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

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

Large Quantities of Manure and

Wastewater Produced

~58 kg manure/cow/day

23x106 kg manure/year in southern

Idaho

Volume of wastewater?

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

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.

Push to Ban Manure Spraying

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

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)

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

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

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

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

Receptor Setup in AERMOD

Pathogen Emissions Rates for

use in AERMODScenario 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

Sensitivity Analysis (Effect of

Averaging Period and Emission

Rate)

Downwind (km)

2 4 6 8 10

Pa

tho

gen

(cell

s m

-3 o

f a

ir)

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

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

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

Risk of Infection After a 1-h

Exposure Event at 1 km Downwind

(Daytime)L

og R

isk

of

Infe

ctio

n

-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:H7Non-O157 Listeria Salmonella C. jejuni E. coli

O157:H7Non-O157 Listeria Salmonella

Risk of Infection After a 1-h

Exposure Event (Nighttime)

-14

-12

-10

-8

-6

-4

-2

0

Scenario A (Low)

1 5 10 k

m

1 5 10 k

m

1 5 10 k

m

1 5 10 k

m

1 5 10 k

m

C. jejuni E. coli

O157:H7Non-O157 Listeria Salmonella

Log R

isk

of

Infe

ctio

n

-14

-12

-10

-8

-6

-4

-2

0

Scenario C (High)

Scenario B (Medium)

C. jejuni E. coli

O157:H7Non-O157 Listeria Salmonella

1 5 10 k

m

1 5 10 k

m

1 5 10 k

m

1 5 10 k

m

1 5 10 k

m

Scenario D (Very High)

Campylobacter jejuni (1 km,

Daytime)

-14

-12

-10

-8

-6

-4

-2

0

Scenario A Scenario B Scenario C Scenario D 1h

8h

24h

Log R

isk o

f

Infe

ction

Campylobacter jejuni (1 km,

Nighttime)

-14

-12

-10

-8

-6

-4

-2

0

Scenario A Scenario B Scenario C Scenario D 1h

8h

24h

Log R

isk o

f

Infe

ction

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

Log R

isk o

f

Infe

ction

* Risk of infection near

zero

*

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

Log R

isk o

f

Infe

ction

Salmonella (1 km, Daytime)

-16

-14

-12

-10

-8

-6

-4

-2

0

Scenario A Scenario B Scenario C Scenario D1h

8h

24h

* *

* Risk of infection near

zero

Log R

isk o

f

Infe

ction

Salmonella (1 km, Nighttime)

-16

-14

-12

-10

-8

-6

-4

-2

0

Scenario A Scenario B Scenario C Scenario D1h

8h

24h

Log R

isk o

f

Infe

ction

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

Thank

You