长三角城市群PM_(2.5)时空变化和影响因素分析

Spatio-temporal Variations in PM_(2.5)and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration

为协调经济发展与环境污染之间的矛盾,实现经济社会的可持续发展.以长三角城市群为研究区,基于PM_(2.5)浓度和气象数据,分析PM_(2.5)浓度的时空变化规律,并利用小波相干(WTC)、偏小波相干(PWC)和多小波相干(MWC),评估PM_(2.5)与气象因子在时频域中的多尺度耦合振荡.结果表明:①长三角城市群PM_(2.5)浓度年均值由西北向东南梯度递减,高值区域空间范围逐年缩小.PM_(2.5)浓度季节均值与年均值的空间分布特征相似,并且具有冬季最高,夏季最低,春秋过渡的特点.②PM_(2.5)浓度从2015~2021年逐年下降,达标率逐年上升.PM_(2.5)浓度差异逐年缩小,具有动态收敛性特征.PM_(2.5)浓度在夏季的收敛性大于冬季.PM_(2.5)浓度日均值具有U型振荡特征,整个研究期间PM_(2.5)浓度等级为优和良的天数占比分别为49.72%和41.45%.③PM_(2.5)与气象因子的相干性在不同时频域上存在差异.时频尺度不同,影响PM_(2.5)的主控因子也不尽相同.在所有时频尺度上,WTC结果表明风速可作为解释PM_(2.5)变化的最佳变量,PWC结果表明温度可作为解释PM_(2.5)变化的最佳变量.④时频尺度越大,多变量组合解释PM_(2.5)变化的相互作用越强,而温度和风速的协同作用可以更好地解释PM_(2.5)变化.结果可为长三角城市群空气污染防治提供参考.

To coordinate the contradiction between economic development and environmental pollution and achieve the sustainable development of the economy and society,the spatio-temporal variations in PM_(2.5)were analyzed based on PM_(2.5)concentration and meteorological data of the Yangtze River Delta(YRD)urban agglomeration.Wavelet transform coherence(WTC),partial wavelet coherence(PWC),and multiple wavelet coherence(MWC)were used to analyze the multi-scale coupling oscillation between PM_(2.5)and meteorological factors in the time-frequency domain.The results showed that:①the concentration of PM_(2.5)in the YRD decreased from northwest to southeast,and the spatial range with high PM_(2.5)concentration decreased annually.The spatial distribution characteristics of the seasonal average PM_(2.5)concentration were similar to those of the annual average PM_(2.5)concentration.PM_(2.5)concentration exhibited the seasonal variation characteristics of high in winter,low in summer,and transitioning between spring and autumn.②PM_(2.5)concentration decreased from 2015 to 2021,and the compliance rate increased.The difference in annual average PM_(2.5)concentration was decreased with dynamic convergence characteristics.The convergence of PM_(2.5)concentration in summer was greater than that in winter.During the whole study period,the daily average PM_(2.5)concentration showed a"U"distribution,and the proportion of days with excellent and good PM_(2.5)levels were 49.72%and 41.45%,respectively.③The wavelet coherence between PM_(2.5)and meteorological factors was different in different time-frequency domains.The main factors affecting PM_(2.5)were different in different time-frequency scales.At all time-frequency scales,WTC and PWC showed that wind speed and temperature were the best explanatory variables of PM_(2.5)variation,respectively.④The larger the time-frequency scale,the stronger the interaction of multi-factor combinations to explain PM_(2.5)variations.The synergistic effect of temperature and wind speed could better explain the variation in PM_(2.5).These results can provide reference for air pollution control in the YRD.