| 浙江省O3浓度时空格局及驱动因子 |
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| 引用本文： | 沈培福,靳全锋,周雨欣,徐端妙,黄海松. 浙江省O3浓度时空格局及驱动因子[J]. 环境科学研究, 2022, 35(9): 2136-2146. DOI: 10.13198/j.issn.1001-6929.2022.06.29 |
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| 作者姓名： | 沈培福 靳全锋 周雨欣 徐端妙 黄海松 |
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| 作者单位： | 1.丽水职业技术学院，浙江 丽水 323000 |
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| 基金项目： | 国家自然科学基金项目(No.31770697)；浙江大花园建设项目(No.DHYB1008)；景宁畲族自治县科技计划项目(No.2022C11) |
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| 摘 要： | 气象因子对臭氧(O3)浓度有重要影响，为探索O3浓度时空变化及相关因子，利用多元线性回归和后向轨迹聚类分析2014—2019年浙江省O3浓度和气象因子数据. 结果表明:①浙江省O3浓度时空分布不均匀，季节性变化差异显著，总体呈夏季>秋季>春季>冬季的特征，年均值呈上升趋势；春季、夏季、秋季和全年O3浓度均于07:00左右达最小值，之后呈上升趋势，至15:00达峰值后降低，冬季O3浓度最小值出现时间较其他季节晚1 h左右. 高浓度O3主要分布在浙江省东北部及北部区域. ②多元线性回归模型结果表明，多元线性回归模型影响因子和拟合效果存在季节性差异，其中，春、秋两季蒸发量对O3浓度的贡献率均超过20%，夏季相对湿度对O3浓度的贡献率超过40%，秋季日光照时长对O3浓度的贡献率超过40%，秋、冬两季NO2浓度对O3浓度的贡献率均超过35%. 春季多元线性回归模型均方根误差(RMSE)、均方绝对百分比误差(MAPE)和变异解释量(R2)分别为0.213、26.45%和0.422，夏季分别为0.234、30.49%和0.359，秋季分别为0.169、24.02%和0.445，冬季分别为0.154、34.14%和0.419. 研究表明，浙江省O3浓度具有显著的时空分布特征，多元线性回归模型拟合结果在浙江省春、秋两季显著优于夏、冬两季.
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| 关 键 词： | 浙江省 臭氧(O3) 时空格局 驱动因子 多元线性回归 |
| 收稿时间： | 2021-07-08 |
Spatial-Temporal Pattern and Driving Factors of Surface Ozone Concentrations in Zhejiang Province |
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| Affiliation: | 1.Lishui Vocational and Technical College, Lishui 323000, China2.Forestry College, Fujian Agriculture and Forestry University, Fuzhou 350002, China |
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| Abstract: | Meteorological factors are essential in the surface ozone (O3) concentration. In order to explore the space-time changes and related factors, the surface O3 concentration and meteorological factor data in Zhejiang Province from 2014 to 2019 are clusters analyzed using multiple linear regression and backward trajectory. The result shows that: (1) Time-space distribution of surface O3 concentration is not uniform, and the seasonal variation is significant in terms of time. It generally shows the distribution of summer > autumn > spring > winter, with an upward trend year by year. The hourly average ozone concentration reaches a minimum of around 07:00 in spring, summer, autumn, and the whole year. After that, it shows a gradual upward trend until it reaches a peak at 15:00. The minimum ozone value in winter is about 1 hour later than in other seasons; the distribution is mainly concentrated in the northeast and northern parts of Zhejiang Province. (2) The multiple linear regression model results show a significant difference in impact factors in different season models. The impact strength of the final models in different seasons is quite different. The large-scale evaporation in spring and autumn contributes to more than 20% O3 concentration. In comparison, the average relative humidity in summer contributes to more than 40% of O3 concentration, and the autumn illumination time contribution exceeds 40%. The NO2 contribution of autumn and winter exceeds 35%. The root-mean-square error (RMSE) of the multiple linear regression model, mean square absolute percentage error (MAPE), and variation interpretation (R2) in spring are 0.213, 26.45% and 0.422, respectively. In summer, they are 0.234, 30.49% and 0.359, respectively. In autumn, these figures are 0.169, 24.02% and 0.445, respectively; in winter they are 0.154, 34.14% and 0.419, respectively. The research shows that the earth's surface ozone has significant space and temporal distribution characteristics. Multiple linear regression model fitting results are significantly better in spring and autumn than in summer and winter. |
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