Transcript colowqforum.org

Ammonia Toxicity Model
AMMTOX
Training Session Held 5 Dec 2005
Hosted by EPA Region VIII
Presented by Jim Saunders,
Colorado WQCD
Purpose of Training Session
• Explain rationale for model
• Identify data needs and sources, including
options for use of site-specific data
• Demonstrate operation of model
• Work with test data sets
Assumptions and Disclaimers
•
•
•
•
Familiarity with Excel is assumed
VB programming is NOT covered
Future tech support is not my job
Merits of National Criteria are not open for
discussion
• Ideas and suggestions presented in this
session may not conform to policies of
state or federal permitting agencies
Section 1: Concepts and Construction
Central Question:
Where is there greatest risk of exceeding
stream standard?
Depends on pollutant behavior and control of
toxicity
Location of Controlling Conditions
Control of Toxicity
Control of
Concentration
Concentration
+ pH & Temp
Conservative
Outfall
Downstream, simple
Non-conservative
Outfall
Downstream, complex
How do you handle a problem like
Ammonia?
• Calculating permit limits becomes difficult
when controlling conditions are displaced
downstream
• Good news: solution likely to benefit
discharger
Pattern of Toxicity, Simple Scenario
8
7
5
4
3
2
1
0
0
2
4
6
8
– pH: 6.6
– Temp: 16.3
• Final
– pH: 8.0
– Temp: 10
10
Miles below Outfall
pH
18
Acute Standard
• Rebound
– pH: 0.2/mi
– Temp: 0.7/mi
Temperature or pH
pH
6
• Initial
10
9
8
7
6
5
4
3
2
1
0
16
14
12
10
8
6
4
2
0
0
2
4
6
8
Miles below Outfall
pH
Temperature
Chronic Standard
10
Chronic Standard, mg/L
50
45
40
35
30
25
20
15
10
5
0
Acute Standard, mg/L
9
• Simple
Scenario pH,
temperature
• Initial ammonia
= 5.5
• Loss = 3/d
• V= 2 fps
Ammonia Concentration, mg/L
Pattern of Toxicity, Complex Scenario
7
6
5
4
3
2
1
0
0
2
4
6
8
Miles below Outfall
Chronic Standard
Ammonia
10
Required Tasks
• Define d/s trajectory of stream standard
• Define d/s trajectory of ammonia
concentration
• Determine maximum effluent
concentration such that instream ammonia
will not exceed standard at any point
downstream
Trajectory of Standard
• Effect of effluent on stream chemistry
generally elevates standard
• Effect is transitory
• Initial value of standard declines
downstream because underlying controls
(pH and temperature) trend separately
toward “equilibrium” values
• Greatest risk of exceedance may occur
anywhere between outfall and equilibrium
conditions
What is equilibrium?
• Stable pH and temperature characteristic
of this mixture of effluent and stream water
• May differ from upstream conditions,
especially if effluent flow is large
• Equilibrium is dynamic with substantial diel
and seasonal variation in pH and
temperature
• This variability must be captured in
standard
Trajectories for pH and Temperature
• Initial mixed conditions defined from flowweighted mean pH and temperature
• Effect of effluent on stream pH and
temperature is transitory
• Initial mixed pH and temperature trend
separately toward “equilibrium” values
• If the equilibrium value and the rate of
change are known, pH or temperature can
be predicted at any point downstream of
the outfall
Setpoint: Equilibrium with Regulatory
Twist
• pH and temperature associated with
greatest risk of exceeding ammonia
standard for equilibrium conditions
• Worst case in each month, subject to
once-in-three-year exceedance
• Terminus for pH and temperature
trajectories, not a fixed location
Why Obtaining Setpoint is Difficult
• Sole task of Recur model
• Field grab samples form framework
• Apply characteristics of temporal variation to
construct set of hourly values spanning entire
period of record
• Calculate standards hourly and determine acute
(1-h) and chronic (30-d) values consistent with
once-in-three-year exceedance threshold
• Find associated pH (acute and chronic) and
temperature (chronic)
Application for Setpoint
• Hidden hand – guides pH and temperature
toward target with regulatory meaning
• Essential for producing d/s trajectory of
ammonia standard, separately for acute
and chronic
Back up a step....
