biomass burning in southeast asia: science questions and proposed study approaches

Biomass Burning in Southeast Asia: Science questions and proposed study approaches

Bob Yokelson, University of Montana

Thanks to: S. Akagi, P. Artaxo, D. Blake, I. Burling, P. Buseck, T. Campos, T. Christian, T. Clarke, H. Coe, J. Craven, J. Crounse, P. DeCarlo, J. de Gouw, A. Fried, J. Gilman, D.

Griffith, A. Guenther, P. Hobbs, R. Holzinger, J. Jimenez, T. Karl, W. Kuster, S. Kreidenweis, A. Laskin, L. Mauldin, G. McMeeking, J. Reid, J. Roberts, J. Seinfeld, I.

Simpson, C. Stockwell, J. Taylor, P. Veres, C. Warneke, A. Weinheimer, P. Wennberg, C. Wiedinmyer, and many others, plus NSF, DoD, JFSP, USFS, DOE, NASA, EPA,+

SEAC4RS Science Team Meeting

Feb 23, 2012, Boulder, CO

Global Emissions Tg per year

Source Total C gas-phase NMOC Primary PM    VOC SVOC BC OC

FF (Total) 7000 200 3 2

BB (Total) 4600 (6300) 200 (365) 200 (365) 5 (5.7) 32 (53)savanna 1600cooking 1500forest 1000crop 500peat El-Nino 1700 165 165 .68 21

Biogenic 1000 800 200    

Sources: Bond et al 2004, Forster et al 2007, Akagi et al., 2011.

Fires are a huge source and atmospheric chemistry is done by putting initial emissions in a chemical transport model.We have problems with SE Asia:1. There have never been any emissions measurements

on real fires in SE Asia. In a recent lab experiment with organic soils (NOAA, Stockwell), ~28% of C emitted as NMOC, normally 1-2 % for other types of BB (DC8 package).

Heritage: NASA/NSF Missions Have Produced Bulk of EF.SCAR-B/LBA-TROFFE BrazilSAFARI 2000 AfricaMILAGRO Mexico-NH TropicsARCTAS Boreal ForestSEAC4RS SE Asia?

2. There have never been any SE Asia plume aging measurements AND aging is extremely fast and variable.

3. Clouds and smoke are two of the largest and least understood climate forcers on Earth and they are intimately mixed in SE Asia. Smoke impacts on clouds are exceedingly complex. There are almost no data on the impact of clouds on smoke chemistry.

What we might see in SEAC4RS

In addition to completing the “big three of biomass burning” we have an opportunity to learn how smoke plumes evolve. Based on limited available evidence, the evolution of aerosols and ozone in biomass burning plumes seems to differ in “warm-wet” vs “cool-dry” plumes and mixing may spur rapid evolution.

MILAGRO: Warm-wet plume (Yokelson et al., 2009)

0.0 0.5 1.0 1.5 2.00.00

2.00

4.00

6.00

8.00

10.00

12.00

1.4

1.6

1.8

2.0

2.2

2.4

OA/CO

OA/OC

Time since emission (h)

DOA/DCO (ma

ss)

DO

A/D

OC

(m

ass)

DeCarlo, Jimenez, Campos, data

Cool-dry plume (Akagi et al., 2012)

Craven, Seinfeld, data

MILAGRO: Warm-wet plume (Yokelson et al., 2009)

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20.70

0.75

0.80

0.85

0.90

0.95

1.00

Time since emission (h)

Sing

le S

catte

ring

Alb

edo

Clarke, Shinozuka, data

0 1 2 3 4 50.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

Time since emission (h)

Frac

tion

"thi

ckly

coa

ted"

BC

Taylor, McMeeking, Coe, data

Cool-dry plume (Akagi et al., 2012)

Warm-wet versus cool-dry: Ozone production

0 1 2 3 4 50.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40Akagi et al 2012

Linear (Akagi et al 2012)

Initial O3

Yokelson et al 2009

Time since emission (h)

ΔO

3/Δ

CO

Weinheimer, Campos, data

Cool-moist mixing with urban: Ozone production

FF/BB mix also in:ARCTAS-CARBLee et al.: 2008

0 1 2 3 4 5

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

Akagi et al 2012

Linear (Akagi et al 2012)

Initial O3

Yokelson et al 2009

South Carolina Prelim

Time since emission (h)

ΔO

3/Δ

CO

Condition or Metric

cool-dry warm-wet SC SEAC4RS

Water % 0.2 1.9 0.6 1.8-2.8

Solar Zenith

50 20 50 15-20

OH 5E6 1E7 TBD ?

Temp 12-15 15-20 10-14 25-35

Mixing w/other

N N Y we think Y often

OA/POA .8 (4 h) 2.6 (1.4 h) TBD ?

DO3/DCO 0.1 (4 h) 0.35 (1.7 h) .3-.9 (1.7h) ?

Where will SE Asian plumes fit in this spectrum?

How do we get more info on the substantial amount of rapid initial change?

Fire are very variable within a fire AND fire to fire so be careful of this scenario…..

