Evolving waste management: The impact of environmental technology, taxes, and carbon emissions on incineration in EU countries.

Amid the urgent global imperatives concerning climate change and resource preservation, our research delves into the critical domains of waste management and environmental sustainability within the European Union (EU), collecting data from 1990 to 2022. The Method of Moments Quantile Regression (MMQR) results reveal a resounding commitment among EU member states to diminish their reliance on incineration, which is evident through adopting green technologies and environmentally conscious taxation policies, aligning with the European Union's sustainability objectives. However, this transition presents the intricate task of harmonizing industrial emissions management with efficient waste disposal. Tailoring waste management strategies to accommodate diverse consumption patterns and unique circumstances within individual member states becomes imperative. Cointegrating regressions highlighted the long-run relationship among the selected variables, while Feasible Generalized Least Squares (FGLS) and Panel-Corrected Standard Errors (PCSE) estimates roughly confirmed MMQR results. ML analyses, conducted through two ensemble methods (Gradient Boosting, GB, and Extreme Gradient Boosting, XGBoost) shed light on the relative importance of the predictors: in particular, environmental taxation, consumption-based emissions, and production-based emissions greatly contribute to determining the variation of combustible renewables and waste. This study recommends that EU countries establish monitoring mechanisms to advance waste management and environmental sustainability through green technology adoption, enhance environmental taxation policies, and accelerate the renewable energy transition.

Evaluating the effects of ECON-ESG on load capacity factor in G7 countries.

For the first time, this study introduces the ECON-ESG quadruple, developed by Isik et al. (2024a), by adding the economy (ECON) dimension to the classical ESG (environment, social, governance) triad. Based on this new concept, it explores the impact of ECON-ESG factors on the Load Capacity Factor (LCF) in G7. The impact of ECON-ESG factors on LCF is vital because sustainability through these factors plays a critical role in a sustainable environment with LCF. CS-ARDL model finds that while governance factors (GOVNF) positively affect LCF, economic factors (ECONF) have negative effects. Environmental factors (ENVF) and social factors (SOCF) do not affect LCF. These findings can be interpreted as follows: (i) Negative effects of ECONF on LCF can be interpreted as high productivity levels in G7 leading to high resource consumption, exceeding biocapacity. (ii) In G7 with high-income levels, increased consumption may lead to overconsumption of natural resources and exceeding biocapacity. (iii) High technological progress in G7 can sometimes paradoxically lead to greater resource consumption rather than encouraging more efficient resource use, increasing an ecological footprint. The positive effects of GOVNF on LCF can be interpreted as follows: (iv) High and quality governance practices and policies in G7 can increase biocapacity. (vi) Under good governance, governments and environmental organizations can positively impact LCF by raising public awareness of environmental issues and enabling society to use natural resources more sustainably. Therefore, policymakers should harmonize economic policies through ECONF and governance policies through social factors (GOVNF), which contradict each other in LCF. Additionally, the effect of the single composite form ECON-ESG introduced and proposed in this study on LCF is found to be negative. This requires policymakers and firms to re-evaluate their sustainability one more time from a holistic perspective, including economic factors, as done in this study.

Geopolitical risk, financial development, and renewable energy consumption: empirical evidence from selected industrial economies.

The rapid rise in climate and ecological challenges have allowed policymakers to introduce stringent environmental policies. In addition, financial limitations may pose challenges for countries looking to green energy investments as energy transition is associated with geopolitical risks that could create uncertainty and dissuade green energy investments. The current study uses PTR and PSTR as econometric strategy to investigate how geopolitical risks and financial development indicators influence energy transition in selected industrial economies. Our findings indicate a non-linear DCPB-RE relationship with a threshold equal to 39.361 in PTR model and 35.605 and 122.35 in PSTR model. Additionally, when the threshold was estimated above, financial development indicators and geopolitical risk positively impacts renewable energy. This confirms that these economies operate within a geopolitical context, with the objective of investing more in clean energy. We report novel policy suggestion to encourage policymakers promoting energy transition and advance the sustainable financing development and ecological sustainability.

The interaction between remittance, FDI, renewable energy, and environmental quality: a panel data analysis for the top remittance-receiving countries.

