A new approach for biological online testing of stack gas condensate from municipal waste incinerators

A biological testing system for the monitoring of stack gas condensates of municipal waste incinerators has been developed using Euglena gracilis as a test organism. The motility, velocity and cellular form of the organisms were the endpoints, calculated by an image analysis system. All endpoints showed statistically significant changes in a short time when organisms were exposed to samples collected during combustion situations with increased pollutant concentrations. The velocity of the organisms proved to be the most appropriate endpoint. A semi-continuous system with E. gracilis for monitoring stack gas condensate is proposed, which could result in an online system for testing stack gas condensates in the future.     

Effect of Diesel Fuel on Growth of Selected Plant Species

Diesel oil is a complex mixture of hydrocarbons with an average carbon number of C8–C26. The majority of components consist of alkanes, both straight chained and branched and aromatic compounds including mono-, di- and polyaromatic hydrocarbons. Regardless of this complexity, diesel oil can be readily degraded by a number of soil microorganisms making it a likely candidate for bioremediation. The concept of using plants to enhance bioremediation, termed phytoremediation, is a relatively new area of scientific interest. It is particularly applicable to diesel oil contamination as diesel oil generally contaminates the top few metres of soil (surface soil) and contamination is not uniform throughout the site. By encouraging plants to grow on diesel oil contaminated soil, conditions are improved for the microbial degradation of the contaminant. During this study, establishing plants on diesel oil contaminated soil proved difficult. Diesel oil is phytotoxic to plants at relatively low concentrations. At concentrations below this phytotoxic level, the development of plants grown in diesel oil contaminated soil differs greatly from plants grown in uncontaminated soil. Tolerance of plants to diesel oil and ability to germinate in diesel oil contaminated soil varied greatly between plant species as well as within plant species. The broadest differences in germination were seen within the grasses with certain species thriving in low levels of contamination (e.g. Creeping bent) while others were intolerant of diesel oil contamination (e.g. Rough meadow grass). The herbs, legumes and commercial crops screened appeared to be largely unaffected by low levels of diesel oil contamination (25g dieselkg^–1). At the higher level of contamination (50g dieselkg^–1), half of the twenty two plants species screened failed to reach a germination rate equal to 50% of the control rate. Two species of grass failed to germinate at all at this contamination level. Plant species that successfully germinated and grew were studied further to determine the effect of diesel oil contamination on the later stages of plant development. This work investigates the effect of diesel oil on plant growth and development.     

Crash analysis and development of safety performance functions for Florida roads in the framework of the context classification system

Introduction: Safety performance functions (SPF) are employed to predict crash counts at the different roadway elements. Several SPFs were developed for the various roadway elements based on different classifications such as functional classification and area type. Since a more detailed classification of roadway elements leads to more accurate crash predictions, multiple states have developed new classification systems to classify roads based on a comprehensive classification. In Florida, the new roadway context classification system incorporates geographic, demographic, and road characteristics information. Method: In this study, SPFs were developed in the framework of the FDOT roadway context classification system at three levels of modeling, context classification (CC-SPFs), area type (AT-SPFs), and statewide (SW-SPF) levels. Crash and traffic data from 2015-2019 were obtained. Road characteristics and road environment information have also been gathered along Florida roads for the SPF development. Results: The developed SPFs showed that there are several variables that influence the frequency of crashes, such as annual average daily traffic (AADT), signalized intersections and access point densities, speed limit, and shoulder width. However, there are other variables that did not have an influence in crash occurrence such as concrete surface and the presence of bicycle slots. CC-SPFs had the best performance among others. Moreover, network screening to determine the most problematic road segments has been accomplished. The results of the network screening indicated that the most problematic roads in Florida are the suburban commercial and the urban general roads. Practical Applications: This research provides a solid reference for decision-makers regarding crash prediction and safety improvement along Florida roads.     

A meta‐analysis of sleep and work performance: An examination of moderators and mediators

The present study utilizes meta‐analytic techniques to examine the literature on sleep and work performance. In line with previous meta‐analytic research, results indicate that sleep and work performance have a positive relationship. However, more importantly, results from moderator analyses reveal that the type of sleep measurement (sleep quantity and sleep quality), work performance measurement (task performance, organizational citizenship behavior, and counterproductive work behavior), analysis method (between‐person and within‐person), sleep report source (self‐report, other report, and objective), sleep recall window (day, week/month, and more than 1 month), and study setting (field and laboratory) differentially influence the strength of the sleep–work performance relationship. Furthermore, meta‐analytic SEM results indicate that certain mediators (affect, job attitudes, and cognitive resources) provide stronger explanations (i.e., stronger indirect effects) for the relationship between sleep and work performance, depending on the specific type of performance being examined. In general, results highlight the importance of construct operationalization and methodology decisions when conducting sleep–work performance research and provide greater insight into explanations for the relationship between sleep and work performance. Research implications, practical implications, potential limitations, and future directions are also discussed.     

