Draft for Comment Version

– March 1, 2014



# Appendix A: Volatilization Screening Tool

Guidance Document

Office of Pesticide Programs

Office of Chemical Safety and Pollution Prevention

U.S. Environmental Protection Agency

Washington, DC

March 1, 20142 Table of Contents 1

1. Introduction

................................ ................................ ................................ ............................. 3 2

2. System Requirements

................................ ................................ ................................ .............. 3 3

3. Using the Tool

................................ ................................ ................................ ......................... 4 4

4. Uncertainty Characterization

................................ ................................ ................................ . 10 5

Attachment A. AERSCREEN Input Values

................................ ................................ ................ 12 6

Attachment B. Development of Peak

- to

- Mean Scaling Ratios Using PERFUM

......................... 15 7

Attachment C. Use of the Modified Woodrow Equation to Estimate Flux Rates

........................ 20 8

9

Figures 10

Figure 1. Input Screen for HED Volatilization Screening Tool

................................ ..................... 5 11

Figure 2. Input Screen Depicting Dropdown List for Application Timing Selection

.................... 6 12

Figure 3. Input Screen Depicting the Dropdown List for the Averaging Time for the 13

Concentration of Concern

................................ ................................ ................................ ............... 8 14

Figure 4. Output Results from HED Volatilization Screening Tool

................................ ............... 9 15

Figure 5. Concentrations at Various Distances

................................ ................................ ............. 10 16

173 1. Introduction 18

19

In 2012 a screening tool ( i.e., the Volatilization Screening Tool ) was developed for estimating 20

screening level air concentrations downwind of treated field s resulting from the volatilization of 21

semi

- volatile pesticides . Up until that time

, the Probabilis tic Exposure and Risk model for 22

FUMigants (PERFUM) was used for such estimations

. However, PERFUM i s resource intensive 23

and require s the input of a time series of flux data (emission rates)

, which was often only 24

available from field volatility studies that were not common for semi

- volatile pesticides

. 25

Alternatively

, the EPA Office of Air AERSCREEN 1 model was used as the basis of this 26

screening tool

. AERSCREEN i s a screening model based on AERMOD 2 , which i s an air quality 27

model that quantifies air dispersion based on planetary boundary layer turbulence structure and 28

scaling concepts, including treatment of both surface and elevated sources, and both simple and 29

complex terrain. AERSCREEN produce s estimates of "worst

- case" 1

- hour concentrations for a 30

single source, without the need for hourly meteorological data. 31

32

The Volatilization Screening Tool was developed using outputs from AERSCREEN based on a 33

standard flux rate of 1x10

- 6 g/m 2

- s, for various field sizes, crop scenarios, emissions/release 34

scenarios, and meteorological conditions . These outputs were import ed into an Excel workbook

. 35

Attachment A details the input parameters used in AERSCREEN model runs

. ). Current 36

AERSCREEN guidance for field source emissions does not s upport calculation of air 37

concentrations beyond 1 hour periods to different exposure periods ( e.g. , 8

- hour time weighted 38

air concentration). However, a peak

- to

- mean scaling factor has been developed, based on runs 39

done in PERFUM, to allow estimation of concentrations for averaging periods longer than one 40

hour, but less than 24 hours in order to match the duration of the potential exposure period to a 41

period similar to that used for defining the toxicological level of concern (e.g., 6 hour inhalation 42

dose administration in a rodent study is typical) ( see Attachment B )

. 43

44

In AERSCREEN, air concentrations are directly related to the emission rate from a field. For 45

fumigants, it was assumed that the emission rate is directly proportional to the application rate 46

( e.g. , the more pesticide that is applied, the more pesticide will volatilize ) . Using a similar 47

premise

, the Volatilization Screening Tool scale s the results from the AERSCREEN runs to 48

estimate off

- field air concentrations quickly, using only the application rate , different release 49

rates ( hourly flux rates ), a combination of meteorological condition s, and crop information . The 50

