多氯联苯醚类化合物污染研究进展

综述了当前国际上多氯联苯醚的研究现状,详细论述了环境中多氯联苯醚的来源、毒性效应、污染状况、迁移转化和生物富集规律以及多氯联苯醚形成机制.我国关于多氯联苯醚类污染物的研究相对滞后,当前开展适合我国国情的多氯联苯醚物质的环境水平、生态安全与毒理学研究十分必要.     

基于改进灰色模型的管壁蜡沉积厚度预测研究

为对含蜡原油管道中的蜡沉积厚度进行准确预测,在函数cot(x2)变换的基础上,结合平移变换思想,利用cot(x2+c)变换建立新的改进GM(1,1)模型。以现场管道结蜡数据和室内环道结蜡数据为例,对比改进GM(1,1)模型、基于函数cot(x2)变换建立的GM(1,1)模型及传统GM(1,1)模型之间的预测精度,并分析平移量c对改进GM(1,1)模型预测精度的影响。结果表明:改进GM(1,1)模型的预测精度最高,其次是基于函数cot(x2)变换建立的GM(1,1)模型,而传统GM(1,1)模型的预测精度最低;随着平移量的增大,改进GM(1,1)模型的平均相对预测误差呈现出先减小后增大的趋势,因此合理的平移量有助于模型精度的提高。应用改进GM(1,1)模型来预测管道蜡沉积厚度是可行的,该方法可为含蜡原油管道蜡沉积厚度的准确预测提供参考和借鉴。     

石油加工过程硫转移分布及风险分析

以典型高硫原油加工炼厂为研究对象,选取常减压蒸馏装置、加氢处理装置、延迟焦化、催化裂化等硫化物处理量较大的装置进行硫转移分析,研究石油加工过程中硫迁移分布规律;以硫迁移分布规律为基础,结合各装置中硫的类型分布,分析各装置存在的主要风险,并提出控制建议,为各装置的风险管理提供依据。     

H∞ loop-shaping controller design for a grid-connected single-phase photovoltaic system

This paper presents a H_∞ loop-shaping controller for controlling dc-link voltage by regulating the switching signal of the inverter associated with a grid-connected single-phase photovoltaic system. To facilitate a robust control design, state-space realisation of the system model is made with uncertainties represented by linear fractional transformation. The controller is achieved through H_∞ synthesis followed by obtaining desired loop shapes through the choice of the proper weighting functions. The controller order is reduced by Henkel-norm method for facilitating its practical implementation. Controller performance is evaluated through carrying out simulations on MATLAB/Simulink platform under standard and changing atmospheric conditions, and fault condition.     

岩溶环境对多环芳烃迁移转化的影响

从水文地质条件、地貌环境和地球化学环境等3个方面,综述了岩溶环境对多环芳烃(PAHs)迁移转化的影响。针对研究现状及存在的不足,提出了未来可能的研究趋势,包括不同气候条件下发育的岩溶系统的对比研究、不同气候条件和不同岩溶系统快速流和慢速流对PAHs迁移的贡献、碳酸盐岩与PAHs相互作用的机理,以及有机质对PAHs迁移行为的影响。     

工业搬迁区绿化带土壤铜污染及其在植物体内的迁移

老工业搬迁区主要道路两旁绿化带土壤由于历经老工业企业的变迁和环境的污染破坏,可在一定程度上对这一地区环境的历史变迁及重金属污染状况起到指示作用。采集沈阳铁西老工业搬迁区绿化带土壤及其绿化乔木和灌木植株样品,分析土壤中铜的总量及生物有效态含量,同时分别分析了绿化乔木(8种)和绿化灌木(6种)植株根、枝条和叶片的含铜量。结果表明,搬迁区绿化带土壤中含铜量为29.14~166.95mg/kg,显著高于沈阳市土壤铜元素的背景值;土壤有效态铜为0.23~1.72mg/kg,达到中等水平(0.3~1.0mg/kg)的占采样点总数的70.0%。数据还显示,绿化乔木和灌木对铜的蓄积能力依品种不同差异显著,同种植物不同部位(根、枝条和叶片)对铜的富集能力不同;总体上,绿化乔木植株体内含铜量的分布规律为根叶片枝条或叶片根枝条,绿化灌木植株体内含铜量的分布规律为根叶片枝条。对铜蓄积能力较强的绿化乔木为榆叶梅(Amygdalus triloba Lindl.)、垂柳(Salix babylonica Linn.)、旱柳(Salix matsudana Koidz.)和银杏(Ginkgo biloba),对铜蓄积能力较强的绿化灌木为大叶女贞(Ligustrum lucidum Ait.)、小叶女贞(Ligustrum quihoui Carr.)和紫叶小檗(Berberis thunbergii cv.Atropurpurea)。     

