Modeling of High Density of Ozone in Seoul Area with Non-Linear Regression

비선형 회귀 모형을 이용한 서울지역 오존의 고농도 현상의 모형화

  • Published : 2009.08.31


While characterized initially as an urban-scale pollutant, ozone has increasingly been recognized as a regional and even global-scale phenomenon. The complexity of environmental data dynamics often requires models covering non-linearity. This study deals with modeling ozone with meteorology in Seoul area. The relationships are used to construct a nonlinear regression model relating ozone to meteorology. The model can be used to estimate that part of the trend in ozone levels that cannot be accounted for by trends in meteorology.


Long term trend;non-linear regression;ozone;seasonal trend


  1. Bloomfield, P., Royle, A., Steinberg, L. J. and Yang, Q. (1996). Accounting for meteorological effects in measuring urban ozone levels and trends, Atmospheric Environment, 30, 3067-3078
  2. Chambers, J. M. and Hastie, T. J. (1993). Statistical Models in S, Chapman & Hall, New York
  3. Cox, W. M. and Chu, S. H. (1992). Meteorologically Adjusted Ozone Trends in Urban Areas: A Probability Approach, U.S. Environmental Protection Agency, Technical Support Division MD-14, Research Triangle Park, NC 27711
  4. Davis, J. M., Brian, K. E. and Bloomfield, P. (1998). Modeling ozone in the Chicago urban area, Case Studies in Environmental Statistics, 5-26
  5. Hastie, T. J. and Tibshirani, R. J. (1990). Generalized additive models, Chapman & Hall, New York
  6. Tukey, J. W. (1977). Explomtory Data Analysis, Addison Wesley, Reading, Massachusetts