Volatilization Screening Tool provides estimates of the distance from the edge of the field where 51

air concentrations fall below the concentration of concern for a chemical

. In this way, the 52

Volatilization Screening Tool can b e used to easily eliminate the inhalation pathway for 53

pesticides not posing a risk of concern to bystanders following applications

. 54

2. System Requirements 55

56

The spreadsheet tool was developed for Microsoft Excel 2007 , so user s must have this version or 57

higher. The tool also uses Visual Basic functions, so user s will have to enable th e use of macros 58

in order to use the tool. 59

1 http://www.epa.gov/scram001/dispersion_screening.htm

2 http://www.epa.gov/ttn/scram/dispersion_prefrec.htm#aermod4 3. Using the Tool 60

61

Before using the tool, user s should collect the following information from labels , submitted flux 62

studies (if a vailable)

, and toxicity studies: 63

1. Maximum label rate, in lb ai/A, for the application of interest . This is only applicable if 64

the pesticide is applied to soil. 65

2. Time of year the pesticide is applied 66

3. I nhalation and oral toxicity information 67

4. Target Margin of exposure (MOE) or Level of Concern (LOC) 68

5. Flux profile , if available 69

70

In order to run the tool, the user should follow these steps: 71

72

1. Go to the Screening Calculator worksheet ( Figure 1 ). 73

74

2. Enter the name of the active ingredient

. This is for information purposes only and does not 75

affect the results of the tool

. 76

77

3. Enter the vapor pressure of the active ingredient in units of torr. This measurement will be 78

used to estimate the flux rate for emissions from soil and plant canopy. 79

80

4. Enter the solubility of the active ingredient in units of mg/L. This parameter is only 81

applicable to applications made to bare soil. 82

83

5. Enter the adsorption coefficient (K

oc ) in units of mL/ g. If only a K d value is available, divide 84

it by 0.01 (assume the soil has an organic carbon content of 1%) . This parameter is only 85

applicable to applications made to bare soil. For active ingredients with multiple K d s/K

oc s, 86

enter the mean value. 87

88

6. The maximum hourly flux estimates for bare soil and the var ious crop types are estimated 89

using the Woodrow equations for soil (bare soil) and plants ( e.g. , cole crop, row crop, and 90

orchard) ( Attachment C ). As t he equation for soil require s the use of the appli cation rate, 91

users should enter the maximum label rate for pre

- emergence applications

. For foliar 92

applications to crops, l eave the application rate cell blank. If a field volatility study is 93

available, users should identify the maximum hourly flux rate reported in the study and use it 94

in the tool. 95

965 97 Figure 1

. Input Screen for Volatilization Screening Tool 98

99

7. Select the application timing from the dropdown list ( Figure 2 ). If the pesticide can be 100

applied anytime during the year, the user should select an application time that coincides 101

with the anticipated pest pressure

. 1026 103 Figure 2

. Input Screen Depicting Dropdown L ist for A pplication T iming S election 104

105

8. Select the averaging time for the target concentration, in hours ( Figure 3 ). This should 106

correspond to the duration of the inhalation point of departure (POD) (see below)

. This will 107

allow the model to scale the one

- hour concentration generated by AERSCREEN to an 108

averaging time comparable to the exposure duration for which the inha lation concentration of 109

concern was derived

. U ser s are limited to 1, 2, 4, 6, 8, 12, and 24

- hour averaging periods. 110

111

9. Enter the inhalation POD

. The inhalation POD refers to the chemical

- specific human

- health 112

point of departure selected for the inhalation route of exposure in a chemical’s most recent 113

human health exposure or risk assessment. For this input, there are three main possibilities: 114

115

• If a route

- specific inhalation toxicological study was used in the latest risk assessment 116

as the basis for the inh alation endpoint, a human equivalent concentration (HEC) was 117

calculated ( via use of the Agency’s reference concentration (RfC) methodology ), the 118

HEC can be utilized for the inhalation POD in the screening analysis. 119

• If a route

- specific inhalation toxicological study was used in the latest risk assessment 120

as the basis for the inhalation endpoint, but an HEC was not calculated, the no 121

observed adverse effect level (NOAEL) can be utilized for the inhalation POD. 122

