Proximity (Mis)perception: Public Awareness of Nuclear, Refinery, and Fracking Sites

• Published in: Risk analysis Vol. 40; no. 2; pp. 385 - 398
• Main Authors: Lyons, Benjamin A., Akin, Heather, Stroud, Natalie Jomini
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.02.2020; John Wiley and Sons Inc
• Subjects: Aesthetics; Bias; Energy sites; Geographic information systems; GIS; Hydraulic fracturing; Impressions; Management information systems; News; Nuclear engineering; Nuclear reactors; Nuclear safety; Original; Original s; Perception; Perceptions; Polls & surveys; Proximity; Public awareness; Quality of life; Refineries; Remote sensing; Risk assessment; Risk perception; GIS; Energy sites; proximity; risk perception
• DOI: 10.1111/risa.13387
• ISSN: 0272-4332

Whether on grounds of perceived safety, aesthetics, or overall quality of life, residents may wish to be aware of nearby energy sites such as nuclear reactors, refineries, and fracking wells. Yet people are not always accurate in their impressions of proximity. Indeed, our data show that only 54% of Americans living within 25 miles of a nuclear site say they do, and even fewer fracking‐proximal (30%) and refinery‐proximal (24%) residents respond accurately. In this article, we analyze factors that could either help people form more accurate perceptions or distort their impressions of proximity. We evaluate these hypotheses using a large national survey sample and corresponding geographic information system (GIS) data. Results show that among those living in close proximity to energy sites, those who perceive greater risk are less likely to report living nearby. Conversely, social contact with employees of these industries increases perceived proximity regardless of actual distance. These relationships are consistent across each site type we examine. Other potential factors—such as local news use—may play a role in proximity perception on a case‐by‐case basis. Our findings are an important step toward a more generalizable understanding of how the public forms perceptions of proximity to risk sites, showing multiple potential mechanisms of bias.