The CO2 capture capacity and cyclic stability of calcium oxide (CaO) prepared from cockle shells (CS) were enhanced by incorporating rice husk (RH) and binder through wet-mixing method. The cyclic reaction of calcination and carbonation was demonstrated using thermal gravimetric analyzer (TGA) which the calcination was performed in a pure N2 environment at 850 °C for 20 min and carbonation at 650 °C for 30 min in 20 vol% of CO2 in N2. The analysis using x-ray fluorescence (XRF) identified silica (Si) as the major elements in the sorbents. The RH-added sorbents also contained several types of metal elements such as which was a key factor to minimize the sintering of the sorbent during the cyclic reaction and contributed to higher CO2 capture capacity. The presence of various morphologies also associated with the improvement of the synthesized sorbents performance. The highest initial CO2 capture capacity was exhibited by CS+10%RH sorbent, which was 12% higher than the RH-free sorbent (CS). However, sorbents with the higher RH loading amount such as 40 and 50 wt% were preferred to maintain high capture capacity when the sorbents were regenerated and extended to the cyclic reaction. The sorbents also demonstrated the lowest average sorption decay, which suggested the most stable sorbent for cyclic-reaction. Once regenerated, the capture capacity of the RH-added sorbent was further increased by 12% when clay was added into the sorbent. Overall, the metal elements in RH and clay were possibly the key factor that enhances the performance of CaO prepared from CS, particularly for cyclic CO2 capture. Graphical abstract Cyclic calcination and carbonation reaction.
The developing world is facing pivotal challenges in recent times. Among these, global warming has ominous repercussions on every segment of society, thus tracing its underlying causes is imperative. This research attempts to investigate the impact of urbanization and energy consumption on carbon dioxide emissions (CO2) for a panel of 8 Asian countries (Bangladesh, China, India, Indonesia, Malaysia, Nepal, Pakistan, and Sri Lanka) over the period 1982 to 2017. The analyses are executed using panel co-integration and Granger causality techniques. The main findings of panel co-integration reveal a long-run relationship between urbanization, energy consumption, and CO2 emissions. Furthermore, the results indicate a positive and significant impact of urbanization and energy consumption on CO2 emissions, indicating that urban development and high energy consumptions are barriers to improve environmental quality in the long run. The results also highlight bi-directional causality between energy consumption and urbanization, while unidirectional causality exists between energy consumption and CO2 emissions. Based on the obtained results, this study offers useful policy implications for plummeting carbon emissions.
The main aim of this article is to examine empirically the impact of urbanization on carbon dioxide emissions in Singapore from 1970 to 2015. The autoregressive distributed lags (ARDL) approach is applied within the analysis. The main finding reveals a negative and significant impact of urbanization on carbon emissions in Singapore, which means that urban development in Singapore is not a barrier to the improvement of environmental quality. Thus, urbanization enhances environmental quality by reducing carbon emissions in the sample country. The result also highlighted that economic growth has a positive and significant impact on carbon emissions, which suggests that economic growth reduces environmental quality through its direct effect of increasing carbon emissions in the country. Despite the high level of urbanization in Singapore, which shows that 100 % of the populace is living in the urban center, it does not lead to more environmental degradation. Hence, urbanization will not be considered an obstacle when initiating policies that will be used to reduce environmental degradation in the country. Policy makers should consider the country's level of economic growth instead of urbanization when formulating policies to reduce environmental degradation, due to its direct impact on increasing carbon dioxide emissions.
This paper investigates the non-linear impacts of the agricultural, industrial, financial, and service sectors on environmental pollution in Malaysia during the 1980-2018 period. It employs the extended STIRPAT model and two indicators of environmental pollution (carbon dioxide emissions and ecological footprints). It uses the autoregressive distributed lag (ARDL) technique to estimate the parameters. Evidence from the study indicate that the agricultural, industrial, and service sectors have inverted U-shaped non-linear impacts on carbon dioxide emissions and ecological footprints, while the financial sector has a U-shaped non-linear relationship with carbon dioxide emissions and ecological footprint. These empirical outcomes are robust to diagnostic tests, structural breaks, and alternative estimation technique and proxies. The economic implication of this paper is that, at the early stage of sectoral growth, the pollution intensity of sectoral output increases, but after a certain turning point, a further increase in sectoral output will reduce environmental pollution. Precisely, environmental pollution will reduce if the agricultural, industrial, and service sectors exceed threshold levels of 11%, 44%, and 49% of GDP, respectively, while environmental pollution will be aggravated if financial sector exceeds a threshold level of 94%. Therefore, efforts to mitigate environmental pollution in Malaysia should integrate sectoral growth to attain sustainable development.
