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Over the last 50 years, urban population of Turkey has grown from 25 to 75%. Urbanization is highly linked with one of the most important global problems which is global warming through accelerating economic growth, energy consumption, and trade openness that are considered to be the main indicators of climate change in environmental literature. The main purpose of the present research is to examine the long-run effect of economic growth, energy consumption, trade openness, and urbanization on environmental degradation and causal link among the indicators under consideration in Turkey by taking into account the moderating role of urbanization over the period of 1960-2016. Aiming to establish robust findings, this study utilized both traditional and modern econometric techniques, including Bayer and Hanck cointegration, Gregory and Hansen cointegration, fully modified ordinary least squares (FMOLS) and dynamic ordinary least square (DOLS), Granger causality, Toda-Yamamoto causality, and Gradual Shift causality tests. The cointegration tests reveal that carbon dioxide (CO 2 ) emissions and economic growth, energy consumption, trade openness, urbanization, and the moderating role of urbanization are cointegrated. The outcomes of the long-run estimators-FMOLS and DOLS-reveals that environmental Kuznets curve (EKC) hypothesis is valid and the existence of moderating role of urbanization on indicators of CO 2 emissions is confirmed for the case of Turkey. Moreover, the causality tests mirror that while energy consumption, trade openness, and urbanization are important for predicting CO 2 emissions, the moderating role of urbanization leads CO 2 emissions in the short run.

The purpose of the present study is to explain the long-run and causal effects of innovation, financial development, and transportation infrastructure on CO 2 emissions using the combined cointegration and wavelet coherence approaches over the period from 1971 to 2018, while using economic growth as a control variable in the model. The outcomes of the Bayer-Hanck cointegration test show that there is an important cointegration equation among CO 2 emissions, innovation, financial development, transportation infrastructure, and real GDP. Moreover, the findings from a wavelet power spectrum reveal that there is a significant vulnerability in innovation, financial development, transportation infrastructure, and CO 2 emissions at different time frames and frequencies. Furthermore, the outcomes of wavelet coherence approach reveal that (i) Innovation is observed as a significant predictor of CO 2 emissions over the period from 2007 to 2013; (ii) In the long run, there are negative correlations between CO 2 emissions and financial development; (iii) Over the periods from 2000 to 2015, and from 1985 to 1989, transportation significantly causes CO 2 emissions. Our findings have substantial policy implications that suggest there is a need to strengthen innovation and transportation infrastructure to achieve environmental sustainability targets., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The role of a reliable carbon emissions measurement is important for devising a relevant climate policy to deals with environmental problems. Based on trade adjusted statistics of carbon emissions, a relevant climate policy response can be provided, especially following the conference of Paris (COP, 21). To explore the unidentified determinants of CO 2 emissions in G7 countries from 1990 to 2017, this study uses second-generation panel co-integration methodologies. Results of P&Y's slope heterogeneity test and Pesaran's CD test confirm the existence of correlation among cross-sectional units and slope heterogeneity across countries. The results confirm a stable long-run relationship among CO 2 emissions, trade, income, environmental innovation and renewable energy consumption. In the long run, imports and income enhance consumption-based carbon emissions, while exports, environmental innovation and renewable energy consumption are helpful in abating consumption-based CO 2 emissions. The results are also reconfirmed by Augmented Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG) methods. Based on the results of the Dumitrescu and Hurlin (2012) Granger causality test, it is argued that any policy to target exports, imports, income and environmental innovation significantly changes CO 2 emissions. On the contrary, any policy to support environmental degradation does not affect these variables. Moreover, any policy to target renewable energy sources significantly affects consumption-based CO 2 emissions and vice versa. This might lead the policymakers to adopt strategies that are eco-friendly such as the deployment of renewable energy and environmental innovation to attain sustainable environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing for financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The present study aims to explore the co-movement between urbanization and environmental sustainability for the period 1950 to 2014 using the wavelet coherence technique within the global framework. The wavelet coherence technique allows us to investigate both the long-run and short-term causal relationships between urbanization and environmental sustainability within the global framework. The findings reveal that (i) wavelet correlation from the global perspectives indicates a significant wavelet relationship between urbanization and environmental sustainability for medium- and long-term horizons; however, the correlations are not significant for the short-term horizons; (ii) significant vulnerabilities in urbanization and environmental sustainability are observed at different periods and different frequency levels; (iii) urbanization has reliable power for explaining environmental sustainability at different periods between 1970 and 2000. Based on our study, we suggest that global urban planners and policymakers should support modern environment-friendly technologies and renewable energies to control global CO 2 emissions and pollutions created by industrialization; policy action to fight climate change is as well recommended as evidence supports to compact city theory.

Given that the volume of carbon emissions in the US is a significant share of the global greenhouse gas emissions, some salient factors are being currently examined so as to reverse the threat to global environmental sustainability. To this regard, the current study investigates the co-movement and long-term and short-term causal relationship between CO 2 emission (a proxy for environmental quality) and renewable consumption, immigration, and healthcare by using the wavelet coherence approach which primarily provides information on dynamic correlations over time and for different time scales. The coherence approach allows the one-dimensional time data into the bi-dimensional time-frequency sphere between the variables. In addition to investigating the causal relationship between CO 2 and renewable consumption, immigration, and healthcare, this study also employs gradual-shift causality and Toda-Yamamoto causality tests. With this, the study found a high variation for CO 2 emission in the US at 8 scales (8 quarters) from 1999 to 2008. Additionally, there is significant feedback causality between CO 2 emission and renewable consumption at different scales while a positive correlation between the variables is observed in the short run. Similarly, the result reveals that immigration significantly causes CO 2 emission in the US from 2008 to 2010 and a two-way causality is detected between CO 2 emission and healthcare at different frequencies and time period. Moreover, the Toda-Yamamoto causality and gradual-shift causality tests provide supportive evidence to the outcomes of the wavelet coherence-based causality test in this study. Overall, the investigation offers significant policy directive especially toward addressing the potential adverse effects from the country's immigration and healthcare amendments.

This study aims to investigate the long-run and causal effects of energy consumption, economic growth, urbanization, and trade openness on CO 2 emissions in Turkey using newly developed econometric techniques. To our best knowledge, there has been no study examining the relationship between CO 2 emissions, energy consumption, trade openness, urbanization, and economic growth in Turkey. Therefore, this study proposes to fill this gap in the literature. In this study, we use time series data covering the years between 1960 and 2015. To capture long-run effects, we used ARDL, FMOLS, and DOLS estimators, while wavelet coherence technique is used to explore causal effects among the variables. Our results reveal that (i) there is a long-run equilibrium relationship between CO 2 emissions and energy consumption, economic growth, urbanization, and trade openness; (ii) in the long-run, CO 2 emission in Turkey is significantly triggered by energy consumption, economic growth, and urbanization; and (iii) the results of the wavelet coherence-based causality test provide supportive evidence to the long-run estimations of this study.