scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (13) ◽  
pp. 5897-5912 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
New Information

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index <1.2) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of both the IASI and TES measurements.

scholarly journals Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

2012 ◽  
Vol 12 (2) ◽  
pp. 3941-3982 ◽  
Author(s):  
K. C. Wells ◽  
D. B. Millet ◽  
L. Hu ◽  
K. E. Cady-Pereira ◽  
Y. Xiao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Degrees Of Freedom ◽  
Transport Model ◽  
A Priori ◽  
Global Scale ◽  
Biogenic Emissions ◽  
Chemical Transport Model ◽  
Area Index ◽  
Model Aircraft

Abstract. Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model : TES regressions are generally consistent with the model : aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS > 0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1–2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 1.0, 0.05 and 8.6 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.75 for expanding canopies with leaf area index < 2.0) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of IASI, TES, and ground-based measurements.

scholarly journals Coupling between surface ozone and leaf area index in a chemical transport model: strength of feedback and implications for ozone air quality and vegetation health

2018 ◽  
Vol 18 (19) ◽  
pp. 14133-14148 ◽  
Author(s):  
Shan S. Zhou ◽  
Amos P. K. Tai ◽  
Shihan Sun ◽  
Mehliyar Sadiq ◽  
Colette L. Heald ◽  
...  
Keyword(s):  
Air Quality ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Area Index ◽  
Ozone Levels

Abstract. Tropospheric ozone is an air pollutant that substantially harms vegetation and is also strongly dependent on various vegetation-mediated processes. The interdependence between ozone and vegetation may constitute feedback mechanisms that can alter ozone concentration itself but have not been considered in most studies to date. In this study we examine the importance of dynamic coupling between surface ozone and leaf area index (LAI) in shaping ozone air quality and vegetation. We first implement an empirical scheme for ozone damage on vegetation in the Community Land Model (CLM) and simulate the steady-state responses of LAI to long-term exposure to a range of prescribed ozone levels (from 0 to 100 ppb). We find that most plant functional types suffer a substantial decline in LAI as ozone level increases. Based on the CLM-simulated results, we develop and implement in the GEOS-Chem chemical transport model a parameterization that computes fractional changes in monthly LAI as a function of local mean ozone levels. By forcing LAI to respond to ozone concentrations on a monthly timescale, the model simulates ozone–LAI coupling dynamically via biogeochemical processes including biogenic volatile organic compound (VOC) emissions and dry deposition, without the complication from meteorological changes. We find that ozone-induced damage on LAI can lead to changes in ozone concentrations by −1.8 to +3 ppb in boreal summer, with a corresponding ozone feedback factor of −0.1 to +0.6 that represents an overall self-amplifying effect from ozone–LAI coupling. Substantially higher simulated ozone due to strong positive feedbacks is found in most tropical forests, mainly due to the ozone-induced reductions in LAI and dry deposition velocity, whereas reduced isoprene emission plays a lesser role in these low-NOx environments. In high-NOx regions such as the eastern US, Europe, and China, however, the feedback effect is much weaker and even negative in some regions, reflecting the compensating effects of reduced dry deposition and reduced isoprene emission (which reduces ozone in high-NOx environments). In remote, low-LAI regions, including most of the Southern Hemisphere, the ozone feedback is generally slightly negative due to the reduced transport of NOx–VOC reaction products that serve as NOx reservoirs. This study represents the first step to accounting for dynamic ozone–vegetation coupling in a chemical transport model with ramifications for a more realistic joint assessment of ozone air quality and ecosystem health.

scholarly journals Coupling between surface ozone and leaf area index in a chemical transport model: Strength of feedback and implications for ozone air quality and vegetation health

2018 ◽  
Author(s):  
Shan S. Zhou ◽  
Amos P. K. Tai ◽  
Shihan Sun ◽  
Mehliyar Sadiq ◽  
Colette L. Heald ◽  
...  
Keyword(s):  
Air Quality ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Area Index ◽  
Ozone Levels

