Traffic is a problem across the globe, reaching perniciously into cities and communities nearly everywhere. The United States (US) has its share of traffic problems; of the ten cities with the highest traffic delay times in 2022, four were in the US. While nearly everyone living in the US has likely experienced traffic congestion of some kind, some cities are notoriously worse than others.
In New York City (NYC), traffic congestion has been a problem as far back as 1913, when Fifth Avenue was so traffic-clogged it could take 40 minutes to go 23 blocks. Today, of the 25 most congested traffic corridors in the US, three are in NYC. One of these runs through the South Bronx, an environmental justice neighborhood we highlight in this dissertation. Traffic congestion is a source of air pollution (traffic-related air pollution, or TRAP) and noise, and it can result in property damage, injuries, and fatalities from collisions with other vehicles, pedestrians, or those using other forms of transportation.
Both traffic congestion and TRAP have been associated with numerous negative health outcomes. For example, TRAP is associated with respiratory, cardiovascular, neurological, and pregnancy outcomes, including asthma exacerbation, incident childhood and adult asthma, reduced lung function, atherosclerosis, hypertension, stroke, myocardial infarction, cardiovascular-related mortality, cognitive decline, neurodevelopmental outcomes, pregnancy loss, term low birth weight, and small for gestational age birth. In general across the US, communities of color and higher-poverty neighborhoods face greater exposure and health burden from traffic.
Throughout this dissertation, we study traffic congestion and TRAP through two lenses: (1) environmental justice; and (2) policy. Additionally, we assess the cardiovascular health impacts of TRAP. In Chapter 1, we provide background on the problem of traffic, focusing on NYC and the South Bronx. In Chapter 2, we present a case study from the South Bronx, where a new trucking-intensive warehouse was opened in 2018. In this study, we quantified the increase in vehicles and trucks following the opening of the warehouse and estimated the resulting increases in black carbon (BC) and noise. We discuss the injustice in the methods used to assess the environmental impact of the warehouse, the warehouse’s siting in a predominantly Black and Lantinx community already overburdened with trucking-intensive industries, and the desire of the community to instead use the land for a community park.
In Chapter 3, we present a study quantifying how traffic congestion in NYC changed during the COVID-19 pandemic. We assess how NY on Pause, the state’s stay-at-home order, impacted traffic congestion by comparing the magnitude of traffic decreases in environmentally burdened or systematically disadvantaged neighborhoods to the magnitude of decreases in less burdened and more advantaged neighborhoods. We discuss the implications of these results for upcoming traffic policies in NYC, such as congestion pricing. In Chapter 4, we present a study evaluating diurnal changes in TRAP in NYC during NY on Pause. We discuss the implications of these results for congestion pricing, including the potential timing of TRAP decreases.
In Chapter 5, we present an epidemiologic study of TRAP and myocardial infarction (MI) in New York State, identifying hazard windows of exposure in a study period where the mean nitrogen dioxide (NO₂) concentration was substantially lower than the hourly national standard. We discuss implications for the NO₂ National Ambient Air Quality Standards (NAAQS) and suggest that the current standard may be insufficient to protect population cardiovascular health. Finally, in Chapter 6, we conclude with a discussion of recommended research directions and policy considerations.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/6217-ng58 |
| Date | January 2023 |
| Creators | Shearston, Jenni A. |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
Page generated in 0.0019 seconds