The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Regionally-Varying Combustion Sources of the January 2013 Severe Haze Events over Eastern China
Abstract
Thick haze plagued northeastern China in January 2013, strongly affecting both regional climate and human respiratory health. Here, we present dual carbon isotope constrained (Δ(14)C and δ(13)C) source apportionment for combustion-derived black carbon aerosol (BC) for three key hotspot regions (megacities): North China Plain (NCP, Beijing), the Yangtze River Delta (YRD, Shanghai), and the Pearl River Delta (PRD, Guangzhou) for January 2013. BC, here quantified as elemental carbon (EC), is one of the most health-detrimental components of PM2.5 and a strong climate warming agent. The results show that these severe haze events were equally affected (∼ 30%) by biomass combustion in all three regions, whereas the sources of the dominant fossil fuel component was dramatically different between north and south. In the NCP region, coal combustion accounted for 66% (46-74%, 95% C.I.) of the EC, whereas, in the YRD and PRD regions, liquid fossil fuel combustion (e.g., traffic) stood for 46% (18-66%) and 58% (38-68%), respectively. Taken together, these findings suggest the need for a regionally-specific description of BC sources in climate models and regionally-tailored mitigation to combat severe air pollution events in East Asia.
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
Cites
Bounding the role of black carbon in the climate system: A scientific assessment
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., et al. (2013) · Journal of Geophysical Research: Atmospheres · doi:10.1002/jgrd.50171 · Cited by 6,385
Cited by
Enhanced haze pollution by black carbon in megacities in China
Ding, A. J., Huang, X., Nie, W., Sun, J. N., Kerminen, V. ‐., Petäjä, T., Su, H., Cheng, Y. F., Yang, X. ‐., Wang, M. H., et al. (2016) · Geophysical Research Letters · doi:10.1002/2016gl067745 · Cited by 895
Pan, Y., Tian, S., Liu, D., Fang, Y., Zhu, X., Zhang, Q., Zheng, B., Michalski, G., & Wang, Y. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b00634 · Cited by 357
Gao, J., Woodward, A., Vardoulakis, S., Kovats, S., Wilkinson, P., Li, L., Xu, L., Li, J., Yang, J., Li, J., et al. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2016.10.231 · Cited by 292
Siberian Arctic black carbon sources constrained by model and observation
Winiger, P., Andersson, A., Eckhardt, S., Stohl, A., Semiletov, I. P., Dudarev, O. V., Charkin, A., Shakhova, N., Klimont, Z., Heyes, C., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1613401114 · Cited by 126
Self-citationAguilera, J., & Whigham, L. D. (2018) · Isotopes in Environmental and Health Studies · doi:10.1080/10256016.2018.1531854 · Cited by 43
Metadata
- Authors
- Andersson, A., Deng, J., Du, K., Zheng, M., Yan, C., Sköld, M., & Gustafsson, Ö.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-01-28
- Volume
- 49
- Issue
- 4
- Pages
- 2038-2043
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2004691206
- Cited by
- 304
- References
- 1
- FWCI
- 17.87
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Regionally-Varying Combustion Sources of the January 2013 Severe Haze Events over Eastern China. https://app.cochat.ai/papers/10.1021/es503855e
- The paper
- Andersson, A., Deng, J., Du, K., Zheng, M., Yan, C., Sköld, M., & Gustafsson, Ö. (2015). Regionally-Varying Combustion Sources of the January 2013 Severe Haze Events over Eastern China. Environmental Science & Technology. https://doi.org/10.1021/es503855e
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.
