废水污泥快速热分解试验研究

本文采用落下床快速效解工艺处理废水污泥,实现污泥的无害化及资源化,实验温度550—850℃,处理量约600g/h.污泥进行快速热解及通空气部分燃烧热解可得民用或工业用煤气、轻油、焦油及可直接做锅炉燃料的半焦.低温下隔绝空气热解的煤气中含较多的小分子烃类物质,可回收做化工原料.所得焦油含贵重化合物,高温下产品含量集中,可分离利用.通部分空气热解时可提供部分内热,以提高热效率,同时简化加工流程.     

南海某深水高温高压气井SS-15型井口头系统薄弱点安全评价

为应对深水高温高压气井生产过程中井口系统复杂性、井口抬升等对整个井口系统完整性的破坏情况,研究环空压力、上顶力、温度、产量对井口头系统薄弱点的影响。基于数值模拟方法建立井口系统有限元力学模型,分析在不同环空压力与上顶力条件下,井口系统各部件的应力大小变化情况,为井口系统薄弱点位置的确定提供理论依据,进而提出深水高温高压井井口系统完整性的管控图版及方法。研究结果表明：环空密封本体与套管挂、锁环与限位槽的接触部位是薄弱点;同一环空压力下,上顶力越大,套管挂等效应力与锁环变形量越大;当上顶力超过700 t时,不论环空压力是否存在,均达到井口系统薄弱点屈服强度。因此,深水高温高压油气井应制定合理生产制度或管理措施,研究结果对保障井口系统完整性,降低深水高温高压井生产阶段风险具有一定参考意义。     

超低沸点挥发性有机物测定中的要点分析

采用大气浓缩仪-气相色谱法测定超低沸点挥发性有机物乙烷、乙烯、丙烷、丙烯、乙炔,选用PLOT-Q柱分析,控制真空罐内相对湿度约50%,通过优化测定条件使方法线性良好,5种低沸点化合物的检出限为0.08 nmol/mol～0.2 nmol/mol,样品保存时间不超过10 d。用该方法测定某地区环境空气中VOCs,结果检出率均为100%。     

适用于移动平台的河流突发污染溯源算法研究

提出了一种适用于小型移动水质检测平台的一维均一地表水单点源污染物溯源新算法,即通过计算污染物在时间域和空间域的质量浓度导数来反推污染物初始排放点的位置、排放时间及污染物总量.首先,通过算例仿真研究表明,此方法具有较高的溯源精度(与理论距离偏差在10％以内).其次,结合目前移动检测的实际限制(平台长度、取样时间等),对算法中涉及的采样时间、距离等因素的选择进行分析,对移动平台的溯源操作给出了优化建议,以确保有较高的溯源精度.最后,通过实验室水槽缩尺模型试验验证了算法有较高溯源精度(最大偏差在30％以内),从而在原理上证明了该算法适用于特定流域下的移动水质污染溯源.     

MNLR and ANN structural group contribution methods for predicting the flash point temperature of pure compounds in the transportation fuels range

A QSPR method is presented for predicting the flash point temperature (FPT) of pure compounds in the transportation fuels range. A structural group contribution method is used to determine the flash point temperature using two techniques: multivariable nonlinear regression and artificial neural networks. The method was used to probe the structural groups that have significant contribution to the overall FPT of pure compounds and arrive at the set of 37 atom-type structural groups that can best represent the flash point for about 375 substances. The input parameters to the model are the number of occurrence of each of the 37 structural groups in each molecule. The neural network method was the better of the two techniques and can predict the flash point of pure compounds merely from the knowledge of the molecular structure with an overall correlation coefficient of 0.996 and overall average and maximum errors of 1.12% and 6.62%, respectively. The results are compared to the more traditional approach of the SGC method along with other methods in the literature.     

Rapid declines of large mammal populations after the collapse of the Soviet Union

Anecdotal evidence suggests that socioeconomic shocks strongly affect wildlife populations, but quantitative evidence is sparse. The collapse of socialism in Russia in 1991 caused a major socioeconomic shock, including a sharp increase in poverty. We analyzed population trends of 8 large mammals in Russia from 1981 to 2010 (i.e., before and after the collapse). We hypothesized that the collapse would first cause population declines, primarily due to overexploitation, and then population increases due to adaptation of wildlife to new environments following the collapse. The long‐term Database of the Russian Federal Agency of Game Mammal Monitoring, consisting of up to 50,000 transects that are monitored annually, provided an exceptional data set for investigating these population trends. Three species showed strong declines in population growth rates in the decade following the collapse, while grey wolf (Canis lupus) increased by more than 150%. After 2000 some trends reversed. For example, roe deer (Capreolus spp.) abundance in 2010 was the highest of any period in our study. Likely reasons for the population declines in the 1990s include poaching and the erosion of wildlife protection enforcement. The rapid increase of the grey wolf populations is likely due to the cessation of governmental population control. In general, the widespread declines in wildlife populations after the collapse of the Soviet Union highlight the magnitude of the effects that socioeconomic shocks can have on wildlife populations and the possible need for special conservation efforts during such times. Declinación Rápida de las Poblaciones de Mamíferos Mayores después del Colapso de la Unión Soviética     

