# Research on the Impact of Output Adjustment Strategy and Carbon Tax Policy on the Stability of the Steel Market

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## Abstract

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## 1. Introduction

## 2. Literature Review

## 3. Method

#### 3.1. The Establishment and Game Analysis of the Static Output Selection Model

_{2}emission reduction and production simultaneously. At this time, enterprise i’s profit function basic form in case K is:

_{2}emission reduction, its profit function can be expressed as:

#### 3.2. Different Emission Reduction Policy Scenarios

_{2}emission reduction policy mentioned in this paper has achieved large-scale application. Only some documents involve the overall emission reduction objectives (only 2020) of the steel industry. Therefore, the combination setting of emission reduction policies and emission reduction scenarios in this section will make reasonable assumptions based on the known emission reduction targets, and also refer to some basic data obtained by the author’s previous research. In the setting of emission reduction indicators, only the emission reduction target in 2020 is relatively certain (the actual production of steel products in recent years is also known), that is, the comprehensive energy consumption per ton of steel in 2020 is about 85% of the energy consumption level in 2010. Therefore, we set the CO

_{2}emission intensity of the iron and steel industry in 2020 to decrease by 15% compared with 2010, assume that the CO

_{2}emission intensity of the iron and steel industry in 2025 will decrease by 20% compared with 2010, and by 2030, the CO

_{2}emission intensity of the iron and steel industry will decrease by 25% compared with 2010.)

- Single carbon tax policy in 2020 (if implemented)

- Mixed carbon tax policy scenario in 2025: carbon tax + subsidy.

_{2}emission intensity of steel and seriously reduce the total profit of production enterprises. If the government provides rebate subsidies to the products produced by enterprises, it will greatly improve the production enthusiasm and production capacity of enterprises, which can be expressed as in Formula (7). Then, changes in various characteristics should be examined when the target is 20–25%. At this time, the basic form of the overall social welfare can be expressed as:

- Multiple mixed carbon tax policy in 2030: carbon tax + subsidy + CCS

_{2}as the two-carbon goal continues to deepen. However, the large-scale investment and technological maturity of CCS projects are also issues of concern to businesses and governments. Likewise, as technological innovation alone is not sufficient to reduce high carbon intensity, carbon taxes and product subsidies will remain necessary policy tools. In this section and the corresponding sections below, carbon taxes, product subsidies and CCS demonstration projects (i.e., 1–2 Mt CO

_{2}levels) (In this section, the application of CCS is assumed only on a very small scale (1–2 MtCO

_{2}levels), and optimistic scenarios for its large-scale application are not discussed. Mainly based on the following viewpoints: (1) CCS technology is not mentioned in the latest national policy documents such as “Guiding Opinions on Promoting High-Quality Development of the Iron and Steel Industry” and “Implementation Plan for Carbon Peaking in the Iron and Steel Industry”. Therefore, this paper maintains a cautious attitude towards the possibility of CCS technology policy implementation, and this paper believes that CCS technology will not be used on a large scale in 2030. (2) Considering the constraints of technology maturity and capital, CCS technology cannot yet become the main way to reduce CO

_{2}emissions, and it is not realistic to apply it to the steel industry on a large scale. From the perspective of policymakers, this paper posits that large-scale realistic scenarios are unlikely.) will be considered together. Then, the changes in various characteristics should be examined when the target is 25–30%. At this time, the basic form of overall social welfare can be expressed as:

#### 3.3. Establishment of Dynamic Output Selection Model and Analysis of Local Stability

_{i}is taken as the decision variable. The base period profit margin is positive (negative), and the firm will increase (decrease) its output in the next period. The product output of enterprise i in period k + 1 is:

_{i}> 0 represents the output adjustment speed of enterprise i, which includes:

_{i}(i = 1, 2, 3, 4, 5, 6), the stable domain of the market can be obtained (the detailed solution and derivation process can be found in Appendix A).

#### 3.4. Data Sources

_{2}accounting data, this research refers to IPCC2006 [50] and Duan et al. [51].

## 4. Results and Discussion

#### 4.1. The Results of Parameter Fitting

#### 4.2. Empirical Analysis

#### 4.2.1. Single Carbon Tax Policy in 2020

- The output adjustment speed of ξ
_{2}, ξ_{5}, ξ_{6}remains unchanged

_{2}, ξ

_{5}, ξ

_{6}are all set to 0 at the same time. The steel market stability domain composed of ξ

_{1}, ξ

_{3}, and ξ

_{4}is analyzed. As can be seen in Figure 1, the adjustment coefficient ξ

_{1}range is [0, 3.40], ξ

_{3}range is [0, 4.00], ξ

_{4}range is [0, 5.00], (the ξ value range considered in this section is [0, 5], and the actual situation will not happen if the value is too large or negative, the same below), which is basically the same as the result when the target is 15%.

_{1}, ξ

_{3}, and ξ

_{4}is basically the same as when the target is 15%.

