فصلنامه فیزیک زمین و فضا
سال چهل و ششم شماره 2 (تابستان 1399)

Inversion of magnetic data is the most important step in the interpretation of magnetic anomalies. Availability of 3-D inversion of magnetic data is required because earth material properties generally change in all three special dimensions. Magnetic data inversion has two main problems about non-uniqueness and instability of the solution which can be obviated by using constraints and a priori information. Non-uniqueness is the consequence of two ambiguities: I) following Gauss theorem, there are many equivalent sources that can produce the same known field at the surface (theoretical ambiguity), II) since the parameterization of the problem is such that there are more unknowns than observations, the system does not provide enough information in order to uniquely determine model parameters (algebraic ambiguity). Every measurement of data on the earth’s surface contains some noise which imposes large changes on the inverse solution, therefore the problem is also ill-posed. There are many constraints including compactness, minimization of inertia around an axis or a point, depth weighting and etc. Different combinations of these constraints in the objective function lead to different algorithms each of which are appropriate for some cases. In this paper, inversion algorithm proposed by Boulanger and Chouteau are utilized for the 3-D inversion of magnetic data. This technique was introduced for inversion of gravity data. Their algorithm takes the advantage of a model weighting matrix derived by multiplying compactness, hardness and depth weighting constraints. Furthermore, smoothness matrix is also inserted in the algorithm. Compactness constraint, introduced by Last and Kubic, try to minimize the volume of the anomalous body in 3-D. Hardness constraint, represented by P, is a diagonal matrix for which diagonal elements pii is fixed at 10-2 or 1 depending on whether the value of the ith initial susceptibility is fixed by geological information or not. Depth weighting function, introduced by Li and Oldenberg, is used to counteract the natural decay of the kernel, so all the cells have an equal probability during the inversion. The subsurface is discretized into a lot of cells for which the susceptibility of each cell is assumed to be constant. The model parameter, susceptibility contrast, is also limited to lower and upper bounds. This algorithm was programmed in MATLAB software, and its efficiency was investigated by applying it on synthetic and real data. The first synthetic model is a cube and inversion process was done for free-noisy and noisy data (5 % random noise) and in both cases recovered models were satisfactory. The second case is the model of vertical and dip dykes as a more complex synthetic example. Inverting free-noisy data leads to the exact recovering of true model. The reconstructed model obtained from noisy data actually represented an acceptable model. Therefore, results of synthetic cases were promising enough and convince us in order to apply the algorithm to real cases. Finally, the algorithm was applied two real profiles related to the archeological data sets of an area in old Pompeii city near Naples in Italy. Both profile lengths are 35.5 m with interval sampling of 10.4 cm. Inversion result of the data using this 3-D algorithm represents anomalies that are in a good agreement with subsurface anomaly positions.

Due to the importance of using an accurate stochastic model in estimation of the coordinates of points using the GNSS observation method, this study investigates the role of the elevation angle-dependent stochastic model. The least-squares estimation method is usually used in processing GNSS observations. This method requires the use of two essential models, one is functional model and the other is stochastic model. The functional model illustrates the relationship between observations and unknown parameters. The stochastic model presents the covariance matrix and the statistical properties (expectation) and dispersion of errors in observation, which expresses the accuracy and the correlation between the types of observations. A precise and detailed stochastic model for observations, expresses the receiver's internal noise, residual errors, and the correlation between the variables. Moreover, by choosing a suitable stochastic model, we can provide the necessary preconditions for solving the reliable phase ambiguity and precise positioning. In this study, we investigate and compare 9 stochastic models based on the satellite elevation angle. These 9 models are expressed as equations of four families of trigonometric functions , , improved trigonometric functions, and exponential functions. To do this, we use observations of a single point in two time epoch where simulated displacement was applied to it very precisely by the device. First, by using precise point positioning method, the horizontal coordinates of the point in two epochs were estimated by using 9 stochastic models. According to the accomplished comparison, we present the closest estimated value to the simulated real value of the stochastic models which are trigonometric functions , improved trigonometric functions and exponential functions respectively. Among these four models, The results of exponential function is closest to the simulated real value. Online services are then used to process point-of-view observations, according to which the two OPUS and AUSPOS services are most closest to the simulated real observations. Then the estimation of the accuracy of the horizontal components is examined by means of 9 presented stochastic models. According to the presented results, the highest accuracy and least error are related to the use of stochastic model  (improved trigonometric functions). Then, two stochastic models and matrix weights  and  (exponential functions) showed the highest accuracy. Using these three models with the highest accuracy, the average accuracy obtained for the East component is between 0.03 mm and 2.8 mm and for the North component is between 0.04 mm and 3.1 mm. In the next section, due to the accuracy obtained for the horizontal coordinate components in all epochs (sampling interval of 5 s) using these three stochastic models, fewer epochs are required to reach the level of accuracy of Dosimeter, Centimeter and Millimeter. In such a way that, for desired point, 277 epochs for the East component and 405 epochs for the North component are required to reach the millimeter precision level. Finally, considering the 5cm convergence condition for the horizontal components East and North, due to the three models used, this convergence condition is achievable after 5 minutes and 50 seconds for the East component and after 8 minutes and 5 seconds for the component North.

