长江南京以下12.5 m深水航道工程新型筑堤结构

针对长江南京以下12.5 m深水航道二期工程落成洲河段整治建筑物的特点,提出在堤高为3.0~6.5 m的堤段采取倒T型构件混合堤替代抛石斜坡堤的新型筑堤结构。对混合堤结构在波、流共同作用下的稳定性采用翻坝水流力和合田波浪力计算公式进行理论受力分析,并通过三维物理模型试验对波、流共同作用下混合堤结构稳定性进行验证,结果判定为稳定。新型倒T型构件混合堤减少块石用量,有利于缓解大宗石料供应难度,适应环保需求,同时减少水上施工时间,加快施工进度。该结构已成功申请实用新型专利,可为类似工程提供指导和借鉴。     

Planning hierarchical urban transit systems for reductions in greenhouse gas emissions

Public transit systems with high occupancy can reduce greenhouse gas (GHG) emissions relative to low-occupancy transportation modes, but current transit systems have not been designed to reduce environmental impacts. This motivates the study of the benefits of design and operational approaches for reducing the environmental impacts of transit systems. For example, transit agencies may replace level-of-service (LOS) by vehicle miles traveled (VMT) as a criterion in evaluating design and operational changes. In previous work, we explored the unintended consequences of lowering transit LOS on emissions in a single-technology transit system. Herein, we extend the analysis to account for a more realistic case: a transit system with a hierarchical structure (trunk and feeder lines) providing service to a city where demand is elastic. By considering the interactions between the trunk and the feeder systems, we provide a quantitative basis for designing and operating integrated urban transit systems that can reduce GHG emissions and societal costs. We find that highly elastic transit demand may cancel emission reduction potentials resulting from lowering LOS, due to demand shifts to lower occupancy vehicles. However, for mass transit modes, these potentials are still significant. Transit networks with buses, bus rapid transit or light rail as trunk modes should be designed and operated near the cost-optimal point when the demand is highly elastic, while this is not required for metro. We find that the potential for unintended consequences increases with the size of the city. Our results are robust to uncertainties in the costs and emissions parameters.     

长江航道大型整治工程施工安全控制关键技术

长江航道大型整治工程施工河段长、工程量大且工序多,施工水域船舶通航密度大、船舶种类多,施工安全生产控制与河段通航安全面临巨大挑战。依托长江干线下、中、上游典型大型航道整治工程,围绕工程施工全过程风险管控及安全保障技术,采用理论分析、仿真模拟、现场试验、系统研发相结合的方法,提出了长江航道大型整治工程风险识别与评估方法,构建了通航安全与施工生产安全风险预测模型,研究了长江航道大型整治工程全方位、全过程、全要素施工安全保障与控制技术,并基于AIS和云技术开发了长江航道整治工程施工区安全综合信息平台,为保障大型航道整治工程生产及通航安全提供了理论依据和技术手段。     

基于神经网络对电控柴油机运行特性影响因素仿真研究

基于AVL-BOOST软件仿真平台建立某船用四缸柴油机仿真模型,标定后的模型进行柴油机全工况仿真计算.仿真出来的3 200组数据作为人工神经网络输入数据,采用贝叶斯统计方法对网络进行训练建立2层的反馈神经网络仿真模型.并分别通过实验、AVL-BOOST和神经网络数据曲线的对比分析,验证人工神经网络预测的准确性.利用验证好的人工神经网络模型预测进排气压力对柴油机转矩的影响,以及预测压缩比和供油定时对柴油机排放性能和动力性能的影响,最后利用扰动法分析不同工况下柴油机各个参数对柴油机性能的影响程度.     

典型航线船舶排放清单及排放特征研究

文章分析了我国典型航线典型船舶排放特征,以船舶自动识别系统数据为基础,收集整理所选研究船舶排放参数,结合船舶实际航行资料,采用动力法估算了秦皇岛港—广州港航线某散货船一个航行周期的排放清单,并分析了靠港、停泊、港内机动、巡航4个船舶状态下的排放特征,绘制了2 km×2 km分辨率的空间排放特征图。结果表明,该典型航线上典型散货船舶一个航行周期排放的SOx、NOx、PM10、PM2.5总量分别为18.88吨、30.87吨、1.85吨和1.69吨。排放源分析表明从在船舶的主机、辅机和锅炉3种排放源中,主机是主要排放源。航行状态上巡航工况排放量最大;船舶排放污染物的空间分析表明,船舶在进出港口区域是污染物排放最密集的区域。     

