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首页> 外文期刊>Environmental & Resource Economics >The Impact of the Wuhan Covid-19 Lockdown on Air Pollution and Health: A Machine Learning and Augmented Synthetic Control Approach
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The Impact of the Wuhan Covid-19 Lockdown on Air Pollution and Health: A Machine Learning and Augmented Synthetic Control Approach

机译：武汉Covid-19锁定对空气污染与健康的影响：机器学习与增强合成控制方法

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We quantify the impact of the Wuhan Covid-19 lockdown on concentrations of four air pollutants using a two-step approach. First, we use machine learning to remove the confounding effects of weather conditions on pollution concentrations. Second, we use a new augmented synthetic control method (Ben-Michael et al. in The augmented synthetic control method. University of California Berkeley, Mimeo, 2019. https://arxiv.org/pdf/1811.04170.pdf) to estimate the impact of the lockdown on weather normalised pollution relative to a control group of cities that were not in lockdown. We find NO2 concentrations fell by as much as 24 mu g/m(3) during the lockdown (a reduction of 63% from the pre-lockdown level), while PM10 concentrations fell by a similar amount but for a shorter period. The lockdown had no discernible impact on concentrations of SO2 or CO. We calculate that the reduction of NO2 concentrations could have prevented as many as 496 deaths in Wuhan city, 3368 deaths in Hubei province and 10,822 deaths in China as a whole.
机译：我们使用两步方法量化武汉Covid-19锁定对四种空气污染物浓度的影响。首先，我们使用机器学习来消除天气条件对污染浓度的混杂效果。其次，我们使用新的增强合成控制方法（Ben-Michael等人。在增强的合成控制方法中。加州大学伯克利大学，Mimeo，2019. Https://arxiv.org/pdf/1811.04170.pdf）估计锁定对天气归一化污染相对于不在锁定的控制组的影响。在锁定期间，我们发现No2浓度低至24 mu g / m（3）（从预锁定水平的减少63％），而PM10浓度则按相似的数量落下，但较短。锁定对SO2或CO的浓度没有可辨别的影响。我们计算武汉市的496人死亡的减少，湖北省3368人死亡和整体死亡人数为10,822人死亡。

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