Strategies for Carbon Reduction in China's Aluminum  Industry: An LMDI-based Decomposition and Sensitivity Analysis Framework

doi:10.21203/rs.3.rs-4943613/v1

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Strategies for Carbon Reduction in China's Aluminum Industry: An LMDI-based Decomposition and Sensitivity Analysis Framework

https://doi.org/10.21203/rs.3.rs-4943613/v1

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In this study, we harnessed Material Flow Analysis (MFA) to meticulously quantify the substance flows across the mining, smelting, electrolysis, Processing and manufacturing, Recycling management, and regeneration stages of China's aluminum industry from 1990 to 2022. Concurrently, we dissected the carbon emissions of primary and secondary aluminum products employing the Logarithmic Mean Divisia Index (LMDI) approach. The LMDI framework facilitated the decomposition of emissions into five endogenous variables: emission factors, energy structure, energy intensity, product structure, and total production. Our analysis foregrounds the principal driving forces shaping the carbon footprint of the aluminum sector and assesses the nuanced impacts of long-term and short-term policy shifts under various baseline years.

Key findings illuminate that: (1)The carbon emission growth in China's aluminum industry has partially decoupled from production.(2)The pivotal elements of the industry's low-carbon transition hinge on technological advancements and enhanced recycling rates of waste products.(3)Enhanced energy efficiency emerges as a critical determinant in curtailing carbon emissions.(4)The industry exhibits robust adaptability to policy shifts.(5)Furthermore, the cumulative and synergistic effects of policies are instrumental in propelling energy conservation, emission reduction, and the cyclical utilization of resources. This research offers not only pivotal insights for the sustainable evolution and carbon mitigation of China's aluminum sector but also serves as a methodological exemplar for CO2 studies in other high-emission industries.

Environmental Science

Aluminum Industry

Material Flow Analysis (MFA)

Carbon Mitigation

LMDI

The global concern over climate change has made emission reduction in the industrial sector a pressing issue worldwide. The aluminium industry, being an energy-intensive sector, plays a significant role in achieving global emission reduction targets. Therefore, it is crucial to implement effective emission reduction measures in this industry. Aluminium is the most abundant metallic element in the earth's crust and is widely used for its excellent performance. It plays an important role in various sectors of the national economy and is also the most used non-ferrous metal in the world. China, as the world's largest producer and consumer of aluminium, holds a pivotal position in the global aluminium supply chain. According to the China Nonferrous Technology Industry Yearbook and the International Aluminium Institute (IAI), China's aluminium production in 2022 is projected to reach 47.87 million tonnes, of which approximately 40.05 million tonnes will be primary aluminium and 7.82 million tonnes will be secondary aluminium. This accounts for 45% of the global total, with primary aluminium accounting for about 59% and secondary aluminium accounting for about 20%. Additionally, China's aluminium consumption is expected to be 48 million tonnes. In 2019, global aluminium consumption reached 34 million tonnes, with primary aluminium consumption accounting for approximately 59% and secondary aluminium consumption accounting for approximately 20%.

On 22 September 2020, the Chinese Government announced its '3060' goal to reach peak carbon dioxide emissions by 2030 and strive for carbon neutrality by 2060. To achieve these goals, the Chinese government has implemented several carbon reduction policies and comprehensively optimized and adjusted the energy and industrial structures. The transformation and upgrading of the aluminium industry, as an industry with high energy consumption and carbon emissions, is crucial for achieving China's energy saving and emission reduction targets and promoting the low-carbon transformation and sustainable development of the industry. The transformation and upgrading of the aluminium industry, as an industry with high energy consumption and carbon emissions, is crucial for achieving China's energy saving and emission reduction targets and promoting the low-carbon transformation and sustainable development of the industry. The transformation and upgrading of the aluminium industry, as an industry with high energy consumption and carbon emissions, is crucial for achieving China's energy saving and emission reduction targets and promoting the low-carbon transformation and sustainable development of the industry. Therefore, research on energy-saving and carbon reduction for the aluminium industry is essential. The study's significance lies not only in its objectives and practical value but also in its distinctive research methodology and comprehensive data.

Material flow modelling is a well-established analytical method that finds wide application in environmental science, resource management, and industrial ecology. It aids in identifying and enhancing resource utilisation efficiency and plays a crucial role in environmental policy-making and urban planning. Wei-Qiang Chen, Qiang Yue , Hao-Jie Lu , Li-Juan Wang , Ming-Yang Li , Xin Du , An-Ping Li, Dimos Paraskevas, Qiangfeng Li , Shupeng Li , and Ning Ding have used MFA at the country, A quantitative study was conducted in China's aluminium industry using material flow analysis (MFA) to analyze the flow, consumption, trade, end-of-life, and inventory of aluminium resources at different stages. The study established detailed budgets for aluminium products at the national, organizational, and product levels. Recent research has highlighted the significance of improving energy efficiency levels and enhancing end-of-life product recycling rates as crucial steps towards achieving a low-carbon transition in the aluminium industry. Scholars and researchers have extensively employed decomposition analysis to examine the drivers of energy consumption and energy-related emissions impacts. Yunlong Liu utilised the LMDI decomposition method to break down China's carbon emissions between 1996 and 2009. They quantitatively analysed the impact of changes in industrial structure on carbon emissions and concluded that changes in industrial structure will help to reduce carbon emissions in the future. Shupeng Li and Qiang Wang et al. also employed the LMDI decomposition model to investigate the impact of greenhouse gas emissions from the primary aluminium industry on China's greenhouse gas emissions. Yuru Shi^, analysed the changing characteristics and main influencing factors of energy consumption and carbon emissions in China's non-ferrous metal industry using the average logarithmic Diels-Alder index method (LMDI). Mingyang Li analysed and predicted the greenhouse gas emission trends of China's aluminium production from 2021 to 2060 using the LMDI and multi-scenario simulation approach, taking into account the effects of energy structure, technological improvement, and product mix. Hao investigated the influence of regional electricity disparities on greenhouse gas emissions in the primary aluminium production sector across various regions in China.

The aim of this study is to analyse the carbon emissions of the Chinese aluminium industry and their drivers over a long time horizon. The language used is clear, concise, and objective, with a formal register and precise word choice. The text adheres to conventional structure and formatting features, with consistent citation and footnote style. The text is free from grammatical errors, spelling mistakes, and punctuation errors. No new content has been added. The study addresses three key questions: Firstly, how can we scientifically quantify the carbon emissions of China's aluminium industry at various stages and track their trends over time? Secondly, what are the key factors constraining changes in carbon emissions in the Chinese aluminium industry? How do these factors affect carbon emissions at different stages in China's aluminium industry?

Additionally, how do policy and market changes impact these emissions? To address the questions at hand, this study utilizes material flow analysis (MFA) to thoroughly analyze the flow data of China's aluminium industry. The analysis covers a thirty-three-year period from 1990 to 2022, encompassing significant turning points in the industry's history, as well as key policy implementations and technological developments. The analysis includes bauxite mining, smelting, electrolysis, processing, recycling management, and regeneration. This study examines the impacts of long-term trends and short-term changes on carbon emissions in the aluminium industry. The data is analysed comprehensively to provide a rich database for an in-depth analysis of carbon emissions.

