重点生态功能区环境污染源排放特征与空间管控模式——以藏东南为例

重点生态功能区以保持并提高生态产品供给能力为主体功能定位，区内自然环境敏感性和脆弱性突出，研究其人类活动过程中的环境污染源排放特征与空间管控模式，对科学协调保护与利用、切实加强重点生态功能区环境保护和治理水平具有重要意义.以青藏高原重要生态安全屏障区藏东南为例，基于环境污染源的固体废弃物、水体污染物和大气污染物排放强度的分类估算与空间特征解析，探讨面向污染源排放强度和多尺度管控精度的分级空间管控方案.研究结果表明：藏东南环境污染源的排放强度整体较低，雅鲁藏布江和雅尼河谷地因人类生产生活活动密度较大，其污染物排放量显著高于其他区域；在重点生态功能区应建立由7个二级类和21个三级类构成的环境污染源空间管控体系，重点管控以城镇居住区和工矿业生产空间为主的"点状"胁迫、以交通运输场所和人文游憩空间为主的"线状"胁迫、以农业种植区和畜禽养殖区为主的"面状"胁迫；针对藏东南各类环境污染源的空间耦合及交互特征，提出城乡生活集聚型、农牧业生产集聚型和休闲旅游集聚型3种典型区，依次制定"分级处理+资源利用"、"源头减排+就地消纳"、"实时动态监控+绿色设施营造+游憩利用规范"的差异化空间管控模式.     

单环芳族化合物结构与生物降解性关系的统计分析

使用量子化学方法MOPAC6．0-AMI软件计算了42种单环芳族化合物的分子最高占有轨道能(EHOMO)、分子最低空轨道能(ELUMO)、分子生成热(Hf)、分子表面积(TSA)、偶极矩(μ)和分子量(Mw)值；从ClogP软件查得分子的辛醇／水分配系数lgP。对化合物的上述7种结构参数进行因子分析，提取3个主因子可代表化合物的绝大部分结构信息。根据因子得分，对化合物进行了聚类分析。分别以各个主亚类中的化合物为对象，进行结构-生物降解性关系分析，得到系列相关方程，所研究化合物的生物降解性主要与取代基的电子效应有关。     

大气降水化学的统计学分析——以浙江省金华市为例

运用相关分析、因子分析和聚类分析等统计学方法,对2004-2005年间浙江省金华市的大气降水化学组成和分布特征进行了分析.结果表明,SO2-4,NH 4,Ca2 ,NO-3和H 是降水的主要离子,降水的pH值、电导率及离子组分均呈明显的正偏态分布,降水样品以低离子含量的样本为主.降水中水溶性离子主要分为4类,SO2-4,NH 4,NO-3,Ca2 和F-主要来自人为活动的贡献,K 和Mg2 主要来自土壤、沙尘等地壳来源,Na 和Cl-属于典型的海盐性成分,H 则反映了各种离子中和作用对降水酸度的综合影响.     

北亚热带过渡区土壤的模糊聚类分析

本文阐述了北亚热带过渡区十个土壤剖面的成土条件和基本性质，应用模糊聚类对土壤的五项诊断指标进行了分析，并与发生分类和诊断分类相比较．在中国土壤系统分类中提出建立淋溶土纲和始成土纲的基础上，探讨了供试土壤的分类地位。其中０１－０４号剖面属于典型铁质湿润淋溶上亚类；０５—０７和０９号剖面归为铁质粘磐半干润淋溶土亚类；０８号剖面为典型半干润淡色始成上亚类，１０号剖面为典型淡色滞水淋溶士亚类。     

Space-time modeling for the Missouri Turkey Hunting Survey

The Missouri Turkey Hunting Survey (MTHS) is a postseason mail survey conducted by the Missouri Department of Conservation. The 1996 MTHS provides information concerning the number of turkeys harvested by hunters on each day and the total number of trips made to the counties by these hunters on each day of the hunting season. The success rates are then found from this information. Small sample sizes produce large standard errors for the estimates at the county level. We use a Bayesian hierarchical generalized linear model to estimate daily hunting success rates at the county level. The model includes an autoregressive process for the days of the hunting season and spatially correlated random geographic effects. The computations are performed using Gibbs sampling and adaptive rejection sampling techniques. Results show that there are significant spatial corelations between counties and correlations between days of the hunting season. The estimates are close to the frequency estimates at the state level and much more stable at the county level.     

Empirical Bayes calculations of concordance between endpoints in environmental toxicity experiments

Hierarchical models are considered for estimating the probability of agreement between two outcomes or endpoints from an environmental toxicity experiment. Emphasis is placed on generalized regression models, under which the prior mean is related to a linear combination of explanatory variables via a monotone function. This function defines the scale over which the systematic effects are modelled as additive. Specific illustration is provided for the logistic link function. The hierarchical model employs a conjugate beta prior that leads to parametric empirical Bayes estimators of the individual agreement parameters. An example from environmental carcinogenesis illustrates the methods, with motivation derived from estimation of the concordance between two species carcinogenicity outcomes. Based on a large database of carcinogenicity studies, the inter-species concordance is seen to be reasonably informative, i.e. in the range 67–84%. Stratification into pertinent potency-related sub-groups via the logistic model is seen to improve concordance estimation: for environmental stimuli at the extremes of the potency spectrum, concordance can reach well above 90%.     

