| 2017—2019年太原南部城区夏季O3特征及其影响因子 |
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| 引用本文： | 卢盛栋,李军霞,李芬,赵俊杰,靳泽辉,李莹,刘潇. 2017—2019年太原南部城区夏季O3特征及其影响因子[J]. 气象与环境学报, 2021, 37(3): 40-46. DOI: 10.3969/j.issn.1673-503X.2021.03.006 |
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| 作者姓名： | 卢盛栋 李军霞 李芬 赵俊杰 靳泽辉 李莹 刘潇 |
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| 作者单位： | 山西省气象灾害防御技术中心,山西 太原030012;五台山气象站,山西 五台山035515;山西省气象科学研究所,山西 太原030002 |
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| 基金项目： | 山西省气象局科学技术面上项目(SXKMSFW20205222) |
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| 摘 要： | 利用2017—2019年夏季(6—8月)太原市污染物浓度和气象逐小时数据,分析了太原南部城区O3浓度及其影响因子的变化特征,通过神经网络构建了O3与其影响因子的关系模型,并进行了检验.结果表明:2017—2019年夏季太原南部城区O3浓度超标天数分别为55 d、39 d、59 d,超标主要集中在6月和7月;O3浓度日变...
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| 关 键 词： | O3浓度 气象因子 神经网络 |
| 收稿时间： | 2020-07-28 |
Analysis of the characteristics of O3 concentration and its influencing factors in summer from 2017 to 2019 in the southern urban area of Taiyuan |
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| Sheng-dong LU,Jun-xia LI,Fen LI,Jun-jie ZHAO,Ze-hui JIN,Ying LI,Xiao LIU. Analysis of the characteristics of O3 concentration and its influencing factors in summer from 2017 to 2019 in the southern urban area of Taiyuan[J]. Journal of Meteorology and Environment, 2021, 37(3): 40-46. DOI: 10.3969/j.issn.1673-503X.2021.03.006 |
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| Authors: | Sheng-dong LU Jun-xia LI Fen LI Jun-jie ZHAO Ze-hui JIN Ying LI Xiao LIU |
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| Affiliation: | 1. Shanxi Meteorological Disaster Prevention Technology Center, Taiyuan 030012, China2. Wutai Mountain Meteorological station, Shanxi 035515, China3. Shanxi Meteorological Science Research Institute, Taiyuan 030002, China |
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| Abstract: | Based on the hourly data of pollutant concentration and relative meteorological factors during summer (June to August) from 2017-2019, the distribution characteristics of O3 concentration and its influencing factors in Taiyuan were analyzed using the neural network method.The results show that, during the summer from 2017-2019, the numbers of days in which the O3 concentration exceeds the limit in Taiyuan are 55 d, 39 d, 59 d, respectively.The cases that the O3 concentration exceeds the limit mostly occur in June and July.The diurnal variation of O3 concentration is unimodal, with the lowest around 06:00, and the peak around 15:00.The conditions such as high temperature, strong radiation, low humidity, low pressure, and southwest wind can easily lead to an increase of O3 concentration in Taiyuan urban areas.The NW wind is beneficial to the diffusion of O3 concentration.The relationships of NO2 and CO with O3 concentration are negative, and the influence of NO2 is more significant.The selected cases show that the O3 concentration fluctuates with the influencing factors.The relationship between O3 concentration and the influencing factors is constructed using the neural network method, with the correlation coefficient of 0.96, the mean square root and average absolute error of 8 μg·m-3 and 6%, respectively, and TS score of 0.95.The neural network model is valuable for the O3 concentration prediction and ozone pollution control in the Taiyuan area. |
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| Keywords: | O3 concentration Meteorological factors Neural network |
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