The magnetic resonance sounding (MRS) method is a relatively novel geophysical method, which allows for the estimation of hydrogeophysical parameters due to the direct sensitivity of hydrogen molecules of water. The use of this method makes it possible to determine the presence or absence of water below the surface more precisely and to determine the important characteristics of the hydrogeology parameters of the aquifer layer such as water content and hydraulic conductivity. The MRS technique is based on the Nuclear Magnetic Resonance (NMR) principles to determine the subsurface distribution of hydrogen protons. MRS field measurements are mostly carried out with a surface antenna as transmitter/receiver of electromagnetic signals. However novel instruments utilize a number of reference loops to mitigate noise in MRS signals. It enables us to use more sophisticated noise canceling strategies and it is possible to overwhelm the drawbacks from the single-channel MRS filtering techniques (Ghanati and Hafizi, 2017; Ghanati, et al, 2016b). To obtain depth information, a series of measurements at different pulse moments,  (where  is current amplitude and τ is pulse duration) are passed through the loop. The larger the pulse moment, the larger the penetration depth. By varying the pulse moment, a spatial distribution of aquifer properties with respect to the depth can be obtained from the MRS data inverse problem. From data space point of view, in the inversion of magnetic resonance sounding data, two types of algorithms have been presented: 1) Initial Amplitude Inversion (IAI) and 2) Time Step Inversion (TSI). Given that in the above-mentioned methods only a portion of the data is used for inversion, it is not possible to provide a stable solution with a suitable depth resolution in the inversion process, while the use of the full waveform inversion of the magnetic resonance signal (i.e., using whole data space) increases the stability and resolution of water content and relaxation time models. Magnetic resonance signals naturally show a multi-exponential behavior that is due to the suppression of signals from layers or sub-volumes that have different relaxation times. In this method, the concept of multi-exponential behavior is considered for magnetic resonance signal data due to the non-uniform distribution of relaxation time at sub-surface pores. The proposed algorithm is evaluated using some synthetic examples and a real data set with the assumption of multi-exponential regime. From the numerical experiments, it is clearly observed that the presented method obtains a more realistic distribution of relaxation time versus the depth of the survey compared to the IAI algorithm with the assumption of the mono-exponential behavior. Furthermore, since the amplitude of the magnetic resonance signal is related to the sub-surface water content directly, the theory of multi-dimensional behavior in the inversion of the magnetic resonance signal provides a significant improvement in the fitting of the signals, which makes it possible a more accurate and reliable estimate of sub-surface water content. Finally, to evaluate the accuracy of the algorithm assuming multi-exponential behavior of signals, Bootstrap uncertainty analysis is performed on the field data. Given the results of the uncertainty analysis and its comparison with the geological model obtained from the borehole results, the power of the proposed approach in estimating the position and water content of subsurface aquifers is clearly visible.