Incorporation of temporal variation
• pH and temperature in stream exhibit
temporal variation of diel and seasonal
scales...thus applies to standard, too
• Predictable diel pattern
– Based on sine curve
– Given amplitude and time of max, one grab
value can define complete 24-h pattern
– Model contains defaults, or user can supply
o
Temperature,
• Pattern of each
is predictable
(sine curve)
• Asynchronous
pH and
temperature
patterns
C
18
9.0
8.8
8.6
8.4
8.2
8.0
7.8
7.6
7.4
7.2
7.0
16
14
12
10
8
6
4
2
0
00:00 04:00 08:00 12:00 16:00 20:00 00:00
Temperature pH
pH
Diel Patterns of Variation
Adjusting Grab Sample Data
10
Daily Maximum
8
Predict ed Temperature
• Translate grab
sample to daily
average or
maximum using
amplitude and
time of
maximum
9
Amplitude
7
Grab Sample
6
5
Daily Mean
4
3
2
1
0
0:00
6:00
12:00
Time of Day
18:00
0:00
Implications for Toxicity
1.4
1.2
pH-dependent Component
• Time of day
matters
• Not a sine
function
• Average toxicity
is not same as
toxicity based on
average pH and
temperature
1.0
0.8
0.6
0.4
0.2
0.0
0:00
4:00
8:00
12:00
Time of Day
16:00
20:00
0:00
Empirical Seasonal Pattern
• Driven by pattern observed in recent
historical record
• Temperature shows strong seasonal
variation in mean; tracking air temperature
• pH shows strong seasonal variation in
amplitude; result of biological activity
Seasonal Variation: Temperature
• Strong pattern
• Monthly time step
• Importance of
physical
processes
Temperature, oC
30
25
20
15
10
5
0
Oct-92
Jul-93
Apr-94
Max
Jan-95
Min
Seasonal Variation: pH
South Platte at Englewood
9.5
9.0
8.5
pH
• Seasonal
change in
maxima, but
not in minima
• Amplitude
varies across
sites in same
region
• Importance of
biological
processes
8.0
7.5
7.0
Dec-00
Apr-01
Jul-01
Daily Max
Oct-01
Jan-02
Daily Min
May-02
Next Task: Ammonia Trajectory
• Initial concentration determined by mass
balance calculations
• Change in concentration d/s affected
strongly by biological processes (i.e., nonconservative behavior)
• Dominant process: nitrification
• Others: uptake (-), ammonification (+)
• Model represents a net loss rate
• Nitrification
reduces
ammonia
• First order
kinetics
• Any loss
increases
limits
Ammonia Remaining
Why Non-conservative Matters
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0.0
0.5
1.0
1.5
2.0
Tim e, days
K3=1
K3=2
K3=4
K3=8
K3 Temperature Dependence
• Nominal rate applies at 20oC
• Ambient rate sensitive to temperature (8%/oC)
Ambient K3, per day
30
25
20
15
10
5
0
0
5
10
15
20
Stream Temperature, o C
K3=6
K3=2
K3=12
25
30
Revisit Scenario with New K3
Ammonia Concentration, mg/L
• Interaction of loss rate and d/s trajectory of standard
• Importance of site-specific data
7
6
5
4
3
2
1
0
0
2
4
6
8
10
Miles below Outfall
Chronic Standard
Ammonia (K3=3)
Ammonia (K3=6)
Next Task: Linking Limits to Standards
• AMMTOX sets monthly limits by manual
iteration (i.e., trial and error)
• Aiming for maximum effluent concentration
such that instream ammonia will not
exceed standard at any point downstream
Ammonia Concentration, mg/L
Trial Iteration
7
6
5
4
3
2
1
0
0
2
4
6
8
10
Miles below Outfall
Chronic Standard
Ammonia (Co=5.5)
Ammonia (Co=4.5)
Organization of AMMTOX
• Recurrence model
– Defines setpoint conditions, integral to
mapping downstream trajectory of toxicity
• Reach Model
– Predicts downstream pattern of stream
standard based on expected spatial patterns
in pH and temperature
– Predicts downstream changes in total
ammonia based on first order kinetics
– Employs graphical approach for setting permit
limits
Section 2: Data Needs and Sources
• Setpoint Determination
– Grab samples from equilibrium stream
conditions; 3-5 yrs, weekly-monthly
– Diel patterns of variation for pH and
temperature (amplitude, time of max)
• Default (3 levels for pH)
• User supplied (confirm or replace default)
– Ecological Conditions
• Implied by classification (warm vs. cold)
• Local knowledge of fish community
Sampling Site Selection
• Ideal site: far enough downstream for
rebound to be complete, yet not influenced
by tributaries, etc.
