# Research on Freight Transportation Carbon Emission Reduction Based on System Dynamics
## 2 Causality Analysis
### Causality  
According to the reality analysis of the causal relationship between the elements of the road-rail system, the causal relationship is shown in Figure 2. The arrows indicate the causal relationship between two elements. The \"+\" sign in the figure indicates a positive effect, and the change trends of the elements on both sides of the arrow are consistent. The \"-\" sign indicates a negative effect, and the changing trends of the elements on both sides of the arrow are opposite.  
In the causality diagram of this paper, the main feedback relationship includes the following three parts.  
1. National economy \(\overset{+}{\rightarrow}\) Environmental investment in railway freight transport \(\overset{-}{\rightarrow}\) Carbon dioxide emissions \(\overset{+}{\rightarrow}\) Carbon levy \(\overset{+}{\rightarrow}\) Road-to-rail freight demand \(\overset{+}{\rightarrow}\) Incremental volume of railway freight \(\overset{+}{\rightarrow}\) Incremental railway transportation revenue \(\overset{+}{\rightarrow}\) National economy. This is negative feedback. Carbon emissions have greatly affected the global climate and environment. Therefore, the government will adjust environmental protection investment to balance environmental problems. The government will give a certain amount of environmental protection investment by  
Figure 2: Causality diagram.  
industry every year to deal with corresponding environmental problems. With the continuous improvement of the national economy, the government's investment in the environmental protection of railway freight will also increase, so the corresponding investment in governance will increase, and carbon dioxide emissions will decrease. In addition, in order to reduce carbon emissions, the government levies a carbon tax based on carbon dioxide emissions. Therefore, compared with road carbon emissions, the railway carbon emissions are relatively low. This will encourage cargo owners to switch from road transportation to railway transportation. So, the demand for road-to-rail freight increases. Considering the freight rates to be invariable will promote the growth of railway freight transport revenue, thereby raising the level of the national economy.
2. Carbon dioxide emissions \(\overset{+}{\rightarrow}\) Carbon levy \(\overset{+}{\rightarrow}\) Road-to-rail freight demand \(\overset{+}{\rightarrow}\) Incremental volume of railway freight \(\overset{+}{\rightarrow}\) Decreasing volume of road freight \(\overset{-}{\rightarrow}\) Carbon dioxide emissions. This is negative feedback. The government levies a carbon tax based on carbon dioxide emissions. Therefore, compared with the road carbon levy, the railway carbon levy is relatively low. This will encourage cargo owners to switch from road transportation to railway transportation. Therefore, the demand for railway freight transportation will increase, and will promote the reduction of freight transportation, so carbon dioxide emissions will be reduced.
3. Carbon dioxide emissions \(\overset{+}{\rightarrow}\) Carbon levy \(\overset{+}{\rightarrow}\) Road-to-rail freight demand \(\overset{+}{\rightarrow}\) Incremental volume of railway freight \(\overset{+}{\rightarrow}\) Carbon dioxide emissions. This is positive feedback. Similar to the second feedback relationship, the government levies a carbon tax based on carbon dioxide emissions. Therefore, compared with the road carbon levy, the railway carbon levy is relatively low. This will encourage cargo owners to switch from road transportation to railway transportation. Therefore, the demand for railway freight transportation will increase. As a result, carbon dioxide emissions will increase.  
However, according to the comparative data of carbon dioxide emissions from roads and railways in previous years, because the railway is a cleaner mode of transportation, the carbon dioxide emissions, after the feedback of A and B are superimposed, on the whole show a decreasing trend.