Abstract4-chlorophenol (4-CP) is a hazardous contaminant that is hardly removed by some technologies. This study investigated the biodegradation, and physical 4-CP removal by a mixed microbial consortium in the Airlift packed bed bioreactor (ALPBB) and modeling by an artificial neural network (ANN) for first the time. The removal efficiency of ALPBB was investigated at 4-CP(1-1000 mg/L) and hydraulic retention time (HRT)(6-96 hr) by HPLC. The results showed that removal efficiency decreased from 85 at 1 to 0.03% at 1000 mg/L, with increasing 4-CP concentration and HRT decreasing. BOD5/COD increased with increasing exposure time and concentration decreasing, from 0.05 at 1000 to 0.96 at 1 mg/L. With time increasing, the correlation between COD and 4-CP removal increased (R2 = 0.5, HRT = 96 h). There was a positive correlation between the removal of 4-CP and SCOD by curve fitting was R2 = 0.93 and 0.96, respectively. Moreover, the kinetics of 4-CP removal follows the first-order and pseudo-first-order equation at 1 mg/L and other concentrations, respectively. 4-CP removal modeling has shown that the 2:3:1 and 2:4:1 were the best structures (MSE: physical = 0.126 and biological = 0.9)(R2allphysical = 0.999 and R2testphysical = 0.999) and (R2allbiological = 0.71, and R2testbiological = 0.997) for 4-CP removal. Also, the output obtained by the ANN prediction of 4-CP was correlated to the actual data (R2physical = 0.9997 and R2biological = 0.59). Based on the results, ALPBB with up-flow submerged aeration is a suitable option for the lower concentration of 4-CP, but it had less efficiency at high concentrations. So, physical removal of 4-CP was predominant in biological treatment. Therefore, the modification of this reactor for 4-CP removal is suggested at high concentrations.

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Introduction: Hospitals, as one of the important elements in the health system, play an important role in patient’s health. Fungi are one of the effective parameters on indoor air quality. This study aimed to compare of fungal contamination of two hospitals in Shiraz City. Materials and Methods: Sampling was conducted based on NIOSH 0800 standard (1.5 meters above the ground level with one stage Anderson and Sabaroud dextrose agar enriched chloramphenicol as the growth media) in January-September 2017. The investigated wards included pathological laboratory, emergency rooms, neonatal specialist care, radiology, operating room, and maternity ward. The results showed that the variation and concentration of fungi were higher in hospital X than hospital Y, which was located in an agricultural area far from the city center. Results: The predominant fungi were Monillia, Aspergillus, and Penicillium in hospital Y, while they were Aspergillus and Penicillium in hospital X. The highest concentrations were found in emergency and laboratory wards. With regard to higher fungal contamination of hospital X and its different location, it can be concluded that the geographical properties and outdoor air are effective factors on indoor air contamination at hospitals.   Conclusion: Appropriate management of patients' admission and visiting time can be effective on indoor air contamination at hospitals. Furthermore, efficient ventilation using high-efficiency particulate air and appropriate devices for elimination of fungi level are recommended to this end. Moreover, these parameters can provide physical and psychometric health problems for patients’ careers and other health workers.

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