Air Concentration Dispersion Modeling Assessment of Methyl ......Sullivan Environmental Consulting, Inc. Methyl Bromide AERMOD Modeling Assessment 1900 Elkin Street, Suite 200, Alexandria,

Sullivan Environmental Consulting, Inc. Methyl Bromide AERMOD Modeling Assessment 1900 Elkin Street, Suite 200, Alexandria, VA 22308 703-780-4580

Page 1 of 76

Air Concentration Dispersion Modeling Assessment of Methyl Bromide

Concentrations in Tauranga Port, New Zealand

Submitted to:

Ian Gear

Stakeholders in Methyl Bromide Reduction

P.O. Box 10986

Wellington, NZ 6143

Submitted by:

David A. Sullivan, Certified Consulting Meteorologist (CCM)

Dennis Hlinka, Certified Consulting Meteorologist (CCM)

Ryan D. Sullivan, Certified Environmental Professional (CEP)

Sullivan Environmental Consulting, Inc.

1900 Elkin Street, Suite 200

Alexandria, VA 22308

DRAFT REPORT

7/10/2018

Sullivan Environmental Consulting, Inc. Methyl Bromide AERMOD Modeling Assessment

1900 Elkin Street, Suite 200, Alexandria, VA 22308 703-780-4580 Page 2 of 76

Table of Contents

1.0 Executive Summary .................................................................................................................. 8

2.0 Scope of Assignment ................................................................................................................ 9

3.0 Methodology ............................................................................................................................. 9

3.1 Fumigation Emissions ......................................................................................................... 10

Table 1. Calculation Worksheet for Computing Flux (µg/m2/sec) for the 120 g/m

3

Application Rate (China) ...................................................................................................... 11

Table 2. Calculations Used to Determine Flux in Table 1 for China ................................... 11

Table 3. Calculation Worksheet for Computing Flux (µg/m2/sec) for the 72 g/m3

Application Rate (India) ....................................................................................................... 12

Table 4. Calculations Used to Determine Flux in Table 3 for India ..................................... 12

3.2 Ventilation Emissions ......................................................................................................... 13

Table 5. Emission Rates Scaling Worksheet Example ......................................................... 14

3.3 Meteorological Data............................................................................................................ 15

Figure 1. Data Availability at Tauranga Airport .................................................................. 15

Figure 2. Location of Pseudo Meteorological Tower at Tauranga Port where logs

fumigation are currently conducted ...................................................................................... 16

Table 6. AERMET-Ready Met Data Generated by WRF and MMIF (June 20, 2017) ....... 17

Table 7. List of Meteorological Files ................................................................................... 18

Figure 3. Wind Rose for Tauranga Port Based on WRF Data .............................................. 19

3.4 Dispersion Modeling ........................................................................................................... 20

3.4.1 Single-Source Runs ...................................................................................................... 21

3.4.2 Multiple-Source Runs .................................................................................................. 22

3.4.3 Ship Emissions ............................................................................................................. 23

Figure 4. Stack and Receptor Placement for Multiple Log Pile Fumigation Modeling ...... 24

Figure 5. Stack and Receptor Placement for Ship and Multiple Log Pile Fumigation

Modeling ............................................................................................................................... 25

4.0 Results ..................................................................................................................................... 26



Table 8. Maximum Downwind Methyl Bromide Concentrations (ppm) at 20 m From Land-

Based Log Pile Sources Based on the 90th

and 95th

Percentile Concentrations .................... 28

Table 9. Maximum Downwind Methyl Bromide Concentrations (ppm) at 20 m From Both

Ship and Land-Based Log Pile Sources Based on the 90th

and 95th

Percentile Concentrations

............................................................................................................................................... 28

Table 10. Maximum Downwind 24-hour Methyl Bromide Concentrations (ppm) at 20 m

From Both Ship and Land-Based Log Pile Sources Based on the 90th

Percentile

Concentrations ...................................................................................................................... 29



Percentile

Concentrations ...................................................................................................................... 29

5.0 References ............................................................................................................................... 30

6.0 APPENDICES ........................................................................................................................ 31

Appendix A: WRF Data Description ........................................................................................... 31

Appendix B: Isopleth Analyses (China) ...................................................................................... 33

Matrix of Model Runs for Single Source Scenarios ............................................................. 33

Matrix of Model Runs for Multiple Source Scenarios ......................................................... 33

Matrix of Model Runs for Ship Only Scenarios ................................................................... 33

Matrix of Model Runs for Multiple Source Scenarios and Ship Emissions (combined) ..... 33

Figure B-1. 90th

Percentile Airborne Methyl Bromide Concentrations (ppm) For China

Emissions Scenario Based on 1-Hour Averaging and Urban Dispersion Conditions Single

