Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 650

The DOI matches its Crossref record.

Chemical composition of emissions from urban sources of fine organic aerosol

Hildemann, Lynn M., Markowski, Gregory R., Cass, Glen R.·1991·Environmental Science & Technology

Abstract

A dilution source sampling system was used to collect \nprimary fine aerosol emissions from important sources of \nurban organic aerosol, including a boiler burning No. 2 fuel \noil, a home fireplace, a fleet of catalyst-equipped and \nnoncatalyst automobiles, heavy-duty diesel trucks, natural \ngas home appliances, and meat cooking operations. Alternative \ndilution sampling techniques were used to collect \nemissions from cigarette smoking and a roofing tar pot, \nand grab sample techniques were employed to characterize \npaved road dust, brake lining wear, tire wear, and vegetative \ndetritus. Organic aerosol constituted the majority \nof the fine aerosol mass emitted from many of the sources \ntested. Fine primary organic aerosol emissions within the \nheavily urbanized western portion of the Los Angeles Basin \nwere determined to total 29.8 metric tons/day. Over 40% \nof these organic aerosol emissions are from anthropogenic \npollution sources that are expected to emit contemporary \n(nonfossil) aerosol carbon, in good agreement with the \navailable ambient monitoring data.

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 · 10.1021/es00016a021

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.

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

Cited by

See all 650

Metadata

Authors
Hildemann, L. M., Markowski, G. R., & Cass, G. R.
Venue
Environmental Science & Technology
Published
1991-04
Volume
25
Issue
4
Pages
744-759
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2035527406
Cited by
650
References
0
FWCI
4.72
Type
journal article
Language
en
Open access
closed

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: Chemical composition of emissions from urban sources of fine organic aerosol. https://app.cochat.ai/papers/10.1021/es00016a021
The paper
Hildemann, L. M., Markowski, G. R., & Cass, G. R. (1991). Chemical composition of emissions from urban sources of fine organic aerosol. Environmental Science & Technology. https://doi.org/10.1021/es00016a021

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.