Abstract
Nighttime light pollution has become an increasingly serious issue in rapidly urbanizing megacities. It not only disrupts circadian rhythms and affects mental health, but also leads to energy waste and undermines the stability of urban and surrounding ecosystems, posing a significant threat to sustainable development. This study evaluated nighttime light pollution in the residential gathering areas of two typical megacities in China (Beijing and Shanghai) using 40-m SDGSAT-1 glimmer imagery (reflecting actual supply) and population grids (reflecting human demand) refined by the high-performance Random Forest model (with R2 values of 0.93 for Beijing and 0.81 for Shanghai). By integrating urban functional zoning data to supplement the demand for nighttime lighting, a Nighttime Light Supply-Demand Mismatch Index (NLSDMI) was developed to quantify the imbalance of nighttime light between supply side and demand side. The results showed that Shanghai's nighttime light pollution area covered 78.25 km2 (15.10 %), a higher proportion than Beijing's 115.61 km2 (11.29 %) of the study area. Shanghai also exhibited higher peak NLSDMI values. In both cities, residential zones were among the primary contributors to nighttime light pollution. Additionally, in Beijing, the largest share was distributed in parks and green spaces, while in Shanghai, the second major distribution was found in industrial zones. The spatial patterns of nighttime light pollution reflected the distinct characteristics of the two megacities: Beijing focuses on cultural and administrative functions, while Shanghai tends to play its role as an economic hub. Accordingly, feasible countermeasures, including targeted lighting strategy formulation, urban land-use planning refinement and energy-saving lighting technology innovation, were proposed to mitigate light pollution and promote urban sustainability. This study demonstrated the promising potential of SDGSAT-1 glimmer imagery in advancing light pollution assessment and urban management. It also provides practical pathways toward the achievement of multiple Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being), SDG 7 (Affordable and Clean Energy), and SDG 11 (Sustainable Cities and Communities). Future research should focus on enhancing data accuracy, improving validation methods, and exploring the applicability of findings to cities with diverse types and scales, thus providing broader theoretical support and practical guidance for global nighttime light pollution management.