Evaluation Seasonal Trend of Iran Aerosol Index (AI) Based on Nimbus 7, Earth Probe and Aura Satellite Data

Introduction
Aerosols are solid or liquid particles in the air with a typical radius of 0.001 to 100 μm, which have significant and harmful effects on human health. Aerosols come from both natural and human sources, and in recent years, human activities associated with urbanization and industrialization has led to a steady increase in the amount of these particles in the airborne state.  Atmospheric aerosols play a key role in the energy budget of the Earth’s climate system through aerosol–radiation interactions (direct effect) and aerosol–cloud interactions (indirect effect). On the one hand, by absorbing and scattering solar and terrestrial radiation, aerosols generally cool the Earth’s surface and heat the atmosphere, depending on the absorption level of the aerosols. The southwestern part of the Asian continent (Middle East, Arabian Peninsula and Iran-Pakistan-Afghanistan, IPA) contains several deserts (Syrian-Iraqi desert, Rub-Al-Khali, An-Nafud, Al-Dahna, Karakum, Margo, Registan) and semi-desert areas (Iranian Plateau, Sistan) responsible for large emissions of dust aerosols that are usually accumulated over the Arabian Sea. The study of the precise variability of the AI ​​index in the long run can provide useful information on aggregates, their origin, spatial temporal variation, climate induction and its feedback in the climate system. This study the purpose of the seasonal evaluation of the Aerosol Absorption Index (AAI) was based on TOMS and OMI sensor data in Iran.
Materials and methods
The study area in this study is Iran based on seasonal period. The climate of Iran ranges from the subtropical dry to extremely dry zone in the eastern half and some central areas, wet to extremely wet zone in the southern coastal plains of the Caspian Sea, relatively wet zone in some areas in the west, and semi arid zones over the rest of the country. In this study, TOMS data from two Nimbus 7 satellites (1992-1979) and Earth Probe (1996-2005) and OMI (2015-2005) satellite EOS Aura The non-parametric Mann-Kendall test was used to identify the Aerosol Index trend.
The parametric and non-parametric methods have been used to identify the trend in many researchers, but nonparametric methods have been more considered by researchers due to their ability to monitor the unrelated data and also lack of necessity for the normality of data. Non-parametric Mann-Kendall test was used to evaluate the trend of Aerosol Index in Iran. This method is widely used in the field of environmental science. Like many other nonparametric methods such as Mann-Kendall, this method is based on the evaluation of the difference between time series observations
Results and discussion
Significant reduction in the trend The TOMS Satellite (EP) Earth Probe's Aerosol Index (AI) is far from waiting for dusty days and Aura satellite data. TOMS sensor data is not recommended for decomposition of the EP, because since 2001, due to the lack of proper calibration of this sensor, data from this sensor and the satellite provide irrational figures; The results have shown that TOMS sensor data is not suitable for the study of the EP, since since 2001, it is not calibrated for the data of this meter. The maximum incremental increase of the Aerosol index (AI) was calculated for OMI and the maximum decreasing trend of the Aerosol index (AI) used for the winter (TOMS satellite satellite EP) in autumn (TOMS sensor of two Nimbus7 and EP satellites). In spring, the soil moisture content decreased and the activation of dust springs decreased relative to the winter season from areas with decreasing trend and increased areas with increasing trend. In summer, areas with an increasing trend based on Nimbus7 satellite (100%) and Aura (96.74%) of the total pixels are covered. Maximum incremental rate and also the maximum average value of the Aerosol index (AI) trend are obtained based on the OMI Satellite Aura sensor in the fall season. The increase in the Aerosol Index (AI) in Iran is due to environmental and climatic conditions. Some factors including summer Shamal wind, the dynamic and thermal patterns of West Asia, and the Indus Low Pressure, played the greatest role in increasing the hygiene of Iran.
Conclusion
The maximum trend in the general trend of the AI ​​indicator in Iran in winter is the TOMS satellite Earth Probe satellite in the northeast and central parts. This is mainly due to the lack of calibration of the sensor and the satellite. The maximum incremental trend of the Iranian Aerosol Index (AI) for the OMI and the maximum decrease of the Aerosol Index (AI) were calculated for the fall (Numbus7 Satellite TOMS Sensor). The average trend of Iran's AI index for winter is not significant for any of the two sensors and three satellites. In the spring, the intensity and percentage increase was increased relative to the winter season. The growing trend in most parts of Iran is associated with dusty events originating from dry and desert lands of southwestern Iran, especially in Iraq. In the summer, Nimbus7 and Aura satellite data showed more than 95% of the country's total traffic. Zones with increasing trend of TOMS sensor Nimbus7 satellites are observed in all metropolis of Iran with 500,000 to 1 million and more than one million people. There were no negative trends in any cities. In the autumn, we observe the maximum percentage and the intensity of the significant increase of the Aerosol Index (AI based on the OMI satellite satellite Aura in the country. This trend can be correlated with decreasing precipitation and the inhibition of the following particles in the airborne atmosphere due to reduced moisture content. The increase in the trend of Huawei index in Iran is resutled from environmental conditions such as land use, soil moisture and drought. The significant factors in HomoSperm regional circulation systems are Caspian Sea–Hindu Kush Index (CasHKI), negative phase of Pacific Decadal Oscillation (PDO)) with fluctuations, Shamal winds, short-term phenomena such as frontal systems, low-level jets (LLJs), and low pressure of the document on the transit of these particles.