Accurate Modeling for Drift Reduction:General Overview and Regulatory

Status

April 11th, 2014

Dan Dyer

On Behalf of the CLA Spray Drift Issue Management Team

Spray Drift Regulation

• Spray drift is complex… Ground, aerial, orchard/airblast sprays Broad range of technologies of spray equipment Significant differences in geography/climate Conservative drift models (perceived drift issue)

• But can be well managed… Local applicators/growers understand appropriate

conditions for application and minimizing drift Training / certification / education Pesticide Label Restrictions – wind speed, buffers,

etc. Newer drift reducing technologies

Spray Drift Regulation

• Recently released spray drift guidance for use of AgDRIFT in human and ecological exposure/risk assessment EPA-HQ-OPP-2013-0676 “Consideration of Spray

Drift in Pesticide Risk Assessment”

• CLA supports development of appropriate drift assessment methodologies

• However, EPA guidance is too restrictive and is limited in ability to make higher tier refinements

Factors Influencing Spray Drift

• Spray Characteristics Droplet size

Chemical / Formulation / Adjuvants

• Equipment & Application Nozzle type, size, orientation Nozzle pressure Height of release

• Weather, etc. Air movement (direction and velocity) Temperature & humidity Air stability/inversions

Droplet Categorization - ASABE

Need to select droplet size to

maximize efficacy and minimize drift

Category Symbol Color Code

 

Approximate

Dv0.5 (VMD)

(microns)

Extremely Fine XF Purple ≈50

Very Fine VF Red <136

Fine F Orange 136-177

Medium M Yellow 177-218

Coarse C Blue 218-349

Very Coarse VC Green 349-428

Extremely Coarse

XC White 428-622

Ultra Coarse UC Black >622

From: ASABE Standard S-572.1

AgDRIFT to Calculate Buffers

• EPA 2014 guidance uses AgDRIFT to determine drift for terrestrial (plant/animal) and aquatic habitat

• AgDRIFT based on Spray Drift Task-force data 48 unique SDTF Deposition Datasets

Excellent quality & GLP Used older (1992-93) spray application technology

• Several conservative approaches result in unrealistic ground drift estimates

• Unable to refine drift estimation using drift reducing technologies (DRT) and best management practices

AgDRIFT – Overestimation of Drift

• AgDRIFT produces unreasonably conservative drift estimates when compared to existing drift data sets

Figure Courtesy J. Wright

Comparison Between AgDrift Outputs vs. Field DataAgDrift Assumes 20 Spray Swaths, 90th% tile

Distance (ft)

0 200 400 600 800 1000

% o

f A

ppli

ed

0.0

0.2

0.4

0.6

0.8

1.0

SDTF 1992SDTF 1993Wolf (PMRA)GanzelemierAgDrift (20 swaths)

Figure Courtesy J. Wright

AgDRIFT – Scale-up Overestimation

• SDTF Data is foundation for AgDRIFT, but use of multipliers to scale-up to a ‘typical’ field is much too conservative

• 90th %ile curves inappropriate

• Gross overestimate at far-field distance

Downwind distance (m)

1 2 5 10 20 40 120

Dep

osi

t (%

of

app

lied

)

0.001

0.01

0.1

1

10 1

1

1

1

1

1

1

1

2

2

2

2

2

33

33

3

5

5

5

5

5

6 66 6

6

7 7

7 7 7

8 88 8

8

9 9

9 9 9

10 1010

1010

44

4 44

2011 AAFC Data – Multiple Swaths

• Dr. Tom Wolf of Agriculture and Agri-Food Canada (AAFC) developed drift dataset as basis for PMRA buffer zone calculator

• No significant deposition after 4-5 swaths (~250-300 ft)

• In AgDRIFT, SDTF data was consolidated into two categories:

• Inappropriate to evaluate medium or coarser sprays

• Inadequate for current nozzle technology

AgDRIFT – Overestimation of DriftNozzle Trial “Data Lumping”

Very Fine to Fine

Fine to Medium/Coarse

Category Symbol Color Code

 

Approximate

Dv0.5 (VMD)

(microns)

Extremely Fine XF Purple ≈50

Very Fine VF Red <136

Fine F Orange 136-177

Medium M Yellow 177-218

Coarse C Blue 218-349

Very Coarse VC Green 349-428

Extremely Coarse

XC White 428-622

Ultra Coarse UC Black >622

Nozzle Types

11

Flat Fan Nozzles

Air Induction Nozzles

AgDRIFTWind Speed “Data Lumping”

12

1 10 1001E-3

0.01

0.1

1

10

Per

cent

of A

pplie

d (lo

g)

log - Down Field Distance (m)

8.4 8.8 11.6 12.8 20.5

Wind (mph)

AI11004

• Drift at distance, is influenced by data generated in high wind (25% of SDTF ground data with >20 mph wind!!)