_{2}, ξ

_{5}, and ξ

_{6}increase from 1.00 to 5.00 (Figure 2); it can be seen that as the northeast, southwest, and northwest regions adopt positive production adjustment coefficients at the same time, the stability of the steel market gradually decreases. The changing trend of the shape of the stability region is very similar to that when the target is 15%. When ξ

_{2}, ξ

_{5}, and ξ

_{6}are large, the other three regions still have sufficient room for output adjustment.

_{2}, ξ

_{5}, and ξ

_{6}are set to 5 at the same time as an example; the results are shown in Figure 3.

_{1}is increased from [0, 1.275] to [0, 1.325], the value range of ξ

_{3}is increased from [0, 1.500] to [0, 1.600], and the value range of ξ

_{4}is increased from [0, 1.900] to [0, 2.025]. Judging from the results, the area of the stability region shows an increasing trend as the target increases. It shows that under the combined effect of the carbon tax and the output adjustment policy of smaller output enterprises, the larger output enterprises’ output adjustment policies will show an increasing trend.

- The output adjustment speed of ξ
_{1}, ξ_{3}, ξ_{4}remains unchanged

_{1}, ξ

_{3}, ξ

_{4}are both set to 0, the steel market stability domain composed of ξ

_{2}, ξ

_{5}, and ξ

_{6}is analyzed. As can be seen in Figure 4, the range of ξ

_{2}is [0, 10.00], ξ

_{5}is [0, 7.50], ξ

_{6}is [0, 10.00], or even more. The value range of ξ considered in this section is [0, 10], which is basically the same as the result when the target is 15%.

_{2}, ξ

_{5}, and ξ

_{6}is basically the same as when the target is 15%.

_{1}, ξ

_{3}, and ξ

_{4}simultaneously increase from 0.50 to 2.00 (Figure 5), it can be seen that when the North, East, and South Central China adopt positive production adjustment coefficients at the same time, the stability of the steel market gradually decreases. It can be clearly found that when ξ

_{1}, ξ

_{3}, ξ

_{4}take small positive values, Northeast China, Southwest China, and Northwest China still have greater autonomy in decision-making. However, when ξ

_{1}, ξ

_{3}, ξ

_{4}gradually increase, the stable area of the entire steel market will shrink sharply. When ξ

_{1}, ξ

_{3}, ξ

_{4}are 2, the value range of ξ

_{2}, ξ

_{5}, ξ

_{6}is very small. Obviously, when ξ

_{1}, ξ

_{3}, ξ

_{4}keep increasing, the market is easily out of balance.

_{1}, ξ

_{3}, and ξ

_{4}take 1.5 at the same time as an example, the results are shown in Figure 6.

_{2}is still maintained at [0, 10] (but through further calculations, the upper limit is increased), the value range of ξ

_{5}is increased from [0, 3.60] to [0, 3.70], the value range of ξ

_{6}is increased from [0, 8.80] to [0, 9.20]. Judging from the results, the area of the stability region shows an increasing trend as the target increases. It means that under the combined effect of the single carbon tax and larger output enterprises’ output adjustment policies, the smaller output enterprises’ output adjustment policies will also increase.

- System dynamic characteristics analysis

_{1}, ξ

_{5}and the change impacts on system stability (we actually calculated all the results with a reduction target of 15–20%, but due to space limitations, this section uses a reduction target of 20% as an example). The results are shown in Figure 7, Figure 8, Figure 9 and Figure 10.

#### 4.2.2. Mixed Carbon Tax Policy Scenario in 2025: Carbon Tax + Subsidy

- The output adjustment speed of ξ
_{2}, ξ_{5}, ξ_{6}remains unchanged

_{2}, ξ

_{5}, and ξ

_{6}take 0 at the same time, the steel market stability domain composed of ξ

_{1}, ξ

_{3}, and ξ

_{4}is analyzed. As can be seen in Figure 11, the adjustment coefficient ξ

_{1}range is [0, 3.50], ξ

_{3}range is [0, 4.05], and ξ

_{4}range is [0, 4.80].

_{2}, ξ

_{5}, ξ

_{6}change from 1.00 to 5.00 (Figure 12), and the stable area is gradually decreasing. The changing trend of its shape is very similar to that of a single carbon tax policy. However, the difference is that when the values of ξ

_{2}, ξ

_{5}, and ξ

_{6}are large (=4), there is still room for output adjustment in the other three regions, but compared to only a single carbon tax scenario, the area of its stability region has been greatly reduced, but when ξ

_{2}, ξ

_{5}, and ξ

_{6}continue to increase to 5, there is not much stability in the region left. It means that with the introduction of the mixed emission reduction policies, enterprises’ output adjustment policies have been compressed, and enterprises with larger output have to carefully consider their next production strategy to avoid the entire steel market falling into an imbalance.

_{2}, ξ

_{5}, and ξ

_{6}are set to 5 at the same time as an example, as shown in Figure 13.

