This study investigates the effect of Chinese environmental regulations on the quality of export products. As the main way for the government to protect the environment, environmental regulations have greatly influenced the production behavior of enterprises. Based on the data of China’s pollutant discharge fee implementation and industrial enterprise-pollution panel data, we find that the government’s environmental regulations have significantly improved the quality of export products, and this conclusion is still valid after a series of robustness tests. Further analysis shows that the increase in the quality of export products originating from the regulated areas could be attributed to promoting enterprise innovation and reducing resource misallocation. The results in this study provide evidence that the Chinese government could coordinate economic and environmental protection in the new era.
We have evaluated the performance of three satellite-based latent heat flux (LE) algorithms over forest ecosystems using observed data from 40 flux towers distributed across the world on all continents. These are the revised remote sensing-based Penman-Monteith LE (RRS-PM) algorithm, the modified satellite-based Priestley-Taylor LE (MS-PT) algorithm, and the semi-empirical Penman LE (UMD-SEMI) algorithm. Sensitivity analysis illustrates that both energy and vegetation terms has the highest sensitivity compared with other input variables. The validation results show that three algorithms demonstrate substantial differences in algorithm performance for estimating daily LE variations among five forest ecosystem biomes. Based on the average Nash-Sutcliffe efficiency and root-mean-squared error (RMSE), the MS-PT algorithm has high performance over both deciduous broadleaf forest (DBF) (0.81, 25.4 W/m2) and mixed forest (MF) (0.62, 25.3 W/m2) sites, the RRS-PM algorithm has high performance over evergreen broadleaf forest (EBF) (0.4, 28.1 W/m2) sites, and the UMD-SEMI algorithm has high performance over both deciduous needleleaf forest (DNF) (0.78, 17.1 W/m2) and evergreen needleleaf forest (ENF) (0.51, 28.1 W/m2) sites. Perhaps the lower uncertainties in the required forcing data for the MS-PT algorithm, the complicated algorithm structure for the RRS-PM algorithm, and the calibrated coefficients of the UMD-SEMI algorithm based on ground-measured data may explain these differences. 相似文献