标题： 中国$PM_{2.5}$浓度的相关性和标度行为 显示英文标题

标题： Correlation and scaling behaviors of $PM_{2.5}$ concentration in China

摘要： 空气污染已成为一个主要问题，并引发了广泛的环境和健康问题。 气溶胶或颗粒物是大气的重要组成部分，并可以在复杂的气象条件下传输。 基于$PM_{2.5}$的观测数据，我们开发了一种网络方法来研究和量化它们的传播和扩散模式。 我们计算了不同季节内各站点之间的时间滞后交叉相关函数。 相关性的概率分布随季节变化。 发现四个季节的概率分布可以通过相关性的平均值和标准差缩放为一个标度函数。 这种季节性标度行为表明，在不同季节的$PM_{2.5}$浓度相关性背后存在相同的机制。 此外，从复杂网络的加权和方向度出发，研究了$PM_{2.5}$浓度的不同特性。 加权度揭示了冬季和华北平原的$PM_{2.5}$浓度最强的相关性。 这些方向度显示了沿戈壁和内蒙古、华北平原、中原地区和长江三角洲的$PM_{2.5}$的净影响。 显示英文摘要

摘要： Air pollution has become a major issue and caused widespread environmental and health problems. Aerosols or particulate matters are an important component of the atmosphere and can transport under complex meteorological conditions. Based on the data of $PM_{2.5}$ observations, we develop a network approach to study and quantify their spreading and diffusion patterns. We calculate cross-correlation functions of time lag between sites within different season. The probability distribution of correlation changes with season. It is found that the probability distributions in four seasons can be scaled into one scaling function with averages and standard deviations of correlation. This seasonal scaling behavior indicates there is the same mechanism behind correlations of $PM_{2.5}$ concentration in different seasons. Further, from weighted and directional degrees of complex network, different properties of $PM_{2.5}$ concentration are studied. The weighted degrees reveal the strongest correlations of $PM_{2.5}$ concentration in winter and in the North China plain. These directional degrees show net influences of $PM_{2.5}$ along Gobi and inner Mongolia, the North China plain, Central China, and Yangtze River Delta.