基于TLSER关系预测POPs在PUF与空气中的分配系数

为开发一种简洁高效预测K_PA值的方法,本文收集了包含多氯联苯（PCBs）、苯类（Benzenes）、多环芳香烃（PAHs）和杀虫剂（Pesticides）等,共95种污染物在聚氨酯泡沫塑料（PUF）与空气中分配系数（K_PA）的实验值,基于理论线性溶解能关系（TLSER）,运用逐步多元线性回归（MLR）构建了预测K_PA值的模型.结果表明,模型的决定系数R_adj²为0.901,外部验证系数Q_ext²为0.748.TLSER模型有较好的拟合度、稳健性和预测能力,可以预测应用域内POPs在PUF和空气之间的分配系数.     

有机污染物土壤吸附预测模型及其影响因素

以701种有机化合物的土壤吸附系数作为数据集,选取594种有机化合物作为训练集,剩余107种作为测试集.根据训练集化合物建立土壤吸附系数Koc与辛醇/水分配系数Kow的线性和非线性模型,应用平均残差(AE),平均绝对残差(AAE)和均方根误差(RMSE)来检验模型的预测能力,模型具有良好的预测能力.同时,比较不同类型的化合物的实测值与预测值,发现部分同系物的预测值与实测值存在系统的偏差,这些偏差主要是由吸附机理,溶解度,水解作用,挥发作用,实验误差等原因造成,这些因素均会对土壤吸附系数的预测产生影响.     

Comparison of sensitivity analysis techniques: A case study with the rice model WARM

The considerable complexity often included in biophysical models leads to the need of specifying a large number of parameters and inputs, which are available with various levels of uncertainty. Also, models may behave counter-intuitively, particularly when there are nonlinearities in multiple input-output relationships. Quantitative knowledge of the sensitivity of models to changes in their parameters is hence a prerequisite for operational use of models. This can be achieved using sensitivity analysis (SA) via methods which differ for specific characteristics, including computational resources required to perform the analysis. Running SA on biophysical models across several contexts requires flexible and computationally efficient SA approaches, which must be able to account also for possible interactions among parameters. A number of SA experiments were performed on a crop model for the simulation of rice growth (Water Accounting Rice Model, WARM) in Northern Italy. SAs were carried out using the Morris method, three regression-based methods (Latin hypercube sampling, random and Quasi-Random, LpTau), and two methods based on variance decomposition: Extended Fourier Amplitude Sensitivity Test (E-FAST) and Sobol’, with the latter adopted as benchmark. Aboveground biomass at physiological maturity was selected as reference output to facilitate the comparison of alternative SA methods. Rankings of crop parameters (from the most to the least relevant) were generated according to sensitivity experiments using different SA methods and alternate parameterizations for each method, and calculating the top-down coefficient of concordance (TDCC) as measure of agreement between rankings. With few exceptions, significant TDCC values were obtained both for different parameterizations within each method and for the comparison of each method to the Sobol’ one. The substantial stability observed in the rankings seem to indicate that, for a crop model of average complexity such as WARM, resource intensive SA methods could not be needed to identify most relevant parameters. In fact, the simplest among the SA methods used (i.e., Morris method) produced results comparable to those obtained by methods more computationally expensive.     

12种有机物在鲤鱼体内富集与释放行为的研究

本实验对第二松花江江水和鱼体中多次检出的12种化合物在鲤鱼(Cyprinus carpio L.)体内累积与释放行为进行了研究。提出了一个描述有机物在鱼体内富集行为的模式。给出了几种化合物生物富集因子(BCF)以及该因子与辛醇-水分配系数(K_(ow))之间的关系。研究结果表明,这些有机污染物在鱼体内的富集行为互不影响。含硝基化合物富集倍率低且易于释放,有机物是以一级动力学方式在鱼体内累积和释放。     

铜陵市空间管制分区与环境保护研究

借鉴国内外城市与区域空间开发与管制的研究理论,以空间开发适宜性分析为基础,通过GIS空间分析技术构建市域空间管制分区技术体系,以空间小尺度500米的地理网格为评价单元,根据其自然生态约束及经济开发需求与支撑能力的综合空间分析,确定评价单元的．．v--,_Ik和城市开发适宜程度,将铜陵市市域空间分为适宜建设区、较适宜建设区、限制建设区与禁止建设区,并就各管制区提出环境保护对策,以促进形成经济发展与人口、资源、环境相协调的空间均衡格局。     

多环芳烃在西江高要段水体中的分布与分配

为了解西江流域水体中多环芳烃(PAHs)的深度和季节分布及其在溶解相和颗粒相的分配以及控制因素,分别在洪水期(2003年8月和2004年7月)和枯水期(2003年11月和2004年3月)采集了西江高要段水柱.结果表明,溶解相和颗粒相中PAHs的浓度分别为21.7~138 ng/L和40.9~664.8μg/kg;水体中PAHs的总含量(颗粒相及溶解相),洪水期大于枯水期.在溶解相中,PAHs的浓度随深度无明显规律;而在颗粒物中,PAHs的浓度都表现出相同的变化趋势,即中层水PAHs含量最高,表层水PAHs含量最低.溶解相和颗粒相中PAHs的浓度都随悬浮颗粒物的含量增加而增加.从PAHs组成特点来看,溶解相以3环的PAHs为主,而颗粒相以3~4环的PAHs为主.PAHs在颗粒相及溶解相中的分配系数(KP)不受颗粒有机碳浓度控制(R2为0.000 1~0.2),而受颗粒物浓度、及溶解有机碳浓度的共同影响(R2为0.15~0.36),尤其是溶解态的细小碳黑有机质的影响.西江高要段水体PAHs在不同季节的lgKOC值大部分超过经典平衡分配模型的上限.除了2003年11月(R2为0.000 4~0.12,p0.001)之外,其它3个季节PAHs的lgKOC与lgKOW均有较强的相关性(R2为0.29~0.91,p0.05).洪水期颗粒物的亲脂性强于枯水期.     

多环芳烃在长江口滨岸颗粒物-水相间的分配

利用长江口滨岸水环境中颗粒相与溶解相多环芳烃的实测浓度,获取了多环芳烃化合物在颗粒物-水相间的分配系数K_p.结果表明,分配系数K_p值在507～10 179 L/kg之间,枯季高于洪季,随多环芳烃环数的增加而增大;K_oc值与辛醇-水分配系数K_ow之间存在较好的线性自由能关系（枯季R²＝0.82,洪季R²＝0.68）,推断出长江口滨岸颗粒物亲脂性较差,对多环芳烃的吸收能力相对较弱.长江口滨岸各采样点多环芳烃化合物的lgK_oc值均超过了经典平衡分配模型的预测值上限,多环芳烃两相分配行为不受颗粒物浓度、粒径及上覆水盐度、溶解态有机碳的控制（R²<0.1）,表现出主要受POC及非均一性混合物PSC共同影响的特点;扩展后的含PSC相的颗粒物-水相分配模型较为准确地模拟了lgK_ow<6的多环芳烃化合物野外原位分配过程.