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This study aims to examine the asymmetric and long‐run effects of energy productivity on the quality of the environment in Sweden. It covers the time series data from 1990Q1 to 2019Q4. Sweden was the first country in 1972 to host a United Nations conference on the environment. Unlike other countries in Europe, Sweden is cognizant of an innovative environment; it hopes to achieve 100% of its electricity from renewable sources by 2040 and lead the way towards a low‐carbon community. The novelty of this study lies in the thorough analysis of how energy productivity affects the quality of the environment in Sweden while controlling for economic growth, trade openness, and financial development utilizing the non‐linear ARDL approach and other robust econometric techniques. Precisely, (i) results indicate non‐linear and asymmetric effects of the variables over long‐term horizons; (ii) energy productivity benefits the environment by lowering CO2 emissions (CO2E) in the long term; (iii) a growth in trade openness positively impacts CO2E; (iv) an increase in financial development and economic growth without eco‐friendly protocols contribute to an increase in CO2E. The findings of this study support the economic theory that energy productivity can stimulate green living and green economic growth. We recommend that policymakers in Sweden invest in energy productivity, pursue R&D that embraces cleaner technologies, and prioritize cleaner, cross‐cutting eco‐friendly policies to combat climate challenges and achieve the long‐term climate policy goals of the EU. [ABSTRACT FROM AUTHOR]

[Display omitted] • The determinants of CO2-related atmospheric pollution in India are assessed. • A composite CO2-related atmospheric pollution index is introduced. • Economic and social globalization stimulate atmospheric pollution. • The renewable energy consumption-atmospheric pollution nexus is inverted U-shaped. • Agricultural output expansion triggers more atmospheric pollution. • More urbanization and population density worsen atmospheric pollution levels. 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. [ABSTRACT FROM AUTHOR]

Despite Portugal's effort to reduce carbon emissions, the country still emits about 1.6% of the European Union's CO2 emissions. Meanwhile, limited empirical studies have been undertaken in the context of Portugal. As a result, this study examines the asymmetric and long-term impact of CO2 intensity of GDP, energy consumption, renewable energy and economic growth on CO2 emissions in Portugal from 1990 to 2019. The nonlinear autoregressive distributed lag (NARDL) is employed to uncover the asymmetric connection. The findings show that there is nonlinear cointegration among the variables. The long-run estimation reveals a positive change in energy consumption positively affects CO2 emissions, while a negative shock in energy consumption has a neutral effect on CO2 emissions. Furthermore, positive shocks of economic growth and CO2 intensity of GDP enhance environmental deterioration by increasing CO2 emissions. Meanwhile, the negative shock of these regressors positively impacts CO2 emissions. In addition, positive shocks in renewable energy enhance environmental quality, while negative shocks in renewable energy increase environmental deterioration in Portugal. Policymakers should focus on reducing per-unit energy usage and CO2 efficiency gains, which would necessitate a significant reduction in CO2 intensity and energy density of GDP. [ABSTRACT FROM AUTHOR]

Graphical presentation of the NARDL estimator. [Display omitted] • The asymmetric effect of financial stability on environmental quality in Iceland is examined. • Fourier ADL cointegration and non-linear ARDL tests are used. • Financial stability has a negative effect on environmental degradation in Iceland. • Economic growth and energy usage cause to increase carbon emissions. In the last decade, the CO 2 emissions in Iceland continues to relatively decrease; simultaneously, the country has been one of the highly financially stable country in the world. However, Iceland has higher per-capita CO 2 emissions than several other European nations. As a result, the major question arising is, "what are the environmental effect of financial stability in Iceland?" This research scrutinizes the asymmetric effect of financial stability on CO 2 emissions in Iceland. Using the quarterly dataset that span from 1995 to 2019. We employ the nonlinear ARDL and Fourier-based approach to uncover these asymmetric interconnections. The empirical findings of non-linear bound test and Fourier-based approach uncover the evident of cointegration between CO 2 emissions and financial stability and other exogenous variables (such as income, energy use, and trade openness). The outcomes of the NARDL showed that a positive variation in financial stability mitigates CO 2 emissions, whereas negative variation has a neutral impact on CO 2 emissions. Furthermore, the result of other exogenous variables suggested that a positive change in energy use have an increased effects on CO 2 emissions while a negative variation in energy use have mitigating effects on CO 2 emissions. Also, Positive variation in income triggers CO 2 emissions, but a negative variation in income has a neutral effect CO 2 emission. Conversely, a negative variation in trade openness have increased effects on CO 2 emissions, while a positive change in mitigating effects on CO 2 emissions. The Fully modified ordinary least square and Dynamic ordinary least square estimators reveal that energy use and income level increase CO 2 emissions, while trade openness and financial stability mitigate CO 2 emissions. Policymakers in Iceland should focus their significant efforts on enhancing financial stability to encourage environmental innovation, investment, and technology by reducing the negative effect of financial stability. Furthermore, strengthening the trade liberalization policies toward the flow of green goods and services extends the environmental impacts of trade openness in Iceland. [ABSTRACT FROM AUTHOR]

