Carbon Emission Peak Research Articles

Construction Contractors’ Carbon Emissions Reduction Intention: A Study Based on Structural Equation Model

The high carbon emissions of the construction industry affect China’s sustainable development. Therefore, reducing the carbon emissions of the construction industry is crucial for China to achieve “carbon peak” by 2030 and “carbon neutrality” by 2060. To understand the factors that affect contractors’ willingness to reduce carbon emissions. This study is based on the Theory of Planned Behavior (TPB) and incorporates three potential influencing factors: personal norms (PN), government regulation (GR), and policy support (PS). It constructs a structural equation model (SEM) to predict the influencing factors of carbon emission reduction intentions (CERI) among construction contractors. This study analyzes the key factors and mechanisms influencing construction contractors’ CERI. The study collected 311 valid questionnaires, which are suitable for SEM research, and the results indicate that: The results show that the model proposed in the study has an explanatory rate of 69% for developers’ willingness to reduce carbon emissions. The most significant influencing factor on construction contractors’ CERI is GR, followed by PS, subjective norms (SN), and perceived behavioral control (PBC). PN and behavioral attitude (BA) towards behavior do not significantly impact CERI. SN mediate the relationship between GR and CERI, while PBC mediates the relationship between PS and CERI. The research findings can guide the government and construction contractors to improve carbon emission reduction governance mechanisms and achieve peak carbon emissions and carbon neutrality.

Recent progress and emerging strategies for carbon peak and carbon neutrality in China

AbstractAs the global climate crisis intensifies, ecosystems, human society and economic activities are significantly affected. Countries around the world have successively put forward the goal of carbon neutrality or zero carbon. At the 75th session of the United Nations General Assembly, the Chinese government explicitly proposed making efforts to reach the goal of Carbon Peak (peak of carbon emissions before 2030) and Carbon Neutrality (Dual Carbon) (carbon neutrality before 2060). In October 2021, the CPC Central Committee and the State Council issued the “Opinions on Fully, Accurately and Comprehensively Implementing the New Development Concepts to Achieve Carbon Peak and Carbon Neutrality” and the Action Plan for Achieving Carbon Peak before 2030, specifying the targets and tasks related to achieving carbon peak and carbon neutrality in China. As the world's largest developing country, the world's largest manufacturer, and a country with the most complete industrial categories, China will face multiple challenges such as climate change, economic transition, and environmental protection, which requires systematic support from policy, economy, technology, and society. How to achieve the goal will be a great challenge to China's sustainable development. The academic community has conducted extensive exploration on the realization of China's carbon peak and carbon neutrality in many fields, such as energy transformation, industrial structure upgrading, transportation carbon reduction, urban planning and construction, carbon sink enhancement, low‐carbon technologies, green finance, and supporting policies. Among them, policy planning and technological innovation are the most important to achieve the goal of carbon peak and carbon neutrality. Second, industrial adjustment and enterprise implementation are also important. Therefore, this review will focus on the development status and prospects of policy support, technological innovation, industrial adjustment, and enterprise implementation for achieving dual carbon goals in China. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

Can the Energy Internet promote China's energy system to achieve carbon emission peak goal?

Energy Internet (EI) is typically characterized by digitalization and clean energy that seeks to revolutionize the energy system and reduce carbon emissions. Even though several scholars conclude that EI accelerates the clean energy transition of energy system, since the controversial relationship between digitalization and energy consumption in academia, current studies on the carbon emission reduction advantages of the EI are still in dispute. This paper employs the effect of EI's construction on the carbon emission peak goal of China's energy system based on the system dynamics model and different scenarios. The simulation results find that: (1) the construction of the EI could enable China's energy system to meet the carbon reduction commitment in 2028, with a carbon emission peak of 11.61 billion tons; (2) As digitalization and clean energy become more extensively employed, rising energy demand is satisfied by the manner of consuming low-carbon electricity energy. This is thought to be the primary factor that could promote China to achieve the carbon peak goal earlier than expected; (3) The advancement of digitalization has further promoted the decoupling of China's economic growth from carbon emissions. It is projected that China's energy system will still achieve the carbon peak goal by 2030 when the expected annual GDP growth rate is increased to 6.32%, 5.75%, and 4.6% for the years 2020–2025, 2026–2030, and 2031–2035, respectively. These findings might provide a new perspective for quantitative research on the environmental outcomes of the EI and the relationship between environmental improvement and economic growth.

