机动车尾气中颗粒物对人体健康的危害

本文介绍了燃油机动车在不同运行状况下排放颗粒物的情况;以及不同粒径颗粒物与其它环境空气中污染物协同作用对人体健康的危害.     

简化活性污泥数学模型的优化

为了从控制运行的角度促进简化数学模型的应用，必须借助其它优化手段进一步提高预测精度。本文主要介绍了应用于简化数学模型的扩展卡尔曼滤波、神经网络和误差反馈系统三种优化方法以及优化后的验证结果。从验证结果来看，优化的ROM模型与ASMl模型的定性变化行为相似，基于神经网络的复合模型对PO4^3-和NOx^-的预测结果非常准确，误差反馈的优化系统模拟性能良好。     

装甲车辆环境适应性论证与试验决策支持系统的初步构想

从装甲车辆环境适应性论证与试验决策需求出发,讨论了决策支持系统组成架构,提出了决策支持系统的基本功能,分析比较了决策支持系统与传统的信息处理系统之间的差异,在明确决策支持系统的基本特征的基础上,粗线条勾画了决策支持系统的基本方案。     

The SITES reserve selection system: A critical review

Numerous models have been put forth to help with the growing demand for the establishment of biodiversity reserves. One site selection model that has been used in several recent studies is SITES [S.J. Andelman, I. Ball, F.W. Davis and D.M. Stoms, SITES V 1.0: an analytical toolbox for designing ecoregional conservation portfolios, Unpublished manual prepared for the nature conservancy, 1999, 1–43. (available at )]. SITES includes two heuristic solvers: based on Greedy and Simulated Annealing. We discuss the formulation of the SITES model, present a new formulation for that problem, and solve a number of test problems optimally using off-the-shelf software. We compared our optimal results with the SITES Simulated Annealing heuristic and found that SITES frequently returns significantly suboptimal solutions. Our results add further support to the argument, started by Underhill [L.G. Underhill, Optimal and suboptimal reserve selection algorithms, Biol. Conserv. 70 (1994) 85–87], continuing through Rodrigues and Gaston [A.S.L. Rodrigues and K.J. Gaston, Optimization in reserve selection procedures – why not?, Biol. Conserv. 107 (2002) 123–129], for greater integration of optimal methods in the reserve design/selection literature.     

Modelling of Motor Vehicle Fuel Consumption and Emissions Using a Power-Based Model

The performance of a power based fuel consumption and exhaust emissions model for spark ignition vehicles has been evaluated using a large Australian database derived from testing a wide range of in-use cars on a chassis dynamometer. It was also applied to results of on-road fuel consumption measurement using a "floating" car which was driven back and forth on hilly roadways in Sydney with a length of 8.6 km. The model is found to predict the fuel consumption well over the standard drive cycles and also for the floating car. Average exhaust emissions were also well predicted, but, as would be expected, vehicle-to-vehicle correlation is impossible due to the well-known high variability of emissions between nominally identical vehicles.     

缸内直喷汽油车颗粒物排放特征及影响因素

随着经济的发展,机动车排放已成为大气颗粒物的重要来源,能够影响人类健康和气候变化.本研究通过整车转鼓实验对国V缸内直喷（GDI）汽油车的颗粒物排放水平及化学组成进行了研究,并探究了汽油车颗粒物排放的影响因素.研究结果表明,我国GDI汽油车的PM、OC、EC排放因子分别为（43.4±16.2）、（11.0±3.5）及（20.5±8.1）mg·kg^-1,其中EC的排放显著高于同类研究.为探索导致颗粒物排放区别的影响因素,本研究探讨了燃油类型、启动方式和循环设定对汽油车颗粒物排放的影响.结果表明,燃油类型（添加体积分数10%的乙醇与纯汽油）对颗粒物排放影响不大.冷启动会排放更多的颗粒物.同时,循环方式也会影响颗粒物排放,中国工况循环（CLTC）会排放比全球测试循环（WLTC）更多的颗粒物,这可能与我国更多的缓加速情况相关.     

Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

Social consequences associated with the use of various optimization methods in the protection of air quality

The fundamental tactics employed by the EU against air contamination, which are intended to maintain concentrations at a level that does not exceed the permissible values, usually entail considerable expense. To reduce this to a minimum, the procedure of economic optimization of air quality can be applied. When performed for a heavily polluted industrial city, it shows that it is possible to maintain concentrations below the threshold of air quality standards with relatively moderate expenditure. These evaluations also reveal that variations in population density distribution call into question the conventional wisdom that uniform air quality standards provide the best protection against air contamination for a whole region. On the contrary, an optimization that forces a drop in concentration to be evenly spread over the population, without reference to air quality standards, may lead to more efficient protection of human health and make no difference to overall expenditure.     

Sleepy driving and risk of obstructive sleep apnea among truck drivers in Saudi Arabia

Objective: Truck drivers represent a group at a particularly higher risk of motor vehicle accidents (MVAs). Sleepy driving and obstructive sleep apnea (OSA) among truck drivers are major risk factors for MVAs. No study has assessed the prevalence of sleepy driving and risk of OSA among truck drivers in Saudi Arabia. Therefore, this study aimed to assess sleepy driving and risk of OSA among these truck drivers.

Methods: This study included 338 male truck drivers working in Saudi Arabia. A validated questionnaire regarding sleepy driving and OSA was used. The questionnaire included sociodemographic assessment, the Epworth Sleepiness Scale (ESS), the Berlin Questionnaire (BQ), and driving-related items.

Results: The drivers had a mean age of 42.9?±?9.7 years. The majority (94.7%) drove more than 5?h a day. A history of MVAs during the last 6 months was reported by 6.5%. Approximately 95% of the participants reported that they had accidentally fallen asleep at least once while driving over the past 6 months, and 49.7% stated that this had happened more than 5 times during the last 6 months. Based on the BQ score, a high risk of OSA was detected in 29% of the drivers. “Not getting good-quality sleep” (odds ratio [OR]?=?2.89; 95% confidence interval [CI], 1.08–7.75; P = .014) and driving experience from 6 to 10 years (OR = 3.37; 95% CI, 1.28–8.91; P = .034) were the only independent predictors of MVAs in the past 6 months.

Conclusions: Sleepy driving and a high risk of OSA was prevalent among the study population of male truck drivers in Saudi Arabia. Not getting good-quality sleep and driving experience from 6 to 10 years contributes to the accident risk among these truck drivers.