An Analysis of Hazardous Chemical Accidents in China between 2006 and 2017

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.


Introduction
With the rapid economic development in China, there are surging demands for hazardous chemicals for use in manufacturing and everyday life.Such chemicals pose considerable risks to safety and the environment, despite their benefits.Based on the accident statistics, 3974 hazardous chemical casualty accidents occurred in the 12-year period from 2006 to 2017, resulting in a total of 5203 deaths.Thus, on average, there is almost one casualty accident per day and more than one death each day.Since 2013, major accidents, which are defined as more than or equal to 3 deaths based on the Chinese classification standard "Production Safety Accident Investigation and Handling Rules" [1], and catastrophic accidents have occurred continuously.On 22 November 2013, an explosion caused by an oil pipeline leakage in Sinopec killed 62 and injured 136 people.On 1 March 2014, two tankers loaded with methanol crashed in a highway tunnel in Shanxi Province and the resulting explosion killed 40 people.On 12 August 2015, in Tianjin, catastrophic explosions occurred at midnight in warehouses where significant amounts of toxic chemicals were stored, killing 178 people, injuring 677 people, and resulting in a severe biochemical crisis [2] These hazardous chemical accidents (HCAs) Additionally, the safety management level of hazardous chemicals of each province is evaluated based on an inverted U-shaped curve that fits the relationship between the number of casualty accidents and petrochemical industry outputs, which has not been investigated previously.

Data Sources
The data used in this study are mainly from the State Work Accident Briefing (SWAB) system and the State Administration of Work Safety (SAWS) [32].SAWS is the most commonly used source for HCAs, as it reports all industrial accidents occurring in China.HCA reports published on the websites of National Registration Center for Chemicals [33], China Safety Production [34], Safety culture [35], Safety Management [36], and Guo Yin safety [37] are also gathered.More than 9000 cases (HCA cases do not include accidents occurring in Hong Kong, Macao and Taiwan; Tibet has no HCAs) were collected with detailed accident information, including time, location, enterprise information, casualty, and primary causes.These cases cover the majority of the HCAs and all of the casualty accidents that occurred from 2006 to 2017 and can therefore be used to analyze the characteristics and trends of casualty accidents in China.3974 casualty accidents (defined as more than or equal to 1 causality) are identified as our base data.To evaluate the safety management level of each province, the output of the petrochemical industry for each province needs to be considered.These data are collected from the National Bureau of Statistics of the People's Republic of China.

Methods
Based on the obtained data, hazardous chemical casualty accidents are analyzed from the perspective of characteristics and causes, probability and forecast, and safety management evaluation.The corresponding measures are proposed to improve safety management levels.Statistical analysis is applied to investigate the characteristics and causes of casualty accidents.The probability of casualty accidents is estimated using a Poisson regression.A time series analysis is used to predict the number of casualty accidents in 2018 and the Kuznets curve is adopted to assess the safety management of hazardous chemicals in 30 Chinese provinces.

The Estimation of the Probability of HCA Occurrence Using Poisson Regression
Typically, Count data modeling techniques are used to analyze accident frequency.The common and convenient assumption is that accidents are Poisson-distributed in accident count analysis [38].Nicholson and Wong [39] showed that the Poisson distribution is appropriate for the analysis of accidents at individual sites.Considering that HCA data are random, discrete, non-negative integers by nature, and that the occurrence probability of HCAs is very small in individual regions, a Poisson regression model can be used to estimate the probability of casualty accident occurrence in our study.
y denotes the number of casualty accidents that occurred.It is assumed that Y is independently distributed and that the Poisson distribution of Y, given by λ(λ > 0), is: The Poisson distribution can be extended to a regression model based on each value of λ.The number of casualty accidents occurring in i location in a certain time period, y i , conforms to the Poisson distribution with λ i : where X = (x 1i , x 2i , • • •, x ki ) T are covariates and β is the vector of estimated regression coefficients.β j represents the expected change in the log of the mean per unit change in the predictor x j .It can be computed using maximum likelihood estimation.

The Prediction of the Number of HCAs Using a Time Series Analysis
A prediction of the number of accidents is critical for the government and enterprises to prepare for accident prevention and to handle accidents effectively.Additionally, this prediction can increase awareness and improve the response capacity to reduce the impact of accidents.However, HCA forecast and modeling for planning and policy-making may entail a high degree of complexity, especially in the preliminary stage of concept formulation and model selection.This is because the factors that affect HCAs not only involve technological and equipment factors, but also human, environmental and management factors.Moreover, these factors dynamically evolve over time, and may lead to irregular and strongly nonlinear observations of HCAs.For example, many HCA phenomena entail strong behavioral and cognitive aspects that are difficult to isolate.To deal with the time dependencies and better reveal the underlying mechanism of HCA occurrence, time series models such as the autoregressive moving average (ARMA) model and autoregressive integrated moving average (ARIMA) model can be employed.These models are used to predict the number of HCAs in this study.
The ARMA model can be described as follows: where y t is the predicted number of casualty accidents at time t; φ and θ are regression parameters; a t is the random disturbance item at time t, and p and q are the number of orders.After implementing the d-th order difference, model ARMA (p, q) becomes ARIMA (p, d, q) model.Due to the seasonal characteristics of casualty accidents, the original time series data need to be adjusted to remove the seasonal factors first.In general, there are two main approaches to the seasonal adjustment, namely a filter-based approach and a model-based approach.To understand how to implement the seasonal adjustment, interested readers can consult Hillmer and Tiao [40], Findley and Hood [41], and Birrell et al. [42].In this paper, the model-based approach is used.The prediction of the number of casualty accidents in 2018 is based on the adjusted data using model ARIMA.The calculated number of casualty accidents must be re-adjusted to account for the seasonal characteristics.

