State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China.
School of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China.
Sci Total Environ. 2022 Oct 15;843:156942. doi: 10.1016/j.scitotenv.2022.156942. Epub 2022 Jun 23.
Although COVID-19 lockdown policies have improved air quality in numerous countries, there is a lack of empirical evidence on the extent to which recovery has resulted in air pollution rebound, and the differences and similarities among regions' recovery modes during the period of easing COVID-19 restrictions. Here, we used daily air quality data and the recovery index constructed by a city-pair inflow index for 119 cities in China to quantify the impact of recovery on air pollution from March 2 to October 30, 2020. Findings show that recovery has significantly increased air pollution. When the recovery level increased by 10 %, the concentration of PM, SO, and NO respectively deteriorated by 1.10, 0.33, 1.25 μg/m, and the average growth rates of three air pollutants were about 3 %-6 %. Moreover, we used the counterfactual framework and time series clustering with wavelet transform to cluster the rebound trajectory of air pollution for 17 provinces into five recovery modes. Results show that COVID-19 has further intensified regional differentiations in economic development ability and green recovery trend. Three northwestern provinces dependent on their resource endowments belong to energy-intensive recovery mode, which have experienced a sharp rebound of air pollution for two months, thereby making green recovery more challenging to achieve. Three regions with a diversified industrial structure are in industrial-restructuring recovery mode, which has effectively returned to a normal level through adjusting industrial structure and technological innovation. Owing to local policies and the outbreak of COVID-19 in other countries, six provinces in policy-oriented and international trade-oriented recovery modes have not fully recovered to the level without COVID-19 until October 2020. The result highlights the importance of diversifying industrial structure, technological innovation, policy flexibility and industrial upgrading for different recovery modes to achieve long-term green recovery in the future.
尽管 COVID-19 封锁政策改善了许多国家的空气质量，但对于复苏在多大程度上导致了空气污染反弹，以及在放宽 COVID-19 限制期间各地区复苏模式的差异和相似之处，仍缺乏经验证据。在这里，我们使用了每日空气质量数据和由城市对流入指数构建的恢复指数，对 2020 年 3 月 2 日至 10 月 30 日期间中国 119 个城市的空气污染恢复情况进行了量化。研究结果表明，复苏显著加剧了空气污染。当恢复水平提高 10%时，PM、SO 和 NO 的浓度分别恶化了 1.10、0.33 和 1.25μg/m，三种空气污染物的平均增长率约为 3%-6%。此外，我们使用反事实框架和带小波变换的时间序列聚类对 17 个省份的空气污染反弹轨迹进行聚类，将其分为五种恢复模式。结果表明，COVID-19 进一步加剧了经济发展能力和绿色复苏趋势的区域差异。三个依赖资源禀赋的西北省份属于能源密集型复苏模式，经历了两个月的空气污染急剧反弹，因此实现绿色复苏更具挑战性。三个产业结构多元化的地区属于产业结构调整型复苏模式，通过调整产业结构和技术创新，已有效恢复到正常水平。由于地方政策和其他国家的 COVID-19 爆发，政策导向和国际贸易导向的六个省份直到 2020 年 10 月才完全恢复到没有 COVID-19 的水平。研究结果强调了对于不同的复苏模式，多样化产业结构、技术创新、政策灵活性和产业升级的重要性，以实现未来的长期绿色复苏。
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