中国岩溶生态地质研究

因自然地理条件特殊，中国南方岩溶区形成组构相对脆弱的岩溶多重介质环境。加上不适当的认为干扰，岩溶多重介质环境遭受严重破坏，导致各类物种急剧减少或消失。文章主要对岩溶多重介质环境的脆弱性、水资源合理开发利用、土壤质量、生态承载力、化学元素迁移演变规律和人类参变作用等方面进行了讨论；针对上述问题提出了解决方案，即划分岩溶多重介质环境结构和功能区，并结合数学物理模型和实验，建立岩溶生态地质研究系统理论框架和实用技术方法库，使岩溶生态地质研究走上科学、合理的轨道。     

A new method for spatially moving correlation analysis in geomedicine

A method of correlation analysis within a spatially moving window was applied to two sets of epidemiological/geochemical data in Norway, (1) mortality/disability rates of multiple sclerosis (MS) versus atmospheric fallout of Mg and concentrations of Se in overbank sediment, and (2) incidence rates of malignant melanoma of the skin (MM) versus concentrations of Ca and K in overbank sediment. It appears that n = 17 observation sites within the moving window is a practical compromise between noise in the data at small values of n and a spatial resolution good enough to detect trends in the distribution patterns of the correlation coefficient. For MS versus Mg, MS versus Se and MM versus Ca the correlation coefficients are generally negative and depict systematic distribution patterns with anomalous clusters of sites with good correlation. For MS versus Se the correlation coefficients also form an additional cluster of positive coefficients. Tests with permutated data show that more than 70% of the negative correlation coefficients for MS versus Mg and for MM versus Ca are both significantly different from zero at p<0.05, while less than 15% of those for MS versus Se are significant at the same level. For MM versus K the correlation coefficients are randomly distributed and not significantly different from zero. The described correlations may be effects of confounders and do not per se indicate any causal relationships. However, further research based on these results may well lead to the identification of possible aetiological factors.     

厦门市大气可吸入颗粒物源解析的研究

采用2004～2005年对厦门大气中PM10开展的3期采样分析数据,利用主因子分析法定性分析厦门大气中可吸入颗粒物的主要来源,并结合多元线性回归法,求出定量的结果。分析结果表明,影响厦门市可吸入颗粒物的主要来源有四种:工业燃煤、汽车尾气、土壤风沙尘和海盐粒子,其中二次粒子为主要污染源,贡献率为30.0%,其次为汽车尾气占29.4%,土壤风沙和建筑尘的贡献约占21.7%,海洋粒子的贡献为6.5%,不可识别源18.1%。     

霍林河中游径流量序列的多时间尺度特征及其效应分析

霍林河是松嫩平原西部地区科尔沁、向海和查干湖湿地的重要补给水源。通过对其中游白云胡硕水文测站46a的年径流量序列的多时间尺度分析,探讨霍林河径流演变的近似周期性,识别霍林河径流变化对其下游洪泛湿地水源补给的规律,以及这种规律控制下的洪泛湿地环境演变。小波分析表明,霍林河白云胡硕水文站年径流序列主要存在3个尺度的周期变化,不同时间尺度下周期信号的强弱在时频域中的分布具有较强的局部特征,以大于30a尺度的年代际周期变化起主导作用,该尺度下,霍林河径流演变呈现出丰、枯、丰的交替振荡,下游洪泛湿地景观演变相应表现出阶段性特征,1990年代以前尤为突出。能量相对较弱的中、小时间尺度径流量周期性变化,与强烈的人类干扰活动相比,对下游洪泛湿地环境演变的作用效果不明显,突出表现在1990年代以后。     

硅藻指数在嫩江支流甘河的适用性评估

为了筛选出适用于甘河水生态评价的硅藻指数,合理评价甘河水生态健康状况,2018年8月在嫩江支流甘河调查了19个点位的着生硅藻群落结构和水环境特征.应用21种硅藻指数对甘河水生态健康状况进行评价,采用箱体图法分析了所选硅藻指数的适用性,使用Spearman相关分析研究了硅藻指数与环境因子的相关性,最后应用多元线性回归方法分析了不同因素对硅藻指数在甘河评价正确率的影响.结果表明:①所选硅藻指数中,IBD（biological diatom index,硅藻生物指数）、EPI-D（diatom eutrophication pollution index,富营养污染硅藻指数）和IPS（specific pollution sensitivity index,特定污染敏感指数）的评价结果区分度最好,最适用于甘河水生态健康状况评价.②甘河丰水期水生态健康状况总体较好,约70%的点位水生态健康状况为健康、较好和一般,约30%的点位水生态健康状况为较差和极差,极差的点位全部位于甘河下游区域.③硅藻指数与COD_Cr的相关性对硅藻指数评价正确率有显著影响（P < 0.01）,硅藻指数与COD_Cr相关性越强,评价的正确率越高;物种覆盖度对硅藻指数评价的正确率也有影响,但不显著,各点位最小物种覆盖度高于65%时,物种覆盖度对藻指数评价的正确率影响较为明显.研究表明,硅藻指数可以有效地评价水生态健康状况,但硅藻指数与环境因子之间的相关性等因素会影响评价的正确率,因此选择合适的硅藻指数进行研究区域的水生态健康状况评价尤为重要.      

