Methods for the preparation of a biodesulfurization biocatalyst using Rhodococcus sp

Several methods to prepare a biodesulfurization (BDS) biocatalyst were investigated in this study using a strain of Rhodococcus sp. 1awq. This bacterium could selectively remove sulfur from dibenzothiophene (DBT) via the "4S" pathway. DBT, dimethylsulfoxide (DMSO), sodium sulphate and mixed sulfur sources were used to study their influence on cell density, desulfurization activity, desulfurization ability, and the cost of biocatalyst production. In contrast to that observed from bacteria cultured in DBT, only partial desulfurization activity of strain 1awq was induced by DBT after cultivation in a medium containing inorganic sulfur as the sole sulfur source. The biocatalyst, prepared from culture with mixed sulfur sources, was found to possess desulfurization activity. With DMSO as the sole sulfur source, the desulfurization activity was shown to be similar to that of bacteria incubated in medium with DBT as the sole sulfur source. The biocatalyst prepared by this method with the least cost could remove sulfur from hydrodesulfurization (HDS)-treated diesel oil efficiently, providing a total desulfurization percent of 78% and suggesting its cost-effective advantage.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Distribution and dissipation pathways of nonylphenol polyethoxylates in the Yellow River: Site investigation and lab-scale studies

Spatial distribution of nonylphenol polyethoxylates (NPEOs) and nonylphenol (NP) was investigated in a field study in Lanzhou Reach of the Yellow River. NPEOs and their metabolites were found in the river, with the maximum dissolved concentrations of 6.38 nmol/L for NPEOs, 0.19 nmol/L for nonylphenol ethoxy acetic acids (NPECs) and 0.79 nmol/L for NP, respectively. The maximum concentrations in the sediment and suspended particle samples were 1.50 and 5.09 nmol/g for NPEOs and NP, respectively. The effects of particles, light and microorganism on the dissipation of NPEOs in the river water were investigated based on lab-scale experiments. When natural particles were removed, 72% and 22% degradation of NPEOs were achieved at 120 h in non-sterile and sterile conditions with light, respectively. Different concentrations of NPECs were also observed in these experiments. When suspended particle matters (SPMs) were present, about 38-50% of NPEOs were sorbed to the particulate phase in only 1 h. As a result, the degradation of NPEOs and production of NPECs were inhibited. However, the combined sorption and degradation in the presence of SPMs resulted in lower dissolved NPEO concentrations than those in the absence of SPMs. Biodegradation was the most important pathway for NPEOs degradation in the river water, while NPECs seemed to be produced through both biological and abiological pathways.     

油层注水过程中水质不合要求的危害及保护措施

分析了油田在二次采油注水过程中,对水质的要求,讨论了水质不合格带来的危害并提出了保护措施.     

液态烃球罐检验风险评价及防范措施

运用危害识别、风险评价理论,对液态烃球罐的检验过程中容易发生的危害进行了分析,找出了存在的重大风险,制订了防范措施,保证了安全检验.     

锅炉蒸汽过热器爆管原因分析及整改措施

针对锅炉过热器管在运行中常见的过热爆管问题 ,从原理及运行工况的角度进行分析 ,并提出了有效的隐患整改措施 ,保证了锅炉的正常运行。     

特警战训服面料开发技术研究

本文介绍了以芳纶纤维为主要材料的我国新一代特警战训服面料的技术研发及达到的主要性能指标。通过试验研究,开发了具有高强防撕裂、永久阻燃、耐高温、防静电、防油拒水、防酸碱等具有集成防护功能的特警战训服系列面料。     

稻田土菌群驯化对稻秆两步发酵产甲烷效果的影响

为提高稻秆的降解率及其厌氧发酵甲烷产量,采用高氨氮畜禽废水作为氮源以驯化稻田土壤微生物,优化其降解稻秆的初始pH值,并评估水解产物液体发酵产甲烷性能.结果表明,混合组驯化的微生物产纤维素酶活性及对稻秆木质素的降解率高于其它组及先前文献报道,分别达到4.01 IU和51.96%,且后期水解液中总有机碳（Total organic carbon, TOC）及还原糖含量最高.随着初始pH值的提高,稻秆中纤维素、半纤维素和木质素的降解率显著增加,稻秆水解液中的挥发性脂肪酸（Volatile fatty acids, VFAs）和TOC含量均显著增加,并在第7 d达到最高值.将水解稻秆7 d的水解液进行厌氧发酵显示,在初始pH=9.0条件下累积甲烷产量达到最大,为37.60 mL·mL^-1水解液.本实验结果表明, 驯化的稻田土微生物在碱性条件下可以更有效地降解稻秆,提高水解液中TOC及VFAs含量,从而提高厌氧发酵的甲烷产量.     

絮凝剂用壳聚糖的中试生产研究

在实验室制备絮凝剂用壳聚糖的基础上,按工业化生产的要求对壳聚糖进行了中试生产研究.经正交试验确定了生产过程中脱钙、脱蛋白、脱乙酰等3步反应的最佳工艺参数. 由此中试工艺生产的壳聚糖的生产成本比国内同类产品下降了22%,生产周期缩短了66%,且主要性能指标均达到或超过国内外同类产品的水平.     

雨雪冰冻灾害后粤北森林各林型凋落物动态

为了考察中国亚热带不同森林类型对雨雪冰冻灾害的响应模式,以粤北天井山3种代表性的林型—针叶林、阔叶林和混交林为对象,于不同森林类型中比较受损森林与未受损森林在凋落物年产量、成分及月际动态方面的差异,从而在凋落物水平上反映不同森林类型在雨雪冰冻灾害后的早期恢复力。研究结果表明,灾后针叶林、阔叶林和混交林的年凋落量分别为0.52、3.21、1.37 t.hm-2,比未受损的同种森林类型年凋落量显著减少,减少程度分别为87.89%、53.46%、76.78%。由此可以看出阔叶林的植被恢复情况最好,说明在凋落物水平上,其灾后恢复的早期阶段恢复力最强。在凋落物成分方面,灾后各森林类型叶凋落物所占比例显著增加,枝凋落物所占比例则显著减少。受损针叶林和阔叶林的凋落物月动态与未受损森林基本一致,但其波动幅度较小;在混交林中,受损和未受损森林其凋落量的季节动态模式则表现出不一致性且为不规则型。根据研究结果,建议在亚热带地区优先考虑种植阔叶林以促进受损森林在类似雨雪冰冻灾害的极端天气后的恢复。