Sustainability Journal (MDPI)
2009 | 1,010,498,008 words
Sustainability is an international, open-access, peer-reviewed journal focused on all aspects of sustainability—environmental, social, economic, technical, and cultural. Publishing semimonthly, it welcomes research from natural and applied sciences, engineering, social sciences, and humanities, encouraging detailed experimental and methodological r...
Study on an Implementation Scheme of Synergistic Emission Reduction of CO2...
Hui Li
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Xianchun Tan
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Jianxin Guo
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Kaiwei Zhu
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
Chen Huang
School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
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Year: 2019 | Doi: 10.3390/su11020352
Copyright (license): Creative Commons Attribution 4.0 International (CC BY 4.0) license.
[Full title: Study on an Implementation Scheme of Synergistic Emission Reduction of CO2 and Air Pollutants in China’s Steel Industry]
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[Summary: This page introduces a study on synergistic emission reduction of CO2 and air pollutants in China's steel industry. It highlights the sector's energy intensity and the importance of reducing CO2, SO2, NOx, and PM2.5 emissions. It outlines a two-stage dynamic optimization model to assess emission reduction plans for 2020 and 2030, considering energy-saving and end-of-pipe technologies. The abstract summarizes the study's findings regarding the impact of PERO and CERO on emission reductions and abatement costs.]
sustainability Article Study on an Implementation Scheme of Synergistic Emission Reduction of CO 2 and Air Pollutants in China’s Steel Industry Hui Li 1,2 , Xianchun Tan 1,2, *, Jianxin Guo 1,2 , Kaiwei Zhu 1,2 and Chen Huang 2 1 Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; lihui 129000@126.com (H.L.); guojianxin@casipm.ac.cn (J.G.); kaiwei_zhu@foxmail.com (K.Z.) 2 School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China; toocold@foxmail.com * Correspondence: txc@casipm.ac.cn; Tel.: +86-186-0120-6217 Received: 12 December 2018; Accepted: 7 January 2019; Published: 11 January 2019 Abstract: China’s steel industry is an energy-intensive sector. Synergistic reduction of emissions of CO 2 and air pollutants (SO 2 , NOx, and PM 2.5) in the steel industry has an important practical significance for climate change and air pollution control. According to the CO 2 emission reduction intensity targets (CERO) and air pollutant emission targets (PERO) for 2020 and 2030, 28 types of energy-saving and emission reduction technologies (20 types of carbon reduction technology and eight types of air pollution end-of-pipe technology) were selected for examination, and a two-stage dynamic optimization model with collaborative implementation of PERO and CERO was built to assess the near future (2015–2020) and long-term (2020–2030) implementation plans for synergistic emissions reduction of CO 2 and air pollutants. The results show that in the near future, the implementation of PERO will have a greater synergistic effect on CO 2 emission reduction CO 2 emission reduction under PERO in 2020 will be 97 million tons (Mt) higher than that of CERO, an increase of nearly 26%. However, the effects of implementing CERO are better in the long run. Under CERO, the emission reductions of SO 2 , NOx, and PM 2.5 in 2030 are 2.44 Mt, 1.47 Mt, and 0.86 Mt, respectively, and 7%, 4%, and 5% higher than the implementation of PERO. As far as marginal abatement cost is concerned, in the near future, the marginal abatement costs of CO 2 and air pollutant equivalents are 1.06 yuan/kgCO 2 and 133 yuan/kg pollution equivalent (pe) under PERO, which are 23% and 11% lower than that of CERO, while in the long run, the marginal abatement costs of CO 2 and pollutant equivalents under CERO are 0.025 yuan/kgCO 2 and 2.73 yuan/kgpe, about 96% and 95% lower than that of PERO Keywords: Air pollution treatment; CO 2 emission reduction; Synergistic emission reduction; steel industry 1. Introduction The steel industry is characterized by high energy consumption and high emissions. Its carbon dioxide (CO 2 ) emissions account for approximately 15% [ 1 ] of China’s total CO 2 emissions. It is an important target industry for China when implementing energy conservation and emission reduction policies. In addition, because of the homology between greenhouse gases and air pollutants, the combustion of fossil energy sources such as coal will also produce emissions of air pollutants such as SO 2 , NOx, and PM 2.5. In 2013, SO 2 , NOx, and smoke and dust in the steel industry accounted for 10.5%, 3.3%, and 5.8% of total industrial emissions, respectively [ 2 ]. SO 2 , NOx, and particulate matter (PM) emissions in the steel industry rank third, third, and first of all industrial sectors [ 3 ], respectively. In recent years, China has plunged into heavy air environmental pollution: 70.7% of Sustainability 2019 , 11 , 352; doi:10.3390/su 11020352 www.mdpi.com/journal/sustainability
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[Summary: This page discusses the significance of synergistic emission reduction in China's steel industry for achieving national targets and combating air pollution. It reviews existing literature on co-benefits, categorizing them into static and dynamic analyses. Static methods include factor, comprehensive index, and MAC curve analyses. Dynamic methods are divided into top-down (CGE models) and bottom-up (GAINS, TIMES models) approaches. The study aims to determine a synergistic emission reduction scheme of CO2 and air pollutants under different objectives by optimizing the technology portfolio.]
Sustainability 2019 , 11 , 352 2 of 22 Chinese cities failed to meet air quality standards in 2017 [ 4 ]. Environmental damage has had a huge impact on China’s economy [ 5 ], accounting for about 5–6% of China’s gross domestic product (GDP) [ 6 ]. Therefore, it is of great practical significance to study the synergistic emission reduction of CO 2 and air pollutants in China’s steel industry to achieve the national NDC target and win China’s “Blue Sky Defense War” The term ‘co-benefit’ first appeared in the third assessment report of the Intergovernmental Panel on Climate Change (IPCC) in 2001. It is defined as the benefit of implementing policies for various reasons at the same time [ 7 ]. Because the definition of co-benefits proposed by the IPCC is relatively broad, different countries and institutions have had different understandings of the term. In the current literature on co-benefits, the understanding of the word is mainly divided into two types: static synergistic effect analysis and dynamic synergistic effect analysis. Static synergistic effect analysis can be further divided into the factor method, comprehensive index method, and marginal abatement cost (MAC) curve analysis method. The factor method is mainly used to compare the synergistic effect of one gas emission reduction measure on another gas emission reduction [ 8 – 10 ]. The comprehensive index method assigns an effect coefficient to each type of gas to measure the synergistic effect of all gases considered under different measures [ 11 , 12 ]. The MAC curve analysis incorporates the air quality benefits or environmental damage costs into the calculation process of MAC, thus determining the sequence of technology adoption [ 13 – 15 ]. In summary, static synergistic effect analysis methods are relatively intuitive and easy to understand, but they cannot predict the synergistic effect of the whole planning period, because they do not consider the time factor Dynamic synergistic effect analysis can also be divided into top-down and bottom-up methods Top-down methods, such as the computable general equilibrium (CGE) model [ 16 – 20 ], can quantify the impact of different policies on the macro-economy by establishing a correlation between air pollution control or carbon emission reduction policies and relevant factors in macro-economy. However, it cannot accurately reflect the effects of technological changes. Bottom-up methods, such as greenhouse gas-air pollution interactions and synergies (GAINS) [ 21 – 25 ], and the integrated MARKAL-EFOM system (TIMES) models [ 26 – 28 ] simulate the technologies used in the energy production process from the micro-level, using a line optimization model to predict the impact of economic activities on the climate and environment. The point of this study is to determine a synergistic emission reduction scheme of CO 2 and air pollutants under different objectives by optimizing the technology portfolio Unlike previous literature, this paper adopts a non-linear bottom-up dynamic optimization method Although some studies use non-linear programming to study the choice of technology [ 29 , 30 ], they are limited to theoretical research, and do not involve synergistic problems In the existing literature, at the spatial level, Yang and Teng [ 31 ] and Wang et al. [ 32 ] studied the impact of China’s coal control policy (2010–2050) and non-fossil energy promotion policy (2005–2100) on SO 2 , NOx, and PM 2.5 emissions. Bhanarkar et al. [ 23 ], Dong et al. [ 17 ], Liu et al. [ 24 ], and Lin et al. [ 33 ] all used 2030 as their target year and explored the synergistic emission reduction of air pollutants (PM 10, PM 2.5, black carbon, SO 2 , CO, VOC, etc.) and CO 2 under the influence of the air pollution control policies or CO 2 emission reduction technologies. Compared to the spatial analysis perspective, more studies focused on the industry or sector level, such as the power sector, transportation sector, and cement industry [ 13 , 33 – 38 ]. However, most of the above studies analyze the long-term synergistic effects of a single policy. Few studies consider the synergistic effects of 2020 air pollution control objectives. However, the current environmental governance is in urgent need of policy guidance and implementation. Peng et al. [ 39 ] also suggested the importance of studying co-controlling air pollutant and carbon emissions with a short-term perspective, in order to guide immediate policy making and analyzed the co-benefits under different scenarios in 2015. However, they did not consider the dynamic development of the relevant industries over time.
