液液萃取—GC-MS法同时测定石化废水中双酚A和邻苯二甲酸二乙酯

建立了液液萃取（LLE）—气相色谱-质谱（GC-MS）法同时测定石化废水中双酚A（BPA）和邻苯二甲酸二乙酯（DEP）的新方法,对液液萃取条件进行了优化。最佳的液液萃取条件为：萃取剂为乙酸乙酯,水样调成酸性（pH<2）,每次加入萃取剂0.1 mL/mL、盐析剂NaCl 0.1 g/mL,萃取次数为6次,每次萃取时间为2 min。实验结果表明：在质量浓度1~100 mg/L的范围内,BPA和DEP测定标准曲线的线性关系良好;BPA和DEP的检出限（LOD）分别为5.18 μg/L和0.89 μg/L,定量限（LOQ）分别为17.11 μg/L和2.96 μg/L,回收率为81.4 %~124.9 %,相对标准偏差（RSD）（n=7）小于5.5 %。     

二氧化硫光谱检测技术

介绍了二氧化硫的性质,综述了紫外荧光分析检测技术、长程吸收光谱检测技术、激光红外吸收检测技术和遥感傅里叶变换红外光谱检测技术的原理及在二氧化硫检测中的应用。     

多管发酵法与其改进法检测水中粪大肠菌群的比较

粪大肠菌群是水体中粪便污染的重要指示菌,对于评价水质污染程度具有重要的卫生学意义。多管发酵法是传统的粪大肠菌群检测方法,但其步骤繁杂、周期长。目前,已有部分监测及科研人员对其进行了改进,笔者采用改进法与国标多管发酵法进行比较验证,认为Ec培养法可完全替代国标多管发酵法,纸片法亦可用于除酸性水样及菌量大的原污水外的其他环境水样中粪大肠菌群的检测。     

Tipping Points in the Arctic: Eyeballing or Statistical Significance?

Arctic ecosystems have experienced and are projected to experience continued large increases in temperature and declines in sea ice cover. It has been hypothesized that small changes in ecosystem drivers can fundamentally alter ecosystem functioning, and that this might be particularly pronounced for Arctic ecosystems. We present a suite of simple statistical analyses to identify changes in the statistical properties of data, emphasizing that changes in the standard error should be considered in addition to changes in mean properties. The methods are exemplified using sea ice extent, and suggest that the loss rate of sea ice accelerated by factor of ~5 in 1996, as reported in other studies, but increases in random fluctuations, as an early warning signal, were observed already in 1990. We recommend to employ the proposed methods more systematically for analyzing tipping points to document effects of climate change in the Arctic.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

Drowsiness and distraction while driving: A study based on smartphone app data

Introduction: Due to the negative impact on road safety from driver drowsiness and distraction, several studies have been conducted, usually under driving simulator and naturalistic conditions. Nevertheless, emerging technologies offer the opportunity to explore novel data. The present study explores retrospective data, which was gathered by an app designed to monitor the driver, which is available to any driver owning a smartphone. Method: Drowsiness and distraction alerts emitted during the journey were aggregated by continuous driving (called sub-journey). The data include 273 drivers who made 634 sub-journeys. Two binary logit models were used separately to analyze the probability of a drowsiness and distraction event occurring. Variables describing the continuous driving time (sub-journey time), the journey time (a set of sub-journeys), the number of breaks, the breaking duration time and the first sub-journey (categorical variable) were included. Additionally, categorical variables representing the gender and age of the drivers were also incorporated. Results: Despite the limitations of the retrospective data, interesting findings were obtained. The results indicate that the main risk factor of inattention is driving continuously (i.e., without stopping), but it is irrelevant whether the stop is long or short as well as the total time spent on the journey. The probability of distraction events occurring during the journey is higher than drowsiness events. Yet, the impact of increasing the driving time of the journey and stopping during the journey on the probability of drowsiness is higher than the probability of distraction. Additionally, this study reveals that the elderly are more prone to drowsiness. The data also include a group of drivers, who did not provide information on gender and age, who were found to be associated to drowsiness and distraction risk. Conclusions: The study shows that data gathered by an app have the potential to contribute to investigating drowsiness and distraction. Practical applications: Drivers are highly recommended to frequently stop during the journey, even for a short period of time to prevent drowsiness and distraction.     

高层建筑逃生缓降器中外技术标准比对与应用研究

为提升应急疏散逃生成功率,完善我国逃生救援装备标准体系,通过对比分析国内外技术标准中逃生缓降器及逃生绳索的强度、负荷性能、下降速度、工作温度指标,以及实验测试应急救援情景下的产品安全性能等,开展逃生缓降器关键性能指标对标研究。结果表明:我国逃生缓降器产品标准在复杂情况应对方面具有一定科学性和先进性,但逃生绳的耐高温及整机超温锁死等可靠性指标有待完善。建议整合相关标准条款统一技术要求,构建产品、建筑及应用情景相结合的部品化发展路径,通过微观层面的产品标准化、中观层面的部品化和宏观层面的有效统筹,支撑我国逃生救援装备产业发展和质量监管。     

基于稳态模型的井下抽采主管道泄漏检测方法研究*

为准确检测煤矿井下瓦斯抽采主管道泄漏位置,提出基于稳态模型的管道泄漏检测与定位方法,采用Comsol数值模拟及地面相似实验研究压力梯度法对煤矿井下抽采管道泄漏检测与定位的可行性及准确性。研究结果表明:管道未泄漏时,管内沿线压力呈均匀分布,当管道突发泄漏时,管内压力分布呈现明显弯折现象,弯折处即为管道漏点位置,并对管道阻力计算公式进行修正,提高了检测准确性;随着管道泄漏程度的加大,湍流效应显著增强,漏点处速度、压力产生明显突变,且当其他条件恒定时,随着管道泄漏孔径的扩大,管道的漏入量越大,定位的相对误差越小;在宏岩矿开展地面相似实验,实验结果绝对误差为4.5 m,相对误差为6%;在阳煤五矿井下8421抽采巷进行现场应用,绝对误差134 m,相对误差约7.95%。     

基于高分遥感的危险化学品重大危险源安全布局动态管控研究*

为遏制危险化学品重特大安全事故,解决传统安全监测手段的空间局限性问题,结合高分遥感与数值模拟技术,开展危险化学品重大危险源区域安全布局动态管控研究。利用数值模拟技术模拟并确定危险化学品重大危险源重点管控范围;基于高分遥感影像提出适用于危险化学品重大危险源安全布局动态管控的变化检测方法,动态监测安全防护范围内的建筑、道路等人工构筑物的变化情况,严控事故影响范围内的人工构筑物密度;以内江市隆桥化工为实例开展示范应用。结果表明:高分遥感技术能够高效监测危险化学品重大危险源安全防护范围内的工程建设情况,有助于危险化学品企业保持足够的外部安全防护距离,降低危险化学品重特大安全事故风险。     

探讨环境检测技术存在的问题及相关建议

在现阶段的环境保护领域中,环境检测技术占据了重要地位。各地通过推行环境检测的措施与方式,应当能做到鉴别当地现有的环境污染程度,进而给出可行的环境改善思路。然而截至目前,环境检测领域的各项日常工作并未能真正达到优化与完善的程度,因此亟待予以相应的转型与改进。在此前提下,目前关于环境检测技术需要做到明确现存的各类技术缺陷,据此给出改进现阶段环境检测技术的具体思路。