Optimized determination of airborne tetracycline resistance genes in laboratory atmosphere

• Sampling parameters with high efficiency was determined. • Operational process to detect airborne ARGs was optimized. • Providing research basis to control airborne ARGs of a laboratory atmosphere Antibiotic resistance genes (ARGs) have been detected in various atmospheric environments. Airborne ARGs transmission presents the public health threat. However, it is very difficult to quantify airborne ARGs because of the limited availability of collectable airborne particulate matter and the low biological content of samples. In this study, an optimized protocol for collecting and detecting airborne ARGs was presented. Experimental results showed that recovery efficiency tended to increase initially and then declined over time, and a range of 550–780 copies/mm² of capture loading was recommended to ensure that the recovery efficiency is greater than 75%. As the cell walls were mechanically disrupted and nucleic acids were released, the buffer wash protects ARGs dissolution. Three ratios of buffer volume to membrane area in buffer wash were compared. The highest concentrations of airborne ARGs were detected with 1.4 µL/mm² buffer wash. Furthermore, the majority of the cells were disrupted by an ultrasonication pretreatment (5 min), allowing the efficiency ARGs detection of airborne samples. While, extending the ultrasonication can disrupt cell structures and gene sequence was broken down into fragments. Therefore, this study could provide a theoretical basis for the efficient filter collection of airborne ARGs in different environments. An optimized sampling method was proposed that the buffer wash was 1.4 µL/mm² and the ultrasonication duration was 5 min. The indoor airborne ARGs were examined in accordance with the improved protocol in two laboratories. The result demonstrated that airborne ARGs in an indoor laboratory atmosphere could pose the considerable health risk to inhabitants and we should pay attention to some complicated indoor air environment.     

Grey Box and Component Models to Forecast Ozone Episodes: A Comparison Study

For the purpose of short-term forecasting of high ozone concentration episodes stochastic models have been suggested and developed in the literature. The present paper compares the quality of forecasts produced by a grey box and a component time-series model. The summer ozone patterns for three European urban areas (two continental and one mediterranean) are processed. By means of forecast performance indices according to EC and WHO guidelines, the following features of the models could be found: The grey box model is highly adaptive and produces forecasts with low error variance that increases with the time horizon of forecast. The component model is more 'stiff' that results in a higher forecast-error variance and poorer adaption in detail. The forecast horizon, however, could be enlarged with this model. The accuracy of predicting threshold exceedance is similar for both models. This can be understood from the assumption of a cyclical time development of ozone that was made for both models.     

A History of Dry Cleaners and Sources of Solvent Releases from Dry Cleaning Equipment

Approximately 25, 000-35, 000 dry cleaning facilities currently operate in the U.S. The release of perchloroethylene and other solvents from these establishments represents a major source of soil and groundwater contamination. The manner in which dry cleaning solvents escape from dry cleaning plants is, for all practical purposes, identical for chlorinated and petroleum hydrocarbon solvents and is related to one of the following events: the catastrophic failure of a component of the dry cleaning system, the improper installation, operation or maintenance of the dry cleaning equipment or a combination of all of these causes. Acceptable customs, codes and regulations can also dictate what is authorized for operation of a dry cleaning facility in a particular community, geographic area during a particular time frame. Environmental litigation dealing with the origin of a solvent release from dry cleaners tends to focus on the design and manufacture of dry cleaning industry machines such as washers, washer extractors, tumblers, solvent filters, water separators, stills and spotting boards. A thorough analysis of the daily operations of dry cleaners often reveals that poor maintenance, failure to follow the manufacturer's instructions and the actions of the operator are the most likely causes of soil and groundwater pollution. In order to forensically evaluate the most probable origins of a solvent release and to examine issues regarding liability, a thorough understanding of the history of dry cleaning and a detailed analysis of the operation and maintenance of the dry cleaning equipment are necessary. The discovery of solvent plumes in the vicinity of dry cleaning plants may suggest that the solvent source is the dry cleaning plant; however, the presence of these plumes does not necessarily indicate that the dry cleaning equipment was defectively designed or manufactured. A thorough review of the type of equipment used over the life of the dry cleaning plant and verifiable solvent mileage records frequently indicates that operators of the plant have disposed of solvent and contaminated solids into the municipal sewer or on ground surfaces.     