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[Summary: This page emphasizes the research gap in comparing synergistic effects of air pollution treatment (PERO) and carbon reduction (CERO) objectives for 2020 and 2030. It details the selection of 20 carbon emission reduction and 8 end-of-pipe technologies. The study constructs a two-stage dynamic optimization model for near-future (2015-2020) and long-term (2020-2030) objectives of CERO and PERO. It compares emission reductions and MACs to suggest which objectives should take precedence in different stages.]
Sustainability 2019 , 11 , 352 3 of 22 In terms of CO 2 and air pollutant synergistic emission reduction in the steel industry, Ma et al. [ 26 ] analyzed the synergistic effect of production restructuring, as well as the effect of energy-saving and emission reduction technologies on air pollutants in the steel industry from 2010–2050. They thought implementing energy-saving technologies was the most effective way to reduce CO 2 emission in the short-term, while adjusting production structures would play an important role in CO 2 emission reduction in the long run. Wu et al. [ 12 ] evaluated the synergistic emission reduction effects of 24 types of energy-saving technology on CO 2 , SO 2 , NOx, and PM 10, by establishing the synergistic benefit function (APeq). Ma et al. [ 15 ] used a static model to analyze the impact of energy-saving technologies on air pollutant emission reduction. However, while these studies discuss the synergistic effect of carbon emission reduction technology on SO 2 , NOx, PM 2.5, and other air pollutant emission reductions, they omit the impact of end-of-pipe technologies on CO 2 emissions. Though Zhang et al. [ 25 ] considered energy-saving technologies and end-of-pipe control technologies in the steel industry, and analyzed the synergies between different technology combinations between 2010–2030, they did not integrate the goal of winning the “Blue Sky Defense War” into the research framework, nor analyze the synergistic effects under the goal of winning the “Blue Sky Defense War” In short, research comparing the synergistic emission reduction effects of air pollution treatment objectives (PERO) and carbon reduction objectives (CERO) in 2020 and 2030 remains scant. Therefore, further research on the optimization of the technology portfolio among carbon emission reduction technology and end-of-pipe technology in the steel industry is necessary to fill the gap. Twenty types of carbon emission reduction technologies and eight types of end-of-pipe technologies have been screened out (as listed Tables 1 and 2 ), based on the principle of advancement and applicability, and a two-stage dynamic optimization comprehensive model involving the near future (2015–2020) objectives and long-term (2020–2030) objectives of CERO and PERO was constructed. The following time spans of near future and long-term are from 2015 to 2020 and 2020 to 2030, respectively. The emission reduction of different gases (CO 2 , SO 2 , NOx, and PM 2.5) and MACs under different targets is compared from vertical and horizontal perspectives, and suggestions on which emission reduction objectives should take precedence in the near future and long term stages are offered.
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[Summary: This page presents Table 1, which lists energy-saving and emission reduction technologies used in China’s steel industry. The table includes information on each technology's annual investment, annual change in operation and maintenance cost, main energy-saving varieties, energy saving (kgce/t Crude Steel), and penetration rate. The technologies range from coal moisture control to online heat treatment.]
Sustainability 2019 , 11 , 352 4 of 22 Table 1. Energy saving and emission reduction technology in China’s steel industry No. Technology/Measure Annual Investment (yuan/t) Annual Change in O&M Cost (yuan/t) Main Energy Saving Varieties Energy Saving (kgce/t Crude Steel) Penetration Rate G 1 Coal moisture control technology 23.1 6.19 Coal 4.771887 0.05 G 2 High temperature and high pressure dry quenching technology 41.47 4.63 Electricity 21.03513 0.13 G 3 Mini-pelletized sintering technology 1.64 1.37 Coal and electricity 6.65409 0.7 G 4 Reduction of air leakage rate in sintering 0.91 1.62 Coal and electricity 0.83022 0.8 G 5 Low temperature sintering technology 1.64 3.09 Integrated energy 7.718744 0.9 G 6 Thick layer sintering technology 3.29 0.6 Integrated energy 24.89633 0.9 G 7 Sintering waste heat recovery and utilization technology (power generation) 16.76 3.89 Electricity 11.0696 0.2 G 8 Technology of recycling waste heat from pellets 44.1 2.22 Coal and electricity 0.735 0.4 G 9 Production technology of grate-rotary kiln pellets 2.2 0.25 Coal and electricity 2.45 0.6 G 10 Blast furnace thick phase high efficiency coal injection technology 10.27 2.28 Coal 79.2 0.6 G 11 Blast furnace dehumidifying blast technology 18.4 2.39 Coal 0.598382 0.05 G 12 Top pressure recovery turbine (TRT) 16.1 4.1 Electricity 12.76 0.5 G 13 Double preheating technology for the hot stove of a blast furnace 10.04 5.28 Coal 8.54832 0.5 G 14 Combined cycle power turbine (CCPP) 50.2 1.27 Electricity 24.776 0.2 G 15 Converter ‘negative energy steelmaking’ technology 15 3.41 Coal 25 0.48 G 16 High efficiency continuous casting technology (HECCT) 14 1.4 Integrated energy 4 0.75 G 17 Thin slab casting technology 30 42.71 Integrated energy 34.41 0.15 G 18 Hot delivery & hot charging technology of a continuous casting slab 1.76 1.54 Integrated energy 11.29997 0.7 G 19 Low temperature rolling technology 2.2 0 Coal 10.584 0.2 G 20 Online heat treatment technology 66.26 9.94 Integrated energy 29.106 0.05 Note: The penetration rate is the ratio of products produced by this technology to total products.
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[Summary: This page presents Table 2, which details end-of-pipe technologies for air pollutants in the steel industry. The table lists each technology's annual investment, annual change in O&M cost, electricity consumption (kwh/t Crude Steel), removal efficiency (%), popularity rate (%), and the pollutant it targets. Technologies include limestone-gypsum FGD, activated carbon desulfurization and denitrification, ESP, and bag-type dust collectors.]
Sustainability 2019 , 11 , 352 5 of 22 Table 2. End-of-pipe technologies of air pollutants in the steel industry No Technology Annual Investment (yuan/t) Annual Change in O&M Cost (yuan/t) Electricity (kwh/t Crude Steel) Removal Efficiency (%) Popularity Rate (%) Pollutant E 1 Limestone-gypsum flue gas desulfurization (FGD) 16 6.3 0.01 0.95 25 SO 2 E 2 Circulating fluidized bed flue gas desulfurization (CFB-FGD) 10 3.4 8.03 0.9 5.8 SO 2 E 3 Activated carbon desulfurization and denitrification technology 25 4.75 0 0.95 1.1 SO 2 E 4 Activated carbon desulfurization and denitrification technology 25 4.75 0 0.4 1.1 NOx E 5 Selective non-catalytic reduction (SNCR) 2 0.7 11 0.45 0 NOx E 6 Selective Catalyst Reduction (SCR) 6 5.7 33 0.8 0 NOx E 7 Electrostatic precipitator (ESP) 11 0.25 57.6 0.96 20 PM 2.5 E 8 Bag-type dust collector 13 0.26 3.5 0.99 10 PM 2.5
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[Summary: This page describes the comprehensive assessment model's framework, including an emission accounting module and a two-stage dynamic optimization module. The emission accounting module calculates CO2 and air pollutant emissions in the BAU scenario. The dynamic optimization module calculates emission reductions under CERO and PERO. The page also details the CO2 emission accounting method, considering emissions from fossil fuel combustion, production processes, and electricity consumption of end-of-pipe technologies.]