Characterization and mapping of photovoltaic solar power plants by Landsat imagery and random forest: A case study in Gansu Province, China

Numbers and sizes of photovoltaic solar power plants have grown unprecedentedly over the last few years in China, which aims to achieve a carbon emission peak by 2030 and carbon neutrality by 2060. Thus, timely and accurate monitoring of photovoltaic solar power plants is crucial to the design and management of renewable electricity systems in China. Random forest algorithm has been used to map photovoltaic solar power plants at multiple scales, however, it always causes several salt-and-pepper noises, limiting its application at larger spatial scales. Here we first develop a photovoltaic solar power plant mapping method through integrating time series Landsat imagery, random forest, and morphological characteristics. Then we apply this method in Gansu Province, which has abundant solar and wind energy resources and provide large amounts of potential lands for photovoltaic development, and generate the annual photovoltaic maps from 2015 to 2020. We further analyze the spatial-temporal dynamics of sizes and areas of photovoltaic solar power plants and major land cover conversion of expansive photovoltaic regions. Finally, we discuss the reliability, uncertainties, implications, and future development of our improved methods. We find our photovoltaic mapping method can remove most of salt-and-pepper noises effectively, and the resultant maps in Gansu for 2020 have very high accuracies with user's and producer's accuracies of 97.57% and 99.22%, respectively. There are 165.29 km2 photovoltaic solar power plants in Gansu for 2020, and most of which are located in the northwestern Gansu. In addition, the photovoltaic with patch size > 1 km2 and ≤ 2 km2 (53.4 km2, 32.3%) has largest patch number (39, 15.7%). The improved photovoltaic mapping methods and further analysis in this study provide critical information for accurate and automatic classification of photovoltaic solar power plants in the future, as well as the environmental and sustainable development of solar energy in China.

Carbon emission peak forecasting and scenario analysis: A case study of educational buildings in Shanghai city

Accurate measurement of carbon emission is the prerequisite for achieving ‘Dual Carbon’ goal in China. In this study, a bottom-up method is proposed to forecast the carbon emissions based on the long-range energy alternatives planning system model which takes pre-primary, primary, and secondary schools in Shanghai city as research subject. The drivers' effects on carbon emission of educational buildings are analyzed with Kaya-LMDI method and three typical scenarios are defined, including normal, energy saving and green scenario. In addition, the electricity carbon emission factor is modified for accurate measure. The results show that these three kinds of schools in Shanghai can achieve carbon peak by 2030 under the above three scenarios. Floor area plays an important role in carbon emission, the peak time would be advanced by two years as the floor area evolves from normal to green scenario. The adoption of dynamically changing electricity carbon emission factor is also essential for accurate measurement. In the end, three policy implications are put forward based on findings. This study enriches the practice of carbon emissions research in building sector from long-term perspective, and provides a new perspective for carbon emission peak forecasting of a segmented industry.

Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China

Buildings are considered to have significant emission reduction potential. Residential building carbon emissions, as the most significant type of building-related carbon emissions, represent a crucial factor in achieving both carbon peak and carbon neutrality targets for China. Based on carbon emission data from Henan Province, a large province located in central China, between 2010 and 2020, this study employed the Kaya-LMDI decomposition method to analyze seven driving factors of carbon emission evolution, encompassing energy, population, and income, and assessed the historical reduction in CO2 emissions from residential buildings. Then, by integrating Kaya identity static analysis with Monte Carlo dynamic simulation, various scenarios were established to infer the future evolution trend, peak time, and potential for carbon emission reduction in residential buildings. The analysis results are as follows: (1) The carbon emissions of residential buildings in Henan exhibited a rising trend from 2010 to 2020, albeit with a decelerating growth rate. (2) Per capita household disposable income is the main driving factor for the increase in carbon emissions, but the household housing purchase index inhibits most of the growth of carbon emissions for the residential buildings in Henan, with the total carbon emission reduction of residential buildings reaches 106.42 million tons of CO2 during the research period. (3) During the period from 2020 to 2050, residential buildings in Henan Province will exhibit an “inverted U-shaped” trend in carbon emissions under the three static scenarios. The base scenario predicts that carbon emissions will reach their peak of 131.66 million tons in 2036, while the low-carbon scenario forecasts a peak of 998.8 million tons in 2030 and the high-carbon scenario projects a peak of 138.65 million tonnes in 2041. (4) Under the dynamic simulation scenario, it is anticipated that residential buildings in Henan Province will reach their carbon peak in 2036 ± 3 years, with a corresponding carbon emission of 155.34 million tons. This study can serve as a valuable reference for the future development of low-carbon pathways within the building sector.

Comparative Analysis of Research Trends and Hotspots of Foreign and Chinese Building Carbon Emissions Based on Bibliometrics

The construction industry has great potential for carbon emission reduction, which strongly impacts the peak of carbon emissions and carbon neutrality. This paper compares foreign and Chinese articles on building carbon emissions from publication objects, journals, subject categories, authors, and institutions. It discusses the differences in research trends and hotspots from keywords, reference co-citation analysis, and historical citation analysis. The results show that the number of publications on building carbon emissions steadily increased. The research on building carbon emissions in foreign articles is earlier and more systematic than that in China, and the output and influence of foreign articles are generally more prominent than those of Chinese articles. However, the production and influence of articles by certain Chinese authors and institutions have been remarkable. The topics of ‘CO2 emission’, ‘life-cycle assessment’, ‘environmental impact’, ‘greenhouse gas emission’, and ‘renewable energy’ are essential subjects for foreign and Chinese articles in the research field of building carbon emissions and the development trend is similar. The thematic direction of Chinese articles is more divergent and lacks well-developed themes that greatly influence other research themes. Finally, based on the research results, this study puts forward the potential future research direction of building carbon emissions. The results of this study will provide a current and systematic overview of this field, which will be helpful for future researchers to promote the development of research on building carbon emissions.

Impact assessment of vehicle electrification pathways on emissions of CO2 and air pollution in Xi'an, China

To assess the environmental impact of promoting the use of electric vehicles in road traffic on emissions of CO2 and air pollution in Xi'an, China, both the proportion of electric vehicles and the power generation mix should be considered. Here, vehicle ownership in 2021 served as the baseline scenario, and the vehicle development trend through 2035 was projected. Using emission factor models for fuel vehicles and the electricity generation required for running electric vehicles, this study estimated the related pollutants' emission inventories at 81 corresponding scenarios, in which differing vehicle electrification paths were coupled with power generation mix. Further, the degree to which different vehicle electrification paths impacted the CO2 and air pollutant emissions was also evaluated. The results show that, to achieve the goal of peak carbon emission in the road transport sector in Xi'an by 2030, the penetration rate of electric vehicles must reach at least 40 % in 2035, and the thermal power generation rate should satisfy the necessary coupling conditions. Although reducing the thermal power generation rate could mitigate the environmental problems, we find that electric vehicle development in Xi'an during 2021–2035 would still exacerbate SO2 emissions despite reducing the thermal power generation rate to 10 %. Finally, to avoid exacerbating the adverse effects on public health from vehicle-related pollutants, the penetration rate of electric vehicles should be at least 40 % in 2035, at which time for the 40 %, 50 %, 60 %, and 70 % scenarios, the corresponding thermal power generation rate should not exceed 10 %, 30 %, 50 %, and 60 %. This study systematically analyzed plausible development paths of electric vehicles from the perspectives of peak carbon emissions, air pollution control, and human health, whose findings can serve as a timely and valuable reference for reducing pollution and carbon in the field of road transport.

