The effect of energy R&D expenditures on CO2 emission reduction: estimation of the STIRPAT model for OECD countries

Will greenhouse gas emissions increase with mining depth in coal mines? An analysis of gas occurrence under varying in-situ stress conditions

The rapid development of the economy leads to the high demand for deep coal resources, which further poses the potential problem of deep gas (or methane) emissions. The clarification of deep gas occurrence law for coal mines provides theoretical and data support for methane emission predictions, and assists industrial and mining enterprises in planning targeted emission reduction measures. This study defined and verified the existence of a critical depth for the deep gas occurrence in coal mines based on a multiple-scale case study of how the gas occurrence is associated with depth and stress status changes in the Pingdingshan No.8 Coal Mine. In addition, 882 sets of gas content data from 7 major mining areas in China were collected and their gas content distributions among various depths were statistically analyzed to prove the universal existence of critical depth. The results show that the critical depth of Pingdingshan No.8 Coal Mine is 509 m, and the critical depth of other Chinese areas is about 400 to 1000 m. Significant differences were observed in the pore space, surface, and gas desorption characteristics for coal samples with different depths and stress states. The pore structure in the critical depth area is relatively developed, and gas is easily accumulated. The gas occurrence of both normal and abnormal gas gradually increases with the depth's increase in areas above the critical depth, whereas the gas occurrence gradually decreases for areas below the critical depth, showing that the existence of critical depth lead to significant deviations in gas emission predictions. The results provide a fundamental reference for gas emission prediction, greenhouse effect assessment, and carbon emission factor calculation and indicate that using the traditional linear method may be misleading for evaluating deep gas occurrence and emission.

How are energy transition and energy-related R&D investments effective in enabling decarbonization? Evidence from Nordic Countries by novel WLMC model

Public interest in climate change-related problems has been developing with the contribution of the recent energy crisis. Accordingly, countries have been increasing their efforts to decarbonize economies. In this context, energy transition and energy-related research and development (R&D) investments can be important strategic tools to be helpful to countries in the decarbonization of economies. Among all, Nordic countries have come to the force because of their well-known position as green economies. Hence, this study examines Nordic countries to investigate the impact of energy transition, renewable energy R&D investments (RRD), energy efficiency R&D investments (EEF) on carbon dioxide (CO2) emissions by performing wavelet local multiple correlation (WLMC) model and using data from 2000/1 to 2021/12. The outcomes reveal that (i) based on bi-variate cases, energy transition and RRD have a mixed impact on CO2 emissions in all countries across all frequencies; EEF has a declining impact on CO2 emissions in Norway (Sweden) at low and medium (very high) frequencies; (ii) according to four-variate cases, all variables have a combined increasing impact on CO2 emissions; (iii) RRD is the most influential dominant factor in all countries excluding Norway, where EEF is the pioneering one. Thus, the reach proves the varying impacts of energy transition, RRD, and EEF investments on CO2 emissions. In line with the outcomes of the novel WLMC model, various policy endeavors, such as focusing on displacement between sub-types of R&D investments, are argued to ensure the decarbonization of the economies.

Assessing the role of green investments and green innovation in ecological sustainability: From a climate action perspective on European countries

In recent years, economies have been increasingly focused on achieving the United Nations' Sustainable Development Goals, recognizing that their achievement is vital to ecological sustainability and green growth. In this context, this paper focuses on investigating the impact of green innovation, green investment, economic growth, and natural resources on ecological sustainability in the five best-performing European Union countries in terms of the Climate Change Performance Index. This study uses the load capacity factor as a comprehensive proxy of ecological sustainability and also assesses the load capacity curve hypothesis in sample nations. Continuously updated fully modified and continuously updated bias-corrected estimators are used to analyze the data from 1995 to 2020 in the context of climate action perspective. The econometric analysis revealed that the load capacity curve hypothesis is invalid in the sample countries. Natural resources decrease environmental sustainability. However, green investments and green innovations contribute to environmental quality and thereby, can be used for effective climate action. Based on these findings, the study recommends specific policies to achieve the Sustainable Development Goals, with a particular focus on target 13.

Impact of public-private partnerships investment and FDI on CO2 emissions: A study of six global investment countries

This study investigates the impact of public-private partnerships investment in energy and FDI on environmental quality in global investment countries during 1995-2018. Economic growth, technological innovations and consumption of clean energy are also considered as additional determinants of environmental quality. The study applied advanced panel econometric models. Our empirical results affirm the evidence of a long-run association between environmental quality and its determinants. Specifically, economic growth as well as clean energy use improves quality of environment by lowering carbon emissions. Public-private partnerships investment in energy, FDI and technological innovations decrease carbon emissions. Energy consumption (generated from fossil fuel) increases carbon emissions. Heterogeneous causality evidence indicates the presence of a unidirectional causality relation from carbon emissions to public-private partnerships investment in energy and a feedback causality occurs between consumption of clean energy and CO2 emissions. This empirical evidence provides new insights for both policymakers and governments to support public-private partnership investments in energy for the improvement of quality of environment in global investment countries.

Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies

There is a call for global efforts to preserve the ecological systems that can sustain economies and people's lives. However, carbon emission (CEM) threatens the sustainability of humanity and ecological systems. This analysis looked into the influence of energy use (ERU), human capital (HCI), trade openness (TOP), natural resource (NRR), population, and economic growth (ENG) on CEM. The paper gathered panel data from the Central Asia region from 1990 to 2020. The CS-ARDL was applied to establish the long-term interaction among the indicators. The paper's findings indicated the presence of the environmental Kuznets curve (EKC) in the Central Asia regions. Also, the empirical evidence highlighted that energy use, natural resources, and trade openness cause higher levels of CEM. However, the research verified that CEM can be improved through human capital and urban population growth. The study also found that HCI moderates the interaction between NRR and CEM. The causality assessment indicated a one-way interplay between ENG, ERU, NRR, and CEM. The study proposes that to support ecological stability in these regions, policy-makers should concentrate on developing human capital, investing in renewable energy sources, and utilizing contemporary technologies to harness natural resources in the economies of Central Asia.

A comprehensive analysis of key factors' impact on environmental performance: Evidence from Globe by novel super learner algorithm

This study aims to analyze comprehensively the impact of different economic and demographic factors, which affect economic development, on environmental performance. In this context, the study considers the Environmental Performance Index as the response variable, uses GDP per capita, tariff rate, tax burden, government expenditure, inflation, unemployment, population, income tax rate, public debt, FDI inflow, and corporate tax rate as the explanatory variables, examines 181 countries, performs a novel Super Learner (SL) algorithm, which includes a total of six machine learning (ML) algorithms, and uses data for the years 2018, 2020, and 2022. The results demonstrate that (i) the SL algorithm has a superior capacity with regard to other ML algorithms; (ii) gross domestic product per capita is the most crucial factor in the environmental performance followed by tariff rates, tax burden, government expenditure, and inflation, in order; (iii) among all, the corporate tax rate has the lowest importance on the environmental performance followed by also foreign direct investment, public debt, income tax rate, population, and unemployment; (iv) there are some critical thresholds, which imply that the impact of the factors on the environmental performance change according to these barriers. Overall, the study reveals the nonlinear impact of the variables on environmental performance as well as their relative importance and critical threshold. Thus, the study provides policymakers valuable insights in re-formulating their environmental policies to increase environmental performance. Accordingly, various policy options are discussed.