Using MFA, we employed the LMDI model to analyze the primary contributors to carbon emissions in China's aluminium industry. These factors include carbon emissions, energy efficiency, energy structure, product structure, and product output. At the same time, we also consider the role of policy and market factors in the long-term carbon emissions of the aluminium industry. This allows us to evaluate the cumulative effect of historical policies and the impact of short-term changes. The carbon emissions of China's aluminium industry were quantified over a 33-year period, with the base year set at 1990 for long-term effects and the previous year for short-term effects. The study explored the contributions of carbon emission factors, energy structure, energy intensity, product structure, and total output in primary and secondary aluminium industries to carbon emission reduction. The cumulative effect of long-term policies and the specific impact of short-term policy changes on the industry's carbon emissions were also assessed. This text examines the effects of short-term policy changes on carbon emissions in the aluminium industry. It highlights the importance of accurately analysing the impact of the grid factor on carbon emissions in each region by combining the geographical distribution of electrolytic aluminium producers in China. The text uses clear and concise language, avoids complex terminology, and maintains a logical flow of information. Technical term abbreviations are explained when first used. The language is objective, value-neutral, and free from biased or emotional language. The text adheres to style guides, uses consistent citation, and follows a consistent footnote style and formatting features. The language is formal, avoiding contractions, colloquial words, informal expressions, and unnecessary jargon. The text is grammatically correct and free from spelling and punctuation errors. The content of the improved text is as close as possible to the source text, and no new aspects have been added.

The aim of this study is to analyze the key contributions of carbon reduction strategies in China's aluminium industry and provide experience for carbon reduction and sustainable development of the aluminium industry in China and globally. The language used is clear, objective, and value-neutral, with a formal register and precise word choice. The text follows a conventional structure with factual and unambiguous titles. The sentences and paragraphs create a logical flow of information with causal connections between statements. The text is free from grammatical errors, spelling mistakes, and punctuation errors. No changes in content were made as per the instructions. This study provides scientific emission reduction strategies and a detailed database for the aluminium industry in the context of global climate change. The information enables industry, academia, and research to gain a better understanding of carbon emissions in the industry. Additionally, it provides policy makers and industry decision makers with practical and feasible strategies for reducing emissions. The study not only helps China's aluminium industry in its low-carbon transformation based on historical facts but also offers valuable experience for reducing emissions in the industrial sector of other countries. By conducting a thorough analysis of the characteristics and drivers of carbon emissions in the aluminium industry, we can gain a better understanding of the industry's crucial role in achieving China's carbon emission reduction targets. This understanding can help us to formulate and implement effective emission reduction strategies and provide valuable guidance for the sustainable development of the global aluminium industry.

This study comprehensively analyses the drivers of carbon emission reduction in China's aluminium industry from 1990 to 2022. The analysis covers the entire aluminium industry chain, from bauxite mining to recycling of aluminium scrap, involving the four major segments of bauxite-alumina-electrolysis-aluminium, as well as the recycling and reclamation of aluminium scrap. The geographical scope is limited to China, but imports and exports of the aluminium industry are taken into account to provide a comprehensive assessment of the carbon footprint in the context of globalisation. We use a wide range of data sources, including official statistics, industry yearbooks, domestic and international research reports and academic papers, focusing on macroeconomic indicators, aluminium flows and stocks, trade volumes, energy consumption and carbon emissions. The calculation of carbon emissions combines activity level data in physical terms with emission factors released by the Chinese government. This covers industrial process emissions from all segments of the aluminium industry. The LMDI method is used to decompose the carbon emissions of the aluminium industry into five factors: carbon emission factor, energy structure, energy intensity, product structure, and total production. Furthermore, we introduced an endogenised economic growth model of technological progress, which subdivides technological progress into human capital, scientific and technological progress, and economies of scale factors. This approach considers the impact of technological progress on carbon emissions. The life cycle analysis of the aluminium industry covers key aspects such as mining, processing, manufacturing, waste recycling, and reuse. It provides a comprehensive and in-depth understanding of carbon emission reduction in China's aluminium industry, supporting the implementation of more effective emission reduction strategies and measures.

2.1 Define boundaries

The aluminium industry chain consists of four major segments: bauxite, alumina, electrolytic aluminium, and aluminium materials, with electrolytic aluminium as its core. According to the National Economic Industry Classification (GB/T 4754 − 2017), the aluminium industry falls under the categories of 'B Mining-0016 Aluminium Ore Mining' and 'C Manufacturing-3216 Aluminium Smelting and 3252 Aluminium Rolling'. Therefore, the socio-economic life cycle of aluminium comprises four main stages:

(i) Mining Stage: This stage refers to the extraction of bauxite from the lithosphere for smelting to produce alumina. The alumina is then electrolysed to obtain the raw material for the production of primary aluminium. This stage considers the trade of bauxite and the depletion of aluminium in the processing chain.

(ii) Processing and Manufacturing Stage: This stage involves the transformation of unwrought aluminium into semi-finished products through sub-processes such as casting, rolling, extrusion, or other processing. Other raw materials are then used to produce final products. It accounts for the trade in unwrought aluminium, aluminium semi-finished products, and the mechanical loss of aluminium during the processes of melting, oxidation, deformation, and processing. It also includes the recycling of waste aluminium that enters the chain.

The smelting process can typically be divided into two categories: the 'long process' and the 'short process'. The 'long process' of obtaining electrolytic aluminium involves using bauxite as raw material and employing the Bayer or mixing method to melt alumina. The resulting substance is then electrolyzed to produce primary aluminium, which has a purity ranging from 99.5–99.8%. On the other hand, the 'short process' utilizes aluminium scrap as raw material. After effective pre-treatment, secondary melting and refining, secondary aluminium can be obtained.

(iii) Use and Consumption Stage: The final product is made available for use in various sectors, including construction, automobile manufacturing, machinery and equipment, consumer durables, power and electronic equipment, and packaging.

(iv) Recycling Stage: This stage includes aluminium scrap and end-product recycling, aluminium scrap pre-treatment, and secondary aluminium melting and casting. It considers the trade in scrap and end-products, as well as the challenges of identifying aluminium for sorting, the loss of aluminium that accumulates somewhere or is disposed of in landfill sites, and the loss of aluminium during melting at high temperatures. Aluminium-containing products act as carriers of aluminium throughout their life cycle. In this study, the amount of aluminium resources in these products was chosen as the functional unit for calculating carbon emissions.

The aluminium industry boundary encompasses the extraction stage, which involves bauxite mining; the processing and manufacturing stage, which includes upstream smelting and downstream processing; and the waste recycling stage, which involves the reuse of new aluminium scrap and the recycling and reclamation of old aluminium scrap. The use and consumption stage is integral to understanding the complete lifecycle of aluminium products.

2.2 Methodology

2.2.1 Calculation of CO₂

To calculate carbon emissions (C) from the aluminium industry in China, multiply the activity level data (AD) of aluminium-containing products in each segment by the carbon emission factor (EF). Aluminium-containing products include bauxite, alumina, primary aluminium, and secondary aluminium in the production stage, which account for industrial process emissions.

