Jochen Mueller- NRCET
Garry Cook, Donovan Marney,- CSIRO
Kevin Tolhurst – Melb Uni
Lachie McCaw- DEC, WA
Bob Symons, NMI
Team:
Supported by the Australian Commonwealth Government
Department of Environment and Water
Mick,Meyer@csiro.au
CSIRO Marine and Atmospheric Research, Aspendale,
Victoria, AUSTRALIA
Mick Meyer
Measurement of Dioxin Emissions from
Bushfires in Australia
That produces a lot of dioxins
8% of Australia
16% of NT,10% of WA,
6% of Qld.
In 2006: 66 Mha
• listed in the Stockholm Convention on
POPs
• 7 PCDDs, 10 PCDFs are assigned
toxicity weightings
• the 2,3,7,8 dioxins and furans are toxic
• 210 PCDDs & PCDFs
Dioxins
National
Dioxin
Program
(2004)
Environment
Australia
(2002)
To air
1081
18
53
2
3
0
1156
1410
82%
To
land
865
14
42
35
60
7
1023
1300
79%
Emission
g
2001
Bushfires are the largest source and the most
uncertain source in the Inventory
216,173,000
3,505,000
10,588,000
3,492,000
6,044,000
653,300
1994
Emission factor
ug TEQ/t
To
land
To air
5
4
5
4
5
4
0.5
10
0.5
10
0.5
10
62- 1240
7-400
72-1700
(46%-81%)
0.5-10
0.5-28
Mass
(t)
3.5-68
Emission (g
TEQ)
0.5-10
Savanna and Temperate Grassland
Prescribed burning of forests
Wildfires
Agricultural residues- wheat
Agricultural residues- coarse grains
Agricultural residues- sugar
Total
All sources
Savanna and temperate
grasslands
Prescribed burning, stubble
burning
Wildfires
Total
Emission
factors
(ug TEQ.t)
Inventories
Fires
Measuring emission factors
Potential measurement artifacts
Residues
Dispersion
Emerging issues
Outline
Fires in Australia
Oct - Dec
July-Sept
April-June
Jan-Mar
M. Simon, S. Plummer, F. Fierens, J. J. Hoelzemann, and O. Arino (2004)
Three estimates of global biomass burning in
2002
Africa
North/Central America
South America
Australia
Asia
Europe
Russia
Global
GBA-2000
Area (Mha) Percentage
224.6
64%
6.2
2%
11.9
3%
55.9
16%
27.1
8%
4.3
1%
22.2
6%
352.2
100%
From Kasischke and Penner (2004)
Australian fire scar analysis
1999/2000 = 52 Mha
GLOBSCAR
Area (Mha)
%
121
57.4%
11
5.2%
13.8
6.5%
18
8.5%
21.2
10.1%
5.8
2.8%
20
9.5%
210.7
100.0%
Global emissions
Fire frequency 1998 to 2006
0
10
5
15
25
20
Sep
Sep
Jul
Jul
May
May
Mar
Mar
Percent annual
regional area
Percent annual
regional area
30
Jan
Jan
40
35
30
25
20
15
10
5
0
Nov
Nov
Fires are NOT fuel limited
Ignition/propagation is weather
dependent
Fires are fuel limited
There is always an ignition source
When fires happen
Lightning
Forestry personnel
Recreational users
Residents/Farmers
Unknown/Arson
Unreported
Cause
Number of
fires
1602
255
600
2117
1627
99
25
4
10
33
26
2
%
Causes of fires in State Forests and National
Parks in Victoria 1990-1999.
Most fires have anthropogenic ignition causes
Wildfire Causes
100
0.12
0.1
1.2
6
13
80
1
0
10
15
49
24
2
100
1.2
0
0
0
0
0
0
0
100
3.9
1.9
0.0
0
2
3
3
4
88
0.5 0.4
5
41
33
21
0
0
100
40.9
34
0
0
66
0
0
100 100 100 100
36.1 0.50 0.4 15.6
2
8
2
0
89
0.0
100
0.0
0
10
90
0
0
0
% Total carbon emitted
NSW Tas WA SA Vic Qld NT ACT
8.1
100
100
2
6
3
0
89
AUST
Wildfires, agricultural and prescribed fires are where most
of the population live-in the South and along the East
Coast
Most of the emissions are from savanna woodland and
arid grassland in Northern Australia where the population
is low.
