Industrial Carbon Emissions Research Articles

Spatiotemporal evolution and influencing factors of urban industrial carbon emission efficiency in the Mid-Yangtze River urban agglomeration of China

Carbon emissions from energy consumption caused by industrial production have become an important factor in global warming, and China now has the highest global carbon emissions, with enormous pressure to reduce emissions. The Mid-Yangtze River urban agglomeration (MYRUA), which is an important region for China, also faces the contradiction of balancing environmental protection and economic production. Currently, there is little discussion on low-carbon pollution research in the MYRUA in China. Therefore, this study takes the MYRUA as the research object, uses a slack-based model (SBM) and exploratory spatial data analysis (ESDA) to explore the spatiotemporal evolution of the industrial carbon emission efficiency (ICEE) of the MYRUA in China from 2006 to 2019, and empirically analyses the factors influencing the ICEE based on a spatial econometric model. The results show that (1) in the period 2006–2019, the ICEE in the MYRUA region generally exhibited a “jagged” trend of decreasing, then increasing until finally decreasing again. Spatially, ICEE generally exhibited a dynamic trend of being low throughout, with high-efficiency areas tending to move to the center and low-efficiency areas being scattered. (2) The global Moran's I coefficient for ICEE ranged between 0.002 and 0.213, with the highest Moran's I value and significant spatial correlation occurring in 2006, after which the value gradually decreased. On the local autocorrelation, the ICEE in 2006 exhibited an agglomeration effect and weakened after 2010. (3) In 2019, the level of industrialization (LI) and the level of external openness (LEO) in the MYRUA changed from nonsignificant to significant positive correlations, and the LEO had the largest impact. The energy consumption structure (ECS) was always significantly negatively correlated. The levels of social development (LSD) and environmental regulation (ER) changed from showing a significant positive correlation to showing a nonsignificant correlation. In conclusion, ICEE is affected by interactions of multiple factors. In the future, the ECS of the MYRUA should be continuously optimized and replaced by clean energy. In addition, foreign investment compensates for the lack of production and technology research funds, which can increase investment and promote the digitalization of manufacturing enterprises.

Research on Provincial Distribution of Total Carbon Emissions in the Power Generation Industry under Carbon Neutrality Constraints

The power generation industry in China is at the forefront of implementing carbon trading market policies, playing a crucial role in carbon emission reduction. Carbon allocation in each province is pivotal for future economic development and achieving a gradual and orderly carbon peak. By analyzing total carbon emissions from 2012 to 2021 and examining emission responsibilities from a producer perspective, this study extends the STIRPAT model to evaluate factors influencing carbon emissions in the national and provincial power generation sectors. Key findings highlight the urgent need for industrial structure changes in provinces like Xinjiang, Tibet, Guangdong, Shandong, and Jiangsu, which bear significant emission reduction responsibilities. The spatial and temporal distribution of carbon emissions is shifting from the southeast coast to central and western regions. Factors such as energy consumption, electric power intensity, urbanization rate, power structure, economic development level, and industrial composition significantly impact carbon emissions. To achieve carbon peak goals, a multifaceted approach is essential for reducing emissions in China's power generation sector, emphasizing the need for strategic interventions across various perspectives.

Does the new energy vehicles subsidy policy decrease the carbon emissions of the urban transport industry? Evidence from Chinese cities in Yangtze River Delta

New energy vehicles (NEV) have become an important driving force for carbon reduction in the transportation industry. This paper adopts the extended environmental pressure assessment (STIRPAT) model and the time-varying difference in differences (DID) model to evaluate the effectiveness of the NEV subsidy policy to achieve sustainable governance. The results show that the NEV subsidy policy can significantly decrease the carbon emission of the transport industry. The mechanism analysis results indicate that the NEV subsidy policy can decrease carbon emissions by promoting a green transformation of the consumer car purchasing structure. Further analysis found that a “fraudulent subsidy” can significantly weaken the policy effect of subsidies. The results of heterogeneity analysis indicate that the subsidy policies introduced by different levels of government have different effects. The subsidy policy of the central government has a more significant effect, and repeated subsidies from central and local governments will weaken the policy's effectiveness. These findings provide valuable insights for policymakers in developing countries to optimize subsidies for new energy vehicles in reducing carbon emissions in the transportation industry.

