Accidents In China Research Articles

Key emergency response technologies for abrupt air pollution accidents in China

Abrupt air pollution accidents can endanger people's health and destroy the local ecological environment. The appropriate emergency response can minimize the harmful effects of accidents and protect people's lives and property. This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years. With decades of effort, China has made significant progress in emergency monitoring technologies and equipment, source estimation technologies, pollutant dispersion simulation technologies and others. Many effective domestic emergency monitoring instruments (e.g., portable DOAS/FT-IR systems, portable FID/PID systems, portable GC-MS systems, scanning imaging remote sensing systems, and emergency monitoring vehicles) had been developed which can meet the demands for routine emergency response activities. A monitoring layout technique combining air dispersion simulation, fuzzy comprehensive evaluation, and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources. Multiple source estimation technologies, including the forward method and the inversion method, have been established and evaluated under various scenarios. Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed. A comprehensive emergency response platform integrating database support, source estimation, monitoring schemes, fast monitoring of pollutants, pollution predictions and risk assessment was developed based on the technical idea of "source identification - model simulation - environmental monitoring" dynamic interactive feedback. It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China.

Statistical analysis of major tunnel construction accidents in China from 2010 to 2020

The increase of transport mileage and expansion of underground space foster rapid development in tunnel engineering, particularly in China. China has the largest number of existing tunnels, and the growth rate has doubled over the past decade; whereas varied geographical environments, complex geological conditions, and incomplete management systems result in frequent tunnel construction accidents. The existing studies mostly focused on an individual accident type or operation stage, and the databases built decades ago are becoming obsolete to match developing construction concepts and technologies. Motivated by this concern, this paper conducts the statistical analysis on 48 cases of major tunnel construction accidents (MTCA, defined as an accident that results in more than three deaths) in China from 2010 to 2020, and examines the accident characteristics, including classification, time, region, location, construction method, and risk source. Based on the above time-space distributions of MTCA, two critical scientific issues concerning the safe construction of underground tunnels are discussed, including how to accurately evaluate the resilient network of hazards -vulnerable tunnel engineering, and how to build an efficient monitoring-mitigation-rescue system. The purpose is to provide a theoretical foundation for developing a database-driven management system that improves the resilience of tunnel construction to multiple hazards.

A Statistical Analysis of Hazardous Chemical Fatalities (HCFs) in China between 2015 and 2021

To study the occurrence characteristics of hazardous chemical accidents in China, mathematical analysis methods were used to study hazardous chemical fatalities (HCFs) in recent years. This research focused on selecting seven accident characteristics including time characteristics, geographical characteristics, accident type characteristics, hazardous chemical types, hazardous chemical production links, accident cause characteristics, and accident classification. The research results show that: (1) the occurrence of HCFs has obvious time-domain and regional characteristics, the number of casualties on Wednesday working days is the largest, 9:00–11:00 (inclusive) and 15:00–16:00 (inclusive) in a day are the two time periods with the largest number of incidents, the number of hazardous chemical accidents and deaths in economically developed coastal provinces is relatively high; (2) Analyze according to the type of accident statistics, the number of accidents and deaths caused by explosions, poisoning, asphyxiation, and fire are the largest; (3) Analyze according to the type of hazardous chemicals, drugs, compressed gas and liquefied gas, flammable solids, and spontaneous combustion materials, as well as flammable materials when wet are the types of hazardous chemicals that cause the most casualties; (4) Analyze according to the type of hazardous chemical accidents, the number of accidents and deaths caused in the production process is the largest; (5) Analyze according to the type of unsafe behavior by personnel, operator errors, the ignorance of safety, and the ignorance of warnings are the main causes of injuries and deaths caused by hazardous chemicals.; (6) Through single-factor feature analysis and multi-feature comprehensive cross-discussion, countermeasures, and suggestions for preventing and controlling accidents in hazardous chemical enterprises are put forward according to the characteristics of accidents caused by different accident characteristics.

An analysis of gas accidents in Chinese coal mines, 2009 – 2019

Underground coal mining has long been a dangerous occupation, particularly in China, where the incidence of gas-related accidents is high. This paper analyzes the frequency and the temporal and spatial distribution of major gas accidents in China that resulted in three or more deaths during the period 2009–2019. The analysis reveals a downward trend between 2009 and 2014, followed by relative stability from 2015 to 2019. The number of gas-related accidents was higher in some months than others, and most accidents occurred between 9 a.m. and 12 noon. There is also a clear geographical distribution pattern, with the majority of accidents occurring in provinces in the southwest region of China. While the immediate cause of these accidents is unsafe conditions or unsafe behavior, the study finds that the root cause is the lack of a safety culture. The article ends by making some suggestions for accident prevention, under the categories of technical measures, safety management, and safety culture.

