Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 586

The DOI matches its Crossref record.

Emission of Polycyclic Aromatic Hydrocarbons in China

Xu, Shanshan, Liu, Wenxin, Tao, Shu·2006·Environmental Science & Technology

Abstract

Emission of 16 polycyclic aromatic hydrocarbons (PAHs) listed as U.S. Environmental Protection Agency (U.S. EPA) priority pollutants from major sources in China were compiled. Geographical distribution and temporal change of the PAH emission, as well as emission profiles, are discussed. It was estimated that the total PAH emission in China was 25,300 tons in 2003. The emission profile featured a relatively higher portion of high molecular weight (HMW) species with carcinogenic potential due to large contributions of domestic coal and coking industry. Among various sources, biomass burning, domestic coal combustion, and coking industry contributed 60%, 20%, and 16% of the total emission, respectively. Total emission, emission density, emission intensity, and emission per capita showed geographical variations. In general, the southeastern provinces were characterized by higher emission density, while those in western and northern China featured higher emission intensity and population-normalized emission. Although energy consumption in China went up continuously during the past two decades, annual emission of PAHs fluctuated depending on the amount of domestic coal consumption, coke production, and the efficiency of energy utilization.

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/es0517062

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 586

Metadata

Authors
Xu, S., Liu, W., & Tao, S.
Venue
Environmental Science & Technology
Published
2005-12-22
Volume
40
Issue
3
Pages
702-708
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2039220086
Cited by
586
References
0
FWCI
9.66
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: Emission of Polycyclic Aromatic Hydrocarbons in China. https://app.cochat.ai/papers/10.1021/es0517062
The paper
Xu, S., Liu, W., & Tao, S. (2006). Emission of Polycyclic Aromatic Hydrocarbons in China. Environmental Science & Technology. https://doi.org/10.1021/es0517062

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.