Land-Based Source Run ....................................................................................................... 34

Figure B-2. 95th




Figure B-3. 90th




Figure B-4. 95th






Figure B-5. 90th Percentile Airborne Methyl Bromide Concentrations (ppm) For China

Emissions Scenario Based on 1-Hour Averaging and Urban Dispersion Conditions Multiple






Emissions Scenario Based on 24-Hour Averaging and Urban Dispersion Conditions

Multiple Land-Based Source Run ......................................................................................... 40





Emissions Scenario Based on 24-Hour Averaging and Urban Dispersion Conditions Ship

Only Run (Adjusted to 45,000 m3 Volume) ......................................................................... 42






Multiple Source (Land-Based plus Ship) Run ...................................................................... 44




Appendix C: Isopleth Analyses (INDIA) .................................................................................... 46

Matrix of Model Runs for Single Source Scenarios ............................................................. 46

Matrix of Model Runs for Multiple Source Scenarios ......................................................... 46

Matrix of Model Runs for Ship Only Scenarios ................................................................... 46

Matrix of Model Runs for Multiple Source Scenarios and Ship Emissions (combined) ..... 46

Figure C-1. 90th

Percentile Airborne Methyl Bromide Concentrations (ppm) For India





Figure C-2. 95th




Figure C-3. 90th




Figure C-4. 95th




Figure C-5. 90th Percentile Airborne Methyl Bromide Concentrations (ppm) For India

















Only Run ............................................................................................................................... 56







APPENDIX D. SHIP MODELING RESULTS PRIOR TO SCALING ............................. 59



Figure D-1. 90th Percentile Airborne Methyl Bromide Concentrations (ppm) For China


Only Run ............................................................................................................................... 60



Only Run ............................................................................................................................... 61

Figure D-3. 90th Percentile Airborne Methyl Bromide Concentrations (ppm) For India


Only Run ............................................................................................................................... 62



Only Run ............................................................................................................................... 63

Appendix E – Recovery Isopleth Analyses (CHINA AND INDIA) ............................................ 64



Multiple Source (Land-Based plus Ship) Run - Using 95% Recovery of Ventilation

Emissions .............................................................................................................................. 65

Figure B-11.1 90th Percentile Airborne Methyl Bromide Concentrations (ppm) For China



Emissions .............................................................................................................................. 66




Emissions .............................................................................................................................. 67




Emissions .............................................................................................................................. 68

Figure B12.1 95th Percentile Airborne Methyl Bromide Concentrations (ppm) For China



Emissions .............................................................................................................................. 69






Emissions .............................................................................................................................. 70



Multiple Source (Land-Based plus Ship) Run Using 95% Recovery of Ventilation

Emissions .............................................................................................................................. 71

Figure C-11.1 90th Percentile Airborne Methyl Bromide Concentrations (ppm) For India



Emissions .............................................................................................................................. 72




Emissions .............................................................................................................................. 73




Emissions .............................................................................................................................. 74




Emissions .............................................................................................................................. 75




Emissions .............................................................................................................................. 76



1.0 EXECUTIVE SUMMARY

Sullivan Environmental Consulting, Inc. (Sullivan Environmental) was engaged by Stakeholders

in Methyl Bromide Reduction (STIMBR) to simulate the expected airborne Methyl Bromide

concentrations at the Port of Tauranga (New Zealand). These simulations were based on

application rates applicable to the regulatory requirements of India and China. Sullivan

Environmental performed this analysis by incorporating the meteorological conditions specific to

the timber exporting Port of Tauranga in New Zealand into the AERMOD modeling system.

The purpose of the modeling assessment is to determine the 90th

and 95th

percentile airborne

concentrations of the Methyl Bromide fumigant for both India and China emission rates by using

five year meteorological data from the Port of Tauranga.

The AERMOD dispersion modeling platform was used to simulate ship, single stack, and

multiple stack scenarios treated at a maximum treatment rate scaled based on the running 24

hour temperature based application rate values for China and India (each country had different

application rates as a function of temperature). For the multiple stack scenarios, ship fumigation

(2 ships per month assumed) was added to the fumigation of the on-land multiple stack scenario.

One hour and 24 hour averages of Methyl Bromide concentrations were computed as a function

of distance. Based on the emissions assessment modeled in this analysis, airborne concentrations

beyond 20 meters would be expected to be lower than shown in the summary tables (Tables 8-

11) in this report.



2.0 SCOPE OF ASSIGNMENT

AERMOD is widely used throughout the U.S. and is globally recognized as a suitable tool for

fumigant emissions modeling. AERMOD contains advanced algorithms to represent transport

and dispersion conditions. These include mixed-layer scaling to refine modeling treatments

during unstable afternoon conditions, and advanced treatments for area sources, terrain effects,

and other special case factors.

