Literature DB >> 32601523

Differentiating between local and remote pollution over Taiwan.

Pavel Kishcha1, Sheng-Hsiang Wang2, Neng-Huei Lin2, Arlindo da Silva3, Tang-Huang Lin2, Po-Hsiung Lin4, Gin-Rong Liu2, Boris Starobinets1, Pinhas Alpert1.   

Abstract

In this study, an approach has been developed for differentiating between local and remote pollution over Taiwan, based on homogeneity perspective (variations of the standard deviation) of both AERONET measurements and NASA MERRA aerosol reanalysis (version 2, MERRA-2) over a 15-year period (2002 - 2017). The analysis of seasonal variations of the standard deviation of aerosol optical depth (AOD) measurements at six AERONET sites and MERRA AOD data in Taiwan showed that, in spring when remote aerosols dominate, the standard deviation is almost three times lower than that in autumn, when aerosols from local sources dominate. This finding was supported by MERRA AOD over the open ocean area: total AOD data were used to differentiate between local and remote pollution over both Taiwan and the open ocean area in the vicinity of Taiwan. Over Taiwan, MERRA total AOD showed a primary maximum in spring and a secondary one in autumn. Over the open ocean area, where there are no local sources of anthropogenic aerosols, MERRA total AOD showed only one maximum in spring and no maximum in autumn. This suggests that, in Taiwan, the maximum in autumn is attributed to local air pollution, while the pronounced maximum in spring is mainly caused by air pollution from continental Asia. The analyses of spatial distribution of 15-year monthly mean MERRA winds confirmed the above-mentioned results. Furthermore, similar to total AOD, MERRA sulfate AOD peaked in autumn over Taiwan, but not over the oceanic area: this indicates the contribution of local emissions of anthropogenic aerosols from the industrial sector. The standard deviation of MERRA sulfate AOD in spring is two-three times lower than the standard deviation in autumn: this is additional evidence that, in spring, sulfate aerosols from remote sources are predominant; while in autumn sulfate aerosols from local sources dominate.

Entities:  

Keywords:  AERONET; Local pollution; MERRA aerosol reanalysis; MERRA-2; Remote pollution; Taiwan

Year:  2018        PMID: 32601523      PMCID: PMC7323735          DOI: 10.4209/aaqr.2017.10.0378

Source DB:  PubMed          Journal:  Aerosol Air Qual Res        ISSN: 1680-8584            Impact factor:   3.063


  5 in total

1.  The PM2.5 and PM10 particles in urban areas of Taiwan.

Authors:  M L Chen; I F Mao; I K Lin
Journal:  Sci Total Environ       Date:  1999-02-09       Impact factor: 7.963

2.  Trans-Pacific transport of dust aerosols from East Asia: Insights gained from multiple observations and modeling.

Authors:  Jianping Guo; Mengyun Lou; Yucong Miao; Yuan Wang; Zhaoliang Zeng; Huan Liu; Jing He; Hui Xu; Fu Wang; Min Min; Panmao Zhai
Journal:  Environ Pollut       Date:  2017-07-27       Impact factor: 8.071

3.  The MERRA-2 Aerosol Reanalysis, 1980 - onward, Part I: System Description and Data Assimilation Evaluation.

Authors:  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
Journal:  J Clim       Date:  2017-07-27       Impact factor: 5.148

4.  Evaluation of PM2.5 surface concentration simulated by Version 1 of the NASA's MERRA Aerosol Reanalysis over Israel and Taiwan.

Authors:  Simon Provençal; Virginie Buchard; Arlindo M da Silva; Richard Leduc; Nathalie Barrette; Emily Elhacham; Sheng-Hsiang Wang
Journal:  Aerosol Air Qual Res       Date:  2017-01-01       Impact factor: 3.063

5.  Effects of Asian dust storm events on daily mortality in Taipei, Taiwan.

Authors:  Yong-Shing Chen; Pai-Ching Sheen; Eng-Rin Chen; Yi-Kuen Liu; Trong-Neng Wu; Chun-Yuh Yang
Journal:  Environ Res       Date:  2004-06       Impact factor: 6.498

  5 in total
  1 in total

1.  Aerosol Impacts on Water Relations of Camphor (Cinnamomum camphora).

Authors:  Chia-Ju Ellen Chi; Daniel Zinsmeister; I-Ling Lai; Shih-Chieh Chang; Yau-Lun Kuo; Jürgen Burkhardt
Journal:  Front Plant Sci       Date:  2022-06-20       Impact factor: 6.627

  1 in total

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