Heterotrophic Biological Denitrification Using Microbial Cellulose as Carbon Source

The objective of this study was to investigate the feasibility of using a microbial biopolymer produced by Acetobacter xylinum as a carbon source for heterotrophic biological denitrification. The denitrification rate, COD availability and nitrite concentration were response parameters. Under the experimental conditions, a denitrification rate of about 0.74 kg NO₃ ⁻N/m³d at 6 h retention time was achieved with microbial cellulose (MC). The reactor effluent contained significantly COD concentrations (20–86 mg/L) so it was not carbon limited, and was receiving enough carbon to facilitate the denitrification process. The maximum nitrite concentration in the effluent was found to be 0.4 mg/L. However, decreasing the retention time to 3 h significantly reduced the efficiency. It can be concluded that the MC is a suitable carbon source for nitrate removal in a heterotrophic biological denitrification process.     

Validity and consistency assessment of accident analysis methods in the petroleum industry

Background. Accident analysis is the main aspect of accident investigation. It includes the method of connecting different causes in a procedural way. Therefore, it is important to use valid and reliable methods for the investigation of different causal factors of accidents, especially the noteworthy ones. Objective. This study aimed to prominently assess the accuracy (sensitivity index [SI]) and consistency of the six most commonly used accident analysis methods in the petroleum industry. Methods. In order to evaluate the methods of accident analysis, two real case studies (process safety and personal accident) from the petroleum industry were analyzed by 10 assessors. The accuracy and consistency of these methods were then evaluated. The assessors were trained in the workshop of accident analysis methods. Results. The systematic cause analysis technique and bowtie methods gained the greatest SI scores for both personal and process safety accidents, respectively. The best average results of the consistency in a single method (based on 10 independent assessors) were in the region of 70%. Conclusion. This study confirmed that the application of methods with pre-defined causes and a logic tree could enhance the sensitivity and consistency of accident analysis.     

High photocatalytic decomposition of the air pollutant formaldehyde using nano-ZnO on bone char

Air pollution is a major issue leading to many serious illnesses. Exposure to formaldehyde may occur by breathing contaminated indoor air, tobacco smoke, or ambient urban air. Exposure to formaldehyde has been associated with lung and nasopharyngeal cancer. Therefore, there is a need for methods to degrade formaldehyde. Here, we studied the photocatalytic decomposition of gaseous formaldehyde over nanosized ZnO particles on bone char. The conditions were UV/bone char, UV/ZnO nanoparticles, and UV/ZnO-bone char in continuous flow mode. We investigated the effects of humidity, initial formaldehyde concentration, and residence time on decomposition of formaldehyde. Agglomeration of ZnO particles in the bone char pores was characterized by Brunauer, Emmett, and Teller surface area, and scanning electron micrograph. Results show that maximum decomposition efficiency of formaldehyde was 73 %. The optimal relative humidity was by 35 %. Findings also indicated that immobilization of ZnO nanoparticles on bone char has a synergetic action on photocatalytic degradation. This is explained by the strong adsorption of formaldehyde molecules on bone char, resulting in higher diffusion to the catalytic ZnO and thus a higher rate of photocatalysis.