[Effect of Meteorological Elements and Air Pollutants on Ozone in Yinchuan City Park].

To examine the underlying determinants of ozone (O<sub>3</sub>) in Yinchuan's urban park during varying seasons and to ascertain the role played by meteorological events and air contaminants in influencing O<sub>3</sub> concentrations at high altitudes, data on O<sub>3</sub>, 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 O<sub>3</sub>. The findings demonstrated a notable seasonal variability in O<sub>3</sub> levels in Yinchuan's urban park, displaying an "unimodal type" with the O<sub>3</sub> concentration peaking in summer (131.18 μg·m<sup>-3</sup>) and bottoming out in winter (71.45 μg·m<sup>-3</sup>). Among the meteorological factors, the highest impact on O<sub>3</sub> was attributed to temperature and wind speed (temperature mainly through direct effects and wind speed mainly through indirect effects). Conversely, air pollutants such as NO<i><sub>x</sub></i> and SO<sub>2</sub> greatly affected O<sub>3</sub> primarily through direct effects. Wind speed was identified as the primary influencing factor on O<sub>3</sub> during spring and summer, potentially contributing 29% and 24.7%, respectively. Conversely, NO<sub>2</sub> 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 O<sub>3</sub> variations throughout various seasons, which could furnish a scientifically rigorous foundation and technical aid for mitigating and managing O<sub>3</sub> levels in high-altitude regions.

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Publication Details

Journal
PubMed
Published
2024-09-08
DOI
https://doi.org/10.13227/j.hjkx.202309171
Citations
2
Primary Topic
Air Quality and Health Impacts
Type
article
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[Effect of Meteorological Elements and Air Pollutants on Ozone in Yinchuan City Park].

Xilu Ni, Conghui Wang, Guang-Yao Shi, Lirong Yang et al.
2 citations
PubMed
Air Quality and Health Impacts
article

[Effect of Meteorological Elements and Air Pollutants on Ozone in Yinchuan City Park].

Xilu Ni, Conghui Wang, Guang-Yao Shi, Lirong Yang, Siqi Yang, Li-Ping Ji
article en
2 citations

Abstract

To examine the underlying determinants of ozone (O<sub>3</sub>) in Yinchuan's urban park during varying seasons and to ascertain the role played by meteorological events and air contaminants in influencing O<sub>3</sub> concentrations at high altitudes, data on O<sub>3</sub>, 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 O<sub>3</sub>. The findings demonstrated a notable seasonal variability in O<sub>3</sub> levels in Yinchuan's urban park, displaying an "unimodal type" with the O<sub>3</sub> concentration peaking in summer (131.18 μg·m<sup>-3</sup>) and bottoming out in winter (71.45 μg·m<sup>-3</sup>). Among the meteorological factors, the highest impact on O<sub>3</sub> was attributed to temperature and wind speed (temperature mainly through direct effects and wind speed mainly through indirect effects). Conversely, air pollutants such as NO<i><sub>x</sub></i> and SO<sub>2</sub> greatly affected O<sub>3</sub> primarily through direct effects. Wind speed was identified as the primary influencing factor on O<sub>3</sub> during spring and summer, potentially contributing 29% and 24.7%, respectively. Conversely, NO<sub>2</sub> 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 O<sub>3</sub> variations throughout various seasons, which could furnish a scientifically rigorous foundation and technical aid for mitigating and managing O<sub>3</sub> levels in high-altitude regions.

PubMedVol. 45(9)
Yinchuan First People's Hospital (CN)
Air Quality and Health Impacts
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