黄海海域水质现状与趋势评价

根据污染监测资料和评价结果，我国黄海近海海域水质状况良好，但是河口、海湾等海区遭到污染，个别海区污染较重。主要污染物质是无机氮、无机磷、油类。大部分海域污染呈逐年减轻的态势，个别海区污染有加重的趋势。由于黄海涡岸流的作用，污染仅限于我国近岸海域，一般不会影响邻国的海水水质。     

南黄海鯷鱼产卵场大型底栖生物次级生产力研究

根据2001至2003年南黄海鯷鱼产卵期在鯷鱼产卵场33个站考察采集的大型底栖生物定量样品资料，利用Brey’s(1990)的经验公式对调查海区进行了大型底栖生物栖息密度、生物量、次级生产力和P/B值的研究计算，结果表明，该海域大型底栖生物平均栖息密度为194．3ind．m^-2，平均生物量以去灰干重计，为4．08gm^-2，平均次级生产力以去灰干重计，为4．09gm^-2a^-1，研究表明，生物量和次级生产力受水深的影响，平均P／B值在研究海域为1．32a^-1，对研究结果与整个南黄海、渤海和东海的结果进行了比较与讨论，证明生产力随水深的加大而降低，P／日值随水漏升高而升高，图2表1参25     

武汉市东西湖农场表层土壤中多环芳烃的含量分布特征

对武汉市东西湖农场土壤中多环芳烃的含量调查表明,除紧靠马路边、居民区的土壤中多环芳烃的浓度高于荷兰制定的土壤修复标准之外,其余地方均在此标准值之内,其中主要是高环多环芳烃含量超标严重。证明了汽车尾气所排放的多环芳烃要高于居民日常生活的排放量。多环芳烃在水平方向上的迁移存在色谱效应。     

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.     

黄河三角洲不同类型湿地土壤盐分的剖面分异特征

为探究高强度人为干扰是否改变滨海湿地土壤盐分的剖面特征,采集黄河三角洲典型自然湿地和人为干扰湿地不同植物群落下的土壤剖面样品,进行实验室测定。运用单因素方差分析、非参数检验、聚类分析等方法,对土壤剖面含盐量及理化性状进行统计分析。结果显示：由陆向海湿地土壤从轻度盐渍化向盐土过渡,盐分剖面特征受人为活动影响显著,同时人为影响因植被类型而异。总体而言,人为干扰湿地土壤盐渍化程度高于自然湿地。土壤盐分剖面类型可划分为表聚型、震荡型和均匀型三种,空间上由海向陆土壤盐分剖面类型由表聚型、震荡型向均匀型转变。人为干扰湿地中的柽柳（Tamarix chinensis）群落和裸地土壤盐分表聚特征明显,属于表聚型剖面,表聚系数为63%,均匀型剖面占比最高,达到2/3。当地人为筑坝修路等建设活动,通过直接阻断或改变地形等方式削弱了湿地潮汐的水文连通过程,进而改变土壤含水率、容重等生境要素,可能成为影响盐分剖面特征的重要因素。通过闸阀调控、生态补水工程等水文连通恢复措施,改善湿地土壤盐碱化问题,有助于推动黄河三角洲滨海湿地的可持续发展与管理。     

黄河口盐沼湿地盐地碱蓬和互花米草凋落物的分解特征

凋落物分解在湿地生态系统中扮演重要的角色。为探索潮汐梯度下凋落物分解过程中质量和营养元素变化情况,采用分解袋的方法,选择盐地碱蓬（Suaeda salsa）和互花米草（Spartina alterniflora）凋落物作为研究对象,沿着潮汐梯度开展凋落物分解的野外实验。结果表明：凋落物分解速率与凋落物类型、土壤盐度、含水率以及潮汐干扰强弱有关;潮汐干扰强的区域互花米草分解快于盐地碱蓬,潮汐干扰弱的区域盐地碱蓬分解快于互花米草,两种凋落物分解速率在0.00134~0.00234 d^-1之间。分解末期,凋落物都呈现C和N的净释放,盐地碱蓬凋落物平均释放了36.9%的C和55.8%的N,互花米草凋落物平均释放了53.1%的C和47.1%的N。本研究强调关注潮汐梯度下的凋落物分解,其在调节生物地球化学循环以及碳累积上具有重要意义。     

调水和季节变化对河流沉积物古菌群落的影响

采用高通量测序方法分析了汾河引黄河段沉积物中古菌群落的组成、相对丰度、多样性,及其与环境因子之间的相关性,揭示引黄调水和季节变化对古菌群落结构的影响.结果表明：冬季时水体SO₄^2-、Cl^-、Na⁺、K⁺等离子浓度、EC、TDS （总溶解固体含量）、沉积物碱解氮和速效磷含量是影响古菌群落结构的主要环境因子,夏季时沉积物pH值、有机质和速效磷含量是主要环境因子.黄河水汇入后河流沉积物中出现了上游未检测到的古菌类群,如TMEG （norank_f_Terrestrial_Miscellaneous_Group）、洛基古菌等.引黄还可以使甲烷杆菌和海洋古菌等在不适宜其生存的时期活跃起来,丰度明显增加.冬季引黄河段古菌数量增加,多样性提高,夏季则相反.季节变化改变了古菌群落的空间相似关系,然而引黄的贡献较季节变化大.研究河段沉积物中古菌群落组成丰富,包含多种至今未被分类定义的古菌.     

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.     

Investigating the effects of monthly weather variations on Connecticut freeway crashes from 2011 to 2015

IntroductionThe objective of this research is to investigate the effects of monthly weather conditions on traffic crash experience on freeways, considering the interactions between weather, traffic volumes, and roadway conditions. Methods: Data from the state of Connecticut from 2011to 2015 were used. Random parameters negative binomial models with first-order, autoregressive covariance were estimated for representative types of freeway crashes (front-to-rear, sideswipe-same-direction, and fixed-object), most severe crashes (i.e., fatal and injury crashes), and non-injury crashes (i.e., property-damage-only crashes). Results: Major findings are that variations in monthly traffic volumes, roadway geometry, and weather conditions explain much of the variations in monthly traffic crashes. Time effects exist in the panel monthly data for all types of crashes. Taking into account this effect improves model prediction results. When the raw weather measures are highly correlated, using dimension reduction techniques helps to extract more interpretable weather factors. By considering the interaction effects between roadway condition variables, additional findings were found. In general, lower temperature, more heavy fog days, decreased precipitation, lower wind speed, higher monthly traffic volumes, and narrower inside shoulder were found to be associated with higher monthly crashes. The effects of area type and outside shoulder width change dramatically as the number of through lanes changes. Practical applications: The findings of this research could help researchers and general readers gain a better understanding of the effects of monthly weather conditions and other roadway factors on freeway crashes and give engineers practical guidelines on improving freeway safety.