Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 265

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Changes in Aerosol Chemistry From 2014 to 2016 in Winter in Beijing: Insights From High‐Resolution Aerosol Mass Spectrometry

Open access
Xu, Weiqi, Sun, Yele, Wang, Qingqing, Zhao, Jian, Wang, Junfeng, Ge, Xinlei, Xie, Conghui, Zhou, Wei, Du, Wei, Li, Jie, Fu, Pingqing, Wang, Zifa, Worsnop, Douglas R., Coe, Hugh·2019·Journal of Geophysical Research: Atmospheres

Abstract

Air quality has been continuously improved in recent years in Beijing, yet severe haze episodes still frequently occur in winter. Here we deployed an Aerodyne high‐resolution aerosol mass spectrometer in two winter seasons during the same period to investigate the changes in aerosol chemistry from 2014 to 2016 in Beijing. Compared to 2014, submicron aerosol (PM 1) species showed ubiquitous increases in mass concentrations by 10–130% in winter 2016, of which nitrate showed the largest increase among all aerosol species leading to a much higher NO 3/SO 4 ratio in 2016 (1.36 ± 0.90) than 2014 (0.72 ± 0.59). This result highlights an increasing role of nitrate in particulate matter pollution in recent years in Beijing. Aerosol composition and size distributions also changed significantly. Secondary inorganic species showed elevated contributions by ~10% in winter 2016 associated with corresponding decreases in organic aerosol (OA). Positive matrix factorization of OA illustrated the significant changes in both primary emissions and secondary production. While cooking OA decreased substantially from 25% in 2014 to 15% in 2016, the contribution of biomass burning OA slightly increased instead. Although secondary OA contributed similarly to OA in the two winters (49% vs. 53%), we observed ubiquitous increases (~50%) in photochemically related oxygenated OA and oxidized primary OA, and oxygen‐to‐carbon ratios of OA, indicating the enhanced photochemical production in winter 2016. Aqueous‐phase production of secondary OA however was relatively similar in the two winters. Further analysis demonstrated that the changes in aerosol and OA composition varied differently across different pollution and relative humidity levels.

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 · 10.1029/2018jd029245

Cites

46 of 46 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 46 references

Cited by

See all 265

Metadata

Authors
Xu, W., Sun, Y., Wang, Q., Zhao, J., Wang, J., Ge, X., Xie, C., Zhou, W., Du, W., Li, J., Fu, P., Wang, Z., Worsnop, D. R., & Coe, H.
Venue
Journal of Geophysical Research: Atmospheres
Published
2019-01-17
Volume
124
Issue
2
Pages
1132-1147
ISSN
  • 0148-0227 (ISSN-L)
  • 2169-897X
  • 2169-8996
OpenAlex
W2905626381
Cited by
265
References
46
FWCI
14.28
Type
journal article
Language
en
Open access
green

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: Changes in Aerosol Chemistry From 2014 to 2016 in Winter in Beijing: Insights From High‐Resolution Aerosol Mass Spectrometry. https://app.cochat.ai/papers/10.1029/2018jd029245
The paper
Xu, W., Sun, Y., Wang, Q., Zhao, J., Wang, J., Ge, X., Xie, C., Zhou, W., Du, W., Li, J., Fu, P., Wang, Z., Worsnop, D. R., & Coe, H. (2019). Changes in Aerosol Chemistry From 2014 to 2016 in Winter in Beijing: Insights From High‐Resolution Aerosol Mass Spectrometry. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2018jd029245

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.