A country's financing system is essential in addressing sustainable development requirements. National sources and international financial flows contribute to economic growth and environmental quality in many ways, and their impact can be critical. This paper applied panel data analysis using a comparative approach of Pooled Mean Group Auto Regressive Distribute Lags (PMG-ARDL) and Cross Sectionally ARDL (CS-ARDL) to estimate the effects of FDI, renewable energy, and remittance on environmental quality in the top remittance-receiving countries, during 2000-2021. The study emphasized the positive relationship between FDI and carbon emissions. Moreover, renewable energy and remittances revealed an inverted U-shaped relationship with carbon emissions. In the case of developing countries from the panel, remittance improves environmental quality after reaching the threshold. Moreover, for some of the developing countries included in the panel, we found that they do not achieve the desired carbon mitigation effect in their early stages of renewable energy implementation. However, renewable energy becomes a key factor for tackling environmental pollution after a certain threshold. The mixed results determined diverse policy recommendations for various stakeholders.

Impact of transportation infrastructure and urbanization on environmental pollution: evidence from novel wavelet quantile correlation approach.

In terms of achieving sustainable development goals (SDGs), the developing economies are facing many issues, and one of the key issues is environmental degradation. Being a developing economy, Pakistan is also experiencing thought-provoking impacts of global warming and still far away from the ideal track of sustainable development. For addressing environment-related issue and achieving the targets of SDGs, a policy-level reorientation might be necessary. In this view, this study investigates the impact of economic growth, transport infrastructure, urbanization, financial development, and renewable energy consumption on CO2 emissions by using the data of Pakistan during 1990-2020. For this purpose, we use novel wavelet quantile correlation approach. The empirical results of wavelet quantile correlation approach demonstrate that economic growth, transport infrastructure, urbanization, and financial development are responsible for environmental pollution. Whereas, result also claims that renewable energy consumption is a useful tool for reducing environmental pollution in Pakistan. Moreover, the results of FMOLS approach show that 1% increase in economic growth, transportation infrastructure, urbanization, and financial development increases CO2 emissions by 0.240, 0.010, 0.478, and 0.102%, respectively. However, 1% increase in renewable energy usage reduces CO2 emission by 1.083%. Based on the empirical outcomes, this study proposes comprehensive policy framework for achieving the targets of SDG 7 (clean energy), SDG 8 (economic growth), SDG 11 (sustainable cities and communities), and SDG 13 (climate action).

Evaluating the impact of technological innovation and energy efficiency on load capacity factor: empirical analysis of India.

The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.

Sustainable pathways for attaining net-zero emissions in European emerging countries - the nexus between renewable energy sources and ecological footprint.

This study aims to investigate the relationship between renewable energy and ecological footprint during the period of 1994-2018 from selected developing countries in Europe (Czechia, Croatia, Poland, Romania, Romania, and Turkey). In this context, the ecological footprint (EF), which has recently been the most widely used environmental indicator in the literature and is known as the most comprehensive because it includes many environmental factors, has been determined as the dependent variable. As independent variables, renewable energy consumption (REC), energy-related tax revenue (ETR), and energy productivity (EP) are included in the model. GDP and development of environment-related technologies (DET), which affect the ecological footprint in the model, are determined as control variables. As a result of the panel data analysis, according to the Durbin-Hausman cointegration test result, a long-term relationship between the variables was determined. According to the CCE estimator analysis, it can be said that there is a positive relationship between ETR and GDP variables and EF. For the AMG estimator analysis, it can be said that there is a positive relationship between GDP and EP variables and EF. Finally, according to the results of the Konya Causality test, a unidirectional causality relationship is detected from environmental technologies to the ecological footprint in Turkey, and a unidirectional causality relationship from the ecological footprint to GDP in Czechia, Romania, and Turkey. Furthermore, no causality relationship is detected between other variables. Based on the results, several policy implications are suggested.

Modelling the role of energy price movements toward economic stability in Malaysia: new evidence from wavelet-based analysis.

Energy is one of the prime factors in influencing the sustainable development of a country. Different energy sources play important roles in driving the income growth of different economic sectors such as industrial, agricultural, and services. Fossil fuels, however, have come under strong criticism for actively accelerating climate change. As such, it is imperative to investigate the contributions of various energy sources toward sustainable growth. With Malaysia as the test-bed, the present study analyzes the impact of energy prices on economic stability using the novel wavelet-based analysis. Specifically, the study analyzed the impact of crude oil, natural gas, and gasoline prices on the economic (brown) and green growth from 1995 to 2020. The results show that in continuous wavelet transform, the cone of influence of all five factors exhibits strong short-run variance and fluctuations from 2005 to 2013. However, the intensity of brown growth is more influential than green growth. Similarly, in wavelet coherence graphs, the downward right arrows indicate positively significant associations between crude oil prices, natural gas prices, and gasoline prices with brown and green growth. Additionally, wavelet-based Granger causality reveals a bidirectional causal relationship between all variables. The results thus strongly suggest that energy prices predominantly affect the economic (brown) and green growth progression of the Malaysian economy. The study concludes with some suggested implications to augment the country's sustainable growth.