A two-stage ensemble Kalman filter for smooth data assimilation

The ensemble Kalman Filter (EnKF) applied to a simple fire propagation model by a nonlinear convection-diffusion-reaction partial differential equation breaks down because the EnKF creates nonphysical ensemble members with large gradients. A modification of the EnKF is proposed by adding a regularization term that penalizes large gradients. The method is implemented by applying the EnKF formulas twice, with the regularization term as another observation. The regularization step is also interpreted as a shrinkage of the prior distribution. Numerical results are given to illustrate success of the new method.     

基于U-D分解卡尔曼滤波地下水污染源溯源辨识

采用基于U-D分解的卡尔曼滤波与非线性规划优化模型相结合,溯源辨识出地下水污染源的个数、位置与释放强度.基于一个假想例子,建立地下水污染质数值模拟模型,运用灵敏度分析筛选出对模型影响较大的参数作为模型中的随机变量.然后,应用基于U-D分解的卡尔曼滤波辨识出污染源的个数与位置.在此基础上建立辨识污染源释放强度的优化模型,应用克里格插值法建立地下水污染质运移数值模拟模型的替代模型,代替模拟模型,作为约束条件嵌入优化模型中,运用遗传算法求解优化模型辨识出地下水污染源源强.结果表明：采用基于U-D分解的卡尔曼滤波方法能够保证滤波的稳定性,有效识别出污染源的个数和位置;非线性规划优化模型,可以辨识出污染源释放强度.在优化模型的求解过程中,应用克里格方法建立模拟模型的替代模型嵌入优化模型,能在保证一定精度的情况下,大幅度减少计算负荷和计算时间.     

Costs and benefits of packaging waste recycling systems

This Special Issue provides several different perspectives on the complex issue of packaging waste recycling. It comprises a diverse and rich set of contributions with insights from very different disciplines that range from economics to engineering. All types of “costs and benefits” are addressed in this collection of articles. In addition to the economic and strictly financial impacts of selective collection and sorting of packaging waste, several authors discuss other types of impacts, such as the environmental and social ones. The reader will find articles that address recycling systems as a whole, pieces that focus on specific impacts and detailed discussions of particular material streams or waste management strategies. The Special Issue represents an indispensable resource for academics, policy-makers and practitioners with interests in recycling and packaging waste management.     

基于变参数模型的北京碳排放影响因素研究

基于STIRPAT模型,建立了北京碳排放与经济发展水平、能源消耗强度、产业结构和能源消费结构间的变参数模型,得出以下结论：①经济发展水平、能源利用效率和能源消费结构与人均碳排放正相关;产业结构大多数年份与人均碳排放负相关.②经济发展水平对人均碳排放的变弹性系数最大,依次是能源消费结构、能源利用效率和产业结构.③经济发展水平、能源利用效率和产业结构的变弹性系数呈现先升后降再升的趋势,只是上升和下降转折点有差异,能源消费结构变弹性系数波动较大.     

Recursive residuals and model diagnostics for normal and non-normal state space models

Model diagnostics for normal and non-normal state space models are based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various diagnostic tools are suggested to check, for example, for wrong observation distributions and for autocorrelation. The paper also discusses such topics as model diagnostics for discrete time series and model discrimination via Bayes factors. The case studies cover environmental applications such as analysing a time series of the number of daily rainfall occurrences and a time series of daily sulfur dioxide emissions.     

曝气生物滤池处理生活污水的试验研究

对升流式二级曝气生物滤池去除COD和NHs—N的效果进行了试验研究,并在各个阶段对比中找出最优的运行工况,从而达到节约能源,降低运行成本的目的。通过试验对水力负荷、有机负荷、气水比等参数的变化对去除COD和NH3-N效果的影响。研究结果表明,在进水水力负荷为1～4m3／m^2·h、有机负荷为4-13kgCOD／ms·d及气水比1：1～3：1的工艺条件下,COD和NH3-N的出水水质均能满足杂用水需要。     

填料对新型曝气生物滤池污水处理效能试验研究

采用新型酶促厌氧填料、半软性填料、酶促好氧填料和PYC挂膜陶粒填料对两段错向流曝气生物滤池反应器进行污水处理试验研究,分析了4种填料对反应器污水处理效能的贡献并为反应器填料的选择提供科学依据.结果表明,以半软性填料和酶促好氧填料为组合填料的两段错向流曝气生物滤池反应器污水处理效能均优于其它填料.