Growth Of CO2 Emissions Research Articles

Molecular insight into the dual effect of salts: Promoting or inhibiting the nucleation and growth of carbon dioxide clathrate hydrates

Facing the huge gap between the growing CO2 emissions and net-zero emissions target to mitigate global warming, the long-term storage of excess CO2 becomes an intractable issue. Sequestering CO2 in the oceans as clathrate hydrates is a promising solution. Many unanswered questions still exist at the molecular level regarding how ions in seawater kinetically affect the formation of CO2 hydrates, particularly the dual effect: as the concentration rises, salt ions shift from being a promoter of hydrate formation to becoming an inhibitor. Herein, we report the homogeneous nucleation process of CO2 hydrates in saline solutions via molecular dynamics simulations. Consistent with experimental findings, our results show that nucleation is promoted within certain salt concentration ranges; however, the evidence suggests that ions do not act as nucleation sites. Multiple ion-induced variations in the aqueous phase are analyzed, including changes in the mobility, structure, and CO2 solubility. We find that the presence of ions strengthens the hydrophobic interactions among the dissolved CO2 molecules, which are associated with the salting-out phenomenon, accounting for the promoting effect of salts at low concentrations. However, as the salt concentration increases, this advantage is offset, leading to the inhibiting effect at high salt concentrations. We demonstrate that anions are inevitably involved in the construction of the solid hydrate phase. Their presence disrupts the native tetrahedral connectivity of water molecules and imparts negative charges to the solid phase, thereby attracting cations. In addition to advancing our understanding of the intricate interactions among water, guest, and additive molecules to germinate ordered solid structures, these findings can accelerate the development and utilization of sustainable hydrate-based applications.

Analysis of Synergistic Drivers of CO2 and NOX Emissions from Thermal Power Generating Units in Beijing–Tianjin–Hebei Region, 2010–2020

Synergistic control of the emissions of air pollutants and CO2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO2 and NOX emission characteristics of these units, and identifies and quantifies the synergistic drivers affecting these emission trends. The inventory data show that, between 2010 and 2020, NOX emissions were reduced by 86.1%, while CO2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NOX emissions through measures such as end-of-pipe treatment, controlling CO2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO2 and NOX emission growth, energy intensity reduction is the main driver of CO2 emission reduction, and end-of-pipe treatment is the main driver of NOX emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing–Tianjin–Hebei region, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NOX emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, this high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Annual and Seasonal Dynamics of CO2 Emissions in Major Cities of China (2019–2022)

To control the growth of CO2 emissions and achieve the goal of carbon peaking, this study carried out a detailed spatio-temporal analysis of carbon emissions in major cities of China on a city-wide and seasonal scale, used carbon emissions as an indicator to explore the impact of COVID-19 on human activities, and thereby studied the urban resilience of different cities. Our research re-vealed that (i) the seasonal patterns of CO2 emissions in major cities of China could be divided into four types: Long High, Summer High, Winter High, and Fluctuations, which was highly related to the power and industrial sectors. (ii) The annual trends, which were strongly affected by the pan-demic, could be divided into four types: Little Impact, First Impact, Second Impact, and Both Impact. (iii) The recovery speed of CO2 emissions reflected urban resilience. Cities with higher levels of de-velopment had a stronger resistance to the pandemic, but a slower recovery speed. Studying the changes in CO2 emissions and their causes can help to make timely policy adjustments during the economic recovery period after the end of the pandemic, provide more references to urban resilience construction, and provide experience for future responses to large-scale emergencies.

Investigating the environmental Kuznets curve hypothesis with urbanization, industrialization, and service sector for six South Asian Countries: Fresh evidence from Driscoll Kraay standard error