Preventing the Immense Increase in the Life-Cycle Energy and Carbon Footprints of LLM-Powered Intelligent Chatbots

Intelligent chatbots powered by large language models (LLMs) have recently been sweeping the world, with potential for a wide variety of industrial applications. Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development, providing several alternatives beyond the famous ChatGPT. However, training, fine-tuning, and updating such intelligent chatbots consume substantial amounts of electricity, resulting in significant carbon emissions. The research and development of all intelligent LLMs and software, hardware manufacturing (e.g., graphics processing units and supercomputers), related data/operations management, and material recycling supporting chatbot services are associated with carbon emissions to varying extents. Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact. In this work, we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots. Based on a life-cycle and interaction analysis of these phases, we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints. While anticipating the enormous potential of this advanced technology and its products, we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.

Environmental Kuznets curve of carbon emissions from China’s forest products industry and decomposition of factors influencing carbon emissions

Carbon emissions from China’s forest products industry were considered based on the data of 2001-2020. Then a carbon emissions Kuznets curve was constructed to judge the relationship between the economic development level and carbon emissions. The logarithmic mean Divisia index (LMDI) was used to analyze the influencing factors of carbon emissions. The carbon emissions from China’s forest products industry showed a trend of rapid growth in the early stage and slow decline in the later stage, increasing from 19.46 million tonnes in 2001 to 54.18 million tonnes in 2020. Consumption of raw coal was the main reason for the increase in carbon emissions. There was an inverted-U relationship between the economic development level and carbon emissions, and the industry output value of CNY 3306.56 billion was the theoretical inflection point. The current economic development level of the industry was in the left-half part of the inverted “U” shape, indicating that carbon emissions from this industry will continue to increase with the increase of industrial output. Economic development was the key factor driving the increase of carbon emissions in the forest products industry, while the energy intensity was the key factor inhibiting the growth of carbon emissions.

CarbonKG: Industrial Carbon Emission Knowledge Graph-Based Modeling and Application for Carbon Traceability of Complex Manufacturing Process

Abstract In the context of the 2030 carbon dioxide emissions peak target, achieving carbon neutrality in manufacturing is essential. However, the complex and extensive supply chain, ranging from raw materials to the final product, presents significant challenges in assessing the carbon footprint throughout the lifecycle. This paper concentrates on the manufacturing process and introduces a modeling approach for quantifying and predicting carbon emissions, utilizing industrial intelligent technologies like process mining and knowledge graphs. First, it is crucial to establish a comprehensive carbon emission quantification model for each manufacturing stage, encompassing the energy, material, personnel, and carbon flow. Subsequently, this paper proposes an industrial carbon emission knowledge graph-based model (CarbonKG) to record and compute emissions at each production stage. Furthermore, process mining technology aids in analyzing the global distribution and movement of carbon emissions within the manufacturing process. Finally, this research presents a two-stage predictive approach for manufacturing process carbon emissions based on CarbonKG. The first stage involves initializing a local order carbon graph for prediction and developing a model to find similar cases. The second stage uses a graph-matching model to identify the Top-K similar order cases, using their carbon emission data for comprehensive prediction. Moreover, the feasibility of the proposed method was verified using actual production process data from industrial companies.

An assessment of the carbon emissions of China's ICT system from the demand and supply perspectives

Previous research has predominantly examined China's Information and Communication Technology (ICT) industry's carbon emissions through the lens of technological progress, overlooking impacts from both demand and supply perspectives. We employ a subsystem input-output model to analyze the total emissions of China's ICT industry from 2002 to 2020, decomposing them into direct, intra-sectoral, feedback, and spillover components from both perspectives. Our findings reveal that between 2002 and 2020, demand-driven emissions increased by 205.1 %, while supply-driven emissions surged by 496.4 %. From both demand and supply perspectives, the spillover component emerged as the dominant contributor from 2002 to 2020, particularly in 2020, accounting for more than 99 % of the total emissions. From a demand-driven perspective, we identify ICT manufacturing as the primary emissions source, contributing to over 66 % of the total emissions during the period and triggering significant spillover emissions in the power and heavy manufacturing sectors. Conversely, the supply-driven approach highlights ICT services as the major emitter, accounting for over 70 % of the total emissions between 2002 and 2020, with notable spillover effects observed in the transport sector. We highlight the significance of shaping consumption behaviors related to ICT manufacturing products and improving emissions efficiency in electricity and heavy manufacturing, both crucial intermediate inputs in ICT production, from a demand perspective. From a supply perspective, promoting the adoption of clean technologies among downstream users of ICT services could aid China's emissions mitigation efforts in the digital era.