Many European nations, including Spain, are having difficulties achieving their Sustainable Development Goals (SDGs) objectives. Resultantly, the current research discusses the development of an SDG framework for Spain, which can be utilized as a model for other EU nations. This research examines whether GDP growth, technological innovation, and energy sources (renewable and non-renewable) have any effect on CO2 emissions utilizing data from 1980 to 2018. The study applied the non-linear ARDL (NARDL) to investigate these interrelations. The outcomes from the NARDL revealed that positive (negative) shocks in renewable energy improve environmental quality in Spain. Furthermore, positive (negative) shocks in technological innovation lead to a decrease (increase) in CO2. Lastly, positive (negative) shocks in energy consumption lead to an increase (decrease) in CO2. The results reveal that Spain is on the right path towards decarburization. This research has important policy ramifications for the policymakers and government of Spain as well as neighbouring countries. [ABSTRACT FROM AUTHOR]

Environmental sustainability is a pressing global concern that demands urgent attention from policymakers and researchers. The objective of our research is to investigate the influence of economic policy uncertainty (determined by the world uncertainty index) and financial development on carbon emissions, followed by green technological innovation, institutional quality, economic growth, foreign direct investment, energy consumption, and trade in Organization of Economic Co-operation and Development, for the period 2003-2019, to analyse the data, the second-generation econometric techniques are used. We applied the two-stage sequential techniques of the linear panel data model and generalised method of moments approach to tackle the endogeneity problem and report robust findings. The findings of the study revealed that economic policy uncertainty, financial development, economic growth, energy consumption, and trade decrease environmental quality by increasing CO2 emissions, while green technological innovation and institutional quality increase environmental degradation by reducing CO2 emissions. Our evidence-based study provides significant outcomes for green technological innovation and institutional quality conditioning's role in reducing carbon emissions in OECD economies. [ABSTRACT FROM AUTHOR]

Countries encounter conflicting policy options in reaching fast development goals due to high resource use, rapid economic expansion, and environmental degradation. Thus, the present research examined the connection between CO2 emissions and urbanization, globalization, hydroelectricity, and economic expansion in China utilizing data spanning the period between 1985 and 2018. The novel quantile-on-quantile (QQ) and quantile regression (QR) approaches were applied to assess this interconnection. The QQ approach is characterized by its ability to incorporate quantile regression fundamentals and non-parametric estimation research. As a result, the method appears to transform the quantile of one parameter into another. The QQ outcomes revealed that in all quantiles (0.1–0.95), gross domestic product (GDP), urbanization, and globalization trigger CO2 emissions in China, while in each quantile (0.1–0.985), hydroelectricity consumption mitigates CO2 emissions. The QR outcomes also affirmed the outcomes of the QQ regression estimates. Policies are suggested based on these findings. [ABSTRACT FROM AUTHOR]