There are many advantages of geothermal energy, as an environmental friend resource. This heat radiation emanating from beneath the earth's surface presents man with good opportunities to harness it and makes a good level of agricultural food production and its processing in the EU region. The primary objective of this research is to examine the impact of geothermal energy on agri-food supply among the 27 European countries (EU27), within the time frame 1990 to 2021. The study adopted the autoregressive distributed lag (ARDL), and the findings from this study revealed that agri-food supply can increase significantly among the 13 European countries (EU13 emerging economies), leveraging on geothermal energy and economic growth variables than in the EU14 emerged economies. Furthermore, the outcome of this study showed that there could be a significant decrease in the food products coming from agricultural practices among the 13 European countries (EU13 emerging economies), due to an ineffective population density than in EU14 emerged economies. Furthermore, fossil fuel and institutional quality contribute more positively to the agri-food supply in the EU14 emerged economies than in the EU13 emerging economies. This results in an outcome that means that the agri-food supply among the EU13 emerging economies could be greatly boosted by replacing fossil fuel consumption with geothermal energy, and this facilitates the attainment of the European energy goals by the year 2030. Substituting fossil fuels with geothermal will also assist in minimizing the risks of environmental pollution and climate change. All projected calculations were seen as valid in this study, and this was confirmed by the three estimators adopted which are the pooled mean group, the mean group, and the dynamic fixed effect. This study, therefore, recommends that the 27 European countries should lay more emphasis on geothermal energy production as this will help in ensuring food security in the region. Policymakers and other government authorities as well as local and foreign investors should make more investments in geothermal energy resources as this study has proven that this will lead to agri-food security and sustainability. Not only this, it will as well curb the incidence of climate change and environmental pollution.
Addressing global environmental concerns requires the widespread adoption of renewable energy sources. More research is needed to examine the relationships between renewable energy (RE) and globalization, economic growth, and environmental quality in Indonesia. Therefore, we examined how renewable energy usage in Indonesia has changed due to the dynamic effects of globalization, financial development, and environmental quality. Time-series data were analyzed using an autoregressive distributed lag (ARDL) model to test for cointegration and long-run/short-run dynamics between 1990 and 2020. In addition to ARDL bounds testing, we used the Johansen and Engle-Granger cointegration methods for confirmation. Globalization, financial progress, human capital, greenhouse gas emissions, and economic expansion have favorable long- and short-term effects on renewable energy sources. Globalization has enabled Indonesia to expand trade, FDI, and financial investment. It has also increased energy-efficient technology use due to environmental policies. The computed results are robust enough to substitute estimators, such as dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). We recommend the implementation of policies that support financial and environmental development by utilizing renewable resources and increasing investments in renewable energy ventures.
Human emissions of carbon dioxide are causing irreversible changes in our oceans and impacting marine phytoplankton, including a group of small green algae known as picochlorophytes. Picochlorophytes grown in natural phytoplankton communities under future predicted levels of carbon dioxide have been demonstrated to thrive, along with redistribution of the cellular metabolome that enhances growth rate and photosynthesis. Here, using next-generation sequencing technology, we measured levels of transcripts in a picochlorophyte Chlorella, isolated from the sub-Antarctic and acclimated under high and current ambient CO2 levels, to better understand the molecular mechanisms involved with its ability to acclimate to elevated CO2. Compared to other phytoplankton taxa that induce broad transcriptomic responses involving multiple parts of their cellular metabolism, the changes observed in Chlorella focused on activating gene regulation involved in different sets of pathways such as light harvesting complex binding proteins, amino acid synthesis and RNA modification, while carbon metabolism was largely unaffected. Triggering a specific set of genes could be a unique strategy of small green phytoplankton under high CO2 in polar oceans.
