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| Titel |
Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory |
| VerfasserIn |
H. Y. Zhao, Q. Zhang, D. B. Guan, S. J. Davis, Z. Liu, H. Huo, J. T. Lin, W. D. Liu, K. B. He |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 10 ; Nr. 15, no. 10 (2015-05-19), S.5443-5456 |
| Datensatznummer |
250119735
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| Publikation (Nr.) |
 copernicus.org/acp-15-5443-2015.pdf |
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| Zusammenfassung |
| Substantial anthropogenic emissions from China have
resulted in serious air pollution, and this has generated considerable
academic and public concern. The physical transport of air pollutants in the
atmosphere has been extensively investigated; however, understanding the
mechanisms how the pollutant was transferred through economic and trade
activities remains a challenge. For the first time, we quantified and tracked
China's air pollutant emission flows embodied in interprovincial trade, using
a multiregional input–output model framework. Trade relative emissions
for four key air pollutants (primary fine particle matter, sulfur
dioxide, nitrogen oxides and non-methane volatile
organic compounds) were assessed for 2007 in each Chinese province. We
found that emissions were significantly redistributed among provinces owing
to interprovincial trade. Large amounts of emissions were embodied in the
imports of eastern regions from northern and central regions, and these were
determined by differences in regional economic status and environmental
policy. It is suggested that measures should be introduced to reduce air
pollution by integrating cross-regional consumers and producers within
national agreements to encourage efficiency improvement in the supply chain
and optimize consumption structure internationally. The consumption-based air
pollutant emission inventory developed in this work can be further used to
attribute pollution to various economic activities and final demand types
with the aid of air quality models. |
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