Experimental study on the mechanism effect of seepage on microstructure of tailings

The deformation of microstructure of tailings caused by seepage is the main factor that leads the tailings dam to be damaged and lose stability. The effect of seepage on microstructure of tailings has been studied by a self-made observation testing apparatus of micro-mechanics and deformation of tailings, and its mechanism also has been explained in mechanics of particulate matter. The results show that the deformation response to microstructure of tailings is fast under load. The settlement of sample increases stepwise. Firstly, the fine particles crumble, then skeleton particles move, so as to noticeable settlement. Because the loose particles migrate taken by seepage water, the upper pores become bigger and lower pores become smaller. The relation of seepage water and settlement changing with time could be divided into two stages. In each stage, the rates of seepage and settlement reduce with time, and between the two stages, the rate of settlement increases significantly and the rate of seepage reduces with time. The seepage has significant effect on the particle size distribution of tailings in different depths, which has a little effect on the coarse tailings; the proportion of fine tailings increases significantly with the depth increasing; the minimum particle size decreases gradually and median diameter reduces stepwise with the depth increasing.     

Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines

Rockburst possibility prediction is an important activity in many underground openings design and construction as well as mining production. Due to the complex features of rockburst hazard assessment systems, such as multivariables, strong coupling and strong interference, this study employs support vector machines (SVMs) for the determination of classification of long-term rockburst for underground openings. SVMs is firmly based on the theory of statistical learning algorithms, uses classification technique by introducing radial basis function (RBF) kernel function. The inputs of models are buried depth H, rocks’ maximum tangential stress σ_θ, rocks’ uniaxial compressive strength σ_c, rocks’ uniaxial tensile strength σ_t, stress coefficient σ_θ/σ_c, rock brittleness coefficient σ_c/σ_t and elastic energy index W_et. In order to improve predictive accuracy and generalization ability, the heuristic algorithms of genetic algorithm (GA) and particle swarm optimization algorithm (PSO) are adopted to automatically determine the optimal hyper-parameters for SVMs. The performance of hybrid models (GA + SVMs = GA-SVMs) and (PSO + SVMs = PSO-SVMs) have been compared with the grid search method of support vector machines (GSM-SVMs) model and the experimental values. It also gives variance of predicted data. A rockburst dataset, which consists of 132 samples, was employed to evaluate the current method for predicting rockburst grade, and the good results of overall success rate were obtained. The results indicated that the heuristic algorithms of GA and PSO can speed up SVMs parameter optimization search, the proposed method is robust model and might hold a high potential to become a useful tool in rockburst prediction research.     

Transferral of HMs pollution from road-deposited sediments to stormwater runoff during transport processes

Ratio of turbidity and TSS (Tur/TSS) was used to characterize PSD of stormwater particles. Pb and Zn preferred to accumulate in finer RDS, while Cu, Cr and Ni in coarser RDS. HMs pollution in stormwater particles increased linearly with Tur/TSS. Dissolvability of HMs and PSD variations contribute to the differences between RDS and stormwater. Stormwater runoff, derived from the wash-off of road-deposited sediments (RDS), contains elevated heavy metal (HM) concentrations and, thus, imposes an increasing threat to urban aquatic ecosystems. In-depth understanding of the variations of HMs pollution from RDS to stormwater during transport processes facilitates the development of effective RDS and stormwater control strategies. Toward this end, the distribution of HMs (Cu, Pb, Zn, Cr, and Ni) in RDS and stormwater were investigated simultaneously. The results show a preferential accumulation of Pb and Zn in the finer (<38.5 μm) RDS, and Cu, Cr and Ni in the coarser (38.5–150 μm) RDS. For stormwater, n.d.~48.6% of HMs fractionated into the dissolved phase, and stormwater particles constitute the primary carriers of HMs. Furthermore, the accumulation of HMs in stormwater particles increased linearly with finer particle size distributions (PSD). Geoaccumulation index (I_geo) highlighted the predominant pollution of both RDS and stormwater particles by Cu, Pb and Zn. Nonetheless, Cu, Pb, and Ni mostly contributed the potential ecological risk of RDS, whereas Cu, Pb, and Zn mainly contributed that of stormwater particles. Moreover, contamination by Cu, Pb and Zn was significantly higher in stormwater particles than that in RDS. These differences are attributable to the solubility and size-dependent accumulation of HMs in RDS, as well as the PSD variations during transport processes. The study outcomes highlight the importance of very fine (nano- and submicron- scale) RDS in stormwater pollution and the necessity of control.     

Acid aerosols in the Pittsburgh Metropolitan area

This article presents data on ambient concentrations of selected acidic aerosols at four existing monitoring sites in the Pittsburgh PA metropolitan area. The data were collected by staff of the Allegheny County Health Department, Division of Air Quality during the summer and fall of 1993. The sampling protocol was focused on obtaining 24 h-average ammonia, ammonium, acidic sulfates, and particle strong acids data on a 2 to 3 day cycle. The data were obtained using Harvard University School of Public Health's “Short-HEADS” annular denuder sampling train. The Pittsburgh area is of interest because it is downwind of a major regional source of sulfur and nitrogen emissions from coal-burning power plants: the Ohio River Valley. The data presented here indicate that ground-level concentrations of acidic aerosols in Pittsburgh are highly correlated spatially and that many pollutants are higher on days when ground-level wind direction vectors indicate that wind is coming from the southwest rather than from the Pittsburgh source area itself. The monitoring site that is most upwind of the Pittsburgh source area – South Fayette – has particle strong acid levels about twice those of sites closer in to the Pittsburgh central business district.     

