Most economists measure labor productivity based on activities conducted at places of work and do not consider leisure time in their calculations. In contrast, psychologists and sociologists argue that leisure has a positive role in the production process: leisure can improve individuals' labor productivity by affecting their self-development. Using empirical data from 21 OECD countries, this study finds that leisure time has a dual effect on labor productivity in terms of per capita per hour GDP. Moreover, leisure time is nonlinearly associated with labor productivity (inverted U-shaped). When leisure time reaches the optimal level (5,813 hours), leisure has a compensatory effect on work and can positively influence labor productivity, but when leisure time exceeds the optimal value, leisure has a substitution effect on work and can negatively influence labor productivity.

The long-term use of wetlands stresses wetland ecosystems and leads to degradation and C loss. This study explored an optimal remote sensing-multivariate linear regression model (RS-MLRM) for estimating wetland soil organic carbon (SOC) by using a combination of the measured SOC and above ground biomass (AGB) from 273 samples, textural features, spectral information, and a vegetation index calculated from Landsat-8 images using the Ningxia Basin of the Yellow River as the study area. To derive the optimal predictor model for SOC, these variables were regressed against the measured SOC. These were used to predict SOC and evaluate the contribution of wetland restoration and conservation projects to soil carbon sequestration and sinks on the Ningxia Basin of the Yellow River in early (2000 and 2005), intermediate (2010), and recent (2015) years. The results show that from 2000 to 2015, the project-induced contribution to C sequestration was 20.49 TC, with an annual sink of 1.37 TC. This accounted for 54.06% of the total wetland ecosystem C sequestration on the Ningxia Basin of the Yellow River. Moreover, there was a significant success of restoration and conservation projects regarding C sequestration. These restoration and conservation projects have substantially contributed to CO2 mitigation in the arid area.

The knowledge spillover effects and the uneven spatial distribution of the creative class have attracted much attention from academia and politicians. Our study provides a comparative quantitative analysis of the spatial–temporal evolution and determinants of creative class concentration in three Chinese agglomerations: Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Pearl River Delta, based on the panel data of 2011, 2012, and 2016 at the city level. It is found that the concentration of the creative class in the three above‐mentioned urban agglomerations in China has clear place‐specific differences. Results from the 2SLS regressions show that social tolerance is significantly and positively correlated with the creative class, but has no effect on the distribution of human capital in the three urban agglomerations. The level of economic development and also the degree of living convenience appear to be the main factors influencing the relative density of creative class (RDCC), while industry structure, university and Hukou all have positive effects on the RDCC in the three urban agglomerations. Moreover, the relative importance of the determinants varies according to the creative occupations. For major creative occupations, they are more inclined to concentrate in cities with high social tolerance, optimal industrial structure, high Hukou availability and qualified universities. For finance and health care occupations, cities with a comfortable climate are more attractive to them; while for management groups, cities with optimal industrial structure, high Hukou availability and adequate educational services are more attractive to them.