This calculation is performed as follows:

$$\:{C}_{Al}=\sum\:_{i=1}^{n}\left({AD}_{i}\times\:{EF}_{i}\right)\:\:$$

The activity level data ($\:{AD}_{i})$ uses physical quantities, while the emission factor data ($\:{EF}_{i})$ relies on information released by the Chinese government . The grid factor of primary aluminium takes into account the carbon emission situation and weight of captive power plant and grid electricity, as shown in Fig. 4 .

2.2.2 Logarithmic Mean Divisia Index

Structural decomposition models, also known as factor decomposition models (IDA), are commonly used by researchers to study the factors that affect energy consumption and energy-related emissions. These models can be classified into the Rasch and Dee-type index methods, such as the Logarithmic Mean Divisia Index (LMDI). Ang compares the centralised methods of structural decomposition modelling. The Logarithmic Mean Divisia Index (LMDI) method is commonly used due to its good theoretical basis, applicability, and strong applicability. In this paper, the LMDI method is used to decompose the carbon dioxide emissions of the non-ferrous metal industry into five factors: carbon emission factor, energy structure, energy intensity, product structure and production.

The decomposition model for China's aluminium:

$$\:C=\sum\:_{ij}{C}_{ij}=\sum\:_{ij}\frac{{C}_{ij}}{{E}_{ij}}\frac{{E}_{ij}}{{E}_{j}}\frac{{E}_{j}}{{Q}_{j}}\frac{{Q}_{j}}{Q}Q=\sum\:_{i}C{I}_{ij}E{S}_{ij}E{I}_{j}Q{S}_{j}Q$$

式中,

$\:i\:\:$ —The types of energy used by China's aluminum industry

$\:j\:\:\:$ —Primary aluminium or secondary aluminum

$\:C\:$ —The total CO₂ emissions of China's aluminum industry(tCO₂)

$\:E\:\:$ —Total energy consumption (tce)

$\:{E}_{j}\:$ —Consumption of energy j (tce)

$\:Q\:\:$ —Total output of aluminium (10,000 tons)

$\:{Q}_{j}$ —Output of primary or secondary aluminium (10,000 tons)

$\:C{I}_{ij}$ , $\:E{S}_{ij}$, $\:E{I}_{j}$, $\:Q{S}_{j}$ are the carbon emission factors of energy $\:i$ consumed by primary and secondary aluminium in China's aluminium industry, the share of energy $\:i\:$in the total energy of primary and secondary aluminium production, the energy intensity of primary and secondary aluminium production, and the share of energy $\:i$ in domestic aluminium production, respectively.

The amount of change in CO₂ emissions from the base year to year T can be expressed as the following equation:

$$\:\varDelta\:{C}^{T}={C}^{T}-{C}^{0}=\varDelta\:{CI}_{effect}^{T}+\varDelta\:{ES}_{effect}^{T}+\varDelta\:{EI}_{effect}^{T}+\varDelta\:{QS}_{effect}^{T}+\varDelta\:{Q}_{effect}^{T}$$

The equation for expressing the annual change in CO₂ emissions is as follows:

$$\:\varDelta\:C={C}^{T+1}-{C}^{T}=\varDelta\:{CI}_{effect}+\varDelta\:{ES}_{effect}+\varDelta\:{EI}_{effect}+\varDelta\:{QS}_{effect}+\varDelta\:{Q}_{effect}$$

The change in CO₂ emissions is determined by four factors:

The $\:{CI}_{effect}$、$\:{ES}_{effect}$、$\:{EI}_{effect}$、$\:{QS}_{effect}$ and $\:{Q}_{effect}$, represent the impacts of the carbon emission factor, energy structure, energy intensity, product structure, and total production volume, respectively.

The LMDI model can calculate the change in each influencing factor using the following five equations:

$$\:\varDelta\:{CI}_{effect}^{T}=\sum\:\frac{{C}_{ij}^{T}-{C}_{ij}^{0}}{\text{ln}{C}_{ij}^{T}-\text{ln}{C}_{ij}^{0}}\times\:\text{ln}\frac{{CI}_{ij}^{T}}{{CI}_{ij}^{0}}$$

$$\:\varDelta\:{ES}_{effect}^{T}=\sum\:\frac{{C}_{ij}^{T}-{C}_{ij}^{0}}{\text{ln}{C}_{ij}^{T}-\text{ln}{C}_{ij}^{0}}\times\:\text{ln}\frac{{ES}_{ij}^{T}}{{ES}_{ij}^{0}}$$

$$\:\varDelta\:{EI}_{effect}^{T}=\sum\:\frac{{C}_{j}^{T}-{C}_{j}^{0}}{\text{ln}{C}_{j}^{T}-\text{ln}{C}_{j}^{0}}\times\:\text{ln}\frac{{EI}_{j}^{T}}{{EI}_{j}^{0}}$$

$$\:\varDelta\:{QS}_{effect}^{T}=\sum\:\frac{{C}_{j}^{T}-{C}_{j}^{0}}{\text{ln}{C}_{j}^{T}-\text{ln}{C}_{j}^{0}}\times\:\text{ln}\frac{{QS}_{j}^{T}}{{QS}_{j}^{0}}$$

$$\:\varDelta\:{Q}_{effect}^{T}=\frac{\text{ln}\frac{{Q}^{T}}{{Q}^{0}}\sum\:({C}_{ij}^{T}-{C}_{ij}^{0})}{\text{ln}{C}_{ij}^{T}-\text{ln}{C}_{ij}^{0}}$$

2.3 data sources

The study utilises data sources that account for energy consumption and CO₂ carbon emissions in the non-ferrous metals industry. The data was collected from various literature yearbooks. The main sources of data are:

(1) Macroeconomic indicators and aluminium flows and stocks from official statistics, such as China Statistical Yearbook, China Nonferrous Metals Industry Yearbook, Industrial Information, research reports from domestic and foreign institutions, such as the International Aluminium Institute IAI, the United States Geological Survey USGS, the Industrial Information website, and relevant research papers ^,;

(2) The import data is sourced from UN Comtrade, using the HS commodity code 6902 for 'Aluminium; waste and scrap'. To calculate our net imports of bauxite and aluminium scrap, we have subtracted exports from imports.

(3) We have calculated the aluminium content shares using reported trade currency values and the annual average London Metal Exchange (LME) primary aluminium prices.

(4) The scrap data has been calculated using the conservation of materials theorem, which was triggered by the Product Life Model and the Stock Driven Model.

(5) Historical data on loss rates, recycling rates ^,, product service lives and trade volumes at each stage were obtained from yearbooks and existing studies.

(6) Carbon emission factors were calculated using the Carbon Footprint Technical Support Document published by the International Aluminium Association , as well as methodologies from the IPCC, and a bottom-up approach.

(7) The energy consumed by the primary aluminium/aluminium electrolysis industry includes crude coal, crude oil, natural gas, grid electricity, and hydropower. This is in accordance with relevant national, industry, and IPCC standards. Other traditional and renewable energy sources, which are more fluctuating and account for a smaller proportion, are not taken into account at this time.

To ensure uniformity in the calculation process, it is necessary to convert all energy sources into standard coal (tce) for analysis. The conversion factors for standard coal and carbon emissions for various energy sources consumed in the production of primary and secondary aluminium are shown in SI Table 3.

