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A Study on Statistical Parameters for the Evaluation of Regional Air Quality Modeling Results – Focused on Fine Dust Modeling –

  • Journal of Environmental Impact Assessment
  • Abbr : J EIA
  • 2020, 29(4), pp.272-285
  • Publisher : Korean Society Of Environmental Impact Assessment
  • Research Area : Engineering > Environmental Engineering
  • Received : April 24, 2020
  • Accepted : July 24, 2020
  • Published : August 31, 2020

Kim, Cheol-Hee ORD ID 1 Lee, Sang-Hyun ORD ID 2 Min Jang ORD ID 3 Sung-Nam Chun ORD ID 4 Suji Kang 4 Ko Kwang-Kun ORD ID 5 Jong-Jae, Lee ORD ID 6 Lee, Hyo-Jung ORD ID 1

1부산대학교
2공주대학교
3한국외국어대학교
4한국전력공사 전력연구원
5연세대학교 동서문제연구원
6울산과학기술원

Accredited

ABSTRACT

We investigated statistical evaluation parameters for 3D meteorological and air quality models and selected several quantitative indicator references, and summarized the reference values of the statistical parameters for domestic air quality modeling researcher. The finally selected 9 statistical parameters are MB (Mean Bias), ME (Mean Error), MNB (Mean Normalized Bias Error), MNE (Mean Absolute Gross Error), RMSE (Root Mean Square Error), IOA (Index of Agreement), R (Correlation Coefficient), FE (Fractional Error), FB (Fractional Bias), and the associated reference values are summarized. The results showed that MB and ME have been widely used in evaluating the meteorological model output, and NMB and NME are most frequently used for air quality model results. In addition, discussed are the presentation diagrams such as Soccer Plot, Taylor diagram, and Q-Q (Quantile-Quantile) diagram. The current results from our study is expected to be effectively used as the statistical evaluation parameters suitable for situation in Korea considering various characteristics such as including the mountainous surface areas.

Citation status

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