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A method for calculating a land-use change carbon footprint (LUC-CFP) for agricultural commodities - applications to Brazilian beef and soy, Indonesian palm oil

Overview of attention for article published in Global Change Biology, June 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
5 tweeters

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
152 Mendeley
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Title
A method for calculating a land-use change carbon footprint (LUC-CFP) for agricultural commodities - applications to Brazilian beef and soy, Indonesian palm oil
Published in
Global Change Biology, June 2014
DOI 10.1111/gcb.12635
Pubmed ID
Authors

U. Martin Persson, Sabine Henders, Christel Cederberg

Abstract

The world's agricultural system has come under increasing scrutiny recently as an important driver of global climate change, creating a demand for indicators that estimate the climatic impacts of agricultural commodities. Such carbon footprints, however, have in most cases excluded emissions from land-use change and the proposed methodologies for including this significant emissions source suffer from different shortcomings. Here, we propose a new methodology for calculating land-use change carbon footprints for agricultural commodities and illustrate this methodology by applying it to three of the most prominent agricultural commodities driving tropical deforestation: Brazilian beef and soybeans, and Indonesian palm oil. We estimate land-use change carbon footprints in 2010 to be 66 tCO2 /t meat (carcass weight) for Brazilian beef, 0.89 tCO2 /t for Brazilian soybeans, and 7.5 tCO2 /t for Indonesian palm oil, using a 10 year amortization period. The main advantage of the proposed methodology is its flexibility: it can be applied in a tiered approach, using detailed data where it is available while still allowing for estimation of footprints for a broad set of countries and agricultural commodities; it can be applied at different scales, estimating both national and subnational footprints; it can be adopted to account both for direct (proximate) and indirect drivers of land-use change. It is argued that with an increasing commercialization and globalization of the drivers of land-use change, the proposed carbon footprint methodology could help leverage the power needed to alter environmentally destructive land-use practices within the global agricultural system by providing a tool for assessing the environmental impacts of production, thereby informing consumers about the impacts of consumption and incentivizing producers to become more environmentally responsible.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 152 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 6 4%
Germany 2 1%
Norway 1 <1%
Italy 1 <1%
Mexico 1 <1%
France 1 <1%
Australia 1 <1%
India 1 <1%
Switzerland 1 <1%
Other 4 3%
Unknown 133 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 24%
Researcher 33 22%
Student > Master 28 18%
Student > Bachelor 13 9%
Student > Doctoral Student 10 7%
Other 31 20%
Readers by discipline Count As %
Environmental Science 57 38%
Agricultural and Biological Sciences 37 24%
Unspecified 16 11%
Engineering 8 5%
Earth and Planetary Sciences 8 5%
Other 26 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 July 2019.
All research outputs
#1,074,164
of 13,635,031 outputs
Outputs from Global Change Biology
#1,299
of 3,714 outputs
Outputs of similar age
#21,334
of 231,540 outputs
Outputs of similar age from Global Change Biology
#27
of 71 outputs
Altmetric has tracked 13,635,031 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.2. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 231,540 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.