AIR DISPERSION MODELLING METHYL BROMIDE · Modelling was undertaken using a combination of the...
Transcript of AIR DISPERSION MODELLING METHYL BROMIDE · Modelling was undertaken using a combination of the...
Prepared by
Todoroski Air Sciences Pty Ltd
Suite 2B, 14 Glen Street
Eastwood, NSW 2122
Phone: (02) 9874 2123
Fax: (02) 9874 2125
Email: [email protected]
AIR DISPERSION MODELLING
METHYL BROMIDE
New Zealand Environmental Protection Authority
4 November 2019
Job Number 19080995
19080995_NZ_EPA_Methylbromide_AirDispersionModelling_191104.docx
DOCUMENT CONTROL
Report Version Date Prepared by Reviewed by
DRAFT - 001 31/10/2019 E McDougall, P Henschke & A Todoroski A Todoroski
FINAL - 001 4/11/2019 P Henschke & A Todoroski A Todoroski
FINAL - 002 4/11/2019 A Todoroski -
This report has been prepared in accordance with the scope of works between Todoroski Air Sciences
Pty Ltd (TAS) and the client. TAS relies on and presumes accurate the information (or lack thereof) made
available to it to conduct the work. If this is not the case, the findings of the report may change. TAS
has applied the usual care and diligence of the profession prevailing at the time of preparing this report
and commensurate with the information available. No other warranty or guarantee is implied in regard
to the content and findings of the report. The report has been prepared exclusively for the use of the
client, for the stated purpose and must be read in full. No responsibility is accepted for the use of the
report or part thereof in any other context or by any third party.
Air Dispersion Modelling
Methyl Bromide
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TABLE OF CONTENTS
1 INTRODUCTION .................................................................................................................................................................. 1
1.1 Objectives .................................................................................................................................................................... 1
2 APPLICABLE ASSESSMENT CRITERIA .......................................................................................................................... 2
2.1 Preamble ...................................................................................................................................................................... 2
2.2 Tolerable Exposure Limits and Workplace Exposure Standard ............................................................. 2
3 DISPERSION MODELLING APPROACH ...................................................................................................................... 3
3.1 Introduction................................................................................................................................................................ 3
3.2 Modelling methodology ....................................................................................................................................... 3
3.2.1 Meteorological modelling ............................................................................................................................... 3
3.3 Dispersion modelling ............................................................................................................................................. 4
3.4 Modelling scenarios ................................................................................................................................................ 4
3.5 Model sources and emission estimation ........................................................................................................ 6
3.5.1 Fugitive emissions during fumigation ........................................................................................................ 6
3.5.2 Ventilation period ............................................................................................................................................... 6
3.5.3 Desorption ............................................................................................................................................................. 9
3.5.4 Temperature varying dose application....................................................................................................... 9
4 DISPERSION MODELLING RESULTS .......................................................................................................................... 11
4.1 Indicative model verification ............................................................................................................................. 11
4.2 Results ........................................................................................................................................................................ 12
5 QUALITATIVE ANALYSIS FOR OTHER LOCATIONS ............................................................................................. 20
6 SUMMARY OF RESULTS ................................................................................................................................................. 22
7 RECOMMENDATIONS .................................................................................................................................................... 24
8 REFERENCES ....................................................................................................................................................................... 26
LIST OF APPENDICES
Appendix A – Meteorological data evaluation
Appendix B – Isopleth diagrams
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LIST OF TABLES
Table 2-1: Methyl bromide TELs and WES-TWA .............................................................................................................. 2
Table 3-1: Surface observation stations .............................................................................................................................. 4
Table 3-2: Seven critical parameters used in CALMET ................................................................................................... 4
Table 3-3: Summary of modelled fugitive source parameters ................................................................................... 6
Table 3-4: Emission estimation for ventilation of the sheet enclosures (g/s) ...................................................... 7
Table 3-5: Summary of modelled ventilation source parameters ............................................................................. 9
LIST OF FIGURES
Figure 3-1: Placement of modelled sources ...................................................................................................................... 5
Figure 3-2: Emission estimation for ventilation of ship holds with 0% recovery ................................................ 8
Figure 3-3: Emission estimation for the desorption of methyl bromide from log piles .................................. 9
Figure 4-1: Maximum extent of specific methyl bromide concentrations, one ship five holds – 40, 80 and
120g/m3 .......................................................................................................................................................................................... 12
Figure 4-2: Maximum 1-hr methyl bromide concentration, three log stacks - 120g/m3 .............................. 13
Figure 4-3: Maximum 1-hr methyl bromide concentration, one ship, five holds – 120g/m3....................... 13
Figure 4-4: Location of sources and receptor for time of day and frequency of impact evaluation Error!
Bookmark not defined.
Figure 4-5: 1-hr methyl bromide concentrations over 5 years at R1, three log stacks – 120g/m3, 80%
capture ............................................................................................................................................................................................ 15
Figure 4-6: Ranked 1-hr methyl bromide concentrations over 5 years at R1, three log stacks – 120g/m3,
80% capture .................................................................................................................................................................................. 16
Figure 4-7: Diurnal profile 1-hr methyl bromide concentrations over 5 years, R1, three log stacks –
120g/m3, 80% capture .............................................................................................................................................................. 17
Figure 4-8: Diurnal profile 1-hr methyl bromide concentrations over 5 years, R1, one ship five holds –
120g/m3, 80% capture .............................................................................................................................................................. 18
Figure 5-1: Comparison of temperature profile near to Tauranga, Northport and Napier .......................... 20
Figure 5-2: Comparison of wind speed profile near to Tauranga, Northport and Napier ............................ 21
Figure 5-3: Comparison of wind rose plots near to Tauranga, Northport and Napier ................................... 21
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1 INTRODUCTION
Todoroski Air Sciences has been engaged by the New Zealand (NZ) Environmental Protection Authority
(EPA) to conduct air dispersion modelling of methyl bromide as a fumigant used for quarantine and
pre-shipment purposes to assist with matters associated with an application for reassessment of the
current Hazardous Substances and New Organisms (HSNO) approval.