_{1}is expanded to [0, 0.125], the value range of ξ

_{3}is expanded to [0, 0.150], and the value range of ξ

_{4}is expanded to [0, 0.200]. This shows that even if there is a mixed emission reduction policy, under the combined effect of the emission reduction policy and the output adjustment policy of an enterprise with a smaller output, as the target gradually increases, the output adjustment policies that enterprises with larger output will show an increasing trend.

- The output adjustment speed of ξ
_{1}, ξ_{3}, ξ_{4}remains unchanged

_{1}, ξ

_{3}, and ξ

_{4}are taken as 0 at the same time, the steel market stability domain composed of ξ

_{2}, ξ

_{5,}and ξ

_{6}is analyzed. As can be seen in Figure 14, the adjustment coefficient ξ

_{2}range is [0, 9.50], ξ

_{5}range is [0, 7.50], and ξ

_{6}range is [0, 10.00], or even more.

_{1}, ξ

_{3}, and ξ

_{4}increase from 0.50 to 2.00.

_{1}, ξ

_{3}, and ξ

_{4}take 1.5, the output adjustment space of the other three regions is as follows: ξ

_{2}is [0, 4.70], ξ

_{5}is [0, 3.70], ξ

_{6}is [0, 9.20]; compared to only a single carbon tax scenario (the target is 20%), the area of its stability area has been greatly reduced. When the values of ξ

_{1}, ξ

_{3}, and ξ

_{4}are larger, it is foreseeable that the moment of system imbalance will be earlier than in the situation where there is only a single carbon tax policy scenario (the target is 20%).

_{1}, ξ

_{3}, and ξ

_{4}take 1.5 at the same time, the value range of ξ

_{2}is increased from [0, 4.70] to [0, 4.80], the value range of ξ

_{5}is maintained at [0, 3.70], and the value range of ξ

_{6}is increased from [0, 9.20] to [0, 9.40]. When ξ

_{1}, ξ

_{3}, and ξ

_{4}take other smaller values, there is a similar rule. However, when ξ

_{1}, ξ

_{3}, and ξ

_{4}take larger values at the same time (and there is a stable region), the conclusion is different. When the target increases from 20% to 25%, ξ

_{1}, ξ

_{3}, and ξ

_{4}take 2, and the value range of ξ

_{2}and ξ

_{5}is maintained in the interval of [0, 0.40] and [0, 0.30], but the value range of ξ

_{6}is reduced from [0, 0.80] to [0, 0.70]. These results are shown in Figure 16 and Figure 17.

- System dynamic characteristics analysis

#### 4.2.3. Multiple Mixed Carbon Tax Policy Implemented in 2030: Carbon Tax + Subsidy + CCS

- The output adjustment speed of ξ
_{2}, ξ_{5}, ξ_{6}remains unchanged

_{2}, ξ

_{5}, and ξ

_{6}take 0 at the same time, the steel market stability domain composed of ξ

_{1}, ξ

_{3}, and ξ

_{4}is analyzed. As can be seen in Figure 22, the adjustment coefficient ξ

_{1}range is [0, 3.60], ξ

_{3}range is [0, 4.15], and ξ

_{4}range is [0, 5.00].

_{2}, ξ

_{5}, and ξ

_{6}change from 1.00 to 4.00 (Figure 23), and the stable area is gradually decreasing. The changing trend of its shape is very similar to that of the mixed carbon tax policy (carbon tax+ subsidy, scenario 2025). However, the difference is that when the values of ξ

_{2}, ξ

_{5}, and ξ

_{6}are large (=4), there is still room for output adjustment in the other three regions, but compared to the mixed carbon tax policy scenario (emission reduction target = 25%), the area of its stability region has been greatly reduced; when ξ

_{2}, ξ

_{5}, and ξ

_{6}continue to increase to 5, there is no longer a stable region. It means that with the implementation of multiple emission reduction policies, enterprises with larger output have to carefully consider their next production strategies to avoid output adjustment strategies that would spur the entire steel market into imbalance.

_{2}, ξ

_{5,}and ξ

_{6}are taken as 4 at the same time as an example, as shown in Figure 24.

_{1}is increased from [0, 0.35] to [0, 0.45], the value range of ξ

_{3}is increased from [0, 0.45] to [0, 0.50], and the value range of ξ

_{4}is increased from [0, 0.50] to [0, 0.60]. This also shows that even if there are more complex mixed emission reduction policies, under the combined effect of the emission reduction policy and the output adjustment policy of an enterprise with a smaller output, as the target gradually increases, the output adjustment policies that enterprises with larger output will show an increasing trend.

- The output adjustment speed of ξ
_{1}, ξ_{3}, ξ_{4}remains unchanged

_{1}, ξ

_{3}, and ξ

_{4}are taken as 0 at the same time, the steel market stability domain composed of ξ

_{2}, ξ

_{5}, and ξ

_{6}is analyzed. As can be seen in Figure 25, the adjustment coefficient ξ

_{2}range is [0, 8.30], ξ

_{5}range is [0, 6.30], ξ

_{6}range is [0, 10.00], or even more, which is smaller than the scenario of carbon tax+ subsidy policy with an emission reduction target of 25%. This suggests that when introducing the multiple emission reduction policies, production plans of enterprises with smaller output will be affected more obviously.

