Pub Date : 2022-04-20DOI: 10.1177/0958305X221094581
Feiyi Yang, Chunchen Wang
This paper constructs a unique dataset of clean energy and adopts static panel models and dynamic panel specifications to explore the correlation between clean energy and CO2 emissions. Furthermore, this paper employs the interaction term of pilot areas and pilot time as the proxy of emission trading policy to examine the effect of China’s emission trading pilot on clean energy. Then, this paper conducts quasi-natural experiments on CO2 emissions. Our findings show a negative correlation between CO2 emissions and clean energy. We also find that China’s emission trading pilot has a significant impact on promoting clean energy. In addition, empirical results affirm that emission trading market pilots can help decrease CO2 emissions. Finally, we put forwards relevant policy recommendations.
{"title":"Clean energy, emission trading policy, and CO2 emissions: Evidence from China","authors":"Feiyi Yang, Chunchen Wang","doi":"10.1177/0958305X221094581","DOIUrl":"https://doi.org/10.1177/0958305X221094581","url":null,"abstract":"This paper constructs a unique dataset of clean energy and adopts static panel models and dynamic panel specifications to explore the correlation between clean energy and CO2 emissions. Furthermore, this paper employs the interaction term of pilot areas and pilot time as the proxy of emission trading policy to examine the effect of China’s emission trading pilot on clean energy. Then, this paper conducts quasi-natural experiments on CO2 emissions. Our findings show a negative correlation between CO2 emissions and clean energy. We also find that China’s emission trading pilot has a significant impact on promoting clean energy. In addition, empirical results affirm that emission trading market pilots can help decrease CO2 emissions. Finally, we put forwards relevant policy recommendations.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"20 1","pages":"1657 - 1673"},"PeriodicalIF":4.2,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85382229","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 : 2022-04-20DOI: 10.1177/0958305X221093465
R. Maniarasu, S. Rathore, S. Murugan
Biomass can be converted into energy, fuels, and value-added products by adopting proper conversion or production methods. For many years, biomass has been considered to be a good candidate for producing biochar or activated carbon. The awareness created on mitigation of carbon dioxide (CO2), which is the major cause of global warming, necessitated developing potential methods and materials for curbing CO2 originating from various sources. Adsorption is the most viable option to mitigate CO2 by using activated carbon which can be derived from various biomass sources. In recent years, activated carbon has been produced from different biomass substances by varying carbonization and activation duration, carbonization and activation temperature, impregnation ratio, and the concentration of the activating agent to improve its surface area and porosity. This review article provides a comprehensive review on utilization, production and characterization of biomass-based activated carbon for CO2 adsorption. Initially, the article discusses the review of research works carried out on utilization of biomass-based activated carbon for CO2 adsorption. Furthermore, the article presents the research works carried out on surface textural characteristics, physicochemical properties, and maximum adsorption capacity of activated carbon obtained from different biomass substances. Finally, the article presents the research works carried out related to the biomass-based activated carbon and the parameters significantly enhancing the CO2 adsorption performance.
{"title":"Biomass-based activated carbon for CO2 adsorption–A review","authors":"R. Maniarasu, S. Rathore, S. Murugan","doi":"10.1177/0958305X221093465","DOIUrl":"https://doi.org/10.1177/0958305X221093465","url":null,"abstract":"Biomass can be converted into energy, fuels, and value-added products by adopting proper conversion or production methods. For many years, biomass has been considered to be a good candidate for producing biochar or activated carbon. The awareness created on mitigation of carbon dioxide (CO2), which is the major cause of global warming, necessitated developing potential methods and materials for curbing CO2 originating from various sources. Adsorption is the most viable option to mitigate CO2 by using activated carbon which can be derived from various biomass sources. In recent years, activated carbon has been produced from different biomass substances by varying carbonization and activation duration, carbonization and activation temperature, impregnation ratio, and the concentration of the activating agent to improve its surface area and porosity. This review article provides a comprehensive review on utilization, production and characterization of biomass-based activated carbon for CO2 adsorption. Initially, the article discusses the review of research works carried out on utilization of biomass-based activated carbon for CO2 adsorption. Furthermore, the article presents the research works carried out on surface textural characteristics, physicochemical properties, and maximum adsorption capacity of activated carbon obtained from different biomass substances. Finally, the article presents the research works carried out related to the biomass-based activated carbon and the parameters significantly enhancing the CO2 adsorption performance.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"45 1","pages":"1674 - 1721"},"PeriodicalIF":4.2,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91121270","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 : 2022-04-18DOI: 10.1177/0958305X221094573
S. Akadiri, T. Adebayo, Obioma Chinenyenwa Asuzu, Ijeoma Christina Onuogu, Izuchukwu Oji-Okoro
China is known for its large industrial sector and diversified energy mix, which could contribute to environmental pollution, as fossil fuels remain China's main source of energy. With the recent drive by the Chinese government to achieve low carbon emissions and further reduce greenhouse gases, this study adds to the existing literature by combining the quantile-on-quantile (QQ) regression and non-parametric techniques to examine the role of economic complexity, nonrenewables energy and renewable energy consumption on the ecological footprint in China over the period 1985Q1–2019Q4. Overall, results show that renewable energy, non-renewable energy use, economic growth and economic complexity affects ecological footprint positively. In addition, the nonparametric causality outcomes revealed that renewable energy, non-renewable energy use, economic growth and economic complexity can significantly predict variations in ecological footprint at different quantiles. We are of the opinion that policymakers in this region should work on the pro-growth mentality of China, which is majorly fossil fuel-driven. This requires an immediate replacement with more eco-friendly sources and energy-saving technologies for economic activities. Otherwise, fulfilling the SDG 13 goals in China will be challenging. For a sustainable renewable energy investment, China should shift to ancillary and spot markets, where the low energy storage and low marginal cost of renewable energy could facilitate higher reduction in electricity cost and encourage higher trading of electricity.
{"title":"Testing the role of economic complexity on the ecological footprint in China: a nonparametric causality-in-quantiles approach","authors":"S. Akadiri, T. Adebayo, Obioma Chinenyenwa Asuzu, Ijeoma Christina Onuogu, Izuchukwu Oji-Okoro","doi":"10.1177/0958305X221094573","DOIUrl":"https://doi.org/10.1177/0958305X221094573","url":null,"abstract":"China is known for its large industrial sector and diversified energy mix, which could contribute to environmental pollution, as fossil fuels remain China's main source of energy. With the recent drive by the Chinese government to achieve low carbon emissions and further reduce greenhouse gases, this study adds to the existing literature by combining the quantile-on-quantile (QQ) regression and non-parametric techniques to examine the role of economic complexity, nonrenewables energy and renewable energy consumption on the ecological footprint in China over the period 1985Q1–2019Q4. Overall, results show that renewable energy, non-renewable energy use, economic growth and economic complexity affects ecological footprint positively. In addition, the nonparametric causality outcomes revealed that renewable energy, non-renewable energy use, economic growth and economic complexity can significantly predict variations in ecological footprint at different quantiles. We are of the opinion that policymakers in this region should work on the pro-growth mentality of China, which is majorly fossil fuel-driven. This requires an immediate replacement with more eco-friendly sources and energy-saving technologies for economic activities. Otherwise, fulfilling the SDG 13 goals in China will be challenging. For a sustainable renewable energy investment, China should shift to ancillary and spot markets, where the low energy storage and low marginal cost of renewable energy could facilitate higher reduction in electricity cost and encourage higher trading of electricity.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"232 1","pages":"2290 - 2316"},"PeriodicalIF":4.2,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73251912","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 : 2022-04-18DOI: 10.1177/0958305X221094666
Wen-ze Wu, C. Liu, Wanli Xie, M. Goh, Tao Zhang
To estimate the dynamic trend of industrial water-waste-energy (hereinafter referred to as WWE) system, this paper proposes a new method for forecasting specific indicators in such a system. First, the fractional accumulated generation operator, fractional derivative and classic nonlinear grey Bernoulli model are simultaneously coupled to develop an optimised nonlinear grey Bernoulli model that identifies the nonlinear trends in industrial WWE systems. Second, the particle swarm optimization algorithm is employed to determine the optimal model parameters in the newly-designed model. Based on this, simulation studies are conducted to examine the stability of the proposed model. Finally, the model is applied in the industrial WWE system. The results demonstrate that (1) the proposed model outperforms other competitive models in terms of error-value metrics and (2) industrial water use and industrial energy consumption will increase, whereas industrial wastewater discharge will decline. Furthermore, the rationality of the predicted results redis analyzed from a policy perspective.
{"title":"Predictive analysis of the industrial water-waste-energy system using an optimised grey approach: A case study in China","authors":"Wen-ze Wu, C. Liu, Wanli Xie, M. Goh, Tao Zhang","doi":"10.1177/0958305X221094666","DOIUrl":"https://doi.org/10.1177/0958305X221094666","url":null,"abstract":"To estimate the dynamic trend of industrial water-waste-energy (hereinafter referred to as WWE) system, this paper proposes a new method for forecasting specific indicators in such a system. First, the fractional accumulated generation operator, fractional derivative and classic nonlinear grey Bernoulli model are simultaneously coupled to develop an optimised nonlinear grey Bernoulli model that identifies the nonlinear trends in industrial WWE systems. Second, the particle swarm optimization algorithm is employed to determine the optimal model parameters in the newly-designed model. Based on this, simulation studies are conducted to examine the stability of the proposed model. Finally, the model is applied in the industrial WWE system. The results demonstrate that (1) the proposed model outperforms other competitive models in terms of error-value metrics and (2) industrial water use and industrial energy consumption will increase, whereas industrial wastewater discharge will decline. Furthermore, the rationality of the predicted results redis analyzed from a policy perspective.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"18 1","pages":"1639 - 1656"},"PeriodicalIF":4.2,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77609016","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 : 2022-04-13DOI: 10.1177/0958305X221093458
R. Adha, Cheng-Yih Hong, Somya Agrawal, Li-Hua Li
The global rise in energy consumption makes managing energy demands a priority. Here, the potential of Information and Communication Technology (ICT) in controlling energy consumption is still debated. Within this context, the main objective of the current study is to measure the impact of ICT, its potential benefit, and environmental factors on household electricity demand in Taiwan. A panel of data from 20 cities in Taiwan was collected during the period 2004–2018. We adopted PMG estimation and applied the DH-causality test for analysis. The estimation results show that ICT, carbon emissions, and climate change will drive household electricity demand in Taiwan in the long term. However, ICT has a higher potential to reduce electricity demand in the short-term period. In addition, the results of the causality test reveal a two-way interrelationship between ICT and electricity demand. Our study also found that climate change indirectly affects the use of electricity through household appliances. We also presented several policy implications at the end of this paper.
{"title":"ICT, carbon emissions, climate change, and energy demand nexus: The potential benefit of digitalization in Taiwan","authors":"R. Adha, Cheng-Yih Hong, Somya Agrawal, Li-Hua Li","doi":"10.1177/0958305X221093458","DOIUrl":"https://doi.org/10.1177/0958305X221093458","url":null,"abstract":"The global rise in energy consumption makes managing energy demands a priority. Here, the potential of Information and Communication Technology (ICT) in controlling energy consumption is still debated. Within this context, the main objective of the current study is to measure the impact of ICT, its potential benefit, and environmental factors on household electricity demand in Taiwan. A panel of data from 20 cities in Taiwan was collected during the period 2004–2018. We adopted PMG estimation and applied the DH-causality test for analysis. The estimation results show that ICT, carbon emissions, and climate change will drive household electricity demand in Taiwan in the long term. However, ICT has a higher potential to reduce electricity demand in the short-term period. In addition, the results of the causality test reveal a two-way interrelationship between ICT and electricity demand. Our study also found that climate change indirectly affects the use of electricity through household appliances. We also presented several policy implications at the end of this paper.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"76 1","pages":"1619 - 1638"},"PeriodicalIF":4.2,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86310975","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 : 2022-04-11DOI: 10.1177/0958305X221092401
Young Gwan Lee, Kihyun Park, Hyun Jae Kim, Seong‐Hoon Cho
This research determines the optimal distribution of firm-specific energy research and development (R&D) investment that balances firms’ return and risk under market-induced uncertainty. We focus on creating optimal portfolios of target firms and their optimal energy R&D investments that maximize their return on investments (ROIs) for given levels of risk. We employ a stochastic optimization framework that maximizes firms’ ROIs for energy R&D investment, measured by the ratio of the number of patents issued for energy technologies to the amount of annual energy R&D expenditures, for 78 energy firms in South Korea between 2006 and 2017. The findings from our mean-standard deviation tradeoff frontiers are summarized as follows: 1) the tradeoff ratio increases as the weights shift from 100% on maximizing expected ROI toward 100% on minimizing its standard deviation regardless of market conditions and 2) the tradeoff ratio during the downturn is higher than during the upturn. These findings suggest that firms mitigate market-induced risk with a smaller sacrifice in the expected number of issued patents when the initial weight is primarily on maximizing expected ROIs and when the market is experiencing an upturn instead of a downturn. From the distribution patterns of prioritized firms for the two extreme risk preference points along the upturn and downturn tradeoff frontiers, we find that the target firms shift under different market conditions and risk assumptions. These priority shifts highlight the importance of decision-maker flexibility in structuring firms’ portfolios to support energy R&D, depending on the governments’ risk tolerances and market conditions.
{"title":"Creating portfolios of firm-specific energy R&D investment under market uncertainty","authors":"Young Gwan Lee, Kihyun Park, Hyun Jae Kim, Seong‐Hoon Cho","doi":"10.1177/0958305X221092401","DOIUrl":"https://doi.org/10.1177/0958305X221092401","url":null,"abstract":"This research determines the optimal distribution of firm-specific energy research and development (R&D) investment that balances firms’ return and risk under market-induced uncertainty. We focus on creating optimal portfolios of target firms and their optimal energy R&D investments that maximize their return on investments (ROIs) for given levels of risk. We employ a stochastic optimization framework that maximizes firms’ ROIs for energy R&D investment, measured by the ratio of the number of patents issued for energy technologies to the amount of annual energy R&D expenditures, for 78 energy firms in South Korea between 2006 and 2017. The findings from our mean-standard deviation tradeoff frontiers are summarized as follows: 1) the tradeoff ratio increases as the weights shift from 100% on maximizing expected ROI toward 100% on minimizing its standard deviation regardless of market conditions and 2) the tradeoff ratio during the downturn is higher than during the upturn. These findings suggest that firms mitigate market-induced risk with a smaller sacrifice in the expected number of issued patents when the initial weight is primarily on maximizing expected ROIs and when the market is experiencing an upturn instead of a downturn. From the distribution patterns of prioritized firms for the two extreme risk preference points along the upturn and downturn tradeoff frontiers, we find that the target firms shift under different market conditions and risk assumptions. These priority shifts highlight the importance of decision-maker flexibility in structuring firms’ portfolios to support energy R&D, depending on the governments’ risk tolerances and market conditions.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"44 1","pages":"1548 - 1563"},"PeriodicalIF":4.2,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85677910","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 : 2022-04-11DOI: 10.1177/0958305X221091543
Daberechi Chikezie Ekwueme, T. Lasisi, K. Eluwole
This paper examines the causation between economic growth, tourism import, industrialization, renewable energy, non-renewable energy use, trade openness, and environmental sustainability which is proxied by carbon emissions for 8 Asian countries (China, Japan, India, Indonesia, South Korea, Philippines, Thailand, and Vietnam) over 20 years. Causal relations were tested using Pooled Mean Group Autoregressive distributive lag model (PMG-ARDL) and Dumitrescu and Hurlin's (2012) panel granger causality test The PMG-ARDL model results reveal that in the long-run renewable energy usage, economic growth, and trade have a significant negative influence on the emission of carbon, while non-renewable energy usage, tourism import, and industrialization exhibit a significant positive impact on CO2 emissions of the sampled Asian countries. In the short run, renewable energy has a significant negative influence on CO2 emissions. While economic growth exhibit a significant positive influence on carbon emissions in the short-run. Furthermore, the Granger causality analysis reveals that there is a feedback mechanism between industrialization, tourism import, non-renewable energy, renewable energy, and CO2 emissions meaning that the future dynamics of carbon emissions in the sampled countries can be significantly explained by industrialization, tourism import, renewable energy, and non-renewable energy. Contrarily, trade and economic growth are good to explain the dynamics of carbon effusion of the sampled Asian countries in the future but without feedback. It is recommended that policymakers in Asian countries should formulate stringent environmental policies that will encourage industries in these countries to utilize clean energy sources so that economic growth will be achieved simultaneously with carbon neutrality.
本文以中国、日本、印度、印度尼西亚、韩国、菲律宾、泰国和越南等8个亚洲国家20年来的碳排放为代表，研究了经济增长、旅游进口、工业化、可再生能源、不可再生能源使用、贸易开放和环境可持续性之间的因果关系。采用集合均值组自回归分布滞后模型(PMG-ARDL)和Dumitrescu and Hurlin(2012)面板格兰杰因果检验检验因果关系。PMG-ARDL模型结果显示，在长期内，可再生能源使用、经济增长和贸易对碳排放具有显著的负向影响，而不可再生能源使用、旅游进口和工业化对样本亚洲国家的二氧化碳排放具有显著的正向影响。从短期来看，可再生能源对二氧化碳排放有显著的负面影响。经济增长在短期内对碳排放有显著的正向影响。此外，格兰杰因果关系分析表明，工业化、旅游进口、不可再生能源、可再生能源和二氧化碳排放之间存在反馈机制，即工业化、旅游进口、可再生能源和不可再生能源可以显著地解释样本国家碳排放的未来动态。相反，贸易和经济增长很好地解释了样本亚洲国家未来的碳溢出动态，但没有反馈。建议亚洲国家的政策制定者制定严格的环境政策，鼓励这些国家的工业利用清洁能源，从而在实现经济增长的同时实现碳中和。
{"title":"Environmental sustainability in Asian countries: Understanding the criticality of economic growth, industrialization, tourism import, and energy use","authors":"Daberechi Chikezie Ekwueme, T. Lasisi, K. Eluwole","doi":"10.1177/0958305X221091543","DOIUrl":"https://doi.org/10.1177/0958305X221091543","url":null,"abstract":"This paper examines the causation between economic growth, tourism import, industrialization, renewable energy, non-renewable energy use, trade openness, and environmental sustainability which is proxied by carbon emissions for 8 Asian countries (China, Japan, India, Indonesia, South Korea, Philippines, Thailand, and Vietnam) over 20 years. Causal relations were tested using Pooled Mean Group Autoregressive distributive lag model (PMG-ARDL) and Dumitrescu and Hurlin's (2012) panel granger causality test The PMG-ARDL model results reveal that in the long-run renewable energy usage, economic growth, and trade have a significant negative influence on the emission of carbon, while non-renewable energy usage, tourism import, and industrialization exhibit a significant positive impact on CO2 emissions of the sampled Asian countries. In the short run, renewable energy has a significant negative influence on CO2 emissions. While economic growth exhibit a significant positive influence on carbon emissions in the short-run. Furthermore, the Granger causality analysis reveals that there is a feedback mechanism between industrialization, tourism import, non-renewable energy, renewable energy, and CO2 emissions meaning that the future dynamics of carbon emissions in the sampled countries can be significantly explained by industrialization, tourism import, renewable energy, and non-renewable energy. Contrarily, trade and economic growth are good to explain the dynamics of carbon effusion of the sampled Asian countries in the future but without feedback. It is recommended that policymakers in Asian countries should formulate stringent environmental policies that will encourage industries in these countries to utilize clean energy sources so that economic growth will be achieved simultaneously with carbon neutrality.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"22 1","pages":"1592 - 1618"},"PeriodicalIF":4.2,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79092115","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 : 2022-04-07DOI: 10.1177/0958305X221077336
S. Sek
The existing literature that examined the effect of oil price on domestic price inflation only focused on consumer price at an aggregate level. The studies that focused on producer and production levels, and based on disaggregated data are very lack. Besides, previous studies also mainly applied the linear regression approach in studying the effect of oil price. This study seeks to explore the mentioned issues by focusing on sectoral consumer (CPI), industrial (IPI), and producer (PPI) prices of Malaysia. The Markov-switching (MS) regression technique is applied. The models are innovated by incorporating the asymmetric effects of oil price changes. The results reveal different reactions of sectoral domestic price inflation to oil price changes. The oil price has asymmetric effects on domestic price inflation with higher impacts on industrial and producer prices than the consumer price. The effect is larger in sectors that have higher linkages with oil/ energy resources. These sectors are oil-intensive and are sensitive to oil price changes. Among these sectors are the CPI transportation sector, IPI manufacturing, and electrical sectors as well as PPI fuel, chemicals, and manufacturing sectors. However, oil is not the main factor causes to domestic inflation. The main determinants of inflation are real exchange rate, aggregate supply, and demand. Besides, the policy decisions are also influential on price stability. The sectors of CPI transportation, PPI animals & vegetable oils, and PPI fuel have a high tendency to increase prices and should be well-monitored.