Groundwater is the largest available freshwater resource in the world. Aquifers provide drinking water to at least 50% of the global population, and account for 43% of all water used for irrigation. Groundwater resources can be expected to be increasingly relied upon, in the near future, as a consequence of rapid population growth and global environmental change. Cost-effective and efficient techniques for groundwater exploration, especially in karstic regions, can be used to as an appropriate tool to recognition of karst hydrogeological potential. This paper provides a method based on the RS/GIS for the recognition of high groundwater potential areas and geoelectrical tomography for precise determination of the water well drilling location. Groundwater mapping has been defined as a tool for systematic development and planning of water resources (Elbeih, 2015). Hydrogeological maps provide spatially distributed information about aquifers, including their geological, hydrogeological and hydrochemical characteristics. In this study, a hydro-tectonic model include effective layers on karst hydrogeology applied for the recognition of the high groundwater potential in karstic areas of Izeh, northeast Khuzestan. The combination of remote sensing and GIS used to overlay the major layers, i.e. distance from discharge point, elevation difference, fracture density, slope, and fracture intersection density. Generally, high altitude regions have a low groundwater potential and more groundwater can be found at lower altitudes; therefore, the altitude map generated from the DEM represents difference to known elevation of the discharge points. The areas away from the discharge point generally have lower probability of groundwater occurrence. The distance analysis in GIS was used to determine the map of distance from discharge point. Slope angle can be considered as a surrogate of surface runoff velocity and vertical percolation which affects recharge processes. However, in this study, the slope angle was considered as a positive factors on groundwater potential in the karstic areas. Geological fractures can have a significant effect on storage and flow of groundwater reservoirs. Especially in areas with shallow bedrock fractures, water infiltration can be enhanced due to increased porosity and hydraulic conductivity (Rao et al. 2001). The fracture locations in the study area were determined from the remote sensing techniques. The parameter are weighted from 1 to 5 based on their importance in karst hydrogeology. For the exact determination of the water well drilling locations in high groundwater potential areas, the geoelectrical operation is done in two profiles using Dipole-Dipole array followed by electrical resistivity tomography. Over 20 boreholes have been drilled in karstic aquifer of Izeh for supplying the residence with drinking water. Despite the common use of geology for improving the siting of boreholes, some of the drilled holes does not deliver enough water to be equipped. The ERT method is used to determine the electrical resistivity distribution of the subsurface. Resistivity of the limestone rocks is linked to several parameters including type of limestone, cavity, water content, marl layer, electrical conductivity of water and the layer thickness. Because of different respective electrical resistivities in karstic areas, the ERT method provides useful results on the geometry of bedrock and aquifer. In an ERT survey, after inversion of the field data, the method provided a two-dimensional (2D) resistivity model of a section of the underground. Field data processing was performed with RES2DINV software. The parameters used in the inversion were the same for both of profiles, and topography was taken to normalize profile elevations to the actual ground surface. A robust algorithm was chosen for the inversion, because it provides more net changes in resistivity between different parts of the section. However, care must be taken when studying the final sections, because the geometry and boundaries of the structures are not always clearly identified and may be influenced by changes in resistivity due to rocks outside the plane of the section. The interpreted sections must be understood as an indication of the approximate location of the lithological boundaries, and not as its true geometry. The interpretation of the resistivity sections for all the ERT profiles has been drawn with the help of the correlation between the resistivity and the lithology along with the hydrogeologic data, and taking into account the continuity of the resistivity values at the crossing of the profiles. Overall, a very complicated structure is interpreted with the presence of dry and wet limestones, cavities, and marly layers interbeded with carbonates. Finally, two locations were proposed for drilling of water wells in the Izeh karstic area. The drilling of a high yield water well (discharge of 61 L/S) and the low drawdown (0.48 m) in the karst of west Izeh at autumn 2019 indicates the effectiveness of the integration of the applied exploration methods. This work shows the power of geoelectrical method in poorly understood and tectonically complex areas in addition to the RS/GIS groundwater potential mapping to evaluate karst hydrogeology.

Iran Plateau is part of the Alpine-Himalayan orogenic system in western Asia. It is located in a seismically active region affected by a transpressional tectonic regime of oblique convergence, generated by the convergence of the Arabian plate toward Eurasia. The current morphology of Iranian plateau had been dominated by opening and closing of the Paleo-Tethys and Neo-Tethys oceans in the past. Current lithospheric deformation in the NW Iran is shaped by the convergence of Arabia and Eurasia and the westward motion of the rigid South Caspian Basin. The South Caspian Basin is a relatively aseismic rigid basement block and has affected the deformation history of its surrounding continental regions. The South Caspian Basin and the Kura depression to its west are thought to be a relic back-arc of the Tethyan Mesozoic subduction caught up in a continental collision zone similar to the Black Sea and the eastern Mediterranean. The South Caspian Basin is a piece of unusually-thick oceanic-like crust, because of its low elevation and its west and southward motion relative to central Iran. Here we present results of a S-receiver function analysis for a 290 km long temporary seismic network in the NW Iran. The network is a linear array stretching from the western coast of the South Caspian Basin to the Lake Urumieh. We computed the individual S receiver functions for 23 broad-band seismic stations and then we stacked them based on their piercing points at depth of 80 km. To calculate S receiver functions, the teleseismic S waveforms were cut from 200 s before to 100 s after the theoretical S wave onset. ZNE-component waveforms were rotated into the ZRT coordinate system and the R component was deconvolved from the Z component. To make S receiver functions similar to P receiver functions, we reversed the time axis and the polarity of S receiver function time series. The Gaussian smoothing factor was selected equal to 1.0 for both data sets, which is equivalent to the application of a Gaussian low pass filter with a corner frequency of ~0.2 Hz to the receiver functions. Piercing points at north and south of the linear profile were separated into two different data sets to avoid the stacking of 3D heterogeneities. Stacking receiver functions confirms a thin crust east of the Talesh Mountains juxtaposing with a thick continental crust beneath the NW Iran. We interpret the thin crust as an oceanic-like crust belonging to the South Caspian Basin. The detected Lithosphere-Asthenosphere boundary is almost shallow with an average depth of ~100 km. However, its variations across the profiles are different in each data set. Variations beneath the region south of the profile are minor revealing a flat, thin lithosphere beneath the region. The lithosphere (as well as crust), however, becomes thick beneath Sabalan volcano, north of the profile, probably due to convergence of the NW Iran and the South Caspian basin above the North Tabriz Fault. This interpretation implies that the North Tabriz Fault is a continental suture between the NW Iran and Central Iran plateau.

