The Estimation and Validation of Isoprene Emission Inventory in China, based on the Most Detailed Vegetation Investigation and Observation

Monday, 15 December 2014
Lingyu Li and Shaodong Xie, Peking University, Beijing, China
China is suffering from serious photochemical pollution and haze. It has been reported that Chemical Transport Model (CTM) may underestimate the level of ambient ozone (O3) and second organic aerosol (SOA) especially in polluted regions (Hodzic et al., 2010). In China, the simulated SOA concentrations might be underestimated by 0–75% (Jiang et al., 2012), which might result from the underestimated emissions of precursors. A major source of simulation uncertainty is the BVOC emission inventory due to their high emissions and activities. Studies have shown that the isoprene emissions in China might be underestimated significantly in the existing inventories (Fu et al., 2007; Geng et al., 2011).

Aiming to reduce the large uncertainties of isoprene emissions estimation, the emission inventory of isoprene in China at a high spatial and temporal resolution of 36 km×36 km and 1 hour is established. Based on the most detailed and latest vegetation investigations, China’s official statistical data and Vegetation Atlas of China (1:1,000,000), isoprene emissions from 82 plant functional types (PFTs) are computed firstly using MEGANv2.1 driven by WRF model. More local species-specific emission rates are developed combining statistical analysis and category classification, and the leaf biomass is estimated based on vegetation volume and production with biomass-apportion models. The total annual isoprene emissions in 2003 are 23.9 Tg C. Our isoprene emission is much higher than those in other studies for China’s isoprene emission estimation. The discrepancy in isoprene emissions is mostly due to the higher emission rate used in this study. In order to validate the species-specific emission rates determined in this study, the measurements of isoprene emissions from dominant tree species in China are conducted. Our study will be very significant for improving the accuracy of SOA and O3 simulation in China.