Total
% National emission
%National emission
excluding tropical
savannah
Tropical savannah
Open woodland and
temperate grassland
Forest, Prescribed
Forest, Wildfire
Cereals
Sugar
Vegetation
Australian carbon emission estimates
(2000)
Fraction Savanna
Area
Savanna fire area (ha)
Fraction Savanna
1995
2000
2005
2010
0
0
1990
1x106
20x106
0.90
1980
0.92
0.94
0.96
0.98
1.00
2x106
40x106
4x106
3x106
1985
Savanna
Wildfire
Prescribed
5x106
60x106
80x106
100x106
Fire Area
Prescribed and Wildfire Areaha
Ash Wednesday, 1983
Sydney, 1992
Emission (Gg CO2-e)
0
1980
5000
10000
15000
20000
25000
20000
15000
10000
5000
0
1985
Savanna
Prescribed
Wildfire
Inventory
Annual
1990
1995
2000
2005
2010
Canberra, 2003
National Emission Timeseries
Fire area (ha)
0
1980
20,000,000
40,000,000
60,000,000
80,000,000
100,000,000
1985
Top
Centre
Total
2002 NGGI
Inter-annual
Variability of
Savanna Fires
-
2000
1988
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
70,000,000
80,000,000
1995
Year
1990
Fire scar area (ha)
2005
1992
NT Top
NT Centre
WA Top
WA Centre
Total
2000
Grasslands ~80
Woodlands ~2
Range min to max
Year
1996
2004
~60% of
forest/woodland
Fire History in Victoria
1940-1999
Forest, woodlands, Arid
Grasslands (Wildfire,
Prescribed fires)
(Agricultural residues)
Agricultural cropping
Landscape uses
Fires from land clearing are very different
Occur once
Often on topsoils with high carbon content
Fires are:
A natural part of the Australian landscape
Highly variable from year to year
A major component of the carbon cycle
How do we measure dioxin emissions
• From atmospheric concentration measurements
using a dual tracer technique – field method
• Direct measurement – mass dioxin emitted/mass
fuel burned - possible in laboratory
How to determine emission factors:
Fuelburned = Area x fuel load x combustion efficiency
Emission = Fuel burned x emission factor
Fuel dependent
0.5 - 55 ug TEQ/kg
• Combustion rooms e.g. Gullett and Touati (US
EPA)
Low rates, OCDD dominated
• Field measurements (e.g (Prange, Mueller et al.
(NRCET)
• Surrogate estimates were made using wood
combustion heaters were made using open
combustion chambers (0.5 to 30 ug TEQ/kg)
Dioxin emissions from biomass burning
Tracer (Ec) is total volatilised fuel carbon
EPCDD
[
PCDD
]
= EC ×
Dual tracer technique
[C ]
Measurement Principle
50% carbon
1 kg burned fuel
=500 g fuel
carbon
Fuel
O2
500 g carbon,
1 ng TEQ PCDD/F,
Raw Smoke
Ambient Air
280 – 8400 m3
From ambient air
56 to 1680 g C
0.1 to 0.4 ng TEQ PCDD/F
ratio =2 pg TEQ (g C)-1
From fuel:
500 g carbon,
1 ng TEQ PCDD/F
Smoke plume
282 – 8402 m3
Dilution
0.2 gC m-3
0.05 pg TEQ PCDD/Fm-3
1.8 m
3
ratio =2 pg TEQ (g C)-1
Combustion
The challenge is to
sample sufficient smoke
to get a dioxin sample
that can be reliably
analysed
Field sampling
CO2
Flow
Pump
Main
pump
Annubar
Pressure
sample lines
SS filter
Flow meter
10 x 8 Filter
Pump
Dioxin Trap
Brass
needle
valve
>5g C, >200 m3 air, in approx 1h
Control box
Gas meter
TSP
filter
1µm particle
filter
Sample inlet
Tedlar bag
In the Field
Late season
Early season
Savanna Fires
13:00:00
0
50
100
150
0
200
400
600
800
14:00:00
15:00:00
16:00:00
2cm depth
Surface
17:00:00
Fuel bed and soil temperatures Prescribed burn,
Victoria
Sugar Cane
Total carbon sampled (g)
Time
17.00
0
0
14.00
16.00
200
2
15.00
400
4
800
600
[CO2]
Total C
1000
6
8
10
CO2 concentrations near a low intensity
prescribed fire
[CO2] (ppm)
•Simulates a backing fire;
either stubble or prescribed
fuel reduction fire in forests
•Smoke is sampled from the
exhaust hood
•Fire progresses across a
fuel bed on the floor of the
corridor
Laboratory sampling
Leaf litter
Burn
Temperature ( C)
o
0
200
400
600
800
1000
0
5
Timecourse
of fire along
the bed
1
o
2
Temperature ( C)
3
10
4 5
0
200
400
600
800
1000
8 9
Time (min)
6 7
0
15
10
5
Time (min)
20
Cane
10
25
15
Straw
20
25
(sampler version 2)
In the field- at close
quarters
For safety, you never see to fire front.