In this study, thermal infrared data from Moderate-resolution Imaging Spectroradiometer (MODIS) sensor with spatial resolution of 1000m are selected to investigate about the Land Surface Temperature (LST) anomalies before Saravan earthquake. Many studies have already documented an extensive elevated thermal anomaly near epicenters that appear within dozens of days before the earthquakes such as (Qiang, et al., 1991, 1999; Tronin, et al., 2002; Tronin, 2006; Saraf, et al., 2007; Huang, et al., 2008; Ma, et al., 2010; Yao and Qiang, 2012; Wu, et al., 2012; Tramutoli, et al., 2013; Akhoondzadeh, M., 2014; Lisi, et al., 2015; Lu, et al., 2016; Venkatanathan, et al., 2017; Zhang, et al., 2017). Satellite-based thermal infrared (TIR) data linked to the LST through the radiative transfer equation. The earthquake of Saravan in Sistan and Baluchistan province occured on April 16, 2013, at Iran Standard Time (local time) of 15:14 pm (Lat: 28.04°, Lon: 62.03°). In this paper, a practical split-window algorithm as named Sob Mao (Mao, et al., 2005) is used to retrieve LST from MODIS data which involves two essential transmittance and emissivity parameters. The general radiance transfer equation for remote sensing of LST is formulated as follows:Bi (Ti)=τi (θ)[εi Bi (TS )+(1-εi ) Ii↓ ]+Ii↑ (1)Where Ts is the LST, Ti is the brightness temperature in channel i, ,τ_i (θ) is the atmosphere transmittance in band i at viewing direction θ (zenith angle from nadir), and ε_i is the ground emissivity. Bi (Ts) is the ground radiance, andI_(i↓) and I_(i↑) are the down. welling and upwelling path radiances, respectively. Time series of LST parameter (Eq2.) has been analyzed to examine about the probable LST fluctuations before and after these events.LST=Ts=C32 (B31+D31 )-C31 (B32+D32 )/(C32 A31-C31 A32 ) (2)The results show positive deviation of >10 °C four days before the main shock on April 12, 2013 (102 of day of year) and it disappears a few days after the main event. The time scale of the observed variations is a one week before the onset of the seismic event. The results confirmed the existence of an anomaly in LST data before for Saravan earthquakes. A comparison of the maps in Fig. 2 reveals that the thermal anomaly had been formed four days before the main shock on April 12, 2013 (i.e. the 102 day of the year) and two days before an aftershock of Mw 5 on April 18 (i.e. the 108 day of the year). The anomalies formed are usually of 50 to 500 km length. They are often of drastic fluctuations. To ensure that the reasons of these anomalies are well understood, the meteorological maps and the model outputs in the weekly time intervals around the time of the event were examined for the Saravan area. Time series of Saravan temperature and the pressure maps are also investigated, as it can be seen no significant meteorological phenomenon was observed that can cause such drastic changes. The LST map results illustrate that before the Saravan earthquake, a large anomaly of LST is created and that these anomalies follow the mentioned trend in other scientific papers, therefore it could be considered as an earthquake precursor.

