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作 者:梁海发 罗莹华[1] 冯海晴 朱迪迪 陈丽珍 韦博淇 LIANG Hai-fa;LUO Ying-hua;FENG Hai-qing;ZHU Di-di;CHEN Li-zhen;WEI Bo-qi(College of Tourism Geographe,Shaoguan University,Shaoguan 512005,Guangdong,China)
机构地区:[1]韶关学院旅游与地理学院
出 处:《韶关学院学报》2019年第6期76-81,共6页Journal of Shaoguan University
基 金:广东省大学生创新创业训练计划项目(201810576098)
摘 要:基于2017年韶关市5个监测点的PM2.5浓度值和对应的气象参数,采用数学统计法和非参数分析法,结合时间和空间的分布差异来探讨出PM2.5的分布规律,并分析出其与气象因子的相互关系.结果表明:韶关市PM2.5在四季中为冬季浓度最高,春季和秋季的浓度居中,夏季浓度最低;月浓度呈“V”字型的分布规律;日浓度呈连续性的脉冲状变化;白天浓度低于夜晚浓度,表现为双尖峰单深谷的结构分布特征.空间分布梯度规律从高到低排列为:曲江监测站、市八中、碧湖山庄、园林处和韶关学院.PM2.5浓度变化受多重气象因子作用,温度、湿度和风速都对PM2.5产生负相关作用,其中温度和风速降低PM2.5浓度的作用更为显著.Based on the PM2.5 concentration values and corresponding meteorological parameters of five monitoring points in Shaoguan City in 2017, the distribution regularity of PM2.5 was discussed by using mathematical statistics and non-parametric analysis method, combining with the difference of time and space distribution, and the relationship between PM2.5 and meteorological factors was analyzed.The results showed that the concentration of PM2.5 in Shaoguan City was the highest in winter, the middle in spring and autumn, and the lowest in summer;the monthly concentration showed a "V" distribution pattern;the daily concentration showed a continuous pulse change;the daytime concentration was lower than the night concentration, showing the structural distribution characteristics of double peaks and single deep valley.The spatial distribution gradient regularity ranges from high to low: Qujiang Monitoring Station, City Bazhong, Bihu Villa, Landscape Architecture Department and Shaoguan College.The change of PM2.5 concentration is affected by multiple meteorological factors. Temperature, humidity and wind speed all have negative correlation with PM2.5, and the effect of temperature and wind speed on reducing PM2.5 concentration is more significant.
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