Fig 5 - uploaded by Gal Hochman
Content may be subject to copyright.
Source publication
The rapid increase in anthropogenic carbon dioxide (CO 2) emissions in recent decades is a major concern because CO 2 emissions are the main precursor of global warming. Thus, a clear understanding of the factors behind this increase is crucial for the design of policies that limit or at least stabilize global concentrations of CO 2. In this study,...
Contexts in source publication
Context 1
... energy investments, other factors likely contributed to the stagnation of the energy intensity effect after the financial crisis, such as technical efficiency, economic structure and behavior, economic development model, spatial patterns, increasing motorization, and lifestyles and intensification of consumption (O' Mahony and Dufour, 2015). Fig. 5 presents the impacts of various factors on global CO 2 emissions on a year-by-year basis to check for abnormalities in any years of the study horizon. Different from the identity decomposition of the pre-and post-financial crisis reported above, the annual results suggest that the trends and magnitude of the various effects are, ...
Context 2
... the annual results suggest that the trends and magnitude of the various effects are, overall, stable across time. However, we notice abnormalities for two years during the financial crisis (2007)(2008)(2009). In these years, changes in the economic growth effect and the energy intensity effect are almost zero compared to the preceding years. Fig. 5 also presents the quantification of various factors of global CO 2 emissions on an annual basis. Between 1997 and 2015, the cumulative effects of GDP ( ), population ( ), and fuel mix ( ) add 16,082.9, 3,846.1, and 245.6 Mt of CO 2 respectively, which is much larger than the cumulative effects of energy intensity ( ) and emission ...
Similar publications
The solar photovoltaic (PV) technology has gained global importance to overcome the global warming and meet future energy needs. The performance of a solar PV plant depends on many factors such as solar irradiance, weather conditions, various types of energy losses and system degradation over time. Although the deterministic models nicely predict t...
Global warming is expected to affect yield-determining factors of soybean (Glycine max (L.) Merr.), including the number of flowers and pods. However, little is known about the effects of high temperature on the temporal patterns of flowering and pod set. Experiments in the temperature-controlled greenhouses were conducted to examine the temporal p...
Solar-driven absorption refrigeration technology has the potential to reduce the peak electricity demand and global warming. Optimization of this technology can change the future energy economy of the world. Herein, the straightforward and inexpensive preparation of new stable aqueous solution for direct solar absorption refrigeration systems is re...
Citations
... Urban economic output is a critical factor in carbon emissions, with income levels closely linked to carbon emissions. From 1997 to 2015, the increase in carbon dioxide emissions mainly came from middle-and high-income countries, with middle-and low-income countries contributing 20% to the global emission increment, and low-income countries contributing almost nothing [43]. Different regions exhibit varying carbon emission trends based on their economic development levels, with the western and central regions of China having higher carbon intensity compared to the eastern and southern regions [44]. ...
... Examining previous articles, we have gathered various factors that influence urban carbon emissions, with articles highlighting how compact urban models, efficient use of building materials, balanced economic growth, improved energy structures, effective policies, managed population density, and enhanced public awareness can contribute to reducing carbon emissions. These factors and their impacts on urban carbon emissions are comprehensively summarized and listed in Table 2. Analysis of driving factors and policy tools of carbon emission in construction industry, based on LMDI model Dong, K.Y.; Hochman, G.l et al. [43] 2020 Analysis of driving factors for global carbon dioxide emission growth, based on LMDI Wu, Y.; Martens, P. et al. [14] 2022 Review of public perceptions and challenges of low-carbon urban transition in China Sun H.P; Chen. T.T. et al. [46] 2024 Analysis of impact of digital finance on carbon productivity ...
As global climate change becomes increasingly severe, low-carbon city construction has emerged as a critical strategy to address this challenge. This study explores the concept, current development status, and challenges of low-carbon cities, focusing on the progress and issues in China’s low-carbon city construction. The research covers defining low-carbon cities, their background, policy impacts, and analysis of practical cases. Specifically, the research focuses on identifying the challenges faced in the development of low-carbon cities in China and proposing strategies to effectively address these obstacles. Findings suggest that difficulties, such as regional disparities, inconsistencies in policy implementation, and technological barriers, hinder progress. By synthesizing insights from previous studies, this paper proposes actionable strategies, including strengthening policy frameworks for consistent application, leveraging smart technologies for efficient energy and resource management, and fostering public engagement through targeted education. These recommendations provide a guideline for future research and practical actions, contributing to sustainable urban development and offering insights for policymakers and urban planners.