Environmental degradation stemming from the combustion of conventional energy sources is not only a major factor behind climate change but it also poses an adverse impact on human health. Undoubtedly, fossil fuels are major drivers of economic growth; however, their detrimental environmental impacts are of global concern. In the literature, there is no comprehensive empirical evidence on the linkage between the use of different energy sources and carbon dioxide emissions in the context of Russia, a nation that is ranked third in the list of the top carbon dioxide-emitting global countries. Hence, this paper aims to scrutinize the relationships between oil consumption, natural gas consumption, coal consumption, and carbon dioxide emissions controlling economic growth for Russia over the 1990–2016 period. The findings from the econometric analysis indicate that carbon dioxide emissions in Russia have long-run associations with economic growth and consumption of oil, gas, and coal. The long-run elasticity estimates reveal that economic growth is not directly harming Russia's environmental quality. However, higher oil, gas, and coal consumption degrades environmental quality by boosting the level of carbon dioxide emissions in Russia. In addition, the results from the Granger causality analysis confirm the existence of both long and short-term causal connections among the variables of concern. In line with these findings, several policy recommendations to address the environmental challenges in Russia are put forward. [ABSTRACT FROM AUTHOR]

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On the role of financial inclusion in terms of promoting a sustainable environment, very limited number of studies are available in the existing literature. These studies do not directly address or link financial inclusion with carbon dioxide emissions. Therefore, this study aims to specifically investigate the effects of financial inclusion on carbon dioxide emissions along with the role of globalization and renewable electricity generation for the case of the emerging seven economies over the 2004–2016 period. This study uses panel quantile regression analysis for estimations, which takes into account the non‐normality issue of the data. The long‐run relationships among carbon dioxide emissions, financial inclusion, renewable electricity generation, globalization, and economic growth are confirmed by Kao and Johansen panel cointegration tests. Besides, the results from quantile regression analysis confirmed that financial inclusion is linked with carbon dioxide emission reductions at the 25th and 50th quantiles; however, it cannot explain the variations in the carbon dioxide emission levels at the 75th and 95th quantiles. Moreover, globalization and renewable energy electricity are found to curb carbon dioxide emissions at all quantiles. Further, the results confirmed the EKC hypothesis for E7 countries at all the quantiles. In line with these findings, this study recommends enhancing financial inclusivity, promoting globalization, elevating renewable electricity generation capacities, and ensuring greener economic growth to lower down the carbon dioxide emission levels across the E7 countries. [ABSTRACT FROM AUTHOR]

To minimize the awful situation confronting the entire globe, the global warming danger has raised the intensity of consciousness from all areas of life. Therefore, the research assesses the impact of CO2 emissions and energy use on economic performance and considers trade openness, urbanization, and agriculture in Indonesia utilizing data covering the period from 1965 to 2019. The current research employed the dynamic ordinary least square (DOLS) and autoregressive distributed lag (ARDL) tests to capture the long-run association between these economic indicators. Furthermore, the gradual shift and wavelet coherence tests are utilized to capture the direction of causality. The ARDL bound test discloses a long-run interconnection among the variables of interest. The outcomes of the ARDL and DOLS depict that CO2 emissions, agriculture, energy use, and urbanization trigger economic growth. Moreover, the wavelet coherence test findings revealed a positive correlation between economic growth and urbanization, CO2 emissions, agriculture, and energy consumption. Furthermore, there is evidence of a weak and positive correlation between economic growth and trade openness. The gradual shift causality test outcomes disclosed that economic growth can predict urbanization and energy consumption, while agriculture can predict economic growth. These outcomes have far-reaching significance for economic growth and the selected variables in Indonesia. [ABSTRACT FROM AUTHOR]

This paper aims to investigate coal consumption and environmental sustainability in South Africa by examining the role of financial development and globalization by using a dataset covering the period from 1980 to 2017. The study utilized the Auto-regressive Distributed Lag Model (ARDL) approach in addition to the Bayer and Hank combined co-integration, fully modified Ordinary least squares (FMOLS), and Dynamic ordinary least Squares (DOLS). The study further utilized the frequency domain causality test to capture the causal linkage between the series. The advantage of the frequency domain causality is that it can capture causal linkages between series at different periods. The Bayer and Hanck co-integration and ARDL bounds tests reveal co-integration among the series. The empirical findings based on the ARDL long-run estimation reveal that a 1% increase in coal consumption increases environmental degradation by 1.077%, while a 1% increase in financial development decreases the environmental degradation by 0.973%. Furthermore, a 1% increase in economic growth decreases environmental quality by 1.449%. The outcomes of the FMOLS and DOLS approaches also provide supportive evidence for the ARDL long-run results. Furthermore, the results of the frequency domain causality test reveal that at a significance level of 1%, coal consumption Granger causes CO2 emissions at different frequencies, while financial development Granger causes CO2 emissions in the long run and short run at a significance level of 10%. In terms of policy suggestions, South Africa should embrace policies that encourage energy consumers to shift toward renewable energy. Furthermore, financial reforms should be implemented to curb environmental degradation. [ABSTRACT FROM AUTHOR]