Theory and Practice of Green Finance under Carbon Neutrality Target

Global climate change is one of great challenges faced by international community currently. To cope with climate change and protect our Earth home on which human beings live, the countries of the world are proactively exploring development models suitable to their own national conditions, in which low carbon economy featured by low carbon emission and zero carbon emission has attracted much attention. In this background, China proposed a strategic decision of achieving peak carbon emissions before 2030 and carbon neutrality before 2060. This means China will transform from a high-carbon emission country to a low-carbon emission country, and a lot of work such as fund support, technical innovation and industrial structure adjustment should be carried out. While, green finance as a new financing way can guide capital into environmental protection and energy conservation field and promote a sustainable development, which is of important significance in advancing peak carbon dioxide emission and carbon centrality. This paper reviewed the basic concept and theoretical basis of green finance, analyzed the composition, main characteristics and operating effect of the EU’s green financial system, finally summarized the EU’s experience in the practice of green finance, and put forward some suggestions on relevant policies according to the actual situation of China.

Low-carbon development pathways for provincial-level thermal power plants in China by mid-century

Phasing out thermal power plants is vital to combatting climate change. Less attention has been given to provincial-level thermal power plants, which are implementers of the policy of phasing out backward production capacity. To improve energy efficiency and reduce negative environmental impacts, this study proposes a bottom-up cost-optimal model to explore technology-oriented low-carbon development pathways for China's provincial-level thermal power plants. Taking 16 types of thermal power technologies into consideration, this study investigates the impacts of power demand, policy implementation, and technology maturity on energy consumption, pollutant emissions, and carbon emissions of power plants. The results show that an enhanced policy combined with a reduced thermal power demand would peak carbon emissions of the power industry at approximately 4.1 GtCO2 in 2023. Meanwhile, most of the inefficient coal-fired power technologies should be eliminated by 2030. Carbon capture and storage technology should be gradually promoted in Xinjiang, Inner Mongolia, Ningxia, and Jilin after 2025. Energy-saving upgrades on 600 MW and 1000 MW ultra-supercritical technologies should be emphatically carried out in Anhui, Guangdong, and Zhejiang. By 2050, all thermal power will come from ultra-supercritical and other advanced technologies.

An overview of the policies and models of integrated development for solar and wind power generation in China

Under the goal of “Carbon Emission Peak and Carbon Neutralization”, the integrated development between various industries and renewable energy (photovoltaic, wind power) is of great significance in China. This paper summarizes the relevant policies, integration schemes and typical cases of the integrated development between renewable energy and other industries. First, the development status of wind and solar generation in China is introduced. Second, we summarize the relevant policies issued by the National Development and Reform Commission, National Energy Administration and other departments to promote the integrated development in photovoltaic and wind power generation in China. Third, eight kinds of photovoltaic three-dimensional development models are described, including “photovoltaic + agriculture, industry, environmental protection, transportation, architecture, communication, hydrogen and ecology”. Fourth, eight kinds of wind power three-dimensional development models are summarized, including “Offshore wind power + marine ranch, marine energy, marine tourism, marine oil and gas, hydrogen, communication, Energy Island” and “Onshore wind power + courtyard”. In the future, the promotion and application of the above integrated development projects will be accelerated. This overview aims to provide reference for the design in photovoltaic and wind energy systems and help potential investors to make decisions.