The Influence of Quartz Powder on the Mechanical–Thermal–Chemical–Durability Properties of Cement-Based Materials

Using industrial by-products to replace cement is an important way to reduce carbon emissions in the cement industry. The purpose of this article is to understand the effect of quartz powder on the properties of cement-based materials. Experimental studies were conducted on the macroscopic and microscopic properties of cement-based materials mixed with quartz powder to evaluate their feasibility as a replacement for cement. The substitution rates of quartz powder were 0% (Qu0), 7.5% (Qu7.5), and 15% (Qu15). The test time was from 1 day to 28 days, and the main results are as follows: In the early stage of the hydration reaction, as the amount of quartz powder substitution increases, the cumulative hydration heat increases. This is mainly because the nucleation effect of quartz powder accelerates the hydration reaction of cement. In the later stage of the hydration reaction, as the amount of quartz powder substitution increases, the cumulative heat of hydration decreases. This is mainly due to the diluting effect of quartz powder. For Qu0, Qu7.5, and Qu15, the decrease in compressive strength after 1 day is not obvious. The decrease in compressive strength at 28 days is more obvious. Overall, there are exponential relationships between the UPV measurement or surface resistivity results and the compressive strength measurement results at 1, 3, 7, and 28 days. The XRD test results show that the main products of the reaction are AFt, CH, Hc, and Mc. From Day 1 to Day 28, the content of Mc becomes evident. The test results for TG showed that, as the amount of quartz powder substitution increases, the mass loss decreases. For different specimens of Qu0, Qu7.5, and Qu15 at different test times (3 and 28 days), there is an exponential function relationship between chemically bound water and strength. A numerical hydration model is proposed for cement–quartz binary blends. The parameters of the hydration model are determined based on the hydration heat normalized by the cement mass. Moreover, the hydration heat at 28 days is calculated using the proposed model. The strength development of all specimens and all test ages can be expressed as an exponential function of hydration heat.

Dynamic assessment of the abatement effects of the low-carbon practices in the prefabricated building supply chain

PurposePrefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.Design/methodology/approachThis study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.FindingsResults show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.Originality/valueThis study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

Evaluation of marginal abatement cost and potential reduction in China's industrial carbon emissions: A quadratic directional output distance function approach

As a relevant indicator for quantifying the value of carbon emissions, the marginal abatement cost (MAC) of carbon emissions has received increasing attention from academics and policymakers. This study uses a quadratic directional output distance function to analyse the technical efficiency, potential emission reduction and shadow prices of China's industrial carbon emissions. The results show that the technical efficiency of China's industry gradually decreased during the sample period. From the perspective of regions with different carbon intensity and industrial output, regions with lower carbon intensity and higher industrial output gradually closed to the optimal frontier for the technology use level and had relatively high technical efficiency. Rising technical inefficiency and carbon emissions led to a potential emission reduction that also exhibits an upwards trend. In addition, the MAC of industrial carbon emissions exhibits a U-shaped trajectory, with 2011 as the turning point. Generally, in recent years, regions with lower carbon intensity and those with higher industrial output have a relatively high MAC for industrial carbon emissions. The empirical findings reveal that a carbon emission reduction policy should be formulated and targeted to each province, and the principle of ‘easy before difficult’ can be followed to promote emission reduction.

