Global Carbon Emissions Research Articles

Modeling of Lithium-Ion Batteries for Electric Transportation: A Comprehensive Review of Electrical Models and Parameter Dependencies

The power and transportation sectors contribute to more than 66% of global carbon emissions. Decarbonizing these sectors is critical for achieving a zero-carbon economy by mid-century and mitigating the most severe impacts of climate change. Battery packs, which enable energy storage in electric vehicles, are a key component of electrified transport systems. The production of these batteries has significantly increased in recent years to meet rising demand, and this trend is expected to continue. However, current traction batteries exhibit lower energy density compared to fossil fuels. As a result, accurate battery models that balance computational complexity and precision are essential for designing high-performance energy storage systems. This paper provides a comprehensive review of the most used electrical models for lithium-ion batteries in traction applications, as reported in the technical literature. By exploring the strengths and limitations of different modeling approaches, this paper aims to offer valuable insights into their practical applicability for the electrification of transportation systems. Additionally, this paper discusses the primary methods employed to derive the values of the electrical components within these models. Finally, it examines the key parameters—such as temperature, state of charge, and aging—that significantly influence the component values. Ultimately, it guides researchers and practitioners in selecting the most suitable modeling approach for their specific needs.

Can Autocracy Handle Climate Change?

ABSTRACT Existing literature on climate politics predominantly concentrates on democracies. However, there is a pressing need to examine how authoritarian regimes respond to climate change, given their growing impact on global carbon emissions and their populations’ acute climate vulnerability. Extant research often assumes that authoritarian regimes have inherent advantages in addressing climate change, leading to overly optimistic perspectives on their capabilities. This study highlights the necessity of qualifying those assumptions and evaluates the comparative advantages and disadvantages of autocracies relative to democracies throughout the policy process: policy formulation (or outputs), implementation, and outcomes. I argue that whereas climate-conscious autocracies may efficiently produce policy outputs based on scientific evidence, they often face more challenges related to information about local enforcement during implementation. This may result in greater hurdles than democracies, even with adequate state capacity and monitoring infrastructure. Furthermore, this analysis contends that a country’s developmental stage, rather than its regime type, is related more directly to the effectiveness of translating implementation efforts into tangible policy outcomes. Therefore, this article posits that the political science discourse, which often juxtaposes democracies with autocracies, should expand its scope to better understand how a country’s developmental level influences the success of its climate strategies.

Trends in Global Agricultural Carbon Emission Research: A Bibliometric Analysis

As climate change intensifies and countries actively pursue carbon peaking and carbon neutrality targets, agriculture has emerged as a significant source of carbon emissions. A comprehensive analysis of global agricultural carbon emission research can enhance the agricultural environment and achieve a mutually beneficial outcome for environmental protection and economic development. Despite the evolution of research domains and methodologies, the global context remains closely connected to the current state of the discipline. Drawing on the Web of Science core collection, this paper develops a knowledge network framework, examines the current status and hotspots of agricultural carbon emissions, forecasts future development trends, and analyzes the findings using CiteSpace visualization software. The findings indicate that the number of papers on agricultural carbon emissions has been increasing annually, with minor fluctuations; time series analysis and sustainable development have emerged as the current focal points, and relevant institutions are collaborating increasingly closely. However, cooperation among scholars requires further enhancement. Countries such as China, the United States, and Germany are the primary nations for paper publication. The hotspot analysis reveals a high frequency of keywords such as greenhouse gas emissions and climate change, indicating that research on agricultural carbon emissions has matured and the emphasis has shifted from accounting to management. This paper develops a domain knowledge framework to assist readers in understanding agricultural carbon emission patterns and provide resources for further research. Follow-up studies should enhance both comprehensiveness and breadth, promote interdisciplinary cooperation, provide a scientific foundation for policymakers, and outline future research directions.

Measuring Global FDI-Embodied Carbon Emissions

ABSTRACT Foreign direct investment (FDI) significantly impacts global carbon emission patterns through the production and supply chains of transnational corporations (TNCs), influencing climate change governance. This study measures FDI-embodied carbon emissions from 2000 to 2019, using multi-regional input-output and hypothetical extraction methods, and analyzes changes via complex network analysis. Findings reveal a 61% increase in global FDI-embodied carbon emissions, with an upward trend since 2016, mainly due to developing countries. The 2008 financial crisis and Copenhagen Accord shifted carbon flows from concentrated to decentralized patterns. Clustering of these flows continues to rise. Strengthened international cooperation and guidelines are needed to promote green investment, guide TNCs, and achieve the Paris Agreement goals.

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.

