Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

我国汽车金融业的发展现状及趋势展望

首先分析了国内外汽车金融业的发展状况，并从当前我国汽车金融业存在的问题入手，着重从内部和外部环境2个方面进行了分析，从而有针对性地提出了我国汽车金融服务的改革思路和解决相关问题的政策建议，并对未来发展趋势作出理性预测和判断，制度设计上更趋于合理、完善；服务质量和水平逐步与国际接轨；竞争推动下的具有中国特色的金融创新渐趋活跃。在此基础上笔者设想了一种银行一体化的营销模式，权当为未来银行汽车金融业务的开展作一有益尝试。     

风积沙的毛细性及其盐胀的室内试验研究

通过毛细水上升高度试验，得出了风积沙在最佳含水量、不同压实度条件下的毛细水上升高度数据；通过室内盐胀试验得到了不同含盐量风积沙的盐胀量，并分析了含盐量及温度与盐胀量的关系。     

Hierarchal assessment of noise pollution in urban areas – A case study

Noise pollution in urban areas has many harmful effects on the citizens. There are varieties of noise generation sources of which the traffic noise could be a major source. The point which is perhaps less noticed is that sound level is not the only parameter to indicate the extent and intensity of noise pollution. Situation of urban land uses, distribution of population centers and types of passages can deeply affect the concern on this environmental issue but not with a similar ratio. This article presents an overlaying technique to define noise prone areas using all different factors involved. A case study was carried out in the District 14 of Tehran Metropolitan City where there are busy streets and highways. For this purpose, the share of each criterion in noise pollution intensity was determined using Analytical Hierarchy Process (AHP). Afterwards, the map layers were overlaid based upon the relative importance of the criteria to get the final map on which the noise prone areas are specified. The developed method could be used as a tool for indirect estimation of noise pollution by which instead of direct measurement of the equivalent sound level, it would be possible to predict noise susceptible areas considering the most important influential factors.     

Congestion and pollution consequences of driving-to-school trips: A case study in Beijing

Parents compete for high-quality education for their children by enrolling them in good schools. However, in a Chinese mega-city like Beijing, three factors jointly lead to the spatial separation between schools and homes: the centralized public goods provision mechanism, the historical dependency in school location, and the constrained supply of housing in downtown. Without an adequate number of school buses, this spatial separation of schools and homes triggers the numerous long-distance driving-to-school trips by private vehicle during workday morning rush hours in Beijing. We use the start and end dates of “school holiday” as exogenous repeated shocks to the aggregate traffic congestion, and employ the two-stage least squares (2SLS) regression approach to examine the congestion and pollution consequences of such driving-to-school trips in Beijing. We find that, all else being equal, workdays during school holidays have a traffic congestion index 20% lower than that of non-school-holiday workdays. Such a sharp reduction in congestion leads to a significant decrease in PM₁₀ concentration. Policymakers should lower such “extra” congestion and environmental costs via optimizing the spatial balance between school supply and demand.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

中韩船舶油污损害赔偿制度的比较

韩国不论是从地理位置还是经济贸易往来,对于我国是很重要的邻国.由于海上运输的国际性,我国的船东有在该国卷入油污损害赔偿案件的可能,研究其油污损害赔偿制度能够更好的保护我国船东的权益,而且对于我国完善油污民事赔偿立法有一定的借鉴作用.本篇论文比较了中韩油污损害赔偿制度,并对完善我国油污损害赔偿制度提出几点建议.     

我国商业银行信息化建设研究综述

我国商业银行信息化建设已走过近20年的路程,在取得巨大业绩的同时也存在若干不足之处．文章在总结我国商业银行信息化建设经验的基础上,对其信息化建设的现状进行了深入的分析,同时指出了我国商业银行信息化建设的总体规划方向,以期大幅度提高我国商业银行的信息化建设绩效。     

汽车运动噪声研究现状及展望

随着汽车运动速度的提高及汽车日益轻量化,汽车的车内外运动噪声越来越严重,影响行车的安全性、舒适性、动力性和经济性,也干扰其它车辆的行驶和附近居民的正常生活,其研究具有重要意义。分析引起运动噪声的主要噪声源,概述其形成机理,介绍其研究现状及方法,并对其发展进行展望。     

新常态下工业4.0对我国汽车产业转型升级的启示

阐述了工业4.0的内涵和目的,分析了当前我国汽车产业发展面临的重大挑战,提出了新常态下借鉴工业4.0,加快我国汽车产业转型升级的几点启示。