Automated system for monitoring trace C2H2 in ambient air by cavity ring-down spectroscopy combined with sample preconcentration

A fully automated instrument combining a continuous wave cavity ring-down spectrometer and dual-trap sample preconcentration has been implemented for monitoring C2H2 mixing ratios in ambient air. A distributed feedback diode laser operating in the near-infrared region (lambda approximately 1534.973 nm in air) detects C2H2 in absorption via the P(17) rotational line of the (v1 + v3) vibrational combination band. The instrument is shown to be capable of fast, quantitative, and precise monitoring of C2H2 mixing ratios, with a detection limit of approximately 8 pptv (parts per trillion by volume). It thus has potential to be deployed for analysis of air samples in many rural and urban environments. In situ measurements were carried out at 30 min intervals over periods of up to 15 h on several days for indoor and outdoor air samples. For indoor air monitored on a Sunday, the C2H2 mixing ratio was stable at 1.45 +/- 0.04 ppbv (parts per billion by volume). On weekdays, both indoor and outside air analyses showed peaks in the range 2-4 ppbv in the early morning and late afternoon that coincided with periods of busy road traffic.     

Measurement of atmospheric ozone by cavity ring-down spectroscopy

Ozone plays a key role in both the Earth's radiative budget and photochemistry. Accurate, robust analytical techniques for measuring its atmospheric abundance are of critical importance. Cavity ring-down spectroscopy has been successfully used for sensitive and accurate measurements of many atmospheric species. However, this technique has not been used for atmospheric measurements of ozone, because the strongest ozone absorption bands occur in the ultraviolet spectral region, where Rayleigh and Mie scattering cause significant cavity losses and dielectric mirror reflectivities are limited. Here, we describe a compact instrument that measures O3 by chemical conversion to NO2 in excess NO, with subsequent detection by cavity ring-down spectroscopy. This method provides a simple, accurate, and high-precision measurement of atmospheric ozone. The instrument consists of two channels. The sum of NO2 and converted O3 (defined as Ox) is measured in the first channel, while NO2 alone is measured in the second channel. NO2 is directly detected in each channel by cavity ring-down spectroscopy with a laser diode light source at 404 nm. The limit of detection for O3 is 26 pptv (2 sigma precision) at 1 s time resolution. The accuracy of the measurement is ±2.2%, with the largest uncertainty being the effective NO2 absorption cross-section. The linear dynamic range of the instrument has been verified from the detection limit to above 200 ppbv (r2>99.99%). The observed precision on signal (2 sigma) with 41 ppbv O3 is 130 pptv in 1 s. Comparison of this instrument to UV absorbance instruments for ambient O3 concentrations shows linear agreement (r2=99.1%) with slope of 1.012±0.002.     

Detection of sulfur dioxide by cavity ring-down spectroscopy

Sulfur dioxide (SO(2)) is a major air pollutant that can contribute to the production of particulate sulfate and increase the acidity in the environment. SO(2) is detected by cavity ring-down spectroscopy (CRDS) utilizing the SO(2) absorption in the 308 nm region. A ferrous sulfate scrubber and a sodium carbonate annular denuder are used to reduce background interferences and to obtain quantitative values of SO(2). The method is characterized using SO(2) standards in the laboratory and compared to a commercial pulsed fluorescence analyzer (PFA). A limit of detection of 3.5 ppb/10 s (S/N = 2) is demonstrated. Ambient measurements are attempted to demonstrate this technique.     

芝麻叶黄酮的超声提取及其对NO2-清除的研究

采用L9(34)正交试验研究超声法提取芝麻叶黄酮的工艺条件,采用分光光度法测定芝麻叶提取物对亚硝酸盐的清除率.结果表明,芝麻叶黄酮超声提取的最佳工艺条件为:乙醇浓度50%,料液比为1:30(W:V),超声功率300 W,超声时间30 min,此时提取率可达96.6%.芝麻叶提取物对亚硝酸盐具有较强的清除作用.在pH为3,温度为35℃时,含0.465 mg黄酮的芝麻叶提取液在30 min内对亚硝酸盐的清除率可达74.6%.     