This paper investigates the atmospheric condition of southeastern of Iran (Sistan-o-Balochistan) during the summer (June, July, and August) with emphasis on planetary boundary layer (PBL) characteristics and dust events. Studying the 30 years (1987-2016) averaged patterns by Era-Interim reanalyzed data from ECMWF showed that with a thermal low dominant in this region, in 850 hPa level, the mean temperature is over 33ºC in the center parts of province and relative humidity is less than 20% of the most parts of the province. It appears that corresponding to the decrease of temperature from north to south of Sistan-o-Balochistan, planetary boundary layer height reduces from 800m in the north to about 200m in the south of province in the coast of Oman sea. The frictional velocity in northern parts of the province (within the borders of Afghanistan) is more than 0.14 m / s, which can provide good conditions for dust emission from the earth surface. Observed meteorological parameters from 5 selected synoptic stations of Sistan-o-Balochistan include Zabol, Zahedan, Khash, Iranshahr and Chabaher are used to examine the summer trend in each station. In general, changes in time series at the selected stations do not follow the same procedure, and each station has special conditions. In Zabol synoptic station, the pressure decline corresponding to temperature enhancement was observed from 1978 to 2016. Moreover, maximum wind speed and relative humidity have deceased. Aerosol Optical Depth (AOD) at 550nm from MODIS-Terra has a downward trend from 2001 to 2016 at this station. The 30-year variation in dust storm index (DSI) for Zabol station is not statistically significant. But there is a significant downward trend from 2001 to 2016, corresponding to significant changes in other meteorological quantities, including significant downward trend in maximum wind speed and relative humidity with significant upward trend visibility at this station. Furthermore, calculating the correlation coefficients between maximum wind speed, visibility and DSI in the last 15-years, it shows that, as the wind speed increases, the DSI increases and, as expected, the horizontal visibility decreases. Using the reanalyzed data from NCEP/NCAR, we investigated the possible Indian summer monsoon effect as a large-scale phenomenon near this area on atmospheric conditions of southeast of Iran, especially dust events from 1987 to 2016. Calculating the correlation coefficients between dynamic Indian Monsoon Index (IMI) and meteorological parameters including temperature, geopotential height, horizontal and vertical components of wind, indicate that there is a significant decrease in geopotential height in northern and central parts of the province at lower levels of atmosphere, corresponding to increase in Indian monsoon intensity. There are no significant correlations between IMI and the other parameters in selected stations. Furthermore, there are no significant correlations between the convective index (CI) of the Indian monsoon and meteorological quantities in southeast of Iran during the summer. Therefore, it can be said that the intensity of convective activities in the Indian monsoon region does not have a significant effect on the air conditions (at low levels of atmosphere) in Sistan and Baluchestan province.

Displaying and quantifying how large-scale climatic signals affect the regional and global climate is one of the issues of interest to researchers. New approch of Network Analysis enables us to study a complex system such as the climate more effectively. In this study, the effect of NAO on precipitation in Iran was investigated using the method of Network Analysis. The data used are daily precipitation and NAO daily indices obtained from ERA-Interim data base. The time period covers the cold months (November, December, Jenury, Februry, March, April) of the years 1979-2016. In order to smooth the daily precipitation data, a weekly moving average was applied to data. A modified Pearson’s cross correlation coefficient  was employed for correction of the bias of traditional Pearson correlation due to many zero-precipitation data. The years of the strong NAO negative and positive phases, NAO- and NAO+, were determined by the frequency of the weekly moving avereage NAO index (WMANAOI) greater that 2 standard deviations ( ), where Sd is the standard deviation. The precipitation network was established based on a constant link density of 0.05 for which vertex degree distribution of network is considered. The later statistics is the covariance between precipitation time series at grid points that show indirectly the effect of the variation of precipitation due to large-scale climate signal. Results demonstrated that Network Analysis method can display and quantified the effect of NAO-and NAO+ on the precipitation of Iran. Degree distribution over the whole duration shows that the most degree distribution is in the northwest, west, southwest and east of Iran. The deserts of Iran that are located in the center of the country have the least degree distribution, and so the least similarity with each other, that are clustered in a group. Also, threshold of network, i.e. , is 0.42 and the histogram of all  has the right skewness. The  is a threshold for selecting the statistically significant  between each two griod points over Iran. The degree distribution for noraml years, with less NAO activities, displays that is 0.42 and degree distribution totally is less than those of NAO+ and NAO-phases. During NAO-, degree distribution is increased in the northwest and southwest of Iran. The  in NAO- is 0.46. During NAO+, the degree distribution is increased in the south of Iran while the threshold of network remain 0.43. Also, the histogram of all  has a positive skewness at NAO+ and NAO-that indicate the strong correlations has positive values. Minimum values of  for the whole period, normal years, NAO+ and NAO-are -0.11, -0.14, -0.3 and -.033, respectively.

