کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4444141 1311225 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Inter-annual variability and long-term trend of UV-absorbing aerosols during Harmattan season in sub-Saharan West Africa
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
پیش نمایش صفحه اول مقاله
Inter-annual variability and long-term trend of UV-absorbing aerosols during Harmattan season in sub-Saharan West Africa
چکیده انگلیسی

The inter-annual variability and long-term trend of UV-absorbing aerosols (mainly soil dust and smoke from biomass burning) during Harmattan seasons in the Sahel zone of Nigeria have been analyzed using the total ozone mapping spectrometer aerosol index (TOMS AI) and horizontal visibility data from synoptic stations in the zone. The relationship between daily TOMS AI and horizontal visibility (Vx  ) during the Harmattan seasons in the zone is also investigated. Analyses of 25-year TOMS AI data and 30-year horizontal visibility data reveal that in addition to inter-annual variability, there was a general decreasing trend which suggests increasing dustiness over the period. The Harmattan season mean horizontal visibility for the 1990–1999 decade was 18.9% lower than the mean value for the corresponding seasons in 1970–1979 decade. Also the mean TOMS AI for 2001–2004 Harmattan seasons was 24% higher than that of the corresponding seasons of 1979–1984. These results suggest that in the Sahel zone of Nigeria, the average atmospheric dust loadings in recent Harmattan seasons were generally higher than those of preceding three decades. It has also been shown that in the Sahel zone of Nigeria the relationship between mean daily TOMS AI and horizontal visibility (Vx¯) is of the form: AI=-kln(Vx¯)+C, where k and C   are constants. The strong correlation coefficient, r=-0.92r=-0.92, between AI and Vx¯ indicates that TOMS AI captures the variability of atmospheric dust concentration in the region nearly as well as horizontal visibility from surface observation. Thus, TOMS AI and surface visibility data could complement each other for monitoring dust and smoke events in the West African Sahel zone.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Environment - Volume 41, Issue 7, March 2007, Pages 1550–1559
نویسندگان
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