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

Publisher： John Wiley & Sons Inc

E-ISSN： 2169-8996|123|3|1883-1898

ISSN： 2169-897x

Source： JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, Vol.123, Iss.3, 2018-02, pp. : 1883-1898

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Abstract

AbstractMany 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 NO_x 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 NO_x 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.