[气象要素和空气污染物对银川市公园臭氧的影响]。

Q2 Environmental Science 环境科学 Pub Date : 2024-09-08 DOI:10.13227/j.hjkx.202309171
Cong-Hui Wang, Guang-Yao Shi, Si-Qi Yang, Xi-Lu Ni, Li-Rong Yang, Li-Ping Ji
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引用次数: 0

摘要

为了研究不同季节银川城市公园臭氧(O3)为研究银川城市公园不同季节臭氧(O3)的基本决定因素,确定气象事件和空气污染物对高空臭氧浓度的影响作用,在宁夏银川国家城市生态系统研究站进行了长时间的定位观测,收集了臭氧、气象因子和空气污染物的数据。利用皮尔逊相关分析和结构方程模型研究了臭氧的时空分布模式、变化趋势和主要影响因素。研究结果表明,银川城市公园的臭氧浓度存在明显的季节性变化,呈 "单峰型",夏季臭氧浓度达到峰值(131.18 μg-m-3),冬季臭氧浓度达到谷底(71.18 μg-m-3)。冬季达到谷底(71.45 μg-m-3)。在气象因素中,对臭氧影响最大的是温度和风速(温度主要通过直接影响,风速主要通过间接影响)。相反,氮氧化物和二氧化硫等空气污染物则主要通过直接影响对臭氧产生重大影响。风速被认为是春季和夏季 O3 的主要影响因素,分别占 29% 和 24.7%。相反,二氧化氮被认为是秋季和冬季的主要影响因素,估计贡献率分别为 26.6% 和 29.7%。因此,结构方程模型可以有效揭示不同季节臭氧变化背后的主要决定因素,为缓解和管理高海拔地区的臭氧水平提供严谨的科学依据和技术支持。
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[Effect of Meteorological Elements and Air Pollutants on Ozone in Yinchuan City Park].

To examine the underlying determinants of ozone (O3) in Yinchuan's urban park during varying seasons and to ascertain the role played by meteorological events and air contaminants in influencing O3 concentrations at high altitudes, data on O3, meteorological factors, and air pollutants were collected through prolonged positional observations carried out at the Ningxia Yinchuan National Urban Ecosystem Research Station. Pearson correlation analysis and a structural equation model were utilized to investigate the spatio-temporal distribution patterns, trends, and the primary factors influencing O3. The findings demonstrated a notable seasonal variability in O3 levels in Yinchuan's urban park, displaying an "unimodal type" with the O3 concentration peaking in summer (131.18 μg·m-3) and bottoming out in winter (71.45 μg·m-3). Among the meteorological factors, the highest impact on O3 was attributed to temperature and wind speed (temperature mainly through direct effects and wind speed mainly through indirect effects). Conversely, air pollutants such as NOx and SO2 greatly affected O3 primarily through direct effects. Wind speed was identified as the primary influencing factor on O3 during spring and summer, potentially contributing 29% and 24.7%, respectively. Conversely, NO2 was implicated as the primary factor during autumn and winter, with an estimated contribution of 26.6% and 29.7%, respectively. Thus, a structural equation model can efficiently reveal the primary determinants behind O3 variations throughout various seasons, which could furnish a scientifically rigorous foundation and technical aid for mitigating and managing O3 levels in high-altitude regions.

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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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