47-342) mg/L with minimum
uncertainty factor of 2.
• Increased maximum guideline from 100 to 250 mg/L –
based on LC50 data (C. dubia, D. Magna, Hyalella) with
minimum uncertainty factor of 2.
15
BC Draft Sulfate WQG
• Water hardness may decrease the toxicity of sulfate for some
endpoints and species; however, no consistent relationship
was found.
• Site-specific water quality objectives using site water would be
more appropriate for determining if the ion composition
decreases, increases or has no-effect on sulfate toxicity to
organisms in a particular water body.
• The development of site-specific water quality objectives to
take local conditions into consideration is done with
consultation with Ministry of Environment staff.
16
MABC Questions received
1) “Early lifestage tests using trout
Test validity: We would like to discuss control performance of the
early life stage rainbow trout tests. We do not believe that the
control in the soft water test passed a reasonable test performance
criterion for this type of test. Furthermore, we are concerned that
the poor survival in the soft water, and the high degree of
variability in this test is indicative of a stressed population of
test organisms, and that these tests should be rejected because of
QA/QC concerns.”
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Response (Craig Buday - Pacific & Yukon
Laboratory for Environmental Testing (PESC))
• The acceptable cumulative control mortality cannot
be > 35% (65% survival or better is OK.)
• For the R. trout eyed egg test there was 27%
cumulative mortality or 73% survival which passes
the validity criteria.
Environment Canada 1998. Biological Test Method: Toxicity Tests Using Early Life Stages
of Salmonid Fish (Rainbow Trout), EPS 1/RM/28 second edition.
18
MABC Questions received
1) “Early lifestage tests using trout
• Statistical analysis: We would like to discuss the
statistical power associated with the early life stage
tests using rainbow trout. Specifically, we do not
believe that the test had sufficient power to detect a
10% deviation from the control with a reasonable
degree of confidence, and that the LC10 value
reported does not make sense in the context of the
dataset.”
19
Response (Carl Schwarz, P. Stat., SFU)
• The sulfate levels vary considerably from control
levels, e,g. up to around 2000. Over the entire range
of measured sulphate level, the probit model
(allowing for overdispersion) had a statistically
significant slope (p=.0016 for hardness 50; p=.0252
for hardness 100; p=.0247 for hardness 200) so an
effect of sulfate level over the range of doses was
detected.
• Once model is fit using ENTIRE dataset, you can
extrapolate back to LC10 values despite there being
large variability in raw data.
20
MABC Questions received
• 3) “Tests using the freshwater mussel
Statistical analysis: We would like to discuss the effect levels
reported for the soft water test using the freshwater
mussel. Specifically, we do not believe that the LC10 reported
in the Draft document is supported by the data because the test
does not have sufficient power to detect that level of effect with
a reasonable degree of confidence, and the statistics used did
not account for background mortality in the control from that
test.
The LC10 value reported does not make sense in the context of
the dataset, and we believe that the LOEC, MATC, LC25 or LC50
might be a more appropriate value.”
21
Response (Carl Schwarz, P. Stat., SFU)
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Mussel "controls" had sulfate levels of 151 (at hardness 250); 60 for hardness
100; 30 for hardness 50. "Control" mortality was 10% at hardness 50 (1 of 10
died); 10% at hardness 100 (1 of 10 died); and 0 (0 of 10 died) at hardness 250.
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We did not fit a model with a natural response because the data are simply too
sparse to fit such a model with very small sample sizes, the control doses are
not at 0 sulphate and virtually no changes over the sulphate levels presented.
Consequently, it is extremely difficult to know if the mortality observed at the
"control" doses are effects of the "sulfate" or actual mortality. This is reflected
in the very wide confidence limits for the LC10 which indicates that it cannot be
estimated very well.
 The CETIS printouts fitted the linear interpolation model which assumes that the
mortality rate at the control dose is known with "certainty", but again, this is
likely not true because of the very small sample sizes (only 10 organisms on
test).
22
Response (MOE)
• Preferred endpoints:
 Most appropriate ECx/ICx representing a low-effects
threshold > EC15-25/IC15-25 > LOEC > MATC > EC26-49/IC26-49
 We report the confidence intervals for all the estimates
in the guideline.
