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Risk Assessment of Accidents for Sustainable Safety

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Health, Well-Being and Sustainability".

Deadline for manuscript submissions: closed (10 April 2024) | Viewed by 20007

Special Issue Editors


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Guest Editor
College of Environment and Safety Engineering, Fuzhou University, Fuzhou 350116, China
Interests: safety science; emergency management; fire science and fire protection engineering

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Guest Editor
College of Quality & Safety Engineering, China Jiliang University, Hangzhou 310018, China
Interests: safety science and engineering; accident prevention; spontaneous combustion; thermodynamics; solid waste resource transformation and safe disposal
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
College of Environment and Safety Engineering, Fuzhou University, Fuzhou 350116, China
Interests: fire safety; fire simulation; tunnel fire
Special Issues, Collections and Topics in MDPI journals
Affiliation: School of Petroleum Engineering, Southwest Petroleum University, Chengdu 610500, China
Interests: process safety and security; critical infrastructure resilience; dynamic risk assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of increasingly complex technology and large-scale industrial projects, all kinds of safety problems become extremely intricate in daily safety management. Accident risks may be an obstacle to the sustainability industries and societies if the risk is not accurately identified and eliminated. Risk assessment is a well-known tool to identify accidents that may result in casualties, economic losses, and environmental pollution. As a result, risk assessment is essential to prevent and mitigate accidents, promoting the sustainable development of human activities. In the safety domain, many risk assessment methods have been developed in recent decades, such as fault tree analysis, event tree analysis, bow-tie model, Bayesian network model, dynamic graph model, etc. Additionally, these methods are developed from a qualitative risk assessment to a quantitative risk assessment, and from static risk assessment to dynamic risk assessment. Therefore, we believe that the timing is ripe to quantify, predict, and visualize risk and hazard levels to acceptable levels in this field with new theoretical perspectives, interdisciplinary methods, multi-source data, and innovative practices.

Therefore, we develop a Special Issue Risk Assessment of Accidents for Sustainable Safety to develop safety theories, risk assessment methods, risk prevention, and analysis tools/frameworks for preventing accidents. We hope that the research findings and policy implications will help us to highlight the latest advances in the field of accident risk analysis and outline possible issues that need to be further explored to better provide a solid scientific basis and technological support for global and regional sustainable safety.

The research topics include, while not limited to:

  • Risk assessment of accidents;
  • Risk management related to accident prevention;
  • Accident analysis and assessment;
  • Literature review related to accident prevention and mitigation;
  • Bibliometric analysis of accident-related research;
  • Accident statistical analysis;
  • Lessons from accidents;
  • Accident simulation and evolution analysis;
  • The relationship between safety and sustainability;
  • Safety culture and safety climate research;
  • Safety and resilience with respect to accidents;
  • Safety barrier management for preventing accidents.

Prof. Dr. Fuqiang Yang
Prof. Dr. Hui Liu
Dr. Longxing Yu
Dr. Chao Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • accident
  • risk assessment
  • safety
  • sustainability

Published Papers (9 papers)