Following the United Nations Sustainable Development Goals (UN-SDGs), which place emphasis on relevant concerns that encompass access to energy (SDG-7) and sustainable development (SDG-8), this research intends to re-examine the relationship between urbanization, CO2 emissions, gross capital formation, energy use, and economic growth in South Korea, which has not yet been assessed using recent econometric techniques, based on data covering the period between 1965 and 2019. The present study utilized the autoregressive distributed lag (ARDL), dynamic ordinary least square (DOLS), and fully modified ordinary least squares (FMOLS) methods, while the gradual shift and wavelet coherence techniques are utilized to determine the direction of the causality. The ARDL bounds test reveals a long-run linkage between the variables of interest. Empirical evidence shows that CO2 emissions trigger economic growth. Thus, based on increasing environmental awareness across the globe, it is necessary to change the energy mix in South Korea to renewables to enable the use of sustainable energy sources and establish an environmentally sustainable ecosystem. Moreover, the energy-induced growth hypothesis is validated. This result is supported by the causality analysis, which shows a one-way causality running from energy consumption to GDP in South Korea. This suggests that South Korea cannot embark on conservative energy policies, as such actions will damage economic progress. Additionally, a unidirectional causality is seen from CO2 emissions and energy consumption to economic growth. These findings have far-reaching consequences for GDP growth and macroeconomic indicators in South Korea. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relationship between CO2 emissions in China and its prospective determinants, namely economic growth, globalization, financial development, and natural resources during the period from 1980 to 2017. We present more detailed analyses across multiple econometric approaches within a multivariate system, e.g., the Bayer‐Hanck combined cointegration approach, the ARDL bounds test approach, ARDL estimates in short run and long run, robustness check by cointegration regressions (i.e., FMOLS, DOLS, CCR), and Granger causality approach in the frequency domain. Our results show that economic growth and natural resources have a positive impact on CO2 emissions in China, although globalization contributes to improving its environmental quality. Meanwhile, there is no statistical evidence that CO2 emissions in China could be affected by financial development. The causality analysis reveals that globalization, economic growth and natural resources all lead to CO2 emissions in the long run, while financial development only causes the short‐run CO2 emissions, which further demonstrate our findings. Such findings are meaningful for policymakers to achieve the sustainable development in China. [ABSTRACT FROM AUTHOR]

This study aims to investigate the long-run and causal effects of energy consumption, economic growth, urbanization, and trade openness on CO2 emissions in Turkey using newly developed econometric techniques. To our best knowledge, there has been no study examining the relationship between CO2 emissions, energy consumption, trade openness, urbanization, and economic growth in Turkey. Therefore, this study proposes to fill this gap in the literature. In this study, we use time series data covering the years between 1960 and 2015. To capture long-run effects, we used ARDL, FMOLS, and DOLS estimators, while wavelet coherence technique is used to explore causal effects among the variables. Our results reveal that (i) there is a long-run equilibrium relationship between CO2 emissions and energy consumption, economic growth, urbanization, and trade openness; (ii) in the long-run, CO2 emission in Turkey is significantly triggered by energy consumption, economic growth, and urbanization; and (iii) the results of the wavelet coherence-based causality test provide supportive evidence to the long-run estimations of this study. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric and long-run effect of energy productivity on the quality of the environment in Finland. Finland, as one of the Nordic countries, is a major contributor to the global drive to achieve decarbonization by 2050. In effect, this study seeks to contribute to the strides by querying the extent to which shocks in energy productivity make or mar the sustainability of the Finland environment from 1990:Q1 to 2019:Q4. The other impacts of financial development, economic growth, and trade openness are considered in the model estimated by using the novel hidden panel cointegration and nonlinear autoregressive distributed lag (NARDL) methodology. The results reveal a significant asymmetric equilibrium cointegration relationship among the variables over long-run time horizons; energy productivity utilization enhances the quality of the environment in Finland over the long run while trade openness, financial development, and economic growth contribute to environmental degradation in Finland in the long term. In particular, a 1% positive and negative fluctuation in energy productivity lowers carbon emissions by 1.79442% and 0.84799% in the long term. Whereas 1% change in trade openness, financial development, and economic growth trigger CO 2 emissions (CO 2 E) by 1.15298%, 0.271365%, and 2.93402% in Finland's economies. The results of the frequency domain causality model corroborate the NARDL results. On the basis of these empirical findings, this study suggests that policymakers in Finland should consider the asymmetric behavior among these variables in setting their trade, environmental, growth, and energy policies. [Display omitted] • The effect of energy productivity on environmental degradation in Finland is examined. • Nonlinear ARDL, Fourier ADL cointegration and frequnecy domain causality tests are employed. • Energy productivity leads to lower environmental degradation in Finland. • Energy productivity causes environmental sustainability at different frequencies. [ABSTRACT FROM AUTHOR]