Study of the Carbon Neutral Path in China: A Literature Review

After the carbon peaking and carbon neutrality goals were proposed, different institutions and scholars carried out research on China’s medium- and long-term mitigation pathways. Through the literature review of China’s research on carbon neutrality, this paper finds that the zero-carbon energy transition is the key to achieving carbon neutrality. The main driving factors of reducing energy-related carbon emissions include the cleanliness of primary and secondary energy supply systems, the electrification of energy consumption and the development of hydrogen energy, energy efficiency improvement, carbon capture and storage (CCS), and negative emissions. Furthermore, based on the literature, this paper conducts a quantitative comparative analysis, and selects key indicators for comparative analysis and summary from seven dimensions, including economic and social development, carbon emission pathways, primary energy consumption, final energy consumption, final hydrogen energy consumption, electricity demand and supply, and installed capacity and structure of power generation. Main conclusions are as follows: (i) In terms of carbon emission pathways, the institutions generally believed that China will peak carbon emissions around 2028 and achieve carbon neutrality between 2050 and 2060. Achieving net-zero or near-zero emissions first in the power sector is the key to carbon neutrality across the society; (ii) In terms of energy supply, it is a consensus to increase the proportion of clean energy and reduce carbon emissions from the source. The proportion of clean energy in primary energy will increase to more than 85%, and the proportion of clean energy power generation and installed capacity will reach more than 90%; (iii) In terms of energy use, electricity will become the core of final energy consumption in the future. The predicted electricity consumption across the society will range 14.3–18.4[Formula: see text]PWh, and the predicted electrification rate will exceed 65%.

Analysis of China's non-ferrous metals industry's path to peak carbon: A whole life cycle industry chain based on copper

Copper is an essential nonferrous metal, and the adjustment of its whole industry chain structure is conducive to realizing a carbon peak in the nonferrous metal industry. We have performed a life cycle assessment to calculate the carbon emissions of the copper industry. Based on the carbon emissions scenarios of shared socioeconomic pathways (SSPs), we have utilized material flow analysis and system dynamics to analyze the structural changes in the copper industry chain from 2022 to 2060 in China. The results show that (1) the flows and in-use stocks of all types of copper resources will increase significantly. The overall copper supply may meet demand around 2040–2045 due to secondary copper production potentially replacing primary copper production to a large extent, and trade supply is the primary pathway for meeting copper demand. (2) The total carbon emissions from the regeneration system are the smallest (4 %), followed by the production and trade subsystems, accounting for 48 %. The embodied carbon emissions from copper product trade in China have expanded annually. (3) Under the SSP scenario, the copper chain carbon emission peak will be achieved by approximately 2040. Based on a balanced copper supply and demand scenario, the recycled copper recovery efficiency must reach 84.6 %, and the energy structure (the proportion of non-fossil energy in electricity) must reach 63.8 % by 2030 to achieve the carbon peak target for the copper industry chain in China. The above conclusions indicate that actively promoting adjustments in the energy structure and resource recovery processes may help encourage the carbon peak of nonferrous metals in China by realizing the carbon peak of the copper industry.

How to Improve Industrial Green Total Factor Productivity under Dual Carbon Goals? Evidence from China

This paper focuses on the relationship between green credit and industrial green total factor productivity under the dual carbon target. In recent years, weather extremes that break historical extremes have occurred frequently around the world, and the resulting loss of life and property has deepened people’s concern about climate change. As a responsible developing country, China has set the goal of reaching peak carbon emissions and reducing carbon intensity by 60–65% by 2030. In this context, based on China’s provincial-level data from 2006 to 2019, this paper first measures the growth rate of industrial green total factor productivity using the SBM-ML model, and then analyzes the impact of green credit on industrial green total factor productivity under the double carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We then analyze the impact of green credit on industrial green total factor productivity under the dual carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We find that green credit can improve the energy consumption structure and thus increase industrial green total factor productivity. In addition, the study finds that the interaction effect of green credit and environmental regulation suppresses the positive impact of green credit on industrial green TFP. This paper provides empirical evidence and policy implications for the orderly promotion of carbon peaking and carbon neutral efforts to effectively improve industrial green total factor productivity and promote high-quality economic development.