Environmental regulations and export performance: firm-level evidence from China’s low-carbon pilot policy

The rapid increase in global carbon emissions has raised significant concerns, prompting various environmental regulations, including China’s low-carbon pilot policy. Prior studies have shown mixed results regarding the impact of environmental regulations on firms’ export performance. Using data from Chinese industrial firms from 2001 to 2015, this study investigates how the low-carbon pilot policy, a quasi-experiment, influences firms’ exports. We employ the Heckman Two-Step Method and the Difference-in-Differences approach to separate the effects on firms’ export participation and the effects on export scales. We find that firms in the pilot provinces/cities become less likely to export after the implementation of the low-carbon pilot policy compared to firms in the non-pilot regions, resulting in a relative decrease in export probability by 4.5 percentage points. For the firms that export, their export values relatively decrease by 10 percent after the policy implementation. The effects are mainly driven by firms in Eastern China. The policy leads to higher exit rates and lower entry rates in international markets for firms in pilot regions. After the implementation of the low-carbon pilot policy, exporting firms increase the unit price of their export products, reduce the quantity of export products, and diversify both their export destinations and product types. However, we do not find evidence supporting the Pollution Haven mechanism.

Optimal Strategies for E-Commerce Platform Supply Chain: Carbon Emission Reduction and Financing

In the context of global carbon emission reduction (CER) targets and slowing economic growth, it is imperative for suppliers to make informed choices regarding CER and financing strategies. However, limited research has explored the impact of financing strategies on CER. This paper develops a supply chain model that includes a supplier, a manufacturer, an E-commerce platform (E-C platform), and consumers with a preference for low-carbon products. The supplier sets the wholesale price, while the manufacturer controls both the production quantity and the unit amount of CER. We examine whether the manufacturer will invest in CER with sufficient capital or under various financing scenarios, namely (1) traditional production with sufficient capital (Scenario ST); (2) CER implementation with sufficient capital (Scenario SG); (3) CER implementation with E-C platform financing (Scenario EG); (4) CER implementation with bank financing (Scenario BG). Through comparative analysis, the analysis reveals that, regardless of the financing method chosen, the supplier’s profit and the manufacturer’s production quantity increase when the manufacturer invests in CER technology innovation compared to the traditional scenario. Furthermore, in terms of the manufacturer’s profit, if the service cost of bank financing exceeds a certain threshold, the manufacturer should either seek financing from the E-C platform or abandon the CER investment. Additionally, with respect to CER outcomes, Scenario BG outperforms Scenario EG. These findings provide a theoretical foundation and decision-making support for supply chain participants when addressing carbon reduction and financing strategy decisions.

Synergetic enzymatic reactive crystallization of cefaclor catalyzed by PGA

In the context of the severe global carbon emission crisis, green and sustainable enzymatic reactions are garnering widespread attention in the industry. However, these processes still face numerous challenges, such as limitations imposed by reaction equilibrium, product decomposition, and inhibition. Product removal via crystallization has the potential to address these issues. More importantly, crystal product properties can be directly manipulated during enzymatic reactive crystallization (ERC), such as polymorphic purity, size, and morphology in a single batch. In the synthesis of cefaclor catalyzed by penicillin G acylase (PGA), primary and secondary hydrolysis greatly limited the efficiency of the reaction. Thus, ERC was performed to combine the advantages of green enzymatic reactions and controllable direct crystallization. Initially, a supersaturated solution of the substrate was established, and cefaclor crystals were seeded to the enzymatic reaction system at a proper time. Subsequently, operating parameters were adjusted to facilitate selective crystallization of cefaclor. It is noteworthy that both immobilized and free enzymes were examined in our research. Ultimately, cefaclor crystals with purity exceeding 99% were obtained directly. The yield of cefaclor reached as high as 88%. It is believed that this method held significant promise for the green and efficient production of high-purity cefaclor and demonstrated considerable potential for application in more similar pharmaceutical scenarios.