... Hence, the second direction is the study of short-term influences on CO 2 emissions. Decomposition analysis techniques, such as structural and index decomposition, are typically used to study the drivers of CO 2 emissions in the short term (Dong et al., 2020;Wang et al., 2021). Structural decomposition analysis is primarily employed in national-scale research. ...
This study explores the factors driving CO2 emissions related to energy use in Fujian Province from 2000 to 2019, with an emphasis on long-term trends, short-term fluctuations, and spatial disparities. Utilizing annual data on CO2 emissions and various influencing factors from multiple cities within Fujian Province, we examine the factors driving long-term changes in CO2 emissions. To analyze short-term emission trajectories, we employ a temporal decomposition model, while spatial decomposition techniques are used to assess the variability in emission drivers across 9 prefecture-level cities over different years. Our findings reveal an inverted U-shaped relationship between CO2 emissions and urbanization over the 20-year study period. Furthermore, short-term fluctuations indicate a gradual reduction in the impact of urbanization on the increase in CO2 emissions within the industrial, transportation, and household sectors in Fujian Province. Additionally, economic development, measured as per capita gross domestic product, is shown to significantly influence CO2 emissions. Efforts to reduce energy intensity, which refers to the amount of energy consumed per unit of economic output, in both the industrial and household sectors are identified as potential strategies for emission reduction. The variability in CO2 emissions among cities is primarily attributed to differences in energy intensity and population sizes. These insights are critical for formulating policies aimed at promoting low-carbon development, reducing carbon emissions, and enhancing sustainability throughout Fujian Province.
... A growing body of research has explored the impact of technological innovation on carbon emissions. Several studies, including those by Dong et al. (2020a), Wang et al. (2019), Tajudeen et al. (2018), and Iftikhar et al. (2016), have used energy efficiency as a metric for technological innovation to assess its influence on carbon emissions. Their findings suggest that improvements in energy efficiency can significantly reduce carbon emissions. ...
Environmental degradation poses a significant global challenge, compelling many nations to recognize the importance of financial development in driving the advancement of renewable energy. Urbanization also presents a critical opportunity for adopting sustainable energy sources. Against this backdrop, our study examines the impact of Tunisia’s financial development, clean energy initiatives, technological innovation, and urbanization on carbon neutrality from 1990 to 2020, using the ARDL model. We assessed both short-term and long-term dynamics through the Bounds test and employed the Granger causality test to explore the relationships among the variables. The ARDL bounds test confirmed a long-term connection between these factors. Our findings suggest that while clean energy and technological innovations significantly reduce carbon emissions in the short term, technological innovations alone lead to increased CO2 emissions in the long term. We conclude that to enhance environmental quality, Tunisia should further develop its financial sector, invest in green technologies, and accelerate the transition to renewable energy.
... The drastic increase in CO2 concentrations is causing serious global warming and climate instability, leading to unwanted natural disasters, melting glaciers, and extreme weather patterns (Gao et al., 2020). In an effort by the global community to start paying attention to environmental problems related to increasing CO2 emissions, many countries have taken various actions to address the increase in CO2 emissions (Dong et al., 2020a;Dong et al., 2020b). ...
G20 member countries are forced to reduce carbon dioxide emissions from the global community as well as economic development constraints from domestic resources and the environment. Literature related to institutional quality and government expenditure is still limited, especially in G20 countries. To provide empirical evidence to support the theoretical argument, the study investigated the effects of institutional quality and government expenditure on CO2 emissions using a balanced panel dataset of nineteen countries that were members of the G20 between 1995 and 2015. Empirical results show that institutional quality is able to reduce carbon emissions. A good government can formulate strict environmental regulations and ensure transparency, which allows investment in green technologies and renewable energy. Other findings suggest that government spending can increase carbon emissions. The findings show that government spending in G20 countries still does not consider environmental impacts. Several policy recommendations are suggested.
