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https://www.selleckchem.com/products/bb-94.html With huge natural gas(NG) reserves and current low (1%) share of non-hydro renewables in Sub-Saharan Africa (SSA), can natural gas offer SSA a low-carbon energy transition? Employing data from 1980 to 2017, this paper investigates the impact of NG consumption on SSA's CO2 emissions using data-driven nonparametric additive regression(NPAR) which can reveal both linear and nonlinear effects. Augmenting NPAR with translog production function(TPF) estimates of interfuel substitution elasticities and bias technological progress over sample period(advantage of TPF), we further provide evidence of the indirect effect of NG consumption on SSA's CO2 emissions through mechanism analysis. From the empirical results, the linear effect shows NG positively impact CO2 emissions while the nonlinear effect indicates a downward decreasing trend (meaning expansion in NG consumption will gradually lower CO2 emissions). Nonlinearly, urbanization and energy efficiency also show positive "inverted U-Shaped" and "downward slopping" n.Soil organic carbon (SOC) significantly influences soil fertility, soil water holding capacity, and plant productivity. In this study, we applied two boosted regression tree (BRT) models to map SOC stocks across China in the 1980s and the 2010s. The models incorporated nine environmental variables (climate, topography, and biology) and 8897 (in the 1980s) and 4534 (in the 2010s) topsoil (0-20 cm) samples. During the two study periods, 20% of the soil samples were randomly selected for model testing, and the remaining samples were used as a training set to construct the models. The verification results showed that incorporating climate environment variables significantly improved the model prediction in both study periods. Mean annual temperature, mean annual precipitation, elevation, and the normalized difference vegetation index were the dominant environmental factors affecting the spatial distribution of SOC st

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