AERMOD is well-suited to modeling Methyl Bromide emissions because the scale of analysis is

well within the applicability of the model, i.e. a modeling domain of less than 50 km. The model

has been prepared using an emission rate sequence to model airborne concentrations of Methyl

Bromide likely to be encountered during the fumigation of log stacks and ship fumigation.

Model input account for the hourly variable emissions rates applicable to India and China. To

model the ship emissions, we used the specifications of a typical vessel carrying logs from New

Zealand. A total volume of 45,000 cubic meters (across 5 holds) holding a total of 25,974 JAS

cubic meters of logs was assumed.

The operating constraints at the Port of Tauranga require fumigators to operate between 7:00

A.M. and 7:00 P.M. These constraints were used as modeling assumptions in this analysis. The

operating restrictions are designed to minimize the impact of potential atmospheric inversion

conditions.

3.0 METHODOLOGY

Section 3 describes the methodology used to conduct this assessment.



3.1 Fumigation Emissions

Note that to maintain consistent 24-hour cycles; the modeling was conducted with a 23 hour

fumigation cycle, followed by ventilation at hour 24. This simplified the treatments within a

single 24-hour cycle and would not be expected to produce any significant differences in the

final results. Fumigation operating hours at the Port of Tauranga and meteorological data (1-

hour increments) were input into the model for on-land / ship fumigation. The hourly emission

file treatment in AERMOD allowed for a more realistic consideration of the variable start times

within the operational window of 7:00 A.M. to 7:00 P.M. through the input of an hourly file for

the five-year input data sets for the model runs.

Emission rates were determined by research conducted by Dr. Ajwa (Ajwa, H. Tarp

permeability testing for Methyl Bromide, Ajwa Analytical laboratories December 2017. )

involving Methyl Bromide flux chamber research. The computation of the emission rate during

fumigation was based on first multiplying the delta concentration (µg/ml) in the receiving

chamber as a function of time by the volume of the receiving chamber in ml. The micrograms

gained were then divided by the area of the permeable surface in square meters (0.0193 m2) and

divided by the number of seconds associated with each time step. The worksheet calculations for

the 120 g/m3 application rate are shown in Table 1 (for China) and the excel calculations used to

determine the emission rates for China are shown in Table 2. The worksheet calculations for the

72 g/m3 application rate are shown in Table 3 (for India) and the excel calculations used to

determine the emission rates for India are shown in Table 4. Note that during hours where data

were unavailable, the flux rate from the previous hour where data were available was used; e.g.

elapsed hour 3 used the flux rate for elapsed hour 2. Dr. Ajwas research was used to determine

the emissions during fumigation; however an alternative approach (Hall et. al., 2017) was used to

determine emissions during ventilation since Dr. Ajwas’ research did not account for ventilation.

Tables 1 and 3 show the maximum flux values that were scaled down based on the temperature

scalers for each country.



Table 1. Calculation Worksheet for Computing Flux (µg/m2/sec) for the 120 g/m

3 Application Rate (China)

Table 2. Calculations Used to Determine Flux in Table 1 for China

China (120 g/m3)

volume (ml) elapsed hrs. Cell 1 Sink Cell 2 Sink average gain (g/ml) elapsed seconds ug gained FLUX (ug/m2/sec)

920 0 0 0 =+MEDIAN(P3:Q3)

area (m2) 0.5 1.19 2.38 =+MEDIAN(P4:Q4) =+R4-R3 =+(O4-O3)*60*60 =S4*$N$3 =+U4/($N$5)/T4

0.0193593 1 Weighted Average of .5 hrs and 2 hrs -> 41.9

C_init. ug/ml 2 4.76 5.95 =+MEDIAN(P6:Q6) =+R6-R4 =+(O6-O4)*60*60 =S6*$N$3 =+U6/($N$5)/T6

119 4 8.33 8.33 =+MEDIAN(P7:Q7) =+R7-R6 =+(O7-O6)*60*60 =S7*$N$3 =+U7/($N$5)/T7

20 28.56 33.32 =+MEDIAN(P8:Q8) =+R8-R7 =+(O8-O7)*60*60 =S8*$N$3 =+U8/($N$5)/T8

ventilation - > 24 27777.7777777778



Table 3. Calculation Worksheet for Computing Flux (µg/m2/sec) for the 72 g/m3 Application Rate (India)

Table 4. Calculations Used to Determine Flux in Table 3 for India

India (72 g/m^3)

volume (ml)

elapsed

hrs Cell 1 Sink Cell 2 Sink average

gain

(g/ml) elapsed seconds

ug

gained FLUX (ug/m2/sec)

920 0 0

=+MEDIAN(C3:

D3)

area (m2) 0.5

=+$A$7*(1/100

)

