Pub Date : 2023-11-08DOI: 10.1177/0958305x231210994
C Sonia, S Tamilselvi
This article proposes a new energy conversion structure by employing a hybrid approach for grid-tied photovoltaic (PV) applications. This structure depends on the LeBlanc transformer and multilevel inverter (MLI). The proposed hybrid system combines the honey badger algorithm (HBA) and the reptile search algorithm (RSA). Crocodiles hunting behavior is enhanced by the HBA technique, also known as the IRSA technique. Voltage source inverters (VSI) are used in the proposed multilevel power converter. The MLI output is attached to the LeBlanc transformer. Multi-string technology is essential to the PV system's configuration. This innovative power converter's structural layout allows for an output voltage at the MLI's output. The proposed IRSA approach is utilized to regulate this power converter. This control system permits a fast and robust response from the MLI. This is also ensured by using the IRSA technique. The performance of the proposed hybrid method is run in MATLAB, and the performance is compared with various existing methods. From the simulation, the proposed approach-based efficiency is higher than the existing one. The proposed method shows a high efficiency of 99% compared with other existing methods, such as the salp swarm algorithm (SSA), bee colony optimization (BCO), and grasshopper optimization algorithm (GOA).
{"title":"A novel power conversion structure for grid-connected photovoltaic applications based on MLI and LeBlanc transformer using IRSA technique","authors":"C Sonia, S Tamilselvi","doi":"10.1177/0958305x231210994","DOIUrl":"https://doi.org/10.1177/0958305x231210994","url":null,"abstract":"This article proposes a new energy conversion structure by employing a hybrid approach for grid-tied photovoltaic (PV) applications. This structure depends on the LeBlanc transformer and multilevel inverter (MLI). The proposed hybrid system combines the honey badger algorithm (HBA) and the reptile search algorithm (RSA). Crocodiles hunting behavior is enhanced by the HBA technique, also known as the IRSA technique. Voltage source inverters (VSI) are used in the proposed multilevel power converter. The MLI output is attached to the LeBlanc transformer. Multi-string technology is essential to the PV system's configuration. This innovative power converter's structural layout allows for an output voltage at the MLI's output. The proposed IRSA approach is utilized to regulate this power converter. This control system permits a fast and robust response from the MLI. This is also ensured by using the IRSA technique. The performance of the proposed hybrid method is run in MATLAB, and the performance is compared with various existing methods. From the simulation, the proposed approach-based efficiency is higher than the existing one. The proposed method shows a high efficiency of 99% compared with other existing methods, such as the salp swarm algorithm (SSA), bee colony optimization (BCO), and grasshopper optimization algorithm (GOA).","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"1 1‐2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135393306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1177/0958305X221112913
Muhammed Sehid Gorus, E. Karagol
For a few decades, factors affecting environmental deterioration have been at the center of much interest This paper examines the impact of income level, disaggregated energy consumption, types of globalization level, and urbanization on per capita ecological footprint by utilizing novel machine learning techniques (tree regression, boosting, bagging, and random forest) for 27 OECD countries during 1971–2016. It is found that the random forest algorithms best fit the dataset. The empirical results exhibit that oil product consumption, electricity consumption, and gross domestic product are the most significant variables for our model. Besides, the partial dependence plots results show that economic growth and especially fossil fuel energy consumption damage the environment. These findings have important implications for both developed and developing countries for designing proper energy and environmental policies. Especially, policymakers should focus on sustainable development instead of plain economic growth.
