摘要
Coal-fired power plants represent a major anthropogenic source of nanoscale particulate matter, yet conventional mass-based regulations overlook the distinct and potent health risks posed by specific components. Here we combine single-particle elemental profiles (169 plants across China) with cellular toxicity (human lung cells). Using interpretable machine learning, we reveal iron-rich nanoparticles as key toxic driver, explaining 27.4% of the observed oxidative stress and 16.9% of cytotoxicity. We then develop a high-resolution national inventory of iron-rich nanoparticles, estimating total emissions of 236 tons in 2020, with Eastern China as a hotspot contributing 38.2%. Tailored regional strategies could achieve a 77.5% reduction in national emission, with electrostatic precipitator upgrades identified as the most cost-effective measure. Our findings provide an actionable framework to advance air pollution policy beyond total emissions control toward component-specific reduction of the most toxic nanoparticles, ultimately mitigating their associated public health impacts. (Figure presented.)
| 源语言 | 英语 |
|---|---|
| 文章编号 | 561 |
| 期刊 | Communications Earth and Environment |
| 卷 | 7 |
| 期 | 1 |
| DOI | |
| 出版状态 | 已出版 - 12月 2026 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
学术指纹
探究 'Targeting key toxic nanoscale particulate matter for precision control of coal power emissions' 的科研主题。它们共同构成独一无二的学术指纹。引用此
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