black-carbon absorption enhancement in the atmosphere ... · evening traffic, wood burning and...
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SUPPLEMENTARY INFORMATIONDOI: 10.1038/NGEO2901
NATURE GEOSCIENCE | www.nature.com/naturegeoscience 1
Supplementary Information for
Black carbon absorption enhancement in the atmosphere
determined by particle mixing state
Dantong Liu1, James Whitehead1, M. Rami Alfarra1,2, Ernesto Reyes-Villegas1, Dominick V.
Spracklen3, Carly L. Reddington3, Shaofei Kong1,4,5, Paul I. Williams1,2, Yu-Chieh Ting1,
Sophie Haslett1, Jonathan W. Taylor1, Michael J. Flynn1, William T. Morgan1, Gordon
McFiggans1, Hugh Coe1 and James D. Allan1,2
1School of Earth, Atmospheric & Environmental Sciences, University of Manchester, UK
2National Centre for Atmospheric Science, UK 3Institute for Climate and Atmospheric Science, School of Earth and Environment, University of
Leeds, Leeds, UK 4School of Atmospheric Physics, Nanjing University of Information Science & Technology, China
5now at School of Environmental Studies, China University of Geosciences (Wuhan), China
Black-carbon absorption enhancement in theatmosphere determined by particle mixing state
S1. Summary of conducted experiments
Fig. 1. A schematic diagram of the set up for the diesel engine emissions experiments.
Table 1. A summary of black carbon particles sampled in this study.
Soot Sources Sampling
conditions Details Abbreviation
Light duty diesel engine - EURO 4 Laboratory Chamber Cold idle condition without
warm up or engine load CI
Light duty diesel engine - EURO 4 Laboratory Chamber
Normal running condition
with 2000rpm, 30% load and
10 minutes warm up
NR
Light duty diesel engine - EURO 4 Laboratory Chamber Thermodenuded normal
running condition NR-TD
Morning Rush hour traffic Ambient 29/10-10/11, 2014 TR
Evening traffic, wood burning Ambient 29/10-10/11, 2014 SF
Evening traffic, wood burning and bonfire Ambient 18:30, 05/11- 03:30, 06/11 BN
S2. Source attribution of particles during the ambient experiment
Fig. 2. Time series of AMS and SP2 data and source attribution from the ambient measurements. A)
the aerosol loadings during the entire ambient experiment; B) The mass spectra of the derived ME-2
factors; C) The diurnal variation of aerosol loadings and ME-2 factors excluding the Bonfire event; D)
the aerosol loadings during Bonfire night; the whiskers, boxes, the line and cross in represent the 10%
(90%), 25% (75%) percentiles, median and mean values for each component.
0.80
0.75
0.70
0.65
0.60
0.55
0.50
29/10/2014 31/10/2014 02/11/2014 04/11/2014 06/11/2014 08/11/2014 10/11/2014
date and time
70
60
50
40
30
20
10
0
Aero
sol m
ass loadin
gs (
µg m
-3)
Bonfire Event OM BC SO4
NO3
A
0.12
0.08
0.04
0.00
1009080706050403020m/z
0.12
0.08
0.04
0.000.100.080.060.040.020.000.100.080.060.040.020.000.250.200.150.100.050.00
BBOA
Re
lative
In
ten
sity
HOA
COA
SVOOA
LVOOA
B
0.70
0.65
0.60
0.55
0.50
20151050Hours of day
1.0
0.8
0.6
0.4
0.2
0.0
4
3
2
1
0
Aero
sol m
ass load
ings (
µg
m-3
) 50
40
30
20
10
0Aero
sol m
ass loa
din
gs (
µg m
-3)
3210BC OM SO4 NO3
non-Bonfire Bonfire Event BC OM NO3
SO4
HOA SFOA COA SVOOA LVOOA
TR SF BN
C D
S3. The calibration and detection efficiency of the SP2 instrument
Fig. 3. The SP2 incandescence response to the particle mass for both thermodenuded NR and Cold
Idle BC.