This study presents the key dynamics and drivers of carbon emissions in China's aluminium industry. It emphasizes the significance of technological advancements, energy efficiency improvements, and policy guidance. Additionally, it highlights the role of the aluminium industry in achieving China's and the world's carbon emission reduction targets in the context of global climate change. The study provides valuable data and insights for relevant policymaking and future research. This text analyses and discusses the aluminium industry in China from three perspectives: material flow and carbon emission trends, emission decomposition and influencing factors, and policy and market sensitivity analysis. The language used is clear, concise, and objective, with a formal register and precise word choice. The structure is logical and follows a clear progression, with causal connections between statements. The text is free from grammatical errors, spelling mistakes, and punctuation errors. No changes in content have been made.

3.1 Analysis of material flow in the aluminium industry

This study employs the Material Flow Analysis (MFA) method to quantify the material flows and stocks of China's aluminium industry in various segments from 1990 to 2022. The results indicate significant carbon emissions and potential changes in primary and secondary aluminium during this period. The key findings are: the carbon emissions of the aluminium industry are partially decoupled from its production; technological progress and increased recycling of waste products are crucial for low-carbon transformation; and improved energy efficiency plays a key role in reducing carbon emissions.

The socio-economic life cycle of aluminium comprises four main stages.

Firstly, the Mining Stage involves extracting bauxite from the lithosphere, which is then smelted to produce alumina. The alumina is then electrolysed to obtain the raw material for primary aluminium production. This stage considers the trade of bauxite and the depletion of aluminium in the processing chain.

(ii) Processing and Manufacturing Stage: This stage refers to the part of unwrought aluminium that is transformed into semi-finished products through sub-processes such as casting, rolling, extrusion, or other processing. Other raw materials are then used to produce final products. This stage takes into account the trade in unwrought aluminium, aluminium semi-finished products, and the mechanical loss of aluminium during the process of melting, oxidation, deformation, and processing. It also includes the recycling of waste aluminium that enters into the chain.

The aluminium industry chain comprises four major segments: bauxite, alumina, electrolytic aluminium, and aluminium materials. Electrolytic aluminium is the core of this chain. The smelting process can typically be divided into two categories: the 'long process' and the 'short process'. The process of obtaining electrolytic aluminium involves using bauxite as raw material and employing the Bayer or mixing method to melt alumina. The resulting substance is then electrolyzed to produce primary aluminium, which has a purity ranging from 99.5–99.8%. On the other hand, the short process utilizes aluminium scrap as raw material. After effective pre-treatment and secondary melting and refining, secondary aluminium can be obtained.

Use and Consumption Stage: The final product is marketed for use in various sectors, including construction, automobile manufacturing, machinery and equipment, consumer durables, power and electronic equipment, and packaging.

Recycling Stage: This stage includes aluminium scrap and end-product recycling, aluminium scrap pre-treatment, and secondary aluminium melting and casting. It takes into account the trade in scrap and end-products, as well as the difficulty of identifying aluminium for sorting, the loss of aluminium that accumulates somewhere or is disposed of in landfill sites, and the loss of aluminium when it is melted at high temperatures. Aluminium-containing products act as carriers of aluminium throughout their life cycle. In this study, the amount of aluminium resources in these products was chosen as the functional unit for calculating carbon emissions. The study aimed to determine the carbon emissions of aluminium-containing products.

The aluminium industry boundary encompasses the extraction stage, which involves bauxite mining, the processing and manufacturing stage, which includes upstream smelting and downstream electrolysis, and the waste recycling stage, which involves the reuse of new aluminium scrap and the recycling and reclamation of old aluminium scrap. The use and consumption stage is not included. It is important to maintain a clear and logical structure when discussing the different stages of the industry.

Table 1

Material Flow Data for China's Aluminum Industry in 2022 (thousands of tons)
Stage	mining	smelting	Electrolysis phase	Processing & Manufacturing	Product Market	Aluminum Scrap Recycling	Aluminum Scrap Regeneration
product	Bauxite	alumina	Pri-Al	Aluminum Alloy	Aluminum Materials	Aluminum Scrap	Sec-Al
production	7,781	8,186	4,005	1,218	6,222	602	782
import	12,547	199	67	127	239	152	-
export	5	101	19	23	660	0	-
Apparent consumption	20,323	8,285	4,052	1,323	5,801	754	782

The data sources used for this study include bauxite mining volume from the China Land and Resources Statistical Yearbook, aluminium alloy and aluminium material from the China Industrial Statistical Yearbook, aluminium scrap recycling volume from the China Renewable Resources Recycling Industry Development Report and the Ministry of Commerce, and import and export volume from the General Administration of Customs. The remaining data was obtained from the China Nonferrous Metals Industry Yearbook. The total alumina production was 43.35 million tonnes, with 40.05 million tonnes for metallurgical use and 3.3 million tonnes for non-metallurgical use.

The material flow analysis diagram used in this study (Fig. 3) was constructed from these data (see Table 1). The diagram shows in detail the entire flow of aluminium from mining, smelting and processing to end use and waste disposal. The representation of flows in the diagram allows us to visualise the distribution of aluminium through the various stages of production and consumption, in particular the key links in terms of energy consumption and emissions.

By analysing these material flows, we identify several key environmental impact points in the aluminium industry. For example, the smelting process is the most energy-intensive and carbon-emitting stage of aluminium production, a finding that is crucial for guiding energy efficiency and emission reduction strategies in the aluminium industry. At the same time, we also observe the potential for recycling aluminium materials after use, which is important for driving the aluminium industry in a more sustainable direction.

This analysis of the aluminium industry's material flow and its environmental impact points corroborates with the findings of Hatayama, who highlighted the significant energy consumption and carbon emissions of the aluminium smelting process. Furthermore, the emphasis on the potential for recycling to enhance the industry's sustainability aligns with the research conducted by Løvik , who studied the dynamic stock and flow of metals in society and the potential benefits of increased recycling rates. These studies reinforce the importance of adopting more efficient processes and recycling strategies to mitigate the environmental impacts of the aluminium industry.

3.2 Overall Trends in Carbon Emissions and Energy Structure

The carbon emissions of the aluminium industry are decomposed using the LMDI decomposition method. The study explores the effects of carbon emission factors, energy structure, energy intensity, product mix, and total production. The study adopts a dual analysis strategy, using 1990 as the base year in one analysis and the previous year of each year as the base year in the other analysis. The main findings are as follows: The cumulative effect of policies and technological progress plays a central role in reducing carbon emissions in the long-term. In the short-term, the analysis highlights the industry's rapid adaptation to policy and market changes. The optimization of the industrial structure and the improvement of energy efficiency play a key role in reducing carbon emissions.

The carbon emissions of China's aluminium industry are closely linked to the product mix and energy structure. Our analysis from 1990 to 2022 shows the changing proportion of primary and secondary aluminium in the product mix of China's aluminium industry, and the corresponding changes in energy composition (Fig. 3). This evolution reflects broader trends in the industry's attempt to balance production needs with environmental sustainability, as discussed in studies focusing on energy efficiency and CO2 reduction in the Chinese aluminium sector.

China's aluminium industry has grown significantly over the past three decades, with total production increasing from 860,000 tonnes in 1990 to 47.87 million tonnes in 2022. The proportion of secondary aluminium has also risen from 0.84% in 1990 to 16.34% in 2022.