Causal Analysis of Bus and Coach Accidents in China Based on Road Alignments

Causal Analysis of Bus and Coach Accidents in China Based on Road Alignments

Systematic Analysis of the Contributory Factors Related to Major Coach and Bus Accidents in China

Systematic Analysis of the Contributory Factors Related to Major Coach and Bus Accidents in China

Statistics and Multidimensional Analysis of Coal Mine Safety Accidents in China

Statistics and Multidimensional Analysis of Coal Mine Safety Accidents in China

Risk Evolution and Prevention and Control Strategies of Maritime Accidents in China's Coastal Areas Based on Complex Network Models

Risk Evolution and Prevention and Control Strategies of Maritime Accidents in China's Coastal Areas Based on Complex Network Models

Gas Accidents in China: From 2012–2021

Gas Accidents in China: From 2012–2021

Risk Coupling Characteristics of Maritime Accidents in Chinese Inland and Coastal Waters Based on N-K Model

The causes of maritime accidents are complex, mostly due to the coupling of four types of factors: human-ship-environmental-management. To effectively analyze the causes of maritime accidents in China, and reveal the risk coupling characteristics of accidents, this paper establishes the N-K model of maritime accident, and calculates and analyzes the four types of coupling of risk factors affecting safety in maritime traffic. This paper collects 922 maritime accidents that occurred in China from 2000 to 2020, and analyzes the location, type, and level of accidents and uses the trigger principle to describe the process of accidents. For marine and inland river accidents, this paper calculates the four types of coupling values of risk factors (single-factor coupling, two-factor coupling, three-factor coupling, four-factor coupling) for comparison and analysis. In addition, this paper calculates the coupling values of six typical maritime accidents of collision, sinking, contact, fire/explosion, stranding, grounding. According to the coupling values and the frequency of sub-factors, this paper analyzes the coupling characteristics of maritime accidents. The results show that in maritime accidents, as the number of risk factors participating in the coupling increases, the coupling value increases, and the multi-factor coupling is more likely to cause accidents. The overall situation of risk coupling causes of maritime accidents is basically consistent with inland river accidents, but they have their own characteristics in the specific degree of risk coupling and the dominant risk elements. In different types of maritime accidents, the risk coupling has different characteristics, and the dominant risk factors are also different.

Identification of Critical Causal Factors and Paths of Tower-Crane Accidents in China through System Thinking and Complex Networks

AbstractTower-crane accidents occur frequently with serious consequences, including deaths, serious injuries, and economic losses. To identify the critical causes and paths of tower-crane accidents...

Tripartite Evolutionary Game and Simulation Analysis of Coal Mining Safe Production Supervision under the Chinese Central Government’s Reward and Punishment Mechanism

In recent years, although coal mine accidents in China have decreased, they still occur frequently. Most previous studies on the evolutionary game of safety mining are limited to a focus on system dynamics and two-party game problems and lack a spatial graphic analysis of strategy evolution. The parameters adopted are too few, and the influencing factors considered are too simple. The purpose of the paper is to introduce more parameters to study which will have an important impact on the strategy choices of participants and the evolution path of the strategy over time. We construct a tripartite evolutionary game model of coal mining enterprises, local governments, and central governments. As our method, a payment matrix of participants and replicated dynamic equations is established, and we also implement parameter simulation in MATLAB. In summary, we found that the reward and punishment mechanism plays an important role in safe coal mining. Specifically, (1) intensifying rewards and penalties for coal mining enterprises and local governments will help encourage coal mining enterprises to implement safe production measures and local governments to implement central government safety supervision policies. However, increased rewards will reduce central government’s willingness to adopt incentive strategies. (2) The central government’s reward for coal mining enterprises’ safe production must be greater than the increased cost of safe production to encourage enterprises to implement such production. Economic incentives for local governments must be greater than the benefits of rent-seeking; only then will local governments choose to strictly implement supervision policies. (3) Increasing sales revenue and rent-seeking costs of coal mining enterprises can also encourage them to implement safe production. Therefore, a well-designed reward and punishment mechanism will change the behaviour of coal enterprises and improve the probability of safe production. The research presented in this paper further works on improving safe coal mining production and designing reasonable reward and punishment mechanisms.