23
MABC Questions received
• 4) Tests using the Pacific Tree frog
Statistical analysis: We would like to discuss the effect levels
reported for moderate hardness test (80 mg/L) using the Pacific
Tree frog. Specifically, the analyses used did not account for
the background mortality in the control from that test and the
LC10 value reported does not make sense in the context of the
dataset. We believe that the point estimates reported by
Elphick et al. (2011) for this test were calculated appropriately
for this test.
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Response (Carl Schwarz, P. Stat., SFU)
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Only 2 hardness levels used. At hardness 15, the control sulfate is given as "1" - was this real or
merely a placeholder for data entry?
No observed mortality observed (0 out of 15 on test). At hardness 80, the control sulfate level is
93 and 2/15 mortalities observed.
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We fit a model where no threshold effect was observed at either hardness level, and the 2/15
mortalities at sulfate level 93 is not unreasonable with the fitted dose response curve. A model
with a control threshold was not fit because of the sparseness of the data.
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If you look at the raw mortality numbers, the effect of sulfate at hardness 80 appears to be
"worse" than at hardness 15 as the total mortalities tend to be higher in general at comparable
sulfate levels. This might be the result of a threshold taking effect at the higher hardness levels,
but is difficult to discern because the control doses are too different between the 2 studies.
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This is also the species where the CETIS printouts use a control threshold in 1 hardness level
and not the other hardness level.
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Need to consider all hardness levels simultaneously. For example, is it biologically reasonable
to have no natural response at hardness 15 and a natural response at hardness 80?
25
MABC Questions received
• 5) “Tests using Hyalella azteca
Statistical analysis: We would like to discuss the effect levels
reported for growth of Hyalella azteca. We do not believe that
these tests are sufficiently robust to calculate an IC10 with a
reasonable degree of confidence. It should be noted that the
data are contradictory to information from other tests
performed by Nautilus, which indicate a lower sensitivity to
sulphate in higher hardness using both growth and survival
endpoints.”
26
Response (Carl Schwarz, P. Stat., SFU)
•
In these studies the observed response "increased" from baseline and then
decreased. We tried a variety of models, but the most suitable was separate
Isotonic Regression model for each hardness level which gave estimates of
1326 at hardness 50, 645 at hardness 100; and 333 at hardness 200.
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CETIS fit a 3P log-gompertz (IC10=683) at hardness 200; a ICPIN=Isotonic
Regression (IC10=638) at hardness 100; a ICPIN=Isotonic Regression
(IC10=1321) at hardness 50.
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Our results are identical to CETIS except for the very hard water, but all our
estimates have very wide confidence limits which are reported in the guideline.
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We didn't have access to this other dataset, but it could be integrated into the
analysis if available.
27
MABC Questions received
• 6) “Tests using fathead minnows (Nautilus data)
Statistical analysis: We would like to discuss the
recalculated LC10 value for 80 mg/L water hardness
(LC10 of 426 mg/L sulphate); this value makes no
sense in the context of the dataset, in which there is
no deviation from the control response at up to 1300
mg/L sulphate.”
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Response (Carl Schwarz, P. Stat., SFU)
•
Raw data has control dose of 37 for sulfate at hardness 40 with 1/30 mortality; control dose
of 74 for sulphate at hardness 80 with 3/30 mortality; control dose of 130 for sulfate at
hardness 160 with 1/30 mortality and control dose of 300 for sulphate at hardness 320 with
0/30 mortality and EC10 1555;
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Two top models are the separate probit model (model weight 0.53) and the monotonic
effect of hardness model (model weight of 0.47). Neither has a natural response.
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Estimated LC10 were 301 for hardness 40; 426 for hardness 80; 1074 for hardness 160;
2318 for hardness 320.
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CETIS EC10 were
2450 for hardness 320 (with a 0% threshold);
3231 for hardness 160 (with a 10% threshold)
1555 for hardness 80 (with a 10% threshold)
558 for hardness 40 (with a 3% threshold);
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The key differences was the use of the threshold by CETIS and no threshold by us. The
CETIS thresholds don't vary in a consistent fashion, i.e. threshold goes from 3% to 10%
and down to 0%. Is this a sensible thing for thresholds? Given the non-zero sulphate levels
at "control" doses the observed mortality is consistent with an effect of sulphate rather
than a threshold.
