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.
Carbon dioxide (CO2) emission will increase due to the increasing global plastic demand. Statistical data shows that plastic production alone will contribute to at least 20% of the annual global carbon budget in the near future. Hence, several alternative methods are recommended to overcome this problem, such as bio-product synthesis. Algae consist of diverse species and have huge potential to be a promising biomass feedstock for a range of purposes, including bio-oil production. The convenient cultivation method of algae could be one of the main support for algal biomass utilization. The aim of this study is to forecast and outline the strategies in order to meet the future demand (year 2050) of plastic production and, at the same time, reduce CO2 emission by replacing the conventional plastic with bio-based plastic. In this paper, the analysis for 25%, 50% and 75% CO2 reduction has been done by using carbon emission pinch analysis. The strategies of biomass utilization in Malaysia are also enumerated in this study. This study suggested that the algal biomass found in Malaysia coastal areas should be utilized and cultivated on a larger scale in order to meet the increasing plastic demand and, at the same time, reduce carbon footprint. Some of the potential areas for macroalgae sea-farming cultivation in Sabah coastline (Malaysia), comprised of about 3885 km2 (388,500 ha) in total, have been highlighted. These potential areas have the potential to produce up to 14.5 million tonnes (Mt)/y of macroalgae in total, which can contribute 370 Mt of phenol for bioplastic production.
The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the nonlinear autoregressive distributive lag (NARDL) model in Malaysia for the period of 1980-2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as the short run in Malaysia. The findings also show that in the long and short run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth, whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia, RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption.
Energy is one of the prime factors in influencing the sustainable development of a country. Different energy sources play important roles in driving the income growth of different economic sectors such as industrial, agricultural, and services. Fossil fuels, however, have come under strong criticism for actively accelerating climate change. As such, it is imperative to investigate the contributions of various energy sources toward sustainable growth. With Malaysia as the test-bed, the present study analyzes the impact of energy prices on economic stability using the novel wavelet-based analysis. Specifically, the study analyzed the impact of crude oil, natural gas, and gasoline prices on the economic (brown) and green growth from 1995 to 2020. The results show that in continuous wavelet transform, the cone of influence of all five factors exhibits strong short-run variance and fluctuations from 2005 to 2013. However, the intensity of brown growth is more influential than green growth. Similarly, in wavelet coherence graphs, the downward right arrows indicate positively significant associations between crude oil prices, natural gas prices, and gasoline prices with brown and green growth. Additionally, wavelet-based Granger causality reveals a bidirectional causal relationship between all variables. The results thus strongly suggest that energy prices predominantly affect the economic (brown) and green growth progression of the Malaysian economy. The study concludes with some suggested implications to augment the country's sustainable growth.
Sustainable development inculcates the process of preserving the environment for future generations while maintaining existing human needs. This study attempts to empirically investigate the relationship between CO2 emissions, GDP, energy consumption, and imports and exports using yearly data between 1980 and 2014 for the panel of eight developing countries (i.e., Bangladesh, Egypt, Iran, Indonesia, Malaysia, Nigeria, Pakistan, and Turkey). All the tests for cointegration establish the long-run association among the variables and confirm the environmental Kuznets curve (EKC) hypothesis for the panel of eight countries. GDP and energy consumption remained significant factors for emission intensity both in the long and short run. However, exports found to be positive factor for emissions in the long run only and imports spur emissions in the short run. The country-specific results validate EKC hypothesis for Bangladesh, Iran, Nigeria, Pakistan, and Turkey. The findings are policy oriented and suggest that the countries' economic growth along with energy consumption and exports are highly emission intensive which require necessary adjustments at sustainable development policy front.
Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts.
The purpose of this study is to explore the effect of financial development on CO2 emission in 129 countries classified by the income level. A panel CO2 emission model using urbanisation, GDP growth, trade openness, petroleum consumption and financial development variables that are major determinants of CO2 emission was constructed for the 1980-2011 period. The results revealed that the variables are cointegrated based on the Pedroni cointegration test. The dynamic ordinary least squares (OLS) and the Granger causality test results also show that financial development can improve environmental quality in the short run and long run due to its negative effect on CO2 emission. The rest of the determinants, especially petroleum consumption, are determined to be the major source of environmental damage in most of the income group countries. Based on the results obtained, the investigated countries should provide banking loans to projects and investments that can promote energy savings, energy efficiency and renewable energy to help these countries reduce environmental damage in both the short and long run.
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.
Environmental quality indicators are crucial for responsive and cost-effective policies. The objective of the study is to examine the relationship between environmental quality indicators and financial development in Malaysia. For this purpose, the number of environmental quality indicators has been used, i.e., air pollution measured by carbon dioxide emissions, population density per square kilometer of land area, agricultural production measured by cereal production and livestock production, and energy resources considered by energy use and fossil fuel energy consumption, which placed an impact on the financial development of the country. The study used four main financial indicators, i.e., broad money supply (M2), domestic credit provided by the financial sector (DCFS), domestic credit to the private sector (DCPC), and inflation (CPI), which each financial indicator separately estimated with the environmental quality indicators, over a period of 1975-2013. The study used the generalized method of moments (GMM) technique to minimize the simultaneity from the model. The results show that carbon dioxide emissions exert the positive correlation with the M2, DCFC, and DCPC, while there is a negative correlation with the CPI. However, these results have been evaporated from the GMM estimates, where carbon emissions have no significant relationship with any of the four financial indicators in Malaysia. The GMM results show that population density has a negative relationship with the all four financial indicators; however, in case of M2, this relationship is insignificant to explain their result. Cereal production has a positive relationship with the DCPC, while there is a negative relationship with the CPI. Livestock production exerts the positive relationship with the all four financial indicators; however, this relationship with the CPI has a more elastic relationship, while the remaining relationship is less elastic with the three financial indicators in a country. Energy resources comprise energy use and fossil fuel energy consumption, both have distinct results with the financial indicators, as energy demand have a positive and significant relationship with the DCFC, DCPC, and CPI, while fossil fuel energy consumption have a negative relationship with these three financial indicators. The results of the study are of value to both environmentalists and policy makers.
