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

Attribution and Statistical Parameterization of the Sensitivity of Surface Ozone to Changes in... Many studies have shown that global land cover change can significantly affect surface ozone air quality, albeit still with great uncertainties due to the complex pathways involved. In this study, we develop a framework to systematically examine the effects of any changes in foliage density as represented by leaf area index (LAI) on surface ozone concentration. We perform a series of perturbation experiments using the GEOS‐Chem chemical transport model. The spatial variability of the simulated results is used as a proxy to build a statistical model to quantify the sensitivity of surface ozone to LAI changes, which is found to arise mostly from the associated changes in dry deposition velocity and isoprene emission rate, whereas other factors and second‐order effects are negligible. The spatial variations of ozone responses to LAI changes are found to be the most correlated with anthropogenic NOx emission, biogenic isoprene emission, wind speed, ozone concentration, baseline LAI, and changes in LAI. We also show that the sign of change in surface ozone under future LAI changes for a given location can be inferred by distinguishing between three different regimes based on local anthropogenic NOx emission and LAI. The statistical model is optimized so that it is applicable to a wide range of LAI changes and can be used as a quick assessment tool to estimate the impacts of various land use policies on ozone air quality, and a diagnostic tool to estimate the relative contribution of different pathways toward the overall ozone‐LAI relationship. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Geophysical Research: Atmospheres Wiley

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

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
©2018. American Geophysical Union. All Rights Reserved.
ISSN
2169-897X
eISSN
2169-8996
D.O.I.
10.1002/2017JD027311
Publisher site
See Article on Publisher Site

Abstract

Many studies have shown that global land cover change can significantly affect surface ozone air quality, albeit still with great uncertainties due to the complex pathways involved. In this study, we develop a framework to systematically examine the effects of any changes in foliage density as represented by leaf area index (LAI) on surface ozone concentration. We perform a series of perturbation experiments using the GEOS‐Chem chemical transport model. The spatial variability of the simulated results is used as a proxy to build a statistical model to quantify the sensitivity of surface ozone to LAI changes, which is found to arise mostly from the associated changes in dry deposition velocity and isoprene emission rate, whereas other factors and second‐order effects are negligible. The spatial variations of ozone responses to LAI changes are found to be the most correlated with anthropogenic NOx emission, biogenic isoprene emission, wind speed, ozone concentration, baseline LAI, and changes in LAI. We also show that the sign of change in surface ozone under future LAI changes for a given location can be inferred by distinguishing between three different regimes based on local anthropogenic NOx emission and LAI. The statistical model is optimized so that it is applicable to a wide range of LAI changes and can be used as a quick assessment tool to estimate the impacts of various land use policies on ozone air quality, and a diagnostic tool to estimate the relative contribution of different pathways toward the overall ozone‐LAI relationship.

Journal

Journal of Geophysical Research: AtmospheresWiley

Published: Jan 16, 2018

Keywords: ; ; ; ; ;

References

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