A novel bacterium designated strain B-16 was isolated from the compost leachate of the municipal solid waste (MSW) in a laboratory reactor. This strain was identified as a gram-negative bacterium, Achromobacter xylosoxidans that could grow on bisphenol A (BPA, a representative endocrine disruptor) as a sole carbon source under aerobic condition. BPA-degrading characteristics of strain B-16 were investigated in liquid cultures. The results show that BPA degradation was influenced by several factors (e.g. inoculum size, substrate concentration, temperature and pH, etc). The half-lives, optimum temperature and pH were found to be 0.58-3.1d, 35 degrees C and 7.0, respectively. BPA-degrading activity and cell growth were inhibited at high substrate concentration. Metabolic intermediates detected during the degradation process were identified as p-hydroxybenzaldehyde, p-hydroxybenzoic acid and p-hydroquinone, respectively. Metabolic pathway of BPA degradation was proposed in this study. 相似文献
Robust decision making, a growing approach to infrastructure planning under climate change uncertainty, aims to evaluate infrastructure performance across a wide range of possible conditions and identify the most robust strategies and designs. Robust decision making seeks to find potential weaknesses in systems in order to gird these through a combination of policy, infrastructure, and, in some cases, resilient or recovery strategies. A system can be explored by simulating many combinations of uncertain climatic and economic parameters; statistical clustering can identify parameter thresholds that lead to unacceptable performance. Often, however, uncertain variables are correlated, complicating the robustness analysis and casting doubt upon the thresholds identified. Here, we evaluate the impact of ordinary, hidden correlations in uncertainty parameters that drive simulation in robust decision making. We induced correlations between temperature and key climatic and economic parameters. We tested correlations of 0%, 30%, 60%, and 90% between temperature and the absolute value of precipitation, coefficient of variation, and downward surface solar radiation, and negative correlations between temperature and net variable benefit and the discount rate. We used a calibrated simulation model of a dam system regulating Lake Tana, Ethiopia, to compute the agricultural supply and net present value of the reservoirs. As the correlation strength increased, the results converged in a smaller region. We found that strong correlations depressed robustness scores of lower-performing alternatives and conversely increased results of the higher-performing alternatives. As the correlations increased in favorable alternatives, the failure thresholds became more extreme, speciously suggesting that only intense changes would result in poor performance. This overall analysis highlights the degree to which correlations of an interconnected climatic and economic system can impact outcomes of robust decision making and suggests methods to avoid confounding results.