• If a route

- specific inhalation toxicolo gical study was not available and an oral 123

toxicological study was used as the basis for the inhalation endpoint i n the latest risk 124

assessment, the NOAEL from the oral study can be converted to an inhalation 1257 equivalent concentration (IEC) as used as the inh alation POD

. The IEC can be 126

estimated using the following equation 127

128

Where: 129

IEC

= inhalation equivalent concentration (μg/m3), 130

NOAEL

= NOAEL from oral study (mg/kg/day), 131

CF1

= conversion factor to convert mg to μg, 132

A

= absorption (unitless), 133

CF2

= conversion factor to account for species specific respiratory 134

volume and body weight (m3/hr/kg), 135

D

= duration (hrs/day), and 136

AF

= activity factor (unitless) 137

138

10. Enter the uncertainty factor (UF). This is equivalent to the target MOE or level of conce rn 139

(LOC)

. 140

141

11. The concentration of concern (COC) is calculated in the spreadsheet, and is essentially the 142

HEC divid ed by the UF. Any estimated air concentrations above the COC would represent a 143

potential risk of concern. 144

1458 146 Figure 3

. Input Screen Depicting the Dropdown List for the A veraging Time for the 147

C oncentration of C oncern 148

Once the information above has been entered into the spreadsheet, the tool will automatically 149

calculate the distance from the field at which the air concentration has decreased below the 150

concentration of concern for the different crop types and field sizes ( Figure 4 ). If the distance is 151

greater than the maximum distance modeled in AERSCREEN, a greater than (>) symbol wi ll 152

appear in the results table. Because the receptor distances used in the AERSCREEN runs are 153

fixed at 25 meter intervals, a simple linear interpolation routine is used to generate a more 154

appropriate estimate. 155

156

Results are generated for four different cro p types (bare soil, cole crops, row crops, and orchards) 157

designed to cover the various release heights and canopy coverages most commonly experienced 158

with semi

- volatile applications. Results for cole crops should be used for low level crops, such 159

as soybe ans, strawberries, and vegetables. Results for field crops should be used for crops that 160

have a somewhat higher canopy height, such as corn, alfalfa, and tomatoes. It should be noted 161

that the 120

- acre field is only applicable for row crops. 162

1639 164 Figure 4 . Output Results from Volatilization Screening Tool 165

The distance to the concentration of concern is designed to give the user an idea of how far away 166

a bystander would need to be from a treated field in order to not be exposed to air concentrations 167

above the level of concern. 168

169

If user s would like to view the concentrations at various distances away from the treated fie l d for 170

the model run, they should select the Concentration by D istance worksheet ( Figure 5 ). This 171

worksheet provides a summary of the results at various distances away from the treated field for 172

all field sizes and all crop scenarios. 173

174

Once finished, the user should save the Excel file under a different name, so the results of the 175

model run wil l be saved. 176

17710 178 Figure 5 . Concentrations at Various D istances 179

4. Uncertainty Characterization 180

181

AERSCREEN generates a maximum one

- hour air concentration assuming air flow remains 182

constant. The values reported in the tool are w orst case values (i.e., always single downwind 183

direction) and should be character ized as such. 184

185

AERSCREEN models air flow for simple, uniform terrain. Because of the complex topography 186

and air flow patterns in an orchard, use of the results generated for orchard s should caveat the 187

values as being highly uncertain. 3 While the topography for cole or row crops is not completely 188

uniform, it is believed that the differen ces are not significant enough to impact the air flow 189

regime and concentrations outside the treated field. 190

191

For simplicity, the field s in AERSCREEN were modeled as squares and the sizes were limited to 192

five values. While this may not reflect real

- world agricultural practices, the sizes and shape 193

should be adequate for screening

- level purposes. 194

195

3 Unlike AERSCREEN, the refined model AERMOD considers flow around or above complex mountainous terrain.

However, neither AERSCREEN nor AERMO D considers complex flow patterns through other non

