CO2 Emissions In India Research Articles

Unlocking the impact of international financial support to infrastructure, energy efficiency, and ICT on CO2 emissions in India

Financial resource constraints prevent developing nations from investing in the infrastructure needed for the green transition. For this reason, it is well known that numerous financial aid programs are offered globally, mainly to wealthy developing nations whose economies are predicated on high energy consumption. It hasn't been looked into if these resources are allocated to worthwhile projects. This study examines how foreign financial assistance in this area affects India's infrastructure emissions. The effects of natural resources, economic growth, information and communication technology, energy efficiency (oil and gas), and natural resources on the environment are being investigated as well. The novel multivariate quantile on-quantile regression technique is used in this context to examine a time-series data set spanning 2000–2021. According to the findings, there is a correlation between reduced carbon emissions and increased foreign financial aid. Likewise, advancements in energy efficiency and information and communication technologies also benefit the ecosystem. However, India's emissions are rising due to its abundant natural resources and economic expansion. Policy recommendations were made regarding the need for India to use international financial aid primarily to strengthen environmentally friendly infrastructure rather than solving problems such as current account deficit or budget deficit.

Correlation between Economic Growth and Carbon Emissions in the Context of the Transition to a Zero-Carbon Economy

Abstract The energy sector is increasingly popular today and plays a vital role in our everyday lives. That is why, in this paper I am trying to analyze the existing literature and find a correlation between economic growth and carbon emissions. I utilized various scenarios for this research. The first direction is based on a study seeks to scrutinize earlier literature encompassing economic growth, energy consumption, and carbon emissions, encompassing both individual country analyses and multi-country studies spanning until the year 2019. The second one on usage of both growth and environmental functions to illustrate the efficacy of renewable energy in fostering economic growth and mitigating carbon emissions in the context of the 15 primary renewable energy-consuming nations. Exploring the impact of disaggregated energy consumption, technological innovations, and capital on economic output and CO2 emissions in India from 1990 to 2018 is the third direction, while the fourth has at its base the influence of Information and Communication Technology (ICT) on renewable energy consumption using panel data from 90 countries spanning the period 2000-2014. The fifth scenario is about the effects of climate change and technological innovation on economic growth, energy consumption, and carbon emissions by analyzing annual observations of diverse variables across Asian and European countries from 1996 to 2021. The final perspective investigates the factors influencing Energy Mix Diversification (EMD) by utilizing a panel sample encompassing seven major emerging (E7) economies—Brazil, China, India, Indonesia, Mexico, Russia, and Turkey—observed from 1995 to 2018.

Impact of battery swapping in the passenger sector: EV adoption, emissions, and energy mix

Transport sector electrification will play a critical role in achieving India's net zero emission target by 2070; however, the adoption of EVs is hindered by challenges such as long charging times, high ownership costs, and limited range. Battery swapping (BS) offers quick recharging, unlike point charging (PC). This study examines BS subscription fees in India's passenger sector (buses, four-wheelers, three-wheelers, and two-wheelers). Furthermore, the assessment of its effects on EV adoption, the energy mix, and CO2 emissions in India's passenger sector is analysed using the global change analysis model (GCAM). The results show that BS is cost-effective for four-wheelers and two-wheelers without subsidies. Providing similar subsidies to BS as to PC achieves cost parity or lower costs for three-wheelers and buses compared to PC. BS could reduce CO2 emissions by 9 % by 2070, with a 6 % increase in EV adoption and an 8 % rise in electricity demand. With BS subsidies, EV penetration may increase by 10 %, resulting in a 14 % reduction in CO2 emissions compared to PC. The study suggests BS is a viable option but may not entirely replace PC.

Asymmetric Role of Economic Growth, Globalization, Green Growth, and Renewable Energy in Achieving Environmental Sustainability

This study fills the gap in the literature by applying novel quantile regression and spectral Granger causality frameworks to evaluate the asymmetric effect of GDP, globalization, green growth, and renewable energy consumption on CO2 emissions in India. The results suggest that in all quantiles, green growth, globalization, and renewable energy consumption impact environmental quality negatively, and the effect of economic growth on CO2 emissions is positive in most of the quantiles. In addition, the nexus between the regressors and CO2 emissions is significant across different time horizons. More specifically, the results from the spectral Granger causality test unveil that all the indicators would predict CO2emissions across various time scales. Several policy implications have been proposed based on the research’s findings so that India might move toward achieving sustainable development. Doi: 10.28991/ESJ-2024-08-02-05 Full Text: PDF

