Abstract
Abstract. 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.
Highlights
Agriculture substantially contributes greenhouse gases (GHGs), mostly CO2, N2O, and CH4, to the atmosphere (IPCC, 2007)
Spectral windows (Table 2) and linear baseline correction were applied in classical least squares (CLS)-1 and partial least squares (PLS) models to calculate mole fractions of N2O and water vapour from the mixedgas spectra using TQ Analyst software version 8.0 (Thermo Fisher Scientific, Inc.) The previous study showed that the integrated window of 2188.7–2204.1 and 2215.8–2223.7 cm−1 (WN3) is less sensitive to a changing environment and provides higher accuracy than the window of 2170.0–2223.7 cm−1 (WN1) for N2O quantification using either CLS or PLS models (Lin et al, 2019a)
Since it was difficult to isolate the effects of the temperature and humidity on quantitative biases from the field experiment, the validation spectra with the fixed mole fractions of N2O and water vapour (310 ppbv N2O mixed with 21 500 ppmv water vapour) were collected at 30, 35, and 40 ◦C from the lab FTIR to evaluate the sensitivity of CLS and PLS to temperature
Summary
Agriculture substantially contributes greenhouse gases (GHGs), mostly CO2, N2O, and CH4, to the atmosphere (IPCC, 2007). Found that CLS models resulted in a substantial error for quantifying the targeted gas under the interference from the non-targeted gases (mostly water vapour) even if the reference spectra of all gas species and the optimal spectral window were considered (Hart et al, 1999; Briz et al, 2007; Shao et al, 2010; Lin et al, 2019a). Ies minimized environmental interferences (e.g. water vapour or wind speed) by developing methods for spectral analyses and gas quantification (Hong and Cho, 2003; Hart et al, 1999, 2000; Muller et al, 1999; Childers et al, 2002; Briz et al, 2007; Shao et al, 2007, 2010; Griffiths et al, 2009; Lin et al, 2019a). The influence of water vapour, temperature, path length, and wind speed on N2O and CO2 quantification is examined using lab- and field-based (OP-FTIR) methods
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