This assessment includes air dispersion modelling of fumigation activity at the Port of Tauranga and
qualitatively assesses the potential for similar fumigation activity at other locations in NZ, including
Northport and Napier.
1.1 Objectives
The purpose of this assessment is to provide guidance to the NZ EPA in regard to its considerations for
the reassessment of the current HSNO approval for methyl bromide.
This assessment follows on the Air Quality Review Dispersion Modelling Assessment of Methyl Bromide
(Todoroski Air Sciences, 2019).
The defined objective of this project is to deliver:
1. …additional air dispersion modelling, and a subsequent report. The modelling will consider a
range of recapture (or recovery) conditions (to 5ppm, and 80%, 90%, and 95% of the treatment
rate) and three treatment rates (40 g/m3, 72 g/m3, and 120 g/m3). The report will include:
why the selected model is appropriate
why the selected parameter values have been chosen and are appropriate
results of the modelling
discussion on the results of the modelling
recommendations on suitable buffer zone distances to protect workers for each
treatment-recapture combination when compared with workplace exposure standards
and tolerable exposure levels published in New Zealand (by WorkSafe New Zealand
and the Environmental Protection Authority respectively)
recommendations on suitable buffer zone distances to protect bystanders for each
treatment-recapture combination when compared with tolerable exposure levels
published in New Zealand (by the Environmental Protection Authority).
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2 APPLICABLE ASSESSMENT CRITERIA
2.1 Preamble
Methyl bromide in its gaseous state is a colourless and highly volatile gas and three time as dense as
air. It is highly toxic at acute exposures and is readily absorbed through the lung and skin which can
lead to chronic health effects with long term exposure.
Methyl bromide gas is able to penetrate a variety of substances which allows its use as a pesticide and
fumigant.
2.2 Tolerable Exposure Limits and Workplace Exposure Standard
Tolerable Exposure Limits (TELs) and Workplace Exposure Standard as a time weighted average (WES-
TWA) set out exposure limits for public exposure to methyl bromide in New Zealand.
The TELs are designed to protect the most sensitive members of the population from adverse effects
from exposure to methyl bromide. These TELs cannot be exceeded outside the minimum buffer zone
established around the fumigation activity.
The WES-TWA over an eight hour day is designed to protect workers from excessive exposure to methyl
bromide. This standard is applicable to workers within the fumigation and buffer zones of a fumigation
activity.
Table 2-1 summarises the methyl bromide TELs and WES-TWA considered in this assessment.
Table 2-1: Methyl bromide TELs and WES-TWA
Pollutant Averaging Period Criteria
ppm (µg/m3)
TELair 1 hour 1 3900
TELair 24 hour 0.333 1300
TELair Annual 0.13 5
WES-TWA 8 hour 5 19000
Source: Bay of Plenty Regional Council, 2018
ppm = parts per million, µg/m³ = micrograms per cubic metre
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3 DISPERSION MODELLING APPROACH
3.1 Introduction
The following sections are included to provide the reader with an understanding of the model and
modelling approach applied for the assessment. CALPUFF is an advanced air dispersion model which
can deal with the effects of complex local terrain on the dispersion meteorology over the modelling
domain in a three-dimensional, hourly varying time step.
The model was setup in general accordance with the model-specific recommendations set out in Generic
Guidance and Optimum Model Setting for the CALPUFF Modeling System for Inclusion into the ‘Approved
Methods for the Modeling and Assessments of Air Pollutants in NSW, Australia’ (TRC, 2011). These model-
specific guidelines are consistent with more generalised guidance for any model, such as the New
Zealand Ministry for the Environment, Good Practice Guide for Atmospheric Dispersion Modelling (MfE,
2004).
CALPUFF is considered an appropriate air dispersion model for this project considering the local terrain
features and proximity to the coast, and in particular the ability of the model to consider low wind speed
conditions and also the release of a large volume of fumigant in a short period.
3.2 Modelling methodology
Modelling was undertaken using a combination of the CALPUFF Modelling System and The Air Pollution
Model (TAPM). The CALPUFF Modelling System includes three main components: CALMET, CALPUFF
and CALPOST and a large set of pre-processing programs designed to interface the model to standard,
routinely available meteorological and geophysical datasets.
TAPM is a prognostic air model used to simulate the upper air data for CALMET input. The
meteorological component of TAPM is an incompressible, non-hydrostatic, primitive equation model
with a terrain-following vertical coordinate for three-dimensional simulations. The model predicts the
flows important to local scale air pollution, such as sea breezes and terrain induced flows, against a
background of larger scale meteorology provided by synoptic analysis.
The CALMET meteorological model uses the geophysical information and observed/simulated surface
and upper air data as inputs to develop wind and temperature fields on a three-dimensional gridded
modelling domain. CALPUFF is a transport and dispersion model that advects "puffs” of material
emitted from modelled sources, simulating dispersion processes along the way. It uses the three
dimensional meteorological field generated by CALMET. CALPOST is a tool used to process the output
of the model and produce tabulations that summarise the results of the simulation.
3.2.1 Meteorological modelling
Meteorological modelling was conducted over the five contiguous years spanning 2014 to 2018.
The TAPM model was applied to the available data to generate a three dimensional upper air data file
for use in CALMET. The centre of analysis for the TAPM modelling used is at Tauranga port, 37deg
39min south and 176deg 11min east. The simulation involved an outer grid of 30km, with three nested
grids of 10km, 3km and 1km with 35 vertical grid levels.
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The CALMET domain was run on an initial domain of 30 x 30km grid with a 0.6km grid resolution and
refined for a final domain of 10 x 10km with a 0.1km grid resolution. The available meteorological data
from nearby meteorological monitoring sites were included in the simulation. Table 3-1 outlines the
parameters used from the station.