Sustainability 2019 , 11 , 352 6 of 22 2. Comprehensive Assessment Model 2.1. Framework of Model The comprehensive assessment model constructed in this paper includes an emission accounting module and a two-stage dynamic optimization module, as shown in Figure 1 . The emission accounting module is used to calculate the emissions of CO 2 and air pollutants in the scenario of “business as usual” (BAU), and the detailed calculation steps are included in Section 2.2 . The two-stage dynamic optimization module is used to calculate the emission reduction of CO 2 and three air pollutants (SO 2 , NOx, and PM 2.5) under CERO and PERO, discussed in Section 2.3 . Sustainability 2019 , 11 , x FOR PEER REVIEW 6 of 22 2. Comprehensive Assessment Model 2.1. Framework of Model The comprehensive assessment model constructed in this paper includes an emission accounting module and a two-stage dynamic optimization module, as shown in Figure 1. The emission accounting module is used to calculate the emissions of CO 2 and air pollutants in the scenario of "business as usual" (BAU), and the detailed calculation steps are included in Section 2.2. The twostage dynamic optimization module is used to calculate the emission reduction of CO 2 and three air pollutants (SO 2 , NOx, and PM 2.5) under CERO and PERO, discussed in Section 2.3. Figure 1. The framework of the comprehensive assessment model. 2.2. Emission Accounting Module 2.2.1. CO 2 Emission Accounting In general, the application of end-of-pipe technologies will increase CO 2 emissions due to electricity consumption, so we calculated the CO 2 emissions from three aspects: CO 2 emissions generated from fossil fuel combustion ( c E ), CO 2 emissions generated from the production process, and CO 2 emissions generated from the electricity consumption of end-of-pipe technologies ( Eend ). CO 2 emissions generated from the production process can be further divided into: emissions from the flux of iron-making in the process of high-temperature decomposition ( 1 p E ), and emissions from the process of carbon reduction in steelmaking ( 2 p E ). The calculation methods of each part are as follows: = c E Q EPC ep × × (1) li 1 m 0.15 = est n p o e rs ep E Q × × × (2) 2 =( 44/12 p E fn fc stc Q × − × × ) (3) j j e j Eend eff Q r ep = × × × , (4) where Q is the output of crude steel, EPC is the comprehensive energy consumption per unit of crude steel, ep represents the comprehensive emission factor, rs is the iron-to-steel ratio (here, iron-making flux is calculated with limestone, and the ratio of flux is 0.15 t/t iron [40]), lim estone ep represents the emission factor of limestone (adopting the default value of IPCC), fn represents iron consumption per ton of steel in steelmaking [41], fc represents the carbon content of pig iron (adopting the default value of IPCC), and stc represents the average amount of carbon in steel (adopting the default value of IPCC). i eff represents the electricity consumption of end-of-pipe Figure 1. The framework of the comprehensive assessment model 2.2. Emission Accounting Module 2.2.1. CO 2 Emission Accounting In general, the application of end-of-pipe technologies will increase CO 2 emissions due to electricity consumption, so we calculated the CO 2 emissions from three aspects: CO 2 emissions generated from fossil fuel combustion ( E c ), CO 2 emissions generated from the production process, and CO 2 emissions generated from the electricity consumption of end-of-pipe technologies ( Eend ) CO 2 emissions generated from the production process can be further divided into: emissions from the flux of iron-making in the process of high-temperature decomposition ( E p 1 ), and emissions from the process of carbon reduction in steelmaking ( E p 2 ). The calculation methods of each part are as follows: E c = Q × EPC × ep (1) E p 1 = Q × 0.15 × rs × ep lim estone (2) E p 2 = ( f n × f c − stc × 44/12 × Q (3) Eend = ∑ j e f f j × Q × r j × ep e , (4) where Q is the output of crude steel, EPC is the comprehensive energy consumption per unit of crude steel, ep represents the comprehensive emission factor, rs is the iron-to-steel ratio (here, iron-making flux is calculated with limestone, and the ratio of flux is 0.15 t/t iron [ 40 ]), ep lim estone represents the emission factor of limestone (adopting the default value of IPCC), f n represents iron consumption per ton of steel in steelmaking [ 41 ], f c represents the carbon content of pig iron (adopting the default value of IPCC), and stc represents the average amount of carbon in steel (adopting the default value of IPCC) e f f i represents the electricity consumption of end-of-pipe technology j , r j represents the penetration rates of end-of-pipe technology j , and ep e represents the emission factor of electricity.
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[Summary: This page continues the description of the emission accounting module, detailing the method for accounting air pollutant emissions. It considers emissions from energy combustion and production processes, deducting the removal volume of end-of-pipe technologies. The page then transitions to describing the two-stage dynamic optimization module, stating that the development level of technologies are the decision variables. Figure 2 shows the modeling ideas of the two-stage dynamic optimization model.]
Sustainability 2019 , 11 , 352 7 of 22 2.2.2. Emissions Accounting of Air Pollutants Air pollutant emissions are mainly derived from energy combustion, with a small percentage derived from production processes. Considering the application of end-of-pipe technologies in the steel industry, we should deduct the removal volume of end-of-pipe technologies from the total emission of each pollutant when calculating the emissions of air pollutants: EP 1 = ∑ k E e ( k , t ) × ep s ( k , t ) × Q (5) EP 2 = ep p × Q (6) EP = ( EP 1 + EP 2 ) × ( 1 − ∑ j r j × η j ) , (7) where EP represents emissions of air pollutants, 1 and 2 represent the energy combustion process and production process, respectively, k represents energy varieties, E e represents energy consumption (calculated by energy structure of ferrous industry), eps represents the air pollutant emission factor of energy varieties, ep p represents the air pollutant emission factor of the production process, and η i represents the removal efficiency of end-of-pipe technology j . The specific value of each parameter is shown in Section 3.1 . 2.3. Two-Stage Dynamic Optimization Module We take the development level of the relevant technologies as the decision variables for discussing the development path of these technologies under the minimum cost. Based on this, the emission reduction of CO 2 and three air pollutants (SO 2 , NOx, and PM 2.5) can be calculated. The modelling ideas of the two-stage dynamic optimization model are shown in Figure 2 . Sustainability 2019 , 11 , x FOR PEER REVIEW 8 of 22 Figure 2. Modeling ideas of the two-stage dynamic optimization model. 2.3.1. Objective Function The forms of objective functions under CERO and PERO are the same (i.e., total cost minimization). The total cost includes the fixed investment cost, operation and maintenance cost, and variable operation cost. The expression of objective function is as follows: 1 [1/ (1 ) ] t t i i T t t t t i i i r q t i MinTC INV FOM VOM ρ = = + + , ( + ) , (8) where TC is the total cost, ρ is the discount rate (5% [42] is adopted here), INV is the fixed investment cost, FOM is the operation and maintenance (O&M) cost, , r q indicate the capacity and output of the technology, respectively, i represents the technology type, including energy-saving, i 1, and end-of-pipe technology, i 2, t represents the year, and T represents the number of planning periods. 2.3.2. Constraints The constraints of the two-stage dynamic optimization model include capacity constraints, CO 2 emission constraints, air pollutants emission constraints, and penetration constraints. Capacity constraints refer to the fact that the output of technology in each period cannot exceed the cumulative capacity of technology of this period, as shown in Formula (9). The calculation of cumulative capacity is shown in the Formula (10), which means that with the expiration of existing technology lifespans, new technology production capacities need to be continuously introduced to meet the demand for steel products. TI in Formula (10) represents the lifespan of technology (adopting 20 years [43]). These constraints are applicable to dynamic optimization models under CERO and PERO. t t i i q C ≤ (9) 1 1 (1 ) t t t i i i i C C r TI − = × − + (10) Figure 2. Modeling ideas of the two-stage dynamic optimization model The optimization process of the first stage is as follows: (1) From a long-term perspective, the synergistical control of four gases (CO 2 , SO 2 , NOx, and PM 2.5) and MACs under a single objective (CERO or PERO) is predicted respectively.
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[Summary: This page continues describing the two-stage dynamic optimization model, elaborating on the objective function and constraints. The objective function minimizes total cost, including fixed investment, operation & maintenance, and variable operation costs. Constraints include capacity limits, CO2 emission limits, air pollutant emission limits, and penetration limits. The page also describes the optimization process of the first stage, which is to predict the synergistical control of four gases (CO2, SO2, NOx, and PM2.5) and MACs under a single objective.]