Being closely correlated with income and economic growth, trade openness impacts the environmental quality through different means. The study analyzes the robustness of the environmental Kuznets curve (EKC) hypothesis in OIC countries by examining the extent to which trade openness influence environmental quality through different environmental indicators for the period 1991 to 2018. A new methodology dynamic common correlated effects (DCCE) is applied to resolve the issue of cross-sectional dependence (CSD). We have used greenhouse gas (GHG) emissions, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) along with ecological footprint as indicators of environmental quality. Results of DCCE estimation identify a negative association of trade openness with CO2, N2O, and CH4, while the positive relationship with the ecological footprint in overall OIC countries and higher income OIC countries. On the other hand, trade openness has a positive association with all environmental indicators in lower income OIC countries. Our findings confirm that inverted-U-shaped EKC exists in all groups of OIC countries when CO2, CH4, and ecological footprint are used as environmental indicators. However, a U-shaped EKC exists in overall OIC countries and lower income OIC countries when N2O is used. Eventually, it is recommended that if OIC countries continue trade openness policies and energy sector reforms and maintain sustainable use of biocapacity; then, they will be able to combat environmental issues with the increase in income.
The well-established emissions-growth debate relies on the symmetric nexus between CO2 emissions and economic growth, thereby ignoring a fundamental component of macro economy in the form of asymmetric relation. This paper considers how CO2 emissions respond asymmetrically to changes in economic growth. While utilizing both linear and nonlinear time series approaches for an environmentally exposed country, Pakistan over the period 1971-2018, we find convincing evidence that CO2 emissions rise more rapidly during negative shocks to economic growth than increase during economic expansions. Thus, contrary to what has previously been reported, the effect is strong as holds both at short run and long run. This is partly due to the increase in informal sector as GDP declines. Our estimated results show that accounting for the shadow economy results a higher magnitude of CO2 emissions due to decrease in economic growth, thus question the traditional symmetric decoupling of economic growth and CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and dynamic OLS (DOLS). Thus, the findings of this study call for a re-thinking on climate policy design that rarely pays attention to the aforementioned outcomes due to fall in economic growth.
There are many advantages of geothermal energy as an environmentally friendly resource; however, there are quite a several challenges that need to be overcome to completely harness sustainable and renewable energy that is also natural. The primary aim of this study is to examine what influence geothermal energy will have on land use changes among the considered 27 states in the European Union from the time being 1990 to 2021. The study adopts the auto-regressive distributed lag (ARDL); the findings show that geothermal energy growth could be leveraged to achieve remarkable growth in land use change among the 13 European developing economies than among the 14 EU developed economies. On the other hand, results from analysis further show that a remarkable decrease in land use change could be better attained among the 14 EU developed economies that among the 13 EU developing economies as a result of institutional quality. Furthermore, the result suggests that through economic growth, there could be a remarkable increase in land use change among the 14 EU developed economies than among the 13 EU developing economies. It was further revealed by the study that the level of land use change among the 27 EU nations could be remarkably increased, boosting the level of geothermal energy production that will assist in attaining the aims behind the 2030 energy union. This will eventually help in curbing the incidence of climate change and pollution in the environment; the projected calculations are observed to be valid, as confirmed through the chosen three estimators for this research. The chosen estimators are the pooled mean group, mean group, and dynamic fixed effect. The regulations and governors in 27 European Union countries should give priority to using geothermal in their renewable energy mix to reduce the incidence of changes in land structures. Also, an increased level of efficiency and effectiveness should be made to the generation of geothermal energy by state actors and investors to prompt sustainability and attainability with no further depreciation in agricultural and forest natural states.
This study is a scholarly effort to broaden the existing literature on the impact of transportation services, urbanization, and financial development on ecological footprints in Pakistan. Data used in this study covers the period of 39 years from 1980 to 2018. This study adopted the QARDL model to tackle the non-linear association of variables and test their long-run stability across the different quantiles. The findings of this study indicated a significant negative association of transportation services and financial development with ecological footprints in Pakistan at almost all quantiles whereas, the urban population was found to be positively associated with the ecological footprint in Pakistan. Results also justify the existence of the EKC hypothesis in the scenario of Pakistan. Policymakers are advised to frame strategies for investors to invest more in eco-friendly projects to curtail the ecological footprints in Pakistan. Minimizing the dependency of the transportation sector on fossil fuel, and increased use of energy-efficient appliances in the urban population would be beneficial to control the negative influence on ecological footprints in Pakistan.
