基于大气分型的福建省臭氧浓度变化特征及归因分析

doi:10.16258/j.cnki.1674-5906.2026.10.008

生态环境学报 ›› 2026, Vol. 35 ›› Issue (10): 1576-1587.DOI: 10.16258/j.cnki.1674-5906.2026.10.008

• 研究论文【环境科学】 • 上一篇下一篇

基于大气分型的福建省臭氧浓度变化特征及归因分析

林瀚¹^,²^,³(), 刘洋俊¹^,²^,³, 王珂月⁴^,^*(), 王宏⁵^,⁶, 邬群勇¹^,²^,³

¹ 福州大学空间数据挖掘与信息共享教育部重点实验室，福建福州 350108
² 卫星空间信息技术综合应用国家地方联合工程研究中心，福建福州 350108
³ 数字中国研究院（福建），福建福州 350108
⁴ 福建华网信息科技有限公司，福建福州 350004
⁵ 福建省灾害天气重点实验室，福建福州 350008
⁶ 中国气象局海峡灾害天气重点开放实验室，福建福州 350008

收稿日期:2026-01-17 修回日期:2026-08-15 接受日期:2026-09-07 出版日期:2026-10-18 发布日期:2026-10-21
通讯作者: *E-mail: 542073173@qq.com
作者简介:林瀚（1994年生），男，博士，研究方向为大气遥感反演。E-mail: hlin@fzu.edu.cn
基金资助:
福建省自然科学基金项目(2024J08143);福建省自然科学基金项目(2024J01152757);福建省自然科学基金项目(2023J011332);福建省自然科学基金项目(2021J01463);国家自然科学基金2022年区域联合重点项目(U22A20578);福建省省属公益类科研院所基本科研专项(2023R1014003)

Variation Characteristics and Attribution Analysis of Ozone Concentration in Fujian Province Based on Atmospheric Classification

Lin Han¹^,²^,³(), Liu Yangjun¹^,²^,³, Wang Keyue⁴^,^*(), Wang Hong⁵^,⁶, Wu Qunyong¹^,²^,³

¹ Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350108, P. R. China
² National and Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou 350108, P. R. China
³ The Academy of Digital China (Fujian), Fuzhou 350108, P. R. China
⁴ Fujian Huawang Information Technology Co., Ltd., Fuzhou 350004, P. R. China
⁵ Fujian Key Laboratory of Severe Weather, Fuzhou 350008, P. R. China
⁶ Key Laboratory of Straits Severe Weather, China Meteorological Administration, Fuzhou 350008, P. R. China

Received:2026-01-17 Revised:2026-08-15 Accepted:2026-09-07 Online:2026-10-18 Published:2026-10-21

摘要/Abstract

摘要：

【目的】揭示福建省不同天气类型下臭氧浓度变化特征及其成因，为区域臭氧污染防治提供依据。【方法】使用结构化自组织映射算法（S-SOM）和混合单粒子拉格朗日积分轨迹（HYSPLIT）模型，对福建省2022年6月－2023年12月的大气环流进行天气分型和后向轨迹分析。【结果】福建省的大气环流在2022年分为4种类型，其中高压-低压过渡带型（2022年S-SOM-Ⅲ）下O_3-8h质量浓度最高（110 µg·m⁻³），2023年分为5种类型，海上低压控制型（2023年S-SOM-Ⅰ）下O_3-8h质量浓度最高（98.7 µg·m⁻³），并且2022年各天气分型臭氧质量浓度整体高于2023年（约4.85%），但都表现为沿海城市臭氧质量浓度高，内陆城市臭氧质量浓度低，平均高约45.3%。后向轨迹表明全省主要有5条气团输送路径，其中Ⅳ型占比最多（39.8%），源于台湾海峡，自平海湾向西北方输送至戴云山山脉。【结论】福建省不同天气类型下的臭氧浓度空间分布及其变化与气团输送模式和气象条件密切相关，高温、低湿、较少降水以及外来污染物输送有利于臭氧的积累，污染物输送主要源自浙江省沿海区域，经福建北部和台湾海峡沿岸输入福建省；而海洋清洁气团和高湿多雨条件不利于臭氧的生成或积累。

关键词: 天气分型, 后向轨迹分析, 臭氧, 污染物输送, 福建省

Abstract:

