An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

建设项目现状环境影响评价数据引用的探讨

对建设项目环境影响现状监测历史数据的所有权归属进行了分析,环境监测机构具有现状监测成果的所有权,委托方有使用权.应对环境现状监测数据进行知识产权保护,使监测数据得到更好利用.     

鸭绿江（丹东段）江水中未知有机污染物分析鉴定与有毒有机物名录筛选

采用美国惠普公司MC/GS联用仪,对鸭绿江（丹东段）江水中有机污染物种类、组成进行了分析鉴定,进而采用高压液相色谱法对多环芳烃类进行定量测定与评价,进行了该江段有毒有机物名录筛选,提出由27种有毒有机污染物组成的名单。     

淮南市防震减灾决策系统的建立

在机制上将一个地市(淮南市)的地震预报与防震决策融为一个动态整体,从而建立起一个实用性强的防震减灾决策系统,使城市各种防震对策的生成有了更科学的基础。成为市政府在防震减灾决策中不可缺少的工具。     

Effect of Monitoring Technique on Quality of Conservation Science

Monitoring free‐ranging animals in their natural habitat is a keystone of ecosystem conservation and increasingly important in the context of current rates of loss of biological diversity. Data collected from individuals of endangered species inform conservation policies. Conservation professionals assume that these data are reliable—that the animals from whom data are collected are representative of the species in their physiology, ecology, and behavior and of the populations from which they are drawn. In the last few decades, there has been an enthusiastic adoption of invasive techniques for gathering ecological and conservation data. Although these can provide impressive quantities of data, and apparent insights into animal ranges and distributions, there is increasing evidence that these techniques can result in animal welfare problems, through the wide‐ranging physiological effects of acute and chronic stress and through direct or indirect injuries or compromised movement. Much less commonly, however, do conservation scientists consider the issue of how these effects may alter the behavior of individuals to the extent that the data they collect could be unreliable. The emerging literature on the immediate and longer‐term effects of capture and handling indicate it can no longer be assumed that a wild animal's survival of the process implies the safety of the procedure, that the procedure is ethical, or the scientific validity of the resulting data. I argue that conservation professionals should routinely assess study populations for negative effects of their monitoring techniques and adopt noninvasive approaches for best outcomes not only for the animals, but also for conservation science. Efecto de la Técnica de Monitoreo en la Calidad de la Ciencia de la Conservación     

VBA在环境监测数据统计中的应用

VBA是Office系列软件内嵌的通用编程语言,用于定制和扩展Office的功能。将VBA应用在环境监测数据统计中,并以功能区噪声等效声级日期筛选为例,通过编制宏代码,方便快捷地实现功能区噪声数据的自动筛选。     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

Applying Statistical Causal Analyses to Agricultural Conservation: A Case Study Examining P Loss Impacts

Estimating the effect of agricultural conservation practices on reducing nutrient loss using observational data can be confounded by factors such as differing crop types and management practices. As we may not have the full knowledge of these confounding factors, conventional statistical meta‐analysis methods can be misleading. We discuss the use of two statistical causal analysis methods for quantifying the effects of water and soil conservation practices in reducing P loss from agricultural fields. With the propensity score method, a subset of data was used to form a treatment group and a control group with similar distributions of confounding factors. With the multilevel modeling method, data were stratified based on important confounding factors, and the conservation practice effect was evaluated for each stratum. Both methods resulted in similar estimates of the conservation practice effect (total P load reduction avg. ~70%). In addition, both methods show evidence of conservation practices reducing the incremental increase in total P export per unit increase in fertilizer application. These results are presented as examples of the types of outcomes provided by statistical causal analyses, not to provide definitive estimates of P loss reduction. The enhanced meta‐analysis methods presented within are applicable for improved assessment of agricultural practices and their effects and can be used for providing realistic parameter values for watershed‐scale modeling.     

大数据时代政府环境治理路径创新

本文针对政府环境治理面临政府失灵、市场失灵和社会低效三个困境,提出运用大数据方法创新治理路径。政府应用大数据提高环境治理过程中的事前、事中和事后监管效能,创新监管模式提升环境治理能力,改善政府失灵困境;依托大数据完善市场化调节机制,激励企业环境行为市场化,构建企业环境信用评价体系,改变企业环境信息披露模式,弥补市场失灵;利用大数据增进公众环境意识,建设公开、透明、平权化的环境信息交互体系,重视环境信息的舆情引导,促进环保价值理念传播,改变公众参与低效现状。进而提出完善大数据治理平台、技术和体系,构建政府、企业、公众共同参与的立体化环境治理模式,提高环境治理的精准化、精细化和智能化水平。