{"title":"A new look at asymmetric effect of oil price changes on inflation: Evidence from Malaysia","authors":"S. Sek","doi":"10.1177/0958305X221077336","DOIUrl":"https://doi.org/10.1177/0958305X221077336","url":null,"abstract":"The existing literature that examined the effect of oil price on domestic price inflation only focused on consumer price at an aggregate level. The studies that focused on producer and production levels, and based on disaggregated data are very lack. Besides, previous studies also mainly applied the linear regression approach in studying the effect of oil price. This study seeks to explore the mentioned issues by focusing on sectoral consumer (CPI), industrial (IPI), and producer (PPI) prices of Malaysia. The Markov-switching (MS) regression technique is applied. The models are innovated by incorporating the asymmetric effects of oil price changes. The results reveal different reactions of sectoral domestic price inflation to oil price changes. The oil price has asymmetric effects on domestic price inflation with higher impacts on industrial and producer prices than the consumer price. The effect is larger in sectors that have higher linkages with oil/ energy resources. These sectors are oil-intensive and are sensitive to oil price changes. Among these sectors are the CPI transportation sector, IPI manufacturing, and electrical sectors as well as PPI fuel, chemicals, and manufacturing sectors. However, oil is not the main factor causes to domestic inflation. The main determinants of inflation are real exchange rate, aggregate supply, and demand. Besides, the policy decisions are also influential on price stability. The sectors of CPI transportation, PPI animals & vegetable oils, and PPI fuel have a high tendency to increase prices and should be well-monitored.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"18 1","pages":"1524 - 1547"},"PeriodicalIF":4.2,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90609599","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 : 2022-03-27DOI: 10.1177/0958305X221089223
S. Asad, Ali Gillani, M. R. Riaz, R. Hameed, A. Qamar, A. Toumi, A. Turatsinze
Using crumb rubber particles obtained from end-of-life tires as aggregate in concrete can reduce the environmental overburden caused by the huge accumulation of these scrap tires. However, reduction in the mechanical properties of concrete is observed with the incorporation of rubber aggregates. To counter this detrimental effect of crumb rubber in concrete, amorphous metallic fibers are added to balance the loss in strength and durability issues. Mechanical characteristics along with the fracture energy of rubberized fiber-reinforced mortar are presented here. Four mortar mix compositions were investigated; the first one is reference mortar (control mortar), the second mix containing 30 kg/m3 of metallic fibers, the third mix containing 30% of rubber aggregates as replacement of sand by equivalent volume and fourth containing both rubber aggregates and metallic fibers with the dosage 30% and 30 kg/m3, respectively. Compression tests, modulus of elasticity and direct tension tests were conducted for mechanical characterization. Deformation capacity, residual post-cracking strength and fracture energy of these composite mortar mixes were evaluated through uniaxial direct tension tests. The fracture energy was determined from the obtained complete softening curves. Test results show a reduction in mechanical properties with the incorporation of crumb rubber as aggregates in mortar. However, a significant increase in fracture energy was observed in rubberized fiber-reinforced mortar mixes. Moreover, the mortar mixes containing both rubber aggregates and metallic fibers show positive synergetic effect resulting in enhanced post-cracking residual tensile strength, strain capacity and energy dissipation capacity.