The Assessment of the Safety Management Level of Hazardous Chemicals Using the Kuznets Curve
Normally, when the output of the petrochemical industry of a province is low, there are fewer economic activities related to hazardous chemicals.Therefore, the number of HCAs will also be low.With the expansion of the petrochemical industry, transitions with hazardous chemicals will increase.Thus, the number of HCAs will also rise.One way to reduce the number of HCAs is better safety management.However, investment in safety management is often delayed.When the petrochemical industry is well-developed, safety management will mature and the number of HCAs will fall.Therefore, the number of HCAs should have an inverted U-shaped relationship with the output of the petrochemical industry.We call this the safety Kuznets curve and use the quadratic function regression to fit the relationship between y and x, as shown in Equation ( 4): where y represents the number of casualty accidents; x represents the petrochemical industry output; a, b and c are the estimated parameters, and ε is the random error.
The fitting of the relationship between the number of casualty accidents and the output of the petrochemical industry is used to evaluate the safety management level of hazardous chemicals of 30 Chinese provinces.At the same production level, fewer accidents suggest a higher safety management level.The statistical significance of the fitted curve represents the average level of safety management of hazardous chemicals in China.

Trend of Number of Casualty and Fatality Accidents
The trend of variation in the number of accidents with casualties and the number of accidents with fatalities can be divided into three phases (Figure 1).The first phase was from 2006 to 2008, and showed a rapid decreasing trend.The number of casualty accidents decreased from 293 in 2006 to 147 in 2008, a 49.83% reduction.The second phase started from 2008 to 2012, with fluctuations in the number of casualty accidents and the number of fatality accidents.For example, in 2008, 2010, and 2012, the number of casualty and fatality accidents was low, while it was high in 2009 and 2011.The number of casualty accidents reached its lowest level in 2010 and 2012.The first reason for this milestone was the Beijing Olympic Games in 2008 and the Shanghai World Expo in 2010, during which time the government allocated significant resources to improving the management of hazardous chemicals.A series of regulatory policies were implemented, and the level of supervision was enhanced.Second, the first revision of the "Hazardous chemicals safety management regulations" was implemented on 1 December 2011.Hazardous chemicals were more strictly regulated in 2012, leading to the decrease in the number of casualty and fatality accidents that year.This suggests that HCAs can be reduced by implementing stricter standards and strengthened management.The third phase was from 2012 to 2017, and exhibited a rapidly increasing trend.The number of casualty accidents increased from 137 in 2012 to 723 in 2016, an 81.05% increase.This means that when the Olympic Games and the World Expo were completed, fewer efforts were devoted to the safety management of hazardous chemicals and the number of casualty and fatality accidents rebounded.The fluctuation of the number of casualty and fatality accidents indicates that the supervision of hazardous chemicals must be a long-term and continuous process.
Sustainability 2018, 10, x FOR PEER REVIEW 5 of 18 30 Chinese provinces.At the same production level, fewer accidents suggest a higher safety management level.The statistical significance of the fitted curve represents the average level of safety management of hazardous chemicals in China.

Trend of Number of Casualty and Fatality Accidents
The trend of variation in the number of accidents with casualties and the number of accidents with fatalities can be divided into three phases (Figure 1).The first phase was from 2006 to 2008, and showed a rapid decreasing trend.The number of casualty accidents decreased from 293 in 2006 to 147 in 2008, a 49.83% reduction.The second phase started from 2008 to 2012, with fluctuations in the number of casualty accidents and the number of fatality accidents.For example, in 2008, 2010, and 2012, the number of casualty and fatality accidents was low, while it was high in 2009 and 2011.The number of casualty accidents reached its lowest level in 2010 and 2012.The first reason for this milestone was the Beijing Olympic Games in 2008 and the Shanghai World Expo in 2010, during which time the government allocated significant resources to improving the management of hazardous chemicals.A series of regulatory policies were implemented, and the level of supervision was enhanced.Second, the first revision of the "Hazardous chemicals safety management regulations" was implemented on 1 December 2011.Hazardous chemicals were more strictly regulated in 2012, leading to the decrease in the number of casualty and fatality accidents that year.This suggests that HCAs can be reduced by implementing stricter standards and strengthened management.The third phase was from 2012 to 2017, and exhibited a rapidly increasing trend.The number of casualty accidents increased from 137 in 2012 to 723 in 2016, an 81.05% increase.This means that when the Olympic Games and the World Expo were completed, fewer efforts were devoted to the safety management of hazardous chemicals and the number of casualty and fatality accidents rebounded.The fluctuation of the number of casualty and fatality accidents indicates that the supervision of hazardous chemicals must be a long-term and continuous process.
The number of fatalities peaked in 2015, reaching 699 deaths (Figure 2).The reason for this is that several major HCAs occurred in 2015.One example is the Tianjin port warehouse explosion, in which 178 people were killed and 677 people were injured.China's safety management of hazardous chemicals requires further improvement.The number of fatalities peaked in 2015, reaching 699 deaths (Figure 2).The reason for this is that several major HCAs occurred in 2015.One example is the Tianjin port warehouse explosion, in which 178 people were killed and 677 people were injured.China's safety management of hazardous chemicals requires further improvement.

