厦门湾空气质量对新冠疫情管控的响应

通过对厦门湾城市群在COVID-19封锁前后6周内（2020-01-11~2020-02-21）的空气污染物浓度变化进行分析，以确定影响本区域空气质量的主要人为污染源.在春节假期与封锁叠加期间，SO₂、NO₂、CO、PM₁₀和PM_2.5浓度相比于节前1周的下降幅度分别为6%~22%、53%~70%、34%~48%、47%~64%和53%~60%，而O₃浓度变化没有一致的规律性；与2018~2019年历史同期相比，PM_2.5、PM₁₀、CO和NO₂的下降幅度更大，但SO₂的下降幅度相当；在复工复产后，NO₂的反弹幅度最大（38%~138%），远高于SO₂（2%~42%），显示交通源相对于固定源更易受到疫情管控的影响；春节后风速增大和降水增多也为SO₂、NO₂和PM的下降提供了正向影响.利用反距离插值权重法，得到管控前后厦门湾城市群不同污染物的空间分布变化特征，显示NO₂浓度高值区的变化与交通源高度相关，CO和SO₂空间分布特征保持稳定，复工后PM_2.5和PM₁₀在人口与路网密集区变化不明显，而在工地相对集中区域有明显上升，O₃空间分布的低值区与NO₂的高值区具有较好的空间匹配性，显示NO₂对O₃滴定作用明显，可为进一步O₃污染减排措施的制定提供参考.

Response of Air Quality to COVID-19 Lockdown in Xiamen Bay

Air pollutant concentrations in the Xiamen Bay cities during the period before and after COVID-19 lockdown(from January 11 to February 21, 2020) were studied to determine the influence of human activities on air quality in this region. During the Chinese Spring Festival holiday and the lockdown period, the concentrations of SO₂, NO₂, CO, PM₁₀, and PM_2.5 decreased by 6%-22%, 53%-70%, 34%-48%, 47%-64%, and 53%-60%, respectively. However, the changes in O₃ concentrations were not consistent with the variations of human activities. The reduction rates for PM_2.5, PM₁₀, CO, and NO₂ during the Spring Festival were greater than in previous years(2018 and 2019), but the reduction rates for SO₂ were comparable. The concentrations of NO₂ increased sharply(38%-138%), and much higher those of SO₂(2%-42%), after the resumption of socioeconomic activities, indicating the importance of traffic reductions due to the lockdown measures on NO₂. Higher wind speeds and rainfall after the Spring Festival were also favorable for the decline of SO₂, NO₂, and PM. The spatio-temporal distributions of the six criterial pollutants in the Xiamen Bay city cluster were obtained based on the Inverse Distance Weight method. The variability in regions with high NO₂ concentrations was strongly linked to traffic emissions, while spatial patterns for CO and SO₂ changed little over the six-week study period. The concentrations of PM_2.5 and PM₁₀ increased notably in the region, linked to more construction activity, but changed comparatively little in regions with dense populations and traffic networks. O₃ remained relatively stable but low-value regions corresponded to those regions with high NO₂ concentrations, indicating the significant titration effect of NO₂ on O₃. These results provide valuable information that can inform O₃ pollution reduction measures.