Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

欠发达地区农户生产效率研究——以西藏自治区为例

以西藏自治区为例,在2009年农户抽样调查数据基础上,利用数据包络法(DEA)探讨西藏不同区域农户生产效率,认为西藏农户生产效率差异与农业生产中自用价值的计算有关,若考虑自用价值,在固定生产规模报酬(CRS)假设下,平均生产效率为0.653,其中拉萨市最高(0.784),日喀则市最低(0.277);若不计入自用价值,山南与那曲地区呈现最高生产效率。表明西藏农户收入中自用价值占了较大比例,扣除自用价值,收入大幅减少,影响生产效率。因此,提高农牧户生产商品率是增加农牧民收入的有效途径。     

Quality Science in the Courtroom: U.S. EPA Data Quality and Peer Review Policies and Procedures Compared to the Daubert Factors

Protection of the environment is critically dependent on the quality of data used in decision making. Whether the decisions are part of the scientific process or relate to application of the laws governing people and their living conditions, good quality data are required/needed by two disciplines with distinct differences. This paper examines some differences between science and the law, provides a brief history of science in law, discusses the effects of law on science, compares United States Environmental Protection Agency (U.S. EPA) guidance and U.S. Supreme Court credible science criteria. This paper further speculates on the future use of science data by the courts.     

Environmental information system for visualizing environmental impact assessment information

The Institute of Environmental Engineering at the University of Pannonia has undertaken the challenge to develop an online environmental information system. This system is able to receive and process the collected environmental data via Internet. The authors have attached importance to the presentation of the data and have included other comprehensible information for laymen as well in order to work out visualisation techniques that are expressive and attract attention for environmental questions through the developed information system. The ways of visualizing physical and chemical parameters of surface water and the effects of motorway construction were examined.     

新空气质量标准实施后空气质量自动监测质保审核的建立探讨

根据上海市空气自动监测网络由市级中心站负责子站和区/县级监测站自建子站共同组成和两级管理的结构特点,上海自2006年开始实施对空气自动监测子站的年度质保审核,并在实践中持续改进和完善。以上海为例对新环境空气质量标准实施和AQI实时发布背景下完整的空气质量自动监测QA/QC体系中的质保审核的建立实施及其效果进行讨论。     

Identification of managerial shaping factors in a petrochemical plant by resilience engineering and data envelopment analysis

Resilience engineering (RE) is a novel approach that is capable of controlling and limiting incidents and accidents. This study identifies managerial shaping factors in a petrochemical plant by RE and data envelopment analysis (DEA). To do this, a standard questionnaire containing resilient factors is completed by managers of a petrochemical plant. Then, the best DEA model is selected based on average efficiency and statistical test. In addition, sensitivity analysis are performed to identify the most important shaping factors. Reporting culture, management commitment, and preparedness are identified as the most important factors in this paper, respectively. Finally, the proposed model is validated and verified through statistical experiment. The proposed approach would help managers to have a comprehensive understanding of the plant with respect to the RE. To the best of our knowledge this is the first paper that examines resilient shaping factors in a petrochemical plant with respect to management and organization by DEA.     

A new methodology for the synthesis of an optimum flexible water networks

This paper presents a new optimization model for the synthesis of direct reuse/recycle water networks with data uncertainties. In this case, data uncertainties were originated from the varying parameters of the water sources and sinks, which fluctuate within a given range of values. The aim of the method is to design an optimum flexible water network (FWN) that ensures minimum fresh water consumption and yet fulfilling all process constraints and uncertain parameters. The resulting FWN also features the minimum number of pipelines, which will ease process operation and control. Due to the complexity of the problem, multistep solving method based on theorem of corner points has been developed. The FWN obtained using the proposed method also includes information on the maximum flow rate in the pipelines, which is essential for detailed network design stage. The resulting model is a mixed integer linear problem (MILP), which may be solved to obtain global optimum solution. Two case studies were used to elucidate the newly proposed method.     

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling (RSM) methodology and serves as a visualization and analysis tool (VAT) for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S. demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias < 2% and assisting in air quality policy making in near real time.     

Atmospheric sulfur hexafluoride in-situ measurements at the Shangdianzi regional background station in China

We present in-situ measurements of atmospheric sulfur hexafluoride（SF6） conducted by an automated gas chromatograph–electron capture detector system and a gas chromatography/mass spectrometry system at a regional background site, Shangdianzi,in China, from June 2009 to May 2011, using the System for Observation of Greenhouse gases in Europe and Asia and Advanced Global Atmospheric Gases Experiment（AGAGE）techniques. The mean background and polluted mixing ratios for SF6 during the study period were 7.22 × 10-12（mol/mol, hereinafter） and 8.66 × 10-12, respectively. The averaged SF6 background mixing ratios at Shangdianzi were consistent with those obtained at other AGAGE stations located at similar latitudes（Trinidad Head and Mace Head）, but larger than AGAGE stations in the Southern Hemisphere（Cape Grim and Cape Matatula）. SF6 background mixing ratios increased rapidly during our study period, with a positive growth rate at 0.30 × 10-12year-1. The peak to peak amplitude of the seasonal cycle for SF6 background conditions was 0.07 × 10-12, while the seasonal fluctuation of polluted conditions was 2.16 × 10-12. During the study period, peak values of SF6 mixing ratios occurred in autumn when local surface horizontal winds originated from W/WSW/SW/SWS/S sectors, while lower levels of SF6 mixing ratios appeared as winds originated from N/NNE/NE/ENE/E sectors.     

浅议建立清洁生产审核内审员制度

阐述了建立内审员制度的必要性与意义.探讨了内审员的工作职能和管理与培训方法,为建立内审员制度提供了参考模式.