Isoprene emissions in Asia 1979-2012 :
variability and trends, effects of changes in
meteorology and land use,
and comparison to top-down estimates
Jenny Stavrakou, Jean-François Müller, Maite Bauwens
Isabelle De Smedt, Michel Van Roozendael
Belgian Institute for Space Aeronomy, Brussels
Alex Guenther
Atmospheric Chemistry Division, NCAR, Table
Mesa Drive, Boulder, US
Isoprene is important because…
 Most abundant VOC emitted by vegetation, global annual
emissions of ~500 TgC
 Highly reactive : with OH (< 1h), O3 (1-2 h) and NO3 (~1 d) but its
degradation in the atmosphere is still not completely elucidated 
 Leads to ozone formation in polluted conditions :
ISOP+OH RO2+HO2 (+NO)  NO2  O3
 Source of SOA  Health impact, negative climate forcing
 Key actor in chemistry-biosphere-climate interactions
Why focus on Asia?
 Two of world’s most rapidly expanding
economies and almost ½ of world population
 Dramatic changes in emissions :
o In China NOx emissions doubled in only 10 years, PM2.5
increase by 2.7 between 1990 and 2005
 Massive land use changes with huge environmental impacts,
forests  crops  urban, urbanized Beijing area doubled in 19851992!
 Massive deforestation  oil palm plantations in Southeast Asia,
Indonesia&Malaysia: 85-90% of the global oil palm production, oil
palm: large isoprene emitter
 Heavy aerosol loading likely impacts SR reaching the ground
(dimming)
How do these effects influence the emitted isoprene?
Model outline




Flux

dSdt
dz





LA
P
T
age
SM


canopy
Emission rate
in standard
conditions
Response
functions to
radiation and
T at leaf level
Dependence to
Leaf area
leaf age and
index
soil moisture
stress
• Latest database of MEGAN basal emission rates
• LAI : collection 5 8-day MODIS
• ERA-Interim ECMWF analyses for downward solar radiation, temperature,
wind, humidity, cloudiness & soil moisture in 4 layers
• Vertical profiles inside the canopy obtained from a 8-layer canopy model
(MOHYCAN, Müller et al., 2008)
Focus : 9 S-55 N, 60-150 E, 0.5°x0.5°, Step = 0.5 h, S0 = Base run
Strong interannual variability, highest isoprene flux in 1997-98, due
to exceptional El Nino, lowest emission in 1984&2008
Largest emission flux in 2007, lower emissions afterwards
Main drivers are : warming rates & radiation trends
Decadal T
trend (oC)
 Strongest warming trend : close
to Shanghai (0.4-0.6oC/decade)&
Northern provinces, in agreement
with Liu et al.(2004) analysis
 Warming rates < 0.4oC/decade in
Southern China
 Positive trend in radiation in
Southern China, negative in
Indonesia
Isoprene trend is stronger in NE
China, Northern Borneo (3%/year)
Annual %
PAR trend
Annual %
isoprene trend
Isoprene Flux Anomaly
 Asia : negative deviations related to WLN (1984-85), SLN (1988-1989), SLN
(1999), MLN (2007-2008), positive to MEN (1987), SEN (97-98), MEN (20092010), China : little correlation with El Niňo
Relation with Oceanic Niňo Index (ONI)
 r = 0.73, in agreement with past studies
 ONI is lagged to account for potentially complex influence of
ENSO on isoprene emissions
Land use changes
1979-2007 trend in cropland fraction
1979-2007 cropland fraction evolution
%/yr
Ramankutty
and Foley (1999)
 Rapid crop expansion in Southeast Asia, related to large-scale
deforestation, Indonesia (1.5%/yr), Malaysia (2.3%/yr)
 Crop abandonment in Central & South China
Fraction of oil palm plantations in 2010
Oil palm plantations
 250-m resolution land cover
map (Miettinen et al., 2012)
gridded onto 0.5 deg.
 Planted palm area expanded
extremely rapidly in1979-2010,
factor of 55 in Sarawak, 20 in
Indonesia and Sabah, 3 in
Peninsular Malaysia
Koh et al. (2011)
Miettinen et al. (2012)
http://bepi.mpob.gov.my
Measurement sites
Solar radiation changes
 ECMWF SR data fail to reproduce the
observations, changes in aerosol loading are
omitted
 ECMWF overestimates by 8-20% ground
observations of SR in China (Jia et al. 2013)
Annual surface solar radiation anomaly data
 Solar dimming in China
until 1990, most
pronounced in eastern
China, brightening after
1990 in SE China
 Significant brightening
in Japan over 1990-2002
 Over India strong solar
dimming after 1985
Simulation
S0
Description
standard
as S0, account for
S1
land use changes
S2
as S1, reduction of isoprene rate for tropical forests
by factor of 4.1 (Langford et al. 2010)
as S2, emissions from oil palms
S3
in Indonesia&Malaysia
as S3, effect of solar radiation
S4
changes and correction
factors from Jia et al. (2013)
 Best bottom-up
Isoprene emissions across S0-S4 in 2005 (mg isoprene/m2/s)
S0 (90 Tg)
S1 (71 Tg)
S2 (42 Tg)
S4 (40 Tg)
 Trend reinforced in S1 due to negative trend in cropland fraction in China
 Consider SR changes in S4  further trend enhancement due to
brightening in SE China, emissions have decreased because we have
adopted decreased SR fields
 Strong emission trend
in S0, due to 0.2o0.6oC/decade warming
rates & positive
radiation trend,
warming rate exceeds
by far the global 20th
century warming rate
(0.6oC, IPCC)
 Increasing trend in
cropland fraction in S1
 reduces trend
 x2-3 emission
reduction in S2
 Further trend
enhancement in S3,
due to the expansion
of oil palm plantations
Evaluation against top-down estimates
 HCHO is major intermediate product in the oxidation of
isoprene in the atmosphere
 Past studies demonstrated the capabilities of HCHO columns to
infer isoprene emissions
Use 2007-2012 GOME-2 HCHO, De Smedt et al., AMT, 2012,
http://www.temis.nl
Perform grid-based inversion with IMAGESv2 global CTM for 6
years using S4 bottom-up as a priori, x2.5 error on biogenic flux
1015 molec.cm-2
GOME-2 HCHO July 2010
A priori IMAGESv2 HCHO
Optimized columns
2008 a priori isoprene emission
Emission change (optimized-prior)
1010 molec. cm-2 s-1
 Small changes wrt the prior, by
up to 30% higher emission in SE
China, by up to 30% lower
emission in Borneo
 Satellite data support the
strong reduction of emission
rate for tropical forests in
Indonesia and Malaysia
Tg/yr
Conclusions
 Best bottom-up inventory has lower emissions by factor of 2
compared to MEGANv2  this enhances the relative importance
of anthropogenic emissions to the total VOC budget !
 Lower emissions
o due to drastic emission rate reduction in tropical forests
 Need for additional measuments
o due to more extensive cropland and lower solar radiation
over China compared to ECMWF
 High isoprene emission rate from oil palms in combination with
rapid oil palm expansion causes higher trend over Indonesia and
Malaysia
 Top-down estimates confirm lower emission rate for tropical
forests & corroborate the decreasing trend over China due to the
cooling epidode since 2007