_{1}, ξ

_{3}, and ξ

_{4}increases from 0.50 to 2.00.

_{1}, ξ

_{3}, and ξ

_{4}take 1.5, the output adjustment space of the other three regions is as follows: ξ

_{2}is [0, 4.40], ξ

_{5}is [0, 3.30], ξ

_{6}is [0, 6.90]; compared to the scenario of carbon tax+ subsidy (emission reduction target of 25%), the area of its stability area has been greatly reduced. However, when the values of ξ

_{1}, ξ

_{3}, and ξ

_{4}are larger (=2), the area of the stability region is larger than the scenario of the carbon tax+ subsidy (the target is 25%). When ξ

_{1}, ξ

_{3}, and ξ

_{4}continue to increase, the system will enter a state of imbalance, but the moment of system imbalance will be later than the scenario of the carbon tax+ subsidy (the target is 25%).

_{1}, ξ

_{3}, and ξ

_{4}take 1.5 at the same time, the value range of ξ

_{2}is increased from [0, 4.40] to [0, 4.50], the value range of ξ

_{5}is maintained at [0, 3.30], and the value range of ξ

_{6}is maintained at [0, 6.90]. When ξ

_{1}, ξ

_{3}, and ξ

_{4}are other smaller values, there is a similar rule. However, when ξ

_{1}, ξ

_{3}, and ξ

_{4}take larger values at the same time (and there is a stable region), the conclusion is different. When the target is increased from 25% to 30%, and when ξ

_{1}, ξ

_{3}, and ξ

_{4}take 2 at the same time, the value range of ξ

_{2}is maintained in the interval of [0, 1.10], but the value range of ξ

_{5}is reduced from [0, 0.80] to [0, 0.70], and the value range of ξ

_{6}is reduced from [0, 1.60] to [0, 1.50]. These results are shown in Figure 27 and Figure 28.

- System dynamic characteristics analysis

#### 4.3. Further Discussions

_{2}emission reduction targets affects the output of North China, East China, and Central South China but increases the production adjustment strategy of these regions, that is, they can adopt more flexible production plans. Obviously, under the dual carbon goal, it is most important for steel enterprises in these regions to complete the corresponding emission reduction plans (the requirements of emission reduction policy combination can be ignored to a certain extent). Previous studies [14,44,54] have conducted corresponding studies on the choice of CO

_{2}emission reduction strategies.

_{2}emission reduction policies is more conducive to market stability and the realization of emission reduction goals.

## 5. Research Conclusions and Recommendations

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A

_{i}(i = 1, 2, 3, 4, 5, 6):

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**Figure 1.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=0$, emission reduction target: 16%).