The Distribution of Casualty Accidents over Time
The average monthly distribution of the 3974 casualty accidents is summarized in Figure 3.The accidents show seasonal variance.There are more accidents in months from April to August than in the other months in the year.From May to August, more than 350 casualty accidents occur each month.This is mainly related to the weather in China.In most parts of China, spring and summer are the seasons with the most rain and the highest temperatures, while autumn and winter are the seasons with clear days and low temperature.On warm and humid days, the likelihood of casualty accidents increases.Weather, as an external factor, significantly affects the number of incidents.Of the winter months, December and January have relatively more accidents.This is because prior to the Spring Festival, there is usually a large demand for hazardous chemicals, such as fire crackers.Moreover, road traffic is often busy during this time period.Additionally, as the Spring Festival holidays approach, safety management is relaxed and workers' safety consciousness is quite low.All of these factors lead to an increase in the number of accidents, even on cold winter days.The distribution of casualty accidents within an average day is shown in Figure 4.This fits well with working hours.The number of accidents is low before 6:00 am and after 5:00 pm, which represents the fact that there are fewer HCAs before and after working hours.The number of casualty accidents gradually increases from 6:00 am and reaches a peak at 10:00 am.Then it starts to decrease as lunch time approaches.During the lunch break, normally between 12:00 pm and 1:00 pm, the number of accidents is relatively low, but it peaks again between 2:00 pm and 4:00 pm.Most

The Distribution of Casualty Accidents over Time
The average monthly distribution of the 3974 casualty accidents is summarized in Figure 3.The accidents show seasonal variance.There are more accidents in months from April to August than in the other months in the year.From May to August, more than 350 casualty accidents occur each month.This is mainly related to the weather in China.In most parts of China, spring and summer are the seasons with the most rain and the highest temperatures, while autumn and winter are the seasons with clear days and low temperature.On warm and humid days, the likelihood of casualty accidents increases.Weather, as an external factor, significantly affects the number of incidents.Of the winter months, December and January have relatively more accidents.This is because prior to the Spring Festival, there is usually a large demand for hazardous chemicals, such as fire crackers.Moreover, road traffic is often busy during this time period.Additionally, as the Spring Festival holidays approach, safety management is relaxed and workers' safety consciousness is quite low.All of these factors lead to an increase in the number of accidents, even on cold winter days.

The Distribution of Casualty Accidents over Time
The average monthly distribution of the 3974 casualty accidents is summarized in Figure 3.The accidents show seasonal variance.There are more accidents in months from April to August than in the other months in the year.From May to August, more than 350 casualty accidents occur each month.This is mainly related to the weather in China.In most parts of China, spring and summer are the seasons with the most rain and the highest temperatures, while autumn and winter are the seasons with clear days and low temperature.On warm and humid days, the likelihood of casualty accidents increases.Weather, as an external factor, significantly affects the number of incidents.Of the winter months, December and January have relatively more accidents.This is because prior to the Spring Festival, there is usually a large demand for hazardous chemicals, such as fire crackers.Moreover, road traffic is often busy during this time period.Additionally, as the Spring Festival holidays approach, safety management is relaxed and workers' safety consciousness is quite low.All of these factors lead to an increase in the number of accidents, even on cold winter days.The distribution of casualty accidents within an average day is shown in Figure 4.This fits well with working hours.The number of accidents is low before 6:00 am and after 5:00 pm, which represents the fact that there are fewer HCAs before and after working hours.The number of casualty accidents gradually increases from 6:00 am and reaches a peak at 10:00 am.Then it starts to decrease as lunch time approaches.During the lunch break, normally between 12:00 pm and 1:00 pm, the number of accidents is relatively low, but it peaks again between 2:00 pm and 4:00 pm.Most The distribution of casualty accidents within an average day is shown in Figure 4.This fits well with working hours.The number of accidents is low before 6:00 am and after 5:00 pm, which represents the fact that there are fewer HCAs before and after working hours.The number of casualty accidents gradually increases from 6:00 am and reaches a peak at 10:00 am.Then it starts to decrease as lunch time approaches.During the lunch break, normally between 12:00 pm and 1:00 pm, the number of accidents is relatively low, but it peaks again between 2:00 pm and 4:00 pm.Most accidents happen during working hours.The accidents before and after working hours are likely related to storage, utilization, and sometimes transportation of hazardous chemicals.

