1. Quantitative Metrics
to Gage the Effects
of an Enhanced
Biodegradation
Program
Iowa Army Ammunitions Plant,
Middletown, Iowa
Melisa Geraghty, Brian
Caldwell, PG; Dr. Tiffany
Downey, Dr. Ronnie Britto,
and Dr. Rick Arnseth

2. Site History
 Iowa Army Ammunition Plant (IAAAP) -
located in Des Moines County, Iowa
 Munitions production and testing beginning in
1941
 Resulted in contamination of the soil,
groundwater, and surface water with
explosives
– Extensive offsite Royal Demolition Explosive
(RDX) groundwater plume sourced by RDX in
surface water runoff.

3.  Off-Site Plume map here

4. Remediation Plan
 To enhance biodegradation and expedite the
natural attenuation of the RDX plume using an
enhanced degradation process (sodium acetate
injection)
– 11 designed-injection wells upgradient of the
highest concentration plume core.
– Analytically modeled injection rates and locations
– Five injection events between October 2007
and April 2009
• initial event employed all 11 injection wells.
• Subsequent events customized injected mass
and number of injection points based on
analytical data

5. Development of Evaluation Metrics
 Remedial progress metrics developed to
account for temporal and spatial comparisons
in order to maintain optimal reducing
conditions
– Quantitative analysis of plume configuration
– Statistical analysis of the RDX concentrations
from individual sampling events

6. Evaluation Metrics Include
 Point by point comparisons
– Statistical trend analysis
– First-order kinetics concentration change
analysis
• degradation rates and times to achieve
remediation goals.
 Plume wide analysis
– Representative population using differential
analysis
– Central Tendency Analysis
– Change in overall plume core mass.

7. Mann-Kendall Trend Analysis
 Non-parametric statistical test (the data are not
required to be normally distributed)
 Assesses point changes in a data set over time for an
increasing or decreasing trend at a given statistical
confidence level.
– Designed to assess four to eighteen rounds of data at
an 80% confidence level
– Determines if the data can be used to estimate a first
order degradation or augmentation rate
– To avoid biasing the MK test, the same value for all ND
results was used (one half of the detection limit from the
round with the lowest detection limit for that well).
– For wells that did not exhibit a increasing or decreasing
trend at an 80% confidence level the coefficient of
variation was used to determine if the well was stable or
unstable

8. Mann-Kendall Trend Analysis Con’t
 For wells that did not have a minimum of four
sampling events or did not exhibit an overall trend
at 80% confidence, the last three measurements
were used to approximate the direction of the
concentration change.
 The point-by-point analysis results indicate an
overall decreasing trend in a majority of the wells.
– 18 wells trended
• 8 = decreasing
• 1 = increasing
• 9 = stable

9. Quantifying a Decreasing Trend
 Plotting of the log-transformed concentrations versus a linear
unit of time (days were used). Finite source degradation is
described by an exponential degradation curve when plotted
on a linear scale. In order to use linear regression to calculate
the slope (the degradation rate), the data were log-
transformed and plotted on a linear scale.
 Performing linear regression calculations on Step 1 by plotting
a trend line (least-squares fit trend line) that minimizes the
variance (squared deviations) of all of the data points from the
line.
 Using the slope of the equation represented by the least-
squares trend line as the fractional change per day. This was
then used to calculate a half-life expressed in days, and to
develop a degradation curve that predicts the time at which
the concentrations at that sampling point will reach 2 ppb.

10. Example Output
DATE RDX (ug/L) Ln Conc. (ug/L)
Degradation Rate
(% per day)
09/28/2007 104 4.644390899 1.021765998
12/19/2007 95.8 4.562262685 1.003697791
02/13/2008 76.9 4.342505877 0.955351293
12/09/2008 41.3 3.7208625 0.81858975
First-order Degradation Rate (day-1) = 0.0022
Half Life (days) = 315.05
Mann Kendall Statistic (S) = -6.0
Number of Rounds (n) = 4
Average = 79.50
Standard Deviation = 27.880
Coefficient of Variation(CV)= 0.351
Trend ≥ 80% Confidence Level DECREASING
Trend ≥ 90% Confidence Level DECREASING

11. Example Output Graphs - Decreasing
y = -0.1440x + 5,771.5677
R² = 0.9731
0
20
40
60
80
100
120
RDXug/L
Date
EMW-06
y = -0.0022x + 90.2403
R² = 0.9880
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
LnRDXug/L
Date
EMW-06
0
5
10
15
20
25
30
35
40
45
0 200 400 600 800 1000 1200 1400 1600
Concentration(ug/L)
Time (days)
Degradation Curve

12. Example Output Graphs – Stable or
Non-Stable
y = 0.0144x - 506.6684
R² = 0.0769
0
10
20
30
40
50
60
70
RDXug/L
Date
IW-05
y = 0.0523x - 1,978.1657
R² = 0.9245
0
10
20
30
40
50
60
RDXug/L
Date
IW-05

13. Example Output Graphs - Increasing
y = 0.0035x - 138.0692
R² = 0.7410
0
0.5
1
1.5
2
2.5
3
3.5
RDXug/L
Date
EMW-08

14. Plume Wide Analysis

15. Plume Core Mass
Plume
Event
Number of
wells sampled
RDX mass
(g)
Change in mass from
Previous events
(g)
Percent
Change
1 16 3,693,903.46 N/A N/A
2 24 61,897,939.34 58,204,035.88 1576%
3 24 61,815,101.54 -82,837.80 0%
4 26 57,380,772.09 -4,434,329.45 -7%

16.  Insert example of plume core mass
wksheet

17. Statistical Mean
 The plume-wide statistical mean decreased
from 101 ppb at baseline in October 2007 to
42.38 ppb in December 2008
 Between December 2008 and December
2009, there was a 70.0% decrease in UCL
means to 12.73 ppb.
 However, based on the differential test
(Kolmogorov-Smirnov), the change in
populations is not statistically significant at a
95% confidence level.
 All data sets result from the same population