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  • 标题:Patterns and Sources of PM10 in the Ecologically Sensitive Himalayan Region in Himachal Pradesh, India
  • 本地全文:下载
  • 作者:Raman Kumar ; Jui-Huan Lee ; Ruei-Hao Shie
  • 期刊名称:Aerosol and Air Quality Research
  • 印刷版ISSN:1680-8584
  • 出版年度:2020
  • 卷号:20
  • 期号:3
  • 页码:410-418
  • DOI:10.4209/aaqr.2019.03.0133
  • 语种:English
  • 出版社:Chinese Association for Aerosol Research in Taiwan
  • 摘要:In this study, we aimed to comprehensively investigate particulate matter less than 10 µm in aerodynamic diameter (PM10) at industrial, residential, and ecologically sensitive sites in the western Himalayan region. To achieve this goal, PM10 data from 20 stations across the state of Himachal Pradesh were used to characterize the spatial and temporal patterns. To determine the potential sources of pollution, we created a bivariate polar plot based on wind speed and direction. Our findings showed that only the PM10 concentrations at the ecologically sensitive sites (59.02 ± 34.77 µg m–3) were below the National Ambient Air Quality Standard of 60 µg m–3. The concentrations at both the industrial (115.9 ± 47.82 µg m–3) and residential (87.16 ± 35.83 µg m–3) sites exceeded the standard, with the highest concentrations occurring during the winter and the lowest occurring during the monsoon season of the same year. The emission sources both within and outside of the Himachal Pradesh for each site were determined based on the bivariate polar plot, and industrial and vehicular emission, biomass and solid waste burning, dust from a nearby unpaved road, and long-range transported pollution were identified as contributors to the deterioration of air quality in this state. Moreover, the monsoon season significantly affected air quality. We conclude that local industrial and traffic pollution and long-range-transported emissions increased the PM10 concentration in Himachal Pradesh, resulting in its exceedance of the limit indicated in the World Health Organization (WHO) guidelines.
  • 关键词:Himachal Pradesh; Air pollution; Spatial and temporal variation; Ecologically sensitive; Bivariate polar plot.
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