Exploring the Scaling Relationships between Human Mobility and Air Pollutants in the Twin Cities

Keywords: Network Analysis, Distance Statistics, Human Mobility, Air Pollutants, Carbon Emissions, Particulate Matter 2.5, Climate Change, Twin Cities, Minneapolis, St. Paul, Minnesota, Allometric Growth, Scaling
Abstract Type: Paper Abstract

Abstract

Transportation is the largest contributing sector to green house gas emissions according to the United States Environmental Protection Agency. In 2020, light-duty (personal) vehicles accounted for over half of these emissions. This project explores this relationship between human mobility and carbon footprint at an urban system level in the Twin Cities Metropolitan Area (TCMA) of Minnesota. We also investigate associations with observed particulate matter 2.5 (PM2.5), another pollutant created during the combustion process within vehicles.

Traditionally, human mobility networks have modeled the likelihood of a person traveling a distance using the power law. This model has proven quite accurate in describing the scale-free nature of these complex networks beyond a critical distance. Our work builds on this concept by utilizing a compound logistic curve from the discipline of ecology (the Ricker Model) to find this critical distance and model both the large and small scale probability distribution of human movement. We perform this and other conventional mobility analyses for the TCMA at various time scales. These indices are then used to determine the scaling factors (allometric growth) between a city’s mobility, its carbon footprint, and observed PM2.5.