Assessing the impact of incentive coordination effect on the equilibrium of agricultural water usage by China's South-to-North Water Diversion Middle Route Project

In recent years, the sustainable development of agricultural water resources has received much attention. The mismatch between agricultural water distribution patterns, land resources, and socioeconomics threatens food production, especially in vast water-scarce plains. Therefore, monitoring agricultural water spatial equilibrium (AWRSE) is necessary. Based on equilibrium theory and information entropy, in this study, the AWRSE evaluation model is constructed from three aspects: agricultural water resources, land resources, and socioeconomics. In addition, the relationship between social factors with cropping pattern as the primary explanatory variable and AWRSE was examined in conjunction with the extended STIRPAT model and applied to the water-receiving area of the Middle Route of South-to-North Water Diversion Project (MR-SNWDP). The results show that compared with the pre-diversion period, the AWRSE of 75% of the water-receiving cities has been significantly improved by the MR-SNWTP water supply. The MK test z value of the overall regional AWRSE has changed from - 0.328 to - 2.65, and the AWRSE development has shifted from not significantly better to significantly better. The cropping pattern shows a positive response to this development, and this effect can be mitigated in the late stage of water transfer; when the proportion of food crop cultivation increases by 1%, the sub-regional AWRSE value will increase by 0.347%. The evaluation model demonstrates a broad range of inclusiveness and application potential; it provides novel insights for examining agroecological, social, and economic stability.

Interdependency and causality between green technology innovation and consumption-based carbon emissions in Saudi Arabia: fresh insights from quantile-on-quantile and causality-in-quantiles approaches

In this paper, we examined the asymmetric dynamics and causality of technological progress--proxied by green technology innovation--on both consumption-based carbon (CCO2) and territory-based carbon (TCO2) emissions in Saudi Arabia using quarterly data from 1990Q1 to 2021Q4. Our initial results reject the normality and linearity assumptions of data series and thus emphasize that the observed associations are quantile dependent. We firstly utilized the quantile-on-quantile regression (QQR) approach to draw the interdependency between green technology innovation and both CCO2 and TCO2 emissions. We found a strong emission-mitigating impact of green technology innovation only at (extreme) upper emission levels. We also identified a weak positive effect at (extreme) higher emission quantiles. Furthermore, we found that higher emission levels are linked with lower green technology innovation across all emission quantiles whereas a weak positive effect is perceived at lower and medium emission quantiles. We further utilized linear and nonlinear Granger causality-in- quantiles (GCQ) tests to capture an entire picture of the impact of green technology innovation on both CCO2 and TCO2 emissions. Under linear specifications of the quantile regression model, we found evidence of strong bidirectional causality between carbon emissions and green technology innovation across lower and upper quantiles. However, we found unidirectional causalities from carbon emissions to green technology innovation at medium quantiles of the conditional distribution. Besides, there is no causality at both extreme lower and extreme upper quantiles. Under nonlinear specifications of the quantile regression model, we found a weak unidirectional causality from green technology innovation to carbon emissions at (extreme) lower quantiles. We also found a weak unidirectional causality from carbon emissions to green technology innovation at medium and extreme upper quantiles. Overall, our findings indicate that green technology innovation helps abate both CCO2 and TCO2 emissions in Saudi Arabia. Our study shows policies that target green technology innovation would significantly change carbon emissions.

Modelling the air pollution induced health effects of energy consumption across varied spaces in OECD countries: An asymmetric analysis

The air pollution-induced health effects of energy consumption remain a grey area in the extant literature. As of yet, there are very limited studies on the subject matter for countries in the Organisation for Economic Co-operation and Development (OECD). To this end, we employ panel data from 1990 to 2019 for 37 OECD countries and panel estimation techniques that control for distributional asymmetry. We also utilize a composite variable of mortality and morbidity to capture the full spectrum of air pollution-induced health burdens. Our findings reveal that renewable energy ameliorates the health burden of air pollution in indoor spaces, evidence for the ameliorating effects of renewable energy in outdoor and occupational spaces was however weak. We also show that income has an ameliorating effect on air pollution-induced health burdens across all spaces and that the effect of non-renewable energy is asymmetric and disparate across all spaces. Furthermore, while technological innovation ameliorates the health burden of air pollution in indoor spaces, it exacerbates the health burden of air pollution in both occupational and outdoor spaces. These findings thus show that the positive health implications of renewable energy policy interventions have more traction in indoor spaces. Capacity needs to be built in the renewable energy sector to reduce the pollution-inducing health burdens emanating from ambient and occupational spaces.

Urbanization, industrialization and SO2 emissions in China: does the innovation ability of cities matter for air quality?

This paper aims to detail the relationships between urbanization, industrialization, the innovation ability of cities and local air quality in 284 cities in China using annual data. For the empirical outputs, the panel quantile regression analysis, which considers the heterogeneous nature of the data set, is employed. Initial findings indicate that (i) urbanization and industrialization negatively affect local air quality. (ii) Innovation capability of cities has a direct and improving impact on local air quality. Then, the paper estimates the moderating role of cities' ability to innovate in the polluting effect of urbanization and industrialization on local air quality. Remarkably, empirical evidence indicates that (iii) the innovation ability of cities also moderates the polluting impact of urbanization and industrialization on local air pollution. Based on the findings, the paper confirms the importance of both direct and moderator effects of the innovative environment in cities in tackling air pollution.

The asymmetric relationship between public-private partnerships investment in energy and environmental degradation for sustainable development: new evidence from quantile-on-quantile regression approach

According to the United Nations Agenda, the 2023 sustainable environment is necessary to secure this planet's future; public-private partnerships investment in energy is crucial to sustainable development. The research examines the quantile association between public-private partnership ventures in energy and environmental degradation in ten developing nations, and data is used from January 1998-December 2016. The advanced econometrics quantile-on-quantile regression approach is used to control the issues of heterogeneity and asymmetric relationship. According to the quantile-on-quantile approach, there is a strong positive association between public-private partnerships in energy and environmental degradation in Argentina, Brazil, Bangladesh, and India. But the negative relationship is observed on different quantiles of China, Malaysia, Mexico, Peru, Thailand, and the Philippines. The findings suggest that the world needs to act as a single community and divert its resources toward renewable energy sources to control climate change; also, to accomplish the UN 15-year road map of Agenda 2023 with 17-SDGs; out of these 17 sustainable goals, SDG-7 is related to affordable and clean energy, SDG-11 is about sustainable cities and communities, and SDG-13 focuses on climate action for sustainable development.

COP27 perspective of resources management: From conflict to COVID-19 of emerging countries

Resources management in the modern era is a crucial perspective of a sustainable environment linked with sustainable development. Therefore, it is crucial to re-estimate the resources-environment management nexus in a new setting. Concerning environmental management from the COP27 perspective, economies are taking various economic, financial, and environmental steps to reduce hazardous emissions in the region. Recently, BRICS economies have invested in renewables and enhanced capital formation to accelerate environmental recovery. In this respect, this study tends to examine the influence of electricity from renewable resources (ELREC), resources management (resources rents), research and development (RDEV) and gross fixed capital formation (GFCF) on carbon emissions of the BRICS economies throughout 1989-2021. Using various diagnostic tests, this study confirms the long-run equilibrium association between the variables. This study uses non-parametric estimation approaches and concludes that ELREC and RDEV significantly enhance environmental sustainability. Except for forest and oil resources, the rest of the forms of the resources increase emissions. On the other hand, economic growth and GFCF significantly lead to higher emissions, which degrades the environment. Resources rents also contribute to increasing carbon emissions.

