{"title":"中国北方高速公路纵向坡度与碳排放的关系","authors":"Xingli Jia, Jinliang Xu, Xingliang Liu","doi":"10.12783/ISSN.1544-8053/14/1/22","DOIUrl":null,"url":null,"abstract":"In Northern China, heavy trucks are common on highways. Vehicles traveling on longitudinal sections of expressways produce higher carbon emissions. Current carbon emission models include the vehicular operating conditions, but do not reveal the influence of highway alignment conditions, such as the longitudinal gradient and slope length, on emissions. To address this problem, this study attempts to relate the design parameters of longitudinal roadway segments with carbon emissions, as derived from diesel fuel consumption data, using an iterative nonlinear multiple regression method. Diesel fuel consumption data were collected through field tests along two typical overloaded expressways in China’s coal-producing regions. The associated carbon emission data were calculated using the method defined by the Intergovernmental Panel on Climate Change. Using this data, a carbon emission prediction model was developed that related carbon emissions with roadway segment gradients, segment slope length, and initial vehicle speed. The proposed model was verified using the field test data. A relative error of 4.9% between predicted and observed data suggested high accuracy and applicability for the proposed prediction model.","PeriodicalId":17101,"journal":{"name":"Journal of Residuals Science & Technology","volume":"53 1","pages":"177-183"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Association of Carbon Emissions and Expressway Longitudinal Slope in Northern China\",\"authors\":\"Xingli Jia, Jinliang Xu, Xingliang Liu\",\"doi\":\"10.12783/ISSN.1544-8053/14/1/22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Northern China, heavy trucks are common on highways. Vehicles traveling on longitudinal sections of expressways produce higher carbon emissions. Current carbon emission models include the vehicular operating conditions, but do not reveal the influence of highway alignment conditions, such as the longitudinal gradient and slope length, on emissions. To address this problem, this study attempts to relate the design parameters of longitudinal roadway segments with carbon emissions, as derived from diesel fuel consumption data, using an iterative nonlinear multiple regression method. Diesel fuel consumption data were collected through field tests along two typical overloaded expressways in China’s coal-producing regions. The associated carbon emission data were calculated using the method defined by the Intergovernmental Panel on Climate Change. Using this data, a carbon emission prediction model was developed that related carbon emissions with roadway segment gradients, segment slope length, and initial vehicle speed. The proposed model was verified using the field test data. A relative error of 4.9% between predicted and observed data suggested high accuracy and applicability for the proposed prediction model.\",\"PeriodicalId\":17101,\"journal\":{\"name\":\"Journal of Residuals Science & Technology\",\"volume\":\"53 1\",\"pages\":\"177-183\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Residuals Science & Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12783/ISSN.1544-8053/14/1/22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Residuals Science & Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12783/ISSN.1544-8053/14/1/22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Association of Carbon Emissions and Expressway Longitudinal Slope in Northern China
In Northern China, heavy trucks are common on highways. Vehicles traveling on longitudinal sections of expressways produce higher carbon emissions. Current carbon emission models include the vehicular operating conditions, but do not reveal the influence of highway alignment conditions, such as the longitudinal gradient and slope length, on emissions. To address this problem, this study attempts to relate the design parameters of longitudinal roadway segments with carbon emissions, as derived from diesel fuel consumption data, using an iterative nonlinear multiple regression method. Diesel fuel consumption data were collected through field tests along two typical overloaded expressways in China’s coal-producing regions. The associated carbon emission data were calculated using the method defined by the Intergovernmental Panel on Climate Change. Using this data, a carbon emission prediction model was developed that related carbon emissions with roadway segment gradients, segment slope length, and initial vehicle speed. The proposed model was verified using the field test data. A relative error of 4.9% between predicted and observed data suggested high accuracy and applicability for the proposed prediction model.
期刊介绍:
The international Journal of Residuals Science & Technology (JRST) is a blind-refereed quarterly devoted to conscientious analysis and commentary regarding significant environmental sciences-oriented research and technical management of residuals in the environment. The journal provides a forum for scientific investigations addressing contamination within environmental media of air, water, soil, and biota and also offers studies exploring source, fate, transport, and ecological effects of environmental contamination.