quantifying nutrient removal by street sweeping -lid talk
TRANSCRIPT
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University of Minnesota
Paula Kalinosky, Lawrence Baker, Sarah Hobbie, Chris Buyarski, In Partnership with the City of Prior Lake, MN
Ross Bintner LID Symposium, August 20, 2013
Quantifying Nutrient Load Recovery through Targeted, Intensive Street Sweeping
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Summary of Questions Addressed
Why Revisit Street Sweeping?
What’s Different About the Prior Lake Street Sweeping Study?
What was found in Prior Lake?
How is this information useful?
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Statement of Problem
Nutrient management is a significant
concern in urban watersheds
Streets act as a conduit for pollution to the storm drainage
network
Meeting watershed management goals
(TMDL, permits) can be costly $$
Is Street Sweeping a Cost-effective Source Control BMP?
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Study Design Nine Study Routes
LOW Canopy MEDIUM Canopy HIGH Canopy
1 X, 2X, 4X/month 1 X, 2X, 4X/month 1 X, 2X, 4X/month
Q: What is the relationship between overhead tree canopy and recovered solids, nutrients?
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Distribution of Sweeping Routes
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Focus on Recovered Material
Collection Protocol WEIGH
INSPECT
DUMP
INSPECT
SAMPLE
INSPECT
Material Removed From the Street is Not Available for Transport
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Lab Methods: Unique Fractionation Scheme
Suited to Focus on Nutrients
Fines (<2mm)
Coarse Organics (≥2mm)
Rocks (≥2mm)*
TP, TN, TOC (Leached during separation process)
TS, TP, TN, TOC, % Organic TS, TP, TN, TOC, % Organic
* Dry mass only, nutrient contribution assumed negligible.
Sweeper Waste
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Findings: Recovered Solids
Average Load Recovered per Month Dry Solids (lb/curb-mile)
Sweeping Frequency Low Canopy Med Canopy High Canopy
1X/mo 183 219 435
2X/mo 269 423 664
4X/mo 478 849 649
Big Picture – Loads increase as tree canopy cover increases.
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Seasonal Trends
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
Jan Feb Mar Apr May Jun Jul Aug Se[ Oct Nov Dec
Tota
l Dry
So
lids
(lb
)
Month
Year 1Year 2
Winter Weather Influence
Sep
Influence of month/season on load intensity is significant.
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Role of Coarse Organics
0%
20%
40%
60%
80%
100%
Jun
-10
Jul-
10
Sep
-10
Oct
-10
No
v-1
0
Jan
-11
Feb
-11
Mar
-11
May
-11
Jun
-11
Jul-
11
Sep
-11
Oct
-11
No
v-1
1
Jan
-12
Feb
-12
Mar
-12
May
-12
Jun
-12
Jul-
12
Au
g-1
2
Pe
rce
nt
Load
as
Co
arse
Org
anic
s
Dry Solids Phosphorus Nitrogen
Coarse organics are a significant source of nutrients
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Trends in Cost Effectiveness
$0
$100
$200
$300
$400
$500
$600
$700
2 4 6 8 10 12
Ave
rage
Co
st-e
ffe
ctiv
en
ess
, $/l
b
Rec
ove
red
Ph
osp
ho
rus
Month
L4
H2
Least cost effective
Most cost effective
In high canopy areas, phosphorus can be recovered for less than $100/lb
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Correlation between Tree Canopy Cover and Recovered Phosphorus
R² = 0.84
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0% 5% 10% 15% 20%
Cu
mu
lati
ve P
Lo
ad, S
no
w-f
ree
sea
son
(l
b/c
urb
-mile
)
Percent Tree Canopy Cover Over the Street
Study Total P Load Intensity
1X/mo 2X/mo 4x/mo
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General Model for Predicting Recoverable Loads
E(Load│m, f, c)=
o + 1(month) + 2(frequency) + 3(canopy)
Goal: Produce a tool for estimating nutrient recovery based on easily obtained inputs.
TIMING of sweeping event
FREQUENCY of sweeping events
CANOPY COVER for sweeping route
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Model Validation
Predicted Study Load, Five Fold Cross-Validation
MEASURED MLR
Prediction RT Prediction
Fresh Solids 853855 756549 (-11%)
793020 (-7%)
Dry Solids 618622 547977 (-11%)
565047 (-9%)
Total Phosphorus 502 424 (-16%)
443 (-12%)
Total Nitrogen 1945 1645 (-15%)
1682 (-14%)
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Spreadsheet Planning Tool: User Inputs
Users define sweeping routes for which nutrient recovery will be estimated.
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Spreadsheet Planning Tool: User Inputs
Use supplies a default cost per curb-miles (Prior Lake Method available in Guidance Manual).
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Spreadsheet Planning Tool: Estimate Nutrient Recovery
1. Choose Route
2. Define Sweepings
3. Check Estimates
4. Save Routine
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Spreadsheet Planning Tool: Output, Annual Summary of Sweepings by Route
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Spreadsheet Planning Tool: Output, Summary of Planned Sweepings by Month
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Spreadsheet Planning Tool: Output, Monthly Subtotals for Planned Sweeping
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Predicted vs. Measured, Prior Lake
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Predicted vs. Measured, Prior Lake
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Potential Application: Tracking Nutrient Recovery
Five –Fold Cross-Validation Exercise using Predicted P-concentrations, Regression Trees
P (lb)
Measured Recovered Phosphorus 505
Estimate based on:
Curb-miles Swept 457 (-9.4%)
Fresh Load (lb) 505 (-0%)
Dry Load (lb) 495 (-1.9%)
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Next Steps
EXTRAPOLATE OPTIMIZE QUANTIFY