mehdi kamari

Bioaerosols are airborne particles that include living organisms, such as bacteria and fungi, and their related metabolites, including endotoxins. This study aimed to investigate the exposure of individuals to bacterial bioaerosols in indoor air and explore the factors influencing their concentration.

This research was conducted across 11 wards of the Camp Collection to assess indoor air quality. A total of 224 samples were analyzed. The resulting bacterial colonies were counted, and bacterial density was expressed as colony-forming units per cubic meter (CFU/m³). The data obtained were analyzed using SPSS, ANOVA.

The mean bacterial concentration was 721 CFU/m³. The most prevalent bacteria identified in the air samples were Staphylococcus aureus and Staphylococcus epidermidis.

In some environments, the bioaerosol concentration in indoor air exceeded the World Health Organization (WHO) guidelines, posing health risks and increasing the likelihood of respiratory diseases. To mitigate these risks, it is recommended to control individual traffic, modify disinfectant types and application procedures on ward surfaces, and establish the standard and suitable ventilation systems.

This paper presents a novel super efficiency model based on the Andersen-Petersen model, which serves as a bridge between input-oriented and output-oriented models. The proposed model defines a path from the deleted decision-making unit to the efficiency frontier with the shortest step length. Initially formulated as a nonlinear programming model, the developed model is transformed into a multi-objective linear programming model and then further simplified into a linear programming model through variable changes and the application of nonlinear programming solving methods. The feasibility of the proposed path is discussed, and a weighted version of the shortest path model is introduced to incorporate preferences regarding the relative importance of inputs or outputs. Addressing a weakness of the AP methods, the inability to prioritize weights is resolved in the developed model. Real case studies in the context of Iranian education are conducted, and the results of the AP and shortest path analyses are analyzed to validate the proposed method.

Phenol is extensively used in various industries and it is mainly discharged to the enviroment from their effluents. In this study, the effectivness of UV activated periodate for removal of phenol in aqueous solutions was investigated.
In this research,experimens were conducted in a bench scale stainless steel reactor equipped with a 55W Hg vapor lamp. The effects of operational parameters such as solution pH (3-10), initial phenol concentration (50-500 mg/L), periodate concentration (8-100 mmol/L) were evaluated. Further, ionic strengh was changed to study its impact on the performance. The final concentration of phenol and mineralization rate were determined using DR-6000 spectrophotometer (at thewavelenght of 500 nm) and COD analysis, respectively.
The findings indicated that the removal of phenol was influenced by different operational parameters. The highest removal rate was obtained at acidic conditions (pH=3), initial periodate concentration of 20 mmol/Land contact time of 60 min, which more than 99.1% of phenol was removed under these optimal conditions. Also,the results showed that maximum COD removal rate was 69% in optimum conditions. It was found that different ionic strengths did not affect the phenol removal rate.
The results indicated that UV activated persulfate process in optimal condition can be used as an alternative technology for treatment of various industrial wastewaters containing phenol.