How are electricity generation effective on carbon neutrality in the global south? Evidence from sectoral CO2 emissions by daily data

In light of the efforts to ensure carbon neutrality by combating climate-related problems, the study investigates the effectiveness of electricity generation (EG) from the main renewable sources (hydro-HEG, solar-SEG, and wind-WEG). In this context, the study examines the countries of the Global South (i.e., Brazil, China, and India), considers EG at a disaggregated level and sectoral CO2 emissions, applies nonlinear methods, and uses daily data between January 2, 2019 and December 31, 2022. The results demonstrate that (i) disaggregated EG sources have a stronger (weaker) time and frequency dependency on sectoral CO2 emissions in China (Brazil and India); (ii) HEG has a stimulating impact on sectoral CO2 emissions in all countries; (iii) SEG has an increasing impact on sectoral CO2 emissions in Brazil and China, while it provides a decrease in sectoral CO2 emissions in India; (iv) WEG upsurges sectoral CO2 emissions in China, while it achieves a CO2 reduction in Brazil and India; (v) disaggregated level EG has a causal impact on sectoral CO2 emissions across all quantiles except some lower, middle, and higher quantiles. The study adds scientific value to existing knowledge by analyzing for the first time which EG sources are effective in reducing daily CO2 emissions in the Global South. Based on the outcomes, the study demonstrates that WEG is the best EG source for Brazil, that SEG and WEG are optimal EG sources for India, and that China cannot benefit from the EG sources considered. In this way, the study provides fresh insights for the countries of the Global South and underlines the crucial role of renewable EG in ensuring carbon neutrality.

Assessing the nonlinear impact of economic growth and renewable energy consumption on CO2 emissions in India: recent evidence from smooth transition autoregression model

PurposeThe purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO2 emissions during the time span from 1980 to 2020.Design/methodology/approachThe study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO2 emissions in the Indian economy.FindingsThe estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO2 emissions. The authors found that economic growth positively impacts CO2 emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO2 emissions. Similarly, RE consumption positively affects CO2 emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO2 emissions.Research limitations/implicationsThe study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO2 emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO2 emissions on further economic growth.Originality/valueTo the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO2 emissions in India, using the STAR model.

Measuring the Impact of Technology Innovations and Renewable Energy Consumption for Enhancing Environmental Sustainability in India: Empirical Evidence from ARDL Approach

Rising carbon dioxide (CO2) emissions at a breakneck pace is a serious problem for sustainable development. To ensure climate-protected sustainable development, we have to promote safe and sustainable energy for the future. Here, the production and consumption of renewable energy is having a vital role. Apart from this, technological innovation is also crucial to taste the benefits of renewable energy and reduce the emission of different harmful gases. Against this backdrop, the present study intends to investigate the contribution of technological innovation along with the use of renewable energy in ensuring environmental sustainability in India using the ARDL model. Further, the Granger causality test is also performed in this study to check the direction of causality among the variables. The results of this study reveal that renewable energy consumption reduces CO2 emissions in India in both the short and long run. This means that using renewable energy would help India to bring environmental sustainability through reducing CO2 emissions. However, a positive relationship is noted between technological innovation and CO2 emissions. This may imply innovation in technology in India is unable to act as an instrument to bring environmental sustainability.

Carbon Emissions from Energy Use in India: Decomposition Analysis

To become the fastest-growing large economy in the world, India has set a target growth rate of 9%, reaching an economy of $5 trillion by 2024-25. It is an immense challenge to meet the growth target and keep the CO2 emissions under control. The present paper aims to discover the determinants for explaining CO2 emissions in India by conducting a complete decomposition analysis, where the residuals are fully distributed to the determinants for the country from 1990-2018. The analysis reveals that the biggest contributor to the rise in CO2 emissions in India is the expansion of the economy (scale effect). The intensity of CO2 and the change in the composition of the economy, which nearly move in tandem, also contribute to the rise in CO2 emissions, although more slowly. A declining energy intensity of the Indian economy is responsible for a considerable reduction in CO2 emissions. As a typical result for an upcoming economy, this paper did not find evidence for an environmental Kuznets curve. This implies that continued economic growth will lead to increased CO2 emissions.