The Caspian Sea, the world's largest enclosed body of water, covers an area and volume of 371,000 km2 and 87,200 km3, respectively, and limited to the north by Russia and Kazakhstan, to the east by Turkmenistan, to the south by Iran, and to the west by Azerbaijan. The Caspian Sea can be considered the most important source of energy storage, although this focus is currently limited to fossil fuel reserves due to the multitude of offshore oil and gas projects in the North, Middle and South basins, while the potential benefits of renewable energy sources such as Oceanic thermal energy in offshore areas has not been well studied. The present study seeks to evaluate the ocean thermal energy in the offshore regions of the Caspian Sea and examine the vertical variations of water temperature using UNESCO data and ECMWF water surface temperature database. Accordingly, the mean water temperature difference has been investigated as daily, monthly and seasonal across the permanent thermocline for the Caspian Sea using Pyferret software and the possibility of the use of ocean thermal energy in offshore oil and gas fields has been evaluated. In order to show the accuracy of the ERA Interim, Daily database data, its surface water temperature data at 25 points in three Caspian basins were validated according to UNESCO field measurements at those sites. Trends of changes between the Unesco and ECMWF data are in good agreement, including in the eastern part of the Caspian Sea basin, indicating a upwelling phenomenon in this region. In general, ECMWF site surface water temperature data with a correlation coefficient of 0.971 have good accuracy. Therefore, due to the lack of field measurement data, ECMWF site data for Caspian surface water temperature can be used. To study the temperature profile of the Caspian Sea to identify areas where the vertical water temperature difference reaches 20 ° C. First, UNESCO field measurement data covering all three Caspian basins were used. By plotting temperature profiles for 25 UNESCO field measured points only at points A and B, respectively, at geographical locations 37.550 N, 50.692 E, 38.380 N and 51.853 E, the eligible temperature difference for oceanic thermal energy extraction was observed. Examining all points in the deep areas shows that the water temperature reaches 6.5 to 7 ° C at 200 m depth, and at lower depths there is no significant change in water depth. Therefore, the OTEC needs to check the water temperature in the upper layers of water. The findings show that ocean thermal energy can be extracted only from the southern basin during July and September, so that the eastern part of the southern basin has the highest coefficient for thermal energy extraction. Daily monitoring of the vertical variations of water temperature in these months shows that in the best conditions of the southern basin, it is possible to obtain the ocean thermal energy with a minimum temperature of difference 20°C, 64 days a year, and only Sardar, Shahdeniz, Ganeshli and Azeri fields have the possibility of obtaining this energy for 54, 34, 31 and 31 days of the year, respectively.

Atmospheric visibility is a Common meteorological parameter and almost all meteorological stations have recorded it for a long time. Visibility is defined as the maximum distance at which a selected target can be seen by human eyesight. Horizontal visibility is a kind of atmospheric visibility and it is a visual perception of weather conditions. Its values depend on different weather conditions like the clear sky (sunshine), fog, rain, snow, hail, thunder, and tornado. Furthermore, it depends on air quality and urban-industrial activities that can change it. Low visibility causes psychological problems and effects on flight safety and transportation. Horizontal visibility variation has both natural and anthropogenic origins and so its values depend on both weather conditions and air pollutants. Almost all large cities of Iran have meteorological stations and for decades, parameters like horizontal visibility and weather condition types have been measured and recorded. On the other hand, atmospheric aerosols are the main air pollutants and retrieval of their parameters needs specific aerosol monitoring stations. Unfortunately, only Zanjan city has an aerosol monitoring station and therefore, we focus on this city in this work. The Zanjan weather station has recorded data from 1973 until now. In this work, the effects of air temperature and weather type on horizontal visibility are first discussed. Also, data acquisition in Zanjan’s aerosol monitoring station (IASBS sun-photometer site) began in 2010. The aerosol optical depth and Angstrom exponent as two important parameters of aerosol are discussed here. Extinction of direct sunlight throughout the atmosphere is related to both aerosol and molecular concentrations and the pure aerosol portion is named aerosol optical depth or AOD and its higher (lower) values are related to aerosol more (less) number densities. Angstrom exponent or alpha is a qualitative indicator of aerosol mean size and higher (lower) values are related to fine (coarse) aerosols. Therefore, both AOD and alpha determine the dominant type of aerosols and their concentrations. In this work, all 10,359 days of recorded data from Zanjan’s weather station during 1973-2017 are selected to investigate the correlation between horizontal visibility, temperature, and atmospheric conditions. The results show that the horizontal visibility is reduced in the colder months of the year due to rainy weather conditions, fog, and snowfall. During 70 days in 1990-2017, horizontal visibility dropped below 5 km and 86% of these days have foggy, rainy, and snowy conditions. So, one concludes that air pollution is not the main reason for visibility reduction in Zanjan city. Furthermore, the optical depth and Angstrom exponent parameters of atmospheric aerosols are extracted from the sun-photometer station of Zanjan during 2010-2017. No significant correlation is observed between the horizontal visibility reduction and the increase in the concentration of dust particles as the dominant aerosol of the Zanjan’s atmosphere. In the studied period, 1269 (76) days (dusty days) were recorded, with mean horizontal visibility of 11 (9) km. Therefore, one concludes that the parameter of horizontal visibility is not sharply decreased during dust events and it is mainly related to dust transportation from external sources to the atmosphere of Zanjan, especially at higher altitudes.