This empirical study assesses the effect of CO2 emissions, urbanization, energy consumption, and agriculture on Thailand's economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO2 emissions positively trigger Thailand's economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO2 emissions, urbanization, energy consumption, and agriculture can predict Thailand's economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand's macroeconomic indicators. [ABSTRACT FROM AUTHOR]

It is widely accepted that CO2 emissions are the primary cause of climate change and environmental destruction. China, the world's biggest carbon emitter, is the subject of this research. Utilizing the wavelet tools (wavelet correlation, wavelet coherence, multiple wavelet coherence, and partial wavelet coherence), the present study intends to capture the time-frequency dependence between CO2 emissions and renewable energy, economic growth, trade openness, and energy usage in China between 1965 and 2019. The advantage of the wavelet tools is that they can differentiate between short, medium, and long-run dynamics over the period of study. Furthermore, the study utilized the gradual shift causality test to capture the causal interconnection between CO2 emissions and the regressors. The findings from Bayer and Hanck showed a long-run relationship among the variables of interest. Furthermore, the findings from the wavelet coherence test revealed a positive relationship between CO2 emissions and economic growth and energy usage at all frequencies. Although there is a weak negative relationship between renewable energy and CO2 emissions in the short run, there is no significant co-movement between CO2 emissions and trade openness. The outcomes of the partial and multiple wavelet coherence also give credence to the outcomes of the wavelet coherence test. Lastly, the gradual shift causality test revealed a one-way causality from energy usage and economic growth to CO2 emissions. Based on the findings, suitable policy suggestions were proposed. [ABSTRACT FROM AUTHOR]

The recent historical increase in energy-related CO 2 emissions globally have put the United States of America's (USA) transportation sector in the spotlight, courtesy of the significantly high pollutant emissions from this particular sector. Taking a cue from this, this paper follows sustainable development goals of the United Nations, and investigates the impact of biomass energy consumption, fossil fuel energy consumption, and economic growth (GDP) on carbon dioxide (CO 2) emissions in the transportation sector of the USA. In doing so, this study also employs the Gregory-Hansen cointegration, Hatemi-J cointegration, cointegration regression (FMOLS, DOLS, and CCR), and Spectral Breitung-Candelon causality test for the period between 1981Q1 and 2019Q4. The findings reveal that (i) a significant nonlinear cointegration among the environmental quality determinants is observed, using the threshold cointegration test. This test determines the structural breaks endogenously and combines two cointegration tests, namely the Gregory-Hansen Cointegration and Hatemi-J Cointegration tests; (ii) while the use of biomass energy consumption and real GDP have a negative effect on CO 2 emissions in the transportation sector, the rising fossil fuel energy consumption is associated with increasing the CO 2 emissions that are stemming from the transportation sector; (iii) in the long-run, biomass energy consumption, fossil fuel energy consumption, and real GDP cause CO 2 emissions to stem from the transportation sector in the USA at different frequency levels. In general, the current study offers policy insights for the transportation sector of the USA and other similar economies that replicate the same conditions. Image 1 • We explore the driving forces of CO 2 emissions in the transport sector for the USA. • We employ advanced time series econometric techniques for empirical analysis. • Biomass energy and real GDP help to mitigate CO 2 emissions in the transport sector. • Fossil fuel energy has a positive impact on CO 2 emissions in the transport sector. • All variables have a causative relationship with CO 2 emissions in the long-run. [ABSTRACT FROM AUTHOR]

