A dynamic food-chain model and program for predicting the consequences of nuclear accident

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噪声环境质量评价方法探讨

根据国家环保局１９９３年公布的《区域环境噪声标准》（ＧＢ３０９６－９３），采用评分模式评价方法，对泰安市各功能区噪声环境进行评价，通过标准值与各功能区实测特征值相比较，确立该功能区噪声环境质量类别。     

IUCN保护区分类系统与中国自然保护区分类标准的比较

通过对世界自然保护联盟(IUCN)和我国分类系统的比较,提出应该根据我国生物多样性、自然及其相关文化资源保护和维持的现状及特点,参照IUCN保护区分类系统,尽快制定出我国新的保护区分类系统。新分类系统应该以保护区主要管理目标为基本依据,同时综合考虑保护对象的特点及人类干扰程度来确定保护区类型,从而促进保护区的规范管理和进一步发展,实现自然保护与可持续发展的双重目标。     

利用程控小总机进行安全防护

介绍了一种利用振铃起动电路与小型程控交换机结合，组成子站自动监测系统辅助装置的实用技术，以解决大气自动监测子站微机死机、受干扰后无法自动恢复正常工作和雷击问题。     

A combination line transect and capture-recapture sampling model for multiple observers in aerial surveys

We present a robust sampling methodology to estimate population size using line transect and capture-recapture procedures for aerial surveys. Aerial surveys usually underestimate population density due to animals being missed. A combination of capture-recapture and line transect sampling methods with multiple observers allows violation of the assumption that all animals on the centreline are sighted from the air. We illustrate our method with an example of inanimate objects which shows evidence of failure of the assumption that all objects on the centreline have probability 1 of being detected. A simulation study is implemented to evaluate the performance of three variations of the Lincoln-Petersen estimator: the overall estimator, the stratified estimator, and the general stratified estimator based on the combined likelihood proposed in this paper. The stratified Lincoln-Petersen estimator based on the combined likelihood is found to be generally superior to the other estimators.     

农村环境质量区划的多元分析

本文提出了适合于农村环境质量区划的分区方法，即首先以主成分分析法分析农村环境质量问题，然后以多种聚类分析法取得一个初始分区系统，最后用判别分析法判别该初始分区系统中各区域单元的类型归属是否正确，对一些类型归属不恰当的作适当调整，最终得到农村环境质量分区系统。文章最后讨论了类型划分问题。     

江苏省重要生态功能保护区的分类及建立方法

阐述了重要生态功能保护区的概念,根据江苏省的自然环境特征,论述了江苏省重要生态功能保护区的建立方法及其分类,并提出了重要生态功能保护区的保护和管理措施.     

在用车推行I/M制度的检测方法的成本效益分析

从检测性能和成本效益两方面对几种检测方法进行分析比较，并结合国内外I/M制度的实施情况和上海市的特点，建议上海市实施I/M制度时，初期对轻型汽油车采用VMAS，后期采用IM240进行检测；对轻型柴油车可采用瞬态简易工况法和Lugdown系统。     

微生物燃料电池在污水处理中的研究进展

微生物燃料电池（microbial fuel cell，MFC）利用微生物催化剂将其代谢能直接转化为电能，具有原料广泛、反应条件温和、清洁高效等优点。简述了MFC的工作原理及分类，总结了用于污水处理的MFC的性能及其影响因素。探讨了MFC在实际应用中的瓶颈，并展望其在污水处理中的应用前景。     

Evaluation of US EPA Environmental Monitoring and Assessment Program's (EMAP)-Wetlands sampling design and classification

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) will monitor the nation's resources by evaluating the status and trends of selected indicators of condition using a probability-based sampling design. The EMAP-Wetlands program will monitor the condition of the nation's wetlands. The EMAP classification system is an aggregation of the many subclasses of the US Fish and Wildlife Service's National Wetlands Inventory (NWI) classification system. This aggregation results in fewer wetland classes with more wetlands per class than the NWI system. Aggregation of the NWI classification was based primarily on dominant vegetation cover, flooding regimes, dominant water source, and adjacency to rivers and lakes. We evaluated the EMAP classification system and sampling design using NWI digital wetlands data for portions of Illinois, Washington, North Dakota, and South Dakata. Relative numbers of wetlands, total areas, average areas, and common versus rare classes were compared between the EMAP and NWI classification systems. As expected, the EMAP classification provided fewer wetland polygons, each with larger areas, without altering total wetland area. Summary statistics comparing sample estimates to true population parameters (represented by the NWI data) demonstrated the effectiveness of the EMAP sampling design with the exception of rare EMAP classes in the selected regions. Although simple random sampling is inadequate for both large and small wetlands, the EMAP sampling design is readily adapted to provide better estimates for these categories. Aggregating the NWI classification to the EMAP classification provides fewer wetland classes, with more wetlands per class, for EMAP's annual reports and statistical summaries. The research in this report has been funded by the United States Environmental Protection Agency (EPA) under contracts 68-C8-0006 to ManTech Environmental Technology, Inc. and 68-03-3532 to The Bionetics Corporation. Mention of trade names does not constitute endorsement or recommendation for use.