Energy security-related risks and the quest to attain USA's net-zero emissions targets by 2050: a dynamic ARDL simulations modeling approach.

The Russia-Ukraine war and other similar conflicts across the globe have heightened risks to the United States of America's (USA's) energy security. However, little is known about the severity of the effect of energy security risks on the USA's quest to attain net-zero emissions targets by 2050. To this end, we examine the effect of energy security risks on the load capacity factor (LCF) in the USA. Employing a time series dataset spinning from 1970 to 2018, the results of the Dynamic Autoregressive Distributed Lag (ARDL) simulations model suggest that energy security-related risk hampers the long-term net-zero emissions targets with its effect decreasing over time until it varnishes in about 5 years time. The results also show that foreign direct investment (FDI) inflows, renewable energy consumption, and green technology have long- and short-run positive effects on the LCF. Conversely, economic expansion and urbanization impede environmental quality by lowering the LCF both in the long run and short run. These findings are upheld by the outcomes of the multivariate quantile-on-quantile regression. Therefore, the study advocates for the consumption of renewable energy, investment in green technologies, and FDI inflows to mitigate energy security-related risks and attain the net-zero emissions targets by 2050 in the USA.

Evaluating the role of financial globalization and oil consumption on ecological quality: A new perspective from quantile-on-quantile granger causality.

Global warming has progressed into a pressing global concern, primarily driven by human activities. To address this issue, it is vital to identify the key drivers of ecological quality and develop effective policies in response. Consequently, this study seeks to empirically examine the causal effect of financial globalization, economic growth, economic policy uncertainty, and oil consumption on the load capacity factor (LF) in Brazil. The analysis utilizes quarterly data spanning from 1990 to 2021. In this pursuit, the study introduces an array of quantile-based methodologies, encompassing quantile ADF, PP, and KPSS tests, as well as the innovative Quantile-on-Quantile Granger Causality (QQGC) approach. The QQGC represents a notable advancement beyond traditional quantile Granger causality (QGC) methods, as it accounts for the conditional distribution of dependent and independent variables. This study bridges a critical gap in the existing literature by introducing the QQGC to capture the causal influence of the regressors on LF. The findings derived from the QQGC analysis indicate that financial globalization, economic growth, economic policy uncertainty, and oil consumption significantly predict LF across all quantiles. These results offer valuable insights that can inform the formulation of effective policies and strategies aimed at addressing ecological quality and mitigating the impacts of global warming.

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.

Dynamic risk connectedness of crude oil price and sustainable investment in the United States: evidence from DCC-GARCH.

Sustainable investment is widely regarded as an important market-based approach to achieving inclusive green growth. To achieve the inclusive green growth objective, companies providing sustainable products must be profitable enough to attract private capital. Oil price changes can however affect the profitability of such companies. This study assesses volatility transmission between crude oil prices and sustainable investment in the USA. Using the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) method, daily data from September 28, 2012, to October 19, 2022, is analyzed. There are several key findings from this analysis. The risk connectedness of crude oil and sustainable investment is found to vary with time. Results further show that the risk connectedness increases in periods of important economic and geopolitical events. The greatest risk connectedness of crude oil and sustainable investment is observed during the outbreak of coronavirus disease (COVID-19). Moreover, the result shows that crude oil is the main risk transmitter, whereas, both the energy efficiency and pollution mitigation indices (i.e., sustainable investment) are risk receivers, and crude oil is constantly dominating sustainable investment. The study findings provide valuable insights for investors and policymakers alike.

Impact of green technological innovations on environmental quality for Turkey: evidence from the novel dynamic ARDL simulation model.

The contribution of this research is to provide empirical evidence that investing in green technology innovation (GTI) can reduce the ecological footprint in Turkey, which can lead to sustainable economic growth and environmental quality. The research also highlights the importance of controlling energy consumption, GDP, trade openness, and urbanization, as these variables have a positive or negative effect on ecological footprint. The findings of this research can be useful for the Turkish government, policymakers, and environmentalists to promote the implementation of GTI and eco-friendly resources, which can reduce the impact of climate change and contribute to economic prosperity. Overall, this research provides important information for decision-makers to adopt policies that prioritize green innovation and environmental protection in Turkey.

Reconsidering the environmental Kuznets curve, pollution haven, and pollution halo hypotheses with carbon efficiency in China: A dynamic ARDL simulations approach.