The Distribution of Casualty Accidents over the Lifecycle of Hazardous Chemicals
The majority of casualty accidents occur during utilization, transportation, production, and storage (Table 1).Regarding the frequency of incidents, utilization ranks first, accounting for 44.6% of the total number of casualty accidents, since the utilization of liquefied gases and firecrackers is the most prone to generate accidents.Transportation and production rank second and third respectively, followed by storage.79.92% of fatality accidents occur during utilization, production, and transportation.Regarding the severity of incidents, the production stage causes the highest number of fatalities, almost one-third of the total fatalities.The utilization stage ranks second, resulting in 25.45% of fatalities.The transportation and storage stages rank third and fourth, respectively.However, the utilization stage leads to more injured people.Major accidents occur primarily during production, utilization, transportation and storage, which are the most critical stages of hazardous chemicals management.Accidents with fewer than 3 deaths occur primarily during the sales and disposal stages.Much emphasis has been on the production, transportation and storage of hazardous chemicals.However, our analysis shows that the utilization of hazardous chemicals is actually a stage with high risk.Greater effort should be allocated to the safety management of hazardous chemicals during the utilization stage.

The Distribution of Casualty Accidents over the Lifecycle of Hazardous Chemicals
The majority of casualty accidents occur during utilization, transportation, production, and storage (Table 1).Regarding the frequency of incidents, utilization ranks first, accounting for 44.6% of the total number of casualty accidents, since the utilization of liquefied gases and firecrackers is the most prone to generate accidents.Transportation and production rank second and third respectively, followed by storage.79.92% of fatality accidents occur during utilization, production, and transportation.Regarding the severity of incidents, the production stage causes the highest number of fatalities, almost one-third of the total fatalities.The utilization stage ranks second, resulting in 25.45% of fatalities.The transportation and storage stages rank third and fourth, respectively.However, the utilization stage leads to more injured people.Major accidents occur primarily during production, utilization, transportation and storage, which are the most critical stages of hazardous chemicals management.Accidents with fewer than 3 deaths occur primarily during the sales and disposal stages.Much emphasis has been on the production, transportation and storage of hazardous chemicals.However, our analysis shows that the utilization of hazardous chemicals is actually a stage with high risk.Greater effort should be allocated to the safety management of hazardous chemicals during the utilization stage.The trends of casualty accidents occurring during different lifecycle stages are not the same (Figure 5).The number of casualty accidents occurring during sales displays a downward trend while the number of casualty accidents occurring during production and storage fluctuates.Moreover, the number of casualty accidents during utilization, transportation, and disposal increases.This is primarily because safety management efforts are devoted to the production, sales, and storage of hazardous materials but not to the utilization and disposal of hazardous materials, as we mentioned above.Therefore, safety management should focus more on the management of utilization, transportation, and disposal of hazardous chemicals.Meanwhile, one integrated system for tracking hazardous chemicals from production to disposal is needed to ensure the seamless control of hazardous chemicals.Moreover, the number of casualty accidents during utilization, transportation, and disposal increases.This is primarily because safety management efforts are devoted to the production, sales, and storage of hazardous materials but not to the utilization and disposal of hazardous materials, as we mentioned above.Therefore, safety management should focus more on the management of utilization, transportation, and disposal of hazardous chemicals.Meanwhile, one integrated system for tracking hazardous chemicals from production to disposal is needed to ensure the seamless control of hazardous chemicals.

The Distribution of Casualty Accidents by Chemical Types
Based on the national standard "Hazardous Chemicals Classification and Code" (GB 6944-2005), casualty accidents can be classified by the chemical types shown in Table 2. Currently, the primary hazardous chemicals involved in casualty accidents are compressed or liquefied gases and flammable liquid.Casualty accidents involving compressed or liquefied gases represent 41.09% of all accidents, more than one third of all accidents.

The Distribution of Casualty Accidents by Chemical Types
Based on the national standard "Hazardous Chemicals Classification and Code" (GB 6944-2005), casualty accidents can be classified by the chemical types shown in Table 2. Currently, the primary hazardous chemicals involved in casualty accidents are compressed or liquefied gases and flammable liquid.Casualty accidents involving compressed or liquefied gases represent 41.09% of all accidents, more than one third of all accidents.

The Distribution of Casualty Accidents by Accident Types
Based on the classification of accident types, the distribution of casualty accidents is shown in Table 3.The major types of casualty accidents are leakage and explosion, accounting for 59.51% of all casualty accidents.Fire ranks third, accounting for 23.98% of the total casualty accidents.If these three types of accidents could be reduced by 50%, then the total number of casualty accidents would fall by 42%.Measures that prevent explosion, leakage, and fire are especially effective for reducing the number of accidents.Note that some accidents may be counted repeatedly in Table 3, since an accident may involve several accident types.

Causes of Accidents
Based on the "Production Safety Accident Investigation and Handling Rules" issued by the SAWS [1], the causes of HCAs can be categorized into direct causes and indirect causes, as shown in Tables 4 and 5.We further classified the direct causes of HCAs into "Unsafe state of machinery, chemicals or the environment", which represent causes related to objects, and "Unsafe behavior of personnel", which are causes related to humans.Table 4 shows that both unsafe objects and unsafe human behavior are critical causes of HCAs."Operation violation" ranks highest in direct causes, followed by "No or defective devices for warning and safety protection" and "Improper maintenance", respectively.In indirect causes, "Insufficient production safety training" is the major reason for casualty accidents."No or inadequate preventive measures" and "No or inadequate safety operation procedures" are also important causes.More safety training in firms is needed to reduce the number of casualty accidents.

