Air pollution from gas refinery through contamination with various elements disrupts semiarid Zagros oak (Quercus brantii Lindl.) forests, Iran

Soils and oak trees (Quercus brantii Lindl.) in Zagros forests are suffering from the air pollution caused by the Ilam Gas Refinery. Thus, for the first time, we investigated the contamination level of sulfur and trace elements in these ecosystems. Sampling of soil and tree leaves was carried out in different seasons of 2019 and at different distances from the gas refinery. The results showed that soils and leaves at the various distances compared with control distance (10,000 m) were more affected by the gas refinery. Distance from the pollution source and physicochemical properties of soils were the main factors affecting contamination of soil elements contents. The soils with pollution load indices (PLI) of 4.54 were in the highly polluted category. Sulfur was at highly polluted category in soils and were highly enriched in trees. The trees mainly absorbed studied elements via their aerial organs. Our findings indicated that oak trees with the highest value of metal accumulation index are influence tools for monitoring various elements in the polluted air produced by the gas refinery. It is recommended that the ecosystem components near the refinery be studied to accurately evaluate disorders in the food chain.

Evaluating the Preparedness of a Process Industry to Deal with an Imminent Fire

Introduction: Due to occurrence of fires in process industries, it is vital to implement crisis management systems in these industries and keep the readiness of these systems high. The purpose of this study is to evaluate the readiness of emergency response teams to deal with a possible fire in a process industry. Methods: This descriptive-analytical study was performed in 2019 in a gas refinery with a statistical population of 200 people. A questionnaire with Likert scale was designed through library and field studies for all teams participating in the firefighting process. Content Validity Ratio (CVR) and Content Validity Index (CVI) were used to measure validity and Cronbach's alpha coefficient was used to measure the reliability of the questionnaires. The collected data were entered into SPSS software version 24 and statistical analysis was performed at 95% significance level using One Way ANOWA test. Results: The results showed that the readiness of this refinery to deal with a possible fire was 68.3%, which among the 11 teams participating in this process, the security team with 53.48% had the lowest and the logistics team with 77.5% had the highest preparedness (P-value = 0.028). The highest CVR was for the safety team questionnaire (0.77) and the highest Cronbach's alpha coefficient was for the liaison team (0.92). Conclusion: The results of this study showed that the readiness of this gas refinery in the firefighting process is satisfactory, although some teams, including the security team, are less prepared than other teams. Therefore, it is better to take intervention measures as soon as possible, including providing the necessary equipment and providing various trainings and maneuvers in order to increase the readiness of the teams.

An integrated fuzzy inference system and AHP approach for criticality analysis of assets: A case study of a gas refinery

The purpose of maintenance is to ensure the maximum efficiency and availability of production assets at optimal cost considering quality, safety, and environmental aspects. Assets criticality analysis is one of the main steps in many maintenance methodologies, including Reliability Centered Maintenance. The present study seeks to provide a solution for determining critical assets for more efficient maintenance management. In this regard, an integrated approach of the analytical hierarchy process and fuzzy inference system was proposed based on the concept of the risk matrix. According to the concept of the risk matrix, two main criteria of failure consequences and probability were employed to determine assets criticality. Analytic Hierarchy Process (AHP) was used to consider all sub-criteria of failure consequences and probability. Finally, using two main criteria as inputs, a fuzzy inference system was developed to determine the criticality of the assets. The proposed approach was implemented in a gas refinery; the results showed its effectiveness and applicability in the process of prioritizing assets based on criticality criteria. The proposed approach has the advantages of multi-criteria decision-making techniques, modeling ambiguity and uncertainty in real issues, modeling the process of inference in the human mind, and storing the knowledge of the organization’s expert.