Given a new perspective on the environmental hypothesis, this paper systematically investigates the validity of the environmental Kuznets curve (EKC), pollution haven, and pollution halo hypotheses using carbon efficiency as the dependent variable. Applying the dynamic autoregressive distributed lag simulations based on the annual time series data over the period 1990-2019, the study found that real GDP per capita has negative effects on China's environmental quality both in the short and long run, whereas the square of real GDP per capita has positive impacts. This validates the EKC hypothesis for China. Furthermore, foreign direct investment has negative effects on environmental quality in China, implying that the case of China exemplifies the pollution haven hypothesis and not the pollution halo hypothesis. The empirical results also demonstrate that energy efficiency and trade openness improve China's environmental quality both in the short run and long run. These findings, therefore, provide insights into achieving the ambitious climate goals in China by 2050.

A consideration of the environmental externality of Turkey's integration into global value chains: evidence from dynamic ARDL simulation model.

The phenomenal growth experienced by Turkey at the turn of the millennium is attributed in part to increased participation in global value chains. While participation in global value chains has been beneficial to the Turkish economy, it also poses unique environmental challenges. Consequently, this study focuses on shedding some light on the environmental externality of Turkey's participation in global value chains. This article examines the environmental effects of Turkey's participation in global value chains for the period 1990-2018, using a dynamic ARDL analysis. The study further compares the environmental effects of Turkey's backward and forward linkages into global value chains, so as to determine which contributes more to carbon emissions. The cointegration test results and dynamic ARDL simulations confirm the existence of a long-run relationship between the environment and global value chain participation. All measures of global value chain participation display a positive long-run impact on carbon emissions. The results also show that the polluting effect of backward and forward linkages into global value chains is not too different. The study finding suggests that Turkey is being assigned segments of the value chain that require dirtier production processes through incentives from global trade integration, thus making Turkey a pollution haven. It is concluded that this is because other countries continually source for inputs requiring dirty production processes from Turkey, as Turkey also exports final goods that are produced using eco-unfriendly techniques. Policymakers in Turkey therefore need to follow more environmentalist policies in the process of global value chain participation.

Is reducing fossil fuel intensity important for environmental management and ensuring ecological efficiency in China?

Since China is a country with high environmental pollution, researchers have intensively studied China's environmental problems using various environmental indicators such as carbon emissions and ecological footprint. Unlike previous literature, this study analyzes the effects of economic growth, globalization, foreign direct investment, and fossil energy intensity on ecological efficiency in China. As an innovation to the literature, the study examines the Chinese ecosystem simultaneously with its economic and environmental aspects by focusing on ecological efficiency. To this end, the study applies dynamic autoregressive distributed lag (DARDL) simulations and kernel-based regularized least squares (KRLS) methods for the period from 1990 to 2018. The results of the DARDL simulations show that globalization, and economic growth enhance ecological efficiency in China. The findings also demonstrate that both foreign direct investment and fossil fuel intensity have a negative impact on environmental quality in China. Based on these results, the study suggests that the Chinese government should adopt policies to channel foreign direct investment into environmentally friendly production, reduce fossil fuel intensity, and improve ecological efficiency by making use of environmentally friendly technologies provided by globalization and economic development.

Characterization and assessment of a large-scale domestic advanced wastewater treatment plant in Turkey.

The paper presents new studies about the removal efficiencies and characterization of the Municipal Wastewater Treatment Plant (MWWTP) in Kayseri, Turkey, which is serving for 800,000 population equivalents with the capacity of 110,000 m(3)/day, between 2006 and 2009. Kayseri discharges its effluents to Karasu Creek that downstream joins the Kizilirmak river, the longest river in Turkey discharging into the Black Sea. Four years of operation data between 2006 and 2009 calendar years were obtained from KASKI General Directorate. Influent and effluent samples were collected daily and suspended solids (SS), chemical oxygen demand (COD), biochemical oxygen demand in 5 days (BOD(5)), total nitrogen (TN), and total phosphorus (TP) were measured, aiming to study the evolution of the removal efficiencies for each year. The following yearly mean removal efficiencies were performed in the treatment plant: 94%, 97%, 97%, 95% for SS; 94%, 96%, 95%, 95% for COD; 98%, 98%, 98%, 98% for BOD(5); 84%, 87%, 89%, 82% for TN; and 71%, 86%, 80%, 86% for TP, in 2006, 2007, 2008, and 2009, respectively. The performance of Kayseri MWWTP was given both in terms of influent and effluent quality and in comparison with the current legislation on discharge limits to the receiving body. During the studied period, mean concentrations in the effluent did not exceed the imposed limits, but sometimes, higher values were noticed for SS, TN, and TP. In conclusion, the plant performances concerning these parameters were excellent and Kayseri MWWTP was operating efficiently according to the conventional control parameters.