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.
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. 相似文献
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. 相似文献
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... 相似文献
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... 相似文献
Artificial Neural Network (ANN) is a flexible and popular tool for predicting the non-linear behavior in the environmental system. Here, the feed-forward ANN model was used to investigate the relationship among the land use, fertilizer, and hydrometerological conditions in 59 river basins over Japan and then applied to estimate the monthly river total nitrogen concentration (TNC). It was shown by the sensitivity analysis, that precipitation, temperature, river discharge, forest area and urban area have high relationships with TNC. The ANN structure having eight inputs and one hidden layer with seven nodes gives the best estimate of TNC. The 1:1 scatter plots of predicted versus measured TNC were closely aligned and provided coefficients of errors of 0.98 and 0.93 for ANNs calibration and validation, respectively. From the results obtained, the ANN model gave satisfactory predictions of stream TNC and appears to be a useful tool for prediction of TNC in Japanese streams. It indicates that the ANN model was able to provide accurate estimates of nitrogen concentration in streams. Its application to such environmental data will encourage further studies on prediction of stream TNC in ungauged rivers and provide a useful tool for water resource and environment managers to obtain a quick preliminary assessment of TNC variations. 相似文献