基于水质水量的城镇污水处理厂工艺运行稳定性研究

采用四川省2座位于不同排水服务区域的城镇污水处理厂的样本数据,统计分析了日处理水量,COD、TN、TP浓度及负荷和C/N、C/P等统计量的累积频率分布规律,并分析了各统计量的分布特征对工艺运行稳定性的影响。结果表明,污水处理厂A进水污染物负荷的累积频率分布范围较大,其采用的周期循环活性污泥(CASS)工艺基本能适应进水水质的随机变化,但因存在碳源随机性不足情况,可能导致其脱氮稳定性降低;污水处理厂B进水污染物负荷的累积频率分布范围较小,虽然其采用的厌氧—缺氧—好氧(A2/O)工艺的调控能力较低,但也基本能适应其服务区域内进水水质的随机变化;2座污水处理厂的日处理水量累积频率分布与污染物浓度及负荷的累积频率分布之间均存在显著的差异,日处理水量的累积频率分布比较集中,而污染物浓度及负荷的累积频率分布的离散范围较大,这也潜在威胁到工艺运行的稳定性。总体来看,2座污水处理厂的处理工艺选择恰当,均能较好适应其服务区域的进水水质和水量的要求。     

亚临界机组锅炉锅筒缺陷统计及检验建议

锅简作为亚临界机组锅炉的重要部件,及时检验发现其存在缺陷并进行控制处理是保证机组安全稳定运行的重要条件。在收集汇总了近百台300MW级别亚临界机组锅炉的检验结果的基础上,对锅简缺陷的出现比例进行了分类统计。检验人员在编制锅筒的检验方案时,参考该统计结果,可提高检验的缺陷检出率及时效性。     

概率统计在矿井通风系统可靠性评估中的应用

构建一个随机非稳定地下矿山通风系统,此通风系统有三个机组,机组的随机运行状态构成了一个完整的“系统的概率结构”。对此通风系统的运行状态进行概率统计分析,探讨了该随机系统的特征。由此推导出了通风系统故障的平均时间是一个显式的概率表达式。同时,假设系统失效时间和更换时间符合指数分布的情况下,得出计算系统故障平均时间的一个五阶多项式公式。通过验证,证明了系统故障平均时间的大小依赖于系统维修和更换的比率,而且是检验系统可靠性的重要指标,有利于提高矿山安全水平。     

2016年7-8月国内环境事件

简要统计了2016年7-8月国内发生的各种环境事件147起,包括沙尘天气2起,污染事件24起,地震41起,山体滑坡和泥石流32起,旱灾3起以及其他自然灾害45起.     

AN EMPIRICALLY‐BASED SEQUENTIAL GROUND WATER MONITORING NETWORK DESIGN PROCEDURE1

ABSTRACT: A procedure using a simple, empirically‐based model that makes efficient use of available information has been developed for designing a ground water monitoring well network. A moving plume is described by siting wells in a sequential manner, relying upon two‐dimensional concentration data obtained from previously installed wells to determine the locations of future wells. Data sets from two well known, densely monitored natural gradient tracer studies were used to test the procedure. Plumes defined by all information in the original networks were compared to those defined by reduced networks designed by the new procedure. The new procedure tracked the plumes using only a portion of that information. The new procedure could have reduced the number of wells in the original tests by about 50 percent without appreciable loss of plume information as measured by plume location and extent and by tracer mass.     

RESOLUTION OF ENDANGERED SPECIES ACT ISSUES IN PERMITTING TILE PLATEAU CREEK PIPELINE1

ABSTRACT: This paper describes how a hydrologic model proved to be a valuable tool to help interested parties understand impacts to four threatened and endangered fish species in the Upper Colorado River. In 1994, the Ute Water Conservancy District initiated permitting and design of the Plateau Creek pipeline replacement. The project was considered a major Federal action and therefore subject to the National Environmental Policy Act. Under Section 7 of the Endangered Species Act, the U.S. Fish and Wildlife Service (USFWS) entered the process to develop a Biological Opinion (BO) and determined that the project could potentially impact the endangered fish in the 15‐mile reach of the Colorado River. The Section 7 consultation was directed by a Core Committee comprised of stakeholders in the Upper Colorado River watershed. Hydrologic modeling became the evaluation tool for comparing flow reductions to USFWS target recovery flows and defining make‐up flow requirements to meet those targets. The Colorado River Recovery Implementation Program was designated to provide the make‐up flows. The USFWS released a final BO in December 1997, approving diversions through 2015. An Environmental Impact Statement for the project was completed and the Record of Decision was issued by the Bureau of Land Management in early 1998.     

基层环境统计年报中的问题及建议

环境统计工作是环境保护工作中的基础,是各级政府和环境保护行政主管部门制定环境保护政策和计划、加强环境监督管理和污染防治的重要依据。本文结合日常工作经验,就目前基层环境统计工作中存在的问题进行探讨,并提出一些建议。     

2004—2017年浙江省较大以上生产安全事故统计分析

为充分探究浙江省生产安全事故发生规律,以2004—2017年浙江省生产安全事故为研究对象,从事故发生的时间关系、区域分布、行业分布、事故类型分布等方面对全省总体、工矿商贸领域、化工领域、典型危险作业4个分类的较大以上事故特点进行了剖析研究;并从政府监管的角度,提出事故防范的措施和建议。     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.