AIM/End-use Model for Selecting of Low-Carbon Technology in Indonesia’s Iron and Steel Industry

An Integrated Analysis on the Synergistic Reduction of Carbon and Pollution Emissions from China’s Iron and Steel Industry

The Hu-Bao-O-Yu urban agglomeration is an important energy exporting and high-end chemical base in China, and is an important source of carbon emissions in China. The early achievement of peak carbon emissions in this region is particularly crucial to achieving the national carbon emission reduction targets. However, there is a lack of multi-factor system dynamics analysis of resource-dependent urban agglomerations in Northwest China, as most studies have focused on single or static aspects of developed urban agglomerations. This paper analyses the relationship between carbon emissions and their influencing factors, constructs a carbon emission system dynamics model for the Hu-Bao-O-Yu urban agglomeration, and sets up different single regulation and comprehensive regulation scenarios to simulate and predict the carbon peak time, peak value, and emission reduction potential of each city and urban agglomeration under different scenarios. The results show that: (1) Hohhot and Baotou are expected to reach peak carbon by 2033 and 2031 respectively, under the baseline scenario, while other regions and the urban agglomeration will not be able to reach peak carbon by 2035. (2) Under single regulation scenarios, the effect of factors other than the energy consumption varies across cities, but the energy consumption and environmental protection input are the main factors affecting carbon emissions in the urban agglomeration. (3) A combination of the economic growth, industrial structure, energy policy, environmental protection, and technology investment is the best measure to achieve carbon peaking and enhance the carbon emission reduction in each region as soon as possible. In the future, we need to coordinate the economic development, energy structure optimisation and transformation, low-carbon transformation of industry, strengthen research on carbon sequestration technology, and further increase the investment in environmental protection to make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration with an optimal emission reduction.

The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China. Thus, exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures, which is of great significance for the realization of low-carbon economic development. This study constructed a spatialization model of carbon emissions based on land use, night lighting, and provincial energy consumption data； explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis； and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path. The results showed that, firstly, the estimated results at the prefectural city level of the carbon emission spatialization model constructed in this study with multi-source data could reach an R2 of 0.92 for a linear fit. Secondly, the total carbon emissions in the farming-pastoral ecotone increased from 176.29 million tons in 1995 to 1 014.51 million tons in 2020. However, the carbon emission intensity and growth rate both decreased, which was related to adjusting the energy structure and improving energy efficiency. Regarding spatial distribution, the cities with high carbon emissions over time were Datong, Baotou, and Yulin in order. Thirdly, the carbon emissions in the study area showed a significant global spatial positive correlation at the county level, with the hot spots mainly located at the junction of Shanxi, Shaanxi, and Inner Mongolia, while the cold spots were extended from Yanan City to Qingyang and Guyuan City after 2010. Finally, based on the differences in carbon emission efficiency and reduction potential, cities could be classified into four types： "high-efficiency and high potential," "low-efficiency and high potential," "high-efficiency and low potential," and "low-efficiency and low potential" to implement targeted emission reduction strategies.

Low-carbon production of iron and steel: Technology options, economic assessment, and policy

The present research is aimed at contributing to the Latvian national climate policy development by projecting total GHG emissions up to 2030, by evaluating the GHG emission reduction path in the non-ETS sector at different targets set for emissions reduction and by evaluating the obtained results within the context of the obligations defined by the EU 2030 policy framework for climate and energy. The method used in the research was bottom-up, linear programming optimisation model MARKAL code adapted as the MARKAL-Latvia model with improvements for perfecting the integrated assessment of climate policy. The modelling results in the baseline scenario, reflecting national economic development forecasts and comprising the existing GHG emissions reduction policies and measures, show that in 2030 emissions will increase by 19.1 % compared to 2005. GHG emissions stabilisation and reduction in 2030, compared to 2005, were researched in respective alternative scenarios. Detailed modelling and analysis of the Latvian situation according to the scenario of non-ETS sector GHG emissions stabilisation and reduction in 2030 compared to 2005 have revealed that to implement a cost effective strategy of GHG emissions reduction first of all a policy should be developed that ensures effective absorption of the available energy efficiency potential in all consumer sectors. The next group of emissions reduction measures includes all non-ETS sectors (industry, services, agriculture, transport, and waste management).