Sustainability 2019 , 11 , 352 8 of 22 (2) By comparing the short-term synergistical effects and MACs under each objective, the best short-term synergetic scheme is determined The second optimization process is to compare the emission reduction effects and MACs of four gases under the implementation of CERO and PERO, separately in the long-term, based on the implementation of the optimal synergistical scheme in the near future, and then determine the optimal long-term collaboration scheme It should be noted that the input of the model of the second stage is the output of the optimal implementation scheme in the near future. In addition, because of the different removal rates of activated carbon flue gas desulfurization and denitrification technology in SO 2 and NOx, we regard it as two technologies. In essence, they are one technology, we equalized their costs and energy consumptions and controlled their popularity rate changes by certain constraints 2.3.1. Objective Function The forms of objective functions under CERO and PERO are the same (i.e., total cost minimization) The total cost includes the fixed investment cost, operation and maintenance cost, and variable operation cost. The expression of objective function is as follows: Min r t i , q t i TC = T ∑ t = 1 [ 1/ ( 1 + ρ ) t ] ∑ i ( I NV t i + FOM t i + VOM t i ) , (8) where TC is the total cost, ρ is the discount rate (5% [ 42 ] is adopted here), I NV is the fixed investment cost, FOM is the operation and maintenance (O&M) cost, r , q indicate the capacity and output of the technology, respectively, i represents the technology type, including energy-saving, i 1, and end-of-pipe technology, i 2, t represents the year, and T represents the number of planning periods 2.3.2. Constraints The constraints of the two-stage dynamic optimization model include capacity constraints, CO 2 emission constraints, air pollutants emission constraints, and penetration constraints Capacity constraints refer to the fact that the output of technology in each period cannot exceed the cumulative capacity of technology of this period, as shown in Formula (9). The calculation of cumulative capacity is shown in the Formula (10), which means that with the expiration of existing technology lifespans, new technology production capacities need to be continuously introduced to meet the demand for steel products T I in Formula (10) represents the lifespan of technology (adopting 20 years [ 43 ]). These constraints are applicable to dynamic optimization models under CERO and PERO q t i ≤ C t i (9) C t i = C t − 1 i × ( 1 − 1 T I i ) + r t i (10) CO 2 emission constraints indicate that the CO 2 emission per industrial added value in each period should not exceed the limited emission intensity of this period, as shown in Formula (11). The left side of the formula consists of three parts: the first part displays the CO 2 emission in the period t under BAU, E t c 0 , and the second part displays the CO 2 emission reduction of carbon reduction technologies in the period t, which can be obtained by the product of energy saving, SEN k ( i 1, t ) , of energy k from technology i 1, the emission factor of energy k , epc ( k ) , and the output of technology i 1. The third part displays the added CO 2 emission of end-of-pipe technologies due to electricity consumption, which can be obtained by the electricity emission factor, eps e , electricity consumption of end-of-pipe technology, e f f e i 2 ( t ) , and the output of end-of-pipe technology. The right side of the formula is the
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[Summary: This page continues describing the constraints of the two-stage dynamic optimization model, specifically focusing on CO2 emission constraints, air pollutants emission constraints, and popularity rate constraints. CO2 emission constraints ensure that the CO2 emission per industrial added value does not exceed the limited emission intensity. Air pollutants emission constraints ensure that the emission amounts do not exceed the prescribed emission limits. Popularity rate constraints are shown as Formulas (13)–(15).]
Sustainability 2019 , 11 , 352 9 of 22 product of CO 2 emission intensity, TE t , and the industry added value, VG t . These constraints are only suitable to the dynamic optimization model under CERO E t c 0 − ∑ k SEN k ( i 1, t ) × ( q t i 1 − q 0 i 1 ) × ep c ( k , t ) + e f f e i 2 ( t ) × ( q t i 2 − q 0 i 2 ) × eps e ( t ) ≤ TE t × VG t (11) Air pollutants emission constraints indicate that the emission amounts of air pollutants in each period should not exceed the prescribed emission limits of air pollutants of this period. While most end-of-pipe technologies remove some air pollutants, they also release air pollutants due to their consumption of electricity. Thus, when calculating the emission of air pollutants, we also consider air pollutants emissions generated by this electricity: ( E t p 0 − ∑ k SEN k ( i 1, t ) × ep s ( k , t ) × ( q t i 1 − a 0 i 1 ) + ∑ i 2 e f f e ( t ) × ep e ( t ) × ( q t i 2 − a 0 i 1 )) × ( 1 − ∑ i 2 q t i 2 × η i 2 ) ≤ E t pm , (12) where, E t p 0 represents the emission of air pollutants (SO 2 , NOx, and PM 2.5) in the period t under BAU, η i 2 represents the removal rate of end-pipe technology, and E t pm represents the emission caps of air pollutants. As we can see in Formula (12), these are non-linear constraints. These non-linear constraints are only suitable to the dynamic optimization model under PERO The popularity rate constraints are shown as Formulas (13)–(15). Formula (13) shows that the penetration rate of technology in the future will not be lower than that of the latest phase, assuming that no new or efficient technologies will replace existing technologies. To avoid repeated calculation, this paper assumes that the end-of-pipe technologies for removing the same air pollutants are mutually exclusive, as shown in Formula (14). Formula (15) ensures the consistency of activated carbon flue gas desulfurization and denitrification technology q t i Q t i − q t − 1 i Q t − 1 i ≥ 0 (13) ni ∑ i 2 = 1 q t i 2 Q t ≤ 1 (14) q t 23 Q t = q t 24 Q t (15) 3. Data Source and Scenario Settings 3.1. Data Source The steel demand and industrial added value are taken from the 13 th “Five-Year Plan of the Iron and Steel Industries” [ 44 ], described Yang and Teng [ 31 ] and Zhang et al. [ 7 ], and shown in Table 3 . Table 3. Related data of the steel industry 2015 2020 2025 2030 Demand of the steel industry (Mt) 803.8 1066 1015 966 The industrial added value of the steel industry (constant price in 2015, billion yuan) 2604 3491.3 4004.2 452.69 The related cost data of all technologies are taken from China’s National Key Energy Conservation Technologies Promotion Catalogue [ 45 ], the Guide to Advanced and Applicable Technologies of Energy-saving and Emission Reduction in the Iron and Steel Industries [ 46 ], the Application of Advanced Applicable Technology for Energy Conservation and Emission Reduction in Iron and Steel Industry [ 47 ], the National Energy Statistic Yearbook [ 48 ], the China Steel Yearbook [ 40 ], and other
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[Summary: This page details the data sources and scenario settings used in the study. Data on steel demand and industrial added value are from the 13th Five-Year Plan. Cost data are from various national catalogs and yearbooks. Energy prices are based on IEA predictions. CO2 emission factors are from China's greenhouse gas inventory. Air pollutant emission factors are from research papers. Equivalent values of air pollutants are from the environmental protection tax law. Tables 4 and 5 show fuel prices and emission factors of electricity and heat. The page also describes scenario settings for CERO and PERO.]
Sustainability 2019 , 11 , 352 10 of 22 related references [ 12 , 49 – 52 ]. Energy prices are calculated based on the change rate of energy prices in the future predicted by IEA, as shown in Tables 2 and 3 . CO 2 emission factors from different energy varieties (apart from electricity and heat) are taken from China’s greenhouse gas inventory of 2008 [ 53 ], and are calculated by the carbon content and carbon oxidation rate per unit calorific value of different energy sources. The emission factors of air pollutants are taken from Zhao et al. [ 54 ], and the emission factors of electricity and heat are referred to in Tan et al. [ 55 ] and Zhao et al. [ 54 ]. Equivalent values of air pollutants are taken from the environmental protection tax law of the People’s Republic of China, as shown in Tables 4 and 5 . Table 4. Fuel price No. Price (yuan/GJ) 2015 2020 2025 2030 1 Raw Coal 26.27 26.32 27.90 28.41 2 Cleaned Coal 26.27 26.32 27.90 28.41 3 Other Washed Coal 26.27 26.32 27.90 28.41 4 Coke 38.64 38.71 41.03 41.78 5 Coke Oven Gas 20 20.04 21.24 21.63 6 Blast Furnace Gas 20 20.04 21.24 21.63 7 Converter Gas 20 20.04 21.24 21.63 8 Other Gas 20 20.04 21.24 21.63 9 Other Coking Products 38.64 38.85 41.18 43.49 10 Crude Oil 100 155.87 173.83 183.83 11 Gasoline 161.52 251.76 280.77 296.92 12 Kerosene 127.54 198.80 221.71 234.46 13 Diesel Oil 124.74 194.43 216.84 229.31 14 Fuel Oil 71.41 111.31 124.14 131.28 15 Naphtha 120.98 188.58 210.31 222.40 16 Lubricants 117.01 182.38 203.40 215.1 17 Paraffin Waxes 158.31 246.76 275.20 291.03 18 White Spirit 154.72 241.16 268.95 284.42 19 Bitumen Asphalt 97.49 151.95 169.47 179.21 20 Petroleum Coke 34.39 53.60 59.78 63.21 21 LPG 77.62 120.99 134.94 142.70 22 Refinery Gas 20 31.17 34.767 36.77 23 Other Petroleum Products 100 155.87 173.83 183.83 24 Natural Gas 10.78 15.27 16.38 16.86 25 LNG 73.79 104.56 112.19 115.44 26 Heat 50 50.09 53.09829 54.07 27 Electricity 85 91.96 93.06 93.45 28 Other energy 20 20 20 20 Table 5. Emission factors of electricity and heat Energy(tCO 2 /tce) 2016 2020 2025 2030 Electricity 5.38 5.3 4.57 3.83 Heat 3.67 3.65 3.63 3.02 3.2. Scenario Settings The cooperative implementation schemes of CERO and PERO are studied in this paper. CERO focuses on the CO 2 emission amount per unit of industrial added value of the target year, while PERO focuses on the emission caps of air pollutants of the target year. Based on the 13 th “Five-Year Work Plan for Greenhouse Gas Control” [ 56 ], China’s NDC target in 2030, and the “Three-Year Plan of Action for Winning the Blue Sky Defense War” [ 57 ], while considering future uncertainty, we set two restriction scenarios for each objective, as shown in Table 6 , assuming that 70% [ 58 ] of energy-saving contributions are derived from energy-saving technology.