- homogeneous

surfaces such as orchard groves.11 In most cases, the maximum AERSCREEN concentration at any distance corresponded to the 196

minimum wind speed of 0.5 m/s. In the case of many

, but not all, semivolatiles, the maximum 197

flux rate occurs during the middle of the day, when temperatures are highest an d the air 198

turbulence and wind speed have increased . As a result, for semivolatiles, matching the 199

maximum flux rate with the minimum wind speed will overestimate air concentrations around a 200

treated field. U ser s may want to look at the impact of lower flux rates and characterize the 201

results accordingly. 202

203

U ser s need appropriate justif ication for selectin g field sizes, crop scenarios , and percent 204

volatilized used in the modeling runs

. Any differences between what was modeled and what is 205

expected to occur in the real

- world should be characterized. 206

207

20812 A ttachment A. AERSCREEN Input Values 209

210

The Volatilization Screening Tool uses the results of several AERSCREEN runs as its 211

underlying basis. AERSCREEN model runs were conducted for a series of crop types (bare 212

ground, cole crop, row crop, and orchard), field sizes (10, 20, 40, 60, 80, and 120 (row crop 213

only) acres), and seasonal conditions (spring, summer, fall, and winter) to simulate pesticide 214

applications at various times during the year. For simplicity, the fields were all squares. The 215

release heights were based on the maximum crop heights of 3, 6 and 18 feet for cole crops, row 216

crops, and orchards, respectively. Cole and row crops were expected to be at half of their 217

maximum height in the spring and reach maturity in the summer. By fall, these crops would have 218

similar heights to summer before harvesting. In the winter, the height of release in row and cole 219

crop fields were equivalent to bare ground, as these crops would have been harvested. Receptor 220

distances were automatically generated by AERSCREEN by providing a minimum distance 221

value of 1 meter and a maximum distance value of 5,000 meters. A receptor height of 1. 5 meters 222

was used to represent the breathing height of a human. 223

A flux rate of 1 x 10

- 6 g/m 2

- s, or 1 μg/m 2

- s, was used for each field. In AERSCREEN, the air 224

concentrations are directly related to emission rate from a field. For fumigants, OPP has 225

assum ed that the emission rate is directly related to the application rate. Using these 226

relationships, the application rate can be converted to an emission rate in μg/m 2

- s, assuming the 227

amount applied is released over a given period. The air concentration val ues can be estimated 228

from the AERSCREEN runs simply by multiplying the results by the converted application rate. 229

Additionally, the following meteorological and land surface input parameters were used: 230

Spring Summer Fall Winter

Minimum temp (K) 273 283 273 273

Maximum temp (K) 305 311 305 300

Minimum wind speed (m/s) 0.5 0.5 0.5 0.5

Anemometer height (m) 10 10 10 10

Land use type 0 0 0 0

Spring 1

Bare soil Cole crop Row crop Orchard

Albedo 0.14 0.12 0.13 0.13

Bowen ratio 3 0.7 2 2

Surface roughness length (m) 0.001 0.015 0.03 1

Release height (m) 0 0.46 0.91 5.5

Summer 1

Bare soil Cole crop Row crop Orchard

Albedo 0.2 0.12 0.13 0.13

Bowen ratio 3 0.3 1 1

Surface roughness length (m) 0.001 0.1 0.2 1.3

Release height (m) 0 0.91 1.83 5.5

Fall 1

Bare soil Cole crop Row crop Orchard13 Albedo 0.18 0.12 0.13 0.13

Bowen ratio 3 1 2 2

Surface roughness length (m) 0.001 0.1 0.2 0.8

Release height (m) 0 0.91 1.83 5.5

Winter 1

Bare soil Cole crop Row crop Orchard

Albedo 0.6 0.6 0.6 0.35

Bowen ratio 3 3 3 1.5

Surface roughness length (m) 0.001 0.001 0.001 0.5

Release height (m) 0 0 0 5.5

1. See discussion below for more details on how values were derived. 231

Minimum temperatures for fall, spring, and winter were kept at 32°F, as pest pressures are not 232

expected below this temperature. Other temperatures were selected to represent the range that 233

might be reasonably anticipated. The minimum wind speed and anemometer height were default 234

values used in the AERSCREEN model. The la nd use type of 0 allowed for the use of specific 235

albedo, Bowen ratio, and surface roughness values. 236

Values for albedo, Bowen ratios, and surface roughness were initially developed using Tables 4