<p indent=0mm>Cities account for more than 70% of global carbon emissions and play an important role in mitigating climate change and achieving carbon peak and carbon neutrality. As the Paris Agreement emphasizes the need to reach global peaking of greenhouse gas emissions as soon as possible, it is significant to predict carbon emissions at the city level. However, the current COVID-19 pandemic has dramatically impacted global socioeconomic development and carbon emissions, downplaying the reference value for most urban carbon emission prediction models. In fact, existing studies on urban carbon emission prediction have also suffered from some shortcomings, such as unclear analyses of the impact of the pandemic, single scenario prediction, unified setting of growth rates, and failure to provide decision support for the government’s carbon peak work. Therefore, a multi-scenario study on urban carbon emission prediction and carbon peak in the post-pandemic period would provide local governments with scientific data to make their carbon peak action plan. To that end, we set five-carbon emission scenarios: bussiness as usual (BAU), high emissions (HE), extremely high emissions (EHE), low emissions (LE) and extremely low emissions (ELE). Based on the Monte Carlo method, we adjust the probabilities of different periods and different carbon emission scenarios to simulate uncertain evolution of carbon emissions as well as carbon emission reduction. Combining with multi-scenario analyses with the Mann-Kendall trend test and Theil Sen’s trend slope estimation method, we predict carbon emissions of the Pearl River Delta Urban Agglomeration (PRD) from 2021 to 2035 and analyze the evolution path of PRD’s carbon emissions as well as its potential for carbon peak and carbon emission reduction from 2006 to 2035. Discussions are made on the possibility of achieving conditional areas’ carbon peak goal in 2025 in Guangdong and China’s carbon peak goal in 2030. We find that: (1) Carbon emissions of PRD increased rapidly from 2006 to 2016. Dynamic simulation shows that carbon emissions a significant peak in 2020 and decrease to 248.85 M~270.06 Mt in 2035. Carbon intensity decreases by 84.18%–85.21% from 2006 to 2035. Based on the emission reduction of the BAU scenario, the cumulative carbon emission reduction potential of the LE scenario and ELE scenario is as high as 304.86 M and 587.22 Mt from 2021 to 2035. Carbon emission reduction potential based on dynamic simulation of random combination scenario is between −81.68 and 128.25 Mt, with a probability of 67.65% to achieve further emission reduction. The probability of reducing 27.44 Mt carbon emissions is the largest. (2) Shenzhen, Zhuhai, Huizhou and Dongguan are four cities that show an inverted “U” shaped evolution path to achieve carbon peak. All of them reach the carbon peak no later than 2020. From 2006 to 2035, especially after the carbon peak, carbon emissions of these cities will decrease significantly. Their carbon emissions will reduce by 14.15 M–15.40 Mt, 9.17 M–9.94 Mt, 24.07 M–26.08 Mt and 22.36 M–24.24 Mt in 2035, respectively. The cumulative carbon emission reduction potential from 2021 to 2035 is −7.99 M–8.69 Mt, −3.48 M–4.87 Mt, −5.97 M–15.39 Mt and −8.77 M–12.62 Mt, respectively. However, being earlier to reach a carbon peak reduces their carbon emission reduction potential from 2021 to 2035. (3) Guangzhou, Foshan, Zhongshan, Jiangmen and Zhaoqing are five cities that could potentially reach carbon peaks but with divergent evolution paths. Some scenarios are at risk of not reaching a carbon peak. The possibility for Guangzhou, Foshan and Zhongshan to achieve the carbon peak target of conditional areas in Guangdong Province in 2025 is more than 96.01%, while that for Jiangmen and Zhaoqing is less than 20.08%. Moreover, there is a possibility of 2.04% for Jiangmen and Zhaoqing not to reach a carbon peak. In 2035, the emission reduction of the five cities will be 56.90 M–61.87 Mt, 44.35 M–48.16 Mt, 23.92 M–25.91 Mt, 33.78 M–36.58 Mt and 20.15 M–21.88 Mt, respectively. The cumulative carbon emission reduction potential of these cities from 2021 to 2035 is significant, which is −23.75M–26.60 Mt, −17.51 M–<sc>22.17 Mt,</sc> −6.64 M–12.19 Mt, −7.57 M–17.82 Mt and −3.86 M–11.79 Mt, respectively. (4) Being earlier to reach a carbon peak is conducive for cities to reduce carbon emissions. The curve of cumulative carbon emission reduction potential shows that the marginal potential of carbon emission reduction increases with time. So early adoption of emission reduction measures and early realization of carbon peak will promote carbon emission reduction. When making action plans for carbon peak, we should prevent cities from reaching false carbon peak during the platform period, pay attention to the demonstration and acceleration effect of carbon peak cities with relatively high carbon emissions, and explore the carbon emission reduction potential of cities that have difficulties in reaching carbon peak by optimizing their energy structure and utilization efficiency.

