RÉSUMÉ
In 2019, South Korea launched the Geostationary Environment Monitoring Spectrometer (GEMS) to observe trace gases with an hourly temporal resolution. Compared to previous payloads on polar-orbiting satellites, the GEMS payload has significant advantages in detecting the diurnal variation characteristics of NO2. However, there is still a lack of ground-based validations regarding the overall accuracy of GEMS in the Chinese region. In this study, we conducted a systematic ground validation of GEMS NO2 data in China for the first time. We validated the accuracy of GEMS NO2 data in four typical pollution regions in China, namely the Beijing-Tianjin-Hebei region (JJJ), the Yangtze River Delta region (YRD), the Pearl River Delta region (PRD), and the Sichuan Basin region (SCB), based on MAX-DOAS and CNEMC data. The averaged correlations using the two datasets for validation were 0.81 and 0.57, respectively, indicating a high level of accuracy for the data in China. Using the GEMS seasonal averaged NO2 data, we studied the distribution of NO2 levels in the four regions. We found that the highest NO2 in all four regions occurred during winter with concentrations of 1.84 × 1016 molecules cm-2, 1.59 × 1016 molecules cm-2, 1.58 × 1016 molecules cm-2 and 9.47 × 1015 molecules cm-2, respectively. The distribution of NO2 was closely related to the terrain. Additionally, we observed a significant underestimation issue with TROPOMI, exceeding 30 % in many regions. Based on MAX-DOAS, we investigated the vertical distribution of NO2 in the four regions and found that NO2 was mainly concentrated below 0.5 km. with the HNU station having the lowest concentration, averaging only 2.12 ppb, which was approximately 41 % of the highest concentration recorded at the CQ station. Furthermore, we conducted a study on regional and cross-regional transport using a combination of MAX-DOAS and GEMS data. We found that the transport flux of NO2 could increase by over 500 % within 1 h, making a significant contribution to local NO2 concentrations. The joint observations of GEMS and MAX-DOAS will provide reliable data support for NO2 research and control in China, making a substantial contribution to environmental protection and sustainable development.
RÉSUMÉ
Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.
