Evidence map›Paper›PMID 41034256›Full record

ArticleScientific reports2025

Towards a remote sensing-based assessment of carbon emissions from peatlands.

Pouya Ghezelayagh, Andrzej Kamocki, Piotr Banaszuk, Mateusz Grygoruk

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Pouya GhezelayaghCentre for Climate Research, Warsaw University of Life Sciences-SGGW, Nowoursynowska 166, Warsaw, 02-787, Poland. pouya_ghezelayagh@sggw.edu.pl.
Andrzej KamockiFaculty of Civil Engineering and Environmental Sciences, Białystok University of Technology, ul. Wiejska 45A, Białystok, 15-351, Poland.
Piotr BanaszukFaculty of Civil Engineering and Environmental Sciences, Białystok University of Technology, ul. Wiejska 45A, Białystok, 15-351, Poland.
Mateusz GrygorukCentre for Climate Research, Warsaw University of Life Sciences-SGGW, Nowoursynowska 166, Warsaw, 02-787, Poland.

Funding

European Commission 101056848
6 · The paper itself

Abstract

Among greenhouse gases-generating sources, biosphere sources from natural carbon (C) reservoirs play a significant role. A vital component of the biosphere is peatlands-the largest natural terrestrial carbon storage on the earth. Peatlands function as both C sink and C source, showing their pivot role in mitigating GHGs. Releasing C results from peat oxidation-the decomposition of organic matter in the peat. This decomposition reduces the volume of peat and, hence, causes subsidence. This study introduces an exclusive remote-sensing-based framework for estimating carbon emissions from peatlands using subsidence rates. This framework integrates peat properties-bulk density and soil organic carbon-with the oxidated peat subsidence, which refers to the proportion of subsidence attributed to the oxidation process rather than shrinkage. Achieving a fully remote-sensing-based approach promises time-effective, cost-effective, and consistent C emission monitoring even in unreachable places in peatlands, addressing the critical need for global climate change mitigation strategies. However, this achievement requires collaborative efforts among researchers to implement it in other sites to improve dataset accuracy for each parameter. By improving this framework, the scientific community can pave the way for robust, large-scale assessments of peatland C emission.

Indexed as

Bulk densityClimate changeOxidationPeat degradationSoil organic carbon (SOC)Subsidence

Identifiers

PMID41034256
PMCPMC12489126

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Registered trials

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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.