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Research

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16 pages, 5964 KiB  
Article
Reflective Properties and Lighting Quality of Urban Asphalt Roads in a Full-Service Cycle: A Longitudinal Study in Zhejiang Province, China
by Chi Zhang, Chuan Lei, Lei Ye, Cheng Kang, Meihong Wang, Zhiyi Huang and Ke Wu
Sustainability 2023, 15(24), 16784; https://doi.org/10.3390/su152416784 - 13 Dec 2023
Viewed by 686
Abstract
To optimize the lighting design of urban roads in China and improve traffic safety, the present study conducted a 10-year longitudinal experiment on urban asphalt roads in Zhejiang Province, China, and analyzed variations of the road surface’s reflective properties and lighting quality with [...] Read more.
To optimize the lighting design of urban roads in China and improve traffic safety, the present study conducted a 10-year longitudinal experiment on urban asphalt roads in Zhejiang Province, China, and analyzed variations of the road surface’s reflective properties and lighting quality with different service lengths, surface areas, and observation angles. The results showed that these roads were R2 roads with low resilience and strong directional reflection. The average luminance coefficient Q0 reached maximum and minimum at the beginning and after around one year of service, respectively. After four years of service, Q0 was about 80% of its initial value and remained stable. The specularity factor S1 reached a maximum of around two years of service. The average luminance Lav was approximately 35%, and overall luminance uniformity U0 was 31%, lower than that of R3 roads during the toughest period of the service life. If the lighting design follows the 1° observation angle r-table recommended by the specification, high Lav and low U0 occur for roads like expressways, leading to a significant increase in traffic safety risks; collector roads may suffer from insufficient Lav. Urban asphalt roads in Zhejiang Province, China, should use the R2 road standard and increase the design value of Lav by 35–45%, and high-level roads should increase the design value of U0 by 40%. The present study will provide scientific references for the design of lighting for urban roads in China, thus promoting long-term sustainable traffic safety in cities. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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18 pages, 4868 KiB  
Article
Analysis of the Severity and Cause and Effect of Occupational Accidents in South Korea
by Jérémie Tuganishuri, Sang-Guk Yum, Manik Das Adhikari and Tae-Keun Oh
Sustainability 2023, 15(20), 15058; https://doi.org/10.3390/su152015058 - 19 Oct 2023
Viewed by 1274
Abstract
The industrial sector in South Korea has recently undergone significant growth; however, it is also known for its hazardous workplaces. Occupational accidents have had a widespread impact across various industries; therefore, the identification of accident-influencing factors is crucial to improve workplace safety. We [...] Read more.
The industrial sector in South Korea has recently undergone significant growth; however, it is also known for its hazardous workplaces. Occupational accidents have had a widespread impact across various industries; therefore, the identification of accident-influencing factors is crucial to improve workplace safety. We analyzed the occupational accident database from the Ministry of Economy and Finance to examine the influencing factors, including worker information, project details, time-related variables, and accident descriptions. Exploratory and correspondence data analyses were performed to identify patterns and relationships between variables. We applied multinomial logistic models and random forest algorithms to understand the correlation between victim status and independent variables. Results showed that 67% of all accidents occurred among workers with less than one month of employment. The multinomial regression model achieved a prediction accuracy of 97.66% with a kappa value of 0.846, outperforming the random forest model (kappa = 0.844). The receiver operating curve illustrated that the random forest had higher misclassification rates when distinguishing between injuries and fatalities. To mitigate accidents among new workers, enhanced safety training and protective measures are needed to enforce a healthy workplace. This study contributes to ongoing efforts to advance workplace safety, reduce occupational accidents, and promote a healthier working environment. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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29 pages, 8323 KiB  
Article
Insights into the Application of Machine Learning in Industrial Risk Assessment: A Bibliometric Mapping Analysis
by Ze Wei, Hui Liu, Xuewen Tao, Kai Pan, Rui Huang, Wenjing Ji and Jianhai Wang
Sustainability 2023, 15(8), 6965; https://doi.org/10.3390/su15086965 - 20 Apr 2023
Cited by 5 | Viewed by 2985
Abstract
Risk assessment is of great significance in industrial production and sustainable development. Great potential is attributed to machine learning in industrial risk assessment as a promising technology in the fields of computer science and the internet. To better understand the role of machine [...] Read more.