A Simulation Study on Peak Carbon Emission of Public Buildings—In the Case of Henan Province, China

With the continuous development of the social economy, carbon emissions from various buildings are increasing. As the most important category of building carbon emissions, the rapid peaking of public buildings is an important part of achieving carbon peak and carbon neutrality. This paper is based on the industrial background of the energy consumption structure of Henan Province, a central province in the developing country of China. Firstly, the energy consumption intensity of buildings and public buildings in Henan Province from 2010 to 2020 was calculated according to the energy balance sheet. The Kaya–LMDI decomposition method was also used to analyse the carbon emissions of public buildings, determining the impact of each influencing parameter on public buildings. Secondly, the scenario prediction model Monte Carlo was run 100,000 times to set the stochastic parameters of the variables in the model to predict the time of carbon peak and carbon emissions. The analysis results indicated that: ① Carbon emissions in Henan Province have exhibited a steady growth trend, increasing from 1533 t in 2010 to 6561 t in 2020; ② The primary factors influencing carbon emissions of public buildings in Henan Province were urbanization rate, public floor area per capita, and energy intensity per unit of public floor area; and ③ Carbon emissions of public buildings in Henan Province followed an inverted U-shaped distribution and are expected to peak at approximately 7423 t by the year 2035. The research method in this paper can guide the simulation study of peak carbon emission prediction in Henan Province based on the influencing parameters of carbon emission from different types of buildings. Moreover, the results of this paper can provide a reference for a more precise study of building carbon reduction in similar regions of developing countries.

An energy storage allocation method for renewable energy stations based on standardized supply curve

The goal of carbon emission peak and carbon neutrality requires China to vigorously develop renewable energy. However, renewable energy has obvious randomness and volatility. Therefore, it is necessary to configure energy storage systems for renewable energy stations to ensure the safe and stable operation of power systems. Given the problem of energy storage system configuration in renewable energy stations, it is necessary to consider the system load characteristics and design appropriate principles to formulate planned output curves for renewable energy stations, so that the joint output curve of renewable energy and energy storage system can match the system load curve as much as possible, which will reduce the system peak shaving pressure and promote the utilization of renewable energy. This paper first considers the impact of renewable energy stations with the different installed scales on the power system and designs the standardized supply curves differentially, and defines the supply curve deviation index to characterize the difference between the renewable energy–energy storage system joint output curve and the standardized supply curve. Then, to minimize energy storage system investment costs and supply deviation costs, an optimization model for energy storage system configuration in renewable energy stations is established, and output deviation control constraints are set to ensure that the operation of energy storage systems conforms to actual conditions. Finally, case studies analyze the energy storage system configuration results and the typical scenario operation results of a single renewable energy station and a renewable energy power generation base, which verify the rationality and effectiveness of the method proposed in this paper.

Can China Achieve Its Carbon Emission Peak Target? Empirical Evidence from City-Scale Driving Factors and Emission Reduction Strategies

The development of differentiated emission reduction strategies plays an important role in achieving carbon compliance targets. Each city should adopt carbon reduction strategies according to its carbon emission characteristics. China is a vast country, and there are significant differences between cities. Therefore, this study classifies 340 Chinese cities according to their carbon emission characteristics since 2020 and proposes differentiated emission reduction strategies accordingly. The results of the research show that Chinese cities can be divided into four categories, and they can strive to achieve their carbon peak targets by adopting differentiated emission reduction strategies. In the baseline scenario, Chinese cities will not be able to meet the peak carbon target by 2030. In the differentiated scenario, eco-agricultural cities, industry-led cities, and high-resource-availability cities will be able to achieve peak carbon by 2030. Unfortunately, resource-poor cities will not reach their peak. However, the extent to which their total carbon emissions contribute to the achievement of national goals is low, and their carbon emissions can be traded off for economic development by appropriately relaxing the constraints on carbon emissions. Therefore, in order to achieve China’s peak carbon goal, this study proposes emission reduction recommendations that should be adopted by different types of cities to form differentiated emission reduction strategies.