The industry is gradually reducing its reliance on coal as the main source of energy for primary aluminium, with coal usage decreasing from 77.34% in 1990 to 63.35% in 2020. Simultaneously, the consumption of oil and natural gas has decreased, while the usage of electricity, hydropower, and other renewable energy sources has significantly increased. This transition demonstrates the aluminium industry's proactive measures to decrease carbon emissions and adopt cleaner energy alternatives. This transition is crucial for reducing the carbon intensity of the aluminium production process and aligns with China's broader environmental goals to lower carbon emissions and combat climate change.

In the case of secondary aluminium, the energy mix for production is progressively shifting towards greater dependence on electricity. The proportion of electricity generated from the grid has increased significantly from a negligible amount in 1990 to 15.81% in 2020 (Fig. 4). This shift not only reflects advancements in energy efficiency but also signifies a positive movement towards a low-carbon transition within the industry. The increasing reliance on grid electricity, especially when sourced from renewable energy, can significantly reduce the environmental impact of secondary aluminium production, fostering a more sustainable industrial ecosystem.

In the analysis of carbon emissions from the aluminum industry across various regions in China, significant regional disparities were observed. The carbon emissions in different regions are significantly influenced by local production capacity, energy structures, and policy differences. In some regions, carbon emissions are relatively higher due to a reliance on energy structures with high carbon emissions. Conversely, in other regions, carbon emissions are relatively lower due to policy advocacy and the widespread use of clean energy.

Equation (1) was used to calculate the carbon dioxide emissions from the primary and secondary aluminium industries in China between 1990 and 2022, as shown in Fig. 5. Over this period, the carbon dioxide emissions from the primary aluminium industry increased significantly due to the rapid development of China's aluminium industry, rising from 0.2 million tonnes in 1990 to 49.7 million tonnes in 2017. Carbon emissions from 2018 to 2022 have slightly decreased due to differences in energy consumption data sources. However, the secondary aluminium industry has shown a year-on-year trend of growth, from 2 tonnes in 1990 to 2,091 tonnes in 2022.

This growth reflects China's expanding share of the global aluminium market, as well as changes in production processes and energy use efficiency. Since China joined the World Trade Organisation (WTO) in 2000, the aluminium industry has experienced significant growth and a consequent increase in carbon emissions. While emissions from secondary aluminium are lower than those from primary aluminium, the growth rate indicates potential for improvement in the recycling and reuse of aluminium materials.

In the comparative analysis, significant differences in carbon emissions between the primary and secondary aluminium industries were observed. The primary aluminium industry has much higher carbon emissions than secondary aluminium due to its energy-intensive nature. The secondary aluminium production process has relatively low energy requirements as it relies on already refined aluminium materials, reducing additional energy consumption and corresponding carbon emissions. This contrast not only highlights the energy and carbon efficiency of secondary aluminium production but also underscores the importance of promoting secondary aluminium to achieve low-carbon development in the aluminium industry.

3.3 Decomposition of Emissions and Impact of Production Volume

This study aims to quantitatively analyze the carbon emission characteristics of China's aluminium industry and its driving factors. The objective is to determine how to scientifically quantify the carbon emissions of the aluminium industry and track its long-term change trends. The carbon dioxide emissions ($\:C$) of China's aluminium industry are broken down into carbon emission factors ($\:C{I}_{ij}$), energy structure ($\:E{S}_{ij}$), energy intensity ($\:E{I}_{j}$), product structure ($\:Q{S}_{j}$), and total production ($\:Q$), according to Eq. (2–9) in 2.2.2.

To gain a deeper understanding of the trends of these factors over time and their impact on total emissions, this study establishes two analysis methods based on the LMDI model. The two methods for selecting a base year are: using 1990 as the base year, or selecting the year before each year as the relative base year. Detailed calculations were performed to determine the change value and contribution rate of each factor relative to the base year.

3.3.1 Method Ⅰ: The base year is 1990

The analysis of the base year, 1990, shows that the total output curve of China's aluminium industry has significantly grown over the thirty-three year period, reflecting the rapid expansion of the economy. This expansion inevitably led to an increase in carbon emissions from the aluminium industry. However, the rate of growth in carbon emissions did not keep pace with the expansion due to energy efficiency improvements and the introduction of clean energy sources, such as hydropower.

Since 1990, the Chinese government has implemented various measures to reduce carbon emissions and improve energy policies. These measures include promoting clean energy and improving energy efficiency, which have enabled the aluminium industry to make significant progress in reducing CO₂ emissions. The progress is mainly reflected in three aspects: firstly, the improvement of carbon emission efficiency, which reflects technological progress and improved production efficiency by reducing carbon emissions generated per unit of aluminium produced; secondly, the reduction of energy intensity, which indicates the reduction of energy consumption required for the same number of aluminium products; and thirdly, the optimization of the energy structure, particularly the increase in the proportion of clean energy sources, which reduces carbon emissions. The increase in the weight of energy sources reduces dependence on carbon emissions.

Figure 6 is placed here to visually demonstrate the results of the LMDI decomposition analysis of China's aluminum industry between 1990 and 2022, with 1990 as the base year. It shows the changes and contribution rates of different factors affecting carbon emissions during this period. The left part of the figure illustrates the changes and contribution rates of LMDI decomposition results in 1990, and the right part details the contribution rates in 2022, offering a clear depiction of the industry's evolution towards reduced carbon emissions and greater energy efficiency.

Throughout the analysed period, the carbon emission factor, energy structure, and energy intensity have consistently decreased year on year, with a more significant decline observed after 2000. The gradual increase in the share of renewable energy demonstrates the role of policy adjustments and technological progress in reducing carbon emissions per unit of energy consumption. This is mainly due to the adoption of clean energy technologies and the improvement of energy use efficiency. It is important to note that the language used is clear, objective, and value-neutral, and the sentence structure is simple and logical. Additionally, technical terms are explained when first used, and the text is free from grammatical errors, spelling mistakes, and punctuation errors. The content of the improved text is as close as possible to the source text, and no new aspects have been added. Over the past three decades, the primary aluminium industry has increased its use of hydropower and explored other renewable energy sources.

Furthermore, the product mix factor has become more intricate over time, reflecting the influence of various product mixes of primary and secondary aluminium on carbon emissions in the aluminium industry. This complexity underscores the evolving market demands and policy guidance shaping the industry's structure. The discussion on the value and contribution of changes in energy demand and carbon emissions from primary and secondary aluminium production highlights the growing importance of integrating secondary aluminium into carbon reduction strategies. This shift is indicative of the broader economic restructuring aimed at enhancing environmental sustainability, a point emphasized by Liu and Lin (2021) in their study on the role of secondary aluminium in reducing the environmental footprint of the aluminium industry.

3.3.2 Method Ⅱ: The base year is the previous year

By setting the base year as the previous year, we can clearly capture the more detailed and short-term changes in China's aluminium industry carbon emissions. This approach helps us to understand the sensitivity and adaptability of the aluminium industry in response to market and policy changes, compared to using a fixed base year of 1990.

