Evaluating nitrite oxidizing organism survival under different nitrite concentrations

亚硝酸盐 氧化剂 化学 染色 有机体 氧气 细菌细胞结构 环境化学 细菌 色谱法 生物 硝酸盐 有机化学 遗传学 古生物学
作者
Bing Liu,Yifan Li,Jinzhu Wu,Yuanyuan Shao,Feiyong Chen,Jer Horng Wu,Rajeev Goel,Mitsuharu Terashima,Hidenari Yasui
出处
期刊:Water Science and Technology [IWA Publishing]
被引量:1
标识
DOI:10.2166/wst.2020.138
摘要

Abstract The objective of this study is to explore the optimal pre-treatment procedures and statistics methods for live/dead bacterial staining using nitrite oxidizing organism (NOO) as the research aim. This staining method was developed and widely utilized to evaluate activated bacterial survival situation, because it is direct and convenience to count live and dead bacteria amount by colour distinguishes (green/red) from pictures taken by microscope. The living cell (green colour) percentage and initial bacterial chemical oxygen demand (COD) could be used for accurate reaction rate calculation at the beginning of tests. While according to the physiological principles, the detection target was limited as the organism has a complete cell shape, that was applicable for the initial phase for decay stage (live cell → particulate dead cell), but it is impossible to evaluate the decayed soluble COD from particulate dead cell during whole reaction. To model the decay stage scientifically, a two-step decay model was developed to cater to the live/dead bacterial staining analysis of biological nitrite oxidizer under inhibition condition of high nitrite concentrations at 35 °C. As results of optimal pre-treatment, a three level ultrasonic wave with 45 seconds was explored, as a reasonable observed picture number, 30 sets with 95% confident interval for datasets statistics was summarized. A set of nitrite oxidizer inhibition test (total CODs and oxygen uptake rates) under high nitrite concentrations was simulated using the above model and obtained experimental schemes. Additionally, the disintegration enhancement from particulate dead cell to soluble COD by nitrite was inspected and modelled on the basis of experimental datasets.
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