The Probability of Casualty Accidents
Based on the distribution of casualty accidents from 2006 to 2017, as shown in Table 6, we used the Poisson regression model to estimate the probability of the number of casualty accidents in China.Table 7 shows the probability of casualty accidents and the cumulative probability distribution.As shown in Table 7, the probability of there being fewer than 100 cases per year is small, at only 15.74%; the probability of there being 200 to 600 cases per year is 59.10%; and the probability of there being more than 700 cases per year is again very small, at only 2.01%.It is highly likely that 200 to 600 casualty accidents will occur each year in China.

The Forecast of Casualty Accidents
The forecast for the number of casualty accidents in 2018 is based on the number of casualty accidents from January 2006 to December 2017 using a time series model.Considering that casualty accidents have seasonal characteristics, the original casualty accidents data are adjusted, as shown in Figure 6.The seasonally adjusted data are smoother and have higher regularity than the original data.The seasonal adjustment factors (SAF) are shown in Table 8.

The Forecast of Casualty Accidents
The forecast for the number of casualty accidents in 2018 is based on the number of casualty accidents from January 2006 to December 2017 using a time series model.Considering that casualty accidents have seasonal characteristics, the original casualty accidents data are adjusted, as shown in Figure 6.The seasonally adjusted data are smoother and have higher regularity than the original data.The seasonal adjustment factors (SAF) are shown in Table 8.The Augmented Dickey-Fuller (ADF) test is applied to validate the stability of the adjusted series, producing a result of -1.679273, meaning that the seasonally adjusted data have a unit root.Then, by implementing the first-order difference, the value of ADF is equal to -11.95606, which is less than the critical values of the 1%, 5%, and 10% significance levels, demonstrating that the seasonally adjusted data have no unit root and that the seasonally adjusted data are a stable series with no stochastic trend after implementing the first-order difference.
Then, the models ARIMA (1, 1, 0), ARIMA (0, 1, 1), ARIMA (2, 1, 0), ARIMA (0, 1, 2), and ARIMA (1, 1, 1) are tested to fit the seasonally adjusted data implementing the first-order difference.Based on the proximity of the Durbin-Watson (DW) statistic to the value of 2, the lower Akaike Information Criterion (AIC) and Schwarz Criterion (SC), and the higher Adjusted R-squared, ARIMA (2, 1, 0) is chosen as the best-fitted model (Table 9).To further test the validity of the model ARIMA (2, 1, 0), the Breusch-Godfrey Serial Correlation LM Test is used to test the residuals.The result shows that the model ARIMA (2, 1, 0) is valid and can be chosen to predict the number of casualty accidents.According to the ARIMA (2, 1, 0) model, we obtained the fitting Equation ( 5): where {∆y t = y t − y t−1 } represents the first-order difference of the casualty accident time series.
Applying Equation ( 5) to forecast the number of casualty accidents in 2018 and applying the seasonal adjustment to the data, we forecast the number of casualty accidents as shown in Table 10.