Risk assessment is of great significance in industrial production and sustainable development. Great potential is attributed to machine learning in industrial risk assessment as a promising technology in the fields of computer science and the internet. To better understand the role of machine learning in this field and to investigate the current research status, we selected 3116 papers from the SCIE and SSCI databases of the WOS retrieval platform between 1991 and 2022 as our data sample. The VOSviewer, Bibliometrix R, and CiteSpace software were used to perform co-occurrence analysis, clustering analysis, and dual-map overlay analysis of keywords. The results indicate that the development trend of machine learning in industrial risk assessment can be divided into three stages: initial exploration, stable development, and high-speed development. Machine learning algorithm design, applications in biomedicine, risk monitoring in construction and machinery, and environmental protection are the knowledge base of this study. There are three research hotspots in the application of machine learning to industrial risk assessment: the study of machine learning algorithms, the risk assessment of machine learning in the Industry 4.0 system, and the application of machine learning in autonomous driving. At present, the basic theories and structural systems related to this research have been established, and there are numerous research directions and extensive frontier branches. “Random Forest”, “Industry 4.0”, “supply chain risk assessment”, and “Internet of Things” are at the forefront of the research. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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11 pages, 3009 KiB  
Article
A Dynamic Emergency Plan Generation Method Considering Different Situations and Limited Resources
by Zixin Zhang, Liang Wang, Jiayan Lai and Yingming Wang
Sustainability 2023, 15(7), 5996; https://doi.org/10.3390/su15075996 - 30 Mar 2023
Viewed by 1022
Abstract
When an emergency event occurs, emergency plans are usually employed to respond the emergency situations in order to prevent or mitigate possible losses of life and property. Therefore, emergency plans play an important and indispensable part in emergency decision-making. With regard to the [...] Read more.
When an emergency event occurs, emergency plans are usually employed to respond the emergency situations in order to prevent or mitigate possible losses of life and property. Therefore, emergency plans play an important and indispensable part in emergency decision-making. With regard to the question of how to generate emergency plans, extant studies have discussed the problem from various perspectives, and fruitful results have been obtained. Dynamic evolution is a typical feature of emergency events, and usually involves the updating of related information regarding an emergency event. Existing studies have considered dynamic evolution during the emergency plan generation process only from a single perspective, neglecting the related need to update information as dynamic evolution occurs. Information related to the emergency event plays a vital role in the emergency plan generation process, and needs to be considered. To overcome these limitations, the present study proposes a novel dynamic emergency plan generation method based on integer linear programming, which considers different emergency situations and limited resources. An illustrative example and descriptive comparisons are provided to demonstrate the novelty, superiority, and validity of the proposed method. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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16 pages, 3325 KiB  
Article
Research on the Construction Method of Double Prevention Mechanism in Chinese Heating Enterprises Based on Bidirectional Dynamic Risk-Hidden Danger Transmission
by Yejiao Liu, Ting Teng, Zeyu Duan, Mengyuan Cui, Wencai Wang, Yuhui Ren and Zhichao Tian
Sustainability 2023, 15(3), 2849; https://doi.org/10.3390/su15032849 - 3 Feb 2023
Cited by 1 | Viewed by 2450
Abstract
The heating industries are extremely dispersed in China, and most heating enterprises are small in scale, poor in foundation, and chaotic in safety management. The construction method of the double prevention mechanism of heating enterprises in China was analyzed and studied based on [...] Read more.
The heating industries are extremely dispersed in China, and most heating enterprises are small in scale, poor in foundation, and chaotic in safety management. The construction method of the double prevention mechanism of heating enterprises in China was analyzed and studied based on the PDCA cycle model and the improved risk assessment method for operating conditions. The analytic hierarchy process was used to determine the weight of dangerous and harmful factors and corresponding control measures for an accident type. The concept of “failure frequency” was introduced, and the calculation method of accident probability (L) was modified so that the accurate hierarchical control and dynamic risk assessment of accident risks can be realized. At the same time, the failure of control measures is defined as “hidden danger” in this paper. Finally, the bidirectional dynamic transmission mechanism of hidden danger investigation and treatment and risk hierarchical control was established. The main problems existing in the construction of double prevention mechanism of heating enterprises in China were discussed and some countermeasures and suggestions were put forward. According to the above methods and steps, the double prevention mechanism of heating enterprises can be reasonably established. Thus, the risks can be effectively identified, the hidden dangers can be controlled, and the safety production of heating enterprises can be guaranteed. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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15 pages, 5682 KiB  
Article
Safety Analysis and Emergency Response of Suspended Oil and Gas Pipelines Triggered by Natural Disasters
by Jin Yu, Chao Chen and Changjun Li
Sustainability 2022, 14(24), 17045; https://doi.org/10.3390/su142417045 - 19 Dec 2022
Cited by 3 | Viewed by 1599
Abstract
Pipelines play a dominant role in the transportation of oil and gas and the safety of pipelines is essential for the supply of energy. However, natural disasters such as floods and land subsidence may lead to suspended pipelines, resulting in pipeline failure accidents, [...] Read more.
