Daily Time Series Analysis of Ambient Ozone and Fine Particulate Matter Levels in Corpus Christi, Texas
摘要
Air pollution represents an environmental health exposure associated with cardiovascular, respiratory, and neurological diseases. The temporal dynamics of key air pollutants, such as ozone (O3) and fine particulate matter (PM2.5), are poorly understood, especially along the Texas industrial coastal region. This study utilizes daily time series analysis to investigate temporal trends in ambient O3 and PM2.5 levels across four monitoring sites in the petrochemical-intensive city of Corpus Christi. Five years (2019–2023) of data from the U.S. Environmental Protection Agency (USEPA) on daily maximum 8-h concentrations of O3 (ppm) and daily mean concentration of PM2.5 (µg/m3) were used. Using classical seasonal decomposition and Autoregressive Moving Average (ARMA) modeling, we identified distinct seasonal patterns and temporal variability. Overall, O3 and PM2.5 concentrations showed an inverse relationship (ρ = -0.197; p < 0.001). Distinct seasonal patterns emerged: O3 peaked in spring with summer minima, while PM2.5 demonstrated summer maxima. Both pollutants demonstrated statistically significant associations with average ambient temperature, average wind speed, and precipitation. Most notably, temperature was inversely correlated with O3 (ρ = -0.373; p < 0.001) but positively with PM2.5 concentrations (ρ = 0.438; p < 0.001), indicating differential temperature influence. PM2.5 also exhibited an extreme spike (70.5 μg/m3) associated with a Saharan dust event in June 2020. ARMA models elucidated that elevated O₃ levels persisted daily (ARMA(1,1), p < 0.0001), while PM2.5 oscillated (ARMA(3,4), p < 0.0001). The successful 30-day forecasting capability in this study provides essential tools for early warning systems and evidence-based air quality interventions in coastal petrochemical communities.