: Evaluating the Computational Values of Suspended Particles Below 10 μm With Their Actual Concentration

Background & Aims of the Study: Dust as a phenomenon is among the significant problems in numerous regions of Iran and other countries. Empirical equations can be used to estimate the concentration of particulate matter. This study evaluated computational values of suspended particles less than 10 μm with their actual concentration in Ahvaz city based on a linear regression model. Materials and Methods: This descriptive cross-sectional study was conducted from April 2016 to March 2018. The dust images were obtained from the MODIS sensor of the Aqua satellite. The meteorological data included 3-hour horizontal visibility data recorded in m. PM10 concentration data were obtained from the Environment Organization. Accordingly, 5 empirical equations between horizontal visibility and PM10 have been used in this case. The calculated values of particulate matter less than 10 μm in Ahvaz City, Iran, were evaluated with actual values of PM10 based on the linear regression model. Results: The study results suggested that the computational R index for empirical equations had higher accuracy in 2017 data. The coefficients of determination using D’Almeida (1986), Dayan (1986), Chung (2003), Jugder et al. (2014), and Camino et al. (2015) indicators were calculated as 0.87, 0.806, 0.745, 0.873, and 0.866, respectively. Conclusion: Jugder et al. (2014) index with R² equal to 0.548667 was the best index for estimating PM10 in this region. The study results showed that empirical equations could estimate particulate matter and dust in southwestern Iran.


Introduction
ineral dust strongly interacts with the climate system through direct and indirect impacts [1]. Mineral dust emissions into the atmosphere negatively impact human health, causing or aggravating allergies, respiratory diseases, and eyes infections [2]. Mineral dust is discussed concerning dust storms and serious environmental problems in arid and semi-arid regions [3]. What is known as the dust today is due to the movement of air ambient forming soils suspended in the air affected by storms and air currents [4]. The speeds over 7 m/s at an altitude of 10 m play an essential role in storm conditions and dust formation. A dust storm develops when a low-pressure system moves toward a desert area [5]. Particle size and concentration, atmospheric persistence, and altitude in different dust storms of various sources are not the same [6]. The horizontal visibility reduces by increasing dust [7]. Horizontal visibility is among the events recorded by observers at meteorological stations [8]. Various atmospheric factors, including dust, reduce horizontal visibility and atmospheric turbidity [9]. The reported horizontal visibility varies according to the intensity of the dust. However, this report depends on the observer's personal experience and does not indicate the amount of dust [10]. Knowing the concentration and intensity of dust will effectively understand its nature and control strategies [11].
Furthermore, it is a criterion for comparing the results of air pollution models. Shao presents a valid classification for dust types based on horizontal visibility, 2015 [12], based on wind dust, blowing dust, dust storm, and severe dust storms. Multiple studies investigated the relationship between horizontal visibility and particulate matter and its importance. The results of various studies, such as Shao et al. [13], Camino et al. [14], and Baddock et al. [6], indicated the importance of the particulate matter in atmospheric parameters significantly influence climate and habitats. Camino et al. (2015) found an empirical equation between horizontal visibility and particulate matter concentrations in North Africa and compared them with other empirical equations in the same region. Bertahina et al. [11] simulated the scattering of dust particles by comparing observational dust data with a gray model with a coefficient of determination greater than 0.8. Dayan [15], in his synoptic analysis and classification of the prevailing air for dust patterns in Palestine, stated that a significant difference was between the seasonal routes of these patterns. He outlined the main routes for Israeli dust from 5 routes in northwestern Europe, Eastern Europe, Jordan, Saudi Arabia, and the coasts of North Africa. D'Almeida [16] outlined a well-described relationship between horizontal visibility and particulate matter based on data from a solar pyranometer. He hypothesized that horizontal visibility and turbidity parameters are often related. Zoljoodi et al. [17] found a relationship between increasing drought and dust storms in west of Iran from 1996 to 2011, highlighting the significance of studying dust in Iran's western and southwestern regions. Ahvaz City has extended boundaries with Iraq from the west. Due to its proximity to the deserts of Iraq, Kuwait, and Saudi Arabia. Besides, this city is affected by the deserts of those areas and experiences several dust events annually [18]. In this article, focusing on particulate matter pollution concentration in Ahvaz City in southwestern Iran, the best empirical equation between horizontal visibility and the extent of particulate matter is determined.

Materials and Methods
This study was conducted in Ahvaz City in southwestern Iran (Ahvaz). Figure 1 shows an image taken from the MODIS sensor of the Aqua satellite. It demonstrates dust routes that cover areas in Iraq, the Persian Gulf, and southwestern Iran on January 21, 2018; periods of dust occurrence in the present study.
This was a descriptive cross-sectional study. The obtained data were analyzed in 3 groups from the beginning of April to the end of March of the following year (2016, 2017, & 2018). This study requires meteorological and environmental data (particulate matter). The meteorological data included 3-hour horizontal visibility data recorded in m. PM 10 concentration data were obtained from the Environment Organization. All data were filtered for less than 10 km (only dust data were extracted). After preparing the given data, using the following empirical equations, PM 10 level was determined by horizontal visibility: After calculating PM 10 using Table 1 relationships, the values were compared with observational PM 10 . A linear regression test was used to investigate the correlation between the two. In this study, regression analysis was used to determine the relationship between empirical equations and the relationship between horizontal visibility and PM 10 concentration in Ahvaz aimed to find the best connection to estimate the amount of particulate matter. The lowest, highest, and mean values were also compared. Finally, particulate matter was classified on the World Wide Web report [12].

Results
The data relating to the main variables, including wind speed and dust concentration based on satellite and field of visibility data, have been used at 3 time periods of 2016, 2017, and 2018. The data relating to horizontal visibility in the city Ahvaz at these three intervals are shown in Figures 2, 3, and 4. Given that the data are recorded hourly, there are 8760 records each year.
Climatic data (wind speed and direction) and environmental data (PM 10 Table 1. The calculations were made only for days when the horizontal visibility was less than 10,000 m.  Table 2. *V: Represents the horizontal visibility in m, and PM 10 represents surface dust concentration in micrograms per cubic meter.       Table 5). The classification of Shao results for the highest and lowest indicators calculated in each category is presented in Table 5.  [23] introduced Gaussian function as the most appropriate function of the fit index. In this study, the linear regression method was used. Camino et al. found an empirical equation between horizontal visibil ity and particulate matter concentrations in North Africa and compared them with other empirical equations in the same region [14]. Bertahina et al. (2012) simulated dust scattering by comparing fine-grained observational data with a gray model with a coefficient of determination greater than 0.8. The results of a study done by Ebrahimi et al. [24] showed that approximately 45 percent of Iran's area has suffered from the increase of dust level in the atmosphere from 1998 to 2018.

Conclusion
The results of the study show that according to Shao classification, dust events in Ahvaz during 2016 to 2018 had an upward trend. Considering that Iran's western and southwestern provinces have had numerous problems with dust storms in recent years, we can use empirical relationships to understand the dust storms better. As we know, different variables effectively affect the occurrence of dust storms. The best indicator should be identified in any region, such as Ahvaz. It is suggested to hold studies like the present case in other areas involved with dust storms to determine the best indicator for estimating the relationship between horizontal visibility and PM. Using empirical equations can lead to faster estimating the concentration of particulate matter and dust.

Compliance with ethical guidelines
There were no ethical considerations to be considered in this research.

Funding
This research did not receive any grant from funding agencies in the public, commercial, or non-profit sectors.