- 237

1, 4

- 2b, and 4

- 3 in the AERMET 4 (the meteorological processor for the AERMOD model) 238

manual (USEPA, 2004 5 ). D aytime Bowen ratio, daytime albedo, and surface roughness length 239

values were used to determine planetary boundary layer values used by AERSCREEN for 240

convective conditions. The t ables in the AERMET manual have different land use categories 241

than those considered in this modeling effort, so justification for the values chosen are described 242

below. 243

Albedo 244

The daytime albedo is the fraction of total incident solar radiation reflected by the surface back 245

to space without absorption. Surface color highly influences albedo values (lighter colors tend to 246

reflect more effectively than darker colors). Albedo val ues for bare soil were equivalent to 247

values for cultivated fields from Table 4

- 1 in the AERMET manual. Albedo values for cole 248

crops were equivalent to values for a deciduous forest as provided in Table 4

- 1, since both 249

surfaces possessed similar colored su rfaces. The only exception was that the albedo for cole 250

crops was assumed to be equivalent to bare soil in the winter, given that these fields would be 251

barren in the winter. For both row crops and orchards, albedo values were selected in between 252

those fo r the bare soil and cole crops, given the staggered distribution of plants and bare areas on 253

these fields. The only exception was during the winter when barren row crop fields have the 254

same albedo as bare fields. Wintertime albedos for orchards would be lower than bare soil, 255

given the coverage of dark colored woody material. 256

4 http://www.epa.gov/ttn/scram/metobsdata_procaccprogs.htm#aermet

5 http://www.epa.gov/scram001/7thconf/aermod/aermetugb.pdf14 Bowen Ratio 257

The daytime Bowen ratio, an indicator of surface moisture, is the ratio of the sensible heat flux to 258

the latent heat flux

. Higher Bowen ratios indicate dry surfaces wher e total evaporation flux is 259

low, and low Bowen ratios indicate moister surfaces where total evaporation flux is higher. 260

Average atmospheric moisture conditions were assumed to determine Bowen ratios. Estimates 261

for the Bowen ratio for bare soil were assum ed to be 3.0 for all seasons, which is typical for an 262

area that does not have much evaporation and evapo

- transpiration contributing to atmospheric 263

moisture levels. Bowen ratios for cole crops were assumed to be equivalent to those for a 264

deciduous forest ( Table 4.2b from the AERMET manual). Even though this is not an equivalent 265

land use category, the evaporation characteristics were expected to be the same assuming similar 266

foliage characteristics and evapo

- transpiration rates. Bowen ratios for orchards an d row crops 267

were selected between those for the bare soil and cole crops, given the staggered distribution of 268

plants and bare areas on these fields. One exception was that a slightly lower Bowen ratio was 269

assumed for orchards in the winter, given that the re would be more evapo

- transpiration from the 270

trunks and limbs of orchard trees than bare row crop fields. In winter, both row crops and cole 271

crops were assumed to have the same Bowen ratios as bare soil. 272

Surface Roughness Length 273

The surface roughness l ength is related to the height of obstacles to the wind flow and is, in 274

principle, the maximum height at which the mean horizontal wind speed is no longer zero due to 275

frictional drag. Below this height exists a thin laminar surface boundary layer characte rized by 276

no wind. The values for bare soil we re closest to the grassland value for winter from Table 4

- 3 277

in the AERMET manual, assuming the surface wa s void of significant vegetation. Surface 278

roughness length values for orchards were derived from the dec iduous forest estimates provided 279

in Table 4

- 3 in the AERMET manual. Roughness lengths for cole and row crops we re assumed 280

to be less than for orchards and greate r than bare fields. Row crops we re assumed to have twice 281

the roughness length of cole crops since row crops we re generally taller than cole crops. In 282

winter, both cole crops and row crops we re assumed to have the same surface roughness as bare 283

soil. 284

References 285

286

USEPA. 2004. User’s guide for the AERMOD Meteorological Preprocessor (AERMET). 287

USEPA, Office of Air Quality Planning and Standards, Emissions, Monitoring, and Analysis 288

