Reduce Carbon Emissions Research Articles

Importance of FinTech and green finance to achieve the carbon neutrality targets: a study of australian perspective

Abstract Based on Australian data from 2000 to 2022, this study examines how FinTech will influence the nation’s environmental future. The research shows that by directly intervening, FinTech-supported green finance is a chief driver of carbon reductions. This study contributes to existing literature by examine the role of Fintech and green finance in carbon neutrality targets of Australia. The complex web of interrelationships between technological and financial innovations is revealed as a factor that impacts the environment. When applied to Australia, which has its own FinTech industry and commitment to sustainable development, these results become even more eye-catching. This synergy takes global dimensions, with the research demonstrating a need to harmonize technological development and workable financial plans if environmental breakthroughs are to be made. However, the study points out to policymakers that they must foster a nurturing environment for digital financial innovations, develop stronger regulatory mechanisms, and encourage sustainable financial products. In terms of methodology, the research uses regression and mediation analysis to reach its conclusions. This research provides empirical evidence on the critical role of Fintech in advancing environmental sustainability in Australia, highlighting its direct and mediated effects on carbon emission reductions. By demonstrating the synergistic impact of technological and financial innovations, the study offers valuable insights for policymakers to foster a supportive ecosystem for sustainable digital finance.

Comparative Anslysis of Carbon Emission Reduction Policies in China’s Manufacturing and Transportation Sectors

This study evaluates China’s environmental policies, specifically the increase of carbon emission tax rates and the reduction of carbon emission intensity, by developing a New Keynesian Dynamic Stochastic General Equilibrium (NK-DSGE) model that incorporates energy consumption and carbon emissions. The production sector is segmented into manufacturing, non-manufacturing, and transportation, with transportation services acting as inputs for both manufacturing and non-manufacturing firms. We construct four cases within two scenarios, each characterized by distinct targets and policies. After calibrating and estimating the relevant parameters, we compare carbon reduction outcomes and economic fluctuations across the two scenarios. Our findings indicate that when targeting the same carbon emission tax rate increase or carbon emission intensity ratio reduction, policies that increase the carbon emission tax rate or reduce carbon emission intensity implemented in the manufacturing sector achieve greater carbon emission reductions compared to the same polices implemented in the transportation sector. Meanwhile, compared to the latter case, output experienced a greater decline, and inflation exhibited a more substantial increase in the former case. However, when the quantities of carbon emission reductions are approximately the same in the first quarter, policies that increase the carbon emission tax rate or reduce carbon emission intensity enacted in the transportation sector demonstrate superior performance relative to the same polices implemented in the manufacturing sector. This leads to smaller final output reductions and milder inflation increases. In summary, for equivalent levels of carbon emission reductions, policies implemented in the transportation sector yield more favorable economic outcomes than those applied in the manufacturing sector.

Patterns and Drivers of CO2 and CH4 Fluxes in an Urbanized River Network and Their Response to Restoration

AbstractCarbon evasion from urban river networks becomes increasingly significant as urbanization accelerates. However, there remains a limited understanding of the overall carbon emission impact integrating CO2 and CH4 dynamics, particularly in response to ecological restoration efforts. In this study, we investigated patterns of fluvial CO2 and CH4 diffusive fluxes across an urban river network in Wuxi, China. Our results reveal that water quality variables, especially dissolved oxygen (DO) and phosphorus content, predominantly influence the variability of carbon emissions. These factors exhibit a stronger correlation with CO2 emissions compared to CH4, indicating a net increase in carbon emissions as water quality deteriorates. Seasonally, higher water temperatures, phosphate levels, and lower DO concentrations lead to increased carbon emissions during summer months. Spatially, areas with lower carbon emissions (averaged 86 mmol m−2 d−1 CO2 and 0.13 mmol m−2 d−1 CH4) are primarily situated near the lake and in river sections where significant water quality improvements have been achieved through ecological restoration efforts. Cluster analysis shows that over 60% of high‐carbon emission (averaged 162 mmol m−2 d−1 CO2 and 1.21 mmol m−2 d−1 CH4) sites in the study area have undergone ecological restoration, suggesting potential for further carbon emission reduction through enhanced restoration practices. Our findings underscore the importance of implementing carbon reduction strategies such as nutrient removal and aeration for oxygenation within water ecological restoration initiatives. Effective matching of restoration strategies holds further potential for mitigating carbon emissions from urban river networks.