Analysis of the Safety Management of Hazardous Chemicals
Figure 7 shows the total number of casualty accidents and the total output of the petrochemical industry for each province in China from 2006 to 2016.Obviously, Shandong, Jiangsu, Guangdong, Zhejiang, Liaoning, Henan, and Shanghai have a stronger petrochemical industry than other provinces.Meanwhile, there is a significant imbalance in the number of casualty accidents in different provinces and regions.For example, casualty accidents occurred primarily in the southeastern coastal provinces, where economic development is more rapid.Jiangsu, Guangdong, Zhejiang, and Shandong are the top four provinces for casualty accidents.The number of casualty accidents in these provinces exceeds 240.The provinces located in the northern and western parts of the country have fewer casualty accidents, and their economic development is relatively slow.Economic activities, especially those related to hazardous chemicals, such as the production, storage, transportation, sales, utilization, and disposal of hazardous chemicals, have the potential to generate HCAs.Therefore, the number of HCAs or casualty accidents alone cannot represent the safety management level.The level of economic development should also be considered when the hazardous chemical safety management level is evaluated.To further analyze the hazardous chemical safety management level, we calculated the average frequency of casualty accidents for each province and compared it to the average petrochemical industry output of that province based on the data from 2006 to 2016, as shown in Figure 8. Equation ( 4) is used to fit the number of casualty accidents and the output of the petrochemical industry, To further analyze the hazardous chemical safety management level, we calculated the average frequency of casualty accidents for each province and compared it to the average petrochemical industry output of that province based on the data from 2006 to 2016, as shown in Figure 8. Equation ( 4) is used to fit the number of casualty accidents and the output of the petrochemical industry, resulting in the equation: The correlation coefficient is 0.8345, indicating that the inverted U-shaped Kuznets curve significantly represents the relationship between the number of casualty accidents and the petrochemical industry output.Moreover, p value is less than 0.01, implying that the regression Equation ( 6) is significant.
To rank the safety management level of 30 provinces, Equation ( 7) is used to calculate the distance difference between each province and the safety Kuznets curve (Figure 8), where s i , y i , and x i represent the distance difference, number of casualty accidents, and petrochemical industry output of province i, respectively.Then, the safety management level of each province is measured by the distance difference.The larger the value of s i is, the higher the ranking and safety management level.Negative and positive values of s i indicate that the province i is above and below the Kuznets curve, respectively.Naturally, the case of s i = 0 represents that the province i is on the Kuznets curve.
Sustainability 2018, 10, x FOR PEER REVIEW 13 of 18 2 0.0011 0.3457 2.5545 In Figure 8, the 14 provinces located above the curve, including Jiangsu, Zhejiang, Guangdong, Hubei, Shaanxi, Hunan, Sichuan, Chongqing, Beijing, Anhui, Guangxi, Yunnan, Guizhou, and Gansu, have lower levels of hazardous chemical management because they have relatively more casualty accidents compared with their petrochemical industry outputs (Figures 7 and 8).The higher the province is above the curve, the lower its safety management level, indicating the need for more safety measures to reduce the frequency of accidents.The 16 provinces located below the curve, including Shanghai, Shandong, Liaoning, Hebei, Tianjin, Henan, Shanxi, Jiangxi, Jilin, Fujian, Heilongjiang, Hainan, Ninxia, Neimenggu, Xinjiang, and Qinghai, are superior in safety management of hazardous chemicals (Figures 7 and 8).The lower the province is below the curve, the higher its level of safety management.For example, Shanghai and Shandong have higher safety management levels, as they have taken effective measures to reduce the risk of hazardous chemicals.In their practices, large hazardous chemical enterprises are required to be located in industrial parks, where centralized management is implemented.The ranking of the 30 provinces with respect to the safety management of hazardous chemicals is given in Table 11.Tianjin, Liaoning, Shanghai, Hebei, and Shandong are the top five provinces for safety management.In particular, although a warehouse explosion occurred in Tianjin port in 2015, Tianjin still ranks first because it has low casualty accidents compared with its petrochemical industry outputs during 2006-2016.However, Hubei, Hunan, Guangxi, Jiangsu, and Shaanxi have lower safety management levels, and Shaanxi ranks last.In Figure 8, the 14 provinces located above the curve, including Jiangsu, Zhejiang, Guangdong, Hubei, Shaanxi, Hunan, Sichuan, Chongqing, Beijing, Anhui, Guangxi, Yunnan, Guizhou, and Gansu, have lower levels of hazardous chemical management because they have relatively more casualty accidents compared with their petrochemical industry outputs (Figures 7 and 8).The higher the province is above the curve, the lower its safety management level, indicating the need for more safety measures to reduce the frequency of accidents.The 16 provinces located below the curve, including Shanghai, Shandong, Liaoning, Hebei, Tianjin, Henan, Shanxi, Jiangxi, Jilin, Fujian, Heilongjiang, Hainan, Ninxia, Neimenggu, Xinjiang, and Qinghai, are superior in safety management of hazardous chemicals (Figures 7 and 8).The lower the province is below the curve, the higher its level of safety management.For example, Shanghai and Shandong have higher safety management levels, as they have taken effective measures to reduce the risk of hazardous chemicals.In their practices, large hazardous chemical enterprises are required to be located in industrial parks, where centralized management is implemented.The ranking of the 30 provinces with respect to the safety management of hazardous chemicals is given in Table 11.Tianjin, Liaoning, Shanghai, Hebei, and Shandong are the top five provinces for safety management.In particular, although a warehouse explosion occurred in Tianjin port in 2015, Tianjin still ranks first because it has low casualty accidents compared with its petrochemical industry outputs during 2006-2016.However, Hubei, Hunan, Guangxi, Jiangsu, and Shaanxi have lower safety management levels, and Shaanxi ranks last.

Measures to Improve the Safety Management of Hazardous Chemicals in China
The rapid development of the petrochemical industry in China has brought with it greater challenges from HCAs.Currently, China lacks systematic safety management of hazardous chemicals.A framework for continuous improvement of safety management is proposed in Figure 9. HCA analysis reflects when and where HCAs frequently occur, indicating where greater efforts in safety management are necessary.The probability and forecast of HCAs show the potential for accidents to occur in the future, helping managers to prepare for accident prevention and to increase awareness and improve the response capacity.The safety management evaluation shows the safety management level of each province, identifying provinces that need to improve safety management.When safety management measures are implemented, the characteristics of HCAs can be changed.Therefore, further data collection, analysis, forecast, and evaluation should be conducted to identify new safety management measures.With this continuous safety management improvement process, we can expect to have fewer HCAs, less severe HCAs, and better environment protection and sustainable development.

Measures to Improve the Safety Management of Hazardous Chemicals in China
The rapid development of the petrochemical industry in China has brought with it greater challenges from HCAs.Currently, China lacks systematic safety management of hazardous chemicals.A framework for continuous improvement of safety management is proposed in Figure 9. HCA analysis reflects when and where HCAs frequently occur, indicating where greater efforts in safety management are necessary.The probability and forecast of HCAs show the potential for accidents to occur in the future, helping managers to prepare for accident prevention and to increase awareness and improve the response capacity.The safety management evaluation shows the safety management level of each province, identifying provinces that need to improve safety management.When safety management measures are implemented, the characteristics of HCAs can be changed.Therefore, further data collection, analysis, forecast, and evaluation should be conducted to identify new safety management measures.With this continuous safety management improvement process, we can expect to have fewer HCAs, less severe HCAs, and better environment protection and sustainable development.

