颗粒物背景值研究是评估城市大气环境质量现状的一项基础性工作，也是制定和检验颗粒物防治措施及其效果的定量化参考依据。但是，目前我国城市大气污染物背景值估算结果时空分辨率较低，且存在背景值影响机制及影响因素尚不明确的问题，不能为精细化污染源管控政策的制定提供支撑。本项目拟以天津地区为研究区域，以大气细颗粒物（PM2.5）为研究对象，旨在（1）建立基于数字信号处理技术（耦合傅立叶频谱分析、交叉频谱分析和KZ滤波法）的高时间解析度背景值估算技术方法体系；（2）建立研究区大气细颗粒物背景浓度空间分布图，探究PM2.5背景值时空分异规律；（3）识别和探讨背景值影响因子及其表征方法，进而阐明细颗粒物背景值影响机制。该研究可为城市大气颗粒物污染防控政策的科学制定以及精准施策提供理论支持。

Background concentration estimation of particulate matters is a basic research of air quality assessment in urban area. It is the quantitative reference for establishing and testing the control measures of particulate matters. However, the spatio-temporal resolutions of background concentrations of air pollutants at urban scale in China are relatively low. Additionally, the influence mechanism and affecting factors of background concentration are not clear. Recent research results of background concentrations cannot support refined management of pollution sources. The study area is selected as Tianjin region, and we focus on the fine particles (PM2.5). This proposal is aimed at (1) establishing estimation method of background concentration with high temporal resolution based on digital signal processing technique (coupling Fourier spectral analysis, cross spectral analysis and Kolmogorov-Zurbenko filter); (2) establishing background concentration distribution map of PM2.5 in the study area, and discussing the law of spatio-temporal differentiation of PM2.5 background concentration; (3) indicating factors that affect the background concentration of fine particles, and exploring the influence mechanism of background concentration. This study could provide academic support to develop and implement efficient control policies of atmospheric particles in urban area.