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The Influencing Factors of CO2 Emissions and the Role of Biomass Energy Consumption: Statistical Experience from G-7 Countries

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Abstract

This paper examines the impact of biomass energy consumption on CO2 emissions and the environmental Kuznets curve (EKC) hypothesis in G-7 countries. We also incorporate capitalization, financial development, and globalization measures (economic, social, and political) as additional determinants of CO2 emissions. This study covers the period of 1980–2014. We apply the generalized method of moments (GMM) for empirical analysis. The empirical results reveal that biomass energy consumption contributes to CO2 emissions. The EKC hypothesis is valid in G-7 countries. Capitalization is inversely linked with CO2 emissions. Financial development deteriorates environmental quality. Foreign direct investment (FDI) and trade openness improve environmental quality. Globalization increases CO2 emissions. Institutional quality improves environmental quality through effective economic and environmental policies. Urbanization impedes environmental quality. These results provide new insights for policy makers in designing comprehensive environmental policy by considering biomass energy as an economic tool for sustainable economic development and to improve environmental quality.

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Notes

  1. Payne [115] examines, through the Toda-Yamamoto causality test, the relationship between biomass energy consumption and income in the USA. The results support a positive unidirectional causality that runs from biomass energy consumption to real GDP. Bildirici [28] examines the short- and long-run causality between biomass energy consumption and income for selected emerging countries. Ozturk and Bilgili [112] find a significant but positive effect of biomass consumption on economic growth.

  2. Although, Panayotou [113] first coined the term Environmental Kuznets Curve, Grossman and Krueger [60] established the EKC relationship using cross-sectional data for 42 countries´ urban areas and 3 pollutants to study the relationship between air quality and economic growth.

  3. The Climate Change Performance Index (CCPI) is an instrument that was designed to enhance transparency in international climate politics. On the basis of standardized criteria, the index evaluates and compares the climate protection performance of 58 countries that together are responsible for more than 90% of global energy-related CO2 emissions. Therefore, 80% of the evaluation is based on indicators of emissions (30% for emissions levels and 30% for recent development of emissions), efficiency (5% level of efficiency and 5% recent development in efficiency), and renewable energy (8% recent development and 2% share of total primary energy supply). The remaining 20% of the CCPI evaluation is based on national and international climate policy assessments by approximately 300 experts from the respective countries.

  4. The atmospheric greenhouse gas implications of burning forest biomass for energy vary depending on the characteristics of bio-energy combustion technology, the fossil fuel technology that it replaces, and the biophysical and forest management characteristics of the forests from which the biomass is harvested. For the biomass replacement of coal-fired power plants, the net cumulative emissions in 2050 are approximately equal to what they would have been burning coal; and for the replacement of natural gas, the cumulative total emissions are substantially higher with biomass electricity generation [100].

  5. Many of the biomass fuels that are used today come in the form of wood products, dried vegetation, crop residue, and aquatic plants. Biomass must be considered in the search for an alternative source of energy that is abundant in a wide-scale yet non-disruptive manner because it is capable of being implemented at all levels of society.

  6. We have also transformed all of the variables into natural-log before empirical analysis for reliable and efficient empirical evidence.

  7. G 7 countries such as France, Germany, Italy, Japan, the USA, and the UK and Canada are shown by 1, 2, 3, 4, 5, 6, and 7, respectively.

  8. For a more detailed explanation, see [16, 17, 30, 62].

  9. To determine whether the EKC hypothesis does exist, the significance of the slope coefficient Y and Y square must be examined. If the slope coefficients of Y are positive and significant (β1 > 0) and the Y square is negative and significant (β2 < 0), an inverted U-shaped relationship can be determined between income and environmental pollution (Table 4). The behavior of the remaining coefficients also helps to explain the relationship between income level and environmental pollution levels. The result of the regression implies that in an initial stage, increases in income levels lead to increases in CO2 emission levels until the first turning point is reached. Beyond this point, higher income levels are inversely related to environmental pollution levels (CO2 levels start to decrease).

  10. Over the period from 1975 through 2004, the annualized growth rate for ocean transport was 3.8%, while for air transport, the growth rate was 8.4% [69]. Consistent with the disparity between the growth rates of aviation and other modes of transport, the Stern report (2007) projects that―between 2005 and 2050―emissions are expected to grow fastest from aviation (tripling over the period, compared to a doubling of road transport emissions) (Stern 2007).

  11. The impact of political globalization on CO2 emissions is positive but statistically insignificant.

  12. The overall globalization disclosures inform nations and people about how to improve institutions and structures. In many cases when there is suffering from a lack of democracy, accountability and transparency, globalization may contribute to power abuses (and potential damages over environmental processes) [59]. This abuse is shaped more by increased consideration about investment objectives than by environmentally sustainable consumption, production and trade.

  13. The hypothesis of interaction effects seeks to determine under what conditions a relationship becomes stronger or weaker, disappears or changes direction. The moderator variable may be qualitative or quantitative, and it affects the magnitude and/or direction of a relationship between an independent variable (predictor) and dependent variable (criterion) [37].

  14. It is argued by Neequaye and Oladi [106] that the relationship between FDI and carbon emissions is linked with a wide number of factors. These are factors such as technology usage for domestic production. The adoption of energy-efficient technology for production lessens carbon emissions (technique effect) and institutional quality, whereas environmental regulations and corruption can affect emissions directly by increasing the cost of production [20, 41] and indirectly through FDI, i.e., the pollution haven hypothesis [63].

  15. Cole and Elliot (2003) establish a strong correlation between a sector’s capital intensity and its pollution intensity, where the capital-intensive goods can be considered pollution goods.

  16. In societies, when there is a tendency toward decreasing institutional quality, this tendency should be particularly strong when there is an abundance of valuable natural resources. In other words, resource abundance correlates with a lower quality of government in general [9]. Therefore, some studies support a correlation between resource abundance and institutional quality ([3]; Treisman 2000; [92]).

  17. The adjusted-R2 indicates the percentage of variation explained by determinants of CO2 emissions. Comparatively, a moderate value of adjusted-R2 also corroborates R2, which is used for the goodness-of-fit of empirical model(s).

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Shahbaz, M., Balsalobre, D. & Shahzad, S.J.H. The Influencing Factors of CO2 Emissions and the Role of Biomass Energy Consumption: Statistical Experience from G-7 Countries. Environ Model Assess 24, 143–161 (2019). https://doi.org/10.1007/s10666-018-9620-8

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