South Asia is the most polluted region in the world and is struggling to deal with the effects of growing CO2 emissions and the ecological impact it has left. The region needs to identify the variables that are most effective in reducing pollution in order to achieve long-term sustainable growth. The current study aims to investigate the environmental impacts of the current and projected urbanization rate, the service sector, and the availability of natural resources to test the environmental Kuznets-curve (EKC) theory in six South Asian countries (SAARC). With cross-sectional dependence present, this research examines panel data from 1972 to 2021 using the newly developed Driscoll Kraay Standard Error (DKSE) approach. To check the robustness of DKSE estimation, the study employs a novel Cross Sectional Autoregressive Distributive Lag (CS-ARDL) method. The results of DKSE show that GDP significantly minimizes CO2 emissions in both the short and long run. At the same time, GDP2, urbanization, and the service sector increase CO2 emissions in the South Asian region. The DKSE estimator also shows that industrialization and abundant natural resources have insignificant impacts on CO2 emissions. Inconsistent with the EKC hypothesis, the findings show that higher economic growth leads to increased environmental pollution and CO2 levels. Meanwhile, the CS-ARDL analysis found that GDP and industrialization reduce CO2 emissions, while urbanization, GDP2, and natural resource availability increase CO2 emissions. This research emphasizes the need for establishing appropriate industrialization and urbanization strategies and promoting cleaner energy adoption to reduce CO2 emissions.

Exploring the link between CO2 emissions, health expenditure, and economic growth in Türkiye: evidence from the ARDL model

In recent times, the literature has seen considerable growth in research at the intersection of CO2 emission, health expenditure, and economic growth. But looking at the literature, it appears that the relationship between health expenditures, CO2 emissions, and economic growth is unclear. To resolve this uncertainty, this study was conducted with different data, countries, and methods. To this end, the present study analyzed the nexus between CO2 emissions, health expenditure, and economic growth in Türkiye from 1975 to 2020 using the Autoregressive Distributed Lagged (ARDL) model developed by Pesaran et al. (J Appl Econ 16(3):289–326, 2001). The study reveals a connection between CO2 emissions, health spending, and economic development in Türkiye over the long term. It also highlights a short-term correlation among these factors. The study indicates that a 1% increase in economic growth results in a 0.553 and 0.297 rise in CO2 emissions in the short and long term, respectively. That is, it suggests that if economic growth in Türkiye doesn’t involve renewable energy, it could negatively affect CO2 emissions both in the short and long term. To address this, substantial efforts are needed to transition to low-carbon technologies like renewable energy and energy efficiency, aiming to reduce emissions and support long-term economic growth. The study further demonstrates that a 1% growth in health expenditure leads to a 0.124% decrease in CO2 emissions over the long term. This implies that Türkiye’s health sector could benefit from utilizing more renewable energy or using fossil fuels more efficiently. Additionally, the study warns that long-term population growth could negatively affect CO2 emissions in Türkiye.

Assessing the socioeconomic and environmental impacts of China's power sector changes in 2010–2020

Power sector changes in China have far-reaching socioeconomic and environmental impacts. To achieve sustainable power transitions, it is crucial to analyze the impact patterns and mechanisms of power sector changes on socioeconomic and environmental systems. For this purpose, we develop a hybrid-unit input-output model with detailed power sectors and endogenous capital for accurately capturing the overall Socio-Economic-Environmental (SEE) impacts induced by power sector changes over 2010–2020, and underlying determinants are identified using the structural decomposition analysis technique. We find that China's power sector changes exerted positive SEE impacts especially after 2015, with a trade-off of creation in value added and employment over CO2 emissions growth. Revealing the impact mechanisms shows that supply chains embodied more impacts than direct demand variants induced by power operation and capacity investments. Increased generation of clean fossil power and expanded capacity investments of renewable power largely contributed to positive SEE impacts, particularly in fuel-related as well as power equipment manufacturing and metal production sectors, while the phase-down of subcritical coal power and capacity reduction of hydropower impeded SEE progress. Production structure improvement and employment intensity decline as well as power generation shifts toward wind and solar power led to negative SEE impacts alongside reductions in value added and employment, and CO2 emissions growth was further induced by more equipment-intensive investment structures. Our empirical results inform policymaking promoting sustainable power transitions.

Spatial-temporal Dynamics and Driving Forces of Provincial CO2 Emission Responsibilities in China from Multiple Perspectives

Abstract A comprehensive analysis of the carbon emission profile of Chinese provinces from multiple perspectives is required to develop equitable and effective policies to reduce carbon emissions. This study estimates the carbon dioxide (CO2) emission responsibilities of China’s 30 provinces and 22 sectors from production, consumption, and income-based perspectives from 2012 to 2017. Structural decomposition analysis (SDA) is used to determine the driving forces of changes in CO2 emissions in China from 2012 to 2017. The results indicate the following. (1) The dominant CO2 emission sectors are the Electric Power, Steam, and Hot Water industry and the Smelting and Pressing of Metals industry. (2) The scale effect of the initial input is the dominant factor affecting the growth of CO2 emissions, followed by the scale effect of the final demand from 2012 to 2017. (3) The structural effect of the production output is the primary carbon reduction factor, followed by the structural effect of the intermediate product input and the carbon intensity effect. Based on these results, recommendations are provided to reduce CO2 emissions, such as developing green and low-carbon technologies, revising and optimizing the energy composition, accelerating the green transition, and a science-based approach to investment. Keywords: Multiple perspectives, China’s Provinces, Spatial-temporal evolution, MRIO model, SDA model.