The energy release is 50- 100 MW m-1
compared with 1 -5 MW m-1 for prescribed
fires.
The front can move at 10-20 km h-1
Wildfires
Measurements
Locations of field measurements
Laboratory samples
Species
Cane
PCDD
3.7
PCDF
5.1
PCB
0.2
Total
8.9
Field samples
Species
Cane
PCDD
1.8
PCDF
0.14
PCB
0.07
Total
1.98
Sorghum
11.5
22.4
0.35
34.2
0.83
Wildfire
0.65
0.13
0.13
0.91
Forest
0.42
0.33
0.09
Prescribed
1.23
0.36
0.18
1.78
30.5
Straw
11.4
18.7
0.35
Savanna
2.03
0.16
0.07
2.3
Results
Emission ratios (pg TEQ gC-1)
EF in ng TEQ/kg dwt
0
10
20
30
40
50
60
G
le
ul
N
tt
C
G
le
ul
OR
tt
N
DP
b
la
N
w
ra
st
e
c
A
ld
um
W
NT
DP
Vi
Q
an
h
N
c
d
d
d
l
l
l
ld
rg
rab
fie
fie
fie
fie
so
te
L
t
i
P
P
P
P
b
P
L
la
bND
ND
ND
ND
ND
P
a
L
D
Forest and Savanna fuels
F
W
EF in ng TEQ/kg dwt
0
5
10
15
20
25
30
t
le
l
u
G
r
&
tw
N
DP
l
ab
ra
st
w
N
DP
b
la
rg
o
s
m
u
h
N
DP
b
La
ne
a
c
Agricultural Residues
C
e
an
fie
ld
TCDD isomers
PeCDD isomers
HxCDD isomers
HpCDD isomers
OCDD
TCDF isomers
PeCDF isomers
HxCDF isomers
HpCDF isomers
OCDF
Total CDD
Cane Wildfire Savanna Prescribed
1
19
4
16
1
9
3
6
2
21
6
9
11
15
10
9
79
17
51
41
4
11
25
17
0
3
0
1
0
2
0
0
1
1
0
0
2
1
0
0
93
82
74
82
Congener Profile for homologue groups
(by mass)
Congener
1,2,3,7,8-PeCDD
1,2,3,4,7,8-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
OCDD
OCDF
Total CDD
Cane
0
0
0
0
6
91
2
97
Wildfire
2
2
2
2
24
62
2
93
Savanna Prescribed
1
0
0
1
1
1
1
1
7
8
89
88
0
0
99
98
Congener profiles- toxic congeners by mass
2,3,7,8-TCDD
1,2,3,7,8-PeCDD
1,2,3,4,7,8-HxCDD
1,2,3,6,7,8-HxCDD
1,2,3,7,8,9-HxCDD
1,2,3,4,6,7,8-HpCDD
OCDD
2,3,7,8-TCDF
1,2,3,7,8-PeCDF
2,3,4,7,8-PeCDF
Total CDD
Cane
12
47
5
7
2
17
3
2
0
2
93
Wildfire Savanna Prescribed
5
16
7
54
49
40
6
4
5
7
6
8
5
9
7
7
7
8
0
1
1
1
1
4
1
0
1
9
4
12
83
93
76
Congener profiles – toxic congeners by toxicity
(TEQ)
Boorolite
1.7 Mha fire
area
Are wildfires really low emitters of PCDD/PCDF ?