Table 3-1: Surface observation stations
Weather Stations Parameters
WS WD CH CC T RH SLP
Tauranga Aero AWS
WS = wind speed, WD= wind direction, CH = cloud height, CC = cloud cover, T = temperature, RH = relative humidity, SLP =
sea level pressure
The seven critical parameters used in the CALMET modelling are presented in Table 3-2.
Table 3-2: Seven critical parameters used in CALMET
Option Parameter Value
Terrain radius of influence (km) TERRAD 10
Vertical extrapolation of surface wind
observations
IEXTRP -4
Layer dependent weighting factor of
surface vs. upper air wind observations in
defining the Initial Guess Field (IGF) winds.
Observations are always weighted by
inverse distance squared (1/R2) from the
station to the grid point. The BIAS
parameter changes that weight.
BIAS (NZ)
-1, -0.5, -0.25, 0, 0, 0, 0, 0
Weighting parameter for Step 1 wind field
vs. observations in Layer 1 (R1) and Layer 2
and above (R2)
R1 and R2
3, 3
Maximum radius of influence for
meteorological stations in layer 1 (Step2)
and layers aloft (Step2)
RMAX1 and RMAX2
6, 6
An evaluation of the TAPM meteorological modelling and the outputs from the CALMET modelling is
presented in Appendix A.
3.3 Dispersion modelling
The CALPUFF air dispersion model has been used to predict the potential emissions of methyl bromide
from its use in the fumigation of timber exports at the Port of Tauranga.
Modelling of the key emission sources was conducted using the emissions rates and parameters
outlined in the following section and utilising the meteorological data described in the previous section.
3.4 Modelling scenarios
Modelling has considered the fumigation and ventilation of timber logs under sheet enclosures and
within ship hold containers while at berth.
Log pile and shipping hold dimensions were based on the information set out in Sullivan (2019) and
ASG (2019), and in general were found to be consistent with Google Earth aerial imagery of ships and
logs at the Tauranga Port.
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Timber log piles under sheet enclosures are included in the model with the following dimensions, length
of 60 metres (m), width of 5m and a height of 4m. The modelling scenarios assume three log piles are
fumigated simultaneously each hour within a central part of the permissible fumigation areas of the
Port of Tauranga.
The ships are modelled as having 5 holds with individual dimensions of 24.5m by 24.5m with a depth
of 15m. This allows for a total volume of 45,000 metres cubed (m3) across 5 holds per ship. This
assessment has modelled one or two shipping vessels adjacent to each other berthed at the harbour.
It is noted that modelled sources in this assessment may not represent the full spatial extent of the
operations but provide a representation of potential impacts from individual sources of methyl bromide
at the modelled locations.
An indicative layout of modelled sources is present in Figure 3-1.
Figure 3-1: Placement of modelled sources
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3.5 Model sources and emission estimation
Methyl bromide emissions associated with the fumigation and ventilation of timber logs at the Project
have been identified to arise:
Diffusing as fugitive emissions from the sheet enclosures and the ship hold containers during
the fumigation period;
During the ventilation period (following the fumigation) when the sheet enclosures are lifted
and the ship hold containers are opened; and,
Desorption of methyl bromide from the timber following the fumigation and ventilation period.
An emissions profile for fumigation, ventilation of a ship with 5 holds and for three log stacks was
developed. The profile contains a 24-hour period of steady fugitive emissions, a brief period of
ventilation (10 minutes for log piles but 6 hours for a ship), followed by 24 hours of desorption. Each
aspect of the profile is further detailed below. These assumptions are consistent with information
provided in ASG (2019) and our previous work relating to fumigation and ventilation of timber logs.
The fumigation and emission for either three log stacks or a ship was modelled for any hour by
separately modelling a ship or three log piles for each hour of the day. This is necessary as for example,
a ship would not be ventilated every hour, but could be ventilated in any hour. The period with the
highest impacts is considered in the assessment, as detailed further in the results section.
Four initial methyl bromide fumigation doses of 40g/m3, 72g/m3, 80g/m3 and 120g/m3 have been
applied with recovery rates associated with the capture of methyl bromide following the fumigation
period which include 0%, 50%, 75%, 80% and 90% recovery.
3.5.1 Fugitive emissions during fumigation
It is assumed that fugitive emissions of methyl bromide occur during the 24-hour fumigation period
due to holes or inadequate seals of the sheet enclosures and ship holds. Consistent with common
assumptions about fugitive releases, and as also considered in ASG (2019), fugitive emissions over this
time are assumed to amount to 10% of the fumigant added, and are modelled as a volume source for
both the log stacks and ship holds. A summary of the modelled fugitive source parameters is presented
in Table 3-3
Table 3-3: Summary of modelled fugitive source parameters
Source Sheet enclosure Ship hold (per hold – 5 holds per
ship)
Type Volume Volume
Effective height (m) 4 7
Initial lateral dimension, Sig y (m) 14 5.7
Initial vertical dimension, Sig z (m) 1 1
3.5.2 Ventilation period
At the end of the fumigation period for the timber logs, the residual methyl bromide is vented to
atmosphere. For the sheet enclosures over the log stacks, the covering material is gathered up to
expose the wood and for the shipping vessels the ship hold covers are lifted.
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On the basis of the retention rate applied by (Sullivan, 2019) and set out in Fumigations for
International Standards for Phytosanitary Measures No. 15 (ISPM 15) (ICCBA, 2018), a retention rate of
50% of the original concentration was used to calculate the amount of methyl bromide remaining
following the fumigation period. Emissions of methyl bromide are also assumed to rapidly peak during
the initial phase of the ventilation period.
Ventilation of the sheet enclosures over log stacks is modelled to occur over a 10-minute period, as per
the assumed time required to remove a sheet from a log pile.