A multi-region analysis on drivers of energy related CO2 emissions in India from 2013 to 2021

As the world's most populous country and the second largest emerging economy, India has become the third largest CO2 emitter in the world for many years. While India has proposed to achieve carbon neutrality target by 2070, previous studies have not systematically investigated factors that influence national and regional CO2 emissions. Thus, we decompose energy related CO2 emissions at national and regional levels based on the panel data of 32 states during the period 2013–2021 using Logarithmic Mean Divisibility Index (LMDI) method and disclose the different driving mechanisms of energy related CO2 emissions across five regions in India. Results show that, the economic output effect majorly promotes national and regional energy related CO2 emissions, followed by the energy structure effect and the population size effect. However, the energy intensity effect and industrial structure effect obviously inhibit national and regional CO2 emissions. Additionally, the population distribution effect inhibits energy related CO2 emissions at the national level (−4.67%), while this effect on regional emissions varies. For instance, the population distribution effect promotes energy related CO2 emissions in the densely populated northern and western regions (2.04% and 0.12%, respectively), but inhibits emissions in the sparsely populated southern, eastern, and northeastern regions (−33.97%, −8.15% and − 1.18%, respectively). Our results suggest that formulation of appropriate economic and population growth plan specifically for India's northern and western states as well as improvements of national and regional industrial structure and energy use structure would be needed.

Time-varying impact of income and fossil fuel consumption on CO2 emissions in India.

This paper investigates the time-varying effects of fossil fuel consumption on CO2 emissions in India utilizing the time-varying cointegration test, allowing for multivariate long-run time-varying cointegration parameter developed by Bierens and Martins (2010) and the time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005). The long-run time-varying coefficients reveal that GDP has a positive and increasing impact on CO2 emissions over time. Moreover, results confirm the polluting effects of all fossil fuels. Besides, the TVP-VAR model findings also demonstrate that changes in income and fossil fuel consumption have a positive and significant impact on environmental degradation. Coal is found to be the most polluting fuel, followed by oil consumption. Furthermore, the time-varying responses show that increased natural gas consumption has the least influence when compared to other fossil fuels on CO2 emissions.

Political competition and environment quality: a study of India.

The focus of sustainable development goals (SDGs) is to promote the use of renewable energy so that countries can achieve better environmental quality. However, the progression is plodding, and still, 80% of energy comes mainly from conventional sources in developing countries. The implementation of procedures depends on the political attitudes, political stability, and quality of institutions. India has a diverse political structure ranging from central government to state government to local governments. In the late '80s, India witnessed a stiff rise in regional and national political parties, which leads more political competition. This paper tries to explain the possible relationship between political competition and CO2 emission in India. With the application of the time series non-linear ARDL (NARDL) model, this study tries to find the asymmetric relationship between political competition and CO2 emission. In our empirical model, we also include other important elements of environmental quality like innovation and fossil fuel consumption. Empirical results show that political competition is asymmetrically related to CO2 emissions in the long run. Fossil fuel consumption and innovation also have a significant relationship with emissions. Based on the results, a few policy recommendations have been discussed.

Is fiscal deficit ‘curse’ or ‘haven’ for environmental quality in India? Empirical investigation employing battery of distinct ARDL approaches

Undoubtedly, throughout the past half-century, environmental quality has emerged as a significant obstacle to both economic and social endeavors. Recent local and international policy debates have focused on environmental deterioration and global warming, but how governments balance economic growth and environmental sustainability is still enigmatic. For this reason, we have examined the determinants of environmental quality in India from 1972 to 2021. More specifically, we have investigated whether the fiscal deficit is ‘curse’ or ‘haven’ for environmental quality (CO2) in India. Moreover, this study deliberated four other predictors, comprising technological development (TIN), fossil fuel consumption (FFC), urbanization (Ub), and human capital index (HCI). In order to attain this objective, a range of econometric estimation techniques are employed to ensure the validity and reliability of the outcomes. For instance, we have employed a battery of ARDL approaches, such as standard ARDL, nonlinear ARDL, and multiple threshold NARDL approaches. In light of our research findings, we will be focusing directly on the examination of the NARDL and MTNARDL outcomes. This is due to the empirical evidence indicating the existence of asymmetric effects resulting from FD on CO2 emissions in India. The NARDL approach reveals that the consequence of fiscal deterioration is more pronounced, and the influence of fiscal progress is mild in terms of CO2 emission growth. Further, the outcomes of the MTNARDL approach revealed that the size of the extremely low changes in FD is much higher than the extremely high changes in FD in both models. This implies that as the FD rises, CO2 ascends more significantly, and when the FD lowers, CO2 declines progressively. In a nutshell, FD has a long-run positive and asymmetric impact on CO2 in India; thus, we may conclude that FD is considered the ‘curse’ for CO2 in India. Furthermore, TIN, HCI, and Ub have detrimental effects on CO2, whereas FFC stimulates CO2 in India. This research work provides some important policy implications for environmentalists, economists and macroeconomic policymakers to promote a green and healthy environment.