Towards environmental degradation mitigation: The role of regulatory quality, technological innovation and government effectiveness in the CEMAC countries

The study explores the interaction between regulatory quality, economic growth, technological innovation, energy consumption, government spending on research and development, and environmental degradation (EVD) in the Economic and Monetary Community of Central Africa (CEMAC) region. The study applied the econometric approach CS-ARDL to estimate the short and long-term interaction between the regressors and the explanatory variable. The study period covers from 1990 to 2020. To summarize the findings of this research, (1) the study discovered a positive relationship between energy consumption, government effectiveness, regulatory quality, and environmental degradation. (2) Economic growth, government spending on research and development, and technological innovation, on the other hand, extensively dissipates EVD in the CEMAC economies. (3) The causality analysis espoused a bidirectional connection between energy consumption, technological innovation, and EVD. (4) Lastly, a unidirectional interplay exists between economic growth, government effectiveness, regulatory quality, and EVD. This study also serves as a reference point for policymakers and governmental institutions to invest in cleaner technologies and increase government research and development spending to mitigate environmental degradation in these areas.

Role of environmentally related technologies and revenue taxes in environmental degradation in OECD countries

The purpose of this study is to validate the impact of foreign direct investment inflows (FDI inflows), trade openness (TO), environmentally related technologies (ERTs), environmentally related tax revenues (ERTRs), and economic growth (EG) on carbon dioxide (CO₂) emissions by employing a PMG (pooled mean group) estimator with a dataset of 36 OECD countries spanning from 1990 to 2020. Im-Pesaran-Shin, Fisher-type, and cross-sectional augmented Dicky-Fuller tests indicate that study variables are stationary at I (0) and I (I). Kao and Pedroni cointegration test results show that cointegration exists across regressors and regressands throughout the sample of OECD countries. The results of the Hausman test confirm that the PMG panel ARDL method can be employed. Empirical results of PMG demonstrate that ERTRs help to reduce CO₂ emissions, while FDI inflows, TO, ERTs, and EG are significant and positively related to environmental degradation. This study is an effort to fill the gap by exploring the role of ERTs and ERTRs in environmental degradation in selected OECD countries. The study findings support the relationship between CO₂ emissions, ERTs, and ERTRs. It has been determined that environmental technologies and revenue taxes are also drivers of environmental sustainability. The study provides policymakers with pertinent implications for promoting the development and adoption of green technologies. The findings suggest that imposing environmental taxes expedites the development of environmentally related technologies for reducing CO₂ emissions and promoting sustainable development in OECD countries, with potential applications in a wide range of countries, particularly as a basis for emerging countries to boost their energy transition timelines.

Realizing the 2050 Paris climate agreement in West Africa: the role of financial inclusion and green investments

International organizations have emphasized the importance of global economies supporting efforts to combat climate change. The Paris Agreement or Agenda 2050 urges nations to ensure that the increase in global temperature is limited to 1.5 °C. Studies have analyzed the factors that contribute to harmful emissions, particularly carbon dioxide emissions, in order to limit temperature rise. However, since there are other equally harmful pollutants, this study evaluates the impact of financial inclusion and green investment on reducing greenhouse gas emissions. The study uses data from West Africa, where environmental pollution has significantly increased. The study employed regression analysis while controlling for economic growth, foreign direct investment (FDI), and energy consumption. The study's key findings reveal that financial inclusion and green investment have a monotonic effect on reducing greenhouse gas emissions. Additionally, the study confirms the environmental Kuznets curve hypothesis and the pollution haven effect for the region. Technological innovation reduces pollution, but green investment and financial inclusion reinforce this effect. Therefore, the study recommends that governments in the sub-region commit to supporting green investment and environmentally friendly technological innovations. It is also crucial to strictly enforce laws regulating the operations of multinational corporations in the region.

Globalization, institutions, and environmental quality in Middle East and North African countries

Sustainable development has received significant attention due to rapidly rising environmental issues, and finding solutions to these issues caused by various indicators are the subject of research nowadays. To this end, the increasing globalization and institutional quality to address environmental challenges have become hot subject and need better attention. Accordingly, this study enhances the literature by examining the role of political stability, the rule of law, control of corruption, and globalization on the environment for 14 Middle Eastern and North African (MENA) countries between 1996 & 2018, applying cross-sectional augmented autoregressive distributed lags (CS-ARDL) approach. The short and long-run estimates obtained from CS-ARDL confirm that globalization, the rule of law, political stability, and corruption control significantly reduce carbon emissions (CO₂e). Contrarily, energy production, financial development, and economic growth have significant positive effects, suggesting they raise CO₂e. The study also estimates a robustness analysis with the Driscoll-Kraay estimator, confirming results on signs and magnitude identical to those with CS-ARDL. These results drive the MENA countries to adhere to environmental standards to reduce CO₂e strictly. Environmental-friendly industrial techniques should be employed, mainly while producing. The governments of these countries should facilitate the governance process through the globalization of environmental products to ensure long-term environmental sustainability.

How to achieve carbon neutrality while maintaining economic vitality: An exploration from the perspective of technological innovation and trade openness

The significant drop in global carbon emissions in 2020 was credited to the enormous loss of economic activity from the impact of COVID-19. The challenge is now to reduce carbon emissions without causing massive disruption and damage to economic production. To achieve carbon neutrality while maintaining economic vitality, the impact of technological innovation and trade openness must be considered. This paper sets technological innovation and trade openness as core variables and establishes two extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) models. The first model focuses on carbon emissions and the second focuses on economic growth. Comparisons were made between the BRICS (i.e., Brazil, Russia, India, China, and South Africa) and G7 (i.e., Canada, France, Germany, Italy, Japan, the UK, and the USA) countries. The fully modified ordinary least squares (FMOLS) regression analysis was used to explore the impact of technological innovation and trade openness on low-carbon economic development. A Panel Granger Causality Test explores the causal relationship between the core, control and dependent variables. The results illustrate that: (1) technological innovation is the primary factor that inhibits carbon emissions and promotes economic growth in both international organizations, (2) trade openness promotes the growth of carbon emissions in BRICS countries, but restrains G7 growth, confirming the "Pollution Haven Hypothesis", (3) per capita GDP is the largest contributor to carbon emissions growth in both the G7 and BRICS countries, which illustrates that per capita GDP is the largest contributor to carbon emissions. It is proportional to G7 and BRICS carbon emissions. This paper provides several policy recommendations: breaking through basic research, adjusting the science and technology evaluation system, optimizing the export trade structure, and increasing the proportion of renewable energy.