For the sheet enclosure of a log stack it is assumed there is a total volume of 1,200m³ (60m x 5m x 4m)
comprised of a log volume of 850m3 and volume of 450m3 of free air space containing the 50%
remaining methyl bromide that would be released to the environment over a 10-minute period during
ventilation.
This volume (450m3) is consistent with the initial lower volume applied in (Sullivan, 2019) and has been
applied in the calculations to estimate the methyl bromide emissions rate for the various initial dose
application and recovery rates, as set out in Table 3-4.
The calculation is as follows; Emission rate (g/s) per log stack = (Volume 450 (m3) x Initial Dose (g/m3) x
50% (residual remaining) x Recovery(%))/ 600(seconds).
Table 3-4: Emission estimation for ventilation of the sheet enclosures (g/s)
Dose application (g/m³)
Recovery (%) 40 72 80 120
0 15 27 30 45
50 7.5 13.5 15 22.5
75 3.75 6.75 7.5 11.25
80 3 5.4 6 9
90 1.5 2.7 3 4.5
Ventilation of ship hold emissions was assumed to occur over a 6-hour period from the time the holds
begin to be opened. Emission rates are assumed to increase for the first two hours as more hold area is
progressively opened, and to thereafter decrease for the next four hours as the fumigant progressively
exits the holds. The ventilation of ship holds assumes a free air space of 3,800m³ per hold during
ventilation and occurs over a 6-hour period. The ventilation profile for the ship holds with 0% recovery
is presented in Figure 3-2.
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Figure 3-2: Emission estimation for ventilation of ship holds with 0% recovery
A summary of the modelled ventilation source parameters is presented in Table 3-5. The emissions
associated with the ventilation sources were set up in the modelling with emissions occurring at the
start of each hour of the day to represent potential ventilation activities occurring at any possible hour
of the day.
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Table 3-5: Summary of modelled ventilation source parameters
Source Sheet enclosure Ship hold (per hold – 5 holds per ship)
Type Volume Point
Effective height (m) 4 -
Initial lateral dimension, Sig y (m) 14 -
Initial vertical dimension, Sig z (m) 1 -
Height (m) - 7
Diameter (m) - 27.6
Temperature (K) - Ambient
Velocity (m/s) - 0.1
3.5.3 Desorption
During the fumigation process methyl bromide is absorbed by the timber logs and after the ventilation
period the methyl bromide would desorb gradually over time. The desorption of methyl bromide from
timber logs has been modelled per the exponential decay model presented in Sorption and desorption
characteristics of methyl bromide during and after fumigation of pine (Pinus radiata D. Don) logs (Hall et
al, 2016).
The initial dose application rate determines the initial emission rate of desorption which reduces rapidly.
Figure 3-3 presents the estimated emissions associated with desorption of methyl bromide from log
stacks following ventilation. A similarly varying rate of desorption is applied for logs treated in ship
holds. The modelling considers desorption for 24 hours after ventilation.
Figure 3-3: Emission estimation for the desorption of methyl bromide from log stack
3.5.4 Temperature varying dose application
Temperature has a significant influence throughout the fumigation process as the fumigant is less
effective at a lower temperature.
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As per the International Cargo Cooperative Biosecurity Arrangement (ICCBA) document Methyl bromide
fumigation methodology (ICCBA, 2018) the methyl bromide dose concentration is to be adjusted if the
temperature is expected to fall below 21°C, requiring 8g/m³ to be added to the dosage each 5 degrees
Celsius (°C) below 21°C. Additionally, fumigation activity becomes increasingly less effective and is not
permitted to occur during temperatures below 10°C (ICCBA, 2018).
As such, temperature adjustments of methyl bromide concentration doses have been considered in the
model commensurate with the hourly temperature observation data at Tauranga Aero AWS.
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4 DISPERSION MODELLING RESULTS
This section presents the predicted methyl bromide ground level concentrations associated with timber
fumigation.
For workers, an 8-hour average TWA criterion of 19,000 µg/m3 applies.
Bystanders are assessed per the various TEL criteria. As the short term ventilation emissions are much
higher than the fugitive and desorption emissions which occur over a 24-hour period, the 1-hour
criterion (3,900µg/m3) is the most limiting for bystander risk evaluation.
Due to known elevated levels recorded beyond the boundary, (see below), the results focus on the 1-
hour maximum levels for bystander impact assessment.
4.1 Indicative model verification
Only two monitoring events for ship ventilation are known, as described in ASG (2019). The monitoring
measured VOC levels at distances ranging up to 600m from a ship ventilating five holds. Based on the
underlying ambient VOC levels, the methyl bromide levels appear to have ranged from approximately
1.0 to 4.0 ppm (3,900 to 15,200 µg/m3). The measurements were made in the early hours of the morning
in August, under low wind speeds. Winds were variable in direction on one day, but relatively steady on
the other day. The initial dosage rate of the fumigant in the ship hold is not known.
For comparison, the modelling results for a ventilating ship, with five holds, a dosage concentration of
40, 80 and 120g/m3 and no recovery are presented in Figure 4-1. The modelling results in the figure
show the maximum extent of the methyl bromide concentrations of 15,200 to 3,900 µg/m3 in the worst
hour of air dispersion over five years. The results show the extent of the impact at these concentrations
ranges from 180 to 1800m from the ship according to the initial dose. As the measured results are
unlikely to have occurred under the most impacting few hours of poor dispersion conditions over 5
years they can be reasonably expected to be lower than the modelled results. The modelling however
shows some results that are lower than the measured results (i.e., for an initial dose of 40g/m3),
indicating that overall, the modelling would be generally consistent with the measurements when
modelling ship ventilation at an initial dose of between 80 to 120g/m3.
A few of the hours of monitoring described in detail in (ASG, 2019) for 1 August 2018 are covered by
the period of modelling for this study. The measurements and modelling for an initial dose of 120g/m3
show close agreement with the model predicting a level of 4.3ppm at approximately 400m NE of the
ship (as measured, where measured) and a level of 3.3ppm approximately 300m ENE of the ship (as
measured but on a downwind axis somewhat off the measured location).
