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Detection of areas prone to wind erosion and air pollution using DSI and PDSI indices

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Abstract

Many significant dust storms have occurred in the Central part of Iran since ancient times. Recently, the frequency and intensity of such events have increased remarkably, especially in hyper-arid and arid zones of Yazd province. Under these conditions, it is necessary to address several notable challenges, including methods of detecting the potential sites for wind erosion and dust storms and degree of success in reducing air pollution and dust storms. Thus, this study utilized weather codes of dust to monitor wind erosion and dust storm frequency in Yazd province, Iran. The study also defined a new appropriate index to evaluate air pollution in terms of different dust events. A new dust storm index for air pollution (PDSI) introduces to monitor air pollution. Daily dust storm index (DSI) is another empirical model to study dust storm activities. Weather codes associated with dust events were used at 11 synoptic stations in the Yazd province during 2000–2017. PDSI assessment using meteorological code 06 and hourly scale is used as the main tools for evaluating air pollution. Evaluation of dust weather codes using different weights performed to properly analyze wind erosion and air pollution status at different spatial and temporal scales. Yazd station had the highest amount of air pollution (105.9). Meybod had the highest amount of wind erosion (9.76) with a significant potential to occur dust storm. Assessment of the DSI and PDSI indicates a significant increase (about ten times) in wind erosion and air pollution in recent years. Poor land management and the existence of outdoor dust haze are the main causes of the terrible increase in air pollution during 2008–2017. It is recommended to promote sustainable industrial development and reduce the negative impacts of mining activities in regions with medium to severe air pollution.

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'ArcGIS 10.3′ – Microsoft EXCEL2013 – SPSS 16.0.

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Correspondence to Mohammad Zare.

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Jebali, A., Zare, M., Ekhtesasi, M.R. et al. Detection of areas prone to wind erosion and air pollution using DSI and PDSI indices. Nat Hazards 108, 1221–1235 (2021). https://doi.org/10.1007/s11069-021-04728-3

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  • DOI: https://doi.org/10.1007/s11069-021-04728-3

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