Safety Management Measures Based on HCA Analysis
1. Based on the analysis of time distribution of casualty accidents, we argue that safety management efforts should be devoted to spring and summer and 9:00-10:00 am and 2:00-4:00 pm during the day.2. The majority of casualty accidents happen during transportation and utilization.Advanced technologies, such as global position system (GPS), geographic information system (GIS),  Based on the analysis of time distribution of casualty accidents, we argue that safety management efforts should be devoted to spring and summer and 9:00-10:00 am and 2:00-4:00 pm during the day.

2.
The majority of casualty accidents happen during transportation and utilization.Advanced technologies, such as global position system (GPS), geographic information system (GIS), electronic toll charge (ETC), and mobile networks can be used to establish an inter-provincial and inter-city monitoring system, resulting in seamless supervision.Moreover, stronger regulation and standard procedures for the utilization of hazardous chemicals are needed.Developing effective training programs for the utilization of hazardous chemicals is also a necessity.The production stage causes almost one-third of the total fatalities, since it involves large amounts of raw chemicals, auxiliary chemicals, and semi-finished and finished products, all of which are very dangerous.Firms that produce hazardous materials should be relocated into a special chemical production zone, in which the management of chemical production is centralized.This relocation can significantly improve the efficiency of management.Storage of hazardous chemicals also results in high casualties.Thus, storage companies must install monitoring systems that provide real-time observations of the environmental factors and the storage facilities.The rapid notification of an HCA occurrence would allow it to be addressed in a timely manner.

3.
Compressed or liquefied gases are the most commonly involved chemicals in HCAs.Specific rules or working processes for the production, transportation, and storage of such chemicals need to be implemented to reduce the possibility of related HCAs.

4.
The cause analysis shows that firms should implement devices for warning and safety protection.
For those who have these devices in place, it is important to check whether these devices work properly.The human aspect is also important.Firms should raise staff risk awareness to prevent operational violations and improper maintenance.More training in the safety management of hazardous chemicals is needed.

Safety Management Measures Based on Probability and Forecast of HCAs
(1) Based on the probability analysis of casualty accidents, it is highly likely that 200 to 600 casualty accidents will occur each year in China.Thus, to reduce the occurrence of accidents, preventive measures should be taken.Moreover, building a resilient system is necessary for responding to unanticipated disturbances and resuming normal operations quickly [43,44].(2) The forecast of casualty accidents can provide the basis for emergency response preparation.
Considering that hazardous chemicals are usually toxic, flammable, and explosive, and that HCAs may easily lead to secondary disasters such as explosions and chemical pollution, the design of an emergency response system must consider and strengthen the linkage mechanism of agencies including fire departments, safety supervisors, environmental protection, and health, to support a robust emergency response capability.

Safety Management Measures Based on Safety Management Evaluation
(1) Jiangsu, Zhejiang, Guangdong, Hubei and 10 other provinces are identified as having lower safety management levels.These 14 provinces should be required to take specific actions for the safety management of hazardous chemicals.Within these 14 provinces, Jiangsu, Guangdong, Zhejiang, and Shandong are the top four for the number of casualty accidents in the last 11 years.
Stricter supervision and more frequent checks for the safety management of these four provinces are necessary.(2) Shandong, Shanghai and some other provinces do better in safety management.Some of their best practices should be disseminated to other provinces.Meetings, conferences, and on-site investigation should be held periodically to disseminate effective measures, technologies, and procedures.(3) A seamless supervision system for hazardous chemicals should be established and collaborations among the provinces in safety management need to be enhanced.HCAs normally happen in the production, transportation, storage, and utilization stages in different provinces.Currently, each province manages its own hazardous chemicals without much information exchange with other provinces.As a result, no province has a clear picture of its own hazardous chemical situation, which is a key difficulty for safety management.If a seamless supervision system is established, and data of hazardous chemicals are all input into the system and shared, it would be possible to supervise the whole lifecycle of hazardous chemicals, from production to utilization and disposal, and to make each province aware of its own situation.

