Accumulation,root-shoot translocation and phytotoxicity of substituted polycyclic aromatic hydrocarbons in wheat

Environmental Chemistry Letters - While pollution of the environment by polycyclic aromatic hydrocarbons has been rather well studied, the fate of substituted polycyclic aromatic hydrocarbons in...     

Adsorption of Pb2+ by insolubilized humic acid extracted from sewage sludge

Journal of Material Cycles and Waste Management - This study used excess sludge from a sewage treatment plant as raw material to extract humic acid (HA) and explore the ability of HA to adsorb Pb2+...     

Effects of Bacillus subtilis on the growth,colony maintenance,and attached bacterial community composition of colonial cyanobacteria

In freshwater aquaculture ponds, application of algicidal Bacillus is a promising way in the control of cyanobacterial blooms. To best understand Bacillus algicidal characters and mechanisms in the field, different-sized colonial cyanobacteria were isolated from an aquaculture pond, and the effects of B. subtilis on their growth, colony maintenance, and colony-attached bacterial community composition were investigated. The results showed that B. subtilis could inhibit the growth of colonial cyanobacteria. Bigger-sized colonies isolated from the field could spontaneously disintegrate into smaller-sized colonies in the laboratory. Algicidal B. subtilis could accelerate the disintegration of colonies and decrease colony size. B. subtilis not only decreased the colony-attached bacterial community diversity but also changed its composition. B. subtilis increased the relative abundances of some attached bacterial genera, including Pseudomonas, Shewanella, Bacillus, Shinella, Rhizobium, and Ensifer. These bacteria with algicidal, microcystin-degrading, and flocculating activities might be an important contributor to algicidal effects of B. subtilis on colonial cyanobacteria.

     

孔石莼和重金属（铜与镉）对海水无机碳体系影响的模拟研究

通过室内实验模拟并应用海洋生态系统动力学模型,研究了孔石莼和重金属(铜与镉)共同作用下,海水二氧化碳体系及海洋碳源汇强度的变化过程.结果表明,二氧化碳体系各组分含量随时间的变化幅度(Δ)和趋势与重金属种类和添加浓度有关.与对照相比,低浓度(0.1μmol·L^-1和1μmol·L^-1)的铜、镉添加组中,DIC、HCO₃^-和pCO₂均随时间的延长呈下降趋势(p=0.01).而当铜、镉浓度大于“转折浓度”后,t=7时DIC、HCO₃^-和p_CO2均要大于初始值,其增幅随着重金属浓度的增加而增大.对于Δ由负值过渡到正值所对应的“转折浓度”,铜添加组要明显低于镉添加组.这与孔石莼对不同种类重金属的耐受程度不同有关.此外,当重金属浓度不同时,箱中的碳源汇格局亦随时间做不同的变化.当重金属浓度较低时,箱内水体表现为CO₂的汇,并且随着时间推移,可能过渡成为大气CO₂的源;高浓度重金属的影响下,箱内水体表现为CO₂的源,且随重金属浓度的增大,其向大气释放CO2的量也增加.     

Speciation and quantification of vapor phases in soy biodiesel and waste cooking oil biodiesel

This study characterizes the compositions of two biodiesel vapors, soy biodiesel and waste cooking oil biodiesel, to provide a comprehensive understanding of biodiesels. Vapor phases were sampled by purging oil vapors through thermal desorption tubes which were then analyzed by the thermal desorption/GC/MS system. The results show that the compounds of biodiesel vapors can be divided into four groups. They include methyl esters (the main biodiesel components), oxygenated chemicals, alkanes and alkenes, and aromatics. The first two chemical groups are only found in biodiesel vapors, not in the diesel vapor emissions. The percentages of mean concentrations for methyl esters, oxygenated chemicals, alkanes and alkenes, and aromatics are 66.1%, 22.8%, 4.8% and 6.4%, respectively for soy biodiesel, and 35.8%, 35.9%, 27.9% and 0.3%, respectively for waste cooking oil biodiesel at a temperature of 25 ± 2 °C. These results show that biodiesels have fewer chemicals and lower concentrations in vapor phase than petroleum diesel, and the total emission rates are between one-sixteenth and one-sixth of that of diesel emission, corresponding to fuel evaporative emissions of loading losses of between 106 μg l⁻¹ and 283 μg l⁻¹. Although diesels generate more vapor phase emissions, biodiesels still generate considerable amount of vapor emissions, particularly the emissions from methyl esters and oxygenated chemicals. These two chemical groups are more reactive than alkanes and aromatics. Therefore, speciation and quantification of biodiesel vapor phases are important.     

A fuzzy Bayesian network approach to improve the quantification of organizational influences in HRA frameworks

Organizational factors are the major root causes of human errors, while there have been no formal causal model of human behavior to model the effects of organizational factors on human reliability. The purpose of this paper is to develop a fuzzy Bayesian network (BN) approach to improve the quantification of organizational influences in HRA (human reliability analysis) frameworks. Firstly, a conceptual causal framework is built to analyze the causal relationships between organizational factors and human reliability or human error. Then, the probability inference model for HRA is built by combining the conceptual causal framework with BN to implement causal and diagnostic inference. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual causal model with BN approach can not only qualitatively model the causal relationships between organizational factors and human reliability but also can quantitatively measure human operational reliability, and identify the most likely root causes or the prioritization of root causes causing human error.     

Air pollution and body burden of persistent organic pollutants at an electronic waste recycling area of China

Environmental Geochemistry and Health - This paper reviews the concentrations of persistent organic pollutants (POPs) in atmosphere of an electronic waste (e-waste) recycling town, Guiyu, in...     

Effect of composition and microstructure of humic acid on 3,3′,4,4′-tetrachlorobiphenyl sorption

Environmental Science and Pollution Research - The fate and transport of polychlorinated biphenyls (PCBs), a class of persistent organic compounds, in soils was markedly affected by their...