## 2 Materials and Methods  
### Meteorological and Chemistry Simulation  
The meteorological parameters over China were simulated by the WRF-Chem model version 4.0 [21], which was jointly developed by the National Oceanic and Atmospheric Administration (NOAA) and the Earth System Research Laboratory (ESRL). The simulation domain covers mainland China, which is centered at (35\({}^{\circ}\) N, 103\({}^{\circ}\) E) and expands 165 and 150 grids with a grid spacing of 36 km along the zonal and meridional direction. The meteorological parameters were simulated by the model at 35 levels below 50 hPa. The simulation incorporated various physical parameterization schemes (Table 1), including the Yonsei University (YSU) planetary boundary layer scheme [22], the Noah land surface model [23], the Grell-3D cumulus convection scheme [24], the Morrison double-moment microphysics scheme [25], and the RRTMG shortwave and longwave radiation schemes [26]. To drive the WRF-Chem model, dynamic initial and boundary conditions were obtained from HighResMIP's (high-resolution model intercomparison project) climate projection (MPI-ESMI-2-HR) data of the CMIP6 (phase 6 of the coupled model intercomparison project), which had a grid resolution of 0.93\({}^{\circ}\)\(\times\) 0.93\({}^{\circ}\) and were interpolated at 6 h intervals [27]. Table 1 demonstrates the model input data and parameterization settings in this study. The CBMZ [28] and MOSAIC [29] mechanisms were employed for simulating gaseous and particulate chemistry. The initial and boundary conditions of atmospheric chemical compositions were derived from climatological chemical data obtained from the model for O\({}_{3}\) and related chemical tracers (MOZART) [30; 31]. The anthropogenic emissions were derived from the multi-resolution emission inventory for China (MEIC) dataset version 1.3 [32; 33] over mainland China and the model inter-comparison study for Asia (MICS-ASIA III) dataset [34] outside of China. The anthropogenic emissions in 2060 over China were derived from the carbon-neutral scenarios of the DPEC dataset [18]. Biogenic emissions were obtained from version 3 of the model of emission of gases and aerosols from nature (MEGAN) [35]. The simulated meteorological parameters (2 m temperature and 2 m relative humidity) and air pollutant concentrations (PM\({}_{2.5}\) and O\({}_{3}\)) in January, April, July, and October of 2016 were compared with the observations from 439 meteorological stations and 1425 state-controlled ambient air quality monitoring stations across China, respectively (see Tables S1 and S2). The meteorological simulation exhibited good model performance as evidenced by small average deviations between simulation results and observation data, such as mean fractional bias (MFB) ranging from \(-30\%\) to \(30\%\), mean fractional error (MFE) below \(50\%\), as well as negligible normalized mean bias (NMB) and normalized mean error (NME). Regarding the air pollutant concentrations, both O\({}_{3}\) and PM\({}_{2.5}\) concentrations exhibited MFBs within the range of \(-60\%\) to \(60\%\), while MFEs remained below \(75\%\). Notably, O\({}_{3}\) simulation demonstrated superior performance in July with MFBs ranging from \(-30\%\) to \(30\%\) along with MFEs below \(50\%\). All NMB values were positive for both O\({}_{3}\) and PM\({}_{2.5}\) concentrations over China, indicating a slight overestimation by the model. Consequently, the model successfully replicated variations in meteorological parameters as well as air quality [36]. derived from the moderate resolution imaging spectroradiometer (MODIS) [37] is arguably the most widely used worldwide GPP product [38], which is based on a light energy utilization model--the MODIS photosynthesis (PSN) algorithm developed by [PERSON] et al. [37]. Model parameter values are provided in the biome specified parameter look-up Table (BPLUT), which is designed to establish a physiological framework for regulating simulated carbon sequestration [39].