南京市15种树木叶片对铅锌的吸收吸附能力

运用ICP仪对南京市15种主要绿化树木的叶片吸收吸附铅、锌的能力进行了研究。结果表明:15种树木叶片对铅、锌具有一定的吸收净化能力,并依污染物和树种的不同差异明显。在被研究的15个树种中,对铅吸收量较高的树种是雪松和圆柏,对锌吸收量较高的树种是杨树。对铅吸附能力强的树种是雪松,对锌吸附能力强的树种是海桐。叶片吸收和吸附铅的能力强的树种是雪松,叶片吸收和吸附锌的能力强的树种是杨树。最后,通过综合分析得出,杨树和雪松叶片中重金属铅和锌的累积量,可作为铅锌污染监测和评价的重要依据。     

含硫油品储罐自燃机理及事故原因分析

通过企业现场调研并结合若干事故案例的剖析分析了含S油品储罐自燃事故的发生原因,总结了事故的主要影响因素。在建立含S油品储罐自燃的事故树（FTA）图的基础上,通过最小割集的计算与分析,探讨了事故的主要原因及发生条件,并提出了相应的预防控制措施。     

2种茶树对铜胁迫的响应及其组织铜化学形态变化的比较研究

为了分析不同茶树对Cu胁迫的生理响应及其组织中不同化学形态Cu的累积特性,本研究采用水培法,探讨铁观音、肉桂2种茶树在不同浓度Cu胁迫下,茶树根系活力、叶绿素含量、茶树组织Cu含量及不同化学形态Cu含量的变化,以期为重金属对茶树毒害机理和茶树对重金属的自我防御研究提供理论依据。结果表明,随着Cu胁迫浓度的增加,茶树根系活力及叶片叶绿素含量呈现下降趋势,而与对照相比,铁观音下降的幅度远高于肉桂。不同茶树品种在相同浓度Cu胁迫下,其根、茎、叶组织的Cu含量差异不显著,而不同组织中则表现为根叶茎。不同化学形态Cu含量分析结果表明,随着Cu胁迫浓度的升高,2种茶树根部可交换态Cu、碳酸盐结合态Cu、有机结合态Cu含量百分比呈现下降趋势,而铁锰氧化态Cu和残留态Cu呈现上升趋势;茎部可交换态Cu、有机结合态Cu含量百分比呈现下降趋势,碳酸盐结合态Cu、铁锰氧化态Cu和残留态Cu呈现上升趋势;叶部可交换态Cu、碳酸盐结合态Cu、有机结合态Cu含量、铁锰氧化态Cu含量的百分比均呈现上升趋势,而残留态Cu呈现下降趋势。进一步分析发现,Cu胁迫下,铁观音茶树根、叶部主要以采取提高有机结合态Cu的形式来降低Cu离子毒害,而肉桂则以提高铁锰氧化态Cu形式降低Cu离子毒害,叶部则以提高铁锰氧化态Cu和残留态Cu的形式降低Cu离子毒害。可见,不同的茶树在Cu胁迫下所表现解毒模式存在着一定的差异。     

基于决策树分类的塔里木河下游沙漠化动态变化分析

运用决策树分类法对1990年,2000年,2006年3期遥感影像进行分类,寻求生态输水对塔里木河下游沙漠化进程的影响.结果表明,2000年生态输水后沙漠化速度减缓,但沙漠化进程仍在继续.沙漠化变化方向主要为非沙漠化→轻度沙漠化→中度沙漠化→重度沙漠化→极重度沙漠化,生态输水后正向变化减小,逆向变化量增加.沙漠化变化区域主要集中在绿洲边缘和河道两侧,生态输水后变化区域离绿洲边缘和河道更近.沙漠化与距河道距离密切相关,距河道越远沙漠化退化越严重;生态输水后,距离河道1 km内的沙漠化得到抑制并出现逆转.      

