Assessment of air quality using AERMOD modeling: a case study in the Middle East.

Emissions of greenhouse gases from industrial facilities, such as refineries, are one of the most significant environmental problems in many countries. This study aimed to assess the present status of emission sources near a gas refinery region, and the contribution of sources to air pollution was estimated by monitoring CO for a year at a fixed station. This descriptive-analytical study was conducted between January and December 2020. A simulation of CO gas distribution and pollutant concentration prediction was carried out. The results show that the maximum concentration of CO in the 1-h period was 2260 µg/m3, which corresponds to the peak concentration in spring, and in the 8-h period, it was 573 µg/m3, which corresponds to the peak concentration in winter. The studied area's maximum pollutant concentration was also compared to national and international standards for clean air. In all four seasons, the maximum simulated CO concentrations were lower than the Iranian and EPA standards for clean air. Maximum concentrations have occurred in the southern slopes of the study area's heights, and, due to the appropriate wind speed, maximum concentrations in the northeastern mountain peaks occurred at a more considerable distance due to the high altitude of the mountains and the lack of suitable conditions for pollutant escape. Furthermore, because of the height of smokestacks and flares from the ground and the effect of wind on the release height, the concentration of pollutants at the foot of the stacks is low and decreases gradually over a certain distance. Finally, the distribution and deposition of pollutants in the pathway of the smoke were influenced by the type of topography.

Comparison of AERMOD and CALPUFF models for simulating SO2 concentrations in a gas refinery.

In this study, concentration of SO2 from a gas refinery located in complex terrain was calculated by the steady-state, AERMOD model, and nonsteady-state CALPUFF model. First, in four seasons, SO2 concentrations emitted from 16 refinery stacks, in nine receptors, were obtained by field measurements, and then the performance of both models was evaluated. Then, the simulated results for SO2 ambient concentrations made by each model were compared with the results of the observed concentrations, and model results were compared among themselves. The evaluation of the two models to simulate SO2 concentrations was based on the statistical analysis and Q-Q plots. Review of statistical parameters and Q-Q plots has shown that, according to the evaluation of estimations made, performance of both models to simulate the concentration of SO2 in the region can be considered acceptable. The results showed the AERMOD composite ratio between simulated values made by models and the observed values in various receptors for all four average times is 0.72, whereas CALPUFF's ratio is 0.89. However, in the complex conditions of topography, CALPUFF offers better agreement with the observed concentrations.

Structural equation modeling of safety performance based on personality traits, job and organizational-related factors.

Purpose. This study investigated the relationship between three selected personality traits and contextual factors with safety performance. Methods. This cross-sectional study was carried out among the operational staff of a gas refinery (n = 487) in Iran. Structural equation modeling was used to model the factors affecting safety performance based on personality traits and job and organizational-related factors including consideration of future safety consequence, safety locus of control and impulsiveness, safety climate, job insecurity and role overload, and mediator roles of safety knowledge and safety motivation. Results. Structural equation modeling results indicated that consideration of future safety consequence was directly correlated with safety performance. Impulsiveness and safety locus of control were indirectly associated with safety performance through the mediator role of safety knowledge and motivation. Furthermore, job insecurity and role overload were partially and directly correlated with safety performance. Moreover, safety climate had a significant relationship with safety performance. Conclusion. Consideration of future safety consequence is a valid personality trait for predicting safety performance. It can therefore be used as an indicator in the employee selection process. Moreover, improving employee safety performance necessitates increased safety knowledge and motivation as well as improved occupational characteristics and safety climate.

Carbon footprint calculation in one of the largest Gas Refinery Companies in the Middle East.

Rapid technological advances in the natural gas industry raised access to natural gas reserves, related to increased greenhouse gas emissions, including CO2 and CH4. This study calculates greenhouse gas emissions (CO2 and CH4) according to sources (direct and indirect) in one of the largest gas Refinery Companies in the Middle East to analyze the carbon footprint for the first time. All computational frameworks for estimating carbon footprint and greenhouse gas emissions (CO2 and CH4) in different sectors were carried out after determining direct sources (combustion, processes, and fugitive) and indirect ones (import from National Grid's electricity) according to the requirement guide and organizations' report involved in the operational activities of the oil industry. The carbon footprint for this refinery, leading to the emission of CO2 and CH4, is in the range of 1507.1 Gg CO2/yr and 0.003 Gg CH4/yr. The highest CO2 emissions are related to the gas-sweetening unit from GHG direct emission sources, and the lowest CO2 emissions are related to fugitive ones. For methane gas, the highest CH4 emissions are related to fugitive emissions. In addition, the emission of CH4 from the gas sweetening unit and waste combustion equipment is estimated to be very small and close to zero. This study showed that it is necessary to carry out more studies in different regions to give a more comprehensive insight into gas emissions and their adverse health effects on human populations.

Variation in Brant's oak (Quercus brantii Lindl.) leaf traits in response to pollution from a gas refinery in semiarid forests of western Iran.

