| Summary: | Improving air quality in the Yellow River Golden Triangle Demonstration Area (YRGTDA) is an important practice for ecological protection and high-quality development in the Yellow River Basin. Preventing and controlling PM<sub>2.5</sub> pollution in this region will require a scientific understanding of the spatiotemporal patterns and characteristics of PM<sub>2.5</sub> pollution. PM<sub>2.5</sub> data from different sources were combined in this study (the annual average of PM<sub>2.5</sub> concentrations were obtained from the Atmospheric Composition Analysis Group of Dalhousie University, and the daily PM<sub>2.5</sub> concentration data were obtained from the China National Environmental Monitoring Centre). Then, the temporal variation of PM<sub>2.5</sub> concentrations at annual, seasonal, and monthly scales, the spatial variation of PM<sub>2.5</sub> concentrations, and the variation of PM<sub>2.5</sub> pollution classes were analyzed. Results showed that: (1) at the annual scale, the PM<sub>2.5</sub> concentrations showed a decreasing trend from 2000 to 2021 in the study area. The variation of PM<sub>2.5</sub> concentrations were divided into two different stages. (2) At the seasonal scale, high PM<sub>2.5</sub> concentrations occurred mainly in winter, low PM<sub>2.5</sub> concentrations occurred in summer. At the monthly scale, PM<sub>2.5</sub> concentrations showed a U-shaped variation pattern from January to December each year. (3) The hotspot analysis of the PM<sub>2.5</sub> concentrations in the study area showed a cyclical variation pattern. (4) The PM<sub>2.5</sub> concentrations exhibited a spatial pattern of high values in the central and low values in the northern and southern parts of YRGTDA. (5) The number of days for different PM<sub>2.5</sub> pollution classes from 2015 to 2021 followed the order of Good > Excellent > Light pollution > Moderate pollution > Heavy pollution > Severe pollution in YRGTDA. The results of this study have great theoretical and practical significance because they reveal the spatiotemporal patterns and pollution characteristics of PM<sub>2.5</sub> and will lead to the development of scientifically based measures to reasonably prevent and control pollution in YRGTDA.
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