Technical Development and Prospect for Collaborative Reduction of Pollution and Carbon Emissions from Iron and Steel Industry in China

Faced with increasingly strict carbon emission control, high-emission enterprises need scientific and rational management systems and methods to strengthen carbon emission reduction management. Among the many management systems and methods, the carbon budget has become an effective emission reduction management tool, allowing the planning of carbon emissions and emission reduction activities and rational arrangement of economic inputs. However, judging from the research status and business practices in China and abroad, there is no general carbon budget system to guide the development of carbon emission and emission reduction activities. Based on this background, this paper first attempts to construct an enterprise carbon budget system comprising four sub-budgets: carbon emission, carbon emission reduction and cost, carbon emission rights trading, and carbon emission reduction net profit/loss. It draws on the idea of interactive control to consider the impact of changes in carbon prices, energy prices, and policy guidelines on carbon emission reductions and losses. A carbon budget management system based on interactive control is then constructed and applied to China National Aviation Holding Air China Group (AC Aviation). The research results show that the carbon budget system based on interactive control can dynamically adjust carbon emission reduction behavior based on changes in carbon and energy prices to make carbon budgeting a more viable carbon reduction tool and institutional arrangement.

In recent years, the issues related to carbon emissions and environment have attracted extensive attentions. Considering four scenarios (the energy conversion, energy capital savings and loans, energy exports and cement production carbon emissions), this paper adopts the energy consumption method and input-output method to analyze China’s carbon emissions structure on the supply-side and demand-side of energy, and finally provides policy recommendations for China’s structural emission reduction. The results show that, if the four influencing factors were not considered, the measurement of carbon emissions from the final demand was 44.91% higher than the baseline scenario, 12.36% lower than the baseline scenario from intermediate demand, and 10.23% lower than the baseline scenario from the total. For China’s carbon emissions structure on the supply-side of energy, the carbon emissions from high-carbon energy, represented by raw coal, accounted for 66.805% of the total energy-related carbon emissions, while the carbon emissions from low-carbon energy, represented by natural gas, only accounted for 2.485%. For China’s carbon emissions structure on the demand-side of energy, the carbon emissions from intermediate demand (enterprise production) accounted for more than 95% of total energy-related carbon emissions, while the carbon emissions from final demand (residents and government use) accounted for less than 5%. For each specific industry in intermediate demand for energy, the heavy industry, electric power, fossil energy, and chemical industry have high carbon emissions and low carbon emissions efficiency. However, the agriculture, construction, light industry, and service are the opposite. Finally, we provide policy recommendations for improving the accuracy of carbon emissions measurement and carbon emissions efficiency.

