%A Wenwei Yang, Yun Zhu, Carey Jang, Shicheng Long, Che-Jen Lin, Bin Yu, Zachariah Adelman, Shuxiao Wang, Jia Xing, Long Wang, Jiabin Li %T Development and case study of a new-generation model-VAT for analyzing the boundary conditions influence on atmospheric mercury simulation %0 Journal Article %D 2018 %J Front. Environ. Sci. Eng. %J Frontiers of Environmental Science & Engineering %@ 2095-2201 %R 10.1007/s11783-018-1010-6 %P 13- %V 12 %N 1 %U {https://journal.hep.com.cn/fese/EN/10.1007/s11783-018-1010-6 %8 2018-02-15 %X

Performance of CMAQ-Hg is better using Model-driven BCs than default BC.

Model-VAT provides a better user experience to convert Model-driven BCs.

Model-VAT is designed to efficiently access and analyze the results of multi-models.

Atmospheric models are essential tools to study the behavior of air pollutants. To interpret the complicated atmospheric model simulations, a new-generation Model Visualization and Analysis Tool (Model-VAT) has been developed for scientists to analyze the model data and visualize the simulation results. The Model-VAT incorporates analytic functions of conventional tools and enhanced capabilities in flexibly accessing, analyzing, and comparing simulated results from multi-scale models with different map projections and grid resolutions. The performance of the Model-VAT is demonstrated by a case study of investigating the influence of boundary conditions (BCs) on the ambient Hg formation and transport simulated by the CMAQ model over the Pearl River Delta (PRD) region. The alternative BC options are taken from (1) default time-independent profiles, (2) outputs from a CMAQ simulation of a larger nesting domain, and (3) concentration files from GEOS-Chem (re-gridded and re-projected using the Model-VAT). The three BC inputs and simulated ambient concentrations and deposition were compared using the Model-VAT. The results show that the model simulations based on the static BCs (default profile) underestimates the Hg concentrations by ~6.5%, dry depositions by ~9.4%, and wet depositions by ~43.2% compared to those of the model-derived (e.g. GEOS-Chem or nesting CMAQ) BCs. This study highlights the importance of model nesting approach and demonstrates that the innovative functions of Model-VAT enhances the efficiency of analyzing and comparing the model results from various atmospheric model simulations.