气体质量流量控制器在汽车VOC检测领域的应用

汽车挥发性有机物组分(VOC)检测过程中,充气和采气体积的计量对检测结果的影响尤为突出.通过气体质量流量控制器与目前VOC检测中常用的恒流气体采样装置的比较,表明在同样满足VOC检测标准要求的情况下,气体质量流量控制器在排除环境干扰等方面体现出更好的稳定性,更有利于汽车VOC检测准确度的提高.     

沙尘暴应急监测方法研究

在沙尘暴应急监测方法研究中，通过对总悬浮颗粒物采样仪器及各种采样参数的研究确定和降尘采样器的研制，制定出沙尘暴应急监测方法。     

哈尔滨市大气气相中多环芳烃的研究

在哈尔滨地区8个采样点同时安装了PUF大气被动采样器,研究了该地区2007年春季(1月末~4月末)大气气相中多环芳烃的含量和分布特征.结果表明,PUF大气被动采样器主要采集了大气气相中三环和四环的多环芳烃,占总量的91.22%~96.37%,PAHs的浓度具有明显的功能区差异,依次为:市区(356.49 ng/d),郊区(162.65 ng/d),农村(278.35 ng/d),偏远地区(183.99 ng/d),市区大气中多环芳烃的浓度是农村的2倍,偏远地区的3倍.污染源是影响大气中多环芳烃含量高低的主要因素,通过特征分子含量比值法对该地区大气中多环芳烃的来源进行了初步研究,结果表明,哈尔滨地区城市大气中多环芳烃主要来自于燃煤,农村大气中的多环芳烃主要来自于农作物秸秆的燃烧.利用毒性当量因子法对该地区大气气相中多环芳烃的健康风险进行了评价,具有与浓度分布类似的功能区差异,表明市区和农村地区大气中PAHs对于人们的健康存在较大潜在威胁.通过安装平行采样器,PUF被动采样器具有很好的重现性,研究表明,可以用于城市尺度多个采样点大气中多环芳烃的同时研究.     

顶空气相色谱法测定水中三氯甲烷四氯化碳的参数优化及测定影响因素探讨

本文探讨了如何提高顶空气相色谱法测定三氯甲烷及四氯化碳的灵敏度、精密度与准确度。重点讨论了平衡条件的优化以及带顶空自动进器的气相色谱仪的各个关键参数的优化。     

基于凸形壁面的虚拟冲击式呼吸性粉尘采样器研究*

为研究满足BMRC曲线的呼吸尘采样器,提高呼吸尘采样的准确性,基于虚拟冲击原理,针对隔离主流和弱流通道壁面的形状,提出1种基于虚拟冲击原理的呼吸尘采样器的改进结构,并对不同模型进行模拟仿真实验,利用Ansys Fluent气-固2相流模拟采样器中的流场,对呼吸性粉尘颗粒在流场内的运动轨迹进行跟踪,对仿真得到的呼吸尘分离效能与BMRC曲线的标准进行对比。结果表明:相比采样器原型和主弱流壁面形状为“凹型”,虚拟冲击式呼吸尘采样器主弱流壁面形状为“凸型”时对呼吸尘采样的效果更好,同时分离效能与BMRC曲线的标准差为δ=2.65%,满足偏差小于等于5%的要求。研究结果可为呼吸尘采样器的优化设计提供参考。     

树皮在大气有机氯农药监测中应用的研究进展

有机氯农药（Organochlorine pesticides, OCPs）曾在全世界被大量使用,即使禁用多年,仍能在各种环境介质中被广泛检出,对生态环境和人体健康存在着潜在的威胁。因此OCPs的环境迁移和归趋一直是该领域的研究热点。树皮是一种天然的被动采样器,能够很好的反映出大气有机物长期的污染程度。本文简要论述了树皮作为被动采样器在大气污染物监测研究中应用的优势,并对OCPs在树皮中的残留浓度、特征及影响其富集的因素进行了探讨,最后特别针对具有手性的OCPs在树皮中的对映体选择性特征进行了评述。     

