Phytoremediation of BTEX from indoor air by Hyrcanian plants

Background: Phytoremediation is one of the available and simple techniques for removing benzene, toluene, ethylbenzene, and xylene (BTEX) from indoor air. This study aimed to evaluate phytoremediation of low concentrations of BTEX by Hyrcanian plants including Ruscus hyrcanus and Danae racemosa. Methods: The test chamber was used to evaluate the removal of BTEX. Benzene, toluene, ethylbenzene, and xylene were injected into the chamber using Gastight syringes (Hamilton) to generate the concentration of 10 (benzene), 20 (toluene), 20 (ethylbenzene), and 50 (xylene) μL/L Results: Ruscus hyrcanus was able to remove BTEX (10, 20, 20, and 50 μL/L) from air after 3 days. D. racemosa could uptake BTEX (10, 20, 20, and 50 μL/L) from air after 4 days. Removal efficiency was calculated based on leaf area and volume of the chamber. R. hyrcanus showed the highest removal efficiency ranged from 8.5075 mg/m3/h.cm2 for benzene to 86.66 mg/m3/h.cm2 for xylene. The increase in BTEX phytoremediation was assessed after repeated exposures. A significant phytoremediation efficiency was obtained after the third injection of BTEX to the chamber. Afterwards, the effects of BTEX on anatomical and morphological structure of plants were studied. The results of Photomicrography showed that tissue structures of leaves and stems changed. Study of D. racemosa and R. hyrcanus stems showed that vascular bundles also changed. The development of crystal in vacuole of spongy parenchyma was the main anatomical change of R. hyrcanus and D. racemose compared to the control samples. Conclusion: It can be concluded that R. hyrcanus and D. racemosa can be used for phytoremediation of indoor air pollution. Keywords: Volatile organic compounds, Air pollution, Indoor, Plant leaves, Sick building syndrom

Study of the Role of Latent Variables in the Trip Gas Sweetening unit by using Human Factor Analysis and Based on Fuzzy Hierarchy Theory: Case Study in the Gas Refinery

سابقه و هدف: حوادث یکی از مهم‌ترین علل بروز خسارت در یک سازمان می‌باشند که به‌واسطه سلسله‌ای از خطاهای اغلب جزئی و کم‌اهمیت یک فرد و یا یک مجموعه رخ می‌دهند. بنابراين شناخت الگو و ريشه‌يابي علل بروز خطا يک رويکرد مهم در درک و بهبود مديريت ايمني در صنايع مي‌باشد. این مطالعه باهدف شناسایی خطاهای انسانی منجر به حوادث با استفاده از روش تجزیه‌وتحلیل فاکتورهای انسانی و سیستم طبقه بندی (HFACS)  و تئوری تحلیل سلسله مراتب فازی (FAHP) از پالایشگاه‌های گاز انجام شد. روش بررسی: پژوهش حاضر برای حادثه توقف تولید استحصال گاز در واحد شیرین‌سازی پالایشگاه گاز انجام شد. بدین منظور با تشکیل یک تیم از 6 نفر مهندسین ارشد پالایشگاه، ابتدا تحلیل علت‌های ریشه‌ای رویدادها با متد نمودار استخوان ماهی تهیه گردید. سپس با ادغام روش تجزیه‌وتحلیل فاکتورهای انسانی و سیستم طبقه بندی و تئوری تحلیل سلسله مراتب فازی احتمال رخداد هر یک از علت‌ها تجزیه‌وتحلیل گردید. نتایج: نتایج حاصل از تحلیل برگه‌های کار 128 فعالیت تعمیراتی نشان داد که در سطوح 4گانه روش تجزیه‌وتحلیل فاکتورهای انسانی و سیستم طبقه بندی ، بیشترین خطای رخداد در سطح اول استفاده از قطعه کیفیت پایین (6.8%=p) و عدم تحلیل صحیح بودجه موردنیاز تعمیرات (2.6%=p) است، سطح دوم زیرگروه نظارت ناکافی سرپرست تعمیرات (3.59%=p)، در سطح سوم زیرگروه فاکتورهای انسانی مرتبط با وظیفه (۳٫۲۵%=p) و در سطح ۴ زیرگروه خطای مبتنی بر دانش پیمانکار (۳٫۲%=p) و عدم دقت پیمانکار در تکمیل چک‌لیست (۲٫۳۱%=p) بیشترین احتمال تأثیر علت در رخداد رویداد توقف واحد و  استحصال گازترش را دارند. نتیجه‌گیری: نتایج مطالعه حاضر نشان داد علت‌های مختلفی از جمله فردی، وابسته به فعالیت (وظیفه) موقعیتی و سازمانی دارند که برای حذف و یا کاهش این خطاها نیازمند برنامه‌ریزی و مدیریت صحیح و دقیق می‌باشد. افزایش اثربخشی آموزش کارکنان و بهبود نظارت بر عملکرد کارکنان به ترتیب بیشترین نقش را در کاهش وقوع رویدادهای ناشی از خطای انسانی در عملیات‌های تعمیر و نگهداری پالایشگاه دارند.   How to cite this article: Askarian A, Mirza Ebrahim Tehrani M, Seyed Mohammad Taghi Sadatipour SM, jozi SA, Marandi A. Study of the Role of Latent Variables in the Trip Gas Sweetening unit by using Human Factor Analysis and Based on Fuzzy Hierarchy Theory: aCase Study in the Gas Refinery. J Saf Promot Inj Prev. 2020; 8(1):46-57.Background and Objectives: Incidents are one of the most important causes of damages in an organization often occurring due to a chain of minor and trivial errors. Therefore, recognizing the pattern and root causes of the errors are an important approach in understanding and improving safety management in the industry. This study aimed to identify human errors leading to incidents in a gas refinery using human factors analysis and classification system (HFACS). Methods and Materials: The present study for conducted for the event of stopping the production of gas extraction in the gas sweetening unit of the refinery. So, a team consisted of six senior refinery engineers, first the analysis of root causes of events with Fishbone Diagram was prepared. Then, by combining the HFACS method and FAHP theory, the probability of occurrence of each of the reasons was analyzed. Results: Analyzing the worksheets of 128 activities in four levels of HFACS showed, that the highest errors rate were the first level use of Use low-quality equipment (p=6.8%) and Failure to properly analyze budget for overhaul maintenance (p=6.2%), the 2nd level of the sub-group of inadequate supervision of the maintenance supervisor (p=3.59%), the 3rd subgroup of Task-related human factors (p=3.25%) and the 4th sub-category of (p=3.2%) and Inaccuracy of the contractor in completing the checklist Contractor knowledge-based error (p=2.31%) with the most probability impact in trip gas sweetening unit incident. Conclusions: The results show that errors have various causes, including individual, activity, situational, and organizational errors that require careful planning and management to eliminate or reduce these errors. Increasing the training effectiveness of operators and supervision improvement respectively are the most important measures in decreasing human error-induced incidents in refinery industry maintenance. How to cite this article: Askarian A, Mirza Ebrahim Tehrani M, Seyed Mohammad Taghi Sadatipour SM, jozi SA, Marandi A. Study of the Role of Latent Variables in the Trip Gas Sweetening unit by using Human Factor Analysis and Based on Fuzzy Hierarchy Theory: aCase Study in the Gas Refinery. J Saf Promot Inj Prev. 2020; 8(1):46-57