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[Summary: This page describes the different scenarios used in the study, including BAU, CERO (CPS-I and CPS-II), and PERO (CES-I and CES-II). It defines each scenario's assumptions and targets for CO2 and air pollutant emission reductions. The BAU scenario assumes no further implementation of energy-saving and air pollution control measures. CERO scenarios focus on CO2 emission reduction per unit of industrial added value. PERO scenarios focus on emission caps for SO2, NOx, and PM2.5. The page then presents an analysis of synergistic effects under CERO.]
Sustainability 2019 , 11 , 352 11 of 22 Table 6. Description of different scenarios Objective/Scenarios Description BAU Assuming that the level of development of existing technologies will remain unchanged in the next 15 years, energy-saving and air pollution control measures will not be further implemented in the future CERO CPS-I CO 2 emissions target of more than 22% reduction per unit of industrial added value, as compared to the 2015 level by 2020, more than 65% reduction per unit of industrial added value as compared to the 2015 level by 2030 CPS-II The CO 2 emission target in 2020 is the same as that of CPS-I, more than 70% reduction as compared to the 2005 level by 2030 PERO CES-I SO 2 , NOx, and PM 2.5 emission targets of more than 15%, 15%, and 18% reduction compared to the 2015 level by 2020, and more than 7.5%, 7.5%, and 9% reduction compare to the 2020 level by 2030 CES-II SO 2 , NOx, and PM 2.5 emission targets are the same as that of CES-I, and SO 2 , NOx, and PM 2.5 emission targets of more than 15%, 15%, and 18% reduction compared to the 2020 level by 2030 4. Results and Discussion 4.1. Analysis of Synergistic Effects under a Single Objective 4.1.1. Analysis of Synergistic Effects under CERO Because the same emission reduction objectives are described in CPS-I and CPS-II, the change trends of gases under the two scenarios are the same in the near future (2015–2020), as shown in Figure 3 . CO 2 emissions will increase from 1.63 billion tons (Bt) in 2015 to 1.78 Bt in 2020, and the annual growth rate is 1.7%. SO 2 , NOx, and PM 2.5 will increase from 4.79 Mt, 3.53 Mt, and 1.82 Mt in 2015 to 4.82 Mt, 4.05 Mt, and 2.36 Mt in 2020, and the annual growth rates are 0.12%, 2.8%, and 5.4%, respectively In the long-term (2020–2030), the emissions of the four gases will decrease annually. Emissions of CO 2 , SO 2 , NOx, and PM 2.5 will decrease to 1.6 Bt, 3.93 Mt, 3.48 Mt, and 2.12 Mt in 2030 under the scenario of CPS-I, showing decreases of 18%, 32%, 18%, and 2.8% compared to BAU. Because the target of CO 2 emission intensity in 2030 under CPS-II is higher than that of CPS-I, CO 2 emission reductions under CPS-II are higher than that of CPS-I, and the emission reduction of air pollutants is also higher than that of CPS-I. Cumulative emissions of the four gases (CO 2 , SO 2 , NOx, and PM 2.5) under CPS-II will decrease to 1.58 Bt, 3.86 Mt, 3.47 Mt, and 2.12 Mt in 2030, showing decreases of 19%, 33%, 18%, and 2.8% compared to BAU Thus, if CERO is implemented separately, the emissions of three air pollutants will also be reduced The ranking of the synergistical degree of the three air pollutant emission reductions is SO 2 , then NOx, and PM 2.5, and the synergistic effect on PM 2.5 emission reduction under CERO is very weak.
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[Summary: This page presents the analysis of synergistic effects under CERO and PERO. Under CERO, CO2 emissions increase initially before decreasing long-term. Air pollutant emissions follow a similar trend. CPS-II achieves higher emission reductions than CPS-I due to a stricter CO2 target. Under PERO, both air pollutants and CO2 emissions decrease significantly. CO2 emissions under PERO are lower than under CERO. The page also includes Figure 3, showing emissions under CERO, and Figure 4, showing emissions under PERO.]
Sustainability 2019 , 11 , 352 12 of 22 Sustainability 2019 , 11 , x FOR PEER REVIEW 12 of 22 ( a ) CO 2 emissions under different scenarios ( b ) Air pollutant emissions under different scenarios Figure 3. Emissions under CERO. 4.1.2. Analysis of Synergistic Effects under PERO According to the results of optimization, as shown in Figure 4, there is no difference in the scenarios of CES-I and CES-II. In the near future (2015-2020), if only PERO is implemented, the cumulative CO 2 emission will be 1.68 Bt in 2020, showing a decrease of 22% compared to BAU. The emission of SO 2 , NOx, and PM 2.5 will be 4.32 Mt, 3.32 Mt, and 1.51 Mt in 2020, showing decreases of 32%, 29%, and 37% compared with BAU. The amount CO 2 emissions under PERO is 97.1 Mt lower than that of CERO. In the long-term (2020-2030), emissions of the four gases will decrease annually, and the emissions of these gases are same in CES-I and CES-II. Emission of CO 2 , SO 2 , NOx, and PM 2.5 will decrease to 1.52 Bt, 3.48 Mt, 2.84 Mt, and 1.36 Mt in 2030 in both scenarios, showing decreases of 22%, 40%, 33%, and 38%, respectively, compared to BAU. The amount CO 2 emissions under PERO is 67 Mt lower than that of CERO. 1000 1200 1400 1600 1800 2000 2200 2400 2015 2016 2017 2018 2019 2020 2021 2022 2024 2025 2026 2027 2028 2029 2030 CO 2 em ission ( M t) Year BAU-CO 2 CPS-I-CO 2 CPS-II-CO 2 0 1 2 3 4 5 6 7 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Pollutant em ission (Mt) Year BAU-SO 2 CPS-I-SO 2 CPS-II-SO 2 BAU-NOx CPS-I-NOx CPS-II-NOx BAU-PM 2.5 CPS-I-PM 2.5 CPS-II-PM 2.5 Figure 3. Emissions under CERO 4.1.2. Analysis of Synergistic Effects under PERO According to the results of optimization, as shown in Figure 4 , there is no difference in the scenarios of CES-I and CES-II. In the near future (2015–2020), if only PERO is implemented, the cumulative CO 2 emission will be 1.68 Bt in 2020, showing a decrease of 22% compared to BAU The emission of SO 2 , NOx, and PM 2.5 will be 4.32 Mt, 3.32 Mt, and 1.51 Mt in 2020, showing decreases of 32%, 29%, and 37% compared with BAU. The amount CO 2 emissions under PERO is 97.1 Mt lower than that of CERO In the long-term (2020–2030), emissions of the four gases will decrease annually, and the emissions of these gases are same in CES-I and CES-II. Emission of CO 2 , SO 2 , NOx, and PM 2.5 will decrease to 1.52 Bt, 3.48 Mt, 2.84 Mt, and 1.36 Mt in 2030 in both scenarios, showing decreases of 22%, 40%, 33%, and 38%, respectively, compared to BAU. The amount CO 2 emissions under PERO is 67 Mt lower than that of CERO.
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[Summary: This page continues the analysis of synergistic effects under PERO. It notes that the two PERO scenarios (CES-I and CES-II) show no significant difference, indicating that reducing air pollution control intensity after achieving 2020 goals has little impact. The section then transitions to comparing synergistic effects between CERO and PERO, focusing on the degree of synergy in each stage.]