Adaptability analysis of H2-rich gas injection and sintered ore performance with different raw material ratios

As a source substitution technology that reduces pollutants emission and optimizes sinter properties, H2-rich gas injection-assisted iron ore sintering holds significant practical value. This study analyzed the adaptability of this technology to different ore blend ratios and basicity levels by comparing sintering indexes, pore structure, mineral phase composition, and metallurgical performance before and after H2-rich gas injection. The carbon emission reduction following H2-rich gas injection was calculated. The results indicate that increasing the proportion of high-silica, low-alumina ore (Ore-A) and basicity, along with H2-rich gas injection, can effectively enhance sinter yield and quality, but shrink the pore structure of sinter. Under H2-rich gas injection conditions, decreasing Ore-A ratios and increasing basicity can augment SFCA phase formation and mineral phase uniformity, thereby improving the anti-pulverization ability and reductivity of the sinter. H2-rich gas injection presents better adaptability to sintered ore with lower Ore-A ratio and basicity, which can achieve greater improvements in the sintering indexes, RDI, and RI. For a 265 m2 sinter plant producing sinter with 18 wt.% Ore-A and 2.0 basicity, annual CO2 emissions can be reduced by approximately 40,000 t.

Long-term investigation of uniaxial compressive and self-sensing performances of ultra-high performance seawater sea-sand concrete incorporating superfine stainless wires: Insights into underlying mechanisms and theoretical models

Developing intrinsic self-sensing concrete is expected to provide a digital intelligence solution to address the infrastructure’s challenges in terms of safety, lifespan, resilience, and carbon emission reduction. Using seawater and sea-sand as well as corrosion-resistant conductive fillers to fabricate self-sensing ultra-high seawater sea-sand performance concrete (UHPSSC) with outstanding mechanical and durability performances is the prerequisite for realizing localized resource utilization and in-situ monitoring of marine infrastructure. However, the potential effect of ions from seawater and sea-sand on the long-term stability of mechanical and electrical performances cannot be ignored. This paper presents a long-term investigation of uniaxial compressive, electrical, and self-sensing performances of superfine stainless wires (SWs) reinforced UHPSSC under natural curing. The results show that incorporating 1.5% SWs improves the compressive strength, elastic modulus, peak strain, and toughness of UHPSSC by 25.0%, 11.7%, 33.8%, and 119.2%, respectively. The established statistical damage constitutive models based on Weibull strength theory highlight the roles of SWs in delaying crack initiation. The dense microstructure of SWs-reinforced UHPSSC inhibits the growth of expansive hydration products formed by corrosive ions, thus guaranteeing its long-term strength development. Additionally, due to incorporating 1.5% SWs, the electrical resistivity of UHPSSC is reduced by seven orders of magnitude, with a strain sensitivity of 119.1 under monotonic compressive loading and a monitoring stress range of 0-148.4 MPa, indicating that SWs-reinforced UHPSSC can sense its stress and strain while providing early warning of crack initiation and propagation. Benefiting from the rust-free property, micron diameter, and high aspect ratio of SWs, the primary conductive path of composites comprises the overlapping networks formed by low-content SWs, which are not influenced by the ion conduction of conductive ions. Hence, SWs-reinforced UHPSSC exhibits stable electrical resistivity and sensitivity during long-term curing, suggesting its considerable potential for long-term in-situ monitoring of marine infrastructure.

Achieving Carbon Neutrality in Emerging Markets: The Dual Impact of Energy Transition Investments on Economic Growth and Carbon Emissions.

This study investigates the effectiveness of energy transition investments (ETIs) in achieving net-zero emissions. Specifically, it revaluates the environmental Kuznets curve (EKC) by analysing whether ETIs can simultaneously stimulate economic activity and reduce carbon emissions (CE) using the Autoregressive Distributed Lag (ARDL) model. The analysis focuses on a sample of emerging countries. In contrast to previous research, the study expands the EKC model by incorporating the ETIs variable, which encompasses a broader and more comprehensive range of investments that contribute to climate change mitigation, beyond just renewable energy. Additionally, the study employs total factor productivity (TFP) as a measure of economic activity, instead of GDP, considering the efficiency of technology, energy, and other resources. Key findings indicate that the TFP coefficient is higher in the short term compared to the long-term supporting the validity of the EKC hypothesis. This suggest that emerging countries have reached a TFP level of that helps reduce their CE, aiding climate change adaptation and mitigation. The study also reveals a negative effect of ETIs on CE and shows that an increase in TFP significantly enhances ETIs, suggesting that higher TFP levels attract more investment in energy transitions. These findings provide insights for policymakers on the impact of ETIs on CE and aid in formulating effective policies to achieve net-zero emissions.