Incoherent broadband cavity-enhanced absorption spectroscopy in the near-ultraviolet: application to HONO and NO2

The first application of incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS) in the near-ultraviolet for the simultaneous detection of two key atmospheric trace species, HONO and NO2, is reported. For both compounds the absorption is measured between 360 and 380 nm with a compact cavity-enhanced spectrometer employing a high power light-emitting diode. Detection limits of approximately 4 ppbv for HONO and approximately 14 ppbv for NO2 are reported for a static gas cell setup using a 20 s acquisition time. Based on an acquisition time of 10 min and an optical cavity length of 4.5 m detection limits of approximately 0.13 ppbv and approximately 0.38 ppbv were found for HONO and NO2 in a 4 m3 atmospheric simulation chamber, demonstrating the usefulness of this approach for in situ monitoring of these important species in laboratory studies or field campaigns.     

Hydroxycarboxylic acid-derived organosulfates: synthesis, stability, and quantification in ambient aerosol

Organosulfates have been proposed as contributors to aerosol growth and have been detected in both chamber and atmospheric aerosol samples. We present a simple method for the synthesis of quantitative analytical standards of two small hydroxycarboxylic acid-derived organosulfates, glycolic and lactic acid sulfate. Additionally, we discuss the stability of hydroxycarboxylic acid-derived organosulfates and their previously proposed sulfate hemiacetal isomers in commonly used solvents for filter extraction. The hydroxycarboxylic acid-derived organosulfates were found to be stable under acidic conditions comparable to those found in ambient aerosol. By using synthesized standards, quantitative organosulfate concentrations were measured from ambient particulate matter (PM(2.5)) collected in urban locations in the United States, Mexico City, and Pakistan. Lactic acid sulfate and glycolic acid sulfate concentrations ranged 0.4-3.8 ng/m(3) and 1.9-11.3 ng/m(3), respectively. We propose that glycolic acid sulfate represents an important tracer for atmospheric processes that form organosulfates in ambient particulate matter.     

Remote identification and quantification of industrial smokestack effluents via imaging Fourier-transform spectroscopy

Industrial smokestack plume emissions were remotely measured with a midwave infrared (1800-3000 cm(-1)) imaging Fourier-transform spectrometer operating at moderate spatial (128 × 64 with 19.4 × 19.4 cm(2) per pixel) and high spectral (0.25 cm(-1)) resolution over a 20 min period. Strong emissions from CO(2), H(2)O, SO(2), NO, HCl, and CO were observed. A single-layer plume radiative transfer model was used to estimate temperature T and effluent column densities q(i) for each pixel's spectrum immediately above the smokestack exit. Across the stack, temperature was uniform with T = 396.3 ± 1.3 K (mean ± stdev), and each q(i) varied in accordance with the plume path length defined by its cylindrical geometry. Estimated CO(2) and SO(2) volume fractions of 8.6 ± 0.4% and 380 ± 23 ppm(v), respectively, compared favorably with in situ measurements of 9.40 ± 0.03% and 383 ± 2 ppm(v). Total in situ NO(x) concentration (NO + NO(2)) was reported at 120 ± 1 ppm(v). While NO(2) was not spectrally detected, NO was remotely observed with a concentration of 104 ± 7 ppm(v). Concentration estimates for the unmonitored species CO, HCl, and H(2)O were 14.4 ± 0.3 ppm(v), 88 ± 1 ppm(v), and 4.7 ± 0.1%, respectively.     