The Impact of Port Total Factor Productivity on Carbon Dioxide Emissions in Port Cities: Evidence from the Yangtze River Ports

This paper investigates the relationship between port productivity and carbon dioxide (CO2) emissions in port cities. The study initially employs the global Malmquist productivity index (MPI) to measure productivity growth in 16 major inland ports along the Yangtze River, obtaining data on the ports’ total factor productivity (TFP). Through an analysis using the panel data model with two-way fixed effects, we find a positive correlation between the improvement of port TFP and the increase in CO2 emissions in port cities. Further panel quantile regression analysis reveals the heterogeneity of this impact, especially in cities with medium and higher CO2 emissions, where the positive effects of TFP on carbon emissions are particularly significant. The study also indicates a threshold effect of port size in the relationship between TFP and CO2 emissions: in smaller ports, the impact of TFP improvement on CO2 emissions is less significant; however, once the port size exceeds a certain threshold, the growth in TFP significantly promotes an increase in CO2 emissions. These findings provide theoretical justification and decision-making references for policymakers to adopt effective measures to mitigate the growth of CO2 emissions while promoting the efficiency of port production.

Teaching simple heuristics can reduce the exponential growth bias in judging historic CO2 emission growth

AbstractAcross the last 150 years, global CO2 emissions have grown at an increasing, exponential pace. Based on the well‐documented tendency to underestimate such exponential growth, we hypothesize and test in three studies (total N = 1796, including one nationally representative US sample) that people would fail to understand the historical, exponential growth of global CO2 emissions. However, we also show that providing a simple rule of thumb can serve as an effective educational boost that helps overcome this biased perception. Participants who were provided with the heuristic that historically, global CO2 emissions have doubled every thirty years provided highly accurate estimates of past emission levels. Compared to participants who relied on intuition, those who applied this doubling heuristic avoided common errors in understanding the current state of the climate change threat and made more realistic expectations of the future consequences of uninterrupted growth. Together, these studies show that overcoming the exponential growth bias helps people form more accurate perceptions of historic CO2 emissions growth and understand the difficulty of curbing future emissions.

Analysis of the Existence of Environmental Kuznets Curve (EKC) Hypothesis on CO2 Emission, Energy Consumption, and Economic Growth in Indonesia

This research explains environmental issues, in the context of Kuznets' theory that links economic growth, energy consumption and CO2 emissions. The focus of the research is to test the Kuznets Environment Curve (EKC) hypothesis in Indonesia in the period 1990-2019 using time series analysis Vector Error Correction Model (VECM). Research findings show that, both in the long and short term, CO2 emissions and energy consumption have a significant impact, while economic growth has no significant impact. These results indicate that the ECC hypothesis is not supported in Indonesia. Emerging policy implications include the transition to clean energy, sustainable farming and forestry management, waste and pollution control, and increased environmental awareness and education. Faced with the complexity of environmental challenges, the implementation of this policy has become crucial toining a balance between environmental sustainability and economic growth.

The Impacts of ICT and innovation on Carbon Dioxide Emissions in G20 Countries

The G20 countries collectively account for a substantial portion of global carbon dioxide (CO2) emissions, as they represent the world’s major economies and industrial powers. The continual growth in CO2 emissions exacerbates the greenhouse effect, which negatively influences the environment and ecosystems by raising temperatures, altering weather patterns, and increasing sea levels. To effectively address global climate action, it is imperative to tackle and reduce CO2 emissions in G20 nations. The objective of this study is to investigate the impacts of ICT and innovation on CO2 emissions in G20 countries. Using panel quantile regression, we analyze data spanning from the year 2000 to 2019 to derive meaningful results. The findings demonstrate a strong positive association between ICT and CO2 in nations that fall between the 10th and 40th quantiles. The countries with carbon dioxide emissions falling between the 30th and 90th quantiles also showed a strong positive correlation between patent applications and CO2. The conclusion of this study shows that innovation and ICT do not always reduce CO2, especially at levels of CO2 emission below the 40th quantile. As a result, depending on the country’s CO2 level, different ICT and innovation-related initiatives may have different effects on CO2. The novelty of this study reveals that the relationship between ICT, innovation, and CO2 emissions is underscored by varying levels of CO2 emissions.