Bayes Estimation of a Distribution Function Using Ranked Set Samples

Aranked set sample (RSS), if not balanced, is simply a sample of independent order statistics gener- ated from the same underlying distribution F. Kvam and Samaniego (1994) derived maximum likelihood estimates of F for a general RSS. In many applications, including some in the environ- mental sciences, prior information about F is available to supplement the data-based inference. In such cases, Bayes estimators should be considered for improved estimation. Bayes estimation (using the squared error loss function) of the unknown distribution function F is investigated with such samples. Additionally, the Bayes generalized maximum likelihood estimator (GMLE) is derived. An iterative scheme based on the EM Algorithm is used to produce the GMLE of F. For the case of squared error loss, simple solutions are uncommon, and a procedure to find the solution to the Bayes estimate using the Gibbs sampler is illustrated. The methods are illustrated with data from the Natural Environmental Research Council of Great Britain (1975), representing water discharge of floods on the Nidd River in Yorkshire, England     

Field Comparison of two NO2 Passive Samplers to Assess Spatial Variation

Two-week average NO₂ concentrations were measured in Amsterdam (NL), Huddersfield (UK) and Prague (CZ) at 80 sites in each study area, to assess small area spatial variation, using a tube type and a badge type passive sampler. The badges appeared to be less robust than the tubes. The lower detection limit for tubes and badges was 3.7 and 0.91 µg/m³, respectively for fortnightly measurements. Accuracy of the samplers was determined with reference methods (chemiluminescence). The mean ratio of the concentration measured by diffusion tube over that by the reference method was 1.16, 1.03 and 0.77 in Amsterdam, Huddersfield and Prague, respectively. Standardizing the badges for the results obtained in Amsterdam, the relative mean ratio of the concentration measured by the badges over that by the reference method was 0.95 and 0.58 in Huddersfield and Prague, respectively. NO₂ concentrations measured by the two designs did not differ significantly. Mean NO₂ concentrations were 36, 26 and 22 µg/m³ in Amsterdam, Huddersfield and Prague, respectively. The precision of duplicate tubes and badges was 8% and 11%, respectively. Both samplers are suitable for determining real variation in small area NO₂ concentrations in the ranges which occurred. It is concluded that low-cost, simple NO₂ passive samplers can provide reliable information about variation in NO₂ concentrations within urban or rural areas on a small spatial scale. Based on its robustness and its precision, tubes were preferred over badges.     

Estimating Air Quality in a Traffic Tunnel Using a Forecasting Combination Model

This study performs a field analysis of the diffusion collection rate coefficients of radial geometry passive samplers to measure NO₂ in a Mediterranean coastal area. The study shows that the collection rate coefficients are not constant and depend on certain environmental parameters as well as on the levels of some co-pollutants. A mathematical model, which explains the variation of the collection rate coefficient, has been established.     

Spatio-Temporal Distribution of Polycyclic Aromatic Hydrocarbons (PAHs) in Atmospheric Air of Tamil Nadu,India, and Human Health Risk Assessment

This study analyzed the seasonal distribution and the possible sources of polycyclic aromatic hydrocarbons (PAHs) in the atmospheric environment of Tamil Nadu, India. Passive air sampling was performed at 32 locations during the period from April 2009 to January 2010, and PAHs were quantified using a gas chromatograph-mass spectrometer. Analysis showed that the concentrations of PAHs were in the range of 5–47.5 ng/m³ with uniform distribution in urban areas in all seasons. Pre-monsoon season showed the highest cumulative concentration of PAHs in both agricultural and coastal areas. Among PAHs, phenanthrene, fluoranthene, and pyrene levels were found to be predominant in all the samples, contributing up to 36%, 35.5%, and 24.5% of total PAHs, respectively. The signature of the PAHs obtained through diagnostic ratio and principal component analysis revealed that diesel emissions was the probable source of PAHs in all locations. Based on Word Health Organization guidelines, the human lung cancer risk due to observed level of PAH concentration (i.e., PAHs exposure) is meager. However, the risk is predicted to be more in the coastal area during summer (18 individuals among 0.1 million people). To the knowledge of these authors, this report is the first on the seasonal analysis of PAHs using passive air sampling in India.