无效变量消除法在油菜籽芥酸近红外无损速测中的应用

探索改善油菜籽芥酸近红外预测模型准确度与精密度的方法,利用无效变量消除法（UVE）,对135个油菜籽样品近红外光谱信号进行筛选,并利用筛选后的光谱对油菜籽芥酸含量进行偏最小二乘法交叉验证。结果表明,UVE法筛选变量后建立的芥酸校正模型对未知样品预测结果的准确度和速度显著优于全波长参与建立的芥酸校正模型。散射校正加一阶导数对光谱预处理,UVE法筛选变量,偏最小二乘法交叉验证建立的校正模型效果最好,其预测值与标准值的相关系数R达到0.92,交叉验证预测均方差为2.2。因此,用UVE进行波长选择后建立的近红外模型,能准确快速地对油菜籽芥酸含量进行定量分析。     

Application of FTIR-HATR spectroscopy and multivariate analysis to the quantification of adulterants in Mexican honeys

Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) accessory was used to quantify three different adulterants (corn syrup, high fructose corn syrup and inverted sugar) in honeys of four different locations of México (Chiapas, Oaxaca, Estado de México and Morelos). The optimal calibrations for the three adulterants were developed with partial least squares (PLS). The developed models were validated with different independent data sets being the standard error of prediction (SEP) between 1.5 and 2.1 for corn syrup, 2.1–3.0 for high fructose corn syrup and 1.4–2.5 for inverted sugar, showing the applicability of these models to the detection and quantification of adulterants in honey bee. Classification of the Mexican honeys from the four different states was carried out with soft independent modeling class analogy giving 100% correct classification rate and no false positive results were obtained.     

Fourier transform infrared spectroscopy and multivariate analysis for the detection and quantification of different milk species

The authenticity of milk and milk products is important and has extended health, cultural, and financial implications. Current analytical methods for the detection of milk adulteration are slow, laborious, and therefore impractical for use in routine milk screening by the dairy industry. Fourier transform infrared (FT-IR) spectroscopy is a rapid biochemical fingerprinting technique that could be used to reduce this sample analysis period significantly. To test this hypothesis we investigated 3 types of milk: cow, goat, and sheep milk. From these, 4 mixtures were prepared. The first 3 were binary mixtures of sheep and cow milk, goat and cow milk, or sheep and goat milk; in all mixtures the mixtures contained between 0 and 100% of each milk in increments of 5%. The fourth combination was a tertiary mixture containing sheep, cow, and goat milk also in increments of 5%. Analysis by FT-IR spectroscopy in combination with multivariate statistical methods, including partial least squares (PLS) regression and nonlinear kernel partial least squares (KPLS) regression, were used for multivariate calibration to quantify the different levels of adulterated milk. The FT-IR spectra showed a reasonably good predictive value for the binary mixtures, with an error level of 6.5 to 8% when analyzed using PLS. The results improved and excellent predictions were achieved (only 4-6% error) when KPLS was employed. Excellent predictions were achieved by both PLS and KPLS with errors of 3.4 to 4.9% and 3.9 to 6.4%, respectively, when the tertiary mixtures were analyzed. We believe that these results show that FT-IR spectroscopy has excellent potential for use in the dairy industry as a rapid method of detection and quantification in milk adulteration.     

NO and NO2 emission ratios measured from in-use commercial aircraft during taxi and takeoff

In August 2001, the Aerodyne Mobile Laboratory simultaneously measured NO, NO2, and CO2 within 350 m of a taxiway and 550 m of a runway at John F. Kennedy Airport. The meteorological conditions were such that taxi and takeoff plumes from individual aircraft were clearly resolved against background levels. NO and NO2 concentrations were measured with 1 s time resolution using a dual tunable infrared laser differential absorption spectroscopy instrument, utilizing an astigmatic multipass Herriott cell. The CO2 measurements were also obtained at 1 s time resolution using a commercial non-dispersive infrared absorption instrument. Plumes were measured from over 30 individual planes, ranging from turbo props to jumbo jets. NOx emission indices were determined by examining the correlation between NOx (NO + NO2) and CO2 during the plume measurements. Several aircraft tail numbers were unambiguously identified, allowing those specific airframe/engine combinations to be determined. The resulting NOx emission indices from positively identified in-service operating airplanes are compared with the published International Civil Aviation Organization engine certification test database collected on new engines in certification test cells.     