In our opinion, the indications are that the modelling for this study is able to reasonably represent the
likely actual case reliably, especially when considering the absence of detailed operational information
to assist in the model preparation.
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Figure 4-1: Maximum extent of specific methyl bromide concentrations, one ship five holds – 40, 80 and 120g/m3
4.2 Results
The maximum extent of possible bystander impact for various capture rates is shown below for an initial
dose of 120g/m3 and various capture rates.
Further results for different initial dose rates are set out in Appendix B.
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Figure 4-2: Maximum 1-hr methyl bromide concentration, three log stacks - 120g/m3
Figure 4-3: Maximum 1-hr methyl bromide concentration, one ship, five holds – 120g/m3
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The results above and those in Appendix B show that the maximum 1-hour average methyl bromide
concentration would exceed the TEL limit of 3,900µg/m3 outside of the fumigation area when three log
stacks or a ship is ventilated irrespective of the initial dose or even with 90% capture.
Therefore, the next key aspect to consider is how often, and at what distance and time of day the
maximum concentrations could occur.
The analysis below considers the maximum impacts in any hour for 5 years at various distances from
the location of the log stacks and/or ship.
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Figure 4-4: 1-hr methyl bromide concentrations over 5 years at 50m, three log stacks – 120g/m3, 80% capture
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The results in Figure 4-4 show that within 50m of ventilation of three log stacks with an initial dose of
120g/m3 and 80% capture of the remaining fumigant prior to ventilation, the results are very near or
below criteria at 8am and at 12 noon, but at 4pm some levels are above the criteria for a few periods,
and between 8pm and 8am extensive occurrences of levels above the criteria are predicted.
The same data are presented in Figure 4-5 but are ranked from highest to lowest to examine how many
hours above the criteria occur in a 5-year period. This shows approximately 250 hours over 5 years,
during which fumigating three log stacks with an initial dose of 120g/m3 and 80% capture would cause
methyl bromide levels above criteria at a distance of approximately 50m.
Figure 4-5: Ranked 1-hr methyl bromide concentrations over 5 years at 50m, three log stacks – 120g/m3, 80% capture
It is not known if ventilation of logs is limited to specific times of day. A diurnal profile showing the
impacts for a range of percentiles and the average concentration in the specific hour for 5 years is shown
below for a distance of 50m from the log stacks.
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Figure 4-6: Diurnal profile 1-hr methyl bromide concentrations over 5 years, 50m, three log stacks – 120g/m3, 80%
capture
The results in Figure 4-6 show that methyl bromide concentrations for ventilation of three log stacks,
with an initial dose of 120g/m3 and 80% capture would be below criteria between 10am and 2pm at a
distance of 35m, but also at a greater distance, likely to within the ventilation area, between 8 am and
3pm. The profile shows the maximum or 100th percentile and the 99.9th, 99th, 98th and 95th percentile of
all results for 5 years in each hour, and also the average level.
The emissions from the ventilation of a ship are shown in Figure 4-7. The results follow a similar trend
to that for ventilation of log stacks, except that impacts are much higher. The results show that 10-hour
average impacts would occur with 130m irrespective of the time of day, at a dosage rate of 120g/m3
and with 80% capture. However, whilst not shown here, the 8-hour average concentration for a single
ship, is significantly lower, and the applicable worker criteria of 19,000µg/m3 as an 8-hour average can
be met on the dock (at a dosage rate of 120g/m3 and with 80% capture).
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Figure 4-7: Diurnal profile 1-hr methyl bromide concentrations over 5 years, 100m, one ship five holds – 120g/m3, 80% capture
The results show that for an initial dose of 120g/m3, even with 80% capture of emissions, there is scope
for log and ship ventilation emissions to exceed criteria at significant distances from the ventilation area.
The results also show that the time of day is a significant factor that can limit the scope for potential
impacts.
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Figure 4-8: Diurnal profile 1-hr methyl bromide concentrations over 5 years, approx. 200m, one ship five holds – 120g/m3, 80% capture
Figure 4-8 shows that for an initial dose of 120g/m3, with with 80% capture of emissions, there is scope
for ship ventilation that occurs between 8am and 3pm at distance of approx. 200m from the ship to be
within criteria more than 95% of the time.
It needs to be noted that the diurnal profiles relate to a specific location relative to the log stacks or
ship, and depending on the prevailing winds, alignment of the sources etc., somewhat different profiles,
with somewhat higher or lower impacts will arise at other locations relative to the log stacks or ships.
However, the overall diurnal trend would not be greatly different.
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5 QUALITATIVE ANALYSIS FOR OTHER LOCATIONS
Emissions are likely to be affected by the prevailing weather conditions. Where the conditions are
similar, and the activity and emissions are similar, it is reasonable to assume similar impacts may arise.
A brief analysis of the prevailing temperature (which also affects dosage rates) and wind speed profile
which predominantly affects dispersion and wind direction which may affect how often an area is down
wind is set out in Figure 5-1, Figure 5-2 and Figure 5-3.
Napier and Northport (Whangerei) show a somewhat larger range of temperature fluctuation, thus
possibly some higher dosage rates may be needed at times relative to Tauranga. However, Napier shows
higher wind speeds, which result in better dispersion. This is expected given that Napier is more exposed
to the ocean than land, relative to the other ports.
Northport shows lower wind speeds, especially from the northwest. Low wind speeds tend to result in
higher impacts, however the receptors are not on the downwind axis of the dominant low wind speed
flows. Northport may also be more sheltered during north to easterly winds but might also be
reasonably expected to experience more turbulent and mixed air flows at the same time due to the
upwind terrain.
Overall, the brief analysis indicates both Northport and Napier bystanders are likely to experience similar
or potentially lower impacts than at Tauranga.