{"title":"Factors affecting per capita ecological footprint in OECD countries: Evidence from machine learning techniques","authors":"Muhammed Sehid Gorus, E. Karagol","doi":"10.1177/0958305X221112913","DOIUrl":"https://doi.org/10.1177/0958305X221112913","url":null,"abstract":"For a few decades, factors affecting environmental deterioration have been at the center of much interest This paper examines the impact of income level, disaggregated energy consumption, types of globalization level, and urbanization on per capita ecological footprint by utilizing novel machine learning techniques (tree regression, boosting, bagging, and random forest) for 27 OECD countries during 1971–2016. It is found that the random forest algorithms best fit the dataset. The empirical results exhibit that oil product consumption, electricity consumption, and gross domestic product are the most significant variables for our model. Besides, the partial dependence plots results show that economic growth and especially fossil fuel energy consumption damage the environment. These findings have important implications for both developed and developing countries for designing proper energy and environmental policies. Especially, policymakers should focus on sustainable development instead of plain economic growth.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"21 1","pages":"2601 - 2618"},"PeriodicalIF":4.2,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139298830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1177/0958305X221108498
Ngo Thai Hung
In connection with environmental degradation in Vietnam, known as an emerging economy, very limited studies have been implemented to demonstrate the environmental aspects of the country's core policies, as well as recent economic policies such as economic growth and globalization policies. Given this driving force, this paper uncovers a novel perspective on the causal associations between CO2 emissions, economic growth, and globalization in Vietnam using wavelet analysis. The empirical results provide evidence of the interconnections between the selected indicators through time and frequency. More accurately, the findings uncover that economic growth and globalization significantly increase carbon dioxide emissions in Vietnam in the medium and long run. These outcomes highlight the importance of policymakers properly coordinating policies to address Vietnam's severe environmental degradation. Furthermore, Vietnam should continue relevant policy reforms such as encouraging investment, allowing for effective governance and promoting human capital accumulation.
{"title":"Causal relationship between globalization, economic growth and CO2 emissions in Vietnam using Wavelet analysis","authors":"Ngo Thai Hung","doi":"10.1177/0958305X221108498","DOIUrl":"https://doi.org/10.1177/0958305X221108498","url":null,"abstract":"In connection with environmental degradation in Vietnam, known as an emerging economy, very limited studies have been implemented to demonstrate the environmental aspects of the country's core policies, as well as recent economic policies such as economic growth and globalization policies. Given this driving force, this paper uncovers a novel perspective on the causal associations between CO2 emissions, economic growth, and globalization in Vietnam using wavelet analysis. The empirical results provide evidence of the interconnections between the selected indicators through time and frequency. More accurately, the findings uncover that economic growth and globalization significantly increase carbon dioxide emissions in Vietnam in the medium and long run. These outcomes highlight the importance of policymakers properly coordinating policies to address Vietnam's severe environmental degradation. Furthermore, Vietnam should continue relevant policy reforms such as encouraging investment, allowing for effective governance and promoting human capital accumulation.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"13 1","pages":"2386 - 2412"},"PeriodicalIF":4.2,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139298454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1177/0958305x231204030
Yiniu Cui, Cheng Zhong, Jianhong Cao, Mengyao Guo
This study employs panel data encompassing a time frame from 2012 to 2020, collected from 30 provinces in China. By employing a geographic Durbin model and introducing green technological innovation as an intermediary variable, the study explores the relationship between green funds and PM2.5 levels on a spatial scale. The research takes a spatial perspective to explore the links between green finance and PM2.5 emissions, with a specific focus on the intermediary role played by green technology innovation. The findings offer comprehensive insights into enhancing air quality in China, promoting the country's transition towards sustainability, improving the overall human living environment, and generating novel ideas for tackling air pollution challenges. The findings of this study are as follows: (1) The progress of green finance proves to be an effective means of reducing local PM2.5 emissions. Additionally, it generates spillover effects on neighboring regions, promoting the growth of green finance and consequently leading to a decrease in PM2.5 emissions in adjacent areas. (2) In the study exploring the relationship between green financing and PM2.5, green technological innovation plays a crucial mediating role. By efficiently allocating financial resources during China's pivotal green revolution phase, green finance offers funding support to enterprises for the advancement of green technology. This, in turn, contributes to the reduction of PM2.5 emissions. As a consequence, this leads to a decline in energy consumption, pollution emissions, and PM2.5 levels. Additionally, with the continuous improvement in green technological innovation, the reverse effect between green finance and PM2.5 is becoming stronger and stronger. (3) The relationship between the two has obvious regional heterogeneity between the north and south regions of China.
{"title":"Can green finance effectively mitigate PM2.5 pollution? What role will green technological innovation play?","authors":"Yiniu Cui, Cheng Zhong, Jianhong Cao, Mengyao Guo","doi":"10.1177/0958305x231204030","DOIUrl":"https://doi.org/10.1177/0958305x231204030","url":null,"abstract":"This study employs panel data encompassing a time frame from 2012 to 2020, collected from 30 provinces in China. By employing a geographic Durbin model and introducing green technological innovation as an intermediary variable, the study explores the relationship between green funds and PM2.5 levels on a spatial scale. The research takes a spatial perspective to explore the links between green finance and PM2.5 emissions, with a specific focus on the intermediary role played by green technology innovation. The findings offer comprehensive insights into enhancing air quality in China, promoting the country's transition towards sustainability, improving the overall human living environment, and generating novel ideas for tackling air pollution challenges. The findings of this study are as follows: (1) The progress of green finance proves to be an effective means of reducing local PM2.5 emissions. Additionally, it generates spillover effects on neighboring regions, promoting the growth of green finance and consequently leading to a decrease in PM2.5 emissions in adjacent areas. (2) In the study exploring the relationship between green financing and PM2.5, green technological innovation plays a crucial mediating role. By efficiently allocating financial resources during China's pivotal green revolution phase, green finance offers funding support to enterprises for the advancement of green technology. This, in turn, contributes to the reduction of PM2.5 emissions. As a consequence, this leads to a decline in energy consumption, pollution emissions, and PM2.5 levels. Additionally, with the continuous improvement in green technological innovation, the reverse effect between green finance and PM2.5 is becoming stronger and stronger. (3) The relationship between the two has obvious regional heterogeneity between the north and south regions of China.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"62 37","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135863515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.1177/0958305x231204958
Dervis Kirikkaleli, Kwaku Addai
Trade effects on atmospheric air contamination of countries have received increasing global policy focus over the past few decades. The United Kingdom is committed to changing the complexities in international trade, current pathways to economic output pursuit, and carbon dioxide emission toward realizing the goals of the Paris Agreement and Kyoto Protocol. This research is motivated to explore the asymmetric long-run impact of demand-based CO 2 emissions productivity on production-based CO 2 emissions for the UK economy. Data for this assessment was drawn from 1990 to 2019 and analyzed using Gregory-Hansen cointegration, nonlinear autoregressive distributed lag (NARDL), and frequency domain causality techniques. Gregory-Hansen estimates for cointegration provide integration evidence for all variables. Estimates for NARDL long-run cointegration indicate (i) demand-based CO 2 emissions productivity is a credible variable that contributes to reducing production-based CO 2 emissions in the UK; (ii) both economic output and globalization contribute in rising production-based CO 2 emissions in the UK; and (iii) the frequency domain causality test indicates one direction causality from demand-based CO 2 emissions productivity, output, globalization, and consumption of green energy to production-based CO 2 emissions in the UK.
{"title":"The asymmetric and long-run effect of demand-based CO<sub>2</sub> emissions productivity on production-based CO<sub>2</sub> emissions in the UK","authors":"Dervis Kirikkaleli, Kwaku Addai","doi":"10.1177/0958305x231204958","DOIUrl":"https://doi.org/10.1177/0958305x231204958","url":null,"abstract":"Trade effects on atmospheric air contamination of countries have received increasing global policy focus over the past few decades. The United Kingdom is committed to changing the complexities in international trade, current pathways to economic output pursuit, and carbon dioxide emission toward realizing the goals of the Paris Agreement and Kyoto Protocol. This research is motivated to explore the asymmetric long-run impact of demand-based CO 2 emissions productivity on production-based CO 2 emissions for the UK economy. Data for this assessment was drawn from 1990 to 2019 and analyzed using Gregory-Hansen cointegration, nonlinear autoregressive distributed lag (NARDL), and frequency domain causality techniques. Gregory-Hansen estimates for cointegration provide integration evidence for all variables. Estimates for NARDL long-run cointegration indicate (i) demand-based CO 2 emissions productivity is a credible variable that contributes to reducing production-based CO 2 emissions in the UK; (ii) both economic output and globalization contribute in rising production-based CO 2 emissions in the UK; and (iii) the frequency domain causality test indicates one direction causality from demand-based CO 2 emissions productivity, output, globalization, and consumption of green energy to production-based CO 2 emissions in the UK.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"127 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136069023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-29DOI: 10.1177/0958305x231204033
Muhammad Salam, Xu Yingzhi
Since the official launch of the Belt and Road Initiative (BRI) in 2013, China and the BRI countries have been working for the implementation of certain environmental measures to make the BRI project green and clean. For this purpose, China and the BRI countries have planned to implement certain environmental measures. Although China can efficiently implement these measures, most of the BRI countries face technological deficiencies and lack of proper environmental plannings. To tackle these deficiencies, the BRI countries can import environmental technology from China. Moreover, they can communicate their environmental protection policies with China for better policy guidance. The current study, therefore, aims to examine whether the BRI countries’ import of environmental technology from China can reduce carbon emissions in these countries. Moreover, it also examines that whether these countries should follow the environmental policy and the import policy of China or they should follow the six European countries (EU-6) with minimum carbon emissions intensity. This study considers a sample of 88 selected BRI countries (BRI-88) for the period 2001–2019. The results obtained with β convergence (based on the panel quantile regression model) suggest that not all the BRI countries but only the BRI countries with relatively higher carbon emissions intensity can significantly reduce their average carbon emissions intensity by importing environmental technology from China. Moreover, BRI countries can follow the environmental policy of China which is more feasible for them. However, regarding the environmental goods import policy, BRI countries can follow both China and the EU-6.
