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Potential of big data approach for remote sensing of vehicle exhaust emissions
At present, remote sensing (RS) is applied in detecting vehicle exhaust emissions, and usually the RS emission results in a definite vehicle specific power (VSP) range are used to evaluate vehicle emissions and identify high-emitting vehicles. When the VSP exceeds this range, the corresponding vehic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7970906/ https://www.ncbi.nlm.nih.gov/pubmed/33750845 http://dx.doi.org/10.1038/s41598-021-84890-7 |
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author | Hao, Lijun Yin, Hang Wang, Junfang Wang, Xiaohu Ge, Yunshan |
author_facet | Hao, Lijun Yin, Hang Wang, Junfang Wang, Xiaohu Ge, Yunshan |
author_sort | Hao, Lijun |
collection | PubMed |
description | At present, remote sensing (RS) is applied in detecting vehicle exhaust emissions, and usually the RS emission results in a definite vehicle specific power (VSP) range are used to evaluate vehicle emissions and identify high-emitting vehicles. When the VSP exceeds this range, the corresponding vehicle emission RS data will not be used to assess vehicle emissions. This method is equivalent to setting only one VSP Bin qualified for vehicle emission evaluation, and generally only one threshold limit is given for each emission pollutant without considering the fluctuation characteristics of vehicle emissions with VSP. Therefore, it is easy to cause misjudgment in identifying high-emitting vehicles and is not conducive to scientific management of vehicle emissions. In addition, the vehicle emissions outside the selected VSP Bin are more serious and should be included in the scope of supervision. This research proposed the methods of vehicle classifications and VSP Binning in order to categorize the driving conditions of each kind of vehicles, and a big data approach was proposed to analyze the vehicle emission RS data in each VSP Bin for vehicle emission evaluation. |
format | Online Article Text |
id | pubmed-7970906 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79709062021-03-19 Potential of big data approach for remote sensing of vehicle exhaust emissions Hao, Lijun Yin, Hang Wang, Junfang Wang, Xiaohu Ge, Yunshan Sci Rep Article At present, remote sensing (RS) is applied in detecting vehicle exhaust emissions, and usually the RS emission results in a definite vehicle specific power (VSP) range are used to evaluate vehicle emissions and identify high-emitting vehicles. When the VSP exceeds this range, the corresponding vehicle emission RS data will not be used to assess vehicle emissions. This method is equivalent to setting only one VSP Bin qualified for vehicle emission evaluation, and generally only one threshold limit is given for each emission pollutant without considering the fluctuation characteristics of vehicle emissions with VSP. Therefore, it is easy to cause misjudgment in identifying high-emitting vehicles and is not conducive to scientific management of vehicle emissions. In addition, the vehicle emissions outside the selected VSP Bin are more serious and should be included in the scope of supervision. This research proposed the methods of vehicle classifications and VSP Binning in order to categorize the driving conditions of each kind of vehicles, and a big data approach was proposed to analyze the vehicle emission RS data in each VSP Bin for vehicle emission evaluation. Nature Publishing Group UK 2021-03-09 /pmc/articles/PMC7970906/ /pubmed/33750845 http://dx.doi.org/10.1038/s41598-021-84890-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Hao, Lijun Yin, Hang Wang, Junfang Wang, Xiaohu Ge, Yunshan Potential of big data approach for remote sensing of vehicle exhaust emissions |
title | Potential of big data approach for remote sensing of vehicle exhaust emissions |
title_full | Potential of big data approach for remote sensing of vehicle exhaust emissions |
title_fullStr | Potential of big data approach for remote sensing of vehicle exhaust emissions |
title_full_unstemmed | Potential of big data approach for remote sensing of vehicle exhaust emissions |
title_short | Potential of big data approach for remote sensing of vehicle exhaust emissions |
title_sort | potential of big data approach for remote sensing of vehicle exhaust emissions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7970906/ https://www.ncbi.nlm.nih.gov/pubmed/33750845 http://dx.doi.org/10.1038/s41598-021-84890-7 |
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