Enhancing the mechanical and environmental performance of solidified soil using construction waste and glass micro-powder

The rapid accumulation of construction waste and waste glass, coupled with their environmental hazards, has highlighted the need for sustainable waste management strategies. This study explores the potential of using construction waste (CW) and glass micro-powder (GMP) as innovative additives in soil stabilization, providing both mechanical and environmental benefits. This research focuses on enhancing the compressive strength, tensile strength, and heavy metal stabilization of solidified soils while reducing carbon emissions. Experimental methodologies involved the systematic preparation of soil samples stabilized with various proportions of CW and GMP. Microstructural analyses were conducted using Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) to understand the formation of cementitious products, including calcium silicate hydrate (C-S-H) and calcium aluminate hydrate (C-A-H), which play a pivotal role in the strength improvement of stabilized soils. This study found that the optimal formulation of 30 % CW and 15 % GMP improved compressive strength by 56.8 %, from 7.25 MPa to 11.38 MPa, while reducing porosity by 57 % and increasing tensile strength by 85 %. In terms of environmental performance, the combination of CW and GMP enhanced the soil's ability to immobilize heavy metals, with 80 % sequestration efficiency, significantly contributing to soil remediation. These findings underscore the practical engineering significance of utilizing CW and GMP for sustainable soil stabilization, providing a greener alternative to traditional binders and promoting resource efficiency in the construction industry.

Soft, crispy, crunchy, sustainable: The role of visual textures in shaping sustainable food preferences

This research evaluates the potential of using visual textural complexity as a subtle yet effective strategy to direct consumer preferences towards more sustainable food choices, addressing the urgent need to reduce greenhouse gas emissions in the food industry.Using a traditional Turkish rice pudding, sütlaç, as a case study, we prepared four variants with varying textural complexities (ranging from simple to complex) by reducing the portion size by half and gradually adding soft, crispy, crunchy, and airy textured food layers onto it. Two parallel sets of variants were formulated to minimize potential bias from differences in composition and visual properties of the layers. One hundred participants individually evaluated paired visual stimuli of these variants under two experimental conditions: non-informative, which included only visuals, and informative, which included visuals with accompanied by sample information.Paired binary analysis revealed consistent preference for variants with higher levels of visual textural complexity, especially those with three layers (soft, crispy and crunchy), regardless of experimental conditions and product formulations. Although sample information affected preference scores, variants with certain levels of textural complexity were still preferred over the traditional sample (p < 0.05). Preferences for sample variants over the control reduced the carbon emission over 31 %. The study links the impact of visual textural complexity on preferences to the Elaboration Likelihood Model (ELM) and demonstrates that this strategy can effectively direct consumer preferences towards more sustainable options. Adopting the insights from this study can assist food producers and marketers in contributing to the broader goal of reducing carbon emissions.

Boosting Electric Vehicle Adoption with PCT Policy: Insights from China's Private Transportation

Personal Carbon Trading (PCT) motivates low-carbon consumption and travel by rewarding sustainable behaviors. This study examines the impact of PCT policies on electric vehicle (EV) adoption in China's private transportation sector. Using a Stackelberg game model involving the government, EV manufacturers, and consumers, it finds that PCT policies can boost EV adoption rates by 2.29% to 14.3%. Each addition of 100,000 new EVs could reduce carbon emissions by 30,000 tons. Effective PCT policies require an independent carbon pricing system and should be implemented where infrastructure and public willingness to pay are high. Both allocation methods are conducive to the promotion of EVs: one facilitates the government in setting regional emission reduction plans, while the other ensures that the government does not incur policy-related expenditures, and different allocation methods should be chosen according to the time and circumstances in different periods of EV market development.