Pipelines play a dominant role in the transportation of oil and gas and the safety of pipelines is essential for the supply of energy. However, natural disasters such as floods and land subsidence may lead to suspended pipelines, resulting in pipeline failure accidents, causing casualties and environmental pollution. To deal with the emergency caused by suspended pipelines, it is needed to identify the failure mechanisms of suspended pipelines caused by natural disasters. Therefore, this study conducts a safety analysis of suspended pipelines using a nonlinear finite element method (FEM), considering the nonlinear pipe–soil contact and plastic deformation. A case study is conducted to investigate the influencing parameters (e.g., the suspended length, the operating pressure, and the fluid mass). This work demonstrates that irreversible plastic strains occur when the suspended length exceeds 50 m, and it will reach 2% when the suspended length is 340 m. Finally, an emergency response plan based on plastic strain and suspended length is proposed to determine the emergency level of the suspended pipelines caused by natural disasters. This study can provide technical support for the emergency response of pipelines in areas with frequent natural disasters, promoting the sustainable development of oil and natural gas pipelines. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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21 pages, 2313 KiB  
Article
Realizing Smart Safety Management in the Era of Safety 4.0: A New Method towards Sustainable Safety
by Xi Huang, Bing Wang and Chao Wu
Sustainability 2022, 14(21), 13915; https://doi.org/10.3390/su142113915 - 26 Oct 2022
Cited by 3 | Viewed by 1936
Abstract
Safety 4.0 is a new stage of safety science coincident with the development of Industry 4.0. In Safety 4.0, safety researchers and professionals attach importance to the perspective of safety information and emerging technologies in safety management, and thus promote a new concept: [...] Read more.
Safety 4.0 is a new stage of safety science coincident with the development of Industry 4.0. In Safety 4.0, safety researchers and professionals attach importance to the perspective of safety information and emerging technologies in safety management, and thus promote a new concept: smart safety management (SSM). However, there are still many gaps in its fundamental theory, and there are few fundamental studies on the concept and essence of SSM. In order to fill these gaps, this paper introduces a theoretical study on the method of SSM. Firstly, in order to clarify the concept of smartness in the era of information, we elaborate the smartness performance of artificial entities and the essence of smart safety capability on the basis of analyzing the smartness performance of smart safety entities (SSEs). Then, we review the new characteristics and requirements of organizational safety management research and practice in the era of Safety 4.0; on this basis, we propose the definition and connotation of SSM in the era of Safety 4.0, and elaborate the specific content of the SSM method. Specifically, we divide SSM into four modules, safety information processing, safety action, inspiring awareness of safety and internal optimization, and thus build the content model of SSM. By expounding the contents and steps of the four modules, we further elaborate how to conduct SSM in industrial organizations. Then, we propose a SSM ecosystem for realizing sustainable safety in industrial organizations and analyze the approaches to realizing SSM in coal mine safety production. Finally, we analyze the significance of SSM in supporting sustainable safety and discuss the practical challenges that SSM may encounter in the future. The results show that SSM is a method based on safety intelligence, and it can support sustainable safety through the four aspects of comprehensive function, safety predictability, safety awareness and continuous optimalization. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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18 pages, 3976 KiB  
Article
Characteristics of Chemical Accidents and Risk Assessment Method for Petrochemical Enterprises Based on Improved FBN
by Lidong Pan, Yu Zheng, Juan Zheng, Bin Xu, Guangzhe Liu, Min Wang and Dingding Yang
Sustainability 2022, 14(19), 12072; https://doi.org/10.3390/su141912072 - 24 Sep 2022
Cited by 12 | Viewed by 2636
Abstract
Refining and chemical integration is the major trend in the development of the world petrochemical industry, showing intensive and large-scale development. The accident risks caused by this integration are complex and diverse, and pose new challenges to petrochemical industry safety. In order to [...] Read more.
Refining and chemical integration is the major trend in the development of the world petrochemical industry, showing intensive and large-scale development. The accident risks caused by this integration are complex and diverse, and pose new challenges to petrochemical industry safety. In order to clarify the characteristics of the accident and the risk root contained in the production process of the enterprise, avoid the risk reasonably and improve the overall safety level of the petrochemical industry, in this paper, 159 accident cases of dangerous chemicals in China from 2017–2021 were statistically analyzed. A Bayesian network (BN)-based risk analysis model was proposed to clarify the characteristics and root causes of accident risks in large refining enterprises. The prior probability parameter in the Bayesian network was replaced by the comprehensive weight, which combined subjective and objective weights. A hybrid method of fuzzy set theory and a noisy-OR gate model was employed to eliminate the problem of the conditional probability parameters being difficult to obtain and the evaluation results not being accurate in traditional BN networks. Finally, the feasibility of the methods was verified by a case study of a petrochemical enterprise in Zhoushan. The results indicated that leakage, fire and explosion were the main types of accidents in petrochemical enterprises. The human factor was the main influencing factors of the top six most critical risk root causes in the enterprise. The coupling risk has a relatively large impact on enterprise security. The research results are in line with reality and can provide a reference for the safety risk management and control of petrochemical enterprises. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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Review