Flash points measurements and prediction for binary miscible mixtures

Flash point is one of the most important parameters used to characterize the potential fire and explosion hazards for flammable liquids. In this study, flash points of twenty eight binary miscible mixtures comprised eighteen flammable pure components with different compositions were measured by using the closed cup apparatus. The obtained experimental data are further employed to develop simple and accurate models for predicting the flash points of binary miscible mixtures. Based on the vapor–liquid equilibrium theory, the normal boiling point, the standard enthalpy of vaporization, the average number of carbon atoms, and the stoichiometric concentration of the gas phase were selected as the dominant physicochemical parameters that were relevant to the overall flash point property of liquids. With these parameters for pure components as well as the compositions of mixtures, the new form of characteristic physicochemical parameters for mixtures were developed and used as the input parameters for the flash point prediction of mixtures. Both the modeling methods of multiple linear regression (MLR) and multiple nonlinear regression (MNR) were employed to model the possible quantitative relationships between the parameters for mixtures and the flash points of binary miscible mixtures. The resulted models showed satisfactory prediction ability, with the average absolute error for the external test set being 2.506 K for the MLR model and 2.537 K for the MNR model, respectively, both of which were within the range of the experimental error of FP measurements. Model validation was also performed to check the stability and predictivity of the presented models, and the results showed that both models were valid and predictive. The models were further compared to other previously published models. The results indicated the superiority of the presented models and revealed which can be effectively used to predict the FP of binary miscible mixtures, requiring only some common physicochemical parameters for the pure components other than any experimental flash point or flammability limit data as well as the use of the Le Chatelier law. This study can provide a simple, yet accurate way for engineering to predict the flash points of binary miscible mixtures as applied in the assessment of fire and explosion hazards and the development of inherently safer designs for chemical processes.     

北京山区典型流域不同海拔椴树种群的空间点格局分析

采用点格局分析法对不同海拔的椴树（Tilia miqueliana Maxim.）种群进行分布格局及其种间关系进行了研究。结果表明：整体上群落内以中龄树个体数为最多,小树次之,成年树个体最少。随着海拔的增加可以看出：小树（d≤5 cm）随着海拔的增加而减少,中树（5 cm20 cm）的规律不明显;椴树种群的空间分布格局与空间尺度（25 m内）有密切关系,在较小的空间尺度上倾向于非随机分布,具有明显的空间相关性;在〉15 m或25m的某临界尺度时却倾向于随机分布,同时空间关联变得微弱。随着海拔的增加,各物种聚集分布的尺度有逐渐减小的趋势。种间关系随着海拔的增加,物种间的正相关尺度有增加的趋势。     

Modeling the Potential Impact of Seasonal and Inactive Multi‐Aquifer Wells on Contaminant Movement to Public Water‐Supply Wells1

Johnson, R.L., B.R. Clark, M.K. Landon, L.J. Kauffman, and S.M. Eberts, 2011. Modeling the Potential Impact of Seasonal and Inactive Multi‐Aquifer Wells on Contaminant Movement to Public Water‐Supply Wells. Journal of the American Water Resources Association (JAWRA) 47(3):588‐596. DOI: 10.1111/j.1752‐1688.2011.00526.x Abstract: Wells screened across multiple aquifers can provide pathways for the movement of surprisingly large volumes of groundwater to confined aquifers used for public water supply (PWS). Using a simple numerical model, we examine the impact of several pumping scenarios on leakage from an unconfined aquifer to a confined aquifer and conclude that a single inactive multi‐aquifer well can contribute nearly 10% of total PWS well flow over a wide range of pumping rates. This leakage can occur even when the multi‐aquifer well is more than a kilometer from the PWS well. The contribution from multi‐aquifer wells may be greater under conditions where seasonal pumping (e.g., irrigation) creates large, widespread downward hydraulic gradients between aquifers. Under those conditions, water can continue to leak down a multi‐aquifer well from an unconfined aquifer to a confined aquifer even when those multi‐aquifer wells are actively pumped. An important implication is that, if an unconfined aquifer is contaminated, multi‐aquifer wells can increase the vulnerability of a confined‐aquifer PWS well.     

Quantifying ecological thresholds from response surfaces

Ecological thresholds are abrupt changes of ecological state. While an ecological threshold is a widely accepted concept, most empirical methods detect them in time or across geographic space. Although useful, these approaches do not quantify the direct drivers of threshold response. Causal understanding of thresholds detected empirically requires their investigation in a multi-factor domain containing the direct drivers (often referred to as state space). Here, we present an approach to quantify thresholds from response surfaces modeled empirically in state space. We present two indices of shape attributes measured from response surfaces. The response surfaces are built using a regression method in state space. The indices are threshold strength (T) and diagonality (D). We use 48 simulated response surfaces of different shapes to test the efficacy of the indices in 3D. Our results show that T is sensitive to the steepness of the transition from one state to the next, with various forms of abrupt, centralized thresholds yielding the highest values among the simulated surfaces. D represents the orientation of the response surface or the simultaneous influence of more than one predictor in eliciting the response gradient. Strongly diagonal surfaces have the most diagonal surface area demonstrated by sharply undulating diagonal surfaces. Given that the success of T and D requires a regression method to accurately capture any shape of complex data structure, we also test the accuracy of empirical regression methods known to be tractable with complex data. We test classification and regression trees (CART), Random Forest, and non-parametric multiplicative regression (NPMR) for binary and continuous responses. We use the 48 simulated response surfaces to test the methods, and we find that prediction accuracy depends on both the T and D of the simulated data for each method. We choose the most accurate method among those we test for capturing any shape of response surface from real data, NPMR. Finally, we use NPMR to build response surfaces and quantify T and D from real ecological data sets. We demonstrate how measuring threshold strength and diagonality from multi-factor response surfaces can advance ecology.