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COVID-19 疫情期间的封锁措施表明中国 174 个城市的空气污染物排放短期得到了控制。

COVID-19-Induced Lockdowns Indicate the Short-Term Control Effect of Air Pollutant Emission in 174 Cities in China.

机构信息

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.

University of Chinese Academy of Sciences, Beijing 100190, China.

出版信息

Environ Sci Technol. 2021 Apr 6;55(7):4094-4102. doi: 10.1021/acs.est.0c07170. Epub 2021 Mar 26.

Abstract

The contradiction between the regional imbalance and an one-size-fits-all policy is one of the biggest challenges in current air pollution control in China. With the recent implementation of first-level public health emergency response (FLPHER) in response to the COVID-19 pandemic in China (a total of 77 041 confirmed cases by February 22, 2020), human activities were extremely decreased nationwide and almost all economic activities were suspended. Here, we show that this scenario represents an unprecedented "base period" to probe the short-term emission control effect of air pollution at a city level. We quantify the FLPHER-induced changes of NO, SO, PM, and PM levels in 174 cities in China. A machine learning prediction model for air pollution is established by coupling a generalized additive model, random effects meta-analysis, and weather research and forecasting model with chemistry analysis. The short-term control effect under the current energy structure in each city is estimated by comparing the predicted and observed results during the FLPHER period. We found that the short-term emission control effect ranges within 53.0%-98.3% for all cities, and southern cities show a significantly stronger effect than northern cities ( < 0.01). Compared with megacities, small-medium cities show a similar control effect on NO and SO but a larger effect on PM and PM.

摘要

中国当前空气污染控制面临的最大挑战之一是区域不平衡与一刀切政策之间的矛盾。随着中国最近针对 COVID-19 疫情实施了一级公共卫生应急响应(共确诊 77041 例,截至 2020 年 2 月 22 日),全国范围内人类活动大幅减少,几乎所有经济活动都暂停。在这里,我们展示了这种情况代表了一个前所未有的“基础期”,可以在城市层面探测空气污染的短期排放控制效果。我们量化了 174 个中国城市中 NO、SO、PM 和 PM 水平因一级公共卫生应急响应而发生的变化。通过将广义加性模型、随机效应荟萃分析和天气研究与预测模型与化学分析相结合,建立了空气污染的机器学习预测模型。通过比较一级公共卫生应急响应期间的预测结果和观测结果,估算了每个城市在当前能源结构下的短期控制效果。我们发现,所有城市的短期排放控制效果范围在 53.0%-98.3%之间,南方城市的效果明显强于北方城市(<0.01)。与特大城市相比,中小城市对 NO 和 SO 的控制效果相似,但对 PM 和 PM 的控制效果更大。

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