The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000
Open accessAbstract
High Resolution Image Download MS PowerPoint Slide PM 2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China’s PM 2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM 2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting–Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM 2.5 data. PM 2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM 2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of −9.0, −7.2, −8.1, −8.4, and −9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM 2.5 components. As part of Tracking Air Pollution in China ( http://tapdata.org.cn ), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.
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
Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., et al. (2018) · Atmospheric Chemistry and Physics · doi:10.5194/acp-18-14095-2018 · Cited by 2,916
Self-citationDrivers of improved PM 2.5 air quality in China from 2013 to 2017
Zhang, Q., Zheng, Y., Tong, D., Shao, M., Wang, S., Zhang, Y., Xu, X., Wang, J., He, H., Liu, W., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907956116 · Cited by 2,204
Self-citationSources and distributions of dust aerosols simulated with the GOCART model
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., & Lin, S. (2001) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2000jd000053 · Cited by 2,167
Turpin, B. J., & Lim, H.-J. (2001) · Aerosol Science and Technology · doi:10.1080/02786820119445 · Cited by 2,036
Asian emissions in 2006 for the NASA INTEX-B mission
Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H., Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., et al. (2009) · Atmospheric Chemistry and Physics · doi:10.5194/acp-9-5131-2009 · Cited by 1,950
Self-citationThe CAMS reanalysis of atmospheric composition
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., et al. (2019) · Atmospheric Chemistry and Physics · doi:10.5194/acp-19-3515-2019 · Cited by 1,480
Randles, C. A., da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A., Govindaraju, R., Smirnov, A., Holben, B., Ferrare, R., Hair, J., et al. (2017) · Journal of Climate · doi:10.1175/jcli-d-16-0609.1 · Cited by 1,469
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
Modeling the atmospheric dust cycle: 1. Design of a soil‐derived dust emission scheme
Marticorena, B., & Bergametti, G. (1995) · Journal of Geophysical Research: Atmospheres · doi:10.1029/95jd00690 · Cited by 1,409
Anthropogenic emission inventories in China: a review
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., et al. (2017) · National Science Review · doi:10.1093/nsr/nwx150 · Cited by 1,304
Self-citation
Cited by
Feng, C., Shao, Y., Ye, T., Cai, C., Yin, C., Li, X., Liu, H., Ma, H., Yu, B., Qin, M., et al. (2023) · Science of The Total Environment · doi:10.1016/j.scitotenv.2023.166755 · Cited by 33
Metadata
- Authors
- Liu, S., Geng, G., Xiao, Q., Zheng, Y., Liu, X., Cheng, J., & Zhang, Q.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2022-11-01
- Volume
- 56
- Issue
- 22
- Pages
- 16517-16527
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W4307804709
- Cited by
- 359
- References
- 56
- FWCI
- 24.27
- 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: Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000. https://app.cochat.ai/papers/10.1021/acs.est.2c06510
- The paper
- Liu, S., Geng, G., Xiao, Q., Zheng, Y., Liu, X., Cheng, J., & Zhang, Q. (2022). Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000. Environmental Science & Technology. https://doi.org/10.1021/acs.est.2c06510
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.
