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

• DOI: 10.5194/acp-2018-351
• Publication Date: 2018-05-04T07:21:42Z
• Authors: Shan S. Zhou; Amos P. K. Tai; Shihan Sun; Mehliyar Sadiq; Colette L. Heald; Jeffrey A. Geddes
• Keywords: Chemical Transport Model; Tropospheric ozone; Biogeochemical Cycle

Abstract. Tropospheric ozone is a significant air pollutant with substantial harm on vegetation, but also strongly dependent various vegetation-mediated processes. The interdependence between and vegetation may constitute feedback mechanisms that can alter concentration itself have not been considered in most studies to date. In this study we examine the importance of biogeochemical coupling surface leaf area index (LAI) shaping quality foliage density. We first implement an empirical scheme for damage Community Land Model (CLM), simulate steady-state responses LAI long-term exposure range prescribed levels (from 0 ppb 100 ppb). find plant functional types (PFTs) suffer decline as level increases. Based CLM-simulated results, develop GEOS-Chem chemical transport model parameterization correlates fractional changes monthly local mean levels. By dynamically forcing respond concentrations timescale, simulates ozone-vegetation synchronously via processes including biogenic volatile organic compound (VOC) emissions dry deposition. ozone-induced lead −1.8 +3 northern summer, corresponding factor −0.1 +0.6. Significantly higher simulated due strong positive ozone-LAI found tropical forests, mainly reductions deposition velocity, whereas reduced isoprene emission plays lesser role these low-NOx environments. high-NOx regions such eastern US, Europe China, however, effect much weaker even negative some regions, reflecting compensating effects (which leads lower regime). remote, low-LAI Southern Hemisphere, generally slightly negative, likely NOx-VOC reaction products serve NOx reservoirs. This represents step account dynamic important ramifications more realistic assessment ecosystem health.