| Summary: | A non-local patch regression (NLPR) denoising-enhanced differential broadband photoacoustic (PA) sensor was developed for the high-sensitive detection of multiple trace gases. Using the edge preservation index (EPI) and signal-to-noise ratio (SNR) as a dual-criterion, the fluctuation was dramatically suppressed while the spectral absorption peaks were maintained by the introduction of a NLPR algorithm. The feasibility of the broadband framework was verified by measuring the C<sub>2</sub>H<sub>2</sub> in the background of ambient air. A normalized noise equivalent absorption (NNEA) coefficient of 6.13 × 10<sup>−11</sup> cm<sup>−1</sup>·W·Hz<sup>−1/2</sup> was obtained with a 30-mW globar source and a SNR improvement factor of 23. Furthermore, the simultaneous multiple-trace-gas detection capability was determined by measuring C<sub>2</sub>H<sub>2</sub>, H<sub>2</sub>O, and CO<sub>2</sub>. Following the guidance of single-component processing, the NLPR processed results showed higher EPI and SNR compared to the spectra denoised by the wavelet method and the non-local means algorithm. The experimentally determined SNRs of the C<sub>2</sub>H<sub>2</sub>, H<sub>2</sub>O, and CO<sub>2</sub> spectra were improved by a factor of 20. The NNEA coefficient reached a value of 7.02 × 10<sup>−11</sup> cm<sup>−1</sup>·W·Hz<sup>−1/2</sup> for C<sub>2</sub>H<sub>2</sub>. The NLPR algorithm presented good performance in noise suppression and absorption peak fidelity, which offered a higher dynamic range and was demonstrated to be an effective approach for trace gas analysis.
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