**Figure 2.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=1~5$, emission reduction target: 16%).

**Figure 3.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=5$, emission reduction target:

**left**15%,

**right**20%).

**Figure 4.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=0$, emission reduction target: 16%).

**Figure 5.**Stability domain of the market (${\xi}_{1}={\xi}_{3}={\xi}_{4}=0.5~2$, emission reduction target: 16%).

**Figure 6.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=1.5$, emission reduction target:

**left**15%,

**right**20%).

**Figure 7.**The bifurcation diagram of ${\xi}_{1}$ (

**left**: ${\xi}_{2}~{\xi}_{6}$ = 0,

**right**: ${\xi}_{2}~{\xi}_{6}$ = 0.4, the reduction target is 20%).

**Figure 8.**The bifurcation diagram of ${\xi}_{5}$ (

**left**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 0,

**right**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 1.5, the reduction target is 20%).

**Figure 9.**The Lyapunov exponent diagram (

**left**: ${\xi}_{2}~{\xi}_{6}$ = 0,

**right**: ${\xi}_{2}~{\xi}_{6}$ = 0.4, the reduction target is 20%).

**Figure 10.**The Lyapunov exponent diagram (

**left**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 0,

**right**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 1.5, the reduction target is 20%).

**Figure 11.**The market stability (${\xi}_{2}={\xi}_{5}={\xi}_{6}=0$, emission reduction target: 20%).

**Figure 12.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=1~5$, emission reduction target: 20%).

**Figure 13.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=5$, emission reduction target:

**left**20%,

**right**25%).

**Figure 14.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=0$, emission reduction target: 20%).

**Figure 15.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=0.5~2$, emission reduction target: 20%).

**Figure 16.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=1.5$, emission reduction target:

**left**20% (2020),

**middle**20% (2025),

**right**25%).

**Figure 17.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=2$, emission reduction target:

**left**20% (2020),

**middle**20% (2025),

**right**25%).

**Figure 18.**The bifurcation diagram of ${\xi}_{1}$ (

**left**: ${\xi}_{2}~{\xi}_{6}$ = 0,

**right**: ${\xi}_{2}~{\xi}_{6}$ = 0.4, the reduction target is 25%).

**Figure 19.**The bifurcation diagram of ${\xi}_{5}$ (

**left**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 0,

**right**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 1.5, the reduction target is 25%).

**Figure 20.**The Lyapunov exponent diagram (

**left**: ${\xi}_{2}~{\xi}_{6}$ = 0,

**right**: ${\xi}_{2}~{\xi}_{6}$ = 0.4, the reduction target is 25%).

**Figure 21.**The Lyapunov exponent diagram (

**left**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 0,

**right**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 1.5, the reduction target is 25%).

**Figure 22.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=0$, emission reduction target: 25%).

**Figure 23.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=1~4$, emission reduction target: 25%).

**Figure 24.**The market stability domain (${\xi}_{2}={\xi}_{5}={\xi}_{6}=4$, emission reduction target:

**left**25%,

**right**30%).

**Figure 25.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=0$, emission reduction target: 25%).

**Figure 26.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=0.5~2$, emission reduction target: 25%).

**Figure 27.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=1.5$, emission reduction target:

**left**25% (2025),

**middle**25% (2030),

**right**30%).

**Figure 28.**The market stability domain (${\xi}_{1}={\xi}_{3}={\xi}_{4}=2$, emission reduction target:

**left**25% (2025),

**middle**25% (2030),

**right**30%).

**Figure 29.**The bifurcation diagram of ${\xi}_{1}$ (

**left**: ${\xi}_{2}~{\xi}_{6}$ = 0,

**right**: ${\xi}_{2}~{\xi}_{6}$ = 0.4, the reduction target is 30%).

**Figure 30.**The bifurcation diagram of ${\xi}_{5}$ (

**left**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 0,

**right**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 1.5, the reduction target is 30%).

**Figure 31.**The Lyapunov exponent diagram (

**left**: ${\xi}_{2}~{\xi}_{6}$ = 0,

**right**: ${\xi}_{2}~{\xi}_{6}$ = 0.4, the reduction target is 30%).

**Figure 32.**The Lyapunov exponent diagram (

**left**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 0,

**right**: ${\xi}_{1},{\xi}_{2},{\xi}_{3},{\xi}_{4},{\xi}_{6}$ = 1.5, the reduction target is 30%).

Researcher | Main Theory and Model |
---|---|

Mathiesen and Maestad [9] | partial equilibrium model |

Liang et al. [10] | CGE model |

Nie et al. [11] | C-D production function |

Kuo et al. [12] | evolutionary game |

Wakiyama and Zusman [13] | time-series autoregressive moving average (ARMA) model |

Duan et al. [14,15] | dynamic game |

Ntombela et al. [16] | CGE model |

Li et al. [17] | environmental-economic simulation model |

Zhu et al. [18] | CGE model |

Wu and Xie [19] | CGE model and the optimization model |

Deng and Adams [20] | life cycle assessment |

Liu et al. [21] | life cycle assessment |

Zhao et al. [22] | supply chain analysis |

Researcher | Industrial Sector |
---|---|

Ji [23] | electricity industry and electricity market |

Sun and Ma [24] | steel industry and steel market |

Tu [25] | power and renewable resources industry |

Dang and Hong [26] | glass substrates industry |

Tan and Liang [27] | coal industry and coal market |

Li et al. [28] | tourism industry |

Di et al. [29,30] | transportation planning |

Liu [31] | carbon trade market |

Yu [32] | transportation industry |

Ding et al. [33] | electricity system |

Zhang [34] | carbon trade market |

Sang, Xie and Wang [35] | ship-building industry |

Zhang et al. [36] | remanufacturing industry |

Wu [37] | electricity market |

Duan et al. [38] | steel industry |

Rezvani and Hudson [39] | oil and gas industry |

Fan et al. [40] | coal Industry |

Gao et al. [41] | creative industry |

Ma et al. [42] | vehicle industry |

Hammond et al. [43] | construction industry |

Notations | Explanations |
---|---|

Q | Steel production |

P | The price of steel |

α | The constant of the market inverse demand curve |

β | The primary coefficient of the market inverse demand curve |

q_{i} | Steel production of region i |

e_{2015,i} | The region i CO_{2} emission intensity of per ton steel in 2015 |

e_{i} | The region i CO_{2} emission intensity of per ton steel at some stage |

r_{i} | The decline range of CO_{2} emission intensity of per ton steel in region i at some stage |

R | The decline target of national CO_{2} emission intensity of per ton steel at some stage |