Cradle-to-gate embodied carbon assessment of green office building using life cycle analysis: A case study from Sri Lanka

One of the most significant contributors to the economies of many nations is the building and construction sector. However, this industry is one of the world's most significant contributors to greenhouse gas emissions. Hence, the concept of green building (GB) has emerged as the cornerstone of sustainable development. Even though GBs have a variety of advantages, the use of low-carbon materials is still lacking for both traditional buildings and green buildings in the Sri Lankan context, and energy-intensive building materials are responsible for 80% of the carbon emissions of the construction industry in the world. In Sri Lanka, buildings make up more than 70.9% of contracts and consume a significant amount of raw materials, and office buildings use 33% of the raw materials. Therefore, this research aimed to assess the embodied carbon (EC) of green office buildings and to provide potential measures to reduce the EC of buildings in Sri Lanka. Following the case study research strategy, the EC emission was calculated using the Life Cycle Assessment (LCA) method for an eight-storey Platinum-rated green office building in Sri Lanka. The results showed that the green office building had an EC 583.82 kgCO2e/m2 of the gross floor area. Reinforcement steel was found to be the significant EC material, contributing 47.88% of the total EC. In addition to that, ready-mixed concrete, cement block, plywood, and aluminium are the other highly intensive EC materials in this study. The findings showed that the use of low-carbon materials, materials minimising design, utilisation of reusable or recycled materials, utilisation of local or regional materials, and utilisation of eco-labelling materials are potential measures to reduce cradle-to-gate EC in the building construction industry in Sri Lanka.

The initial stages of cement hydration at the molecular level

Cement hydration is crucial for the strength development of cement-based materials; however, the mechanism that underlies this complex reaction remains poorly understood at the molecular level. An in-depth understanding of cement hydration is required for the development of environmentally friendly cement and consequently the reduction of carbon emissions in the cement industry. Here, we use molecular dynamics simulations with a reactive force field to investigate the initial hydration processes of tricalcium silicate (C3S) and dicalcium silicate (C2S) up to 40 ns. Our simulations provide theoretical support for the rapid initial hydration of C3S compared to C2S at the molecular level. The dissolution pathways of calcium ions in C3S and C2S are revealed, showing that, two dissolution processes are required for the complete dissolution of calcium ions in C3S. Our findings promote the understanding of the calcium dissolution stage and serve as a valuable reference for the investigation of the initial cement hydration.

Disentangling the direct and indirect impacts of non-pharmaceutical interventions on production activities and carbon emissions

Non-pharmaceutical interventions (NPIs) have been crucial in mitigating the COVID-19 pandemic, yet they've also heterogeneously disrupted production across sectors, highlighting socio-economic vulnerabilities. This study develops an ensemble model combining a Bayesian hierarchical model with supply chain dynamics to assess the direct and indirect impacts of three NPI themes—Gathering Restrictions, Mobility Restrictions, and Health Measures—on industrial output and carbon emissions in Beijing. The findings show that Health Measures enhanced local economic output by 1.12 %, yet also boosted regional carbon emissions by 6.15 %, primarily from the increased production in the Electric and Heat Power Production (EHP) sector, with a carbon intensity 1.96 times above the regional average. This emphasizes the urgent need for decarbonizing EHP to align health and environmental objectives in future pandemics. Furthermore, Mobility Restrictions had the most severe economic impact, 2.01 times greater than Gathering Restrictions, with Stationery Manufacturing being the most affected. Textile Manufacturing showed particular sensitivity to both Gathering Restrictions and Health Measures. These insights contribute to a more nuanced understanding of NPIs' impacts, supporting the development of balanced pandemic response strategies that consider economic, environmental, and health outcomes.

Route Planning of Supermarket Delivery through Third-Party Logistics Considering Carbon Emission Cost

China’s policies about reducing carbon emissions mainly focus on saving energy and reducing pollutant emissions. However, the carbon emissions of the logistics industry remain high. Thus, logistics companies should not only reduce distribution costs, but also consider the impact of carbon emissions when planning distribution routes. This paper studies the supermarket delivery distribution route planning problem considering carbon emissions. Aiming at the lowest economic operating cost composed of fixed cost, driving cost, and carbon emission cost, we propose a grey wolf optimized genetic algorithm to generate delivery route plans, where the social rank and hunting behavior of the grey wolf optimization algorithm are integrated into the selection operation of the genetic algorithm. Finally, a real case of a large third-party logistics enterprise in Beijing is studied. The case study results verify the effectiveness and applicability of the model and algorithm.