Overall, based on this analysis of the weather conditions and a review of the local terrain, in our opinion
the modelling at Tauranga is not anticipated to significantly under estimate the overall potential effects
at Northport and Napier, and the conclusions could be reasonably applied to the other ports.
Figure 5-1: Comparison of temperature profile near to Tauranga, Northport and Napier
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Figure 5-2: Comparison of wind speed profile near to Tauranga, Northport and Napier
Figure 5-3: Comparison of wind rose plots near to Tauranga, Northport and Napier
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6 SUMMARY OF RESULTS
This report has assessed the potential methyl bromide ground level concentrations associated with
fumigation activity at the Port of Tauranga.
Air dispersion modelling with the CALPUFF model was used to predict the potential for air quality
impacts in the area surrounding the Project. The modelling considered four initial dosage rates; 40, 72,
80 and 120g/m3, and five capture rates, 0, 50, 75, 80 and 90%.
The modelling considers the potential for ventilation to occur at any hour of 5 years from log stacks or
ship holds. Methyl bromide concentration contour plots showing the maximum spatial extent of impact
in any hour of the day over 5 years are shown. Time series plots and a diurnal profile of concentrations
at nearby locations is provided for illustrative purposes. The diurnal profile considers the concentrations
by hour of day for the 100th, 99.9th, 99th 98th and 95th percentile, and the average of all the concentration
data in each hour for 5 years.
The results in this study are significantly higher than the results in the study by Sullivan (2019)
commissioned by the applicant for reasonably comparable scenarios. The results in this assessment
however appear to be reasonably close to the measured monitoring data available for ship ventilation,
whereas those in Sullivan (2019) are not.
The results in the contour plots show that irrespective of the initial dose and even with 90% capture of
the remaining fumigant prior to ventilation, the maximum 1-hour average methyl bromide
concentration in any hour over the 5 years modelled would exceed the TEL limit of 3,900µg/m3 outside
of the fumigation area when three log stacks or a ship is ventilated.
However, the results also show:
Limiting the time of day for ventilation has a large bearing on the outcomes, with significantly
less scope for impacts during the daytime period. Overall, the following factors have a
significant bearing on potential for compliance with criteria:
o the time of day of ventilation;
o the number of log stacks (or ship holds) ventilated per hour;
o the initial dose;
o the capture rate (or final concentration); and,
o distance to the nearest receptor location.
For fumigation and ventilation of log stacks on the dock; with careful attention to these factors
it is possible to fumigate and ventilate log stacks on the dock without undue risk of impacts on
workers or bystanders. However, there appears to be a need for potentially significant
restrictions on the time of day of ventilation, and other such factors to achieve compliance.
More detailed modelling than can be reasonably conducted in this study would be necessary
to develop suitable control parameters for any ongoing fumigation operations.
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Fumigation and ventilation of ships has significant scope to exceed criteria for bystanders. The
8-hour average worker exposure results (not shown) have less potential for on-site impacts,
assuming only one ship ventilation event over 8 hours, at 120g/m3 with 80% capture. Either
way, the results indicate that night time ventilation of ship holds has a high scope to cause
impacts, and daytime ventilation also has potential to cause bystander impacts. Systems that
predict the weather and extent of plume impact, such as the Terrock EnvMet system used
extensively by mines in Australia, should be able to alleviate the potential impacts, provided
that there is scope to bring forward or delay the time when a ship hold is opened, to align with
favourable air dispersion conditions. Other technical or planning options may also be available
to alleviate the potential impacts or minimise the risk.
There is a significant difference in the spatial extent of potential impacts for 50% capture relative
to 80% capture for the maximum impacting hour of all hours in the 5 years modelled. The
relative spatial extent between the 50% and 80% capture rates would remain relatively similar
at times other than for the maximum impacting hour (shown in the contour plots in this study).
The results from the existing modelling (in this study or that of the applicant) thus do not
support adoption of a 50% capture rate at present, and further work including re-doing the
modelling by the applicant, would be needed to support less than an 80% capture rate, for
example to determine if it is feasible to restrict use of a 50% capture rate to a subset of daytime
hours, and not all daytime hours, or a range of other limiting factors.
The limited analysis of the prevailing weather conditions and terrain of other ports indicates that
the results and conclusions of this study appear to reasonably apply to the fumigation operations
at Northport and Napier. Whilst specific studies could be done for these other ports, they are
unlikely to reach conclusions that are greatly different to those in this study.
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7 RECOMMENDATIONS
The results in this study indicate that daytime ventilation is a key control measure and is likely to be a
key limitation on operations that is necessary to prevent impacts above criteria. This is especially the
case when ventilation occurs closer to receptors than the location represented in the modelling, or when
more or larger volumes than modelled for the log stacks or ship are ventilated, or are ventilated
concurrently.
The exact time of day that ventilation of logs on the dock can be conducted without undue risk of
exceeding worker and bystander criteria would vary according to the buffer distance to staff or off-site
receptors, the initial dose and capture rate of methyl bromide prior to ventilation, and also the number
of log stacks (or total volume of fumigated logs) being ventilated.
The results show that impacts above criteria due to ventilation of ship’s holds can be limited, but not
always eliminated by restricting the ventilation to specific daytime periods. Thus there remains a risk of
exceeding the criteria at any time. However, the analysis also indicates that other potentially viable
means to mitigate ship impacts may be available.
As we do not have access to all necessary operational data to reasonably specify detailed operational
controls, it is not appropriate to make specific and detailed recommendations for operational mitigation
and control.
With this in mind, and in consideration that the previous review (TAS, 2019) identified scope for
underestimation in the applicant’s modelling and also as the results of this study appear to align well
with observed data and show greater levels than in the applicants modelling, it is recommended that
the applicant re-do the modelling supporting its application.
