Directed causal coupling between urban heat and air pollution in U.S. cities
Bibliographic Data
| ID | 15545517 |
|---|---|
| Authors | Xueli Yang (0000-0002-8373-4389, Scripps Institution of Oceanography, corresponding author), Zhihua Wang (0000-0002-0967-287X, Arizona State University), Zhi‐Hua Wang (0000-0001-9155-8605), Chenghao Wang (0009-0009-5655-3740, Cooperative Institute for Mesoscale Meteorological Studies) |
| Year | 2026 |
| Volume | 21 |
| Issue | 6 |
| Pages | 064029-064029 |
| Publication date | 2026-03-18 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/ae53fd |
| OpenAlex | W7139126989 |
| Language | EN |
| Citations received | 1 |
| References cited | 56 |
Urban air quality and temperature are closely linked through coupled physical and chemical processes. However, most existing evidence relies on correlation-based associations lacking directionality, or process-based models whose causal pathways depend on model structure and parameterizations. Here we apply a nonlinear causal inference method to quantify directed coupling between near-surface air temperature and three major air pollutants (PM 2.5 , ozone, and NO 2 ) across 481 U.S. urban areas using 14 years of daily data. We identify distinct diurnal and seasonal regimes of temperature–pollution coupling not captured by linear correlation. Temperature–PM 2.5 and temperature–O 3 coupling strengthens in summer, whereas temperature–NO 2 coupling intensifies in winter. Ozone shows the most consistent causal structure among all pollutants, with temperature dominant in roughly 80% of urban areas in both seasons. PM 2.5 exhibits balanced and spatially heterogeneous coupling, while NO 2 shifts from mixed behavior in summer to pronounced temperature dominance in winter. Across pollutants, linear correlations frequently overestimate coupling strength, especially for winter NO 2 . As the first continental-scale causal assessment of urban temperature–pollution interactions in the U.S., this study offers a data-driven complement to process-based modeling. The identified pollutant-specific sensitivities and their regional, diurnal, and seasonal variability provide new insight for understanding and managing urban heat stress and air quality
Air pollution · Air quality index · Air temperature · Causal inference · Causal model · Coupling (piping · Dominance (genetics · Nonlinear system · Atmospheric chemistry and aerosols · Urban Heat Island Mitigation · Wind and Air Flow Studies
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |