Analyzing the Freight Characteristics and Carbon Emission of Construction Waste Hauling Trucks

Big Data Analytics of Hong Kong

Dados Bibliográficos

ID15509866
AutoresXiaoxuan Wei (0000-0002-2163-9888, University of Hong Kong, autor correspondente), Meng Ye (0000-0002-7281-0411, Southwest Jiaotong University), Liang Yuan (0000-0002-4716-7073, University of Hong Kong), Wei Bi (0000-0003-1042-4547, University of Hong Kong), Weisheng Lu (0000-0001-7504-5316, University of Hong Kong)
Ano2022
Volume19
Fascículo4
Páginas2318-2318
Data de publicação2022-02-17
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoInternational Journal of Environmental Research and Public Health (JOURNAL)
Identificadores do periódicoISSN: 1661-7827 • E-ISSN: 1660-4601
EditoraMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19042318
PMID35206502
OpenAlexW4212875966
IdiomaEN
Referências citadas48

Unlike their counterparts that are used for container or municipal solid waste hauling, or their peers of taxies and other commercial vehicles, construction waste hauling trucks (CWHTs) are heterogeneous in that they transport construction waste from construction sites to designated disposal facilities. Depending on the intensity of the construction activities, there are many CWHTs in operation, imposing massive impacts on a region's transportation system and natural environment. However, such impacts have rarely been documented. This paper has analyzed CWHTs' freight characteristics and their carbon emission by harnessing a big dataset of 112,942 construction waste transport trips in Hong Kong in May 2015. It has been observed that CWHTs generate 4544 daily trips with 307.64 tons CO 2 -eq emitted on working days, and 553 daily trips emitting 28.78 tons CO 2 -eq on non-working days. Freight carbon emission has been found to be related to the vehicle type, transporting weight, and trip length, while the trip length is the most influential metric to carbon emission. This research contributes to the understanding of freight characteristics by exploiting a valuable big dataset and providing important benchmarking metrics for monitoring the effectiveness of policy interventions related to construction waste transportation planning and carbon emission

Analytics · Big data · Business · Data mining · Database · Transport engineering · Truck · Computer Science · Engineering · Environmental Science · Maritime Ports and Logistics · Urban and Freight Transport Logistics · Vehicle emissions and performance · Automotive Engineering