How does green technology innovation affect urban carbon emissions? Evidence from Chinese cities

Green technology innovation is regarded as a key catalyst for sustainable urban development. This study mainly utilizes 278 Chinese cities data from the China Urban Statistical Yearbook, adopting ordinary least squares (OLS) and mediation effect model to investigate the dual impact and mechanism of green technology innovation on urban carbon emissions. Besides, spatial Durbin model (SDM) and threshold model are employed to examine spillover and non-linear impact. The results indicate that: (1) Green technology innovation can significantly mitigate carbon emission intensity, but cannot reduce carbon emissions. Thus, both carbon emission reduction effect and rebound effect coexist, and there is heterogeneity across different cities. (2) Green technology innovation has the potential to decrease carbon intensity through optimizing energy intensity, government participation and basic life cleanliness. (3) There is a spatial spillover effect concerning the emission reduction impact of green technology innovation. (4) The relationship between carbon emission intensity and green technology innovation exhibits a non-linear impact under varying levels of energy intensity, government participation, industrial structure rationalization, and environmental regulation. Building upon these findings, policy recommendations outlined in this study encompass the reinforcement of technological utilization, avoidance of excessive governmental intervention, and adoption of strategies for regional connectivity and differentiation.

Carbon Emission under Industry 5.0

Industry 5.0 integrates people and machines into production to achieve more personalization, possibilities, and sustainable development. Industry 5.0 has three core elements: Humancentric, sustainability, and resilience. Humancentric emphasizes human-machine collaboration. Talent is the core of industrial operation. Technology is to serve humans better, not to replace humans. The sustainability of Industry 5.0 includes economic, environmental, social, and technological sustainability. In these aspects, Industry 5.0 has new requirements and development directions for sustainability. The carbon footprint runs through every link of the industry. Reducing carbon emissions is the requirement of Industry 5.0 for environmental sustainability. The technological innovation and progress of Industry 5.0, as well as the concept of sustainability, all affect and reduce carbon emissions to varying degrees.

Gender empowerment and environmental impact: A quantile regression analysis in BRICS economies

This study, with its significant findings, delves into the impact of women's status on environmental quality in BRICS economies (Brazil, Russia, India, China, South Africa) from 1960 to 2022. Using a novel method, the Method of Moments Quantile Regression, this study has been able to analyse the relationship. The results, which are of utmost importance, show that women's political empowerment and leadership positions (government chief executives) significantly reduce carbon emissions, while the impact of women's civil liberties along with population growth increases emissions across the analysed quantiles. Economic growth is insignificantly negatively associated with environmental quality. The paper's findings reveal a unidirectional causal relationship from women's political empowerment to emissions, carbon emissions to women's civil liberties and emissions to economic growth. Additionally, a bi-directional causality connection is evident between population growth and environmental quality. These insights, which are crucial for policymaking, suggest that promoting improved women's status is a crucial policy strategy for mitigating climate change in BRICS economies. Thus, this paper suggests that empowerment of women is an effective strategy for reducing carbon emissions. It emphasizes the need for climate policy to promote gender equality, prioritise women's leadership in the clean energy industry, and enhance their access to resources and opportunities.

Recycling and optimum utilization of CRT glass as building materials: An application of low CO2 based circular economy for sustainable construction

The construction industry is the major contributor of CO2 emission around the globe. The rapid advances in the electronics industry have transformed the disposal of cathode ray tube glass waste (CRT-WG) into a prominent environmental concern. Recycling of CRT glasses as building materials can help in the production of sustainable construction. Numerous previous studies have documented that CRT-WG can be utilized either as a component of fine aggregate or binder material as it provides a cleaner solution and reduce carbon emission. Under this cleaner production and low CO2 emission perspective, this paper provides a thorough review of the previous studies on the utilization of CRT glass as a partially and fully substitute of sand and cementitious material in mortar production and propose an application of CO2 based circular economy model for reduce carbon emissions. This paper summarized the fresh, mechanical and durability properties of mortar incorporating treated and un-treated CRT-WG with different mineral additives and w/b ratios. Furthermore, this research explores the optimal proportions of CRT glass that can be use as replacements for sand and cement powder to make eco-friendly and sustainable low carbon mortar suitable for both structural and non-structural applications. More particularly, this review emphasizes the benefits, the need for additional research, and the drawbacks of CRT-WG use in construction building. Overall, this study proposes that incorporating CRT glass into building materials through a low CO2 based circular economy offers significant potential advantages. This study will help in optimization of CRT glass in concrete mix design in combination with waste materials for sustainable construction.

Optimal planning method of distributed generation in AC/DC microgrid considering power balance

Abstract To optimize AC/DC hybrid microgrid power planning, improve operational efficiency, and balance power distribution, we constructed an optimization model for AC/DC microgrid power generation, covering power, economy, reliability, and environmental protection, and set constraints to solve optimal planning. The experiment shows that this method enhances voltage stability, improves power supply quality, enhances distributed power generation efficiency, and reduces carbon emissions.