(Top left) The carbon emission factor (CI) changes resulting from lmdi decomposition when the base year is the previous year (i.e., year N-1). (Top right) The energy structure (ES) changes resulting from lmdi decomposition when the base year is the previous year (i.e., year N-1). (Right) The energy intensity (EI) changes resulting from lmdi decomposition when the base year is the previous year (i.e., year N-1). Year N-1: Top left panel shows the change in energy intensity (EI) of the LMDI decomposition results when the base year is the previous year. Centre left panel shows the change in carbon intensity (CI) of the LMDI decomposition results when the base year is the previous year. Centre right panel shows the change in the product mix (QS) of the LMDI decomposition results when the base year is the previous year. Bottom left panel shows the change in the total production (Q) of the LMDI decomposition results when the base year is the previous year. Bottom right panel shows the contribution of the LMDI decomposition results when the base year is the previous year (Year N-1).

The analysis of CO₂ emissions from China's aluminium industry between 1990 and 2022 reveals the impact of several key factors on carbon emissions (Fig. 7). Firstly, there is a significant positive correlation between growth in total production (Q) and carbon emissions, indicating the challenge and necessity of reducing carbon emissions while pursuing industrial growth. This positive correlation underscores the intricate balance required between achieving economic objectives and fulfilling environmental responsibilities. Studies such as those by Zhang and Wang (2019) have highlighted the complexities of managing industrial growth alongside reducing carbon emissions, suggesting that policy measures and technological innovations are critical in addressing this challenge effectively.

Secondly, the preparation of electrolytic aluminium and the smelting of scrap aluminium to make secondary aluminium are dominated by electricity consumption. In the past, China's electricity was mainly generated by coal-fired power plants, which have high carbon emissions. However, with the advancement and popularity of renewable energy power generation technology, the emission factor of the power grid has been decreasing year by year. This change has directly affected the carbon emission characteristics of the aluminium industry, highlighting the key role of optimising the energy structure in reducing carbon emissions. However, the shift towards renewable energy sources for power generation has progressively lowered the emission factor of the power grid, thereby influencing the carbon emission profile of the aluminium industry. This transition reflects broader trends towards cleaner energy usage within the industrial sector and underscores the significant impact of energy structure optimization on carbon emissions. The decreasing emission factor of the power grid exemplifies the critical role that advancements in renewable energy technologies and their increasing adoption play in environmental sustainability.

Furthermore, changes in the product mix of the aluminium industry, particularly the shift from primary aluminium to secondary aluminium, are significant in reducing carbon emissions. The aluminium industry has room for improvement in promoting a circular economy and environmentally friendly production. While the increase in secondary aluminium has reduced carbon emissions in some years, the aluminium industry as a whole is still dominated by primary aluminium. It is important to note that the non-ferrous metals industry was hit hard by the global financial crisis in 2008. Additionally, the revitalisation policy of the Chinese government has led to the construction of many new projects that consume higher amounts of energy. These projects have resulted in a significant increase in energy intensity due to rapid expansion and excessive focus on economic recovery, resulting in inadequate energy management and regulation. This period witnessed a notable increase in energy intensity, highlighting challenges in energy management and regulation during times of aggressive economic pursuits.

The impacts of energy intensity (EI) and energy structure (ES) on carbon emissions show significant fluctuations after 2010, reflecting the important but unstable impact of energy efficiency and energy type choices on carbon emissions. In particular, electricity consumption dominates the aluminium preparation process. The production of secondary aluminium has a lower energy intensity because it relies on already refined aluminium. This allows for a significant reduction in energy demand during its production. Therefore, promoting the use of secondary aluminium is an effective way to reduce the overall energy intensity and carbon emissions of the aluminium industry. Enhancing the production and use of secondary aluminium emerges as an effective strategy to reduce the overall energy intensity and carbon emissions of the aluminium industry, aligning with the objectives of sustainable development and environmental protection.

This section explores the impact of policy and market changes on carbon emissions in China's aluminium industry. A comparative analysis of long-term and short-term effects is used to answer the central question.

4.1 Policy sensitivity analysis

The focus of this section is to analyze the impact of policy changes on carbon emissions within China's aluminium industry, specifically examining the sensitivity of long-term and short-term policy changes. This analysis is crucial for understanding how policy influences carbon emission dynamics in the industry, directly addressing the key question outlined in the introduction: "How do policy changes impact carbon emissions in China's aluminium industry?"

The LMDI decomposition results reveal that long-term analysis based on 1990 as the reference year, in comparison to short-term analysis based on the previous year, demonstrates the significant impact of policy changes on carbon emissions, energy intensity, and production in the aluminium industry(Fig. 8). Long-term trends reflect the cumulative effects of policies, while short-term analysis exposes annual fluctuations and rapid market responses. Policies are responsive to changes in Q, CI, EI, ES, and QS in the aluminium industry; the influence of short-term policies on the industry strongly correlates with long-term policies. This correlation between policy impact and industry metrics emphasizes the importance of strategic long-term planning alongside immediate policy adjustments to ensure sustainable industry growth and environmental protection.

During the period from the Eighth Five-Year Plan to the Tenth Five-Year Plan, the aluminium industry experienced energy exploration, resulting in constant shocks and fluctuating ES indicators. These fluctuations indicate the instability in the process of policy adjustment and market adaptation. This instability was particularly pronounced in 2002 when the domestic market faced severe oversupply, leading to fluctuations in the QS indicators. However, with the state's restrictions on excessive investment in industries such as electrolytic aluminium from 2003 onwards, along with the implementation of stricter control measures in 2004 and incentives such as taxation, the market gap gradually narrowed from 2006 onwards, reflected in the gradual stabilization of the QS indicators. The response of the aluminium industry to these policy and market adjustments showcases the dynamic nature of industrial adaptation to regulatory frameworks, highlighting the critical role of government intervention in stabilizing market conditions^,.

The financial crisis in 2008 weakened the non-ferrous metals industry, and the government's revitalization policies may have positively influenced the CI and EI indicators in the subsequent years, encouraging the industry to resume development. This indicates that post-economic crisis, China's aluminium industry faces the dual challenges of carbon emission management and energy efficiency improvement while resuming development, as evidenced by the improved CI and EI indicators post-crisis. The proactive stance of the Chinese government in formulating and implementing policies aimed at revitalizing the aluminium industry post-crisis demonstrates the crucial interplay between policy intervention and industry resilience

The implementation of the Aluminium Industry Code, particularly the establishment of the energy intensity of secondary aluminium access at 130kgce/t in 2020, has significantly impacted the overall energy efficiency of the aluminium industry, tightly controlling energy usage by the secondary aluminium industry. This regulatory measure reflects the government's commitment to enhancing energy efficiency and sustainability within the industry, a critical step towards achieving China's environmental targets.

Regulations like the Law on the Promotion of Circular Economy and the Energy Conservation Law have established a legal framework for the sustainable development of the aluminium industry. These policies may provide support for the decline in CI and EI indicators in the long-term trend. The introduction of these laws underscores the importance of legal and regulatory frameworks in guiding industries towards sustainable development paths, by encouraging the adoption of circular economy principles and energy conservation measures^,.

Policies from 2017, such as the Action Plan for Industrial Energy Conservation and Green Standardization and the Guiding Opinions on Accelerating the Construction of a Recycling System for Waste Materials, reflect the significance of the circular economy and the effective use of resources. These policies may have led to improvements in QS indicators, indicating increased resource utilization efficiency. The emphasis on the circular economy and resource efficiency not only aligns with global sustainability goals but also represents a strategic pivot in China's approach to industrial policy, focusing on resource conservation and environmental protection.

Additionally, policies such as the Limit of Energy Consumption per Unit Product for Electrolytic Aluminium and Alumina, the Implementation Guidelines for Energy Conservation, Carbon Reduction, Renovation and Upgrading in Key Areas of High Energy-Consuming Industries, and the Benchmarking Level and Benchmarking Level of Energy Efficiency in Key Areas of Industry emphasize the improvement of energy efficiency and the control of energy consumption. These policies may be directly correlated with the decline in EI indicators and the improvement in ES indicators, signifying substantial progress in energy management and carbon reduction within the industry. The strategic focus on energy efficiency and carbon reduction reflects China's commitment to mitigating environmental impacts while ensuring industrial growth^,.

The "Guidelines on Greenhouse Gas Emission Accounting Methods and Reporting for China's Electrolytic Aluminium Producing Enterprises (Trial)" of 2013, together with the "Instructions for Enterprises to Fill in the Greenhouse Gas Emission Accounting and Reporting Aluminium Smelting" issued in October 2023, form a policy framework, outlining GHG accounting methodology and effectively promoting continuous improvement of carbon emission factors in the aluminium industry. This comprehensive policy framework for GHG emission management in the aluminium industry highlights the government's proactive approach to addressing climate change and promoting sustainability within key industrial sectors.

4.2 Market sensitivity analysis

The primary objective of this section is to examine the market sensitivity of the aluminium industry in China, particularly how the interplay between supply and demand influences carbon emissions. This analysis is crucial for comprehending the impact of market dynamics on carbon emissions from China's aluminium industry and directly addresses the key question outlined in the introduction: "How do market changes affect carbon emissions in China's aluminium industry?"

Upon scrutinizing the supply and demand dynamics from 1990 to 2022 (Fig. 9), it is evident that although overall aluminium production and consumption have remained in close proximity, there have been substantial fluctuations during pivotal periods. These fluctuations mirror the market's responsiveness to changes in policy and the economic landscape. For instance, around 2000, there was an oversupply in the Chinese aluminium market, indicating that consumption surpassed production. The 2008 financial crisis resulted in a spike in the supply-demand gap and a significant oversupply. Subsequently, the government enacted policies to stimulate aluminium production, leading to either an oversupply or a deceleration in economic growth, accompanied by a decrease in consumer demand without a corresponding reduction in production. The post-2020 period has seen considerable volatility in supply and demand, highlighting the impact of policies on energy efficiency and carbon reduction on the aluminium market^,.

Further examination (Fig. 10) illustrates a noteworthy correlation between Production (Q) and Energy Structure (ES) in China's Aluminium Industry. Notably, there is a strong positive correlation with Coal, Hydroelectricity, and other Renewable Energy sources, as well as a significant negative correlation with Crude Oil, Natural Gas, and Electricity. Specifically, there is a highly negative correlation between primary aluminium (Pri-Al) production and the carbon emission factor for electricity (-0.956), as well as for secondary aluminium (Sec-Al) production and the carbon emission factor for electricity (-0.925). These findings emphasize the industry's shift towards more environmentally friendly and sustainable production methods, in response to growing domestic and international demand for such practices. The decreasing carbon emission factor for electricity further highlights the industry's move towards adopting lower-carbon or cleaner energy solutions in power production, aligning with China's broader environmental and sustainability goals.

This trend not only reflects the aluminium industry's adaptability to environmental trends and policy changes but also signifies China's commitment to transitioning towards low-carbon energy sources. This commitment is part of a larger strategy to mitigate environmental impacts while fostering sustainable industrial growth, indicating a pivotal shift in energy policy and industry practices towards sustainability and environmental responsibility^,.

The aluminum industry in China, a significant contributor to the country's economic development, encounters challenges related to energy usage and environmental impacts. This analysis examines the CO2 emissions of China's aluminum industry and the influencing factors between 1990 and 2022 through material flow analysis and LMDI decomposition model and driver correlation study. The findings indicate that economic scale expansion is the primary contributor to the increase in CO2 emissions, but the growth of carbon emissions has not kept pace with production volume, mostly due to enhanced energy efficiency and the implementation of clean energy. Energy intensity improvement is crucial for emission reduction, while energy mix and carbon emission factors demonstrate inconsistent effects on emissions. Furthermore, the aluminum industry is highly adaptive to market changes and can flexibly adjust to supply and demand fluctuations.

5.1 conclusion

Based on this analysis, the following conclusions are drawn:

1) Decoupling of economic growth and carbon emissions

Between 1990 and 2022, China's aluminum industry displayed substantial economic expansion, while its carbon emissions growth did not parallel production growth. This indicates significant progress in energy efficiency improvement and the adoption of cleaner energy sources, marking a partial decoupling between economic growth and carbon emissions.

2) Critical pathways for a low-carbon transition in the aluminum industry

The study underscores the importance of upgrading technology and increasing the recycling rate of waste products for a low-carbon transition in the aluminum industry. Optimizing carbon emission factors, energy structure, and energy use efficiency are decisive factors in reducing overall carbon emissions in the production processes of primary and recycled aluminum.

3) The primary importance of enhancing energy efficiency

The research indicates that enhancing energy efficiency is essential for decreasing carbon emissions in the aluminium industry. This discovery underscores the fundamental nature of improving energy utilization efficiency and implementing more effective production technologies on the sustainable development trajectory of the aluminium industry.

4) Non-simultaneous impacts of energy combination and carbon emission factors

This study unveils the intricate and non-simultaneous effects of energy combination and carbon emission factors on carbon emissions in the aluminium industry, highlighting the significance of optimizing energy combination and refining production processes to lower carbon emissions. The potential reason for this lies in the inherent disjointed relationship between energy and carbon emissions, which is not extensively examined in this paper.

5) Prospective transformation potential of the aluminium sector

This study emphasizes the substantial potential of the aluminium sector to optimize its energy combination and enhance energy efficiency. Key measures include promoting the transformation and enhancement of the energy combination, advocating for the adoption of cleaner, low-carbon energy sources, and expediting the implementation of technological innovations and policy incentives. Additionally, the cumulative impact and coordination of policies play a pivotal role in advancing energy conservation, emission reduction, and resource recycling in the aluminium industry.

6) Market adaptability and dynamic equilibrium of supply and demand

Research indicates that China's aluminium industry exhibits robust adaptability to market variations and can flexibly adjust to fluctuations in supply and demand. Government policies play a critical role in ensuring equilibrium between economic growth and environmental protection, particularly during periods of economic expansion and market overheating.

7) The substantial influence of cumulative effects and policy synergies

This study reveals that the cumulative effects of long-term policies and short-term policy alterations have a significant impact on carbon emissions in the aluminium industry, underscoring the industry's capacity to swiftly adapt to policy changes. This discovery not only underlines the importance of policy continuity in environmental protection and energy efficiency enhancement in the aluminium industry, but also highlights the key role of synergies among different policies.

