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 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.

Effects of Dry Deposition on Surface Ozone over South Asia Inferred from a Regional Chemical Transport Model

2020 ◽  
Vol 4 (2) ◽  
pp. 321-327 ◽  
Author(s):  
Amit Sharma ◽  
Narendra Ojha ◽  
Tabish U. Ansari ◽  
Som K. Sharma ◽  
Andrea Pozzer ◽  
...  
Keyword(s):  
South Asia ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Chemical Transport Model

scholarly journals Implementation of Yale Interactive terrestrial Biosphere model v1.0 into GEOS-Chem v12.0.0: a tool for biosphere–chemistry interactions

2020 ◽  
Vol 13 (3) ◽  
pp. 1137-1153 ◽  
Author(s):  
Yadong Lei ◽  
Xu Yue ◽  
Hong Liao ◽  
Cheng Gong ◽  
Lin Zhang
Keyword(s):  
Stomatal Conductance ◽  
Atmospheric Chemistry ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Eastern China ◽  
Deposition Velocity ◽  
Chemical Transport Model ◽  
Terrestrial Biosphere ◽  
Area Index

Abstract. The terrestrial biosphere and atmospheric chemistry interact through multiple feedbacks, but the models of vegetation and chemistry are developed separately. In this study, the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic vegetation model with biogeochemical processes, is implemented into the Chemical Transport Model GEOS-Chem (GC) version 12.0.0. Within this GC-YIBs framework, leaf area index (LAI) and canopy stomatal conductance dynamically predicted by YIBs are used for dry deposition calculation in GEOS-Chem. In turn, the simulated surface ozone (O3) by GEOS-Chem affect plant photosynthesis and biophysics in YIBs. The updated stomatal conductance and LAI improve the simulated O3 dry deposition velocity and its temporal variability for major tree species. For daytime dry deposition velocities, the model-to-observation correlation increases from 0.69 to 0.76, while the normalized mean error (NME) decreases from 30.5 % to 26.9 % using the GC-YIBs model. For the diurnal cycle, the NMEs decrease by 9.1 % for Amazon forests, 6.8 % for coniferous forests, and 7.9 % for deciduous forests using the GC-YIBs model. Furthermore, we quantify the damaging effects of O3 on vegetation and find a global reduction of annual gross primary productivity by 1.5 %–3.6 %, with regional extremes of 10.9 %–14.1 % in the eastern USA and eastern China. The online GC-YIBs model provides a useful tool for discerning the complex feedbacks between atmospheric chemistry and the terrestrial biosphere under global change.

scholarly journals Implementation of Yale Interactive terrestrial Biosphere model version 1.0 into GEOS-Chem version 12.0.0: a tool for biosphere-chemistry interactions

2019 ◽  
Author(s):  
Yadong Lei ◽  
Xu Yue ◽  
Hong Liao ◽  
Cheng Gong ◽  
Lin Zhang
Keyword(s):  
Stomatal Conductance ◽  
Atmospheric Chemistry ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Eastern China ◽  
Deposition Velocity ◽  
Chemical Transport Model ◽  
Terrestrial Biosphere ◽  
Area Index

Abstract. The terrestrial biosphere and atmospheric chemistry interact through multiple feedbacks, but the models of vegetation and chemistry are developed separately. In this study, the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic vegetation model with biogeochemical processes, is implemented into the Chemical Transport Model GEOS-Chem version 12.0.0. Within the GC-YIBs framework, leaf area index (LAI) and canopy stomatal conductance dynamically predicted by YIBs are used for dry deposition calculation in GEOS-Chem. In turn, the simulated surface ozone (O3) by GEOS-Chem affect plant photosynthesis and biophysics in YIBs. The updated stomatal conductance and LAI improve the simulated daytime O3 dry deposition velocity for major tree species. Compared with the GEOS-Chem model, the model-to-observation correlation for dry deposition velocities increases from 0.76 to 0.85 while the normalized mean error decreases from 35 % to 27 % using the GC-YIBs model. Furthermore, we quantify O3 vegetation damaging effects and find a global reduction of annual gross primary productivity by 2–5 %, with regional extremes of 11–15 % in the eastern U.S. and eastern China. The online GC-YIBs model provides a useful tool for discerning the complex feedbacks between atmospheric chemistry and terrestrial biosphere under global change.

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 Importance of Dry Deposition Parameterization Choice in Global Simulations of Surface Ozone

2019 ◽  
Author(s):  
Anthony Y. H. Wong ◽  
Jeffrey A. Geddes ◽  
Amos P. K. Tai ◽  
Sam J. Silva
Keyword(s):  
Land Cover ◽  
Dry Deposition ◽  
Transport Model ◽  
Surface Ozone ◽  
Deposition Velocity ◽  
Chemical Transport Model ◽  
Area Index ◽  
Ozone Sensitivity ◽  
Dry Deposition Velocity ◽  
The Impact

Abstract. Dry deposition is the second largest sink of tropospheric ozone. Increasing evidence has shown that ozone dry deposition actively links meteorology and hydrology with ozone air quality. However, there is little systematic investigation on the performance of different ozone dry deposition parameterizations at the global scale, and how parameterization choice can impact surface ozone simulations. Here we present the results of the first global, multi-decade modelling and evaluation of ozone dry deposition velocity (vd) using multiple ozone dry deposition parameterizations. We use consistent assimilated meteorology and satellite-derived leaf area index (LAI) to simulate vd over 1982–2011 driven by four sets of ozone dry deposition parametrization that are representative of the current approaches of global ozone dry deposition modelling, such that the differences in simulated vd are entirely due to differences in deposition model structures. In addition, we use the surface ozone sensitivity to vd predicted by a chemical transport model to estimate the impact of mean and variability of ozone dry deposition velocity on surface ozone. Our estimated vd from four different parameterizations are evaluated against field observations, and while performance varies considerably by land cover types, our results suggest that none of the parameterizations are universally better than the others. Discrepancy in simulated mean vd among the parameterizations is estimated to cause 2 to 5 ppbv of discrepancy in surface ozone in the Northern Hemisphere (NH) and up to 8 ppbv in tropical rainforest in July, and up to 8 ppbv in tropical rainforests and seasonally dry tropical forests in Indochina in December. Parameterization-specific biases based on individual land cover type and hydroclimate are found to be the two main drivers of such discrepancies. We find statistically significant trends in the multiannual time series of simulated July daytime vd in all parameterizations, driven by warming and drying (southern Amazonia, southern African savannah and Mongolia) or greening (high latitudes). The trends in July daytime vd is estimated to be 1 % yr−1 and leads to up to 3 ppbv of surface ozone changes over 1982–2011. The interannual coefficient of variation (CV) of July daytime mean vd in NH is found to be 5 %–15 %, with spatial distribution that varies with the dry deposition parameterization. Our sensitivity simulations suggest this can contribute between 0.5 to 2 ppbv to interannual variability (IAV) in surface ozone, but all models tend to underestimate interannual CV when compared to long-term ozone flux observations. We also find that IAV in some dry deposition parameterizations are more sensitive to LAI while others are more sensitive to climate. Comparisons with other published estimates of the IAV of background ozone confirm that ozone dry deposition can be an important part of natural surface ozone variability. Our results demonstrate the importance of ozone dry deposition parameterization choice on surface ozone modelling, and the impact of IAV of vd on surface ozone, thus making a strong case for further measurement, evaluation and model-data integration of ozone dry deposition on different spatiotemporal scales.

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.

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