پژوهش در بهداشت محیط
سال:1400 | دوره: | شماره: |تعداد مقالات:3

Background and Aim: The presence of drugs in water and wastewater sources poses risks to humans and the environment. These materials are not completely eliminated by conventional water and wastewater treatment methods. This study aimed to investigate the photocatalytic removal of acetaminophen from aqueous solutions by the advanced UV/H2O2/ZnO oxidation method. Materials and Methods: In this experimental analytical study, zinc oxide and hydrogen peroxide were used in a 500 ml reactor under UV-C irradiation to remove acetaminophen. The effects of initial parameters of acetaminophen, solution pH, contact time, hydrogen peroxide concentration, and zinc oxide nanoparticle concentration were investigated. Experiments were designed and analyzed using the CCD method by Design Expert 10 software. Results: The maximum removal efficiency of acetaminophen was obtained as 94% at pH 7, contact time 8 min, the initial contaminant concentration 62. 5 mg/l, catalyst dose 0. 0275 g, and H2O2 concentration 2 ml. By changing the time to 1 and 15 minutes, the removal rate decreased by 26 and 76%, respectively, and by increasing the catalyst dose from 0. 0275 g to 0. 05 g, the removal rate increased by 99%. Conclusion: In this study, the efficiency decreased with increasing contaminant concentration. The removal efficiency was higher in neutral conditions than in acidic and alkaline conditions. The photocatalytic process (UV/H2O2/ZnO) is highly potent for removing acetaminophen from aqueous solutions.

Background and Aim: COVID-19, also commonly referred to as coronavirus disease, is an acute respiratory infection caused by a novel coronavirus. The virus affects the respiratory system and can cause headaches and fever for up to several days. This study aimed to investigate the preventive behaviors regarding COVID-19 based on the health belief model in Kermanshah. Materials and Methods: This descriptive-analytical cross-sectional study was performed on 500 individuals in Kermanshah in 2020. The sample was selected by cluster sampling. Data were collected using a researcher-made questionnaire based on a pilot study according to the health belief model. Data were analyzed using Pearson correlation coefficient and linear regression. Results: The correlation coefficient showed that the strongest correlation was reported between the constructs of perceived barriers and in terms of behavior, the strongest correlation was observed between perceived benefits and behavior. The results of linear regression analysis predicted 17% of the variance of COVID-19 prevention behaviors. Among them, perceived sensitivity (0. 593) was the strongest predictor. Conclusion: The results of this study strongly showed the application of the health belief model in predicting the prevention behavior of COVID-19, and it seems that this model can be used in developing educational programs and interventions to change people’, s attitudes and behavior.