[Objective] This study aimed to characterize ozone (O₃) variations under different weather regimes in Fujian Province and identify their major influencing factors, thereby providing a scientific basis for regional O₃ pollution prevention and control. [Methods] The structured self-organizing map (S-SOM) algorithm and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were used to classify atmospheric circulation patterns and analyze backward air-mass trajectories over Fujian Province from June 2022 to December 2023. [Results] Atmospheric circulation over Fujian Province was classified into four weather regimes in 2022. Among them, the high-low pressure transition regime (S-SOM-III in 2022) exhibited the highest O_3-8h mass concentration (110 µg·m⁻³). In 2023, five weather regimes were identified, with the marine low-pressure-dominated regime (S-SOM-I in 2023) exhibiting the highest O_3-8h mass concentration (98.7 µg·m⁻³). Overall, O₃ mass concentrations under the weather regimes in 2022 were approximately 4.85% higher than those in 2023. In both years, O₃ mass concentrations were higher in coastal cities than in inland cities, with an average difference of approximately 45.3%. Backward trajectory analysis identified five major air-mass transport pathways across the province, among which Pathway IV accounted for the largest proportion (39.8%). This pathway originated from the Taiwan Strait and transported air masses northwestward from Pinghai Bay to the Daiyun Mountains. [Conclusion] The spatial distribution and variation of O₃ concentrations under different weather regimes in Fujian Province were closely related to air-mass transport patterns and meteorological conditions. High temperatures, low relative humidity, limited precipitation, and external pollutant transport favored O₃ accumulation. Pollutant transport mainly originated from the coastal areas of Zhejiang Province and entered Fujian Province through northern Fujian and along the coast of the Taiwan Strait, whereas clean marine air masses and humid, rainy conditions were unfavorable for O₃ formation or accumulation.

Key words: weather classification, backward trajectory analysis, ozone, pollutant transport, Fujian Province

中图分类号:

林瀚, 刘洋俊, 王珂月, 王宏, 邬群勇. 基于大气分型的福建省臭氧浓度变化特征及归因分析[J]. 生态环境学报, 2026, 35(10): 1576-1587.

Lin Han, Liu Yangjun, Wang Keyue, Wang Hong, Wu Qunyong. Variation Characteristics and Attribution Analysis of Ozone Concentration in Fujian Province Based on Atmospheric Classification[J]. Ecology and Environmental Sciences, 2026, 35(10): 1576-1587.

图/表 14

表1 S-SOM算法流程

Table 1 Workflow of the S-SOM algorithm

输入：一组向量，X={x₁, x₂, …, x_N}
输出：一组原型，Y={y₁, y₂, …, y_M}
开始
随机初始化Y={y₁, y₂, …, y_M}
循环
随机选择x∈X
找到与x最匹配的最佳单元y^*
y^=max(S_x*_,_y), y∈Y 训练
对于所有的y∈Y
y=y+ηh(y, y^*)(x−y)
更新学习率η和邻域函数h
直到终止条件为真
结束

图1 全时段与四季逐小时O3质量浓度均值变化特征

Figure 1 Hourly mean O? concentration variation characteristics for the entire period and each season

图2 2022年与2023年的轮廓系数均值结果（a）2022年SOM对应轮廓系数（b）2023年SOM对应轮廓系数

Figure 2 Mean silhouette coefficient results for 2022 and 2023

图3 2022年和2023年福建省天气分型结果

Figure 3 Weather regime results for Fujian Province in 2022 and 2023

表2 福建省2022年S-SOM分型结果对应的平均气象条件

Table 2 Mean meteorological conditions for the 2022 S-SOM weather regime in Fujian Province

气象条件	S-SOM-I	S-SOM-II	S-SOM-III	S-SOM-IV
地表温度/℃	27.7	26.6	24.1	17.7
10 m风速/(m·s⁻¹)	2.20	2.20	2.87	3.21
降水量/mm	0.163	0.403	0.0605	0.0941
地表相对湿度/%	79.1	80.0	70.6	73.2

表3 福建省2023年S-SOM分型结果对应的平均气象条件

Table 3 Mean meteorological conditions for the 2023 S-SOM weather regime in Fujian Province

气象条件	S-SOM-I	S-SOM-II	S-SOM-III	S-SOM-IV	S-SOM-V
地表温度/℃	27.0	25.2	20.3	24.1	15.9
10 m风速/(m·s⁻¹)	1.90	2.20	2.32	2.34	2.83
降水量/mm	0.315	0.213	0.203	0.248	0.125
地表相对湿度/%	83.1	80.4	79.0	81.4	76.1

