企业环境管理中政府和企业作用分析

我国的经济发展伴随着日益严重的环境问题。在引起环境问题的诸多因素中,来自企业方面的因素对环境的影响最为深远,因此改善环境首先就需要加强企业的环境管理。在推动企业进行环境管理的各种因素中,既有如政府的管制等外部因素,也有如减少成本、产品差异化等企业自身内部因素。外部因素和内部因素对推动企业环境管理都具有重要作用,但也有其局限性。本文通过政府管制及企业自身因素对驱动企业进行环境管理的作用机制的研究,分析各个驱动因素优缺点,寻求各驱动因素的最佳的组合,促使企业更好地加强环境管理。     

三门湾近海有机污染对浮游细菌群落的影响

近海污染问题日趋严重,因此亟需评价污染对海洋环境造成的潜在影响.微生物作为对环境变化的首要响应者,可能作为评价污染水平的指示生物.为此,本文采集三门湾和邻近鱼山保护区共21个站点的表层海水,利用Illumina技术测定细菌16S rRNA基因,对比研究有机污染对浮游细菌群落的影响.三门湾的有机污染(A)为4.57±2.41,显著(P0.001)高于鱼山保护区0.43±0.74.三门湾和鱼山保护区的浮游细菌多样性和群落结构差异显著,其中三门湾水域的放线菌门(Actinobacteria)、α-变形菌纲(α-Proteobacteria)、β-变形菌纲(β-Proteobacteria)、SAR406的相对丰度显著高于鱼山保护区,而拟杆菌门(Bacteroidetes)、蓝细菌门(Cyanobacteria)、浮霉菌门(Planctomycetes)的相对丰度低于鱼山保护区.多元回归树分析(multivariate regression tree,MRT)发现浮游细菌多样性主要受pH、有机污染和叶绿素a(Chl-a)的影响,分别控制了27.7%、15.6%和6.7%的多样性变异.冗余分析(redundancy analysis)结果表明驱动细菌群落变异环境因子为有机污染、pH和盐度(salinity),共解释了14.8%的群落变异.同时,空间距离与细菌群落组成显著相关,解释了4.42%的变异,表明浮游细菌的空间分布不是随机的.此外,本研究筛选到与有机污染状况显著相关的23个细菌科,各科相对丰度的变化与其已知的生态功能特征相吻合,因此可以作为潜在的有机污染指示种群.本实验结果表明近海有机污染显著地改变了浮游细菌群落结构,特别是潜在病原菌丰度的增加;此外,筛选到敏感指示种群用于评估有机污染程度.     

基于多年遥感数据分析长江河口海岸带湿地变化及其驱动因子

研究河口海岸带湿地长时间演变对湿地保护管理和海岸带资源评估具有重要意义.本文获取长江口1979—2015年10景Landsat-MSS/TM/OLI影像和2015年13景GF1-PMS高空间分辨率数据,对比两个典型实验区分类算法,选用最优的决策树算法应用到长江口Landsat影像中,得到沿岸湿地要素近40年的面积变化情况.研究表明,2015年长江河口海岸带湿地总面积为4725 km2,自然湿地占63.5%,人工湿地占21.2%,湿地总面积相比1979年增加了662 km2,自然湿地面积减少了163 km2,而人工湿地面积增加了766 km2.长江口自然湿地面积在1979—2000年减少幅度较大,2000年后由于保护管理加强而减少幅度变小;人工湿地和建筑面积增加较为明显,主要是由于大型水库的修建和人工鱼塘开发及港口建设.湿地总的变化趋势为河口区不断淤积,自然湿地转变为人工湿地,人工湿地转变为建筑用地等非湿地;其中,滩涂面积减少283 km2,水库、养殖鱼塘和水稻田面积分别增加了92、355和319 km2,主要发生在崇明东滩和启东沿岸;非湿地中建筑用地面积增加154 km2,灌木草场面积减少147 km2,主要发生在上海和启东沿岸.同时比较分析长江口3个区域湿地驱动因子发现,北岸启东沿岸和南岸南汇东滩湿地因经济快速发展和港口水利工程修建,以及过度开垦滩涂等自然湿地使人工湿地增加明显;而长江上游径流量、区域降水和海平面上涨等自然因素控制着中支河道区(如崇明东滩)自然湿地的变化.     

盾构施工对不同刚度桩体影响的数值分析

针对苏州轻轨一号线盾构隧道的施工情况,采用三维有限元数值模型,研究了盾构施工对不同刚度桩体的影响.计算结果表明:当盾构施工时,不同刚度桩体均偏向隧道移动,在隧道轴线处的横向位移均为最大.桩身横向位移最大值、竖向位移随桩体刚度增大而变小,桩身轴力、弯矩则随桩体刚度增大而逐渐增大,桩身最大负弯矩均出现在隧道轴线位置处.在盾...     

智能手机应用程序使用与操作的驾驶分心风险影响研究

为研究智能手机应用程序操作方式与使用行为对驾驶分心影响的问题,探讨智能手机程序操作方式对驾驶分心影响的优劣关系,基于结构方程模型提出4个因果关系假设,构建涵盖程序使用、驾驶分心、驾驶绩效等潜变量的智能手机使用行为影响的结构方程模型。通过收集线下问卷的方式进行调查,搭建模拟场景,设计6项实验方案,通过驾驶模拟实验方式收集相关数据,建立相对偏差矩阵。研究结果表明：手机通话功能的使用(路径系数0.472)对驾驶分心影响显著,手机导航功能使用(路径系数0.256)、手机音乐功能使用(路径系数0.249)对驾驶分心影响不显著。语音交互方式均优于手动操作方式,其中语音交互启动导航方式(F₃=0.019)的影响最小。研究结果可对道路驾驶情况下智能手机应用使用与操作方式的研究起推动作用。     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

Identification of aggressive driving from naturalistic data in car-following situations

Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

江苏苏中3市的沿江岸线资源开发利用变化及驱动因素

长江是我国重要的黄金水道,其岸线资源有着丰富的开发利用价值。近年来,苏中地区长江岸线资源利用发展迅速。因此,选取苏中扬州、泰州、南通3市为研究对象,基于2002年和2008年的长江岸线利用状况数据,对比分析了3市岸线发展变化的规律。研究表明:2002年以来,苏中3市的岸线利用率大幅提高;新增岸线中工业岸线占比最大,港口岸线和生活服务岸线次之;工业岸线和生活服务岸线的增幅最为显著;各类型岸线的增加主要来源于未利用岸线,已有岸线类型的转换主要流向工业岸线和未利用岸线。港口建设需求、沿江基础工业化进程加快、港产城融合发展、规划和政策引导等是岸线利用变化的重要驱动力。     

南京市2000~2014年城市建设用地变化及驱动因子研究

基于土地利用模型测度2000~2014年南京市城市建设用地的动态变化,再运用典型相关分析、主成分分析及逐步回归分析组合的偏最小二乘回归法对南京市城市建设用地的驱动因子进行分析。结果表明：（1）2000~2014年南京市城市建设用地面积总体上呈上升趋势,年均增长率为11.73%;（2）南京市用地结构信息熵呈波动下降趋势,城市建设用地系统结构性增强,但是用地扩展的综合效益趋降;（3）人口增长、道路扩展、投资水平提高及文化产业发展等能够较好的解释南京市城市建设用地的增长,这4类因子对城市建设用地变化具有正向作用;（4）逐步线性回归结果表明,园林绿地面积的增加相对其他因子对南京市建设用地规模增长的作用最大,其次是道路长度和公路里程。