Including Greenhouse Gas Emissions Research Articles

Environmental Efficiency of Agriculture in Visegrád Group Countries vs. the EU and the World

The production of foodstuffs for an ever-increasing population is the basic, irreducible and unalienable function of agriculture. It involves environmental impacts, including greenhouse gas emissions. This is what makes it so important to examine the levels of environmental efficiency of agriculture. As countries differ in their emission levels, it is reasonable to look for what determines them. Hence, the purpose of this study was to identify the changes in the environmental efficiency of agriculture in Visegrád Group countries and worldwide in 1961–2020. These countries share a similar economic history and demonstrate comparable environmental and geographic conditions, making it possible to pinpoint the factors responsible for how the parameters covered by the study change over time. The research used data from the FAOSTAT database. Environmental efficiency of agriculture was defined as the relationship between production volumes in kilocalories and emissions. Initially, this parameter deteriorated in the Visegrád countries, but since the late 1970s it has improved, first linked to the crisis of the socialist economy and its collapse (including a drastic decline in livestock production) and then to the implementation of CAP instruments.

Forecasting Electric Vehicle Adoption in the USA Using Machine Learning Models

Electric vehicles (Electric Vehicles) are at the vanguard of the global dispensation to sustainable transportation, depicting a pivotal step toward diminishing greenhouse gas emissions and reliance on fossil fuels. Notwithstanding, the adoption of Electric Vehicles has been growing in the USA, but their future remains at a crossroads. The objective of the research is to design and execute machine learning models capable of providing accurate predictions of future trends in electric vehicle adoption in the USA. The dataset gathered for analyzing EV adoption in the USA comprises data across three primary categories: environmental data, economic indicators, and policy-related data. The economic indicators include household income, fuel prices, electricity rates, and lithium battery costs that affect EV purchasing power obtained from the U.S. Census Bureau and the U.S. Energy Information Administration (EIA). Environmental data include greenhouse gas emissions and air quality indices from the EPA, providing information on regional environmental conditions that might affect EV attractiveness. Other policy data included federal and state incentives such as tax credits, rebates, and EV infrastructure data, collected from the U.S. Led by the U.S. Department of Energy's Alternative Fuels Data Center and the Energy Laboratory, additional EV sales trends were pulled from databases of the automotive industry. In this research project, credible and proven machine learning models were employed, most notably, Linear Regression, Random Forest, and XG-Boost. The performance of the models was tested for EV adoption prediction by considering a few important metrics: Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R²). From the model performance metrics presented, the Gradient Boosting Regressor and Random Forest models performed far better by a big margin than Linear Regression. The prediction models, particularly, the Random Forest regressors and Gradient Boosting regressors demonstrated incredible forecasting of electric vehicle adoption. The model works excellently on the premise that historical data with relevant features can be utilized to gain some valuable insight into future trends. Policy-makers interested in stimulating the wider use of electric vehicles can ensure that targeted policies address both current barriers and future demands. Results of this analysis suggest incentives, such as tax credits, rebates, and subsidies, are some of the most common actions to reduce the upfront cost of an EV, a key circumventing factor in the choice that many consumers face.

Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms.

Methane (CH4) from livestock, particularly enteric CH4 emission (EME), is one contributor to greenhouse gas emissions and climate change. This review analyzed 1294 scientific abstracts on EME in ruminants from 1986 to May 2024, using Scopus® data. Descriptive statistics, text mining, and topic analysis were performed. Publications on EME have risen significantly since 2005, with the Journal of Dairy Science being the most frequent publisher. Most studies (82.1%) were original research, with Northern Hemisphere countries leading in publication numbers. The most frequent terms were "milk", "cow", and "diet", while key research topics included greenhouse gas emissions from livestock, diet composition, and prediction models. Despite progress, some areas like CH4 emission from animals need further investigation.