The following suggestions in this regard are provide for consideration;
1. A modelling methodology generally similar to that set out in this report, or in ASG (2019);
2. An analysis of the revised new modelling results to:
a. define the factors that can control the operations to ensure compliance with criteria for
fumigation and ventilation of logs on the dock. This should include consideration of
the following;
i. staff buffer distance;
ii. distance to off-site receptors;
iii. time of day for ventilation;
iv. initial dose;
v. capture rate and final concentration;
vi. total volume of logs and number of log stacks per hour;
vii. ship ventilation emissions; and,
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viii. any combination of two or more of the above.
b. develop a strategy to manage ship fumigation to within worker and bystander criteria.
The strategy must consider but not be limited to; the following:
i. all of the above the factors for ventilation of log stacks;
ii. feasibility of cessation of ship hold fumigation;
iii. feasibility of using predictive systems to schedule ship ventilation to times of
favourable air dispersion conditions; and
iv. other means to mitigate potential impacts from ship ventilation.
3. The re-modelling and assessment (per the above) be subject to an independent peer review,
with the reviewer confirming their satisfaction with the final report.
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8 REFERENCES
ASG (2019)
“Review of an Air Concentration Dispersion Modelling Assessment of Methyl Bromide
Concentrations in Tauranga Port, New Zealand”, prepared for Bay of Plenty Regional Council by
Atmospheric Science Global (ASG), August 2019.
Bay of Plenty Regional Council (2018)
“Section 32 Evaluation Report Plan Change 13 (Air Quality) to the Regional Natural Resources
Plan”, Bay of Plenty Regional Council, February 2018.
Emery et al. (2005)
Emery, C., E. Tai, and G. Yarwood, 2001, Enhanced Meteorological Modeling and Performance
Evaluation for Two Texas Ozone Episodes, prepared by ENVIRON, International Corp, for The
Texas Natural Resource Conservation Commission Novato, August 2001.
Hall et al. (2016)
Hall, M., Najar-Rodriguez, A., Adlam, A., Hall, A. and Brash, D., 2016, Sorption and desorption
characteristics of methyl bromide during and after fumigation of pine (Pinus radiata D. Don) logs,
Society of Chemical Industry, August 2016.
ICCBA (2018)
“Methyl bromide fumigation methodology”, International Cargo Cooperative Biosecurity
Arrangement (ICCBA), May 2018.
Sullivan (2019)
“Addendum to Air Concentration Dispersion Modelling Assessment of Methyl Bromide
Concentration in Tauranga Port, New Zealand”, prepared for Stakeholders in Methyl Bromide
Reduction by Sullivan Environmental Consulting (Sullivan), March 2019.
TAS, 2019
“Air Quality Review Dispersion Modelling Assessment of Methyl Bromide”, prepared for New
Zealand Environmental Protection Authority by Todoroski Air Sciences, September 2019.
TRC (2011)
"Generic Guidance and Optimum Model Settings for the CALPUFF Modelling System for
Inclusion into the Approved Methods for the Modelling and Assessments of Air Pollutants in
NSW, Australia", Prepared for the NSW Office of Environment and Heritage by TRC
Environmental Corporation.
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Appendix A: Meteorological data evaluation
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Meteorological data evaluation
To examine whether the TAPM and CALMET generated data used in the assessment are likely to
adequately represent the local terrain and meteorological effects in the modelling domain, an
evaluation of quantitative statistical comparisons of two meteorological datasets was performed.
For this evaluation the Tauranga Aero AWS observation station data for each modelling year was
compared with the TAPM model output and also the predicted CALMET model outputs.
The statistical measures include;
Index of Agreement (IOA) which determines the magnitude of deviations of the predicted
model meteorological datasets are related to the mean from the observational meteorological
dataset with a perfect score being 1;
Root-mean-square error (RMSE) which is calculated as the square root of the mean squared
difference in model-observation pairings with an ideal value of 0;
Bias error which determines the average difference between model and observational data; and,
Gross error which determines the average of the absolute value between model and
observational data.
The statistical output was evaluated using benchmarks developed by Emery et al. in Enhanced
Meteorological Modeling and Performance Evaluation for Two Texas Ozone Episodes (Emery et al. 2005)
and are listed in Table A-1.
Table A-1: Benchmarks for meteorological modelling evaluation
Parameter IOA RMSE Mean Bias Gross Error
Wind speed ≥0.6 ≤2 m/s ≤±0.5
Wind direction ≤±10° ≤30°
Temperature ≥0.8 ≤±0.5 K ≤2 K
The result of the statistical evaluation for each year modelled is presented in Table A-2 to Table A-6.
Results highlighted in orange are those which do not meet the relevant benchmarks.
The evaluation of the TAPM vs observational data indicate that for some of the statistical measures the
relevant benchmarks are not met. For the majority of these, the values are only marginally exceeded
with the exception of the gross error for wind direction.
The statistical evaluation of the CALMET vs observational data indicates the statistical measures meet
the relevant benchmarks and indicate the CALMET data compares reasonably well with the
observational data.
We also note that the statistical output is consistent across each modelled year and shows good
correlation between CALMET and observational data from Tauranga Aero AWS.
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It is noted that whilst the RMSE is a good overall measure of model performance large errors are
weighted heavily which can be seen from the statistical output for wind direction for the TAPM and
CALMET predicted data.
The annual windroses shown below in Table A-7 for each modelling year from Tauranga Aero AWS
observation station, TAPM generated data and CALMET generated data appear to adequately represent
the observational data.