Causation of Metro Operation Accidents in China: Calculation of Network Node Importance Based on DEMATEL and ISM

Continuous metro-operation accidents lead to serious economic loss and a negative social impact. The accident causation analysis is of great significance for accident prevention and metro operation safety promotion. Network node importance (NNI) evaluation has been widely used as a tool for ranking the nodes in complex networks; however, traditional indicators such as degree centrality (DC) are insufficient for examining accident networks. This study proposed an improved method by integrating decision making trail and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) into traditional NNI evaluation, where the key nodes are determined by both the nature of the accident network topology and the contribution of the nodes to accident development. Drawing on this method, 32 accident causal factors were identified and prioritized on the ground of 248 accident cases. It was found that 14 important factors related to staff (e.g., “driver noncompliance”), environment (e.g., “extrinsic nature disturbance”), passenger (e.g., “passenger sudden illness”), and machine (e.g., “track failures”) should be given priority in safety management due to their significant tendency of causing metro accidents. Theoretical and managerial implications were discussed to provide useful insights into the understanding of the causation of metro accidents and form a basis for metro managers to develop targeted safety countermeasures related to metro operation. The proposed hybrid method is proven effective in investigating accident networks involving sequential and casual relationships and revealing factors with high possibility to increase accidents.

Adaptation and validity of the Sleep Quality Scale among Chinese drivers.

PurposePoor sleep quality is closed related with driving accidents. However, due to the lack of a valid instrument for assessing drivers’ sleep quality, few studies have examined drivers’ sleep quality and its associations with driving behaviours and traffic accidents in China. The aim of this paper is to revise the Sleep Quality Scale (SQS) and assess its reliability and validity in Chinese drivers.Methods522 Chinese drivers aged from 18 to 56 years old agreed to complete the SQS, Daytime Sleepiness Perception Scale version 4 (DSPS-4), Self-report of Risky Driving Behavior (RD-SR) and Self-assessment of the Likelihood of Being Involved in a Risky Driving Situation (RD-SA).ResultsThe final Chinese version of the SQS contained 23 items across four factors: difficulty in getting up, difficulty in falling asleep, sleep recovery and daytime dysfunction. Second, man scored lower on the difficulty in falling asleep factor but higher on the sleep recovery factor than women. Third, low to moderate correlations were found between the SQS factors and the DSPS-4, RD-SA and RD-SR, indicating that the validity of the revised scale was satisfactory. More importantly, daytime dysfunction factor is an effective predictor of violation involvement and accident involvement.ConclusionThe revised SQS has acceptable reliability and validity and can be used as a tool to measure the sleep quality of Chinese drivers.

Current status, challenges, and future directions of university laboratory safety in China

The past two decades have seen a rise in university laboratory accidents in China. Although there is a growing awareness due to higher reporting and media coverage, the evaluation and understanding of common hazards and deficiencies in university laboratories remains to be addressed. Aiming to enhance safety in laboratory-related activities, this study analyzed the current status and challenges of university laboratory safety in China and presented future directions to reduce accidents using engineering and administrative controls. A descriptive statistical analysis of 110 publicly reported university laboratory accidents in mainland China since 2000 was performed to investigate the proximate causes of the accidents, and further, to identify potential deficiencies existing in the current safety management of laboratories. It was found that human factors were the most contributing cause and the training element was a vulnerable competency in laboratory safety management. Based on the results, a comparative analysis between the underlying reasons for the poor safety situation and the efforts that have been made has brought the challenges and possible solutions for safety improvements in university laboratories. By suggesting top-down and bottom-up approaches, the present study provides valuable insights and serves as a reference for universities and relevant authorities to enhance safety in university laboratories.

5G-V2X Based Traffic Safety Warning System through Mobile Sensor and Wireless Communication

This project designs a traffic safety early warning system based on 5G-V2X for the current situation of increasing traffic accidents in China, which concentrates on two modules of V2V (vehicle-to-vehicle), V2I (vehicle-to-road) for early warning system design, with OBU (vehicle communication unit) and RSU (roadside communication unit) based on 5G-V2X communication technology to establish vehicle-to-vehicle and vehicle-to-road interactive communication, and realize V2V collision warning and V2I traffic light emergency event warning at intersections through collision risk warning algorithm and intersection passage assistance algorithm, thus alerting drivers to avoid dangerous situations and reducing the incidence of traffic accidents.

Evolutionary Process of Promoting Construction Safety Education to Avoid Construction Safety Accidents in China.

