Carbon monoxide (CO) is primarily the result of incomplete combustion, which has important impacts on the atmospheric chemical cycle and climate. Improved quantitative characterization of long-term CO trends is important for both atmospheric modeling and the design and implementation of policies to efficiently control multiple pollutants. Due to the limitations of high time-resolution and high-quality long-term observational data, studies on long-term trends in the CO concentration in China are quite limited. In this study, the observational data of the concentration of CO in a rural site of Beijing during 2006-2018 was used to analyze the long-term trend in CO concentration in Beijing. The Theil-Sen method and the generalized additive model (GAM)-based method, were used to conduct the trend estimation analysis. We found that the concentration of CO at the Shangdianzi site showed a significant downward trend during 2006-2018, with a decline rate of 22.8 ± 5.1 ppbV per year. The declining trend in CO also showed phasic characteristics, with a fast decreasing rate during the period of 2006-2008, stable variations during the period of 2009-2013 and a continuous downward trend after 2013. The declining trend in the CO concentration in the south to west (S-W) sectors where the polluted air masses come from is more rapid than that in the sectors where the clean air masses come from. The declining trend in the CO concentration implies the improved combustion efficiency and the successful air pollution control policies in Beijing and the surrounding area.
Keywords: Carbon monoxide; Generalized additive model (GAM)-based method; Long-term trend; Stratified analysis; Theil-Sen method.
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