长江南京以下深水航道二期工程碍航水道演变特性及航道治理思路

长江南京以下12.5 m深水航道二期工程建设是落实国家"一带一路"战略、打造长江综合立体交通走廊的重大举措。针对二期工程河段4个水道的碍航情况,在分析上游来流来沙特性、各水道分流分沙特性及演化过程的基础上,对碍航特性、河床演变特性及趋势进行分析,提出各水道的整治时机、关键部位和治理思路。成果为航道整治工程设计与建设提供技术支撑,也为感潮河段航道整治积累经验。     

基于多源数据的公交车能耗碳排放测算模型

公交车能耗碳排放强度与车辆、线路和驾驶员有显著相关关系，为精准刻画其能耗碳排放强度特征，整合OBD监测数据、加油(气)数据、运营排班数据等多源数据资源. OBD监测数据和加油(气)数据呈显著的线性关系，证明修正后的OBD监测数据可满足分析要求. 搭建“速度-能耗碳排放强度曲线”测算模型，幂函数关系的拟合优度R2 =0.972 6 为最高. 实证研究发现，平均速度在10~60 km/h 变化时，液化天然气(LNG)车比柴油车能耗碳排放强度高 3.3%~33.7%，双层车比铰接车高2.4%~13.3%；LNG铰接车在不同线路、相同速度下的强度相差9.6%；不同驾驶员在相同线路的能耗碳排放强度可相差24.2%. 模型为各城市基于多源数据开展公交能耗碳排放目标设定提供数据支撑.     

Did Chinese cities that implemented driving restrictions see reductions in PM10?

Imposing driving restrictions is becoming increasingly popular as a policy intended to control urban air pollution. Existing studies on this topic offer highly mixed observations, and each study tends to focus on only one city. In this paper, we used 11 Chinese cities with driving restrictions as the treatment group, and compared them to other cities that did not implement the policy. Based on a propensity score matching and difference-in-difference analysis, we found no evidence of a decrease in PM10 concentrations in cities after they implemented driving restrictions. This finding may be attributed to an increase in the number of cars in these cities after implementing driving restrictions, but we also found no evidence of an improvement in air quality for a given number of cars after implementation of the policies.     

Efficiency evaluation and PM emission reallocation of China ports based on improved DEA models

The emission of particulate matter (PM) and other atmospheric pollutants in port operations and shipping have caused a huge negative impact on the environment. Consequently, how to evaluate the environmental efficiency of ports and put forward corresponding countermeasures on this basis is becoming a more important issue than ever before from the perspectives of the government, academia, and society. We construct three data envelopment analysis (DEA) models to evaluate the environmental efficiency of ports under the circumstances of environmental control, non-environmental control and PM emission through inter-ports cooperation. The innovation of the DEA models constructed in this paper lies in: (1) Setting environmental control parameters to uniformly manipulate the situations of environmental control and non-environmental control, etc.; (2) Allowing non-equal proportional change of input index, expected output and non-expected output index; (3) Setting preference coefficients for ports to admit favorable decisions; (4) Providing a distance formula of expected output for PM emission reallocation. Further, data from 11 major ports in China are collected to compare the expected output under different PM emission standards assuming the situation of environmental control and non-environmental control, port cooperation, and non-cooperative sewage discharge. The empirical results show that: (1) Ports in the eastern China (Shanghai, Ningbo, and Nanjing) have higher port efficiency; (2) Port cooperation can improve the overall expected output but it will lose its edge with the improvement of PM emission standards. (3) Ports follow the same trend of output loss regardless of favorable decisions. In the end, the author makes a summary, puts forward relevant policy suggestions and makes the recommendation for future research.     

Shaping the Coast with Permits: Making the State Regulatory Permitting Process Transparent with Text Mining

This paper examines the California Coastal Commission's permitting process. Using several text mining techniques, including web scraping, information extraction, and supervised classification, I demonstrate how to retrieve empirical data from unstructured texts, namely public meeting agendas and staff reports. Contrary to the concern that the Commission routinely delays or rejects permitting requests, the data reveal that outright rejection of permit applications is rare. On average, eight of ten applications were approved. Single-family homes and commercial development projects were approved about 80% of the time; the rates were about 70% for seawalls and retaining walls, and 60% for land-use changes. Most applications were processed swiftly, with a median application length of 3 months. The agency's influence comes primarily from negotiating each application. Qualitative study of 50 cases pertaining to single-family home construction reveals that the agency adopts a “managed development” approach, that is, allowing development but scrupulously managing various aspects of development. These case studies illustrate how the agency interprets the broad, abstract state laws and translates the mandates into enforceable actions as permitting conditions. In areas where the state mandates conflict, particularly over development in receding shorelines, the agency has the largest leverage in creating and implementing its preferred policies. The text mining techniques demonstrated in this paper can be applied to study any governmental agency. These techniques help to extract information from a massive volume of papers and organize them into a database for analyses. The empirical data extracted from texts can significantly increase bureaucratic transparency.