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Cited by 192

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Exposure to ambient black carbon derived from a unique inventory and high-resolution model

Open access
Wang, Rong, Tao, Shu, Balkanski, Yves, Ciais, Philippe, Boucher, Olivier, Liu, Junfeng, Piao, Shilong, Shen, Huizhong, Vuolo, Maria Raffaella, Valari, Myrto, Chen, Han, Chen, Yuanchen, Cozic, Anne, Huang, Ye, Li, Bengang, Li, Wei, Shen, Guofeng, Wang, Bin, Zhang, Yanyan·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: In this study, we have developed a unique global black carbon (BC) emission inventory using a 10-km grid based on the latest source and emission factor information. The inventory is used to model BC concentrations using a global atmospheric aerosol climate model, with a high-resolution grid for Asia, to better resolve the exposure of populations to elevated BC concentration. The model with even higher resolution (10 km) is used for the North China Plain. Finally, the population exposure concentrations are evaluated.

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Crossref · 10.1073/pnas.1318763111

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Metadata

Authors
Wang, R., Tao, S., Balkanski, Y., Ciais, P., Boucher, O., Liu, J., Piao, S., Shen, H., Vuolo, M. R., Valari, M., Chen, H., Chen, Y., Cozic, A., Huang, Y., Li, B., Li, W., Shen, G., Wang, B., & Zhang, Y.
Venue
Proceedings of the National Academy of Sciences
Published
2014-01-27
Volume
111
Issue
7
Pages
2459-2463
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2037534385
Cited by
192
References
3
FWCI
12.36
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Exposure to ambient black carbon derived from a unique inventory and high-resolution model. https://app.cochat.ai/papers/10.1073/pnas.1318763111
The paper
Wang, R., Tao, S., Balkanski, Y., Ciais, P., Boucher, O., Liu, J., Piao, S., Shen, H., Vuolo, M. R., Valari, M., Chen, H., Chen, Y., Cozic, A., Huang, Y., Li, B., Li, W., Shen, G., Wang, B., & Zhang, Y. (2014). Exposure to ambient black carbon derived from a unique inventory and high-resolution model. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1318763111

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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.