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Open Access

Correction

Correction: Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements

  • Siwatt Pongpiachan,
  • Qiyuan Wang,
  • Ronbanchob Apiratikul,
  • Danai Tipmanee,
  • Li Li,
  • Li Xing,
  • Xingli Mao,
  • Guohui Li,
  • Yongming Han,
  • Junji Cao,
  • Vanisa Surapipith,
  • Aekkapol Aekakkararungroj,
  • Saran Poshyachinda

An additional affiliation is missing for the first author. Siwatt Pongpiachan is also affiliated with the National Astronomical Research Institute of Thailand (Public Organization), Chiangmai, Thailand.

The correct affiliations are as follows:

Siwatt Pongpiachan1,2, Qiyuan Wang3, Ronbanchob Apiratikul4, Danai Tipmanee5, Li Li3, Li Xing6, Xingli Mao6, Guohui Li3, Yongming Han3, Junji Cao3, Vanisa Surapipith1, Aekkapol Aekakkararungroj7, Saran Poshyachinda1

1 National Astronomical Research Institute of Thailand (Public Organization), Chiangmai, Thailand, 2 NIDA Center for Research & Development of Disaster Prevention & Management, School of Social and Environmental Development, National Institute of Development Administration (NIDA), Bangkok, Thailand, 3 State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences (IEECAS), Xi’an, China, 4 Faculty of Science, Suansunandha Rajabhat, Bangkok, Thailand, 5 Faculty of Technology and Environment, Prince of Songkla University, Phuket, Thailand, 6 School of Geography and Tourism, Shaanxi Normal University, Xi’an, China, 7 Asian Disaster Preparedness Center (ADPC), Bangkok, Thailand.

Reference

  1. 1. Pongpiachan S, Wang Q, Apiratikul R, Tipmanee D, Li L, Xing L, et al. (2024) Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements. PLoS ONE 19(3): e0287187. https://doi.org/10.1371/journal.pone.0287187.

Citation: Pongpiachan S, Wang Q, Apiratikul R, Tipmanee D, Li L, Xing L, et al. (2024) Correction: Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements. PLoS ONE 19(4): e0302975. https://doi.org/10.1371/journal.pone.0302975

Published: April 30, 2024

Copyright: © 2024 Pongpiachan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.