MACHINE LEARNING BASED BIAS CORRECTION FOR MODIS AEROSOL OPTICAL DEPTH IN BEIJING

The TanSat-2 satellite is designed for global carbon monitoring. It provides high-resolution, dual-band observations of solar-induced chlorophyll fluorescence, a key indicator of plant photosynthesis. Through simulations, we optimized the satellite's data processing and found it can retrieve this fluorescence with great accuracy. These findings suggest that TanSat-2 will enhance global monitoring of carbon cycles and vegetation health, offering valuable insights for climate change research.

During 2006–2015, emissions of SO₂, NO_x, PM_2.5 and PM₁₀ saw an obvious downtrend. However, most emissions still have large reduction potential. On-road mobile sources and solvent use are the two key sources that should receive more effective control measures in GD. Also, controls measures on VOC and NH₃ should be weighted since they still increased in 2006–2015. Since most control measures focused on PRD rather than non-PRD in GD, emissions in non-PRD were increasingly important.

Both AIRS and GOSAT TANSO-FTS TIR have been used to retrieve atmosphere CH₄. The purpose of an intercomparison is to provide useful information to users on the characteristics of these two different products when they investigate the spatial and temporal variation of CH₄. On the other hand, AIRS V6 CH₄ data were already validated by comparing with aircraft data. This intercomparison is also a kind of indirect validation to GOSAT data.