The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Pyrolysis gas chromatography-mass spectrometry in environmental analysis: Focus on organic matter and microplastics
Open accessAbstract
Abstract Pyrolysis gas chromatography-mass spectrometry (Py-GC-MS) has great potential within environmental analysis. This technique is mainly used for the chemical identification of macromolecules that cannot be characterized by either liquid or gas chromatography due to their big size. Through pyrolysis (controlled thermal degradation), these macromolecules are broken down into simpler molecules that can be separated by gas chromatography and detected by mass spectrometry. This technique has been traditionally used in environmental samples for the characterization of organic matter and humic substances, contaminants, lignins, etc. It attains the identification of the different types of chemical units that integrate the macromolecules. In addition, recently, this technique has experienced an important boom in the chemical characterization of microplastics present in environmental samples. This has triggered its use in this type of matrix. We describe the fundamentals and modalities of Py-GC-MS and outline some of the recent applications for the environmental analysis with special emphasis on humic substances and/or other types of organic matter components as well as microplastics, but reporting also other interesting application of environmental relevance.
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
Compendium of chemical terminology
Gold, V. (1987) · Cited by 2,525
Li, J., Liu, H., & Paul Chen, J. (2018) · Water Research · doi:10.1016/j.watres.2017.12.056 · Cited by 2,314
Microplastics in the environment: Challenges in analytical chemistry - A review
Silva, A. B., Bastos, A. S., Justino, C. I. L., da Costa, J. P., Duarte, A. C., & Rocha-Santos, T. A. P. (2018) · Analytica Chimica Acta · doi:10.1016/j.aca.2018.02.043 · Cited by 843
Fischer, M., & Scholz-Böttcher, B. M. (2017) · Environmental Science & Technology · doi:10.1021/acs.est.6b06362 · Cited by 647
Hendrickson, E., Minor, E. C., & Schreiner, K. (2018) · Environmental Science & Technology · doi:10.1021/acs.est.7b05829 · Cited by 419
Picó, Y., & Barceló, D. (2019) · ACS Omega · doi:10.1021/acsomega.9b00222 · Cited by 396
Self-citationA review of methods for measuring microplastics in aquatic environments
Mai, L., Bao, L.-J., Shi, L., Wong, C. S., & Zeng, E. Y. (2018) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-1692-0 · Cited by 385
Lv, L., He, L., Jiang, S., Chen, J., Zhou, C., Qu, J., Lu, Y., Hong, P., Sun, S., & Li, C. (2020) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.138449 · Cited by 374
Separation, characterization and identification of microplastics and nanoplastics in the environment
Fu, W., Min, J., Jiang, W., Li, Y., & Zhang, W. (2020) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.137561 · Cited by 361
Hermabessiere, L., Himber, C., Boricaud, B., Kazour, M., Amara, R., Cassone, A.-L., Laurentie, M., Paul-Pont, I., Soudant, P., Dehaut, A., et al. (2018) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-018-1279-0 · Cited by 360
Cited by
Chemical Analysis of Microplastics and Nanoplastics: Challenges, Advanced Methods, and Perspectives
Ivleva, N. P. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00178 · Cited by 1,172
Recent advances and future technologies in nano-microplastics detection
Nene, A., Sadeghzade, S., Viaroli, S., Yang, W., Uchenna, U. P., Kandwal, A., Liu, X., Somani, P., & Galluzzi, M. (2025) · Environmental Sciences Europe · doi:10.1186/s12302-024-01044-y · Cited by 173
Metadata
- Authors
- Picó, Y., & Barceló, D.
- Venue
- TrAC Trends in Analytical Chemistry
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 130
- Pages
- 115964
- ISSN
- 0165-9936 (ISSN-L)
- OpenAlex
- W3040236379
- Cited by
- 341
- References
- 58
- FWCI
- 10.29
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Pyrolysis gas chromatography-mass spectrometry in environmental analysis: Focus on organic matter and microplastics. https://app.cochat.ai/papers/10.1016/j.trac.2020.115964
- The paper
- Picó, Y., & Barceló, D. (2020). Pyrolysis gas chromatography-mass spectrometry in environmental analysis: Focus on organic matter and microplastics. TrAC Trends in Analytical Chemistry. https://doi.org/10.1016/j.trac.2020.115964
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.