=+$A$7*(2/100

)

=+MEDIAN(C4:

D4) =+E4-E3 =+(B4-B3)*60*60

=+F4*$A

$3 =+H4/($A$5)/G4

0.01935927932958

37 1

Weighted Average of .5 hrs and 2

hrs -> =((2*I4)+(I6))/3

C_init. ug/ml 2

=+$A$7*(4/100

)

=+$A$7*(5/100

)

=+MEDIAN(C6:

D6) =+E6-E4 =+(B6-B4)*60*60

=+F6*$A

$3 =+H6/($A$5)/G6

119 4

=+$A$7*(7/100

)

=+$A$7*(7/100

)

=+MEDIAN(C7:

D7) =+E7-E6 =+(B7-B6)*60*60

=+F7*$A

$3 =+H7/($A$5)/G7

20 =+$A$7*(24/100)

=+$A$7*(28/100)

=+MEDIAN(C8:D8) =+E8-E7 =+(B8-B7)*60*60

=+F8*$A$3 =+H8/(A5)/G8

ventilation - > 24

=+(72/2)*1000000*(500)/3600/

300



3.2 Ventilation Emissions

The determination of the emissions occurring at ventilation take into account Methyl Bromide

absorption by Pinus radiata logs during fumigation. The emission rate for the ventilation period

was based on laboratory modeling that included consideration of absorption of Methyl Bromide

by logs. It was assumed that 50 percent of the product is remaining at the time of ventilation

(Hall et. al, 2017). It was assumed that the concentration was associated with a 500 m3 air space

(very conservative assumption because the expected volume of air would be substantially lower

than this value) and all of the emissions are lost in the first hour of ventilation. By multiplying

the residual (endpoint) concentration times the conservative representation of air space and

dividing by the (area x 3600 seconds) the ventilation emission rate was conservatively

represented. This emission rate was used as a conservative representation that could be refined

as necessary in the future. The maximum calculated flux during ventilation was computed as

follows:

Equation 1. Ventilation flux Calculation for India:

[72

𝑔𝑚3

2 𝑔

𝑚3 ] [1

𝑔

𝑚3 𝑥 106

µ𝑔

𝑔𝑥 500 𝑚3] /300 𝑚2/ 3,600

𝑠𝑒𝑐ℎ𝑟 = 16666.7

µ𝑔

𝑚2 𝑠𝑒𝑐

Equation 2. Ventilation flux Calculation for China:

[120

𝑔𝑚3

2 𝑔

𝑚3 ] [1

𝑔

𝑚3 𝑥 106

µ𝑔

𝑔𝑥 500 𝑚3] /300 𝑚2/ 3,600

𝑠𝑒𝑐ℎ𝑟 = 27777.8

µ𝑔

𝑚2 𝑠𝑒𝑐

Emissions for each hour were assessed based on a running 24 hour average of the temperature

and associated emission rates by using a scaling file for all of the hours modeled (one for India



and one for China). These files were incorporated into the AERMOD modeling runs. An

example of this scaling file (day 1 of 5 years of data) is shown in Table 5.

Table 5. Emission Rates Scaling Worksheet Example

YEAR MONTH DAY HOUR TEMP

24-

HR

CONCENTRATION

CHINA

CONCENTRATION

INDIA

12 1 1 1 292.6 20.7 0.53 0.32

12 1 1 2 292.6 20.7 0.53 0.32

12 1 1 3 292.6 20.6 0.53 0.32

12 1 1 4 292.6 20.4 0.53 0.37

12 1 1 5 292.5 20.3 0.53 0.37

12 1 1 6 292.6 20.2 0.53 0.37

12 1 1 7 293.1 20.1 0.53 0.37

12 1 1 8 293.7 20.0 0.53 0.37

12 1 1 9 294.4 19.9 0.53 0.37

12 1 1 10 295.0 19.9 0.53 0.37

12 1 1 11 295.7 20.0 0.53 0.37

12 1 1 12 295.1 20.1 0.53 0.37

12 1 1 13 296.0 20.2 0.53 0.37

12 1 1 14 296.2 20.3 0.53 0.37

12 1 1 15 296.2 20.3 0.53 0.37

12 1 1 16 295.9 20.2 0.53 0.37

12 1 1 17 294.9 20.1 0.53 0.37

12 1 1 18 294.4 20.0 0.53 0.37

12 1 1 19 293.6 20.0 0.53 0.37

12 1 1 20 293.3 20.0 0.53 0.37

12 1 1 21 293.1 19.9 0.53 0.37

12 1 1 22 293.0 19.9 0.53 0.37

12 1 1 23 292.3 19.9 0.53 0.37

12 1 1 24 291.6 19.8 0.53 0.37



3.3 Meteorological Data

A review of the meteorological data for Tauranga Airport for the most recent five-year period

(2012-2016) determined that the data only accounted for 53 percent of the critical data

parameters (see Figure 1) required to develop a robust model. Since meteorological data

covering a 24 hour period is needed, we concluded that the meteorological data for the Tauranga

airport was unsuitable for use in this analysis.

