Javascript must be enabled to continue!
Isoprene and monoterpene emissions in Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric concentration observations
View through CrossRef
Abstract. One of the key challenges in atmospheric chemistry is to reduce the uncertainty of biogenic emission estimates from vegetation to the atmosphere. In Australia, eucalypt trees are a primary source of biogenic emissions, but their contribution to Australian air sheds is poorly quantified. CSIRO developed the Australian Biogenic Canopy and Grass Emissions Model (ABCGEM) 15 years ago to investigate this issue. Previously unpublished, ABCGEM is applied as an inline biogenic emissions inventory to model volatile organic compounds in the air shed overlaying Sydney, Australia. For comparison, biogenic emissions are calculated by the well-accepted Model of Emissions of Gases and Aerosols from Nature (MEGAN) for the same region using the same meteorological inputs. The two models use independent inputs of Leaf Area Index (LAI), Plant Functional Type (PFT) and emission factors. We find that LAI, a proxy for leaf biomass, has a small role in spatial, temporal and inter-model biogenic emission variability, particularly in urban areas for ABCGEM. After removing LAI as the source of the differences, we found large differences in the emission activity function for monoterpenes. In MEGAN monoterpenes are partially light dependent, reducing their dependence on temperature. In ABCGEM monoterpenes are not light dependent, meaning they continue to be emitted at high rates during hot summer days, and at night. Comparison with observations suggests that monoterpenes emitted from Australian vegetation may not be as light dependent as vegetation globally, as assumed in MEGAN. The simplified ABCGEM model is comparable with the state-of-the-art MEGAN model when measured by normalised mean bias values between the models and observed atmospheric isoprene and monoterpene observations. Observed ratios of isoprene to monoterpene carbon in south east Australia are approximately unity. ABCGEM replicates this ratio for both emission rates and predicted concentrations, while MEGAN over-estimates by a factor of 4. This suggests the correct balance between isoprene and monoterpene emissions in ABCGEM, but their magnitudes need further assessment. We estimate the uncertainty in Australian BVOC emissions to be a factor of 2 for isoprene and 3 for monoterpenes. This study identifies the uncertainties associated with the ABCGEM emission estimates, and data requirements necessary to improve isoprene and monoterpene emissions estimates for the application of both ABCGEM and MEGAN in Australia.
Title: Isoprene and monoterpene emissions in Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric concentration observations
Description:
Abstract.
One of the key challenges in atmospheric chemistry is to reduce the uncertainty of biogenic emission estimates from vegetation to the atmosphere.
In Australia, eucalypt trees are a primary source of biogenic emissions, but their contribution to Australian air sheds is poorly quantified.
CSIRO developed the Australian Biogenic Canopy and Grass Emissions Model (ABCGEM) 15 years ago to investigate this issue.
Previously unpublished, ABCGEM is applied as an inline biogenic emissions inventory to model volatile organic compounds in the air shed overlaying Sydney, Australia.
For comparison, biogenic emissions are calculated by the well-accepted Model of Emissions of Gases and Aerosols from Nature (MEGAN) for the same region using the same meteorological inputs.
The two models use independent inputs of Leaf Area Index (LAI), Plant Functional Type (PFT) and emission factors.
We find that LAI, a proxy for leaf biomass, has a small role in spatial, temporal and inter-model biogenic emission variability, particularly in urban areas for ABCGEM.
After removing LAI as the source of the differences, we found large differences in the emission activity function for monoterpenes.
In MEGAN monoterpenes are partially light dependent, reducing their dependence on temperature.
In ABCGEM monoterpenes are not light dependent, meaning they continue to be emitted at high rates during hot summer days, and at night.
Comparison with observations suggests that monoterpenes emitted from Australian vegetation may not be as light dependent as vegetation globally, as assumed in MEGAN.
The simplified ABCGEM model is comparable with the state-of-the-art MEGAN model when measured by normalised mean bias values between the models and observed atmospheric isoprene and monoterpene observations.
Observed ratios of isoprene to monoterpene carbon in south east Australia are approximately unity.
ABCGEM replicates this ratio for both emission rates and predicted concentrations, while MEGAN over-estimates by a factor of 4.
This suggests the correct balance between isoprene and monoterpene emissions in ABCGEM, but their magnitudes need further assessment.
We estimate the uncertainty in Australian BVOC emissions to be a factor of 2 for isoprene and 3 for monoterpenes.
This study identifies the uncertainties associated with the ABCGEM emission estimates, and data requirements necessary to improve isoprene and monoterpene emissions estimates for the application of both ABCGEM and MEGAN in Australia.
Related Results
Isoprene and monoterpene emissions in south-east Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric observations
Isoprene and monoterpene emissions in south-east Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric observations
Abstract. One of the key challenges in atmospheric chemistry is to reduce the uncertainty of biogenic volatile organic compound (BVOC) emission estimates from vegetation to the atm...
Effect of isoprene emissions from major forests on ozone formation in the city of Shanghai, China
Effect of isoprene emissions from major forests on ozone formation in the city of Shanghai, China
Abstract. Ambient surface level concentrations of isoprene (C5H8) were measured in the major forest regions located south of Shanghai, China. Because there is a large coverage of b...
Effect of isoprene emissions from major forests on ozone formation in the city of Shanghai, China
Effect of isoprene emissions from major forests on ozone formation in the city of Shanghai, China
Abstract. Ambient surface level concentrations of isoprene (C5H8) were measured in the major forest regions located south of Shanghai, China. Because there is a large coverage of b...
Human breath isoprene and its relation to blood cholesterol levels: new measurements and modeling
Human breath isoprene and its relation to blood cholesterol levels: new measurements and modeling
Numerous publications have described measurements of breath isoprene in humans, and there has been a hope that breath isoprene analyses could be a noninvasive diagnostic tool to as...
Improved isoprene emission estimates from MEGAN and comprehensive modeling of BVOCs driven aerosol dynamics in the Boreal forests
Improved isoprene emission estimates from MEGAN and comprehensive modeling of BVOCs driven aerosol dynamics in the Boreal forests
Accurate representation of biogenic volatile organic compound (BVOC) emissions is critical for understanding their role in atmospheric chemistry and secondary organic aerosol (SOA)...
Air mixing and sub-canopy advection in an oil palm plantation in Indonesia
Air mixing and sub-canopy advection in an oil palm plantation in Indonesia
<p>In tall vegetation canopies, such as forest or oil palm monoculture plantations, the below-canopy airflow can be influenced by the local topography and thereby cau...
Mapping isoprene emissions over North America using formaldehyde column observations from space
Mapping isoprene emissions over North America using formaldehyde column observations from space
We present a methodology for deriving emissions of volatile organic compounds (VOC) using spaceābased column observations of formaldehyde (HCHO) and apply it to data from the Globa...
GEOINFORMATION FOR DISASTER MANAGEMENT 2020 (GI4DM2020): PREFACE
GEOINFORMATION FOR DISASTER MANAGEMENT 2020 (GI4DM2020): PREFACE
Abstract. Across the world, nature-triggered disasters fuelled by climate change are worsening. Some two billion people have been affected by the consequences of natural hazards ov...

