WAG AG Wagerup Phase3A FinalReport 14Feb2005

Meteorological and Dispersion Modelling Using
TAPM for Wagerup
Phase 3A: HRA (Health Risk Assessment) Concentration
Modelling – Current Emission Scenario
Final Report
Prepared for
Alcoa World Alumina Australia
P. O. Box 252,
Applecross, Western Australia, 6153
By
CSIRO Atmospheric Research
Private Bag 1
Aspendale, Vic 3195
Tel: (03) 9239 4400
Fax: (03) 9239 4444
Contact:
E-mail: [email protected]
Report C/0986
14 February 2005
This report has been prepared by CSIRO for its client and CSIRO
(including its employees and consultants) unless otherwise agreed, makes no
representations or warranties regarding merchantability, fitness for purpose
or otherwise with respect to the Report. Any third party relying on the
Report does so entirely at their own risk. CSIRO and all persons associated
with it exclude all liability (including liability for negligence) in relation to
any opinion, advice or information contained in this Report, including,
without limitation, any liability which is consequential on the use of such
opinion, advice or information to the full extent of the law, including,
without limitation, consequences arising as a result of action or inaction
taken by that person or any third parties pursuant to reliance on the Report.
Project Team:
Mark Hibberd
Peter Hurley
Mary Edwards
Ashok Luhar
Ian Galbally
Simon Bentley
PHASE 3A. FINAL REPORT
Contents
EXECUTIVE SUMMARY ........................................................................................................................3
GLOSSARY................................................................................................................................................5
1.
INTRODUCTION ............................................................................................................................12
2.
TAPM ................................................................................................................................................15
2.1.
3.
MODEL INPUTS .............................................................................................................................20
3.1.
3.2.
3.3.
3.4.
3.5.
4.
TAPM SETTINGS .........................................................................................................................17
SOURCES .....................................................................................................................................20
SOURCES MODELLED ...................................................................................................................23
EMISSION RATES .........................................................................................................................27
NOX TO NO2 CONVERSION ..........................................................................................................33
MODELLING SHORT-TERM PEAK CONCENTRATIONS ...................................................................34
MODEL OUTPUTS .........................................................................................................................37
4.1.
4.2.
4.3.
4.4.
4.5.
4.6.
4.7.
RECEPTOR LOCATIONS ................................................................................................................37
UNCERTAINTY IN MODELLED CONCENTRATIONS .........................................................................38
QUALITY ASSURANCE RUNS .......................................................................................................42
CONCENTRATION STATISTICS (SORTED BY SPECIES) ...................................................................43
CONCENTRATION STATISTICS (SORTED BY RECEPTOR SITE) .......................................................55
CONCENTRATION CONTOURS ......................................................................................................66
PEAK EVENTS ..............................................................................................................................76
5.
SUMMARY.......................................................................................................................................81
6.
REFERENCES .................................................................................................................................82
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Executive Summary
The work presented in this report is part of a study entitled “Meteorological and
Dispersion Modelling Using TAPM for Wagerup”.
The aspect addressed here is Phase 3A: Concentration Modelling for the Health Risk
Assessment (HRA) for the Current Emissions Scenario of 6,600 tonnes per day of
alumina.
The concentration modelling was carried out using TAPM (The Air Pollution Model)
with the configuration determined by the evaluations of meteorology in Phase 1 of the
Study and dispersion in Phase 2, which evaluated TAPM for air quality predictions at
Wagerup using a database of emissions and observed ambient air concentrations.
The following emission sources are included in the modelling:
• Liquor Burner Stack
• Calciner stacks 1, 2, 3, 4
• Boiler stacks 1, 2, 3
• Gas Turbine 1 stack
• Calciner 1, 2, 3 Vac Pump, 50B and Dorrco
• Calciner 4 Vac Pump and Dorrco
• 45K Cooling Tower 1
• 45K Cooling Towers 2 and 3
• 50 Cooling Towers 1 and 2
• Milling Vents
• 25A Tank Vents
• 35A Vents
• 35J Tank Vents.
The following chemical species are included in the modelling:
• 1,2,4, trimethylbenzene
• 1,3,5 trimethylbenzene
• 2-butanone
• acetaldehyde
• acetone
• acrolein
• ammonia
• arsenic
• benzo(a)pyrene equivalents
• benzene
• cadmium
• carbon monoxide (CO)
• chromium VI
• dust
• ethylbenzene
• formaldehyde
• manganese
• mercury
• methylene chloride
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•
•
•
•
•
•
•
•
•
nickel
nitrogen dioxide (NO2)
oxides of nitrogen(NOx)
selenium
styrene
sulphur dioxide (SO2)
toluene
vinyl chloride
xylenes.
Each of these species is released at different rates from one or more of the emission
sources listed above. Modelling has been carried out for the Current Emissions Scenario
(i.e. an Alumina production rate of 6,600 tonnes per day). Two sets of emissions have
been considered – the Average emission rates and the Peak emission rates. The
emission rates used have been provided by Alcoa World Alumina Australia. CSIRO has
had no role in the development or verification of these emissions. The atmospheric
concentrations modelled in this study are the direct consequence of the emissions
included in the model. Different emission rates would produce different concentrations.
The following concentration statistics are tabulated at 15 receptor points located around
and at distances up to 7 km from the Refinery:
• Annual average concentration (at average emission rates)
• Maximum 1-hour average concentrations (at peak emission rates)
• 95th percentile 1-hour average concentrations (at peak emission rates)
• 95th percentile 24-hour average concentrations (at peak emission rates)
• Maximum 10-minute average concentrations (at peak emission rates)
• Maximum 3-minute average concentrations (at peak emission rates).
Concentrations were obtained from the model TAPM (version 2.6), which was run with
four nested grid domains at 20-km, 7-km, 2-km, and 0.5-km resolution for meteorology
(31 × 31 grid points). Similarly four nested domains of 53 × 53 horizontal grid points
with resolutions of 10-km, 3.5-km, 1-km and 0.25-km were used for the pollutant
dispersion modelling. The lowest ten of the 25 vertical levels were 10, 25, 50, 100, 150,
200, 250, 300, 400 and 500 m. The default databases of soil properties, topography, and
the monthly sea-surface temperature and deep soil parameters (with a deep-soil
moisture content of 0.15) were used. The Wagerup-specific land-use database and a
refinery-generated surface heat flux value of 150 W m-2, both derived as part of the
Phase 1 work (CSIRO, 2004b), were used. The runs included building wake effects with
a total of 29 rectangular buildings included, ranging in height between 8 m and 42 m. In
all the Phase 3 runs, the Lagrangian mode was used on the inner-most grid in the
pollution dispersion calculations. The period modelled was one year from April 2003 to
March 2004.
The uncertainty of the model predictions, based on consideration of results from a range
of TAPM studies as well as uncertainties in the Wagerup region, is a factor of
approximately 2 (i.e. the actual values lie in the range of +100% to -50% of the listed
concentrations) at the 95% confidence level.
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Glossary
Simple definitions of various technical terms are given here to assist the reader. If
required, the reader should look to other sources for more formal and technical
definitions.
ABL
Atmospheric Boundary Layer. The ABL is the lowest
100 to 3000 m of the atmosphere modified by the earth’s
surface. The ABL responds to surface forcings (i.e.
heating, cooling, and roughness) with a time scale of
about an hour or less, and its extent is deeper in the
daytime and shallower in the nighttime. It is often
turbulent and is capped by a temperature inversion (see
definition below).
Aerosol
A suspension of fine solid, liquid or mixed-phase
particles in air.
AGL
Height Above Ground Level
ANSTO
Australian Nuclear Science and Technology Organisation
(http://www.ansto.gov.au/)
AUSPLUME
A simple, steady-state, Gaussian plume dispersion model
used for predicting ground-level concentrations of
pollutants from a variety of sources. It is a regulatory
model developed and approved by EPA Victoria and
other regulatory agencies. AUSPLUME requires input,
which typically contains hourly values of temperature,
wind speed, wind direction, stability, and mixing height.
BaP equivalents
Benzo(a)pyrene equivalents. This species is used as a
marker for a group of chemical compounds called
Polycyclic Aromatic Hydrocarbons (PAH). The relative
toxicities of the various PAHs have been assessed
compared to BaP (e.g. Nisbet and LaGoy, 1992).
Multiplying the concentration of each PAH by its relative
toxicity yields a concentration for the total PAH mixture
that is expressed in terms of an equivalent concentration
(with regard to toxic potency) of BaP.
Buoyancy enhancement
An increase in the effective buoyancy of a plume as a
result of merging with another buoyant plume. This leads
to greater plume rise of the combined plume than of the
individual plumes.
CALMET
A computer model providing the meteorological input for
the dispersion model CALPUFF. It is driven by observed
or large-scale model meteorology and is capable of
calculating temporally and spatially varying wind fields.
CALPUFF
An air pollution dispersion model developed by Earth
Tech Inc. (USA). It simulates the transport and diffusion
of a plume via the puff approach in which a plume is
described as consisting of a series of puffs. CALPUFF
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typically uses meteorological data generated by the
processor CALMET.
(http://www.src.com/calpuff/calpuff1.htm)
CAR
CSIRO Atmospheric Research (http://www.dar.csiro.au)
CO
Carbon monoxide
Combined source
The representation of two or more closely-spaced
emission sources (usually within the same stack) which
have similar emission characteristics by a single source.
Convective mixed layer
Also called the convective boundary layer, mixed layer
or mixing layer. A type of atmospheric boundary layer
(ABL) characterised by vigorous turbulence, generated
by the solar heating of the ground, tending to stir and mix
pollutants particularly in the vertical.
CSIRO
Commonwealth Scientific and Industrial Research
Organisation (http://www.csiro.au)
Diffusion
In air pollution meteorology the words dispersion and
diffusion are often used interchangeably. This is also the
case in this report. However, strictly speaking the two
words mean different things. Diffusion refers to dilution
of pollutants by turbulent eddies in the atmosphere whose
dimensions are smaller than that of a pollutant plume or a
puff (see also Dispersion).
Dispersion
Dispersion refers to the movement or transport of
pollutants horizontally or vertically by the wind field and
their dilution by atmospheric turbulence. Dispersion
includes both transport and diffusion of pollutants (see
also Diffusion).
Emission rate
Specifies the rate at which gas or particles are emitted
from a source. The quantity is expressed in units of
grams per second.
EPAV
Environment Protection Authority of Victoria (Australia)
(http://www.epa.vic.gov.au)
Eulerian approach
An approach to describing atmospheric diffusion in
which the behaviour of species is described relative to a
fixed coordinate system.
Exit temperature
The temperature of the gas released from a source.
Exit velocity
The velocity at which gases are emitted from source. For
a stack, the volume flow rate from the stack is obtained
by multiplying the exit velocity by the internal crosssectional area of the top of the stack.
Exponential notation
A notation used in scientific, engineering and computing
applications to represent very large and small numbers
without having to use a large number of zeros. For
example, the value 4.8E-06 = 4.8×10-6 = 0.0000048.
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GASP
Global AnalySis and Prediction. A meteorological
modelling system currently used by the Australian
Bureau of Meteorology that can provide the large-scale
(synoptic) meteorological input needed in the models
TAPM and CALMET.
glc
Ground-level concentration. Refers to pollutant
concentrations at a height where it is detected by people
standing on the ground. In modelling it is the
concentration in the lowest model level, typically 0–10 m
above the ground.
Inversion
An atmospheric layer in which temperature increases
with altitude (e.g. the layer above the atmospheric
boundary layer). These layers are stable and resistant to
vertical mixing and hence may restrict the dispersion of
pollutants. Properly described as a temperature inversion.
Lagrangian approach
An approach to describing atmospheric diffusion in
which concentration changes are described relative to the
moving fluid.
LAPS
Limited Area Prediction System. A meteorological
modelling system previously used by the Australian
Bureau of Meteorology that can provide the large-scale
(synoptic) meteorological input needed in the model
TAPM.
mg
Milligram (1 mg = 10-3 gram = 0.001 gram). One
thousandth of a gram
mg m-3
Milligram per cubic metre. 1 mg m-3 = 1000 µg m-3
NBL
Neutral Boundary Layer. A type of atmospheric
boundary layer (ABL) that forms when winds are strong
and/or when there is negligible heating or cooling of the
ground (e.g. overcast conditions). The turbulence
responsible for mixing under these conditions is
generated by wind shear.
NO
Nitric oxide
NOx
Oxides of nitrogen (commonly NOx = NO + NO2)
NO2
Nitrogen dioxide
O3
Ozone
OU
Odour Unit. The odour units are dimensionless and are
effectively “dilutions to odour threshold.” An odour
present at a concentration of 1 OU will be discerned as
odourless by approximately half the population. 10 OU
represents a mixture, which if diluted by 10 will then
have an odour detected by 50% of the respondents and so
forth.
Percentile
The pth percentile is a value so that roughly p% of the
data are smaller and (100-p)% of the data are larger than
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this value; the 50th percentile is called the median.
Quantile is a more general definition than percentile.
pg
Picogram (1 pg = 10-12 gram = 0.000000000001 gram).
One trillionth of a gram
pg m-3
Picogram per cubic metre. 1 pg m-3 = 0.000001 µg m-3
Pollutant
Used in this report in the non-legal sense to refer to a
chemical species being modelled by air pollution
dispersion models, such as TAPM.
ppb
Parts per billion (by volume): 1 ppb = 1/1000 ppm.
ppm
Parts per million (by volume): a unit for the
concentration of a gas in the atmosphere based on the
mixing ratio approach. A concentration of 1 ppm is
equivalent to a volume of 1 cubic metre of pure undiluted
gas in 1 million cubic metres of air. The expression ppm
(or ppb) is without dimensions. The ppm (or ppb) unit is
useful because its value is unaffected by changes in
temperature and pressure, and also because many
sampling techniques are based on volume concentrations.
Concentrations of gaseous compounds can be converted
from mixing ratio units, e.g. ppm units (volumetric), to
density units, e.g. mg m-3 (mass/volume), using the
following formula:
C (mg m −3 ) =
273.15 × M w × C
,
22.4136 × (273.15 + T )
where C is the concentration (ppm), Mw is the molecular
weight of the gas, and T is the ambient temperature in
degrees Celsius.
At a temperature of 0 degrees Celsius, the conversion
factor from 1 ppm to mg m-3 for nitrogen dioxide (NO2)
is 2.050.
Prognostic equation
Any equation governing a system that contains change
with time of a quantity, and therefore can be used to
determine the value of that quantity at a later time when
the other terms in the equation are known.
Quantile
The fraction (or percent) of points below the given value.
That is, the 0.3 (or 30%) quantile is the point at which
30% percent of the data fall below and 70% fall above
that value. Certain quantiles have special names. The
0.25-, 0.50-, and 0.75-quantiles are called the first,
second and third quartiles. The 0.01-, 0.02-, 0.03-, ... ,
0.98-, 0.99-quantiles are called the first, second, third, ... ,
ninety-eighth, and ninety-ninth percentiles.
Q-Q plot
A graphical data analysis technique for comparing the
distributions of two data sets. The plot consists of the
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following: vertical axis = estimated quantiles from data
set 1; horizontal axis = estimated quantiles from data
set 2. However, it is common to directly plot the one data
set against the other. That is, the actual quantile level is
not plotted. Hence, in an air pollution model evaluation
application, the Q-Q plot is essentially a plot of the sorted
observed concentrations against the sorted predicted
concentrations.
RDA
Residue Disposal Area
RHC
Robust Highest Concentration (Cox and Tikvart, 1990).
A robust test statistic calculated using information
contained in the upper end of the distribution of
concentrations. It is defined as:
RHC = C ( R) + (C − C ( R) )ln[(3R − 1) 2] ,
where C (R) is the Rth highest concentration and C is the
mean of the top R − 1 concentrations. A value of R = 11
is used in the present analysis so that C is the average of
the top ten concentrations. The RHC is based on an
exponential fit to the highest R – 1 values of the
cumulative frequency distribution.
In air quality studies, the RHC is often preferred to the
maximum value because it removes the undesirable
influence of unusual (stochastic) events, while still
representing the highest concentrations.
SBL
Stable Boundary Layer. A type of atmospheric boundary
layer (ABL) that develops during the night when the
ground is substantially cooler than the air above it, thus
forming a stable temperature gradient with height in the
air that opposes vertical motions of air and resulting in
little ambient turbulence.
SKM
Sinclair Knight Merz (an environmental consulting
company)
SO2
Sulfur dioxide
Stack
Commonly a chimney. Also referred to in air pollution
studies as a point source because the inside crosssectional area is small compared to the size of typical
eddies in the atmosphere.
Stack diameter
For air pollution studies, the inside diameter of the stack
at the exit. It is used together with the exit velocity to
calculate the volume flow rate of gas from the stack.
Stochastic
Stochastic is synonymous with “random”. It is used to
indicate that a particular subject is seen from point of
view of randomness. Stochastic is often used as
counterpart of the word “deterministic”, which means
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that random phenomena are not involved.
TAPM
The Air Pollution Model. A prognostic meteorological
and air pollution dispersion model developed by CSIRO
Atmospheric Research (http://www.dar.csiro.au/tapm).
The meteorological component of TAPM predicts the
local-scale flow, such as sea breezes and terrain-induced
circulations, given the larger-scale synoptic meteorology.
The air pollution component uses the model-predicted
three-dimensional meteorology and turbulence, and
consists of a set of species conservation equations and an
optional particle trajectory module.
Temperature inversion
see Inversion
TSP
Total Suspended Particulates– all particles below about
50 µm in diameter suspended in the atmosphere.
US EPA
United States Environmental Protection Agency
(http://www.epa.gov)
Vent
A short chimney or stack, usually located on top of a
building to vent emissions from the building.
WA
Western Australia
Wind data assimilation
A technique in which at one or more locations in a
meteorological model, the wind speed and wind direction
in the model are adjusted towards those observed in the
atmosphere. The model adjusts its airflow at this and
surrounding locations to ensure that the model wind
speed and direction at the location closely follow that
observed.
µg
Microgram (1 µg = 10-6 gram = 0.000001 gram). One
millionth of a gram
µg m-3
Microgram per cubic metre: a unit for the concentration
of a gas or particulate matter in the atmosphere based on
the density approach (mass per unit volume of air).
Concentrations of gaseous compounds can be converted
from density units, e.g. mg m-3 (mass/volume), to mixing
ratio units, e.g. ppm units (volumetric), using the
following formula:
C (ppm) =
22.4136 × (273.15 + T ) × C
,
273.15 × M w
where C is the concentration (mg m-3), Mw is the
molecular weight of the gas, and T is the ambient
temperature in degrees Celsius.
At a temperature of 0 degrees Celsius, the conversion
factor from 1 mg m-3 to ppm for nitrogen dioxide (NO2)
is 0.488.
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1. Introduction
The Wagerup alumina refinery of Alcoa World Alumina Australia is located about
130 km south of Perth in Western Australia, 25 km inland from the coast and in the
western foothills of the north-south Darling escarpment (Figure 1). The local
communities in the proximity of the Refinery include Yarloop, a small town 15° west of
south and 3 km away from the Refinery, and Hamel and Waroona, two small towns
approximately 5 km and 8 km north of the Refinery (see Figure 1).
The work presented in this report forms Phase 3A of the project “Meteorological and
Dispersion Modelling Using TAPM for Wagerup”. The larger project consists of the
components:
• Phase 1: Meteorology Evaluation of the capability of CSIRO’s The Air Pollution
Model (TAPM) to acceptably produce meteorological predictions matching
available field observations at Wagerup (CSIRO, 2004b);
• Phase 2: Dispersion Evaluation of TAPM for air quality predictions at Wagerup
using a database of emissions and observed ambient air concentrations
(CSIRO, 2004c); and
• Phase 3: Concentration Modelling Use of TAPM to generate modelled
concentrations as input for the Health Risk Assessment (HRA) and the Public
Environmental Review Document concerning the Wagerup Refinery expansion
plans.
The objective of Phase 3 is:
“To run TAPM with Wagerup specific input for four scenarios of emissions (CurrentAverage, Current-Peak, Expanded- Average, and Expanded-Peak) for agreed sources to
produce selected concentration statistics at receptor points for input into the Health
Risk Assessment and the Public Environmental Review Document. Investigate the
temporal variation of concentration around, and mechanisms causing the modelled
short-term peak concentrations.”
It has been agreed that the Phase 3 study be split into two parts; Phase 3A for the
Current emission scenarios, and Phase 3B for the Expanded emissions scenarios. This
report presents results from the Phase 3A modelling with the two emission scenarios
corresponding to a production rate of 6,600 tonnes per day of alumina, namely CurrentAverage (average emission rates) and Current-Peak (peak emission rates).
The atmospheric concentrations modelled in this study are the direct consequence of the
emissions included in the model. Different emission rates would produce different
concentrations. The emissions used have been provided by Alcoa World Alumina
Australia. CSIRO has had no role in the development or verification of these emissions.
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Bancell Road met
Station
Residue Disposal Area
met station
Figure 1: A map of Wagerup area showing the Alcoa Wagerup Refinery, Bancell Road
meteorological station, Residue Disposal Area (RDA) meteorological station, Boundary Road
air quality monitoring station, and the Upper Dam monitoring site. The Yarloop monitoring site
and the Waroona Monitor are non-operative. To the east of the Refinery is the north-south
Darling escarpment (adapted from SKM, 2002).
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The detailed objectives of Phase 3A are:
“Run the refined TAPM (as resolved in Phases 1 and 2) for the annual meteorological
file (1 April 2003 to 31 March 2004) and agreed sources to produce estimates of the
following parameters for 28 pollutants at 15 receptor points:
• Annual average concentration (at average emission rates)
• Maximum 1-hour average concentrations (peak emissions)
• 95th percentile 1-hour average concentrations (peak emissions)
• 95th percentile 24-hour average concentrations (peak emissions)
• Maximum 10-minute average concentrations (peak emissions)
• Maximum 3-minute average concentrations (peak emissions).
The 28 pollutants are oxides of nitrogen(NOx), carbon monoxide (CO), sulphur dioxide
(SO2), dust, arsenic, selenium, manganese, cadmium, chromium VI, nickel, mercury,
ammonia, benzo(a)pyrene equivalents, acetone, acetaldehyde, formaldehyde, 2butanone, benzene, toluene, xylenes, acrolein, ethylbenzene, methylene chloride,
styrene, 1,2,4 trimethylbenzene, 1,3,5 trimethylbenzene, vinyl chloride, and nitrogen
dioxide (NO2).
Produce contour plots of these six statistics for three example substances (NOx,
Formaldehyde and Mercury) to indicate the different concentration distribution
patterns for substances predominantly emitted from high and low level sources.
Calculate the conversion of NOx to NO2 using a simple titration algorithmic method.
Describe the best practice methods for deriving shorter time period (3 and 10-minute)
maximum concentrations from the Wagerup hourly TAPM concentration fields.
Investigate the temporal variation of concentration around, and mechanisms causing
the modelled 5 highest short-term peak concentrations for NOx and Formaldehyde for
three receptors (at sites 1, 3, and 14) for the peak emission scenario.
Undertake separate quality assurance runs for selected pollutants to confirm the
accuracy of the main modelling technique. Comment on the expected accuracy/level of
confidence in model predictions, based on the work performed in Phases 1 and 2.”
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2. TAPM
The Phase 1 report of the present project (CSIRO, 2004b) provides a brief introduction
to the various classes of air pollution models, and presents the advantages offered by the
prognostic approach used by CSIRO’s The Air Pollution Model (TAPM) over some of
the other commonly-used air pollution models. Although a brief description of TAPM
has been given in the CSIRO (2004b) report, we describe TAPM here again for the sake
of completeness.
TAPM is a three-dimensional, prognostic meteorological and air pollution model (see
Hurley, 2002; http://www.dar.csiro.au/tapm/ for model details). The model uses a
complete set of mathematical equations governing the behaviour of the atmosphere and
the dispersion of pollutants. The global databases input to TAPM include terrain height
(given at a resolution of about 300 m for Australia), land use, sea-surface temperature,
and synoptic meteorological analyses. All input datasets, except emissions, accompany
the TAPM software, and are easily transferred through a graphical user interface to
nested grids for the region of interest.
The meteorological component of TAPM uses the large-scale weather information
(synoptic analyses or, potentially, weather forecasts), typically obtained from the
Bureau of Meteorology LAPS (Limited Area Prediction System) or GASP (Global
Analysis and Prediction) analyses at a horizontal grid spacing of about 100 km at 6hourly intervals as boundary conditions for the model outer grid. These synoptic data
are for the horizontal wind components, temperature and moisture, and are obtained
from the output of Bureau of Meteorology meteorological model(s) that assimilates
meteorological observations from a network of stations. The vertical levels of the
synoptic analyses are in a scaled pressure coordinate system. For the present
application, the lowest of these correspond typically to 0, 75, 200, 425, 650, 875, 1100,
1325 and 1800 m above mean-sea level. TAPM then ‘zooms-in’ from the 100-km data
to model local scales at a finer resolution using a one-way nested approach to improve
efficiency and resolution, predicting local-scale meteorology (typically down to a
resolution of 1 km), such as sea breezes and terrain induced flows.
The model solves a set of momentum equations for horizontal wind components, the
incompressible continuity equation for the vertical velocity in a terrain-following
coordinate system, and scalar equations for potential virtual temperature, specific
humidity of water vapour, cloud water and rain water. Pressure is determined from the
sum of hydrostatic and (when necessary) non-hydrostatic components, and a Poisson
equation is solved for the non-hydrostatic component. Explicit cloud microphysical
processes are included. Wind observations can optionally be assimilated into the
momentum equations as nudging terms. The turbulence closure terms in the mean
equations use a gradient diffusion approach, including a counter-gradient term for the
heat flux, with eddy diffusivity determined using prognostic equations for turbulence
kinetic energy and eddy dissipation rate. A weighted vegetative canopy, soil and urban
land-use scheme is used to predict energy partitioning at the surface, while radiative
fluxes, both at the surface and at upper levels, are also included. Boundary conditions
for the turbulent fluxes are determined by Monin-Obukhov surface-layer scaling
variables and parameterisations for stomatal resistance.