Pathway to net zero: Reviewing sustainable aviation fuels, environmental impacts and pricing

Supporting the pathway to net zero carbon emissions in the aviation industry, sustainable aviation fuels (SAF) will contribute to a large extent to reduce net CO2 emissions in the next decades to deliver on climate targets. For this reason, the large-scale uptake of SAFs in aviation is on top of the agenda of regulatory policy. However, challenges remain for building the respective infrastructure and supply chains at the appropriate scale to produce and distribute SAF at a reasonable cost. Currently, only one percent of fuels consumed by airlines in Europe are blended with sustainable aviation fuels. The paper examines current SAF production pathways, environmental benefits, and estimated fuel prices from the state-of-the art literature. Further, regulatory policies established by governments, regulatory agencies and industry associations are examined, regarding blending mandates in different regional markets. The authors conclude with the statistical analysis of minimum selling prices for different types of SAF, and discuss their respective availability.

Towards low-carbon steel: System dynamics simulation of policies impact on green hydrogen steelmaking in China and the European Union

Green hydrogen (GH) has been included in the steel emission reduction plans of many countries. This study evaluates the status quo of GH and steel industry and the related subsidy and regulatory policies in two major steelmaking countries/regions: China and the European Union. A system dynamics model coupling GH and steel industry is established to conduct simulation analysis of the low-carbon transition path of GH replacing fossil fuels in these two countries/regions' steel industry under several carbon emission reduction scenarios. Results verify the feasibility of using GH in the steelmaking and GH's contribution to the steel industry's carbon emission reduction. And this study assesses the policy impacts on the development of green hydrogen steel and gives specific policy implications on the timing and measures. The methodology and policy tools in this study also provide the reference for other countries who are still in wait-and-see attitude towards the development of GH steel.

The Influencing Factors of Carbon Emissions in the Industrial Sector: Empirical Analysis Based on a Spatial Econometric Model

To promote the low-carbon, high-quality development of China’s industrial sector and achieve the national carbon peak goal as soon as possible, this study explores the influencing factors of carbon emissions among industrial sectors. Based on the panel data of 36 industrial sectors in China from 2009 to 2021, the spatial effects and characteristics of industrial sectors are examined by the spatial Durbin model (SDM) based on analyzing the spatial correlation among industrial sectors. The results show the following: (1) Moran’s I statistical results show that China’s industrial carbon emissions have a strong positive spatial correlation, and with time, the spatial correlation between industrial sectors gradually increases. (2) The empirical results of the whole industrial sector show that the property rights structure, capital intensity, and energy structure are the main driving forces promoting carbon emission reduction; the grouping analysis results show that the impact of FDI and property rights structure on the carbon emissions of the industrial sector in different sample groups is different. Among them, the energy structure and research and development play a role in reducing carbon emissions in each sample group. (3) Therefore, in the future, to reduce carbon emissions in the industrial sector, it is necessary to inhibit growth factors and promote the role of reduction factors; optimizing the energy structure and improving the rationality of the property rights structure are effective ways to achieve energy conservation and emission reduction.

Carbon emissions in the logistics industry: driving factors and decoupling effects.

The explosive growth of the logistics industry has led to an increase in energy consumption and carbon emissions. To reduce emissions and increase the efficiency of the logistics industry, we studied the driving factors and decoupling effects of carbon emissions of logistics industry (LICE). First, an energy coefficient method is used to calculate the LICE. Second, the Logarithmic Mean Divisia Index (LMDI) decomposition method is used to decompose the driving factors of LICE into five types. Third, the decoupling model is used to explore the decoupling relationship between economic growth and LICE. Considering Anhui Province as an example, this study describes the method's implementation process based on a comparison of the four Yangtze River Delta provinces and cities. The results indicate that the growth rate of LICE in Anhui Province has decreased during the research period, from 9.7% in 2013 to 2.1% in 2021; however, the Tapio decoupling elasticity has been approximately 0.4 for the last 2 years, remaining in a weak decoupling stage from economic development. The LMDI decomposition results indicate that the average contribution of economic level to carbon emissions is 1.763. This study proposes some solutions and recommendations for the logistics industry's low-carbon development to offer methodological and theoretical support for LICE research.

