Asymptotics in adaptive cluster sampling

In this article we consider asymptotic properties of the Horvitz-Thompson and Hansen-Hurwitz types of estimators under the adaptive cluster sampling variants obtained by selecting the initial sample by simple random sampling without replacement and by unequal probability sampling with replacement. We develop an asymptotic framework, which basically assumes that the number of units in the initial sample, as well as the number of units and networks in the population tend to infinity, but that the network sizes are bounded. Using this framework we prove that under each of the two variants of adaptive sampling above mentioned, both the Horvitz-Thompson and Hansen-Hurwitz types of estimators are design-consistent and asymptotically normally distributed. In addition we show that the ordinary estimators of their variances are also design-consistent estimators.     

Estimating the Effect of Protected Lands on the Development and Conservation of Their Surroundings

Abstract:  The fate of private lands is widely seen as key to the fate of biodiversity in much of the world. Organizations that work to protect biodiversity on private lands often hope that conservation actions on one piece of land will leverage the actions of surrounding landowners. Few researchers have, however, examined whether protected lands do in fact encourage land conservation nearby or how protected lands affect development in the surrounding landscape. Using spatiotemporal data sets on land cover and land protection for three sites (western North Carolina, central Massachusetts, and central Arizona), we examined whether the existence of a protected area correlates with an increased rate of nearby land conservation or a decreased rate of nearby land development. At all sites, newly protected conservation areas tended to cluster close to preexisting protected areas. This may imply that the geography of contemporary conservation actions is influenced by past decisions on land protection, often made for reasons far removed from concerns about biodiversity. On the other hand, we found no evidence that proximity to protected areas correlates with a reduced rate of nearby land development. Indeed, on two of our three sites the development rate was significantly greater in regions with more protected land. This suggests that each conservation action should be justified and valued largely for what is protected on the targeted land, without much hope of broader conservation leverage effects.     

全氟辛烷磺酰基化合物水生生态风险和人体健康风险评价

全氟辛烷磺酰基化合物（Perfluorooctanesulfonate,PFOS ）广泛用于工农业生产,PFOS可通过不同的迁移路径迁移到大气、水和土壤等环境介质中。研究表明,PFOS是一种新的持久性有机物污染物,具有毒性,可通过食物链富集。2006年PFOS被欧盟议会和部长理事会列为限制销售和使用物质。本文引用中国沿海、亚洲海域和美国部分水域的PFOS暴露浓度数据,采用商值法对PFOS的水生生态环境风险进行了评价,建立了5 种因素水平的数学模型,并应用此数学模型对PFOS的人体健康风险进行了评价。结果表明我国部分地区和亚洲沿海PFOS的水生生态风险低于美国水域,亚洲沿海、我国部分地区以及美国部分城市水体中PFOS个人风险大小依次是我国部分地区<亚洲沿海<美国部分城市。     

人工快渗的强化预处理研究

通过室内实验并结合实际工程研究了一种新型组合式人工快渗系统处理氨氮负荷较高的污水。结果表明,简易曝气装置有效降低了人工快渗池的污染物负荷,保障了整个系统的出水水质。实际工程中,经过简易曝气池的预处理,人工快渗池的水力负荷可达2.5 m/d,降低了人工快渗系统的占地面积,出水COD、氨氮、总氮等指标达到了《城镇污水处理厂污染物排放标准》(GB/T18918-2002)一级A排放标准。     

水环境模拟中变异函数的稳健性分析

文章将稳健统计学（RS）引入地质统计学（GS）,对廊坊市地下水现场采样数据中Cl^-运用影响系数法和估计邻域法识别并处理特异值,取得了较好的稳健效果。在此基础上,用Cressie-Hawkins法、中位调节法两种稳健统计学方法系统的对进行特异值处理前后的数据作了处理和分析。结果表明,变量Cl^-离子经ICM法处理特异值后再进行稳健计算方法中以MA法有较大的优势,而且获得稳健变异函数γR（h）及其估计量对于改善变异函数的结构性和理论模型的主要参数有明显效果。因此,稳健地质统计学的方法可以移植到水环境科学中应用,这对加强水环境空间变异性以及稳健变异函数的基础研究有着重要的应用价值和学术价值。     