{"title":"Fracture energy of fiber-reinforced and rubberized cement-based composites: A sustainable approach towards recycling of waste scrap tires","authors":"S. Asad, Ali Gillani, M. R. Riaz, R. Hameed, A. Qamar, A. Toumi, A. Turatsinze","doi":"10.1177/0958305X221089223","DOIUrl":"https://doi.org/10.1177/0958305X221089223","url":null,"abstract":"Using crumb rubber particles obtained from end-of-life tires as aggregate in concrete can reduce the environmental overburden caused by the huge accumulation of these scrap tires. However, reduction in the mechanical properties of concrete is observed with the incorporation of rubber aggregates. To counter this detrimental effect of crumb rubber in concrete, amorphous metallic fibers are added to balance the loss in strength and durability issues. Mechanical characteristics along with the fracture energy of rubberized fiber-reinforced mortar are presented here. Four mortar mix compositions were investigated; the first one is reference mortar (control mortar), the second mix containing 30 kg/m3 of metallic fibers, the third mix containing 30% of rubber aggregates as replacement of sand by equivalent volume and fourth containing both rubber aggregates and metallic fibers with the dosage 30% and 30 kg/m3, respectively. Compression tests, modulus of elasticity and direct tension tests were conducted for mechanical characterization. Deformation capacity, residual post-cracking strength and fracture energy of these composite mortar mixes were evaluated through uniaxial direct tension tests. The fracture energy was determined from the obtained complete softening curves. Test results show a reduction in mechanical properties with the incorporation of crumb rubber as aggregates in mortar. However, a significant increase in fracture energy was observed in rubberized fiber-reinforced mortar mixes. Moreover, the mortar mixes containing both rubber aggregates and metallic fibers show positive synergetic effect resulting in enhanced post-cracking residual tensile strength, strain capacity and energy dissipation capacity.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"147 1","pages":"1509 - 1523"},"PeriodicalIF":4.2,"publicationDate":"2022-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84476891","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 : 2022-03-21DOI: 10.1177/0958305X221087502
Dan Armeanu, Ș. C. Gherghina, J. Andrei, Camelia Cătălina Joldeș
The COVID-19 pandemic remained a global risk factor and integrated into various means in the functioning of companies, economies and financial markets. Therefore, this paper investigates how COVID-19 influences the energy market in the main financial markets (China, France, Germany, Italy, Spain and the United States), using time series from February 28, 2020, to November 3, 2020. The goal of this research is to investigate the asymmetric impact of COVID-19 from leading financial markets on energy commodities. In this regard, the non-linear auto-regressive distributed lag (NARDL) framework is employed to capture the long-run asymmetric reactions. The econometric design allows to explore the long-term asymmetric reactions of dependent variables through positive and negative partial sum decompositions of changes in the explanatory variables. The quantitative results show a significant long-run asymmetric interdependence between the number of new SARS-CoV-2 incidence and mortality and the daily percent change in close price of future contracts pertaining to Brent oil, crude oil WTI, carbon emissions, gasoline RBOB, heating oil, Chukyo kerosene, and natural gas. Furthermore, no asymmetry is found in the case of ethanol and fuel oil futures. The novelty of this article is the study of the impact of COVID-19 on the energy sector during the first two waves of COVID-19 by applying the NARDL model that allows to capture long-term asymmetric reactions. Certainly, further research on this topic is necessary due to the permanent shifts in the pandemic, as well as the availability of longer data periods on COVID-19.
{"title":"Evidence from the nonlinear autoregressive distributed lag model on the asymmetric influence of the first wave of the COVID-19 pandemic on energy markets","authors":"Dan Armeanu, Ș. C. Gherghina, J. Andrei, Camelia Cătălina Joldeș","doi":"10.1177/0958305X221087502","DOIUrl":"https://doi.org/10.1177/0958305X221087502","url":null,"abstract":"The COVID-19 pandemic remained a global risk factor and integrated into various means in the functioning of companies, economies and financial markets. Therefore, this paper investigates how COVID-19 influences the energy market in the main financial markets (China, France, Germany, Italy, Spain and the United States), using time series from February 28, 2020, to November 3, 2020. The goal of this research is to investigate the asymmetric impact of COVID-19 from leading financial markets on energy commodities. In this regard, the non-linear auto-regressive distributed lag (NARDL) framework is employed to capture the long-run asymmetric reactions. The econometric design allows to explore the long-term asymmetric reactions of dependent variables through positive and negative partial sum decompositions of changes in the explanatory variables. The quantitative results show a significant long-run asymmetric interdependence between the number of new SARS-CoV-2 incidence and mortality and the daily percent change in close price of future contracts pertaining to Brent oil, crude oil WTI, carbon emissions, gasoline RBOB, heating oil, Chukyo kerosene, and natural gas. Furthermore, no asymmetry is found in the case of ethanol and fuel oil futures. The novelty of this article is the study of the impact of COVID-19 on the energy sector during the first two waves of COVID-19 by applying the NARDL model that allows to capture long-term asymmetric reactions. Certainly, further research on this topic is necessary due to the permanent shifts in the pandemic, as well as the availability of longer data periods on COVID-19.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"71 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81831264","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}
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