RESUMO
Detection of gas concentration with tunable diode laser absorption spectroscopy (TDLAS) techniques is affected by baseline drift and high-frequency noise. Therefore, how to remove the systematic noises has been a hot spot. This paper analyzes the significance of singular value decomposition (SVD) in TDLAS detection system with two different methods of constructing a matrix, and it discusses the differences of processing results for different noises. The second harmonic signal is arranged in a matrix and decomposed. We select the appropriate threshold and putthose singular values smaller than the threshold into zero, then reconstruct the matrix. Experiments show that SVD method does not require additional system components or pass into the zero gas to subtract background. This method is able to remove noises of TDLAS system quickly and effectively. We found that the method of constructing a hankel matrix is suitable for removing high-frequency noise. However, the method of constructing a continuous-cutoff-signal matrix is suitable for removing baseline drift. For example, we set up a TDLAS system to measure the concentration of NH3 while the noise removal rate of the second harmonic curve is up to 80% with this method.
RESUMO
Atmospheric aerosol over Macao was monitored by using a 355 nm Mie scattering lidar during the dust event on March 22nd, 2010. Vertical profiles of aerosol extinction coefficients were obtained and correlated with local PM10 concentration. The near-surface aerosol extinction coefficients have good agreement with PM10 concentration values. The aerosol extinction vertical profiles showed that there were distinct layers of dust aerosol concentration. The source and tracks of dust aerosol were analyzed by back-trajectory simulation. Observations showed that this lidar could run well even in dust storm episode, and it would help to further the study on aerosol properties over Macao.