基于CEEMDAN的多时间尺度的北京市PM2.5浓度影响因素研究

Study on the Influencing Factors of PM2.5 Concentration in Beijing at Multiple Time Scales Based on CEEMDAN

中文关键词:  PM_2.5  多时间尺度  影响因素  CEEMDAN  空气质量

英文关键词:PM_2.5  multiple time scales  influencing factors  CEEMDAN  air quality

中文摘要:

      研究PM_2.5浓度的主要影响因素，对提升北京市空气质量具有重要意义。与以往仅限于原始时间尺度的研究不同，本文基于CEEMDAN方法考察了多时间尺度下年平均风速、城市绿化、人口密度、产业结构和能源强度对北京市PM_2.5浓度波动的影响，并与原始时间尺度的主导因素进行对比。研究发现：原始尺度的北京市PM_2.5浓度影响因素是不同时间尺度内影响因素合力作用结果，不同时间尺度下影响因素不同。城市绿化、人口密度、产业结构和能源强度在多时间尺度中起到短期增强波动的作用，城市绿化和产业结构是贯穿于各个时间尺度的具有趋势性，决定北京市PM_2.5浓度基本走势的影响因素。

英文摘要:

      It is of great significance to study the main influencing factors of PM_2.5 concentration for improving the air quality in Beijing. Different from previous studies limited to the original time range, this paper investigates the influence of annual average wind speed, urban greening, population density, industrial structure and energy intensity on PM_2.5 concentration fluctuations in Beijing at multiple time scales based on CEEMDAN method, and compares them with the dominant factors at the original time scale. It is found that the influencing factors of PM_2.5 concentration in Beijing at the original scale are the resultant effects of influencing factors at different time scales, and the influencing factors are different at different time scales. Urban greening, population density, industrial structure and energy intensity play a role in enhancing short-term fluctuations in multiple time scales. Urban greening and industrial structure are the influencing factors that have trend across all time scales and determine the basic trend of PM_2.5 concentration in Beijing.