The impact of financial innovation, green energy, and economic growth on transport-based CO2 emissions in India: insights from QARDL approach

The impact of financial innovation, green energy, and economic growth on transport-based CO2 emissions in India: insights from QARDL approach

Exploring the link between green energy, CO2 emissions, exchange rate and economic growth: Perspective from emerging South Asian countries

This paper investigates the nexus between renewable energy use, CO2 emissions, exchange rate, and economic development within emerging South Asian nations, namely Bangladesh, India, Pakistan, and Sri Lanka, employing the Autoregressive Distributed Lag (ARDL) framework. It examines annual data spanning from 1990 to 2019, examining key indicators of renewable energy consumption, CO2 emissions, exchange rate, and economic development. The ARDL bounds test results demonstrate the existence of co-integration among the variables in the long run. The empirical result finds that the renewable energy consumption, CO2 emissions, and exchange rate have a significant impact on economic growth in Bangladesh, Pakistan, and Sri Lanka in the long run. In India no significant relationship found in the long run. In short run assessment, Bangladesh, India, and Sri Lanka also found same relationship with economic growth and renewable energy consumption, CO2 emissions, and exchange rate. Interestingly, In Pakistan no significant relationship has found in short run estimation analysis. Furthermore, study tried to determine the causality direction by using the Toda Yamamoto granger causality approach, which reveals bidirectional causation between exchange rate and CO2 emission in India. In Pakistan, study also found bi-directional causality among the variables renewable energy consumption, CO2 emissions, and economic growth. Finally, this paper emphasizes developing the policy as well as making a concrete decision regarding the renewable energy consumption, CO2 emissions, exchange rate, and economic development for ensuring sustainable economic growth in South Asian region. Future research could extend this work by including different dimensional data, additional countries, or using alternative or supplementary modeling techniques.

Assessing the thermal performance of upcycled shipping container as a sustainable building material in a Warm humid climate

The current trends in the construction sector are responsible for majority of the CO2 emissions in India. The sustainable methods to reduce the CO2 emissions should include not just recycling but also upcycling the materials, for instance – shipping containers. Despite the industry’s best efforts to minimize waste generation, millions of shipping containers end up as scrap materials, every year. This phenomenon can be changed effectively by reusing the scrap materials as alternate building materials. The trend of reusing the shipping containers as building materials is at its peak in Western countries, while in India, it is still in a nascent stage. The aim of the current research paper is to evaluate and assess the thermal performance of upcycled shipping containers as a building material in warm humid climatic condition. This research includes a review of literature about the strengths and weaknesses of the shipping containers as a building material; it also compares and evaluates the thermal performance of uninsulated container buildings with base case conventional building and the insulated container building through Opaque simulation method. The results were obtained by comparing and assessing the thermal performance and cost of various insulating materials for a container building. The study outcomes greatly help the architects to reuse the shipping containers as a sustainable alternative building material in warm humid regions.

Carbon footprint analysis considering production activities of informal sector: The case of manufacturing industries of India

This study estimates an input-output table for India that distinguishes between the formal and informal sectors in 25 manufacturing industries to investigate the informal sector's contribution to the national carbon footprint (CO2 emissions embodied in supply chains). The proposed table reflects the differences in terms of input structure and carbon emission intensity between each industry's formal and informal sectors. The results showed that the informal sector in several industries contributed significantly to the carbon footprint of the top three supply chains with larger CO2 emissions in India. The study suggests that environmental policymakers target the informal sector and identify the actors involved in achieving CO2 emission reduction in the informal sector.

Modelling the asymmetric effects of renewable and nonrenewable energy consumption and financial development on CO2 emissions in India: Empirical findings from the NARDL and Wavelet Coherence Approach.

