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• W4385760657 abstract "Middle Eastern countries suffer from dust events due to extended arid areas. Among them, Iran is a country experiencing a high record of dust events each year causing major environmental challenges. Although there are previous studies of the present situations of dust storm occurrences in Iran, most studies have analyzed the meteorological dataset in limited weather stations and areas in Iran. To understand the nationwide trends of the distributions and frequencies of dust storm events, comprehensive statistical evaluations of dust storm events, based on different dust categories, are required. Therefore, this study analyzes 12-year meteorological databases obtained at 427 stations in Iran to clarify the distribution of dust events and occurrence frequencies of the dust in a recent decade by classifying the dust events into suspended dust, rising dust, and dust storm. The highest record of the days belongs to rising dust, which surpassed 150 days per year, followed by suspended dust with over 100 days per year, and, finally, dust storms with a frequency of 30 days per year as annual statistics of dust events. In contrast, there were some stations that recorded minimal occurrences of dust events during the observation periods. To prove the spatial nonuniformity of the dust events, suspended dust events showed a distinct concentration in the western regions of the country, while rising dust tended to occur more frequently in the southern, eastern, and central parts of Iran. Accordingly, seasonal analyses indicate that the highest number of dust events occurred during the spring season, with the number of stations experiencing dust events being greater than during other seasons in all three categories. Nonetheless, annual analyses of dust events do not demonstrate any significant trends, with only 2012 having the highest record of dust events across all three categories. In terms of monthly analyses, dust events tended to increase from late spring to early summer in the suspended dust and rising dust categories. These analyses demonstrate the importance of studying numerous weather station datasets to clarify spatial trends of dust events with long-term variations." @default.
• W4385760657 created "2023-08-12" @default.
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• W4385760657 date "2023-08-11" @default.
• W4385760657 modified "2023-10-18" @default.
• W4385760657 title "Identifying the Distribution and Frequency of Dust Storms in Iran Based on Long-Term Observations from over 400 Weather Stations" @default.
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• W4385760657 doi "https://doi.org/10.3390/su151612294" @default.
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