Figure 1. Data Availability at Tauranga Airport 1

.

1 http://dpds.weatheronline.co.uk/historical_data/weather_stations_download/#forward



Consequently, we have used five years of Weather Research and Forecasting (WRF) data (2012-

2016) to provide the cover required to develop a representative model. (Refer Appendix A for

further details on the WRF data, which were purchased from Lakes Environmental). The data

were processed into a pseudo meteorological tower 2 for the region of the port. A pseudo 10 m

tower was established from the three dimensional wind fields on an hour-by-hour basis (24

hours/day) based on WRF data. The location of the pseudo tower was placed at the mid-point of

the stacks shown near the Port of Tauranga log wharves as shown in Figure 2.

Figure 2. Location of Pseudo Meteorological Tower at Tauranga Port where logs

fumigation are currently conducted

2 A pseudo meteorological tower is based on three-dimensional WRF gridded meteorological data as subsequently

described. Data are then extracted specific to the location of interest (in this case the Tauranga Port) and the height

of interest (set to 10 m standard).



Table 6 (provided by Lakes Environmental Software Met Data Services) summarizes the WRF

meteorological data used in this modeling analysis. Table 7 provides a list and description of the

meteorological files.

Table 6. AERMET-Ready Met Data Generated by WRF and MMIF (June 20, 2017)

Met Data Order Information: Order No. MET1710361

Ordered by Dennis Hlinka

Company Sullivan Environmental Consulting,

Inc.

Met Data Type AERMET-Ready WRF-MMIF

(Surface & Upper Air Met Data)

Start-End Date Jan 01, 2012 hour 00 - Dec 31, 2016

hour 23

Center Latitude 37.65936 S

Center Longitude 176.1825 E

WRF Grid Cell 4 km x 4 km

Datum WGS 84

Site Time Zone UTC/GMT UTC + 12 hour(s)

Closest City & Country Tauranga - New Zealand



Table 7. List of Meteorological Files

The table below contains a

description of the files that you

are receiving with your met

order. These files were

produced by running the WRF

prognostic model and then

using the US EPA Mesoscale

Model Interface Program

(MMIF) to generate the

following files: #

File Name Description

1 MET1710361_AERMET_201

2-2016.IN1 AERMET Stage 1 Input File

2 MET1710361_AERMET_201


3 MET1710361_AERMET_201


4 MET1710361_AERMET_201

2-2016.DAT Onsite Surface Met File

5 MET1710361_AERMET_201

2-2016.FSL FSL Upper Air Met File

Figure 3 presents a wind rose produced from the WRF meteorological data provided by Lakes

Environmental Software Met Data Services.



Figure 3. Wind Rose for Tauranga Port Based on WRF Data



3.4 Dispersion Modeling

For this application, the AERMOD feature of accepting hourly emission files was used to

account for the random start times of the fumigation activities at the port and to limit the

fumigation start times to within the operating hours of 7:00 A.M. to 7:00 P.M. The model was

populated with WRF 3 generated hourly meteorological data (24 hours for 5 years) representative

of the port. All model input files, output files, FORTRAN processing programs, and Excel

spreadsheets used in computations are available upon request.

For the multiple stack scenario modeling simulations, the fumigation start times for the three

blocks of 10 stacks each were independently determined using Monte Carlo methods. The

number of stack sets per day was also randomly identified as 1 stack set (10 stacks), 2 stack sets

(20 stacks), or 3 stack sets (30 stacks). Once a stack set was initiated, the fumigations were

assumed to proceed with two stacks being fumigated per hour, i.e. five subareas as shown in

Figure 4 for each of the three stack sets.

For the ship scenarios, it was assumed that statistically two times per month ship fumigation took

place at the dock with start time restrictions for the same as for the on-land scenarios. These

start times were selected based on comparable Monte Carlo methods as used for the on-land log

sets.

3 Refer to Appendix A for a description of Weather Research and Forecasting (WRF) data.



Term Input / Approach

Model U.S. EPA dispersion model AERMOD

Meteorological

data Five years of WRF-generated 10 m pseudo tower data

Emissions during

fumigation

Ajwa 2017 Analytical Laboratories tarp permeability study 150 g/m3

scenario

Emissions during

ventilation

Hall et al 2017 determined the Methyl Bromide end point concentrations for

the three treatment rates following hour 24 fumigations. These results were

used in the modeling as the Methyl Bromide concentration under the

tarpaulin at the start of venting.

