资源环境科技发展态势分析平台

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.

Plain Language Summary Many studies have shown that global land cover change can significantly affect surface ozone air quality, albeit still with great uncertainties. In this study, we develop a method to examine the effects of any changes in total leaf area on surface ozone level. We perform a series of computer simulations and use the results to derive a set of formulae describing how total leaf area could affect surface ozone. Changes in surface ozone are found to arise mostly from the associated changes in its rate of removal at the land surface and isoprene emission, which can be further related to anthropogenic NOx emission, biogenic isoprene emission, wind speed, baseline ozone level and leaf area, and changes in leaf area. The statistical model is refined so that it can be applicable to different years and a wide range of changes in leaf area and can be used as a quick assessment tool to estimate the impacts of various land use policies on air quality. We also show that the sign of such change in surface ozone for a given region can be inferred by distinguishing between three different regimes based on the anthropogenic NOx emission and leaf area of that region.