ارزیابی زمانی - مکانی غلظت ستونی ذرات معلق (PM2.5) ناشی از رویدادهای گردوغباری در ایران با استفاده از داده‌های مدل بازتحلیل NASA/MERRA-2

نوع مقاله : پژوهشی

نویسنده

استادیار، گروه جغرافیا، دانشکده علوم انسانی، دانشگاه زنجان، زنجان، ایران

چکیده

ذرات معلق کوچکتر از 5/2 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. مطالعه‌ی حاضر با هدف بررسی تراکم و پراکنش فضایی ـ زمانی ذرات معلق PM2.5 ناشی از رویدادهای گردوغباری در جوِ ایران طی دوره‌ی آماری (2019 – 1980) براساس مدل ماهواره مبنای MERRA-2 انجام شده‌است. داده‌های مربوطه با قدرت تفکیک زمانی ماهانه، فصلی و سالانه و مکانی 0.5° x 0.625° تهیه و پس از اِعمال پیش پردازش‌های لازم، تجزیه و تحلیل گردید. نتایج حاصله به خوبی بیانگر افت‌وخیزهایی در تراکم ذرات معلق PM2.5 طی سال‌های آماری مورد مطالعه‌‌است. اما به طور کلی تراکم ذرات معلق PM2.5 رو به افزایش بوده و روند صعودی آن بخصوس در سال‌های آخر دوره‌ی آماری مشاهده گردید. تحلیل‌های آماری تفاوت‌های زیادی را به لحاظ زمانی و مکانی در میزان ذرات معلق PM2.5 نشان می‌دهد. در میان ماه‌های مورد مطالعه؛ بیش‌ترین/کم‌ترین تراکم ذرات معلق PM2.5 به ترتیب در ماه‌های می، آوریل و جولای/ دسامبر، ژانویه و نوامبر برآورد گردید. به لحاظ فصلی هم بیشترین/کمترین تراکم PM2.5 در فصول تابستان/ زمستان اتفاق افتاده‌است. توزیع مکانی حاکی از بیشترین تراکم ذرات معلق در بخشهای جنوبی، شرقی و شمال‌شرق می باشد که بیانگر تأثیر قابل توجه کانون‌های محلی و فرامحلی گردوغبار بر افزایش تراکم ذرات معلقPM2.5 در این نواحی می‌باشد. تحلیل همبستگی نیز رابطه‌ی مثبت معناداری میان میزان ذرات معلق PM2.5 با دمای سطح زمین و رابطه‌ی منفی معناداری با رطوبت سطح خاک و بارش نشان داده‌است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

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

نویسنده [English]

  • Koohzad Raispour
Assistant Professor, Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan, Iran
چکیده [English]

Mineral suspended particles, in addition to being important components of the Earth's atmosphere, play an important role in the atmosphere-Earth 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 Earth-Earth 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 occur, he explained. 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 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 MERRA-based satellite model have excellent capabilities in the study of particles and its time series analysis. The MERRA-2 model (the Modern-Era Retrospective analysis for Research and Applications, Version 2 called MERRA-2) 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. The study aims was to investigate the spatio-temporal density and dispersion of PM2.5 suspended particles due to dust events in the Iranian atmosphere during the statistical period (1980-2019) based on the MERRA-2 based satellite model. In this study, the meaning of column PM2.5 suspended particles are the measurement of PM2.5 suspended particles of dust origin that has gone into space 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 are increasing and its upward trend was observed especially in the last years of the statistical period. The results showed that MERRA-2 model has a good performance in monitoring the concentration of PM2.5 particulate matter in the vertical column of the Iranian atmosphere. The average of particulate matter PM2.5 in the atmosphere of Iran is 61/23 Mg/m2, which indicates the high concentration of these particles in the Iranian atmosphere compared to other parts of the world, including the United States (Bouchard et al., 2016), Taiwan (Provence et al., 2017) And Europe (Provence et al., B2017). On the other hand, the highest concentration 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 in the Iranian atmosphere 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 Iranian 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 Iranian atmosphere. Analysis of correlation values based on Pearson linear regression relationship between PM2.5 suspended particles in Iranian 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 in Iranian barley 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 in the Iranian atmosphere 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 of Iran.

کلیدواژه‌ها [English]

  • Particulate Matter (PM 2.5)
  • MERRA-2 Model
  • atmospheric pollution
  • Dust Phenomena
  • Iran