AUTHOR=Jing Bian , Xiaofeng Ren 

TITLE=Study on the evolution patterns and predictive modeling of ambient air quality in oasis cities of arid regions: a case study of Urumqi

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1632713

DOI=10.3389/fpubh.2025.1632713

ISSN=2296-2565

ABSTRACT=BackgroundThis study investigates the evolution patterns and future trends of ambient air quality in oasis cities within arid regions, with Urumqi as a representative case.MethodsUtilizing observational data from eight urban monitoring stations, we comprehensively analyze air quality variations and project future scenarios through the Air Quality Index (AQI), Spearman’s rank correlation coefficient, and Grey correlation modeling. Our aim is to elucidate the contributions of atmospheric pollutants to ambient air quality in arid oasis cities.ResultsThe results show that: (1) In 2022, Urumqi’s AQI ranged from 24 to 363, with exceed rates of 2.5% for severely polluted weather, 6.15% for heavily polluted conditions, 5.8% for moderate pollution, and 10% for mild pollution. (2) Dust events elevated inhalable particulate matter (PM) concentrations by 5 μg·m−3, contributing 6.5% to pollution levels, while the ambient air quality composite index reached 4.45. Dust’s specific contribution to this index was 0.05(1.1%).(3) Meteorological factors—precipitation, wind speed, temperature, and vapor pressure—exhibited significant negative correlations (p < 0.05) with PM₂.₅, PM₁₀, SO₂, NO₂, and CO concentrations, but a positive correlation with O₃. Wind speed showed a strong negative association with NO₂ (p < 0.01), while temperature and vapor pressure were positively linked to O₃ (p < 0.01). (4) The GM (1,1) model demonstrated high predictive accuracy, with errors between 1.0 and 4.2%. Projections indicate a rising trend in ozone concentrations, with the 90th percentile O₃-8 h potentially exceeding 160 μg·m−3 by 2025.ConclusionThese results provide critical insights into the spatiotemporal dynamics of air pollution in Urumqi and its natural drivers, offering a scientific basis for regional air quality management and pollution mitigation strategies.