长江口滨岸潮滩无齿相手蟹体内重金属元素的时空分布及其在环境监测中的指示作用

对长江口滨岸带无齿相手蟹体内的重金属元素分析表明:无齿相手蟹体内的Zn、Cr、Ni三种元素季节分布的总体趋势是夏季>春季>秋季。无齿相手蟹对重金属元素的累积也存在着地点间的差异。青龙港、浒浦两地的无齿相手蟹对Cu、Pb、Cr、Ni的累积量都很高,东海农场和崇明东滩的无齿相手蟹对Zn的累积量较高。对无齿相手蟹、沉积物、悬浮颗粒物中的重金属含量分析表明,无齿相手蟹对重金属Cu有一定的富集能力,适于做长江口滨岸带Cu的指示生物。     

绿色生态城区规划及实践的比较研究

目前,是以提倡低碳环保、绿色生态城市为发展规划的社会,生态化建设正如火如荼地进行中。本文以中新天津生态城、曹妃甸唐山湾生态城、青岛中德生态园这三个地点作比较,以建设绿色生态城市规划协同、共生城市理念、混合开发和生态社区结构这几点进行了分析,总结了城区建设间的问题,并针对这些问题研究解决方案,以达到绿色生态区建设的目的。     

SBR工艺中原生动物肉足虫的硝化指示作用

通过对SBR反应器曝气量的控制达到了控制硝化率的目的。对肉足虫虫体密度与硝化率相关关系分析结果表明,弯凸表壳虫、普通表壳虫,以及盖厢壳虫均可以作为硝化指示生物。与盖厢壳虫相比,弯凸表壳虫和普通表壳虫与硝化率的相关关系更高,虫体较大易于显微镜观察与计数,更适宜用作硝化指示生物。     

高危作业有害因素预防控制水平预警模型

针对职业卫生领域出现的急慢性职业病及突发性化学中毒等事件,本文采用预防控制水平指标体系,用因子分析法构建了单项有害因素的预警模型。在此基础上,利用加权平均法给出了多项有害因素的综合预警模型,其中,应用层次分析法确定各个有害因素的权重。高危作业有害因素预警模型的提出为高危作业有害因素防治提供了量化的科学依据。     

循环经济发展指标体系研究及实证评价

以“3R”原则为指导和出发点,构建了自上而下的树型指标体系(包含目标层-控制层-指标层三层指标体系)。并形成了理论指标体系和操作指标体系,分别面向推广应用的理论研究和规划管理。据此,运用灰色关联度分析方法,对南通市循环经济规划进行预评价。分析发现：随着循环经济建设的不断推进。南通市循环经济发展水平将不断提升,但是其提升与发展表现出明显的阶段性特征,具体是：2002—2007年是对传统经济发展方式的延续与改造,因而仍处于相对粗放型的经济发展状态。循环经济建设的重点是污染减量排放和资源减量化;2008—2010年是粗放经济向集约经济转轨的阶段,此阶段更加注重生态环境保护以及污染减排和治理;2011-2020年进入了循环经济发展的初级阶段,资源集约型和节约型的循环经济初具规模。     

基于AHP和DEA模型的农业生态效率评价——以无锡市为例

农业面源污染已成为我国重要环境污染源之一,但由于农业面源污染具有分散、面广、周期长、随机性等特点,在评价上存在较大难度。根据生态效率理论,结合农业生产的特点,建立了综合考虑经济效益和环境影响的农业生态效率评价指标体系,并以江苏省无锡市为例,选取该市1998~2008年农业生产和面源污染相关数据,运用偏好锥的数据包络分析模型（DEA）对其农业生态效率进行了评价分析。结果显示：1998~2008年,无锡市农业生态效率呈现先下降后上升的趋势,近三年累计上升幅度达22%。表明近年来无锡市农业面源污染治理成效显著,农业可持续发展水平显著提高。提出的农业生态效率评价体系和方法为进一步推进农业面源污染治理工作提供了依据     

Molecular tools for bathing water assessment in Europe: Balancing social science research with a rapidly developing environmental science evidence-base

The use of molecular tools, principally qPCR, versus traditional culture-based methods for quantifying microbial parameters (e.g., Fecal Indicator Organisms) in bathing waters generates considerable ongoing debate at the science–policy interface. Advances in science have allowed the development and application of molecular biological methods for rapid (~2 h) quantification of microbial pollution in bathing and recreational waters. In contrast, culture-based methods can take between 18 and 96 h for sample processing. Thus, molecular tools offer an opportunity to provide a more meaningful statement of microbial risk to water-users by providing near-real-time information enabling potentially more informed decision-making with regard to water-based activities. However, complementary studies concerning the potential costs and benefits of adopting rapid methods as a regulatory tool are in short supply. We report on findings from an international Working Group that examined the breadth of social impacts, challenges, and research opportunities associated with the application of molecular tools to bathing water regulations.     

Postfire succession in a forest of the cryolithozone: The example of central Yakutia

The results of studies on postfire succession in larch forests of the permafrost zone are discussed. The main directions of successional processes in burned-out areas of different ages are described. It has been shown that secondary pyrogenic successions in larch forests follow the scheme of rapid regeneration without tree species replacement and the model of succession tolerance. Groups of plant species with different life strategies and indicator species characterizing different stages of the overgrowing of burned-out areas have been identified.     

基于粗糙集-神经网络的矿山地质环境影响评价模型及应用

采用衡山白果地区石膏矿山的11个评价指标,综合运用粗糙集和神经网络理论,构建了基于粗糙集-神经网络(RS-ANN)的矿山地质环境影响评价模型,对RSES软件约简的数据和无约简的数据采用EasyNN-plus软件进行预测评价。神经网络模型的输入属性为8个,而粗糙集-神经网络模型的输入属性为6个,训练样本均为13个,预测样本均为4个,前者的平均预测精度为1.85%～24.86%,后者为1.23%～15.28%。研究发现,粗糙集在保留关键信息的前提下可有效地对数据表进行约简,约简后的神经网络预测结果与实际情况吻合,并比无约简时总体精度有较大幅度提高。     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.