The air pollution component of TAPM consists of an Eulerian (fixed location) gridbased set of species conservation equations for determining a spatially explicit
distribution of time varying ground-level pollutant concentrations, either using the
Eulerian grid-based approach and/or a Lagrangian particle approach targeted at
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PHASE 3A. FINAL REPORT
important point sources. In the Lagrangian mode (where the model coordinates move
with the flow), mass is represented as a puff in the horizontal direction and as a particle
in the vertical direction. The Lagrangian option was used in the present work. The
pollutants are transported and dispersed according to the air motions determined by the
meteorological component.
Previous versions of TAPM have been used, for example, to model year-long
meteorology and air pollution for the industrial area of Kwinana (Hurley et al., 2001)
and the Pilbara (Physick and Blockley, 2001; Physick et al., 2002); to model year-long
urban meteorology, photochemical smog and particulate matter in Melbourne (Hurley et
al., 2003a); and to compare with international model validation data sets (Luhar and
Hurley, 2003).
The performance of the meteorological component of TAPM is discussed in Section 10
of the Phase 1 report (CSIRO, 2004b) – for completeness, the main results are repeated
here.
The Index of Agreement has been found to be the most useful measure of the degree to
which the observed variable is accurately estimated by the model. It is defined as:
2
N
IOA = 1 −
∑ (P − O )
i =1
i
N
∑(P − O
i =1
i
mean
i
2
+ Oi − Omean )
,
(1)
where N is the number of observations O and predictions P. An IOA value of 0 means
no agreement whereas a value of 1 means perfect agreement. A value greater than 0.5
represents a good result for prediction of meteorology.
For the model comparisons presented in the Phase 1 report for Wagerup, the overall
IOA for TAPM for the near-surface meteorology (with winds at 30 m AGL) at Bancell
Road is 0.65 for wind speed, 0.79 for the U component, and 0.92 for the V component,
0.97 for temperature, 0.94 for net radiation, and 0.87 for relative humidity. For the
winter months, when low to moderate winds are important from the point of view of
point source emissions from the Refinery, the respective IOA values are 0.79, 0.86,
0.93, 0.89, and 0.81. The overall IOA for the near-surface meteorology at RDA is 0.73
for wind speed, 0.83 for the U component, and 0.90 for the V component. For the
summer months, when high and variable winds are relevant from the point of view of
dust emissions and management at RDA, the respective IOA values are 0.65, 0.79 and
0.84. In the summer months, the IOA values for net radiation and relative humidity at
Bancell Road are 0.94 and 0.90, respectively.
The comparisons presented in the Phase 1 report indicate that TAPM’s overall
performance is as good as and in some cases better than some of the other
internationally used prognostic meteorological models such as MM5, RAMS, and CSU.
The performance of TAPM at Wagerup is comparable to its performance elsewhere for
the near-surface meteorology, except that TAPM generally predicts stronger wind
speeds at Wagerup than the measurements. Its performance for wind speed at Wagerup
is not as good as the best of TAPM modelling for other locations. This may be due to
the complexity of the area being studied.
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The uncertainty of the TAPM modelling of ground-level concentrations is discussed in
more detail in Section 4.2 of this report. For the RHC (robust highest concentration, see
Glossary) the ratio of modelled to observed values for a range of TAPM studies shows
an average value of 1.07 with an uncertainty of ±40% at the 95% confidence level.
2.1. TAPM Settings
Version 2.6 of TAPM was used for all the simulations presented in this report. This is
the same version as used in Phases 1 and 2 (CSIRO, 2004b, c) of the present project.
The most appropriate settings of TAPM for the Wagerup modelling have been
described in Phase 1 (Meteorology) and Phase 2 (Dispersion), the latter of which
evaluated TAPM using several different databases of emissions and observed ambient
air concentrations at Wagerup.
The meteorological grids used here are the same as those used in Phase 2, but the
pollution grids cover a larger area to include all the defined receptor points (Figure 2).
Four nested domains of 31 × 31 horizontal grid points with resolutions of 20-km, 7-km,
2-km and 0.5-km are used for the meteorological modelling. Similarly four nested
domains of 53 × 53 horizontal grid points with resolutions of 10-km, 3.5-km, 1-km and
0.25-km are used for the pollutant dispersion modelling. The pollution grid was selected
to include all receptor points (Figure 2(d) and Figure 8) with the best possible
combination of fine grid resolution and model computing time. The grids are all centred
on the location 115°54′ E, 32°54.5′ S, which is equivalent to 397.133 km east and
6358.326 km north in the AMG84 (Australian Map Grid) coordinate system. The centre
point is about 1 km north-west of the Refinery and was selected to optimise the
locations of the grids with respect to the receptors. This centre point is situated 2 km
north-northwest of the centre point used in the Phase 2 modelling and 3.8 km slightly
west of north from the centre point used in the Phase 1 modelling. The lowest ten of the
25 vertical levels were 10, 25, 50, 100, 150, 200, 250, 300, 400 and 500 m, with the
highest model level at 8000 m. The default databases of soil properties, topography, and
the monthly sea-surface temperature and deep soil parameters (with a deep-soil
moisture content of 0.15) were used. The Wagerup-specific land-use database and a
refinery-generated surface heat flux value of 150 W m-2, both derived as part of the
Phase 1 work (CSIRO, 2004b), were used. The change in the centre of the grids
compared to Phases 1 and 2 produced slight changes in the apparent pattern of land-use
because of the need to map the underlying complex pattern of land-use onto a single
value for each grid square of the TAPM grids. However, the sensitivity tests reported in
the Phase 2 report indicate that the model results at the receptor points change by less
than 10% for runs with and without the Refinery heat flux. This is indicative of the
sensitivity of the model to the slight changes caused by different grid centres. In all the
Phase 3 runs, the Lagrangian mode was used on the inner-most grid in the pollution
dispersion calculations and the Eulerian mode was used on the outer grid pollutant
calculations.
The TAPM runs included building wake effects. A total of 29 rectangular buildings
were considered, ranging in height between 8 m and 42 m. The locations and horizontal
size of these buildings are shown in Figure 3, based on data supplied by Pitts (pers.
comm. 20 Aug 2004). The figure also shows the locations of the Wagerup Refinery
point sources modelled in this work, as supplied by Coffey (pers. comm. 7 Sep 2004).
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PHASE 3A. FINAL REPORT
(a)
(b)
6450
6600
6400
AMG Northing (km)
AMG Northing (km)
6500
6400
6300
6200
6350
6300
6100
6250
100
200
300
400
500
AMG Easting (km)
600
300
700
(c)
350
400
AMG Easting (km)
450
500
(d)
6366
13
6364
6380
8
9
10
6362
14
AMG Northing (km)
AMG Northing (km)
6370
6360
6350
11
6360
16
7
6358
15
6356
4
1
2
6
6354
6340
5
3
6352
6330
370
380
390
400
AMG Easting (km)
410
420
390
392
394
396
398
AMG Easting (km)
400
402
404
Vegetation types
Pasture mid-dense (seasonal)
Refinery, Urban
Shrubland low mid-dense
Forest mid-dense
Water
Grassland mid-dense tussock
Figure 2: The horizontal grid domain used in TAPM for meteorology (31 × 31 grid points). The
domains are successively nested with grid resolutions of (a) 20 km, (b) 7 km, (c) 2 km, and
(d) 0.5 km. The dispersion grids are located within these grids and have higher resolutions of
53 × 53 grid points per domain. The resolutions for the dispersion grids are (a) 10 km,
(b) 3.5 km, (c) 1 km, and (d) 0.25 km. The inner grid (d) shows the grid lines and the numbered
receptor locations.
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The period modelled was one year from 1 April 2003 to 31 March 2004. This is the
same as the period used in Phases 1 and 2 and was selected for those phases because it
had the best meteorological data available. This period was also used for Phase 3 to
maintain consistency. In order to reduce run time for dispersion modelling of the many
sources, the meteorological part of the model was only run once with the output stored
at hourly intervals (in the TAPM *.m3d files) for use in all further pollution modelling
runs.
6358
Milling Vents
AMG Norhting (km)
25A Vents
35J Vents
6357.5
Powerhouse Boiler
Multiflue
35A Vents
100 m Multiflue
Gas Turbine
Cooling Tower (50)
C4 Vac Pump
6357
Cooling Towers (45)
Calciner 4
398
398.5
AMG Easting (km)
399
Figure 3: The locations and horizontal size of the buildings used in the
TAPM runs (shown in aqua). The modelled point sources are shown – those
in red are the higher stacks (40–100 m), those in blue are shorter than 25 m.
The TAPM runs presented here do not include wind data assimilation. The Phase 2
results on the effect of including data assimilation are mixed. The wind data available
for assimilation were from 30 m at Bancell Road (18 July 2003 – 31 March 2004) and
from 8 m at the RDA (1 April 2003 – 31 March 2004), although errors in the low wind
speeds from the RDA meant that there were gaps where data from only one site were
assimilated.
Comparisons with observed ground-level concentrations were limited by the available
data: one year of NOx data from Bancell Road and Upper Dam, and 13 hours of
ANSTO tracer data. The Bancell Road data were “contaminated” by NOx sources other
than the Refinery (such as local traffic and Yarloop), which were not included in the
TAPM modelling. While wind data assimilation will generally improve modelled
concentrations close to the location where the wind data is recorded, it can worsen the
accuracy of both the modelled winds and the modelled concentrations further afield. In
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PHASE 3A. FINAL REPORT
a topographically complex region such as Wagerup where there is significant influence
of the escarpment on local wind fields, the radius of influence of 5 km for the
assimilated winds means that the influence of these assimilated winds can extend into
regions where the local wind fields differ from those at the wind data site, thus
worsening the accuracy of the modelled winds in these regions. For example, wind
direction data measured at the Bancell Road and RDA sites, which are less than 3 km
apart, show that north-easterlies are much less frequent at Bancell Road than at the
RDA (Phase 1 report; CSIRO, 2004b). Similarly, wind roses from Hamel and Yarloop
for October/November 2003 show much more frequent easterlies and south-westerlies
and much less frequent south-easterlies at Hamel than at Yarloop (WADEP, pers.
comm.). As the aim of the Phase 3 modelling for the HRA is to provide the best model
results for the whole 15 km × 15 km region around the Refinery (Figure 2(d), Figure 8),
the modelling presented here did not include wind data assimilation. The sensitivity of
the results to changes in the wind patterns is presented in Section 4.2 as part of the
discussion of model uncertainty.
All model runs were carried out on a computer cluster using Intel Pentium IV
processors running under the Linux operating system. The TAPM code was compiled
using an Intel Fortran compiler version 8.0.
3. Model Inputs
3.1. Sources
The stack (chimney) sources used in the modelling along with the relevant properties
for the modelling were provided by Alcoa World Alumina Australia (pers. comm.
13 Sep 2004). They are listed in Table 1.
Some of the stacks (for example, the 100 m Multiflue and the 65 m Boilerhouse stacks)
contain several closely-spaced flues which release buoyant plumes, i.e. the exit
temperature of the gas emitted from the flue is greater than the temperature of the
surrounding air. Buoyant plumes emitted from closely-spaced flues tend to merge
quickly with one another after their release (Briggs, 1984; Manins et al, 1992; Anfossi
et al, 1978; Overcamp and Ku, 1988). This plume merging results in an enhancement of
the plume buoyancy, thus causing a greater plume rise of the combined plume than the
individual plume rises that occur when the flues are treated as separate point sources.
The enhancement of the plume buoyancy (and plume rise) can be understood by noting
that as the hot air rises it mixes in (entrains) cooler surrounding air, which reduces the
temperature of the rising plume. Eventually the temperature of the air in the plume is
reduced to that of the surrounding air and the plume stops rising. If one buoyant plume
is rising close to another buoyant plume, then some of the air entrained by the first
plume will be warmer air from the second plume rather than the cooler surrounding air.
The consequence of this is that it takes longer for the plume to cool to the temperature
of the surrounding air so that both plumes together continue to rise higher than they
would individually.
The emissions from the multiflue stacks are best modelled using a single combined
source with its emission characteristics (stack height, diameter, exit temperature, exit
velocity) chosen such that the buoyancy flux and momentum flux (defined below) of the
combined source is equal to the sum of these quantities for the individual flues.
Merging of buoyant plumes can also occur for plumes that are released from stacks
separated by some tens of metres or even a hundred metres. In this case, each of the
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stacks is modelled separately but the buoyancy of each plume is increased by a
buoyancy enhancement factor NE. This factor can be specified as an input parameter for
each source in TAPM.
For a number of stacks with the same emission geometries and exit conditions, the
buoyancy enhancement factor is defined as (e.g. Manins et al, 1992):
⎡n + S ⎤
NE = ⎢
,
⎣ 1 + S ⎥⎦
(2)
where n is the number of stacks and S is the dimensionless separation factor, defined as
⎡ (n − 1) ⋅ ∆s ⎤
S = 6⋅⎢ 13
⎣ n ⋅ ∆z ⎥⎦
32
,
(3)
where ∆s is the stack separation and ∆z is the rise of an individual plume.
The plume rise ∆z depends on wind speed and other meteorological conditions. Figure 4
shows histograms of the plume rise from the individual Boiler 1 and Calciner 1 flues as
modelled by TAPM for the annual model year considered in this report (April 2003 to
March 2004). In most case the plume rise lies between 20 and 200 m. The median
plume rise is 45 m for the Boiler 1 flue and 65 m for the Calciner 1 flue.
1500
Frequency (hours per year)
Boiler 1 flue
1000
500
0
0
100
200
Plume rise above stack top (m)
300
1500
Frequency (hours per year)
Calciner 1 flue
1000
500
0
0
100
200
Plume rise above stack top (m)
300
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Figure 4: Histograms of plume rise modelled by TAPM for the
year April 2003 to March 2004 for two separate flues, one in the
65 m Boilerhouse multiflue and one in the 100 m Multiflue stacks.
Figure 5 shows the results from equation (2) for the variation of NE with stack
separation (and n = 2) for two typical values of plume rise. For two stacks, an
enhancement factor of 2 is referred to as full buoyancy enhancement and is seen to
occur for stacks separated by less than about 10 m. This corresponds to the case of the
Wagerup multiflues where two or more flues are separated by much less than 10 m.
2
m
1.8
e
ris
e
∆z
=
20
0
1.6
m
Pl
um
e
ris
e
1.4
∆z
=
65
m
Buoyancy enhancement factor, NE
Pl
u
1.2
1
0
50
100
Stack Separation, ∆s (m)
150
200
Figure 5: Buoyancy enhancement factor for two stacks as a function of stack
separation for two values of plume rise ∆z = 65 m and ∆z = 200 m. Values for
NE calculated using equations (2) and (3).
The merging of the buoyant plumes from each of the flues in the multiflue stacks can be
taken into account in the modelling either by using the buoyancy enhancement factors
or, equivalently, by treating them as a combined source.
If the buoyancy enhancement factors are used, then each flue is modelled separately and
the appropriate buoyancy enhancement factor is included in the modelling, which
increases the individual plume buoyancy by this factor. For two flues NE = 2 and for
three flues NE = 3. In cases where each flue has the same emission geometry and exit
conditions, then each of these enhanced plumes will be modelled as having the same
plume rise and dispersion behaviour. Rather than modelling the same plume three times,
it is computationally more efficient to model them as a combined source (single plume)
that has its buoyancy flux (Fb) and momentum flux (Fm) equal to (or as close as possible
to) the sum of these quantities for the individual flues. The pollution emission rate from
the combined source is set equal to the sum of the pollution emission rates from the
individual flues.
The quantities Fb (m4 s-3) and Fm (m4 s-2) are defined as:
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PHASE 3A. FINAL REPORT
⎛ T
Fb = ⎜⎜1 − e
⎝ Ts
⎞
⎟⎟ g ws rs2 ,
⎠
(4)
⎛T ⎞
Fm = ⎜⎜ e ⎟⎟ ws2 rs2 ,
⎝ Ts ⎠
(5)
where Te is the ambient temperature (K) of the environment, Ts is the stack exit
temperature (K), rs is the stack top radius (m), ws is the stack exit velocity (m s-1), and g
is the acceleration due to gravity (m s-2).
A common method for matching the fluxes is first to set the diameter of the combined
source such that the exit area of the combined source is equal to the sum of the areas of
the flues being combined. Then the combined source exit velocity and exit temperature
are set equal to the averages of the values for the individual flues. Small adjustments to
the exit velocity and temperature are then made to match the buoyancy and momentum
fluxes of the combined source as closely as possible to the sums of these quantities for
the individual flues. For cases where the buoyancy flux dominates the plume rise (such
as for the Wagerup plumes), it is more important to match the buoyancy flux than the
momentum flux.
For two flues with equal emission characteristics, the buoyancy flux of the combined
source will be twice that from a single flue. This is equivalent to using a buoyancy
enhancement factor of 2 for an individual flue. Thus the combined source approach is
sometimes referred to as full plume buoyancy enhancement.
In contrast to these cases, there are some other sources such as the Milling Vents, where
there are several sources with identical emission characteristics located near to each
other but with very low buoyancy and not close enough for there to be any plume-rise
enhancement. Within a few hundred to a thousand metres from these sources, the
plumes overlap. Thus these sources can be modelled as a single source with the
emission characteristics (stack height, diameter, exit temperature, exit velocity) of one
of the sources and with the emission rate (in g/s) equal to the total from the sources
being modelled by the single stack. The validity of this approach can be demonstrated
by considering the case of two stacks, each with identical emission characteristics. If the
pollutant emission rate from one stack is x g/s and this produces ground-level
concentrations (glcs) of y µg/m3 at some point, say 1 km downwind, then two such
stacks will produce glcs of 2y µg/m3 at the same point. The same glcs are achieved if
just one stack is modelled with an emission rate of 2x g/s.
3.2. Sources modelled
The properties of the stack sources included in the modelling are listed in Table 1. The
sources shown in italics are the individual flues that are modelled as combined sources.
The properties of the combined sources are listed directly above the data for each set of
individual flues. These properties were calculated using the procedure outlined in the
previous section. Combined sources were used for the Calciner 1–3 and the
Boilerhouse 1–3 multiflues.
Flues from the Liquor Burner and the Calciner 1, 2, 3 Vacuum Pump and Dorrco are
part of the 100 m Multiflue with the Calciner 1–3 flues but the former have not been
included in the combined source because of their quite different emission
characteristics, which lead to different plume trajectories.
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The trajectory of a plume above its release point is given by the relation (Weil, 1988):
1
F
F
⎛
⎞3
z = ⎜ 8.3 m2 ⋅ x + 4.2 b3 ⋅ x 2 ⎟ ,
U
⎝ U
⎠
(6)
where z is the height of the plume above the release point, x is the downwind distance,
and U is the local wind speed at stack height.
The trajectories of the individual plumes from the 100 m Multiflue are shown in Figure
-1
6 for a wind speed of 4 m s and assuming no interaction between the plumes. Changes
in the wind speed change the absolute heights of the plume but not the relativities
between the trajectories of the plumes from the different flues. The similarity of the
plume rise from the three Calciner flues reflects the similarities between their emission
characteristics and justifies them being treated as a combined source. As expected, the
trajectory for the combined Calciner source shows considerably more plume rise than
the individual sources.
Plume rise from top of stack (m)
80
in
mb
Co
60
ed
C
r 1ine
alc
3 fl
ues
e
3 flu ue
iner
fl
Calc iner 1
e
Calc er 2 flu
in
Calc
40
Liquor Bu
20
Vac. Pump
rner flue
& Dorrco flu
e
0
0
20
40
60
80
100
Downwind distance from stack (m)
Figure 6: Plume trajectories for the plumes from the flues in the 100 m
Multiflue calculated according to equation (6) for a wind speed of 4 m s-1
assuming no interaction between the plumes (except for the Combined Source
trajectory)
On the other hand, the trajectory of the Liquor Burner (LB) plume shows only one-third
of the plume rise of the combined Calciner plume, and the Vacuum Pump/Dorrco
(VPD) plume shows only one-quarter of the rise of the combined Calciner plume. The
large differences between these trajectories make it unlikely that there will be much
interaction between these plumes and so unlikely that there will be any buoyancy
enhancement between either of these two plumes or with the combined Calciner plume.
In the absence of information on the degree of such interaction, the LB and VPD
plumes are modelled as separate plumes, i.e. without any buoyancy enhancement. If any
buoyancy enhancement occurs, it will lead to lower ground-level concentrations from
these sources.
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The details of the assumptions made in modelling the other sources are listed below:
•
Calciner 4 Vac Pump and Dorrco. There are two separate stacks but the emissions
rates supplied by Alcoa are the total for both stacks. Because most of the volume
flow (92%) occurs from the 50VAC4 stack and the stack heights are similar (40 m
and 37 m), only the 50VAC4 stack was included in the modelling using the exit
characteristics of this stack with the total emission rate attributed to this stack.
•
Cooling Towers 1 and 2 (50CT). The two cooling towers are treated as one source
with the diameter set to give the same effective area as the total of the two separate
towers.
•
Milling Vents. There are three separate Mill Vents, which are all low enough (12 m)
to be affected by building wakes so that they rapidly effectively become volumes
sources. As these are close to each other but not so close that they can be considered
to produce a single plume, just one of these is modelled with the typical exit
characteristics for a single vent. However, the total emission rate of the pollutants
released from these vents is considered to all be discharged through the single
modelled vent.
•
25A Tank Vents. There are two stacks 25A1 and 25A3. These have been treated in
the same way as the Milling Vent stacks with just a single stack included in the
modelling at the location of 25A1.
•
35A Vents. There are two separate vent stacks. These have been treated like the
Milling Vents with just a single stack included in the modelling.
•
35J Vents. There are seven separate vent stacks. These have been treated like the
Milling Vents with just a single stack included in the modelling.
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PHASE 3A. FINAL REPORT
Table 1. Relevant properties of the sources modelled in Phase 3A (location, stack height, exit
temperature, stack diameter, and both average and peak exit velocities) for the Current Emissions
Scenario (6,600 tpd) as supplied by Coffey (pers. comm. 13 Sep 2004).
Stacks modelled
AMG84 Coordinates
East
North
Stack
height
Temper
-ature
Current scenario
Average
Peak
Exit
Exit
Velocity Velocity
(m/s)
(m/s)
(km)
(km)
(m)
Stack
Diamet
-er
(m)
Liquor Burner (in Multiflue)
398.179
6357.052
100
0.925
338
27.9
28.7
Calciner 1–3 flues (modelled
as combined source)
398.179
6357.052
100
3.44
450
20.6
24.2
Calciner1 flue (in Multiflue stack)
398.179
6357.052
100
1.9
432
21.6
24.7
Calciner2 flue (in Multiflue stack)
398.179
6357.052
100
1.9
433
20.8
24.3
Calciner 3 flue (in Multiflue stack)
398.179
6357.052
100
2.15
469
19.6
23.8
Calciner 4 stack
398.270
6356.955
48.8
2.35
430
20.1
23.8
Boiler 1–3 flues (modelled as
combined source)
398.622
6357.512
65
3.71
390
14.6
21.8
Boiler 1 (in Boilerhouse Multiflue)
398.622
6357.512
65
2.4
374
14.5
20.2
Boiler 2 (in Boilerhouse Multiflue)
398.622
6357.512
65
2.0
397
16.2
25.0
Boiler 3 (in Boilerhouse Multiflue)
398.622
6357.512
65
2.0
404
13.7
20.6
Gas Turbine 1 stack
398.583
6357.395
40
3.03
371
22.4
30.7
Calciner 1,2,3 Vac Pump,
50B and Dorrco
(in Multiflue)
398.179
6357.052
100
1.1
345
7.5
12.6
Calciner 4 Vac Pump and
Dorrco (combined emission),
use 50VAC4 stack details
398.245
6357.012
40
0.914
345
7.5
12.6
45K Cooling Tower 2 and 3
(1 duty, 1 standby cell)
398.504
6357.000
16.3
8
323
15.3
15.3
45K Cooling Tower 1
398.485
6357.000
8
7
323
13.7
13.7
50 Cooling Tower 1 and 2
398.228
6357.052
4
7.07
322
3.7
3.7
Milling Vents
398.142
6357.840
12
0.44
343
2.3
2.3
25A Tank Vents
398.131
6357.744
20
0.5
371
12.9
12.9
35A Vents
398.399
6357.415
19
0.6
370
1.3
1.8
35J Tank Vents
398.380
6357.540
9
0.49
357
1.7
2.0
(K)
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 26
PHASE 3A. FINAL REPORT
3.3. Emission Rates
In a typical TAPM run, all sources of a particular pollutant are included as input to
TAPM, with the output being hourly modelled ground-level concentrations of that
pollutant for each hour of the period modelled (in this case a full year).
However, because of the complexity and large computing time required to use this
method for the 28 pollutant species and 2 emissions scenarios to be modelled in this
Phase, separate model runs are undertaken for each stack source listed in Table 1 with
separate runs for average and peak exit rates when these differed from each other. This
required a total of 26 annual runs of TAPM. In each case the emission rate was assumed
to be 1 g/s of a notional pollutant. The TAPM runs thus produced concentration fields
for a nominal pollutant from each stack. The results from these runs were scaled
according to the actual emission rates of each pollutant from each stack, as listed in
Table 2, and then combined to derive concentration fields for each pollutant for both
average and peak emission rates using the relation
GLC species = e1 ⋅ GLC1 + e2 ⋅ GLC 2 + K + en ⋅ GLC n ,
(7)
where GLCspecies is the ground-level concentration for the species which is emitted at a
rate ei (in g/s) from source i and GLCi is the modelled ground-level concentration for an
emission rate of 1 g/s from source i.
The validity of this approach was verified by comparison of concentrations derived in
this manner with those for the same species from a “typical” TAPM run where all
sources of the particular pollutant were included, as described in Section 0.
The NO2 concentrations were derived from modelled NOx and representative O3
concentrations using the method described in Section 3.4.
The emissions listed as from “Boiler 2/3 (Non-condensables)” were split 50:50 between
the Boiler 2 flue and Boiler 3 flue.