MAC | Marginal abatement cost curve in steel industry |

a_{i} | The quadratic coefficient of steel industry’s MAC in region i |

b_{i} | The primary coefficient of steel industry’s MAC in region i |

C_{i} | The cost function of steel industry in region i |

C_{0,i} | The production cost of steel industry in region i |

c_{i} | The cost of base period emission reduction in region i |

T | The total carbon tax |

t | The unit value of carbon tax |

W | Social welfare function |

CS | Consumer surplus |

PS | Producer surplus |

D(E) | Total macro external environment loss of CO_{2} emission |

θ | The external loss parameter of CO_{2} |

π_{i} | The profit function of steel industry in region i |

E | The total CO_{2} emissions in steel industry |

ξ_{i} | The adjustment coefficient, rate of output adjustment |

η | The production subsidies |

m | The CO_{2} emission reduced by the CCS demonstration project |

A | The primary coefficient of CCS demonstration project cost curve |

B | The constant of the CCS demonstration project cost curve |

S | The total subsidy |

M | The total cost of the CCS demonstration project |

Notations | Unit | i = 1 | i = 2 | i= 3 | i = 4 | i = 5 | i = 6 |
---|---|---|---|---|---|---|---|

e_{2015,i} | t CO_{2}/t | 2.3344 | 3.5698 | 2.9040 | 2.8779 | 3.2202 | 4.5864 |

a_{i} | - | 11,661 | 17,208 | 16,932 | 12,952 | 6397.2 | 3485 |

b_{i} | - | −169.76 | 8876.7 | −166.92 | 1483.6 | 502.52 | 421.13 |

c_{i} | Yuan | 2168.2 | 3511.1 | 2165.4 | 3325.1 | 2368.7 | 3814.3 |

C_{0,case,k,i} | Yuan, 2015 | 2833.15 | 4898.47 | 3453.53 | 4153.15 | 3799.03 | 3832.38 |

Yuan, 2020 | 2124.86 | 3918.77 | 2590.15 | 2491.89 | 3609.08 | 3640.76 | |

Yuan, 2025 | 1699.89 | 2743.14 | 2072.12 | 1868.92 | 3067.72 | 3094.64 | |

Yuan, 2030 | 1444.91 | 2194.51 | 1761.30 | 1588.58 | 2454.17 | 2475.71 |

Emission Reduction Target | 15% | 16% | 17% | 18% | 19% | 20% |
---|---|---|---|---|---|---|

q_{1} | 2.5789 | 2.5803 | 2.5817 | 2.5833 | 2.5850 | 2.5867 |

q_{2} | 0.3823 | 0.3793 | 0.3758 | 0.3720 | 0.3677 | 0.3629 |

q_{3} | 2.1623 | 2.1619 | 2.1614 | 2.1609 | 2.1603 | 2.1597 |

q_{4} | 1.7354 | 1.7348 | 1.7341 | 1.7333 | 1.7324 | 1.7313 |

q_{5} | 1.1672 | 1.1660 | 1.1648 | 1.1634 | 1.1620 | 1.1606 |

q_{6} | 0.4867 | 0.4823 | 0.4778 | 0.4731 | 0.4683 | 0.4634 |

Emission Reduction Target | 15% | 16% | 17% | 18% | 19% | 20% |
---|---|---|---|---|---|---|

J_{11} | 1−0.5828ξ_{1} | 1−0.5831ξ_{1} | 1−0.5835ξ_{1} | 1−0.5838ξ_{1} | 1−0.5842ξ_{1} | 1−0.5846ξ_{1} |

J_{12} = J_{13} = J_{14} = J_{15} = J_{16} | −0.2914ξ_{1} | −0.2916ξ_{1} | −0.2917ξ_{1} | −0.2919ξ_{1} | −0.2921ξ_{1} | −0.2923ξ_{1} |

J_{22} | 1−0.0864ξ_{2} | 1−0.0857ξ_{2} | 1−0.0849ξ_{2} | 1−0.0841ξ_{2} | 1−0.0831ξ_{2} | 1−0.0820ξ_{2} |

J_{21} = J_{23} = J_{24} = J_{25} = J_{26} | −0.0432ξ_{2} | −0.0429ξ_{2} | −0.0425ξ_{2} | −0.0420ξ_{2} | −0.0415ξ_{2} | −0.0410ξ_{2} |

J_{33} | 1−0.4887ξ_{3} | 1−0.4886ξ_{3} | 1−0.4885ξ_{3} | 1−0.4884ξ_{3} | 1−0.4888ξ_{3} | 1−0.4881ξ_{3} |

J_{31} = J_{32} = J_{34} = J_{35} = J_{36} | −0.2443ξ_{3} | −0.2443ξ_{3} | −0.2442ξ_{3} | −0.2442ξ_{3} | −0.2441ξ_{3} | −0.2440ξ_{3} |

J_{44} | 1−0.3922ξ_{4} | 1−0.3921ξ_{4} | 1−0.3919ξ_{4} | 1−0.3917ξ_{4} | 1−0.3915ξ_{4} | 1−0.3913ξ_{4} |

J_{41} = J_{42} = J_{43} = J_{45} = J_{46} | −0.1961ξ_{4} | −0.1960ξ_{4} | −0.1960ξ_{4} | −0.1959ξ_{4} | −0.1958ξ_{4} | −0.1956ξ_{4} |

J_{55} | 1−0.2638ξ_{5} | 1−0.2635ξ_{5} | 1−0.2632ξ_{5} | 1−0.2629ξ_{5} | 1−0.2626ξ_{5} | 1−0.2623ξ_{5} |