The moderating role of technological innovation between tourism and carbon emission: short and long-run panel analysis

In contemporary times of globalization, tourism and travel are among the fastest-growing economic sectors and are highly related to climate change; however, technological innovations as a powerful tool positively contribute to the environment. The present study examines the tourism receipt and CO2 emission relationship and the triple interaction effect of technological innovation, energy consumption, and tourism receipts on CO2 emissions in the short and long run. To achieve study objectives, we utilized panel data of 64 Belt and Road Initiative (BRI) countries over the period of 1995 to 2019. Considering the cross-sectional dependence in the panel data set, we employed a series of econometric panel data estimation techniques-including the panel unit root tests, panel co-integration tests, and the generalized method of moments (GMM). The panel unit root results confirmed the level of stationarity, and the panel co-integration results verified the long-run relationship among study variables. The sys-GMM results indicate that tourism receipts and CO2 emissions have an inverse relationship for 64 BRI countries. In addition, the negative coefficients for joint interaction imply that tourism receipts, technological innovation, and energy consumption reduce CO2 emissions. Considering the theoretical underpinnings of the study outcomes, we discussed significant policy implications to reduce CO₂ emissions and achieve sustainable tourism.

The driving factors of corporate carbon emissions: an application of the LASSO model with survey data

Corporate carbon performance is a key driver of achieving corporate sustainability. The identification of factors that influence corporate carbon emissions is fundamental to promoting carbon performance. Based on the carbon disclosure project (CDP) database, we integrate the least absolute shrinkage and selection operator (LASSO) regression model and the fixed effects model to identify the determinants of carbon emissions. Furthermore, we rank determining factors according to their importance. We find that Capx enters the models under all carbon contexts. For Scope 1 and Scope 2, financial-level factors play a greater role. For Scope 3, corporate internal incentive policies and emission reduction behaviors are important. Different from absolute carbon emissions, for relative carbon emissions, the financial-level factors' debt-paying ability is a vital reference indicator for the impact of corporate carbon emissions.

Analyzing the role of green innovation and public-private partnerships in achieving sustainable development goals: a novel policy framework

The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13.

Revisiting Research and Development Expenditures and Trade Adjusted Emissions: Green Innovation and Renewable Energy R&D Role for Developed Countries

Research and development’s role in achieving the Sustainable Development Goals is crucial. More specifically, to achieve a sustainable environment, the role of environment-related research and development expenditures, along with renewable energy research and development, is also important. This study focuses on the sustainable development perspective and the role of a sustainable environment via building a knowledge-based economy. A knowledge-based economy is more research and development oriented, and its role is undeniable in ensuring sustainable development. The current study focuses on the role of general research and development, environmental research and development, and cleaner energy research and development perspective for developed economies from 1989 to 2021. The study evaluated the role of research and development expenditures for the environment and cleaner energy on consumption-based carbon emissions along with political risk, income, green innovation, exports, and imports. The study used novel panel methods for econometric analysis. The study found that research and development expenditures for the environment and cleaner energy help limit carbon emissions. Moreover, reducing political risk, increasing green innovation, renewable energy consumption, and exports are also linked inversely with carbon emissions. In contrast, imports and income are deteriorating factors for consumption-based carbon emissions. The study recommends increasing research and development expenditures, encouraging green innovation, and limiting political risk for sustainable development.

Influence of research and development, environmental regulation, and consumption of energy on CO2 emissions in China-novel spatial Durbin model perspective

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

The role of economic growth, information technologies, and globalization in achieving environmental quality: a novel framework for selected Asian countries

This study examines the impact of information and communication technologies (ICT), GDP growth, population, and globalization on the environmental quality of 31 Asian economies (i.e., categorized as lower middle-income, upper middle-income, and high-income groups Asian economies). This analysis employed the time series data from 1990 to 2018. The robust second-generation econometric technologies are used in this analysis. This study applied the Environmental Kuznets curve (EKC) premises under the extended "STIRPAT model" to add population and GDP (per capita) and information technologies (ICTs) by employing ecological footprint. To estimate, the estimators of this study used the CS-ARDL estimates, and for robustness check, this study used the augmented mean group (AMG) test. The co-integration test found the long-run association between ecological footprint and its main determinants. The results of CS-ARDL have confirmed the imperative role of information technologies in mitigating the ecological footprint in the higher, upper-middle, and lower-middle-income economies of Asian economies. The statistical findings of this study are robust to diagnostic tests and alternative estimation proxies and techniques. Moreover, policymakers need to identify the direction of the information technology-ecological footprint nexus through cooperation in combating climate change with financial assistance in the ICT sector.

Environmental sustainability and green technologies across BRICS countries: the role of institutional quality

In recent years, a growing body of research has focused on the environment and economic growth nexus. However, there has not been much research done on how environmentally friendly technologies and institutional quality affect pollution levels. It is found that in developed countries, the rate of environmental deterioration has slowed thanks to more sustainable environmental regulations, advances in technology, and improvements in the quality of institutions. In contrast, limited modern technology in developing nations has resulted in havens of high carbon emissions. Therefore, the current research tried to analyze the environmental quality by using green technologies (GT), institutional quality (IQ), and energy efficiency (EE) as independent variables. In this study, we utilized data from 1995 to 2019 from BRICS countries to estimate long-term and short-term relationships. Used second-generation econometric techniques indicated that IQ, GT, and EE repair reduced environmental damage. The EKC does not exist, which means pollution in selected countries will improve with an expansion in economic activities. In the long term, a reform in institutions and more spending are required on green technologies to secure a sustainable future in BRICS countries. Results hold up when it comes to policy implications.

How do economic and financial factors influence green logistics? A comparative analysis of E7 and G7 nations

Logistics is an important sector that supports every sector of the economy, and thus, the development of nations is impossible without efficient logistics. Alongside this, the logistics sector generates various kinds of emissions that degrade the quality of the environment. Developed countries are striving to introduce green logistics to avoid environmental damages caused by transportation. Also, developing countries will start focusing on developing green logistics sooner or later. Keeping this in view, a comparative panel study on the group of seven (G7) and Emerging Seven (E7) nations is conducted to study the impacts of various economic and financial variables on green logistics. The data from 1996 to 2018 is analyzed using some reliable methods that produce efficient and consistent results during heterogeneity and cross-sectional dependence. The findings disclosed that cointegration is present in E7 and G7 panels. For E7 countries, the results disclosed that research and development (R&D), FDI, portfolio investment, and trade openness reduce green logistics. However, in the G7, R&D, FDI, portfolio investment, and trade increase green logistics. The empirical analysis did not show any meaningful impact of financial development and economic growth on green logistics in both groups of nations. Lastly, based on the comparative analysis, various policies are suggested for E7 to catch up with the G7 regarding logistics development. Also, policies for G7 are suggested to boost green logistics.

Heterogeneous impact of eco-innovation on premature deaths resulting from indoor and outdoor air pollution: empirical evidence from EU29 countries

Environmental innovations play a vital role in reducing air pollution and the number of pollution-related mortality. Most of the previous studies have examined the role of eco-innovations in environmental quality. However, to our knowledge, no study has evaluated the effects of eco-innovation on air pollution as a cause of mortality. For this purpose, this research examines the effect of eco-innovations on premature deaths from indoor and outdoor air pollution in twenty-nine European countries from 1995 to 2019. The Method of Moments Quantile Regression (MM-QR) is used to assess the impacts. The results confirm the heterogeneous effects of the main variables in both models. Both models indicate that eco-innovations reduce premature deaths from outdoor and indoor air pollution, and these effects are more significant in high quantities (75th and 90th). Also, the effect of eco-innovations on reducing mortality due to indoor pollution is more significant than that related to outdoor pollution. Eco-innovation, economic growth, renewable energy consumption, and urbanization reduce premature mortality indoors and outdoors, but CO₂ emissions increase this mortality. The results of the Dumitrescu-Hurlin causality test also support that all variables, including eco-innovation and CO₂ emissions, have a bidirectional causal relationship with indoor (LIND) and outdoor (LOUT) mortality due to air pollution. Governments and politicians can help mitigate this problem by providing more environmental innovations by increasing support packages and reducing taxes.

