Characterizing carbon emissions from China V and China VI gasoline vehicles based on portable emission measurement systems-Reference-Cited by-同舟云学术

Characterizing carbon emissions from China V and China VI gasoline vehicles based on portable emission measurement systems

Published:2022-12 Issue: Volume:378 Page:134458
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Zhu Xing-hang^ORCID,He Hong-di^ORCID,Lu Kai-fa,Peng Zhong-ren,Gao H. Oliver

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Strategy and Management,General Environmental Science,Renewable Energy, Sustainability and the Environment,Building and Construction

Reference46 articles.

1. A comparative analysis of Gradient Boosting algorithms[J];Bentéjac;Artif. Intell. Rev.,2020

2. Using portable emissions measurement systems (PEMS) to derive more accurate estimates of fuel use and nitrogen oxides emissions from modern euro 6 passenger cars under real-world driving conditions[J];Bishop;Appl. Energy,2019

3. Multimodel inference understanding AIC and BIC in model selection;Burnham;Socio. Methods Res.,2004

4. On-road emission characteristics of VOCs from light-duty gasoline vehicles in Beijing, China[J];Cao;Atmos. Environ.,2016

5. The Research Report: Digital Mobility for Carbon Neutrality. Beijing;Center for Environmental Education and Communications of Ministry of Ecology and Environment,2021

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Uncovering driving factors and spatiotemporal patterns of urban passenger car CO2 emissions: A case study in Hangzhou, China;Applied Energy;2024-12

2. When green transportation backfires: High-speed rail's impact on transport-sector carbon emissions from 315 Chinese cities;Sustainable Cities and Society;2024-11

3. Exhaust emissions and energy conversion of hybrid and conventional CNG buses;Transportation Research Part D: Transport and Environment;2024-10

4. CO2 emission characteristics of China VI hybrid vehicles;Transportation Research Part D: Transport and Environment;2024-10

5. Fine particulate matter concentration prediction based on hybrid convolutional network with aggregated local and global spatiotemporal information: A case study in Beijing and Chongqing;Atmospheric Environment;2024-09