Spatial and temporal patterns of urban air pollution in tehran with a focus on PM_2.5 and associated pollutants.

ABSTRACT: Understanding the spatial and temporal dynamics of air pollutants is crucial for effective urban air pollution management. This study focuses on the temporal dynamics of air quality monitoring stations (AQMSs) and the association among air pollutants, particularly PM_2.5, in Tehran, Iran. Using time series clustering and the Copula model, we analyzed data from 2019 to 2022. We found that the levels and dynamics of O₃ and SO₂ were similar across most AQMSs and unrelated to geographical positions. CO levels and dynamics were consistent among urban and border AQMSs, with higher concentrations in urban stations. NO₂ levels and dynamics varied significantly among northern AQMSs with no relationship geographical positions. PM₁₀ levels and dyn

SUBMITTER: Abbasi MT 

PROVIDER: S-EPMC11502892 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature