Exploring the influence of contributing factors and impact degree on bus emissions in real-world conditions

Author:

Wang Chao,Ye Zhirui,Bi Hui

Funder

Jiangsu Province Science Fund for Key Research and Development Program

National Natural Science Foundation of China

Jiangsu Province Science Fund for Distinguished Young Scholars

Science and Technology Innovation Project for Overseas Scholars of Nanjing

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Reference49 articles.

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2. Antanasijević DZ, Pocajt VV, Perić-Grujić AA, Ristić MĐ (2018) Multiple-input-multiple-output general regression neural networks model for the simultaneous estimation of traffic-related air pollutant emissions. Atmosph Pollut Res 9(2):388–397

3. Baidu baike. (2013). Table of standard body weight, http://baike.baidu.com/view/93890.html. accessed July 10, 2018.

4. Bel G, Bolancé C, Guillén M, Rosell J (2015) The environmental effects of changing speed limits: a quantile regression approach. Transp Res D 36:76–85

5. Bel G, Holst M (2018) Evaluation of the impact of bus rapid transit on air pollution in Mexico City. Transp Policy 63:209–220

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