Evidence of coal combustion contribution to ambient VOCs during winter in Beijing

Volatile organic compounds(VOCs)play an important role in ozone and secondary organic aerosol(SOA)formation,but VOCs sources during winter are not fully understood.To investigate VOCs sources during winter,mixing ratios of C2–C12 VOCs were measured at an urban site in Beijing from December 29,2011to January 17,2012.Correlation analysis of toluene to benzene and i-pentane to n-pentane suggest that coal combustion could also be an important source for VOCs besides vehicular emissions.Source apportionment results show that coal combustion and vehicular emissions contributed 28%–39%and31%–45%to ambient VOCs during winter,respectively.Backward trajectory analyses demonstrated that contributions from the burning of coal were higher when air masses came from southern regions outside Beijing.Close attention should be paid to VOCs emissions from coal combustion in Beijing city and the vicinity to the South.     

Determination of volatile organic compounds in urban and industrial air from Tarragona by thermal desorption and gas chromatography-mass spectrometry

This study describes the optimisation of an analytical method to determine 54 volatile organic compounds (VOCs) in air samples by active collection on multisorbent tubes, followed by thermal desorption and gas chromatography-mass spectrometry. Two multisorbent beds, Carbograph 1/Carboxen 1000 and Tenax/Carbograph 1TD, were tested. The latter gave better results, mainly in terms of the peaks that appeared in blank chromatograms. Temperatures, times and flow desorption were optimised. Recoveries were higher than 98.9%, except methylene dichloride, for which the recovery was 74.9%. The method's detection limits were between 0.01 and 1.25 μg m⁻³ for a volume sample of 1200 ml, and the repeatability on analysis of 100 ng of VOCs, expressed as relative standard deviation for n = 3, was lower than 4% for all compounds. Urban and industrial air samples from the Tarragona region were analysed. Benzene, toluene, ethylbenzene and xylenes (BTEX) were found to be the most abundant VOCs in urban air. Total VOCs in urban samples ranged between 18 and 307 μg m⁻³. Methylene chloride, 1,4-dichlorobenzene, chloroform and styrene were the most abundant VOCs in industrial samples, and total VOCs ranged between 19 and 85 μg m⁻³.     

Determination of volatile organic compounds in industrial wastewater plant air emissions by multi-sorbent adsorption and thermal desorption-gas chromatography-mass spectrometry

This paper describes the process of determining the presence of volatile organic compounds in air emissions from industrial wastewater treatment plants (WWTP). The analytical method, based on thermal desorption-gas chromatography-mass spectrometry, was developed to simultaneously determine of 99 volatile organic compounds (VOCs) in air samples. This method is rapid, environmentally-friendly (since no organic solvents are used to extract the analytes) and compatible with a large range of thermally stable polar and apolar compounds. The target VOCs were selected on the basis of their occurrence in real samples and their adverse effects on the environment and human health. To cover the wide range of target compounds, multisorbent tubes filled with Tenax TA and Carbograph 1TD were used. Method validation showed good repeatabilities, low detection limits, a high linear range and good recoveries. At a fixed sample volume of 600?mL no significant losses for any of the target compounds were found in the samples. Stability during storage indicated that samples must be keep refrigerated at 4°C and analysed within three days of collection. Real samples were taken from air emissions of an industrial wastewater treatment plant located in the Southern Industrial Area of Tarragona (Spain) with the aim of studying its contribution as a source of atmospheric VOCs. This WWTP collects wastewater from several chemical factories which produce isocyanates, polyurethanes, chlorinated organics and functional chemicals among other products. Samples from the collecting tank after the primary sedimentation showed higher VOC concentrations than samples from the secondary treatment tank. The most abundant VOCs found in these emissions are included in the USEPA List of Hazardous Air Pollutants. The highest values correspond to acrylonitrile (up to 1843?µg?m^?3) and styrene (up to 573.70?µg?m^?3). The levels of chloroform, 1,4-dioxane, ethylbenzene, 1,2,3-trimethylbenzene and 1,4-diethylbenzene were also high.     