J_{51} = J_{52} = J_{53} = J_{54} = J_{56} | −0.1319ξ_{5} | −0.1318ξ_{5} | −0.1316ξ_{5} | −0.1315ξ_{5} | −0.1313ξ_{5} | −0.1311ξ_{5} |

J_{66} | 1−0.1100ξ_{6} | 1−0.1090ξ_{6} | 1−0.1080ξ_{6} | 1−0.1069ξ_{6} | 1−0.1058ξ_{6} | 1−0.1047ξ_{6} |

J_{61} = J_{62} = J_{63} = J_{64} = J_{65} | −0.0550ξ_{6} | −0.0545ξ_{6} | −0.0540ξ_{6} | −0.0535ξ_{6} | −0.0529ξ_{6} | −0.0524ξ_{6} |

Emission Reduction Target | 20% | 21% | 22% | 23% | 24% | 25% |
---|---|---|---|---|---|---|

q_{1} | 2.4978 | 2.5017 | 2.5057 | 2.5099 | 2.5140 | 2.5184 |

q_{2} | 0.9221 | 0.9176 | 0.9126 | 0.9071 | 0.9012 | 0.8947 |

q_{3} | 2.1472 | 2.1481 | 2.1488 | 2.1496 | 2.1502 | 2.1508 |

q_{4} | 1.8109 | 1.8113 | 1.8117 | 1.8119 | 1.8121 | 1.8122 |

q_{5} | 1.1672 | 1.1675 | 1.1677 | 1.1681 | 1.1685 | 1.1689 |

q_{6} | 0.4669 | 0.4639 | 0.4611 | 0.4585 | 0.4563 | 0.4544 |

Emission Reduction Target | 20% | 21% | 22% | 23% | 24% | 25% |
---|---|---|---|---|---|---|

J_{11} | 1−0.5645ξ_{1} | 1−0.5654ξ_{1} | 1−0.5663ξ_{1} | 1−0.5672ξ_{1} | 1−0.5682ξ_{1} | 1−0.5692ξ_{1} |

J_{12} = J_{13} = J_{14} = J_{15} = J_{16} | −0.2823ξ_{1} | −0.2827ξ_{1} | −0.2831ξ_{1} | −0.2836ξ_{1} | −0.2841ξ_{1} | −0.2846ξ_{1} |

J_{22} | 1−0.2084ξ_{2} | 1−0.2074ξ_{2} | 1−0.2062ξ_{2} | 1−0.2050ξ_{2} | 1−0.2037ξ_{2} | 1−0.2022ξ_{2} |

J_{21} = J_{23} = J_{24} = J_{25} = J_{26} | −0.1042ξ_{2} | −0.1037ξ_{2} | −0.1031ξ_{2} | −0.1025ξ_{2} | −0.1018ξ_{2} | −0.1011ξ_{2} |

J_{33} | 1−0.4853ξ_{3} | 1−0.4855ξ_{3} | 1−0.4856ξ_{3} | 1−0.4858ξ_{3} | 1−0.4860ξ_{3} | 1−0.4861ξ_{3} |

J_{31} = J_{32} = J_{34} = J_{35} = J_{36} | −0.2426ξ_{3} | −0.2427ξ_{3} | −0.2428ξ_{3} | −0.2429ξ_{3} | −0.2430ξ_{3} | −0.2430ξ_{3} |

J_{44} | 1−0.4093ξ_{4} | 1−0.4094ξ_{4} | 1−0.4094ξ_{4} | 1−0.4095ξ_{4} | 1−0.4095ξ_{4} | 1−0.4096ξ_{4} |

J_{41} = J_{42} = J_{43} = J_{45} = J_{46} | −0.2046ξ_{4} | −0.2047ξ_{4} | −0.2047ξ_{4} | −0.2047ξ_{4} | −0.2048ξ_{4} | −0.2048ξ_{4} |

J_{55} | 1−0.2638ξ_{5} | 1−0.2638ξ_{5} | 1−0.2639ξ_{5} | 1−0.2640ξ_{5} | 1−0.2641ξ_{5} | 1−0.2642ξ_{5} |

J_{51} = J_{52} = J_{53} = J_{54} = J_{56} | −0.1319ξ_{5} | −0.1319ξ_{5} | −0.1320ξ_{5} | −0.1320ξ_{5} | −0.1320ξ_{5} | −0.1321ξ_{5} |

J_{66} | 1−0.1055ξ_{6} | 1−0.1048ξ_{6} | 1−0.1042ξ_{6} | 1−0.1036ξ_{6} | 1−0.1031ξ_{6} | 1−0.1027ξ_{6} |

J_{61} = J_{62} = J_{63} = J_{64} = J_{65} | −0.0528ξ_{6} | −0.0524ξ_{6} | −0.0521ξ_{6} | −0.0518ξ_{6} | −0.0516ξ_{6} | −0.0513ξ_{6} |

