Limin Shao

Measurement of atmospheric ammonia, methane, and nitrous oxide at a concentrated dairy production facility in Southern Idaho using open-path FTIR spectrometry

The number of dairy cows in Idaho has increased by approximately 80% in the last decade, with the majority of these facilities located in southern Idaho, causing air quality concerns in this region. To determine the potential air quality impacts of these facilities, we measured ammonia (NH3), methane (CH4), and nitrous oxide (N2O) concentrations over the pens, wastewater storage pond, and composting area on a 700-cow open-lot dairy using open-path Fourier transform infrared spectrometry (OP/FTIR). Concentrations were measured for one or two days at each location during January, March, June, and September. Median NH3 concentrations over the pens, storage pond, and composting area ranged from 0.14 to 0.39 ppmv, 0.04 to 0.17 ppmv, and 0.06 to 0.22 ppmv, respectively, with concentrations tending to be lower in January. Average CH4 concentrations over the pens, storage pond, and composting area ranged from 2.07 to 2.80 ppmv, 1.87 to 2.15 ppmv, and 1.71 to 1.76 ppmv, respectively. Average N2O concentrations ranged from 0.31 to 0.33 ppmv for all areas, which was similar to global background N2O concentrations. Combined ammonia emissions for the pen and storage pond areas, calculated with a backward Lagrangian stochastic inverse-dispersion technique, were 0.04, 0.25, 0.19, and 0.15 kg NH3 cow-1 d-1 for January, March, June, and September, respectively, and methane emissions were 0.34, 0.55, 0.21, and 0.20 kg CH4 cow-1 d-1 for the same months. Assuming this limited monitoring was representative of the entire year, annual emissions from the pens and storage pond were 57 kg NH3 cow-1 and 120 kg CH4 cow-1. These emission rates were similar to the limited number of comparable studies that have been published. However, more extensive monitoring is needed to better quantify variations in emissions throughout the year and among locations.

Self-Weighted Correlation Coefficients and Their Application to Measure Spectral Similarity

A technique for spectral searching with noisy data is described that improves the performance over contemporary approaches. Instead of simply calculating the correlation coefficient between the spectrum of an unknown and a series of reference spectra, greater weight is given to the more intense features in the reference spectra. The weight array, w, is given by |r|/{1 + d}, where the vector r represents the reference spectrum and the difference vector, d, contains the difference between the sample and reference data points, equal to |s — kr|, where k is a scaling factor that eliminates the effect of signal strength. By this approach, a large weight is only given to those points that have relatively high absorbance and are close to their counterparts in the reference spectrum. This technique was shown to give significantly improved performance when applied to noisy spectra of trace atmospheric components obtained by target factor analysis.

A WAVELET TRANSFORM AND ITS APPLICATION TO SPECTROSCOPIC ANALYSIS

ABSTRACT An introduction to the wavelet transform and its applications in spectroscopy analysis are presented. Owing to the property of the dual localization both in time and in frequency domains, the wavelet transform exhibits several useful characteristics. With the wavelet transform a signal can be decomposed into series of contributions according to the frequency difference, these contributions are respectively called discrete approximations and discrete details. By applying certain treatment to the discrete approximations (the low frequency part) or the discrete details (the high frequency part), a part of the original signal within a certain frequency range can be obtained. The wavelet transform has been applied in various fields of the analytical chemistry, including removal of high frequency noise, information extraction, resolution of overlapping signals, and data compression etc. Research concerning application in analytical chemistry are introduced in respect of photoacoustic spectroscopy, EXAFS spectrum, NMR analysis, and Raman spectrum.

Advances in Data Processing for Open-Path Fourier Transform Infrared Spectrometry of Greenhouse Gases †

The automated quantification of three greenhouse gases, ammonia, methane, and nitrous oxide, in the vicinity of a large dairy farm by open-path Fourier transform infrared (OP/FT-IR) spectrometry at intervals of 5 min is demonstrated. Spectral pretreatment, including the automated detection and correction of the effect of interrupting the infrared beam, is by a moving object, and the automated correction for the nonlinear detector response is applied to the measured interferograms. Two ways of obtaining quantitative data from OP/FT-IR data are described. The first, which is installed in a recently acquired commercial OP/FT-IR spectrometer, is based on classical least-squares (CLS) regression, and the second is based on partial least-squares (PLS) regression. It is shown that CLS regression only gives accurate results if the absorption features of the analytes are located in very short spectral intervals where lines due to atmospheric water vapor are absent or very weak; of the three analytes examined, only ammonia fell into this category. On the other hand, PLS regression works allowed what appeared to be accurate results to be obtained for all three analytes.

Extraction of extended X-ray absorption fine structure information from the experimental data using the wavelet transform

A novel method for extracting the extended X-ray absorption fine structure (EXAFS) information from a measured absorption spectrum is proposed. Owing to the dual localization characteristic of the wavelet transform, the EXAFS oscillation information can be easily retrieved from the experimental spectrum by means of wavelet decomposition. The spectra of a Cu sample have been analyzed by use of the method. Compared with the conventional method, the wavelet transform method is proved to be convenient and fast in retrieving the oscillation, and results obtained by the method are reasonable.