This paper uses the quantile autoregressive distributed lag (QARDL) model to analyze the impact of economic growth, tourism, transportation, and globalization on carbon dioxide (CO2) emissions in the Malaysian economy. The QARDL model is employed utilizing quarterly data from 1995Q1 to 2018Q4. The results demonstrate that economic growth is significantly positive with CO2 emissions at lower to upper quantiles. Interestingly, tourism has a negative effect on CO2 emissions at higher quantiles. Moreover, globalization and transportation services are positive, with CO2 emissions at upper-middle to higher quantiles. Furthermore, we tested the environmental Kuznets curve, and the outcomes confirm the presence of the inverted U-shaped curve in the Malaysian economy. The results of this study suggest that ecotourism is beneficial for economic growth in underdeveloped areas; it increases employment opportunities and, thus, achieves a win-win situation for protection and development. The government should encourage the low-carbon development of ecotourism and achieve green development of both tourism and the economy.
The aim of this research is to explore the association between financial development, research and development (R&D) expenditures, globalization, institutional quality, and energy consumption in India by using the quarterly data of 1995-2018. Quantile Autoregressive Distributed Lag (QARDL) approach is employed to examine the relationship. An application of the QARDL approach suggests that the R&D, financial development, globalization, and institutional quality significantly influence energy utilization in India. R&D and institutional quality have a negative effect on energy utilization which shows that due to the increase in the quality of institutions and R&D in the country, energy utilization is likely to decrease. However, globalization and financial performance have a positive influence on energy which depicts that due to the increase in financial performance and globalization in India the energy consumption is likely to increase. According to the outcomes of this research, India should make a policy to ease the penalties of energy utilization by monitoring resource transfer by means of globalization and by implementing energy conversation procedures through the advancement of the financial sector.
This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase.
The aim of this research is to explore the effect of biomass energy consumption on CO2 emissions in 80 developed and developing countries. To achieve robustness, the system generalised method of moment was used and several control variables were incorporated into the model including real GDP, fossil fuel consumption, hydroelectricity production, urbanisation, population, foreign direct investment, financial development, institutional quality and the Kyoto protocol. Relying on the classification of the World Bank, the countries were categorised to developed and developing countries. We also used a dynamic common correlated effects estimator. The results consistently show that biomass energy as well as fossil fuel consumption generate more CO2 emissions. A closer look at the results show that a 100% increase in biomass consumption (tonnes per capita) will increase CO2 emissions (metric tons per capita) within the range of 2 to 47%. An increase of biomass energy intensity (biomass consumption in tonnes divided by real gross domestic product) of 100% will increase CO2 emissions (metric tons per capita) within the range of 4 to 47%. An increase of fossil fuel consumption (tonnes of oil equivalent per capita) by 100% will increase CO2 emissions (metric tons per capita) within the range of 35 to 55%. The results further show that real GDP urbanisation and population increase CO2 emissions. However, hydroelectricity and institutional quality decrease CO2 emissions. It is further observed that financial development, foreign direct investment and openness decrease CO2 emissions in the developed countries, but the opposite results are found for the developing nations. The results also show that the Kyoto Protocol reduces emission and that Environmental Kuznets Curve exists. Among the policy implications of the foregoing results is the necessity of substituting fossil fuels with other types of renewable energy (such as hydropower) rather than biomass energy for reduction of emission to be achieved.
Rapid evolution in the population age structure of the Middle East countries has major economic, social, and environmental outcomes. Therefore, to fill the gap in the previous literatures, in this study, the effect of age structure on environmental degradation was investigated in the Middle East region. To achieve this goal, a panel data of 10 Middle East countries were examined over the period of 1990 to 2014. Moreover, the carbon dioxide emission per capita was used as an environmental pollution index in this study. According to the stationary property of the variables, small sample size data, and the assumptions of the model, the panel autoregressive distributed lag method of mean group, pooled mean group, and dynamic fixed effect estimators were investigated in this study. The empirical results implied that the pooled mean group model emerged as the most efficient among the three estimators. Also, results revealed that the age structure have a significant relationship with environmental pollution. Children and working age population have a positive elasticity, whereas elderly people have negative elasticity. Furthermore, the results showed that the working age population has the greatest explanatory power on the carbon emissions. Also, the relationship between per capita energy consumption and gross domestic product per capita with air pollution was positive. Overall, the empirical results showed that any attempt to decrease carbon dioxide emissions in the Middle East region should consider the population age structure.