Emission Reduction Target | 25% | 26% | 27% | 28% | 29% | 30% |
---|---|---|---|---|---|---|

q_{1} | 2.4158 | 2.4198 | 2.4239 | 2.4280 | 2.4321 | 2.4361 |

q_{2} | 1.0427 | 1.0359 | 1.0287 | 1.0210 | 1.0128 | 1.0043 |

q_{3} | 2.0944 | 2.0947 | 2.0950 | 2.0951 | 2.0950 | 2.0948 |

q_{4} | 1.7284 | 1.7283 | 1.7280 | 1.7277 | 1.7271 | 1.7265 |

q_{5} | 1.3805 | 1.3810 | 1.3815 | 1.3822 | 1.3828 | 1.3835 |

q_{6} | 0.6691 | 0.6680 | 0.6674 | 0.6673 | 0.6676 | 0.6685 |

Emission Reduction Target | 25% | 26% | 27% | 28% | 29% | 30% |
---|---|---|---|---|---|---|

J_{11} | 1−0.5460ξ_{1} | 1−0.5469ξ_{1} | 1−0.5478ξ_{1} | 1−0.5487ξ_{1} | 1−0.5497ξ_{1} | 1−0.5506ξ_{1} |

J_{12} = J_{13} = J_{14} = J_{15} = J_{16} | −0.2730ξ_{1} | −0.2734ξ_{1} | −0.2739ξ_{1} | −0.2744ξ_{1} | −0.2748ξ_{1} | −0.2753ξ_{1} |

J_{22} | 1−0.2357ξ_{2} | 1−0.2341ξ_{2} | 1−0.2325ξ_{2} | 1−0.2307ξ_{2} | 1−0.2289ξ_{2} | 1−0.2270ξ_{2} |

J_{21} = J_{23} = J_{24} = J_{25} = J_{26} | −0.1178ξ_{2} | −0.1171ξ_{2} | −0.1162ξ_{2} | −0.1154ξ_{2} | −0.1145ξ_{2} | −0.1135ξ_{2} |

J_{33} | 1−0.4733ξ_{3} | 1−0.4734ξ_{3} | 1−0.4735ξ_{3} | 1−0.4735ξ_{3} | 1−0.4735ξ_{3} | 1−0.4734ξ_{3} |

J_{31} = J_{32} = J_{34} = J_{35} = J_{36} | −0.2367ξ_{3} | −0.2367ξ_{3} | −0.2367ξ_{3} | −0.2367ξ_{3} | −0.2367ξ_{3} | −0.2367ξ_{3} |

J_{44} | 1−0.3906ξ_{4} | 1−0.3906ξ_{4} | 1−0.3905ξ_{4} | 1−0.3904ξ_{4} | 1−0.3903ξ_{4} | 1−0.3902ξ_{4} |

J_{41} = J_{42} = J_{43} = J_{45} = J_{46} | −0.1953ξ_{4} | −0.1953ξ_{4} | −0.1953ξ_{4} | −0.1952ξ_{4} | −0.1952ξ_{4} | −0.1951ξ_{4} |

J_{55} | 1−0.3120ξ_{5} | 1−0.3121ξ_{5} | 1−0.3122ξ_{5} | 1−0.3124ξ_{5} | 1−0.3125ξ_{5} | 1−0.3127ξ_{5} |

J_{51} = J_{52} = J_{53} = J_{54} = J_{56} | −0.1560ξ_{5} | −0.1560ξ_{5} | −0.1561ξ_{5} | −0.1562ξ_{5} | −0.1563ξ_{5} | −0.1563ξ_{5} |

J_{66} | 1−0.1512ξ_{6} | 1−0.1510ξ_{6} | 1−0.1508ξ_{6} | 1−0.1508ξ_{6} | 1−0.1509ξ_{6} | 1−0.1511ξ_{6} |

J_{61} = J_{62} = J_{63} = J_{64} = J_{65} | −0.0756ξ_{6} | −0.0755ξ_{6} | −0.0754ξ_{6} | −0.0754ξ_{6} | −0.0754ξ_{6} | −0.0755ξ_{6} |

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## Share and Cite

**MDPI and ACS Style**

Li, D.; Di, Q.; Zhang, H.; Zhang, D.; Han, Z.; Duan, Y.
Research on the Impact of Output Adjustment Strategy and Carbon Tax Policy on the Stability of the Steel Market. *Energies* **2022**, *15*, 6678.
https://doi.org/10.3390/en15186678

**AMA Style**

Li D, Di Q, Zhang H, Zhang D, Han Z, Duan Y.
Research on the Impact of Output Adjustment Strategy and Carbon Tax Policy on the Stability of the Steel Market. *Energies*. 2022; 15(18):6678.
https://doi.org/10.3390/en15186678

**Chicago/Turabian Style**

Li, Di, Qianbin Di, Hao Zhang, Daquan Zhang, Zenglin Han, and Ye Duan.
2022. "Research on the Impact of Output Adjustment Strategy and Carbon Tax Policy on the Stability of the Steel Market" *Energies* 15, no. 18: 6678.
https://doi.org/10.3390/en15186678