0.0 0.2 0.4 0.6 0.8 1.0 1.202468

101214161820

Plume 1Pume 2

Plume age in lifetimes of “X”

DX/DCO (mm

ol/mol

)Emission Ratio (ER) DX/DCO = 10 ± 8 (2s)

Lefer et al., 1994 JGR

Lifetime @ measured OHBenzene 9 d

Toluene 2 d

Ethane 47 d

Propane 11 d

Quantitative plume evolution measurements. (Akagi et al., 2012)

Species EF (g/kg burned) After 4 h agingCO2 1697.0 " CO 72.68 " MCE 0.9369 " Methane 3.67 " Ethene 0.78 0.39Propene 0.45 0.0 2Acetic Acid 1.59 5.56Formic Acid 0.06 0.69Formaldehyde 1.29 1.87 Methanol 1.59 " HCN 0.90 " Acetylene 0.11 " HONO 0.70 ~0.01NO 0.90 ~0.01NO2 2.66 ~0.1NH3 1.68 0.84PM2.5 8.61 ~6.9? Ozone 0.00 16.20PAN 0.00 2.10

Need an approach that’s practical for the DC8 and GV

The single long-axis sample “time-machine” flight plan works sometime. DC8, GV alt.

(DX/DY)I (DX/DY)F

Windspeed 10 mph Aircraft speed 250 mphCheck e.g. DBC/DCO

0 0.2 0.4 0.6 0.8 1 1.2 1.40.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

BC/COinitial value BC/COJNO2

Time since emission (h)

BC

/CO

(mg/

sm3/

ppb)

or J

NO

2 (1

/s)

STARTS1 & S2

A

B

C

S3 END OR REPEAT

Sample other targets or swap airspace

with GV if small fire for time “X”

Pseudo-lagrangian can be as simple as breaking off to another target (ships, megacities, another fire, etc) and then coming back to projected downwind location later.

F

E

D

A + X

B + X

C + X

This could work for convective outflow too!

Finding fires

Harder and easier then some may think.

Case Study from SAFARI 2000: A prescribed fire seen from the flagship NASA aircraft was not seen by MAS on ER-2 or by TERRA as a thermal anomaly.

MILAGRO: Out of 56 fires found visually – only 10 were hotspots. Orbit gaps, clouds, and timing.

However a simple strategy works. If there were hotspots today & fair weather is forecast tomorrow go look.

0 1 2 3 4 5 6 7 80

1

2

3

4

5MILAGRO Early Dry Season: 14 flights

Number fires found in ~3.5 h flight

Num

ber o

f flig

hts

YES WE CAN FIND FIRES! THAT ALLOWS ACTUAL QUANTITATIVE AGES!

Back trajectories and hot-spots method.

48 38 36 31 28 26 22 18 11 2 HOURS UPWIND

http://geonetwork4.fao.org/firemap/ or http://firefly.geog.umd.edu/firemap/ or http://lance.nasa.gov/data-products/modis-products/ & Ed Hyer

20090923 1400 LT Tagged BB-CO at 2 km Patrick Kim, Harvard

20090918 1400 LT Tagged BB-CO at 2 km Patrick Kim, Harvard

Sawa et al., 1999 GRL

FLAMBE for SEAC4RS

Edward Hyer20 February 2012

Characteristics of FLAMBE-SEAC4RSBasic Characteristics

• Spatial resolution of satellite inputs (~5km)

• Hourly temporal resolution• Latency: Incorporation of fire

observations within 6 hours• Fuels description using new LC

map from National University of Singapore– Based on 2010 observations– Includes tree plantations

• Improved trace gas partitioning information– Yokelson

Advanced Characteristics• Full coverage correction, and angular

correction of MODIS• Diurnal cycle from geostationary

observations• Tagging of fire regimes, vegetation

types• Uncertainty estimates usable for

ensemble generation• “probable fire under cloud”

combining cloud data with persistence forecast

• Forecast emissions fields based on empirical relations between weather and fire activity

Timeline of FLAMBE-SEAC4RS

• 1 May: Generation of preliminary near-real-time product, and draft documentation available

• 1 June: Reprocessing of 10/2010 to present complete (MTSAT-2 era)

• 1 July: FLAMBE-SEAC4RS finalized with feedback from modelers, final documentation released

• 21 July: October 2010-present processed with final version

• 21 September: Reprocessing from 9/2008 to 10/2010 complete (MTSAT-1R era)

Idealized search cal/val procedure: will likely have to do one dipping and one off-shore.

1000

2000

3000

4000

0 0.01 0.02 0.03 0.04 0.05 0.06Ratio of Compounds to CO

Alti

tude

(msl)

HCHOCH3OH

NH3 HAc NO2

NO

Courtesy, Paulo Artaxo

All (rare) tropical O3 formation for testing model mechanism: 2005, O3 works if NMOC increased ~3 or HONO added

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0 20 40 60 80 100Smoke Age (minutes)

Africa Timbavati Fire

Africa Beira Fire

Africa Miombo Fire

Simulated TimbavatidO3/dCO

Yucatan C-130 Fire 3

DO

3 / D

CO

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0 20 40 60 80 100Smoke Age (minutes)

Africa Timbavati Fire

Africa Beira Fire

Africa Miombo Fire

Simulated TimbavatidO3/dCO

Yucatan C-130 Fire 3

DO

3 / D

CO

Headlines

Experts predict thousands to die as smog spreadsAgence France-Presse (Paris)Sept 26, 1997HONG KONG – Thousands of people will be killed by the smog blanketing Southeast Asia, experts in Hong Kong warned yesterday, adding some regions could face famine as crops are devastated and livestock chokes to death.“It will destroy the ecology of the region,” said Fang Ming, senior climatology programme manager at Hong Kong University of Science and Technology’s research centre.“Insects, animals, and vegetation alike will be largely destroyed,” he said.