Multi-Scenario land cover changes and carbon emissions prediction for peak carbon emissions in the Yellow River Basin, China

Research on future land cover changes and carbon emissions is essential for effective land resource management and developing feasible carbon mitigation strategies. This study focused on the Yellow River Basin and employed the Future Land Use Simulation (FLUS) and Autoregressive Integrated Moving Average (ARIMA) models to project future land cover and carbon emissions. Additionally, bivariate spatial autocorrelation was utilized to analyze the relationship between them. Key findings are as follows: 1) Historically, the Yellow River Basin has experienced an expansion in construction land, forests, grasslands, and water, while cropland and unused land have diminished. Notably, construction land displayed the most significant changes, whereas grasslands showed minimal modification. Looking ahead, both the ecological protection and inertial development scenarios exhibit consistent trends with historical patterns across the land type categories. In contrast, the economic priority development scenario forecasts an increase in construction land, cropland, and grasslands, indicating a distinct shift compared to the other scenarios. However, the ecological protection scenario proves to be more sustainable. 2) In the absence of intervention, the simulated carbon emissions from construction land throughout the basin display a linear increase across various scenarios, with provincial-level variations showing an increase from southwest to northeast. However, Henan and Sichuan are expected to experience slower reductions in carbon emissions, compared to other projections. There is a notable positive correlation between carbon emissions and the comprehensive index, indicating that regions with high emissions typically experience substantial land and economic development. 3) Energy consumption projections for 2030 and 2060 indicate that to align with China’s carbon goals, it is essential to reduce energy consumption and adjust the fossil to non-fossil fuel ratio to reduce carbon emissions. Substituting coal with clean energy and enhancing energy efficiency will be more effective for achieving low-carbon emission targets. In summary, this study provides significant guidance for China’s ecological conservation, low-carbon emission strategies, and global carbon emission control efforts.

Perceptions of decarbonisation challenges for the process industry in Sweden and Norway

The energy-intensive process industries (EPIs) account for a high share of global carbon emissions but have so far been slow to decarbonise. One of the reasons for the slow pace is that central problems and solutions are contested among stakeholders. To develop effective and inclusive transition policy, a better understanding of different perspectives on decarbonisation challenges is needed. In this paper, we use Q methodology to address this gap with an analysis of EPI decarbonisation in Sweden and Norway. The research draws on 50 interviews where different types of stakeholders sorted and reflected upon statements that describe potential decarbonisation challenges. Through factor analysis, we identify four salient narratives in each country, which emphasise different problems and trade-offs. However, we also find similarities across the narratives, both within and across countries. A key challenge that is emphasized in both countries is to ensure a sufficient supply of electricity at competitive prices. Ultimately, we demonstrate how these findings are important for providing policy recommendations.

Cobalt-based Molecular Electrocatalyst-Mediated Green Hydrogen Generation: A Potential Pathway for Decarbonising Steel Industry

Amid the climate change crisis, researchers are investigating the transformative potential of green hydrogen produced by renewable energy electrolysis to decarbonize the steel sector, a significant contributor to global carbon emissions. It aims to lower the carbon footprint of the steel industry by showcasing green hydrogen's potential as a cleaner substitute for traditional fossil fuels in the production process. Despite its potential, issues such as high costs, restricted availability, and infrastructural alterations must be addressed. Cobalt-based synthetic catalysts, especially cobaloximes, are being considered as a key electrocatalytic component for hydrogen production via water-splitting. Cobaloximes, noted for their efficiency and stability in catalysing hydrogen evolution, have made considerable advances in the field of molecular catalysis. Recently, advanced immobilisation procedures have appreciably enhanced their overall catalytic output and application. This article discusses several electrolyser technologies, such as proton exchange membrane (PEM) and alkaline electrolysis, highlighting the benefits of multi-stacked electrolyser systems for boosting hydrogen generation efficiency. These encouraging results are vital for unravelling a durable catalytic material that can be scaled up without much financial stringency. In light of the global climate pledges, the document concludes that green hydrogen might provide 24% of the world's energy needs by 2050, resulting in a considerable reduction in CO2 emissions.

Accounting for Decarbonization Impacts across the Full Life Cycle of Alternative Concrete Materials: A case-study for graphene-amended cementitious composites

Concrete's extensive use worldwide comes with significant environmental cost, contributing to 8% of annual global carbon emissions. This study investigates the use of life cycle assessment (LCA) and technoeconomic assessment (TEA) as tools to quantify anticipated reductions in global warming potential (GWP) arising from use of novel concrete mixtures or innovative production techniques, with specific focus on a case study related to graphene nanoplatelets (GNPs) as functional fillers. LCA and TEA results are reported for several choices of functional unit (FU) and system boundaries (SB). This approach illustrates how various LCA and TEA framings are differently useful to articulate how changes in technical performance properties such as mechanical strength and durability influence overall life-cycle environmental impacts. Framing 1 make use of a nominal volume-based FU (1 m3) and cradle-to-gate SB. Under this framing, addition of GNPs to the base mix seems to increase GWP and production cost. Framing 2 makes use of a strength-normalized FU and cradle-to-gate SB. Under this framing, life-cycle GWP and production cost for the GNP-amended mortars are decreased relative to the control, due to the appreciable increase in mechanical strength of the GNP-amended mortars. Finally, Framing 3 makes use of the nominal volume-based FU (1 m3) and cradle-to-grave SB. Under this framing, GWP and production cost for the GNP-amended mortars again seem to decrease, due to improved durability which gives rise to longer estimated service life and reduced maintenance. This study illustrates that use of GNPs as function filler is a seemingly promising strategy for decarbonizing concrete. More broadly, it is concluded that LCAs and TEAs of novel concretes should be framed in a way that articulates how changes in mechanical strength and/or durability properties contribute to changes in environmental impacts over all stages of the concrete life-cycle (i.e., cradle-to-grave). Such framing will help ensure that results that are meaningful to support decision-making in the area of sustainable construction materials.

