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Distinguishing Between Remote and Local Air Pollution Over Taiwan: An Approach Based on Pollution Homogeneity Analysis

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Air Pollution Modeling and its Application XXVI (ITM 2018)

Abstract

An analysis of pollution homogeneity has been conducted to distinguish between remote and local pollution which contributes to month to month changes in aerosol optical depth (AOD) over the Taiwan area. This was carried out using both AERONET measurements at six monitoring sites in Taiwan and NASA MERRA-2 reanalysis, over the 15-year period from 2002 to 2017. As a measure of air pollution homogeneity we used the AOD standard deviation: the more homogeneous the spatial distribution of air pollution, the lower the AOD standard deviation is. Using this approach, we found that, over Taiwan, in autumn, inhomogeneous local air pollution is predominant, while, in spring, homogeneous remote air pollution from south-east Asia dominates. In autumn, when inhomogeneous aerosols from local sources dominate, the AOD standard deviation is essentially higher than that in spring, when homogeneous aerosols from remote sources dominate. Our approach allowed us to distinguish between homogeneous remote and inhomogeneous local sulfate air pollution of similar optical properties and chemical composition.

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References

  1. V. Buchard, A. Randles, A.M. da Silva, A. Darmenov, P.R. Colarco, R. Ggovindaraju, R. Ferrare, J. Hair, A.J. Beyersdorf, L.D. Ziemba, H. Yu, The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: evaluation and case studies. J. Clim. 30, 6851–6872 (2017). https://doi.org/10.1175/JCLI-D-16-0613.1

    Article  Google Scholar 

  2. P. Kishcha, S.-H. Wang, N.-H. Lin, A.M. da Silva, T.-H. Lin, P.-H. Lin, G.-R. Liu, B. Starobinets, P. Alpert, Differentiating between local and remote pollution over Taiwan. Aerosol Air Qual. Res. 18, 1788–1798 (2018). https://doi.org/10.4209/aaqr.2017.10.0378

    Article  CAS  Google Scholar 

  3. C.A. Randles, A.M. da Silva, V. Buchard, P.R. Colarco, A. Darmenov, R. Govindaraju, A. Smirnov, B. Holben, R. Ferrare, J. Hair, Y. Shinozuka, C.J. Flynn, The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: system description and data assimilation evaluation. J. Clim. 30, 6823–6850 (2017). https://doi.org/10.1175/JCLI-D-16-0609.1

    Article  CAS  Google Scholar 

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Correspondence to Pavel Kishcha .

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Kishcha, P. et al. (2020). Distinguishing Between Remote and Local Air Pollution Over Taiwan: An Approach Based on Pollution Homogeneity Analysis. In: Mensink, C., Gong, W., Hakami, A. (eds) Air Pollution Modeling and its Application XXVI. ITM 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-22055-6_44

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