1. Estimation of Infectious Risks in
Residential Populations Near a
Center Pivot Spraying Dairy
Wastewater
Robert S. Dungan, Ph.D.
USDA-ARS, Northwest Irrigation and Soils Research
Laboratory, Kimberly, Idaho 83341
Voice: 208.423.6553; E-mail:
robert.dungan@ars.usda.gov

2. Dairy Production in Idaho
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
1975 1985 1995 2005 2015
Number of Milk Cows
Magic Valley
70% of cows

3. Large Quantities of Manure and
Wastewater Produced
 ~58 kg manure/cow/day
 23x106 kg manure/year in southern
Idaho
 Volume of wastewater?

4. Land Application of
Wastewater
 Wastewater is a
combination of
manure liquids,
flush waters, and
lot runoff
 Source of irrigation
water and crop
nutrients
 Quasi disposal
technique

5. Risk of Exposure to
Pathogens
 Wastewaters are not treated prior to land
application
 Variety of zoonotic pathogens present in
cattle manures:
◦ Salmonella spp.
◦ E. coli O157:H7
◦ Campylobacter jejuni
◦ Listeria monocytogenes
◦ Mycobacterium spp.
◦ Leptospira spp.
◦ Yersinia enterocolitica
◦ Cryptosporidium and Giardia spp.

6. Push to Ban Manure Spraying

7. Conceptual Model of Human
Infection from Land Application of
Wastewater
Aerosolization/
Evaporation Dispersion Inhalation
Risk of
infection
Dry/wet deposition
Produce
and
fomites
Ingestion
Small droplets
(< 150 um)
Large droplets
(> 150 um)
Deposition

8. Quantitative Microbial Risk
Assessment (QMRA) Approach
(Pathogen/Microbial
Agent)
(Pathogen Dose
Inhaled and/or
Ingested)
(Risk of Infection Based on
Dose)
(Integration of Information;
Estimate Probability of
Harm)
(Reduce or Eliminate
Risks)

9. Hazard Identification
 Campylobacter jejuni,
Escherichia coli O157:H7
and non-O157, Listeria
monocytogenes, and
Salmonella spp.
 Based on qPCR,
pathogen concentrations
in 30 dairy wastewaters
were found to range from
103 to 106 cells/100 mL

10. Exposure Assessment Model
 d = ec x br x t x ag
 d = number pathogens/dose
 ec = airborne pathogen conc.
(cells/m3 of air); determined
with dispersion model
 br = breathing rate (m3/h); set
to 0.61 m3/h
 t = hours of exposure; 1, 8, or
24 h or multiday (1 h/d for 7 d)
 ag = aerosol ingestion rate;
set to 0.1

11. Dose-Response Model
 b-Poisson model
 Pi = 1- (1 + d/b)-a
• where Pi is the probability of infection
based on a one-time pathogen exposure
• d is the pathogen dose
• a and b are dose-response factor from the
literature
 Probability of infection over a multiday
event determined using Pann = 1- (1- Pi)n
• where n is the number of days per year

12. Dispersion Model Setup
 AERMOD (Steady-state dispersion
model for up to 50 km)
 Area source was 396 m x 15 m to
mimic droplet pattern from a center
pivot with 94 flat plate sprinklers (34
L/min)
 Receptors placed at 1, 2, 3, 4, 5, 7, and
10 km from the pivot, with 10 degrees
of separation (total of 252 receptors)
 Used 5 years of meteorological data
(2000 to 2004); April to October only

13. Receptor Setup in AERMOD

14. Pathogen Emissions Rates for
use in AERMOD
Scenario Flow
rate
(l/min)
Pathoge
n conc.
(cells/100
mL)
Waste-
water
(%)
Sprinkler
impact
factor
Aerosol-
ization
efficiency
(%)
Pathogen
emission
rate (cell/s)
A (low) 3217 103 5 0† 0.1 2.7 x 101
B (Medium) 3217 104 10 0 1.5 8.0 x 103
C (High) 3217 105 10 0 1.5 8.0 x 104
D (Very
high)
3217 106 20 0 3.0 3.2 x 106
† Sprinkler impact on microorganism viability was determined
to be minimal, thus the Impact Factor (I) was set to zero