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.

Hydrate management strategies for CO2 injection into depleted gas reservoirs

Sequestering CO2 in depleted gas reservoirs using carbon capture, utilization, and storage technologies has emerged as a viable strategy for mitigating global carbon emissions. However, CO2 hydrate formation during injection processes is challenging and poses a risk to the operational integrity and efficiency of sequestration projects. This study investigated CO2 hydrate formation dynamics within silica gel environments that closely mimicked the median pore size of natural sandstone reservoirs, particularly targeting depleted gas fields in the East Sea of Korea. Integrating kinetic insights into experimental hydrate formation assessments and molecular dynamics simulations provided a comprehensive understanding of the CO2 hydrate formation mechanisms, as well as the formation dynamics and stability of the CO2 hydrates. For example, the hydrate formation kinetics were significantly reduced in the small pores, suggesting the feasibility of implementing more economical hydrate inhibitor injection strategies during CO2 injection. Moreover, this study evaluated the inhibitory effects of NaCl and methanol on CO2 hydrate stability by accurately measuring the three-phase (H-Lw-V) equilibria and employing silica gels (6 nm pore size). The presence of methanol and amorphous silica significantly impacted hydrate formation, with methanol potentially influencing the local structure around the hydrate phase and silica hindering hydrate growth through dynamic interactions with CO2 molecules. In addition, we elucidated the complex interplay between CO2, water, and methanol (hydrate inhibitor) within the constrained environments of porous media, offering strategic insights for the development of effective CO2 injection and sequestration strategies. Integrating molecular-level observations with real-world geological modeling presents a novel methodology for enhancing the safety, efficiency, and environmental sustainability of carbon capture and storage operations. The findings of this study provide critical insights into hydrate phase behavior, highlighting the importance of precise equilibrium determination under simulated reservoir conditions to effectively anticipate and mitigate hydrate formation challenges.

Agricultural carbon emissions in China: measurement, spatiotemporal evolution, and influencing factors analysis

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

Multi-objective optimization of non-fossil energy structure in China towards the carbon peaking and carbon neutrality goals

Numerous nations and regions are earnestly dedicated to propelling energy transition. China accounts for 31.78 % of the total global carbon emissions, and China's energy structure holds paramount significance in the broader context of global initiatives. China has officially proposed to achieve the target of carbon peak by 2030 and carbon neutrality by 2060, imposing substantial pressure on the transformation of the energy structure. In this study, we propose a multi-objective optimization model for the non-fossil energy structure, encompassing three primary optimization objectives: maximizing power generation, minimizing economic costs, and reducing CO₂ emissions. The optimization involves determining the proportion of seven key non-fossil energy sources—hydropower, onshore wind, offshore wind, photovoltaic (PV), bioenergy, geothermal, and nuclear power—while adhering to constraints related to power demand, nuclear safety, and other factors. The analysis explores the installed capacity, power generation, power generation costs, and CO₂ emission reductions of non-fossil energy under distinct scenarios in 2025, 2030, and 2060. The findings reveal that by 2030, the optimal share of power generation should be sequenced as onshore wind, hydropower, nuclear power, offshore wind, PV, bioenergy, and geothermal. Subsequently, by 2060, the top three developed power should be onshore wind, nuclear power, and hydropower.