Sustainability 2019 , 11 , 352 13 of 22 Sustainability 2019 , 11 , x FOR PEER REVIEW 13 of 22 ( a ) Future CO 2 emissions under "business as usual " (BAU) and CES ( b ) Emissions of air pollutants under BAU and CES Figure 4. Emissions under PERO. Thus, if only PERO is implemented, the emissions of air pollutants and CO 2 will all be reduced to a large degree. Although the promotion of most end-of-pipe technologies will increase CO 2 emissions due to electricity consumption, it will not change the synergistic emission reduction characteristics of the implementation of PERO on CO 2 as a whole. Although the scenario of CES-II continues the control target of air pollutants in 2020, while the scenario of CES-I relaxes the control of air pollutants compared to 2020, there is no obvious difference in the optimization results in either scenario- This also shows that even if the control intensity of air pollution is reduced in the future, it will not have a significant impact on the environment under the premise of realizing the goals of air pollution control in 2020. 4.2. Comparison of Synergistic Effects between CERO and PERO Based on the comprehensive evaluation model, this section focuses on comparing the degree of synergy of each stage in CERO and PERO. 4.2.1. Comparison of Synergistic Effects in CERO and PERO in the Near Future In the near future (2015-2020), because both scenarios have the same objectives, we use CPS to express CPS-I and CPS-II. Thus, we only compare the three scenarios: BAU, CPS, and CES. The Development of Technologies Portfolio 1000 1200 1400 1600 1800 2000 2200 2400 2015201620172018201920202021202220232024202520262027202820292030 C O 2 em issi on (M t) Year BAU-CO 2 CES-I-CO 2 CES-II-CO 2 0 1 2 3 4 5 6 7 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Pollutant em isison (Mt) Year BAU-SO 2 CES-SO 2 BAU-NOx CES-NOx BAU-PM 2.5 CES-PM 2.5 Figure 4. Emissions under PERO Thus, if only PERO is implemented, the emissions of air pollutants and CO 2 will all be reduced to a large degree. Although the promotion of most end-of-pipe technologies will increase CO 2 emissions due to electricity consumption, it will not change the synergistic emission reduction characteristics of the implementation of PERO on CO 2 as a whole. Although the scenario of CES-II continues the control target of air pollutants in 2020, while the scenario of CES-I relaxes the control of air pollutants compared to 2020, there is no obvious difference in the optimization results in either scenario. This also shows that even if the control intensity of air pollution is reduced in the future, it will not have a significant impact on the environment under the premise of realizing the goals of air pollution control in 2020 4.2. Comparison of Synergistic Effects between CERO and PERO Based on the comprehensive evaluation model, this section focuses on comparing the degree of synergy of each stage in CERO and PERO 4.2.1. Comparison of Synergistic Effects in CERO and PERO in the Near Future In the near future (2015–2020), because both scenarios have the same objectives, we use CPS to express CPS-I and CPS-II. Thus, we only compare the three scenarios: BAU, CPS, and CES.
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[Summary: This page compares synergistic effects in CERO and PERO in the near future (2015-2020). It describes the development of technology portfolios under CPS (CERO) and CES (PERO). To meet CERO, most carbon reduction technologies are rapidly popularized. Under CES, carbon reduction technologies are accelerated. End-of-pipe technologies for SO2 see no major changes, while E5 and E8 for NOx and PM2.5 are accelerated. The page also discusses the emission reductions of CO2 and air pollutants under different scenarios.]
Sustainability 2019 , 11 , 352 14 of 22 The Development of Technologies Portfolio To meet the CERO of 2020, all carbon reduction technologies except G 1, G 7, G 8, G 11, G 16, G 17, and G 20, should be rapidly popularized, and they are set to be comprehensively popularized in 2019. Because there are no constraints on the emissions of air pollutants, end-of-pipe technologies experience no major changes in CPS Compared with CPS, the carbon reduction technologies, aforementioned technologies, and G 17 will be accelerated to development in CES, and will be comprehensively popularized in 2019. For the emission reductions of SO 2 , carbon reduction technologies have more cost-effective advantages than end-of-pipe technologies, so there will be no major changes in the development of end-of-pipe technologies for removing SO 2 . Because the technologies of carbon reduction have less effect on NOx and PM 2.5, E 5 and E 8 will be also accelerated to development under CES, the popularity rate of these two technologies in 2020 are set to be 30% and 46%, respectively Emission Reductions of CO 2 and Air Pollutants As shown in Figure 5 , although the emissions of CO 2 in CPS and CES are significantly lower than BAU, the extent of their decline is different. In 2020, cumulative CO 2 emissions in CES will be 97 Mt lower than that of CPS. From the perspective of CO 2 emission intensity, without considering the emission reduction of non-energy-saving technologies, the emission intensity of CO 2 in CES in 2020 will be 23% lower than in 2015, which fully meets the target of 22% reduction of CERO in 2020 Sustainability 2019 , 11 , x FOR PEER REVIEW 14 of 22 To meet the CERO of 2020, all carbon reduction technologies except G 1, G 7, G 8, G 11, G 16, G 17, and G 20, should be rapidly popularized, and they are set to be comprehensively popularized in 2019. Because there are no constraints on the emissions of air pollutants, end-of-pipe technologies experience no major changes in CPS. Compared with CPS, the carbon reduction technologies, aforementioned technologies, and G 17. will be accelerated to development in CES, and will be comprehensively popularized in 2019. For the emission reductions of SO 2 , carbon reduction technologies have more cost-effective advantages than end-of-pipe technologies, so there will be no major changes in the development of end-of-pipe technologies for removing SO 2 . Because the technologies of carbon reduction have less effect on NOx and PM 2.5, E 5 and E 8 will be also accelerated to development under CES, the popularity rate of these two technologies in 2020 are set to be 30% and 46%, respectively. Emission Reductions of CO 2 and Air Pollutants As shown in Figure 5, although the emissions of CO 2 in CPS and CES are significantly lower than BAU, the extent of their decline is different. In 2020, cumulative CO 2 emissions in CES will be 97 Mt lower than that of CPS. From the perspective of CO 2 emission intensity, without considering the emission reduction of non-energy-saving technologies, the emission intensity of CO 2 in CES in 2020 will be 23% lower than in 2015, which fully meets the target of 22% reduction of CERO in 2020. Figure 5. CO 2 emissions under different scenarios from 2015-2020. Figure 6 shows the emissions of air pollutants under different scenarios in 2020. Although the emissions of the three air pollutants under CPS are obviously lower than that of BAU, their emission trends will increase annually. Considering the emission reduction caused by non-energy-saving technologies, the emissions of the three air pollutants (SO 2 , NOx, and PM 2.5) in 2020 will be 4.16 Mt, 3.78 Mt, and 2.33 Mt, respectively. Obviously, emissions of NOx and PM 2.5 are still higher than that of 2015. Therefore, if only considering the implementation of CERO in the near future, the PERO of 2020 will not be met. 1000 1200 1400 1600 1800 2000 2200 2400 2015 2016 2017 2018 2019 2020 CO 2 emissions (Mt) Year BAU CPS CES Figure 5. CO 2 emissions under different scenarios from 2015-2020 Figure 6 shows the emissions of air pollutants under different scenarios in 2020. Although the emissions of the three air pollutants under CPS are obviously lower than that of BAU, their emission trends will increase annually. Considering the emission reduction caused by non-energy-saving technologies, the emissions of the three air pollutants (SO 2 , NOx, and PM 2.5) in 2020 will be 4.16 Mt, 3.78 Mt, and 2.33 Mt, respectively. Obviously, emissions of NOx and PM 2.5 are still higher than that of 2015. Therefore, if only considering the implementation of CERO in the near future, the PERO of 2020 will not be met.
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[Summary: This page continues the comparison of synergistic effects in the near future. It notes that CO2 emissions are significantly lower under CPS and CES compared to BAU, with CES achieving lower emissions than CPS. Air pollutant emissions under CPS are lower than BAU but increase annually, failing to meet 2020 PERO targets. MAC analysis shows PERO is better than CERO. PERO is recommended for synergistic control of CO2 emissions due to its effectiveness in reducing all pollutants and its cost advantage.]