A major challenge for humans in the twenty-first century is devising a way to minimize environmental pollution while fostering economic growth that will not deplete the planet's resources. Despite increased awareness of climate change and efforts to combat it, the amount of pollution emissions on the Earth continues to drop significantly. This study employs cutting-edge econometric methods to examine the long- and short-term asymmetric and causal impacts of renewable and non-renewable energy consumption and financial development on CO2 emissions in India at both aggregate and disaggregated levels. Thus, this work fills a significant gap in research. A time series from 1965 to 2020 was used for this study. Wavelet coherence was employed to investigate causal effects among the variables, while the NARDL model addressed long-run and short-run asymmetry effects. Our findings indicate that (i) REC, NREC, FD, and CO2 emissions are all interconnected in the long run, (ii) NREC and FD significantly trigger CO2 emissions in India in the long run, and (iii) the results of a wavelet coherence-based causality test support the long-term estimates of this study.

The asymmetry effect of industrialization, financial development and globalization on CO2 emissions in India

This study investigates the effects of India's economic growth, industrial development, fossil fuel energy output, financial development and globalisation on CO2 emissions. Using annual time series data from 1971 to 2019, the study used Non-Linear autoregressive distributive lag (NARDL) to examine the relationship. The findings show a long-term association between CO2 emissions and other factors. While industrialization and economic expansion have a large and long-term positive impact on CO2, globalisation considerably cuts CO2 emissions. The study's findings add to the pool of knowledge by presenting fresh data on the connection between environmental factors and developmental measures. These findings are crucial for policymakers and governmental agencies to focus on economic development without endangering environmental damage. India has to enact laws that support cleaner production practises and the growth of non-polluting sectors in order to uphold its commitment to sustainability. It must also discourage CO2 emitting industries concurrently.

The impacts of globalization, renewable energy, and agriculture on CO2 emissions in India: Contextual evidence using a novel composite carbon emission-related atmospheric quality index

At the 26th Conference of Parties in Glasgow, India declared the environmental agendas of turning carbon neutral by 2070 and substantially lowering its carbon intensity level. Thus, it can be assumed that India is committed to improving its atmospheric health over the next couple of decades. Thus, strategizing plans for limiting carbon emission-related environmental pollution has gone on to become a critically important objective of the Indian government. Against this backdrop, this current study aims to examine the factors influencing atmospheric quality in India. As opposed to the previously adopted approaches in the existing studies, a composite atmospheric quality index is estimated using data concerning different carbon dioxide emission-related atmospheric quality indicators (total carbon dioxide emissions, carbon footprints, and carbon intensity levels). Furthermore, the analysis of the possible non-linear association between renewable energy use and atmospheric pollution makes an additional contribution to the environmental literature. Using quarterly frequency data from 1990q1 to 2018q4 and employing advanced econometric techniques suitable for handling structural break issues, the empirical results reveal that globalization through economic and social channels, agricultural output expansion, and greater population density trigger atmospheric pollution in the long run. Besides, the relationship between renewable energy consumption and atmospheric quality is found to exhibit an inverted U-shape. In this regard, the threshold share of renewable energy in the total final energy consumption level of India is predicted at around 45.75% which is comparatively higher than India’s current renewable energy consumption share. Furthermore, urbanization is evidenced to stimulate the deterioration of India's atmospheric quality, both in the short- and long-run. In line with these major findings, some policy-oriented recommendations are made.

Geothermal energy and carbon emissions nexus in leading geothermal-consuming nations: Evidence from nonparametric analysis

The pursuit of decarbonization has created an awareness globally in relation to geothermal energy, either for electricity generation or direct usage, since fuel combustion is not needed. Premised on this intriguing detail, this present research scrutinizes the impact of geothermal energy on CO2 emissions in the top seven geothermal energy-consuming nations. Using the quarterly dataset of geothermal and CO2 emissions stretching over the period between 1990 and 2019. The quantile-on-quantile (QQ) approach, which considers the conventional quantile analysis and nonparametric, is utilized in this research to provide more accurate and robust estimations. Furthermore, the QQ approach differentiates the impacts of geothermal energy on CO2 emissions into three quantiles: upper, medium, and lower. Additionally, the nonparametric causality-in-quantiles is used to evaluate the causation in quantiles between geothermal and CO2 emissions. From the outcomes of the QQ approach, we discovered that in several quantiles, geothermal energy mitigates environmental deterioration, wherein CO2 emission is reduced in Italy, Mexico, and New Zealand. However, geothermal energy boosts CO2 emissions in India, the USA, Turkey, and the Philippines. Furthermore, the nonparametric causality-in-quantiles discovered that geothermal energy predicts CO2 emissions in all nations.