Does R&D element flow promote the spatial convergence of regional carbon efficiency?

Carbon efficiency has attracted increased attention due to the carbon neutrality goal of various responsible countries, including China. R&D element has been proved to be an effective method to promote carbon efficiency from a static perspective without considering spatial factors. However, due to regional inequality in China, the level of carbon efficiency and R&D element flow vary in different regions. If ignoring the importance of R&D element flow from a dynamic perspective and neglecting the spatial factors of carbon efficiency convergence, it may be not conducive to the improvement of carbon efficiency and its overall development. Thus, this study proposes a gravity model to figure out the specific condition of R&D element flow (including R&D personnel flow and R&D capital flow) between Chinese provinces and cities from 2009 to 2019, builds up a MinDS model with undesirable outputs to estimate carbon efficiency and analyzes the characteristics of regional carbon efficiency with kernel density estimation, and employs a spatial Durbin model to investigate the effect of R&D element flow on regional carbon efficiency convergence. The results show that, firstly, the R&D personnel flow and R&D capital flow show a gathering trend in the neighboring regions, and the flow distribution is unbalanced. Secondly, the overall regional carbon efficiency has improved at first, then decreased gradually. There are large spatial differences among Chinese regional carbon efficiency, and the carbon efficiency between provinces and cities converges. Thirdly, R&D element flow promotes regional carbon efficiency convergence. The results of this study can be useful for solving the problem of unequal regional carbon efficiency development by managing the distribution and transfer of R&D element among provinces and cities.

Dissipating environmental pollution in the BRICS economies: do urbanization, globalization, energy innovation, and financial development matter?

The question of how Brazil, Russia, India, China, and South Africa (BRICS countries) can substantially dissipate environmental pollution (EVP) remains unsolved. In this regard, this research explores the dynamic association between energy consumption (EGC), economic expansion (EXP), globalization (GLO), energy innovation (ENI), urbanization (URB), financial development (FID), and environmental pollution (EVP) using panel data from 1990 to 2020. This study integrated the augmented mean group (AMG), common correlated effect means group estimator (CC-MG), and fully modified ordinary least square (FMOLS) model approach to estimate the long-run interaction among the series. The findings of this study reveal a positive and significant association between economic expansion, energy consumption, urbanization, financial development, and environmental pollution. In contrast, globalization and energy innovation extensively abate EVP in the BRICS economies. Moreover, the outcome of the Granger causality test indicates that energy consumption and energy innovation have a bidirectional association with EVP. The Granger causality test further revealed a unidirectional causality between globalization, urbanization, financial development, and environmental pollution. Finally, this research has implications for policymakers in the BRICS countries.

The role of government spending on energy efficiency R&D budgets in the green transformation process: insight from the top-five countries

The transition to a low carbon economy has become more realistic with sustainable development goals (SDGs). Economies are on their way to 2030 and 2050 targets by increasing their environmental awareness. However, the most important issue that complicates this process is the dependence on fossil fuels and the need for sufficient time for renewable resources to mature. Previous literature has neglected this and focuses directly on renewable and fossil energy research and development (R&D) budgets. This paper fills the gap in the literature by showing whether the budgets allocated by countries for energy efficiency R&D are important in the maturation process of renewable energy sources. This paper offers policy recommendations to the countries (the USA, Canada, Germany, France, and Japan) that allocate the highest share of the budget to energy efficiency. It also presents the current situation of countries investing in energy efficiency as examples for other countries looking to transition into green energy. This study tackles the effects of energy efficiency R&D budgets, economic growth, trade openness, and natural resources on CO₂ emissions over the period 1985-2019 using Augmented Means Group and Common Correlated Effects Mean Group methods. Empirical findings show that the energy efficiency R&D budgets are not at a level to enhance environmental quality. Moreover, economic growth and trade openness also contribute to environmental damage. On the contrary, natural resources increase environmental quality. In the light of the empirical findings, the considered countries with the largest budgets (top five) should expand their energy efficiency budgets until the transition to renewable energy gains momentum to achieve SDG-13, i.e., climate action, and SDG-7, i.e., affordable and clean energy.

Energy R&D trends and sustainable energy strategies in IEA countries: efficiency, dependency, and environmental dynamics

Understanding the factors affecting R&D trends in the energy sector has a key role in overcoming environmental concerns such as combating climate change, as well as other economic and political problems related to energy. Based on such concerns, this study aims to analyze fundamental factors that determine the energy R&D trends of 29 International Energy Agency (IEA) countries. The data set, consisting of annual indicators for the period 1990-2015, is analyzed with the Driscoll-Kraay panel data estimator. Empirical findings for overall sample show that efficiency, import dependency, and the share of renewable energy use are positively related with R&D expenditure in energy sector. CO₂ intensity is found to be statistically insignificant. When countries are grouped considering their energy composition structures, the dynamics of energy R&D expenditures differ between groups. In overall evaluation, our findings illustrate efficiency and dependency to have greater priority compared to environmental dynamics on energy R&D expenditures for IEA countries during the period.

Interaction and mediation effects of economic growth and innovation performance on carbon emissions: Insights from 282 Chinese cities

China is under rapid urbanization and consequently facing increasing carbon emissions (CE). Economic growth (EG) and innovation performance (IP), as two critical indicators of urbanization, are considered the driving forces of CE. Although economy and innovation are entangled and can jointly affect CE in reality, the measured effects of economy and innovation on CE are often treated separately in traditional studies. We adopted a three-part research framework including the total, interaction and mediation effect tests to elucidate how EG and IP affected CE in China from 2005 to 2015 based on insights from 282 Chinese cities. The empirical results showed that both economy and innovation contributed to CE, although the contribution has reduced over the 11 years. In particular, the interaction effect between economy and innovation for North China, Northeast China, and Southwest China was -4.201, -8.442, and - 3.897, respectively, in 2015, meaning that these regions adversely affect CE. In addition, we found that the economy helps reduce CE via innovation. When considering the changes of economy and innovation, their mediation effect on CE changes varied in different regions, attributable to the level of economy and innovation as well as the stocks of energy resources. Therefore, future planning for low-carbon transition should regard the economy and innovation together. Based on this principle, we propose five detailed policies. Overall, this study is valuable not only for further understanding the triangle relationship among economy, innovation, and CE, but also for reaching low-carbon goals.