Air pollution and climate change are two of the most serious problems facing human societies which interact with each other through radiation, dynamic and chemical processes. Increasing air pollutants some as greenhouse gases in addition to adverse effects on health, economic and social sectors of societies, during chemical and photochemical reactions in the atmosphere, disrupt the Earth's energy balance and cause radiation forcing and rapid negative climate gains, such as global warming. With the recent climate change the quality of life of urban communities is also facing a serious threat. With the importance of this issue and with the aim of achieving a unified approach to reducing air pollution and mitigating climate change, it is essential to know the quality of major air pollutants in the face of recent climate change. In this study, long-term data (2002-2017) of Tehran Air Quality Control Company were used for analysis of annual, seasonal and monthly air quality conditions and changes of trends of air pollutants concentrations and the air quality index (AQI) of six major air pollutants .Also, for the statistical analysis, linear regression model, frequency distribution and calculation of variation percentage were used. According to the results, the air quality of Tehran is in a poor condition due to concentrations of more than two to four times the national and international standards of most pollutants (except CO and SO2 which have improved). So that during 16 years of study according to the highest values of AQI and the highest frequency of contaminated days, three general air pollution periods (2002-2006:CO), (2007-2009: ), (2010-2017: ) were determined for Tehran. Accordingly, the third period with an (11%) unfavorable growth in average annual AQI and a decrease (-19%) in total frequency of desirable days (-184% clean, -13 healthy) and increase (33%) in total adverse days, especially unhealthy days for sensitive groups (35%) was the most affected period compared to that of the other previous two periods. In the third period of air pollution only about (2%) of the days of the year were at the clean level and more than one third of the days (36%) with the criteria air pollutant  contaminated. Also, seasonally due to the influence of the specific weather conditions of each season on the exacerbation of adverse pollutants status, two peak of pollution in cold and hot periods of the year were determined. In hot seasons,)41%( of the annual contaminated days were recorded, especially in summer (%23) due to high concentrations of pollutants (  (70%),  (27%) and  (3%)). The monthly pollution peaks of this period are also in June, July and August respectively. The peak of pollution in cold period of the year was designated as the most polluted peak. During this period, 59% of the frequency of adverse annual days, especially in winter (31%), was recorded due to high concentrations of pollutants (87%),  (10%)and  (3%) have been in December, January and February respectively. Also, in recent years (2010-2017), the winter pollution peak has been associated with a )24%( increase in the quality index and 70% in the frequency of contaminated days. Therefore, due to the direct and indirect effects of air quality pollutants in the face of aggravating climate change, in addition to the need to further reduce long-term greenhouse gas emissions in related policies, formulating stricter strategies to reduce pollutants emission in urban areas as Tehran should be improvised.