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MABC Questions received
• 7) “Selection of point estimates - General
We would like to discuss problems with calculation
and use of tenth percentile effect levels from tests
that allow 10 or 20 percent effect in the control as
acceptable, and in which the minimum significant
difference that is statistically detectable is typically
in the range of 20 to 30%. In such tests, variability
precludes calculation of 10th percentile estimates
with a reasonable degree of confidence.”
30
Response (Carl Schwarz, P. Stat., SFU)
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Yes, there can be problem where the threshold effects are large
and the control "doses" are not zero. Are these effects of the
sulfate or natural responses?
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Yes, trying to estimate small changes from an ill-determined
baseline is problematic and likely highly model dependent, but
don't forget that the ENTIRE dataset is used to fit the curve and so
a reasonably well fitted dose-response curve does provide some
(but not overwhelming) information about small effects. The
alternative is larger experiments.
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Caution would be advised if estimating very small effects, e.g.
LC01 or LC001, but LC10 is well within the range of observed data.
•
Wide confidence limits would indicate poor estimates. Model
averaging would account for estimates that are highly model
dependent.
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MABC Questions received
• 8) “We would also like to discuss inconsistencies
between MoE guidance on deriving water quality
• guidelines, which suggest that "the lowest observedeffect concentration (LOEC) or EC(low-effect
generally thought to be EC15-20) from a reliable
chronic exposure study, preferably on sensitive
native BC species, are selected.".
32
Response (MOE)
 Preferred endpoints:
 Most appropriate ECx/ICx representing a low-effects
threshold > EC15-25/IC15-25 > LOEC > MATC > EC26-49/IC26-49
 We will clarify in the Derivation document
33
MABC Questions received
• 9) “Selection of statistical methods - General
• We would like to discuss the use of linear
interpolation for determination of point estimates
from data sets with continuous data, since this
approach is considered less appropriate than nonlinear regression by Environment Canada".
34
Response (Carl Schwarz, P. Stat., SFU)
•
Yes, there are problems in using the linear interpolate (isotonic
regression) method. Note that CETIS often chooses this type of model as
well (!). One problem is that there is no possibility to extrapolate below the
smallest observed dose nor above the largest observed dose.
•
Another problem is that the method implicitly chooses the observed
response at the lowest dose as the baseline against which effects are to
be determined, i.e. the EC10 is 10% below baseline. If the control dose is
far from "0" this may not be appropriate.
•
We modelled continuous measurements (such as weight) using several
different models (the 3 parameter logistic) but these may not fit as well.
There are hundreds of other models that could be fit, but regardless of the
model, extrapolation before the smallest observed dose must be taken
with a grain of salt as there is no data available.
•
Estimates of moderate effects, e.g. LC25 or LC50 likely don’t depend very
much on model (assuming doses cover the endpoint). Estimate of LC10 is
more model dependent, but still within the range of observed doses.
35
MABC Questions received
• 10) “Role of water hardness in modifying acute toxicity: We
would like to discuss the role that water hardness plays in
altering the acute toxicity of sulphate. Toxicity test results
from acute toxicity tests are consistent with the conclusion that
water hardness reduces toxicity of sulphate (with the sole
exception being Chironomids, which are insensitive to
sulphate), and we would like to discuss why water hardness
was not incorporated into the maximum guideline for
sulphate".
36
Response (MOE)
• BC Water Quality Guidelines intended for generic provincial
application
• Protect most sensitive species and life stage during indefinite
exposure
• We did not find a consistent relationship with water hardness
and sulfate toxicity
37
MABC Questions received
• 11) “Role of water hardness in modifying chronic toxicity: We
would like to discuss why it is necessary that decreasing
toxicity with increasing water hardness is observed with all test
species. As long as sensitive test organisms are protected
across the full range of hardnesses, it should not matter is
some less sensitive species do not show less sensitivity to
sulphate at higher hardness.".
38
Response (MOE)
• BC Water Quality Guidelines intended for generic provincial
application
• Protect most sensitive species and life stage during indefinite
exposure
• We did not find a consistent relationship with water hardness
and sulfate toxicity
39
MABC Questions received
• 12) “Role of total dissolved solids in toxicity to
Ceriodaphnia: We would like to discuss adverse effects
observed with Ceriodaphnia in 320 mg/L water hardness, and
the relevance of this datapoint to setting water quality
guidelines for sulphate".
40