Environmental Kuznets curve for CO2 emissions in Baltic countries: an empirical investigation

Recognizing the factors responsible for the gradual increase in greenhouse gas [e.g. carbon dioxide (CO2)] emissions is crucial to reduce the detrimental consequences on environmental sustainability and human life. Accordingly, spotting the sectors which contribute the most to CO2 emissions and dampen economic growth have become one of the major concerns for policymakers around the globe. Against this background, this paper examines the nexus between economic growth and CO2 emissions in three Baltic countries namely Estonia, Latvia and Lithuania. Thus, the study basically checks the validity of the environmental Kuznets curve (EKC) hypothesis by taking into account the role of energy consumption and financial development over the period of 1990-2018. This type of study is highly important for the region in order to comply with the commitments of the Paris Agreement and Sustainable Development Goals of the United Nations. The study first employs appropriate testing procedures and second-generation panel data methods to account for cross-sectional dependency and slope heterogeneity among countries. Applying unit roots and cointegration tests, the study then employed different mean group estimation models and heterogeneous panel causality methods suitable for cross-sectionally dependent and heterogeneous panels. The results of the econometric analyses reveal that the inverted U-shaped EKC hypothesis does not hold in the Baltic countries. But the pollution haven hypothesis is evidenced to hold for these nations. By boosting the CO2 emissions figures, again, the study also revealed that higher levels of energy consumption exhibit adverse environmental consequences. Financial development is found to be effective in explaining the variations in the CO2 emission figures of the selected countries as well. Causality test results confirm bi-directional causality between economic growth and CO2 emissions, energy use and CO2 emissions, CO2 emissions and financial development, energy use and economic growth as well as between energy use and financial development. Furthermore, country-specific impacts are found to be similar to the corresponding panel estimates. Consistent with the findings, the study finally puts forward some policy-level suggestions. Accordingly, it is recommended that the Baltic countries need to move away from fossil-fuel dependent energy consumption growth policies to mitigate environmental degradation.

Application of grey model in influencing factors analysis and trend prediction of carbon emission in Shanxi Province

In recent years, global warming has attracted extensive attention. The main cause of global warming is the emission of greenhouse gases, known as carbon emissions. Therefore, it is of great significance to explore the influencing factors of carbon emissions and accurately predict carbon emissions for reducing carbon emissions and slowing down climate warming. This paper takes the carbon emissions of Shanxi Province in China as the research object. Firstly, the emission factor method is used to calculate the carbon emissions, and then the grey correlation model is used to screen out the factors that have a greater impact on carbon emissions (per capita GDP, urbanization rate, resident population, energy consumption, expenditure on R&D projects). Then, an improved grey multi-variable convolution integral model (AGMC(1, N)) is used to accurately predict carbon emissions. The results show that the application of the AGMC(1,N) model to carbon emission prediction has a good prediction effect. In addition, the carbon emissions of Shanxi Province will increase with the growth rate of per capita GDP, energy consumption, resident population, and expenditure on R&D projects, while the carbon emissions will gradually decrease with the increase of urbanization level. The prediction results provide the direction for carbon emission reduction in Shanxi Province. At the same time, theAGMC(1,N) model can also be applied to the prediction of carbon emissions in other provinces or other fields.

Cleaner Technology and Natural Resource Management: An Environmental Sustainability Perspective from China

In economies, cleaner technology, increased demand for renewable energy, and more efficient use of natural resources contribute to meeting environmental sustainability targets. The Chinese economy is no exception in its attempts to conserve economic and natural resources via collaborative efforts to embrace cleaner technology, green energy sources, and resource conservation management to preserve resources for future generations. This research examines the influence of cleaner technologies, green energy sources, and natural resource management on reducing greenhouse gas emissions using quarterly data for the Chinese economy from 2000Q1 to 2020Q4. The findings demonstrate that increasing demand for green energy reduces greenhouse gas emissions, hence substantiating the premise of ‘green is clean’ energy development. Additionally, optimum resource usage enhances environmental quality, corroborating the ‘resource cleaner blessing’ hypothesis. The positive link between inward foreign direct investment and greenhouse gas emissions substantiates the ‘pollution haven’ concept, according to which inward foreign direct investment uses unsustainable technology in manufacturing processes, hence degrading air quality indicators. Inadequate access to clean cooking technology and increased population density has a detrimental effect on the country’s environmental sustainability agenda, which must be corrected via sustainable regulations. The causality estimates show the feedback relationship between renewable energy demand (and economic growth) and cleaner technology, between economic growth and green energy (and inbound foreign direct investment), and between population density and economic growth (and green energy). The Impulse Response function estimates suggested that economic growth and population density would likely increase GHG emissions. In contrast, cleaner technology, green energy demand, natural resource management, and inbound foreign direct investment would likely decrease greenhouse gas emissions for the next ten-year time period. The sustainability of the environment and natural resources in China is bolstered by developing cleaner technologies, a greater reliance on renewable energy sources, and better management of natural resources.

Does energy innovation play a role in achieving sustainable development goals in BRICS countries?

It is widely discussed that greenhouse gases (GHGs) are the main culprit behind global warming. The conventional energy sources (oil, coal, and gas) mainly realize GHGs in the atmosphere. Due to this, the world's countries are switching towards clean energy sources and investing more in projects related to innovation in the energy sector. Thus, this study investigates the role of energy innovation in combating GHGs emissions by taking the environmental Kuznets curve for BRICS economies. The FMOLS and DOLS estimators are employed throughout 1996-2016. The findings documented that energy innovation plays an important role in mitigating GHGs emissions. Moreover, the result strongly approves the EKC hypothesis for BRICS countries in the significance of energy innovation. Finally, it is recommended that expanding the public budget in energy R&D expenditures can help to reduce GHG emissions and promote sustainable growth in BRICS countries.

Will China's R&D investment improve green innovation performance? An empirical study

In 2020, China's R&D investment reached 2442.6 billion RMB, and it ranks second in the world, but the performance of green innovation has not proportionately improved. The question of how to promote the improvement of green innovation performance is particularly important in order to mitigate future environmental problems and issues due to rapid development of China's economy. While past research has examined the relationship between R&D investment and green innovation, they have not explicitly considered the effect of regional technological innovation level on this relationship. Hence, we fill this gap by exploring the relationship between R&D investment and green innovation performance using data from various regions in China from 2015 to 2019, under the effect of a threshold variable, namely, technological innovation. We explore the impact of economic development level, environmental regulation level, foreign direct investment, and science and technology in fiscal expenditures on green innovation performance. The empirical results show that when the regional technological innovation level is used as the threshold variable, the R&D investment has a significant double-threshold effect with the lagging three-phase green innovation performance. When the technological innovation level is low (< 0.1082), R&D investment has a negative impact on green innovation performance. Moreover, when the technological innovation level is high (>0.5837), the impact of regional R&D investment on green innovation performance is sub-optimal. Consequently, the range of [0.1082 to 0.5837] is the best range for the positive impact of R&D investment on green innovation performance. Furthermore, among China's 30 provinces and cities, 24% (mostly areas located in the southwest and northeast of China) have the technological innovation level in the optimal range. Our results help explain the current status of China's R&D investment and green innovation development, and provide a theoretical basis for the formulation of government innovation investment policies.

Determinants of ecological footprint in OCED countries: do environmental-related technologies reduce environmental degradation?

The world is in a clash between the perspectives of economic expansion and sustainable environment. The high pace of technological progress opens space for fostering economic growth but at the same time, it creates a big dilemma for humans in protecting the environmental quality. The environmentally specific technologies are expected to help human beings to achieve dual objectives of economic prosperity and environmental sustainability. Despite its importance, attention to the role of environmental-related technologies in reducing environmental degradation is limited. This paper, therefore, intends to discover the impact of environmental-related technologies on the ecological footprint for 20 OECD from 1990 to 2015. The results endorse a long-run relationship between ecological footprint and green technologies, renewable energy, international trade, energy intensity, and real income. Environmental-related technologies and renewable energy consumption are found to be impetuous to sustainable development. The study provides relevant implications for policymakers to support the development and adoption of green technologies.

