数据挖掘在预测组织事故防控效果中的应用*

为进一步探索数据挖据技术在组织事故预防工作中的融入性与适用性,基于24Model构建事故预控基础模型,通过预测准确率数值及接受者操作特性曲线（ROC曲线）对比分析随机森林（RF）、支持向量机(SVM)、决策树（DT）与神经网络（NN）4种方法对组织事故防控效果的预测性能。结果表明:针对事故率控制（Y1）、职业危害预防（Y2）、财产损失3类预测目标（Y3）,RF方法均能达到较高的准确率及稳定性,具有较优的预测性能。根据特征重要度（FI）排序,明确对组织事故水平影响最显著的因素为安全实践活动认知（SC5）及安全管理程序文件（SMS3）,FI值均大于0.150 0。研究结果可为有效预测组织事故防控效果提供方法依据,同时为企业安全工作的规划设计提供思路。     

大气环境监测全过程质量控制研究

我国经济飞快的发展速度,不但丰富了人们的生活内容、方便了人们的生活,而且还在人们生活中产生了一些负面影响,大气污染问题已经引起了国家政府以及我国民众的一致关注,国家还为此制定并颁布了相关的整顿治理措施,在大气环境治理方面,大气监测是重要手段,本文对大气环境监测全过程质量控制问题展开分析研究。     

Thermal decomposition mechanism of 65% lysine sulfate powder and its thermal stability based on thermal analysis

Lysine is widely used in the fields of food, medicine and feed, which generally appears in the form of lysine sulfate or lysine hydrochloride dust because of the high instability of the free L-lysine. The L-lysine Sulfate is in high risk of decomposition, spontaneous ignition and even the dust explosion, because the control temperature in its production process is high up to 90 °C. Thus, the thermal behaviors and its thermal stability of 65% lysine sulfate are experimentally explored in Air and Nitrogen using the simultaneous TG-DSC measurements. Results show: (1) the decomposition of 65% lysine sulfate can be divided into three stages both in the atmospheres of air and nitrogen, and most of the weight loss occurred in the first two stages, which are related with the decarboxylation and deamination process. (2) The effects of atmosphere on the decomposition of 65% lysine sulfate mainly occur at the third stage. In this stage, the weight loss in nitrogen is only 14.2%, which is much lower than that in air (34.3%), which is related to the oxidative degradation at high temperature. Besides, the active energy is slightly increased in nitrogen compared to that in air. (3) The initial temperatures of the decomposition of the 65% lysine sulfate are 145 °C and 155 °C, for the air and nitrogen atmosphere, respectively, which are much lower than that (260 °C) of the pure lysine.     

喀斯特峡谷区工程性缺水原因及解决途径——以贵州省花江峡谷示范区为例

喀斯特峡谷区河深坡陡,地下水深埋,水资源利用难度大,加之经济和水利工程薄弱,是贵州省工程性缺水的典型区域。通过对花江峡谷示范区工程性缺水的原因剖析,提出一系列解决工程性缺水问题的措施,如雨水收集、表层喀斯特水和基岩裂隙水的开发利用、节水、加强对水利工程设施的管理和维护、加大水利投入以及提高植被覆盖率等,这对解决喀斯特峡谷及类似区域的工程性缺水问题有一定的指导和参考意义。     

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.     

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.     

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.     

Nationwide monitoring of atmospheric PCDD/Fs and dioxin-like PCBs in South Korea

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (DL-PCBs) were measured in ambient air samples collected from different parts of South Korea in 2008, and the measured levels were used for assessing the spatial and temporal distribution of atmospheric PCDDFs and DL-PCBs in South Korea. The average concentrations of atmospheric PCDD/Fs and DL-PCBs among the 37 sites were 28 fg I-TEQ m⁻³ (ND ∼ 617) and 1 fg WHO-TEQ m⁻³ (ND ∼ 0.016). Elevated atmospheric levels of PCDD/Fs and DL-PCBs observed at residential/industrial sites and in the north-west of Korea, indicated a potential contribution and impacts of anthropogenic sources of PCDD/Fs and DL-PCBs. These levels were similar or lower than those previously reported in other ambient air surveys. Average concentrations of PCDD/Fs showed small seasonal variations (ANOVA analysis, p = 0.144). The highest concentrations of PCDD/Fs were observed during winter, followed by spring, autumn and summer. Atmospheric PCDD/Fs and DL-PCBs in South Korea rapidly decreased during the last 10 years (1998-2008), demonstrating the efficiency of stricter regulations and the application of best available technologies/best environmental practices at emission sources. Comparison of the congener profiles and principal component analysis showed that current atmospheric PCDD/Fs are mostly influenced by industrial sources and PCBs from old commercial PCB uses. Nationwide POPs monitoring will continue and allows an effective evaluation of the implementation of the Stockholm Convention on POPs.