Authors: Andre Eanes*, University of Richmond, Todd Lookingbill, University of Richmond, Kelly Saverino, University of Richmond, Jeremy Hoffman, Science Museum of Virginia
Topics: Geography and Urban Health, Hazards and Vulnerability, Medical and Health Geography
Keywords: Air Quality, Urban Air Quality, Environmental Quality, Environmental Monitoring, AQI, Socioeconomic Inequality, Geospatial Analysis, Data Analysis, Richmond, Virginia
Session Type: Lightning Paper
Start / End Time: 5:35 PM / 6:50 PM
Room: Cleveland 1, Sheraton, IM Pei Tower, Lobby Level
Presentation File: No File Uploaded
Pollution and poor air quality have detrimental effects on human and environmental well-being, and they are often tied to complex societal factors. This study aims to track the spatial and temporal variability of air quality in Richmond, Virginia through a series of ongoing campaigns to gather data from both stationary and mobile sensing schemes. Currently, particulate matter concentration is used to indicate air quality, as the required equipment is relatively inexpensive given its applicability. Still, detecting a wider variety of pollutants would eventually prove optimal, time and resources permitting. The ultimate goal of this study is to map out the spatial distribution of air quality throughout the city and track short- and long-term temporal trends to determine if significant variation exists on either scale. Building off of a similar study on the urban heat island effect in Richmond, which found correlations between the spatial distribution of (particularly high) temperatures with socioeconomic and land use factors, this study aims to uncover to what extent air quality may correlate with such factors and how to mitigate the exposure of vulnerable communities to hazardous air quality in the future. Currently, areas of potentially high vulnerability in terms of proximity to large emitters of pollution have been identified, and efforts are being focused on expanding data collection in those areas. Additionally, preliminary data is beginning to paint a picture of significant spatial and temporal patterns of air quality throughout the city, although further data collection and analyses are required to substantiate these findings.