Abstract. Tropospheric ozone is a significant air pollutant with substantial harm on vegetation, but is also strongly dependent on various vegetation-mediated processes. The interdependence between ozone and vegetation may constitute feedback mechanisms that can alter ozone concentration itself but have not been considered in most studies to date. In this study we examine the importance of biogeochemical coupling between surface ozone and leaf area index (LAI) in shaping ozone air quality and foliage density. We first implement an empirical scheme for ozone damage on vegetation in the Community Land Model (CLM), and simulate the steady-state responses of LAI to long-term exposure to a range of prescribed ozone levels (from 0 ppb to 100 ppb). We find that most plant functional types (PFTs) suffer a substantial decline in LAI as ozone level increases. Based on the CLM-simulated results, we develop and implement in the GEOS-Chem chemical transport model a parameterization that correlates the fractional changes in monthly LAI to local mean ozone levels. By dynamically forcing LAI to respond to ozone concentrations on a monthly timescale, the model simulates ozone-vegetation coupling synchronously via biogeochemical processes including biogenic volatile organic compound (VOC) emissions and dry deposition. We find that ozone-induced damage on LAI can lead to an ozone feedback of −1.8 ppb to +3 ppb in northern summer, with a corresponding ozone feedback factor of −0.1 to +0.6. Significantly higher simulated ozone due to strong positive ozone-LAI feedback is found in most tropical forests, mainly due to the ozone-induced reductions in LAI and dry deposition velocity, whereas reduced isoprene emission plays a lesser role in these low-NOx environments. In high-NOx regions such as eastern US, Europe and China, however, the feedback effect is much weaker and even negative in some regions, reflecting the compensating effects of reduced dry deposition and reduced isoprene emission (which leads to lower ozone in the high-NOx regime). In remote, low-LAI regions including most of the Southern Hemisphere, the ozone feedback is generally slightly negative, likely due to reduced transport of NOx-VOC reaction products that serve as NOx reservoirs. This study represents the first step to account for dynamic ozone-vegetation coupling in a chemical transport model with important ramifications for more realistic assessment of ozone air quality and ecosystem health.

scholarly journals Ability of the land surface model ISBA-A-gs to simulate leaf area index at the global scale: Comparison with satellites products

2006 ◽  
Vol 111 (D18) ◽  
Author(s):  
Anne-Laure Gibelin ◽  
Jean-Christophe Calvet ◽  
Jean-Louis Roujean ◽  
Lionel Jarlan ◽  
Sietse O. Los
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Land Surface Model ◽  
Global Scale ◽  
Surface Model ◽  
Area Index

scholarly journals New constraints on biogenic emissions using satellite-based estimates of carbon monoxide fluxes

2019 ◽  
Vol 19 (21) ◽  
pp. 13569-13579 ◽  
Author(s):  
Helen M. Worden ◽  
A. Anthony Bloom ◽  
John R. Worden ◽  
Zhe Jiang ◽  
Eloise A. Marais ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
A Priori ◽  
Primary Source ◽  
Biogenic Emissions ◽  
Chemical Production ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Top Down ◽  
Decadal Scale

Abstract. Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation are a primary source for the chemical production of carbon monoxide (CO) in the atmosphere, and these biogenic emissions account for about 18 % of the global CO burden. Partitioning CO fluxes to different source types in top-down inversion methods is challenging; typically a simple scaling of the posterior flux to prior flux values for fossil fuel, biogenic and biomass burning sources is used. Here we show top-down estimates of biogenic CO fluxes using a Bayesian inference approach, which explicitly accounts for both posterior and a priori CO flux uncertainties. This approach re-partitions CO fluxes following inversion of Measurements Of Pollution In The Troposphere (MOPITT) CO observations with the GEOS-Chem model, a global chemical transport model driven by assimilated meteorology from the NASA Goddard Earth Observing System (GEOS). We compare these results to the prior information for CO used to represent biogenic NMVOCs from GEOS-Chem, which uses the Model of Emissions of Gases and Aerosols from Nature (MEGAN) for biogenic emissions. We evaluate the a posteriori biogenic CO fluxes against top-down estimates of isoprene fluxes using Ozone Monitoring Instrument (OMI) formaldehyde observations. We find similar seasonality and spatial consistency in the posterior CO and top-down isoprene estimates globally. For the African savanna region, both top-down CO and isoprene seasonality vary significantly from the MEGAN a priori inventory. This method for estimating biogenic sources of CO will provide an independent constraint on modeled biogenic emissions and has the potential for diagnosing decadal-scale changes in emissions due to land-use change and climate variability.

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