Assumed days 10

stack sets

60 % (Number of stack fumigation per day at Tauranga Port depends upon

the availability of timber, logs price, demand from importing countries etc.)

Assumed days 20

stack sets

30% (Number of stack fumigation per day at Tauranga Port depends upon


Assumed days 30

stacks sets

10% (Number of stack fumigation per day at Tauranga Port depends upon


Basis to assign #

stacks Random each day for each of the 3, 10-stack clusters

Basis for daily

emissions Hourly emission file option in AERMOD

Ship fumigation 2 times/month

3.4.1 Single-Source Runs

Single-source runs start times during operating hours were determined using Monte Carlo. The

hourly emission rates based on the temperature scalers (see Table 5 for an example of these

scalers) were then used. Each analysis was based on 200 simulated years (i.e. 40 passes through

the five year data set representative of the port). The stacks modeled were each 60 m long x 5 m

wide x 2.5 m high i.e. 750 m3 which is slightly larger than the average stack size. The sources

were modeled as area sources with initial dispersion associated with the 2.5 m height of the

sources. The AERMOD output was post-processed using FORTRAN programming to show the

90th

and 95th

percentiles for the 1-hour and 24-hour averaging periods.



Dispersion rates at the port are considered to be more consistent with urban applications (i.e.

higher dispersion rates) when compared with rural settings because of the cement / asphalt

surface and numerous support buildings found on the port site.

3.4.2 Multiple-Source Runs

A comparable approach to Section 3.4.1 was used for the multiple stack runs. Monte Carlo

methods also were employed to define the application start times within the operating hours for

this scenario. It was assumed that:

1. 60 percent of the days had one co-located set of 10 stacks, randomly selected among

the three stack sets, with each stack separated by 1 m spacing, and start times

randomly selected within the period of 7:00 A.M. to 7:00 P.M. (which also applies to

the other two scenarios that follow).

2. For 30 percent of the days it was randomly assumed that two sets of 10 stack groups

each were fumigated during the day, i.e. two of the three source areas were randomly

selected as the sources, i.e. a total of 20 stacks with start times randomly selected

within the period of 7:00 A.M. to 7:00 P.M.; and,

3. 10 percent of the days it was randomly assumed that three sets of 10 stacks each were

treated during the same day. The model assumed that each stack was fumigated at

randomly selected start times within the period of 7:00 A.M. to 7:00 P.M.



4. The placement of the stacks and the receptors (locations where the model estimated

atmospheric concentrations) for the multiple stack analyses is shown in Figure 5. The

blue boxes represent the stacks being fumigated (sources) while the red boxes

represent the receptor placement used in the model. In the multiple source runs it was

assumed that when a block of 10 stacks was modeled based on Monte Carlo selection

that two stacks per hour would be fumigated in sequence; i.e. over a five hour period

all ten stacks would be fumigated. For 20 stacks fumigation, four stacks per hour

would be fumigated in sequence. For 30 stacks fumigation, six stacks per hour would

be fumigated in sequence. Figures 4 and 5 describe the modeling layout. In Figure 4,

the log piles are identified by the blue piles and the red dots are the receptors. In

Figure 5, the blue rectangles resemble the log piles (with the exception of the

rectangle on the left which represents the ship).

3.4.3 Ship Emissions

On a Monte Carlo basis, emissions for ship fumigation were assumed to occur two times per

month. The ships were modeled with four equal size cargo bay hold areas comprising total

cargo area of 2,376 m2, with four stacks/vents per modeled cargo hold. Each stack was set to 1

meter height, representing the minimum height of the ship deck above grade during low tide.

EPA’s BPIP model was used to define building downwash parameters for each of these stacks

relative to the ship dimensions. The smaller rectangle inside the larger rectangle in Figure 5

represents the superstructure of the ship (which was included in the building downwash

assessment). Building downwash was included in the modeling of the stacks to properly account

for the expected additional dispersion due to the ships’ super structure. The presence of the ship

and its superstructure disturbs the wind flow pattern, particularly downwind of the structure. In

order to properly account for this disturbance in the wind flow and the resulting increased

dispersion and downwash of pollutants in the modeling, the AERMOD model includes a

Building Profile Input Program (BPIP). This BPIP module can only be used when only



modeling with stacks/vents within the AERMOD model. In order to properly address these

expected structure downwash effects, the five cargo bays were represented and modeled as four

stacks with heights set at the same height as the deck of the ship with very low exit velocity

(0.0006 m/sec) and a width of 1 meter each were established. The BPIP estimates the ship

dimensions for every 10 degrees around the compass, which helps define the expected increased

dispersion of the emission plumes downwind of the ship.

