Accurate Modeling for Drift Reduction: General Overview and Regulatory Status April 11 th, 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 “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 CategorySymbolColor Code Approximate Dv0.5 (VMD) (microns) Extremely FineXFPurple≈50 Very FineVFRed<136 FineFOrange MediumMYellow CoarseCBlue Very CoarseVCGreen Extremely Coarse XCWhite Ultra CoarseUCBlack>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 ( ) 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
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 90 th %ile curves inappropriate Gross overestimate at far-field distance
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 (~ 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 Drift Nozzle Trial “Data Lumping” Very Fine to Fine Fine to Medium/Coarse CategorySymbolColor Code Approximate Dv0.5 (VMD) (microns) Extremely FineXFPurple≈50 Very FineVFRed<136 FineFOrange MediumMYellow CoarseCBlue Very CoarseVCGreen Extremely Coarse XCWhite Ultra CoarseUCBlack>622
Nozzle Types 11 Flat Fan Nozzles Air Induction Nozzles
AgDRIFT Wind Speed “Data Lumping” 12 Drift at distance, is influenced by data generated in high wind (25% of SDTF ground data with >20 mph wind!!) 90 th percentile could be ‘off-label’
Summary Mathematical model used in AgDRIFT to describe the conservative 90 th 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) ‘ unique AAFC Deposition Datasets Spray Drift Task Force ‘1992 Spray Drift Task Force ‘ 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 Transform 2.Simple Regression (y=mx+b) Since Deposition Data is highly non-linear Accurate description of data Doesn’t assume drift is unlimited
Deposition Data Calculation Tab 24 1.Select Dataset 2.Select Nozzle 3.Boom Height 4.Wind Speed 5.Enter Rate 6.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