The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Fine particle pH and the partitioning of nitric acid during winter in the northeastern United States
Open accessAbstract
Particle pH is a critical but poorly constrained quantity that affects many aerosol processes and properties, including aerosol composition, concentrations, and toxicity. We assess PM1 pH as a function of geographical location and altitude, focusing on the northeastern U.S., based on aircraft measurements from the Wintertime Investigation of Transport, Emissions, and Reactivity campaign (1 February to 15 March 2015). Particle pH and water were predicted with the ISORROPIA-II thermodynamic model and validated by comparing predicted to observed partitioning of inorganic nitrate between the gas and particle phases. Good agreement was found for relative humidity (RH) above 40%; at lower RH observed particle nitrate was higher than predicted, possibly due to organic-inorganic phase separations or nitrate measurement uncertainties associated with low concentrations (nitrate < 1 µg m−3). Including refractory ions in the pH calculations did not improve model predictions, suggesting they were externally mixed with PM1 sulfate, nitrate, and ammonium. Sample line volatilization artifacts were found to be minimal. Overall, particle pH for altitudes up to 5000 m ranged between −0.51 and 1.9 (10th and 90th percentiles) with a study mean of 0.77 ± 0.96, similar to those reported for the southeastern U.S. and eastern Mediterranean. This expansive aircraft data set is used to investigate causes in variability in pH and pH-dependent aerosol components, such as PM1 nitrate, over a wide range of temperatures (−21 to 19°C), RH (20 to 95%), inorganic gas, and particle concentrations and also provides further evidence that particles with low pH are ubiquitous.
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
The contribution of outdoor air pollution sources to premature mortality on a global scale
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., & Pozzer, A. (2015) · Nature · doi:10.1038/nature15371 · Cited by 5,977
Evolution of Organic Aerosols in the Atmosphere
Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang, Q., Kroll, J. H., DeCarlo, P. F., Allan, J. D., Coe, H., Ng, N. L., et al. (2009) · Science · doi:10.1126/science.1180353 · Cited by 4,167
Self-citation
Cited by
The acidity of atmospheric particles and clouds
Pye, H. O. T., Nenes, A., Alexander, B., Ault, A. P., Barth, M. C., Clegg, S. L., Collett Jr., J. L., Fahey, K. M., Hennigan, C. J., Herrmann, H., et al. (2020) · Atmospheric Chemistry and Physics · doi:10.5194/acp-20-4809-2020 · Cited by 785
Self-citationFang, T., Guo, H., Zeng, L., Verma, V., Nenes, A., & Weber, R. J. (2017) · Environmental Science & Technology · doi:10.1021/acs.est.6b06151 · Cited by 584
Self-citationFine particle pH during severe haze episodes in northern China
Liu, M., Song, Y., Zhou, T., Xu, Z., Yan, C., Zheng, M., Wu, Z., Hu, M., Wu, Y., & Zhu, T. (2017) · Geophysical Research Letters · doi:10.1002/2017gl073210 · Cited by 308
On the implications of aerosol liquid water and phase separation for organic aerosol mass
Pye, H. O. T., Murphy, B. N., Xu, L., Ng, N. L., Carlton, A. G., Guo, H., Weber, R., Vasilakos, P., Appel, K. W., Budisulistiorini, S. H., et al. (2017) · Atmospheric Chemistry and Physics · doi:10.5194/acp-17-343-2017 · Cited by 293
Self-citationGuo, H., Weber, R. J., & Nenes, A. (2017) · Scientific Reports · doi:10.1038/s41598-017-11704-0 · Cited by 268
Self-citation
Metadata
- Authors
- Guo, H., Sullivan, A. P., Campuzano‐Jost, P., Schroder, J. C., Lopez‐Hilfiker, F. D., Dibb, J. E., Jimenez, J. L., Thornton, J. A., Brown, S. S., Nenes, A., & Weber, R. J.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2016-09-15
- Volume
- 121
- Issue
- 17
- ISSN
- 0148-0227 (ISSN-L)
- 2169-897X
- 2169-8996
- OpenAlex
- W2511369165
- Cited by
- 310
- References
- 2
- FWCI
- 16.50
- 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: Fine particle pH and the partitioning of nitric acid during winter in the northeastern United States. https://app.cochat.ai/papers/10.1002/2016jd025311
- The paper
- Guo, H., Sullivan, A. P., Campuzano‐Jost, P., Schroder, J. C., Lopez‐Hilfiker, F. D., Dibb, J. E., Jimenez, J. L., Thornton, J. A., Brown, S. S., Nenes, A., & Weber, R. J. (2016). Fine particle pH and the partitioning of nitric acid during winter in the northeastern United States. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1002/2016jd025311
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.