Based on the analysis of carbon emission sources in steel manufacturing process, the status quo and the characteristics of GHG emission in the steel industry are analyzed. It is concluded that CO₂ is the major greenhouse gas that contributes to greenhouse effect and it is mainly caused by energy consumption. As there are many CO₂ emission calculation methods for the steel industry or plants, involving aspects such as direct emission, indirect emission, and credits, it should be noted that it makes little sense to compare CO₂ emission indexes from different sources. Based on the estimation of direct CO₂ emissions in the steel industry in China from 1991 to 2008, it is indicated that the specific direct CO₂ emission per ton steel is decreased from 3.29t in 1991 to 1.92t in 2008, which shows that energy-saving and emission reduction in the Chinese steel industry has made significant progress. Besides, this paper introduces international developments in low carbon technologies, such as ULCOS, COURSE 50, etc.. Meanwhile, the low-carbon technologies, mainly the secondary energy utilization technologies, and CO₂ emission reduction potential during the "Twelfth Five-year Plan" in China are analyzed. This paper predicts that, compared with the specific CO₂ emission per ton steel in 2005, the figure in 2015 will be reduced by 104.01kg. Finally, GHG emission reduction measures and roadmap in Chinese steel industry are put forward, and some policies are suggested.

The emission of greenhouse gases poses enormous pressure on current carbon emissions and carbon reduction. Accurate quantification of carbon emissions from coal-fired power plants is of great significance for achieving the dual carbon goal. To enable enterprises to better understand their carbon emissions, this study constructs a carbon emission model and carbon emission data accounting model for coal-fired power plants. Case data calculations and a carbon emission reduction analysis were conducted. The experiment showcases that the carbon sensitivity of the inner side of the boiler under control conditions is higher than that of the operating parameters controlled on the inner side of the steam turbine, with a maximum total value of 16.67 g/MJ; the annual average low calorific value of coal remains between 16,000 kJ/kg; the activity level of coal remains between 30,000 TJ; and the oxidation probability of coal char during combustion fluctuates, with a maximum of 99.8%. In the calculation of coal-fired carbon emissions, the fitting difference between the emissions of generator unit 1 and generator unit 2 is maintained within 2%. Overall, the CO2 emissions of power plants involved in the study are generally high. The model built through this study has well analyzed the carbon emissions of power plants. It is of great significance for the actual carbon emission reduction of coal-fired power plants.

As the world's largest country regarding energy consumption and carbon emissions， analyzing China's carbon emissions and emission reduction potential is essential to the fight against global climate change. This study constructs the LEAP-China model to forecast and analyze China's carbon emissions and emission reduction potential in three dimensions： primary energy， end-use industries， and carbon emission contribution. The conclusions are as follows： ① Except for the baseline scenario， the industrial structure emission reduction， technological progress， energy structure emission reduction， and blueprint scenarios were all able to realize the goal of "peaking by 2030." ② From 2022 to 2060， carbon emissions from all industries except industry were declining. ③ The carbon emissions of various industrial sectors varied significantly according to their energy consumption， with chemicals &gt; other industries &gt; non-metallic mineral products industry &gt; ferrous metal smelting and rolling processing industry &gt; non-ferrous metal smelting and rolling processing industry &gt; paper and paper products industry. ④ The optimization of energy structure had apparent emission reduction effects in the short term； the optimization of industrial structure was a continuous driving force for carbon emission reduction， and technological progress was a long-term driving force for carbon emission reduction. The study can provide a decision-making basis for China to realize the medium- and long-term carbon emission reduction path.