Figure 4. Stack and Receptor Placement for Multiple Log Pile Fumigation Modeling

Relative “x” axis (m)

Rel

ativ

e “y”

axis

(m

)



Figure 5. Stack and Receptor Placement for Ship and Multiple Log Pile Fumigation

Modeling



3.4.3 Ship Only Scenarios

We modeled the 4 cargo bay areas with the sixteen tacks/vents (4 stacks per cargo bay). The

modeled ship dimensions were 30 meters by 180 meters. The heights of the stacks were set to 1

meter above grade based on the minimums height at low tide relative to dock height. We

considered building downwash based on the ships dimensions including ship height to more

accurately define the dispersion of the emissions downwind from the ship.

3.4.4 Multiple Land-based Log Pile Stacks and Ship Scenarios

We integrated the ship emissions within the original land based log piles emissions into a

common scenario.

4.0 RESULTS

Table 8 provides the maximum modeling results 20 m downwind of the source for land based

pile sources based on the 90th and 95th percentile results for both 1 and 24 hour time periods.

All 90th

and 95th

percentile 1 hour and 24-hour results were less than 1 ppm for all application

rates. Table 9 provides the maximum downwind methyl bromide concentrations (ppm) at 20 m

from both ship and land-based log pile sources based on the 90th and 95th percentile

concentrations. Tables 10 and 11 provide comparisons between India and China in terms of

maximum modeled concentrations. Table 10 provides the maximum downwind 24-hour methyl

bromide concentrations (ppm) at 20 m from both ship and land-based log pile sources based on

the 90th percentile concentrations. Table 11 provides the same comparison as Table 10, however

provides the results based on the 95th

percentile concentrations.



The ship based modeled concentrations accounted for the volume of logs in the ship and these

modeling results were scaled using linear scaling4 to account for the total space in the hold of the

ship. The emission isopleths for the log volume only excluding the total space in the ships’

storage holds can be found in Appendix D. All model results for all receptors show 90th

and 95th

percentile concentrations less than 1 ppm. Isopleth analyses showing the spatial variation in

concentrations for the various model runs are available in Appendix B (China emissions) and

Appendix C (India emissions). As a point of comparison, Appendix E presents results assuming

various percent recovery of methyl bromide during ventilation (assuming 80%, 90%, and 95%

recovery).

4 45,000 m

3 (total space in ship’s storage hold) / 25,974 m

3 (modeled wood emissions) = 1.732 (conservative) scale

up factor to account for total area in the ships’ hold. This factor was applied to accurately represent total emissions

from the ship including all space in the fumigated areas and was applied to the total emissions.



Table 8. Maximum Downwind Methyl Bromide Concentrations (ppm) at 20 m From

Land-Based Log Pile Sources Based on the 90th

and 95th

Percentile Concentrations

Emissions

Scenario

Percentile

Single Source Multiple Sources

1-hour 24-hours 1-hour 24-hours

China 90th

.005 .120 .015 .380

India 90th

.005 .070 .015 .220

China 95th

.008 .210 .041 .700

India 95th

.008 .130 .040 .420

Table 9. Maximum Downwind Methyl Bromide Concentrations (ppm) at 20 m From Both

Ship and Land-Based Log Pile Sources Based on the 90th

and 95th

Percentile

Concentrations

Emissions

Scenario

Percentile

Ship Only Source Combined Ship and

Land-Based Sources

1-hour 24-hours 1-hour 24-hours

China 90th

5 .003 .017 .400

India 90th

.002 .017 .240

China 95th

.031 .050 .730

India 95th

.027 .043 .450

5 Ship only one hour runs are in still in progress.





Percentile

Concentrations

Emission

Scenario

95%

Recovery

90%

Recovery

80%

Recovery

China 0.03 0.05 0.08

India 0.02 0.03 0.06



Percentile

Concentrations

Emission

Scenario

95%

Recovery

90%

Recovery

80%

Recovery

China 0.05 0.08 0.15

India 0.03 0.05 0.10



5.0 REFERENCES

Ajwa, H. Tarp permeability testing for Methyl Bromide, Ajwa Analytical laboratories December

2017.

Hall, M. , Najar Rodriguez, A. , Adlam, A. , Hall, A. and Brash, D. (2017), Sorption and

desorption characteristics of methyl bromide during and after fumigation of pine (Pinus radiata

D. Don) logs. Pest. Manag. Sci., 73: 874-879. doi:10.1002/ps.4355

U.S. Environmental Protection Agency, AMS/EPA Regulatory Model AERMOD User’s Guide,

EPA-454/B-03-001, September 2004 (with updates)



6.0 APPENDICES

APPENDIX A: WRF DATA DESCRIPTION 6

The Weather Research and Forecasting (WRF) Model is a next-generation mesoscale numerical

weather prediction system designed for both atmospheric research and operational forecasting

needs. It features two dynamical cores, a data assimilation system, and a software architecture

facilitating parallel computation and system extensibility. The model serves a wide range of

meteorological applications across scales from tens of meters to thousands of kilometers. The

effort to develop WRF began in the latter part of the 1990's and was a collaborative partnership

principally among the National Center for Atmospheric Research (NCAR), the National Oceanic

and Atmospheric Administration (represented by the National Centers for Environmental

Prediction (NCEP) and the (then) Forecast Systems Laboratory (FSL)), the Air Force Weather

Agency (AFWA), the Naval Research Laboratory, the University of Oklahoma, and the Federal

Aviation Administration (FAA).

