| Energy is the fundamental source for industrial,commercial,and household activities;its availability and affordability strengthen economic,social,and environmental development and make domestic life more manageable.Consequently,the importance of energy for economic development is undeniable.However,the continuous rise in energy consumption to meet energy demands for industrial,commercial,and residential sectors has significantly affected the ecological environment,thereby increasing global warming.Burning fossil fuels is mainly blamed for climate change,which has badly degraded environmental quality.The consumption of large quantities of energy at industrial and household levels has resulted in elevated pollutant emissions,including Carbon Dioxide(CO2)and other greenhouse gases.As CO2 emissions from fossil fuels have proved to be one of the most challenging and complex human activities driving climate change debates,the issue has become increasingly risky and complex for the environment.Overall,this dissertation investigates the impact of energy consumption on CO2 emissions in China,India,and USA.In this context,this study aims to analyze whether energy consumption contributes to CO2 emissions.More specifically,this dissertation uses three empirical studies to cover the nexus between energy consumption and CO2 emissions.Study 1 investigates the role of energy consumption in CO2 emissions,particularly.It investigates the impact of coal,natural gas,petroleum,and renewable energy consumption on CO2 emissions.Also,study 1 forecasts CO2 emissions trends in China,India,the USA.From the methodological perspective,study 1 uses time-series data from China,India,and USA(1980-2018)and employs Nonlinear Autoregressive Distributed Lag(NARDL)model and Machine Learning(ML)algorithms,such as;support vector machine(SVM),artificial neural network(ANN),and long-short term memory(LSTM).Considering the conceptual model of study 1,this dissertation further extends the model to empirically investigate the impact of energy consumption,Gross domestic product(GDP,population,financial development,and renewable energy consumption)on CO2 emissions.Study 2 uses panel Autoregressive Distributed Lag(ARDL)model data and investigates short-run and long-run estimates among variables.The data set covers the periods from 1980 to 2018.This study employs the FMOLS model for the more robust results to confirm the nexus between energy use,GDP,financial development,population,renewable energy consumption,and CO2 emissions.Apart from panel ARDL and Fully Modified Ordinary Least Squares(FMOLS)techniques,study 2 employs ML models to find the impact between the variables mentioned above.It is also important to note that population growth and urbanization affect energy use by industrial and technological development,which influences the environment.For instance,rapid population growth influences environmental quality,like the size of the population matters in CO2 emission.Considering population growth and increasing energy demand in urbanization,study 3 strives to assess the impact of energy use,energy intensity,energy consumption per capita,income,and population growth on CO2 emissions from 1980 to2016.In particular,this study evaluates the impact of energy use,energy intensity,energy consumption per capita,income,and population growth with their positive and negative shocks on CO2 emissions.Study three employs the NARDL model;this approach proves that fluctuations in independent variables can drive long-term asymmetric changes in the emissions of carbon dioxide.Finally,this dissertation uses an artificial neural network to explore CO2 emissions trends in China,India,and USA.The findings of this study show that energy consumption significantly increases CO2 emissions.More particularly,the results demonstrated that the positive shocks of coal consumption on CO2 emissions significantly impact CO2 emissions in the three countries.The co-efficient value of coal consumption suggests that a 1% increase in coal consumption increases CO2 emissions by 1.12% in China,1.02% in India,and 0.84% in the USA.Moreover,the findings revealed that Natural gas consumption decreases CO2 emissions in China and India and increases CO2 emissions in USA;also,Petroleum consumption increases CO2 emissions in USA.Furthermore,the findings show that GDP has a positive and significant impact on CO2 emissions,whereas population and renewable energy consumption improve environmental quality,as reported in the panel analysis of three countries.Lastly,the findings revealed that the positive shocks of energy consumption per capita on CO2 emission significantly impact CO2 emissions in China and the USA.A 1% increase in energy consumption per capita increases CO2 emissions by 1.65% in China and 1.289% in the USA.An increase in income and energy intensity increases CO2 emissions in China;in contrast,an increase in energy intensity and income decreases CO2 emissions in USA.The results in the case of India show that energy use,energy intensity,population,and income increase CO2 emissions in India.Based on the empirical analysis,this dissertation concludes that following key points.(1)Energy consumption is an effective driver of CO2 emissions,which leads to environmental degradation.The findings of the present dissertation show that energy consumption is an important determinant of CO2 emissions.It is also important to note that increasing energy consumption severely affects environmental quality.The empirical findings show that China,India,and USA are overly dependent on non-renewable energy consumption.Non-renewable energy sources to meet energy demands increases environmental degradation.The historical trend shows that mostly energy consumption in China,India and USA is filled with coal,natural gas,and petroleum.In comparison,a small volume of renewable energy consumption is used in three countries.Our empirical findings highlight that coal,natural gas,and petroleum consumption degrades environmental quality.(2)An increase in economic growth accompanies energy consumption and while energy use is dependent on non-renewable energy consumption this can be the primary source of CO2 emissions in China,India and USA.It is important to recall that China,India,and the USA are the leading energy consumer and CO2 emitters globally.This employs the goal of slashing emissions within ten years will be challenging,particularly in today’s rapid economic growth age.Therefore,it depends on government policies that can noticeably enhance the renewable energy sector and analyze the possibility of implementing carbon taxes to combat the use of non-renewable energy consumption.