Examining Localized Patterns of Air Quality Perception in Texas: A Spatial and Statistical Analysis

Abstract

Environmental and human health issues associated with outdoor air pollution, such as ozone, sulfur dioxide, and other pollutants in metropolitan regions, are an area of growing concern for both policy officials and the general public. Increasing attention from the news media, new health data, and public debate over the effectiveness of clean air regulations have raised the importance of air quality in the public consciousness. While public perceptions of air quality have been studied thoroughly dating back to the 1960s, little empirical research has been conducted to explain the spatial aspects of these perceptions, particularly at the local level. Although recent studies suggest characteristics of local setting are important in shaping perceptions of air quality, the roles of proximity, neighborhood characteristics, and location have not been clarified. This study seeks to improve understanding of the major factors shaping public perceptions of air quality by examining the spatial pattern of local risk perception, the role of socioeconomic characteristics in forming these perceptions, and the relationship between perceived and scientifically measured air pollution. First, we map the spatial pattern of local air quality perceptions using Geographic Information Systems (GIS) across the Dallas and Houston metropolitan areas. Next, we explain these perceptions through local contextual factors using both bivariate correlations and multivariate regression analysis. Results indicate that perceptions of air quality in the study areas are not significantly correlated with air quality based on readings of air monitoring stations. Instead, perceptions appear to be influenced by setting (urban vs. rural), state identification, access to information, and socioeconomic characteristics such as age, race, and political identification. We discuss the implications of the findings and provide direction on how further research can provide a deeper understanding of the local contextual factors influencing public perceptions.

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