Qiu Weihong, He Heng, Xu Tao, Jia Chengyong, Li Wending
Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
J Clean Prod. 2021 Jul 25;308:127327. doi: 10.1016/j.jclepro.2021.127327. Epub 2021 May 1.
Air quality changes during the coronavirus disease 2019 (COVID-19) pandemic in China has attracted increasing attention. However, more details in the changes, future air quality trends, and related death benefits on a national scale are still unclear. In this study, a total of 352 Chinese cities were included. We collected air pollutants (including fine particulate matter [PM], inhalable particulate matter [PM], nitrogen dioxide [NO], and ozone [O]) data for each city from January 2015 to July 2020. Convolutional neural network-quantile regression (CNN-QR) forecasting model was used to predict pollutants concentrations from February 2020 to January 2021 and the changes in air pollutants were compared. The relationships between the socioeconomic factors and the changes and the avoided mortality due to the changes were further estimated. We found sharp declines in all air pollutants from February 2020 to January 2021. Specifically, PM, PM, NO, and O would drop by 3.86 μg/m (10.81%), 4.84 μg/m (7.65%), 0.55 μg/m (2.18%), and 3.14 μg/m (3.36%), respectively. The air quality changes were significantly related to many of the socioeconomic factors, including the size of built-up area, gross regional product, population density, gross regional product per capita, and secondary industry share. And the improved air quality would avoid a total of 7237 p.m.-related deaths (95% confidence intervals [CI]: 4935, 9209), 9484 p.m.-related deaths (95%CI: 5362, 13604), 4249 NO-related deaths (95%CI: 3305, 5193), and 6424 O-related deaths (95%CI: 3480, 9367), respectively. Our study shows that the interventions to control COVID-19 would improve air quality, which had significant relationships with some socioeconomic factors. Additionally, improved air quality would reduce the number of non-accidental deaths.
2019年冠状病毒病（COVID-19）大流行期间中国的空气质量变化受到了越来越多的关注。然而，这些变化的更多细节、未来空气质量趋势以及全国范围内相关的死亡益处仍不清楚。在本研究中，共纳入了352个中国城市。我们收集了2015年1月至2020年7月每个城市的空气污染物（包括细颗粒物[PM]、可吸入颗粒物[PM]、二氧化氮[NO]和臭氧[O]）数据。使用卷积神经网络-分位数回归（CNN-QR）预测模型预测2020年2月至2021年1月的污染物浓度，并比较空气污染物的变化。进一步估计了社会经济因素与这些变化之间的关系以及因这些变化避免的死亡率。我们发现2020年2月至2021年1月期间所有空气污染物都急剧下降。具体而言，PM、PM、NO和O将分别下降3.86μg/m（10.81%）、4.84μg/m（7.65%）、0.55μg/m（2.18%）和3.14μg/m（3.36%）。空气质量变化与许多社会经济因素显著相关，包括建成区面积、地区生产总值、人口密度、人均地区生产总值和第二产业份额。改善的空气质量将分别避免总计7237例与PM相关的死亡（95%置信区间[CI]：4935，9209）、9484例与PM相关的死亡（95%CI：5362，13604）、4249例与NO相关的死亡（95%CI：3305，5193）和6424例与O相关的死亡（95%CI：3480，9367）。我们的研究表明，控制COVID-19的干预措施将改善空气质量，这与一些社会经济因素有显著关系。此外，改善的空气质量将减少非意外死亡人数。
