Evidence map›Paper›PMID 41100707›Full record

ArticleEnvironmental science & technology2025

From Global Emissions to Local Impacts: Spatially Explicit Modeling of Ocean Acidification in Life Cycle Assessment.

Sedona R Anderson, Konstantin Stadler, Francesca Verones

Abstract read
In one paragraph

Article in Environmental science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Sedona R AndersonIndustrial Ecology Programme, Department of Energy and Process Engineering, NTNU, 7491 Trondheim, Norway.ORCID 0000-0002-4428-4290
Konstantin StadlerIndustrial Ecology Programme, Department of Energy and Process Engineering, NTNU, 7491 Trondheim, Norway.
Francesca VeronesIndustrial Ecology Programme, Department of Energy and Process Engineering, NTNU, 7491 Trondheim, Norway.ORCID 0000-0002-2908-328X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ocean acidification poses a critical threat to marine ecosystems. While life cycle assessment frameworks provide a method for assessing and combatting many anthropogenic impacts, marine impact models remain underdeveloped compared to their terrestrial counterparts. This study presents the first spatially explicit characterization model for quantifying the impacts of ocean acidification that includes both midpoint and endpoint characterization factors (CFs). Midpoint CFs were spatially delineated by using marine ecoregions and Food and Agriculture Organization fishing areas, leveraging spatially explicit fate and fate sensitivity factors. Endpoint CFs were calculated using species sensitivity distributions that include species across a range of calcification levels, climate zones, and trophic levels. Results demonstrate significant geographic variability in ocean acidification impacts, with polar regions showing heightened vulnerability. Our findings emphasize the need for spatially explicit modeling to account for the diverse biogeochemical and ecological responses to ocean acidification. This work advances marine impact assessment by integrating spatial and biological complexity, providing critical tools for quantifying ocean acidification's global ecological and economic consequences.

Indexed as

SeawaterEcosystemHydrogen-Ion ConcentrationModels, TheoreticalOcean AcidificationOceans and Seasbiodiversitycharacterization factorecosystem damageimpact modelLCALCIAmarineocean acidification

Identifiers

PMID41100707
PMCPMC12573785

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.