Sustainability 2019 , 11 , 352 15 of 22 Sustainability 2019 , 11 , x FOR PEER REVIEW 15 of 22 Figure 6. Emissions of air pollutant under different scenarios from 2015-2020. MAC MAC is the cost of reducing one additional unit of gas. For convenient comparison, we converted the emission reductions of the three air pollutants into pollution equivalents, and then calculated the MAC. As shown in Figure 7, the MACs of CO 2 and air pollutant equivalents in 2020 are 1.39 yuan/kgCO 2 and 229 yuan/kgCO 2 under CERO, and 1.07 yuan/kgCO 2 and 133 yuan/kgCO 2 under PERO. Thus, from the perspective of MACs, PERO is better than CERO. In summary, although the implementation of CERO can lead to the emission reductions of the three air pollutants, it has a weak cooperative effect on PM 2.5. Compared to 2015, emissions of air pollutants will be increasing annually, and will not meet the control target of air pollution in 2020. Implementing PERO not only reduces the emissions of CO 2 , but also reduces emissions of other air pollutants. In addition, PERO has the absolute cost advantage. Thus, PERO should be given priority for the synergistical control of CO 2 emissions. ( a ) The marginal abatement cost (MAC) of CO 2 under CES and CPS 0 1 2 3 4 5 6 SO 2 NOx PM 2.5 Em issions ( Mt) Air Pollutants (2015-2020) 2015-CPS 2020-CPS 2015-CES 2020-CES 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 122 275 426 579 732 Marginal abatement costs (y uan/kgCO 2) Cumulative CO 2 emission reductions from 2016 to 2020 (Mt) CES CPS Figure 6. Emissions of air pollutant under different scenarios from 2015-2020 MAC MAC is the cost of reducing one additional unit of gas. For convenient comparison, we converted the emission reductions of the three air pollutants into pollution equivalents, and then calculated the MAC. As shown in Figure 7 , the MACs of CO 2 and air pollutant equivalents in 2020 are 1.39 yuan/kgCO 2 and 229 yuan/kgCO 2 under CERO, and 1.07 yuan/kgCO 2 and 133 yuan/kgCO 2 under PERO. Thus, from the perspective of MACs, PERO is better than CERO In summary, although the implementation of CERO can lead to the emission reductions of the three air pollutants, it has a weak cooperative effect on PM 2.5. Compared to 2015, emissions of air pollutants will be increasing annually, and will not meet the control target of air pollution in 2020 Implementing PERO not only reduces the emissions of CO 2 , but also reduces emissions of other air pollutants. In addition, PERO has the absolute cost advantage. Thus, PERO should be given priority for the synergistical control of CO 2 emissions Sustainability 2019 , 11 , x FOR PEER REVIEW 15 of 22 Figure 6. Emissions of air pollutant under different scenarios from 2015-2020. MAC MAC is the cost of reducing one additional unit of gas. For convenient comparison, we converted the emission reductions of the three air pollutants into pollution equivalents, and then calculated the MAC. As shown in Figure 7, the MACs of CO 2 and air pollutant equivalents in 2020 are 1.39 yuan/kgCO 2 and 229 yuan/kgCO 2 under CERO, and 1.07 yuan/kgCO 2 and 133 yuan/kgCO 2 under PERO. Thus, from the perspective of MACs, PERO is better than CERO. In summary, although the implementation of CERO can lead to the emission reductions of the three air pollutants, it has a weak cooperative effect on PM 2.5. Compared to 2015, emissions of air pollutants will be increasing annually, and will not meet the control target of air pollution in 2020. Implementing PERO not only reduces the emissions of CO 2 , but also reduces emissions of other air pollutants. In addition, PERO has the absolute cost advantage. Thus, PERO should be given priority for the synergistical control of CO 2 emissions. ( a ) The marginal abatement cost (MAC) of CO 2 under CES and CPS 0 1 2 3 4 5 6 SO 2 NOx PM 2.5 Em issions ( Mt) Air Pollutants (2015-2020) 2015-CPS 2020-CPS 2015-CES 2020-CES 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 122 275 426 579 732 Marginal abatement costs (y uan/kgCO 2) Cumulative CO 2 emission reductions from 2016 to 2020 (Mt) CES CPS Figure 7. Cont.
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[Summary: This page compares synergistic effects between CERO and PERO in the long term, based on implementing PERO in the near future. It analyzes technology development under CES-CPS (PERO before 2020, CERO after) and CES. Under CES-CPS, most technologies are comprehensively popularized by 2022. Under CES, G20 is accelerated. CO2 emission reduction is lower under CES-CPS than CES. Air pollutant emissions are lower under CES-CPS than CES.]
Sustainability 2019 , 11 , 352 16 of 22 Sustainability 2019 , 11 , x FOR PEER REVIEW 16 of 22 ( b ) The MAC of air pollutant equivalents under CES and CPS Figure 7. The MAC of air pollutant equivalents under CES and CPS. 4.2.2. Comparison of Synergistic Effects between CERO and PERO in the Long Term Based on the best synergistical scheme for the near future—the implementation of PERO to cocontrol CO 2 emissions—we will further analyze the development of the technological portfolio in the long-term. Although the targets for 2030 under the two scenarios of CERO are different, there are no obvious differences in optimization results. This is because the development of carbon reduction technologies has been accelerated to a high level prior to 2020 under PERO. CES-CPS represent the scenarios of implementing PERO before 2020 and implementing CERO after 2020. Next, we compare the synergistical effects of the two scenarios of CES-CPS and CES in the long-term. The Development of Technology Mix in the Long-Term Under CES-CPS, to meet CERO of 2030, all technologies, except G 1 and G 20, are set to be comprehensively popularized in 2022. G 1 will be comprehensively popularized in 2030, while the end-of-pipe technologies will experience no major changes. Under CES, in addition to maintaining the development level of technologies in 2020, G 20 will be accelerated to development in the latter period, and will be comprehensively popularized by 2029. The Emission Reduction Potentials of CO 2 and Air Pollutants under CERO and PERO From the long-term perspective, as shown in Figure 8, the emission reduction of CO 2 under CES- CPS is lower than that of CES. The emissions of CO 2 under CES and CES-CPS in 2030 will be 1.52 Bt and 1.48 Bt, respectively. In terms of the emissions of air pollutants, as shown Figure 9, the emissions of SO 2 , NOx, and PM 2.5 in 2030 under CES will be 3.48 Mt, 2.84 Mt, and 1.36 Mt, respectively. The emission of these air pollutants in 2030 under CES-CPS will be 0.87 Mt, 2.16 Mt, and 0.67 Mt, respectively, which are 2.61 Mt, 0.67 Mt and 0.7 Mt lower than that of CES, respectively. 0 50 100 150 200 250 0 730 1460 2191 2921 3652 4382 5113 5843 Marginal abatement costs (y uan/kgpe) Cumulative pullutant emission reductions from 2016 to 2020 (Mt) CES CPS Figure 7. The MAC of air pollutant equivalents under CES and CPS 4.2.1.4. Comparison of Synergistic Effects between CERO and PERO in the Long Term Based on the best synergistical scheme for the near future—the implementation of PERO to co-control CO 2 emissions—we will further analyze the development of the technological portfolio in the long-term. Although the targets for 2030 under the two scenarios of CERO are different, there are no obvious differences in optimization results. This is because the development of carbon reduction technologies has been accelerated to a high level prior to 2020 under PERO. CES-CPS represent the scenarios of implementing PERO before 2020 and implementing CERO after 2020. Next, we compare the synergistical effects of the two scenarios of CES-CPS and CES in the long-term The Development of Technology Mix in the Long-Term Under CES-CPS, to meet CERO of 2030, all technologies, except G 1 and G 20, are set to be comprehensively popularized in 2022. G 1 will be comprehensively popularized in 2030, while the end-of-pipe technologies will experience no major changes Under CES, in addition to maintaining the development level of technologies in 2020, G 20 will be accelerated to development in the latter period, and will be comprehensively popularized by 2029 The Emission Reduction Potentials of CO 2 and Air Pollutants under CERO and PERO From the long-term perspective, as shown in Figure 8 , the emission reduction of CO 2 under CES-CPS is lower than that of CES. The emissions of CO 2 under CES and CES-CPS in 2030 will be 1.52 Bt and 1.48 Bt, respectively In terms of the emissions of air pollutants, as shown Figure 9 , the emissions of SO 2 , NOx, and PM 2.5 in 2030 under CES will be 3.48 Mt, 2.84 Mt, and 1.36 Mt, respectively. The emission of these air pollutants in 2030 under CES-CPS will be 0.87 Mt, 2.16 Mt, and 0.67 Mt, respectively, which are 2.61 Mt, 0.67 Mt and 0.7 Mt lower than that of CES, respectively.
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[Summary: This page continues the comparison of synergistic effects in the long term. It discusses the MAC under CES and CES-CPS, noting that the effects of energy-saving are apparent under CES-CPS. In 2030, the MACs of CO2 and air pollutant equivalents are lower under CES-CPS. The page acknowledges uncertainties in the study, including the lack of specific CO2 emission intensity targets and the potential impact of new technologies. It concludes with a summary of the implementation scheme and policy discussion.]