Can environmentally friendly technology help China to achieve a carbon neutrality target by 2060? An asymmetrical based study in China.

Climate change-related environmental challenges are prompting an increasing number of countries to set carbon-neutral targets. Since 2007, China has pursued numerous initiatives to attain carbon neutrality by 2060, including increasing the percentage of non-fossil energy, developing zero-emission and low-emission technologies, and taking actions that reduce CO2 emissions or boost carbon sinks. As a result, utilizing quarterly data from 2008/Q1 to 2021/Q4, and applying the nonlinear autoregressive distributed lag (NARDL) approach, this study evaluates the effectiveness of the measures taken by China to improve the ecological situation. The results of the study show that the measures enacted to reduce CO2 emissions did not accomplish their ultimate purpose. Specifically: (i) high-speed railways and new energy vehicles do not improve the environment in the long run; (ii) investments and patents in the energy sector, as well as low-carbon sources, will degrade the environment; (iii) only investments in the treatment of environmental pollution will improve the ecological situation. Various policy implications are suggested based on the empirical results in order to attain environmental sustainability.

The Dynamic Nexus Between International Tourism and Environmental Degradation in Top Twenty Tourist Destinations: New Insights From Quantile-on-Quantile Approach.

Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.

Reducing environmental pollution by organisational citizenship behaviour in hospitality industry: the role of green employee involvement, performance management and dynamic capability.

Being a prominent tourist destination, the hotel industry's demand in Malaysia has been increasing day by day. There is still a shortage of studies focusing on how hotels can make environmental management routine work, take environmental laws seriously and be more responsive to the environment. This study focused on the connections between green employee involvement, green performance management and green dynamic capability in implementing environmental law in the hospitality industry. The study also evaluates the mediating role of implementing environmental law between green employee involvement, green performance management, green dynamic capability and organisational citizenship behaviour to reduce pollution. This study employed a quantitative approach to test the hypotheses and a convenient sampling method to collect the data from hotel employees. Out of 600 distributed questionnaires, useable responses were 253 to proceed with data analysis. Data were analysed through structural equation modelling (SEM) using the Smart-PLS and SPSS. The relationship between green employee involvement, green performance management, green dynamic capability and implementation of environmental laws was discovered and considered unique in the hotel industry in Malaysia. The study further established the mediating role of environmental law between independent and dependent variables.

Enabling green shared vision: linking environmental strategic focus and environmental performance through ISO 14001 and technological capabilities.

Consistent with the worldwide call to combat environmental degradation concerns and advance sustainable development, there is increasing pressure on organizations to ensure organizational strategies include green initiatives. In this regard, environmental strategic focus is a relevant concept for scholars and business leaders. Underpinned by dynamic capability and stakeholder theory, the present study hypothesizes that ESF derives environmental performance, coordinated by mediating role of green shared vision that strategic environmental planning and decision making. Additionally, the current study employed ISO 14001 and technological capability as moderators between ESF and the green shared vision link. Methodologically, the data for this study was collected from 162 senior managerial officials working in EMS 14,001-accredited manufacturing firms in Malaysia. The data were analyzed with the AMOS 23 software to perform covariance-based structural equation modeling (CB-SEM), and then hierarchical regression analysis and moderated-mediation analysis were applied with SPSS 25. The findings confirmed that ESF is positively linked to environmental performance. The results validate that green shared vision acts as a positive mediator between ESF and environmental performance, in which the creation and sharing of knowledge embedded in a green shared vision serve as enablers to create higher environmental performance. The current study also validates a significant moderating role of ISO 14001 and technological capability between ESF and green shared vision. The study confirms how environmental strategies are integrated into environmental management processes that can serve as a source of dynamic capabilities.

Integration of renewable energy and technological innovation in realizing environmental sustainability: the role of human capital in EKC framework.