Energy and material balance of CO2 capture from ambient air

Current Carbon Capture and Storage (CCS) technologies focus on large, stationary sources that produce approximately 50% of global CO2 emissions. We propose an industrial technology that captures CO2 directly from ambient air to target the remaining emissions. First, a wet scrubbing technique absorbs CO2 into a sodium hydroxide solution. The resultant carbonate is transferred from sodium ions to calcium ions via causticization. The captured CO2 is released from the calcium carbonate through thermal calcination in a modified kiln. The energy consumption is calculated as 350 kJ/mol of CO2 captured. It is dominated by the thermal energy demand of the kiln and the mechanical power required for air movement. The low concentration of CO2 in air requires a throughput of 3 million cubic meters of air per ton of CO2 removed, which could result in significant water losses. Electricity consumption in the process results in CO2 emissions and the use of coal power would significantly reduce to net amount captured. The thermodynamic efficiency of this process is low but comparable to other "end of pipe" capture technologies. As another carbon mitigation technology, air capture could allow for the continued use of liquid hydrocarbon fuels in the transportation sector.     

Seasonal variation of 2-methyltetrols in ambient air samples

PM2.5 samples were collected from June to December 2005 in Potsdam, New York and analyzed for polar organic compounds by GC/MS. The major compounds that were identified in the samples included 2-methyltetrols (2-methylthreitol and 2-methylerythritol), levoglucosan, cispinonic acid, and mannitol. 2-Methyltetrols were quantified during the analysis. A seasonal variation for these two diastereoisomers was observed, with the highest concentrations occurring during the summer and the lowest concentrations occurring during the winter. OC/EC analyses of these samples were also performed. The variation of the carbon contribution of 2-methyltetrols to OC was found to follow the same pattern as the concentration variation of 2-methyltetrols. During summer, the period of high photochemical activity, the maximum carbon contribution of 2-methyltetrols to OC was 2.8%. The observation of high 2-methyltetrol concentrations during the summer indicates isoprene is a significant summertime source of secondary organic aerosol in this rural area in the northeastern United States.     

Measurement of N2, N2O, NO, and CO2 emissions from soil with the gas-flow-soil-core technique

Here we describe a newly designed system with three stand-alone working incubation vessels for simultaneous measurements of N(2), N(2)O, NO, and CO(2) emissions from soil. Due to the use of a new micro thermal conductivity detector and the redesign of vessels and gas sampling a so-far unmatched sensitivity (0.23 μg N(2)-N h(-1) kg(-1) ds or 8.1 μg N(2)-N m(-2) h(-1)) for detecting N(2) gas emissions and repeatability of experiments could be achieved. We further tested different incubation methods to improve the quantification of N(2) emission via denitrification following the initialization of soil anaerobiosis. The best results with regard to the establishment of a full N balance (i.e., the changes in mineral N content being offset by simultaneous emission of N gases) were obtained when the anaerobic soil incubation at 25 °C was preceded by soil gas exchange under aerobic conditions at a lower incubation temperature. The ratios of N and C gas emission changed very dynamically following the initialization of anaerobiosis. For soil NO(3)(-) contents of 50 mg N kg(-1) dry soil (ds) and dissolved organic carbon (DOC) concentrations of approximately 300 mg C kg(-1) ds, the cumulative emissions of N(2), N(2)O, and NO were 24.3 ± 0.1, 12.6 ± 0.4, and 10.1 ± 0.3 mg N kg(-1) ds, respectively. Thus, N gas emissions accounted (on average) for 46.2% (N(2)), 24.0% (N(2)O), and 19.2% (NO) of the observed changes in soil NO(3)(-). The maximum N(2) emission reached 1200 μg N h(-1) kg(-1) ds, whereas the peak emissions of N(2)O and NO were lower by a factor of 2-3. The overall N(2):N(2)O and NO:N(2)O molar ratios were 1.6-10.0 and 1.6-2.3, respectively. The measurement system provides a reliable tool for studying denitrification in soil because it offers insights into the dynamics and magnitude of gaseous N emissions due to denitrification under various incubation conditions.     