Division, Research Triangle Park, North Carolina 27711. EPA

- 454/B

- 03

- 002, November 2004 289

(http://www.epa.gov/ttn/scram/metobsdata_procaccprogs.htm#aermet) 290

29115 Attachment B . Development of Peak

- to

- Mean Scaling Ratios Using PERFUM 292

Introduction 293

The Volatilization Screening Tool uses results generated from AERSCREEN to estimate 294

screening

- level concentrations to bystanders near a treated field. AERSCREEN provides a 1

- 295

hour maximum average air concentration, while averaging periods of concern can vary from 1 to 296

24 hours. As such, while the AERSCREEN estimates will be conservative because of the 297

mism atched exposure durations which makes this screening tool inappropriate for use in 298

quantitative risk assessment without further adjustment of the 1 hour concentrations . EPA’s 299

Office of Air has developed 3, 8, and 24

- hour peak to mean scaling factors for AERSCREEN 300

estimates, but recommends, per EPA’s screening guidance (USEPA, 1992), that these values 301

should not be used for area sources, as 302

“....concentrations close to an area source will not vary as much as those for point 303

sources in response to varying wind directions, and the meteorological conditions which 304

are likely to give maximum 1

- hour concentrations and can persist for several hours. 305

Therefore it is recommended that the maximum 1

- hour concentration be conservatively 306

assumed to apply for averaging periods out to 24 hours.” 307

In an effort to find a way to use the one

- hour AERSCREEN estimates and scale them to the 308

appropriate exposure averaging period for HED, the PERFUM model was used to evaluate air 309

concentrations around treated fields. Using various field sizes and meteorological regions, OPP 310

developed peak to mean scaling factors for area sources to be used in the interim HED 311

Volatilization Screening Tool

. 312

Methodology 313

Five field siz es (10, 20, 40, 60, and 80 acres) and 2 meteorological areas (Ventura, CA and 314

Bradenton, FL) were examined to estimat e peak to mean scaling factors for 2, 4, 6, 8, 12, and 24 315

hour periods. Ventura and Bradenton were selected as, historically, these meteor ological 316

conditions have routinely produced the highest near

- field concentrations. Fields were modeled 317

as squares. 318

For each meteorological region, OPP conducted initial runs using a 10

- acre field and a constant 319

flux rate to determine the application tim e that would generate the maximum period 320

concentrations for both meteorological regions. These analyses were only done for 2, 4, 6, 8, 321

and 12

- hour averaging periods, as 1 and 24

- hour averaging periods are not affected by an 322

application’s start time. The a pplication time that generated the highest period concentrations 323

was then held constant during the remainder of the model runs for other field sizes. Table B

- 1 324

depicts the start times for the various field sizes and meteorological regions used in the 325

modeling. 32616 Table B

- 1 . Start Time of Application for PERFUM Runs, Based on Meteorological Region 327

Averaging period (hours) Start hour of application

California meteorological

region Florida meteorological region

2 2 2

4 3 2

6 4 6

8 6 7

12 9 6

328

OPP then conducted 1

- hour averaging period runs with constant flux rates over a 24

- hour period. 329

A threshold concentration of 500 μg/m 3 in PERFUM was specified. The flux rates were selected 330

so that the 99.9 th percentile concentration did not exceed 10 times the rounded threshold 331

concentration of 500 μg/m 3 . This would allow a more accurate comparison of the maximum 332

concentrations generat ed by PERFUM, as resulting concentrations on the highest end of the 333

range would not be capped 6 . Once acceptable flux rates were determined, these flux rates were 334

used with 2, 4, 6, 8, 12, and 24

- hour averaging periods. 335

The values at each ring for the 2, 4, 6, 8, 12, and 24

- hour averaging periods were compared to 336

the corresponding values for the 1

- hour averaging period to estimate a peak to mean scaling 337

ratio. In order to be conservative, the maximum ratio was selected for each averaging period. 338

