A Simulation Study to Assess the Sensitivity of a Forest Health Monitoring Network to Outbreaks of Defoliating Insects

The sensitivity of the United States Forest Health Monitoring network to outbreaks of defoliating insects was examined by means of a simulation study. A model constructed specifically for the study was used to generate a wide variety of defoliation patterns in forested landscapes. Forest configuration was that of Minnesota, USA, as expressed by the GAP land cover classification. Combinations of model parameters were based on a Latin Hypercube sample. The relationship between the average number of plots defoliated and outbreak characteristics was then examined via multiple regression. Both theoretical and model results pointed to a strong, linear relationship between the average number of plots defoliated and outbreak size. Model results provided additional insight, suggesting a significant relationship between the average number of plots defoliated and other outbreak characteristics after outbreak size was taken into account.     

Targeted Sustainable Development: 15 Years of Government and Community Intervention on the St. Lawrence River

From 1988 to 2003, the St. Lawrence Action Plan, a Canada – Quebec cooperation agreement on the St. Lawrence River, helped to mobilize a still-growing number of stakeholders in the conservation and protection of this great river and generated tangible results in a number of areas of intervention. The successes enjoyed in the area of industrial, agricultural and urban clean-up, in protecting plant and animal species and their habitats, and in acquiring new knowledge on the state and trends of the ecosystem reflect the sustained efforts of government and non-government partners over the course of those 15 years. The committed involvement of local communities provides assurance of the sustainable development of this vast ecosystem.The Canadian Crown reserves the right to retain a non-exclusive, royalty free licence in and to any copyright.     

供水管网震后流量监测点的动态分级优化布局研究

为了提高管网地震监测点布局的准确性和合理性,基于管网微观水力计算模型和动态分级法,提出供水管网震后流量监测点的动态分级优化布局模型。首先,利用管网微观水力计算模型计算管段流量的影响系数,构建管段的影响系数矩阵,并利用信息熵确定管段权重;其次,标准化处理影响系数矩阵,通过聚类迭代提出供水管网地震流量监测点优化布局的动态分级方法,对供水管网震后流量监测点进行优化布置分级评定;最后,根据工程实例进行方法实践,结果表明:供水管网中的管线分类较为科学合理,地震监测点在供水管网上分布也比较均匀,而且该模型在一定程度上消除了人为因素的影响,保障了震时管网的监控效果和日常建设的合理性。     

基于ACF-AMDF的气井环空液面回波特征提取方法

为了精确有效地提取声波法检测气井环空液位的回波周期,在分析环空中测试波的传播特征及基音周期检测的基础上,提出1种基于检测信号短时自相关函数(ACF)及平均幅度差函数(AMDF)的液面回波周期提取方法;利用自主搭建的室内模拟实验系统开展了不同初始环空压力下环空液位检测实验;对检测信号进行中心削波处理并计算ACF/AMDF,提取出液面回波周期并与理论计算值对比分析;同时分析了现场环空液位检测信号,提取其回波周期。研究结果表明:提出的新方法能有效地用于提取环空液面回波周期;室内实验中,该方法最大误差绝对值为1.54%;该方法能够有效抑制液面回波信号中的随机噪声及接箍反射波等,处理后的信号曲线在回波周期处峰值更加突出、集中,而在其他位置更加平滑,提高了对液面回波周期特征的辨识能力。     

基于平衡计分卡的大气环境监测数据共享网站绩效评估研究

基于平衡计分卡原理,结合网站特点,建立了大气环境监测数据共享网站绩效评估模型。以共享网站的战略愿景为模型框架的中心,以财务、顾客、内部程序、学习与成长等4个基本维度为一级指标,构建了绩效评估指标体系,并采用层次分析法确定了各指标的权重。利用该模型对长三角区域空气质量预测预报系统和宁波市空气质量预报预警平台的大气数据共享模块进行实证研究,绩效评估结果均为良好。     

《环境监测 分析方法标准制修订技术导则》(HJ 168—2010)对土壤环境监测标准制修订适用性探讨

针对土壤环境监测的复杂性和特殊性,从空白试验、检出限、方法验证、质量控制和标准文本等方面,指出了《环境监测分析方法标准制修订技术导则》《HJ 168—2010》对土壤环境监测标准制修订工作的适用性和执行中存在的问题。提出,为保证土壤标准制修订质量和标准执行质量,应研究适宜土壤监测方法标准的质量控制指标体系和评价体系,及时修订《HJ 168—2010》或发布补充要求;对现有土壤监测方法标准进行技术评估,加强对于土壤标准制修订工作的指导和监管。     

新形势下环境质量综合分析思路探讨

随着中国共产党第十九次全国代表大会的顺利召开,环保"大部制"改革、环境监测垂直管理制度改革以及国家"大气十条""水十条""土十条"的全面实施均对生态环境保护、环境监测乃至环境质量综合分析工作提出了新要求。新形势下,环境质量综合分析应与时俱进、开拓创新,进一步优化工作机制,加强系统分析,增强综合分析报告的科学性、规范性、时效性、精准性、客观性等,强化技术与能力支撑,更好发挥环境监测对环境管理和决策的引领作用。     

浅谈县级环境监测质量管理工作现状及对策

当前环保系统垂直改革稳步推进,县级环境监测质量管理工作也迎来新的机遇与挑战。从县级环境监测站质量管理工作现状着手,分析新形势下存在质量管理体系有效性缺乏、现场监测过程质量管理薄弱、质量管理意识尚待提高等问题。提出,应从加强体系建设、提高现场监测水平、强化考核培训力度等方面改进县级环境监测质量管理工作水平。     

Radium geochemistry in Na-Cl type groundwater in Niigata Prefecture, Japan

Radium isotopes in 23 Na-Cl type groundwater sampled mainly from deep wells in Niigata Prefecture, which is the site of the largest oil- and gas-fields in Japan, were measured along with U isotopes, chemical components and hydrogen and oxygen isotope ratios to elucidate the distribution and behavior of Ra in a brackish environment underground. Also analyzed were U and Th isotopes in 38 rock samples collected from outcrops at 17 locations. Ra-226 concentrations (8.86-1637 mBq kg⁻¹) of groundwater samples roughly correlated with total dissolved solid (TDS) concentrations and other alkaline earth contents. Their ²²⁸Ra/²²⁶Ra activity ratios (0.32-5.2) were similar to or higher than the ²³²Th/²³⁸U activity ratios (0.6-1.7) in the rocks. The most likely transport mechanism of Ra isotopes into groundwater was due to their α-recoil from the solid phase, probably from the water-rock interface where Th isotopes had accumulated, and adsorption/desorption reaction based on the increase in ²²⁶Ra contents with TDS.     

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of ^131mXe, ¹³³Xe, ^133mXe, and ¹³⁵Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naïve Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.