Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 715

The DOI matches its Crossref record.

Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013

Sun, Yele, Jiang, Qi, Wang, Zifa, Fu, Pingqing, Li, Jie, Yang, Ting, Yin, Yan·2014·Journal of Geophysical Research: Atmospheres

Abstract

China experienced severe haze pollution in January 2013. Here we have a detailed characterization of the sources and evolution mechanisms of this haze pollution with a focus on four haze episodes that occurred during 10–14 January in Beijing. The main source of data analyzed is from submicron aerosol measurements by an Aerodyne Aerosol Chemical Speciation Monitor. The average PM1 mass concentration during the four haze episodes ranged from 144 to 300 µg m−3, which was more than 10 times higher than that observed during clean periods. All submicron aerosol species showed substantial increases during haze episodes with sulfate being the largest. Secondary inorganic species played enhanced roles in the haze formation as suggested by their elevated contributions during haze episodes. Positive matrix factorization analysis resolved six organic aerosol (OA) factors including three primary OA (POA) factors from traffic, cooking, and coal combustion emissions, respectively, and three secondary OA (SOA) factors. Overall, SOA contributed 41–59% of OA with the rest being POA. Coal combustion OA (CCOA) was the largest primary source, on average accounting for 20–32% of OA, and showed the most significant enhancement during haze episodes. A regional SOA (RSOA) was resolved for the first time which showed a pronounced peak only during the record‐breaking haze episode (Ep3) on 12–13 January. The regional contributions estimated based on the steep evolution of air pollutants were found to play dominant roles for the formation of Ep3, on average accounting for 66% of PM1 during the peak of Ep3 with sulfate, CCOA, and RSOA being the largest fractions (> ~ 75%). Our results suggest that stagnant meteorological conditions, coal combustion, secondary production, and regional transport are four main factors driving the formation and evolution of haze pollution in Beijing during wintertime.

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 · 10.1002/2014jd021641

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.

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

Cited by

See all 715

Metadata

Authors
Sun, Y., Jiang, Q., Wang, Z., Fu, P., Li, J., Yang, T., & Yin, Y.
Venue
Journal of Geophysical Research: Atmospheres
Published
2014-04-09
Volume
119
Issue
7
Pages
4380-4398
ISSN
  • 0148-0227 (ISSN-L)
  • 2169-897X
  • 2169-8996
OpenAlex
W1819362720
Cited by
715
References
0
FWCI
43.69
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: Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013. https://app.cochat.ai/papers/10.1002/2014jd021641
The paper
Sun, Y., Jiang, Q., Wang, Z., Fu, P., Li, J., Yang, T., & Yin, Y. (2014). Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1002/2014jd021641

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.