近20年来中国典型区域PM2.5时空演变过程

近20年来PM_(2.5)污染严重制约了中国可持续发展.长时间序列历史监测数据的缺失阻碍了相关研究.为此,本文以四大典型区域2013~2016年的PM_(2.5)浓度监测值和2000~2016年MODIS AOD数据、边界层高度、温度等气象数据作为基础数据,将反向人工神经网络和支持向量回归机两种算法相结合,构建组合模拟模型,并利用地理空间分析技术实现近20年来PM_(2.5)浓度历史变化过程的情景再现.研究结果表明,组合模型具有较低的误差和更高的泛化能力;时空分析结果表明,2000~2010年京津冀和东三省PM_(2.5)浓度持续增长,珠三角PM_(2.5)浓度缓慢下降,3个研究区PM_(2.5)污染范围呈扩大趋势,长三角PM_(2.5)浓度值及污染范围基本保持稳定.2012年4个研究区PM_(2.5)浓度值降低且污染范围缩小,但2013~2016年PM_(2.5)浓度略微上升后又下降,高污染范围缩小,这与国家采取PM_(2.5)区域联防等治理措施有关.     

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。     

中国碳排放及影响因素的市域尺度分析

评估区域碳排放及其与社会经济状况的关系对于制定碳减排措施至关重要.以中国339个地级及以上城市(不含新疆部分城市和港澳台地区)为研究对象,探究了非化石能源占比、土地开发度、常住人口城镇化率、第二产业占比、人均GDP和人均建设用地面积对人均CO₂排放量的影响.通过构建模拟人均CO₂排放量的贝叶斯信念网络,识别各因素对人均CO₂排放量的全局影响;采用多尺度地理加权回归模型,分析各因素对人均CO₂排放量的局部影响.结果表明：(1)2020年,中国地级及以上城市人均CO₂排放量呈现出由南向北递增,东部沿海向内陆递减的格局.(2)从全局来看,人均CO₂排放量对各因素的敏感性从高到低依次为：人均建设用地面积>人均GDP>常住人口城镇化率>土地开发度>第二产业占比>非化石能源占比.(3)从局部来看,各因素与人均CO₂排放量的空间关系方向与全局关系一致,关系强度上存在空间异质性.(4)清洁能源、脱碳技术、土地节约集约利用...     

多因素作用下同庭湖洪水调蓄量的变化

用实测资料分析比较了出口水位31．0m时,洞庭湖调蓄量的变化趋势及影响调蓄量的各种因素。用多元线性回归方法建立了调蓄量经验公式,并用该公式计算分析了各因素对调蓄量变化的影响。结果表明,该公式能够较全面地反映调蓄量变化的原因,且能够近似区分淤积和围垦对调蓄量的影响。     

遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.     

矿工心理因素、工作压力反应和不安全行为关系研究

为研究在巨大工作压力下,矿工的心理因素与工作压力反应和不安全行为的关系,以问卷的形式调查陕西省2家具代表性煤矿的工人,分别以矿工的心理因素、工作压力反应和作业过程中的不安全行为作为外生变量、中介变量和内生变量,构建心理因素、压力反应和不安全行为的结构方程模型。通过对调研数据处理与分析,得出如下结论:本研究中的4项心理因素,性格因素、心理素质、注意力和工作态度显著影响不安全行为的发生;性格因素、心理素质和注意力对压力反应有显著影响;工作态度与煤矿工人的压力反应的关系不显著;性格因素、心理素质、注意力和工作态度通过影响矿工的压力反应,间接影响矿工的不安全行为。     

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。     

火灾发生率空间分异及影响因素研究

为了探究我国火灾空间聚集特征与影响因素的空间异质性,采用全局莫兰指数、局部莫兰指数、逐步回归模型、地理加权回归模型、地理探测器方法对我国地级市单元进行研究。研究结果表明:我国火灾发生率具有显著的聚集性;我国火灾发生率较低的“冷点”区域有1个,火灾发生率较高的“热点”区域有4个;人均GDP、城镇居民人均可支配收入、人口密度、年平均气温4 个因素的影响效应具有空间异质性。人均GDP与火灾发生率为正相关,另外3影响因素对火灾发生率的作用表现出正负2种相关关系;2因素交互作用要比单因素作用于火灾发生率时影响力更显著,各影响因素的交互作用类型有非线性增强型和双因子增强型2种。