Development of an ecophysiology module in the GEOS-Chem chemical transport model version 12.2.0 to represent biosphere−atmosphere fluxes relevant for ozone air quality
- 1Earth System Science Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Sha Tin, Hong Kong
- 2State Key Laboratory of Agrobiotechnology, and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, Hong Kong
- 3Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, Florida, USA
- 4Lynker Technologies, LLC, Leesburg, Virginia, USA
Abstract. Ground-level ozone (O3) is a major air pollutant that adversely affects human health and agricultural productivity. Removal of air pollutants including tropospheric O3 from the atmosphere by vegetation is controlled mostly by the process of dry deposition, an important component of which is plant stomatal uptake that can in turn cause damage to plant tissues with ramifications for ecosystem and crop health. In many atmospheric and land surface models, the openness of plant stomata is represented by a bulk stomatal conductance, which is often semi-empirically parameterized, and highly fitted to historical observations. A lack of mechanistic linkage to ecophysiological processes such as photosynthesis may render models insufficient to represent plant-mediated responses of atmospheric chemistry to long-term changes in CO2, climate and short-lived air pollutant concentrations. A new ecophysiology module was thus developed to mechanistically simulate land−atmosphere exchange of important gas species in GEOS-Chem, a chemical transport model widely used in atmospheric chemistry studies. We adopted the formulations from the Joint UK Land Environmental Simulator (JULES) to couple photosynthesis rate, bulk stomatal conductance and isoprene emission rate dynamically. The implementation not only allows dry deposition to be coupled with plant ecophysiology, but also enables plant and crop productivity and functions to respond dynamically to atmospheric chemical changes. The research questions of this study include: 1) how the new ecophysiology module compares with the prior, semi-empirical parameterization in terms of simulating concentration and dry deposition velocity of O3 with respect to site measurement-based estimates; and 2) whether the ecophysiology module simulates vegetation productivity, dry deposition, isoprene emission rate and O3–vegetation interactions reasonably under a present-day and an elevated CO2 concentration. We conduct simulations to evaluate the effects of the ecophysiology module on simulated dry deposition velocity and concentration of surface O3 against an observation-derived dataset known as SynFlux. Our estimated dry deposition velocity of O3 is close to SynFlux dry deposition velocity with root-mean-squared errors (RMSE) ranging from 0.1 to 0.2 cm s–1 across different plant functional types (PFTs), despite an overall positive bias in surface O3 concentration (by up to 16 ppbv). Representing ecophysiology was found to reduce the simulated biases in deposition fluxes from the prior model, but worsen the positive biases in simulated O3 concentrations. The increase in positive concentration biases is mostly attributable to the ecophysiology-based stomatal conductance being generally smaller (and closer to SynFlux values) than that estimated by the prior semi-empirical formulation, calling for further improvements in non-depositional processes relevant for O3 simulations. Estimated global O3 deposition flux is 864 Tg O3 yr–1 with GEOS-Chem, and the new module decreases this estimate by 92 Tg O3 yr–1. Estimated global gross primary product (GPP) is 119 Pg C yr–1, with an O3-induced damage of 4.2 Pg C yr–1 (3.5 %). An elevated CO2 scenario (580 ppm) yields higher global GPP (+16.8 %) and lower global O3 depositional sink (–3.3 %). Global isoprene emission simulated with a photosynthesis-based scheme is 318 Tg C yr–1, which is 31 Tg C yr−1 (−8.9 %) less than that calculated using the MEGAN emission algorithm. This new model development dynamically represents the two-way interactions between vegetation and air pollutants, and thus provides a unique capability in evaluating pollutant impacts on vegetation health and feedback processes that can shape atmospheric chemistry and air quality especially for any timescales shorter than the multidecadal timescale.
Joey C. Y. Lam et al.
Status: final response (author comments only)
Joey C. Y. Lam et al.
Joey C. Y. Lam et al.
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