Research & Development World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • Call for Nominations: The 2025 R&D 100 Awards
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
    • Explore the 2024 R&D 100 award winners and finalists
  • Resources
    • Research Reports
    • Digital Issues
    • R&D Index
    • Subscribe
    • Video
    • Webinars
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE

Researchers improve soil carbon cycling models

By R&D Editors | August 17, 2012

/sites/rdmag.com/files/legacyimages/RD/News/2012/08/CarbonCycle2x500.jpg

click to enlarge

Oak Ridge National Laboratory’s new carbon cycling model could help scientists understand the role of soil in climate change by tracking the microbial processes that break down carbon-rich materials.

A new carbon cycling model developed at the U.S. Department of
Energy’s (DOE) Oak Ridge National Laboratory (ORNL) better accounts for the
carbon dioxide-releasing activity of microbes in the ground, improving
scientists’ understanding of the role soil will play in future climate change.

Predicting climate change depends heavily on the cycling of
carbon dioxide, which is found in four main reservoirs: the atmosphere,
biosphere, oceans, and soil. ORNL’s model was designed to replace traditional
soil carbon cycling models.

“Soil is a big reservoir of carbon,” says co-author
Melanie Mayes of ORNL’s Environmental Sciences Division. “And most of the
soil carbon cycling models in use today are so vastly simplified that they
ignore the fact that decomposition is actually performed by microbes.”

In a paper published in Ecological
Applications
, ORNL researchers integrated data from scientific literature
on carbon degradation in soil to form the Microbial-Enzyme-mediated
Decomposition, or MEND, model that improves upon previous models.

“Our MEND model does a better job of representing the
mechanisms of soil carbon decomposition than existing models,” Mayes says.

ORNL’s comprehensive model accounts for how the different forms
of carbon in soil, or “pools,” react with extracellular enzymes
excreted into the soil by microbes, allowing scientists to understand how
quickly carbon is moving through soils.

The model simulates the carbon cycle, beginning after a decaying
plant or animal releases carbon-rich materials into the soil. The organic
material is degraded by enzymatic reactions, releasing dissolved carbon
molecules that can be absorbed by microbes for growth or metabolism. These
processes ultimately result in the release of carbon dioxide.

ORNL’s MEND model is the first model able to track degradation
by accounting for most of the relevant processes and by estimating the
parameters based on a comprehensive literature review. This model, which is
based on the physiological functions of microbes, accounts for how temperature
affects the ability of microbes to emit carbon dioxide. Soil can either store
or release carbon depending on how rapidly carbon-rich materials in the soil
are decomposed.

“What we think will happen is that as temperature goes up,
microbial physiology will change, altering their ability to break down carbon
chains and release carbon dioxide into the atmosphere,” Mayes says.
“If our models don’t account for this process, then our ability to predict
future climate change will be less realistic.”

For the next six to eight months, ORNL’s team will run laboratory-scale
experiments to ensure that the MEND model accurately represents the
decomposition of carbon compounds in soils. Eventually, team members hope to
incorporate their model into the publicly available supercomputing program
called the Community Land Model, a module used in the Community Earth System
Model that helps researchers predict future climate change.

Source: Oak Ridge National Laboratory

Related Articles Read More >

Floating solar mats clean polluted water — and generate power
New AI model offers faster, adaptive CO₂ retrieval from satellite data
8 major R&D moves this week: Samsung invests record $24B while Porsche cuts 3,900 jobs
Ex-Google AI team launches “Generation,” an AI-driven fragrance venture
rd newsletter
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, trends, and strategies in Research & Development.
RD 25 Power Index

R&D World Digital Issues

Fall 2024 issue

Browse the most current issue of R&D World and back issues in an easy to use high quality format. Clip, share and download with the leading R&D magazine today.

Research & Development World
  • Subscribe to R&D World Magazine
  • Enews Sign Up
  • Contact Us
  • About Us
  • Drug Discovery & Development
  • Pharmaceutical Processing
  • Global Funding Forecast

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search R&D World

  • R&D World Home
  • Topics
    • Aerospace
    • Automotive
    • Biotech
    • Careers
    • Chemistry
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Software
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
    • Semiconductors
  • R&D Market Pulse
  • R&D 100
    • Call for Nominations: The 2025 R&D 100 Awards
    • R&D 100 Awards Event
    • R&D 100 Submissions
    • Winner Archive
    • Explore the 2024 R&D 100 award winners and finalists
  • Resources
    • Research Reports
    • Digital Issues
    • R&D Index
    • Subscribe
    • Video
    • Webinars
  • Global Funding Forecast
  • Top Labs
  • Advertise
  • SUBSCRIBE