The Impact of International Cooperation on the Development of Renewable Energy Sources in Kazakhstan

In recent decades, renewable energy sources (hereinafter - RES) have become an increasingly important component of global energy policy, especially in the context of the need for sustainable development and the fight against climate change. This study analyzes the role of international cooperation in the development of RES in Kazakhstan and assesses its impact on national strategies for reducing greenhouse gas emissions and transitioning to sustainable energy. The research employs cluster analysis to identify groups of partner countries with similar energy and environmental profiles, complemented by Ward’s dendrogram and scenario analysis to predict the future directions of international cooperation. Data from the Bureau of National Statistics of the Republic of Kazakhstan, including greenhouse gas emissions, the share of renewable energy in total energy consumption, water resource availability, fuel exports, and energy intensity, were utilized. Three main clusters were identified: countries with advanced technologies in the field of RES, countries with emerging RES markets, and countries focused on hydrocarbon exports but seeking to diversify their energy resources. Cluster analysis revealed that Kazakhstan falls into the group with high energy intensity and a low share of RES in the energy balance (1.8%). Scenario analysis demonstrated that with active international cooperation, the share of RES in Kazakhstan could increase to 10-12% by 2030, and energy intensity could decrease, leading to a reduction in CO2 emissions. For future research, an in-depth analysis of Kazakhstan’s international cooperation in the field of renewable energy sources with an emphasis on regional specifics is recommended.

Climate impact of alternative organic fertilizers using life cycle assessment

Abstract Anaerobic digestion is a common method for managing liquid manure and other biomasses, generating biogas as a renewable energy source. The resulting digestate can be processed into organic fertilizers to enhance nutrient recycling, but its environmental impact warrants investigation. In this study, a life cycle assessment (LCA) was conducted to examine the impact of fertilizers derived from cattle slurry and grass-clover co-digestion on global warming (measured in CO2 equivalent) compared to untreated cattle slurry. The different treatments analyzed include untreated cattle slurry, digestate, liquid fractions from digestate separation, and an enriched liquid nitrogen-sulfur product derived from post-processing of biogas and drying the solid fraction. The functional units of this study were 100 kg of total nitrogen in the final organic fertilizer (FU1) with the cradle-to-processing gate boundary and the harvesting 1 ton of spring barley dry matter (FU2) with the cradle-to-field application boundary. The carbon footprint ranged from 24 to 49% of the baseline scenario for FU1, and from -6 to 177% of the baseline scenario for FU2. The main contributors to the carbon footprint of fertilizers included greenhouse gas emissions from storage and field application. However, biogas production from anaerobic digestion, together with the concurrent mitigation of CH4 emissions during storage, contributed most to a reduction in the overall global warming potential associated with anaerobic digestate and its liquid fraction. This study showed large climate prospects in replacing untreated slurry as organic fertilizer with alternatives resulting from its anaerobic digestion and post-treatment.

Potential use of district heating networks and the prospects for the advancements within urban areas of Nottingham as a case study

Buildings in urban areas significantly contribute to global energy consumption, necessitating solutions to reduce energy demands and mitigate environmental impacts. This study investigates district heating networks in urban areas, using Nottingham as a case study. A literature review addresses key barriers to decarbonising building energy in the UK, focusing on: (1) Information, engagement, and behaviour, (2) Strategy, policy, and regulation, (3) Infrastructure, (4) Supply chain and skills, and (5) Distribution of costs and impacts. The study examines the network's location, current processes, energy performance, and potential future impacts. Heat mapping and energy flow assessments identify areas for energy savings, guiding system optimisation. The findings suggest that increasing the energy output from the heat station to the network can enhance performance. The analysis highlights the potential of a life cycle perspective for district heating networks, proposing a framework that considers all stages from material sourcing to system utilisation. This approach helps assess environmental impacts, including greenhouse gas emissions and resource depletion, identifying opportunities to improve resource efficiency and reduce environmental impacts. By evaluating current sustainability goals and regulatory compliance, the study provides insights into the environmental and social implications of the district heating network's operations, pinpointing areas for improvement. It emphasises the need for continuous optimisation and innovation throughout the network's life cycle. The potential of a full life cycle assessment (LCA) approach is highlighted to evaluate four main future advancements: (1) heating network with added energy storage, (2) advanced system operations through model predictive control (MPC) for demand prediction, (3) general network improvements, and (4) network expansion. Overall, this study aims to enhance the sustainability, efficiency, and resilience of district heating networks, contributing to the transition towards sustainable energy systems while ensuring environmental and economic viability over time.

Sustainable Materials In Aircraft Construction: A Viable Alternative To Aluminium?

This paper explores the viability of sustainable materials as alternatives to traditional metals like aluminium in aircraft manufacturing. Aluminium, widely used due to its lightweight and corrosion-resistant properties, poses significant environmental and structural challenges, including greenhouse gas emissions and susceptibility to thermal expansion. Composite materials, such as bio-based composites and natural-fiber reinforced composites, offer promising solutions by reducing weight, fuel consumption, and greenhouse gas emissions, while also being more cost-effective. The Boeing 787 Dreamliner serves as a case study, demonstrating how composite materials can enhance flight efficiency and sustainability. Although composites present challenges such as damage detection, thermal sensitivity, and manufacturing complexity, ongoing innovations are addressing these limitations. The paper concludes that sustainable composites have the potential to transform aviation, offering a greener, more efficient future.