Measurement of toxic volatile organic compounds in indoor air of semiconductor foundries using multisorbent adsorption/thermal desorption coupled with gas chromatography-mass spectrometry

A method for the qualitative and quantitative analysis of volatile organic compounds (VOCs) in the air of class-100 clean rooms at semiconductor fabrication facilities was developed. Air samples from two semiconductor factories were collected each hour on multisorbent tubes (including Carbopack B, Carbopack C, and Carbosieve SIII) with a 24-h automatic active sampling system and analyzed using adsorption/thermal desorption coupled with gas chromatography-mass spectrometry. Experimental parameters, including thermal desorption temperature, desorption time, and cryofocusing temperature, were optimized. The average recoveries and the method detection limits for the target compounds were in the range 94-101% and 0.31-0.89 ppb, respectively, under the conditions of a 1 L sampling volume and 80% relative humidity. VOCs such as acetone, isopropyl alcohol, 2-heptanone, and toluene, which are commonly used in the semiconductor and electronics industries, were detected and accurately quantified with the established method. Temporal variations of the analyte concentrations observed were attributed to the improper use of organic solvents during operation.     

Voltammetric Electronic Tongue for the Qualitative Analysis of Beers

This paper deals with the application of a voltammetric electronic tongue (ET) towards beers classification. For this purpose, samples were analyzed using cyclic voltammetry without performing any sample pretreatment, albeit its dilution with distilled water. The voltammetric signals were first preprocessed employing Fast Fourier Transform (FFT). Then, using the obtained coefficients, responses were evaluated using three different clustering techniques: Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS‐DA) and Linear Discriminant Analysis (LDA). In this case, the ET has demonstrated a good capability to correctly discriminate and classify the different beer samples according to its type (Lager, Stout and IPA) and manufacture process (commercial and craft).     

热脱附-单体稳定同位素技术测定挥发性有机物

采用热脱附与稳定同位素质谱联用技术分析了城市不同源及大气环境中挥发性有机物排放的单体同位素特征。系统考察了样品进样量、进样方式和样品分离度对同位素分馏影响情况。使用填有Tenax TA的吸附管采集汽油车尾气、汽油挥发、柴油车尾气、柴油挥发、溶剂挥发和餐饮油烟等污染源,以及城市不同功能区的挥发性有机物(VOCs)样品,不同污染源中挥发性有机物的稳定碳同位素δ13C值不同,97#汽油车尾气的δ13 C值偏重,平均值为-25.84‰,富集13 C;餐饮油烟的δ13 C值偏轻,平均值为-30.26‰。油品挥发比燃烧后以尾气的形式排放的苯系物δ13 C值重。厦门市各功能区挥发性有机物的δ13 C平均范围在-27.03‰~-25.40‰,接近于汽油和柴油挥发及尾气中的δ13 C值,表明厦门市空气中挥发性有机物以机动车排放源为主。     

Evaluation of multi-walled carbon nanotubes as an adsorbent for trapping volatile organic compounds from environmental samples

A type of purified multi-walled carbon nanotubes (PMWCNTs) prepared by catalytic decomposition of methane, with a surface area of 98 m2/g, was evaluated as an adsorbent used for tapping volatile organic compounds (VOCs). The performance in evaluation was based on breakthrough volumes (BTVs) and recoveries of selected VOCs. PMWCNTs were also used as a trap packing material to adsorb VOCs purged from spiked water sample. Due to their porous structure, PMWCNTs were found to have much higher BTVs than that of Carbopack B, a graphitized carbon black with the same surface area as PMWCNTs. The recoveries of the tested VOCs trapped on PMWCNTs ranged from 80 to 110%, and not affected by the humidity of purge gas. The results indicate that PMWCNTs are a potential useful adsorbent for direct trapping VOCs from air samples and may be a supplement to VOCARB 3000, a commercially available trap, in purge-and-trap system to preconcentrate VOCs from water samples.     

热脱附-气相色谱-三重四极杆串联质谱法测定环境空气中的挥发性有机物

采用热脱附(TD)结合气相色谱-三重四极杆串联质谱(GC-MS/MS)建立了环境空气中23种挥发性有机物(VOCs)同时检测的分析方法。空气样品通过主动采样的方式富集到装有Tenax-TA填料的热脱附管中,热解吸后在选择反应监测(SRM)模式下用GC-MS/MS进行检测,内标法定量。结果表明,23种VOCs在0.01~1 ng和1~100 ng低、高两个范围内线性关系良好,相关系数(r²)均大于0.99,方法定量限为0.00008~1 μ g/m³。加标水平为2、10和50 ng时,23种VOCs的平均回收率为77%~124%。除了最低加标水平的氯苯,相对标准偏差(RSD, n=6)均小于20%。对市内3个采样点的环境空气进行测定,其中苯、甲苯、乙苯、二甲苯、苯乙烯、1,2,4-三甲基苯和六氯丁二烯均有检出。实验证明,该TD和GC-MS/MS相结合的检测方法具有准确、可靠、灵敏度高等优点,适用于环境空气中VOCs的同时测定。     