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17 pages, 3891 KiB  
Review
Review on Improvements to the Safety Level of Coal Mines by Applying Intelligent Coal Mining
by Xuefei Wu, Hongxia Li, Baoli Wang and Mengbo Zhu
Sustainability 2022, 14(24), 16400; https://doi.org/10.3390/su142416400 - 7 Dec 2022
Cited by 13 | Viewed by 3266
Abstract
China suffers the worst coal mine disasters in the world. Lots of miners lose their lives or suffer occupational injury. Fortunately, China is developing vigorously intelligent coal mining, which is the combination of traditional coal mining and the latest technology. Mining expects to [...] Read more.
China suffers the worst coal mine disasters in the world. Lots of miners lose their lives or suffer occupational injury. Fortunately, China is developing vigorously intelligent coal mining, which is the combination of traditional coal mining and the latest technology. Mining expects to relieve or solve coal mine safety, health and intensive labor issues and ensure energy security by applying intelligent coal mining. This paper fully reviews the promotion of intelligent coal mining to coal mine safety. Firstly, a brief history of intelligent coal mining is introduced. Then the safety motivation of the intelligent coal mine is discussed in four perspectives, including current the coal mine safety tendency, the positive impact of mechanized coal mining on safety, coal mine safety conception of “Mechanization Replacement and Automation Reduction”, and government initiatives. The intelligent prevention and control scheme of major disasters matching intelligent coal mining are also reviewed in the present paper, including intelligent gas extraction, intelligent coal and gas outburst/rock-burst prevention, and the real-time monitoring of water diversion fissure zone. Finally, the positive impacts of intelligent coal mining on safety are evaluated. Compared with traditional longwall face, the number of miners of coal cutting shift is reduced from 20~30 to 5~7, and the working environment is greatly improved. The statistics have shown that the employees in large coal mines, the mortality rates per 106 tons of coal output, and the number of deaths decreased by 33%, 72.2%, and 66.9% during the period of rapid development of intelligent mining technology (2016–2021). In the future, more and more key technologies and management skills should be introduced, aiming at workless mining and the intrinsic safety of the coal mine. This paper provides a way for safety researchers around the world to understand the tendency of coal mine safety in China. Full article
(This article belongs to the Special Issue Risk Assessment of Accidents for Sustainable Safety)
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