Modelling the fate of hydrophobic organic contaminants in a boreal forest catchment: A cross disciplinary approach to assessing diffuse pollution to surface waters

The fate of hydrophobic organic compounds (HOCs) in soils and waters in a northern boreal catchment was explored through the development of a chemical fate model in a well-characterised catchment system dominated by two land types: forest and mire. Input was based solely on atmospheric deposition, dominated by accumulation in the winter snowpack. Release from soils was governed by the HOC concentration in soil, the soil organic carbon fraction and soil-water DOC content. The modelled export of selected HOCs in surface waters ranged between 11 and 250 ng day⁻¹ during the snow covered period, compared to 200 and 9600 ng/d during snow-melt; highlighting the importance of the snow pack as a source of these chemicals. The predicted levels of HOCs in surface water were in reasonable agreement to a limited set of measured values, although the model tended to over predict concentrations of HOCs for the forested sub-catchment, by over an order of magnitude in the case of hexachlorobenzene and PCB 180. This possibly reflects both the heterogeneity of the forest soils and the complicated and changing hydrology experienced between the different seasons.     

河南省旅游—经济发展类型及其开发战略

以河南省18个地市旅游与经济统计数据为样本,运用典型相关模型探讨旅游与区域经济发展之间的关系。第一典型变量揭示旅游产业发展有利于区域经济发展与对外开放;第二典型变量显示旅游发展能够促进工业化、拉动消费与固定资产投资。依据典型方程得分,划分为旅游与经济发达地区、较发达地区、一般地区等三种类型,并提出旅游发展策略。     

Impact of demographic dynamics on CO_2 emissions in Sichuan,China

Global climate change is one of the major environmental issues faced by humans.Existing evidence indicates that the anthropogenic push for a rise in the atmospheric concentration of greenhouse gases(GHGs)(particularly CO_2)has been a primary cause for global warming.Aside from economic and teclinological factors,demographic dynamics(including human consumption in a broad demographic sense)has been a major driver for CO_2 emissions.In this paper,we performed both nonlinear regression analysis(based on the STIRPAT model)and gray correlation degree analysis(based on gray system theory)on the impact of demographic dynamics on CO_2 emissions.Our results reveal that CO_2 emissions are positively correlated with population size and GDP per capita and negatively correlated with energy intensity.We also show that gray correlation degree with CO_2 emissions for five variables(i.e.,household consumption,urbanization rate,household size,population aging rate,population size)varies substantially:household consumptionurbanization ratehousehold sizepopulation aging ratepopulation size,with household consumption being the highest,and population size the lowest.To mitigate the impact of demographic dynamics on CO_2 emissions,it is of vital significance to nurture people's awareness of sustainable consumption and to adhere to current population control policies.     

锰矿区土-水界面污染流中重金属来源分析

基于对湘潭锰矿红旗矿区土-水界面重金属污染流的采样分析,通过相关性和主成分分析法,研究了锰矿区土-水界面重金属污染流中的锰、镍、铜、锌、镉、铅重金属的来源以及同源性。结果表明:6种重金属的差异性、离散程度、变异性较大;锰—镍、锰—锌、锰—镉、锰—铅、镍—锌、铜—锌、铜—铅、锌—镉、锌—铅、铅—镉呈极显著正相关,镍与锰以外的其他重金属相关性都较低;3个主成分的贡献率分别为58.300%、16.628%、11.115%,累积贡献率达到了81.543%,并且6种重金属在主成分1的载荷非常高。结合矿区的周边环境和自身特点,表明6种重金属的主要共同来源为矿区内的矿业活动,并且工业活动、交通运输、农业活动等也对矿区造成了一定程度的重金属污染。     

Evaluating and reducing a model of radiocaesium soil-plant uptake

An existing model of radiocaesium transfer to grasses was extended to include wheat and barley and parameterised using data from a wide range of soils and contact times. The model structure was revised and evaluated using a subset of the available data which was not used for model parameterisation. The resulting model was then used as a basis for systematic model reduction to test the utility of the model components. This analysis suggested that the use of 4 model variables (relating to radiocaesium adsorption on organic matter and the pH sensitivity of soil solution potassium concentration) and 1 model input (pH) are not required. The results of this analysis were used to develop a reduced model which was further evaluated in terms of comparisons to observations. The reduced model had an improved empirical performance and fewer adjustable parameters and soil characteristic inputs.     

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L⁻¹), medium dose (amended at 100 μg U L⁻¹), and high dose (500 μg U L⁻¹). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier.     

河流近域土地利用格局与水质相关性分析——以巢湖流域为例

以河流近域土地利用构成与水环境质量间定量关系为研究对象,基于巢湖流域40个水质监测断面和320个河流近域作用区,运用GIS空间分析功能计算不同尺度作用区内土地利用构成,借助相关分析、冗余分析(RDA)等数理统计手段,分析土地利用构成与水质指数间的相关关系;并分析和比较了流域内山区和平原地区土地利用构成与水质之间关系。结果表明,巢湖流域近河道地区土地利用构成对各水质指数有重要影响,且受地形因素影响。其中,建设用地对河流水质恶化具有明显作用;河流沿岸林地布局能显著改善水质,尤其是对氨氮和高锰酸盐指数敏感;耕地面积变化与水质相关性不显著。RDA冗余分析证实了不同尺度下的土地利用类型对水环境影响具有尺度效应。研究成果对巢湖流域水环境管理具有重要的实际指导意义,并为同类研究提供借鉴     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

人口长期均衡发展及其评价监测模型的构建与应用

在借鉴已有理论的基础上,界定了人口长期均衡发展的内涵,提出人口长期均衡包含人口内部均衡和人口外部均衡两个方面,人口内部均衡包括人口数量、人口质量和人口结构三个维度,人口外部均衡包括人口与经济、人口与社会、人口与资源、人口与环境四个维度;在此基础上构建了人口长期均衡发展的指标体系和评价模型,指标体系设定为三级,第一级包括人口内部均衡和人口外部均衡两个方面,第二级由人口数量、人口质量、人口结构等七个部分构成;第三级指标包括反映内部均衡的7个指标以及反映外部均衡的13个指标.并使用层次分析法确定了指标的权重;采用2000-2007年31个省级单位的数据对人口长期均衡发展评价模型进行了验证,并对人口总体均衡水平以及影响人口均衡发展的关键要素进行了实证分析.结果表明.北京、上海和浙江分列前三,人口均衡发展程度最高.从影响均衡程度的关键因素看.人口质量和人口结构是制约人口自身均衡的主要因素,人口与社会的均衡状况对人口与外部系统均衡制约最大,其次是人口与经济的均衡状况.     

基于变异系数法的安徽省节能减排评价研究

以行政区域为单位进行节能减排评价研究,分析其中的影响因素,便于因地制宜地采取措施开展节能减排工作。本文以安徽省为研究对象,运用变异系数法对节能减排作评价研究。研究表明,节能减排总体成效显著,但减排问题突出,其中污染物排放与产业结构存在密切关系,进一步的关联分析得出影响减排的主要行业因素。据此,提出从调整产业结构、加强科技创新、完善法规政策方面推进节能减排。