Using a Convolutional Neural Network and Mid-Infrared Spectral Images to Predict the Carbon Dioxide Content of Ship Exhaust

Strengthening regulations on carbon emissions from ships is important for ensuring that China can achieve its dual carbon aims of reaching peak carbon emissions before 2030 and achieving carbon neutrality before 2060. Currently, the primary means of monitoring ship exhaust emissions are the sniffing method and non-imaging optical remote sensing; however, these methods suffer from a low prediction efficiency and high cost. We developed a method for predicting the CO2 content of ship exhaust that uses a convolutional neural network and mid-infrared spectral images. First, a bench experiment was performed to synchronously obtain mid-wave infrared spectral images of the ship exhaust plume and true values for the CO2 concentration from the online monitoring of eight spectral channels. Then, the ResNet50 residual neural network, which is suitable for image prediction tasks, was selected to predict the CO2 content. The preprocessed mid-infrared spectral image of each channel and the corresponding true value for the CO2 content were input to the neural network, and convolution was applied to extract the radiation characteristics. The neural network then mapped the relationship between the true CO2 content and the radiation characteristics for each channel, which it used to predict the CO2 content in the ship exhaust. The results demonstrated that the predicted and true CO2 contents had a root mean square error of <0.2, mean absolute error of <0.15, and mean absolute percentage error of <3.5 for all eight channels. The developed model demonstrated a high prediction accuracy with one channel in particular demonstrating the best performance. This study demonstrates that the method used for predicting the CO2 content of ship exhaust based on convolutional neural networks and mid-infrared spectral images is feasible and has reference significance for the remote monitoring of ship exhaust emissions.

Prediction, evaluation and optimization of China's copper resource supply system under carbon constraints

Copper is one of China's strategic mineral resources, and its supply security is of great strategic significance to China. In this study, a model of China's copper resource supply system under carbon constraints is constructed using the system dynamics method, and the future supply potential of the system is analyzed and evaluated. Based on the evaluation results, the differential evolution algorithm is used to optimize the supply system to obtain the optimal supply structure that meets the supply-demand balance and carbon emission constraints. Under the carbon constraint scenario, although the carbon emissions of China's copper supply system have declined, a series of problems have also been exposed: such as insufficient primary copper production, excessive dependence on external copper resources, and excessive scrapping of unstable copper-containing products, The supply of secondary copper is affected by the import policy. These factors not only hinder the carbon emission reduction of the copper industry, but also make China's future copper supply full of uncertainty. The optimized supply system significantly reduces carbon emissions (12,664,300 tons per year on average) while meeting the supply-demand balance conditions. The optimal supply structure under the carbon constraint is 26.7 %, 36.3 %, and 37.0 % of the supply shares of the production, recycling, and trading subsystems, respectively. The study results found that improving recycling efficiency can effectively reduce carbon emissions, and when the recycling rate reaches 80 %, China's copper resource supply system will achieve “carbon peak” in 2025, with a peak carbon emission of 41.182 million tons. According to the results, this study suggests that policymakers should strengthen the exploration of primary copper resources, support the development of the secondary recovery industry, and realize diversified import distribution.

CarbonVCA: A cadastral parcel-scale carbon emission forecasting framework for peak carbon emissions

Forecasting cities' carbon emissions is an essential support for peak carbon emissions. Previous studies have mainly focused on estimating carbon emissions at large regional scales. Higher spatial resolution mapping of carbon emissions and simulation of future scenarios are important to support locally appropriate policy guidance to reduce carbon emissions. This paper proposes a bottom-up cadastral parcel-scale Carbon emission forecasting framework based on Vector-based Cellular Automata (CarbonVCA) by integrating land use modelling and carbon emission estimation. Shenzhen's cadastral parcel-scale carbon emissions from 2020 to 2060 are predicted as a case study. A good performance was achieved using CarbonVCA (MAPE = 19.017 %, RMSE = 0.175 Mtpa (C)). Three progressive scenarios are designed for carbon emission simulation from land use planning and energy structure restructuring perspectives. The designed carbon emission reduction scenario limits carbon emissions and enables Shenzhen to achieve peak carbon emissions between 2025 and 2030. However, the efforts to reach peak carbon emissions may prompt the relocation of industrial land to the suburbs. Such areas will need appropriate infrastructure construction to break through terrain and landscape constraints, maintain economic growth and achieve sustainable development. This framework can forecast a high spatial resolution of land-use-based carbon emissions, which helps construct low-carbon cities.