These emission rates from each source are as supplied by Alcoa World Alumina
Australia on 7 September 2004 and updated for the Vent Stacks on 13 September 2004.
CSIRO had no role in the development or verification of these emissions. The modelled
concentrations are directly dependent on these emissions. If the emissions are different,
then the modelled concentrations will be different.
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 27
PHASE 3A. FINAL REPORT
Table 2. Emission rates (Current Scenario with a production rate of 6,600 tonnes per day) as
supplied by Alcoa World Alumina Australia from each of the sources for each of the
27 modelled species (Coffey, pers. comm. 13 Sep 2004, revised 16 Dec 2004). The 28th species
(NO2) is modelled separately, as described in Section 3.4. Both the average and peak emission
rates are listed. In the modelling, the emissions listed as from “Boiler 2/3 (Non-condensables)”
were split 50:50 between the Boiler 2 and Boiler 3 flues. The numbers in the table are given
using exponential notation which is commonly used in computing, for example, the value
4.81E-01 = 4.81×10-1 = 0.481.
CHEMICAL SPECIES
STACK SOURCE
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Gas Turbine 1
AVERAGE
EMISSION
RATE (g/s)
1.24E+00
2.16E+00
1.25E+00
3.60E+00
2.43E+00
7.61E+00
7.96E+00
2.64E+00
3.00E+00
PEAK
EMISSION
RATE (g/s)
4.20E+00
3.18E+00
4.47E+00
6.93E+00
4.28E+00
1.77E+01
1.65E+01
4.37E+00
1.36E+01
1. NOx
2. CO
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Gas Turbine 1
7.65E+00
5.11E+00
8.89E+00
1.27E+00
2.29E+00
2.97E-01
2.47E-01
1.20E-01
2.99E+00
2.11E+01
1.11E+01
2.42E+01
3.69E+00
4.28E+00
2.31E+00
2.66E+00
8.37E-01
7.83E+00
3. SO2
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Gas Turbine 1
1.04E-01
3.22E-01
4.05E-01
2.34E-01
1.24E-01
1.96E-01
2.12E-01
1.79E-01
4.27E-01
4.33E-01
9.94E-01
9.17E-01
1.24E+00
3.32E-01
9.46E-01
1.38E+00
4.73E-01
2.56E+00
4. Dust
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
7.01E-02
5.94E-01
4.10E-01
4.19E-01
4.06E-01
5.33E-01
3.42E+00
2.40E+00
1.24E+00
7.97E-01
5. Arsenic
Liquor Burner
Boiler 1
Boiler 2
Boiler 3
Boiler 2/3 (Non-condensables)
25A Tank Vents
1.42E-04
2.20E-03
9.84E-05
8.26E-05
2.97E-06
2.08E-05
1.46E-04
3.03E-03
1.52E-04
1.25E-04
2.97E-06
4.12E-05
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 28
PHASE 3A. FINAL REPORT
AVERAGE
EMISSION
RATE (g/s)
PEAK
EMISSION
RATE (g/s)
Liquor Burner
Boiler 2
Boiler 3
Boiler 2/3 (Non-condensables)
Milling Vents
25A Tank Vents
8.50E-04
3.54E-05
2.97E-05
2.76E-05
5.74E-06
7.27E-05
8.74E-04
5.47E-05
4.49E-05
2.76E-05
5.74E-06
1.44E-04
7. Manganese
Liquor Burner
Boiler 1
Boiler 2
Boiler 3
Boiler 2/3 (Non-condensables)
Milling Vents
25A Tank Vents
7.08E-05
1.02E-03
5.81E-04
4.88E-04
6.54E-04
1.15E-05
6.85E-03
7.28E-05
1.41E-03
8.97E-04
7.36E-04
6.54E-04
1.15E-05
1.35E-02
8. Cadmium
Boiler 2/3 (Non-condensables)
2.23E-07
2.23E-07
9. Chromium VI
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
3.17E-07
1.82E-06
1.82E-06
1.82E-06
1.82E-06
4.44E-06
4.44E-06
4.44E-06
3.17E-07
1.82E-06
1.82E-06
1.82E-06
1.82E-06
4.44E-06
4.44E-06
4.44E-06
10. Nickel
Boiler 2
Boiler 3
Boiler 2/3 (Non-condensables)
25A Tank Vents
1.01E-04
8.44E-05
1.15E-04
2.15E-04
1.55E-04
1.27E-04
1.15E-04
4.25E-04
11. Mercury
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 2/3 (Non-condensables)
Milling Vents
25A Tank Vents
3.05E-04
6.28E-05
6.28E-05
6.28E-05
6.28E-05
3.55E-03
3.18E-05
2.77E-04
3.05E-04
6.28E-05
6.28E-05
6.28E-05
6.28E-05
3.55E-03
3.18E-05
2.77E-04
12. Ammonia
Boiler 2
Boiler 3
Milling Vents
25A Tank Vents
1.19E-01
1.00E-01
3.56E-02
6.35E-02
1.84E-01
1.51E-01
3.56E-02
1.25E-01
13. BaP Equivalents
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
2.61E-06
5.09E-07
4.84E-07
5.71E-07
7.24E-07
2.68E-06
5.82E-07
5.64E-07
6.92E-07
7.97E-07
CHEMICAL SPECIES
STACK SOURCE
6. Selenium
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 29
PHASE 3A. FINAL REPORT
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
Milling Vents
25A Tank Vents
35A Vents (Non cons)
AVERAGE
EMISSION
RATE (g/s)
2.41E-06
2.41E-06
6.89E-08
8.10E-07
8.96E-06
PEAK
EMISSION
RATE (g/s)
4.05E-06
4.05E-06
6.89E-08
1.60E-06
1.22E-05
14. Acetone
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
45K Cooling Tower 2 and 3
45K Cooling Tower 1
50 Cooling Tower 1 and 2
Milling Vents
25A Tank Vents
35A Vents (Non cons)
35J Tank Vents (Non cons)
4.87E-02
3.48E-02
3.75E-02
3.38E-02
6.52E-02
2.80E-02
2.44E-02
0.00E+00
7.50E-02
7.50E-02
2.89E-01
9.99E-02
1.30E-02
1.49E-02
1.62E-01
8.61E-02
4.08E-02
1.39E-01
9.11E-02
8.68E-02
7.61E-02
1.06E-01
3.82E-02
2.59E-02
2.65E-02
2.29E-01
2.29E-01
9.17E-01
3.16E-01
8.79E-02
1.49E-02
7.01E-02
1.44E-01
4.68E-02
15. Acetaldehyde
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
45K Cooling Tower 2 and 3
45K Cooling Tower 1
50 Cooling Tower 1 and 2
Milling Vents
25A Tank Vents
35A Vents (Non cons)
35J Tank Vents (Non cons)
7.37E-03
5.68E-02
5.21E-02
7.27E-02
9.29E-02
7.64E-03
8.62E-03
4.82E-03
1.39E-02
1.39E-02
0.00E+00
0.00E+00
0.00E+00
8.04E-03
2.00E-02
1.28E-02
1.19E-02
6.37E-02
8.90E-02
8.68E-02
1.09E-01
1.30E-01
7.64E-03
1.15E-02
4.82E-03
4.02E-02
4.02E-02
1.15E-01
3.96E-02
1.10E-02
8.04E-03
2.00E-02
1.61E-02
1.38E-02
16. Formaldehyde
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
2.83E-03
5.04E-02
4.48E-02
3.34E-01
8.87E-02
7.64E-03
5.75E-03
4.82E-03
1.01E-03
2.83E-03
9.96E-02
9.89E-02
6.42E-01
1.30E-01
7.64E-03
5.75E-03
4.82E-03
3.22E-03
CHEMICAL SPECIES
STACK SOURCE
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 30
PHASE 3A. FINAL REPORT
CHEMICAL SPECIES
STACK SOURCE
Calciner 4 VacPump & Dorrco
45K Cooling Tower 2 and 3
45K Cooling Tower 1
Milling Vents
25A Tank Vents
35A Vents (Non cons)
35J Tank Vents (Non cons)
AVERAGE
EMISSION
RATE (g/s)
1.01E-03
0.00E+00
0.00E+00
1.15E-04
3.92E-04
1.49E-04
1.38E-04
PEAK
EMISSION
RATE (g/s)
3.22E-03
1.15E-01
3.96E-02
1.15E-04
4.88E-04
1.73E-04
1.38E-04
17. 2-Butanone
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
45K Cooling Tower 2 and 3
45K Cooling Tower 1
Milling Vents
25A Tank Vents
35A Vents (Non cons)
35J Tank Vents (Non cons)
5.67E-03
4.95E-03
5.38E-03
1.66E-02
1.01E-02
7.64E-03
5.75E-03
4.82E-03
4.36E-03
4.36E-03
0.00E+00
0.00E+00
9.19E-04
5.29E-03
2.97E-02
6.21E-03
1.27E-02
8.48E-03
8.07E-03
4.04E-02
1.81E-02
7.64E-03
5.75E-03
4.82E-03
7.65E-03
7.65E-03
1.15E-01
3.96E-02
9.19E-04
5.29E-03
2.48E-02
7.57E-03
18. Benzene
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
45K Cooling Tower 2 and 3
45K Cooling Tower 1
Milling Vents
25A Tank Vents
35A Vents (Non cons)
35J Tank Vents (Non cons)
3.29E-02
4.98E-03
4.94E-03
2.38E-03
7.54E-03
4.78E-03
3.59E-03
3.01E-03
4.69E-04
4.69E-04
0.00E+00
0.00E+00
7.75E-05
0.00E+00
0.00E+00
0.00E+00
5.24E-02
8.48E-03
8.07E-03
2.38E-03
9.05E-03
5.73E-03
4.31E-03
3.62E-03
6.04E-04
6.04E-04
5.73E-02
1.98E-02
7.75E-05
3.31E-04
3.25E-05
2.06E-04
19. Toluene
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
1.70E-03
1.91E-03
1.82E-03
2.14E-03
2.72E-03
3.82E-03
2.87E-03
2.41E-03
4.02E-02
4.25E-03
2.12E-03
2.02E-03
2.38E-03
3.02E-03
3.82E-03
2.87E-03
2.41E-03
4.02E-02
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 31
PHASE 3A. FINAL REPORT
CHEMICAL SPECIES
STACK SOURCE
Calciner 4 VacPump & Dorrco
45K Cooling Tower 2 and 3
45K Cooling Tower 1
50 Cooling Tower 1 and 2
Milling Vents
25A Tank Vents
35A Vents (Non cons)
AVERAGE
EMISSION
RATE (g/s)
4.02E-02
0.00E+00
0.00E+00
0.00E+00
1.03E-04
3.19E-03
6.79E-04
PEAK
EMISSION
RATE (g/s)
4.02E-02
5.73E-02
1.98E-02
2.20E-04
1.03E-04
3.19E-03
6.79E-04
20. Xylenes
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
25A Tank Vents
7.15E-04
6.89E-04
6.56E-04
7.73E-04
9.81E-04
9.26E-03
9.26E-03
3.55E-04
9.49E-04
1.06E-03
1.01E-03
1.19E-03
1.51E-03
9.26E-03
9.26E-03
4.79E-04
21. Acrolein
Calciner 1
Calciner 2
Calciner 3
Calciner 4
8.48E-03
8.07E-03
9.51E-03
1.21E-02
9.70E-03
9.41E-03
1.15E-02
1.33E-02
22. Ethylbenzene
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
25A Tank Vents
3.97E-04
2.12E-04
2.02E-04
2.38E-04
3.02E-04
1.16E-04
4.08E-04
2.43E-04
2.35E-04
2.88E-04
3.32E-04
2.29E-04
23. Methylene Chloride
Calciner 1
Calciner 2
Calciner 3
Calciner 4
Boiler 1
Boiler 2
Boiler 3
Calciner 1-3 VacPump & Dorrco
Calciner 4 VacPump & Dorrco
25A Tank Vents
9.33E-03
8.88E-03
1.05E-02
1.33E-02
1.53E-02
1.15E-02
9.65E-03
4.02E-02
4.02E-02
3.14E-03
1.07E-02
1.03E-02
1.27E-02
1.46E-02
2.10E-02
1.77E-02
1.46E-02
6.75E-02
6.75E-02
6.21E-03
24. Styrene
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
45K Cooling Tower 2 and 3
45K Cooling Tower 1
50 Cooling Tower 1 and 2
25A Tank Vents
5.24E-04
3.18E-04
3.03E-04
3.57E-04
4.53E-04
3.65E-03
1.26E-03
1.64E-04
1.65E-05
5.39E-04
3.64E-04
3.53E-04
4.32E-04
4.98E-04
3.65E-03
1.26E-03
1.64E-04
3.27E-05
25. 1,2,4 Trimethylbenzene
Liquor Burner
2.27E-04
2.33E-04
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 32
PHASE 3A. FINAL REPORT
25A Tank Vents
AVERAGE
EMISSION
RATE (g/s)
4.79E-04
PEAK
EMISSION
RATE (g/s)
9.47E-04
26. 1,3,5 Trimethylbenzene
Liquor Burner
Calciner 1
Calciner 2
Calciner 3
Calciner 4
25A Tank Vents
5.67E-05
5.30E-05
5.05E-05
5.94E-05
7.54E-05
1.49E-04
5.83E-05
6.06E-05
5.88E-05
7.21E-05
8.30E-05
2.94E-04
27. Vinyl Chloride
Calciner 1
Calciner 2
Calciner 3
Calciner 4
5.30E-05
5.05E-05
5.94E-05
7.54E-05
6.06E-05
5.88E-05
7.21E-05
8.30E-05
CHEMICAL SPECIES
STACK SOURCE
3.4. NOx to NO2 Conversion
The NOx (nitrogen oxides) emission rates were used to calculate NOx concentration
fields. The NO2 (nitrogen dioxide) concentrations were derived using a simple titration
algorithm for the conversion of nitric oxide (NO) to NO2 in the presence of ozone (O3):
NO + O3 Æ NO2 + O2,
(8)
which is approximately correct at night-time but is conservative (i.e. potentially overestimates NO2) in the near field (less than 1 hour downwind of the source) during
daylight hours when photochemical reactions become important.
This reaction equation shows that both compounds on the left-hand side (nitric oxide
and ozone) are needed to produce nitrogen dioxide, NO2. The amount of NO2 produced
is limited by the smaller of either the NO or the O3 concentration. If there is more O3
than NO then all of the NO will be converted to NO2. If, on the other hand, there is
more NO than O3, then NO2 is only produced until all of the O3 is used up. Thus the
NO2 concentration is taken to be the minimum of the NOx and the ozone concentration
with both expressed in ppb. The NOx emission rates used in the TAPM modelling to
generate NOx glcs are expressed in terms of NO2, as is standard practice in air pollution
studies.
In the absence of hourly ozone data for the modelled period (April 2003 to March
2004), the average diurnal variation of ozone concentrations at the Upper Dam site for
the period March 2002 to March 2003 reported by Johnson (2003) was used. These data
are reproduced in Figure 7.
Capping of the peak 10-minute and 3-minute averages for NO2 due to the limited
availability of ozone for titration of NO to NO2 is discussed at the end of Section 3.5.
The affected peak NO2 concentrations are indicating by shading of the cells in the tables
in Sections 4.4 and 4.5.
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 33
PHASE 3A. FINAL REPORT
Average Ozone Concentration (ppb)
30
20
10
0
0
6
12
Time of day (hours)
18
24
Figure 7. Average diurnal variation of ozone concentration used for deriving NO2
concentrations from modelled NOx concentrations (after Johnson, 2003). Concentrations
are given in ppb (parts per billion).
3.5. Modelling Short-term Peak Concentrations
It is well established in the literature that observed annual peak ground level
concentrations for averaging times ranging from minutes to hours can be related
through a power law expression of the form (e.g. Hibberd, 1998, NSW EPA, 2001):
c max,2
⎛t
= c max,1 ⎜⎜ 1
⎝ t2
p
⎞
⎟⎟ ,
⎠
(9)
where cmax,i is the maximum concentration for an averaging time ti and the value of the
exponent p typically lies in the range 0.1 to 0.4 with lower values representative of
stable conditions and larger values more appropriate for highly unstable (convective)
conditions. The value of p also decreases with increasing distance from the source.
Provided that an appropriate value of p is used, this equation has been found to give
good estimates of the highest concentrations likely to be observed in a year. For
example, knowing the highest 1-hour average concentration in a year, it is possible to
predict the highest 10-minute average or highest 3-minute average concentration.
Uncertainty in these estimates arises because the value of the exponent p depends on
many factors, including:
• the configuration of the source, e.g. point, area
• atmospheric stability
• the distance from the source.
Table 3 lists commonly-used values of p with an indication of the origin of data used to
derive these exponents.
In many cases, the maximum 1-hour average ground-level concentrations near tall
stacks are observed during convective conditions and a value of p = 0.4 is used. This
gives the peak 10-minute average as 2.0 × cmax,1hr and the peak 3-minute average as
3.3 × cmax,1hr. In cases where the maximum ground-level concentrations are observed at
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night in stable conditions, for example as plume impact on nearby hills, a value of
p = 0.2 is more commonly applied. This gives the peak 10-minute average as
1.4 × cmax,1hr and the peak 3-minute average as 1.8 × cmax,1hr.
Many modelling studies use a default value of p = 0.2, and this value is included in the
commonly-used air quality models AUSPLUME and CALPUFF.
Table 3. Power-law exponents derived from a range of studies for different
source configurations. After Katestone Scientific (1998).
Source type
Power-law
exponent
p
Types of studies
F – field, L – laboratory
N – numerical, T – theoretical
Area
0.10 – 0.15
L, N
Line
0.25
Surface point
L, N, T
0.15 – 0.2
F, L, N, T
Tall wake-free point
0.4
F, L, N, T
Wake-affected point
0.10
F, L
Volume
0.10
T
Although equation (9) is only valid for long data series such as year-long sets of data, it
is often mis-applied to much shorter periods. For example, it is often applied to 1-hour
average data for each hour of a year to calculate a maximum short-term peak during that
hour, even though the actual “peak” may be much larger or much smaller than the
calculated peak value. This discrepancy can easily be seen by considering two simple
cases:
1. A pollutant concentration of 60 µg m-3 is observed for the first 3 minutes of an
hour with a concentration of zero for the rest of the hour. The 1-hour average
concentration is then 3 µg m-3 so that cmax,3-min = 20 × cmax,1hr.
2. A pollutant concentration of 10 µg m-3 is observed for each 3 minutes of a full
hour. Both the maximum 3-minute average concentration and the 1-hour average
concentration are 10 µg m-3. Thus cmax,3-min = 1 × cmax,1hr.
The factors of 1 and 20 are clearly much different from the factors obtained from the
power-law model with p = 0.2 or 0.4, as given above. This occurs because the equation
is based on properties of statistical extremes – it accurately predicts extreme statistics
when there are a sufficiently large number of events, but it does not apply to data in any
particular hour.
A consequence of this limitation is that the power-law method cannot be used to
generate a time series of, for example, 10-minute average concentrations from modelled
1-hour average concentrations. It is only the annual peak 10-minute average
concentration that can be obtained.
The most uncertain aspect of the power-law method is the selection of the correct value
of p for calculating the peak values. In this study we determine the value of p from the
magnitude of the concentration variance (a measure of the variability in the
concentrations) calculated by the model, which accounts for its variability with
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prevailing meteorological and dispersion conditions and hence for its variability with
distance from the sources and time of day. The TAPM modelling for this study had the
option switched on to calculate the concentration variance. In the processing step
combining the model results from each stack source (represented by equation (7)), the
variances contributed by each source is also taken into account. The larger the
concentration variance, the larger the value was of p and vice versa, with values of p
ranging between 0.1 and 0.4. Thus the most appropriate value of p was calculated for
each hour of the day at each point on the modelled domain. Using equation (9) and the
modelled 1-hour average concentration, a set of numbers was produced, from which the
annual maximum 10-minute and 3-minute concentrations were derived at each point on
the modelled domain. (As noted above, the individual values at each hour of the year
are not realistic, but the annual maxima of these numbers do represent the extremes of
the distribution.) A significant advantage of the technique is that the exponent chosen
each hour more closely represents the dispersion conditions prevailing at that time. It
can be more accurate than the simple AUSPLUME technique of applying a constant
value of p = 0.2, as it correctly accounts for the larger exponent that applies for tall
stack emissions into convective conditions and the smaller exponent for near-surface
sources. This TAPM technique has been validated for peak 10-minute concentrations
using emissions and ground-level monitoring data in the Kwinana region (Hurley, pers.
comm.).
This TAPM approach represents the current state of knowledge for statistical modelling
of extreme annual events.
The results obtained in this study for the maximum 1-hour, 10-minute and 3-minute
concentrations show that at the 15 receptor points, the short-term peaks are equivalent to
using exponents between 0.12 and 0.24 with the value varying across the grid.
The model results can be compared with observations of 6-minute average NOx
concentrations at Upper Dam for the calendar year 2003, where the maximum observed
1-hour average concentration in 2003 was 76 µg m-3 and the maximum 6-minute
average concentration was 102 µg m-3, corresponding to an exponent p = 0.13. The
caveat on this calculation is that the numbers were derived from single points at the
extreme end of the distribution of values and so are subject to some uncertainty, which
cannot be quantified without a much more detailed analysis.
The modelled TAPM results for NOx obtained in this study for the Upper Dam site
corresponds to an exponent of p = 0.24, which is somewhat larger than the observed
value. This indicates that the results for the 10-minute and 3-minute peaks presented
here may be conservative, i.e. they will tend to be over-predictions rather than underpredictions.
The peak-to-mean ratios for NO2 are affected by the capping of the 10-minute and 3minute averages for NO2 due to the limited availability of ozone for titration of NO to
NO2 (as described in Section 3.4). The ozone data used in this study do not include
short-term (sub-hourly) variations (which in any case are small because of the nature
and extent of ozone sources in the background air). On occasions when the 1-hour
average NOx concentration exceeds the ozone concentration for that hour, then the
modelled 10-minute and 3-minute NO2 concentrations will be the same as the 1-hour
average NO2 and ozone concentration for that hour. This is equivalent to a power law
exponent p = 0. On other occasions, just the modelled 10-minute or 3-minute NOx
concentration will exceed the 1-hour average ozone concentration, so only these shorter
term NO2 peaks will be capped (producing values of p between 0 and that for NOx). As
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described above, the individual 10-minute and 3-minute concentrations calculated each
hour are not realistic, but the annual peak values do represent the extreme values. The
peak NO2 concentrations that are limited by the available ozone are highlighted by
shading of the cells in which they occur in the tables in Sections 4.4 and 4.5.
4. Model Outputs
4.1. Receptor Locations
Table 4 lists the coordinates and Figure 8 shows the locations of the 15 receptor sites at
which the required concentration statistics of the 28 chemical species were extracted.
Table 4. Locations of each of the fifteen receptors used in the modelling study.
(NB. Receptor 12 was not included in the selected sites.)
Receptor
AMG84 Coordinates
Location
Eastings (km)
Northings (km)
1
398.091
6354.834
2
399.393
6355.006
3
396.830
6352.949
4
397.138
6354.827
5
395.721
6352.503
6
399.650
6354.240
7
390.775
6358.733
Bremner Rd
8
392.360
6362.131
Somers/McClure Rds
9
396.099
6362.024
10
398.460
6362.000
11
398.207
6360.331
13
400.520
6364.215
14
400.727
6360.830
15
400.726
6356.435
16
397.365
6359.285
Boundary Rd
Yarloop
Hamel
Escarpment
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Figure 8: Location of the receptors used in this modelling study
overlaid on an aerial photograph of the site.
4.2. Uncertainty in modelled concentrations
The performance statistics for the meteorological component of TAPM were presented
in Section 2. The performance of the concentration (pollution) modelling component of
TAPM has been evaluated using the robust highest concentration and is described here.
The robust highest concentration (Cox and Tikvart, 1990) is a robust test statistic
calculated using information contained in the upper end of the distribution of
concentrations. It is defined as:
RHC = C ( R) + (C − C ( R) )ln[(3R − 1) 2] ,
(10)
where C(R) is the Rth highest concentration and C is the mean of the top R − 1
concentrations. A value of R = 11 is usually used in TAPM studies, in which case C is
the average of the top ten concentrations. The RHC is based on an exponential fit to the
highest R – 1 values of the cumulative frequency distribution. In air quality studies, the
RHC is often preferred to the maximum value because it removes the undesirable
influence of unusual (stochastic) events, while still representing the highest
concentrations.
Table 5 lists the ratio of modelled-to-observed RHCs from the most recent studies
undertaken using TAPM Version 2. The ratio ranges from 0.83 (a 17% underprediction)
to 1.46 (a 46% over-prediction) with a mean of 1.07. The results indicate that in any
particular modelling study, the uncertainty in the modelled RHCs is approximately
±40% at the 95% confidence level (i.e. two standard deviations). For more extreme
statistics such as the annual maximum 1-hour average, 10-minute average or 3-minute
average concentration, the uncertainty will be somewhat greater, and for less extreme
statistics such as the annual average or 95th percentiles the uncertainty will be smaller,
but the magnitude of these uncertainties have not been evaluated. Although it should be
simple to evaluate the uncertainty in modelled annual averages, this is not the case.
Measured concentrations are often confounded by zero offset problems, which can be of
similar magnitude to the annual average, although much smaller than peak
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concentrations. In addition, modelling often doesn’t include all sources of the particular
pollutant (such as the vehicular and Yarloop sources of NOx in the current modelling).
Table 5. List of the ratio of modelled to observed robust highest concentrations
(RHC) for a range of studies using TAPM.