The Environmental Risk Assessment of Fire and Explosion in Storage Tanks of Petroleum Products

The present study provides a framework for assessing the environmental risk associated with fire and explosion of gasoline storage tanks in oil depots. The proposed framework includes three main steps: problem formulation, risk analysis, and risk description. The necessary basic details were identified and collected in formulating the problem. The source, pathway, receptor (SPR) model was employed in the risk analysis process. Each part was analyzed using tools that provide appropriate results and maintain the model integrity; additionally, the findings can be used in the whole process. The Dow Fire and Explosion Index (F&EI) was deployed to scrutinize the source, the pollutant dispersion and transmission path characteristics were measured to inspect the pathway, and the vulnerability indicators of the receptor and the degree of impact were determined to scrutinize the receptor. Finally, the risk assessment results were presented in the form of risk description tables. The purpose of this integration was to develop a framework thoroughly evaluating the risk associated with fire and explosion to the point of environmental consequences and providing a better understanding of the outcomes. This study, conducted for the first time specifically for an oil depot, provides an exhaustive view highly contributing to managers and decision makers

Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran

Cutaneous Leishmaniasis (CL) is a neglected tropical disease that continues to be a health problem in Iran. Nearly 350 million people are thought to be at risk. We investigated the impact of the environmental factors on CL incidence during the period 2007- 2015 in a known endemic area for this disease in Isfahan Province, Iran. After collecting data with regard to the climatic, topographic, vegetation coverage and CL cases in the study area, a decision tree model was built using the classification and regression tree algorithm. CL data for the years 2007 until 2012 were used for model construction and the data for the years 2013 until 2015 were used for testing the model. The Root Mean Square error and the correlation factor were used to evaluate the predictive performance of the decision tree model. We found that wind speeds less than 14 m/s, altitudes between 1234 and 1810 m above the mean sea level, vegetation coverage according to the normalized difference vegetation index (NDVI) less than 0.12, rainfall less than 1.6 mm and air temperatures higher than 30°C would correspond to a seasonal incidence of 163.28 per 100,000 persons, while if wind speed is less than 14 m/s, altitude less than 1,810 m and NDVI higher than 0.12, then the mean seasonal incidence of the disease would be 2.27 per 100,000 persons. Environmental factors were found to be important predictive variables for CL incidence and should be considered in surveillance and prevention programmes for CL control

Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors

Leishmaniasis is a parasitic disease caused by different species of protozoan parasites. Cutaneous leishmaniasis (CL) is still a great public health problem in Iran, especially in Isfahan Province. Distribution and abundance of vectors and reservoirs of this disease is affected by different factors such as climatic, socioeconomic and cultural. This study aimed to identify the hotspot areas for CL in Isfahan and assess the relations between the climatic and topographic factors with CL incidence using spatial analysis. We collected data on the total number of CL cases, population at risk, vegetation coverage, altitude and climatic data for each district of the province from 2011 to 2015. Global Moran’s Index was used to map clustering of CL cases across districts and the Getis-Ord (Gi*) statistics was used to determine hotspots areas of the disease in Isfahan. We applied overlay analysis to assess the correlation between the climatic and topographic factors with CL incidence. We found the CL distribution significantly clustered (Moran’s Index=0.17, P<0.001) with the Ardestan and Aran va Bidgol (P<0.01) districts along with the Naein and Natanz districts (P<0.05) to be strong hotspot areas. Overlay analysis revealed a high incidence of CL in areas with relative humidity of 27-30%, mean temperature of 15-19°C, mean precipitation of 5-20 mm, maximum wind speed about 12-16 m/s and an altitude of 600-1,800 m. Our study showed that spatial analysis is a feasible approach for identifying spatial disease pattern and detecting hotspots of this infectious disease