哈尔滨市阿什河水环境治理技术探讨

阿什河是松花江流域水环境质量最差支河之一,为科学合理地推进阿什河水环境治理,在既定截污治污方案的基础上,研究收集分析了河道水环境治理的最新研究进展,并采用数值模型作为技术手段,综合分析提出了污水处理厂升级改造+人工湿地+引清调度的水环境治理和保护措施.     

煤矿建立职业安全健康管理体系是实现安全生产和提高经济效益的必由之路

煤矿是我国的首要能源企业,也是伤亡事故和职业病最严重的企业.仅尘肺病患者每年新增2000多人.伤亡事故和职业病造成的经济损失高达几百亿人民币.     

Work division of floral scent compounds in mediating pollinator behaviours

Floral scents are known as an olfactory signal for attracting pollinators, but why the flowers pollinated by highly specialised pollinators emit scents consisting of mixtures of many compounds and dominated by one or a few compounds is still poorly understood. We supposed that each (especially characteristic) chemical in floral scents may play a specific role in mediating pollinator behaviours and tested this supposition in a fig-fig wasp mutualism. Ficus curtipes is obligately pollinated by an undescribed Eupristina species. In the scent of F. curtipes receptive figs, over 50 compounds have been identified, and the scent is dominated by two compounds, 6-methyl-5-hepten-2-ol (OL) and 6-methyl-5-hepten-2-one (NE). We therefore tested the roles of the two major chemicals in mediating the pollinator behaviours. Our results show that OL and NE, respectively, act as a long-distance attractant and a fig-entry behaviour stimulant to the obligate pollinator wasp. Namely, OL attracts the wasps to the figs and NE guides the wasps into the figs. This finding on the work division of floral scent compounds partially explains the maintenance mechanism of the fig-fig wasp mutualism and the significance of the chemical diversity of floral scent in plant–pollinator interactions, especially in specialised pollination systems.     

中国职业安全健康标志认证的前景及价值

本文分析了职业安全健康标志应用的必要性和前景,结合国内外先进技术经验,初步设计了基于价值理论的职业安全健康标志的认证和使用制度。与我国现行的生产许可证特种劳防用品强制性认证制度对照,这种社会化自愿形式的认证模式涵盖企业和产品范围更广,认证要求更高,提供个性化服务的功能更强。它是对我国个体防护领域认证制度的一个有益补充,也是接轨全球个体防护产业和产品市场的必要手段。     

电梯部件错误安装的危害

通过检验案例发现的隐患,阐述了安全部件在电梯运行中的重要性。对安全部件安装过程中存在的问题,分析了失效原因以及存在的问题,提出了解决方法。     

New insights into FeS/persulfate system for tetracycline elimination: Iron valence, homogeneous-heterogeneous reactions and degradation pathways

In this study, complete tetracycline（TTC） and above 50% of total organic carbon（TOC） were removed by Fe S/PS after 30 min under optimized conditions. Although free radicals and high-valent iron ions were identified to generate in the process, the apparent similarity between intermediate products of Fe S/PS, Fe/PS, and UV/PS systems demonstrated that the degradation of TTC was due to sulfate radicals(SO₄^·-) and hydroxyl radicals（ ·OH）. Based on the reaction between free radi...     

Sorption and desorption of pymetrozine on six Chinese soils

Pymetrozine is a selective insecticide with a unique chemical structure and mode to control hemipteran and homopteran. While pymetrozine has brought great benefits to crop production by killing insects, its residues in soil may have a detrimental effect on environment. Therefore, it is of great importance to investigate its behaviors in soil. In this study, the sorption and desorption of pymetrozine on six Chinese soils were investigated using a batch equilibrium approach to understand its mobile behavior in the soils. Both sorption and desorption isotherms of pymetrozine were in good agreement with the Freundlich model. The sorption coefficient K_F varied between 3.37 and 58.32 mL∙g⁻¹ and the sorption isotherms were nonlinear, with 1/n ranging from 0.57 to 0.91. A regression equation was proposed to predict the sorption of pymetrozine on six different soil samples: log K_F = 4.3708 − 4.5709 × log (pH in 0.01mol·L⁻¹ CaCl₂) + 0.4700 × log OC% + 0.0057 × sand (%) + 0.0022 × CEC(clay), with R² = 0.9982. The organic carbon content of soil positively affected the sorption of pymetrozine, but soil pH had a negative effect on the sorption. Additionally, effects of CaCl₂ concentration, soil to solution ratio and pesticide form were investigated. The sorption was promoted with an increase in soil to solution ratio and a decrease in CaCl₂ concentration. The possible variation of the five formulated products of pymetrozine was also investigated.     

