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Isoprene emissions in Asia 1979-2012 : variability and trends, effects of changes in meteorology and land use, and comparison to top-down estimates Jenny.

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Presentation on theme: "Isoprene emissions in Asia 1979-2012 : variability and trends, effects of changes in meteorology and land use, and comparison to top-down estimates Jenny."— Presentation transcript:

1 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

2 Isoprene is important because… Most abundant VOC emitted by vegetation, global annual emissions of ~500 TgC Highly reactive : with OH (< 1h), O 3 (1-2 h) and NO 3 (~1 d) but its degradation in the atmosphere is still not completely elucidated  Leads to ozone formation in polluted conditions : ISOP+OH  RO2+HO 2 (+NO)  NO 2  O 3 Source of SOA  Health impact, negative climate forcing Key actor in chemistry-biosphere-climate interactions

3 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, PM 2.5 increase by 2.7 between 1990 and 2005 Massive land use changes with huge environmental impacts, forests  crops  urban, urbanized Beijing area doubled in 1985- 1992! 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?

4 Model outline Emission rate in standard conditions Response functions to radiation and T at leaf level Dependence to leaf age and soil moisture stress Leaf area index 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)

5 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

6 Main drivers are : warming rates & radiation trends

7 Annual % isoprene trend Decadal T trend ( o C) Strongest warming trend : close to Shanghai (0.4-0.6 o C/decade)& Northern provinces, in agreement with Liu et al.(2004) analysis Warming rates < 0.4 o C/decade in Southern China Positive trend in radiation in Southern China, negative in Indonesia Annual % PAR trend Isoprene trend is stronger in NE China, Northern Borneo (3%/year)

8 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 (2009- 2010), China : little correlation with El Niňo

9 Relation with Oceanic Niňo Index (ONI)  r = 0.73  r = 0.73, in agreement with past studies  ONI is lagged to account for potentially complex influence of ENSO on isoprene emissions

10 Land use changes 1979-2007 trend in cropland fraction1979-2007 cropland fraction evolution 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 %/yr

11 Oil palm plantations Fraction of oil palm plantations in 2010 Koh et al. (2011) Miettinen et al. (2012)  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

12 Solar radiation changes Annual surface solar radiation anomaly data  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) Measurement sites  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

13 SimulationDescription S0standard S1 as S0, account for land use changes S2 as S1, reduction of isoprene rate for tropical forests by factor of 4.1 (Langford et al. 2010) S3 as S2, emissions from oil palms in Indonesia&Malaysia S4 as S3, effect of solar radiation changes and correction factors from Jia et al. (2013)  Best bottom-up

14 Isoprene emissions across S0-S4 in 2005 (mg isoprene/m 2 /s) S0 (90 Tg) S1 (71 Tg) S2 (42 Tg) S4 (40 Tg)

15  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

16  Strong emission trend in S0, due to 0.2 o - 0.6 o C/decade warming rates & positive radiation trend, warming rate exceeds by far the global 20 th century warming rate (0.6 o C, 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

17 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 GOME-2 HCHO July 2010A priori IMAGESv2 HCHOOptimized columns 10 15 -2 Use 2007-2012 GOME-2 HCHO, De Smedt et al., AMT, 2012, Perform grid-based inversion with IMAGESv2 global CTM for 6 years using S4 bottom-up as a priori, x2.5 error on biogenic flux

18 10 10 molec. cm -2 s -1 2008 a priori isoprene emission Emission change (optimized-prior)  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

19 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

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