碱激发胶凝材料及其固化Pb^2＋的试验研究

对碱激胶凝材料（碱-偏高岭土、碱-矿渣和碱-粉煤灰）与水-水泥体系固化Ph^2＋进行了试验研究,其中水-水泥体系为对比样。结果表明：对于相同稠度的碱激发胶凝材料,即使Pb^2＋含量达到2．4％,除了碱-粉煤灰的抗压强度略低外,其他都达到30MPa以上,满足填埋或做建筑基材的使用要求;与水泥相比,碱激发胶凝材料能显著降低重金属离子（Ph^2＋）浸出浓度,其规律性与其NH4交换容量大小的规律性一致,与其固化体的抗压强度的大小没有相关性。     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

降解丙烯酰胺的活性污泥培养及驯化研究

采用阶梯式驯化法,控制温度在18℃～24℃,pH在6—8,溶解氧在4—8mg／L,在容积为6L的驯化器中对活性污泥进行培养驯化。经过25d的培养之后,得到了稳定降解丙烯酰胺的活性污泥。驯化后的活性污泥SVI为85—132,COD去除率达70％。     

A soil sampling intercomparison exercise for the ALMERA network

Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a “reference site”, aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.     

Assessment of present and future risk to Italian forests and human health: Modelling and mapping

A review of ozone pollution in Italy shows levels largely above the thresholds established by EU regulation for vegetation and human health protection. The Italian air quality monitoring network appears quantitatively inadequate to cover all the territorial surface, because of scarcity and unequal distribution of monitoring sites. By applying the integrated assessment model RAINS-Italy to the year 2000, the whole of Italy exceeds the AOT40 critical level for forest, while Northern and central areas show strong potential of O₃ impact on human health with ∼11% of territory >10 O₃-induced premature deaths. Two scenarios for the year 2020, the Current Legislation and the Maximum Technical Feasible Reduction, show a reduction of AOT40Forest by 29% and 44%, SOMO35 by 31% and 47%, and O₃-induced premature deaths by 32% and 48%, compared to 2000. RAINS-Italy can be used to improve the map quality and cover areas not reached by the national monitoring network.     

River channel network design for drought and flood control: A case study of Xiaoqinghe River basin, Jinan City, China

Vulnerability of river channels to urbanization has been lessened by the extensive construction of artificial water control improvements. The challenge, however, is that traditional engineering practices on isolated parts of a river may disturb the hydrologic continuity and interrupt the natural state of ecosystems. Taking the Xiaoqinghe River basin as a whole, we developed a river channel network design to mitigate river risks while sustaining the river in a state as natural as possible. The river channel risk from drought during low-flow periods and flood during high-flow periods as well as the potential for water diversion were articulated in detail. On the basis of the above investigation, a network with “nodes” and “edges” could be designed to relieve drought hazard and flood risk respectively. Subsequently, the shortest path algorithm in the graph theory was applied to optimize the low-flow network by searching for the shortest path. The effectiveness assessment was then performed for the low-flow and high-flow networks, respectively. For the former, the network connectedness was evaluated by calculating the “gamma index of connectivity” and “alpha index of circuitry”; for the latter, the ratio of flood-control capacity to projected flood level was devised and calculated. Results show that the design boosted network connectivity and circuitry during the low-flow periods, indicating a more fluent flow pathway, and reduced the flood risk during the high-flow periods.     

六自由度气锤振动技术与电磁斜面振动技术比较

六自由度气锤振动与电磁斜面振动是两种模拟产品三轴振动的振动技术。由于两种振动技术的机理不同,其对样品的振动影响也会有区别。本文研究讨论两种不同振动技术的不同特点,以及对不同产品的振动效果别,我们可以根据样品特点和测试需求,选择更合适的震动技术。     

OHS风险控制方法在烟气排放控制工程中的应用

介绍了烟气排放控制工程中OHS风险控制的方法,并以香港青山“B”电厂4X680MW机组排放控制工程（CPBEC）为例,阐述了目前国内外环保项目在OHS风险管理方面的差距和改进措施。     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。