Sustainability 2019 , 11 , 352 17 of 22 Sustainability 2019 , 11 , x FOR PEER REVIEW 17 of 22 Figure 8. CO 2 emissions under different scenarios in the long-term period. Figure 9. The emission of air pollutants under different scenarios. MAC With the development of technology, the benefits of energy-saving will also increase annually in both scenarios. Compared with CES, the effects of energy-saving of CES-CPS are apparent. In 2030, the MACs of CO 2 and air pollutant equivalents are 0.55 yuan/kgCO 2 and 59.8 yuan/kgpe under CES, and 0.02 yuan/kgCO 2 and 2.7 yuan/kgpe under CES-CPS, as shown in Figure 10. Uncertainty still exists in this study. For CERO, there are no quantitative objectives for CO 2 emission intensity of the 14 th and 15 th "five-year plans" in the steel industry. Similarly, for the goal of air pollutants control, the Chinese government has only issued the "Three-year Action Plan to Win the Blue Sky Defense War". Therefore, changes in the above factors in the future will have an impact on the optimization results. In addition, the emergence of new technologies will also affect the accuracy of the results of this study. 1000 1200 1400 1600 1800 2000 2200 2400 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 CO 2 emission (Mt) Year BAU-CO 2 CES-CO 2 CES-CPS-CO 2 0 1 2 3 4 5 SO 2 NOx PM 2.5 Em issions(Mt) Air Pollutnats 2020-CES 2030-CES 2020-CES-CPS 2030-CES-CPS Figure 8. CO 2 emissions under different scenarios in the long-term period Sustainability 2019 , 11 , x FOR PEER REVIEW 17 of 22 Figure 8. CO 2 emissions under different scenarios in the long-term period. Figure 9. The emission of air pollutants under different scenarios. MAC With the development of technology, the benefits of energy-saving will also increase annually in both scenarios. Compared with CES, the effects of energy-saving of CES-CPS are apparent. In 2030, the MACs of CO 2 and air pollutant equivalents are 0.55 yuan/kgCO 2 and 59.8 yuan/kgpe under CES, and 0.02 yuan/kgCO 2 and 2.7 yuan/kgpe under CES-CPS, as shown in Figure 10. Uncertainty still exists in this study. For CERO, there are no quantitative objectives for CO 2 emission intensity of the 14 th and 15 th "five-year plans" in the steel industry. Similarly, for the goal of air pollutants control, the Chinese government has only issued the "Three-year Action Plan to Win the Blue Sky Defense War". Therefore, changes in the above factors in the future will have an impact on the optimization results. In addition, the emergence of new technologies will also affect the accuracy of the results of this study. 1000 1200 1400 1600 1800 2000 2200 2400 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 CO 2 emission (Mt) Year BAU-CO 2 CES-CO 2 CES-CPS-CO 2 0 1 2 3 4 5 SO 2 NOx PM 2.5 Em issions(Mt) Air Pollutnats 2020-CES 2030-CES 2020-CES-CPS 2030-CES-CPS Figure 9. The emission of air pollutants under different scenarios MAC With the development of technology, the benefits of energy-saving will also increase annually in both scenarios. Compared with CES, the effects of energy-saving of CES-CPS are apparent. In 2030, the MACs of CO 2 and air pollutant equivalents are 0.55 yuan/kgCO 2 and 59.8 yuan/kgpe under CES, and 0.02 yuan/kgCO 2 and 2.7 yuan/kgpe under CES-CPS, as shown in Figure 10 . Uncertainty still exists in this study. For CERO, there are no quantitative objectives for CO 2 emission intensity of the 14 th and 15 th “five-year plans” in the steel industry. Similarly, for the goal of air pollutants control, the Chinese government has only issued the “Three-year Action Plan to Win the Blue Sky Defense War”. Therefore, changes in the above factors in the future will have an impact on the optimization results. In addition, the emergence of new technologies will also affect the accuracy of the results of this study.
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[Summary: This page summarizes the choice of implementation scheme under the two-stage dynamic optimization model. It states that in the short term, PERO has better synergistic effects, while in the long term, CERO is better. It then presents a policy discussion based on the results, proposing three suggestions. These include implementing a variety of control measures, prioritizing PERO in the near future and CERO in the long term, and strengthening policy support for technology.]
Sustainability 2019 , 11 , 352 18 of 22 Sustainability 2019 , 11 , x FOR PEER REVIEW 18 of 22 ( a ) The MAC of CO 2 under CES and CPS ( b ) The MAC of air pollutant equivalents under CES and CPS Figure 10. The MACs under CES and CPS. 4.3. The Choice of Implementation Scheme under the Two-Stage Dynamic Optimizaiton Model In summary, there are synergistic effects between CERO and PERO in different periods, but the synergistic effects are different. In the short-term period, the synergistic effects of PERO are better than those of CERO (i.e., under PERO, three air pollutants can be reduced significantly and CO 2 can also be reduced in a large extent at the same time), while in the long-term, the synergistic effects of CERO are better than those of PERO. 4.4. Policy Discussion Based on the above results, three suggestions are proposed in this paper: (1) To alleviate the dual pressures of the steel industry in coping with climate change and environmental protection, a variety of control measures should be implemented. Each emission reduction measure has its own focus. Thus, the coordinated implementation of various measures can play a complementary role for maximizing the advantages of different strategies. 0 0.1 0.2 0.3 0.4 0.5 0.6 0 151 304 455 608 761 912 Marginal abatement cost (y uan/kg CO 2 Cumulative CO 2 emission reductions from 2016 to 2020 (Mt) CES-CPS CES 0 10 20 30 40 50 60 70 0 730 1460 2191 2921 3652 4382 5113 5843 6574 7304 8035 Marginal abatement cost (y uan/kgpe) Cumulative pollutant emission reductions from 2016 to 2020 (Mt) CES-CPS CES Figure 10. The MACs under CES and CPS 4.2.2. The Choice of Implementation Scheme under the Two-Stage Dynamic Optimizaiton Model In summary, there are synergistic effects between CERO and PERO in different periods, but the synergistic effects are different. In the short-term period, the synergistic effects of PERO are better than those of CERO (i.e., under PERO, three air pollutants can be reduced significantly and CO 2 can also be reduced in a large extent at the same time), while in the long-term, the synergistic effects of CERO are better than those of PERO 4.2.3. Policy Discussion Based on the above results, three suggestions are proposed in this paper: (1) To alleviate the dual pressures of the steel industry in coping with climate change and environmental protection, a variety of control measures should be implemented. Each emission
[[[ p. 19 ]]]
[Summary: This page continues the policy discussion, emphasizing the importance of implementing the correct synergistic scheme to maximize emission reductions. It suggests that PERO can alleviate environmental pressure and have a strong synergistic effect on CO2 emissions in the near future, while CERO can ensure the realization of NDC goals in the long term. The page then presents the conclusions of the study, summarizing the findings on synergistic effects between CERO and PERO and the recommended implementation strategies.]
Sustainability 2019 , 11 , 352 19 of 22 reduction measure has its own focus. Thus, the coordinated implementation of various measures can play a complementary role for maximizing the advantages of different strategies (2) The steel industry should prioritize the implementation of PERO and the synergistic emission control of CO 2 in the near future and prioritize the implementation of CERO and the synergistic emission control of air pollutants in the long-term. Although these two objectives have synergistic effects on each other in the implementation process, the degree of synergy is quite different, so the implementation of the correct synergistic scheme will play a multiplier role in reducing the emissions of CO 2 and three air pollutants. Thus, in the framework of this paper, implementing PERO could not only alleviate the current environmental pressure, but also have a strong synergistic effect on CO 2 emissions in the near future, and with the gradual improvement of environmental governance, implementing CERO will ensure the realization of NDC goals in China in the long-term (3) Policy support of technology should be strengthened. Although accelerating technological development will lead to a higher initial investment, increasing the benefits of energy-saving with the popularization of technology will offset and may even exceed the input cost, transforming it into income in the long run. Therefore, accelerating the popularization of technology is not only conducive to greatly reducing the emissions of various gases, but also enables enterprises to enjoy the benefits of energy-saving incomes as soon as possible 5. Conclusions The implementation schemes of synergistic emissions reduction of CO 2 and air pollutants in China’s steel industry are studied in this paper. Considering 20 types of carbon emission reduction technologies and eight types of end-of-pipe technologies in the steel industry, a non-linear comprehensive evaluation model including co-control of CO 2 emission reduction intensity targets (CERO), and air pollutants emission targets (PERO) in 2020 and 2030 was established. Through the emissions predictions of CO 2 and three air pollutants (SO 2 , NOx, and PM 2.5) in the steel industry and the analysis of synergistic effects under different emission reduction targets, synergistic effects between CERO and PERO were found. We compared the implementation effects of a single objective from two aspects: emission reductions of four gases and MACs. From the results of this study, in the near future (2015-2020), the intensity of carbon emission reduction can be reduced by 23% by the implementation of PERO, which can fully meet the target of carbon emission reduction by 2020. At the same time, the marginal abatement cost of CO 2 and air pollutant equivalents are 23% and 11% lower than that of CERO, respectively. On this basis, we have suggested the implementation of CERO in the long-term period (2020–2030), which can ensure the realization of China’s NDC goals while also ensuring environmental improvement at a lowest cost. The marginal abatement cost of CO 2 and air pollutant equivalents are 96% and 95% lower than that of PERO, respectively Author Contributions: Conceptualization, H.L., X.T. and J.G.; Methodology, H.L., X.T. and J.G.; Investigation, H.L., K.Z. and C.H.; Data Curation, H.L.; Writing—Original Draft Preparation, H.L.; Supervision, X.T. and J.G.; Project Administration, X.T. and J.G Funding: This work is supported by National Natural Science Foundation of China (71573249), the Key Task Project of Institutes of Science and Development of Chinese Academy of Sciences (Y 02015003), the Clean Development Mechanism Fund of China (2014091), the Project-Impact and Adaptation of Climate Change in Major Economies of the Belt and Road (2018 YFA 0606500), and National Natural Science Foundation of China (71801212) Acknowledgments: Thanks to the comments and suggestions of the two reviewers and the editors, the quality of this article has been further improved Conflicts of Interest: The authors declare no conflict of interest.
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[Summary: This page provides a list of references used in the study, citing various articles, reports, and online resources related to carbon emissions, air pollution, energy efficiency, and the steel industry in China.]
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