Significant enhancement in catalytic ozonation efficacy: From granular to super-fine powdered activated carbon

In this study, super-fine powdered activated carbon (SPAC) has been proposed and investigated as a novel catalyst for the catalytic ozonation of oxalate for the first time. SPAC was prepared from commercial granular activated carbon (GAC) by ball milling. SPAC exhibited high external surface area with a far greater member of meso- and macropores (563% increase in volume). The catalytic performances of activated carbons (ACs) of 8 sizes were compared and the rate constant for pseudo first-order total organic carbon removal increased from 0.012 min^–1 to 0.568 min^–1 (47-fold increase) with the decrease in size of AC from 20 to 40 mesh (863 mm) to SPAC (~1.0 mm). Furthermore, the diffusion resistance of SPAC decreased 17-fold compared with GAC. The ratio of oxalate degradation by surface reaction increased by 57%. The rate of transformation of ozone to radicals by SPAC was 330 times that of GAC. The results suggest that a series of changes stimulated by ball milling, including a larger ratio of external surface area, less diffusion resistance, significant surface reaction and potential oxidized surface all contributed to enhancing catalytic ozonation performance. This study demonstrated that SPAC is a simple and effective catalyst for enhancing catalytic ozonation efficacy.

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The combined effects of biomass and temperature on maximum specific ammonia oxidation rate in domestic wastewater treatment

• Actual SAORs was determined using MLVSS and temperature. • Measured SAOR decreased with increasing MLVSS 1.1‒8.7 g/L. • Temperature coefficient (θ) decreased with increasing MLVSS. • Nitrification process was dynamically simulated based on laboratory-scale SBR tests. • A modified model was successfully validated in pilot-scale SBR systems. Measurement and predicted variations of ammonia oxidation rate (AOR) are critical for the optimization of biological nitrogen removal, however, it is difficult to predict accurate AOR based on current models. In this study, a modified model was developed to predict AOR based on laboratory-scale tests and verified through pilot-scale tests. In biological nitrogen removal reactors, the specific ammonia oxidation rate (SAOR) was affected by both mixed liquor volatile suspended solids (MLVSS) concentration and temperature. When MLVSS increased 1.6, 4.2, and 7.1-fold (1.3‒8.9 g/L, at 20°C), the measured SAOR decreased by 21%, 49%, and 56%, respectively. Thereby, the estimated SAOR was suggested to modify when MLVSS changed through a power equation fitting. In addition, temperature coefficient (θ) was modified based on MLVSS concentration. These results suggested that the prediction of variations ammonia oxidation rate in real wastewater treatment system could be more accurate when considering the effect of MLVSS variations on SAOR.     

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

• UV-vis absorption analyzer was applied in drainage type online recognition. • The UV-vis spectrum of four drainage types were collected and evaluated. • A convolutional neural network with multiple derivative inputs was established. • Effects of different network structures and input contents were compared. Optimizing sewage collection is important for water pollution control and wastewater treatment plants quality and efficiency improvement. Currently, the urban drainage pipeline network is upgrading to improve its classification and collection ability. However, there is a lack of efficient online monitoring and identification technology. UV-visible absorption spectrum probe is considered as a potential monitoring method due to its small size, reagent-free and fast detection. Because the performance parameters of probe like optic resolution, dynamic interval and signal-to-noise ratio are weak and high turbidity of sewage raises the noise level, it is necessary to extract shape features from the turbidity disturbed drainage spectrum for classification purposes. In this study, drainage network samples were online collected and tested, and four types were labeled according to sample sites and environment situation. Derivative spectrum were adopted to amplify the shape features, while convolutional neural network algorithm was established to conduct nonlinear spectrum classification. Influence of input and network structure on classification accuracy was compared. Original spectrum, first-order derivative spectrum and a combination of both were set to be three different inputs. Artificial neural network with or without convolutional layer were set be two different network structures. The results revealed a convolutional neural network combined with inputs of first and zero-order derivatives was proposed to have the best classification effect on domestic sewage, mixed rainwater, rainwater and industrial sewage. The recognition rate of industrial wastewater was 100%, and the recognition rate of domestic sewage and rainwater mixing system were over 90%.