Location
Species
Ratio of modelled
to observed RHC
Reference
Kwinana, site 1
SO2
0.87
Hurley et al., 2002
Kwinana, site 2
SO2
0.91
Hurley et al., 2002
Kwinana, site 3
SO2
1.46
Hurley et al., 2002
Kwinana, site 4
SO2
0.83
Hurley et al., 2002
Kwinana, site 5
SO2
1.27
Hurley et al., 2002
Kwinana, site 6
SO2
1.13
Hurley et al., 2002
Pilbara, site 1
NOx
0.87
Hurley et al., 2003b
Pilbara, site 2
NOx
1.06
Hurley et al., 2003b
Anglesea, site 1
SO2
1.01
Hill and Hurley, 2003
Anglesea, site 2
SO2
1.29
Hill and Hurley, 2003
Kincaid (USA)
SF6
1.19
Luhar and Hurley, 2003
Indianapolis
SF6
0.92
Luhar and Hurley, 2003
Pilbara, site 1
NO2
1.27
Hurley et al., 2003b
Pilbara, site 2
NO2
1.21
Hurley et al., 2003b
Perth
NO2
0.90
Hurley et al., 2002
Melbourne, site 1
NO2
1.12
Hurley et al., 2003a
Melbourne, site 2
NO2
1.14
Hurley et al., 2003a
Melbourne, site 3
NO2
1.20
Hurley et al., 2003a
Melbourne, site 4
NO2
1.21
Hurley et al., 2003a
Pilbara
O3
1.05
Hurley et al., 2003b
Perth
O3
1.02
Hurley et al., 2002
Melbourne, site 1
O3
0.80
Hurley et al., 2003a
Melbourne, site 2
O3
1.00
Hurley et al., 2003a
Melbourne, site 3
O3
0.94
Hurley et al., 2003a
Melbourne, site 4
O3
1.02
Hurley et al., 2003a
Average ± standard deviation
1.07 ± 0.17
Factors contributing to the uncertainty in model results include the turbulent (random)
nature of dispersion in the turbulent atmosphere, inaccuracies in the mathematical
description of the physical processes that occur in the atmosphere, and uncertainties in
the numerical solutions of the many equations in the model. A further factor is
uncertainty or variability in the source emission rates. As mentioned above, the
modelling of extreme events, such as annual maximum 1-hour average concentrations,
has the highest level of uncertainty. The nature of the TAPM uncertainty is similar to
the uncertainty in weather predictions of the timing and location of thunderstorms.
Uncertainties are inherent in any modelling of the atmosphere. TAPM incorporates the
best techniques for dispersion modelling consistent with the ability to do year-long
model runs, albeit using large amounts of computing resources.
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Two further analyses of uncertainty are undertaken. An analysis is presented of the
year-to-year variation in synoptic wind directions at Wagerup and an analysis is made
of the sensitivity of model results to wind data assimilation of the available wind data
from Wagerup.
The annual variability in the large-scale synoptic weather pattern in the Wagerup region
and the representativeness of the modelled year has been investigated by analysing the
6-hourly 10-m wind directions for the grid point closest to Wagerup in the Bureau of
Meteorology’s GASP (Global Analysis and Prediction) analyses, which are used as the
synoptic input to TAPM. The data have been sorted into 22.5º bins centred on the
directions labelled on the axis of Figure 9.
The pattern shows that the winds are in the southerly quadrants (south-east and southwest) about two-thirds of the time, and in the northerly quadrants (north-east and northwest) about one-third of the time. The annual variability in the frequency of each wind
direction is represented by the shaded vertical bar; it is typically ±30% about the mean
(range 12% to 49%). The modelled year is seen to be a fairly average year with all
frequencies within 20% of the median values, except for easterlies (33% less frequent
than the median) and southerlies (24% more frequent than the median). Although
ground-level concentrations are influenced by more meteorological conditions than just
the wind directions, the inter-annual variability of ±30% in the frequency of wind in
each sector would be expected to lead to similar sized variations in the annual average
concentrations, but determining the effect on maximum concentrations is more
complicated. In fact, a full comparison of the inter-annual variability would require
repeat modelling for several years, which is currently beyond the scope of what is
possible for such a complex set of modelling conditions. Even the current modelling for
the Current and Expansion scenarios required more than 10,000 hours of CPU time.
Probability (%) of wind in given direction
during full year
12
10
Modelled Year
(Apr03-Mar04)
2004
2003
2002
2001
2000
1999
1998
1997
Range (1997-2004)
8
6
4
2
0
N
NE
E
SE
S
SW
W
NW
N
Wind direction
Figure 9. Probability distribution of 10-m wind directions at Wagerup for the years 1997–
2004 compared with those for the modelled year (April 2003–March 2004) indicated by the
solid line. Data are from the 6-hourly GASP (Global Analysis and Prediction) records that
are used as the synoptic input to TAPM.
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Some model runs for NOx were undertaken using wind data assimilation, as discussed
in Section 2.1. The results from these runs provide an indication of the sensitivity of the
model results to uncertainties in the wind direction and speed in the meteorological
input to the model. The simulations were an annual run for NOx using the Current
Scenario peak emission rates presented in Table 2 of the Phase 3A report (CSIRO,
2004d) with assimilation of available wind data from 30 m at Bancell Road and 8 m at
the RDA. Table 6 lists the ratio at the receptor site of the concentration modelled with
data assimilation to that without data assimilation.
For the maximum 1-hour average concentration, the bulk of the ratios are in the range
from 0.4 to 2.0, with an outlier at site 3, where the ratio is 3.1. As can be seen from
Figure 25, site 3 is in a region of low 1-hr average ground-level concentrations bordered
by a steep concentration gradient to the west. A rotation of the modelled wind with
wind data assimilation brings in the much higher ground-level concentrations from the
west to receptor 3. Because the maximum 1-hour average concentration only occurs
once per year, this difference between results with and without wind data assimilation at
receptor 3 would not necessarily occur at that receptor if another year’s meteorology
was used. The extreme sensitivity of this statistic (maximum concentration) is seen
when comparing its ratios with the ratios of the 10th highest concentration in the table,
which are all within the range 0.5 to 1.5, i.e. within ±50% of the runs without data
assimilation.
Table 6. Ratio of modelled concentrations for NOx (Current Scenario
– Peak Emissions) when TAPM was run with data assimilation
compared to the results obtained without data assimilation.
Receptor
cmax
(1-hr avg)
RHC
(1-hr avg)
10th highest
(1-hr avg)
Annual
average
1
1.5
1.6
1.5
1.9
2
1.3
1.3
1.4
2.4
3
3.1
2.8
1.4
1.6
4
2.0
1.8
1.2
1.5
5
1.0
1.1
1.1
1.2
6
1.0
1.3
1.3
2.1
7
0.4
0.4
0.5
1.0
8
0.8
0.9
0.7
1.2
9
0.9
1.1
0.7
1.1
10
0.7
0.7
0.6
1.1
11
0.8
0.9
0.8
1.0
13
1.0
1.2
1.1
1.5
14
1.2
1.3
1.5
1.7
15
1.5
1.4
1.2
1.3
16
1.0
1.0
0.9
1.1
average
1.2 ± 0.7
1.2 ± 0.6
1.1 ± 0.3
1.4 ± 0.4
These results in Table 6 and Figure 9 indicate that the TAPM model uncertainty of
±40% derived from Table 5 from a range of studies is an underestimate for the
topographically complex region of Wagerup with the significant influence of the
escarpment on local wind fields. As mentioned elsewhere, wind direction data measured
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at the Bancell Road and RDA sites, which are less than 3 km apart, show that northeasterlies are much less frequent at Bancell Road than at the RDA (Phase 1 report;
CSIRO, 2004b). Similarly, wind roses from Hamel and Yarloop for October/November
2003 show much more frequent easterlies and south-westerlies and much less frequent
south-easterlies at Hamel than at Yarloop (WADEP, pers. comm.). Although wind data
assimilation will generally improve modelled concentrations close to the location where
the wind data is recorded, this will not be the case to the north of the Refinery including
at Hamel or for much of the 15 km × 15 km region considered in this modelling. The
comparison of results with and without data assimilation is presented here to indicate
the sensitivity of the model results to changes in the wind patterns.
Based on an analysis of all the above information, taking into account the occurrence of
one outlier in Table 6, we conclude that the scenario model results for maximum 1-hour
average concentrations presented in this report have an uncertainty of a factor of
approximately 2 (i.e. the actual values lie in the range of +100% to -50% of the scenario
model concentrations) at the 95% confidence level. We conclude that the same level of
uncertainty also applies to the other reported scenario concentrations (annual averages,
95th percentiles, maximum 10-minute and maximum 3-minute average concentrations).
4.3. Quality Assurance Runs
For two pollutants, NOx and formaldehyde, TAPM was run using all sources of the
pollutant in a single input file to generate quality assurance runs. For example, for NOx,
the method includes all the NOx sources with the associated emission rates (g/s) in a
single TAPM run.
Table 7. Comparison of results from Quality Assurance (QA) run with results from the
weighted sum method described in Section 3.3.
Site
Species
Max. 1-hr average (µg m-3)
Results
using
Eq(1)
QA
run
Difference
Species
Max. 1-hr average (µg m-3)
Results
using
Eq(1)
QA
run
Difference
1
NOx
55.1
53.6
-3%
Formaldehyde
0.86
0.83
-3%
2
NOx
68.9
67.5
-2%
Formaldehyde
0.99
1.00
+1%
3
NOx
74.9
69.6
-7%
Formaldehyde
0.95
0.92
-3%
4
NOx
84.5
73.9
-13%
Formaldehyde
0.99
0.98
-1%
5
NOx
95.3
98.2
+3%
Formaldehyde
1.06
1.05
-1%
6
NOx
89.2
85.7
-4%
Formaldehyde
1.01
1.10
+9%
7
NOx
83.9
84.7
+1%
Formaldehyde
0.66
0.62
-6%
8
NOx
36.2
33.0
-9%
Formaldehyde
0.58
0.54
-7%
9
NOx
40.6
42.8
+5%
Formaldehyde
0.58
0.57
-2%
10
NOx
42.1
45.7
+9%
Formaldehyde
0.72
0.70
-3%
11
NOx
48.5
48.5
0%
Formaldehyde
0.77
0.84
+9%
13
NOx
33.9
32.7
-4%
Formaldehyde
0.46
0.45
-2%
14
NOx
85.0
86.1
+1%
Formaldehyde
0.69
0.72
+4%
15
NOx
74.7
72.8
-3%
Formaldehyde
1.35
1.34
-1%
16
NOx
52.0
52.6
+1%
Formaldehyde
0.98
1.00
+2%
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These results are compared with the results obtained from the method used in the rest of
the modelling presented in this report, which is described by Equation (7). This
combines the TAPM results from each point source with a weighting according to the
emission rates from each source. The quality assurance runs were designed to test both
the model and the post-processing steps.
Table 7 lists the results for the maximum 1-hour average concentrations at each of the
receptor sites. (As the maximum 1-hour average concentration is a once in a year
extreme event, it represents the most stringent test that can be used for this comparison.
Other statistics will show smaller differences.) It compares the results obtained using
the weighted sum method with those from the QA run and lists the differences as a
percentage at each receptor point. The differences range from -13% to +9%.
These reflect uncertainties in TAPM modelling which arise from the numerical
solutions of a large number of equations and the stochastic (Lagrangian) modelling
technique used on the inner grid. Comparison of contour plots of the modelled
concentration fields indicate similar agreement over the whole modelled domain (not
shown). These results confirm the veracity of the weighted sum approach for computing
the ground-level concentrations of a large number of species emitted from a large
number of separate sources.
4.4. Concentration Statistics (sorted by Species)
Table 8 lists the concentration statistics for all 28 chemical species modelled at each of
the 15 receptor sites. The same results are shown in Table 9 sorted by receptor site. The
results are shown to one decimal place as this represents an uncertainty of at most 10%
in the results. As indicated in the previous section, results of many TAPM modelling
studies indicate that it is not possible to obtain better accuracy than this, particularly for
peak statistics.
The 95th percentile value represents a concentration where 95% of the data are smaller
and 5% of the data are larger than this concentration. For the 24-hour averages, it
represents the 18th highest concentration in a year of 365 24-hour averages, whereas for
the 1-hour averages it represents the 440th highest concentration in a year of 8760 1hour averages. Although on any particular day, the 24-hour average will always be
smaller than (or equal to) the maximum 1-hour average for that day, for the 95th
percentiles there is no simple relation. The 95th percentile 24-hour average can be either
larger or smaller than the 95th percentile 1-hour average, as is observed in Table 8.
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Table 8. Selected modelled concentration statistics sorted by chemical species for each of the
28 chemical species at each of the 15 receptor sites for the Current Emissions Scenario of 6,600
tonnes per day (as revised 16 Dec 2004 (Coffey, pers. comm.)). The annual averages are for the
average emission rates, whereas all other statistics are for peak emission rates. The shaded NO2
cells indicate values that are limited by the available ozone, see Section 3.5.
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
NOx
1
2.6E-01
2.9E+00
1.4E+00
5.5E+01
8.4E+01
1.1E+02
NOx
2
2.9E-01
3.4E+00
2.0E+00
6.9E+01
1.0E+02
1.3E+02
NOx
3
2.0E-01
2.4E+00
5.8E-01
7.5E+01
1.1E+02
1.4E+02
NOx
4
2.5E-01
3.2E+00
8.7E-01
8.4E+01
1.3E+02
1.6E+02
NOx
5
1.9E-01
2.5E+00
4.5E-01
9.5E+01
1.4E+02
1.8E+02
NOx
6
2.8E-01
3.1E+00
2.1E+00
8.9E+01
1.2E+02
1.5E+02
NOx
7
2.5E-01
3.3E+00
1.3E+00
8.4E+01
1.2E+02
1.6E+02
NOx
8
1.7E-01
2.5E+00
1.5E+00
3.6E+01
5.4E+01
7.0E+01
NOx
9
2.7E-01
3.0E+00
3.0E+00
4.1E+01
6.3E+01
8.6E+01
NOx
10
2.3E-01
2.4E+00
2.1E+00
4.2E+01
6.2E+01
8.1E+01
NOx
11
3.8E-01
4.8E+00
4.9E+00
4.8E+01
7.7E+01
1.0E+02
NOx
13
1.4E-01
1.5E+00
1.2E+00
3.4E+01
5.2E+01
6.9E+01
NOx
14
3.7E-01
4.0E+00
3.5E+00
8.5E+01
1.3E+02
1.6E+02
NOx
15
4.4E-01
5.2E+00
3.3E+00
7.5E+01
1.1E+02
1.4E+02
NOx
16
5.4E-01
6.9E+00
8.3E+00
5.2E+01
8.1E+01
1.1E+02
CO
1
2.7E-01
3.4E+00
1.9E+00
5.6E+01
8.1E+01
1.0E+02
CO
2
3.2E-01
4.2E+00
2.4E+00
6.5E+01
9.7E+01
1.3E+02
CO
3
1.9E-01
2.7E+00
8.4E-01
7.7E+01
1.0E+02
1.3E+02
CO
4
2.3E-01
3.3E+00
1.3E+00
5.6E+01
8.3E+01
1.1E+02
CO
5
1.7E-01
2.5E+00
5.7E-01
6.5E+01
9.6E+01
1.2E+02
CO
6
2.9E-01
4.0E+00
2.5E+00
7.2E+01
9.7E+01
1.2E+02
CO
7
1.6E-01
2.4E+00
1.4E+00
3.4E+01
5.1E+01
6.7E+01
CO
8
1.5E-01
2.5E+00
1.7E+00
3.9E+01
5.8E+01
7.5E+01
CO
9
2.4E-01
3.1E+00
3.6E+00
4.1E+01
6.5E+01
8.7E+01
CO
10
2.1E-01
2.8E+00
2.5E+00
5.2E+01
8.1E+01
1.1E+02
CO
11
3.5E-01
4.2E+00
5.1E+00
5.2E+01
8.4E+01
1.2E+02
CO
13
1.6E-01
2.0E+00
2.2E+00
3.6E+01
5.5E+01
7.2E+01
CO
14
3.7E-01
4.3E+00
5.2E+00
1.1E+02
1.6E+02
2.1E+02
CO
15
4.7E-01
6.9E+00
3.4E+00
1.0E+02
1.6E+02
2.1E+02
CO
16
5.2E-01
8.1E+00
8.5E+00
5.0E+01
8.0E+01
1.1E+02
SO2
1
1.8E-02
3.7E-01
1.7E-01
6.5E+00
1.0E+01
1.4E+01
SO2
2
2.0E-02
4.2E-01
2.3E-01
7.8E+00
1.2E+01
1.5E+01
SO2
3
1.3E-02
3.1E-01
7.8E-02
9.8E+00
1.5E+01
1.9E+01
SO2
4
1.7E-02
4.0E-01
1.2E-01
1.1E+01
1.6E+01
2.2E+01
SO2
5
1.3E-02
3.0E-01
5.8E-02
1.1E+01
1.7E+01
2.2E+01
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 44
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
SO2
6
1.9E-02
3.9E-01
2.5E-01
1.0E+01
1.4E+01
1.7E+01
SO2
7
1.6E-02
4.1E-01
1.6E-01
9.2E+00
1.4E+01
1.8E+01
SO2
8
1.2E-02
3.1E-01
1.9E-01
3.9E+00
5.9E+00
7.7E+00
SO2
9
1.8E-02
3.9E-01
3.9E-01
4.7E+00
7.1E+00
9.3E+00
SO2
10
1.5E-02
3.1E-01
2.7E-01
5.1E+00
7.7E+00
1.0E+01
SO2
11
2.5E-02
5.5E-01
5.7E-01
5.3E+00
8.4E+00
1.1E+01
SO2
13
9.6E-03
1.8E-01
1.4E-01
4.1E+00
6.2E+00
8.2E+00
SO2
14
2.4E-02
4.8E-01
4.2E-01
1.0E+01
1.5E+01
2.0E+01
SO2
15
3.0E-02
7.1E-01
4.2E-01
9.1E+00
1.4E+01
1.8E+01
SO2
16
3.9E-02
8.7E-01
1.1E+00
6.4E+00
1.0E+01
1.4E+01
Dust
1
1.3E-02
2.5E-01
9.6E-02
4.9E+00
7.7E+00
1.0E+01
Dust
2
1.7E-02
2.9E-01
1.2E-01
6.4E+00
1.0E+01
1.3E+01
Dust
3
8.9E-03
1.8E-01
5.4E-02
5.5E+00
7.5E+00
9.3E+00
Dust
4
1.2E-02
2.5E-01
7.9E-02
5.2E+00
8.6E+00
1.2E+01
Dust
5
8.2E-03
1.7E-01
4.2E-02
3.8E+00
5.2E+00
6.3E+00
Dust
6
1.4E-02
2.4E-01
1.2E-01
5.9E+00
8.7E+00
1.1E+01
Dust
7
9.8E-03
1.6E-01
9.6E-02
3.1E+00
4.0E+00
4.8E+00
Dust
8
8.6E-03
1.8E-01
1.3E-01
3.0E+00
4.5E+00
5.8E+00
Dust
9
1.4E-02
2.5E-01
2.6E-01
4.1E+00
6.5E+00
8.7E+00
Dust
10
1.1E-02
2.4E-01
1.7E-01
5.5E+00
8.7E+00
1.2E+01
Dust
11
1.9E-02
3.6E-01
3.3E-01
5.9E+00
9.4E+00
1.3E+01
Dust
13
7.4E-03
1.5E-01
1.2E-01
3.2E+00
5.1E+00
6.9E+00
Dust
14
1.7E-02
3.6E-01
3.3E-01
4.9E+00
7.3E+00
9.5E+00
