Characteristics of hazardous chemical accidents in China: A statistical investigation

2012 ◽  
Vol 25 (4) ◽  
pp. 686-693 ◽  
Author(s):  
He-Da Zhang ◽  
Xiao-Ping Zheng
2019 ◽  
Vol 27 (3) ◽  
pp. 125-133
Author(s):  
Yapeng Wang ◽  
Jinguo Zhang ◽  
Yundou Wang ◽  
Xiaowen Xiong ◽  
Xin Zhao

Background: An objective, comprehensive and scientific evaluation of emergency medical rescue capability (EMRC) is of great realistic significance in assisting the health administrative department to grasp the overall response capability of all emergency medical rescue teams, enabling each team to have a full understanding of its own strengths and weakness and improve itself accordingly. At present, the research on the evaluation of EMRC in Hazardous Chemicals Accidents (HCA) is not systematic and in-depth, and the existing research results also have some shortcomings, such as, the lack of strong theoretical support for the evaluation index system, the relatively single function of evaluation methods, and so on. Objectives: The objective of this article is to research the evaluation index system and a new evaluation method of EMRC in HCA to overcome the above shortcomings. Methods: It establishes an emergency medical rescue capability model by employing the competency model and then constructs the evaluation index system on the basis of the analysis of all the factors of emergency medical rescue capability in hazardous chemical accidents and sets up an evaluation model based on the theory of connection numbers and partial connection numbers. It determines the competence ranking of several emergency medical rescue teams and the competence state of an individual emergency medical rescue team by calculating the connection principal value, and it also predicts how the emergency medical rescue capability will develop based on the values of partial connection numbers. Results: The example shows that the calculation process of this model is relatively simple, and its assessment results are objective and authentic, and moreover, its multi-functions can make up for the deficiency of the simplified function of other evaluation models. Conclusion: This method is scientific and rational to some extent and can provide reference for evaluation problems of the same kind.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Huyen Thi Thu Do ◽  
Tram Thi Bich Ly ◽  
Tho Tien Do

Abstract In this study, a combination of semi-quantitative risk assessment, composite indicator and fuzzy logic has been developed to identify industrial establishments and processes that represent potential environmental accidents associated with hazardous chemicals. The proposed method takes into consideration the root causes of risk probability of hazardous chemical accidents (HCAs), such as unsafe onsite storing and usage, inadequate operation training, poor safety management and analysis, equipment failure, and factors affected by the potential consequences of the accidents, including human health, water resources, and building and construction. These issues have been aggregated in a system of criteria and sub-criteria, demonstrated by a list of non-overlapping and exhaustive categorical terms. Semi-quantitative risk assessment is then applied to develop a framework for screening industrial establishments that exhibit potential HCAs. Fuzzy set theory with triangular fuzzy number deals with the uncertainty associated with the data input and reduces the influence of subjectivity and vagueness to the final results. The proposed method was tested among 77 industrial establishments located within the industrial zones of Ho Chi Minh City, Vietnam. Eighteen establishments were categorized as high HCA risk, 36 establishments were categorized as medium HCA risk, and 23 ones were of low HCA risk. The results are compatible with the practical chemical safety situation of the establishments and are consistent with expert evaluation.


Author(s):  
Xiaowei Li ◽  
Tiezhong Liu ◽  
Yongkui Liu

Hazardous chemical accidents (HCAs) seriously endanger public life, property, and health. Human and organizational factors are important causes of many kinds of accidents. In order to systematically explore the influencing factors of unsafe behaviors in HCAs in China, the method of human factors analysis and classification system based on the Bayesian network (BN-HFACs) was introduced. According to the 39 investigation reports of HCAs in China, the origin Bayesian network (BN) was obtained and the failure sensitivity of every node in BN was calculated. The results have shown that hazardous material environment (1.63) and mechanical equipment (0.49) in the level of preconditions of unsafe behavior have the same direction failure effect with operation error, while there is no factor has the same direction failure effect with operation violate. Some factors in organization influence and unsafe supervision, such as organization climate (0.34), operation guidance (0.37), planned operation (0.22), and legal supervision (0.19), are also important reasons for operational errors, while resource management (0.12), hidden investigation (0.18) and legal supervision (0.13) have an impact on operation violates. Moreover, there are still close relationships between other hierarchical elements, such as the operation guidance effect on the hazardous material environment (6.60), and the organizational climate has the most obvious impact on other factors at the level of organizational factors. Based on the above research conclusions, suggestions for individual, enterprise, and government were put forward, respectively, and the limitations of this study were also clarified.


2018 ◽  
Vol 10 (8) ◽  
pp. 2935 ◽  
Author(s):  
Laijun Zhao ◽  
Ying Qian ◽  
Qing-Mi Hu ◽  
Ran Jiang ◽  
Meiting Li ◽  
...  

From the perspective of characteristics and causes, probability and forecast, and safety management evaluation, this paper analyzes 3974 hazardous chemical casualty accidents that occurred between 2006 and 2017 in China. The trends, monthly and hourly distributions, lifecycles, chemical and accident types, and the direct and indirect causes of casualty accidents are analyzed first. To estimate the probability of casualty accidents, the Poisson regression model is employed. The time series model is developed to forecast the number of casualty accidents. The safety management of hazardous chemicals is evaluated based on an inverted U-shaped curve that fits the relationship between the number of casualty accidents and petrochemical industry outputs. Moreover, measures for improving the safety management of hazardous chemicals are provided based on the analysis, forecast, and evaluation. The results show that the probability of 200–600 casualty accidents occurring per year in China is 59.10%. Sixteen of thirty provinces are identified as having better safety management with regard to hazardous chemicals.


Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Jiang-Hua Zhang ◽  
Hai-Yue Liu ◽  
Rui Zhu ◽  
Yang Liu

The recent rapid development of information technology, such as sensing technology, communications technology, and database, allows us to use simulation experiments for analyzing serious accidents caused by hazardous chemicals. Due to the toxicity and diffusion of hazardous chemicals, these accidents often lead to not only severe consequences and economic losses, but also traffic jams at the same time. Emergency evacuation after hazardous chemical accidents is an effective means to reduce the loss of life and property and to smoothly resume the transport network as soon as possible. This paper considers the dynamic changes of the hazardous chemicals’ concentration after their leakage and simulates the diffusion process. Based on the characteristics of emergency evacuation of hazardous chemical accidents, we build a mixed-integer programming model and design a heuristic algorithm using network optimization and diffusion simulation (hereafter NODS). We then verify the validity and feasibility of the algorithm using Jinan, China, as a computational example. In the end, we compare the results from different scenarios to explore the key factors affecting the effectiveness of the evacuation process.


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