Abstract: A data processing method is designed to deal with the severe baseline drift and complex
peak shape of the volatile organic compounds (VOCs) chromatography. Methods of moving
average and wavelet transform are applied to deal with the high frequency noise and
baseline drift, which ensure the accuracy of peak recognition and area calculation.
The combination of first order  and two order derivative method is
used to identify the chromatographic peaks. The Gauss curve fitting method is used
to calculate the peak area, which improves the calculation accuracy of peak area.
The experimental results show that the algorithm is very fast and the effect of the
denoising and baseline correction are obvious. The algorithm can accurately identify
overlapping peaks, acromion peaks and can get high precision of peak area calculation,
which are able to meet the requirements of VOCs data processing in ambient air.

Key words: volatile organic compounds, baseline correction, wavelet transform, peak recognition, curve fitting