Dust
15
2.2E-02
4.2E-01
1.7E-01
7.7E+00
1.2E+01
1.6E+01
Dust
16
2.9E-02
7.3E-01
5.9E-01
5.3E+00
7.0E+00
8.4E+00
Arsenic
1
2.2E-05
1.4E-04
1.0E-04
2.5E-03
4.0E-03
5.5E-03
Arsenic
2
2.3E-05
1.3E-04
1.0E-04
3.6E-03
5.7E-03
7.7E-03
Arsenic
3
1.7E-05
1.1E-04
5.9E-05
2.8E-03
3.9E-03
4.9E-03
Arsenic
4
2.2E-05
1.4E-04
9.8E-05
3.0E-03
4.8E-03
6.6E-03
Arsenic
5
1.6E-05
1.0E-04
4.9E-05
4.0E-03
6.1E-03
8.1E-03
Arsenic
6
2.4E-05
1.2E-04
9.0E-05
4.5E-03
6.2E-03
7.8E-03
Arsenic
7
2.0E-05
1.3E-04
5.0E-05
4.8E-03
7.5E-03
1.0E-02
Arsenic
8
1.4E-05
9.2E-05
6.4E-05
2.2E-03
3.3E-03
4.4E-03
Arsenic
9
2.3E-05
1.3E-04
1.4E-04
2.4E-03
3.9E-03
5.5E-03
Arsenic
10
2.2E-05
1.2E-04
1.6E-04
2.0E-03
3.2E-03
4.6E-03
Arsenic
11
3.7E-05
2.5E-04
3.2E-04
3.8E-03
5.5E-03
7.0E-03
Arsenic
13
1.2E-05
7.1E-05
5.9E-05
1.5E-03
2.5E-03
3.5E-03
Arsenic
14
3.1E-05
1.9E-04
1.7E-04
3.5E-03
5.4E-03
7.3E-03
Arsenic
15
3.3E-05
2.2E-04
1.3E-04
3.7E-03
5.8E-03
7.8E-03
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 45
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
Arsenic
16
5.0E-05
2.9E-04
4.2E-04
4.0E-03
5.7E-03
7.2E-03
Selenium
1
2.3E-05
1.6E-04
1.2E-04
2.6E-03
3.9E-03
5.0E-03
Selenium
2
2.3E-05
1.5E-04
1.0E-04
2.7E-03
4.0E-03
5.2E-03
Selenium
3
1.6E-05
1.4E-04
8.2E-05
1.7E-03
2.3E-03
2.9E-03
Selenium
4
2.4E-05
2.0E-04
1.1E-04
4.6E-03
6.5E-03
8.3E-03
Selenium
5
1.2E-05
9.8E-05
6.8E-05
1.5E-03
2.1E-03
2.6E-03
Selenium
6
2.0E-05
1.4E-04
9.1E-05
2.4E-03
3.4E-03
4.2E-03
Selenium
7
9.2E-06
7.2E-05
4.9E-05
8.4E-04
1.2E-03
1.6E-03
Selenium
8
9.6E-06
7.4E-05
5.8E-05
1.0E-03
1.4E-03
1.7E-03
Selenium
9
1.9E-05
1.1E-04
1.5E-04
1.8E-03
2.6E-03
3.3E-03
Selenium
10
2.1E-05
1.7E-04
1.7E-04
4.2E-03
6.0E-03
7.8E-03
Selenium
11
4.2E-05
3.5E-04
3.1E-04
1.4E-02
2.0E-02
2.5E-02
Selenium
13
1.2E-05
7.3E-05
1.0E-04
9.5E-04
1.4E-03
1.9E-03
Selenium
14
2.6E-05
1.3E-04
2.2E-04
4.2E-03
6.2E-03
8.1E-03
Selenium
15
3.0E-05
2.1E-04
1.0E-04
4.1E-03
6.4E-03
8.7E-03
Selenium
16
6.2E-05
4.7E-04
5.2E-04
1.5E-02
2.1E-02
2.6E-02
Manganese
1
7.3E-04
7.3E-03
1.6E-03
2.4E-01
3.5E-01
4.6E-01
Manganese
2
4.7E-04
4.9E-03
1.3E-03
1.3E-01
2.0E-01
2.6E-01
Manganese
3
5.5E-04
6.1E-03
1.2E-03
1.4E-01
2.0E-01
2.7E-01
Manganese
4
1.1E-03
1.6E-02
2.1E-03
4.2E-01
6.0E-01
7.7E-01
Manganese
5
4.1E-04
5.4E-03
1.2E-03
1.3E-01
1.9E-01
2.3E-01
Manganese
6
3.3E-04
3.8E-03
9.7E-04
1.0E-01
1.5E-01
2.0E-01
Manganese
7
3.4E-04
3.6E-03
9.9E-04
7.6E-02
1.1E-01
1.5E-01
Manganese
8
2.9E-04
3.2E-03
1.3E-03
8.2E-02
1.2E-01
1.5E-01
Manganese
9
7.2E-04
6.8E-03
4.6E-03
1.5E-01
2.2E-01
2.8E-01
Manganese
10
9.6E-04
1.0E-02
5.7E-03
3.8E-01
5.5E-01
7.1E-01
Manganese
11
2.3E-03
2.3E-02
1.1E-02
1.3E+00
1.8E+00
2.3E+00
Manganese
13
2.4E-04
2.3E-03
1.9E-03
3.1E-02
4.4E-02
5.5E-02
Manganese
14
5.8E-04
4.6E-03
4.9E-03
8.5E-02
1.3E-01
1.8E-01
Manganese
15
3.5E-04
4.0E-03
8.5E-04
7.5E-02
1.2E-01
1.5E-01
Manganese
16
3.4E-03
3.8E-02
1.9E-02
1.3E+00
1.9E+00
2.4E+00
Cadmium
1
1.6E-09
7.4E-09
1.2E-09
1.7E-07
2.3E-07
2.8E-07
Cadmium
2
1.8E-09
7.5E-09
1.3E-09
2.4E-07
3.8E-07
5.2E-07
Cadmium
3
1.3E-09
6.0E-09
6.9E-10
1.7E-07
2.7E-07
3.7E-07
Cadmium
4
1.5E-09
7.2E-09
1.2E-09
2.0E-07
3.0E-07
4.1E-07
Cadmium
5
1.3E-09
5.8E-09
7.4E-10
2.6E-07
4.0E-07
5.3E-07
Cadmium
6
1.9E-09
6.7E-09
1.5E-09
2.9E-07
4.0E-07
5.0E-07
Cadmium
7
1.7E-09
7.0E-09
1.5E-09
3.2E-07
5.0E-07
6.8E-07
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 46
PHASE 3A. FINAL REPORT
Chemical Species
Cadmium
Site
8
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
1.1E-09
5.1E-09
2.5E-09
1.4E-07
2.2E-07
2.9E-07
Annual
average
Cadmium
9
1.8E-09
8.2E-09
6.0E-09
1.6E-07
2.6E-07
3.7E-07
Cadmium
10
1.6E-09
7.2E-09
4.9E-09
1.3E-07
2.2E-07
3.1E-07
Cadmium
11
2.6E-09
1.3E-08
1.0E-08
1.8E-07
3.2E-07
4.5E-07
Cadmium
13
9.4E-10
4.3E-09
2.0E-09
9.5E-08
1.6E-07
2.3E-07
Cadmium
14
2.5E-09
1.1E-08
7.1E-09
2.2E-07
3.5E-07
4.8E-07
Cadmium
15
2.6E-09
1.3E-08
2.5E-09
2.5E-07
3.9E-07
5.3E-07
Cadmium
16
3.4E-09
1.6E-08
1.3E-08
1.7E-07
2.9E-07
4.3E-07
Chromium (VI)
1
1.5E-07
7.3E-07
2.6E-07
1.2E-05
1.9E-05
2.6E-05
Chromium (VI)
2
1.8E-07
8.0E-07
4.0E-07
1.8E-05
2.6E-05
3.4E-05
Chromium (VI)
3
1.2E-07
5.8E-07
1.2E-07
1.6E-05
2.1E-05
2.6E-05
Chromium (VI)
4
1.4E-07
7.1E-07
1.7E-07
1.6E-05
2.5E-05
3.3E-05
Chromium (VI)
5
1.1E-07
5.1E-07
1.1E-07
2.1E-05
3.0E-05
3.9E-05
Chromium (VI)
6
1.7E-07
7.6E-07
4.2E-07
2.2E-05
2.9E-05
3.6E-05
Chromium (VI)
7
1.4E-07
6.2E-07
2.6E-07
2.0E-05
2.9E-05
3.9E-05
Chromium (VI)
8
1.0E-07
5.6E-07
3.3E-07
8.9E-06
1.3E-05
1.7E-05
Chromium (VI)
9
1.6E-07
7.1E-07
7.5E-07
9.8E-06
1.5E-05
2.1E-05
Chromium (VI)
10
1.4E-07
6.2E-07
4.9E-07
9.7E-06
1.4E-05
1.9E-05
Chromium (VI)
11
2.3E-07
1.3E-06
1.2E-06
1.3E-05
2.0E-05
2.7E-05
Chromium (VI)
13
8.7E-08
3.9E-07
2.6E-07
8.9E-06
1.4E-05
1.8E-05
Chromium (VI)
14
2.2E-07
1.0E-06
7.7E-07
1.9E-05
2.8E-05
3.6E-05
Chromium (VI)
15
2.5E-07
1.2E-06
6.8E-07
2.0E-05
3.0E-05
3.9E-05
Chromium (VI)
16
3.2E-07
1.7E-06
2.0E-06
1.3E-05
1.7E-05
2.0E-05
Nickel
1
2.4E-05
2.3E-04
7.6E-05
7.5E-03
1.1E-02
1.4E-02
Nickel
2
1.6E-05
1.6E-04
6.2E-05
4.0E-03
6.1E-03
8.2E-03
Nickel
3
1.8E-05
1.9E-04
5.4E-05
4.3E-03
6.4E-03
8.4E-03
Nickel
4
3.7E-05
5.0E-04
1.0E-04
1.3E-02
1.9E-02
2.4E-02
Nickel
5
1.4E-05
1.7E-04
5.6E-05
4.1E-03
5.8E-03
7.4E-03
Nickel
6
1.2E-05
1.2E-04
5.1E-05
3.2E-03
4.9E-03
6.4E-03
Nickel
7
1.2E-05
1.2E-04
4.1E-05
2.4E-03
3.5E-03
4.6E-03
Nickel
8
1.0E-05
1.0E-04
5.5E-05
2.6E-03
3.7E-03
4.7E-03
Nickel
9
2.4E-05
2.3E-04
1.6E-04
4.7E-03
6.8E-03
8.8E-03
Nickel
10
3.1E-05
3.3E-04
2.0E-04
1.2E-02
1.7E-02
2.2E-02
Nickel
11
7.5E-05
7.4E-04
3.9E-04
4.0E-02
5.7E-02
7.2E-02
Nickel
13
8.5E-06
7.3E-05
7.7E-05
9.9E-04
1.4E-03
1.7E-03
Nickel
14
2.1E-05
1.6E-04
1.9E-04
2.7E-03
4.1E-03
5.5E-03
Nickel
15
1.3E-05
1.3E-04
3.9E-05
2.6E-03
4.0E-03
5.3E-03
Nickel
16
1.1E-04
1.2E-03
6.5E-04
4.2E-02
5.9E-02
7.4E-02
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 47
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
Mercury
1
6.4E-05
2.9E-04
2.7E-04
5.4E-03
7.9E-03
1.0E-02
Mercury
2
5.7E-05
2.5E-04
2.6E-04
4.0E-03
6.3E-03
8.5E-03
Mercury
3
4.9E-05
2.5E-04
1.7E-04
3.5E-03
4.8E-03
6.0E-03
Mercury
4
8.0E-05
4.0E-04
2.7E-04
9.0E-03
1.3E-02
1.6E-02
Mercury
5
4.2E-05
2.0E-04
1.6E-04
4.6E-03
7.1E-03
9.4E-03
Mercury
6
5.1E-05
2.3E-04
2.2E-04
5.2E-03
7.2E-03
9.0E-03
Mercury
7
4.5E-05
2.0E-04
1.4E-04
5.4E-03
8.4E-03
1.1E-02
Mercury
8
3.4E-05
1.5E-04
1.6E-04
2.8E-03
4.2E-03
5.6E-03
Mercury
9
6.6E-05
2.4E-04
3.5E-04
3.5E-03
5.0E-03
6.4E-03
Mercury
10
7.3E-05
3.7E-04
4.1E-04
8.6E-03
1.2E-02
1.6E-02
Mercury
11
1.5E-04
6.4E-04
8.3E-04
2.8E-02
4.0E-02
5.1E-02
Mercury
13
3.0E-05
1.2E-04
1.9E-04
1.9E-03
3.1E-03
4.4E-03
Mercury
14
7.3E-05
3.1E-04
4.8E-04
4.1E-03
6.3E-03
8.5E-03
Mercury
15
6.8E-05
3.5E-04
2.6E-04
4.9E-03
7.5E-03
1.0E-02
Mercury
16
2.2E-04
1.1E-03
1.1E-03
3.0E-02
4.2E-02
5.3E-02
Ammonia
1
1.2E-02
8.5E-02
4.3E-02
2.8E+00
4.0E+00
5.1E+00
Ammonia
2
8.0E-03
6.3E-02
3.4E-02
1.5E+00
2.2E+00
2.9E+00
Ammonia
3
8.9E-03
7.8E-02
3.2E-02
1.6E+00
2.3E+00
3.0E+00
Ammonia
4
1.8E-02
1.9E-01
6.0E-02
4.3E+00
6.1E+00
7.7E+00
Ammonia
5
7.0E-03
6.9E-02
3.1E-02
1.4E+00
1.9E+00
2.4E+00
Ammonia
6
6.1E-03
4.8E-02
2.9E-02
1.2E+00
1.8E+00
2.4E+00
Ammonia
7
6.9E-03
4.6E-02
2.5E-02
9.5E-01
1.4E+00
1.8E+00
Ammonia
8
5.8E-03
4.6E-02
3.0E-02
9.6E-01
1.4E+00
1.7E+00
Ammonia
9
1.3E-02
9.2E-02
8.4E-02
1.8E+00
2.6E+00
3.3E+00
Ammonia
10
1.6E-02
1.4E-01
9.5E-02
4.4E+00
6.4E+00
8.1E+00
Ammonia
11
3.8E-02
3.0E-01
2.0E-01
1.4E+01
2.0E+01
2.6E+01
Ammonia
13
4.3E-03
2.7E-02
3.8E-02
3.7E-01
5.1E-01
6.2E-01
Ammonia
14
1.0E-02
7.0E-02
9.8E-02
9.8E-01
1.5E+00
2.0E+00
Ammonia
15
6.9E-03
5.4E-02
2.3E-02
1.1E+00
1.6E+00
2.1E+00
Ammonia
16
6.1E-02
4.8E-01
3.6E-01
1.6E+01
2.2E+01
2.7E+01
BaP Equivalents
1
1.7E-06
1.4E-05
5.1E-06
1.7E-04
2.5E-04
3.2E-04
BaP Equivalents
2
1.1E-06
8.6E-06
3.8E-06
1.3E-04
2.0E-04
2.7E-04
BaP Equivalents
3
1.0E-06
8.1E-06
3.3E-06
1.3E-04
1.9E-04
2.4E-04
BaP Equivalents
4
1.8E-06
1.6E-05
6.8E-06
3.4E-04
5.0E-04
6.5E-04
BaP Equivalents
5
8.2E-07
8.3E-06
2.6E-06
1.1E-04
1.6E-04
2.0E-04
BaP Equivalents
6
7.5E-07
6.3E-06
2.6E-06
1.1E-04
1.6E-04
2.1E-04
BaP Equivalents
7
6.3E-07
4.8E-06
2.2E-06
1.1E-04
1.5E-04
1.9E-04
BaP Equivalents
8
5.2E-07
4.0E-06
2.5E-06
7.6E-05
1.1E-04
1.4E-04
BaP Equivalents
9
1.2E-06
8.1E-06
7.5E-06
1.4E-04
1.9E-04
2.4E-04
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 48
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
BaP Equivalents
10
1.4E-06
1.1E-05
7.7E-06
2.2E-04
3.2E-04
4.1E-04
BaP Equivalents
11
2.8E-06
2.0E-05
1.6E-05
4.0E-04
5.8E-04
7.4E-04
BaP Equivalents
13
4.3E-07
2.5E-06
2.9E-06
4.1E-05
5.5E-05
6.8E-05
BaP Equivalents
14
1.0E-06
6.5E-06
7.5E-06
8.6E-05
1.2E-04
1.5E-04
BaP Equivalents
15
8.3E-07
7.9E-06
3.3E-06
9.9E-05
1.5E-04
1.9E-04
BaP Equivalents
16
5.0E-06
3.3E-05
3.4E-05
7.4E-04
1.0E-03
1.3E-03
Acetone
1
5.8E-02
5.6E-01
4.8E-01
5.5E+00
8.1E+00
1.0E+01
Acetone
2
3.9E-02
4.0E-01
3.1E-01
6.5E+00
9.7E+00
1.3E+01
Acetone
3
3.9E-02
3.4E-01
2.9E-01
5.6E+00
8.3E+00
1.1E+01
Acetone
4
7.2E-02
7.0E-01
5.9E-01
7.1E+00
1.0E+01
1.3E+01
Acetone
5
3.3E-02
3.2E-01
2.1E-01
7.5E+00
1.1E+01
1.4E+01
Acetone
6
2.9E-02
3.2E-01
2.6E-01
5.4E+00
7.9E+00
1.0E+01
Acetone
7
2.7E-02
2.6E-01
1.7E-01
3.7E+00
5.2E+00
6.5E+00
Acetone
8
2.1E-02
1.8E-01
1.6E-01
3.1E+00
4.5E+00
5.7E+00
Acetone
9
4.7E-02
3.1E-01
4.0E-01
4.9E+00
6.8E+00
8.4E+00
Acetone
10
5.2E-02
3.9E-01
4.0E-01
9.4E+00
1.3E+01
1.7E+01
Acetone
11
1.1E-01
7.3E-01
8.2E-01
1.2E+01
1.7E+01
2.2E+01
Acetone
13
1.7E-02
1.2E-01
2.0E-01
1.3E+00
2.0E+00
2.6E+00
Acetone
14
3.9E-02
2.8E-01
4.5E-01
3.8E+00
5.3E+00
6.7E+00
Acetone
15
3.5E-02
4.5E-01
2.6E-01
7.8E+00
1.1E+01
1.5E+01
Acetone
16
1.9E-01
1.1E+00
1.5E+00
1.8E+01
2.5E+01
3.0E+01
Acetaldehyde
1
1.0E-02
9.4E-02
1.1E-01
1.1E+00
1.6E+00
2.1E+00
Acetaldehyde
2
8.2E-03
8.5E-02
7.0E-02
1.2E+00
1.7E+00
2.2E+00
Acetaldehyde
3
7.0E-03
6.5E-02
6.7E-02
1.1E+00
1.6E+00
2.0E+00
Acetaldehyde
4
1.3E-02
1.3E-01
1.4E-01
1.1E+00
1.7E+00
2.1E+00
Acetaldehyde
5
5.7E-03
6.3E-02
5.0E-02
1.1E+00
1.6E+00
2.0E+00
Acetaldehyde
6
6.1E-03
6.5E-02
6.4E-02
1.2E+00
1.8E+00
2.3E+00
Acetaldehyde
7
5.4E-03
5.9E-02
4.3E-02
7.4E-01
1.1E+00
1.4E+00
Acetaldehyde
8
4.5E-03
3.9E-02
4.4E-02
6.7E-01
9.6E-01
1.2E+00
Acetaldehyde
9
9.4E-03
6.8E-02
9.7E-02
9.6E-01
1.3E+00
1.6E+00
Acetaldehyde
10
9.9E-03
8.3E-02
9.6E-02
1.9E+00
2.7E+00
3.4E+00
Acetaldehyde
11
2.1E-02
1.6E-01
1.9E-01
2.6E+00
3.7E+00
4.6E+00
Acetaldehyde
13
3.6E-03
2.8E-02
5.0E-02
3.8E-01
5.6E-01
7.3E-01
Acetaldehyde
14
8.5E-03
6.6E-02
1.1E-01
8.8E-01
1.2E+00
1.6E+00
Acetaldehyde
15
7.9E-03
1.0E-01
7.0E-02
1.7E+00
2.5E+00
3.2E+00
Acetaldehyde
16
3.7E-02
2.4E-01
3.7E-01
4.3E+00
5.9E+00
7.3E+00
Formaldehyde
1
3.4E-03
4.9E-02
2.9E-02
7.1E-01
1.1E+00
1.4E+00
Formaldehyde
2
4.4E-03
4.2E-02
2.1E-02
9.5E-01
1.4E+00
1.8E+00
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 49
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
Formaldehyde
3
2.4E-03
3.3E-02
1.3E-02
9.0E-01
1.3E+00
1.7E+00
Formaldehyde
4
3.3E-03
4.9E-02
2.6E-02
9.5E-01
1.4E+00
1.8E+00
Formaldehyde
5
2.2E-03
3.5E-02
1.0E-02
8.8E-01
1.3E+00
1.7E+00
Formaldehyde
6
3.6E-03
3.7E-02
1.9E-02
9.8E-01
1.5E+00
1.9E+00
Formaldehyde
7
2.5E-03
4.3E-02
1.7E-02
6.4E-01
9.5E-01
1.2E+00
Formaldehyde
8
2.3E-03
3.3E-02
2.4E-02
5.8E-01
8.6E-01
1.1E+00
Formaldehyde
9
3.7E-03
4.3E-02
5.5E-02
5.8E-01
9.1E-01
1.2E+00
Formaldehyde
10
3.3E-03
3.6E-02
3.1E-02
7.1E-01
1.1E+00
1.6E+00
Formaldehyde
11
5.6E-03
5.5E-02
6.2E-02
7.0E-01
1.2E+00
1.6E+00
Formaldehyde
13
2.0E-03
2.1E-02
1.6E-02
4.5E-01
7.1E-01
9.7E-01
Formaldehyde
14
4.7E-03
4.9E-02
4.3E-02
6.8E-01
1.0E+00
1.3E+00
Formaldehyde
15
5.5E-03
7.0E-02
2.6E-02
1.2E+00
1.8E+00
2.4E+00
Formaldehyde
16
8.3E-03
1.1E-01
1.3E-01
7.3E-01
9.6E-01
1.2E+00
2-Butanone
1
6.6E-03
5.5E-02
4.8E-02
6.9E-01
1.0E+00
1.3E+00
2-Butanone
2
4.1E-03
3.8E-02
2.9E-02
7.6E-01
1.1E+00
1.5E+00
2-Butanone
3
4.0E-03
3.7E-02
2.8E-02
6.6E-01
9.8E-01
1.3E+00
2-Butanone
4
7.7E-03
7.2E-02
6.5E-02
8.6E-01
1.2E+00
1.6E+00
2-Butanone
5
3.4E-03
3.5E-02
2.2E-02
8.4E-01
1.2E+00
1.5E+00
2-Butanone
6
2.9E-03
2.8E-02
2.6E-02
5.4E-01
8.1E-01
1.1E+00
2-Butanone
7
2.8E-03
2.9E-02
1.8E-02
4.3E-01
6.4E-01
8.3E-01
2-Butanone
8
2.3E-03
2.0E-02
1.8E-02
3.2E-01
4.7E-01
6.1E-01
2-Butanone
9
5.1E-03
3.1E-02
4.3E-02
4.5E-01
6.2E-01
7.8E-01
2-Butanone
10
5.6E-03
4.2E-02
4.3E-02
7.9E-01
1.1E+00
1.4E+00
2-Butanone
11
1.2E-02
7.1E-02
8.8E-02
1.1E+00
1.5E+00
1.9E+00
2-Butanone
13
1.8E-03
1.1E-02
2.1E-02
1.5E-01
2.2E-01
2.9E-01
2-Butanone
14
4.3E-03
2.7E-02
4.5E-02
3.2E-01
4.6E-01
6.0E-01
2-Butanone
15
3.3E-03
4.3E-02
2.6E-02
7.5E-01
1.1E+00
1.5E+00
2-Butanone
16
2.2E-02
1.2E-01
1.6E-01
2.2E+00
3.1E+00
3.8E+00
Benzene
1
8.5E-04
1.6E-02
1.0E-02
3.0E-01
4.4E-01
5.8E-01
Benzene
2
1.0E-03
1.4E-02
7.2E-03
3.4E-01
5.2E-01
6.8E-01
Benzene
3
6.0E-04
1.1E-02
4.6E-03
3.4E-01
5.1E-01
6.6E-01
Benzene
4
6.9E-04
1.6E-02
8.5E-03
4.1E-01
6.1E-01
8.0E-01
Benzene
5
4.8E-04
9.3E-03
3.0E-03
4.3E-01
6.1E-01
7.8E-01
Benzene
6
9.0E-04
1.4E-02
7.1E-03
2.8E-01
4.1E-01
5.4E-01
Benzene
7
4.3E-04
1.4E-02
4.1E-03
2.0E-01
2.9E-01
3.8E-01
Benzene
8
4.1E-04
8.4E-03
5.0E-03
1.9E-01
2.8E-01
3.6E-01
Benzene
9
6.9E-04
1.2E-02
1.1E-02
1.8E-01
2.7E-01
3.4E-01
Benzene
10
6.2E-04
8.6E-03
8.8E-03
2.0E-01
2.9E-01
3.8E-01
Benzene
11
1.0E-03
1.3E-02
1.9E-02
2.3E-01
3.4E-01
4.4E-01
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 50
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
Benzene
13
4.8E-04
5.7E-03
5.9E-03
8.5E-02
1.3E-01
1.7E-01
Benzene
14
1.1E-03
1.1E-02
1.4E-02
2.8E-01
4.1E-01
5.3E-01
Benzene
15
1.5E-03
2.0E-02
7.4E-03
4.9E-01
7.2E-01
9.4E-01
Benzene
16
1.5E-03
2.7E-02
3.2E-02
2.7E-01
4.0E-01
5.2E-01
Toluene
1
5.8E-03
4.2E-02
2.8E-02
4.4E-01
6.7E-01
9.0E-01
Toluene
2
4.8E-03
2.9E-02
2.1E-02
4.4E-01
6.5E-01
8.6E-01
Toluene
3
3.8E-03
2.3E-02
1.7E-02
4.4E-01
6.5E-01
8.5E-01
Toluene
4
5.2E-03
3.7E-02
2.4E-02
5.6E-01
8.4E-01
1.1E+00
Toluene
5
2.8E-03
2.0E-02
1.1E-02
5.7E-01
8.2E-01
1.0E+00
Toluene
6
3.6E-03
2.5E-02
1.8E-02
4.0E-01
6.0E-01
7.8E-01
Toluene
7
1.8E-03
1.8E-02
8.1E-03
2.7E-01
3.9E-01
5.1E-01
Toluene
8
1.6E-03
1.2E-02
9.2E-03
2.4E-01
3.4E-01
4.4E-01
Toluene
9
3.7E-03
2.0E-02
2.2E-02
3.5E-01
5.0E-01
6.3E-01
Toluene
10
4.2E-03
2.4E-02
2.5E-02
8.5E-01
1.2E+00
1.6E+00
Toluene
11
7.9E-03
3.9E-02
4.1E-02
1.2E+00
1.8E+00
2.3E+00
Toluene
13
1.7E-03
9.5E-03
1.4E-02
1.0E-01
1.4E-01
1.8E-01
Toluene
14
4.1E-03
2.1E-02
3.1E-02
3.8E-01
5.4E-01
6.9E-01
Toluene
15
4.3E-03
3.6E-02
1.7E-02
6.3E-01
9.3E-01
1.2E+00
Toluene
16
1.3E-02
6.5E-02
7.3E-02
1.4E+00
1.9E+00
2.4E+00
Xylenes
1
1.3E-03
6.8E-03
3.0E-03
9.8E-02
1.5E-01
2.0E-01
Xylenes
2
1.1E-03
6.0E-03
2.8E-03
7.3E-02
1.1E-01
1.5E-01
Xylenes
3
8.2E-04
3.9E-03
2.3E-03
9.6E-02
1.4E-01
1.9E-01
Xylenes
4
1.1E-03
5.6E-03
2.8E-03
1.2E-01
1.8E-01
2.4E-01
Xylenes
5
6.1E-04
3.3E-03
1.3E-03
8.0E-02
1.2E-01
1.5E-01
Xylenes
6
8.0E-04
4.5E-03
2.4E-03
7.6E-02
1.1E-01
1.5E-01
Xylenes
7
3.8E-04
2.2E-03
1.1E-03
3.3E-02
4.5E-02
5.6E-02
Xylenes
8
3.4E-04
1.9E-03
1.3E-03
2.9E-02
4.2E-02
5.5E-02
Xylenes
9
8.0E-04
3.7E-03
3.5E-03
7.6E-02
1.1E-01
1.4E-01
Xylenes
10
8.8E-04
3.8E-03
3.6E-03
1.8E-01
2.6E-01
3.4E-01
Xylenes
11
1.6E-03
6.7E-03
6.5E-03
2.6E-01
3.9E-01
5.1E-01
Xylenes
13
3.8E-04
1.6E-03
2.2E-03
2.1E-02
2.8E-02
3.4E-02
Xylenes
14
9.0E-04
3.7E-03
5.2E-03
8.4E-02
1.2E-01
1.5E-01
Xylenes
15
9.6E-04
5.8E-03
2.2E-03
8.3E-02
1.2E-01
1.6E-01
Xylenes
16
2.7E-03
1.1E-02
1.1E-02
3.1E-01
4.4E-01
5.6E-01
Acrolein
1
2.8E-04
1.7E-03
4.7E-04
3.2E-02
5.2E-02
7.1E-02
Acrolein
2
3.8E-04
1.7E-03
5.5E-04
4.5E-02
6.9E-02
9.1E-02
Acrolein
3
2.0E-04
1.2E-03
2.5E-04
3.3E-02
5.1E-02
6.9E-02
Acrolein
4
2.6E-04
1.7E-03
4.3E-04
4.2E-02
6.5E-02
8.7E-02
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 51
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
Acrolein
5
1.9E-04
1.3E-03
2.2E-04
3.7E-02
5.6E-02
7.6E-02
Acrolein
6
3.1E-04
1.5E-03
5.2E-04
4.7E-02
7.1E-02
9.4E-02
Acrolein
7
2.4E-04
1.6E-03
5.9E-04
3.2E-02
4.8E-02
6.4E-02
Acrolein
8
1.9E-04
1.3E-03
8.8E-04
2.3E-02
3.4E-02
4.5E-02
Acrolein
9
3.0E-04
1.7E-03
1.8E-03
2.6E-02
4.1E-02
5.6E-02
Acrolein
10
2.4E-04
1.4E-03
8.7E-04
2.9E-02
4.6E-02
6.2E-02
Acrolein
11
4.0E-04
2.0E-03
1.8E-03
3.0E-02
4.8E-02
6.6E-02
Acrolein
13
1.5E-04
8.2E-04
6.0E-04
1.9E-02
2.9E-02
3.8E-02
Acrolein
14
3.6E-04
2.1E-03
1.6E-03
3.6E-02
5.4E-02
7.2E-02
Acrolein
15
4.9E-04
2.8E-03
8.6E-04
6.2E-02
9.6E-02
1.3E-01
Acrolein
16
6.3E-04
4.2E-03
3.8E-03
3.4E-02
5.4E-02
7.3E-02
Ethylbenzene
1
2.6E-05
1.9E-04
1.4E-04
4.1E-03
6.0E-03
7.7E-03
Ethylbenzene
2
2.5E-05
1.8E-04
1.3E-04
2.3E-03
3.5E-03
4.7E-03
Ethylbenzene
3
1.9E-05
1.7E-04
1.0E-04
2.3E-03
3.5E-03
4.5E-03
Ethylbenzene
4
3.0E-05
2.9E-04
1.4E-04
7.2E-03
1.0E-02
1.3E-02
Ethylbenzene
5
1.5E-05
1.3E-04
9.2E-05
