杨明航

摘 要：为探究煤炭资源型城市鹤壁供暖期PM2.5浓度变化特征，利用MATLAB对其进行小波分析，分析PM2.5的时间序列周期和突变特征。结果表明：鹤壁市供暖期内PM2.5污染程度以良为主，占比为40.16%，严重污染天数最少，为3天;PM2.5浓度最高值出现在1月，最低值出现在3月，总体趋势为先上升后下降;Morlet小波分析结果表明鹤壁市PM2.5日均变化序列存在多时间尺度特征，第一主周期为15 d，第二主周期为50 d;鹤壁市共有4次突变事件，多发生在冬季。与陕北地区的煤炭资源型城市榆林、延安相比，鹤壁優良天数远低于二者，人口密度、地理环境也是影响空气质量的重要因素。

关键词：PM2.5;供暖期;小波分析;突变

中图分类号：X51文献标识码：A文章编码：1003-5168（2021）08-0149-03

Characteristics of PM2.5 Concentration in Heating Period of

Hebi City Based on Wavelet Analysis

YANG Minghang

（Shaanxi Key Laboratory of Disasters Monitoring & Mechanism Simulation， Baoji University of Arts and Sciences，

Baoji Shaanxi 721013）

Abstract： In order to explore the variation characteristics of PM2.5 concentration during heating period in Hebi， a coal resource-based city， the wavelet analysis of PM2.5 was carried out by using MATLAB， and the period and mutation characteristics of PM2.5 time series were analyzed. The results show that： the PM2.5 pollution degree was mainly good， accounting for 40.16%， the days of serious pollution was the least， only 3 days; the highest PM2.5 concentration appears in January， the lowest in March， the overall trend was first rising and then falling; Morlet wavelet analysis results show that the PM2.5 daily average Change Series in Hebi City has multi time scale characteristics， the first main cycle was 15 days， the second main cycle was 15 days.There were four mutation events in Hebi City， most of which occurred in winter. Compared with Yulin and Yan'an， which were both coal resource-based cities in Northern Shaanxi， the number of excellent days in Hebi was far lower than both. Population density and geographical environment are also important factors affecting air quality.

Keywords： PM2.5; heating period; wavelet analysis; mutation

PM2.5是指细颗粒物，粒径小于2.5 μm，能较长时间悬浮于空气中，具有明显的周期性变化规律[1-2]，空气中PM2.5质量浓度越高就代表空气污染越严重[3]。冬季由于供暖等活动使城市用电量增大，更容易导致PM2.5质量浓度超标。对于煤炭资源型城市，产业结构偏向于重工业，研究该种类型城市的PM2.5浓度特征，对于改善城市空气质量具有重要意义。

近年来，许多学者对PM2.5的时空分布特征进行了研究。易文利等对陕西省冬春季PM2.5时空分布特征进行了研究[4];苏明伟等对西北内陆和东部沿海地区的12座城市的PM2.5分布特征进行研究[5]。以上研究均是利用小波分析的手段对城市PM2.5特征进行分析，但对于易发生PM2.5污染事件的煤炭资源型城市的相关研究还比较少。

本文基于2019年供暖期空气质量逐小时监测数据，结合Origin和MATLAB（矩阵实验室）软件，运用小波分析对煤炭资源型城市鹤壁市供暖期PM2.5的质量浓度、周期特征进行了研究。……