• Practical site
– Upstream OK if too many confounding
influences downstream
– Small effluent: upstream or 2-4 mi downstream
– Large effluent: trajectory based on interim sites
Site-Specific Characterization of Diel
Patterns of Variation
• Summer (July-August best)
• Low flow
• Data logger: 15-min intervals; get
amplitude and time of max
• Grab: sunrise for minima, mid- to late
afternoon for maxima; get amplitude
• With either approach, a few sunny days
will determine usefulness of defaults
700
9.0
600
8.8
500
8.6
400
8.4
300
8.2
200
8.0
100
7.8
pH
Sunlight, W/m2
Sunny Days and pH Amplitude
0
6:00
18:00
6:00
18:00
Time of Day
Light
pH
7.6
6:00
Sampling Time and Default Amplitude
8.40
8.20
8.00
7.80
7.60
7.40
7.20
00:00
06:00
12:00
Low
Medium
18:00
High
00:00
Define Ecological Setting for Reach
Model
• Are salmonids present?
– Default assumption might be yes for Cold
water classification
– Affects pH component (applies to acute and
chronic standards)
• Are Early Life Stages (ELS) present?
– Must specify for each month
– Applies to all species in fish community
– Affects temperature component (does not
apply to acute)
Salmonids and Effect of FAV
60
CMC, mg/L
50
40
30
20
10
0
6.5
7.0
7.5
8.0
pH
Present
Absent
8.5
9.0
Acute Values (CMC)
•
•
•
•
1-h average
Nonlinear function of pH
Not a function of temperature
Linear function of FAV
– Salmonids present: 11.23
– Salmonids absent: 16.8
Temperature Dependence and ELS
CCC Temperature Dependence
5.0
4.5
4.0
Adjustment Term
• T<7oC; max
effect of ELS
• 7<T<14.5oC;
diminishing
effect
• T>14.5oC; no
effect of ELS
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
5
10
15
20
Tem perature, oC
ELS present
ELS absent
25
30
Chronic Values (CCC)
•
•
•
•
30-d average
Nonlinear function of pH
Linear function of FAV
Nonlinear function at higher temperature
– Invertebrate slope: 10-0.028*(T-25); T>7oC
• Linear function at lower temperature
– ELS absent; invertebrate GMCV (1.45)
applies at T<7
– ELS present; fish GMCV (2.85) applies at
T<14.5
Reach Model Inputs
• Flows
• Water Quality
• Basis for trajectories
– Rebound
– Setpoint
– K3
– Travel time
• Characteristics of standards
• Consistency with Recur Model (not linked)
Hydrologic Conditions
• Upstream: Regulatory low flow (e.g.,
DFLOW)
• Effluent: Design capacity
• Tributaries and diversions: preserve low
flow regime; reconstructions and DFLOW
by difference
• Seepage: Residual between gages;
includes alluvial discharge, direct surface
runoff and small, ungaged tributaries
Input Water Quality
• Avoid worst of worst scenarios
• Upstream: average or median
• Effluent (pH, temperature): average or
median
• Seepage: average or median
• Diversions: no direct effect on WQ
Rebound Rates
• Default rates used in AMMTOX
– pH: 0.2 units per mile
– Temperature: 0.7 oC per mile
• Site-specific rates are very rare
• Produces gradual, linear shift toward
setpoint conditions
o
• Addition of effluent
changes
temperature and
depresses pH in
stream
• Shift is transitory,
but can be
dramatic
Temperature, C
Spatial Patterns of Variation
18
16
14
7.6
7.5
7.4
7.3
7.2
7.1
7.0
6.9
6.8
6.7
6.6
6.5
12
10
8
6
4
2
0
0
5
10
15
Distance, mi
Temperature
pH
Ammonia Loss Rate
• Measured for many CO streams
• Wide range of values; generous default
• Study design considerations
– Paired samples d/s of mixing zone
– Travel time critical; must be able to see
change in concentration
– Detection limit and resolving power
– Implications for DO modeling
– Dilution by seepage vs. biological decay
Velocity
• Channel Geometry
– Default
– Site-specific: USGS Surface-water
Measurements
• Manning’s Eqn
• Fixed Value; enter manually by reach
• Special Considerations
– Acute and chronic can be set separately
– Multiple equations or approaches can be used
when proper links are established
Time of Travel
St Vrain at Lyons
10
0.6405
Average Velocity, ft/s
y = 0.0788x
2
R = 0.989
1
0.1
10
100
Discharge, cfs
1000
Design of Basic Sampling Program
• What
– Stream: pH, temperature, time, ammonia (u/s)
– Effluent: pH, temperature
• When
– Stream: biweekly or monthly
– Effluent: individual, not DMR summary
• Where
– Upstream
– Downstream (equilibrium conditions)
• Supplemental
–
–
–
–
Ammonia loss rate
Diel variation in pH and temperature
Seepage
Velocity