| 桂林城区大气能见度与颗粒物浓度和气象因子关系研究 |
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| 引用本文： | 龙凤翔,张瑀琳. 桂林城区大气能见度与颗粒物浓度和气象因子关系研究[J]. 气象与环境学报, 2020, 36(1): 21-27. DOI: 10.3969/j.issn.1673-503X.2020.01.003 |
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| 作者姓名： | 龙凤翔 张瑀琳 |
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| 作者单位： | 桂林市气象局, 广西 桂林 541001 |
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| 基金项目： | 中国气象局华南区域气象中心科技攻关项目(GRMC2014M12);桂林市科技攻关项目(20150127-2)共同资助 |
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| 摘 要： | 利用2015年1月至2017年6月桂林国家基本气象站能见度、相对湿度、气温、气压、降水等气象要素和PM10、PM2.5、PM1.0颗粒物质量浓度资料，分析桂林城区大气能见度与颗粒物浓度和气象因子之间关系。结果表明：桂林城区大气能见度和PM10、PM2.5、PM1.0呈对数关系，相关系数分别为-0.341、-0.461、-0.509，颗粒物对大气能见度影响在相对湿度为60%—70%时最为显著。在各气象因子中，大气能见度与风速的相关性最好，其次为相对湿度，与风速呈二次函数关系，与相对湿度呈幂指数关系，与温度相关性较小，与气压在秋冬季节呈正相关，相关系数冬季可达0.301，但在春、夏季节相关性不显著；利用颗粒物浓度和气象要素建立8种大气能见度非线性统计回归模型，比较后发现利用PM1.0、风速、相对湿度、气温等因子建立的不同季节大气能见度拟合公式在实际检验中效果最优，能较好地模拟桂林地区大气能见度的变化。
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| 关 键 词： | 大气能见度 颗粒物浓度 气象因子 非线性相关 回归模型 |
| 收稿时间： | 2018-11-28 |
Relationship between atmospheric visibility and particulate matter concentration and meteorological parameters in Guilin urban area |
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| Feng-xiang LONG,Yu-lin ZHANG. Relationship between atmospheric visibility and particulate matter concentration and meteorological parameters in Guilin urban area[J]. Journal of Meteorology and Environment, 2020, 36(1): 21-27. DOI: 10.3969/j.issn.1673-503X.2020.01.003 |
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| Authors: | Feng-xiang LONG Yu-lin ZHANG |
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| Affiliation: | Guilin Meteorological Service, Guilin 541001, China |
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| Abstract: | The relationships between atmospheric visibility and particulate matter(PM)concentrations and meteorological parameters in the urban area of Guilin city were analyzed using the meteorological observation data(including visibility,wind speed,relative humanity,air temperature,air pressure,rainfall,etc)and particulate matter(PM10,PM2.5,and PM1.0)mass concentrations observed at the Guilin National Basic Meteorological Station from January 2015 to June 2017.The results indicated that there is a logarithmic function relationship between atmospheric visibility and PM10,PM2.5,and PM1.0,with the correlation coefficients of-0.341,-0.461 and-0.509,respectively.The effect of PM on visibility is most remarkable when relative humidity varied between 60%and70%.Atmospheric visibility has the largest correlation with wind speed in a quadratic function relationship,followed by relative humidity in a power-law relationship.Visibility has a small correlation with air temperature,and a positive correlation with air pressure in autumn and winter,with a correlation coefficient of 0.301 in winter,but such correlation is poor in spring and summer.We establish eight non-linear statistical regression models to predict atmospheric visibility using different meteorological parameters and PM concentrations.The model shows the best performance to simulate the variation of visibility in different seasons when considering PM10,wind speed,relative humidity,and air temperature. |
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| Keywords: | Atmospheric visibility Particulate matter concentration Meteorological parameter Non-linear correlation Regression model |
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