Using Multiple Calibration Sets to Improve the Quantitative Accuracy of Partial Least Squares (PLS) Regression on Open-Path Fourier Transform Infrared (OP/FT-IR) Spectra of Ammonia over Wide Concentration Ranges

The use of multiple calibration sets in partial least squares (PLS) regression was proposed to improve the quantitative determination of NH3 over wide concentration ranges from open-path Fourier transform infrared (OP/FT-IR) spectra. The spectra were measured near animal farms, where the path-integrated concentration of NH3 can fluctuate from nearly zero to as high as approximately 1000 ppm-m. PLS regression with a single calibration set did not cover such a large concentration range effectively, and the quantitative accuracy was degraded due to the nonlinear relationship between concentration and absorbance for spectra measured at low resolution (1 cm−1 and poorer.) In PLS regression with multiple calibration sets, each calibration set covers a part of the entire concentration range, which significantly decreases the serious nonlinearity problem in PLS regression occurring when only a single calibration set is used. The relative error was reduced from approximately 6% to below 2%, and the best results were obtained with four calibration sets, each covering one quarter of the entire concentration range. It was also found that it was possible to build the multiple calibration sets easily and efficiently without extra measurements.

Increasing the Quantitative Credibility of Open-Path Fourier Transform Infrared (FT-IR) Spectroscopic Data, with Focus on Several Properties of the Background Spectrum

The choice of the type of background spectrum affects the credibility of open-path Fourier transform infrared spectroscopy (OP/FT-IR) data, and consequently, the quality of data analysis. We systematically investigated several properties of the background spectrum. The results show that a short-path background measured with the lowest amplifier gain could significantly reduce noise in the calculated absorbance spectrum, by at least 30% in our case. We demonstrated that by using a short-path background, data analysis is more resistant to interferences such as wavenumber shift or resolution alteration that occurs as a consequence of aging hardware or misalignment. We discussed a systematic error introduced into quantitative analyses by the short-path background and developed a procedure to correct that error. With this correction approach, a short-path background established five years ago was still found to be valid. By incorporating these findings into the protocol for quantitative analysis, we processed the measurements with two OP/FT-IR instruments set up side by side in the vicinity of a large dairy farm, to monitor NH3, CH4, and N2O. The two sets of calculated concentrations showed high agreement with each other. The findings of our investigations are helpful to atmospheric monitoring practitioners of OP/FT-IR spectroscopy and could also be a reference for future amendments to the protocols outlined in the guidelines of the U.S. Environmental Protection Agency, the American Society for Testing and Materials, and the European Committee for Standardization.

Information extraction from a complex multicomponent system by target factor analysis.

A theoretical investigation into the mechanism of information extraction by target factor analysis (TFA) is presented from experimental data in the form of a matrix, and the results were validated using composite spectra obtained by open-path Fourier transform-infrared (FT-IR) spectrometry. The composite spectra were generated by adding the spectral information of a target molecule with known path-integrated concentrations to the raw open-path FT-IR spectra obtained in a pristine atmosphere. Target molecules are deemed to be detected when the weighted correlation coefficient between the calculated spectrum of the analyte and its reference spectrum exceeds 0.90. The effective detection by TFA is shown to depend on the variation of their concentrations over the period of the measurement and not necessarily on the magnitude of concentration. When TFA fails to detect an analyte at high, but relatively constant, concentration that varies so little as to have low variance, blank spectra, i.e., spectra in which the analyte is known to be absent, are included in the data matrix. This procedure effectively increases the variance of the concentrations in the whole data set, and TFA detects the analyte.

Quantitative Vapor-Phase Infrared Spectrometry of Ammonia

Reference spectra of ammonia from four sources are compared. Low-resolution spectra (i.e., spectra for which the spectrometer resolution is numerically greater than the full-width at half-height of the rotational lines) were obtained from the Environmental Protection Agency (EPA) web site and from Infrared Analysis, Inc. High-resolution (0.12 cm−1) spectra were obtained from the National Institute for Standards and Technology (NIST) and Pacific Northwest National Laboratory (PNNL). Two protocols were used to validate the EPA and Infrared Analysis spectra, with one requiring that Beers law be obeyed by the low-resolution spectrum and the other that Beers law be obeyed by the high-resolution spectrum. In all cases, the second protocol gave a significantly better spectral match. It is shown that the path-integrated concentrations for the low-resolution reference spectra were in error by as little as 4% to as much as an order of magnitude, presumably because of the effect of adsorption on the cell walls. Measured absorptivities of the NIST and PNNL spectra were different by ≈2.6% and it is believed that the effect of adsorption on these spectra is small. When the same protocols were used to test the reference spectrum of methane, the calculated path-integrated concentration was only ∼2% different from the one that was calculated from the NIST reference spectrum, suggesting that the data processing protocols provide accurate data.

Detection of chemical agents in the atmosphere by open-path FT-IR spectroscopy under conditions of background interference: II. Fog and rain

Open-path FT-IR spectra of low-concentration releases of diethyl ether were measured both when a glycol fog was passed into the infrared beam and when large water droplets from a lawn sprinkler were sprayed into the beam. It was shown that the glycol fog, for which the droplet size was much less than the wavelength of the infrared radiation, gave rise to a significant interference such that partial least squares (PLS) regression would only yield reasonable values for the ether concentration if background spectra in which the glycol fog was present were included in the calibration set. On the other hand, target factor analysis (TFA) allowed the presence of the ether to be recognized without precalibration. When large water droplets were present in the beam, any infrared radiation entering the droplet was completely absorbed, so that both PLS and TFA would yield accurate results.