珠三角地区大气PM_(2.5)理化特性季节规律与成因

基于珠三角大气超级站2013年8月至2014年3月PM2.5、PM2.5中主要水溶性无机离子组分及其重要气态前体物等参数的逐时在线监测结果,揭示当地大气PM2.5中二次无机组分与其气态前体物的相互作用,以及PM2.5理化特性与成因的季节差异。结果表明,观测期间,PM2.5、PM10的年平均质量浓度分别为64.2、105.1μg/m3,PM2.5在PM10中所占比例(PM2.5/PM10)平均为61.1%。SO2-4、NO-3、NH+4的年平均质量浓度分别为16.6、9.0、10.2μg/m3,3者之和(SNA)占PM2.5的比例(SNA/PM2.5)平均为55.8%,体现了二次转化对珠三角地区PM2.5污染的重要影响;不同季节,SNA/PM2.5为46.0%~64.3%,夏季最低,冬季最高,其中SO2-4、NH+4对PM2.5的贡献相对稳定,NO-3贡献的季节差异较大;秋、冬季各项观测参数浓度的日变化规律相对明显,夏季除HNO3和NH3外,多项观测参数在低浓度水平波动,日变化规律不明显;珠三角大气中具有足量气态NH3以中和硫酸盐和硝酸盐,PM2.5中NH+4、SO2-4、NO-3主要以(NH4)2SO4和NH4NO3形式存在;本研究站点夏季的硫氧化率和氮氧化率均高于广州市,这充分体现了该站点的区域性特征。     

Geogenic Distribution of Arsenic (As) and Antimony (Sb) in Soils of the Murcia Region in Spain

The objective of this study was to determine the As and Sb contents in soils from the Murcia Region of Spain and the possible relationship between the mineralogical composition, soil properties, and As and Sb concentrations. In this study, 490 samples were selected from areas with different characteristics in order to study As and Sb variability. Results show that As and Sb concentrations are positively correlated with the phyllosilicate and quartz content but negatively correlated with the calcite content. The generic reference level (GRL) for these elements was determined according to the Spanish legislation. Established GRL values vary according to the established mineralogical groups, suggesting that GRL has to be determined considering the lithological characteristics of the study area.     

Technological innovation paths toward green industry in China

With the environmental carrying capacity reaching its limits and the decreasing margin benefits of traditional production factors, the green transformation and green development through technological innovations has been a major direction for the future development of Chinese industries. However, the characteristics and heterogeneities of various types of industries call for different approaches regarding technological innovations. How to choose the most effective mode of technological innovation according to the characteristics of a certain industry has been a key issue. This paper measures the green total factor productivity of 32 industrial trades using the Slacks Based Measure(SBM)-DDF method. The effects of three innovation modes in the green transformation of industrial industry, including the independent innovation(Ⅱ), the technology introduction(TI), and the government support(GS), are empirically analyzed based on industry heterogeneity. Results indicate that the green total factor productivities of different industries show significant differences if taking into account the energy input and the undesirable output of pollutant emissions. The green total factor productivities of traditional high input,high pollution, and high energy consumption industrial trades were significantly lower than those with obvious green features. The year of 2009 is a leap year for the industrial green transformation in China. For resource-intensive industries, the II and the GS are the important ways to achieve green transformation. For labor-intensive industries, the TI is the best path to achieve green transformation, while for technology-intensive industries, the II is the primary driving force for the promotion of green developments. In addition, the innovation-compensating effect of the current Chinese environmental regulations to the resource-intensive industries has been revealed. Improving the overall scale and the industrial concentration of the industries is also beneficial for the green transformation of the industries.     

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.