Manure Irrigation: Airborne Pathogen Transport

and Assessment of Technology Use in Wisconsin

Waste to Worth

March 31, 2015

Seattle, WA

Becky Larson, Ph.D.Assistant Professor & Extension Specialist, UW – Madison

Mark Borchardt, Ph.D. Research Microbiologist, USDA-ARS

Dr. Susan Spencer, Dr. Tucker Burch, Dr. Chris Choi, Zach Zopp, Yifan Liang

2

Why Study Manure Irrigation?

3

Workgroup Outline

• Led by Dr. Ken Genskow, University of Wisconsin-

Madison

• Workgroup consists of many different stakeholders

18 members

• Assess application benefits and concerns in comparison

to other practices

• Examine impacts related to human health, water quality,

air quality, drift, etc.

• http://fyi.uwex.edu/manureirrigation/

• Workgroup report to be completed in the Spring of 2015

4

Benefits

• Reduced hauling costs

• Reduced road traffic and the issues

associated (when pumped)

• Multiple crop applications

• Potential to reduce irrigation water demand

• Reduced soil compaction

• Use when storage may overtop

• Water quality

5

Challenges

• Odor

• Drift

• Water quality

• Air quality

• Operational issues

• Human health concerns from pathogens and other additives

• Lack of data

6

Traveling Gun

7

8

Center Pivot

9

10

11

12

13

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Field Measurements

Portable Weather Station

• wind direction and speed

• air temperature

• solar radiation

• relative humidity

Commensal Microbes and Pathogens

• qPCR

• conventional culture

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Field Sampler Configuration

Wind direction

Gun tow path

100 Ft 200 Ft 350 Ft 500 Ft 700 Ft

0 Ft

Upwind

controls

Button sampler

Note: Paired samplers were

located 50 Ft apart.

0 Ft

200 Ft wide spray path

400+ Ft

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Summary of Experimental Trials

• 3 farms

• 25 trials conducted 2012 - 2014

8 center pivot trials

15 traveling gun trials

2 tanker trials

3 nighttime trials

15 trials with bacterial culture data

25 trials with qPCR (i.e., genetic marker) data

• Two trials omitted because wind direction shifted

90°during irrigation

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Mean

temperature

(°F)

Max wind

speed

(MPH)

Mean wind

speed (MPH)

Mean solar

irradiance

(W/m2)

Mean relative

humidity (%)

Weather Conditions

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Microbe Manure Detections %

(# trials measured)

Downwind Air Detections

%

(# air samples measured)

Bovine Bacteroides

by qPCR

100%

(18)

82%

(185)

Gram negative bacteria

by culture

100%

(10)

54%

(127)

E. coli (commensal)

by culture

100%

(8)

11%

(92)

Enterococci spp.

by culture

100%

(10)

56%

(98)

Campylobacter jejuni

by qPCR

89%

(18)

17%

(176)

Campylobacter jejuni

by culture

70%

(10)

6%

(112)

E. coli O157:H7

by qPCR

0%

(17)

Not measured

Salmonella spp.

by qPCR

0%

(17)

Not measured

Salmonella spp.

by culture

0%

(10)

0.8%

(126)

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Pathogens

InhaledPool of

Doses

10,000

Iterations

Individual

Dose

0.8

Ingestion5

1. Hutchison et al. 2004

2. US Department of Agriculture 2003

3. US Census Bureau 2010

4. US Environmental Protection Agency

2011

5. Idaho Department of Environmental

Quality 2006

Pool of

Individuals

Inhalation

Rate4

Time

Outdoors4

(Assume

irrigation)

Inhalation

Volume

WI

Age3

Random

Draws

Air

Samples

Surrogate

Conc. at

Distance

Pathogen

Conc. at

Distance

Model Pathogen:Surrogate1,2

Calculating Pathogen Dose

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Assumptions of Basic E. coli O157:H7

Scenario

1. E. coli O157:H7 prevalence = 38.5%

2. E. coli O157:H7 concentration in

manure = 2.6×105 CFU/L manure

3. E. coli O157:H7 is aerosolized like

bovine Bacteroides

4. E. coli O157:H7 survival characteristics

are the same as bovine Bacteroides

Pathogen: E. coli O157:H7Surrogate: bovine BacteroidesOutcome: risk of illness at 500 feet from irrigation

Pathogen: E. coli O157:H7Surrogate: bovine BacteroidesOutcome: risk of illness as function of distance

Pathogen: E. coli O157:H7Surrogate: bovine BacteroidesOutcome: worst-case (100% prevalence) risk of illness at 500 feet from irrigation

Pathogen: E. coli O157:H7Surrogate: bovine BacteroidesOutcome: worst-case (100% prevalence) risk of illness as function of distance

Pathogen: E. coli O157:H7Surrogate: culturable gram negative microorganismsOutcome: risk of illness at 500 feet from irrigation

Pathogen: E. coli O157:H7Surrogate: culturable gram negative microorganismsOutcome: risk of illness as function of distance

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Risk estimates are conservative

towards protecting public health

because…• Bovine Bacteroides as a surrogate exhibits high

resistance to environmental inactivation

• qPCR measurements overestimate the number of live

bacteria

• In worst-case scenario, E. coli O157:H7 prevalence is

assumed to be 100%

• Dose-response model derived from outbreak data, likely

represents:

the most virulent pathogen strains

the most vulnerable human populations

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Results

Distance

Ris

k

Estimate from this

study

Acceptable level

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Basic Models

• Gaussian Dispersion Model

•(Pasquill, 1961); (Peterson and Lighthart, 1977); (Teltsch et al., 1980);

(Lighthart and Mohr, 1987); (Down et al., 2000); (Dungan, 2010)

𝑄 : Microorganism release rate [copies/s]

𝑢 : Wind speed [m/s]

𝜎𝑦 : Horizontal dispersion coefficient [m]

𝜎𝑧 : Vertical dispersion coefficient [m]

𝑦 : Receptor distance from centerline [m]

𝑧 : Receptor height from ground [m]

𝜆 : Microbial decay constant [s-1

]

𝑡 : Time [s]

𝐸 : Aerosolization efficiency factor [-]

𝑄 = 𝑊𝐹𝐼

𝑊 : Microorganism concentration in the source [CFU/L]

𝐹 : Application rate [L/s]

𝐼 : Impact factor [-]

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Field Sampling Data

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Model vs Field Data

• Travelling gun #3

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Thank you