The accidents caused by hazardous material during road transportation may result in catastrophic losses of lives and economics, as well as damages to the environment. Regarding the deficiencies in the information systems of hazmat transportation accidents, this study conducts a survey of 371 accidents with consequence Levels II to V involving road transportation in China from 2004-2018. The study proposes a comprehensive analysis framework for understanding the overall status associated with key factors of hazmat transportation in terms of characteristics, cause, and severity. By incorporating the adaptive data analysis techniques and tackling uncertainty, the preventative measures can be carried out for supporting safety management in hazmat transportation. Thus, this study firstly analyzed spatial-temporal trends to understand the major characteristics of hazmat transportation accidents. Secondly, it presents a quantitative description of the relation among the hazmat properties, accident characteristics, and the consequences of the accidents using the decision tree approach. Thirdly, an enhanced F-N curve-based analysis method that can describe the relationship between cumulative probability and number of deaths , was proposed under the power-law distribution and applied to several practical data sets for severity analysis. It can evaluate accident severity of hazmat material by road transportation while taking into account uncertainty in terms of data sources. Through the introduction of the as low as reasonably practicable (ALARP) principle for determining acceptable and tolerable levels, it is indicated that the F-N curves are above the tolerable line for most hazmat accident scenarios. The findings can provide an empirically supported theoretical basis for the decision-makers to take action to reduce accident frequencies and risks for effective hazmat transportation management.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215458 | PMC |
http://dx.doi.org/10.3390/ijerph17082793 | DOI Listing |
J Occup Health
January 2024
School of Interdisciplinary Informatics, College of Information Science & Technology, University of Nebraska, Omaha, NE, 68182, United States.
Heliyon
September 2023
"Babeş-Bolyai" University, Faculty of Environmental Science and Engineering, 30 Fantanele Street, 400294 Cluj-Napoca, Romania.
Accid Anal Prev
October 2023
Jiangsu Key Laboratory of Urban ITS, Southeast University, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, China; School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing, Jiangsu 211189, China.
Comput Intell Neurosci
February 2023
Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China.
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