CAPP-GPT: A computer-aided process planning-generative pretrained transformer framework for smart manufacturing

Smart manufacturing (SM) constitutes the backbone of Industry 4.0 (I4.0), allowing for heightened autonomy of the various interacting cyber-physical systems, making the various entities on the production floor. Connectivity, a vital enabler, plays a crucial role through state-of-the-art Digital Twinning (DT) technologies driven by underlying innovations like the industrial Internet of Things, Cloud Computing, and advancements in sensory devices. DT, which plays a vital role in the various planning functions under the production and operations management umbrella, is being used in the developed combined CAPP-GPT (Computer-Aided Process Planning-Generative Pretrained Transformer) and production scheduling approach to address disruptions on the shopfloor and in self-healing of the manufacturing processes at a micro-CAPP level by optimally adapting the process parameters and the developed toolpath on the fly based on online process signature measurements. In a leap commensurate with that which has taken place in Natural Language Processing-Large Language Models (Chat-GPT), similar efforts are currently being undertaken to parse CAD data structures and blueprints, fusing operations research and predictive analytics algorithms to carry out setup planning as well as sequencing and grouping manufacturing sub-operations. A hybridized Optimization and Machine Learning (ML) approach is employed where Logical Analysis of Data is used to solve the problem heuristically, exploiting various generative and variant methods at heart. Another extension of this macro-CAPP problem is being tackled by integrating the problem with delayed product differentiation, lot-sizing, and transfer line balance for futuristic batch-production shops employing Hybrid Manufacturing (HM) and Smart Assembly. At the micro-CAPP level, HM process parameters are optimized using a comprehensive approach employing the Taguchi loss function to assess surface roughness, internal failure costs, and other criteria, including greenhouse gas emissions and expended energy. Online measurements of the process signatures are also employed to adapt the initial set of process parameters using different automatic control schemes. ML is used to identify the process parameters carrying simulations on Simulink before the system is deployed.

From Farm to Fork: Addressing Food Waste in Households

With the rising environmental awareness, the issue of food waste is drawing considerable attention from civil society, scholars, industry practitioners and policymakers alike. Addressing food waste is crucial, as it incurs a variety of social, health, economic and environmental costs, including greenhouse gas emissions, soil degradation and the depletion of natural resources. The objective of this study is to analyze processes in food waste management to gain insight into factors influencing consumer behaviour, attitudes, and practices regarding consumption and food waste and loss prevention in the supply chain. This requires the analysis of decision making methods and waste reduction strategies and approaches, particularly for households. The goal is to emphasize the importance of raising consumer awareness and sense of individual responsibility, especially given the recent surge in collective community intentions to live more sustainably. However, translating these intentions into tangible actions is uncertain and filled with socio-economic complexities. Reports indicate that, households are responsible for approximately half of all food waste generated. Therefore, it's important to review the literature on barriers and triggers related to behaviour patterns and variations in food related lifestyle dimensions, to determine the factors that might influence food handling and food waste knowledge. Targeting households presents a promising starting point for future interventions, highlighting actions that may influence the current food consumption model to reduce the amount of food wasted. The methodological approach was structured into three steps. First, a literature review was conducted to gather insights and identify factors and interconnections between consumer behaviour and food waste. Second, related drivers and triggers were analysed. Lastly, the findings were summarized to highlight gaps and opportunities for improving attitudes towards food waste prevention.

Current Status and Future Perspectives for Mobility Options Toward Sustainable Transportation With a Focus on Fuel Cells

ABSTRACTThis paper presents a comprehensive analysis of five different vehicle technologies with a particular emphasis on fuel cell vehicles (FCVs) in comparison to conventional gasoline and diesel ICEs, hybrid electric vehicle (HEV), and electric vehicle (EV) technologies. Key parameters in comparison included greenhouse gas emissions (GHG), social cost of carbon (SCC), energy efficiency, fuel consumption, fuel price, driving range, and total cost of ownership (TCO). A normalization approach is employed to rank the technologies across parameters, providing valuable insights for sustainable transportation decision‐making. FCV technology showed the highest average performance (5.343/10) followed by EV technology (4.760/10). The paper also presents current and anticipated hydrogen demand and supply centers, accompanied by a brief overview of commercially available fuel cell technologies. Finally, the sustainability of FCV technology as well as economic, legal, and infrastructural limitations associated with the widespread adoption are also discussed.