(3)ML algorithms indicate an increasing trend in CO2 emissions in China and India.The historical evidence of CO2 emissions in China and India suggests that CO2 has remained upward for the past few decades.Our results with ML algorithms also indicate an increasing trend in CO2 emissions in China and India.Moreover,based on econometrics and ML interpretations,the findings show that increasing energy consumption increases CO2 emissions.These findings suggest that CO2 emissions can still be a significant obstacle for China and India in the forthcoming years.(4)Renewable energy consumption improves environmental quality in China,India,and the USA.This dissertation highlights that increasing renewable energy consumption can decrease CO2 emissions.Renewable energy sources are not burnt like fossil fuels;therefore,these fuels are eco-friendly and reliable for the environment.China,India,and the USA are the future renewable leaders.Enhancing renewable energy consumption across China,India,and the USA can address major environmental obstacles.(5)The increasing population significantly and positively impacts CO2 emissions in India.India’s population is ranked second highest globally.It is estimated that the country will surpass China in terms of population in the next decade.It is understood that population has a direct association with energy consumption,leading to the growth in demand for energy.However,reducing the population is not the only solution to combat environmental challenges.India also needs to accelerate clean energy fuels.(6)Energy consumption is crucial to economic development;however,producing goods and services with contaminated fuels will increase environmental concerns.In the last few decades,manufacturing industries,mainly cement and steel production in China,India,and the USA,have significantly increased.Fuels used in traditional kilns include petroleum coke,coal,oil,and natural gas.Therefore,it is very important to note that China,India,USA,and other economies overly dependent on non-renewable energy consumption and contaminated fuels must strike a balance between energy sources(to produce the products)and the environment.(7)The reduction in CO2 emissions is dependent on rigorous government policies.USA’s and China’s economy is growing faster than India’s;however,this growth is mainly dependent on energy consumption.Increasing renewable energy consumption can improve environmental quality without sacrificing economic development.It is apparent that there is a significant swap between renewable and non-renewable energy consumption,which becomes one of the main reasons why governments should choose clean energy sources.It depends on government policies that can noticeably enhance the renewable energy sector and analyze the possibility of implementing carbon taxes to combat the use of non-renewable energy consumption.The contribution of this study lies in the following:(1)A new research perspective: This unique study advances in energy research and makes important theoretical and empirical contributions to the existing literature.Despite the wide range of existing studies on the association between energy consumption and CO2 emissions,the existing studies lack the effect of coal consumption,natural gas consumption,and petroleum consumption on CO2 emissions.For instance,the majority of the existing studies discuss the impact of energy consumption on CO2 emissions;however,the findings are limited on the depth analysis of energy consumption,particularly,the association between coal,petroleum,natural gas,renewable energy consumption and CO2 emission.This dissertation puts energy use as a key influence factor of environmental quality to examine its impact on CO2 emission in the case of China,India,and USA,the countries responsible for half of the world’s environmental quality.Besides,most existing studies either cover the impact of non-renewable energy consumption or renewable energy consumption on CO2 emission and only provide the statistical association between these variables.In contrast,this study thoroughly investigates the role of energy consumption and the impact of non-renewable and renewable energy on CO2 emissions.And finally distinguishes the contribution of renewable energy consumption to environmental quality.(2)New empirical studies: Since most of the existing studies have identified the association between energy consumption and CO2 emission;however,the existing studies lack a detailed analysis of the association between energy consumption and CO2 emission influenced by income,GDP,and growing population.China,India,and USA are developing,emerging and developed economies.A rise in income,growth in urbanization,and industrialization will subsequently increase energy demand.Furthermore,most of the existing studies on the relationship between energy consumption and CO2 emissions have neglected to comprehensively assess the future trend of CO2 emissions in light of the current energy consumption trends.On the other hand,the historical energy consumption and CO2 emission trend suggest that these countries use a large volume of energy with fossil fuels,whereas the CO2 emission trend has remained upward for many years in China and India.This study contributes to analyzing the forthcoming CO2 emission trend in China,India,and the USA and distinguishes whether increasing energy consumption,GDP,energy consumption per capita,income,and population growth contributes to or reduces CO2 emissions.Accordingly,the study suggests policies to overcome environmental issues.(3)Advanced methodological approaches: An in-depth causality assessment is performed using a new method of data testing derived from the concept of artificial intelligence that allows for the complete analysis of any data.The combination of both econometrics and machine learning techniques further strengthen the comprehensive analysis on the association between energy consumption and CO2 emissions,also provides robust analysis of future trend of CO2 emissions.This call advanced strategy devoted to energy and environment topics.This dissertation will help out the policymakers and governments in many ways.First,this study thoroughly investigates the association between energy consumption and CO2 emissions.The results based on empirical findings will not only benefit China,India,and USA to revise their policies,but also our findings can help other countries that are dependent on non-renewable energy consumption,particularly coal,natural gas,and petroleum.USA and China are the economically strong countries,whereas China and India are the most populous countries globally;therefore,at the current stage,this study is very useful for examining the impact of energy consumption on CO2 emissions along with the demographic and economic indicators.In this context,this study provides important implications to the government and policymakers in the decision-making. |
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