2.2E-03
3.1E-03
4.0E-03
Ethylbenzene
6
2.0E-05
1.4E-04
1.1E-04
2.4E-03
3.5E-03
4.6E-03
Ethylbenzene
7
1.4E-05
1.1E-04
8.6E-05
1.3E-03
1.9E-03
2.5E-03
Ethylbenzene
8
1.2E-05
9.9E-05
8.7E-05
1.4E-03
2.0E-03
2.5E-03
Ethylbenzene
9
2.4E-05
1.6E-04
2.0E-04
2.6E-03
3.8E-03
4.9E-03
Ethylbenzene
10
2.6E-05
2.3E-04
2.1E-04
6.4E-03
9.3E-03
1.2E-02
Ethylbenzene
11
5.5E-05
4.9E-04
3.8E-04
2.1E-02
3.1E-02
3.9E-02
Ethylbenzene
13
1.2E-05
6.9E-05
1.2E-04
9.2E-04
1.4E-03
1.7E-03
Ethylbenzene
14
2.7E-05
1.6E-04
2.7E-04
2.2E-03
3.2E-03
4.2E-03
Ethylbenzene
15
3.0E-05
2.0E-04
1.4E-04
2.9E-03
4.3E-03
5.7E-03
Ethylbenzene
16
8.2E-05
7.2E-04
6.8E-04
2.2E-02
3.2E-02
4.0E-02
Methylene Chloride
1
6.1E-03
5.2E-02
2.8E-02
7.2E-01
1.1E+00
1.5E+00
Methylene Chloride
2
5.2E-03
4.6E-02
2.7E-02
5.3E-01
8.1E-01
1.1E+00
Methylene Chloride
3
4.0E-03
2.9E-02
2.1E-02
7.0E-01
1.1E+00
1.4E+00
Methylene Chloride
4
5.5E-03
4.2E-02
2.7E-02
8.9E-01
1.3E+00
1.8E+00
Methylene Chloride
5
3.1E-03
2.5E-02
1.3E-02
5.8E-01
8.6E-01
1.1E+00
Methylene Chloride
6
4.0E-03
3.3E-02
2.2E-02
5.6E-01
8.4E-01
1.1E+00
Methylene Chloride
7
2.2E-03
1.8E-02
1.1E-02
2.4E-01
3.3E-01
4.1E-01
Methylene Chloride
8
1.8E-03
1.5E-02
1.2E-02
2.2E-01
3.2E-01
4.2E-01
Methylene Chloride
9
4.1E-03
2.7E-02
3.1E-02
5.8E-01
8.2E-01
1.0E+00
Methylene Chloride
10
4.5E-03
3.1E-02
3.3E-02
1.4E+00
2.0E+00
2.6E+00
Methylene Chloride
11
8.3E-03
5.7E-02
5.7E-02
2.0E+00
3.0E+00
3.9E+00
Methylene Chloride
13
2.0E-03
1.2E-02
1.9E-02
1.6E-01
2.1E-01
2.6E-01
Methylene Chloride
14
4.7E-03
3.1E-02
4.7E-02
5.8E-01
8.4E-01
1.1E+00
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 52
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
Methylene Chloride
15
5.0E-03
4.2E-02
2.6E-02
6.1E-01
9.1E-01
1.2E+00
Methylene Chloride
16
1.3E-02
9.0E-02
9.6E-02
2.3E+00
3.2E+00
4.1E+00
Styrene
1
1.5E-04
7.2E-04
4.6E-04
1.8E-02
2.7E-02
3.5E-02
Styrene
2
1.1E-04
5.4E-04
3.1E-04
2.0E-02
3.0E-02
4.0E-02
Styrene
3
1.1E-04
5.1E-04
2.7E-04
1.9E-02
2.8E-02
3.7E-02
Styrene
4
1.6E-04
9.1E-04
5.0E-04
2.4E-02
3.7E-02
4.8E-02
Styrene
5
1.1E-04
4.3E-04
1.9E-04
2.5E-02
3.7E-02
4.7E-02
Styrene
6
9.5E-05
5.1E-04
3.0E-04
1.4E-02
2.2E-02
2.8E-02
Styrene
7
9.6E-05
6.7E-04
2.1E-04
1.2E-02
1.8E-02
2.3E-02
Styrene
8
6.5E-05
4.2E-04
2.2E-04
9.0E-03
1.3E-02
1.7E-02
Styrene
9
1.1E-04
5.6E-04
5.0E-04
1.0E-02
1.5E-02
1.9E-02
Styrene
10
8.3E-05
3.8E-04
4.2E-04
1.3E-02
1.9E-02
2.4E-02
Styrene
11
1.4E-04
7.3E-04
8.2E-04
1.4E-02
2.1E-02
2.8E-02
Styrene
13
4.0E-05
2.0E-04
2.3E-04
3.3E-03
5.0E-03
6.7E-03
Styrene
14
8.9E-05
4.0E-04
5.2E-04
6.8E-03
1.0E-02
1.3E-02
Styrene
15
1.5E-04
8.0E-04
3.0E-04
2.3E-02
3.4E-02
4.4E-02
Styrene
16
2.4E-04
1.3E-03
1.4E-03
1.8E-02
2.7E-02
3.5E-02
1-2-4 Trimethylbenzene
1
5.3E-05
5.1E-04
1.3E-04
1.7E-02
2.5E-02
3.2E-02
1-2-4 Trimethylbenzene
2
3.6E-05
3.8E-04
1.0E-04
9.0E-03
1.4E-02
1.8E-02
1-2-4 Trimethylbenzene
3
4.0E-05
4.4E-04
1.0E-04
9.7E-03
1.4E-02
1.9E-02
1-2-4 Trimethylbenzene
4
8.0E-05
1.1E-03
1.6E-04
3.0E-02
4.2E-02
5.4E-02
1-2-4 Trimethylbenzene
5
3.0E-05
3.8E-04
9.5E-05
9.1E-03
1.3E-02
1.6E-02
1-2-4 Trimethylbenzene
6
2.6E-05
2.8E-04
7.7E-05
7.2E-03
1.1E-02
1.4E-02
1-2-4 Trimethylbenzene
7
2.4E-05
2.5E-04
7.5E-05
5.3E-03
7.9E-03
1.0E-02
1-2-4 Trimethylbenzene
8
2.1E-05
2.2E-04
1.0E-04
5.7E-03
8.2E-03
1.0E-02
1-2-4 Trimethylbenzene
9
5.2E-05
4.8E-04
3.3E-04
1.1E-02
1.5E-02
2.0E-02
1-2-4 Trimethylbenzene
10
6.8E-05
7.3E-04
4.0E-04
2.6E-02
3.8E-02
4.9E-02
1-2-4 Trimethylbenzene
11
1.6E-04
1.6E-03
8.0E-04
8.8E-02
1.3E-01
1.6E-01
1-2-4 Trimethylbenzene
13
1.8E-05
1.7E-04
1.4E-04
2.2E-03
3.1E-03
3.9E-03
1-2-4 Trimethylbenzene
14
4.4E-05
3.4E-04
3.6E-04
6.0E-03
9.2E-03
1.2E-02
1-2-4 Trimethylbenzene
15
2.9E-05
3.0E-04
1.2E-04
5.0E-03
7.8E-03
1.0E-02
1-2-4 Trimethylbenzene
16
2.4E-04
2.7E-03
1.4E-03
9.3E-02
1.3E-01
1.7E-01
1-3-5 Trimethylbenzene
1
1.8E-05
1.6E-04
5.6E-05
5.2E-03
7.7E-03
9.9E-03
1-3-5 Trimethylbenzene
2
1.3E-05
1.4E-04
5.0E-05
2.8E-03
4.3E-03
5.7E-03
1-3-5 Trimethylbenzene
3
1.3E-05
1.4E-04
4.6E-05
3.0E-03
4.5E-03
5.8E-03
1-3-5 Trimethylbenzene
4
2.6E-05
3.5E-04
7.8E-05
9.2E-03
1.3E-02
1.7E-02
1-3-5 Trimethylbenzene
5
1.0E-05
1.2E-04
4.6E-05
2.8E-03
4.0E-03
5.1E-03
1-3-5 Trimethylbenzene
6
9.6E-06
8.9E-05
4.2E-05
2.2E-03
3.4E-03
4.5E-03
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 53
PHASE 3A. FINAL REPORT
Chemical Species
Site
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
1-3-5 Trimethylbenzene
7
8.8E-06
8.6E-05
4.0E-05
1.7E-03
2.5E-03
3.2E-03
1-3-5 Trimethylbenzene
8
7.6E-06
7.8E-05
4.7E-05
1.8E-03
2.5E-03
3.2E-03
1-3-5 Trimethylbenzene
9
1.8E-05
1.7E-04
1.3E-04
3.3E-03
4.7E-03
6.1E-03
1-3-5 Trimethylbenzene
10
2.2E-05
2.3E-04
1.4E-04
8.2E-03
1.2E-02
1.5E-02
1-3-5 Trimethylbenzene
11
5.3E-05
5.4E-04
2.8E-04
2.7E-02
3.9E-02
5.0E-02
1-3-5 Trimethylbenzene
13
6.6E-06
5.2E-05
5.8E-05
6.8E-04
9.6E-04
1.2E-03
1-3-5 Trimethylbenzene
14
1.5E-05
1.2E-04
1.4E-04
1.9E-03
2.9E-03
3.8E-03
1-3-5 Trimethylbenzene
15
1.2E-05
1.1E-04
6.5E-05
1.6E-03
2.4E-03
3.3E-03
1-3-5 Trimethylbenzene
16
7.7E-05
8.3E-04
4.8E-04
2.9E-02
4.1E-02
5.1E-02
Vinyl chloride
1
1.7E-06
1.1E-05
2.9E-06
2.0E-04
3.3E-04
4.5E-04
Vinyl chloride
2
2.4E-06
1.1E-05
3.5E-06
2.8E-04
4.3E-04
5.7E-04
Vinyl chloride
3
1.2E-06
7.4E-06
1.6E-06
2.1E-04
3.2E-04
4.3E-04
Vinyl chloride
4
1.6E-06
1.0E-05
2.7E-06
2.6E-04
4.1E-04
5.4E-04
Vinyl chloride
5
1.2E-06
7.8E-06
1.4E-06
2.3E-04
3.5E-04
4.7E-04
Vinyl chloride
6
1.9E-06
9.1E-06
3.2E-06
2.9E-04
4.4E-04
5.9E-04
Vinyl chloride
7
1.5E-06
1.0E-05
3.7E-06
2.0E-04
3.0E-04
4.0E-04
Vinyl chloride
8
1.2E-06
7.8E-06
5.5E-06
1.4E-04
2.2E-04
2.8E-04
Vinyl chloride
9
1.9E-06
1.1E-05
1.1E-05
1.6E-04
2.6E-04
3.5E-04
Vinyl chloride
10
1.5E-06
8.4E-06
5.4E-06
1.8E-04
2.9E-04
3.9E-04
Vinyl chloride
11
2.5E-06
1.2E-05
1.1E-05
1.9E-04
3.0E-04
4.1E-04
Vinyl chloride
13
9.6E-07
5.1E-06
3.7E-06
1.2E-04
1.8E-04
2.4E-04
Vinyl chloride
14
2.3E-06
1.3E-05
1.0E-05
2.2E-04
3.4E-04
4.5E-04
Vinyl chloride
15
3.1E-06
1.7E-05
5.4E-06
3.9E-04
6.0E-04
8.1E-04
Vinyl chloride
16
3.9E-06
2.7E-05
2.4E-05
2.1E-04
3.3E-04
4.6E-04
Shaded values limited by available ozone
NO2
1
2.6E-01
2.9E+00
1.4E+00
5.0E+01
5.4E+01
5.4E+01
NO2
2
2.9E-01
3.4E+00
2.0E+00
5.1E+01
5.4E+01
5.4E+01
NO2
3
2.0E-01
2.4E+00
5.8E-01
5.4E+01
5.4E+01
5.4E+01
NO2
4
2.4E-01
2.9E+00
8.7E-01
5.3E+01
5.4E+01
5.4E+01
NO2
5
1.9E-01
2.3E+00
4.5E-01
5.0E+01
5.0E+01
5.4E+01
NO2
6
2.8E-01
3.1E+00
2.1E+00
5.1E+01
5.3E+01
5.4E+01
NO2
7
2.4E-01
3.3E+00
1.3E+00
3.8E+01
3.9E+01
4.7E+01
NO2
8
1.7E-01
2.5E+00
1.5E+00
3.6E+01
3.8E+01
4.3E+01
NO2
9
2.7E-01
3.0E+00
3.0E+00
4.1E+01
4.8E+01
5.1E+01
NO2
10
2.3E-01
2.4E+00
2.1E+00
4.2E+01
5.1E+01
5.4E+01
NO2
11
3.8E-01
4.8E+00
4.9E+00
4.5E+01
5.4E+01
5.4E+01
NO2
13
1.4E-01
1.5E+00
1.2E+00
3.4E+01
4.7E+01
4.8E+01
NO2
14
3.7E-01
4.0E+00
3.5E+00
5.4E+01
5.4E+01
5.4E+01
NO2
15
4.3E-01
5.0E+00
3.3E+00
5.4E+01
5.4E+01
5.4E+01
NO2
16
5.4E-01
6.9E+00
8.3E+00
4.4E+01
5.2E+01
5.4E+01
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 54
PHASE 3A. FINAL REPORT
4.5. Concentration Statistics (sorted by Receptor Site)
Table 9. Selected modelled concentration statistics sorted by receptor site for each of the 28
chemical species at each of the 15 receptor sites for the Current Emissions Scenario of 6,600
tonnes per day. The annual averages are for the average emission rates, whereas all other
statistics are for peak emission rates. The shaded NO2 cells indicate values that are limited by
the available ozone, see Section 3.5.
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
1
NOx
2.6E-01
2.9E+00
1.4E+00
5.5E+01
8.4E+01
1.1E+02
1
CO
2.7E-01
3.4E+00
1.9E+00
5.6E+01
8.1E+01
1.0E+02
1
SO2
1.8E-02
3.7E-01
1.7E-01
6.5E+00
1.0E+01
1.4E+01
1
Dust
1.3E-02
2.5E-01
9.6E-02
4.9E+00
7.7E+00
1.0E+01
1
Arsenic
2.2E-05
1.4E-04
1.0E-04
2.5E-03
4.0E-03
5.5E-03
1
Selenium
2.3E-05
1.6E-04
1.2E-04
2.6E-03
3.9E-03
5.0E-03
1
Manganese
7.3E-04
7.3E-03
1.6E-03
2.4E-01
3.5E-01
4.6E-01
1
Cadmium
1.6E-09
7.4E-09
1.2E-09
1.7E-07
2.3E-07
2.8E-07
1
Chromium (VI)
1.5E-07
7.3E-07
2.6E-07
1.2E-05
1.9E-05
2.6E-05
1
Nickel
2.4E-05
2.3E-04
7.6E-05
7.5E-03
1.1E-02
1.4E-02
1
Mercury
6.4E-05
2.9E-04
2.7E-04
5.4E-03
7.9E-03
1.0E-02
1
Ammonia
1.2E-02
8.5E-02
4.3E-02
2.8E+00
4.0E+00
5.1E+00
1
BaP Equivalents
1.7E-06
1.4E-05
5.1E-06
1.7E-04
2.5E-04
3.2E-04
1
Acetone
5.8E-02
5.6E-01
4.8E-01
5.5E+00
8.1E+00
1.0E+01
1
Acetaldehyde
1.0E-02
9.4E-02
1.1E-01
1.1E+00
1.6E+00
2.1E+00
1
Formaldehyde
3.4E-03
4.9E-02
2.9E-02
7.1E-01
1.1E+00
1.4E+00
1
2-Butanone
6.6E-03
5.5E-02
4.8E-02
6.9E-01
1.0E+00
1.3E+00
1
Benzene
8.5E-04
1.6E-02
1.0E-02
3.0E-01
4.4E-01
5.8E-01
1
Toluene
5.8E-03
4.2E-02
2.8E-02
4.4E-01
6.7E-01
9.0E-01
1
Xylenes
1.3E-03
6.8E-03
3.0E-03
9.8E-02
1.5E-01
2.0E-01
1
Acrolein
2.8E-04
1.7E-03
4.7E-04
3.2E-02
5.2E-02
7.1E-02
1
Ethylbenzene
2.6E-05
1.9E-04
1.4E-04
4.1E-03
6.0E-03
7.7E-03
1
Methylene Chloride
6.1E-03
5.2E-02
2.8E-02
7.2E-01
1.1E+00
1.5E+00
1
Styrene
1.5E-04
7.2E-04
4.6E-04
1.8E-02
2.7E-02
3.5E-02
1
1-2-4 Trimethylbenzene
5.3E-05
5.1E-04
1.3E-04
1.7E-02
2.5E-02
3.2E-02
1
1-3-5 Trimethylbenzene
1.8E-05
1.6E-04
5.6E-05
5.2E-03
7.7E-03
9.9E-03
1
Vinyl chloride
1.7E-06
1.1E-05
2.9E-06
2.0E-04
3.3E-04
4.5E-04
1
NO2
2.6E-01
2.9E+00
1.4E+00
5.0E+01
5.4E+01
5.4E+01
2
NOx
2.9E-01
3.4E+00
2.0E+00
6.9E+01
1.0E+02
1.3E+02
2
CO
3.2E-01
4.2E+00
2.4E+00
6.5E+01
9.7E+01
1.3E+02
2
SO2
2.0E-02
4.2E-01
2.3E-01
7.8E+00
1.2E+01
1.5E+01
2
Dust
1.7E-02
2.9E-01
1.2E-01
6.4E+00
1.0E+01
1.3E+01
2
Arsenic
2.3E-05
1.3E-04
1.0E-04
3.6E-03
5.7E-03
7.7E-03
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 55
PHASE 3A. FINAL REPORT
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
2.3E-05
1.5E-04
1.0E-04
2.7E-03
4.0E-03
5.2E-03
Annual
average
2
Selenium
2
Manganese
4.7E-04
4.9E-03
1.3E-03
1.3E-01
2.0E-01
2.6E-01
2
Cadmium
1.8E-09
7.5E-09
1.3E-09
2.4E-07
3.8E-07
5.2E-07
2
Chromium (VI)
1.8E-07
8.0E-07
4.0E-07
1.8E-05
2.6E-05
3.4E-05
2
Nickel
1.6E-05
1.6E-04
6.2E-05
4.0E-03
6.1E-03
8.2E-03
2
Mercury
5.7E-05
2.5E-04
2.6E-04
4.0E-03
6.3E-03
8.5E-03
2
Ammonia
8.0E-03
6.3E-02
3.4E-02
1.5E+00
2.2E+00
2.9E+00
2
BaP Equivalents
1.1E-06
8.6E-06
3.8E-06
1.3E-04
2.0E-04
2.7E-04
2
Acetone
3.9E-02
4.0E-01
3.1E-01
6.5E+00
9.7E+00
1.3E+01
2
Acetaldehyde
8.2E-03
8.5E-02
7.0E-02
1.2E+00
1.7E+00
2.2E+00
2
Formaldehyde
4.4E-03
4.2E-02
2.1E-02
9.5E-01
1.4E+00
1.8E+00
2
2-Butanone
4.1E-03
3.8E-02
2.9E-02
7.6E-01
1.1E+00
1.5E+00
2
Benzene
1.0E-03
1.4E-02
7.2E-03
3.4E-01
5.2E-01
6.8E-01
2
Toluene
4.8E-03
2.9E-02
2.1E-02
4.4E-01
6.5E-01
8.6E-01
2
Xylenes
1.1E-03
6.0E-03
2.8E-03
7.3E-02
1.1E-01
1.5E-01
2
Acrolein
3.8E-04
1.7E-03
5.5E-04
4.5E-02
6.9E-02
9.1E-02
2
Ethylbenzene
2.5E-05
1.8E-04
1.3E-04
2.3E-03
3.5E-03
4.7E-03
2
Methylene Chloride
5.2E-03
4.6E-02
2.7E-02
5.3E-01
8.1E-01
1.1E+00
2
Styrene
1.1E-04
5.4E-04
3.1E-04
2.0E-02
3.0E-02
4.0E-02
2
1-2-4 Trimethylbenzene
3.6E-05
3.8E-04
1.0E-04
9.0E-03
1.4E-02
1.8E-02
2
1-3-5 Trimethylbenzene
1.3E-05
1.4E-04
5.0E-05
2.8E-03
4.3E-03
5.7E-03
2
Vinyl chloride
2.4E-06
1.1E-05
3.5E-06
2.8E-04
4.3E-04
5.7E-04
2
NO2
2.9E-01
3.4E+00
2.0E+00
5.1E+01
5.4E+01
5.4E+01
3
NOx
2.0E-01
2.4E+00
5.8E-01
7.5E+01
1.1E+02
1.4E+02
3
CO
1.9E-01
2.7E+00
8.4E-01
7.7E+01
1.0E+02
1.3E+02
3
SO2
1.3E-02
3.1E-01
7.8E-02
9.8E+00
1.5E+01
1.9E+01
3
Dust
8.9E-03
1.8E-01
5.4E-02
5.5E+00
7.5E+00
9.3E+00
3
Arsenic
1.7E-05
1.1E-04
5.9E-05
2.8E-03
3.9E-03
4.9E-03
3
Selenium
1.6E-05
1.4E-04
8.2E-05
1.7E-03
2.3E-03
2.9E-03
3
Manganese
5.5E-04
6.1E-03
1.2E-03
1.4E-01
2.0E-01
2.7E-01
3
Cadmium
1.3E-09
6.0E-09
6.9E-10
1.7E-07
2.7E-07
3.7E-07
3
Chromium (VI)
1.2E-07
5.8E-07
1.2E-07
1.6E-05
2.1E-05
2.6E-05
3
Nickel
1.8E-05
1.9E-04
5.4E-05
4.3E-03
6.4E-03
8.4E-03
3
Mercury
4.9E-05
2.5E-04
1.7E-04
3.5E-03
4.8E-03
6.0E-03
3
Ammonia
8.9E-03
7.8E-02
3.2E-02
1.6E+00
2.3E+00
3.0E+00
3
BaP Equivalents
1.0E-06
8.1E-06
3.3E-06
1.3E-04
1.9E-04
2.4E-04
3
Acetone
3.9E-02
3.4E-01
2.9E-01
5.6E+00
8.3E+00
1.1E+01
3
Acetaldehyde
7.0E-03
6.5E-02
6.7E-02
1.1E+00
1.6E+00
2.0E+00
3
Formaldehyde
2.4E-03
3.3E-02
1.3E-02
9.0E-01
1.3E+00
1.7E+00
3
2-Butanone
4.0E-03
3.7E-02
2.8E-02
6.6E-01
9.8E-01
1.3E+00
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 56
PHASE 3A. FINAL REPORT
Site Chemical Species
3
Benzene
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
6.0E-04
1.1E-02
4.6E-03
3.4E-01
5.1E-01
6.6E-01
Annual
average
3
Toluene
3.8E-03
2.3E-02
1.7E-02
4.4E-01
6.5E-01
8.5E-01
3
Xylenes
8.2E-04
3.9E-03
2.3E-03
9.6E-02
1.4E-01
1.9E-01
3
Acrolein
2.0E-04
1.2E-03
2.5E-04
3.3E-02
5.1E-02
6.9E-02
3
Ethylbenzene
1.9E-05
1.7E-04
1.0E-04
2.3E-03
3.5E-03
4.5E-03
3
Methylene Chloride
4.0E-03
2.9E-02
2.1E-02
7.0E-01
1.1E+00
1.4E+00
3
Styrene
1.1E-04
5.1E-04
2.7E-04
1.9E-02
2.8E-02
3.7E-02
3
1-2-4 Trimethylbenzene
4.0E-05
4.4E-04
1.0E-04
9.7E-03
1.4E-02
1.9E-02
3
1-3-5 Trimethylbenzene
1.3E-05
1.4E-04
4.6E-05
3.0E-03
4.5E-03
5.8E-03
3
Vinyl chloride
1.2E-06
7.4E-06
1.6E-06
2.1E-04
3.2E-04
4.3E-04
3
NO2
2.0E-01
2.4E+00
5.8E-01
5.4E+01
5.4E+01
5.4E+01
4
NOx
2.5E-01
3.2E+00
8.7E-01
8.4E+01
1.3E+02
1.6E+02
4
CO
2.3E-01
3.3E+00
1.3E+00
5.6E+01
8.3E+01
1.1E+02
4
SO2
1.7E-02
4.0E-01
1.2E-01
1.1E+01
1.6E+01
2.2E+01
4
Dust
1.2E-02
2.5E-01
7.9E-02
5.2E+00
8.6E+00
1.2E+01
4
Arsenic
2.2E-05
1.4E-04
9.8E-05
3.0E-03
4.8E-03
6.6E-03
4
Selenium
2.4E-05
2.0E-04
1.1E-04
4.6E-03
6.5E-03
8.3E-03
4
Manganese
1.1E-03
1.6E-02
2.1E-03
4.2E-01
6.0E-01
7.7E-01
4
Cadmium
1.5E-09
7.2E-09
1.2E-09
2.0E-07
3.0E-07
4.1E-07
4
Chromium (VI)
1.4E-07
7.1E-07
1.7E-07
1.6E-05
2.5E-05
3.3E-05
4
Nickel
3.7E-05
5.0E-04
1.0E-04
1.3E-02
1.9E-02
2.4E-02
4
Mercury
8.0E-05
4.0E-04
2.7E-04
9.0E-03
1.3E-02
1.6E-02
4
Ammonia
1.8E-02
1.9E-01
6.0E-02
4.3E+00
6.1E+00
7.7E+00
4
BaP Equivalents
1.8E-06
1.6E-05
6.8E-06
3.4E-04
5.0E-04
6.5E-04
4
Acetone
7.2E-02
7.0E-01
5.9E-01
7.1E+00
1.0E+01
1.3E+01
4
Acetaldehyde
1.3E-02
1.3E-01
1.4E-01
1.1E+00
1.7E+00
2.1E+00
4
Formaldehyde
3.3E-03
4.9E-02
2.6E-02
9.5E-01
1.4E+00
1.8E+00
4
2-Butanone
7.7E-03
7.2E-02
6.5E-02
8.6E-01
1.2E+00
1.6E+00
4
Benzene
6.9E-04
1.6E-02
8.5E-03
4.1E-01
6.1E-01
8.0E-01
4
Toluene
5.2E-03
3.7E-02
2.4E-02
5.6E-01
8.4E-01
1.1E+00
4
Xylenes
1.1E-03
5.6E-03
2.8E-03
1.2E-01
1.8E-01
2.4E-01
4
Acrolein
2.6E-04
1.7E-03
4.3E-04
4.2E-02
6.5E-02
8.7E-02
4
Ethylbenzene
3.0E-05
2.9E-04
1.4E-04
7.2E-03
1.0E-02
1.3E-02
4
Methylene Chloride
5.5E-03
4.2E-02
2.7E-02
8.9E-01
1.3E+00
1.8E+00
4
Styrene
1.6E-04
9.1E-04
5.0E-04
2.4E-02
3.7E-02
4.8E-02
4
1-2-4 Trimethylbenzene
8.0E-05
1.1E-03
1.6E-04
3.0E-02
4.2E-02
5.4E-02
4
1-3-5 Trimethylbenzene
2.6E-05
3.5E-04
7.8E-05
9.2E-03
1.3E-02
1.7E-02
4
Vinyl chloride
1.6E-06
1.0E-05
2.7E-06
2.6E-04
4.1E-04
5.4E-04
4
NO2
2.4E-01
2.9E+00
8.7E-01
5.3E+01
5.4E+01
5.4E+01
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 57
PHASE 3A. FINAL REPORT
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
5
NOx
1.9E-01
2.5E+00
4.5E-01
9.5E+01
1.4E+02
1.8E+02
5
CO
1.7E-01
2.5E+00
5.7E-01
6.5E+01
9.6E+01
1.2E+02
5
SO2
1.3E-02
3.0E-01
5.8E-02
1.1E+01
1.7E+01
2.2E+01
5
Dust
8.2E-03
1.7E-01
4.2E-02
3.8E+00
5.2E+00
6.3E+00
5
Arsenic
1.6E-05
1.0E-04
4.9E-05
4.0E-03
6.1E-03
8.1E-03
5
Selenium
1.2E-05
9.8E-05
6.8E-05
1.5E-03
2.1E-03
2.6E-03
5
Manganese
4.1E-04
5.4E-03
1.2E-03
1.3E-01
1.9E-01
2.3E-01
5
Cadmium
1.3E-09
5.8E-09
7.4E-10
2.6E-07
4.0E-07
5.3E-07
5
Chromium (VI)
1.1E-07
5.1E-07
1.1E-07
2.1E-05
3.0E-05
3.9E-05
5
Nickel
1.4E-05
1.7E-04
5.6E-05
4.1E-03
5.8E-03
7.4E-03
5
Mercury
4.2E-05
2.0E-04
1.6E-04
4.6E-03
7.1E-03
9.4E-03
5
Ammonia
7.0E-03
6.9E-02
3.1E-02
1.4E+00
1.9E+00
2.4E+00
5
BaP Equivalents
8.2E-07
8.3E-06
2.6E-06
1.1E-04
1.6E-04
2.0E-04
5
Acetone
3.3E-02
3.2E-01
2.1E-01
7.5E+00
1.1E+01
1.4E+01
5
Acetaldehyde
5.7E-03
6.3E-02
5.0E-02
1.1E+00
1.6E+00
2.0E+00
5
Formaldehyde
2.2E-03
3.5E-02
1.0E-02
8.8E-01
1.3E+00
1.7E+00
5
2-Butanone
3.4E-03
3.5E-02
2.2E-02
8.4E-01
1.2E+00
1.5E+00
5
Benzene
4.8E-04
9.3E-03
3.0E-03
4.3E-01
6.1E-01
7.8E-01
5
Toluene
2.8E-03
2.0E-02
1.1E-02
5.7E-01
8.2E-01
1.0E+00
5
Xylenes
6.1E-04
3.3E-03
1.3E-03
8.0E-02
1.2E-01
1.5E-01
5
Acrolein
1.9E-04
1.3E-03
2.2E-04
3.7E-02
5.6E-02
7.6E-02
5
Ethylbenzene
1.5E-05
1.3E-04
9.2E-05
2.2E-03
3.1E-03
4.0E-03
5
Methylene Chloride
3.1E-03
2.5E-02
1.3E-02
5.8E-01
8.6E-01
1.1E+00
5
Styrene
1.1E-04
4.3E-04
1.9E-04
2.5E-02
3.7E-02
4.7E-02
5
1-2-4 Trimethylbenzene
3.0E-05
3.8E-04
9.5E-05
9.1E-03
1.3E-02
1.6E-02
5
1-3-5 Trimethylbenzene
1.0E-05
1.2E-04
4.6E-05
2.8E-03
4.0E-03
5.1E-03
5
Vinyl chloride
1.2E-06
7.8E-06
1.4E-06
2.3E-04
3.5E-04
4.7E-04
5
NO2
1.9E-01
2.3E+00
4.5E-01
5.0E+01
5.0E+01
5.4E+01
6
NOx
2.8E-01
3.1E+00
2.1E+00
8.9E+01
1.2E+02
1.5E+02
6
CO
2.9E-01
4.0E+00
2.5E+00
7.2E+01
9.7E+01
1.2E+02
6
SO2
1.9E-02
3.9E-01
2.5E-01
1.0E+01
1.4E+01
1.7E+01
6
Dust
1.4E-02
2.4E-01
1.2E-01
5.9E+00
