02 Jan 2020

02 Jan 2020

Review status: this discussion paper is a preprint. It has been under review for the journal Biogeosciences (BG). The manuscript was not accepted for further review after discussion.

Estimation of biogenic volatile organic compound (BVOC) emissions in China using WRF–CLM–MEGAN coupled model

Lifei Yin1, Zhenying Xu1, Mingxu Liu1, Tingting Xu1,2, Tiantian Wang1, Wenling Liao1, Mengmeng Li3, Xuhui Cai1, Ling Kang1, Hongsheng Zhang4, and Yu Song1 Lifei Yin et al.
  • 1State Key Joint Laboratory of Environmental Simulation and Pollution Control, Department of Environmental Science, Peking University, Beijing 100871, China
  • 2Environmental College, Chengdu University of Technology, Chengdu 610059, China
  • 3School of Atmospheric Sciences, Nanjing University, Nanjing 210000, China
  • 4Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China

Abstract. Biogenic volatile organic compounds (BVOCs) emitted by terrestrial vegetation significantly influence the atmospheric chemistry and global climate. Previous studies calculated BVOC emissions outside the comprehensive terrestrial ecosystem processes and oversimplified the representation of canopy environments which exert substantial impacts on BVOC emissions. The sophisticated land surface model CLM (Community Land Model) reproduces essential ground and canopy characteristics and can calculate BVOC emissions as a step of integrated biogeochemical processes. In this study, the land surface scheme CLM version4 (CLM4) of WRF (Weather Research and Forecasting model) was used to estimate BVOC emissions in China. Based on highly-resolved meteorological outputs derived from WRF, CLM4 computed real-time physical and biological variables to drive MEGAN (Model of Emissions of Gases and Aerosols from Nature), a BVOC estimation algorithm embedded within biogeochemistry component of CLM4, to calculate plant emission flux. MODIS (Moderate Resolution Imaging Spectroradiometer) land-use data with high resolutions was introduced in WRF to replace the outdated land surface parameters. An emission inventory of isoprene and monoterpenes (including α-pinene, β-pinene, 3-carene, t-β-ocimene, limonene, sabinene and myrcene) with high spatiotemporal resolution (12 × 12 km, hourly) was established for the year 2018. The annual BVOC emission in China was 14.7 Tg C, in which isoprene contributes about 78.3 % (11.5 Tg C), followed by α-pinene (1.2 Tg C) and β-pinene (0.7 Tg C). Due to the strong emission capacity and large areas, broadleaf forests contribute to 76.8 % of total isoprene emission and 72.1 % of monoterpenes emission, respectively. BVOC emissions showed marked seasonal and diurnal patterns with the peak emission occurring in summer and midday. Spatially, high emissions of BVOC were mainly concentrated in southern and northeastern China, as well as the Qinling Mountains in central China, accounting for 91.4 % of national emission. Guangxi, Yunnan and Hunan provinces are significant emitters due to large area of vegetation with high emission rate and favored environmental conditions. The emission estimates are compared to past modeling results, field measurements and further evaluated against top-down isoprene emission estimates. Generally, the coupled mode produced a reasonable simulation in both emission amounts and the spatiotemporal distribution of BVOCs. The WRF–CLM–MEGAN coupling framework could be further integrated with atmospheric chemistry model to investigate BVOC chemistry and their effects on regional pollution and climate.

Lifei Yin et al.

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Lifei Yin et al.


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Short summary
Biogenic Volatile Organic Compounds (BVOCs) emission of terrestrial vegetation is an important part of biogeochemical cycle. Compared with previous studies which calculate regional BVOC emissions independently, the coupled model WRF-CLM-MEGAN achieves an integrated parameterization of BVOC emissions and other land surface processes, and therefore provides a more reasonable estimate. The model could be further coupled with chemistry module to fully investigate the land-atmosphere interactions.