• 90th percentile could be ‘off-label’

1 10 100

1E-3

0.01

0.1

1

10

Per

cent

of A

pplie

d

Down Field Distance (m) - log

90th Pct

50th Pct

Mean

Nozzle - 11004

Dr. T. Wolf AAFC '2000

• Summary• Mathematical model used in AgDRIFT to

describe the conservative 90th percentile drift curves are subjective, and overestimate drift• ‘Best fit’ curves in AgDRIFT never

intersect zero

• Lumping of data for trials with different nozzles (spray quality / droplet sizes), and wind speed produces excessive overestimates* of drift from ground sprays, and removes capability to refine model

AgDRIFT – Overestimation of Drift

* in some circumstances AgDRIFT can predict movement of more off-target material than the amount applied

Drift Overestimation – The Impact?

• AgDRIFT used to calculate proximity distances and buffers for FIFRA ecological and human health risk assessments, and Endangered Species Risk Assessments

• Appropriate for ‘screening’ assessment, but requires refinement options• Risk should be refined before buffer size is

determined (mitigation)

Large Action Areas(Endangered Species)

• Spray Drift – 360 degrees, wind blowing in all directions, simultaneously

• Threshold’ = EEC / LOC

• EEC from AgDrift

Significant overestimate of action area and potential

buffer distances

Drift Overestimation – Impact on Agriculture

• Impact on agriculture (example)

• ~600 feet of field or parts of field cannot be treated

Drift Overestimation –Impact on Agriculture

• ‘Freedom to operate’ for grower Possible need to remove land from production as more

buffers and larger buffers are required (value / cost?) Cost effectiveness of having to use ground applications

instead of aerial

• Resistance Development Cutting rates to meet buffer requirements No applications to certain parts of field Incomplete coverage due to coarser spray droplet

Spray Drift – A Pragmatic Solution

• Need to find appropriate balance between efficacy, drift and resistance management, to allow cost-effective pest control. Model refinement is necessary – reasonable

conservatism ‘Drift education’ / Best Management Practices are critical Automation is desirable to allow flexibility

REGDISP

• Model built on AGDISP (v. 8.26) • USFS made code available to Industry • the current EPA accepted version of AGDISP • desire to keep the mechanistic ground model

• No changes to existing AGDISP code existing • Better interface for AGDISP calculators• Enables parsing of data/ addition of data• Addresses issues with AgDRIFT described

19

Canada Drift Regulation

• Pest Management Regulatory Agency in Canada worked with Dr. Tom Wolf of Agriculture and Agri-Food Canada (AAFC) and developed their own dataset as basis for their buffer zone calculator

• Launched in 2011

REGDISP Data Sets

• Agricultural Agri Food Canada (AAFC) ‘2000• Agricultural Agri Food Canada (AAFC) ‘2004• Agricultural Agri Food Canada (AAFC) ‘2011• 49 unique AAFC Deposition Datasets

• Spray Drift Task Force ‘1992• Spray Drift Task Force ‘1993• 48 unique SDTF Deposition Datasets

• 97 unique deposition datasets

21

Canadian Field Study Design (‘00 and ‘04)

XR8001, XR8003, AI110025, AI11005, AI11004 Nozzles

Fine to V. Coarse sprays

60 and 90 cm boom heights

Wind speed = 3 to 12 m/s

Single pass, 18m (60 ft) spray boom

Data Fit Method

23

Log/Log Transform Data

1. Log Transform2. Simple Regression (y=mx+b)

10 1001E-4

1E-3

Fra

ctio

n of

App

lied

Distance (m)

0 20 40 60 80 100 120

0.000

0.001

0.002

0.003

0.004

0.005

0.006

Fra

ctio

n of

App

lied

Distance (m)

Since Deposition Data is highly non-linear

• Accurate description of data• Doesn’t assume drift is unlimited

Deposition Data Calculation Tab

24

1. Select Dataset2. Select Nozzle3. Boom Height4. Wind Speed5. Enter Rate6. Run

Use Existing Calculators (and Code)

25

Toolbox

Consideration of DRTs in Risk Assessment

• DRTs are proposed for use in reducing the size of required buffers Promote Best Management Practices (BMPs)

• Recommendations for specific Spray Quality or Droplet Size likely needed to ameliorate ESA restrictions – and maintain a viable product

• REGDISP facilitates consideration of specific field data or combinations of DRTs in determining a suitable action area or buffer distance

Pragmatic Approach to Spray Drift

• Use of REGDISP as conservative, yet realistic drift model No ‘infinite’ drift

Ability to refine ground spray drift estimates – spray quality, wind, DRTs, BMPs, etc.

Defines reasonable proximity/buffer distances to expedite FIFRA and endangered species risk assessments

• Education / Stewardship Promote Best Management Practices

CropLife, chemical producers, nozzle manufacturers, product distributors, retailers, etc.

Ag extension, federal/state agencies, universities

Continued research

Pragmatic Approach to Spray Drift

• Use of automation of spray technology e.g. GIS on conjunction with automated nozzle

switching allows precision application with respect to buffer areas

• Need to provide spray drift options that growers and applicators can use today to:• allow safe use of products (human and

ecological),• without unduly impacting growers’ ability to

effectively produce crops

Thank you