The interaction of income inequality and energy poverty on global carbon emissions: A dynamic panel data approach

Income inequality and energy poverty are critical obstacles to the worldwide low-carbon transformation and deeply affect human behavior. Applying a dynamic panel data model, this study investigates the effect of income inequality and energy poverty on global carbon emissions. We determine the effect of the interaction between income inequality and energy poverty on the global low-carbon transformation based on a panel data set of 193 countries from 1990 to 2019. A one standard deviation decrease in the Gini coefficient causes a 2.98 % decrease in carbon emissions per capita, with the median value of energy poverty. However, in poor countries where the proportion of population with access to electricity is less than 86.0 %, reducing income inequality will increase carbon emissions. The role of energy poverty on carbon emissions per capita is also affected by income inequality. When the Gini coefficient is lower than 0.461, increasing access to electricity will reduce carbon emissions. In contrast, when the Gini coefficient is higher than the critical value of 0.461, increased access to electricity will raise carbon emissions. These findings indicate a new strategy for advancing low-carbon transformation based on the interrelationship between income equality and energy poverty eradication.

Electric vehicle battery closed-loop supply chain pricing and carbon reduction decisions under the carbon cap-and-trade and reward-penalty policies

Recycling end-of-life electric vehicles (EVs) batteries to conserve resources and reduce carbon emissions has obtained a great deal of concern. This paper studied how carbon cap-and-trade and reward-penalty measures jointly impacted EV battery pricing and decarbonization strategies. Three recycling modes covering single-participator, mixed-participator, and joint recycling are established. Optimal pricing and carbon mitigation strategies, total revenue, and recycling percentage are solved and compared. The dynamic effects of target recycling percentage and rewards and punishments on total revenue and recycling percentage are analyzed by numerical examples. Results show that: (1) The factory price, selling price, collection price, and carbon emission mitigation scale of power batteries are affected by cap-and-trade and reward-penalty mechanisms; (2) Reward-penalty can improve both total revenue and recycling percentage; (3) The cap-and-trade mechanism optimizes the total revenues, showing that the total revenue increase with the increasement of carbon quota and carbon price, while the increase of carbon price leads to worse recycling percentage; (4) The supply chain performance under different recycling modes is affected by policy intervention, and the joint recycling mode is better.

Can carbon labels shift consumers towards sustainable food? Evidence from Chinese consumers

Carbon labels are becoming an essential tool for policymakers in many countries to promote low-carbon consumption. To assess customers’ willingness to pay for five carbon-labeled agricultural products (CAP), we used payment card to conduct a questionnaire survey among 641 respondents in Shanghai, Nanjing, Wuhan, and Xi'an, all located in China. This study quantitatively analyzes the influencing factors and interactive mechanisms of the public's willingness to purchase CAP through the extended Theory of Planned Behavior and Norm Activation Model. The results show that consumers' willingness to pay a premium for carbon-labeled milk, corn, bananas, tomatoes, and eggs is 27.50%, 29.73%, 26.86%, 26.51%, and 24.26% respectively. Perceived behavioral control has the strongest positive influence on purchase intention, followed by subjective norms, attitudes toward the behavior, and personal norms. There is a significant mediating effect between awareness of consequences and personal norms, which indirectly influences personal norms through the ascription of responsibility and subsequently affects purchase intention. Additionally, there is a gap between purchase intention and behavior, and risk perception negatively moderates the relationship between the two. Based on the research findings of this paper, practical and effective policy suggestions are proposed for the government to promote carbon labeling policies and reduce carbon emissions.

Isolation and Characterization of Ureolytic Calcifying Bacteria from Methane Hydrate-Bearing Marine Sediments for Bio-cementation Application

