Roadside vehicle particulate matter concentration estimation using artificial neural network model in Addis Ababa, Ethiopia
文献类型：期刊论文
| 作者 | Jida, Solomon Neway; Hetet, Jean-Francois; Chesse, Pascal; Guadie, Awoke |
| 刊名 | JOURNAL OF ENVIRONMENTAL SCIENCES
 |
| 出版日期 | 2021-03 |
| 卷号 | 101页码:428-439 |
| 关键词 | Addis Ababa Artificial neural network PM prediction Roadside emission |
| ISSN号 | 1001-0742 |
| 英文摘要 | Currently, vehicle-related particulate matter is the main determinant air pollution in the urban environment. This study was designed to investigate the level of fine (PM2.5) and coarse particle (PM10) concentration of roadside vehicles in Addis Ababa, the capital city of Ethiopia using artificial neural network model. To train, test and validate the model, the traffic volume, weather data and particulate matter concentrations were collected from 15 different sites in the city. The experimental results showed that the city average 24-hr PM2.5 concentration is 13%-144% and 58%-241% higher than air quality index (AQI) and world health organization (WHO) standards, respectively. The PM10 results also exceeded the AQI (54%-65%) and WHO (8%-395%) standards. The model runs using the Levenberg-Marquardt (Trainlm) and the Scaled Conjugate Gradient (Trainscg) and comparison were performed, to identify the minimum fractional error between the observed and the predicted value. The two models were determined using the correlation coefficient and other statistical parameters. The Trainscg model, the average concentration of PM2.5 and PM10 exhaust emission correlation coefficient were predicted to be (R-2 = 0.775) and (R-2 = 0.92), respectively. The Trainlm model has also well predicted the exhaust emission of PM2.5 (R-2 = 0.943) and PM10 (R-2 = 0.959). The overall results showed that a better correlation coefficient obtained in the Trainlm model, could be considered as optional methods to predict transport-related particulate matter concentration emission using traffic volume and weather data for Ethiopia cities and other countries that have similar geographical and development settings. (C) 2020 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. |
| WOS研究方向 | Environmental Sciences |
| 源URL | [http://ir.rcees.ac.cn/handle/311016/46150]  |
| 专题 | 生态环境研究中心_中国科学院环境生物技术重点实验室 |
| 作者单位 | 1.Arba Minch Univ, Fac Mech & Prod Engn, Inst Technol, Dept Mech Engn, Arba Minch 21, Ethiopia 2.Arba Minch Univ, Coll Nat Sci, Dept Biol, Arba Minch 21, Ethiopia 3.Chinese Acad Sci, Key Lab Environm Biotechnol, Res Ctr Ecoenvironm Sci, Beijing 100085, Peoples R China 4.Ecole Cent Nantes, Res Lab Hydrodynam Energet & Atmospher Environm L, F-44300 Nantes, France |
| 推荐引用方式 GB/T 7714 | Jida, Solomon Neway,Hetet, Jean-Francois,Chesse, Pascal,et al. Roadside vehicle particulate matter concentration estimation using artificial neural network model in Addis Ababa, Ethiopia[J]. JOURNAL OF ENVIRONMENTAL SCIENCES,2021,101:428-439. |
| APA | Jida, Solomon Neway,Hetet, Jean-Francois,Chesse, Pascal,&Guadie, Awoke.(2021).Roadside vehicle particulate matter concentration estimation using artificial neural network model in Addis Ababa, Ethiopia.JOURNAL OF ENVIRONMENTAL SCIENCES,101,428-439. |
| MLA | Jida, Solomon Neway,et al."Roadside vehicle particulate matter concentration estimation using artificial neural network model in Addis Ababa, Ethiopia".JOURNAL OF ENVIRONMENTAL SCIENCES 101(2021):428-439. |
入库方式： OAI收割
来源：生态环境研究中心
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