## 1 Introduction  
The study of air quality on industrial platforms has become increasingly important due to phenomena that directly manifest through the zonal concentration of pollutants in some regions or indirectly through phenomena such as acid rain, ozone layer depletion,and photochemical smog. Various anthropogenic and natural sources emit Volatile Organic Components (VOCs). Given their photochemical property, VOC may react with nitrogen oxides from the atmosphere, resulting in secondary products that may injure the population's health ([PERSON] et al., 2002) ([PERSON] et al., 2002). Benzene and 1-3-butadiene are highly toxic ([PERSON] et al., 2002; 2019; 2020). They frequently affect the health of workers from the refineries and the population in the settlements nearby ([PERSON] et al., 2002; 2019; 2020). Therefore, the VOC series study is essential as an early warning instrument for assessing air quality and monitoring other pollutants in the same area (2020), maintaining the air quality and avoiding negative impacts on people's health, especially when the refineries are situated in urban zones. Different software has been developed to facilitate modeling various categories of pollutants. For example, the US-EPA has developed comprehensive atmospheric dispersion modeling packages incorporating applications like AERMOD (AMS/EPA Regulatory Model) or ISCST (Industrial Source Complex--Short Term) into a single interface. These models are based on the Gaussian normal distribution, which the pollutants' series does not always follow. Therefore, the results show ([PERSON] et al., 2019) the overestimation of the pollutants' concentrations. Still, AERMOD proved to be a valuable tool for modeling various pollutant series. For example, [PERSON] et al. (2019) explored the spatial dispersion of VOCs in a petroleum products tank farm of a crude oil refining complex in eastern Thailand in various scenarios, including the presence of a vapor recovery unit (VRU), double sealing of the storage tank, and modifications to the external floating roof of the tank. In a study by [PERSON] et al. (2019), the dispersion of benzene was evaluated across four seasons at a petroleum waste storage site on Kharg Island (Iran). The authors employed TANKS 4.0.9 (US EPA) benzene's atmospheric emission rates and simulated benzene series dispersion over an area of 10 \(\times\) 10 km\({}^{2}\) with AERMOD. Digital GIS representations can be a powerful tool in air quality management. For instance, [PERSON] ([PERSON] et al., 2019) used them to show the distribution of VOCs during loading ships with petroleum products. This visualization provided a clear understanding of the problem and facilitated the proposal of various measures for reducing benzene emissions. [PERSON] et al. (2019) undertook a comprehensive study of VOC emissions in Tehran in 2013, utilizing the IVE (International Vehicle Emissions) model. This model considers various factors influencing emissions. Similarly, [PERSON] and [PERSON] (2013) performed a spatio-temporal analysis of the atmospheric pollutant immersions produced during and after a fire at a petrochemical complex in Taiwan, employing the Back Trajectory (BT) model and Surfer software 9.0. Multiple linear and nonlinear regressions and ANNs proved useful for [PERSON] et al. 's (2013) research on the accumulation of BTEX on road surfaces encompassing typical commercial, industrial, and residential lands. [PERSON] and [PERSON] (2015) applied the COMIS model ([PERSON] et al., 2013) to the benzene emission rates series from an apartment in China. [PERSON] (2015) used a combination of geostatistical methods and land-use regression to forecast the VOC pollution in Montreal, demonstrating the practicality and versatility of these techniques. Similarly, [PERSON] et al. (2013) employed spatial interpolation methods to emphasize the population exposure to different atmospheric pollutants, including VOCs, showcasing the broad applicability of these methods.