Conclusions
This study comprehensively analyzes the characteristics and causes of 3974 hazardous chemical casualty accidents that occurred between 2006 and 2017 in China.The Poisson regression model is applied to estimate the probability of casualty accidents, and the time series model is developed to forecast the number of casualty accidents.Evaluation of the safety management level of 30 provinces is conducted using the inverted U-shaped curve similar to the environmental Kuznets curve.Finally, based on our analysis and evaluation, we propose measures to improve the management of hazardous chemicals.This study contributes to the body of knowledge on safety management of hazardous chemicals and provides approaches to estimate and forecast HCAs.In particular, using an inverted U-shaped Kuznets curve that fits the relationship between the number of casualty accidents and petrochemical industry outputs is a new attempt to evaluate the safety management of hazardous chemicals.
The statistical analysis shows that the number of casualty accidents declined from 2006 to 2008, fluctuated from 2008 to 2012, and increased rapidly from 2012 to 2017.April to August is the peak season for accidents each year.Each day, the number of casualty accidents peaks at 10 am and 3 pm.Casualty accidents primarily occurred during utilization, transportation, production, and storage.Compressed gases, liquefied gases, and flammable liquids are the primary types of chemicals causing accidents.Leakage and explosion are the primary types of accidents.Operation violation and insufficient production safety training are the major reasons causing accidents.The probability of the number of casualty accidents between 200 and 600 per year is 59.10% in China.More casualty accidents occur in eastern China, with its high economic development level.Sixteen provinces, including Shanghai, Shandong, and Tianjin, are identified as having higher safety management, while others, including Jiangsu, Zhejiang, Guangdong, and Hubei, have lower levels of hazardous chemical management.
There are several possible directions for future work.First, in this study, only the traditional Poisson model is employed to analyze accident frequency.However, when the data show over-dispersion or under-dispersion, other models, such as the negative binomial model, the Conway-Maxwell-Poisson model, the Bernoulli model, and the hurdle Poisson model may be better for fitting HCA frequency.Second, only the quadratic function regression model is applied to fit the relationship between the number of casualty accidents and petrochemical industry outputs.Future research can investigate and compare various alternate models.Third, the ranking of 30 provinces for safety management of hazardous chemicals is determined based on the evaluation of the inverted U-shaped curve.However, in practice, some provinces may have similar safety management levels.It would be more reasonable to consider a clustering analysis.Finally, since the safety management of hazardous chemicals is a complex socio-technical problem, it needs to be further studied from a resilience engineering perspective in future work.

Figure 1 .
Figure 1.Number of casualty and fatality accidents in China from 2006 to 2017.Figure 1. Number of casualty and fatality accidents in China from 2006 to 2017.

Figure 1 .
Figure 1.Number of casualty and fatality accidents in China from 2006 to 2017.Figure 1. Number of casualty and fatality accidents in China from 2006 to 2017.

Figure 2 .
Figure 2. Number of casualties and fatalities in China from 2006 to 2017.

Figure 3 .
Figure 3. Monthly distribution of casualty accidents in China from 2006 to 2017.

Figure 2 .
Figure 2. Number of casualties and fatalities in China from 2006 to 2017.

Figure 2 .
Figure 2. Number of casualties and fatalities in China from 2006 to 2017.

Figure 3 .
Figure 3. Monthly distribution of casualty accidents in China from 2006 to 2017.

Figure 3 .
Figure 3. Monthly distribution of casualty accidents in China from 2006 to 2017.

Figure 4 .
Figure 4. Hourly distribution of casualty accidents in China from 2006 to May 2018.

Figure 4 .
Figure 4. Hourly distribution of casualty accidents in China from 2006 to May 2018.

Figure 5 .
Figure 5. Number of casualty accidents occurring during different stages of the lifecycle.

Figure 5 .
Figure 5. Number of casualty accidents occurring during different stages of the lifecycle.

Figure 6 .
Figure 6.Seasonally adjusted data and original time series data for casualty accidents.Figure 6. Seasonally adjusted data and original time series data for casualty accidents.

Figure 6 .
Figure 6.Seasonally adjusted data and original time series data for casualty accidents.Figure 6. Seasonally adjusted data and original time series data for casualty accidents.
Sustainability 2018, 10, x FOR PEER REVIEW 12 of 18 transportation, sales, utilization, and disposal of hazardous chemicals, have the potential to generate HCAs.Therefore, the number of HCAs or casualty accidents alone cannot represent the safety management level.The level of economic development should also be considered when the hazardous chemical safety management level is evaluated.

Figure 8 .
Figure 8. Evaluation of safety management for hazardous chemicals in 30 provinces based on safety Kuznets curve.

Figure 8 .
Figure 8. Evaluation of safety management for hazardous chemicals in 30 provinces based on safety Kuznets curve.

Figure 9 .
Figure 9.A framework for continuous improvement in safety management.

Table 1 .
Number of casualties and fatalities during the life cycle.
casualty accidents occurring during different lifecycle stages are not the same

Table 1 .
Number of casualties and fatalities during the life cycle.

Table 2 .
Distribution of casualty accidents by chemical types in China from January 2006 to May 2018.

Table 2 .
Distribution of casualty accidents by chemical types in China from January 2006 to May 2018.

Table 3 .
Distribution of casualty accidents by accident types in China from January 2006 to May 2018.

Table 4 .
Direct causes of HCAs in China from January 2006 to May 2018.

Table 5 .
Indirect causes of HCAs in China from January 2006 to May 2018.

Table 6 .
Distribution of casualty accidents in China from 2006 to 2017.

Table 7 .
Probability of casualty accidents in China.

Table 9 .
Results of parameter estimation for ARIMA models.

Table 10 .
Prediction of the number of casualty accidents in 2018.

Table 11 .
Ranking of 30 provinces for safety management of hazardous chemicals.

Table 11 .
Ranking of 30 provinces for safety management of hazardous chemicals.