In this paper by using the most recent findings in the field of the Kappa distribution statistics for the non-equilibrium space plasmas, dust-acoustic waves have been studied in a dusty plasma comprising of the inertial dust particles with negative charges and suprahermal distributions of electrons and positrons. The velocity distribution function for stationay state of the plasma in this model is labeled by an invariant Kappa index which is independent of the numbers of degrees of freedom, and the parameter  which represents the the numbers of degrees of freedom. In linear analysis, the dispersion relation of dust-acoustic waves is studied, whrere the true sound speed of the problem is derived. The derived dust-sound speed is a generalized one which depends on the polytropic index of Kappa distributed paricles , which itself depends on the spectral index  and the potential degrees of freedom . Generally, the dust-sound speed has its maximum in an equilibrium plamsa with Maxwellian distribution or isothermal electrons , and it reduces by approaching to the anti-equilibrium regions with sub-isothermal electrons . On the other hand, in the non-linear analysis, the dust-acoustic solitary waves have been studied by deriving an energy-integral equation, where we have used the true dust-sound speed for defining the true Mach number (the fractional wave speed to the sound speed). The formation conditions of the potential well, the true Mach number domains, and the effects of the parameters of soliton speed, the spectral index  and the potential degrees of freedom via the perturbation in the propagation of dust-acoustic solitary waves have been studied analytically and numerically.  In such a plasma, only the negative polarity solitons are possible. The reason is the negative charge of dust paricles via the attracted electrons, which causes the formation of negative potential solitons. The structure of dust-acoustic solitons are examined in the near-equilibrium states, where the spectral indices are distributed with the values of , and also in the far-from-thermal equilibrium states which are labeled by the spectral indices with the values of . It is found that the threshold Mach nmber is proportional to the square root of the polytropic index of Kappa distributed paricles which vaies in the range . So, the threshold Mach number increases by approaching to the equilibrium state and it reduces in far-from-thermal equilibrium states.  It is shown that the subsonic solitons are possible in the far-from-thermal equilibrium plasmas. On the other hand, in an equilibrium plasma, corresponding to the asymptotic limit of , only the altrasonic solitons are possible which confirms the classical theory of solitons in equilibrium statistical mechanics. It is found that the amplitude and steepening of the dust-acoustic solitons grows in far-from-thermal equilibrium states, which corresponds to the lower values of the spectral index . It is because of the impact the suprathermal particles on dust-acoustic solitons in that regions. Furthermore, an increase in Mach number results in the propagation of dust-acoustic solitons with more amplitude and steepening, in agreement with the standard theory of solitary waves. Moreover, decreasing the potential degrees of freedom causes an increase in the maximum amplitude and pulse steepening of dust-acoustic solitons.

Sea Surface Temperature (SST) variability, especially its slow variability, creates a potentially predictable source for climate fluctuations. Therefore, the SST variability study sheds light at climate changes, marine life, and prediction of short term and long term climate variation. In this research, the trend and interannual variability of the Persian Gulf SST were analyzed by employing monthly detrended Optimum Interpolation Sea Surface Temperature (OISST) data in 1982-2018. According to the effects of teleconnection patterns on atmospheric and oceanic parameters in different regions, the correlation between NAO, IOD, and ENSO with Persian Gulf SST anomaly is considered in this research. For this purpose, OISST data and MEI.V2, IOD, and NAO indices from 1982 to 2018 were analyzed. The Climatological mean of Persian Gulf SST during this period is shown in figure 5. According to figure 5, northwest of the Persian Gulf was found to be the coolest and southeast of the Persian Gulf was the warmest regions of the Persian Gulf. According to the investigation of this research on monthly variability of the Persian Gulf SST, there are two main seasons with four months, including Summer (June, July, August, September), and Winter (December, January, February, March), and two transition periods with two months, including Spring (April, May), and Autumn (October, November). Based on figure 6, February was the coldest month of winter and August was the warmest month of summer. In both of these months the minimum temperature was observed in the northeast, and the maximum temperature in the southeast of the Persian Gulf. The strongest and the weakest temperature gradient were calculated to be 5 ̊C in winter and 2 ̊C in summer, respectively. There was more than 13 ̊C difference between the spatial mean temperature of February and August. Evaluation of the SST anomaly variance indicated that the maximum variance belonged to the northwest of the Persian Gulf at the coast of Khuzestan province and Kuwait and also to the southwest of the Persian Gulf on the coast of Bahrain, Qatar, and east of Saudi Arabia. Sea surface temperature time series trend triggered by global warming from 1982 to 2018 was calculated to be 0.4 ̊C per decade using the least linear square method. Spatial distribution of trend implies that the maximum trend is observed in the northwest of the Persian Gulf in Khuzestan province and Kuwait coast and the minimum trend is observed in the east and southeast of the Persian Gulf. According to the Pearson correlation method, the maximum (minimum) correlation was calculated to be -0.23 (0.16) employing ENSO (IOD) index considering 4(13) months of delays. The spatial distribution of the correlation between teleconnection patterns indices and the Persian Gulf SST anomaly is demonstrated in figure 9. Results of the analysis pointed out that regarding IOD index, the maximum correlation (0.18) was found at the northwest of the Persian Gulf and the minimum correlation (0.12) was observed at the southeast of the Persian Gulf. Regarding ENSO index, the maximum correlation (-0.24) was at the central region of the Persian Gulf and the minimum correlation (-0.18) was at the south of the Persian Gulf. Concerning NAO index, the maximum correlation (-0.20) was seen at the northwest and the southwest of the Persian Gulf, and the minimum correlation (-0.16) was at the northwest and southeast of the Persian Gulf, near the strait of Hormuz. Therefore, the spatial distribution of correlation between the teleconnection patterns indices and SST anomaly, reveals that there is no center with significant maximum correlation which could give the possibility of distinguishing these areas from the others.