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南京大气能见度变化规律及影响因子分析 被引量:35

Characterization of visibility variation trend and its influence factors in Nanjing
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摘要 利用累积百分率法、Ridit中值分析法、"非常好"能见度出现频率法以及平均能见度年际和季节变化法,对1980—2005年南京大气能见度年际变化趋势进行分析,发现1980—1984年能见度呈上升趋势,1985年以后则在波动中呈明显下降趋势。26 a中,日均大气能见度最小值为0.55 km,最大值为29.25 km,平均值为8.59 km。大气能见度具有明显的日变化和季节变化特征,一日之中,14时最好,08时最差;一年之中,冬季能见度最低,夏季最高。能见度与相对湿度呈负相关,与风速呈正相关,与温度和气压的相关性相对较小。PM10是影响南京地区大气能见度的首要污染物,通过对能见度与PM10平均质量浓度进行曲线拟合发现,二者呈负相关,复相关系数在秋季最高,夏季最低。由统计预报方程可知,空气污染和气象条件协同作用对能见度的影响在春季、秋季、冬季较为明显,夏季则相对较差。 Visibility variation trends from 1980 to 2005 have been constructed using four different statis- tical methods:Ridit analysis, cumulative percentiles, frequency of “very good” visibility, and annual and seasonal means.Improvements in visibility were experienced from 1980 to 1984.A decline trend can be observed after 1985 with some fluctuations in the process.In these 26 years, the mean daily visibility was 8.59 km with the maximum at 29.25 km and the minimum at 0. 55 km, respectively.There were obvious seasonal and daily variation features in visibility.It was worst in winter and best in summer in one year while it was worst at 08:00 BST and best at 14:00 BST in one day.Visibility showed a posi- tive correlation with wind speed and a negative correlation with relative humidity.However,temperature and atmospheric pressure showed comparatively little correlation with it.PM10 was the major pollutant in Nanjing.Curve estimation of daily mean PM10 mass concentration and the visibility presented a negative correlation and the coefficient was the largest in autumn and the smallest in summer.A regression model based on relative humidity, PM10, wind speed and temperature has been developed.There were seasonal differences in the coactions of air pollution and meteorological condition on visibility, which was worse in summer than that in the other three seasons.
出处 《大气科学学报》 CSCD 北大核心 2014年第1期91-98,共8页 Transactions of Atmospheric Sciences
基金 国家自然科学基金资助项目(41305135 41275143) 中国科学院战略先导科技专项(B类)子课题(XDB05020206)
关键词 能见度趋势 气象要素 大气污染物 相关系数 visibility trends meteorological elements air pollutant correlation coefficient
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