Construction safety is related to the life and health of construction workers and has always been a hot issue of concern for government and construction units. The government can use “construction safety education” to reduce the probability of safety accidents in the construction process and avoid the loss of life and property of construction workers. To encourage construction units to provide safety education for construction workers before construction starts and promote construction workers to actively participate in safety education. In this paper, a tripartite evolutionary game model of government–construction units–construction workers is established, and the factors affecting each party’s behavior strategy are comprehensively analyzed. Firstly, evolutionary game theory is used to investigate the influence of different behavior strategies among government, construction units, and construction workers on the behavior strategies of the other two parties. Secondly, according to the events in different situations, the influence of critical factors on the evolution process of the model is analyzed. On this basis, combined with the construction experience and construction data of actual construction projects, the established model and preliminary conclusions are verified. Finally, a sensitivity analysis of all parameters is carried out. The results show that: (1) The government’s enhancement of reward and punishment is conducive to promoting the choice of "providing safety education" for construction orders and the choice of “actively participating in safety education” for construction workers, but the excessive reward will lead to the government’s unwillingness of participation; (2) The reasonable reward and punishment mechanism set by the government must meet the condition that the sum of rewards and punishments for all parties is more significant than their speculative gains, to ensure the construction safety under the evolutionary stability; (3) Increasing welfare subsidies for construction workers who choose to participate in safety education actively is an effective way to avoid unwilling participation of construction workers.

Research on Control Strategy and Central Control System of Intelligent Electric Vehicle

With the continuous improvement of world science and technology, vehicle technology has also been greatly developed. Cars bring convenience to people’s travel, and occupy an increasingly high proportion in social life. Automobile plays an important role in the continuous progress of contemporary society and the change of human travel conditions. At the same time, the increasing number of cars also brings many problems: energy consumption and environmental pollution are worsening, traffic accidents are increasing year by year. According to the who survey, the number of casualties caused by traffic accidents in China is gradually increasing. High traffic accidents have caused irreversible losses to social development, people’s lives and property. It has become the development goal to improve the vehicle active safety, control the vehicle to automatically identify the road, drive according to the planned route and reduce the frequency of traffic accidents. In the traditional driving environment, people occupy a dominant position. In the face of complex and changeable traffic environment and a large number of traffic information, it is easy to make mistakes in driving and cause serious traffic accidents. Therefore, it is very important to extricate the driver from the complex and changeable traffic environment and make driving safer. The intelligent vehicle collects the information about the road and the vehicle itself through the sensor, and sends it to the central controller which controls the transverse and longitudinal movement of the electric vehicle. The central controller sends out corresponding instructions to control the horizontal and longitudinal operation of the vehicle according to the control strategy, so as to realize the control of the driving behavior of the vehicle, so that the vehicle can drive safely on the desired track at the expected speed, It can avoid driver fatigue driving behavior and traffic accidents caused by driving technology. Various sensors in the intelligent vehicle can obtain more vehicle information at the same time, and control the vehicle through the controller processing.

Driving anger scale validation: Relationship of driving anger with the aberrant driving behaviour of truck drivers

Truck-related accidents in China have substantially increased. Truck driver safety issues have elicited considerable attention from transportation safety researchers. Driving anger is one of the most important factors that influence driving behaviour. However, little knowledge about the driving anger of truck drivers was available in the relevant literature. This study aimed to (1) provide empirical data about the driving anger of truck drivers, (2) examine the factor structure and psychometric properties of the driving anger scale (DAS) with a sample of truck drivers and (3) explore how the driving anger of truck drivers predicts their aberrant driving behaviour. The three-part survey data from 475 randomly selected truck drivers were collected in this study. The self-reported aberrant driving behaviour that was measured with the driving behaviour questionnaire was predicted by the drivers’ DAS ratings. One-factor structure and three-factor structure of the DAS were tested for Chinese truck drivers. Results indicated that the one-factor structure of the six-item DAS was more suitable for truck drivers than the three-factor structure. The factor structure of the DAS for Chinese truck drivers was consistent with the structure of the original version by Deffenbacher, Oetting, and Lynch (1994). The internal consistency, convergent validity and criterion-related validity of the six-item DAS were acceptable. Driving anger amongst truck drivers can be used to predict their aberrant driving behaviour. This study identified several practical implications to reduce the driving anger of truck drivers and consequently improve their driving behaviour.

Empirical Analysis on Influencing Factors of Traffic Casualties in China

In order to further explore the complex correlation between the influencing factors of road traffic accidents in China, this paper takes the road traffic safety-related data of 31 provinces from 2004 to 2018 as the sample data, selects five index data that may affect the occurrence of traffic accidents in various regions of the country, i.e. resident population, urban population, population density, GDP and number of car drivers, and uses Eviews software for stepwise regression analysis to establish a fixed effect model of the influencing factors of traffic accidents and analyze the macro and micro factors that affect the death toll of traffic accidents in China. The model shows that each index has a significant impact on the number of road traffic casualties. Urban population, population density and number of car drivers are positively correlated with the number of road traffic casualties. The resident population and GDP are negatively correlated with the number of road traffic casualties. According to the research conclusions, this paper puts forward some suggestions, such as optimizing the management technology of road traffic construction, strengthening the education system of traffic safety awareness of residents in the new urbanization, increasing the investment in traffic construction, and establishing an institution for differentiated training and management of drivers based on driving experience.