Bags with oven-dried moss for the active monitoring of airborne trace elements in urban areas

To define a harmonized methodology for the use of moss and lichen bags as active monitoring devices of airborne trace elements in urban areas, we evaluated the element accumulation in bags exposed in Naples in different spring weather conditions for 6- and 12-weeks. Three different pre-exposure treatments were applied to moss and lichen materials: water-washing, acid-washing and oven-drying. During the different exposure periods in the Naples urban environment the moss accumulated always higher amounts of elements (except Hg) than lichens and the element accumulation increased during wetter weather and higher PM₁₀ conditions. The oven pre-treatment did not substantially modify the morphology and element composition of moss and the exposure in bags of this material for 6-weeks was sufficient to detect the pattern of airborne trace elements.     

Requirements for estimation of doses from contaminants dispersed by a ‘dirty bomb’ explosion in an urban area

The ARGOS decision support system is currently being extended to enable estimation of the consequences of terror attacks involving chemical, biological, nuclear and radiological substances. This paper presents elements of the framework that will be applied in ARGOS to calculate the dose contributions from contaminants dispersed in the atmosphere after a ‘dirty bomb’ explosion. Conceptual methodologies are presented which describe the various dose components on the basis of knowledge of time-integrated contaminant air concentrations. Also the aerosolisation and atmospheric dispersion in a city of different types of conceivable contaminants from a ‘dirty bomb’ are discussed.     

Carrousel氧化沟单个表曝机流态的模型试验和分析比较

对仅安装1个倒伞形表面曝气机(简称表曝机)的Carrousel氧化沟模型进行了水力学测定,通过颗粒动态分析仪(PDA)系统分析流出和流入表曝机一侧的液体流动速度、沉降速度,以及固体含量分布.结果表明,流出表曝机一侧,距表曝机较近的x轴位置流速较大;沉降速度沿y轴有个转折点,位于沟壁与挡板的中间;远离单个表曝机,固体含量逐渐增大.并将单个表曝机的测量结果与氧化沟内安装2个表曝机的流动试验进行比较,发现2个表曝机所产生的流场与单个表曝机产生的流场差别较大,且2个表曝机所产生的流场更稳定.      

大气样品中阳离子的离子色谱法测定

用单往离子色谱法测定了降水、TSP、降尘中的一价和二价阳离子(水溶物),方法精密度实验的变异系数≥2.02％;改进了ZIC—ⅡA型离子色谱仪的原流路系统。     

Advances in airborne microorganisms detection using biosensors: A critical review

• Airborne microorganism detection methods are summarized. • Biosensors play an important role in detecting airborne microorganisms. • The principle of biosensor detection of airborne microorganisms is introduced. • The application and progress of biosensor in recent years is summarized. • The future perspectives of biosensor are identified. Humanity has been facing the threat of a variety of infectious diseases. Airborne microorganisms can cause airborne infectious diseases, which spread rapidly and extensively, causing huge losses to human society on a global scale. In recent years, the detection technology for airborne microorganisms has developed rapidly; it can be roughly divided into biochemical, immune, and molecular technologies. However, these technologies still have some shortcomings; they are time-consuming and have low sensitivity and poor stability. Most of them need to be used in the ideal environment of a laboratory, which limits their applications. A biosensor is a device that converts biological signals into detectable signals. As an interdisciplinary field, biosensors have successfully introduced a variety of technologies for bio-detection. Given their fast analysis speed, high sensitivity, good portability, strong specificity, and low cost, biosensors have been widely used in environmental monitoring, medical research, food and agricultural safety, military medicine and other fields. In recent years, the performance of biosensors has greatly improved, becoming a promising technology for airborne microorganism detection. This review introduces the detection principle of biosensors from the three aspects of component identification, energy conversion principle, and signal amplification. It also summarizes its research and application in airborne microorganism detection. The new progress and future development trend of the biosensor detection of airborne microorganisms are analyzed.     

沈阳市室内空气细菌与真菌粒子的关系

用ＡＮＤＥＲＳＥＮ生物粒子采样器和平皿沉降法观测了室内空气细菌和真菌粒子浓度、浓度分布、粒度分布、粒数中值直径和沉降量．结果表明，室内空气细菌粒子浓度为真菌粒子浓度的２．５倍，细菌粒数中值直径为真菌粒数中值直径的１．４倍，细菌粒子沉降量为真菌粒子沉降量的５，３倍。＜８．２μｍ的空气细菌和真菌粒子浓度差别不大，而＞８．２μｍ的空气细苗比真苗粒子浓度高４．１倍．＜８．２μｍ的可吸入真菌粒数百分比大于＜８．２μｍ的细菌粒数百分比．在一天的７：００时～２２：００时，室内空气细菌和真菌粒子的浓度、沉降量均呈双峰变化；细苗和真菌粒子浓度的相关系数为０．８２２，细菌和真菌粒子沉降量的相关系数为０．８９６，均呈明显的正相关关系；细菌和真菌粒数中值直径的相关系数为－０．０９６，相关关系不大。