Evidence map›Paper›PMID 41255873›Full record

ArticleEnvironmental research letters : ERL [Web site]2025

High populations near fossil fuel energy infrastructure across the supply chain and implications for an equitable energy transition.

Jonathan J Buonocore, Fintan A Mooney, Erin J Campbell, Brian Sousa, Breanna van Loenen, M Patricia Fabian, Amruta Nori-Sarma, Mary D Willis

Abstract read
In one paragraph

Article in Environmental research letters : ERL [Web site], 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jonathan J BuonocoreDepartment of Environmental Health, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0000-0001-7270-892X
Fintan A MooneyDepartment of Epidemiology, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0009-0006-3700-4066
Erin J CampbellDepartment of Epidemiology, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0000-0002-4884-1621
Brian SousaDepartment of Environmental Health, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0000-0002-5017-6990
Breanna van LoenenDepartment of Environmental Health, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0009-0004-4538-835X
M Patricia FabianDepartment of Environmental Health, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0000-0002-1658-3349
Amruta Nori-SarmaDepartment of Environmental Health, School of Public Health, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0000-0003-2335-6811
Mary D WillisInstitute for Global Sustainability, Boston University, Boston, MA, United States of America.ORCID https://orcid.org/0000-0002-0247-7983

Funding

A Preconception Cohort Study on Oil and Gas Development, Fertility, and PregnancyDP5OD033415 · OD · BOSTON UNIVERSITY MEDICAL CAMPUS · PI WILLIS, MARY D · 2022 to 2025
$2.2M
NIH HHS DP5 OD033415
6 · The paper itself

Abstract

Fossil fuel energy infrastructure poses health risks for local communities, primarily due to the presence of air pollution emissions and other hazards. There is also evidence of racial/ethnic disparities in the siting of this infrastructure for select components. However, population counts and demographic composition near fossil fuel energy infrastructure have not been systematically characterized across all types, supply chain stages, and predominant fuel types. Here, we construct a dataset of 25 elements of fossil fuel energy infrastructure and characterize the populations living near this infrastructure (defined as within 800 m [∼0.5 mile] or 1.6 km [∼1 mile]). We estimated that 46.6 million people in the contiguous U.S., representing 14.1% of the population, live within 1.6 km of at least one piece of energy infrastructure, with racial/ethnic disparities observed across nearly all stages of the supply chain. End use infrastructure has the most people residing within 1.6 km, with 20.9 million people, followed by extraction (20.3 million), and storage (6.16 million). Storage infrastructure has an average of ∼2,900 people living within 1.6 km of each element; end use infrastructure has an average of 1,900 people residing within 1.6 km of each element; extraction infrastructure has an average of 17 people residing within 1.6 km of each element. Almost 90% of the population near end use, transportation, refining, and storage infrastructure are in urban areas. Our results represent a substantial population in the U.S. that is potentially exposed to hazards that are not well-characterized, with unknown cumulative impacts, and which constitute a major environmental justice issue.

Indexed as

energy infrastructureexposure assessmentfossil fuelsoil and gaspopulation exposuresupply chains

Identifiers

PMID41255873
PMCPMC12621303

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.