[en] Traditional approaches to risk communication ignore the emotional, cognitive and social factors that interact to influence the meaning people attribute to hazards and protective actions. The aim of this study was to investigate the emotional and cognitive factors predicting preparedness intention and community’s preparedness for flood hazards. A cross-sectional study was conducted between June and July 2015, in Dire Dawa town, Ethiopia. Using stratified systematic random sampling, a structured questionnaire was administered to individuals aged 18 and over in 660 households. Data were analyzed using structural equation modeling (SEM) (STATA version 13.0). The study participants’ mean age was 34 years, ranging from 18 to 80 (SD = 12) with equal gender balance. SEM analysis revealed that the total effects of preparedness intention (path coefficient (β) = 0.202, 95% CI: [0.036, 0.369]), past flood disaster experience (β = 0.034, 95% CI: [0.008, 0.061]), trust (β = 0.100, 95% CI: [0.059, 0.142]), anxiety (β = 0.026, 95% CI: [0.018, 0.034), positive outcome expectancy (β = − 0.139, 95% CI: [− 0.253, − 0.026]), negative outcome expectancy (β = 0.105, 95% CI: [0.062, 0.149]), perceived flood likelihood (β = 0.049, 95% CI: [0.012, 0.086]) and consequence (β = − 0.040, 95% CI: [− 0.077, − 0.003]) on community preparedness for flood hazards were statistically significant. The main implication of these findings is that people affected by hazard events in the past experience more anxiety and are more likely to participate in community preparedness activities than those who were not affected.

[en] Antibiotics, as one of the emerging pollutants, are non-biodegradable compounds and long-term exposure to them may affect endocrine, hormonal, and genetic systems of human beings, representing a potential risk for both the environment and human health. The presence of antibiotics in surface waters and drinking water causes a global health concern. Many researches have stated that conventional methods used for wastewater treatment cannot fully remove antibiotic residues, and they may be detected in receiving waters. It is reported that nanoparticles could remove these compounds even at low concentration and under varied conditions of pH. The current study aimed to review the most relevant publications reporting the use of different nanoparticles to remove antibiotics from aqueous solutions. Moreover, meta-analysis was conducted on the results of some articles. Results of meta-analysis proved that different nanoparticles could remove antibiotics with an acceptable efficiency of 61%. Finally, this review revealed that nanoparticles are promising and efficient materials for degradation and removal of antibiotics from water and wastewater solutions. Furthermore, future perspectives of the new generation nanostructure adsorbents were discussed in this study.