不同类型压力对飞行员安全绩效的影响规律研究

为探究各类型压力对飞行员安全绩效的影响规律，为飞行员日常工作管理提供依据，选取某航空公司200名飞行员进行压力测试，并调取其近6 a的飞机品质(QAR)数据，通过相关性分析和线性回归分析将飞行员压力数据与其QAR数据进行对比分析，探究飞行员压力对飞行安全绩效的影响规律。研究结果表明:工作负荷压力、家庭压力、人际关系压力和组织管理压力会显著负向影响飞行员安全绩效；角色压力和专业发展压力会显著正向影响飞行员安全绩效。     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

基于绝对主成分-多元线性回归的滇池污染源解析

定量解析污染源是湖泊流域水环境管理的重要基础.基于滇池草海和外海多年水质监测数据,采用主成分分析（PCA）方法识别了主要水质指标的污染源类型,利用绝对主成分-多元线性回归模型（APCS-MLR）得到不同污染源对水质的贡献程度.结果表明,草海主要的污染源有农业面源、城市面源和内源3类,外海的主要污染源是农业面源、城镇生活污染源、城市面源和内源4类.与河流水污染源解析结果不同,底泥内源与气象因子对滇池主要水质指标的影响较大.     

特殊区域地表水环境背景值表征技术方法研究与应用

选取黑龙江省源头水保护区作为研究对象,根据DEM数据对保护区内随机布设的水质监测点控制单元进行划分并提取单元内的相关指标建立监测点背景特性量化模型,基于量化结果提出地表水环境背景值监测方案,建立背景值数据库.选取研究区自然属性指标与空间属性指标,以空间叠置技术与聚类分析方法对研究区地表水进行背景值分区,最终将黑龙江省分为六大地表水水质背景值地理分区,并计算了各分区地表水环境背景值表征范围.表征范围显示：依据现行标准进行水质评价,保护区内水质背景值已超出Ⅱ类水质标准限值.因此,基于水质背景值研究成果提出了考虑背景值影响下的水环境质量评价方法,并将方法应用于研究区,结果表明方法切实可行且优于单因子评价法.研究成果可为区域制定背景值影响下的水环境评价方法提供科学的数据支撑与理论依据.     

中国“四化”建设对水足迹强度的影响分析

采用2000—2016年中国30省市（不包括香港、澳门、台湾、西藏四省区）的数据,构建四化指标体系,计算四化发展指数,进行地区四化水平评价,通过OLS和GMM回归模型考察四化发展对水足迹强度的影响,同时设置四化之间的交互项来识别四化指标之间的相互作用。主要结论如下：首先,从四化水平的地域发展差异上来看,中国四化水平总体上呈现出东部优于中部、中部优于西部的格局,水足迹强度的分布与之类似,说明四化水平发展与水足迹强度之间可能存在相关关系;其次,计量模型显示四化水平的提升对于水足迹强度的改善有积极影响,但每一化对于水足迹强度改善的影响大小不一;第三,以交互项衡量的四化相互作用对于水足迹强度的影响作用为正,表明四化发展对水足迹强度的改善效果逐渐趋于收敛。因此,优先提升落后地区的四化水平,以四化水平的提升推动水足迹强度的降低,能够有效降低我国总体水足迹强度水平。     

典型西南工业城市春冬季PM2.5来源与潜在源区分析——以柳州市为例

为了揭示柳州城区春冬季PM_2.5的来源及其潜在源区分布和贡献,利用2018年24h自动监测数据和气象数据对柳州市大气污染物浓度变化特征进行了分析,并且使用后向轨迹模型（HYSPLIT）对春冬季柳州市PM_2.5逐日72h气流后向轨迹和前向轨迹进行聚类分析,同时结合潜在源贡献因子分析法（WPSCF）和轨迹浓度权重法（WCWT）对其潜在源区和浓度贡献进行了分析.结果显示,（1）在研究期内,不利的主导风向和工业区布局导致研究区PM_2.5在春冬季污染较严重,且工业源和交通源是其主要本地来源;（2）春冬季PM_2.5高值主要来源于西北和东南方向,其中,西北向PM_2.5主要来源于本地排放,且浓度在空间上呈现西高东低的趋势;（3）春季后向轨迹PM_2.5浓度整体大于冬季,春冬季中对柳州市PM_2.5影响最大轨迹均来自东部的短距离输送,而来自西北的气流轨迹输对PM_2.5贡献最低.春冬季柳州市大气PM_2.5通过气流传输对贵州地区大气环境有较大影响;（4）春季,柳州市PM_2.5的主要潜在源区分布在广西东南部、广东中西部、南海沿岸海域、湖南中部、江西西北部、湖北东部及安徽西北部;冬季,主要分布在广西东南部、广东西南部和南海沿岸海域.     

海河下游水体中DO与NH_3-N、COD_(Mn)相关关系探讨

本文应用近年来海河下游监测数据对ＤＯ与ＮＨ３Ｎ和ＣＯＤＭｎ进行一元线性回归，得到两回归方程：ＮＨ３Ｎ＝－１２８ＤＯ＋１０５４；ＣＯＤＭｎ＝－１１３ＤＯ＋１６９２。并经相关系数和回归系数显著性检验，表明在９９９％的置信水平下ＤＯ与ＮＨ３Ｎ和ＣＯＤＭｎ线性相关均极其显著     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.