Inclusion of phone use while driving data in predicting distraction-affected crashes

Introduction: Given the tremendous number of lives lost or injured, distracted driving is an important safety area to study. With the widespread use of cellphones, phone use while driving has become the most common distracted driving behavior. Although researchers have developed safety performance functions (SPFs) for various crash types, SPFs for distraction-affected crashes are rarely studied in the literature. One possible reason is the lack of critical distracted behavior information in the commonly used safety data (i.e., roadway inventory, traffic, and crash counts). Recently, the frequency of phone use while driving (referred to as phone use data) is recorded by mobile application companies and has become available to safety researchers. The primary objective of this study is to examine if phone use data can potentially predict distracted-affected crashes. Method: The authors first integrated phone use data with roadway inventory, traffic, and crash data in Texas. Then, the Random Forest (RF) algorithm was applied to assess the significance of the feature - phone use while driving - for predicting the number of distraction-affected crashes on a road segment. Further, this study developed two SPFs for distraction-affected crashes with and without the phone use data, separately. Both SPFs were assessed in terms of model fitting and prediction performances. Results: RF results rank the frequency of phone use as an important factor contributing to the number of distraction-affected crashes. Performance evaluations indicated that the inclusion of phone use data in the SPFs consistently improved both fitting and prediction abilities to predict distracted-affected crashes. Practical Applications: The phone use data provide new insights into the safety analyses of distraction-affected crashes, which cannot be achieved by only using the conventional roadway inventory and crash data. Therefore, safety researchers and practitioners are encouraged to incorporate the emerging data sources in reducing distraction-affected crashes.     

工业安全帽抗冲击性能研究*

为研究安全帽安全性与保护性问题,利用落锤冲击实验,对不同材质安全帽吸能率、冲击力峰值进行研究。结果表明:随冲击能量增加,安全帽受冲击力峰值呈指数倍增长,吸能率呈指数倍下降;ABS树脂与玻璃钢材质安全帽头模受冲击力峰值小于HDPE材质安全帽;当冲击能量大于60 J,HDPE材质安全帽丧失保护功能;ABS安全帽能够承受最大冲击力能量值为70 J,玻璃钢安全帽最大承载力高于ＡＢＳ树脂安全帽。研究结果可为安全帽质量设计提供理论依据。     

基于Meta分析的安全氛围与安全绩效的关系研究*

为更系统地归纳安全氛围与安全绩效的关系,探究安全氛围、安全绩效及安全结果间的影响机制,采用Meta分析方法,通过2000—2020年54篇文献的55个独立研究样本进行定量综合分析,并进一步探讨安全氛围与安全绩效各维度间的关系,同时运用Meta二元回归探究潜在调节变量对2者间关系的调节作用。结果表明:安全氛围显著正向影响安全绩效,在高危行业中安全氛围对安全绩效影响更大;安全氛围与安全参与、安全遵守均显著正相关,且安全氛围对安全参与的影响强于对安全遵守的影响;安全氛围和安全绩效均与安全结果显著负相关,且安全绩效对安全结果的影响强于安全氛围对安全结果的影响。     

贵州百花湖水中溶解有机质的分子量分布随深度的变化规律

利用高效体积排阻色谱法测量了百花湖水中溶解有机质的分子量及其分布。结果表明百花湖水中溶解有机质（DOM）主要以分子量小于3500道尔顿（Da）的组分为主,其中重均（Mw）和数均（Mn）分子量分别界于2300～2500 Da和1900～2150 Da之间,说明其主要来源于降水对土壤有机物的淋滤和径流作用。根据色谱分析的结果,可以把溶解有机质的分子量分布分为四个组分：大分子量组分（MW〉3500 Da）;中等偏大分子量组分（3500～2000 Da）;中等分子量组分（2000～1000 Da）和小分子量组分（MW〈1000 Da）。由于生物活动和光降解作用以及有机物的分解作用,导致各分子量组分随深度的变化规律不同,其中分子量在3500～2000 Da之间的有机物的含量随深度的增大而增大,其余组分的含量随深度的增大而减少。计算所得的溶解有机质的Mw和Mn在表层较小,在中部随深度基本保持不变,到底部又变大。这种变化趋势与分子量组分的变化结果一致。     

混合表面活性剂-浊点萃取法测定沉积物中多环芳烃的含量

以混合型表面活性剂（十二烷基硫酸钠（SDS）和对叔辛基苯基聚己二醇醚（Triton X-114））为萃取剂，采用浊点萃取法萃取沉积物中的15种多环芳烃（PAHs），并利用HPLC技术测定15种PAHs的含量。实验结果表明，当混合型表面活性剂的加入量 3％（w）、混合型表面活性剂中SDS含量 50%（φ）、Na2SO4含量 8％（w）、萃取温度 60 ℃、超声萃取时间 10 min 时，15种PAHs的线性关系良好，r=0.998 9~0.999 7，检出限0.4~8.2 μg/L，加标回收率71.22%~97.36%，相对标准偏差0.92%~4.36%（n=6）。     

3M测试片法在膜法水处理技术中的应用

采用3M测试片法测定膜法水处理系统的细菌总数，找出双膜系统的微生物污染环节，并采用正交实验筛选出适宜的杀菌剂种类、杀菌剂加入量和杀菌时间。实验结果表明：3M测试片法的测定结果数据准确可靠，且操作简便，节省时间，可以替代常规的平皿培养法用于评价膜的微生物污染情况；某炼化公司双膜系统的反渗透膜已受到微生物的污染，确定的适宜杀菌条件为杀菌剂Trsea 380、杀菌剂加入量50 mg/L、杀菌时间2.0 h，在此条件下杀菌率可达100%。