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A nonnegativity preserved efficient chemical solver applied to the air pollution forecast

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  • Feng, Fan
  • Chi, Xuebin
  • Wang, Zifa
  • Li, Jie
  • Jiang, Jinrong
  • Yang, Wenyi

Abstract

Air pollution forecast is becoming more and more important nowadays. The numerically sticky chemical ordinary differential equations (ODEs) is a critical component of air pollution models. Various solvers have been designed for the chemical ODEs in the past. However, they are either slow or imprecise. In our previous work, we have designed a nonnegativity preserved efficient chemical solver MBE, which is an acronym for Modified-Backward-Euler. In this paper, we review MBE method and prove its convergence and stability mathematically, which guarantee that MBE results converge to the exact solutions as the step-size becomes smaller and MBE results with relatively small step-size can be used as the standard. Then we apply MBE to the Nested Air Quality Prediction Modeling System (NAQPMS). Comparison between MBE and the most popular solver LSODE is also made. Considering the speed and precision, MBE is a better choice for the air pollution forecast.

Suggested Citation

  • Feng, Fan & Chi, Xuebin & Wang, Zifa & Li, Jie & Jiang, Jinrong & Yang, Wenyi, 2017. "A nonnegativity preserved efficient chemical solver applied to the air pollution forecast," Applied Mathematics and Computation, Elsevier, vol. 314(C), pages 44-57.
    • Handle: RePEc:eee:apmaco:v:314:y:2017:i:c:p:44-57
    DOI: 10.1016/j.amc.2017.06.008
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    References listed on IDEAS

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    1. Feng, Fan & Wang, Zifa & Li, Jie & Carmichael, Gregory R., 2015. "A nonnegativity preserved efficient algorithm for atmospheric chemical kinetic equations," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 519-531.
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    Cited by:

    1. Tan, Jing & Liu, Hui & Li, Yanfei & Yin, Shi & Yu, Chengqing, 2022. "A new ensemble spatio-temporal PM2.5 prediction method based on graph attention recursive networks and reinforcement learning," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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