Fig. 4. The SP2 detection efficiency as a function of rBC mass and Dve for the laboratory diesel in
normal running condition. The arrows show the change when increasing SP2 laser power.
800
600
400
200
0
N (
cm
-3)
4 5 6 7 8 9
0.12 3 4 5 6 7 8 9
12
CPMA mass (fg)
1.0
0.8
0.6
0.4
0.2
0.0
SP
2/C
PC
35 40 50 60 75 100 130
rBC Dve (nm)
CPC SP2
increase SP2 laser current from 2600 to 3000mA
S4. The density and shape of diesel soot particles
Fig. 5. The effective density as a function of particle mass for laboratory diesel soot particles
generated under different conditions.
1.4
1.2
1.0
0.8
0.6
0.4
Eff
ective
de
nsity (
g c
m-3
)
9
0.12 3 4 5 6 7 8 9
12 3 4 5 6 7 8 9
10Particle mass (fg)
Normal Running (NR) Cold Idle NR with TD Cold Idle with TD
S5. The optical models used to estimate the scattering properties of black carbon
particles
Fig. 6. A schematic of the models used to estimate the optical properties of the black carbon particles.
For internally mixed black carbon particles, two different approaches for computing the effective
refractive index (m) of the mixture are considered.
𝑚 = √𝜀 , (S1)
where ε denotes the electric permittivity. The Maxwell-Garnett mixing rule1 assumes that an inclusion
with a permittivity ε1 and volume fraction f1 is embedded in a host matrix of permittivity ε2. The
resulting effective permittivity εeff is obtained from
f1ε1−ε2
ε1+2ε2=
εeff−ε2
εeff+2ε2 , (S2)
The Bruggemann mixing rule 2 assumes the two materials are embedded in a host medium with an εeff
given by
f1ε1−εeff
ε1+2εeff+ (1 − f1)
ε2−εeff
ε2+2εeff= 0 , (S3)
The Bruggemann rule treats the two materials more symmetrically.
The RDG approximation used in this study assumes a monomer diameter Ds=50nm and assumes the
coating volume is evenly distributed on each monomer with the same coating content 3. The number
of monomers Ns is given by
Ns=(Dc/Ds)3 , (S4)
Where Dc is the diameter of the BC core.
The resulting integrated scattering cross section is given by
SSca=Ns2×Ss,Sca , (S5)
Where Ss,Sca is the scattering cross section of the monomer and Ssca is that of the entire particle.
S6. The transition in optical behaviour resulting from changes in mixing ratio, MR, as a
function of particle mass
Fig. 7. The measured and modelled optical properties as a function of mass ratio as presented in Fig. 1
but for different particle masses. The grey line on each plot shows the ratio between the externally
mixed model prediction of the scattering cross section compared to that from the core-shell model
(Sext/Sc-s). The values in brackets denote the range of non-BC densities used to calculate the
uncertainty in each data set represented by the bars in each figure. The scattering signal measured at
1fg may be biased towards smaller MrBC due to the reduced instrument S/N ratio for small particles.
