Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Sources of nitrous oxide emissions from agriculturally managed peatlands

Yuqiao Wang, Pierluigi Calanca, Jens Leifeld

Global Change Biology · 2024

Read source ↗ All evidence

Summary

This machine learning study analysed global observational data to quantify N₂O emissions from agriculturally managed peatlands and apportion sources between fertiliser application and peat decomposition. The findings indicate that croplands emit substantially more N₂O than grasslands (401 vs 64 kt N year⁻¹), with fertiliser contributing 121.6 kt N year⁻¹ on croplands but only 4.6 kt N year⁻¹ on grasslands. The study suggests land-use-specific mitigation strategies: fertiliser reduction and rewetting both offer promise for croplands, whilst rewetting takes priority for grasslands to arrest peat degradation.

UK applicability

The United Kingdom contains extensive managed peatlands, particularly in upland regions and the Fens, where agriculture-driven N₂O emissions contribute significantly to national greenhouse gas inventories. The findings support UK climate and agricultural policy by providing evidence that rewetting degraded peatlands—increasingly advocated in UK peatland restoration strategies—can deliver substantial N₂O reductions, alongside or in place of fertiliser reduction.

Key measures

Annual N₂O emissions (kt N year⁻¹) from peatland croplands and grasslands; fertiliser-induced N₂O emission factors (%); N₂O reduction potential from 20% fertiliser reduction and rewetting scenarios

Outcomes reported

The study quantified N₂O emissions from agriculturally managed peatlands globally, distinguishing contributions from fertiliser application versus peat decomposition, and evaluated the relative mitigation potential of fertiliser reduction versus rewetting across croplands and grasslands.

Theme
Climate & resilience
Subject
Climate & greenhouse gas mitigation
Study type
Research
Study design
Machine learning modelling study using global observational data
Source type
Peer-reviewed study
Status
Published
Geography
Global
System type
Mixed farming
DOI
10.1111/gcb.17144
Catalogue ID
BFmou2mcwq-b7koqb

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.