8.7E+00
1.1E+01
6
Arsenic
2.4E-05
1.2E-04
9.0E-05
4.5E-03
76.2E-03
7.8E-03
6
Selenium
2.0E-05
1.4E-04
9.1E-05
2.4E-03
3.4E-03
4.2E-03
6
Manganese
3.3E-04
3.8E-03
9.7E-04
1.0E-01
1.5E-01
2.0E-01
6
Cadmium
1.9E-09
6.7E-09
1.5E-09
2.9E-07
4.0E-07
5.0E-07
6
Chromium (VI)
1.7E-07
7.6E-07
4.2E-07
2.2E-05
2.9E-05
3.6E-05
6
Nickel
1.2E-05
1.2E-04
5.1E-05
3.2E-03
4.9E-03
6.4E-03
6
Mercury
5.1E-05
2.3E-04
2.2E-04
5.2E-03
7.2E-03
9.0E-03
6
Ammonia
6.1E-03
4.8E-02
2.9E-02
1.2E+00
1.8E+00
2.4E+00
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 58
PHASE 3A. FINAL REPORT
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
7.5E-07
6.3E-06
2.6E-06
1.1E-04
1.6E-04
2.1E-04
Annual
average
6
BaP Equivalents
6
Acetone
2.9E-02
3.2E-01
2.6E-01
5.4E+00
7.9E+00
1.0E+01
6
Acetaldehyde
6.1E-03
6.5E-02
6.4E-02
1.2E+00
1.8E+00
2.3E+00
6
Formaldehyde
3.6E-03
3.7E-02
1.9E-02
9.8E-01
1.5E+00
1.9E+00
6
2-Butanone
2.9E-03
2.8E-02
2.6E-02
5.4E-01
8.1E-01
1.1E+00
6
Benzene
9.0E-04
1.4E-02
7.1E-03
2.8E-01
4.1E-01
5.4E-01
6
Toluene
3.6E-03
2.5E-02
1.8E-02
4.0E-01
6.0E-01
7.8E-01
6
Xylenes
8.0E-04
4.5E-03
2.4E-03
7.6E-02
1.1E-01
1.5E-01
6
Acrolein
3.1E-04
1.5E-03
5.2E-04
4.7E-02
7.1E-02
9.4E-02
6
Ethylbenzene
2.0E-05
1.4E-04
1.1E-04
2.4E-03
3.5E-03
4.6E-03
6
Methylene Chloride
4.0E-03
3.3E-02
2.2E-02
5.6E-01
8.4E-01
1.1E+00
6
Styrene
9.5E-05
5.1E-04
3.0E-04
1.4E-02
2.2E-02
2.8E-02
6
1-2-4 Trimethylbenzene
2.6E-05
2.8E-04
7.7E-05
7.2E-03
1.1E-02
1.4E-02
6
1-3-5 Trimethylbenzene
9.6E-06
8.9E-05
4.2E-05
2.2E-03
3.4E-03
4.5E-03
6
Vinyl chloride
1.9E-06
9.1E-06
3.2E-06
2.9E-04
4.4E-04
5.9E-04
6
NO2
2.8E-01
3.1E+00
2.1E+00
5.1E+01
5.3E+01
5.4E+01
7
NOx
2.5E-01
3.3E+00
1.3E+00
8.4E+01
1.2E+02
1.6E+02
7
CO
1.6E-01
2.4E+00
1.4E+00
3.4E+01
5.1E+01
6.7E+01
7
SO2
1.6E-02
4.1E-01
1.6E-01
9.2E+00
1.4E+01
1.8E+01
7
Dust
9.8E-03
1.6E-01
9.6E-02
3.1E+00
4.0E+00
4.8E+00
7
Arsenic
2.0E-05
1.3E-04
5.0E-05
4.8E-03
7.5E-03
1.0E-02
7
Selenium
9.2E-06
7.2E-05
4.9E-05
8.4E-04
1.2E-03
1.6E-03
7
Manganese
3.4E-04
3.6E-03
9.9E-04
7.6E-02
1.1E-01
1.5E-01
7
Cadmium
1.7E-09
7.0E-09
1.5E-09
3.2E-07
5.0E-07
6.8E-07
7
Chromium (VI)
1.4E-07
6.2E-07
2.6E-07
2.0E-05
2.9E-05
3.9E-05
7
Nickel
1.2E-05
1.2E-04
4.1E-05
2.4E-03
3.5E-03
4.6E-03
7
Mercury
4.5E-05
2.0E-04
1.4E-04
5.4E-03
8.4E-03
1.1E-02
7
Ammonia
6.9E-03
4.6E-02
2.5E-02
9.5E-01
1.4E+00
1.8E+00
7
BaP Equivalents
6.3E-07
4.8E-06
2.2E-06
1.1E-04
1.5E-04
1.9E-04
7
Acetone
2.7E-02
2.6E-01
1.7E-01
3.7E+00
5.2E+00
6.5E+00
7
Acetaldehyde
5.4E-03
5.9E-02
4.3E-02
7.4E-01
1.1E+00
1.4E+00
7
Formaldehyde
2.5E-03
4.3E-02
1.7E-02
6.4E-01
9.5E-01
1.2E+00
7
2-Butanone
2.8E-03
2.9E-02
1.8E-02
4.3E-01
6.4E-01
8.3E-01
7
Benzene
4.3E-04
1.4E-02
4.1E-03
2.0E-01
2.9E-01
3.8E-01
7
Toluene
1.8E-03
1.8E-02
8.1E-03
2.7E-01
3.9E-01
5.1E-01
7
Xylenes
3.8E-04
2.2E-03
1.1E-03
3.3E-02
4.5E-02
5.6E-02
7
Acrolein
2.4E-04
1.6E-03
5.9E-04
3.2E-02
4.8E-02
6.4E-02
7
Ethylbenzene
1.4E-05
1.1E-04
8.6E-05
1.3E-03
1.9E-03
2.5E-03
7
Methylene Chloride
2.2E-03
1.8E-02
1.1E-02
2.4E-01
3.3E-01
4.1E-01
7
Styrene
9.6E-05
6.7E-04
2.1E-04
1.2E-02
1.8E-02
2.3E-02
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 59
PHASE 3A. FINAL REPORT
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
2.4E-05
2.5E-04
7.5E-05
5.3E-03
7.9E-03
1.0E-02
Annual
average
7
1-2-4 Trimethylbenzene
7
1-3-5 Trimethylbenzene
8.8E-06
8.6E-05
4.0E-05
1.7E-03
2.5E-03
3.2E-03
7
Vinyl chloride
1.5E-06
1.0E-05
3.7E-06
2.0E-04
3.0E-04
4.0E-04
7
NO2
2.4E-01
3.3E+00
1.3E+00
3.8E+01
3.9E+01
4.7E+01
8
NOx
1.7E-01
2.5E+00
1.5E+00
3.6E+01
5.4E+01
7.0E+01
8
CO
1.5E-01
2.5E+00
1.7E+00
3.9E+01
5.8E+01
7.5E+01
8
SO2
1.2E-02
3.1E-01
1.9E-01
3.9E+00
5.9E+00
7.7E+00
8
Dust
8.6E-03
1.8E-01
1.3E-01
3.0E+00
4.5E+00
5.8E+00
8
Arsenic
1.4E-05
9.2E-05
6.4E-05
2.2E-03
3.3E-03
4.4E-03
8
Selenium
9.6E-06
7.4E-05
5.8E-05
1.0E-03
1.4E-03
1.7E-03
8
Manganese
2.9E-04
3.2E-03
1.3E-03
8.2E-02
1.2E-01
1.5E-01
8
Cadmium
1.1E-09
5.1E-09
2.5E-09
1.4E-07
2.2E-07
2.9E-07
8
Chromium (VI)
1.0E-07
5.6E-07
3.3E-07
8.9E-06
1.3E-05
1.7E-05
8
Nickel
1.0E-05
1.0E-04
5.5E-05
2.6E-03
3.7E-03
4.7E-03
8
Mercury
3.4E-05
1.5E-04
1.6E-04
2.8E-03
4.2E-03
5.6E-03
8
Ammonia
5.8E-03
4.6E-02
3.0E-02
9.6E-01
1.4E+00
1.7E+00
8
BaP Equivalents
5.2E-07
4.0E-06
2.5E-06
7.6E-05
1.1E-04
1.4E-04
8
Acetone
2.1E-02
1.8E-01
1.6E-01
3.1E+00
4.5E+00
5.7E+00
8
Acetaldehyde
4.5E-03
3.9E-02
4.4E-02
6.7E-01
9.6E-01
1.2E+00
8
Formaldehyde
2.3E-03
3.3E-02
2.4E-02
5.8E-01
8.6E-01
1.1E+00
8
2-Butanone
2.3E-03
2.0E-02
1.8E-02
3.2E-01
4.7E-01
6.1E-01
8
Benzene
4.1E-04
8.4E-03
5.0E-03
1.9E-01
2.8E-01
3.6E-01
8
Toluene
1.6E-03
1.2E-02
9.2E-03
2.4E-01
3.4E-01
4.4E-01
8
Xylenes
3.4E-04
1.9E-03
1.3E-03
2.9E-02
4.2E-02
5.5E-02
8
Acrolein
1.9E-04
1.3E-03
8.8E-04
2.3E-02
3.4E-02
4.5E-02
8
Ethylbenzene
1.2E-05
9.9E-05
8.7E-05
1.4E-03
2.0E-03
2.5E-03
8
Methylene Chloride
1.8E-03
1.5E-02
1.2E-02
2.2E-01
3.2E-01
4.2E-01
8
Styrene
6.5E-05
4.2E-04
2.2E-04
9.0E-03
1.3E-02
1.7E-02
8
1-2-4 Trimethylbenzene
2.1E-05
2.2E-04
1.0E-04
5.7E-03
8.2E-03
1.0E-02
8
1-3-5 Trimethylbenzene
7.6E-06
7.8E-05
4.7E-05
1.8E-03
2.5E-03
3.2E-03
8
Vinyl chloride
1.2E-06
7.8E-06
5.5E-06
1.4E-04
2.2E-04
2.8E-04
8
NO2
1.7E-01
2.5E+00
1.5E+00
3.6E+01
3.8E+01
4.3E+01
9
NOx
2.7E-01
3.0E+00
3.0E+00
4.1E+01
6.3E+01
8.6E+01
9
CO
2.4E-01
3.1E+00
3.6E+00
4.1E+01
6.5E+01
8.7E+01
9
SO2
1.8E-02
3.9E-01
3.9E-01
4.7E+00
7.1E+00
9.3E+00
9
Dust
1.4E-02
2.5E-01
2.6E-01
4.1E+00
6.5E+00
8.7E+00
9
Arsenic
2.3E-05
1.3E-04
1.4E-04
2.4E-03
3.9E-03
5.5E-03
9
Selenium
1.9E-05
1.1E-04
1.5E-04
1.8E-03
2.6E-03
3.3E-03
9
Manganese
7.2E-04
6.8E-03
4.6E-03
1.5E-01
2.2E-01
2.8E-01
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 60
PHASE 3A. FINAL REPORT
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Cadmium
1.8E-09
8.2E-09
6.0E-09
1.6E-07
2.6E-07
3.7E-07
9
Chromium (VI)
1.6E-07
7.1E-07
7.5E-07
9.8E-06
1.5E-05
2.1E-05
9
Nickel
2.4E-05
2.3E-04
1.6E-04
4.7E-03
6.8E-03
8.8E-03
9
Mercury
6.6E-05
2.4E-04
3.5E-04
3.5E-03
5.0E-03
6.4E-03
9
Ammonia
1.3E-02
9.2E-02
8.4E-02
1.8E+00
2.6E+00
3.3E+00
9
BaP Equivalents
1.2E-06
8.1E-06
7.5E-06
1.4E-04
1.9E-04
2.4E-04
9
Acetone
4.7E-02
3.1E-01
4.0E-01
4.9E+00
6.8E+00
8.4E+00
9
Acetaldehyde
9.4E-03
6.8E-02
9.7E-02
9.6E-01
1.3E+00
1.6E+00
9
Formaldehyde
3.7E-03
4.3E-02
5.5E-02
5.8E-01
9.1E-01
1.2E+00
9
2-Butanone
5.1E-03
3.1E-02
4.3E-02
4.5E-01
6.2E-01
7.8E-01
9
Benzene
6.9E-04
1.2E-02
1.1E-02
1.8E-01
2.7E-01
3.4E-01
Site Chemical Species
9
Annual
average
9
Toluene
3.7E-03
2.0E-02
2.2E-02
3.5E-01
5.0E-01
6.3E-01
9
Xylenes
8.0E-04
3.7E-03
3.5E-03
7.6E-02
1.1E-01
1.4E-01
9
Acrolein
3.0E-04
1.7E-03
1.8E-03
2.6E-02
4.1E-02
5.6E-02
9
Ethylbenzene
2.4E-05
1.6E-04
2.0E-04
2.6E-03
3.8E-03
4.9E-03
9
Methylene Chloride
4.1E-03
2.7E-02
3.1E-02
5.8E-01
8.2E-01
1.0E+00
9
Styrene
1.1E-04
5.6E-04
5.0E-04
1.0E-02
1.5E-02
1.9E-02
9
1-2-4 Trimethylbenzene
5.2E-05
4.8E-04
3.3E-04
1.1E-02
1.5E-02
2.0E-02
9
1-3-5 Trimethylbenzene
1.8E-05
1.7E-04
1.3E-04
3.3E-03
4.7E-03
6.1E-03
9
Vinyl chloride
1.9E-06
1.1E-05
1.1E-05
1.6E-04
2.6E-04
3.5E-04
9
NO2
2.7E-01
3.0E+00
3.0E+00
4.1E+01
4.8E+01
5.1E+01
10
NOx
2.3E-01
2.4E+00
2.1E+00
4.2E+01
6.2E+01
8.1E+01
10
CO
2.1E-01
2.8E+00
2.5E+00
5.2E+01
8.1E+01
1.1E+02
10
SO2
1.5E-02
3.1E-01
2.7E-01
5.1E+00
7.7E+00
1.0E+01
10
Dust
1.1E-02
2.4E-01
1.7E-01
5.5E+00
8.7E+00
1.2E+01
10
Arsenic
2.2E-05
1.2E-04
1.6E-04
2.0E-03
3.2E-03
4.6E-03
10
Selenium
2.1E-05
1.7E-04
1.7E-04
4.2E-03
6.0E-03
7.8E-03
10
Manganese
9.6E-04
1.0E-02
5.7E-03
3.8E-01
5.5E-01
7.1E-01
10
Cadmium
1.6E-09
7.2E-09
4.9E-09
1.3E-07
2.2E-07
3.1E-07
10
Chromium (VI)
1.4E-07
6.2E-07
4.9E-07
9.7E-06
1.4E-05
1.9E-05
10
Nickel
3.1E-05
3.3E-04
2.0E-04
1.2E-02
1.7E-02
2.2E-02
10
Mercury
7.3E-05
3.7E-04
4.1E-04
8.6E-03
1.2E-02
1.6E-02
10
Ammonia
1.6E-02
1.4E-01
9.5E-02
4.4E+00
6.4E+00
8.1E+00
10
BaP Equivalents
1.4E-06
1.1E-05
7.7E-06
2.2E-04
3.2E-04
4.1E-04
10
Acetone
5.2E-02
3.9E-01
4.0E-01
9.4E+00
1.3E+01
1.7E+01
10
Acetaldehyde
9.9E-03
8.3E-02
9.6E-02
1.9E+00
2.7E+00
3.4E+00
10
Formaldehyde
3.3E-03
3.6E-02
3.1E-02
7.1E-01
1.1E+00
1.6E+00
10
2-Butanone
5.6E-03
4.2E-02
4.3E-02
7.9E-01
1.1E+00
1.4E+00
10
Benzene
6.2E-04
8.6E-03
8.8E-03
2.0E-01
2.9E-01
3.8E-01
10
Toluene
4.2E-03
2.4E-02
2.5E-02
8.5E-01
1.2E+00
1.6E+00
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 61
PHASE 3A. FINAL REPORT
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Xylenes
8.8E-04
3.8E-03
3.6E-03
1.8E-01
2.6E-01
3.4E-01
10
Acrolein
2.4E-04
1.4E-03
8.7E-04
2.9E-02
4.6E-02
6.2E-02
10
Ethylbenzene
2.6E-05
2.3E-04
2.1E-04
6.4E-03
9.3E-03
1.2E-02
10
Methylene Chloride
4.5E-03
3.1E-02
3.3E-02
1.4E+00
2.0E+00
2.6E+00
10
Styrene
8.3E-05
3.8E-04
4.2E-04
1.3E-02
1.9E-02
2.4E-02
10
1-2-4 Trimethylbenzene
6.8E-05
7.3E-04
4.0E-04
2.6E-02
3.8E-02
4.9E-02
10
1-3-5 Trimethylbenzene
2.2E-05
2.3E-04
1.4E-04
8.2E-03
1.2E-02
1.5E-02
10
Vinyl chloride
1.5E-06
8.4E-06
5.4E-06
1.8E-04
2.9E-04
3.9E-04
10
NO2
2.3E-01
2.4E+00
2.1E+00
4.2E+01
5.1E+01
5.4E+01
11
NOx
3.8E-01
4.8E+00
4.9E+00
4.8E+01
7.7E+01
1.0E+02
11
CO
3.5E-01
4.2E+00
5.1E+00
5.2E+01
8.4E+01
1.2E+02
11
SO2
2.5E-02
5.5E-01
5.7E-01
5.3E+00
8.4E+00
1.1E+01
11
Dust
1.9E-02
3.6E-01
3.3E-01
5.9E+00
9.4E+00
1.3E+01
11
Arsenic
3.7E-05
2.5E-04
3.2E-04
3.8E-03
5.5E-03
7.0E-03
11
Selenium
4.2E-05
3.5E-04
3.1E-04
1.4E-02
2.0E-02
2.5E-02
11
Manganese
2.3E-03
2.3E-02
1.1E-02
1.3E+00
1.8E+00
2.3E+00
11
Cadmium
2.6E-09
1.3E-08
1.0E-08
1.8E-07
3.2E-07
4.5E-07
11
Chromium (VI)
2.3E-07
1.3E-06
1.2E-06
1.3E-05
2.0E-05
2.7E-05
11
Nickel
7.5E-05
7.4E-04
3.9E-04
4.0E-02
5.7E-02
7.2E-02
11
Mercury
1.5E-04
6.4E-04
8.3E-04
2.8E-02
4.0E-02
5.1E-02
11
Ammonia
3.8E-02
3.0E-01
2.0E-01
1.4E+01
2.0E+01
2.6E+01
11
BaP Equivalents
2.8E-06
2.0E-05
1.6E-05
4.0E-04
5.8E-04
7.4E-04
11
Acetone
1.1E-01
7.3E-01
8.2E-01
1.2E+01
1.7E+01
2.2E+01
11
Acetaldehyde
2.1E-02
1.6E-01
1.9E-01
2.6E+00
3.7E+00
4.6E+00
11
Formaldehyde
5.6E-03
5.5E-02
6.2E-02
7.0E-01
1.2E+00
1.6E+00
11
2-Butanone
1.2E-02
7.1E-02
8.8E-02
1.1E+00
1.5E+00
1.9E+00
11
Benzene
1.0E-03
1.3E-02
1.9E-02
2.3E-01
3.4E-01
4.4E-01
11
Toluene
7.9E-03
3.9E-02
4.1E-02
1.2E+00
1.8E+00
2.3E+00
11
Xylenes
1.6E-03
6.7E-03
6.5E-03
2.6E-01
3.9E-01
5.1E-01
11
Acrolein
4.0E-04
2.0E-03
1.8E-03
3.0E-02
4.8E-02
6.6E-02
11
Ethylbenzene
5.5E-05
4.9E-04
3.8E-04
2.1E-02
3.1E-02
3.9E-02
11
Methylene Chloride
8.3E-03
5.7E-02
5.7E-02
2.0E+00
3.0E+00
3.9E+00
11
Styrene
1.4E-04
7.3E-04
8.2E-04
1.4E-02
2.1E-02
2.8E-02
11
1-2-4 Trimethylbenzene
1.6E-04
1.6E-03
8.0E-04
8.8E-02
1.3E-01
1.6E-01
11
1-3-5 Trimethylbenzene
5.3E-05
5.4E-04
2.8E-04
2.7E-02
3.9E-02
5.0E-02
11
Vinyl chloride
2.5E-06
1.2E-05
1.1E-05
1.9E-04
3.0E-04
4.1E-04
11
NO2
3.8E-01
4.8E+00
4.9E+00
4.5E+01
5.4E+01
5.4E+01
13
NOx
1.4E-01
1.5E+00
1.2E+00
3.4E+01
5.2E+01
6.9E+01
13
CO
1.6E-01
2.0E+00
2.2E+00
3.6E+01
5.5E+01
7.2E+01
Site Chemical Species
10
Annual
average
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 62
PHASE 3A. FINAL REPORT
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
SO2
9.6E-03
1.8E-01
1.4E-01
4.1E+00
6.2E+00
8.2E+00
13
Dust
7.4E-03
1.5E-01
1.2E-01
3.2E+00
5.1E+00
6.9E+00
13
Arsenic
1.2E-05
7.1E-05
5.9E-05
1.5E-03
2.5E-03
3.5E-03
13
Selenium
1.2E-05
7.3E-05
1.0E-04
9.5E-04
1.4E-03
1.9E-03
13
Manganese
2.4E-04
2.3E-03
1.9E-03
3.1E-02
4.4E-02
5.5E-02
13
Cadmium
9.4E-10
4.3E-09
2.0E-09
9.5E-08
1.6E-07
2.3E-07
13
Chromium (VI)
8.7E-08
3.9E-07
2.6E-07
8.9E-06
1.4E-05
1.8E-05
13
Nickel
8.5E-06
7.3E-05
7.7E-05
9.9E-04
1.4E-03
1.7E-03
13
Mercury
3.0E-05
1.2E-04
1.9E-04
1.9E-03
3.1E-03
4.4E-03
13
Ammonia
4.3E-03
2.7E-02
3.8E-02
3.7E-01
5.1E-01
6.2E-01
13
BaP Equivalents
4.3E-07
2.5E-06
2.9E-06
4.1E-05
5.5E-05
6.8E-05
13
Acetone
1.7E-02
1.2E-01
2.0E-01
1.3E+00
2.0E+00
2.6E+00
13
Acetaldehyde
3.6E-03
2.8E-02
5.0E-02
3.8E-01
5.6E-01
7.3E-01
13
Formaldehyde
2.0E-03
2.1E-02
1.6E-02
4.5E-01
7.1E-01
9.7E-01
13
2-Butanone
1.8E-03
1.1E-02
2.1E-02
1.5E-01
2.2E-01
2.9E-01
13
Benzene
4.8E-04
5.7E-03
5.9E-03
8.5E-02
1.3E-01
1.7E-01
13
Toluene
1.7E-03
9.5E-03
1.4E-02
1.0E-01
1.4E-01
1.8E-01
13
Xylenes
3.8E-04
1.6E-03
2.2E-03
2.1E-02
2.8E-02
3.4E-02
13
Acrolein
1.5E-04
8.2E-04
6.0E-04
1.9E-02
2.9E-02
3.8E-02
13
Ethylbenzene
1.2E-05
6.9E-05
1.2E-04
9.2E-04
1.4E-03
1.7E-03
13
Methylene Chloride
2.0E-03
1.2E-02
1.9E-02
1.6E-01
2.1E-01
2.6E-01
13
Styrene
4.0E-05
2.0E-04
2.3E-04
3.3E-03
5.0E-03
6.7E-03
13
1-2-4 Trimethylbenzene
1.8E-05
1.7E-04
1.4E-04
2.2E-03
3.1E-03
3.9E-03
13
1-3-5 Trimethylbenzene
6.6E-06
5.2E-05
5.8E-05
6.8E-04
9.6E-04
1.2E-03
13
Vinyl chloride
9.6E-07
5.1E-06
3.7E-06
1.2E-04
1.8E-04
2.4E-04
13
NO2
1.4E-01
1.5E+00
1.2E+00
3.4E+01
4.7E+01
4.8E+01
14
NOx
3.7E-01
4.0E+00
3.5E+00
8.5E+01
1.3E+02
1.6E+02
14
CO
3.7E-01
4.3E+00
5.2E+00
1.1E+02
1.6E+02
2.1E+02
14
SO2
2.4E-02
4.8E-01
4.2E-01
1.0E+01
1.5E+01
2.0E+01
14
Dust
1.7E-02
3.6E-01
3.3E-01
4.9E+00
7.3E+00
9.5E+00
14
Arsenic
3.1E-05
1.9E-04
1.7E-04
3.5E-03
5.4E-03
7.3E-03
14
Selenium
2.6E-05
1.3E-04
2.2E-04
4.2E-03
6.2E-03
8.1E-03
14
Manganese
5.8E-04
4.6E-03
4.9E-03
8.5E-02
1.3E-01
1.8E-01
14
Cadmium
2.5E-09
1.1E-08
7.1E-09
2.2E-07
3.5E-07
4.8E-07
14
Chromium (VI)
2.2E-07
1.0E-06
7.7E-07
1.9E-05
2.8E-05
3.6E-05
14
Nickel
2.1E-05
1.6E-04
1.9E-04
2.7E-03
4.1E-03
5.5E-03
14
Mercury
7.3E-05
3.1E-04
4.8E-04
4.1E-03
6.3E-03
8.5E-03
14
Ammonia
1.0E-02
7.0E-02
9.8E-02
9.8E-01
1.5E+00
2.0E+00
14
BaP Equivalents
1.0E-06
6.5E-06
7.5E-06
8.6E-05
1.2E-04
1.5E-04
14
Acetone
3.9E-02
2.8E-01
4.5E-01
3.8E+00
5.3E+00
6.7E+00
Site Chemical Species
13
Annual
average
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
Page 63
PHASE 3A. FINAL REPORT
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
8.5E-03
6.6E-02
1.1E-01
8.8E-01
1.2E+00
1.6E+00
Annual
average
14
Acetaldehyde
14
Formaldehyde
4.7E-03
4.9E-02
4.3E-02
6.8E-01
1.0E+00
1.3E+00
14
2-Butanone
4.3E-03
2.7E-02
4.5E-02
3.2E-01
4.6E-01
6.0E-01
14
Benzene
1.1E-03
1.1E-02
1.4E-02
2.8E-01
4.1E-01
5.3E-01
14
Toluene
4.1E-03
2.1E-02
3.1E-02
3.8E-01
5.4E-01
6.9E-01
14
Xylenes
9.0E-04
3.7E-03
5.2E-03
8.4E-02
1.2E-01
1.5E-01
14
Acrolein
3.6E-04
2.1E-03
1.6E-03
3.6E-02
5.4E-02
7.2E-02
14
Ethylbenzene
2.7E-05
1.6E-04
2.7E-04
2.2E-03
3.2E-03
4.2E-03
14
Methylene Chloride
4.7E-03
3.1E-02
4.7E-02
5.8E-01
8.4E-01
1.1E+00
14
Styrene
8.9E-05
4.0E-04
5.2E-04
6.8E-03
1.0E-02
1.3E-02
14
1-2-4 Trimethylbenzene
4.4E-05
3.4E-04
3.6E-04
6.0E-03
9.2E-03
1.2E-02
14
1-3-5 Trimethylbenzene
1.5E-05
1.2E-04
1.4E-04
1.9E-03
2.9E-03
3.8E-03
14
Vinyl chloride
2.3E-06
1.3E-05
1.0E-05
2.2E-04
3.4E-04
4.5E-04
14
NO2
3.7E-01
4.0E+00
3.5E+00
5.4E+01
5.4E+01
5.4E+01
15
NOx
4.4E-01
5.2E+00
3.3E+00
7.5E+01
1.1E+02
1.4E+02
15
CO
4.7E-01
6.9E+00
3.4E+00
1.0E+02
1.6E+02
2.1E+02
15
SO2
3.0E-02
7.1E-01
4.2E-01
9.1E+00
1.4E+01
1.8E+01
15
Dust
2.2E-02
4.2E-01
1.7E-01
7.7E+00
1.2E+01
1.6E+01
15
Arsenic
3.3E-05
2.2E-04
1.3E-04
3.7E-03
5.8E-03
7.8E-03
15
Selenium
3.0E-05
2.1E-04
1.0E-04
4.1E-03
6.4E-03
8.7E-03
15
Manganese
3.5E-04
4.0E-03
8.5E-04
7.5E-02
1.2E-01
1.5E-01
15
Cadmium
2.6E-09
1.3E-08
2.5E-09
2.5E-07
3.9E-07
5.3E-07
15
Chromium (VI)
2.5E-07
1.2E-06
6.8E-07
2.0E-05
3.0E-05
3.9E-05
15
Nickel
1.3E-05
1.3E-04
3.9E-05
2.6E-03
4.0E-03
5.3E-03
15
Mercury
6.8E-05
3.5E-04
2.6E-04
4.9E-03
7.5E-03
1.0E-02
15
Ammonia
6.9E-03
5.4E-02
2.3E-02
1.1E+00
1.6E+00
2.1E+00
15
BaP Equivalents
8.3E-07
7.9E-06
3.3E-06
9.9E-05
1.5E-04
1.9E-04
15
Acetone
3.5E-02
4.5E-01
2.6E-01
7.8E+00
1.1E+01
1.5E+01
15
Acetaldehyde
7.9E-03
1.0E-01
7.0E-02
1.7E+00
2.5E+00
3.2E+00
15
Formaldehyde
5.5E-03
7.0E-02
2.6E-02
1.2E+00
1.8E+00
2.4E+00
15
2-Butanone
3.3E-03
4.3E-02
2.6E-02
7.5E-01
1.1E+00
1.5E+00
15
Benzene
1.5E-03
2.0E-02
7.4E-03
4.9E-01
7.2E-01
9.4E-01
15
Toluene
4.3E-03
3.6E-02
1.7E-02
6.3E-01
9.3E-01
1.2E+00
15
Xylenes
9.6E-04
5.8E-03
2.2E-03
8.3E-02
1.2E-01
1.6E-01
15
Acrolein
4.9E-04
2.8E-03
8.6E-04
6.2E-02
9.6E-02
1.3E-01
15
Ethylbenzene
3.0E-05
2.0E-04
1.4E-04
2.9E-03
4.3E-03
5.7E-03
15
Methylene Chloride
5.0E-03
4.2E-02
2.6E-02
6.1E-01
9.1E-01
1.2E+00
15
Styrene
1.5E-04
8.0E-04
3.0E-04
2.3E-02
3.4E-02
4.4E-02
15
1-2-4 Trimethylbenzene
2.9E-05
3.0E-04
1.2E-04
5.0E-03
7.8E-03
1.0E-02
15
1-3-5 Trimethylbenzene
1.2E-05
1.1E-04
6.5E-05
1.6E-03
2.4E-03
3.3E-03
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
Site Chemical Species
(µg m-3)
95th %
24-hr
average
(µg m-3)
95th %
1-hr
average
(µg m-3)
Max.
1-hr
average
(µg m-3)
Max.
10-min
average
(µg m-3)
Max.
3-min
average
(µg m-3)
Annual
average
15
Vinyl chloride
3.1E-06
1.7E-05
5.4E-06
3.9E-04
6.0E-04
8.1E-04
15
NO2
4.3E-01
5.0E+00
3.3E+00
5.4E+01
5.4E+01
5.4E+01
16
NOx
5.4E-01
6.9E+00
8.3E+00
5.2E+01
8.1E+01
1.1E+02
16
CO
5.2E-01
8.1E+00
8.5E+00
5.0E+01
8.0E+01
1.1E+02
16
SO2
3.9E-02
8.7E-01
1.1E+00
6.4E+00
1.0E+01
1.4E+01
16
Dust
2.9E-02
7.3E-01
5.9E-01
5.3E+00
7.0E+00
8.4E+00
16
Arsenic
5.0E-05
2.9E-04