{"title":"Environmental technology import and carbon emissions intensity convergence: Analysis for the Belt and Road Initiative countries","authors":"Muhammad Salam, Xu Yingzhi","doi":"10.1177/0958305x231204033","DOIUrl":"https://doi.org/10.1177/0958305x231204033","url":null,"abstract":"Since the official launch of the Belt and Road Initiative (BRI) in 2013, China and the BRI countries have been working for the implementation of certain environmental measures to make the BRI project green and clean. For this purpose, China and the BRI countries have planned to implement certain environmental measures. Although China can efficiently implement these measures, most of the BRI countries face technological deficiencies and lack of proper environmental plannings. To tackle these deficiencies, the BRI countries can import environmental technology from China. Moreover, they can communicate their environmental protection policies with China for better policy guidance. The current study, therefore, aims to examine whether the BRI countries’ import of environmental technology from China can reduce carbon emissions in these countries. Moreover, it also examines that whether these countries should follow the environmental policy and the import policy of China or they should follow the six European countries (EU-6) with minimum carbon emissions intensity. This study considers a sample of 88 selected BRI countries (BRI-88) for the period 2001–2019. The results obtained with β convergence (based on the panel quantile regression model) suggest that not all the BRI countries but only the BRI countries with relatively higher carbon emissions intensity can significantly reduce their average carbon emissions intensity by importing environmental technology from China. Moreover, BRI countries can follow the environmental policy of China which is more feasible for them. However, regarding the environmental goods import policy, BRI countries can follow both China and the EU-6.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"21 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136135025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-29DOI: 10.1177/0958305x231207057
Jingxue Zhang, Kun Zhang
CEO characteristics influence their strategic preferences, which are crucial for promoting corporate green innovation (GI). However, the influence and its mechanisms of CEO green experience (GreCEO) on GI of energy firms, especially when comparing different firm types holistically, remain understudied. This study used a moderated mediation model with fixed effects to examine the relationship between GreCEO and GI of energy firms, based on the unbalanced panel data of 821 listed Chinese energy firms during 2004–2021. We find that: (1) GreCEO positively affects energy firms’ GI. (2) Heterogeneity exists in the GI effect of GreCEO regarding business ownership and industry characteristics, and this effect is more prominent in non-state-owned energy firms and high-tech energy firms. (3) Green management (GM) and debt-to-asset ratio (DAR) partially mediate GreCEO's impact on GI of energy firms. (4) Renewable energy policy (REP) moderates the relationship between GreCEO and GI of energy firms, and its influencing mechanisms. In contrast to studies that focus on the direct effect of CEO characteristics on GI, this study identifies the potential influencing mechanisms through which GreCEO affects GI of energy firms. In addition, the moderation analysis reveals the boundary condition that GreCEO affects GI, enriching our understanding of GreCEO's effect on GI from the perspective of a firm's internal conditions and external policy environment. Regarding green development, CEOs’ early experience should be included in the management system and evaluation criteria of energy firms. The Chinese government should continue to implement the REP and accelerate energy firms’ green transition.
