Estimation of the global carbon fluxes due to agricultural management activities using a land surface model (ISAM)

Sharma, Prateek

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https://hdl.handle.net/2142/109638 Copy

Description

Title

Estimation of the global carbon fluxes due to agricultural management activities using a land surface model (ISAM)

Author(s)

Sharma, Prateek

Issue Date

2020-12-09

Director of Research (if dissertation) or Advisor (if thesis)

Jain, Atul

Department of Study

Atmospheric Sciences

Discipline

Atmospheric Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Land-use change
• Greenhouse gas
• Agricultural land management

Abstract

Agricultural activities contribute to global greenhouse gas (GHG) emissions and climate. The worldwide hike in the food demand due to the rapidly growing population over time has intensified agricultural activities, resulting in a significant amount of GHG emissions (e.g., CO2, CH4, and N2O). Previous global studies have focused on non-CO2 emissions (i.e., CH4, N2O) and ignored the CO2 emissions from the agriculture sector. This study uses a land surface model with spatially heterogeneous representations of agricultural land management practices to estimate the carbon dynamics induced by agricultural land management practices (i.e., planting crops, fertilization, irrigation, harvesting, and grazing) and land-use change (i.e., agricultural land expansion). The estimated global net carbon emission from agriculture and its related land-use change is 2.26 Pg C/yr (net source) in ca. 2010. The land management activities released 0.85 Pg C/yr (38%), and the land-use change activities emitted 1.41 Pg C/yr (62%). Cropland and grazing land released about 72% and 28% of the total agriculture emissions. Maize, rice, and wheat are the greatest contributing crops. South America (22%), North America (19%) and, South and Southeast Asia (13%) are the leading emitting regions. By quantifying the carbon emissions induced by different agricultural management practices, this study help in improving the representations of land management practices in the climate models.

Graduation Semester

2020-12

Type of Resource

Thesis

Permalink

http://hdl.handle.net/2142/109638

Copyright and License Information

Copyright 2020 Prateek Sharma

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