<p>Comprehensive control of fine particulate matter (PM<sub>2.5</sub>) and ozone (O<sub>3</sub>) is essential for improving environmental quality. In this study, spatiotemporal pattern mining methods were used to study the spatiotemporal evolution of PM<sub>2.5</sub> and O<sub>3</sub> in Shandong Province, and Kolmogorov‒Zurbenko (KZ) filtering and stepwise regression methods were integrated to study their influencing factors. The results revealed that (1) from 2014–2023, the PM<sub>2.5</sub> concentrations in Shandong were high in winter and low in summer, forming a “U”-shaped pattern, and the O<sub>3</sub> concentration showed a seasonal pattern of summer &gt; spring &gt; fall &gt; winter, revealing an inverted “U”-shaped pattern. The median PM<sub>2.5</sub> concentration decreased annually, whereas the O<sub>3</sub> concentration increased. (2) The variations in the PM<sub>2.5</sub> and O<sub>3</sub> concentrations were determined mainly by short-term and seasonal components. The average contributions of the short-term and seasonal components of the PM<sub>2.5</sub> concentration were 55.23% and 27.34%, respectively, and those of the O<sub>3</sub> concentration were 39.03% and 52.32%, respectively. (3) The spatial and temporal distributions of the PM<sub>2.5</sub> levels in Shandong were characterized by a clear pattern, with cold spots located mainly in eastern coastal cities and hot spots located mainly in western cities. The spatial distributions of O<sub>3</sub> cold spots and hot spots varied across the four seasons of the year. (4) The concentrations of PM<sub>2.5</sub> and O<sub>3</sub> in Shandong were affected mainly by anthropogenic emissions, which contributed 84.30–96.00% of the total PM<sub>2.5</sub> concentration and 97.50–99.50% of the total O<sub>3</sub> concentration. The impacts of human-induced emissions and meteorological variables on PM<sub>2.5</sub> and O<sub>3</sub> concentrations were not significantly related to their spatiotemporal patterns.</p>

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The spatiotemporal evolution and contributing factors of PM2.5 and O3 concentrations in Shandong Province from 2014–2023

  • Lin Chen,
  • Baoyan Shan,
  • Lina Wang,
  • Wenjing Li,
  • Changkuan Shui,
  • Yangyang Liu

摘要

Comprehensive control of fine particulate matter (PM2.5) and ozone (O3) is essential for improving environmental quality. In this study, spatiotemporal pattern mining methods were used to study the spatiotemporal evolution of PM2.5 and O3 in Shandong Province, and Kolmogorov‒Zurbenko (KZ) filtering and stepwise regression methods were integrated to study their influencing factors. The results revealed that (1) from 2014–2023, the PM2.5 concentrations in Shandong were high in winter and low in summer, forming a “U”-shaped pattern, and the O3 concentration showed a seasonal pattern of summer > spring > fall > winter, revealing an inverted “U”-shaped pattern. The median PM2.5 concentration decreased annually, whereas the O3 concentration increased. (2) The variations in the PM2.5 and O3 concentrations were determined mainly by short-term and seasonal components. The average contributions of the short-term and seasonal components of the PM2.5 concentration were 55.23% and 27.34%, respectively, and those of the O3 concentration were 39.03% and 52.32%, respectively. (3) The spatial and temporal distributions of the PM2.5 levels in Shandong were characterized by a clear pattern, with cold spots located mainly in eastern coastal cities and hot spots located mainly in western cities. The spatial distributions of O3 cold spots and hot spots varied across the four seasons of the year. (4) The concentrations of PM2.5 and O3 in Shandong were affected mainly by anthropogenic emissions, which contributed 84.30–96.00% of the total PM2.5 concentration and 97.50–99.50% of the total O3 concentration. The impacts of human-induced emissions and meteorological variables on PM2.5 and O3 concentrations were not significantly related to their spatiotemporal patterns.