4种重要因素对柴油机颗粒物排放因子的量化影响研究

在发动机台架测试基础上,按照发动机排放阶段、油品种类、后处理装置和运行工况4种因素的不同,进行了24组测试,研究了颗粒物排放因子.同时,应用单因素敏感性分析,探究了发动机排放阶段和油品种类对颗粒物排放因子的影响;并运用多元线性回归分析,探讨了4种因素对颗粒物排放因子的影响力大小排序.结果显示:24组柴油机测试的颗粒物排放因子均值为(21.9±24.5) mg·kWh~(-1);使用国Ⅴ排放标准柴油机的颗粒物排放因子((14.7±5.6) mg·kWh~(-1))比国Ⅳ排放标准柴油机((19.4±16.4) mg·kWh~(-1))有所下降;国Ⅳ柴油、国Ⅴ柴油和混合柴油的颗粒物排放因子平均值分别为120.0、(11.8±1.0)和(11.5±1.3) mg·kWh~(-1),混合柴油颗粒物排放因子与国Ⅴ柴油相近,两者相比国Ⅳ柴油有明显下降;油品种类是影响颗粒物排放因子的第一大因素,后处理是影响颗粒物排放因子的第二大因素.     

多承载索货运索道计算方法及张力不平衡效应分析

通过分析多承载索货运索道工作索的空间位置关系,在弹性悬链线计算方法的基础上,建立包括索道结构守恒方程和力平衡方程的非线性方程组,形成多承载索货运索道系统整体耦合计算方法。针对四承载索货运索道的典型设计工况,应用该方法完成承载索长度不一致情况下,货运索道的承载索张力变化分析。研究结果表明:多承载索货运索道承载索间的张力不平衡受索长偏差影响极大,而且不平衡效应与索长变化工况（索长偏差变化量、变化索的位置等）和载荷重量密切相关,多索索长不一致造成的张力不平衡使得承载索破断风险急剧增加。     

基于支持向量机的管制疲劳检测模型研究

管制疲劳是影响民航安全的重大隐患,准确检测疲劳状态是进行疲劳预警、降低疲劳风险的关键。提出应用支持向量机模型融合多生理参数和眼动指标进行管制疲劳检测,通过MP150多导生理记录仪与眼动仪,采集模拟管制试验中正常与剥夺睡眠状态下被试的试验数据,同时记录其Karolinska疲劳等级和操作绩效。结果表明,RR间期、LF/HF、快慢波比值、PERCLOS和扫视速度均与管制疲劳呈较强相关,利用支持向量机融合五项指标构建管制疲劳检测模型,对于五级疲劳度的识别准确率为78. 1%,判断正常组与剥夺睡眠组的准确率为94. 2%。     

Variation of reservoir fluid property during the high pressure air injection process

This research aimed at determining the variation of reservoir fluid property during the high-pressure air injection process. For this purpose, the forward multiple contact experiment was employed by pressure–volume–temperature (PVT) system to investigate the physical property variation of the crude oil and the complex oxidation reactions. The results show: under the relative low temperature and pressure condition, instead of carbon dioxide, carbon monoxide dominates the products in the air phase. The gas/oil ratio and volume ratio increased due to the generated gas while the viscosity and density achieved a descending trend. The colloid and bitumen in the oil phase reduced by half but the amount of wax achieved a small increase. The low-temperature oxidation and pyrolysis reactions caused the fluctuated change of the different compounds. The amount of light compounds decreased at the beginning and then increased while that of heavy compounds showed the opposite trend. But at last, due to the H/C ratio, the light compounds increased to more than their initial value.     

Spatially explicit sensitivity and uncertainty analysis for multicriteria-based vulnerability assessment

This research analyses the application of spatially explicit sensitivity and uncertainty analysis for GIS (Geographic Information System) multicriteria decision analysis (MCDA) within a multi-dimensional vulnerability assessment regarding flooding in the Salzach river catchment in Austria. The research methodology is based on a spatially explicit sensitivity and uncertainty analysis of GIS-CDA for an assessment of the social, economic, and environmental dimensions of vulnerability. The main objective of this research is to demonstrate how a unified approach of uncertainty and sensitivity analysis can be applied to minimise the associated uncertainty within each dimension of the vulnerability assessment. The methodology proposed for achieving this objective is composed of four main steps. The first step is computing criteria weights using the analytic hierarchy process (AHP). In the second step, Monte Carlo simulation is applied to calculate the uncertainties associated with AHP weights. In the third step, the global sensitivity analysis (GSA) is employed in the form of a model-independent method of output variance decomposition, in which the variability of the different vulnerability assessments is apportioned to every criterion weight, generating one first-order (S) and one total effect (ST) sensitivity index map per criterion weight. Finally, in the fourth step, an ordered weighted averaging method is applied to model the final vulnerability maps. The results of this research demonstrate the robustness of spatially explicit GSA for minimising the uncertainty associated with GIS-MCDA models. Based on these results, we conclude that applying the variance-based GSA enables assessment of the importance of each input factor for the results of the GIS-MCDA method, both spatially and statistically, thus allowing us to introduce and recommend GIS-based GSA as a useful methodology for minimising the uncertainty of GIS-MCDA.