Publication date: Jul 12, 2024

PM is a main atmospheric pollutant with various sources and complex chemical compositions, which are influenced by various factors, such as anthropogenic emissions (AE) and meteorological conditions (MC). MC have a significant impacts on variations in atmospheric pollutant; therefore, emission reduction policies and ambient air quality are non-linearly correlated, which hinders the accurate assessment of the effectiveness of control measures. In this study, we conducted online observations of PM and its chemical composition in Hohhot, China, from December 1, 2019, to February 29, 2020, to investigate how the chemical compositions of PM respond to the variations in AE and MC. Moreover, the random forest (RF) model was used to quantify the contributions of AE and MC to PM and its chemical composition during severe hazes and the COVID-19 pandemic lockdown period. During the clean period, MC reduced PM concentrations by 124%, while MC incresed PM concentrations by 49% during severe pollution episode. Inorganic aerosols (SO, NO, and NH) showed the strongest response to MC. MC significantly contributed to PM (36%), SO (32%), NO (29%), NH (28%), OC (22%), and SOC (17%) levels during pollution episodes. From the pre-lockdown to lockdown period, AE (MC) contributed 52% (48%), 81% (19%), 48% (52%), 68% (32%), 59% (41%), and 288% (-188%) to the PM, SO, NO, NH, OC, and SOC reductions, respectively. The variations in MC (especially the increase in relative humidity) rapidly generated meteorologically sensitive species (SO, NO, and NH), which led to severe winter pollution. This study provides a reference for assessing the net benefits of emission reduction measures for PM and its chemical compositions.

Semantics

Original Article