长江流域水质的综合评价与预测

长江流域水质演变过程可看成是一个具有多节点,向下流关联的复杂网络系统。本文运用统计学的统计推断原理及复杂系统理论,对长江近两年的水质情况作定量的综合评价。     

隧道施工水体污染的集对分析及生物测试验证

隧道施工不可避免会造成水体污染,应用集对分析法对隧道施工前后周边水体进行评价,得出各水体受污与否及水体质量的优劣顺序,为施工单位针对性治理污染提供理论依据,同时用生物测试法对集对分析的结果进行验证。     

“雾闪”情况下牵引大电流冲击对京广高铁影响的案例分析

通过对京广高铁雾闪案例介绍,探讨"雾闪"原因及规律,分析"雾闪"对铁路行车设备的危害及造成红光带的原因,提出减少"雾闪"的措施。     

浅议建筑施工企业如何做好节能减排工作

节能减排是国家重视、民众关心的热点问题,建筑施工企业无疑也在寻找一条开展节能减排的佳径。根据工作实践,从节能减排的管理体系、规章制度建设和节能减排与企业管理的融和、项目节能减排工作重点,以及宣传教育、人员素质等方面综合论述了建筑施工企业开展节能减排工作的方式和方法,为施工企业节能增效提供了一个系统的思路。     

船舶油污事故中环境损害的赔偿范围

国际油污赔偿机制下对可予赔偿的“环境损害”是明确的。我国对船舶溢油污染损害的民事赔偿在《民法通则》、《海商法》、《环境保护法》、《海洋环境保护法》中都包含了相关方面的法律规定。结合国内外法律规定，依据平等、国际公约优先、与国际接轨等原则，我国船舶溢油事故中海洋环境损害的赔偿范围应限定在《1992责任公约》所限定的“实际已采取或行将采取的合理复原措施的费用”。     

控制公路环境污染,提高公路运营质量

从当前公路环境保护的主要任务出发,提出了控制公路环境污染的四项措施。     

基于S7-200 PLC和TP170A的船舶中央空调综合控制系统的实现

本文利用S7-200PLC实现船舶中央空调的综合控制和管理，对制冷压缩机进行有级能量调节，温度和湿度实现PID和PWM控制，达到了节能和操作方便的效果。     

船舶造成空气污染成因分析及对策研究

近年空气质量不断恶化,控制气体污染成为社会关注焦点。船舶排放已成为了第三大空气污染源,仅次于工业气体排放和机动车尾气。据测算,1艘中型集装箱船使用普通燃料（含硫量为3.5%）航行1天,其排放量等于50万辆货车。国际海事组织加强对船舶造成大气污染的控制,2005年5月19日起实施《防止船舶造成空气污染规则》。2016年1月,我国在珠三角、长三角、环渤海水域设立3个船舶排放控制区。本文主要分析船舶造成大气污染的原因,探寻较少排放污染的方法。     

A methodology for identifying similar days in air traffic flow management initiative planning

This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.     

Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand

This paper proposes a novel short/medium-term prediction method for aviation emissions distribution in en route airspace. An en route traffic demand model characterizing both the dynamics and the fluctuation of the actual traffic demand is developed, based on which the variation and the uncertainty of the short/medium-term traffic growth are predicted. Building on the demand forecast the Boeing Fuel Flow Method 2 is applied to estimate the fuel consumption and the resulting aviation emissions in the en route airspace. Based on the traffic demand prediction and the en route emissions estimation, an aviation emissions prediction model is built, which can be used to forecast the generation of en route emissions with uncertainty limits. The developed method is applied to a real data set from Hefei Area Control Center for the en route emission prediction in the next 5 years, with time granularities of both months and years. To validate the uncertainty limits associated with the emission prediction, this paper also presents the prediction results based on future traffic demand derived from the regression model widely adopted by FAA and Eurocontrol. The analysis of the case study shows that the proposed method can characterize well the dynamics and the fluctuation of the en route emissions, thereby providing satisfactory prediction results with appropriate uncertainty limits. The prediction results show a gradual growth at an average annual rate of 7.74%, and the monthly prediction results reveal distinct fluctuation patterns in the growth.