2015—2021年四川盆地近地面O<sub>3</sub>时空演化及潜在源区分析

谭华荣; 林跃胜; 姚有如; 马康; 方凤满

doi:10.13198/j.issn.1001-6929.2023.01.07

2015—2021年四川盆地近地面O₃时空演化及潜在源区分析

doi: 10.13198/j.issn.1001-6929.2023.01.07

谭华荣^1,,
林跃胜^{1, 2},
姚有如^{1, 2},
马康¹,
方凤满^{1, 2, ,}

1.
安徽师范大学地理与旅游学院，安徽芜湖　241003
2.
安徽师范大学, 江淮流域地表过程与区域响应安徽省重点实验室，安徽芜湖　241003

基金项目: 国家自然科学基金项目(No.41977402)

详细信息

作者简介:
谭华荣（1999-），男，重庆人，tanhr@ahnu.edu.cn

通讯作者:
方凤满(1974-)，女，安徽池州人，教授，博士，博导，主要从事污染物迁移与转化研究，ffm1974@ahnu.edu.cn

中图分类号: X51
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出版历程
- 收稿日期: 2022-11-08
- 修回日期: 2023-01-08

Spatiotemporal Evolution and Potential Source Areas of Surface Ozone in the Sichuan Basin during 2015-2021

TAN Huarong^1
,,
LIN Yuesheng^{1, 2},
YAO Youru^{1, 2},
MA Kang¹,
FANG Fengman^{1, 2
, ,}

1.
School of Geography and Tourism, Anhui Normal University, Wuhu 241003, China
2.
Key Laboratory of Earth Surface Processes and Response in the Yangtze-Huaihe River Basin, Anhui Normal University, Wuhu 241003, China

Funds: National Natural Science Foundation of China (No.41977402)

摘要

摘要: 近地面O₃污染已经成为我国最严重的环境问题之一，特别是在地形相对闭塞的盆地区域更加突出，而盆地地形区域O₃的时空演化、潜在源区及驱动因素尚未被完全揭示. 因此，以典型盆地地形区—四川盆地为研究区，基于长时间尺度(2015—2021年)的 O₃浓度监测数据，采用后向轨迹、时空地理加权回归等模型探讨O₃的时空变化特征、传输路径、潜在源区以及驱动因素的空间分布特征. 结果表明：①时间分布上，2015—2021年四川盆地O₃-8 h浓度第90百分位数为(143±7)µg/m³，夏季O₃-8 h浓度高于其他季节，O₃-8 h浓度存在明显的“周末效应”和昼夜差异. ②空间格局上，四川盆地O₃-8 h浓度第90百分位数总体呈西高东低的分布特征，西部平原地带是核心污染区域. ③2015—2021年影响成都市的气流轨迹中短距离输送轨迹占比为74.24%，长距离输送轨迹占比平均值为25.76%. 2015—2021年成都市O₃的潜在源区由西向东迁移，并表现出以盆地为中心逐渐集聚的趋势. ④时空地理加权回归结果显示，气温和日照时数的回归系数分别为0.738和0.289，是四川盆地O₃的主导自然因子，人口密度(0.412)和人均GDP(0.369)是导致O₃浓度升高的主要社会经济因素. 研究显示，受盆地内部自然环境和人类活动的共同影响，2015—2021年四川盆地的O₃污染较为严重.
- 臭氧(O₃) /
- 传输路径 /
- 潜在源区 /
- 驱动因素 /
- 四川盆地
Abstract: Surface ozone pollution has become one of the most prominent environmental problems in China, especially in the topographically isolated basin areas. However, the spatial and temporal evolution, potential source areas and driving factors of O₃ in the basin topographic region have not been systematically studied and confirmed. In this study, the Sichuan Basin was chosen as a typical case site, and real-time O₃ monitoring data of long-term monitoring stations were selected for analysis. The backward trajectory, geographically and temporally weighted regression were used to explore the spatiotemporal variation characteristics, transport paths, potential source areas and distribution characteristics of driving factors of O₃. (1) The results showed that the average 90^th percentile of the O₃-8 h concentration in the Sichuan Basin was (143±7)µg/m³ from 2015 to 2021. The O₃-8 h concentration in summer was higher than that in other seasons, and O₃ pollution in May should be focused on. In addition, there were significant ‘weekend effects’ and diurnal differences in O₃-8 h concentration. (2) Spatially, the average 90^th percentile of the O₃-8 h concentration in the western regions of the Sichuan Basin was higher than that in the eastern regions, and the western plain was the core area of O₃ pollution. (3) From 2015 to 2021, the influence of short-range air mass trajectories on airflow transport in Chengdu City was dominant (74.24%). The potential source areas of O₃ pollution in Chengdu migrated from west to east, showing a trend of gradual accumulation in the basin. (4) The geographically and temporally weighted regression results showed that the regression coefficients of temperature and sunshine duration were 0.738 and 0.289, respectively, which were the dominant natural factors of O₃ in the Sichuan Basin. Population density (0.412) and per capita GDP (0.369) were the main socio-economic factors influencing O₃ concentration. The study showed that O₃ pollution in the Sichuan Basin was relatively serious from 2015 to 2021 due to the combined influence of natural environment and human activities.
- ozone (O₃) /
- transport path /
- potential source area /
- driving factors /
- Sichuan Basin

