# Causality Analysis and Risk Assessment of Haze Disaster in Beijing
## 2 Materials and Methods
### Causal Analysis of Influencing Factors  
The causal correlation at the macro-level is the key to analyzing the urban haze system. Based on the nonlinear with-time-lags Granger causality analysis [45; 46] for Beijing haze pollution in our past studies, the causal relationship between PM2.5 and different influencing factors was tested. The inputs included PM2.5, coal consumption, crude oil consumption, unban greening rate and pollution emissions of Beijing, Tianjin and Hebei. The outputs were \(p\)-test values between PM2.5 and other inputs. At the significance level of 10%, Granger causality exists when \(p\)-test values are less than 0.1. The historical data were obtained from China Yearbook Full-text Database [47]. The pollution emission data of Beijing, Tianjin and Hebei is shown in Figure 3. The variation trends of SO2 (Figure 3a) and dust emissions (Figure 3b) in Beijing were basically the same. However, the change trend of SO2 emissions in Hebei and Tianjin (Figure 3c) was obviously different from Beijing (Figure 3a), which indicates the importance of cross-regional analysis of pollutant emissions. According to the result of Granger causality analysis, Beijing's crude oil consumption system, coal consumption system, unit GDP energy consumption system, urban greening system and Tianjin and Hebei's sulfur dioxide emission system could be established.  
Figure 3: \(Cont\).  
Crude oil consumption is an important source of haze pollution in Beijing and is mainly reflected in two aspects. One is the fuel consumption of urban motor vehicles, and the other is the consumption of crude oil in oil refining, petrochemical and other industries. In addition, the use of new energy vehicles and the implementation of environmental protection policies can reduce the oil consumption effectively. The corresponding causality diagram is shown in Figure 4.  
Beijing's coal consumption mainly includes residents' coal consumption and thermal power generation consumption. In recent years, the proposal of environmental policies and the change in energy structure have significantly reduced coal consumption. The causality diagram between Beijing's coal consumption and Beijing's urban haze is shown in Figure 5.  
Energy consumption per unit of GDP is the ratio of total primary energy supply to gross domestic product (GDP), which is an indicator of energy utilization efficiency. With the development of science and technology, the energy utilization rate has significantly improved, which can reduce the energy consumption effectively. The causality diagram between them is shown in Figure 6.  
Figure 4: Causality diagram of Beijing crude oil consumption system.  
Figure 3: SO\({}_{2}\) (**a**) and dust emission data (**b**) of Beijing and SO\({}_{2}\) emission data of Tianjin and Hebei (**c**).  
Figure 5: Causality diagram of Beijing coal consumption system.  
Figure 6: Causality diagram of Beijing energy consumption system per unit GDP.  
Figure 7: Causality diagram of Beijing urban greening system.  
Each subsystem in Figures 4-8 is combined through its logical relationship, and the Beijing urban haze system is shown in Figure 9. Figure 9 shows that the direct reason for the change in PM2.5 is the emission of pollutants. In particular, cross-regional pollutant transport also significantly affects the change in PM2.5. The accuracy of the prediction of pollutant emissions significantly affects the prediction of haze disaster.