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Long-Term Spatiotemporal Characteristics and Influencing Factors of Dust Aerosols in East Asia (2000–2022)

Remote Sensing, ISSN: 2072-4292, Vol: 16, Issue: 2
2024
  • 4
    Citations
  • 0
    Usage
  • 10
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    4
    • Citation Indexes
      4
  • Captures
    10
  • Mentions
    2
    • Blog Mentions
      1
      • 1
    • News Mentions
      1
      • 1

Most Recent Blog

Remote Sensing, Vol. 16, Pages 318: Long-Term Spatiotemporal Characteristics and Influencing Factors of Dust Aerosols in East Asia (2000–2022)

Remote Sensing, Vol. 16, Pages 318: Long-Term Spatiotemporal Characteristics and Influencing Factors of Dust Aerosols in East Asia (2000–2022) Remote Sensing doi: 10.3390/rs16020318 Authors: Yanjiao

Most Recent News

Study Results from University of Chinese Academy of Sciences Update Understanding of Remote Sensing [Long-Term Spatiotemporal Characteristics and Influencing Factors of Dust Aerosols in East Asia (2000-2022)]

2024 FEB 13 (NewsRx) -- By a News Reporter-Staff News Editor at Tech Daily News -- A new study on remote sensing is now available.

Article Description

The Taklamakan Desert Region (TDR) and the Gobi Desert Region (GDR) in East Asia significantly impact air quality, human health, and climate through dust aerosols. Utilizing the MERRA-2 dataset’s long-term dust aerosol optical depth (DAOD) at 550 nm from 2000 to 2022, we systematically monitored the spatiotemporal dynamics of DAOD. Our analysis covered annual, seasonal, and monthly scales, employing geographical detector analyses to investigate the impact of eight factors on DAOD distribution. Over the 23-year period, the interannual variability in DAOD across East Asia was not pronounced, but a discernible decreasing trend was observed, averaging an annual decrease of −0.0002. The TDR had higher DAOD values (0.337) than the GDR (0.103). The TDR showed an average annual increase of 0.004, while the GDR exhibited an average annual decrease of −0.0003. The spatial distribution displayed significant seasonal variations, with peak values in spring, although the peak months varied between the TDR and GDR. The driving factor analysis revealed that relative humidity and soil moisture significantly impacted the DAOD spatial distribution in East Asia, which were identified as common driving factors for both the region and the major dust sources. Complex mechanisms influenced the variation in DAOD, with interactions between variables having a greater impact than individual effects. The geodetector-derived interaction q-value identified the collective impact of soil temperature and relative humidity (0.896) as having the highest impact on the spatial and temporal DAOD distribution. The overall spatial pattern exhibited a nonlinear enhancement trend, with the TDR and GDR showing bilinear enhancement patterns. These findings contribute to a better understanding of the factors influencing DAOD, offering a theoretical basis for atmospheric pollution control in East Asia.

Bibliographic Details

Yanjiao Wang; Jiakui Tang; Wuhua Wang; Zhao Wang; Jiru Wang; Bowen Chu; Shunbo Liang

MDPI AG

Earth and Planetary Sciences

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