Development and application of a generalized empirical model of BVOC emission (GEMBE) using observations from four Chinese forests

Abstract

Based on the measurements of emissions of biogenic volatile organic compounds (BVOCs), solar radiation and meteorological variables in three representative forests from temperate to subtropical zone in China, a primary empirical model of BVOC emissions (EMBE) has been developed. During 2018 and 2019, BVOC emission fluxes were measured in a tropical rubber tree plantation in China, and EMBE was improved to a generalized empirical model of BVOC emissions (GEMBE) and evaluated. This paper presents GEMBE as a fully empirical modeling framework, developed directly from ecosystem-scale flux observations, and compares this approach with MEGAN, a widely-used model that includes both empirical and process-based components. Isoprene emission estimated with GEMBE, using an emission factor based on the average for other sites, overestimated the observation by 34.8 % and monoterpenes by 41.0 %. A summary of the BVOC emission fluxes in the four typical forests in China is reported. With site-specific flux measurements the GEMBE model can be used to calculate BVOC emissions in China. Using GEMBE, the responses of BVOC emissions to their driving factors showed that isoprene and monoterpene emissions were more sensitive to the change in PAR than to changes in other factors. The responses of BVOC emissions to their driving factors were discussed for the four representative forests. The emission factors (EFs) calculated using GEMBE and MEGAN were summarized for the typical forests and grassland. The MEGAN estimated isoprene EF at this rubber plantation is lower, and the monoterpene EF is higher. Both GEMBE and MEGAN showed reasonable agreement in simulations of temporal trends over one year and two years, and well reproduced the evident monthly and seasonal BVOC emissions. As a fully empirical model, GEMBE provides a framework for estimating regional BVOC emissions, and investigating their impact on atmospheric chemistry, with an alternative approach to more complex process-based models that require biophysical parameterization.