4.2E-04
4.0E-03
5.7E-03
7.2E-03
16
Selenium
6.2E-05
4.7E-04
5.2E-04
1.5E-02
2.1E-02
2.6E-02
16
Manganese
3.4E-03
3.8E-02
1.9E-02
1.3E+00
1.9E+00
2.4E+00
16
Cadmium
3.4E-09
1.6E-08
1.3E-08
1.7E-07
2.9E-07
4.3E-07
16
Chromium (VI)
3.2E-07
1.7E-06
2.0E-06
1.3E-05
1.7E-05
2.0E-05
16
Nickel
1.1E-04
1.2E-03
6.5E-04
4.2E-02
5.9E-02
7.4E-02
16
Mercury
2.2E-04
1.1E-03
1.1E-03
3.0E-02
4.2E-02
5.3E-02
16
Ammonia
6.1E-02
4.8E-01
3.6E-01
1.6E+01
2.2E+01
2.7E+01
16
BaP Equivalents
5.0E-06
3.3E-05
3.4E-05
7.4E-04
1.0E-03
1.3E-03
16
Acetone
1.9E-01
1.1E+00
1.5E+00
1.8E+01
2.5E+01
3.0E+01
16
Acetaldehyde
3.7E-02
2.4E-01
3.7E-01
4.3E+00
5.9E+00
7.3E+00
16
Formaldehyde
8.3E-03
1.1E-01
1.3E-01
7.3E-01
9.6E-01
1.2E+00
16
2-Butanone
2.2E-02
1.2E-01
1.6E-01
2.2E+00
3.1E+00
3.8E+00
16
Benzene
1.5E-03
2.7E-02
3.2E-02
2.7E-01
4.0E-01
5.2E-01
16
Toluene
1.3E-02
6.5E-02
7.3E-02
1.4E+00
1.9E+00
2.4E+00
16
Xylenes
2.7E-03
1.1E-02
1.1E-02
3.1E-01
4.4E-01
5.6E-01
16
Acrolein
6.3E-04
4.2E-03
3.8E-03
3.4E-02
5.4E-02
7.3E-02
16
Ethylbenzene
8.2E-05
7.2E-04
6.8E-04
2.2E-02
3.2E-02
4.0E-02
16
Methylene Chloride
1.3E-02
9.0E-02
9.6E-02
2.3E+00
3.2E+00
4.1E+00
16
Styrene
2.4E-04
1.3E-03
1.4E-03
1.8E-02
2.7E-02
3.5E-02
16
1-2-4 Trimethylbenzene
2.4E-04
2.7E-03
1.4E-03
9.3E-02
1.3E-01
1.7E-01
16
1-3-5 Trimethylbenzene
7.7E-05
8.3E-04
4.8E-04
2.9E-02
4.1E-02
5.1E-02
16
Vinyl chloride
3.9E-06
2.7E-05
2.4E-05
2.1E-04
3.3E-04
4.6E-04
16
NO2
5.4E-01
6.9E+00
8.3E+00
4.4E+01
5.2E+01
5.4E+01
CSIRO Atmospheric Research
TAPM Modelling for Wagerup: Phase 3A. Current Refinery Modelling for HRA
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PHASE 3A. FINAL REPORT
4.6. Concentration Contours
Figure 5 to Figure 27 show the modelled concentration contour patterns for the six
statistics (annual average, 95th percentile 24-hour average, 95th percentile 1-hour
average, maximum 1-hour average, maximum 10-minute average, and maximum 3minute average) for mercury, formaldehyde, and NOx. These were selected as
representative of low-level, medium level and tall-stack releases from the Refinery for
investigating the different patterns of ground-level concentrations. The mercury sources
modelled here only include stack sources; the area source contributions are being
modelled separately. The strongest mercury stack source is the Boilerhouse Mutiflue
whereas the strongest formaldehyde stack source is the Calciner stacks.
For the annual average and 95th percentile 24-hour average, the highest concentrations
in the spatial distribution all occur within the Refinery within a few hundred metres of
the 100 m Multiflue stack. The same is true for the modelled maximum 1-hour average
concentrations for formaldehyde and mercury although for formaldehyde there is a lobe
with concentrations greater than 2 µg m-3 extending 4 km west-south-west from the
Refinery.
For NOx, the modelled maximum 1-hour average concentrations (Figure 25) show a
highest concentration in the spatial distribution of about 180 µg m-3 at a distance of
4 km approximately west-south-west of the 100 m Multiflue stack. Modelled maximum
concentrations through Yarloop are lower (from 50 to 100 µg m-3) and less than
50 µg m-3 in Hamel. The NOx results differ from those for formaldehyde because most
of the NOx emissions occur from the taller stacks that have significant plume rise
because of the high temperature and volume of flow from the Calciner and Boilerhouse
stacks. The highest ground-level concentrations from these stacks occur under
convective or fumigation conditions. The maximum 10-minute and 3-minute average
concentrations show similar patterns but with higher concentrations.
These yearly maximum 1-hour average concentrations represent the most extreme hour
in the year with respect to ground-level concentrations. In a different year with different
meteorology the location and magnitude of these yearly maximum 1-hour average
concentrations could change. This is why the 9th highest concentration (99.9th perentile)
or robust highest concentration (RHC) is often chosen as the key statistic to represent
the extremes, rather than the modelled or observed maximum.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
Formaldehyde concentration (µg/m3)
Annual average, Current scenario (6600 tpd) - Average emissions
13
6364
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
2
1
6
6354
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 10: Annual-average modelled formaldehyde concentrations for Current Emissions
Scenario (6600 tpd)– Average Emissions.
3
Formaldehyde concentration (µg/m )
95th percentile 24-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 11: 95th percentile 24-hour average modelled formaldehyde concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
3
Formaldehyde concentration (µg/m )
95th percentile 1-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
2
1
4
6354
6
YARLOOP
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 12: 95th percentile 1-hour average modelled formaldehyde concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
3
Formaldehyde concentration (µg/m )
Maximum 1-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 13: Maximum 1-hour average modelled formaldehyde concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
3
Formaldehyde concentration (µg/m )
Maximum 10-minute average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
2
1
4
6354
6
YARLOOP
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 14: Maximum 10-minute average modelled formaldehyde concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
3
Formaldehyde concentration (µg/m )
Maximum 3-minute average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 15: Maximum 3-minute average modelled formaldehyde concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
Mercury concentration (µg/m3)
Annual average, Current scenario (6600 tpd) - Average emissions
13
6364
6362
8
9
10
AMG84 Northing (km)
14
11
6360
max 0.0024
16
05
00
0.
7
6358
100 m Multiflue
15
6356
4
2
1
6
6354
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 16: Annual-average modelled mercury concentrations for Current Emissions Scenario
(6600 tpd)– Average Emissions.
3
Mercury concentration (µg/m )
95th percentile 24-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
max 0.006
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 17: 95th percentile 24-hour average modelled mercury concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
3
Mercury concentration (µg/m )
95th percentile 1-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
max 0.009
7
6358
100 m Multiflue
15
6356
2
1
4
6354
6
YARLOOP
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 18: 95th percentile 1-hour average modelled mercury concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
3
Mercury concentration (µg/m )
Maximum 1-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 19: Maximum 1-hour average modelled mercury concentrations for Current Emissions
Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
3
Mercury concentration (µg/m )
Maximum 10-minute average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
2
1
4
6354
6
YARLOOP
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 20: Maximum 10-minute average modelled mercury concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
3
Mercury concentration (µg/m )
Maximum 3-minute average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 21: Maximum 3-minute average modelled mercury concentrations for Current
Emissions Scenario (6600 tpd) – Peak Emissions.
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PHASE 3A. FINAL REPORT
NOx concentration (µg/m3)
Annual average, Current scenario (6600 tpd) - Average emissions
13
6364
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
2
1
6
6354
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 22: Annual-average modelled NOx concentrations for Current Emissions Scenario
(6600 tpd) – Average Emissions.
3
NOx concentration (µg/m )
95th percentile 24-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 23: 95th percentile 24-hour average modelled NOx concentrations for Current Emissions
Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
3
NOx concentration (µg/m )
95th percentile 1-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
2
1
4
6354
6
YARLOOP
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 24: 95th percentile 1-hour average modelled NOx concentrations for Current Emissions
Scenario (6600 tpd) – Peak Emissions.
3
NOx concentration (µg/m )
Maximum 1-hour average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 25: Maximum 1-hour average modelled NOx concentrations for Current Emissions
Scenario (6600 tpd) – Peak Emissions.
CSIRO Atmospheric Research
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PHASE 3A. FINAL REPORT
3
NOx concentration (µg/m )
Maximum 10-minute average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
2
1
4
6354
6
YARLOOP
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 26: Maximum 10-minute average modelled NOx concentrations for Current Emissions
Scenario (6600 tpd) – Peak Emissions.
3
NOx concentration (µg/m )
Maximum 3-minute average, Current scenario (6600 tpd) - Peak emissions
6364
13
HAMEL
6362
8
9
10
AMG84 Northing (km)
14
11
6360
16
7
6358
100 m Multiflue
15
6356
0
10
4
6354
1
YARLOOP
2
6
3
5
6352
392
394
396
398
400
402
AMG84 Easting (km)
Figure 27: Maximum 3-minute average modelled NOx concentrations for Current Emissions
Scenario (6600 tpd) – Peak Emissions.
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PHASE 3A. FINAL REPORT
These yearly maximum 1-hour average concentrations represent the most extreme hour
in the year with respect to ground-level concentrations. In a different year with different
meteorology the location and magnitude of these yearly maximum 1-hour average
concentrations could change. This is why the 9th highest concentration or robust highest
concentration (RHC) is often chosen as the key statistic to represent the extremes, rather
than the modelled or observed maximum.
4.7. Peak Events
Figure 28 to Figure 30 show the temporal variation of the modelled 1-hour average
concentrations around the five highest concentration events for formaldehyde, NOx and
NO2.
One-half of the model events occur at the same time for NOx and formaldehyde, though
not always at the same site, with most of these events during the winter months (April to
September).
For both formaldehyde and NOx the peaks at receptor 14 (Escarpment) all occur
between 10:00 to 18:00, whereas at receptors 1 (Boundary Road) and 3 (Yarloop),
peaks are observed both at night and during the day. Most of the peaks only last for one
hour; the longest is a four-hour formaldehyde peak at site 1 from 19:00 to 23:00.
Figure 31 shows that the wind directions at the times of the peak concentrations
correspond closely with the Refinery being directly upwind from the receptor except for
one case at receptor 3 for both NOx and formaldehyde. This one case occurred on
9 Aug 2004 at 21:00 with a wind speed of 2 m s-1 and an inversion height of 34 m. It
occurs with a more easterly component indicating some turning of the wind and flow
from the escarpment towards the receptor. In the other cases, the wind speeds were
higher, typically 4 to 8 m s-1. These features are similar to those identified in the
Wagerup Air Quality Review (CSIRO, 2004a) when examining the peak NOx
concentrations observed at Boundary Road and Upper Dam, except that the wind speeds
in those cases tended to be lower, generally less than 4 m s-1. These features also closely
match those identified in Section 6 of the Phase 2 report (CSIRO, 2004c), where most
model events were identified as occurring with wind speeds from 2 to 6 m s-1 and at
lower speeds under easterly flows. Night-time model events occurred with mixing
heights less than 300 m, whereas daytime model events occur in strongly convective
conditions with mixing heights up to 2000 m, similar to the results shown in Figure 31.
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Figure 28: Time series of the five highest formaldehyde concentrations at three receptor sites.
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Figure 29: Time series of the five highest NOx concentrations at three receptor sites.
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Figure 30: Time series of the five highest NO2 concentrations at three receptor sites.
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1200
NOx, Site 1
NOx, Site 3
NOx, Site 14
Formaldehyde, Site 1
Formaldehyde, Site 3
Formaldehyde, Site 14
Mixing Height (m)
1000
800
600
400
200
0
0
90
180
Wind direction (degrees)
270
360
Figure 31: Modelled wind direction (at 25 m) and mixing height at Bancell Road
for the 5 highest peak concentrations of NOx and formaldehyde at receptors 1, 3,
and 14.
The peaks at the Escarpment site all show a pattern of gradual build-up over two to
three hours and then decay within an hour, whereas those at the other sites tend to be
events that last just one hour.
The results for NO2 in Figure 30 are very similar to those for NOx in Figure 29. This
reflects the fact that the daily maximum NOx concentration only rarely exceeds the
maximum ozone concentration of 54 µg m-3 (28.2 ppb), which is used in the NO2
modelling (see Figure 7, Section 3.4).
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PHASE 3A. FINAL REPORT
5. Summary
The work presented in this report is part of a study entitled “Meteorological and
Dispersion Modelling Using TAPM for Wagerup”, consisting of three closely defined
objectives.
This report deals with the third objective (Phase 3A: HRA Concentration Modelling),
with the following objectives completed:
1. The refined TAPM (as resolved in Phases 1 and 2) has been run for the annual
meteorological file (1 April 2003 to 31 March 2004) and the agreed sources listed in dot
point 2 to produce estimates of the following parameters for 28 pollutants at 15 receptor
points:
• Annual average concentration (at average emission rates)
• Maximum 1-hour average concentrations (peak emissions)
• 95th percentile 1-hour average concentrations (peak emissions)
• 95th percentile 24-hour average concentrations (peak emissions)
• Maximum 10-minute average concentrations (peak emissions)
• Maximum 3-minute average concentrations (peak emissions).
2. The 28 pollutants are oxides of nitrogen, carbon monoxide, sulphur dioxide, dust,
arsenic, selenium, manganese, cadmium, chromium VI, nickel, mercury, ammonia,
benzo(a)pyrene equivalents, acetone, acetaldehyde, formaldehyde, 2-butanone, benzene,
toluene, xylenes, acrolein, ethylbenzene, methylene chloride, styrene,
1,2,4, trimethylbenzene, 1,3,5 trimethylbenzene, vinyl chloride, and nitrogen dioxide.
3. Contour plots have been produced of these six statistics for three example substances
(NOx, Formaldehyde and Mercury) to indicate the different concentration distribution
patterns for substances predominantly emitted from high and low level sources.
4. A simple titration algorithmic method has been described and used to calculate the
conversion of NOx to NO2 using available data on the diurnal variation in ozone
concentrations at Wagerup.
5. The best practice method has been used for deriving shorter time period (3 and 10minute) maximum concentrations from the Wagerup hourly TAPM concentration fields.
A detailed description of this method has been presented.
6. The temporal variation of concentration around, and mechanisms causing, the
modelled 5 highest short-term peak concentrations has been investigated for NOx and
formaldehyde for the peak emission scenario at three receptors (sites 1, 3, and 14). The
mechanisms identified as responsible for the highest short-term peak concentrations
match those identified in Phase 2 of this work (CSIRO, 2004c) and in the Wagerup Air
Quality review (CSIRO, 2004a).
7. Separate quality assurance runs have been undertaken for NOx and formaldehyde to
confirm the accuracy of the main modelling technique.
8. The uncertainty of the model predictions has been determined from consideration of
results from a range of TAPM studies and an analysis of the sensitivity of model results
to wind data assimilation. We conclude that the results for the modelled concentrations
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presented in this report have an uncertainty of a factor of approximately 2 (i.e. the actual
values lie in the range of +100% to -50% of the listed concentrations) at the 95%
confidence level.
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