... Carbon emissions vary across different regions and stages of development, influenced by several factors including economic development, population quality, and energy consumption (Dong et al., 2020;Jiang et al., 2017). The ridge regression analysis revealed a positive relationship between carbon emission and energy consumption, economic level, and population level ( (Dong et al., 2020). ...
... Carbon emissions vary across different regions and stages of development, influenced by several factors including economic development, population quality, and energy consumption (Dong et al., 2020;Jiang et al., 2017). The ridge regression analysis revealed a positive relationship between carbon emission and energy consumption, economic level, and population level ( (Dong et al., 2020). Moreover, economic growth and rising energy consumption contribute to increased carbon emissions in developing countries compared to other nations Waheed et al., 2019). ...
China is the world's largest carbon emitter, its carbon peaking and carbon neutrality goals significantly reduce climate change and global warming problems. Although the Chinese government proposed carbon emissions will peak by 2030, how do different development models affect carbon emissions in the future? Here, we analyzed the spatial and temporal trends of carbon emissions over the past two decades. Then we constructed the STIRPAT carbon emissions model based on ridge regression analysis. Finally, one national STIRPAT model and eight STIRPAT models at the sub-regional scales were generated because the effects of population, economy, and energy consumption vary significantly across regions and periods. Meanwhile, we established nine different future development models based on various population, economy, and energy consumption levels, and forecast their carbon emissions from 2020 to 2060 by eight sub-region STIRPAT models. Our results documented that (1) China's carbon emissions significantly increased by 445.79 million-ton/yr between 2000 and 2019. Meanwhile, population, total energy consumption, and GDP were growing at a rate of 7.60 million people/yr, 185.37 million-ton/yr, and 4791.74 billion-yuan/yr, respectively. (2) Ridge regression results indicated that carbon emissions are positively influenced by population, economic growth, and energy consumption in all regions, but the degree of influence varies across sub-regions. (3) In 2060, carbon emissions will be lowest across all variables at low levels of development and highest at high levels of development. Meanwhile, low energy consumption and population levels are possibly the main directions for controlling carbon emissions in the future. The findings indicate that the carbon peak target could be achieved by 2030 by controlling population and energy consumption alone. However, relying solely on these strategies may pose significant challenges in meeting the dual carbon targets, which emphasizes the need for a scientific foundation to inform low-carbon development policies. The findings provide a scientific basis and reference for the low-carbon sustainable development in China.
... Footnote 1 continued Cansino et al. (2016), Dong et al. (2020), Rodrigues et al. (2020), and Serrano-Puente (2021), and the references therein, for applications within the EU or Spain. The rest of the paper is organized as follows. ...
In this paper, we analyse the relationship between the rate of growth of emissions and economic activity in Spain from 1964 to 2020. We explain emissions by fitting a structural regression model with selected indicators of economic activity augmented with dynamic common factors extracted from a large macroeconomic database, as explanatory variables. The variables to include in the regression are selected using Machine Learning procedures while we use alternative supervised and non-supervised procedures to extract the factors. We find that, regardless of the procedure used for variable selection, private consumption and maritime transportation have the highest explanatory power for the rate of growth of emissions. We also show that the way the common factors are extracted is crucial to exploit their information content. The common factors extracted by partial least squares add valuable information on top of that of the selected individual indicators, while they are not significant when extracted by two-step-Kalman filter (2SKF).
... Overall, findings from Figure 9 suggest that the onus is on the upper-middle-income emitters to reduce carbon intensity because some countries from this income group converge toward the long-run carbon intensities significantly above the global average. Such a finding corroborates Dong et al (2020), who document that the upper-middle-income is the primary source of worldwide CO2 emissions post-2008 financial crisis. Moreover, the results suggest that middle-income economies incur relatively higher environmental externalities (emissions per USD of GDP) for their economic development (Zang et al 2018, Wang et al 2021. ...
