The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes
Open accessAbstract
Significance: Severe haze events with large temporal/spatial coverages have occurred frequently in wintertime northern China. These extremes result from a complex interplay between emissions and atmospheric processes and provide a unique scientific platform to gain insights into many aspects of the relevant atmospheric chemistry and physics. Here we synthesize recent progress in understanding severe haze formation in northern China. In particular, we highlight that improved understanding of the emission sources, physical/chemical processes during haze evolution, and interactions with meteorological/climatic changes are necessary to unravel the causes, mechanisms, and trends for haze pollution. This viewpoint established on the basis of sound science is critical for improving haze prediction/forecast, formulating effective regulatory policies by decision makers, and raising public awareness of environmental protection.
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
Cohen, A. J., Brauer, M., Burnett, R., Anderson, H. R., Frostad, J., Estep, K., Balakrishnan, K., Brunekreef, B., Dandona, L., Dandona, R., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)30505-6 · Cited by 6,583
Formation of Urban Fine Particulate Matter
Zhang, R., Wang, G., Guo, S., Zamora, M. L., Ying, Q., Lin, Y., Wang, W., Hu, M., & Wang, Y. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00067 · Cited by 1,426
Self-citationFine particulate matter (PM2.5) in China at a city level
Zhang, Y.-L., & Cao, F. (2015) · Scientific Reports · doi:10.1038/srep14884 · Cited by 921
China׳s international trade and air pollution in the United States
Lin, J., Pan, D., Davis, S. J., Zhang, Q., He, K., Wang, C., Streets, D. G., Wuebbles, D. J., & Guan, D. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1312860111 · Cited by 482
Elser, M., Huang, R.-J., Wolf, R., Slowik, J. G., Wang, Q., Canonaco, F., Li, G., Bozzetti, C., Daellenbach, K. R., Huang, Y., et al. (2016) · Atmospheric Chemistry and Physics · doi:10.5194/acp-16-3207-2016 · Cited by 389
Self-citationGuo, H., Weber, R. J., & Nenes, A. (2017) · Scientific Reports · doi:10.1038/s41598-017-11704-0 · Cited by 268
Rate constant for the reaction of nitrogen dioxide with sulfur(IV) over the pH range 5.3-13
Clifton, C. L., Altstein, N., & Huie, R. E. (1988) · Environmental Science & Technology · doi:10.1021/es00170a018 · Cited by 152
In utero ultrafine particulate matter exposure causes offspring pulmonary immunosuppression
Rychlik, K. A., Secrest, J. R., Lau, C., Pulczinski, J., Zamora, M. L., Leal, J., Langley, R., Myatt, L. G., Raju, M., Chang, R. C.-A., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1816103116 · Cited by 98
Self-citation
Cited by
Identifying airborne transmission as the dominant route for the spread of COVID-19
Zhang, R., Li, Y., Zhang, A. L., Wang, Y., & Molina, M. J. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2009637117 · Cited by 1,236
Self-citationContrasting trends of PM2.5 and surface-ozone concentrations in China from 2013 to 2017
Wang, Y., Gao, W., Wang, S., Song, T., Gong, Z., Ji, D., Wang, L., Liu, Z., Tang, G., Huo, Y., et al. (2020) · National Science Review · doi:10.1093/nsr/nwaa032 · Cited by 545
Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000
Liu, S., Geng, G., Xiao, Q., Zheng, Y., Liu, X., Cheng, J., & Zhang, Q. (2022) · Environmental Science & Technology · doi:10.1021/acs.est.2c06510 · Cited by 359
Aerosol–photolysis interaction reduces particulate matter during wintertime haze events
Wu, J., Bei, N., Hu, B., Liu, S., Wang, Y., Shen, Z., Li, X., Liu, L., Wang, R., Liu, Z., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1916775117 · Cited by 119
Self-citationWu, G., Brown, J., Zamora, M. L., Miller, A., Satterfield, M. C., Meininger, C. J., Steinhauser, C. B., Johnson, G. A., Burghardt, R. C., Bazer, F. W., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902925116 · Cited by 76
Self-citation
Metadata
- Authors
- An, Z., Huang, R.-J., Zhang, R., Tie, X., Li, G., Cao, J., Zhou, W., Shi, Z., Han, Y., Gu, Z., & Ji, Y.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2019-04-15
- Volume
- 116
- Issue
- 18
- Pages
- 8657-8666
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2939064738
- Cited by
- 1,015
- References
- 8
- FWCI
- 58.03
- 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: Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes. https://app.cochat.ai/papers/10.1073/pnas.1900125116
- The paper
- An, Z., Huang, R.-J., Zhang, R., Tie, X., Li, G., Cao, J., Zhou, W., Shi, Z., Han, Y., Gu, Z., & Ji, Y. (2019). Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1900125116
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.
