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Assessment of black carbon exposure level and health economic loss in China

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Abstract

Based on the geographic information system (GIS) software and the application of the black carbon (BC) and fine particulate matter (\({\mathrm{PM}}_{2.5}\)) ratio method, this paper analyzed and calculated the national BC distribution from 2015 to 2017 and evaluated the national human exposure to BC. The results showed that from 2015 to 2017, 2/3 of the national land area and nearly half of the population were exposed to 1–3 \({\mathrm{\mu g}/\mathrm{m}}^{3}\), and the area and population exposed to a concentration less than 2 \({\mathrm{\mu g}/\mathrm{m}}^{3}\) increased yearly, while the area and population exposed to a concentration higher than 9 \({\mathrm{\mu g}/\mathrm{m}}^{3}\) decreased yearly. The estimated economic loss showed that 77.3% of the targeted districts or counties claimed a loss per square kilometer of 50 million Chinese Yuan (CNY) or less from the perspective of annual changes, and districts and counties in Beijing-Tianjin-Hebei and Hunan with annual losses between 50 and 500 million CNY showed an increasing trend. The BC ratio (the proportion of BC economic loss to GDP) of Beijing-Tianjin-Hebei and Hunan also showed an increasing trend yearly.

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Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Acknowledgements

The authors are grateful to the Chinese Ministry of Environmental Protection for sharing PM2.5 data on the website and LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2016YFA0602004), and the National Natural Science Foundation of China (41075102).

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Formal analysis, Liang Ke; methodology, Sun Zhaobin and Zhang Chao; writing—original draft, Hou Qing; writing—review and editing, An Xingqin.

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Correspondence to Xingqin An.

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Hou, Q., An, X., Sun, Z. et al. Assessment of black carbon exposure level and health economic loss in China. Environ Sci Pollut Res 29, 52123–52132 (2022). https://doi.org/10.1007/s11356-021-17776-w

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