Our study employs the distribution dynamics approach to uncover transition probabilities and the long-term evolution of relative per capita carbon emissions (REPC) and relative carbon intensity (REPGDP) across 204 countries. We split the period of analysis into pre-crisis (2000-2007), and post-crisis (2007-2016) and divided countries into four income groups. The results indicate the emergence of new convergence clubs post-crisis in both REPC and REPGDP. On the one hand, the majority (many) of the low- (high) income countries congregate to extremely low (above the global average) REPC levels in the long run. On the other hand, most of the upper-medium- (high) income economies cluster around REPGDP levels far above (below) the global average. Finally, using mobility probability plots, we identify above-average carbon emitters with the highest probabilities of diverging further above the global average in the coming years. The study delivers nascent evidence supporting the usefulness of the MPP display tool in clarifying the positions and responsibilities of specific countries in future agreements on climate change. The results support the argument for using both measures of carbon emissions as a suite of future multilateral climate negotiations and policies.
... Numerous possible contributors to GHG emissions have been highlighted in the literature, including RE [38], economic growth [39], and gross value chains [38]. This research examines the synergistic influence of GF and globally competitive and diversified production ability (economic fitness) on RE growth (REG) and GHG emissions in the context of economic growth, effective governance, regulatory quality, human capital, and economic risk in light of the significance of RE in reducing the environmental effects of energy use. ...
... This paper is an attempt to determine which factors can affect CO2 emissions in the Gulf region to help policymakers formulate strategies to reduce environmental degradation to achieve the targets set for the coming years. Research on the factors influencing CO2 emissions has increased dramatically over the last 20 years (Andreoni & Galmarini, 2016;Dong, Hochman, & Timilsina, 2020;Henriques & Borowiecki, 2017). According to Liu (2020) many factors, including globalization, renewable energies, research and development, economic expansion, and urbanization, can have an important impact on CO2 emissions. ...
Article History JEL Classification : E61; Q28; Q43; Q54. Most countries, particularly developing and growing economies, have the primary goal of achieving greater economic growth in order to improve living standards. However, a boost in economic activity raises energy demand, which in turn raises carbon dioxide emissions and deteriorates the environment. This paper investigates the effect of economic growth, energy consumption, and research and development on CO2 emissions in Gulf Council Cooperation (GCC) countries. The study uses the Vector Error Correction Model to investigate the short-and long-run synergy between variables over the period 2000-2022. The results indicate that boosting economic activity requires more energy consumption and will increase CO2 emissions in the long run. Investing in research and development can enhance the quality of the environment, yet the effect of urbanization on CO2 emissions in GCC countries remains unclear. To reduce energy consumption, it is first necessary to expand renewable energy sources and encourage energy-saving techniques. Then, to lower CO2 emissions, the government must promote investments in green technologies, particularly in manufacturing. Third, the government should encourage sustainable urbanization by putting laws in place that encourage the growth of green cities and transportation networks. Contribution/ Originality: The paper's contribution is to construct a framework that connects CO2 emissions to urbanization, economic expansion, and technical advancement for Gulf Cooperation Council countries, as previous GCC research studies have not thoroughly studied the relationship between these variables in the short and long run.
... In addition, the impact of population and economic growth on CO2 emissions is very significant across regions, with emissions decreasing at higher levels of renewable energy intensity (Dong et al., 2018). The main drivers of CO2 emissions worldwide are economic growth, population growth, energy intensity, and clean and renewable energy (Dong et al., 2020). ...
The increase in world carbon emissions is always in line with national economic growth programs, which create negative environmental externalities. To understand the effectiveness of related factors in mitigating CO2 emissions, this study investigates the intricate relationship among macro-pillars such as economic growth, foreign investment, trade and finance, energy, and renewable energy with CO2 emissions of the high gross domestic product economies in East Asia Pacific, such as China, Japan, Korea, Australia and Indonesia (EAP-5). Through the application of the Vector Error Correction Model (VECM), this research reveals the long-term equilibrium and short-term dynamics between CO2 emissions and selected factors from 1991 to 2020. The long-term cointegration vector test results show that economic growth and foreign investment contribute to carbon reduction. Meanwhile, the short-term Granger causality test shows that economic growth has a two-way causality towards carbon emissions, while energy consumption and renewable energy consumption have a one-way causality towards carbon emissions. In contrast, the variables trade, foreign direct investment, and domestic credit to the private sector do not have two-way causality towards CO2 emissions. The findings reveal that economic growth and foreign investment play significant roles in carbon reduction, which are observed in long-term causality relationships, while energy consumption and renewable energy are notable factors. Thus, the study offers implications for mitigating environmental concerns on national economic growth agendas by scrutinizing and examining the efficacy of related factors.