0.70
0.65
0.60
0.55
0.50
0.1 1 10MR
2.0
1.5
1.0
0.5
0.0
S/S
c-s
Diesel NR(1.04) NR TD(1.04) Cold Idle(1.04)
Ambient TR (1.1) SF (1-1.2) BN (1-1.2)
Model only
Sext/Sc-s
Particle mass 1fg
Externally mixed
Transition
Internally mixed
Unknown
0.70
0.65
0.60
0.55
0.50
0.1 1 10MR
2.0
1.5
1.0
0.5
0.0
S/S
s-c
Diesel NR (1.04) NR TD (1.04) Cold Idle (0.9-1.1)
Model only Sext/Sc-s
Particle mass 3fg
Internally mixedExternally mixed
Transition Unknown
0.70
0.65
0.60
0.55
0.50
0.1 1 10MR
2.0
1.5
1.0
0.5
0.0
S/S
c-s
Diesel NR (1.04) NR TD (1.04) Cold Idle (0.9-1.1)
Ambient TR (1) SF (1-1.2) BN (1-1.2)
Model only
Sext/Sc-s
Particle mass 5fg
Internally mixedExternally mixed
Transition Unknown
0.70
0.65
0.60
0.55
0.50
0.1 1 10MR
2.0
1.5
1.0
0.5
0.0
S/S
c-s
Particle mass 10fg
Ambient TR(1.1) SF(1-1.2) BN(1-1.2)
Model Only
Sext/Sc-s
Internally mixedExternally mixed
Transition Unknown
MR
Normal
Running
Cold Idle TR SF BN Average
MP=1fg
Transition Start 0.28 0.26 0.31 0.30 0.29 0.3
Transition End Transition* 2.82 transition 2.51 2.63 2.7
2fg
Transition Start external** transition external 1.48 1.44 1.5
Transition End external 4.5 external 2.86 2.90 3.3
3fg
Transition Start external 1.36
Transition End external 4.15
5fg
Transition Start transition transition 0.56 0.48 0.35 0.5
Transition End transition 3.23 transition 2.24 2.55 2.7
10fg
Transition Start 0.46 0.42 internal† 0.4
Transition End transition 0.88 internal 0.9
*means there is no data beyond the transition region
**means there is no data beyond region characterised by the external mixing model best representing the data
†means all of the data is within internal mixing model regime
Table 2. Threshold values of MR characterising the transition in the optical properties of black carbon
at various particle masses. The BC calculated using the hybrid model is considered to be effectively
externally or internally mixed when either the external mixing or core-shell model can represent the
measured scattering to within 20%.
S7. SP2 measured scattering enhancement (Esca) as a function of MR
Fig. 8. The influence of MR on the scattering enhancement (Esca) using the Mie-core-shell and external
mixing approaches for a range of different particle masses and experimental conditions. A) Esca at
1064 nm at different particle masses derived from Mie-core-shell and external mixing model. B) SP2
measured Esca under a variety of environments mapped in the model frame at particle mass 2fg; the
grey bar shows the transition regime. The top panel shows the internal mixing fraction, with the dash
line showing the lineal fitting against MR.
S8. Direct measurements of absorption enhancement
Laboratory-generated diesel
Fig. 9. Results from cold idle laboratory diesel. A) BC properties since engine emission injection into
the aerosol chamber, from top to bottom: rBC mass, rBC core mass median diameter, MR,bulk and
absorption coefficient (Babs) measured by PASS-3, the right axis is the internal mixing faction
assuming threshold MR at 1.5 and 3; B) measured MAC and Mie calculated uncoated rBC MAC;
bottom panel is the average Eabs at three wavelengths calculated as the ratio between measured MAC
and Mie calculated MAC of uncoated rBC core, with the error bar denoting the standard deviation.
Ambient experiment
Fig. 10. Absorption measurements in the ambient atmosphere. A) An example of measured absorption
coefficient (Babs) switching between direct and heated line in 30mins during bonfire night. The
markers show the average within 30mins. B) Babs from direct line correlated with the heated line. Eabs
is obtained by ODR.
500
400
300
200
100
0
Ba
bs (
Mm
-1)
12:0005/11/2014
18:00 00:0006/11/2014
06:00
UTC time
PASS measured Babs Heated line Direct line
A
30
25
20
15
10
5
0
Ba
bs D
ire
ct
(Mm
-1)
3020100
Babs Heated (Mm-1
)
Slope=1.02±0.03TR
B 40
30
20
10
0
Ba
bs D
ire
ct
(Mm
-1)
403020100
Babs Heated (Mm-1
)
Slope=1.16±0.03
SF
300
250
200
150
100
50
0
Ba
bs D
ire
ct
(Mm
-1)
250200150100500
Babs Heated (Mm-1
)
Slope=1.23±0.07
BN
Table 3. A summary of measured and calculated Eabs at 532nm for all of the sources in this study. The
error in the hybrid model is the uncertainty when varying the threshold MR spanning over the
transition regime. The error for ambient measurement is the error in the slope derived from the ODR
fitting. The other errors denote standard deviations with respect to the average. The values in brackets
are the calculated Eabs when applying different transition regimes at different particle masses.
