Can forests realize the carbon neutrality dream? Evidence from a global sample.

The enlarge in economic activities and the urban population at the global level has brought about an increase in the demand for energy, food, and natural resources, as well as an exacerbation in global climate change concerns. In this respect, it is important to ensure the balance between global climate change and global economic activities. Therefore, a wide literature has emerged that searches for alternative solutions to improve climate change and carbon dioxide (CO2) emissions. The majority of existing studies emphasize the importance of renewable energy sources in environmental improvement efforts. Few studies highlight the importance of forestation in environmental improvement efforts, highlighting the non-linear effects of forestation. To fill this gap, this study uses panel data from 181 countries between 1990 and 2022 and evaluates the non-linear impact of economic growth, forest extent, energy efficiency, and urban growth on per capita CO2 emissions using a dynamic panel threshold and dynamic panel quantile threshold methods. Furthermore, we extend the model and conduct robustness tests examining the non-linear threshold effects of renewable and non-renewable energy consumption on per capita CO2 emissions. Our findings provide pieces of evidence that forest extents are an alternative solution to renewable energy use and energy efficiency in environmental improvement efforts.

Testing the EKC hypothesis for ecological and carbon intensity of well-being: The role of forest extent.

The G-20 countries represent a considerable percentage of the global economy and are crucial in matters to do with support for environmental sustainability. The uniqueness of this study lies in determining the effects of forests on human well-being and environmental degradation with respect to G20, offering a unique perspective regarding the efforts to battle climate change. The study analyzed the impact of income, forest extent and education on ecological and carbon intensity of well-being following the Environmental Kuznets Curve (EKC) hypothesis. Based on annual data from 1990 to 2022 and employing the Method of Moments Quantile Regression, the results validate the presence of an inverted U-shaped relationship between GDP and environmental well-being which refers to the existence of EKC. Our results connect improved ecological and carbon intensity of well-being with expanding forest extent and improving education levels. Forest management combined with educational management work as an effective mechanism reducing environmental degradation while also positively contributing to human well-being. In addition, through these informed and rational decisions, policy makers can promote the environmental stability of forests.

Examining the nonlinear impact of human capital on environmental degradation in N-11 countries: an application of the PSTR approach.

The emergence of globalization and human capital has played a crucial role in the economic integration of countries, leading to the growth of the economies and a reduction in carbon dioxide (CO2) emissions. This study highlights the importance of investing in human capital development to control ecological degradation and promote sustainable economic growth. This paper employs the PSTR method to investigate the threshold impact of GDP, globalization, information communication technology, and energy consumption on CO2 emissions. The study examines two regimes, with a single threshold to analyze the transition of human capital on these variables. The results reveal that human capital developments play a central role in controlling ecological degradation due to reduced CO2 emissions. Based on the empirical findings, this research study offers corresponding policy suggestions.

Hydropower, human capital, urbanization and ecological footprints nexus in China and Brazil: evidence from quantile ARDL.

The relations among ecological footprints, biocapacity per capita, gross domestic product per capita, natural resources, urbanization, human capital, and hydroelectric consumption are analyzed from 1971Q1 to 2017Q4 for Brazil and China. The novel quantile autoregressive distributive lag method was employed to analyze the long-run and short-run dynamics of environmental degradation. The findings revealed that economic growth has a positive role in the environmental degradation of both countries. However, human capital, natural resources, and hydropower have heterogeneous effects across quantile distribution and between the two countries. Based on the quantile dynamics of environmental degradation, the present study mentions policy implications for sustainable development.

Revisiting global energy efficiency and CO2 emission nexus: fresh evidence from the panel quantile regression model.

Given the importance of energy efficiency in environmental degradation, the effects of energy efficiency and renewable and nonrenewable energy consumption on global environmental pollution were investigated. For this purpose, panel data from 107 countries from 1996 to 2014 were examined. In addition, the present study also tested the well-known environmental Kuznets curve (EKC). The long-run relations were estimated by applying a panel quantile regression (PQR) approach, which is useful for finding heterogeneous effects at lower- and upper-level quantiles of CO2 emissions. The empirical results indicated that energy efficiency had a significantly negative impact on CO2 emissions with low intensity at higher-level quantiles.Furthermore, the impact of renewable and nonrenewable energy consumption on environmental degradation was significantly negative and positive across all quantiles, respectively. The empirical results provide evidence supporting an inverted U-shaped nexus between GDP and CO2, whereby the EKC is found valid. Hence, energy efficiency improvement and renewable energy consumption policies must align with strategies to curb environmental degradation.

The nonlinear links between urbanization and CO2 in 15 emerging countries: Evidence from unconditional quantile and threshold regression.

The extant literature has provided empirical evidence about the relationship between urbanization and the environment; however, little attention has been paid to the non-linear relationship among them. This study aims to measure the effects of urbanization on carbon dioxide emission using quantile and threshold regression methods. To this end, the study employed threshold analysis and quantile regression methods in a sample of 15 emerging economies from 1995 to 2015 and analyzed the variation of such non-linearity at different levels of carbon dioxide. The results illustrate that a single threshold and two regimes exist and the threshold for urbanization is 29.56%. Among the two regimes, the elasticity estimates form an inverted U-shape impact of urbanization on carbon dioxide emission. The increase in the marginal effect of urbanization on carbon dioxide emissions up to the median level and a declining trend after this level implies that environmental quality is likely to improve in the emerging countries.