Related Experiment Video
Updated: Oct 29, 2025

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
Published on: June 24, 2019
The non-linear relationship between carbon dioxide emissions, financial development and energy consumption in
Leng Chunyu1, Syed Zain-Ul-Abidin2, Wajeeha Majeed3
1School of Economics, Capital University of Economics and Business, Beijing, China.
Abstract:
A sizeable amount of scholarly work has been done on different aspects of financial, economic, and environmental factors. In the present study, the nonlinearity is determined between financial development and carbon dioxide emissions in the long-run and short-run periods. According to the finding, the continued financial development initially increases the carbon dioxide emissions in the short and long run. Simultaneously, the square term of financial development reduces carbon dioxide emissions and proves the inverted U-shaped hypothesis in the short and long periods. The consumption of fossil fuels produces carbon dioxide emissions, leading to environmental pollution. In contrast, renewable energy sources have fostered ecological sustainability by reducing CO2 emissions in the long and short term. At the same time, a positive response from labor productivity to carbon dioxide emissions causes environmental pollution, while capital formation is not acknowledged as a significant contributor to CO2 emissions. The Error Correction term has ascertained the reduction in error and convergence of the model from short to long term with a speed of 8% per annum. The study suggested that renewable energy and financial development should be indorsed for environmental preservation in developing European and Central Asian economies. Financial development in favor of low-cost renewables, advancing cleaner production methods, solar paneling, and electrification are a few possible remedies to achieve environmental sustainability in the short-run as well as long-run time frame.
More Related Videos
Related Concept Videos
Calculating and Interpreting the Linear Correlation Coefficient
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Sustainable Development
Energy Budgets
Correlation
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
The Carbon Cycle