表4 闽浙相邻区域（左）与台湾海峡区域（右）风速和福建省各市臭氧质量浓度相关性表

Table 4 Correlations of wind Speed in the Fujian-Zhejiang border region (left) and the taiwan strait region (right) with ozone mass concentrations in cities of Fujian Province

城市臭氧质量浓度	r	p	城市臭氧质量浓度	r
龙岩市	0.526	0.000	宁德市	0.664
三明市	0.445	0.001	南平市	0.660
漳州市	0.389	0.004	莆田市	0.633
南平市	0.372	0.006	福州市	0.612
厦门市	0.360	0.008	泉州市	0.608
泉州市	0.341	0.013	三明市	0.596
莆田市	0.317	0.021	龙岩市	0.553
福州市	0.253	0.068	厦门市	0.541
宁德市	0.184	0.188	漳州市	0.500

图4 福建省O3-8h质量浓度时空分布图本图基于国家地理信息公共服务平台（天地图）下载的审图号为GS（2024）0650号行政区划底图制作，下同

Figure 4 Spatiotemporal distribution of O3-8h mass concentration in Fujian Province

表5 不同海拔站点组与全省整体O3-8h浓度变化的相关性

Table 5 Correlations between O3-8h concentration variations at stations of different elevations and the overall variation across Fujian Province

相关性指标	0－200 m	200－500 m	>500 m
r	0.996	0.941	0.947
p	0.000	0.000	0.000

图5 聚类分析肘部图

Figure 5 Elbow diagram for cluster analysis

图6 研究期间48 h后向轨迹图

Figure 6 48-Hour backward trajectory map during the study period

图7 不同天气类型下后向轨迹模式频率占比 ☆表示频率占比大于15%的组合，轨迹样本量N=3722

Figure 7 Frequency proportions of backward trajectory patterns under different weather regime

表6 天气类型与后向轨迹类型组合对应的福建省O3-8h统计结果

Table 6 Statistical results of O3-8h in Fujian Province for different combinations of weather regime and backward trajectory types

天气分型	48 h后向轨迹类型	福建省O_3-8h 均值	O_3-8h超标率/ %
2022年S-SOM-I	轨迹III	88.1	28.2
2022年S-SOM-I	轨迹V	76.4	16.7
2022年S-SOM-II	轨迹III	101	55.0
2022年S-SOM-II	轨迹V	79.8	27.3
2022年S-SOM-III	轨迹I	111	63.2
2022年S-SOM-III	轨迹III	110	72.7
2022年S-SOM-IV	轨迹I	85.9	26.4
2022年S-SOM-IV	轨迹III	84.0	22.6
2022年S-SOM-IV	轨迹IV	81.0	13.9
2023年S-SOM-I	轨迹III	97.7	45.5
2023年S-SOM-I	轨迹IV	103	50.0
2023年S-SOM-I	轨迹V	78.9	0
2023年S-SOM-II	轨迹III	92.0	31.9
2023年S-SOM-II	轨迹V	78.3	15.4
2023年S-SOM-III	轨迹I	95.6	40.0
2023年S-SOM-III	轨迹III	88.9	33.3
2023年S-SOM-III	轨迹IV	84.3	26.3
2023年S-SOM-IV	轨迹I	92.3	40.0
2023年S-SOM-IV	轨迹III	87.9	30.0
2023年S-SOM-V	轨迹I	86.1	29.1
2023年S-SOM-V	轨迹III	83.5	31.9
2023年S-SOM-V	轨迹IV	84.5	26.6

表7 不同分型下臭氧质量浓度与不同影响因子之间的相关性

Table 7 Correlations between ozone mass concentration and influencing factors under different weather regime

天气分型	NO₂质量浓度	2 m温度	相对湿度	10 m东北风速	p值
2022年 S-SOM-Ⅰ	−0.253	0.368	−0.609	0.556	0.000
2022年 S-SOM-Ⅲ	−0.350	0.383	−0.525	0.301	0.000

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基于大气分型的福建省臭氧浓度变化特征及归因分析

Variation Characteristics and Attribution Analysis of Ozone Concentration in Fujian Province Based on Atmospheric Classification

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