{"title":"核磁共振成像(MRI)设备和计算机断层扫描(CT)扫描仪二氧化碳排放量的预测模型","authors":"Giorgos P. Kouropoulos","doi":"10.4090/JUEE.2018.V12N2.172-187","DOIUrl":null,"url":null,"abstract":"The scope of the specific study is the statistical prediction of the annual carbon dioxide use emissions due to the operation of computed tomography (CT) scanners and magnetic resonance imaging (MRI) units in hospitals, health units and diagnostic centers, for the period between 2018 and 2030, in 120 countries across the world. The main sources of information for this study comprise statistical data from international organizations, scientific articles and measurements. The basic calculation tool of the study is a mathematical model, modified in such a way so that the calculations can be carried out using the available statistical data. In the final stage of the study, the functions that predict the carbon dioxide use emissions in relation to the years, will be extracted. Furthermore, all the errors and uncertainties of the mathematical model will be estimated. The conclusion, arising after implementation of the calculations, is that the carbon dioxide use emissions of CT scanners and MRI units are expected to grow by 30%, i.e., from 0.344 gigatonnes in 2018 to 0.497 gigatonnes in 2030.","PeriodicalId":17594,"journal":{"name":"Journal of Urban and Environmental Engineering","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A PREDICTIVE MODEL FOR THE ESTIMATION OF CARBON DIOXIDE EMISSIONS OF MAGNETIC RESONANCE IMAGING (MRI) UNITS AND COMPUTED TOMOGRAPHY (CT) SCANNERS\",\"authors\":\"Giorgos P. Kouropoulos\",\"doi\":\"10.4090/JUEE.2018.V12N2.172-187\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The scope of the specific study is the statistical prediction of the annual carbon dioxide use emissions due to the operation of computed tomography (CT) scanners and magnetic resonance imaging (MRI) units in hospitals, health units and diagnostic centers, for the period between 2018 and 2030, in 120 countries across the world. The main sources of information for this study comprise statistical data from international organizations, scientific articles and measurements. The basic calculation tool of the study is a mathematical model, modified in such a way so that the calculations can be carried out using the available statistical data. In the final stage of the study, the functions that predict the carbon dioxide use emissions in relation to the years, will be extracted. Furthermore, all the errors and uncertainties of the mathematical model will be estimated. The conclusion, arising after implementation of the calculations, is that the carbon dioxide use emissions of CT scanners and MRI units are expected to grow by 30%, i.e., from 0.344 gigatonnes in 2018 to 0.497 gigatonnes in 2030.\",\"PeriodicalId\":17594,\"journal\":{\"name\":\"Journal of Urban and Environmental Engineering\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Urban and Environmental Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4090/JUEE.2018.V12N2.172-187\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Urban and Environmental Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4090/JUEE.2018.V12N2.172-187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
A PREDICTIVE MODEL FOR THE ESTIMATION OF CARBON DIOXIDE EMISSIONS OF MAGNETIC RESONANCE IMAGING (MRI) UNITS AND COMPUTED TOMOGRAPHY (CT) SCANNERS
The scope of the specific study is the statistical prediction of the annual carbon dioxide use emissions due to the operation of computed tomography (CT) scanners and magnetic resonance imaging (MRI) units in hospitals, health units and diagnostic centers, for the period between 2018 and 2030, in 120 countries across the world. The main sources of information for this study comprise statistical data from international organizations, scientific articles and measurements. The basic calculation tool of the study is a mathematical model, modified in such a way so that the calculations can be carried out using the available statistical data. In the final stage of the study, the functions that predict the carbon dioxide use emissions in relation to the years, will be extracted. Furthermore, all the errors and uncertainties of the mathematical model will be estimated. The conclusion, arising after implementation of the calculations, is that the carbon dioxide use emissions of CT scanners and MRI units are expected to grow by 30%, i.e., from 0.344 gigatonnes in 2018 to 0.497 gigatonnes in 2030.
期刊介绍:
Journal of Urban and Environmental Engineering (JUEE) provides a forum for original papers and for the exchange of information and views on significant developments in urban and environmental engineering worldwide. The scope of the journal includes: (a) Water Resources and Waste Management [...] (b) Constructions and Environment[...] (c) Urban Design[...] (d) Transportation Engineering[...] The Editors welcome original papers, scientific notes and discussions, in English, in those and related topics. All papers submitted to the Journal are peer reviewed by an international panel of Associate Editors and other experts. Authors are encouraged to suggest potential referees with their submission. Authors will have to confirm that the work, or any part of it, has not been published before and is not presently being considered for publication elsewhere.