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.
The objective of this paper is to examine the dynamic impact of urbanization, economic growth, energy consumption, and trade openness on CO 2 emissions in Nigeria based on autoregressive distributed lags (ARDL) approach for the period of 1971-2011. The result shows that variables were cointegrated as null hypothesis was rejected at 1 % level of significance. The coefficients of long-run result reveal that urbanization does not have any significant impact on CO 2 emissions in Nigeria, economic growth, and energy consumption has a positive and significant impact on CO 2 emissions. However, trade openness has negative and significant impact on CO 2 emissions. Consumption of energy is among the main determinant of CO 2 emissions which is directly linked to the level of income. Despite the high level of urbanization in the country, consumption of energy still remains low due to lower income of the majority populace and this might be among the reasons why urbanization does not influence emissions of CO 2 in the country. Initiating more open economy policies will be welcoming in the Nigerian economy as the openness leads to the reduction of pollutants from the environment particularly CO 2 emissions which is the major gases that deteriorate physical environment.
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 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.
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.
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's main goal is to evaluate how the research will look at the impact of geothermal energy production on the quality of the subterranean in the 27 European nations from 1990 to 2021. A considerable decline in the subterranean water supply can occur in EU14 emerging nations employing geothermal energy growth compared to EU13 emerging economies, according to research that uses the autoregressive distributed lag (ARDL). Fossil fuel use, population growth, and economic expansion are some factors that have a more detrimental effect on the subterranean water supply in EU14 emerging economies than in EU13 emerging nations. In contrast, the study's findings indicate that EU13 emerging nations may be better able to enhance their underground water supply than EU14 emerging economies because of more effective institutional qualities. The findings so indicate that increasing the amount of geothermal energy generation among the 27 European Union countries can accelerate subsurface water degradation at a high capacity and help achieve unionism's 2030 energy-related goals. When this is achieved, climate change will be put to check, as pollution of the environment. All calculations projected were seen to be of a good level of validity, and this is ascertained through three estimators considered in this study.
The availability of natural energy resources and the environmental issues are the most significant issues that are often highlighted by the world communities. With regard to these problems, isobutanol is a higher chain alcohol with four carbons which can be derived from biomass resources and it is potential to become an alternative fuel source besides the biodiesel for a diesel engine. The aim of this study is to evaluate the effect of isobutanol with Calophyllum inophyllum methyl ester and diesel as the ternary blend on physicochemical properties, engine performance, and emission characteristics. Five different fuel blends containing Calophyllum inophyllum biodiesel and isobutanol were tested on a single-cylinder direct injection diesel engine at different engine load of brake mean effective pressure. The physicochemical properties of the fuel blends were measured and then compared with neat diesel. The results indicate that the blend containing isobutanol and CIME gives a slight increase in BSEC and EGT and a minimal drop in BTE as compared to that of neat diesel. Besides that, the tested blends show a reduction of carbon monoxide and unburned hydrocarbon emissions. Meanwhile, all the fuel blends show a minimal increase in carbon dioxide and nitrogen oxides emissions, compared to that of neat diesel. Isobutanol can be proved as a preferred substitute for biodiesel and diesel fuels to achieve desired engine performance and emissions level.
As the world's second largest palm oil producer and exporter, Malaysia could capitalize on its oil palm biomass waste for power generation. The emission factors from this renewable energy source are far lower than that of fossil fuels. This study applies an integrated carbon accounting and mitigation (INCAM) model to calculate the amount of CO2 emissions from two biomass thermal power plants. The CO2 emissions released from biomass plants utilizing empty fruit bunch (EFB) and palm oil mill effluent (POME), as alternative fuels for powering steam and gas turbines, were determined using the INCAM model. Each section emitting CO2 in the power plant, known as the carbon accounting center (CAC), was measured for its carbon profile (CP) and carbon index (CI). The carbon performance indicator (CPI) included electricity, fuel and water consumption, solid waste and waste-water generation. The carbon emission index (CEI) and carbon emission profile (CEP), based on the total monthly carbon production, were determined across the CPI. Various innovative strategies resulted in a 20%-90% reduction of CO2 emissions. The implementation of reduction strategies significantly reduced the CO2 emission levels. Based on the model, utilization of EFB and POME in the facilities could significantly reduce the CO2 emissions and increase the potential for waste to energy initiatives.
This paper presents a fresh understanding of the vigorous connection between inward FDI, renewable energy consumption, economic growth and carbon emission in the Chinese economy employing novel Morlet wavelet analysis. Wavelet correlation, continuous wavelet transform and partial and the multiple wavelet coherence analyses are applied on variables under study for data acquired during the period 1979 to 2017. The outcome of these analyses reveals that the connections among the variables progress over frequency and time. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages, although time domain reveals inconsistent associations among the considered variables. The wavelet analysis according to economic point of view supports that inward foreign direct investment (FDI) and renewable energy consumption help to enhance economic condition in Chinese economy. The results also suggested that inward FDI enhances the environmental degradation in medium and long run in China. The results emphasize the significance of having organized strategies by the policymakers to cope with huge environmental degradation occurred for a couple of decades in China.
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.