相对湿度和PM2.5浓度对大气能见度的影响研究:基于小时资料的多站对比分析

Impacts of relative humidity and PM2.5 concentration on atmospheric visibility: A comparative study of hourly observations of multiple stations

  • 摘要: 为了全面分析浙江省不同区域能见度变化基本特征及影响机理,基于杭州、宁波、温州3个国家基本气象站2013-2014年逐时能见度观测资料,比较分析了3市能见度变化的基本特征。发现3市不同等级能见度出现频率基本一致,随着能见度等级的提高,出现频率逐渐降低;从能见度的日变化来看,07时(北京时)前后最低,之后缓慢上升,14-15时达到最高,随后逐渐下降;全年有两个能见度较低时段,分别出现在12月-次年2月和5-6月;总体而言,宁波能见度最优,杭州和温州大体相当。功率谱分析结果表明,3市能见度均有显著的日周期,高频波段呈现出多个显著谱峰,低频波段存在若干显著谱峰。进一步开展机理分析,发现相对湿度和PM2.5浓度是调制大气能见度的关键因子,相对湿度增大、PM2.5浓度升高导致能见度降低。在同一相对湿度等级下,初始阶段能见度随PM2.5浓度的升高迅速降低,到达“拐点”之后降低速率趋于缓慢。在同一PM2.5浓度水平下,相对湿度越大,能见度越低,说明水汽对能见度也有重要影响。基于相对湿度和PM2.5浓度两个因子,采用非线性拟合方案构建了大气能见度定量统计模型,总体而言模型拟合效果较好。最后针对研究中存在的不足和未来值得进一步发掘的科学问题进行了讨论。

     

    Abstract: To comprehensively investigate fundamental characteristics and associated influencing mechanisms in different regions of Zhejiang province, based on hourly visibility data during 2013-2014 at Hangzhou station, Ningbo station and Wenzhou station, comparative analysis is conducted to study visibility variability at different time-scales for the three cities. It is found that the occurrence frequency of different visibility levels for the three cities are broadly consistent; with the rise of visibility level, the occurrence frequency gradually decreases. Besides, the visibility displays significant diurnal cycle. There are two low-visibility periods during the year, i. e. December to February and May to June. Generally speaking, the visibility in Ningbo is better while those in Hangzhou and Wenzhou are similar. Power spectrum analysis indicates that visibility in the three cities exhibits significant diurnal periodicity; many distinct peaks occur in the high-frequency range, and some peaks are also prominent in the low-frequency band. Further studies have been carried out to investigate the mechanism responsible for the change in visibility. Relative humidity and PM2.5 concentration are critically important and can effectively influence visibility. Increases in relative humidity and PM2.5 concentration can lead to the decline of visibility. At the same relative humidity level, the visibility drops rapidly in the beginning but decreases much slower after the "point of inflection". At the same level of PM2.5 concentration, the visibility gradually falls with the elevation of the relative humidity, which proves the importance of water vapor. Using the relative humidity and PM2.5 concentration as the impact factors, a quantitative statistical-model is constructed with nonlinear fitting scheme. It is demonstrated that the fitting result is pretty good. Finally, some existing problems and valuable scientific issues are discussed.

     

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