Knowledge Distillation for Urban Tree Image Classification Based on the Diffusion Model

As urban areas continue to emerge as significant contributors to global carbon emissions, the classification of urban street trees has gained increasing importance in carbon sequestration research. By precisely identifying and categorizing different tree species, the carbon absorption capabilities of urban vegetation can be evaluated more accurately. This understanding is essential for addressing the growing environmental challenges posed by carbon emissions, as urban trees play a crucial role in absorbing carbon dioxide and mitigating the effects of climate change. In this study, a Feature Distillation Based on Diffusion Model (FDBD) framework was proposed, utilizing state-of-the-art image classification technology to enhance the accuracy of urban tree species identification. The framework utilized knowledge distillation, a process where a smaller, more efficient “student” model is trained to mimic the performance of a larger, more complex “teacher” model, significantly reducing computational demands while maintaining high accuracy. The model’s effectiveness has been validated through combination experiments with a selected backbone model, achieving promising results. This approach not only enhances the understanding of urban trees’ carbon sequestration potential but also provides crucial insights for policymakers. By facilitating precise tree classification, it empowers urban planners to implement more informed and targeted strategies for carbon reduction, ultimately promoting more sustainable urban environments.

Textile Recycling: Efficient Polyester Recovery from Polycotton Blends Using the Heated High-Ethanol Alkaline Aqueous Process.

Textile production has doubled in the last 20 years, but only 1% is recycled into new fibers. It is the third largest contributor to water pollution and land use, accounting for 10% of global carbon emissions and 20% of clean water pollution. A key challenge in textile recycling is blended yarns, such as polycotton blends, which consist of polyester and cotton. Chemical recycling offers a solution, in particular, alkali treatment, which hydrolyzes polyester (PET) into its components while preserving cotton fibers. However, conventional methods require high temperatures, long durations, or catalysts. Our study presents, for the first time, the heated high-ethanol alkaline aqueous (HHeAA) process that efficiently hydrolyzes PET from polycotton at lower temperatures and without a catalyst. A near-complete PET hydrolysis was achieved in 20 min at 90 °C, while similar results were obtained at 70 °C and 80 °C with longer reaction times. The process was successfully scaled at 90 °C for 20 min, and complete PET hydrolysis was achieved, with a significantly reduced liquid-to-solid ratio, from 40 to 7 (L per kg), signifying its potential to be implemented in an industrial context. Additionally, the cotton maintained most of its properties after the treatment. This method provides a more sustainable and efficient approach to polycotton recycling.

Geo-based fabrics: using earthen materials for wearables

ABSTRACT Over 50% of synthetic textiles in existence originate from polyester derived from petroleum oil. Synthetic textiles make up over 65% of global circulating textiles and the industry is known for being highly pollutant, resource wasteful, and responsible for nearly 10% of global carbon emissions annually. One prominent solution to the industry’s negative environmental impact is to develop alternative textiles for garment and architectural fabric applications. This paper presents a novel development of earth – and bio-based wearable textiles coined as BioMud Fabric which consists entirely of bio-based materials; 65% of which is clay-rich raw soil. More specifically, the material integrates raw soil with naturally occurring bio-based plastics to create a flexible, lightweight and biodegradable fabric. The research methodology includes a mix-design analysis, using electron microscopy, and a macro-scale structural characterisation using tearing tests. The final demonstrations showcase speculative design applications which serve to expand the possibilities of the material through fashion.

The United European Gastroenterology green paper-climate change and gastroenterology.

Climate change, described by the World Health Organization (WHO) in 2021 as 'the single biggest health threat facing humanity', causes extreme weather, disrupts food supplies, and increases the prevalence of diseases, thereby affecting human health, medical practice, and healthcare stability. Greener Gastroenterology is an important movement that has the potential to make a real difference in reducing the impact of the delivery of healthcare, on the environment. The WHO defines an environmentally sustainable health system as one which would improve, maintain or restore health while minimizing negative environmental impacts. Gastroenterologists encounter the impacts of climate change in daily patient care. Alterations in the gut microbiome and dietary habits, air pollution, heat waves, and the distribution of infectious diseases result in changed disease patterns affecting gastrointestinal and hepatic health, with particularly severe impacts on vulnerable groups such as children, adolescents, and the elderly. Additionally, women are disproportionally affected, since climate change can exacerbate gender inequalities. Paradoxically, while healthcare aims to improve health, the sector is responsible for 4.4% of global carbon emissions. Endoscopy is a significant waste producer in healthcare, being the third highest generator with 3.09kg of waste per day per bed, contributing to the carbon footprint of the GI sector. Solutions to the climate crisis can offer significant health co-benefits. Steps to reduce our carbon footprint include fostering a Planetary Health Diet and implementing measures for greener healthcare, such as telemedicine, digitalization, education, and research on sustainable healthcare practices. Adhering to the principles of 'reduce, reuse, recycle' is crucial. Reducing unnecessary procedures, which constitute a significant portion of endoscopies, can significantly decrease the carbon footprint and enhance sustainability. This position paper by the United European Gastroenterology aims to raise awareness and outline key principles that the GI workforce can adopt to tackle the climate crisis together.