Long-term trend in CHF sub(2)Cl (HCFC-22) from high spectral resolution infrared solar absorption measurements and comparison with in situ measurements

• Published in: Journal of quantitative spectroscopy & radiative transfer Vol. 90; no. 3-4; pp. 367 - 375
• Main Authors: Rinsland, C P, Chiou, L S, Goldman, A, Wood, S W
• Format: Journal Article
• Language: English
• Published: 01-02-2005
• Subjects: IN, Pacific; USA, Colorado; USA, Arizona
• ISSN: 0022-4073
• DOI: 10.1016/j.jqsrt.2004.04.008

The average tropospheric volume mixing ratio of CHF sub(2)Cl (HCFC-22) has been retrieved from a time series of high spectral resolution ground-based infrared solar absorption spectra recorded with the McMath Fourier transform spectrometer located at the U.S. National Solar Observatory facility on Kitt Peak in southern Arizona (31.9 degree N, 111.6 degree W, 2.09 km altitude) for the time period October 1987-November 2002. The retrievals are based on fits to the well- isolated, unresolved 2 nu sub(6) Q branch at 829.05 cm super(-1) and the SFIT2 retrieval algorithm. The measured daily averages show a near linear rise per year in the mean tropospheric volume mixing ratio as a function of time with a best fit yielding an average increase rate of (5.66+/-0.15) parts per trillion (10 super(-12)) by volume per year, corresponding to (6.47+/-0.17)%yr super(-1), 1 sigma, at the beginning of the time series. The tropospheric mixing ratios retrieved from the solar spectra have been compared with monthly average surface flask sampling measurements from the Climate Monitoring and Diagnostic Laboratory (CMDL) station at Niwot Ridge, Colorado (40.0 degree N, 105.5 degree W, 3013 m altitude), archived measurement from the same location, and early CMDL northern hemisphere Pacific cruise measurements. The average ratio of the retrieved tropospheric mixing ratio relative to the CMDL surface mixing ratio is 1.053 for the overlapping 1987 to 2002 time period. The retrieved mean tropospheric mixing ratio is consistent with the surface measurements within the errors estimated for the remote sensing observations.