Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 340

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Estimating profitability of two biochar production scenarios: slow pyrolysis vs fast pyrolysis

Brown, Tristan R., Wright, Mark M., Brown, Robert C.·2011·Biofuels, Bioproducts and Biorefining
DOI 10.1002/bbb.254
Open this paper in CoChat — free account

Abstract

We estimate the profitability of producing biochar from crop residue (corn stover) for two scenarios. The first employs slow pyrolysis to generate biochar and pyrolysis gas and has the advantage of high yields of char (as much as 40 wt‐%) but the disadvantage of producing a relatively low‐value energy product (pyrolysis gas of modest heating value). The second scenario employs fast pyrolysis to maximize production of bio‐oil with biochar and pyrolysis gas as lower‐yielding coproducts. The fast pyrolysis scenario produces a substantially higher value energy product than slow pyrolysis but at the cost of higher capital investment. We calculate the internal rate of return (IRR) for each scenario as functions of cost of feedstock and projected revenues for the pyrolysis facility. The assumed price range for delivered biomass feedstock is $0 to $83 per metric ton. The assumed carbon offset value for biochar ranges from $20 per metric ton of biochar in 2015 to $60 in 2030. The slow pyrolysis scenario in 2015 is not profitable at an assumed feedstock cost of $83 per metric ton. The fast pyrolysis scenario in 2015 yields 15% IRR with the same feedstock cost because gasoline refined from the bio‐oil provides revenues of $2.96 per gallon gasoline equivalent. By 2030, the value of biochar as a carbon offset is projected to increase to $60 per metric ton and the price of gasoline is expected to reach $3.70 per gallon, which would provide investors with an IRR of 26%. © 2010 Society of Chemical Industry and John Wiley & Sons, Ltd

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/bbb.254

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 30 references

Cited by

Metadata

Authors
Brown, T. R., Wright, M. M., & Brown, R. C.
Venue
Biofuels, Bioproducts and Biorefining
Publisher
Wiley
Published
2010-12-07
Volume
5
Issue
1
Pages
54-68
ISSN
  • 1932-1031 (ISSN-L)
  • 1932-104X
DOI
10.1002/bbb.254
OpenAlex
W2051769438
Cited by
340
References
30
FWCI
8.56
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.