湖南省生态经济分区及其发展研究

生态经济分区旨在协调区域经济发展与生态环境保护及自然资源利用的关系，是宏观管理区域社会经济持续发展的一种新模式、文章根据省级生态建设与发展需要，从生态经济系统原理出发，选择了34个适合湖南省生态经济系统分类的特征指标，以行政县为分类的基本单元，采用模糊聚类分析方法对湖南省进行了不重叠、内在的聚合分类。研究结果将湖南省分为6个生态经济区和24个生态经济亚区，与实际相符。在此基础上，对各生态经济区的生态经济特点、发展方向和环境保护策略进行了具体分析，为宏观指导湖南省生态经济建设与可持续发展提供科学依据。     

Statistics: an essential technology in environmental research and management

Statistical methods as developed and used in decision making and scientific research are of recent origin. The logical foundations of statistics are still under discussion and some care is needed in applying the existing methodology and interpreting results. Some pitfalls in statistical data analysis are discussed and the importance of cross examination of data (or exploratory data analysis) before using specific statistical techniques are emphasized. Comments are made on the treatment of outliers, choice of stochastic models, use of multivariate techniques and the choice of software (expert systems) in statistical analysis. The need for developing new methodology with particular relevance to environmental research and policy is stressed.Dr Rao is Eberly Professor of Statistics and Director of the Penn State Center for Multivariate Analysis. He has received PhD and ScD degrees from Cambridge University, and has been awarded numerous honorary doctorates from universities around the world. He is a Fellow of Royal Society, UK; Fellow of Indian National Science Academy; Foreign Honorary Member of American Academy of Arts and Science; Life Fellow of King's College, Cambridge; and Founder Fellow of the Third World Academy of Sciences. He is Honorary Fellow and President of International Statistical Institute, Biometric Society and elected Fellow of the Institute of Mathematical Statistics. He has made outstanding contributions to virtually all important topics of theoretical and applied statistics, and many results bear his name. He has been Editor of Sankhya and theJournal of Multivariate Analysis, and serves on international advisory boards of several professional journals, includingEnvironmetrics and theJournal of Environmental Statistics. This paper is based on the keynote address to the Seventh Annual Conference on Statistics of the United States Environmental Protection Agency.     

生活垃圾焚烧厂周边土壤中PCDD/Fs及重金属含量

为了解城市生活垃圾焚烧发电厂周边表层土壤中二噁英、重金属来源及分布特征,选取成都地区3座典型生活垃圾焚烧厂作为研究对象,开展了周边土壤中17种多氯二苯并对二噁英/呋喃（PCDD/Fs）及11种重金属含量监测.结果显示,土壤样品中的PCDD/Fs和重金属的浓度范围分别为0.25~7.5ng I-TEQ/kg和0.23～580.57mg/kg;3座垃圾焚烧厂周边土壤中多氯二苯并呋喃（PCDFs）的毒性当量浓度贡献率要高于多氯二苯并二噁英（PCDDs）,PCDFs毒性当量浓度平均贡献率达到55%;土壤样品中Cd、Hg、Pb、Cu、Zn之间具有良好的相关性,Hg、Pb、Zn与部分PCDFs具有良好的相关性,相关系数r分别为0.792、0.760、0.788,所对应的p值分别为0.034、0.047、0.035,并被归类为同一聚类,可将这部分重金属元素作为重金属示踪剂来表征PCDFs的来源.     

我国大气降水中δ18O变化的多气象因子分析及分区研究

分析了我国29个GNIP站1961—2015年逐月降水中δ~(18)O与局地气象要素(近地面的气温、降水量和大气可降水量、外向长波辐射以及500 hPa高度的风速)和大尺度环流因子(Nino 4区海表温度距平及南方涛动指数)的关系,并基于层次聚类分析和逐步回归分析方法,讨论了我国降水中δ~(18)O的分区,计算了区内降水中δ~(18)O依各气象因子的回归方程.结果表明,秦岭-淮河一线南北两侧站点降水中δ~(18)O与气象因子之间的关系差异显著,是我国的一条重要的降水稳定同位素环境效应分界线.我国降水中δ~(18)O可以分为3个区域,即北部区(包括西北和东北地区)、中部过渡区(含华北及青藏地区)和南部区,其中北部区和中部过渡区的分界线大致与我国西北地区和北方地区的分界线吻合,中部过渡区与南部区大体与我国北方地区和南方地区的分界线相一致.不同地区控制降水中δ~(18)O的气象因子存在差异:北部区为温度,中部过渡区为温度、500 hPa高度风速以及外向长波辐射,南部区是500 hPa高度的风速.研究结果对于认识我国大气降水中稳定同位素空间分布的特征及其内在机制具有重要意义.