Application of a Self-developed Proton Transfer Reaction-Mass Spectrometer to On-line Monitoring Trace Volatile Organic Compounds in Ambient Air

Real-time and on-line monitoring volatile organic compounds(VOCs) are valuable for real-time evalua- ting air quality and monitoring the key source of pollution. A self-developed proton transfer reaction-mass spectrometer(PTR-MS) was constructed and applied to on-line monitoring trace VOCs in ambient air in Hefei, China. With the help of a self-developed catalytic converter, the background signal of the instrument was detected and the stability of the instrument was evaluated. The relative standard deviation of signal at m/z 21 was only 0.74% and the detection limit of PTR-MS was 97 part per trillion(97×10^-12, volume ratio). As a case of the air monitoring in Hefei, the ambient air at Dongpu reservoir spot was on-line monitored for 13 d with our self-developed PTR-MS. Meanwhile, a solid-phase micro-extraction(SPME) technique coupled to gas chromatography-mass spectrometry/mass spectrometry (GC-MS/MS) was also used for the off-line detection of the air. The results show that our self-developed PTR-MS can be used for the on-line and long-term monitoring of VOCs in air at part per trillion level, and the change trend of VOCs concentration monitored with PTR-MS was consistent with that detected with the conventional SPME-GC-MS. This self-developed PTR-MS can fully satisfy the requirements of air quality monitoring and real-time monitoring of the key pollution sources.     

Optimization of FLEC-SPME for field passive sampling of VOCs emitted from solid building materials

The FLEC^®-SPME sampler, described in a previous paper, consists of an emission cell coupled with solid phase microextraction (SPME) for passive sampling of VOCs emitted from building materials. It represents an interesting alternative to standard dynamic sampling protocol as it is easier to implement. If standard dynamic sampling determines emission rates, passive FLEC^®-SPME aims to the determination of the concentration in air at the material surface. That could be assumed provided that material/air equilibrium is reached. Thus, VOCs emission kinetics were studied for 3 different materials (pine wood panel, carpet and PVC floor) to determine equilibrium times. Then, the relevance of the method has been assessed using new materials through a 3-day emission test. Qualitative results were compared to those obtained from the standard method to check the ability of FLEC^®-SPME to detect the most toxic compounds, named “VOCs of interest” and listed in the French regulation. Minor differences were observed, so this methodology seems promising, especially for field studies aiming in the identification of VOCs sources in buildings. Moreover, the concentration at the material surface combined to emission modeling could be used to predict indoor VOCs concentrations helping in indoor air quality diagnostic.     

大气环境中挥发性有机化合物的测定

 参考美国环保局大气中挥发性有机化合物 (VOCs)的标准分析方法TO14A和TO15 ,采用预浓缩器与气相色谱联用 ,以质谱或氢火焰离子化检测器检测 ,建立了 5 6种VOCs(主要是臭氧前体物 )的快速分析方法。该方法在同一台仪器上采用单柱、单检测器 ,准确测定了高浓度CO2 下的VOCs。方法检出限为 0 1μg·m-3 ,相对标准偏差(RSD)为 2 5 7%～ 9 82 %。用该法分析了实际大气样品中的VOCs,结果令人满意。     

Passive sampling application to control air quality in interior of new vehicles

The investigation of air pollution is a highly important field of research. Air quality in a vehicle’s interior has attracted growing attention since people spend much of their time in vehicles and those frequently travelling in new cars are exposed to harmful compounds. The main air pollutants inside new vehicles are volatile organic compounds (VOCs), present as a result of interior materials’ de-gassing. Among the sampling methods used in indoor air quality research, active sampling for VOCs collection is one method that has been extensively described and applied. The present study sought to implement passive sampling with Radiello® samplers to collect air samples directly in the car factory. The results from passive sampling were compared with results derived from active sampling using Carbograph 1TD and silicagel coated with 2,4-dinitrophenylhydrazine cartridges, based on previously validated methods. The identification and quantification of organic compounds was performed using gas chromatography with flame ionisation coupled with a mass spectrometer after thermal desorption. Aldehydes were determined by means of high-performance liquid chromatography. In the present study, the results obtained with the use of active and passive methods of air sampling were compared, correlations between the two sampling methods were designated and the repeatability of passive sampling was detailed.     