The dynamic relationship between nuclear energy, CO2 emissions, and economic growth: evidence from the richest countries in Europe and Asia.

This study examines the dynamic relationship between the share of nuclear energy, growth in CO2 emissions, and GDP growth for the wealthiest countries of the two continents, Europe and Asia, from 1965 to 2021. The results from the SVAR model show a significant positive relationship between GDP growth and the growth of CO2 emissions in all countries. However, the values of the coefficients vary in the case of different countries of both continents. Further, it has been observed that the relationship between the growth of nuclear energy and the growth in CO2 emissions is more complex and varies from country to country. The results indicate that there is a strong negative relationship between nuclear energy and CO2 emissions in France, Russia, the United Kingdom, and India. At the same time, there is no significant relationship between Germany, Italy, and China. Finally, the result shows that there is an insignificant relationship between the growth in the share of nuclear energy and the GDP growth rate. From the policy perspective, this study suggests that alternative energy sources like nuclear energy can be leveraged to obtain a clean environment.

CO2 emission, life expectancy, and economic growth: a triad analysis of Sub-Saharan African countries

CO2 emission, life expectancy, and economic growth: a triad analysis of Sub-Saharan African countries

How Religiosity Affect Climate Change? A Cross-Country Analysis

Climate change demands a collective response, including from religious perspectives, but it presents a dualistic challenge. On one hand, some believers see it as a divine, immutable law (theocentric), urging humans not to defy it. Conversely, others attribute climate change to human actions that exploit nature (anthropocentric). This study scrutinizes the relationship between religiosity and climate change, using per capita CO2 emissions as a proxy. It employs cross-country regression analysis, along with robustness and sensitivity tests. The findings highlight religiosity's substantial role in curbing per capita CO2 emissions growth. This underscores religion's potential as a societal force in overcoming environmental problems, global climate issues, safeguarding natural resources and ecosystems, and ensuring a comfortable, secure existence on Earth.

Investigating the Relationship Between Tourism, Economic Growth, and CO2 Emissions in Uzbekistan

In this study, the relationship between the economic growth of Uzbekistan, CO2 emissions and international tourism from 2000 to 2023 was investigated by using the ARDL (Autoregressive Distributed Lag) limit testing approach. The findings suggest that there is a strong long-run equilibrium relationship between these variables. In particular, a 1% increase in GDP per capita is associated with a 1.43% increase in international tourist arrivals, which highlights the positive impact of economic growth on tourism demand. Furthermore, a 1% increase in CO2 emissions corresponds to a 3.93% increase in tourist arrivals, which shows the complex interplay between environmental impact and tourism development. This may be due to the role of urbanization and industrialization, which cause emissions, in improving tourism infrastructure and services. These results highlight the importance of developing integrated strategies aimed at sustainable tourism development that take into account both economic and environmental aspects.

Carbon dioxide and asset pricing: Evidence from international stock markets

We use carbon dioxide (CO2) emissions growth to measure consumption risk within a consumption-based capital asset pricing model framework. Given the comprehensive worldwide coverage of CO2 emissions, this measure allows us to use the full history of stock market data in the US, Europe, the world, and fifteen international markets. For the US (Europe/the world), we are able to explain the observed equity market premium with a relative risk aversion of 6 (10/12), which is less than half the size of that estimated using the canonical expenditures-based consumption growth measure. The average estimated relative risk aversion across fifteen other international markets is 5. We also find evidence that the growth of CO2 emissions is a priced risk factor that captures the cross section of stock portfolio returns.