Effects of economic complexity, economic growth, and renewable energy technology budgets on ecological footprint: the role of democratic accountability

The economic structure of countries can influence economic growth, energy demand, and environmental footprints. However, the literature on economic complexity and ecological footprint (EFP) nexus is scarce. Besides, democracy is an important factor that may affect environmental policies and environmental sustainability. Hence, this paper investigates the effect of democracy, economic complexity, and renewable energy technology budgets on the EFP in G7 countries controlling income and financial development from 1985 to 2017. The findings from Westerlund (J Appl Econ 23:193-233, 2008) and other cointegration methods depict cointegration among variables. The long-run estimates from the continuously updated fully modified method unfold that economic complexity contributes to reducing the EFP. However, greater democratic accountability boosts the EFP figures rather than reducing them. On the flipside, renewable energy technology budgets and financial development are evidenced to mitigate EFP. Moreover, the study unveils a U-shaped linkage between economic growth and EFP, which indicates that an increase in income level will boost EFP. Further, the study found causality from economic complexity, democracy, and renewable energy budgets to EFP. Based on these findings, it is pertinent for the G7 countries to increase the manufacturing of sophisticated and complex products. In addition, enhancing renewable energy technology budgets is essential to ensure environmental well-being.

Role of FDI and energy intensity in mitigating the environmental pollution in the Chinese steel industry: does technological innovation makes a difference?

To accomplish China's sustainable growth, it is critical to identify the primary factors affecting environmental quality in the steel industry. In this positioning, foreign direct investment (FDI), energy intensity, and technological innovation have emerged as strong pillars of the steel industry. However, there are growing concerns of carbon emission from this industry which is still debatable. In this context, this study measures the effect of FDI, energy intensity, and technology innovation on environmental quality in the steel industry from 28 provinces of China. The study uses the provincial data for China over the period 2000-2018. In addition to examining unit root properties and cointegration, this study employed Augmented Mean Group regression for estimating long-run relationships among study variables. The findings reveal the negative effect of FDI and technology innovation on environmental quality. These findings indicate that FDI and technology innovation have shaped the energy intensity in the steel industry. The positive coefficient value of energy intensity shows that innovations for environmental conservation and energy usage are minimal and did not perform an integral part in lowering carbon emissions. These findings are important in formulating successful emission reduction policies after controlling the effects of urbanization and economic growth for the Chinese steel sector.

On the nexus between globalization, tourism, economic growth, and biocapacity: evidence from top tourism destinations

Several studies have investigated the relationship between tourism, consumption of energy, globalization, and ecological footprint. However, the role of biocapacity alongside tourism development in environmental sustainability is yet to be documented in the extant literature. No doubt, the biocapacity of a country, its level of tourist's arrival, as well as globalization all contribute immensely to ecological footprint. Consequently, this study looks at long-run and causality connections with a special focus on bio-capacity. The study uses the pooled mean group-autoregressive distributed lag model (PMG-ARDL) methodology to test the causality relationship during 2016 international tourists' receipt from world tourism organization data files for 10 tourism destinations. Empirical result based on the panel PMG-ARDL confirms the environmental Kuznets curve (EKC) hypothesis for the 10 tourism destinations countries investigated. Furthermore, the panel ARDL estimator was used to estimate the short-run and long-run relationships simultaneously between biocapacity, tourist arrivals, GDP per capita, globalization, and ecological footprints. While the Dumitrescu and Hurlin panel causality test was used to establish causality relationships among the highlighted variables. The trade-off between economic growth and environmental quality suggests that tourist arrival dampens environmental quality. In addition, the study finds that growing biocapacity affects ecological footprints negatively. Furthermore, an increase in tourism-related activities, globalization, and economic production has the potential to damage the quality of the environment. To this end, given the study results, there is a need to pursue green tourism which can reduce environmental degradation and destruction of land caused by multiple tourism-related transportation and construction of tourist facilities respectively in the top ten tourist destination countries.

The cyclical impact of green and sustainable technology research on carbon dioxide emissions in BRICS economies

This paper explored the asymmetrical relationships between green and sustainable technology research and environmental sustainability among the BRICS states from 1990 to 2018. The data was analyzed by second- and third-generation economic techniques such as slope heterogeneity and cross-section independence test, unit root test, structural break unit root test, panel cointegration with structural breaks cointegration tests, cross-section autoregressive distributed lags technique, augmented mean group, and Dumitrescu-Hurlin panel causality test. First, the results validated a long-run cointegration among variables. Second, the results showed that renewable energy consumption and positive shocks to green and sustainable technology research are proper to mitigate carbon dioxide emissions (short- and long-run). Third, gross domestic product, foreign direct investment, exports, and negative shocks to green and sustainable technology research increase carbon dioxide emissions. Fourth, the nexus between green and sustainable technology research and carbon dioxide emissions was counter-cyclical during economic expansion and contraction periods. Fifth, the impact of positive shocks to green and sustainable technology research on carbon dioxide emissions was more than the impact of negative shocks to green and sustainable technology research on carbon dioxide emissions.

Towards mitigating ecological degradation in G-7 countries: accounting for economic effect dynamics, renewable energy consumption, and innovation

The 21^st century economic growth is characterized by extensive production and consumption, which increases anthropogenic emissions. However, reducing emission levels require ecological sustainability through innovation and modern technological consideration. This paper investigated not only renewable energy-driven environmental quality but also captured innovation research investment in renewables within the framework of the environmental Kuznets curve (EKC) model for G-7 countries. The findings confirmed the presence of EKC hypothesis for G-7 countries. In addition, renewable energy and innovation were identified to exert negative effects on ecological footprint. To capture the entire conditional distribution of the ecological footprint, we applied the Method of Moments Quantile Regression with fixed-effects. The results affirmed the negative effects of renewable energy innovation. Besides, their effects were heterogeneous across the quantiles with evidence of diminishing effects from lower to higher quantiles, suggesting that countries with lower levels of ecological footprint are possibly more prone to the environmental deterioration effect of income growth. The results of the causality test support economic growth-induced ecological degradation, growth-induced renewables, and innovation-induced ecological conservation. The results further showed a feedback effect between renewables and ecological footprint, innovation, and income growth as well as innovation and renewables. These findings portend important implications for the realization of carbon-free economies in G-7 countries by 2100.

Role of financial development, environmental-related technologies, research and development, energy intensity, natural resource depletion, and temperature in sustainable environment in Canada

Environmental sustainability concerns are increasing worldwide; both developing and developed countries face environmental degradation. Literature has highlighted the environment-growth nexus; however, the impact of environmental-related technologies on the environment is ignored in early studies. This study aims to explore the implications of financial development, environmental-related technologies, research and development, energy intensity, renewable energy production, natural resource depletion, and temperature in a sustainable environment in Canada by using a time series model, i.e., dynamic ARDL simulations (Jordan and Philips 2018) with data from 1989 to 2020. The examined findings of the dynamic ARDL simulations indicate that environmental-related technologies in Canada help to reduce environmental degradation both in the short run and in the long run. At the same time, financial development, energy intensity, renewable energy production, research and development, natural resource depletion, and temperature causes boost the environmental degradation in Canada. To achieve sustainable environment, Canada needs to improve innovations in the environmental-related technologies for achieving sustainable growth and environment.