Metal bioaccumulation in aquatic species: quantification of uptake and elimination rate constants using physicochemical properties of metals and physiological characteristics of species

Mechanistic bioaccumulation models are powerful tools in environmental risk assessment as they provide insight in varying accumulation patterns across species, contaminants, and conditions, and they are applicable beyond tested cases. In these models key parameters, as absorption and elimination rate constants, are predicted based on chemical specific properties and physiological characteristics. However, due to the complex environmental behavior of metals, the development of mechanistic bioaccumulation models has lagged behind that for organic chemicals. Absorption and elimination rate constants of organic substances have long been linked to their octanol-water partition coefficient, yet no equivalent quantitative relationships exist for metals. In the present study, we successfully related metal absorption rate constants to a metal specific property, the covalent index, and a species-characteristic, the ventilation rate. This quantitative relationship holds for a wide range of organisms and metals, i.e., 17 aquatic species and 10 metals, suggesting that a generic modeling approach of metal uptake kinetics is feasible for aquatic organisms. In contrast, elimination rate constants show no metal - specific character. Average, weight-corrected elimination rate constants are relatively similar among metals and species, suggesting that a single weight-corrected elimination rate constant can be used in bioaccumulation studies on aquatic species.     

Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef

This study aimed to evaluate the potential of near infrared spectroscopy (NIRS) as a fast and non-destructive tool for detecting and quantifying different adulterants in fresh and frozen-thawed minced beef. Partial least squares regression (PLSR) models were built under cross validation and tested with different independent data sets, yielding determination coefficients (R_P²) of 0.96, 0.94 and 0.95 with standard error of prediction (SEP) of 5.39, 5.12 and 2.08% (w/w) for minced beef adulterated by pork, fat trimming and offal, respectively. The performance of the developed models declined when the samples were in a frozen-thawed condition, yielding R_P² of 0.93, 0.82 and 0.95 with simultaneous augments in the SEP of 7.11, 9.10 and 2.38% (w/w), respectively. Linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA) and non-linear regression models (logistic, probit and exponential regression) were developed at the most relevant wavelengths to discriminate between the pure (unadulterated) and adulterated minced beef. The classification accuracy resulting from both types of models was quite high, especially the LDA, PLS-DA and exponential regression models which yielded 100% accuracy. The current study demonstrated that the VIS-NIR spectroscopy can be utilized securely to detect and quantify the amount of adulterants added to the minced beef with acceptable precision and accuracy.     

带籽屑棉结的去除研究

实验研究了梳棉机在不同产量、不同速度、不同类型刺辊的条件下,生条中棉结的数量和尺寸变化情况。研究认为：清棉过程中棉结数量增加,刺辊对棉结的去除作用很大,后罩板处加固定盖板和棉网清洁器的作用则不大。     

Application of visible and near infrared spectroscopy for rapid and non-invasive quantification of common adulterants in Spirulina powder

The authentication of food products is critically important in a global economy in public-health and economic terms. The specific aims of this study were to evaluate the application of full-spectrum and NIR spectroscopy and to evaluate the adoption of PLS and LS-SVM models to accomplish a rapid and non-invasive quantification of the two common adulterants, flour and mungbean powder, in Spirulina powder. The results showed that, using all treatment sets, only the LS-SVM models were adequate in predicting either adulterant under both full spectra and NIR spectra. The use of NIR spectra would allow detection of adulterants even when masked by food dyes. Design value analysis indicated that the benefits per unit cost of applying the NIR spectra to quantify adulterants in Spirulina powder significantly exceeded that of using full spectra, and that the value of employing the LS-SVM models under NIR spectra exceeded that of using the PLS models.