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Open-path Fourier transform infrared spectroscopy (OP-FTIR) is susceptible to environmental variables which can become sources of errors for gas quantification. In this study, we assessed the effects of water vapour, temperature, path length, and wind speed on quantitative uncertainties of nitrous oxide (N2O) and carbon dioxide (CO2) derived from OP-FTIR spectra. The presence of water vapour in spectra underestimated N2O mole fractions by 3 % and 12 %, respectively, from both lab and field experiments using a classical least squares (CLS) model when the reference and sample spectra were collected at the same temperature (i.e. 30 ∘ C). Differences in temperature between sample and reference spectra also underestimated N2O mole fractions due to temperature broadening and the increased interferences of water vapour in spectra of wet samples. Changes in path length resulted in a non-linear response of spectra and bias (e.g. N2O and CO2 mole fractions were underestimated by 30 % and 7.5 %, respectively, at the optical path of 100 m using CLS models). For N2O quantification, partial least squares (PLS) models were less sensitive to water vapour, temperature, and path length and provided more accurate estimations than CLS. Uncertainties in the path-averaged mole fractions increased in low-wind conditions (<2 m s -1). This study identified the most common interferences that affect OP-FTIR measurements of N2O and CO2 , which can serve as a quality assurance/control guide for current or future OP-FTIR users. [ABSTRACT FROM AUTHOR]

Open-path Fourier transform infrared spectroscopy (OP-FTIR) is susceptible to environmental variables which can become sources of errors for gas quantification. In this study, we assessed the effects of water vapour, temperature, path length, and wind speed on the uncertainty of nitrous oxide (N2O) and carbon dioxide (CO2) concentrations derived from OP-FTIR spectra. The presence of water vapour resulted in underestimating N2O in both lab (−3 %) and field (−12 %) experiments at 30 °C using a classical least squares (CLS) model. Differences in temperature between the sample and reference spectra also underestimated N2O concentrations due to temperature broadening and the increased interferences of water vapour in spectra of wet samples. Changes in path length resulted in a non-linear response of spectra and bias (e.g. N2O and CO2 concentrations were underestimated by 30 % and 7.5 %, respectively, at the optical path of 100-m using CLS models). For N2O quantification, partial least squares (PLS) models were less sensitive than CLS to the influence of water vapour, temperature, and path length, and provided more accurate estimations. Uncertainties in the path-averaged concentrations increased in low wind conditions (< 2 m s-1). This study identified the most common interferences that affect OP-FTIR measurements of N2O and CO2. The quantified errors can be used as references for current or future OP-FTIR users. [ABSTRACT FROM AUTHOR]

Open-path Fourier transform infrared spectroscopy (OP-FTIR) has often been used to measure hazardous or trace gases from hot point sources (e.g. volcano, industrial, or agricultural facilities) but seldom used to measure greenhouse gases (GHGs) from field-scale sources (e.g. agricultural soils). Closed-path mid-IR laser-based N2O , nondispersive-IR CO2 analysers, and OP-FTIR were used to measure concentrations of N2O and CO2 at a maize cropping system during 9–19 June 2014. To measure N2O and CO2 concentrations accurately, we developed a quantitative method of N2O/CO2 analysis that minimized interferences from diurnal changes of humidity and temperature. Two chemometric multivariate models, classical least squares (CLS) and partial least squares (PLS), were developed. This study evaluated various methods to generate the single-beam background spectra and different spectral regions for determining N2O and CO2 concentrations from OP-FTIR spectra. A standard extractive method was used to measure the actual path-averaged concentrations along an OP-FTIR optical path in situ, as a benchmark to assess the feasibilities of these quantitative methods. Within an absolute humidity range of 5000–20 000 ppmv and a temperature range of 10–35 ∘ C, we found that the CLS model underestimated N2O concentrations (bias =-4.9±3.1 %) calculated from OP-FTIR spectra, and the PLS model improved the accuracy of calculated N2O concentrations (bias =1.4±2.3 %). The bias of calculated CO2 concentrations was -1.0±2.8 % using the CLS model. These methods suggested that environmental variables potentially lead to biases in N2O and CO2 estimations from OP-FTIR spectra and may help OP-FTIR users avoid dependency on extractive methods of calibrations. [ABSTRACT FROM AUTHOR]