Supplementary material to "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"

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.

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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

10.5194/acp-2018-351 ◽

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.

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Attribution and Statistical Parameterization of the Sensitivity of Surface Ozone to Changes in Leaf Area Index Based On a Chemical Transport Model

Journal of Geophysical Research Atmospheres ◽

10.1002/2017jd027311 ◽

2018 ◽

Vol 123 (3) ◽

pp. 1883-1898 ◽

Cited By ~ 6

Author(s):

Anthony Y. H. Wong ◽

Amos P. K. Tai ◽

Yin‐Ying Ip

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Transport Model ◽

Surface Ozone ◽

Chemical Transport ◽

Chemical Transport Model ◽

Area Index

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-5897-2012 ◽

2012 ◽

Vol 12 (13) ◽

pp. 5897-5912 ◽

Cited By ~ 33

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.

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

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-3941-2012 ◽

2012 ◽

Vol 12 (2) ◽

pp. 3941-3982 ◽

Cited By ~ 6

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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A new diagnostic for tropospheric ozone production

10.5194/acp-2017-378 ◽

2017 ◽

Author(s):

Peter M. Edwards ◽

Mathew J. Evans

Keyword(s):

Air Quality ◽

Tropospheric Ozone ◽

Transport Model ◽

Chemical Transport ◽

Ozone Production ◽

Chemical Transport Model ◽

Organic Species ◽

Earth’S Climate ◽

Oxidation Of Organics

Abstract. Tropospheric ozone is important for the Earth’s climate and air quality. It is produced during the oxidation of organics in the presence of nitrogen oxides. Due to the range of organic species emitted and the chain like nature of their oxidation, this chemistry is complex and understanding the role of different processes (emission, deposition, chemistry) is difficult. We demonstrate a new methodology for diagnosing ozone production based on the processing of bonds contained within emitted molecules, the fate of which is determined by the conservation of spin of the bonding electrons. Using this methodology to diagnose ozone production in the GEOS-Chem chemical transport model, we demonstrate its advantages over the standard diagnostic. We show that the number of bonds emitted, their chemistry and lifetime, and feedbacks on OH are all important in determining the ozone production within the model and its sensitivity to changes. This insight may allow future model-model comparisons to better identify the root causes of model differences.

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

ACS Earth and Space Chemistry ◽

10.1021/acsearthspacechem.0c00004 ◽

2020 ◽

Vol 4 (2) ◽

pp. 321-327 ◽

Cited By ~ 1

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

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The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-1645-2014 ◽

2014 ◽

Vol 7 (2) ◽

pp. 1645-1689

Author(s):

E. Hache ◽

J.-L. Attié ◽

C. Tourneur ◽

P. Ricaud ◽

L. Coret ◽

...

Keyword(s):

Air Quality ◽

Transport Model ◽

Statistical Tests ◽

Surface Ozone ◽

A Priori ◽

Thermal Infrared ◽

Added Value ◽

Chemical Transport Model ◽

Geo Satellite ◽

Sky Conditions

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.

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Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

10.20944/preprints201811.0607.v1 ◽

2018 ◽

Author(s):

Scott D. Chambers ◽

Elise-Andree Guérette ◽

Khalia Monk ◽

Alan D. Griffiths ◽

Yang Zhang ◽

...

Keyword(s):

Air Quality ◽

Diurnal Cycle ◽

Transport Model ◽

Chemical Transport ◽

Chemical Transport Model ◽

Transport Models ◽

Potential Health ◽

Meteorological Model ◽

Model Skill ◽

Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

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