Lag Associations of Precipitation and Temperature with Seven Types of Ambient Air Pollution Concentrations in the Midwestern United States: A Time Series Analysis

The frequency and intensity of extreme precipitation and temperature events has been increasing over the past decades. These changes could impact daily exposure to high concentrations of pollutants like SO2, NO2, Ozone and particulate matter (PMx), exacerbating risks for numerous health problems. We used monitor based measurements of daily concentrations of seven common pollutants and raster based climate datasets to test associations of precipitation and temperature with daily pollutant levels for the years 2005 to 2022. Concentrations and climate change data were mapped using latitude longitude locations of pollution monitors. We visualized daily measures of pollutants and temperature to explore possible same-day correlation between each. To explore lag associations of pollutants and climate variables, we used cross correlation functions and identified lag days where the association was strongest. We found that Ozone and PM10 had strong positive correlations with temperature (Pearson corr: .31 and .25 respectively), while NO2 had strong negative correlations (Pearson corr: -.21). Precipitation was negatively associated with nearly all pollutants. Cross-correlations suggested that there were important lag associations of temperature and precipitation pollutants, but that specific predictive lag days varied by pollutant. Further study of pollutant concentration patterns would allow researchers to better predict airborne pollutant exposures based on available daily weather data, thus better assessing potential risks to human health for at risk populations.