In light of global climate crisis, it is imperative to implement measures aimed at reducing energy consumption and carbon emissions in the iron and steel industry. This study focuses on the development of innovative methodologies for minimizing energy consumption and carbon emissions during steel production, with particular emphasis on the synergistic optimization of both long‐ and short‐flow steelmaking processes. A carbon flow model has been constructed to analyze the material and energy flows associated with long‐process (BF–BOF) and short‐process (electric arc furnace (EAF)) steelmaking, as well as to assess the potential for carbon reduction through industrial symbiotic technologies. The findings illustrate that in the S2 scenario, where the proportion of EAF steel is increased to 50%, carbon emissions are reduced to 1,464.12 kg tcs, representing an 18.9% decrease. This reduction is lower than that achieved by traditional long‐process steelmaking; and the industrial symbiosis technologies, such as chemical production and coke oven gas hydrogen production, can facilitate an additional reduction in carbon emissions of 41.33 kg tcs. This study offers a new pathway and reference for the green transformation of the iron and steel industry.

The steel industry plays a critical role in advancing green and low-carbon development. This study introduces the Integrated Assessment Model for Energy, Pollutant Emissions, and Carbon Emissions at the city level （iPCEM-city）, with a case study focusing on the steel industry in Anyang. By simulating different scenarios to evaluate pollution and carbon emission effects, as well as air quality improvement benefits, this study proposes future development pathways for the steel industry in Anyang from four perspectives： industrial structure adjustment, production capacity control, technology promotion, and policy incentives. Key findings include： ① The ranking of integrated mitigation benefits across scenarios was： industrial integration &gt; synergy orientation &gt; decarbonization orientation &gt; pollution reduction orientation &gt; baseline scenario. ② Under the comprehensive pathway, by 2025, 2030, and 2035, crude steel output was projected to decrease by 26%, 32%, and 42%, respectively, compared to 2020 levels； coal consumption was projected to decline by 34%, 51%, and 68%； and carbon emissions would reduce by 27%, 39%, and 54%. Notably, emissions of SO2, NOx, and PM would also see significant reductions. ③ The industrial integration scenario demonstrated the most pronounced benefits for air quality improvement, with PM2.5 mass concentrations forecasted to drop to 53 μg·m-3 in 2025 and 49 μg·m-3 in 2035. ④ In all scenarios, the overall carbon emission reduction costs for BF-BOF were generally higher than those for EAF. As the proportion of production capacity covered by ultra-low emissions increased, the total emission reduction costs for ultra-low emissions gradually decreased across all scenarios. This research provides a scientific basis for formulating detailed strategies for pollution and carbon emission reduction at the micro-scale for steel industries in cities like Anyang that are characterized by coal dependency, heavy industry, slow transition, and difficulty in air-quality improvement. It also serves as a case reference for the adaptation and application of macro-pathway strategies for the steel industry at the city micro-scale.

This paper establishes the framework of influencing factors of carbon emission reduction efficiency from two aspects of driving factors and braking factors and makes theoretical analysis. The panel data model is used to construct the model of influencing factors of carbon emission reduction efficiency. Collecting relevant data from 30 regions in China from 2011 to 2016 and selecting reasonable indicators，the impact of industrial structure, carbon rights market and technological innovation on carbon emission reduction efficiency have been empirically analyzed. According to the analysis conclusion, further calculate the energy efficiency of each region, and then come to carbon dioxide emission reduction potential, energy-saving space and emission reduction space of different regions. The concept of carbon emission decoupling is introduced to calculate the decoupling index of four stages in China and analyze the change of decoupling degree. The results show that: (1) The industrial structure greatly affects the efficiency of carbon emission reduction. The increase of the proportion of the secondary industry will increase the rate of change of carbon emission and reduce the efficiency of carbon emission reduction. The establishment of carbon rights market and improvement of technological innovation ability can effectively improve the efficiency of carbon emission reduction; (2) China's regional energy efficiency is not balanced. There is still great potential for carbon reduction, energy saving and emission reduction; (3) The stage decoupling index of different regions is different, but the degree of decoupling is strengthened year by year. The space of emission reduction is gradually reduced, indicating that the overall trend of economic growth on the pressure of emission reduction eased.