{"title":"How does CEO green experience affect green innovation of energy firms? Evidence from China","authors":"Jingxue Zhang, Kun Zhang","doi":"10.1177/0958305x231207057","DOIUrl":"https://doi.org/10.1177/0958305x231207057","url":null,"abstract":"CEO characteristics influence their strategic preferences, which are crucial for promoting corporate green innovation (GI). However, the influence and its mechanisms of CEO green experience (GreCEO) on GI of energy firms, especially when comparing different firm types holistically, remain understudied. This study used a moderated mediation model with fixed effects to examine the relationship between GreCEO and GI of energy firms, based on the unbalanced panel data of 821 listed Chinese energy firms during 2004–2021. We find that: (1) GreCEO positively affects energy firms’ GI. (2) Heterogeneity exists in the GI effect of GreCEO regarding business ownership and industry characteristics, and this effect is more prominent in non-state-owned energy firms and high-tech energy firms. (3) Green management (GM) and debt-to-asset ratio (DAR) partially mediate GreCEO's impact on GI of energy firms. (4) Renewable energy policy (REP) moderates the relationship between GreCEO and GI of energy firms, and its influencing mechanisms. In contrast to studies that focus on the direct effect of CEO characteristics on GI, this study identifies the potential influencing mechanisms through which GreCEO affects GI of energy firms. In addition, the moderation analysis reveals the boundary condition that GreCEO affects GI, enriching our understanding of GreCEO's effect on GI from the perspective of a firm's internal conditions and external policy environment. Regarding green development, CEOs’ early experience should be included in the management system and evaluation criteria of energy firms. The Chinese government should continue to implement the REP and accelerate energy firms’ green transition.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136136357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The demand for carbon-free or renewable energy sources is on the rise due to their role in boosting environmental performance and controlling emissions. The majority of previous research is based on the symmetry assumption while analyzing the association between tourism demand (TD), exchange rate volatility (ERV), and renewable energy consumption (REC). To plug this hole, this research scrutinizes the impact of TD and ERV on REC in China. To investigate the short and long-run implications of TD and ERV on REC, this analysis employs the autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) techniques. The study's innovative approach enhances its scientific value through a novel and insightful examination of the variables of interest. The linear model results indicate that TD has a positive and significant long-run impact on REC. Conversely, ERV has a negative and significant long-run impact on REC. The NARDL model finds that a positive TD shock significantly and positively affects REC in the long run, while a negative TD shock does not exert a noticeable impact on REC. A positive ERV shock significantly and negatively affects REC in the long term, whereas a negative ERV shock has an insignificant impact on REC. Conversely, only a positive ERV shock has a significant positive impact on REC in the short run. These findings imply that policymakers must adopt stable and reliable foreign exchange market policies and promote sustainable tourism practices at tourist hotspots.
{"title":"Exploring the impacts of tourism development and exchange rate on renewable energy demand in China: A nonlinear perspective","authors":"None Chenjie, Xu Yunbao, Peng Zhubin, Sidra Sohail","doi":"10.1177/0958305x231195362","DOIUrl":"https://doi.org/10.1177/0958305x231195362","url":null,"abstract":"The demand for carbon-free or renewable energy sources is on the rise due to their role in boosting environmental performance and controlling emissions. The majority of previous research is based on the symmetry assumption while analyzing the association between tourism demand (TD), exchange rate volatility (ERV), and renewable energy consumption (REC). To plug this hole, this research scrutinizes the impact of TD and ERV on REC in China. To investigate the short and long-run implications of TD and ERV on REC, this analysis employs the autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) techniques. The study's innovative approach enhances its scientific value through a novel and insightful examination of the variables of interest. The linear model results indicate that TD has a positive and significant long-run impact on REC. Conversely, ERV has a negative and significant long-run impact on REC. The NARDL model finds that a positive TD shock significantly and positively affects REC in the long run, while a negative TD shock does not exert a noticeable impact on REC. A positive ERV shock significantly and negatively affects REC in the long term, whereas a negative ERV shock has an insignificant impact on REC. Conversely, only a positive ERV shock has a significant positive impact on REC in the short run. These findings imply that policymakers must adopt stable and reliable foreign exchange market policies and promote sustainable tourism practices at tourist hotspots.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"62 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136135676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-29DOI: 10.1177/0958305x231209418
Jiasen Sun, Tong Liu, Junfei Chu
The electricity power (EP) industry, a primary source of emissions, significantly affects China's energy conservation and reduction efforts. The Chinese government has introduced various regulatory policies to limit the emissions and waste generated by the EP industry. This paper intends to assess the influence of environmental regulation (ER) on the environmental efficiency (EE) within China's EP sector, particularly concerning spatial spillover effects. The slack-based and the spatial Durbin models are applied to quantify EE and analyze the nonlinear connection between ER and EE. Some findings are summarized below. First, the EE of China's EP industry has significant regional heterogeneity and exhibits a positive spatial agglomeration effect of EE. Second, the influence of ER on EE in local provinces shows a U-shaped relationship, while it exhibits an inverted U-shaped effect in neighboring provinces. Third, ER can indirectly drive EE in the local province by affecting technological innovation. Finally, policy recommendations are offered to enhance the EE in China's EP industry.