Depending on the averaging period, the number of concentration distributions generated in each 339

output file from PERFUM was equivalent to 24 divided by the averaging period of interest. For 340

instance, 24 concentration distributions were generated for a 1

- hour averag ing period, while 12 341

concentrations were generated for a 2

- hour averaging period. The output files from each 342

PERFUM run were analyzed to determine which averaging period resulted in the highest 99.9 th 343

percentile concentrations. The highest 99.9 th percent ile values were obtained for each receptor 344

ring and exported into a spreadsheet. 345

T his process was repeated for the remaining field sizes and meteorological regions. E levated area 346

sources to mimic cole and row crops, to see if the elevated source would generate different peak 347

to mean scaling factors were also included . It was assumed that seasonally dependent variables, 348

such as albedo, surface roughness length, and Bowen Ratio, were the same between mo del runs, 349

as PERFUM does not distinguish between varying surface characteristics. 350

Results and Conclusions 351

The overall results of the analysis are presented in Table B

- 2 . Results from individual runs are 352

presented in Tables B

- 3 and B

- 4 . The results from th e modeling runs present similar peak to 353

mean scaling factors for the different averaging periods, with standard deviations of less than 354

6 The current version of PERFUM au tomatically caps estimated concentrations at 10 times above the threshold

concentration to conserve processing time.17 3%. Therefore, the maximum peak to mean scaling factor found for each averaging period is 355

being proposed to be applied, with the exception of the 2

- hour averaging period, where the peak 356

to mean scaling factor is being set to 100%. 357

Table B

- 2 . Overall Scaling Results from PERFUM Runs 358

Avg

Time

(hr) Overall Proposed

scaling

factor Max Avg Stdev

2 101% 1 96% 3% 100%

4 93% 91% 1% 93%

6 86% 83% 1% 86%

8 83% 81% 1% 83%

12 75% 73% 2% 75%

24 47% 45% 1% 47%

1. The maximum peak to mean ratio for the 2

- hour period is greater than 100 percent. This is 359

believed to be an artifact of the binning process used in PERFUM to generate concentration 360

distributions. 361

Uncertainties 362

PERFUM provides concentrations as distributions for a 5

- year period. The highest percentile is 363

99.9 th percentile. While not the maximum concentration, for purposes of air modeling pestic ide 364

applications, it is assumed to representative of the maximum concentration at the prescribed 365

distance from the edge of the field. 366

Since peak to mean scaling factors are computed based on the ratio of the 99.9 th percentile one

367

hour concentration and concentration of other averaging period at the same ring distance, there is 368

the potential that the actual ratio for an individual receptor could be higher. For instance, 369

suppose there are two receptors 5 meters from the field ( Figure B

- 1 ). For the 1

- hour 370

concentration distribution, the point east of the field is the 99.9 th percentile 1

- hour concentration 371

on 1/10/95. The point to the southwest is comparable, but not quite as high, and occurred on 372

7/10/97. However, the 2

- hour concentration estimation at the point to the east results in a lower 373

2

- hour concentration than the point to the southwest, where the meteorological conditions were 374

more stagnant in the second hour. PERFUM does not provide results at every poin t along the 375

ring, just at the percentile specified for a certain ring. As a result, the scaling factor that is 376

arrived at in this analysis would be 95% (190/200), instead of 97% (190/195). Given the number 377

of PERFUM runs used to generate the scaling fact ors, OPP does not believe this situation 378

significantly impacts the scaling factor results ( e.g. , the scaling factor for a particular averaging 379

period would change by only 1

- 2%). 380

Lastly, PERFUM post

- processes the results from Industrial Source Complex Short Term 381

(ISCST3) model. AERSCREEN is a screening

- level version of the AERMOD model. While 382

both ISCST3 and AERMOD are Gaussian

- plume models, they differ on how they process and 38318 us e meteorological parameters. However, OPP does not the differences between to two models 384

is significant enough to prevent the use of peak to mean scaling factors, generated using ISCST3, 385

on AERMOD results. On the contrary, OPP believes similar, if not ide ntical, scaling factors 386

would have been generated if PERFUM used AERMOD instead of ISCST3. 387

Figure B

- 6 . PERFUM Results Illustration 388 

### 200 μg/m 3 

### , 1/10/95 (99.9 th 

### )

195 μg/m 3 

### , 7/10/97 (99.8 th 

### ) 1

- hour concentration

185 μg/m 3 

### , 1/10/95 (99.8 th 

### )

190 μg/m 3 

### , 7/10/97 (99.9 th 

### ) 2

- hour concentration

Note: PERFUM does not provide results for the 99.8 th percentile value. These results are provided for illustrative purposes only.19 Table B