For the purpose of this study, the role of technological innovation is examined. Few studies have examined empirically and theoretically the relationship between technological innovation and ecological footprint in conjunction with other factors, such as the human capital index and renewable energy sources, such as biofuels and nuclear power. This study examines the impact of technological innovation on G-7 countries' ecological footprints from 1990 to 2020. A cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model is used in the study. The results of the study show that technological innovation minimizes the ecological footprint. A lower ecological footprint is also associated with increased usage of human capital and renewable energy. Depletion of the natural environment is a short-term and long-term consequence of increased GDP growth. Our results confirm that ecologically sustainable technology enhances the quality of the environment. Consistent panel causality results were achieved. In the context of the G-7 countries, our study's results could support the idea that there are new policy ideas that could help achieve the Sustainable Development Goals (SDG 3, 4, 7, 8, 9, and 13).

The impact of renewable and non-renewable energy consumption on carbon emission intensity in China: Fresh evidence from novel dynamic ARDL simulations.

Given the dire state of global warming, it is critical to investigate the elements that influence carbon emissions intensity and to precisely monitor progress in carbon emissions intensity growth in order to meet the aim of lowering CO2 emissions. This research explores the association among renewable energy and non-renewable energy consumption, the urban population, research and development expenditure, technological innovation, and carbon emissions intensity in China using annual time series data over the period 1990 to 2019. The Dynamic ARDL simulation technique was utilized to investigate the long-run and short-run correlations between renewable and non-renewable energy consumption and CEI. The results suggest that there is strong evidence of a long-run correlation between the variables. The findings indicate that in the long-run, renewable energy and non-renewable energy consumption, and research and development expenditure have a positive influence on CEI by 0.27%, 0.75%, and 0.21%, whereas the urban population has a negative influence by 2.31%, respectively. However, the urban population and technological innovation have positively affected the short-run CEI by 12.17% and 0.23%, respectively. Policies should focus on continuous investment in renewable energy sources, clean energy innovation, improving energy efficiency, forest restoration, and carbon neutrality initiatives to lessen the environmental extreme pressure associated with CO2 emissions.

Recent scenario and nexus of globalization to CO2 emissions: Evidence from wavelet and Quantile on Quantile Regression approach.

The ubiquitous increase in globalization and high carbon emissions, aiming to achieve non-zero emissions in the future, is a feasible challenge for a sustainable environment. Our study aims to investigate the impact of economic globalization on carbon emissions of the developed country covering the period of 1970-2019. The Wavelet Coherence (WC) and Quantile on Quantile Regression (QQR) approach have been used to analyse co-movements and feedback linkages of CO2 emissions with globalization, economic growth, and consumption of coal at different quantiles. The results obtained from WC show that there exist significant positive co-movements in the in-phase and leading globalization, economic growth, coal consumption with CO2 emissions. Further, the results of QQR indicate the existence of a positive and significant linkage between coal consumption and CO2 emissions for the majority of quantiles, the positive. Still, there is an insignificant association between CO2 with globalization and economic growth at most quantiles. Lastly, the quantile regression (QR) comparison with QQR suggests that our model is a good fit as the intercept estimates are similar and the slope coefficients follow a similar trend. To conclude, CO2 emissions have positive associations and co-movements with globalization, economic growth, and coal consumption, but their statistical significance varies and directly affects the Country.

Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach.

The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.

The role of economic complexity in the environmental Kuznets curve of MINT economies: evidence from method of moments quantile regression.

In the face of mounting climate change challenges, reducing emissions has emerged as a key driver of environmental sustainability and sustainable growth. Despite the fact that research has been conducted on the environmental Kuznets curve (EKC), few researchers have analyzed this in the light of economic complexity. Thus, the current research assesses the effect of economic complexity on CO2 emissions in the MINT nations while taking into account the role of financial development, economic growth, and energy consumption for the period between 1990 and 2018. Using the novel method of moments quantile regression (MMQR) with fixed effects, an inverted U-shape interrelationship is found between economic growth and CO2 emissions, thus validating the EKC hypothesis. Energy consumption and economic complexity increase CO2 emissions significantly from the 1st to 9th quantiles. Furthermore, there is no significant interconnection between financial development and CO2 emissions across all quantiles (1st to 9th). The outcomes of the causality test reveal a feedback causal connection between economic growth and CO2, while a unidirectional causality is established from economic complexity and energy use to CO2 emissions in the MINT nations. Based on the findings, we believe that governments should stimulate the financial sector to provide domestic credit facilities to industrialists, investors, and other business enterprises on more favorable terms so that innovative technologies for environmental protection can be implemented with other policy recommendations.