Table A-2: Statistical evaluation for predicted TAPM and CALMET – 2014 modelling year
Parameter TAPM
IOA RMSE BIAS Gross Error
Wind speed (m/s) 0.6 2.4 -0.2 1.9
Wind direction (deg) 0.7 101.7 -3.6 68.4
Temperature (K) 0.6 4.2 0.0 3.5 CALMET
Wind speed (m/s) 1.0 0.3 -0.1 0.2
Wind direction (deg) 1.0 28.6 1.2 6.5
Temperature (K) 1.0 0.0 0.0 0.0
Table A-3: Statistical evaluation for predicted TAPM and CALMET – 2015 modelling year
Parameter TAPM
IOA RMSE BIAS Gross Error
Wind speed (m/s) 0.5 2.5 -0.1 2.0
Wind direction (deg) 0.6 111.2 -3.9 77.1
Temperature (K) 0.7 4.3 0.3 3.6 CALMET
Wind speed (m/s) 1.0 0.3 -0.1 0.2
Wind direction (deg) 1.0 37.5 0.1 9.6
Temperature (K) 1.0 0.0 0.0 0.0
Table A-4: Statistical evaluation for predicted TAPM and CALMET – 2016 modelling year
Parameter TAPM
IOA RMSE BIAS Gross Error
Wind speed (m/s) 0.6 2.3 -0.5 1.8
Wind direction (deg) 0.7 107.6 -7.4 72.5
Temperature (K) 0.7 4.1 0.2 3.3 CALMET
Wind speed (m/s) 1.0 0.2 -0.1 0.2
Wind direction (deg) 1.0 22.5 1.0 5.4
Temperature (K) 1.0 0.0 0.0 0.0
Table A-5: Statistical evaluation for predicted TAPM and CALMET – 2017 modelling year
Parameter TAPM
IOA RMSE BIAS Gross Error
Wind speed (m/s) 0.6 2.3 -0.4 1.8
Wind direction (deg) 0.6 111.2 -3.6 77.9
Temperature (K) 0.7 4.2 0.3 3.4 CALMET
Wind speed (m/s) 1.0 0.3 -0.1 0.2
Wind direction (deg) 1.0 30.3 0.6 6.9
Temperature (K) 1.0 0.0 0.0 0.0
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Table A-6: Statistical evaluation for predicted TAPM and CALMET – 2018 modelling year
Parameter TAPM
IOA RMSE BIAS Gross Error
Wind speed (m/s) 0.6 2.2 -0.4 1.8
Wind direction (deg) 0.6 112.4 -5.7 78.9
Temperature (K) 0.7 4.0 0.2 3.3 CALMET
Wind speed (m/s) 1.0 0.3 -0.1 0.2
Wind direction (deg) 1.0 25.4 0.7 6.2
Temperature (K) 1.0 0.0 0.0 0.0
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Table A-7: Comparison of annual windroses
Year Tauranga Aero AWS Observation station TAPM data extract at site of observation station CALMET extract extract at port site
2014
2015
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Year Tauranga Aero AWS Observation station TAPM data extract at site of observation station CALMET extract extract at port site
2016
2017
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Year Tauranga Aero AWS Observation station TAPM data extract at site of observation station CALMET extract extract at port site
2018
A-4
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The outputs from the CALMET modelling are evaluated using visual analysis of the wind fields and
extracted data and also through a comparison of the CALMET generated data at locations with
measured observational meteorological data within the modelling domain.
Figure A-1 to Figure A-6 present a snapshot visualisation of the wind field generated by CALMET for
a single hour of the modelling period for each modelling year. The wind fields are seen to follow the
terrain well and indicate the simulation produces realistic fine scale flow fields (such as terrain forced
flows) in surrounding areas.
CALMET generated meteorological data were extracted from a point within the CALMET domain. Figure
A-7 to Figure A-10 present the annual and seasonal windroses from the CALMET data for each
modelling year. Overall, the windroses generated in the CALMET modelling reflect the expected wind
distribution patterns of the area as determined based on the available measured data and the expected
terrain effects on the prevailing winds.
Figure A-11 to Figure A-15 include graphs of the temperature, wind speed, mixing height and stability
classification for each modelling year and show sensible trends considered to be representative of the
area.
Figure A-1: Representative snapshot of wind field for the Project – 2014 modelling year
A-5
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Figure A-2: Representative snapshot of wind field for the Project – 2015 modelling year
Figure A-3: Representative snapshot of wind field for the Project – 2016 modelling year
A-6
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Figure A-4: Representative snapshot of wind field for the Project – 2017 modelling year
Figure A-5: Representative snapshot of wind field for the Project – 2018 modelling year
A-7
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Figure A-6: Annual and seasonal windroses from CALMET - 2014 modelling year (Cell reference 5051)
A-8
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Figure A-7: Annual and seasonal windroses from - CALMET 2015 modelling year (Cell reference 5051)
A-9
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Figure A-8: Annual and seasonal windroses from CALMET - 2016 modelling year (Cell reference 5051)
A-10
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FigureA-9: Annual and seasonal windroses from CALMET - 2017 modelling year (Cell reference 5051)
A-11
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Figure A-10: Annual and seasonal windroses from CALMET - 2018 modelling year (Cell reference 5051)
A-12
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Figure A-11: Meteorological analysis of CALMET - 2014 modelling year (Cell Ref 5051)
A-13
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Figure A-12: Meteorological analysis of CALMET - 2015 modelling year (Cell Ref 5051)
A-14
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Figure A-13: Meteorological analysis of CALMET - 2016 modelling year (Cell Ref 5051)
A-15
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Figure A-14: Meteorological analysis of CALMET - 2017 modelling year (Cell Ref 5051)
A-16
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Figure A-15: Meteorological analysis of CALMET - 2018 modelling year (Cell Ref 5051)
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Appendix B: Isopleth diagrams
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Figure B-1: Maximum predicted 1-hour average for x3 log stack – 40g/m³
Figure B-2: Maximum predicted 1-hour average for x3 log stack – 72g/m³
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Figure B-3: Maximum predicted 1-hour average for x3 log stack – 80g/m³
Figure B-4: Maximum predicted 1-hour average for x3 log stack – 120g/m³
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Figure B-5: Maximum predicted 1-hour average for ship – 40g/m³
Figure B-6: Maximum predicted 1-hour average for ship – 72g/m³
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Figure B-7: Maximum predicted 1-hour average for ship – 80g/m³
Figure B-8: Maximum predicted 1-hour average for ship – 120g/m³