{"title":"Spatial spillover effect of environmental regulation on environmental efficiency of electric power industry in China","authors":"Jiasen Sun, Tong Liu, Junfei Chu","doi":"10.1177/0958305x231209418","DOIUrl":"https://doi.org/10.1177/0958305x231209418","url":null,"abstract":"The electricity power (EP) industry, a primary source of emissions, significantly affects China's energy conservation and reduction efforts. The Chinese government has introduced various regulatory policies to limit the emissions and waste generated by the EP industry. This paper intends to assess the influence of environmental regulation (ER) on the environmental efficiency (EE) within China's EP sector, particularly concerning spatial spillover effects. The slack-based and the spatial Durbin models are applied to quantify EE and analyze the nonlinear connection between ER and EE. Some findings are summarized below. First, the EE of China's EP industry has significant regional heterogeneity and exhibits a positive spatial agglomeration effect of EE. Second, the influence of ER on EE in local provinces shows a U-shaped relationship, while it exhibits an inverted U-shaped effect in neighboring provinces. Third, ER can indirectly drive EE in the local province by affecting technological innovation. Finally, policy recommendations are offered to enhance the EE in China's EP industry.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"214 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136134883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-29DOI: 10.1177/0958305x231210993
Ugur Korkut Pata, Rundong Luo, Mustafa Tevfik Kartal, Tomiwa Sunday Adebayo, Sami Ullah
Sustainable manufacturing and green growth are prominent concerns for both advanced and emerging countries to reach the sustainable development goals. Most emerging economies rely heavily on fossil fuels to meet their energy needs, which increases greenhouse gas emissions and degrades environmental quality. This study accessed the role of renewable energy, trade globalization, and technological innovations in predicting environmental quality in China using quarterly data from 2001 to 2019. The study employed a novel nonparametric causality-in-quantiles approach, because causality may not exist in the mean, but a higher-order relationship may be observed in the variance. The outcomes revealed that renewable energy, globalization and technology, all have significant and asymmetric power to predict carbon emissions and ecological footprint in China. The main finding of the study is that technology seems to be the most significant predictor of carbon emissions, while the ecological footprint is highly driven by renewable energy. Based on these results, the Chinese government should reduce ecological degradation by increasing investments in technological progress and renewable energy to achieve sustainable development.
{"title":"Do technological innovations and clean energies ensure CO<sub>2</sub> reduction in China? A novel nonparametric causality-in-quantiles","authors":"Ugur Korkut Pata, Rundong Luo, Mustafa Tevfik Kartal, Tomiwa Sunday Adebayo, Sami Ullah","doi":"10.1177/0958305x231210993","DOIUrl":"https://doi.org/10.1177/0958305x231210993","url":null,"abstract":"Sustainable manufacturing and green growth are prominent concerns for both advanced and emerging countries to reach the sustainable development goals. Most emerging economies rely heavily on fossil fuels to meet their energy needs, which increases greenhouse gas emissions and degrades environmental quality. This study accessed the role of renewable energy, trade globalization, and technological innovations in predicting environmental quality in China using quarterly data from 2001 to 2019. The study employed a novel nonparametric causality-in-quantiles approach, because causality may not exist in the mean, but a higher-order relationship may be observed in the variance. The outcomes revealed that renewable energy, globalization and technology, all have significant and asymmetric power to predict carbon emissions and ecological footprint in China. The main finding of the study is that technology seems to be the most significant predictor of carbon emissions, while the ecological footprint is highly driven by renewable energy. Based on these results, the Chinese government should reduce ecological degradation by increasing investments in technological progress and renewable energy to achieve sustainable development.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"2 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136134821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：