A Study on the Environmental Impact Assessment According to the Material Change of the Debris Barrier using Life Cycle Analysis: Focusing on the Case of Yanggu-gun, Gangwon-do

Objectives : The purpose of this study is to evaluate and analyze the environmental performance of an debris barrier installed in Yanggu-gun, Gangwon-do through life cycle analysis. Throughout the entire process of the debris barrier, the six major environmental categories, including greenhouse gas emissions, will be quantitatively evaluated and based on the derived alternatives, it is intended to help improve environmentality to the extent applicable to future plans for the installation of the debris barrier.Methods : In this study, the major environmental categories (Resource Footprint, Carbon Footprint, Ozone Depletion, Acidification, Eutrophication and Photochemical Smog) for each scenario were calculated and evaluated for changes to major materials of debris barrier according to the methodology of the Environmental Product Declaration Preparation Guidelines. Considering the characteristics of debris barrier, the life cycle evaluation stage considered raw material collection and production stages, and exclude the use stage and disposal stage.Results and Discussion : As a result of analyzing environmental feasibility after setting scenarios for each major material (ready-mixed concrete, natural stone) derived through life cycle evaluation for the debris barrier that is the subject of this study, the maximum difference was resource footprint 4.45E+02 kg Sb-eq., carbon footprint 1.46E+05 kg CO2–eq., ozone Depletion 6.97E-03 kg CFC-11-eq., acidification 2.16E+02 kg SO2–eq., eutrophication 3.94E+01 kg PO43-–eq., photochemical smog was evaluated as 5.28E-01 kg C2H4–eq.Conclusion : It was found that it was possible to reduce the environmental category by up to 64.54% or more when changing construction materials during the construction of an debris barrier. Among these, the carbon footprint was the highest at over 70%, which confirmed that the environmental impact of the ready-mix concrete production process was significant. Based on the results of this study, it is believed that in order to improve the environment when planning the installation of an debris barrier, it is necessary to minimize the use of ready-mixed concrete, introduce eco-friendly materials such as natural stone, and improve eco-friendly technology and construction methods.

An exploration of biodiversity limits to grazing ruminant milk and meat production

The production and consumption of animal-source foods must be transformed to mitigate negative environmental outcomes, including greenhouse gas emissions and land-use change. However, livestock are also key for food production and for livelihoods in some settings, and they can help preserve biodiversity and certain ecosystems. Previous studies have not yet fully explored sustainability limits to the use of grazing lands for food production in the context of biodiversity. Here we explore ‘biodiversity limits’ to grassland ruminant production by estimating the meat and milk production from domestic ruminants limited to grazing areas and stocking densities where livestock can contribute to the preservation or restoration of biodiversity. With biodiversity-friendly grazing intensities at 0–20% biomass removal depending on aridity, this take on biodiversity limits corresponds to 9–13% and 26–40% of the current grassland-based milk and meat production, respectively. This equals only 2.2 kg of milk and 0.8 kg of meat per capita per year, globally, but altered management and moving from meat-specialized to meat-and-dairy systems could increase the potential production while still remaining within this approach to biodiversity limits.

Urban Scaling Functions: Emission, Pollution and Health

Urban scaling is widely used to characterize the population dependence of city indicators including greenhouse gas emission. Here we analyze the population dependence of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} and PM2.5 emissions and concentrations across all European cities. Our analysis reveals considerable variations in emissions among cities of comparable population size which are not captured by conventional urban scaling. We thus characterize these fluctuations by multi-parameter scaling functions and multifractal spectral analysis. We find that the distribution of emissions and population is multifractal while that of air pollution is not, leading to non-trivial relations between emission and pollution in some large cities. We also analyze the impact of forests in curbing emission and the impact of air pollution on health. Our work provides a detailed picture of the fluctuations in the scaling of urban metabolism in Europe and suggests a general strategy that goes beyond conventional urban scaling laws.