(fg TEQ m )
-3
mass (µg m )
-3
0
May-02
200
400
600
800
0
5
10
15
20
Sep-02
Dec-02
non-sea-salt
potassium
mass
Mar-03
Fire event
Jun-03
0.0
Oct-03
0.4
0.8
1.2
1.6
non sea salt potassium
PCDD/PCDF concentration
PCDD/PCDF concentrations were at ambient background
concentrations
-3
TSP and NSS-K concentrations were very high from impact a dense
smoke plume BUT
The smoke plume from the NE fires impacted Boroolite in Jan/Feb
(µg m )
Compare field and laboratory
measurements
L-straw_1
L-straw_2
L-straw_3
L-straw_4
L-straw_5
L-straw_6
L-straw_7
L_sorghum_1
L_sorghum_3
25% 50% 75% 100%
% PCDD
F_Cane_1
F_Cane_2
WF_Vic_1
WF_Vic_2
S_NT_1
S_NT_2
S_NT_3
S_NT_4
PF_WA_1
PF_WA_2
PF_WA_5
L_cane_4
PF_WA_3
PF_Vic_1
PF_Vic_2
PF_Vic_3
PF_Vic_4
PF_Qld_1
PF_Qld_2
PF_WA_4
0%
ΣTCDDs
ΣTCDFs
PF_Qld_3
PF_Qld_4
0%
25%
% PCDD
50%
ΣTCDFs
ΣTCDDs
75%
100%
Field measurements
L_cane_1
L_cane_2
L_cane_3
litter_Vic1-1
litter_Vic1-2
litter_Vic1-3
litter_Vic2
litter_Qld
Laboratory tests
0
100
Mass emissions
300
pg (g C)-1
200
400
500
600
O
D
D
C
O
D
C
F
field, prescribed, n=13
field, cane, n=2
lab, sorghum, n=3
field, prescribed, n=13
field, wild, n=2
field, savanna, n=3
field, cane, n=2
lab, forest, n=5
lab, cane, n=3
lab, sorghum, n=3
lab, straw, n=7
PCDD/PCCF homologue mass profiles
D
D DD D D
C
D
D
-T PeC xC xCD CD DD DD F F
8
7 , - -H H x C C D D F F
3, ,7,8 7,8 ,8- 9-H -Hp O -TC eC CD CD DF F F
,
e
2 ,3 4, ,7 8, ,8
D
8
F
7, ,8-P 8-P -Hx HxC xC CD D DF F
2 ,3, ,6 ,7, ,7
,
,
3 ,7 7, ,8 8- -H Hx pC C D
1 ,2 ,3 ,3 ,6
,
2 ,3 4, ,7 7, ,8 9- -H p C
1 1,2 ,2 3,4
1 2,
,2 ,3, 3,4 ,6, 6,7 ,8, ,8 ,9-H O
1
,
2 ,2, ,3 4, ,7 6,7 ,8
1
1 1,2 ,3, 2,3 ,4, 4,7
2 1, ,3 3,
2 ,
1, 1,2
10
9
8
7
6
Toxic emissions
5
-1
pg Teq (g C)
4
3
2
1
0
field, prescribed, n=13
field, cane, n=2
lab, sorghum, n=3
field, prescribed, n=13
field, wild, n=2
field, savanna, n=3
field, cane, n=2
lab, forest, n=5
lab, cane, n=3
lab, sorghum, n=3
lab, straw, n=7
PCDD/PCCF toxic congener profiles
And we see PCDD/PCDF production
In furnaces, in slow combustion heaters and in open fire
places the combustion gases are retained at high
temperature in the flue.
• heterogeneous chemistry at 200 - 450oC.
• gas phase chemistry at 400 – 600oC
Dioxins form by
Mechanisms
Leaf litter
Burn
Temperature C
o
0
200
400
600
800
1000
0
20
Timecourse
of fire along
the bed
o
40
0
200
400
600
800
1000
0
Time (min)
Temperature ( C)
60
5
80
6
10
10
5
4
9
3
2
15
20
100
Leaf litter
Time (min)
1
7
Straw- fan assisted
25
Mass Emission PCDD+PCDF
(pg gC-1)
PCDD fraction (%)
0
0
200
400
400
Natural Ventilation
Forced ventilation
200
600
600
Mean Corridor Temperature (C)
0
20
40
60
80
100
0
500
1000
1500
2000
With fan-assisted
ventilation air flow
is more turbulent
and smoke
residence time is
shorter
This is very difficult to reproduce precisely therefore
laboratory tests should be interpreted with caution.
