بررسی روند تغییرات گردوغبار در نیمه‌شرقی ایران

در سال‌های اخیر، پدیده گردوغبار به یکی از مهمترین چالش‌های زیست‌ محیطی در سراسر جهان تبدیل شده است. کشور ایران با توجه به حاکم بودن اقلیم خشک و نیمه‌خشک بر آن، همیشه از تولید و گسترش مواد معلق در هوا به ویژه گردوغبار آسیب دیده است. در پژوهش حاضر به ارزیابی روند و شدت تغییرات گردوغبار با استفاده از شاخص عمق نوری هواویز یا aerosol optical depth در نیمه‌شرقی ایران پرداخته شد. بدین منظور ابتدا در سامانه گوگل ارث انجین از داده‌های aod باند آبی با طول موج nm470 محصول mcd19a2 سنجنده مودیس در مقیاس زمانی روزانه میانگین‌گیری شد و داده‌های ماهانه aod از ابتدای سال 1380 تا انتهای سال 1401 استخراج شد. در مرحله بعد ماه‌های دارای بیشترین میانگین aod انتخاب شد و ارزیابی روند و شدت تغییرات گردوغبار بر روی داده های این ماه‌ها انجام. به‌منظور ارزیابی روند تغییرات aod از آزمون من‌کندال و همچنین برای ارزیابی شدت تغییرات آن از رگرسیون خطی استفاده شد. نتایج حاکی از آن است که بیشترین مقدار aod در محدوده مورد بررسی در چهار ماه آوریل، می، ژوئن و جولای معادل با ماه‌های شمسی فروردین تا مرداد رخ داده است. همچنین نتایج تحلیل روند و شدت تغییرات aod در ماه آوریل با احتمال بیش از 70% و با شدت زیاد و خیلی زیاد در بیشتر مناطق مورد بررسی در حال افزایش است. این درحالی است که شاخص مورد بررسی در ماه های می، ژوئن و جولای به‌ترتیب در بخش قابل ملاحظه‌ای از نیمه‌غربی، نیمه‌شمالی و نیمه‌شرقی با شدت‌های مختلف با احتمال بیش از 70% در حال افزایش است. با توجه به نتایج پژوهش حاضر لازم است با مدیریت مناسب، عوامل موثر بر ایجاد گردوغبار در مناطقی که گردوغبار در حال افزایش است، روند تغییرات را کنترل یا کاهش داد.

investigating the trend of dust changes in the eastern half of iran

introduction the impact of dust storms on the ecosystem, human health, and economy is significant in the affected areas. in arid and semi-arid regions, dust is a natural occurrence that covers about one third of the earth's surface. this phenomenon is caused by wind erosion and factors such as the size of soil particles and their adhesion force, surface roughness, weather conditions such as longterm droughts cause it to intensify. to understand the impact of the dust phenomenon on humans and the environment, it is essential to evaluate the spatial and temporal distribution of dust and its changes and effects. numerous studies have been carried out in the field of evaluating dust changes using different methods. for example, using cmip5 models, synoptic fog systems are predicted to increase during the 21st century in the middle east. in addition, using aod obtained from modis and merra-2 sensors, researchers showed a significant upward trend in dust changes from 2000 to 2010. a significant upward trend was shown in iran's winter aod values during the period 2000 to 2010, and a decreasing trend during the period 2010 to 2018. a point can be spotted by examining various studies in the middle east and iran that evaluate the spatiotemporal changes of dust. statistical tests of time series study, such as mann-kendall spatially and pixel by pixel, have been used in limited research to evaluate the trend of dust changes. in iran, there is a research gap in not using spatial and pixel-by-pixel statistical tests to evaluate the trend of dust changes, as stated. this research aimed to provide a solution and address the problem by analyzing the spatial and temporal changes of dust using the aod index in the eastern half of the country. material and methods in this research, in order to evaluate the temporal-spatial changes of dust, the aod data of the blue band (470 nm) of the mcd19a2 product of the modis sensor was used. aod parameter is known as one of the most key factors in studying the climatic effects of aerosols and atmospheric pollution. in order to extract aod data, monthly data from 2001 to 2022 were obtained in the google earth engine system by averaging the daily aod data. over a 22-year period, the average of each month was calculated. the months that had the highest average aod values were chosen and their changes were evaluated. in this research, the mann-kendall test was used to evaluate the change process. menkendall's zm coefficient was calculated for months in the earth trend modeler (etm) of the terrset software to achieve this. in the next step, the intensity of monthly aod changes per time unit was calculated for 22 years in selected months. to simulate the process of changes, linear regression analysis can be utilized for this purpose. this method is used to determine the linear relationship between all the data of a dependent variable and the corresponding data of the independent index. if the slope is higher than zero, the dependent variable will change in the same direction as the independent variable. the dependent variable changes in the opposite direction of the independent variable if the slope is smaller than zero. the steeper the slope of changes, the greater the impact of the independent variable on the dependent variable. the earth trend modeler (etm) of terrset software also carried out this step. results and discussion based on the evaluation of the monthly average aod changes in the studied area, the trend and intensity of aod changes from 2001 to 2022 were assessed in april, may, june, and july. in most areas of the studied area, aod is increasing with a probability of more than 70%, and the intensity of changes is mostly high and very high in april. it can be concluded that aod is experiencing a strong increase in april. this is despite the fact that in may, june and july, respectively, a considerable