ارزیابی زمانی-مکانی غلظت ستونی ذرات معلق (pm2.5) ناشی از رویدادهای گردوغباری در ایران با استفاده از داده‌های بازتحلیل nasa/merra-2

ذرات معلق کوچک‌تر از 2.5 میکرون یکی از مهم‌ترین آلاینده‌های هوا هستند که از تنوع و انتشار گسترده‌ای برخوردار می‌باشند. رویدادهای گردوغبار یکی از مهم‌ترین منابع طبیعی انتشار ذرات معلق در جو می‌باشند. مطالعه‌ حاضر با هدف بررسی تراکم و پراکنش فضاییزمانی ذرات معلق pm2.5 ناشی از رویدادهای گردوغباری در جو ایران طی دوره آماری (2019–1980) بر اساس سامانه ماهواره مبنای merra-2 انجام شده‌است. داده‌های مربوطه با قدرت تفکیک زمانی ماهانه، فصلی و سالانه و مکانی°0.625 × °0.5 تهیه و پس از اعمال پیش پردازش‌های لازم، بارزسازی، تجزیه‌وتحلیل شد. نتایج حاصله به خوبی بیانگر افت‌وخیزهایی در تراکم ذرات معلق pm2.5 طی سال‌های آماری مورد مطالعه‌‌است. اما به‌طور کلی تراکم ذرات معلق pm2.5 رو به افزایش بوده و روند صعودی آن به‌خصوص در سال‌های آخر دوره آماری مشاهده شد. تحلیل‌های آماری تفاوت‌های زیادی را به لحاظ زمانی و مکانی در میزان ذرات معلق pm2.5 نشان می‌دهد. در میان ماه‌های موردمطالعه، بیشترین/کمترین تراکم ذرات معلق pm2.5 به‌ترتیب در ماه‌های می، آوریل و جولای/دسامبر، ژانویه و نوامبر برآورد شد. به‌لحاظ فصلی هم بیشترین/کمترین تراکم pm2.5 در فصول تابستان/زمستان اتفاق افتاده‌است. توزیع مکانی حاکی‌از بیشترین تراکم ذرات معلق در بخش‌های جنوبی، شرقی و شمال‌شرق می‌‌باشد که بیانگر تاثیر قابل‌توجه کانون‌های محلی و فرامحلی گردوغبار بر افزایش تراکم ذرات معلق pm2.5 در این نواحی می‌باشد. تحلیل همبستگی نیز رابطه مثبت معناداری میان میزان ذرات معلق pm2.5 با دمای سطح زمین و رابطه منفی معناداری با رطوبت سطح خاک و بارش نشان داده‌است.

Evaluation of Spatiotemporal Column Particulate Matter Concentration (PM2.5) Due to Dust Events in Iran Using Data from NASAN / MERRA-2 Reanalysis Model

Mineral suspended particles, in addition to being important components of the Earth’s atmosphere, play an important role in the atmosphereEarth energy interactions and geochemical cycles of the Earth system. The meteorological and climatic importance of atmospheric particulate matter can be attributed to its effects on the energy level of the EarthEarth system, physical, dynamic, and chemical changes in the atmosphere at regional and global scales, absorption and emission of radiation in the atmosphere, micro physical changes and radiative properties of clouds and changes in snow and ice levels that occur. Fine particles smaller than 2.5 microns are one of the most important air pollutants with a wide variety, complexity and diffusion. Dust events are one of the most important natural sources of particulate matter in the atmosphere. In recent decades, air pollution in many parts of the world has raised public concerns about their health effects. Epidemiological studies have shown that lung disease, cardiovascular disease, and their mortality are associated with particulate matter. Although the effects of particles on both climate and air quality has been evident over the past few decades, continuous monitoring will still be important. In recent years, techniques, and models based on satellite data has made significant contributions to the monitoring of particles. Different versions of the MERRAbased satellite model have excellent capabilities in the study of particles and its time series analysis. The MERRA2 model (the ModernEra Retrospective analysis for Research and Applications, Version 2 called MERRA2) is based on the analysis of satellite data (Moloud et al., 2012) and is one of the most reliable models for assisting various environmental scientists to answer questions related to climate research and climate change, to make optimal use of the created satellite observations. This study aims to investigate the spatiotemporal density and dispersion of PM2.5 suspended particles due to dust events in the Iranian atmosphere during the statistical period (19802019) based on the MERRA2 based satellite model. Here, the meaning of column PM2.5 suspended particles is PM2.5 suspended particles of dust in a vertical column from the ground. Relevant data was prepared with monthly, seasonal, annual and spatial time steps of 0.5°x 0.625°and after applying the necessary preprocessing, they were identified and analyzed. The results show good fluctuations in PM2.5 particulate matter density during the statistical years studied. But in general, the density of PM2.5 suspended particles increasing and its upward trend is observed especially in the last years of the statistical period. The results showed that MERRA2 model has a good performance in monitoring the concentration of PM2.5 particulate matter in the vertical column of the atmosphere. The average of particulate matter PM2.5 in the atmosphere of this area is 61/23 Mg/m2, which indicates the high concentration of these particles in the atmosphere compared to other parts of the world, including the United States (Bouchard et al., 2016a), Taiwan (Provence et al., 2017a) and Europe (Provence et al., 2017b). On the other hand, the highest concentrations of these particles are in the southwest of Iran, southern coastal areas, eastern regions, deserts of central Iran and part of northern Iran and the lowest is estimated over the Zagros highlands. The spatial distribution of PM2.5 suspended particles over the Iran area depends on the frequency of dust events, distance from emission centers, seasons, rainfall and other climatic parameters (soil surface temperature, soil moisture, etc.). In this sense, in the warm months and seasons of the year, which are associated with the increasing land surface temperature, decreasing rainfall and, consequently, decreasing soil surface moisture, the conditions for the formation of the dust events are the release of suspended particles into the atmosphere. So that among the months of the year, May/December and between the seasons, summer/winter had the highest/the lowest value of column concentration of PM2.5 suspended particles in the over Iran. Analysis of correlation values based on Pearson linear regression relationship between PM2.5 suspended particles in the atmosphere (response variable) with some meteorological parameters (independent variables) such as; precipitation, soil surface moisture and soil surface temperature in the geographical area of Iran, well indicate the significant relationship between this variable and the above parameters. So that in the meantime; the amount of correlation between PM2.5 suspended particles over Iran with soil surface temperature indicates a significant positive relationship (R = 81%), a strong negative relationship with soil surface moisture (R = 76%) and a significant relationship with monthly precipitation, negative (R = 61%). This means that the concentration of PM2.5 suspended particles over Iran is strongly influenced by environmental parameters, so that in the time series analysis, the presence of seasonal behavior indicates a relatively stable time pattern of PM2.5 suspended particles distribution in the atmosphere over Iran.