The carbon-energy-water nexus of the carbon capture, utilization, and storage technology deployment schemes: A case study in China's cement industry

Carbon capture, utilization, and storage (CCUS) technology plays a crucial role in the transition towards low-carbon emissions in the cement industry. However, it also results in numerous energy and water consumption. To formulate proper CCUS deployment strategies, it is essential to optimize spatial CCUS layouts and examine the carbon-energy-water nexus of the technology. This study combines China's cement emission inventory, representing carbon sources, with carbon storage sites data, and develops a source-sink matching model to determine optimal CCUS deployment schemes under different mitigation target scenarios. In addition, the spatial distribution of energy and water consumption impacts, as well as the carbon-energy-water nexus, are evaluated. Results indicate that the deployment of CCUS in 229, 445, and 627 cement plants is necessary to mitigate 20%, 40%, and 60% of carbon emissions in China's cement industry, respectively. The estimated economic costs of these schemes are 79.4, 167.9, and 269.5 billion CNY, posing a significant financial challenge for the industry. Carbon capture technologies greatly influence the carbon-energy-water nexus of the CCUS deployment schemes, with net energy and water consumption ranging from 271.5 to 2410.9 PJ and − 28.5 to 872.4 million m3. Totally, 13–15 provinces achieve synergic carbon mitigation and water extraction effects by using the technologies with low water intensity. Nevertheless, trade-offs between carbon and energy exist regardless the technology. In conclusion, this study provides valuable insights for planning CCUS deployment schemes by revealing the multi-dimensional impacts on economic costs, energy consumption, and water consumption, which supports the decarbonization of China's cement industry.

Evolution and Influencing Factors of Spatial Correlation Network of Construction Carbon Emission in China from the Perspective of Whole Life Cycle

Based on the whole life cycle perspective, the carbon emissions of the provincial construction industry in China from 2011 to 2019 were calculated from the production, construction, operation, and demolition stages of building materials. A spatial correlation network matrix of the carbon emissions in the construction industry was constructed by using the modified gravity model, and the structural characteristics of the correlation network were described by introducing social network analysis. Through the quadratic assignment program, the spatial correlation matrix of carbon emissions in the construction industry and its influencing factors were regressed and analyzed. The conclusions were as follows:① the spatial correlation network of carbon emissions in China's construction industry clearly existed. The network density and network correlation numbers were gradually rising, and the network tightness and stability were gradually improving. ② Shanghai, Tianjin, Beijing, and Jiangsu had a higher degree centrality and closeness centrality, which are the core and dominant positions of the spatial correlation network of carbon emissions in the construction industry. Zhejiang replaced Shanghai in the top four from 2013 to 2018, and the betweenness centrality of each province had unbalanced characteristics. ③ Beijing, Tianjin, Jiangsu, Inner Mongolia, Shanghai, and Shandong were "net beneficiaries" blocks, receiving the carbon emissions from other regions. Four provinces, Guangdong, Chongqing, Fujian, and Shandong, belonged to the "broker" sector, achieving a dynamic balance between the production and consumption sides of building carbon emissions. The remaining 20 provinces played a "net spillovers" role, actively sending carbon emissions from the construction industry to other provinces. The correlation between blocks was much greater than the correlation relationship within the blocks. ④ Industrial structure, urban population, spatial adjacency, consumption level, and construction industry process structure had a significant influence on the spatial correlation of carbon emissions in the construction industry. The greater the inter-provincial differences in industrial structure, urban population, spatial adjacency, and consumption level, the greater the similarity of inter-provincial construction industry process structure, and the stronger the spatial correlation and spatial spillover of the construction industry carbon emissions. Finally, according to the evolution characteristics and influencing factors of the spatial correlation network of building carbon emissions, relevant countermeasures and suggestions were provided for the collaborative carbon reduction development of the construction industry region.