How FDI and technology innovation mitigate CO2 emissions in high-tech industries: evidence from province-level data of China

The high technology (high-tech) industry of China has gained a key strategic position in the Chinese economic goals. In this positioning, foreign direct investment (FDI) and technological innovation have emerged as strong pillars of the high-tech industry. However, there are growing concerns of carbon emission from this industry which is still debatable. In this context, this study measures the effect of FDI and technology innovation on carbon emissions in the high-tech industry from 28 provinces of China. The study uses the provincial data for China over the period 2000-2018. In addition to examining unit root properties, structural breaks, and cointegration, this study uses quantile regression for estimating long-run relationships among study variables. The findings reveal the negative impact of FDI on carbon emissions. Technology innovation positively impacts in the initial three quantiles, whereas negatively impacts in the next six quantiles. These results indicate that FDI and technology innovation have shaped the energy intensity in the high-tech industry, which causes fluctuation in carbon emissions over time. After controlling the effects of urbanization, energy intensity, and economic growth, this study recommends that policymakers should emphasize on the heterogeneous effects of FDI and technology-lead emissions at different quantiles during the process of CO₂ emission reduction.

Influencing factors and decoupling analysis of carbon emissions in China's manufacturing industry

The manufacturing industry directly reflects national productivity, and it is also an industry with high energy consumption and severe carbon emissions. This study decomposes the influential factors on carbon emissions in China's manufacturing industry from 1995 to 2018 into industry value added, energy consumption, fixed asset investment, carbon productivity, energy structure, energy intensity, investment carbon intensity, and investment efficiency by Generalized Divisia Index Model. The decoupling analysis of carbon emissions and industry value added is carried out to investigate the states of the manufacturing industry under the pressure of "low carbon" and "economy." Results show that first, fixed asset investment is the driving force of carbon emissions, followed by industry value added; investment carbon intensity, carbon productivity, investment efficiency, and energy intensity are the mitigating factors; simultaneously, the impacts of energy consumption and energy structure are fluctuating. Second, the decoupling of manufacturing has improved, especially in the light industry. Third, the decoupling of carbon emissions and economic development is mainly dominated by the decoupling of energy consumption and industry added value. Therefore, reducing the proportion of coal consumption and optimizing the energy structure are significant ways to promote the low-carbon development of the manufacturing industry.

Innovative Carbon Mitigation Techniques to Achieve Environmental Sustainability Agenda: Evidence from a Panel of 21 Selected R&D Economies

Technological innovation in the energy sector is highly needed to reduce carbon emission costs, which requires knowledge spillovers, financial development, and carbon pricing to achieve a green developmental agenda. The current study examines the role of knowledge innovations in achieving the environmental sustainability agenda under financial development and carbon pricing in a panel of 21 selected R&D economies from 1990 to 2018. The study constructed a composite index of financial development and knowledge innovation in the carbon pricing model. The results show that carbon pricing, a financial development index, innovation index, and energy demand fail to achieve stringent carbon reduction targets. A U-shaped relationship is found between carbon emissions and per capita income in the absence of a financial development index and trade openness. At the same time, this study shows the monotonic decreasing function in the presence of all factors. The causality estimates confirmed the feedback relationship between carbon pricing and carbon emissions, carbon pricing and the financial index, and the financial development index and innovation index. Further, the causality results established the carbon-led financial development and innovation, growth-led carbon emissions, and trade-led emissions, pricing, and financial development in a panel of selected countries. The estimates of the innovation accounting matrix (forecasting mechanism) confirmed the viability of the environmental sustainability agenda through carbon pricing, knowledge innovation, and financial development over a time horizon. However, these factors are not achievable carbon reduction targets in a given period. The study concludes that carbon pricing may provide a basis for achieving an environmental sustainability agenda through market-based innovations, green financing options, and improved energy resources. This would ultimately help desensitize carbon emissions across countries.

Environmental pollution and energy research and development: an Environmental Kuznets Curve model through quantile simulation approach

Energy research and development (R&D) and environmental sustainability is often referred to as two interrelated trends, especially in the current context of the 4^th industrial revolution. As a primary input of energy innovations, R&D in the energy sector constitutes a vital tool in addressing global environmental and energy challenges. In this frame, we observe the effects of disaggregated energy R&D on environmental pollution within the Environmental Kuznets Curve (EKC) framework in thirteen developed countries over the period 2003-2018. By employing the panel quantile regression technique, we find an inverted U-shaped nexus between economic growth and carbon emissions only in higher carbon-emitting countries, thus, confirming the EKC hypothesis. However, the U-shaped nexus is more predominant in lower carbon-emitting countries. As such, we demonstrate that there is not any single dynamic in the relationship between economic growth and pollution as reported in previous studies. Contrary to expectations, we find that energy efficiency research and development is more effective in curbing carbon emissions compared to fossil fuels and renewable energy research and development. The empirical results indicate also that only energy efficiency R&D mitigates significantly the CO₂ emissions from the 50^th quantile up to 90^th quantile, although the magnitude of the negative sign is more pronounced (in absolute term) at the highest quantile (90th). In this light, our findings would guide policymakers in the establishment of sustainable energy research and development schemes that will allow the preservation of equilibrium for the environment while also promoting energy innovations.

The effects of research and development and financial development on CO2 emissions: evidence from selected WAME economies

Earth is in the Anthropocene era and humankind deteriorates the global environment; thus, there is a dire need for sustainable policies at all levels. This study investigates the causal and long-run association between financial development, research and development expenditures, and carbon dioxide emission including energy intensity and income level for selected West Asia and Middle East (WAME) economies along the belt and road. The long-run panel estimation findings reveal that the research and development expenditures (R&D) are negatively associated with environmental degradation, as they significantly mitigate carbon emissions. In contrast, financial development contributes to environmental degradation. The findings validated the environmental Kuznets curve (EKC) phenomenon for the WAME economies considering R&D and financial development. Further, energy intensity exacerbates environmental quality. Additionally, the findings from Dumitrescu-Hurlin (DH) causal approach reveal bidirectional causal associations between financial development and carbon emissions and between R&D and emissions. The findings have implications for policy and practice to attain environmental sustainability in the selected WAME countries.

Time-frequency relationship between R&D intensity, globalization, and carbon emissions in G7 countries: evidence from wavelet coherence analysis

The seven leading industrial countries, called the G7, are becoming a pivotal group to fulfil their emissions-reduction commitments to manage the climate crisis. This paper investigates the relationships between R&D intensity, globalization, and carbon emissions in the context of the G7 countries for the period from 1970 to 2017. Our analysis, which examines these relationships, focuses on the wavelet coherence approach to conduct time-frequency domain analyses. The empirical results show that there is heterogeneity across different time scales and frequencies for R&D intensity, globalization, and carbon emissions within each country. Specifically, R&D intensity and globalization are negatively correlated with carbon emissions for the G7 countries, except Japan, for which they are positive. The long-term correlations between R&D intensity, globalization, and carbon emissions are higher than those in the short- and medium-term periods. In addition, the multiscale connectedness network results reveal that the strongest bidirectional correlations exist between energy consumption, economic growth, and carbon emissions. Our results provide a useful reference for policymakers in the G7 countries to effectively regulate carbon emissions.