In bio-calcification, microbes precipitate calcium carbonate (CaCO3), forming versatile solid substances that promotes eco-friendly materials and reduce carbon emissions. Marine bacteria can generate bio-cements to strengthen dikes and combat coastal erosion. However, the role of marine bacteria in generating bio-cements for enhancing coastal structures and combating erosion is not fully understood. This study investigates the potential of CaCO₃ precipitating bacteria isolated from methane hydrate-bearing marine sediments. Five calcifying marine bacteria were isolated using Christensen's urea agar from marine sediments collected from Gawadar coastal, Pakistan. Bacterial strains induced CaCO3 precipitation producing urease enzymes. Strains were identified as Pseudomonas putida, Bacillus altitudinis, Vibrio sp., Bacillus sp., and Vibrio plantisponsor. Energy-dispersive X-ray spectroscopy, scanning electron microscopy, and X-ray diffraction were applied for the identification and differentiation of calcite and vaterite precipitates. The growth of isolates and precipitation potential were observed optimum at 5% NaCl and pH 9.5-11. Bacillus altitudinis (ST4SD3) and Bacillus sp. (ST4SD1) produced more soluble Ca2+ (8532.53 mg/l and 7581.98 mg/l) as compare to other isolates at higher pH 10 and pH 11, favorable for CaCO3 precipitation. It is concluded that marine ureolytic bacteria possess significant potential for bio-cementation, which can stabilize methane hydrate-bearing sediments, improve soil properties, protect coastal regions from erosion, and crucial in the methane cycle, a greenhouse gas. We recommend further exploration of such bacteria's applications in marine construction and sediment stabilization to enhance the robustness and longevity of coastal infrastructures. Furthermore, such bacteria could also be beneficial in extracting gas from unconsolidated methane hydrates containing sediments.

Soft Computing Techniques to Model the Compressive Strength in Geo-Polymer Concrete: Approaches Based on an Adaptive Neuro-Fuzzy Inference System

Media visual sculpture is a landscape element with high carbon emissions. To reduce carbon emission in the process of creating and displaying visual art and structures (visual communication), geo-polymer concrete (GePC) is considered by designers. It has emerged as an environmentally friendly substitute for traditional concrete, boasting reduced carbon emissions and improved longevity. This research delves into the prediction of the compressive strength of GePC (CSGePC) employing various soft computing techniques, namely SVR, ANNs, ANFISs, and hybrid methodologies combining Genetic Algorithm (GA) or Firefly Algorithm (FFA) with ANFISs. The investigation utilizes empirical datasets encompassing variations in concrete constituents and compressive strength. Evaluative metrics including RMSE, MAE, R2, VAF, NS, WI, and SI are employed to assess predictive accuracy. The results illustrate the remarkable precision of all soft computing approaches in predicting CSGePC, with hybrid models demonstrating superior performance. Particularly, the FFA-ANFISs model achieves a MAE of 0.8114, NS of 0.9858, RMSE of 1.0322, VAF of 98.7778%, WI of 0.9236, R2 of 0.994, and SI of 0.0358. Additionally, the GA-ANFISs model records a MAE of 1.4143, NS of 0.9671, RMSE of 1.5693, VAF of 96.8278%, WI of 0.8207, R2 of 0.987, and SI of 0.0532. These findings underscore the effectiveness of soft computing techniques in predicting CSGePC, with hybrid models showing particularly promising results. The practical application of the model is demonstrated through its reliable prediction of CSGePC, which is crucial for optimizing material properties in sustainable construction. Additionally, the model’s performance was compared with the existing literature, showing significant improvements in predictive accuracy and robustness. These findings contribute to the development of more efficient and environmentally friendly construction materials, offering valuable insights for real-world engineering applications.

Role of supply chain digitalization and global supply chain in decarbonization of natural resources sector supply chain

Environmental management and decarbonization are becoming increasingly critical as industries seek sustainable development paths that align with global climate targets. As businesses aim to reduce their carbon footprint, integrating effective environmental strategies with technological advancements is essential. This necessitates a clear understanding of digital technologies and environmental policies to drive decarbonization efforts. In this context, this study explores the role of digitalization in reducing carbon emissions in the natural resources sector supply chain. Furthermore, it examines the role of supply chain mapping as a mediator in the relationship between supply chain digitalization and supply chain decarbonization efforts, providing a novel perspective on how technology can intersect to foster environmental sustainability. This research targets the metal sector supply chain, a significant contributor to global carbon emissions. The data for the study was gathered through a questionnaire administered to 246 employees from various levels of the metal industry in China. We employed Covariance-based Structural Equation Modelling (CB-SEM) using AMOs for analysis. Our results show that level digitalization of supply chain processes in the metal sector has a profound and direct impact on its supply chain decarbonization. Digital technologies facilitate more efficient resource use, improved energy efficiency, and the adoption of cleaner production methods. Importantly, the study identifies supply chain mapping as a crucial mechanism through which digitalization exerts its positive influence on decarbonization. Through detailed mapping, organizations can gain visibility over their entire supply chain, identifying carbon hotspots and opportunities for improvement that digital solutions can address. The novelty of this study lies in its systematic exploration of how supply chain mapping serves not just as a tool for transparency and efficiency but as a strategic facilitator of the beneficial impacts of digitalization on decarbonization.