WRF can generate atmospheric simulations using real data (observations, analyses) or idealized

conditions. WRF offers operational forecasting a flexible and computationally-efficient

platform, while providing recent advances in physics, numerics, and data assimilation

contributed by developers across the very broad research community. WRF is currently in

operational use at NCEP, AFWA, and other centers.

WRF has a large worldwide community of registered users (over 30,000 in over 150 countries),

and workshops and tutorials are held each year at NCAR. The WRF system contains two

dynamical solvers, referred to as the ARW (Advanced Research WRF) core and the NMM

(Nonhydrostatic Mesoscale Model) core. The ARW has been largely developed and maintained

by the MMM Laboratory, and its users' page is: WRF-ARW Users' Page. The NMM core was

6 (extracted from http://www.wrf-model.org/index.php)

http://www.mmm.ucar.edu/wrf/users/



developed by the National Centers for Environmental Prediction. It is currently used in the

HWRF (Hurricane WRF) system, for which user support is provided by the Developmental

Testbed Center (see WRF for Hurricanes.)

This site (wrf-model.org) provides general information on the WRF model and its organization

and offers links to WRF users' pages, real-time applications, and WRF announcements.

However, for detailed information on the content, use, and updates of the modeling system, and

for all code downloads and documentation, users should visit the WRF-ARW and WRF-NMM

home pages (see above).

http://www.dtcenter.org/HurrWRF/users/index.php



APPENDIX B: ISOPLETH ANALYSES (CHINA)

The following figures show the concentrations of methyl bromide using the country specific

(China) 24 hour running average temperature scalers.

Matrix of Model Runs for Single Source Scenarios

Figure # Averaging Time Dispersion Mode Percentile

B-1 1-hour Urban 90th




Matrix of Model Runs for Multiple Source Scenarios






Matrix of Model Runs for Ship Only Scenarios




Matrix of Model Runs for Multiple Source Scenarios and Ship Emissions (combined)






Figure B-1. 90th



Land-Based Source Run



Figure B-2. 95th






Figure B-3. 90th






Figure B-4. 95th








Multiple Land-Based Source Run





Only Run (Adjusted to 45,000 m3 Volume)





Multiple Source (Land-Based plus Ship) Run



APPENDIX C: ISOPLETH ANALYSES (INDIA)

The following figures show the concentrations of methyl bromide using the country specific

(India) 24 hour running average temperature scalers.

Matrix of Model Runs for Single Source Scenarios


C-1 1-hour Urban 90th




Matrix of Model Runs for Multiple Source Scenarios






Matrix of Model Runs for Ship Only Scenarios




Matrix of Model Runs for Multiple Source Scenarios and Ship Emissions (combined)






Figure C-1. 90th






Figure C-2. 95th






Figure C-3. 90th






Figure C-4. 95th








Only Run



APPENDIX D. SHIP MODELING RESULTS PRIOR TO SCALING

Matrix of Model Runs

Figure # Averaging Time Country Percentile

D-1 24-hour China 90

D-2 24-hour China 95

D-3 24-hour India 90

D-4 24-hour India 95





Only Run



APPENDIX E – RECOVERY ISOPLETH ANALYSES (CHINA AND INDIA)

Matrix of Model Runs

Figure # Averaging Time Dispersion Mode Percentile Recovery % Country


95 China

B-11.1 24-hour Urban 90th

90 China

B-11.2 24-hour Urban 90th

80 China

B-12 24-hour Urban 95th 95 China

B-12.1 24-hour Urban 95th 90 China

B-12.2 24-hour Urban 95th 80 China

Figure # Averaging Time Dispersion Mode Percentile Recovery % Country


95 India

C-11.1 24-hour Urban 90th

90 India

C-11.2 24-hour Urban 90th

80 India

C-12 24-hour Urban 95th 95 India

C-12.1 24-hour Urban 95th 90 India

C-12.2 24-hour Urban 95th 80 India






Emissions

Documents

Air Concentration Dispersion Modeling Assessment of Methyl ......Sullivan Environmental Consulting, Inc. Methyl Bromide AERMOD Modeling Assessment 1900 Elkin Street, Suite 200, Alexandria,