In addition, the combined impact of policies on promoting energy conservation, emission reduction, and resource recycling in the aluminium industry demonstrates their synergies. To align with national long-term environmental protection and energy efficiency goals, the aluminium industry should proactively adjust its sustainable development strategies to align with current policy trends and market changes.

Limitations of this study include: i) failure to differentiate between direct and indirect carbon dioxide emissions in calculations; ii) consideration of carbon emission factors only for specific aluminium products, neglecting others; iii) lack of in-depth analysis on the discord between energy structure adjustment and carbon dioxide emissions impact.

In summary, to synchronize carbon reduction and sustainable development in the aluminium industry, it is crucial to moderately control industry expansion, enhance product structure's efficiency and environmental performance, and promote the use of low-carbon technologies. Technological advancements and improvements in energy efficiency can decrease energy intensity, while reducing environmental impact per output unit requires enhancing clean energy, clean power, and resource utilization efficiency. Governments should expedite technological development and innovation in electricity production, encourage new power generation technologies, and increase investment in clean energy. By improving energy efficiency and adopting clean energy, the aluminium industry has not only partially decoupled from economic growth but also showcased significant potential for energy-saving, emission reduction, and resource recycling through technological advancements, optimized energy structure, and policy support. These findings underscore the vital role of policy continuity and synergy in the aluminium industry's sustainable development, along with its adaptability to market and environmental pressures. This paper forecasts future industry carbon emissions based on historical emissions and provides recommendations and rationale for emission reduction direction. This type of study can be replicated in other high-emission industries to understand CO2 emission characteristics and future trends.

5.2 Policy recommendations

In this context, we suggest the following policy recommendations:

(1) Balancing industrial expansion with carbon emissions

To reconcile economic expansion with environmental protection, the government needs to maintain equilibrium between supply and demand, and optimize the industrial structure during periods of high market growth. This includes reducing the proportion of highly polluting industries and actively promoting the development of low-carbon, high-technology, and service-oriented industries to achieve sustainable economic growth.

(2) Controlling industrial scale and optimizing product structure

It is advised that the expansion of the aluminum industry be moderately controlled, and that the environmental performance and efficiency of the product structure be improved. Simultaneously, encouraging the application of low-carbon technologies and product innovation to enhance the competitiveness and sustainability of the aluminum industry.

(3) Accelerating technological progress and popularizing clean power

The government should expedite the development of clean energy and new power generation technologies, especially in the field of power production, to reduce the environmental impact of the aluminum industry. There should be an increased investment in and application of clean energy to provide a solid foundation for the efficient and environmentally friendly transformation of the aluminum industry.

(4) Industrial technology innovation and resource recycling

Upgrading the technology level of the aluminum industry and the recycling rate of waste products is crucial to achieving a low-carbon transition. The government should promote the reduction of carbon emission factors and the optimization of energy structure in primary and recycled aluminum production, while emphasizing the improvement of energy use efficiency.

(5) Transformation of energy structure and technological innovation

The aluminum industry has great potential for optimizing the energy structure and improving the efficiency of energy use. Promoting the transformation of the energy structure to a cleaner, low-carbon direction, accelerating technological innovation, and the implementation of relevant policy incentives are key to achieving this goal.

(6) Cumulative effects and synergies of policies

The cumulative effects of long-term government policies and synergies between policies play a crucial role in improving energy efficiency and environmental performance in the aluminum industry. It is recommended that the synergy of these policies be strengthened to promote the comprehensive effect of the aluminum industry in terms of energy saving, emission reduction, and resource recycling.

(7) International cooperation and promotion of environmental policies

Actively participate in international cooperation and absorb international advanced experience and technology to support the sustainable development of the aluminum industry. At the same time, formulate and implement effective environmental protection policies to ensure consistency with the country's long-term goals on environmental protection and energy efficiency.

Figure 6: LMDI decomposition of China's aluminum industry in 1990 ~ 2022 (base year is 1990s)

(Left: Changes and contribution rates of LMDI decomposition results in 1990, and right: Contribution rates of LMDI decomposition results in 1990.)

Figure 7: LMDI decomposition of China's aluminum industry in 1990 ~ 2022 (base year is N-1)

Author Contribution

Jing Chang: Conceptualization, Methodology, Writing-Original Draft, Data Collection and AnalysisProf. Guangwen Hu: Validation, Methodology, Data Analysis, Writing-Review & EditingProf. Yifan Gu: Project Administration, ResourcesProf. Yufeng Wu: Supervision, Writing-Review & Editing

ACKNOWLEDGEMENTS:

I would like to express my sincere gratitude to my supervisor, Prof. Hu, for his continuous guidance and encouragement. Special thanks are also due to the anonymous reviewers for their constructive comments that greatly improved the quality of this paper.

During the preparation of this work the author(s) used ChatGPT's DALL·E and Python in order to generate illustrations. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
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No competing interests reported.

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Strategies for Carbon Reduction in China's Aluminum Industry: An LMDI-based Decomposition and Sensitivity Analysis Framework

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Abstract

Figures

1 Introduction

2 Methodology and data

2.1 Define boundaries

2.2 Methodology

2.2.1 Calculation of CO₂

2.2.2 Logarithmic Mean Divisia Index

2.3 data sources

3 Results

3.1 Analysis of material flow in the aluminium industry

3.2 Overall Trends in Carbon Emissions and Energy Structure

3.3 Decomposition of Emissions and Impact of Production Volume

3.3.1 Method Ⅰ: The base year is 1990

3.3.2 Method Ⅱ: The base year is the previous year

4 Discussion

4.1 Policy sensitivity analysis

4.2 Market sensitivity analysis

5 conclusion and policy recommendations

5.1 conclusion

5.2 Policy recommendations

Declarations

Figure 6: LMDI decomposition of China's aluminum industry in 1990 ~ 2022 (base year is 1990s)

Figure 7: LMDI decomposition of China's aluminum industry in 1990 ~ 2022 (base year is N-1)

Author Contribution

ACKNOWLEDGEMENTS:

References

Additional Declarations

Supplementary Files

Status:

Version 1

Strategies for Carbon Reduction in China's Aluminum Industry: An LMDI-based Decomposition and Sensitivity Analysis Framework

Status:

Version 1

Abstract

Figures

1 Introduction

2 Methodology and data

2.1 Define boundaries

2.2 Methodology

2.2.1 Calculation of CO2

2.2.2 Logarithmic Mean Divisia Index

2.3 data sources

3 Results

3.1 Analysis of material flow in the aluminium industry

3.2 Overall Trends in Carbon Emissions and Energy Structure

3.3 Decomposition of Emissions and Impact of Production Volume

3.3.1 Method Ⅰ: The base year is 1990

3.3.2 Method Ⅱ: The base year is the previous year

4 Discussion

4.1 Policy sensitivity analysis

4.2 Market sensitivity analysis

5 conclusion and policy recommendations

5.1 conclusion

5.2 Policy recommendations

Declarations

Figure 6: LMDI decomposition of China's aluminum industry in 1990 ~ 2022 (base year is 1990s)

Figure 7: LMDI decomposition of China's aluminum industry in 1990 ~ 2022 (base year is N-1)

Author Contribution

ACKNOWLEDGEMENTS:

References

Additional Declarations

Supplementary Files

Status:

Version 1

2.2.1 Calculation of CO₂