Air pollution around refineries and factories is one of the major environmental challenges affecting forest ecosystems' health. Although there have been many studies on Iran's forest ecosystems, the physiological and morphological responses of Brant's oak (Quercus brantii Lindl.) leaves to the pollution of the gas refineries in the semiarid forests have not received much attention. We sampled healthy and mature leaves from four oak stands in different seasons (spring, summer, and autumn of 2019) and at various distances from the gas refinery (1,000, 1,500, 2,000, 2,500, and 10,000 m). The results showed that oak trees in different seasons and at different distances from the refinery had different physiological and morphological leaf trait responses to the pollution source. Oak trees with an air pollution tolerance index value of less than 11 were in a sensitive range to air pollution and can be used to biomonitor air pollution around the gas refinery in Zagros forests. Physiological traits in different seasons and at various distances in comparison with morphological traits (persistent reaction responses) were well distinguished from one another and were more affected by pollution. Oak trees in summer and autumn and at distances up to 2,500 m had rapid reaction responses, including oxidative stress indicators such as electrolyte leakage (EL), hydrogen peroxide, and different enzymatic and nonenzymatic antioxidants such as phenol, flavonoids, catalase, and proline. Because of their high sensitivity to atmospheric pollutant stresses, we recommend that these traits be used for rapid and low-cost environmental monitoring of pollution in different seasons and distances from pollution sources in semiarid ecosystems.

An evaluation of CO, CO2, and SO2 emissions during continuous and non-continuous operation in a gas refinery using the AERMOD.

Air quality modeling can be considered as a useful tool to predict air quality in the future and determine the control strategies of emissions abatement. In this study, the AERMOD dispersion model has been applied as a tool for the analysis of the values of pollutant emissions from the flares of the Maroon gas refinery located in the suburb of Ahvaz, Iran. First, the values of pollutant emissions from the refinery's flares were investigated by measurement and using the emission factors during cold and warm seasons of 2018. The gas burns continuously in two flares and the other 11 flares are used in emergency situations and only their spark plugs are lit. The type of compounds and their molar, volumetric, and weight percentages were determined by gas chromatography (GC) injection. By entering data such as emission rate, flare characteristics, and topographic and meteorological data of the study area into the AERMOD model, dispersion of pollutants was predicted by using the AERMOD model in the region with an area of 2500 km2. The statistical evaluation showed that the maximum 8-h concentration of CO in the cold season was 133441 µg/m3 which was higher than the standard and reached 9755 µg/m3 in the warm season that was close to the standard. The maximum hourly concentration of SO2 was in the cold season with 215 µg/m3 that was higher than the standard value, occurred in a local scale of 50 km2. This can be attributed to the high concentration of SO2 wet deposition. According to the direction of the wind from the northwest, pollutant emissions can lead to adverse health effects on the population of refinery employees, residents around the refinery, and occupants of passing vehicles. The concentration of pollutants generated due to the high volume of heavier compounds in the gas in the winter season was higher than that of the warm season. Comparison of maximum concentrations of the predicted results with the national and international standards showed that SO2 and CO concentration is higher than standard values. In total, according to the evaluation of the predictions made, the performance of the AERMOD model was acceptable in the prediction of pollutant concentrations in the study area.

Evaluation of hazard distances related to toxic releases in a gas refinery: comparison of chemical exposure index and consequence modeling approaches.

The release of toxic chemicals is an important hazard of chemical plants. The purpose of this study is to compare the chemical exposure index (CEI) and consequence modeling to determine the hazard distance of toxic chemical release, utilizing a gas refinery as the case study. The CEI was utilized and considerable release scenarios were determined. The process hazard analysis software tool model was performed for consequence modeling of the scenarios with the highest airborne quantity. In the case of toxic chemical release based on both the CEI and consequence modeling, the sludge catcher unit was identified as the most dangerous unit. Hazard distances calculated by the CEI are significantly greater than those using consequence modeling. This is acceptable in terms of safety, but may not be applicable in reality. The results of the study showed a procedure for selecting an appropriate method in order to reduce costs and time.

Metal(loid)s urinary level among workers of gas refinery and petrochemical companies: Health risk assessment of metal(loid)s in drinking water and dust.

BACKGROUND: Asalouyeh (southern Iran) contains many pollution sources like petrochemical and gas refinery companies. Few studies were conducted on the body burden of metal(loid)s in occupationally exposed workers of the companies in this area. OBJECTIVES: The urine concentration of metal(loid)s in workers of gas refinery and petrochemical companies in Asalouyeh (who have been worked as "two weeks work-two weeks rest" schedule) was evaluated during a before-and-after observational study. The risks of metal(loid)s in drinking water and dust particles in the studied area were also assessed. METHODS: Urinary samples (n = 179) were gathered at the first day of two weeks of work (before) and at the end of two weeks of work (after). The concentration of V, Ni, Mn, Cd, and As was measured using a graphite furnace atomic absorption spectrometry. The health hazards of metal(loid)s in the air dust and drinking water of workers were also evaluated. RESULTS: The median concentration of metal(loid)s for workers of gas refinery and petrochemical companies for before and after two weeks of work was measured, respectively, as: As (11.44 and 9.31 µg/L), Ni (1.06 and 0.51 µg/L), Cd (0.36 and 0.31 µg/L), Mn (0.29 and 0.24 µg/L), and V (0.08 and 0.05 µg/L). After two weeks work, the median of all metal(loid)s in the urine of petrochemical and gas refinery workers was significantly increased. The non-cancer risk due to intake metal(loid)s from drinking water was more than the threshold value and the cancer risk from drinking water and inhaled air dust was less than the threshold. CONCLUSION: Our results revealed the effect of gas refinery and petrochemical activities on increasing the metal(loid)s concentration of the worker's body and the necessity to protect this group. Additionally, the metal(loid)s intake from drinking water and inhaled dust posed no cancer risk to the workers.