The DOI matches its Crossref record.
Coal to gas: the influence of methane leakage
Open accessAbstract
Carbon dioxide (CO 2 ) emissions from fossil fuel combustion may be reduced by using natural gas rather than coal to produce energy. Gas produces approximately half the amount of CO 2 per unit of primary energy compared with coal. Here we consider a scenario where a fraction of coal usage is replaced by natural gas (i.e., methane, CH 4 ) over a given time period, and where a percentage of the gas production is assumed to leak into the atmosphere. The additional CH 4 from leakage adds to the radiative forcing of the climate system, offsetting the reduction in CO 2 forcing that accompanies the transition from coal to gas. We also consider the effects of: methane leakage from coal mining; changes in radiative forcing due to changes in the emissions of sulfur dioxide and carbonaceous aerosols; and differences in the efficiency of electricity production between coal- and gas-fired power generation. On balance, these factors more than offset the reduction in warming due to reduced CO 2 emissions. When gas replaces coal there is additional warming out to 2,050 with an assumed leakage rate of 0%, and out to 2,140 if the leakage rate is as high as 10%. The overall effects on global-mean temperature over the 21st century, however, are small.
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.
Integrity signals
Registry
Cites
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.
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
Cited by
Air Quality and Climate Connections
Fiore, A. M., Naik, V., & Leibensperger, E. M. (2015) · Journal of the Air & Waste Management Association · doi:10.1080/10962247.2015.1040526 · Cited by 537
Machine vision for natural gas methane emissions detection using an infrared camera
Wang, J., Tchapmi, L. P., Ravikumar, A. P., McGuire, M., Bell, C. S., Zimmerle, D., Savarese, S., & Brandt, A. R. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.113998 · Cited by 205
Metadata
- Authors
- Wigley, T. M. L.
- Venue
- Climatic Change
- Published
- 2011-08-26
- Volume
- 108
- Issue
- 3
- ISSN
- 0165-0009 (ISSN-L)
- 1573-1480
- OpenAlex
- W2153286071
- Cited by
- 196
- References
- 0
- FWCI
- 49.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Coal to gas: the influence of methane leakage. https://app.cochat.ai/papers/10.1007/s10584-011-0217-3
- The paper
- Wigley, T. M. L. (2011). Coal to gas: the influence of methane leakage. Climatic Change. https://doi.org/10.1007/s10584-011-0217-3
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.