Eugene Y.C. Wong , Kev K.T. Ling , Allen H. Tai , Andrew Yuen
{"title":"基于两阶段多边贸易的欧亚大陆桥 \"一带一路 \"沿线国家货运碳排放预测模型","authors":"Eugene Y.C. Wong , Kev K.T. Ling , Allen H. Tai , Andrew Yuen","doi":"10.1080/15568318.2024.2392190","DOIUrl":null,"url":null,"abstract":"<div><div>Global freight distribution patterns have been affected by trading policies and the pandemic outbreak. The Belt and Road Initiative, trade conflicts, and the COVID-19 pandemic have changed the global logistics flow, shifting cargos from maritime and air transport to railway transport along the countries in the Eurasian Landbridge. Though railway freight emits less carbon than road truck transportation, the increased use of railway freight brings in a higher volume of carbon emissions to cities located along the landbridges. Achieving net zero carbon emission is becoming more important, but there is a lack of literature in assessing the environmental impact of cross-border railway logistics transportation among Belt and Road countries. A novel two-stage multilateral trade-based prediction model is developed, integrating a modified gravity model and nonlinear autoregressive neural network for trade and emission forecasting. The model evaluates railway freight along the landbridge over ten years and forecasts the impact of carbon emissions from trading and logistics along the corridor in the subsequent five years. It further analyses the emissions impact of the proposed Third Eurasian Landbridge and the extended Second Eurasian Landbridge. The findings provide insights for the development of railway freight transport, considering trade and logistics flow, carbon emission mitigation strategies, and sustainability impact between China and other Belt and Road countries. While countries such as India and Kazakhstan were forecast to have significant amounts of carbon emissions in the projected period, the rapid growths in locations with smaller emission amounts such as Kunming and Georgia should draw attention and require continuous monitoring.</div></div>","PeriodicalId":47824,"journal":{"name":"International Journal of Sustainable Transportation","volume":"18 8","pages":"Pages 633-650"},"PeriodicalIF":3.1000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Two-stage multilateral trade-based prediction model for freight transport carbon emission of Belt and Road countries along Eurasian Landbridges\",\"authors\":\"Eugene Y.C. Wong , Kev K.T. Ling , Allen H. Tai , Andrew Yuen\",\"doi\":\"10.1080/15568318.2024.2392190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Global freight distribution patterns have been affected by trading policies and the pandemic outbreak. The Belt and Road Initiative, trade conflicts, and the COVID-19 pandemic have changed the global logistics flow, shifting cargos from maritime and air transport to railway transport along the countries in the Eurasian Landbridge. Though railway freight emits less carbon than road truck transportation, the increased use of railway freight brings in a higher volume of carbon emissions to cities located along the landbridges. Achieving net zero carbon emission is becoming more important, but there is a lack of literature in assessing the environmental impact of cross-border railway logistics transportation among Belt and Road countries. A novel two-stage multilateral trade-based prediction model is developed, integrating a modified gravity model and nonlinear autoregressive neural network for trade and emission forecasting. The model evaluates railway freight along the landbridge over ten years and forecasts the impact of carbon emissions from trading and logistics along the corridor in the subsequent five years. It further analyses the emissions impact of the proposed Third Eurasian Landbridge and the extended Second Eurasian Landbridge. The findings provide insights for the development of railway freight transport, considering trade and logistics flow, carbon emission mitigation strategies, and sustainability impact between China and other Belt and Road countries. While countries such as India and Kazakhstan were forecast to have significant amounts of carbon emissions in the projected period, the rapid growths in locations with smaller emission amounts such as Kunming and Georgia should draw attention and require continuous monitoring.</div></div>\",\"PeriodicalId\":47824,\"journal\":{\"name\":\"International Journal of Sustainable Transportation\",\"volume\":\"18 8\",\"pages\":\"Pages 633-650\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Sustainable Transportation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/org/science/article/pii/S1556831824000273\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Sustainable Transportation","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1556831824000273","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Two-stage multilateral trade-based prediction model for freight transport carbon emission of Belt and Road countries along Eurasian Landbridges
Global freight distribution patterns have been affected by trading policies and the pandemic outbreak. The Belt and Road Initiative, trade conflicts, and the COVID-19 pandemic have changed the global logistics flow, shifting cargos from maritime and air transport to railway transport along the countries in the Eurasian Landbridge. Though railway freight emits less carbon than road truck transportation, the increased use of railway freight brings in a higher volume of carbon emissions to cities located along the landbridges. Achieving net zero carbon emission is becoming more important, but there is a lack of literature in assessing the environmental impact of cross-border railway logistics transportation among Belt and Road countries. A novel two-stage multilateral trade-based prediction model is developed, integrating a modified gravity model and nonlinear autoregressive neural network for trade and emission forecasting. The model evaluates railway freight along the landbridge over ten years and forecasts the impact of carbon emissions from trading and logistics along the corridor in the subsequent five years. It further analyses the emissions impact of the proposed Third Eurasian Landbridge and the extended Second Eurasian Landbridge. The findings provide insights for the development of railway freight transport, considering trade and logistics flow, carbon emission mitigation strategies, and sustainability impact between China and other Belt and Road countries. While countries such as India and Kazakhstan were forecast to have significant amounts of carbon emissions in the projected period, the rapid growths in locations with smaller emission amounts such as Kunming and Georgia should draw attention and require continuous monitoring.
期刊介绍:
The International Journal of Sustainable Transportation provides a discussion forum for the exchange of new and innovative ideas on sustainable transportation research in the context of environmental, economical, social, and engineering aspects, as well as current and future interactions of transportation systems and other urban subsystems. The scope includes the examination of overall sustainability of any transportation system, including its infrastructure, vehicle, operation, and maintenance; the integration of social science disciplines, engineering, and information technology with transportation; the understanding of the comparative aspects of different transportation systems from a global perspective; qualitative and quantitative transportation studies; and case studies, surveys, and expository papers in an international or local context. Equal emphasis is placed on the problems of sustainable transportation that are associated with passenger and freight transportation modes in both industrialized and non-industrialized areas. All submitted manuscripts are subject to initial evaluation by the Editors and, if found suitable for further consideration, to peer review by independent, anonymous expert reviewers. All peer review is single-blind. Submissions are made online via ScholarOne Manuscripts.