15. Sensitivity Analysis (Effect of
Averaging Period and Emission
Rate)
Downwind (km)
2 4 6 8 10
Pathogen(cellsm-3ofair)
0
2
4
6
8
10
12
1-h
3-h
24-h
2 4 6 8 10
0
50
100
150
200
2.7x101 cells s-1
8.0x103 cells s-1
8.0x104 cells s-1
3.2x106 cells s-1

16. Additional QMRA
Assumptions
 All bioaerosols were < 100 mm in
aerodynamic diameter
 Aerosol density was 1.1 g/cm3
 Only dry deposition was considered
 Deposition behavior among pathogens
was similar
 Inactivation of airborne pathogens
occurred
 Aerosol age (ad) based on average wind
speed of 4.4 m/s

17. Microorganism Die-Off Factor
 Md = e-lad
• where l is the viability decay rate (/s)
• ad is the aerosol age (s)
 Aerosol age ranged from 3.8 to 38 min
 To account for daytime or nighttime
conditions, respective decay rates of
0.07/s or 0.002/s were used
 The airborne pathogen
concentration was then corrected for
die-off

18. Risk of Infection After a 1-h
Exposure Event at 1 km Downwind
(Daytime)LogRiskofInfection
-16
-14
-12
-10
-8
-6
-4
-2
0
-16
-14
-12
-10
-8
-6
-4
-2
0
Scenario A (Low) Scenario B (Medium)
Scenario C (High) Scenario D (Very High)
C. jejuni E. coli
O157:H7
Non-O157 Listeria Salmonella C. jejuni E. coli
O157:H7
Non-O157 Listeria Salmonella

19. Risk of Infection After a 1-h
Exposure Event (Nighttime)
-14
-12
-10
-8
-6
-4
-2
0
Scenario A (Low)
1
5
10
km
1
5
10
km
1
5
10
km
1
5
10
km
1
5
10
km
C. jejuni E. coli
O157:H7
Non-O157 Listeria Salmonella
LogRiskofInfection
-14
-12
-10
-8
-6
-4
-2
0
Scenario C (High)
Scenario B (Medium)
C. jejuni E. coli
O157:H7
Non-O157 Listeria Salmonella
1
5
10
km
1
5
10
km
1
5
10
km
1
5
10
km
1
5
10
km
Scenario D (Very High)

20. Campylobacter jejuni (1 km,
Daytime)
-14
-12
-10
-8
-6
-4
-2
0
Scenario A Scenario B Scenario C Scenario D 1h
8h
24h
LogRiskof
Infection

21. Campylobacter jejuni (1 km,
Nighttime)
-14
-12
-10
-8
-6
-4
-2
0
Scenario A Scenario B Scenario C Scenario D 1h
8h
24h
LogRiskof
Infection

22. E. coli non-O157 (1 km,
Daytime)
-16
-14
-12
-10
-8
-6
-4
-2
0
Scenario A Scenario B Scenario C Scenario D 1h
8h
24h
LogRiskof
Infection
* Risk of infection near
zero
*

23. E. coli non-O157 (1 km,
Nighttime)
-16
-14
-12
-10
-8
-6
-4
-2
0
Scenario A Scenario B Scenario C Scenario D 1h
8h
24h
LogRiskof
Infection

24. Salmonella (1 km, Daytime)
-16
-14
-12
-10
-8
-6
-4
-2
0
Scenario A Scenario B Scenario C Scenario D
1h
8h
24h
* *
* Risk of infection near
zero
LogRiskof
Infection

25. Salmonella (1 km, Nighttime)
-16
-14
-12
-10
-8
-6
-4
-2
0
Scenario A Scenario B Scenario C Scenario D
1h
8h
24h
LogRiskof
Infection

26. Conclusions and
Recommendations
 Risk assessment is not an exact science
 This QMRA provides a useful starting point to
understand and manage infectious risks associated
with the spray irrigation of dairy wastewaters
 Residential populations ≥ 1 km downwind should
have a very low risk of infection during daytime
applications
 Infectious risks will likely be higher during nighttime
applications (infection  disease)
 Wastewater should be applied during daylight
hours when dilution and microbial die-off are
highest
 Apply the lowest possible percentage of
wastewater to decrease the number of aerosolized
pathogens

27. Thank
You