Sources Eabs
Measurement
Eabs by
Hybrid model
Eabs by
Mie-core-shell
MR,bulk Internal mixing
fraction (MR>2)
Laboratory diesel
NR 1.01±0.02 1.14±0.11 1.31±0.04 1.13±0.03 0.25±0.02
CI start 1.02±0.03 1.03±0.02 1.23±0.03 1.10±0.06 0.14±0.03
CI middle 1.10±0.08 1.16±0.04 1.40±0.02 2.70±0.21 0.42±0.08
CI end 1.30±0.06 1.27±0.07 1.54±0.03 4.38±0.07 0.58±0.02
Ambient
TR 1.02±0.03 1.03±0.02 1.22±0.06 0.38±0.13 0.07±0.05
SF 1.16±0.03 1.19±0.04(1.21) 1.36±0.05 0.59±0.11 0.18±0.08
BN 1.23±0.07 1.25±0.05(1.32) 1.46±0.03 1.08±0.17 0.38±0.11
S9. Summary of previous field experiments used as data sources in this work
The CalNEx-LA experiment took place from 15 May–15 June 2010. The site was located on the
Caltech campus in Pasadena, CA, USA. The site was influenced by advected plumes from the source-
rich western LA basin as well as fresher more local emissions 4. The main source of black carbon in
the region is thought to be diesel emissions. Biomass burning did not strongly influence the site
during the measurement period.
The Weybourne experiment was conducted at the Weybourne Atmospheric Observatory (WAO)
(52.9504◦ N, 1.1219◦ E) from June–July, 20115. The WAO is located near the North Norfolk coast in
the UK and represents a rural environment remote from major populated or industrial areas. This site
routinely experiences polluted plumes from the UK and mainland Europe.
The Clean Air for London (ClearfLo) winter campaign was conducted from 11 January to 8 February,
2012 6. The experimental site was located in the grounds of a school in North Kensington, London,
which is representative of a typical urban background environment. The London urban environment
in winter is significantly influenced by solid fuel burning sources, such as wood burning for
residential heating as well as from traffic.
The South American Biomass Burning Analysis (SAMBBA) campaign was carried out in Brazil in
September and October 20127. The aircraft based study focussed on characterising smoke from
biomass burning in regions remote from other black carbon emission sources.
S10. Black Carbon and Organic Carbon inventories used in GLOMAP
We use the MACCity emissions inventory to represent the anthropogenic emissions of black carbon
and organic carbon 8, which provides annually-varying emissions for the period 1979–2010. Fire
emissions of black carbon and organic carbon were taken from the Global Fire Emissions Database
(GFED) version 3 emission inventory (GFED3 9). GFED3 provides yearly-varying, monthly-mean
fire emissions of aerosol and gas-phase species from 1997 to 2011 at 0.5º×0.5º resolution. The global
emissions are derived using estimates of burnt area, active fire detections, and plant productivity from
the Moderate resolution Imaging Spectroradiometer (MODIS) satellite (post year 2000) combined
with estimates of fuel loads and combustion completeness for each monthly time step from the
Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model.
Fig. 11. The global BC and OC emissions for fossil fuel, biofuel and biomass burning.
S11. The MR for different sources used in GLOMAP
The MR used in GLOMAP for fossil fuel, biofuel and open biomass burning, as derived from BC and
OC inventories.
Fig. 12. The global annually averaged MR for fossil fuel, biofuel and open biomass burning.
-50
0
50
La
titu
de
(De
gº)
-100 0 100Longitude(Degº)
10
8
6
4
2
MR
bio
fue
l
-50
0
50
La
titu
de
(De
gº)
-100 0 100
Longitude(Degº)
10
8
6
4
2
MR
fossil fu
el
-50
0
50
Latitu
de (
Deg º
)
-150 -100 -50 0 50 100 150Longitude (Deg º)
10
8
6
4
2
MR
open b
iom
ass b
urn
ing
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