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图 1 研究区示意

Figure 1. Location of the study area

下载: 全尺寸图片幻灯片

图 2 2015—2021年四川盆地O₃-8 h浓度时间变化特征

注：灰色区域为95%置信区间.

Figure 2. Temporal variation of O₃-8 h concentration in Sichuan Basin from 2015 to 2021

下载: 全尺寸图片幻灯片

图 3 2015—2021年四川盆地O₃-8 h浓度第90百分位数空间分布情况

Figure 3. Spatial distribution of 90^th percentile of O₃-8 h concentration in Sichuan Basin from 2015 to 2021

下载: 全尺寸图片幻灯片

图 4 2015—2021年四川盆地O₃-8 h浓度第90百分位数的标准差椭圆和平均中心

Figure 4. The standard deviational ellipse and mean center of the 90^th percentile of O₃-8 h concentration in the Sichuan Basin from 2015 to 2021

下载: 全尺寸图片幻灯片

图 5 2015—2021年成都市气流传输路径后向轨迹分析

Figure 5. Backward trajectory of air transmission path in Chengdu from 2015 to 2021

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图 6 2015—2021年夏季成都市气流传输路径后向轨迹分析

Figure 6. Backward trajectory of air transmission path in Chengdu during the summer period from 2015 to 2021

下载: 全尺寸图片幻灯片

图 7 2015—2021年成都市O₃的潜在源区

Figure 7. Potential source areas of O₃ in Chengdu from 2015 to 2021

下载: 全尺寸图片幻灯片

图 8 基于时空地理加权回归模型的回归系数空间分布

Figure 8. Spatial distribution of regression coefficients based on geographically and temporally weighted regression

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表 1 2015—2021年四川盆地监测站点O₃-8 h浓度第90百分位数统计数据

Table 1. Statistical data of the 90^th percentile of the O₃-8 h concentration at monitoring stations in Sichuan Basin from 2015 to 2021

年份	站点数/个	O₃-8 h浓度第90百分位数/(µg/m³)
年份	站点数/个	最小值	最大值	平均值	标准差
2015	96	56	200	140	28
2016	94	67	193	144	25
2017	96	60	184	149	20
2018	96	115	191	154	17
2019	102	97	205	141	19
2020	102	75	189	139	23
2021	125	91	170	135	18

下载: 导出CSV

表 2 自然环境和社会经济因子的回归系数和方差膨胀因子(VIF)

Table 2. Regression coefficients and variance inflation factor of natural environment and socio-economic factors

项目种类	项目	VIF	回归系数
社会经济因子	人口密度	1.555	0.412
	人均GDP	2.439	0.369
	第二产业占GDP比重	1.152	0.157
	工业烟粉尘排放量	3.445	0.172
	公路客运量	4.499	0.045
	建成区绿化覆盖面积	5.754	−0.318
自然环境因子	风速	1.502	0.285
	日照时数	4.547	0.289
	平均气温	2.772	0.738
	相对湿度	2.711	−0.182
	DEM	1.452	−0.226

下载: 导出CSV

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