The main purpose of this work is to analyze the impact of environmental degradation proxied by CO2 emissions per capita along with some other explanatory variables namely energy use, trade, and human capital on economic growth in selected higher CO2 emissions economies namely China, the USA, India, and Japan. For empirical analysis, annual data over the period spanning between 1971 and 2013 are used. After using relevant and suitable tests for checking data properties, the panel fully modified ordinary least squares (FMOLS) method is employed as an analytical technique for parameter estimation. The panel group FMOLS results reveal that almost all variables are statistically significant, whereby test rejects the null hypotheses of non cointegration, demonstrating that all variables play an important role in affecting the economic growth role across countries. Where two regressors namely CO2 emissions and energy use show significantly negative impacts on economic growth, for trade and human capital, they tend to show the significantly positive impact on economic growth. However, for the individual analysis across countries, the panel estimate suggests that CO2 emissions have a significant positive relationship with economic growth for China, Japan, and the USA, while it is found significantly negative in case of India. The empirical findings of the study suggest that appropriate and prudent policies are required in order to control pollution emerging from areas other than liquefied fuel consumption. The ultimate impact of shrinking pollution will help in supporting sustainable economic growth and maturation as well as largely improve society welfare.
The rise of urbanisation in Belt and Road Initiative (BRI) countries that contribute to the disruption of the ecosystem, which would affect global sustainability, is a pressing concern. This study provides new evidence of the impact of urbanisation and institutional quality on greenhouse gas (GHG) emissions in the selected 48 BRI countries from the years 1984 to 2017. The models of this study are inferred by using panel regression model and panel quantile regression model to meet the objectives of our study as it contemplates unobserved country heterogeneity. From the panel regression model, the findings indicate that although urbanisation in BRI supports the 'life effect' hypothesis that could dampen the environment quality, this effect could be reduced through better institutional quality. Using the quantile regression method, this study concludes that one-size-fits-all strategies to reduce GHG emissions in countries with different GHG emissions levels are improbable to achieve success for all. Hence, GHG emissions control procedures should be adjusted differently across high-emission, middle-emission and low-emission countries. Based on these results, this study provides novel intuitions for policymakers to wisely plan the urbanisation blueprints to eradicate unplanned urbanisation and improve institutional quality in meeting pollution mitigation goals.
This study investigates the influence of Internet retailing on carbon dioxide (CO2) emission in 77 countries categorized into developed and developing countries during the period of 2000-2013. To realize the aims of the study, a model that represents pollution is established utilizing the panel two-stage least square (TSLS) and the generalized method of moments (GMM). The results for both regressions similarly indicated that GDP growth, electricity consumption, urbanization, and trade openness are the main factors that increase CO2 emission in the investigated countries. Although the results show that Internet retailing reduces CO2 emission in general, a disaggregation occurs between developed and developing countries whereby Internet retailing has a significant negative effect on CO2 emission in the developed countries while it has no significant impact on CO2 emission in the developing countries. From the outcome of this study, a number of policy implications are provided for the investigated countries.
The relationship between environmental factors and human health has long been a concern among academic researchers. We use two indicators of environmental pollution, namely particulate matter (PM10) and carbon dioxide (CO2) to examine the effects of poor air quality on human mortality. This study explores an issue that has largely been ignored, particularly in the African literature, where the effect of air pollution on human mortality could be influenced by gender specification. We analyse a panel data from 35 African countries and our result suggests that the elevated levels of PM10 and CO2 have a significant effect on the increasing mortality rates in infants, under-five children and adults. Although the effect of poor air quality on adults is found to differ between genders, such difference is not statistically significant. We conclude that the air pollution effects, on average, are similar between genders in the African countries.