Shanghai has gained much attention in terms of air quality research owing to its importance to economic capital and its huge population. This study utilizes ground-based remote sensing instrument observations, namely by Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), and in situ measurements from the national air quality monitoring platform for various atmospheric trace gases including Nitrogen dioxide (NO2), Sulfur dioxide (SO2), Ozone (O3), Formaldehyde (HCHO), and Particulate Matter (PM; PM10: diameter ≤ 10 µm, and PM2.5: diameter ≤ 2.5 µm) over Shanghai from June 2020 to May 2021. The results depict definite diurnal patterns and strong seasonality in HCHO, NO2, and SO2 concentrations with maximum concentrations during winter for NO2 and SO2 and in summer for HCHO. The impact of meteorology and biogenic emissions on pollutant concentrations was also studied. HCHO emissions are positively correlated with temperature, relative humidity, and the enhanced vegetation index (EVI), while both NO2 and SO2 depicted a negative correlation to all these parameters. The results from diurnal to seasonal cycles consistently suggest the mainly anthropogenic origin of NO2 and SO2, while the secondary formation from the photo-oxidation of volatile organic compounds (VOCs) and substantial contribution of biogenic emissions for HCHO. Further, the sensitivity of O3 formation to its precursor species (NOx and VOCs) was also determined by employing HCHO and NO2 as tracers. The sensitivity analysis depicted that O3 formation in Shanghai is predominantly VOC-limited except for summer, where a significant percentage of O3 formation lies in the transition regime. It is worth mentioning that seasonal variation of O3 is also categorized by maxima in summer. The interdependence of criteria pollutants (O3, SO2, NO2, and PM) was studied by employing the Pearson’s correlation coefficient, and the results suggested complex interdependence among the pollutant species in different seasons. Lastly, potential source contribution function (PSCF) analysis was performed to have an understanding of the contribution of different source areas towards atmospheric pollution. PSCF analysis indicated a strong contribution of local sources on Shanghai’s air quality compared to regional sources. This study will help policymakers and stakeholders understand the complex interactions among the atmospheric pollutants and provide a baseline for designing effective control strategies to combat air pollution in Shanghai.
Full Text Finder