Forestry College of Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China.
Mountain Tai Forest Ecosystem Research Station of State Forestry Administration/Key Laboratory of State Forestry Administration for Silviculture of the Lower Yellow River, Tai'an, 271018, Shandong, China.
Sci Rep. 2022 Jul 15;12(1):12099. doi: 10.1038/s41598-022-16105-6.
A number of strict lockdown measures were implemented in the areas most affected by COVID-19 in China, including Ji'nan city, from 24 January to 7 February 2020. Due to these forced restrictions, the pollution levels in cities across the country drastically decreased within just a few days. Since traffic pollution and industrial emissions are important factors affecting regional air quality, congestion has a significant impact on the environment. Therefore, using the aid of air quality data for six pollutants (PM, PM, SO, NO, CO and O) from 11 monitoring stations (located in urban, suburban and urban-industrial regions) across Ji'nan, we employed the air quality index (AQI) to investigate the spatial pattern of air quality in the pre-COVID-19 (pre-COVID) and COVID-19-related lockdown (COVID lockdown) periods. The results showed that air quality significantly improved during the COVID lockdown period. Among the selected pollutants, compared to the corresponding pre-COVID levels, the greatest reduction was observed for the concentration of NO (54.02%), while the smallest reduction was observed for the concentration of SO (27.92%). The PM (38.73%), PM (44.92%) and CO (30.60%) levels also decreased during the COVID lockdown period; only the O concentration increased (37.42%) during this period. Overall, air quality improved by approximate improvements of 37.33% during the COVID lockdown period. Approximately 35.48%, 37.01% and 43.43% in the AQI were observed in urban, suburban and urban-industrial regions, respectively. Therefore, the AQI exhibited remarkable regional differences in Ji'nan. This study demonstrates the contributions of the transportation sector and local emissions to improving air quality in typical urban areas, and these research results can provide guidance for the further monitoring of air pollution in northern Chinese cities.
中国受 COVID-19 影响最严重的地区，包括济南市，于 2020 年 1 月 24 日至 2 月 7 日实施了多项严格的封锁措施。由于这些强制限制，仅几天时间，全国城市的污染水平就大幅下降。由于交通污染和工业排放是影响区域空气质量的重要因素，拥堵对环境有重大影响。因此，我们利用济南 11 个监测站（位于城市、郊区和城市工业区）的六种污染物（PM 、PM 、SO 、NO 、CO 和 O ）的空气质量数据，采用空气质量指数（AQI）调查了 COVID-19 前（COVID-19 前）和 COVID-19 相关封锁（COVID 封锁）期间空气质量的空间格局。结果表明，COVID 封锁期间空气质量显著改善。在所选择的污染物中，与相应的 COVID-19 前水平相比，NO 的浓度降幅最大（54.02%），而 SO 的浓度降幅最小（27.92%）。COVID 封锁期间，PM （38.73%）、PM （44.92%）和 CO （30.60%）的浓度也有所下降；只有 O 的浓度在此期间增加（37.42%）。总的来说，在 COVID 封锁期间，空气质量改善了约 37.33%。城市、郊区和城市工业区的 AQI 分别提高了约 35.48%、37.01%和 43.43%。因此，济南的 AQI 呈现出显著的区域差异。本研究证明了交通部门和本地排放对改善典型城市地区空气质量的贡献，这些研究结果可为进一步监测中国北方城市的空气污染提供指导。