- 3 . Individual Results, B are Soil PERFUM R uns 389

Avg

Time

(hrs) CA

- Max Ratio FL

- Max Ratio

Bare soil Bare soil

10 A 20 A 40 A 60 A 80 A 10 A 20 A 40 A 60 A 80 A

2 92% 95% 93% 93% 93% 97% 98% 99% 98% 98%

4 88% 90% 90% 90% 91% 90% 91% 92% 92% 93%

6 80% 82% 82% 84% 84% 83% 83% 84% 85% 85%

8 78% 80% 80% 81% 83% 80% 81% 82% 82% 83%

12 71% 72% 72% 74% 75% 72% 73% 74% 74% 75%

24 46% 47% 46% 47% 47% 44% 44% 44% 44% 45%

390

Table B

- 4

. Individual R esults, Elevated S ource PERFUM R uns 391

Avg

Time

(hrs) CA

- Max Ratio FL

- Max Ratio

Cole crop Row crop Cole crop Row crop

10 A 40 A 80 A 10 A 40 A 80 A 10 A 40 A 80 A 10 A 40 A 80 A

2 94% 93% 97% 101% 93% 94% 96% 98% 100% 96% 98% 98%

4 88% 90% 92% 89% 90% 91% 92% 92% 92% 91% 92% 92%

6 80% 84% 85% 82% 83% 84% 84% 84% 86% 84% 84% 85%

8 78% 81% 83% 80% 81% 82% 81% 82% 83% 81% 82% 83%

12 71% 73% 75% 72% 73% 74% 73% 70% 75% 73% 69% 74%

24 46% 46% 47% 46% 46% 46% 44% 44% 44% 44% 43% 43%20 Attachment C . Use of the Modified Woodrow Equation to Estimate Flux Rates 392

393

In Woodrow et al (1997) and Woodrow et al (2001), study authors developed a linear 394

relationship between the natural logarithm of a chemical’s physical and chemical properties to 395

the natural logarithm of the amount of chemical emitted from soil or a plant surface. However, 396

like all linear relatio nships, half of the emissions were underestimated when compared to the 397

measured values used to derive the relationship. In order to be conservative and health 398

protective, EFED used the data provided in the Woodrow et al (1997) to construct an alternative 399

linear model using the 90% lower confidence limit of the slope and 90% upper confidence limit 400

of the intercept as the model parameters. The results of the regressions are provided in Figures 401

C

- 1 and C

- 2 , for the soil

- and foliar

- applied pesticides, respec tively. 402

403

For soil applied pesticides , the following equation can be used to derive a flux rate 404

405

flux

= e ( 0

. 8688 R + 21

. 535 ) / 3600

406

R = ln � VP x AR

Sol x K OC �

407

where 408

409

flux

= flux rate (μg/m 2

- s) 410

VP

= vapor pressure (Pa) 411

AR

= application rate (kg/ha) 412

Sol

= solubility (mg/L) 413

Koc

= organic carbon sorption coefficient ( m L/g) 414

415

For foliar applied pesticides, the following equation can be used to derive a flux rate 416

417

flux

= e ( 0

. 8268 ln ( VP ) + 12

. 081 ) / 3600

418

where 419

420

flux

= flux rate (μg/m 2

- s) 421

VP

= vapor pressure (Pa) 422

423

Reference 424

Woodrow, J., Seiber, J., Baker, L. 1997. Correlation Techniques for Estimating Pesticide 425

Volatilization Flux and Downwind Concentrations . Environ. Sci. Technol., 31:523

- 529 426

Woodrow, J., Seiber, J., Dary, C. 2001. Predicting Pesticide Emissions and Downwind 427

concentrations Using Correlations with Estimated Vapor Pressures . J. Agric. Food Chem. 428

49:3841

- 3846 42921 430

43122 432

433

434