基于复杂网络的中国臭氧拓扑特征

伴随着颗粒物浓度的快速下降，大气臭氧（O₃）污染呈快速上升和蔓延态势，已成为制约我国空气质量持续改善的瓶颈问题之一.因此，理清O₃浓度变化特征对于改善空气质量有重要意义.应用复杂网络方法，基于城市间O₃浓度的相关关系和其时滞，构建中国O₃浓度网络，并分析O₃浓度的关联结果和传输特征.结果表明，统计指标度、加权度和连边长度的概率密度函数遵循幂律分布，这说明O₃浓度的变化不是随机的，存在一定的规律性.加权度的空间分布分析表明，加权度的高值集中在京津冀和周边地区，与O₃浓度高值区分布一致.其中，北京、天津和河北东部（渤海湾沿线）城市向其他城市传输的能力较强.并且，冬季传输能力强于其它季节，主要是受到冬季风的影响.研究结果不仅有助于理解O₃浓度变化特征，也是复杂网络方法应用到大气环境中的有益尝试.

Complex Networks Reveal the Characteristics of Ozone in China

Along with the rapid decline in fine particulate matter concentrations, ozone (O₃) pollution is rapidly rising and spreading, which has become one of the critical issues that limit the improvement of air quality in China. It is important to understand the characteristics of O₃ concentration changes to improve air quality. In this study, we applied the complex network method to construct an O₃ concentration network in China and analyze the characteristics and transport of O₃ concentrations. The study has shown that the probability density functions of weighted degree and edge length followed a power-law distribution, which indicated that the variation in O₃ concentration was not random behavior. The analysis of the spatial distribution of the weighted degree showed that the higher weighted degrees were concentrated in the Jing-Jin-Ji-region and its surrounding areas, which was consistent with the distribution of the higher values of O₃ concentrations. Cities in Beijing, Tianjin, and eastern Hebei (along the Bohai Bay) had a strong transmission ability to other cities. Thus, more control is needed in the Jing-Jin-Ji-region because this area can export O₃ pollution to other cities. Moreover, the transmission capacity in winter was stronger than that in other seasons, which was mainly affected by the winter monsoon. The results of this study not only aid understanding of the characteristics of O₃ concentration variabilities but are also a useful application of complex network methods to the atmospheric environment.