基于火灾风险评估的企业火灾保险费率的厘定

我国的保险公司并不单独承保企业火灾保险,而是包含在企业财产保险中。本文基于财产保险业务统计结果,应用火灾风险评估技术,结合标的的占用性质和所采取的消防措施对企业火灾保险纯费率厘定方法进行了研究,提出了基于火灾风险评估技术和标的占用性质相耦合的火灾保险费率的厘定方法。     

北京城市道路地表径流及相关介质中多环芳烃的源解析

将道路地表径流及降雨、路面积尘和行道树树冠穿透水作为整体系统,对其中多环芳烃(PAHs)的来源进行分析.选择北京市3种主要类型城市道路(主干路机动车道、主干路自行车道、支路),于2006年雨季对上述4类介质进行采样分析.结果显示,5～6月各介质中PAHs的平均浓度明显高于7～8月.应用因子分析和多元回归方法解析各介质中PAHs的来源.因子分析结果表明,径流中的PAHs更多体现路面积尘的来源特征,但在自行车道和支路,雨水和树冠水的影响也分别得到体现.多元回归结果表明,路面积尘和地表径流中PAHs的来源.在支路和主干路机动车道以机动车排放源为主,在自行车道,机动车源和燃煤源的贡献相近.雨水中的PAHs以燃煤/燃油源为主,行道树树冠水中机动车源的贡献较大.     

The effect of species response form on species distribution model prediction and inference

Ecological theory and current evidence support the validity of various species response curves according to a variety of environmental gradients. Various methods have been developed for building species distribution models but it is not well known how these methods perform under various assumptions about the form of the underlying species response. It is also not well known how spatial correlation in species occurrence affects model performance. These effects were investigated by applying an environmental envelope method (BIOCLIM) and three regression-based methods: logistic regression (LR), generalized additive modelling (GAM), and classification and regression tree (CART) to simulated species occurrence data. Each simulated species was constructed as a sum of responses with varying weights. Three basic species response curves were assumed: Gaussian (bell-shaped), Beta (skew) and linear. The two non-linear responses conform to standard ecological niche theory. All three responses were applied in turn to three simulated environmental variables, each with varying degrees of spatial autocorrelation. GAM produced the most consistent model performance over all forms of simulated species response. BIOCLIM and CART were inclined to underrate the performance of variables with a linear response. BIOCLIM was less sensitive to data density. LR was susceptible to model misspecification. The use of a linear function in LR underestimated the performance of variables with non-linear species response and contributed to increased spatial autocorrelation in model residuals. Omission of important environmental variables with non-linear species response also contributed to increased spatial autocorrelation in model residuals. Adding a spatial autocovariate term to the LR model (autologistic model) reduced the spatial autocorrelation and improved model performance, but did not correct the misidentification of the dominant environmental determinant. This is to be expected since the autologistic approach was designed primarily for prediction and not for inference. Given that various forms of species response to environmental determinants arise commonly in nature: (1) higher order functions should always be tested when applying LR in modelling species distribution; (2) spatial autocorrelation in species distribution model residuals can indicate that environmental determinants with non-linear response are missing from the model; and (3) deficiencies in LR model performance due to model misspecification can be addressed by adding a spatial autocovariate to the model, but care should be taken when interpreting the coefficients of the model parameters.     

基于故障树与贝叶斯网络的钻井井塌事故的定量分析

井塌事故在钻井过程极其常见,由于钻井液、井身结构等设计不合理,以及钻井过程的误操作均会造成井塌的发生,其后果主要是造成卡钻、卡套管等事故,严重时造成井眼毁坏。为了对井塌事故进行危险性分析,采用贝叶斯网络与故障树相结合的方法,避免传统故障树方法的局限性。首先对井塌事故的所有危险因素进行辨识建立故障树,然后将故障树转化为贝叶斯网络,建立条件概率表,运用贝叶斯网络的推理能力对井塌事故进行危险性分析。对井塌事故各基本事件概率分布的计算分析结果表明,考虑事件的多态性,综合利用故障树分析法和贝叶斯网络法能有效提高井塌事故分析的有效性,推算出井塌事故概率分布更为准确。     

基于地理信息技术的树种分布知识的挖掘与发现——以四川省石棉县为例

论文以四川省石棉县为例,对空间数据库支持下的树种分布知识的发现进行了研究。利用GIS技术建立相关空间数据库,主要有森林资源二类调查GIS数据库、树种GIS数据库,以及10 m分辨率的DEM、多年平均大于10 ℃的年积温和多年平均年降雨量等栅格数据库。利用GIS的叠加统计分析等方法,发现了各树种分布的的海拔、年平均大于10 ℃的积温、年平均降雨量等带谱知识。利用GIS的拓扑空间分析方法,挖掘了各树种间的空间配置知识。该知识可用于退耕还林、造林绿化中,因地制宜地选择树种,以及配置树种。该知识对于辅助数据协同下的各树种遥感识别也具有重要意义。此外,对其他区域也有示范意义。