Innovation in environmental sustainability: Carbon credits with proof of reserve on rural properties according to the standards of regulated markets

Farms are increasingly recognized as carbon sinks with significant potential to mitigate climate change. This study documents how farms can become positive climate assets by using portable sensors, satellite imagery, blockchain, and AI to quantify and monetize carbon removal. This technological integration enables the issuance of traceable and secure carbon credits, promoting sustainable land use and granting a range of farms access to carbon markets. We evaluated the reliability and spatial consistency of soil carbon retention in agricultural and forestry systems on four rural properties in Brazil during the 2022/2023 harvest. Using a protocol certified by the Brazilian legislation, we compared sensor-derived carbon estimates with reference measurements in farmland and forest areas. In agricultural areas, sensor readings showed high agreement with reference standards, reflecting strong adherence to certified standards. Agreement was more heterogeneous in forested areas, suggesting spatial variations in carbon stocks not captured by conventional methods. Spatial analysis revealed distinct patterns of autocorrelation between land use types, with stronger spatial clustering in agricultural systems. The results demonstrate that proprietary sensors integrated with artificial intelligence platforms are effective for estimating carbon retention, especially in cultivated areas, and offer great potential for supporting the certification of carbon credits based on auditable data. The results also highlight the effectiveness of land management practices and the potential of forest and agricultural areas as legitimate sources of regulated carbon credits. These credits can serve as effective tools for the transition to a low-carbon economy, especially in sectors that are harder to decarbonize. In addition, they promote social and climate justice by linking the carbon sequestration potential of the Global South with the North’s demand for compensation, providing environmental, economic, and social benefits.

Authors

Institutions

Publication Details

Journal
PLOS Climate
Published
2025-11-05
DOI
https://doi.org/10.1371/journal.pclm.0000639
Primary Topic
Conservation, Biodiversity, and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Innovation in environmental sustainability: Carbon credits with proof of reserve on rural properties according to the standards of regulated markets

Miguel Ángel Uribe-Opazo, Marcos Alexandre Fernandes Ferronato, Ana Carolina Clivatti Ferronato
PLOS Climate
Conservation, Biodiversity, and Resource Management
article

Innovation in environmental sustainability: Carbon credits with proof of reserve on rural properties according to the standards of regulated markets

Miguel Ángel Uribe-Opazo, Marcos Alexandre Fernandes Ferronato, Ana Carolina Clivatti Ferronato
article en

Abstract

Farms are increasingly recognized as carbon sinks with significant potential to mitigate climate change. This study documents how farms can become positive climate assets by using portable sensors, satellite imagery, blockchain, and AI to quantify and monetize carbon removal. This technological integration enables the issuance of traceable and secure carbon credits, promoting sustainable land use and granting a range of farms access to carbon markets. We evaluated the reliability and spatial consistency of soil carbon retention in agricultural and forestry systems on four rural properties in Brazil during the 2022/2023 harvest. Using a protocol certified by the Brazilian legislation, we compared sensor-derived carbon estimates with reference measurements in farmland and forest areas. In agricultural areas, sensor readings showed high agreement with reference standards, reflecting strong adherence to certified standards. Agreement was more heterogeneous in forested areas, suggesting spatial variations in carbon stocks not captured by conventional methods. Spatial analysis revealed distinct patterns of autocorrelation between land use types, with stronger spatial clustering in agricultural systems. The results demonstrate that proprietary sensors integrated with artificial intelligence platforms are effective for estimating carbon retention, especially in cultivated areas, and offer great potential for supporting the certification of carbon credits based on auditable data. The results also highlight the effectiveness of land management practices and the potential of forest and agricultural areas as legitimate sources of regulated carbon credits. These credits can serve as effective tools for the transition to a low-carbon economy, especially in sectors that are harder to decarbonize. In addition, they promote social and climate justice by linking the carbon sequestration potential of the Global South with the North’s demand for compensation, providing environmental, economic, and social benefits.

PLOS ClimateVol. 4(11)
Universidade Estadual do Oeste do Paraná (BR)
Openalex Percentile: Top 70%
Conservation, Biodiversity, and Resource Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.