In the open, ambient air is entrained into the smoke
plume. It
rapidly dilutes and
rapidly cools
Who else has seen these patterns
0
1
2
3
4
5
Congener
All HW
HW-C low flow
HW-C2-low-dry
HW-C2-hi_dry
HW-NC-dry-lo
HW-C2-low-dry
HW-C1-low-dry
HW-C-hi-wet
HW-C-hi-dry
HW-oload
HW-C low flow
HW-C high flow
HW open fireplace
All Pine
MF
All HW
Mean 4 ng TEQ (g fuel)-1
Furans dominate
D
D DD DD D D
TC eC xC CD CD DD DD F F F
x
8 P
C C CD D D
F F F
7 , 8 - -H -H H x p
D
C
3, ,7, ,7,8 7,8 ,9- 8-H O ,8-T Pe eC xC CD CD DF DF F F
,
x x xC C
P
2 ,3 ,4 6, ,8 7,
,7 ,8 8- -H H
CD D
,
2
,
7
,3 3,7 ,7, 7,8 ,8- ,8-H 9-H -Hp Hp OC
1, ,2,3 2,3 ,3, 4,6
2
,
7
,
,
,
4
8
,
,
7
, ,4
,
1 1 1,2 ,3
9
,
8
2
1, 2,3 2,3 ,3,6 4,6 ,7, ,6,7 ,8,
2
7
,
1,
1, 1,2 2,3 ,2,3 3,4 ,4,
1 ,2,
,3
1 1,2
Emission (ng
-1
kg fuel )
6
7
8
9
10
(Gras et al. , 2002)
Slow combustion woodheaters
Gullett and Touati (2003) saw similar patterns for wheat and rice
Prange et al., (2002)
Dioxins in smoke, Combustion hood test
Hawaii Florida Florida Florida
I
II
II
leaves
Also Oregan and North
Carolina forest fuels
Gullett et al. (2006)
1
10
100
1000
Sugar Cane- burn hut
Emission (ng TEQ g C-1)
-
Fuel (residues, or formation chemistry)
– possible but not large
Soil (volatilisation or formation from pyrolysis of soil
carbon
- some evidence for this in recent work
Fractionation of smoke in the field (flaming
combustion smoke rises in the plume, smouldering
remains)
- Little evidence that this occurs to any
substantial extent
Sampling artifacts
- Most likely in our study
Why the differences
0
Height
200
400
600
Is it fuel? Is it soil?
Tropical Coastal
There is something in the location of
the fire.
Cluster analysis of field emission factors by PDCC/PDCF homologue groups
F-Cane-1
PF-Qld-4
PF-Qld-3
S-NT-4
PF-Qld-1
PF-Qld-2
F-Cane-2
WF-Vic-1
PF-WA-4
PF-WA-3
PF-WA-2
WF-Vic-2
S-NT-2
PF-WA-1
PF-Vic-2
PF-WA-5
PF-Vic-1
S-NT-3
PF-Vic-4
PF-Vic-3
-3
0
2
4
6
8
10
0
2.5%
0.2
97.5%
0.6
PCDD/F & PCB emission (kg TEQ)
0.4
0.8
Down from 70-1700
1
All sources
Revised Emissions
142g TEQ (30-490)
1994 – Revised EA (2002)
Frequency (10 )
216,173,000
3,505,000
10,588,000
3,492,000
6,044,000
653,300
Mass
(t)
Emission factor
ug TEQ/t
To air
To land
5
4
5
4
5
4
0.5
10
0.5
10
0.5
10
Emission
g
To air
To land
1081
865
18
14
53
42
2
35
3
60
0
7
1156
1023
1410
1300
82%
79%
Revised
To air
230
3
4.7
2.9
5
0.45
246.05
500
49%
Emissions to air reduce by a factor of 4, but still
comprise 50% of emissions (with a high range of
uncertainty)
Savanna and Temperate Grassland
Prescribed burning of forests
Wildfires
Agricultural residues- wheat
Agricultural residues- coarse grains
Agricultural residues- sugar
Total
All sources
2001 Estimates
UNEP toolkit
Fuel (32 pg)
Fuel
0.18
0.1
0.61
2
29
0.2
0.1
0.1
0.05
0.02
32.4
Homologue group
Total TCDD isomers
