HSE管理体系审核的主要记录

对一个单位进行HSE管理体系审核时,短时间内要面对大量的记录,做到面面俱到比较困难.因此,审核时重点选择重要记录作为审核对象十分必要,这样不但可以有效取得审核的证据,而且,也把握住了体系运行的关键环节,提高了审核的效率.     

浅谈作业场所有害因素检测工作的质量控制

从实际工作出发,围绕质量管理体系的控制要点,探讨了作业场所有害因素检测工作的质量控制.     

灌区上游水源区生态价值评估方法及实例研究

灌区上游水源区所产生的巨大生态效益对灌区的经济社会发展有着举足轻重的作用。基于对灌区上游水源区生态价值要素的识别,构建了包含4个层次、18项评估指标的灌区上游水源区生态价值评估指标体系,较为全面地反映了区域生态价值的整体构成。并以淠史杭灌区的上游水源区为例,用影子工程法、市场价值法等定量的方法,分别从物质产品价值和生态服务价值两方面评估了其生态价值。结果表明：淠史杭灌区上游水源区的生态价值总量为425．17亿元,充分体现了上游水源区对下游乃至全社会做出的巨大生态服务贡献。     

铁屑在印染废水处理中的应用研究

印染废水由于污染物浓度高,成分复杂,可生化性差,成为难处理的工业废水之一。本文从铁屑的还原性、电化学性质和絮凝作用三方面阐述了铁屑对印染废水的作用机理,介绍了铁屑微电解法处理印染废水,铁屑与其他物质组合处理印染废水,生物铁法等在印染、染料废水处理方面的研究现状、应用情况以及部分作用机理,研究表明铁屑在印染废水的COD和色度去除率方面显示出良好的治理效果,利用铁屑治理染料和印染废水,有以废治废的特点,具有很高的推广应用价值。     

石化装置苯泄漏检测及危害控制方法

石化装置苯泄漏的危害严重,已引起广泛关注。对石化装置苯泄漏的危害、苯泄漏的检测方法进行了评述,指出苯泄漏检测需要多种检测手段联合进行,同时应对泄漏危害加以控制。     

Pilot study on bromate reduction in ozonation of water with low carbonate alkalinities by carbon dioxide

A pilot study was carried out to explore the application of carbon dioxide for pH depression in a bubble column and its ability to inhibit bromate formation for water with a low alkalinity. Results showed that in the absence of ammonia, CO2 was capable of reducing bromate 38.0%–65.4% with one-unit pH depression. CO2 caused a slightly lower bromate reduction (4.2%) than did H2SO4 when the pH was depressed to 7.4, and a more a pronounced lower reduction (8.8%) when the pH was depressed to 6.9. In the presence of 0.20 mg/L-N ammonia, bromate was largely inhibited with 73.9% reduction. When the pH was depressed to 7.4, CO2 and H2SO4 showed an 11.3% and 23.5% bromate reduction respectively, demonstrating that the joint use of CO2 and ammonia might be a plausible strategy of blocking all three bromate formation pathways. CO2 could be applied through the aeration diffuser together with ozone gas, resulting in a similar bromate reduction compared with the premixing method through Venturi mixer.     

Speciation characterization and coagulation of poly-silica-ferric-chloride: The role of hydrolyzed Fe(Ⅲ) and silica interaction

The highly efficient inorganic polymer flocculants (IPFs) of the ferric-silica system is a new and promising coagulant. Interactions between ferric species and silica play a large part in the coagulation of suspensions. These effects are quite distinct from those associated with polymeric or colloid silica. However, although these species are key to coagulation efficiency, they have not been comprehensively discussed. A new type of coagulant, poly-silica-ferric-chloride (PFSC), was synthesized by co-polymerization and characterized by time complexation spectroscopy and photon correlation spectroscopy. Compared with traditional ferric salt, the results indicated that PFSC had a higher molecular weight, lesser positive charge, lower Feb and higher Fec. The higher the Si/Fe ratio, the higher the silica and lower the silicac found. The PFSC with appropriate polysilica acid not only obtained better coaguiation/fiocculation efficiency in turbidity removal, enhanced the flocculation index (FI) and provided less residual ferric, it also lowered water treatment costs compared to traditional ferric salt. Results showed that PFSC could remove colloid particles in water by charge neutralization and sweeping,adsorption bridging mechanism.     

三维粒子电极填充方式对焦化废水深度处理能耗的影响

采用钌钛网(Ti/Ru O2)为阳极、钛网(Ti)为阴极、活性炭颗粒为三维粒子电极的电催化氧化装置深度处理焦化废水,通过分析处理效果和能耗研究了三维粒子电极填充方式的影响。结果显示三维悬挂电极填充方式的处理效果和能耗与传统三维电极填充方式相近,但所需材料质量及反应器容积分别为后者的34%与67%。新的填充方式在电流密度2.5 m A/cm2、悬挂电极总质量49.4g、流速100 m L/min的条件下处理120 min后,焦化废水ρ(COD)由99 mg/L降至53 mg/L,COD去除率为46.5%,单位COD处理能耗为68.5 k W·h/kg,吨水能耗为3.15 k W·h/t。     

Effects of elevated atmospheric CO2 concentration and temperature on the soil profile methane distribution and diffusion in rice-wheat rotation system

The aim of this experiment was to determine the impacts of climate change on soil profile concentrations and diffusion effluxes of methane in a rice–wheat annual rotation ecosystem in Southeastern China. We initiated a field experiment with four treatments:ambient conditions(CKs), CO_2 concentration elevated to ~ 500 μmol/mol(FACE),temperature elevated by ca. 2°C(T) and combined elevation of CO_2 concentration and temperature(FACE + T). A multilevel sampling probe was designed to collect the soil gas at four different depths, namely, 7 cm, 15 cm, 30 cm and 50 cm. Methane concentrations were higher during the rice season and decreased with depth, while lower during the wheat season and increased with depth. Compared to CK, mean methane concentration was increased by 42%, 57% and 71% under the FACE, FACE + T and T treatments, respectively, at the 7 cm depth during the rice season(p 0.05). Mean methane diffusion effluxes to the 7 cm depth were positive in the rice season and negative in the wheat season, resulting in the paddy field being a source and weak sink, respectively. Moreover, mean methane diffusion effluxes in the rice season were 0.94, 1.19 and 1.42 mg C/(m~2·hr) in the FACE,FACE + T and T treatments, respectively, being clearly higher than that in the CK. The results indicated that elevated atmospheric CO_2 concentration and temperature could significantly increase soil profile methane concentrations and their effluxes from a rice–wheat field annual rotation ecosystem(p 0.05).     

Forecasting of dissolved oxygen in the Guanting reservoir using an optimized NGBM (1,1) model

An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet(China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.