Classification of GC‐MS measurements of wines by combining data dimension reduction and variable selection techniques

Different classification methods (Partial Least Squares Discriminant Analysis, Extended Canonical Variates Analysis and Linear Discriminant Analysis), in combination with variable selection approaches (Forward Selection and Genetic Algorithms), were compared, evaluating their capabilities in the geographical discrimination of wine samples. Sixty‐two samples were analysed by means of dynamic headspace gas chromatography mass spectrometry (HS‐GC‐MS) and the entire chromatographic profile was considered to build the dataset. Since variable selection techniques pose a risk of overfitting when a large number of variables is used, a method for coupling data dimension reduction and variable selection was proposed. This approach compresses windows of the original data by retaining only significant components of local Principal Component Analysis models. The subsequent variable selection is then performed on these locally derived score variables. The results confirmed that the classification models achieved on the reduced data were better than those obtained on the entire chromatographic profile, with the exception of Extended Canonical Variates Analysis, which gave acceptable models in both cases. Copyright © 2008 John Wiley & Sons, Ltd.     

Affinity-based elimination of aromatic VOCs by highly crystalline multi-walled carbon nanotubes

Carbon nanotubes (CNTs) are capable of adsorbing pollutant chemicals. Their adsorptive capacities and adsorbing mechanisms, however, are not fully understood. As-grown CNTs often contain both crystalline and amorphous carbon, and the ratio of carbon types can affect adsorption. In this study, highly crystalline multi-walled carbon nanotubes (HC-MWCNTs) were used as the adsorbent for volatile organic compounds (VOCs) in contaminated air samples. Air containing 23 added VOCs (1,1-dichloroethylene, dichloromethane, trans-1,2-dichloroethylene, cis-1,2-dichloroethylene, chloroform, 1,1,1-trichloroethane, carbon tetrachloride, 1,2-dichloroethane, benzene, trichloroethylene, 1,2-dichloropropane, bromodichloromethane, cis-1,3-dichloropropene, toluene, trans-1,3-dichloropropene, 1,1,2-trichloroethane, tetrachloroethylene, dibromochloromethane, m-xylene, p-xylene, o-xylene, bromoform, and p-dichlorobenzene) was used for model samples. Adsorptive experiments were carried out by passing the air samples through a cartridge packed with HC-MWCNTs. Initial results showing high selectivity and high affinity for adsorbing aromatic VOCs (benzene, toluene, m-xylene, p-xylene, o-xylene, and p-dichlorobenzene) have provided new insight into the adsorption mechanisms. Data suggest that the HC-MWCNTs, unlike conventional carbon materials, adsorb aromatic compounds according to Fukui's frontier theory, which is based on the interactions between the HOMO and LUMO of the aromatic VOCs and those of the HC-MWCNTs.     

Development and validation of a method for air-quality and nuisance odors monitoring of volatile organic compounds using multi-sorbent adsorption and gas chromatography/mass spectrometry thermal desorption system

An analytical method based on thermal desorption (TD) coupled to gas chromatography (GC) and mass spectrometry detection (MS) has been developed and validated for the determination of a wide range of odor nuisance and air-quality volatile organic compounds (VOC) in air. New generation isocyanates, isocyanato- and isothiocyanatocyclohexane, have been included for the first time as target compounds due to their high occurrence in air samples. A dynamic air sampling method to trap gas and vapor on multi-sorbent tubes using portable pump equipment has been also developed. Sorbent tubes were filled with Carbotrap (70mg), Carbopack X (100mg) and Carboxen-569 (90mg). Validation of the TD-GC-MS method showed good selectivity, sensibility and precision according to Compendium Method TO-17 (US Environment Protection Agency) criteria. Limits of detection (signal-to-noise=3, ng in tube) ranges were 0.004-0.03ng (alcanes), 0.001-0.1ng (aromatics), 0.03-14ng (aldehydes), 0.003-7ng (alcohols), 0.003-0.04ng (chlorides), 0.02-0.5ng (esters), 0.002-0.1ng (ketones), 0.01-0.53ng (terpenes), 14-97ng (amides), 0.2-10ng (isocyanates) and 0.001ng (carbon disulfide). The linear dynamic range was over 3-5 orders of magnitude, depending of the VOC. TD-GC-MS analysis was reproducible, with relative standard deviation (n=5) within 20%. VOCs breakthrough examination showed no significant losses when about 2000ng standard was prepared. In order to evaluate the performance of the developed method on real samples, several industrial and urban air samples were analysed. VOCs were found to be stable on the sorbent tubes for at least 1 week when stored at 4 degrees C.     