Total PeCDD isomers
Total HxCDD isomers
Total HpCDD isomers
OCDD
Total TCDF isomers
Total PeCDF isomers
Total HxCDF isomers
Total HpCDF isomers
OCDF
Total
Ash (34 pg)
Smoke (238 pg)
1.2
0.6
0.1
0.1
283.8
pg ( g fuel)
Smoke
10.3
15.5
26.9
40.4
182.2
6.4
-1
0.2
0.2
0.1
0.1
34.1
Ash
0.2
0.2
1.9
4.1
27.0
0.3
Mass Balance- Coastal savanna woodland
Residues
Smoke plumes are transported
hundreds to thousands of kilometers
Where the smoke contacts the
surface, there is surface deposition
Dispersion- where does it fall
Northing (km)
Northing (km)
100
500
600
700
800
900
300
400
500
600
700
800
900
Easting (km)
7900
200
7900
8200
8300
8400
8500
8600
8700
8000
100
Grid Centre
Jabiru
PM2.5 (kg ha-1), Aug. - Sept. 04
7900
8000
0
Darwin
400
8100
-200 -100
(c)
300
Easting (km)
200
8000
8100
8200
8300
8400
8500
8600
8700
8100
8200
8300
8400
8500
8600
8700
7900
0
8000
15
20
25
30
5
Grid Centre
Jabiru
8100
0
Darwin
PM2.5 (kg ha-1), April - May 04
10
-200 -100
(a)
8200
8300
8400
8500
8600
8700
-200 -100
(d)
-200 -100
(b)
100
0
100
Darwin
0
Darwin
300
400
300
400
Easting (km)
200
Grid Centre
Jabiru
500
600
700
800
500
600
700
800
900
900
PM2.5 (kg ha-1), Oct. - Nov. 04
Easting (km)
200
Grid Centre
Jabiru
PM2.5 (kg ha-1), June - July 04
PM2.5 Emissions (kg ha-1)
Northing (km)
Northing (km)
-200
8000
8200
8400
8600
-200
8000
8200
8400
8600
8800
8800
Northing (km)
Northing (km)
0
Darwin
0
Darwin
(a)
Jabiru
600
800
400
600
800
(c)
PM2.5 (µg m-3), Aug. - Sept. 04
Easting (km)
200
400
Easting (km)
200
Jabiru
PM2.5 (µg m-3), April - May 04
30
35
400
600
800
25
-200
400
Easting (km)
600
800
5
5
200
10
10 8200
0
15
15
8000
20
20 8400
25
30
Jabiru
(d) PM2.5 (µg m-3), Oct. - Nov. 04
Easting (km)
200
5
10
15
20
25
30
30 8600
Darwin
0
Jabiru
35
35
8800
-200
8000
Darwin
(b)
PM2.5 (µg m-3), June - July 04
35
5
10 8200
15
20 8400
25
8600
8800
PM2.5 Surface Concentrations
Northing (km)
Northing (km)
270
225
315
180
0
0
20
60
45
135
80
90
In the late fire season,
some is transported SW to
NW WA.
A large proportion is
transported into the Timor
Sea
100
Apr - May
Jun - Jul
Aug - Sep
Oct - Nov
2004
PM2.5 (Gg)
40
Total emitted 668 Gg
Where does it end up: PM2.5 leaving the
domain
Quantifying the emissions is only the start- to
understand impacts of dioxins we first need
to understand the dispersion and
deposition.
Slash burns from forest clearing
Peat fires in forests
other fuels and soils may have different emissions
Soil pyrolysis. What happens when there is
substantial soil heating e.g.
But that may not be universal –
The impact may be distant from the source.
Emissions to land require review
Long-range transport can be significant
careful measurement protocols are required
The emissions in Australian ecosystems are low
Measurement artifacts may be a problem
Conclusions/ Emerging Area