Effects of regional freight structure and energy intensity on CO2 emission of transport—a case study in Yangtze River Delta

Taking the Yangtze River Delta (YRD) of China as the research area, this paper studies the influence of freight structure adjustment and energy intensity on carbon dioxide (CO2) emission from the transportation industry. Sample data from 1990 to 2019 are selected, and co-integration analysis is performed using three independent variables: energy intensity, turnover ratio of railway to highway (R/H), and turnover ratio of railway to waterway (R/W). Then, an autoregressive distribution lag-error correction model (ARDL-ECM) is established to estimate the long-run and short-run relationships among the variables through unit root test, autoregressive distributed lag (ARDL) boundary test, and Granger test. The results show that in the long run, the growth of energy intensity leads to the long-term growth of CO2 emission in the transportation sector of the YRD, and R/W and R/H have a suppressive effect on CO2 emission. Granger causality indicates that there is a bidirectional causal relationship between energy intensity and CO2 emission. This work can be a reference for government departments to formulate policies related to carbon emissions in the transportation industry.

THE IMPACT OF TRADE, FOREIGN DIRECT INVESTMENT (FDI), AND ECONOMIC GROWTH ON CARBON DIOXIDE (CO2) EMISSIONS IN SELECTED ASIAN COUNTRIES

This study examines the impact of trade, foreign direct investment (FDI), and economic growth on carbon dioxide (CO2) emissions in Selected Asian countries for the period 1990 to 2019. The objectives of this study are (1) to investigate the relationship between trade and CO2 emission, (2) to investigate the relationship between FDI and CO2 emission, and (3) to investigate the relationship between economic growth and CO2 emission.
 This study uses ordinary least squares (OLS) method to analyze the data. Multicollinearity test, heteroskedasticity test, and serial correlation test were also used to check the stability of the model. In addition, Granger causality test was applied to this study.
 The results show that there is a significant positive correlation between economic growth and CO2 emissions. If GDP increases by 1%, the average CO2 emission will increase by 0.186%, holding other variables constant. The explanation of trade and FDI on CO2 emissions is insignificant. Multicollinearity, heteroskedasticity and serial correlation are not present in the model of this study. Finally, the results of Granger causality test show that there is no Granger causality between independent variables and dependent variable.
 The government establishes better environmental regulations and strengthens the regulation of chemical and heavy industry sectors. Promoting technological advancement and investment in new energy technologies, government focus on energy efficiency and environmental initiatives in the corporate sector can effectively curb the growth of CO2 emissions.

Investigating the fast energy-related carbon emissions growth in African countries and its drivers

Efforts to avoid the acceleration of global warming have tended to focus on countries with high CO2 emissions levels and large populations, with a high level of economic development or industrialization. African countries, which often do not conform to such criteria, are more vulnerable to climate change due to their dependence on climate-sensitive industries and their limited infrastructure and technological capacity to cope with its impacts. The long-term economic growth rates projected for Africa's rapid development period will, further, make Africa a potential emission hotspot in the near future. Here, for the first time, we built an energy-related emissions inventory for 19 African countries for 2010–2019, which addresses emissions from 47 economic sectors and 5 energy types, making it the most comprehensive of its kind. The degree of decoupling of economy and emissions, and drivers of CO2 emission changes are also examined. Most African countries experienced rapid growth in CO2 emissions, with an average annual growth rate of 5.5% for fossil fuel-related CO2 emissions and 6.0% for unsustainable biomass-related CO2 emissions. Only two countries, South Africa and Tanzania, have achieved a strong decoupling of economic growth from CO2 emissions. Economic and population are the most important drivers of emissions, while energy intensity has been identified as a key factor in mitigating CO2 emissions, especially for those countries that have reached strong or weak decoupling. The findings from this study provide essential insights that could guide the development of low-carbon policies and strategies in Africa.

Synergy among finance, energy and CO2 emissions in a dynamic setting: Measures to optimize the carbon peaking path

Financial development and energy consumption are expected to exert a significant effect on CO2 emission changes. However, there remains a research gap in optimizing pathways to carbon peaking under financial and energy drivers. This paper constructs a novel model covering finance and energy consumption using the generalized Divisia Index (GDI) method. The GDI allows to quantify the drivers behind the CO2 emission change in China during 2005–2020. Furthermore, it combines a Monte Carlo simulation with scenario analysis to forecast the path of CO2 emissions during 2021–2030. The results demonstrate that energy structure and carbon factor remain the principal drivers for CO2 emission growth in China. Thus, it is still pivotal to optimize energy saving and carbon reduction policies. Financial energy saving has enormous potential for reducing CO2 emissions over time, even though the immediate influence on CO2 emission is not significant. China has a substantial probability of reaching the peaking target in 2026 under the technology breakthrough scenario, whereas in the other two scenarios the target cannot be achieved.