Novel sample preparation technique with needle-type micro-extraction device for volatile organic compounds in indoor air samples

A novel needle-type sample preparation device was developed for the effective preconcentration of volatile organic compounds (VOCs) in indoor air before gas chromatography–mass spectrometry (GC–MS) analysis. To develop a device for extracting a wide range of VOCs typically found in indoor air, several types of particulate sorbents were tested as the extraction medium in the needle-type extraction device. To determine the content of these VOCs, air samples were collected for 30 min with the packed sorbent(s) in the extraction needle, and the extracted VOCs were thermally desorbed in a GC injection port by the direct insertion of the needle. A double-bed sorbent consisting of a needle packed with divinylbenzene and activated carbon particles exhibited excellent extraction and desorption performance and adequate extraction capacity for all the investigated VOCs. The results also clearly demonstrated that the proposed sample preparation method is a more rapid, simpler extraction/desorption technique than traditional sample preparation methods.     

Atmospheric trace elements collected with use of passive sorption sampling

Instrumental Neutron Activation Analysis (INAA) was used to determine trace elemental composition of air. Continuous simultaneous sampling of air contaminants during two weeks in 75 sites of Samarkand city of Uzbekistan was performed with use of passive sorption method on polyethylene collectors. In addition samples of snow were collected. Enrichment factors for elements on sorption collectors and in snow water were calculated. The data obtained allowed to make conclusions on speciation and possible sources of various trace elements in the air and their distribution over the studied region.     

A versatile and uncomplicated method for the analysis of volatile organic compounds in ambient urban air

A method was developed for sampling and selective quantitative determination of typical volatile organic compounds (VOCs) in ambient urban air. A mobile and self-contained dual-channel air sampling tool based on solid phase adsorption was constructed. A simple calibration procedure circumventing the adsorption/desorption process was designed. The method was validated for seven “key-analytes”: n-hexane, 3-methyl-2-pentene, benzene, tetrachloroethene, styrene, 1,2,4-trimethylbenzene and acetophenone. The complete air sampling equipment is easily accommodated in a business suitcase. The lower limits of the practical working ranges are between 0.1 μg m^–3 (tetrachloroethene) and 1.2 μg m^–3 (benzene). Air samples were collected at a location in Salzburg with heavy motor vehicle traffic and measured in order to prove a satisfactory method performance under practical monitoring conditions.     

An application of cluster analysis and multivariate classification methods to spring water monitoring data

An optimized model of multivariate classification for the monitoring of eighteen spring waters in the land of Serra St. Bruno, Calabria, Italy, has been developed. Thirty analytical parameters for each water source were investigated and reduced to eight by means of Principal Component Analysis (PCA). Water springs were grouped in five distinct classes by cluster techniques (CA) and a model for their classification was built by a Partial Least Squares–Discriminant Analysis (PLS–DA) procedure. The model was optimized and validated and then applied to new data matrices, containing the analytical parameters carried out on the same sources during the successive years. This model proved to be able to notice deviations of the global analytical characteristics, by pointing out in the course of time a different distribution of the samples within the classes. The variation of nitrate concentration was demonstrated to be the major responsible for the observed class shifts. The shifting sources were localized in areas used as sowable lands and high variability of nitrate content was ascribed to the practice of crop rotation, involving a varying use of the nitrogenous chemical fertilizers.     

基于RF_AdaBoost模型的血液种属鉴别算法

针对人类和非人类血液种属鉴别对无损、 高效分析方法的需求, 结合随机森林(Random Forest)和AdaBoost(Adaptive Boosting Algorithm)算法, 提出了一种血液种属鉴别方法(RF_AdaBoost). 该方法将RF作为AdaBoost的弱分类器, 以达到提高模型鉴别准确度, 增强模型鲁棒性的目的. 采用RF、 支持向量机(SVM)、 极限学习机(ELM)、 核极限学习机(KELM)、 堆栈自编码网络(SAE)、 反向传播网络(BP)、 主成分分析-线性判别法(PCA-LDA)及偏最小二乘判别分析(PLS-DA)与RF_AdaBoost模型进行对比, 以不同规模血液拉曼光谱数据训练集进行鉴别实验评估其性能. 结果表明, 随着训练样本的增加, RF_AdaBoost鉴别准确度最高达100%, 预测标准偏差趋于0. 与其它模型相比, RF_AdaBoost具有较高的分类准确度及较强的稳定性, 为血液种属的鉴别工作提供了新方法.