便携式GC-MS仪快速测定水中硝基苯及其在应急监测中的应用

采用便携式GC-MS仪快速测定水中硝基苯,通过优化水中离子强度和顶空加热时间,使方法在0μg/L^300μg/L范围内线性良好,方法检出限为2.5μg/L。标准溶液6次测定结果的RSD为7.8%~10.9%,实际水样的加标回收率为80.7%~103%。同步测定试验表明,硝基苯与7种苯系物分离良好。与国标方法对比,该方法单个样品测定时间由2 h缩短为15 min。将该方法用于应急监测工作中,及时有效的数据可为污水处理及事故调查提供分析和研判依据。     

基于火探管式的锂离子电池灭火技术研究

为研究锂离子电池灭火方案,基于火探管灭火技术同时利用新型清洁灭火剂Novec 1230,组装成火探管灭火系统。在灭火测试平台上以功率为200 W的电热管作为外热源引发单电池或电池模组热失控,通过改变火探管的布置位置,记录相应的灭火行为以及灭火效率,并对实验结果进行了分析。研究结果表明,当火探管灭火系统直接布置在电池正上方时,在起火后的5.6s内控制火情;随着灭火剂用量增加可以显著降低体系温度,防止电池复燃以及连锁热失控现象发生;火探管有效覆盖区域外的失控电池作为热源将继续加热临近电池,引发连锁热失控,造成灭火系统失效;根据电池热失控后的燃烧行为以及传热行为,提出相应的火探管灭火系统复合方案。     

Motorcycle crashes potentially preventable by three crash avoidance technologies on passenger vehicles

Objective: The objective of this study was to identify and quantify the motorcycle crash population that would be potential beneficiaries of 3 crash avoidance technologies recently available on passenger vehicles.

Methods: Two-vehicle crashes between a motorcycle and a passenger vehicle that occurred in the United States during 2011–2015 were classified by type, with consideration of the functionality of 3 classes of passenger vehicle crash avoidance technologies: frontal crash prevention, lane maintenance, and blind spot detection. Results were expressed as the percentage of crashes potentially preventable by each type of technology, based on all known types of 2-vehicle crashes and based on all crashes involving motorcycles.

Results: Frontal crash prevention had the largest potential to prevent 2-vehicle motorcycle crashes with passenger vehicles. The 3 technologies in sum had the potential to prevent 10% of fatal 2-vehicle crashes and 23% of police-reported crashes. However, because 2-vehicle crashes with a passenger vehicle represent fewer than half of all motorcycle crashes, these technologies represent a potential to avoid 4% of all fatal motorcycle crashes and 10% of all police-reported motorcycle crashes.

Discussion: Refining the ability of passenger vehicle crash avoidance systems to detect motorcycles represents an opportunity to improve motorcycle safety. Expanding the capabilities of these technologies represents an even greater opportunity. However, even fully realizing these opportunities can affect only a minority of motorcycle crashes and does not change the need for other motorcycle safety countermeasures such as helmets, universal helmet laws, and antilock braking systems.     

Improving pedestrian safety using combined HOG and Haar partial detection in mobile systems

Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.

Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.

Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.

Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian.     

环境空气自动监测方法检出限相关问题探讨

探讨了环境空气自动监测中实际评估方法检出限的意义,详细介绍了常规气态污染物自动监测方法检出限的评估方法。并以EC 9850型SO2分析仪为例,说明了环境空气自动监测的测定步骤和方法检出限的计算。     

Complex and nonlinear climate-driven changes in freshwater insect communities over 42 years

