ArticleGeoHealth2025
Fueling Inequity: Geospatial Analyses Reveal Racial Patterns in Vulnerability to Natural Gas Pipeline Impacts in North Carolina.
Article in GeoHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the United States (US) has increased its domestic production of natural gas, transmission pipeline infrastructure continues to expand. Previous research highlights the environmental justice implications of this situation in the US, including fugitive methane emissions and the disproportionate concentration of pipelines in counties with high social vulnerability. However, gaps in publicly-available data make it difficult to understand the intersection of social factors, pipeline prevalence, and race, particularly in rural areas and at community-level spatial scales. This study begins to address this gap by examining the relationship between natural gas pipeline prevalence and demographics at the census block group level. This study uses North Carolina as a case study due to the state's dramatic increase in natural gas consumption driving an increase in pipeline infrastructure in recent years. This work highlights two critical findings: First, African American and American Indian people make up a disproportionately large share of the population living in block groups characterized by high social vulnerability and high densities of natural gas pipelines. Second, our main finding is insensitive to the threshold used to determine disproportionality, suggesting these results are robust. These data demonstrate a need for more equitable methods for energy infrastructure planning and maintenance. These results underscore the need for geospatial analysts to critically evaluate their methods for identifying disparities.
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