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Cited by 1,083

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Mortality from Ship Emissions: A Global Assessment

Corbett, James J., Winebrake, James J., Green, Erin H., Kasibhatla, Prasad, Eyring, Veronika, Lauer, Axel·2007·Environmental Science & Technology

Abstract

Epidemiological studies consistently link ambient concentrations of particulate matter (PM) to negative health impacts, including asthma, heart attacks, hospital admissions, and premature mortality. We model ambient PM concentrations from oceangoing ships using two geospatial emissions inventories and two global aerosol models. We estimate global and regional mortalities by applying ambient PM increases due to ships to cardiopulmonary and lung cancer concentration-risk functions and population models. Our results indicate that shipping-related PM emissions are responsible for approximately 60,000 cardiopulmonary and lung cancer deaths annually, with most deaths occurring near coastlines in Europe, East Asia, and South Asia. Under current regulation and with the expected growth in shipping activity, we estimate that annual mortalities could increase by 40% by 2012.

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Metadata

Authors
Corbett, J. J., Winebrake, J. J., Green, E. H., Kasibhatla, P., Eyring, V., & Lauer, A.
Venue
Environmental Science & Technology
Published
2007-11-05
Volume
41
Issue
24
Pages
8512-8518
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2092838154
Cited by
1,083
References
17
FWCI
29.89
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Mortality from Ship Emissions: A Global Assessment. https://app.cochat.ai/papers/10.1021/es071686z
The paper
Corbett, J. J., Winebrake, J. J., Green, E. H., Kasibhatla, P., Eyring, V., & Lauer, A. (2007). Mortality from Ship Emissions: A Global Assessment. Environmental Science & Technology. https://doi.org/10.1021/es071686z

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.