Towards DCS in the UV Spectral Range for Remote Sensing of Atmospheric Trace Gases

The development of increasingly sensitive and robust instruments and new methodologies are essential to improve our understanding of the Earth’s climate and air pollution. In this context, Dual-Comb spectroscopy (DCS) has been successfully demonstrated as a remote laser-based instrument to probe infrared absorbing species such as greenhouse gases. We present here a study of the sensitivity of Dual-Comb spectroscopy to remotely monitor atmospheric gases focusing on molecules that absorb in the ultraviolet domain, where the most reactive molecules of the atmosphere (OH, HONO, BrO...) have their highest absorption cross-sections. We assess the achievable signal-to-noise ratio (SNR) and the corresponding minimum absorption sensitivity of DCS in the ultraviolet range. We propose a potential light source for remote sensing UV-DCS and discuss the degree of immunity of UV-DCS to atmospheric turbulences. We show that the characteristics of the currently available UV sources are compatible with the unambiguous identification of UV absorbing gases by UV-DCS.

Parameterization of thermal properties of aging secondary organic aerosol produced by photo-oxidation of selected terpene mixtures

Formation and evolution of secondary organic aerosols (SOA) from biogenic VOCs influences the Earth's radiative balance. We have examined the photo-oxidation and aging of boreal terpene mixtures in the SAPHIR simulation chamber. Changes in thermal properties and chemical composition, deduced from mass spectrometric measurements, were providing information on the aging of biogenic SOA produced under ambient solar conditions. Effects of precursor mixture, concentration, and photochemical oxidation levels (OH exposure) were evaluated. OH exposure was found to be the major driver in the long term photochemical transformations, i.e., reaction times of several hours up to days, of SOA and its thermal properties, whereas the initial concentrations and terpenoid mixtures had only minor influence. The volatility distributions were parametrized using a sigmoidal function to determine TVFR0.5 (the temperature yielding a 50% particle volume fraction remaining) and the steepness of the volatility distribution. TVFR0.5 increased by 0.3±0.1% (ca. 1 K), while the steepness increased by 0.9±0.3% per hour of 1×10(6) cm(-3) OH exposure. Thus, aging reduces volatility and increases homogeneity of the vapor pressure distribution, presumably because highly volatile fractions become increasingly susceptible to gas phase oxidation, while less volatile fractions are less reactive with gas phase OH.

Simple Monte Carlo methods to estimate the spectra evaluation error in differential-optical-absorption spectroscopy

Differential-optical-absorption spectroscopy (DOAS) permits the sensitive measurement of concentrations of trace gases in the atmosphere. DOAS is a technique of well-defined accuracy; however, the calculation of a statistically sound measurement precision is still an unsolved problem. Usually one evaluates DOAS spectra by performing least-squares fits of reference absorption spectra to the measured atmospheric absorption spectra. Inasmuch as the absorbance from atmospheric trace gases is usually very weak, with optical densities in the range from 10(-5) to 10(-3), interference caused by the occurrence of nonreproducible spectral artifacts often determines the detection limit and the measurement precision. These spectral artifacts bias the least-squares fitting result in two respects. First, spectral artifacts to some extent are falsely interpreted as real absorption, and second, spectral artifacts add nonstatistical noise to spectral residuals, which results in a significant misestimation of the least-squares fitting error. We introduce two new approaches to investigate the evaluation errors of DOAS spectra accurately. The first method, residual inspection by cyclic displacement, estimates the effect of false interpretation of the artifact structures. The second method applies a statistical bootstrap algorithm to estimate properly the error of fitting, even in cases when the condition of random and independent scatter of the residual signal is not fulfilled. Evaluation of simulated atmospheric measurement spectra shows that a combination of the results of both methods yields a good estimate of the spectra evaluation error to within an uncertainty of ~10%.