Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6155-2021
https://doi.org/10.5194/gmd-14-6155-2021
Model description paper
 | 
13 Oct 2021
Model description paper |  | 13 Oct 2021

Modeling sensitivities of BVOCs to different versions of MEGAN emission schemes in WRF-Chem (v3.6) and its impacts over eastern China

Mingshuai Zhang, Chun Zhao, Yuhan Yang, Qiuyan Du, Yonglin Shen, Shengfu Lin, Dasa Gu, Wenjing Su, and Cheng Liu

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Cited articles

Abdi-Oskouei, M., Pfister, G., Flocke, F., Sobhani, N., Saide, P., Fried, A., Richter, D., Weibring, P., Walega, J., and Carmichael, G.: Impacts of physical parameterization on prediction of ethane concentrations for oil and gas emissions in WRF-Chem, Atmos. Chem. Phys., 18, 16863–16883, https://doi.org/10.5194/acp-18-16863-2018, 2018. 
Arghavani, S., Malakooti, H., and Bidokhti, A. A.: Numerical evaluation of urban green space scenarios effects on gaseous air pollutants in Tehran Metropolis based on WRF-Chem model, Atmos. Environ., 214, 116832, https://doi.org/10.1016/j.atmosenv.2019.116832,​​​​​​​ 2019. 
Arneth, A., Niinemets, Ü., Pressley, S., Bäck, J., Hari, P., Karl, T., Noe, S., Prentice, I. C., Serça, D., Hickler, T., Wolf, A., and Smith, B.: Process-based estimates of terrestrial ecosystem isoprene emissions: incorporating the effects of a direct CO2-isoprene interaction, Atmos. Chem. Phys., 7, 31–53, https://doi.org/10.5194/acp-7-31-2007, 2007. 
Bao, H., Shrestha, K. L., Kondo, A., Kaga, A., and Inoue, Y.: Modeling the influence of biogenic volatile organic compound emissions on ozone concentration during summer season in the Kinki region of Japan, Atmos. Environ., 44, 421–431, 2010. 
Bonan, G. B.: A land surface model (LSM version 1.0) for ecological, hydrological, and atmospheric studies: Technical description and user’s guide, NCAR Tech. Note 4171STR, 150 pp., available at: http://opensky.ucar.edu/islandora/object/technotes:185 (last access: 25 May 2016), 1996. 
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Short summary
Biogenic volatile organic compounds (BVOCs) can influence atmospheric chemistry and secondary pollutant formation. This study examines the performance of different versions of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in modeling BVOCs and ozone and their sensitivities to vegetation distributions over eastern China. The results suggest more accurate vegetation distribution and measurements of BVOC emission fluxes are needed to reduce the uncertainties.
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