The ongoing biodiversity crisis becomes evident in the widely observed decline in abundance and diversity of species, profound changes in community structure, and shifts in species’ phenology. Insects are among the most affected groups, with documented decreases in abundance up to 76% in the last 25–30 years in some terrestrial ecosystems. Identifying the underlying drivers is a major obstacle as most ecosystems are affected by multiple stressors simultaneously and in situ measurements of environmental variables are often missing. In our study, we investigated a headwater stream belonging to the most common stream type in Germany located in a nature reserve with no major anthropogenic impacts except climate change. We used the most comprehensive quantitative long-term data set on aquatic insects available, which includes weekly measurements of species-level insect abundance, daily water temperature and stream discharge as well as measurements of additional physicochemical variables for a 42-year period (1969–2010). Overall, water temperature increased by 1.88 °C and discharge patterns changed significantly. These changes were accompanied by an 81.6% decline in insect abundance, but an increase in richness (+8.5%), Shannon diversity (+22.7%), evenness (+22.4%), and interannual turnover (+34%). Moreover, the community's trophic structure and phenology changed: the duration of emergence increased by 15.2 days, whereas the peak of emergence moved 13.4 days earlier. Additionally, we observed short-term fluctuations (<5 years) in almost all metrics as well as complex and nonlinear responses of the community toward climate change that would have been missed by simply using snapshot data or shorter time series. Our results indicate that climate change has already altered biotic communities severely even in protected areas, where no other interacting stressors (pollution, habitat fragmentation, etc.) are present. This is a striking example of the scientific value of comprehensive long-term data in capturing the complex responses of communities toward climate change.     

典型有机磷酸酯阻燃剂分析方法研究进展

有机磷酸酯(OPEs)是一类重要的有机磷阻燃剂,近些年逐渐取代了溴代阻燃剂,广泛应用于各行各业,也因此导致在多种环境介质中有较高的暴露量和潜在风险。已有研究表明,OPEs具有一定的毒理效应,对人体及其他生物均有潜在危害。本文综述了近年来国内外OPEs的检测技术,详述了不同环境介质OPEs的前处理方法。结果表明,目前固相萃取(SPE)和固相微萃取(SPME)仍是水样前处理的主要方法;对于固体样品,加速溶剂萃取/加压液相萃取(ASE/PLE)和微波辅助萃取(MAE)应用较多;虽然大气样品仍以固体吸附剂方式为主,但已向在线一体化方向发展;而生物样品的前处理方法多与水样和固体样品方法相似;但是对于复杂环境介质中OPEs样品的前处理较为困难,方法有待改善;气相色谱-质谱联用(GC-MS)和气相色谱-氮磷检测器(GC-NPD)对弱极性和易挥发的OPEs分析效果好,而强极性和难挥发的OPEs多用液相色谱-质谱联用(LCMS);气相色谱-质谱串联(GC-MS/MS)、液相色谱-质谱串联(LC-MS/MS)和高效液相色谱-质谱串联(UPLC-MS/MS)等对多种复杂的环境介质中的OPEs均有较好的检测分析效果,但并未普及。最后,对OPEs分析测试方法的发展趋势提出了展望。     

两种吹扫捕集浓缩仪在测定土壤VOCs时的性能比较

从仪器精密度、方法检出限、准确度等角度对吹扫捕集浓缩仪Stratum PTC与Eclipse 4660的性能进行比较。结果表明,大部分分析物用Stratum PTC的方法检出限略高于Eclipse 4660,但精密度比Eclipse 4660稍差;Eclipse 4660用于分析极性的、水溶性物质的效果比Stratum PTC好,回收率更高。两种吹扫捕集仪的测试结果均满足《土壤和沉积物挥发性有机物的测定吹扫捕集/气相色谱-质谱法》(HJ 605-2011)标准方法的指标要求。     

PVC电缆火灾早期特征气体的组成分析和传感器探测

利用气体传感器对电缆绝缘过热释放的气体进行监测有望实现电气火灾早期预警,目前该技术的发展由于特征气体未得到确认而受到限制。分析了聚氯乙烯(PVC)电缆绝缘层在不同温度下释放的气体组成,并对其主要成分进行传感器测试。TG-IR和GC-MS分析表明PVC电缆绝缘层在200℃前已出现微小失重,释放出以邻苯二甲酸二辛酯(DOP)等塑化剂为主的气体。气敏测试中,商用半导体气体传感器对DOP和电缆蒸气产生较好、相似的响应性能。因此,DOP可以作为PVC电缆火灾早期的特征气体。     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.