PREDICTION OF MEAN ANNUAL FLOWS IN NORTH AND CENTRAL FLORIDA1

ABSTRACT: A frequency analysis approach for the prediction of flow characteristics at ungaged locations is applied to a region of high annual precipitation and low topography in north and central Florida. Stationary time series of annual flows are fitted with the lognormal distribution and estimated parameters of the distribution are fitted by third order trend surfaces. These explain 65 and 74 percent of the observed variances in the mean and standard deviation, respectively. Predictions of parameters are then made for several locations previously unused in the study and they are used to estimate the return periods of various flows from the lognormal distribution. Application of the Kolmogorov-Smirnov goodness-of-fit test suggests that only one of the five test stations can be considered significantly different from the observed data, confirming the applicability of this technique.     

Adjusted two-stage adaptive cluster sampling

An adjusted two-stage sampling procedure is discussed for adaptive cluster sampling where some networks are large and others are small. A two-stage sample is drawn from the large networks and a single-stage sample is drawn from the rest. The simple random sampling (SRS) procedure without replacement is used at the initial stage. An estimator for the population mean along with its properties is discussed.     

Accounting for large-scale factors in the study of understory vegetation using a conditional logistic model

Local-scale and large-scale factors can affect the presence of a species of understory vegetation in the forest. Local-scale factors may be the influence of surrounding trees, while climate and latitude are typically considered large-scale factors. A model for the presence of a species needs to take into account both scales. A conditional logistic model is proposed for those studies where only the local-scale factors are of interest and that avoids estimating the large-scale parameters. Conditioning is carried out by the number of quadrats in the plot where the vegetation is found. As the latter is a sufficient statistic for the large-scale factors, a model free from these parameters is obtained. Data gathered in the permanent sample plots of the 1985–1986 National Forest Inventory of Finland is used for illustration, where the local-scale factor of interest is the influence of the trees, quantified by an index based on the size and location of the trees. The model fitted to Vaccinium vitis-idaea showed a significant and positive influence of Scots pine on the presence of this species, while for Calamagrostis arundinacea, a decrease in the odds ratio was observed due to the influence of Norway spruce.     

Interpolation performance of a spatio-temporal model with spatially varying coefficients: application to PM<Subscript>10</Subscript> concentrations in Rio de Janeiro

In this work we present a Bayesian analysis in linear regression models with spatially varying coefficients for modeling and inference in spatio-temporal processes. This kind of model is particularly appealing in situations where the effect of one or more explanatory processes on the response present substantial spatial heterogeneity. We describe for this model how to make inference about the regression coefficients and response processes under two scenarios: when the explanatory processes are known throughout the study region, and when they are known only at the sampling locations. Using a simulation experiment we investigate how parameter inference and interpolation performance are affected by some features of the data and prior distribution that is used. The proposed methodology is used to model the dataset on PM₁₀ levels in the metropolitan region of Rio de Janeiro presented in Paez and Gamerman (2003).     

实施简易工况法排气检测若干问题探讨

国标GB18285-2005和GB3847-2005规定在用机动车的排气检测方法选择与简易工况法标准限值的制定均由地方根据实际情况确定,虽增强了地方排气监管工作灵活性,但困难也增加了.各地在推动实施简易工况法时,检测方法的选择应重点从地方管理、地方经济、技术条件和机动车排气监督管理发展方向进行综合考虑,条件许可的地方选用简易瞬态工况法.简易工况法的初始标准限值可以先选用HJ/T 240-2005和HJ/T241-2005两个行业标准中的最松限值,然后在推进简易工况法的过程中逐步收集检测数据,并重新确定地方的排放限值.