Observation of Atmospheric Water Vapor and Its Stable Isotopes at the Seaside Based on Fourier Transform Infrared Spectroscopy
Objective Water vapor,the most prevalent greenhouse gas in Earth's atmosphere,plays a pivotal role in atmospheric chemistry and climate dynamics.Its sources,sinks,and transportation mechanisms are integral to the hydrological cycle.Analyzing the isotopic composition of water vapor sheds light on diverse hydrological processes.Furthermore,concurrent observations of atmospheric water vapor and its isotopes offer insights into the origins of atmospheric humidity across various regions.Ground-based Fourier Transform Infrared Spectroscopy(FTIR)technology is a powerful tool for remotely sensing atmospheric gases through the collection of solar spectra,characterized by high accuracy and precision.A portable FTIR spectrometer is employed to conduct continuous observations at the Shenzhen Observatory over a period of approximately two weeks.It successfully collects the solar near-infrared(NIR)spectra of the coastal atmosphere,leading to the derivation of measurement results for water vapor and its stable isotopes in the ambient atmosphere through sophisticated inversion techniques.Methods The experimental setup for this study primarily included a portable FTIR spectrometer,an automated sun tracker,a comprehensive meteorological station,and a dedicated computer system.This spectrometer utilized natural sunlight as its primary incident light source,while the sun tracker continuously and accurately followed the sun's position in real time.The solar rays were precisely channeled into the interferometer,where the resulting interference pattern was captured by a sensitive detector.This pattern was then transformed into a detailed NIR spectrum through a Fourier transform process.The spectrometer was designed to capture a NIR spectral range spanning 5000-11000 cm-1,offering a spectral resolution of 0.5 cm-1.The core of the analysis lay in the utilization of a sophisticated non-linear least squares iterative algorithm,which enabled precise inversion of the vertical column concentration of the target gas.This involved a two-step process:initial forward modelling followed by meticulous spectral iterative fitting calculations.Upon determining the vertical column concentration of the sample gas,the dry air mole fraction(DMF)was then derived by correlating it with the total column concentration of dry air.Results and Discussions In our study,several specific spectral window bands are meticulously selected for the inversion of characteristic absorption features of atmospheric H2O and its isotope,HDO,in NIR spectroscopy.The average root mean square error of the residual fits for H2O and HDO spectra stands at 0.026％and 0.032％,respectively(Fig.2,Fig.3).This small residual indicates a high-quality fit to the solar spectra.During the observation period,the mean molar mixing ratio of water vapor(XH2O)in the dry air column demonstrates an increasing trend,with a standard deviation of 27.42 mg/kg.Notably,the peak concentration of XH2O is recorded at 5298.21 mg/kg on March 11,exhibiting a daily variation range of 1111.69 mg/kg,while the minimum value of 1377.45 mg/kg occurs on March 6,with a much narrower daily variation range of 323.09 mg/kg(Fig.6).To explore the relationship between surface XH2O and temperature during this period,a correlation analysis is performed,revealing a strong correlation between the natural logarithm of XH2O ln(XH2O)and surface temperature,evidenced by a high correlation coefficient of 0.94(Fig.7).Regarding the isotopic ratio of water vapor(δD),our observations indicate a variation range from-122.52 ‰ to 16.54‰,averaging at-72.83 ‰.The lowest δD value,averaging at-103.43‰,is measured on March 6,while the highest average value of-53.36‰ is observed on March 3(Fig.8).These δD values are primarily influenced by factors such as humidity,characteristics of water vapor evaporation,and the isotopic composition of the atmosphere in the measurement area.Employing the Keeling ratio method,we observe the water vapor evaporation characteristics of the coastal city.The evaporative δDET during the measurement period varies between(-289.92±8.89)‰ and(21.79±7.19)‰,averaging at(-111.85±14.51)‰(Fig.11).The significant variability in 8DET values in the Shenzhen area can be attributed to its coastal location,where evaporation predominantly originates from the sea.This evaporation process is influenced by various factors,including sunlight,temperature,wind force,and humidity.Conclusions This study utilizes near-infrared solar absorption spectra captured by a portable Fourier Transform Infrared(FTIR)spectrometer.We employ the advanced PROFFAST inversion algorithm to accurately derive the column concentrations of atmospheric H2O and its isotope,HDO.A key aspect of our experiment involves vigilant monitoring of the Instrument Line Shape(ILS)and Xair,revealing that the spectrometer maintains excellent long-term measurement stability.We simultaneously correct portable FTIR instrument readings with high-resolution FTIR instrument readings.Our research,leveraging the portable FTIR spectrometer,focuses on the coastal atmosphere of Shenzhen.We successfully measure water vapor and its isotopes,yielding valuable data on the column concentration of water vapor,the water vapor isotope ratio,and the characteristics of water vapor evapotranspiration during the measurement period.These results demonstrate the spectrometer's capability to precisely monitor variations in water vapor and its stable isotopes in a coastal atmospheric setting.The data provided by these measurements offer a robust scientific foundation for understanding and tracking the diffusion and transport dynamics of water vapor in the ambient atmosphere.In future,our research endeavors will concentrate on the accurate retrieval of the water vapor isotope H28O from solar absorption spectra.By integrating data on H2O,HDO,and H28O,we aim to achieve a more comprehensive understanding of the water cycle,enhancing our insights into its complexities and interactions within the Earth's atmosphere.
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