Data

Data on zero tillages affect on greenhouse gas emissions

University of Southern Queensland
Narayan Maraseni, Tek, Dr ; Cockfield, Geoff, Dr
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft.title=Dataset Greenhouse gas emissions from zero tillage&rft.identifier=USQ-DataColl-0005&rft.publisher=University of Southern Queensland&rft.description= The Australian Government has recommended that farmers move from cultivation-based dryland farming to reduced or zero tillage systems. The private benefits could include improvements in yields and a decrease in costs while the public benefits could include a reduction in greenhouse gas (GHG) emissions due to a diminution in the use of heavy machinery. The aim of this study is to estimate and compare total on-farm GHG emissions from conventional and zero tillage systems based on selected grain crop rotations in the Darling Downs region of Queensland, Australia. The value chain was identified, including all inputs, and emissions. In addition, studies of soil carbon sequestration and nitrous oxide emissions under the different cropping systems were reviewed. The value chain analysis revealed that the net effect on GHG emissions by switching to zero tillage is positive but relatively small. In addition though, the review of the sequestration studies suggests that there might be soil-based emissions that result from zero tillage that are being under-estimated. Therefore, zero tillage may not necessarily reduce overall GHG emissions. This could have major implication on current carbon credits offered from volunteer carbon markets for converting conventional tillage to reduced tillage system. &rft.creator=Narayan Maraseni, Tek &rft.creator=Cockfield, Geoff &rft.date=2013&rft.coverage=150.922851,-27.201755 149.823583,-27.201755 149.823583,-28.413942 150.922851,-28.413942 150.922851,-27.201755&rft_subject=70106&rft_subject=Environmental Management&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=Farming Systems Research&rft_subject=AGRICULTURAL AND VETERINARY SCIENCES&rft_subject=AGRICULTURE, LAND AND FARM MANAGEMENT&rft_place=Toowoomba&rft.type=dataset&rft.language=English Access the data

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Contact Information

Postal Address:
University of Southern Queensland Toowoomba Qld 4350 Australia

Maraseni@usq.edu.au

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Contact Dr Tek Maraseni
by email Maraseni@usq.edu.au

Full description

The Australian Government has recommended that farmers move from cultivation-based dryland farming to reduced or zero tillage systems. The private benefits could include improvements in yields and a decrease in costs while the public benefits could include a reduction in greenhouse gas (GHG) emissions due to a diminution in the use of heavy machinery. The aim of this study is to estimate and compare total on-farm GHG emissions from conventional and zero tillage systems based on selected grain crop rotations in the Darling Downs region of Queensland, Australia. The value chain was identified, including all inputs, and emissions. In addition, studies of soil carbon sequestration and nitrous oxide emissions under the different cropping systems were reviewed. The value chain analysis revealed that the net effect on GHG emissions by switching to zero tillage is positive but relatively small. In addition though, the review of the sequestration studies suggests that there might be soil-based emissions that result from zero tillage that are being under-estimated. Therefore, zero tillage may not necessarily reduce overall GHG emissions. This could have major implication on current carbon credits offered from volunteer carbon markets for converting conventional tillage to reduced tillage system.

Notes

Files

 

Greenhouse gas emissions

        XLSX (1)

    MS Office Excel 2007

 

Available: 19 01 2013

This dataset is part of a larger collection

Click to explore relationships graph

151.93783,-27.59039 151.90769,-27.59039 151.90769,-27.62095 151.93783,-27.62095 151.93783,-27.59039

151.9227575,-27.6056685

150.92285,-27.20176 149.82358,-27.20176 149.82358,-28.41394 150.92285,-28.41394 150.92285,-27.20176

150.373217,-27.8078485

Identifiers
  • Local : USQ-DataColl-0005