The purpose of the present study is to explain the long-run and causal effects of innovation, financial development, and transportation infrastructure on CO 2 emissions using the combined cointegration and wavelet coherence approaches over the period from 1971 to 2018 , while using economic growth as a control variable in the model. The outcomes of the Bayer-Hanck cointegration test show that there is an important cointegration equation among CO 2 emissions, innovation, financial development, transportation infrastructure, and real GDP. Moreover, the findings from a wavelet power spectrum reveal that there is a significant vulnerability in innovation, financial development, transportation infrastructure, and CO 2 emissions at different time frames and frequencies. Furthermore, the outcomes of wavelet coherence approach reveal that (i) Innovation is observed as a significant predictor of CO 2 emissions over the period from 2007 to 2013; (ii) In the long run, there are negative correlations between CO 2 emissions and financial development; (iii) Over the periods from 2000 to 2015, and from 1985 to 1989, transportation significantly causes CO 2 emissions. Our findings have substantial policy implications that suggest there is a need to strengthen innovation and transportation infrastructure to achieve environmental sustainability targets. • This study examines the determinants of CO 2 emissions in China following COP21. • This study employs Bayer-Hanck cointegration and wavelet coherence approaches. • Transportation and innovation significantly cause CO 2 emissions in the long run. • There is negative correlation between CO 2 emissions and financial development. [ABSTRACT FROM AUTHOR]

The United Nations' "Sustainable Development Goals" (SDGs) express attention to climate action. Even though a considerable number of papers have targeted this issue, the literature on the top five, "China, India, Japan, Russia, and the United States" economies is uncommon. Therefore, this paper is targeted to examine the influence of renewable energy (RE), environmental technologies (ETs), and economic policy uncertainty (EPU) on carbon emissions. By using the most recent data available from 1992 to 2020, results are estimated with robust econometric techniques, i. e. "cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and augmented mean group (AMG)". Findings reflect the harmful role of EPU. However, RE and ETs have a supportive role in the transition towards a sustainable environment. The findings are also strong in terms of policy implications for the top five polluters. • Renewable Energy, Economic policy uncertainty, Environment-related technologies, and CO 2 emissions' nexus is empirically investigated. • CSD-test, CADF, CIPS, Westerlund co-integration, AMG, and CS-ARDL estimations are applied. • ERT and RE are found as a supportive for a sustainable environment. • Economic policy uncertainty is deteriorating the environment. [ABSTRACT FROM AUTHOR]

Carbon neutrality target is of great importance to all countries around the globe recently. Innovative methods are being evaluated to achieve the environmental sustainability. In this study, we aim to inspect the influence of public-private partnership in energy and energy efficiency on CO 2 emissions in China from 1991Q1 to 2017Q4. In doing so, we include other important determinants of CO 2 emissions also, such as environmental innovation, renewable energy, energy productivity and economic growth in our model. We employ the advanced cointegration methods that are developed recently. Moreover, spectral Breitung and Candelon (BC) causality test is used to find the causal effects of technological innovation, energy productivity, public-private partnership in energy, renewable energy consumption and GDP on CO 2 emissions. The results suggest that increase in income and public-private partnership enhance carbon emission in China. Conversely, an improvement in energy productivity, renewable energy and technological innovation exert negative influence over CO 2 emissions. There is a need to improve the efficiency of public-private partnership in energy projects in terms of carbon emission. Policymakers in China need to ensure an effective and timely transition towards renewable energy sources through environment related innovations and improved efficiency in all sources of energy. • Influence of energy productivity and public-private investments in energy over carbon neutrality targets is investigated. • The data is used for China from 1991Q 1 to 2017Q 4. • Income and public-private energy investments increase emissions. • Energy productivity, innovation and renewable energy limit emissions. • Energy efficiency and eco-innovation are crucial for China. [ABSTRACT FROM AUTHOR]