Sustainable food choices require product-specific environmental footprints: The case of packaged food in Australia

The current food system is a major driver of global environmental change. Despite significant research interest in the environmental impacts of alternative diets, most studies estimate the effects of dietary shifts based on assumed changes in the consumption of raw agricultural commodities instead of simulating changes in the actual food and beverages consumed. In response to increasing consumer demand for product-specific health and sustainability labelling on packaged food products, it is necessary to develop robust environmental footprinting approaches to estimate the environmental impacts of foods and beverages available through retail outlets. This study quantifies the environmental impacts of 63,926 packaged food products in Australian supermarkets across five indicators including greenhouse gas emissions, land use, water use, acidification, and eutrophication potential. We integrated cradle-to-retail environmental estimates from life cycle assessment databases with ingredient proportions derived through a linear programming algorithm to measure product-specific impacts. Meat products consistently showed the highest impacts across all environmental indicators, while fruits, vegetables, plant-based meat alternatives, and non-alcoholic beverages had the lowest impacts. This study also shows that the dietary environmental footprints of Australian consumers can be significantly reduced by switching from high-impact to low-impact products within the same food category (e.g., meat products). Transitioning from high-impact to low-impact products across all food categories could reduce greenhouse gas emissions by up to 96 %, with synergies across all other environmental indicators. The comprehensive results of this study can empower consumers, producers, and governments to identify context-specific opportunities for improving food system sustainability in Australia.

Impact of Food Waste on Society, Specifically at Retail and Foodservice Levels in Developed and Developing Countries.

Food loss and waste pose significant challenges in both industrial and agricultural food production sectors. In recent decades, their environmental and economic impacts have intensified due to increasing food demand, heightened production activities, and varying standards across the global supply chain. Specifically, the complexities surrounding the causes of food waste at the retail and household levels persist as a multifaceted issue, constituting a crucial topic in food policy. This is driven by various interplaying aspects, such as food security, safety, quality, and environmental sustainability, including greenhouse gas emissions from decaying food, water pollution from leaching, and the proliferation of landfills. Additionally, consumer concerns and financial losses exacerbate the urgency of addressing this issue. Therefore, this paper aims to highlight these complexities as a focal point of its discussion by the examination of interconnected causes of food waste and potential solutions and initiatives to reduce food waste occurring at these critical points in the food supply chain. Less attention has been paid to retail and foodservice than production and consumer sectors, and this review specifically focuses on these industries, where food waste is more important than food loss. This review also looks at examples in developing countries which have received less attention until now. We believe that because of the complexity of the process to reduce food waste across the food supply chain, and the many stakeholders involved, the goal of a 50% reduction by 2030 set by the United Nations will be difficult to achieve on time.

Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images

This study utilizes satellite data to detect undocumented oil and gas wells, which pose significant environmental concerns, including greenhouse gas emissions. Three key findings emerge from the study. Firstly, the problem of imbalanced data is addressed by recommending oversampling techniques like Rotation–GaussianBlur–Solarization data augmentation (RGS), the Synthetic Minority Over-Sampling Technique (SMOTE), or ADASYN (an extension of SMOTE) over undersampling techniques. The performance of borderline SMOTE is less effective than that of the rest of the oversampling techniques, as its performance relies heavily on the quality and distribution of data near the decision boundary. Secondly, incorporating pre-trained models trained on large-scale datasets enhances the models’ generalization ability, with models trained on one county’s dataset demonstrating high overall accuracy, recall, and F1 scores that can be extended to other areas. This transferability of models allows for wider application. Lastly, including persistent homology (PH) as an additional input improves performance for in-distribution testing but may affect the model’s generalization for out-of-distribution testing. A careful consideration of PH’s impact on overall performance and generalizability is recommended. Overall, this study provides a robust approach to identifying undocumented oil and gas wells, contributing to the acceleration of a net-zero economy and supporting environmental sustainability efforts.

Geospatial analysis of hydrogen production from biogas derived from residual biomass in the dairy cattle and porcine subsectors in Antioquia, Colombia

The specialized dairy cattle and porcine subsectors in the Region of Antioquia offer a sustainable and renewable energy source through anaerobic digestion of residual biomass. This process offers multiple advantages, including greenhouse gas emissions reduction, environmentally friendly fertilizer production, and the establishment of self-sustaining models for remote rural areas lacking access to traditional energy sources. Recent advancements in hydrogen production through methane conversion using biogas reforming technologies have garnered substantial attention as a viable fossil fuel alternative. The Colombian National Hydrogen Strategy, aimed at 2030, envisions an electrolysis capacity of 1–3 GW, requiring an estimated USD 5.5 billion investment in hydrogen production and demand projects, notably in mobility and refineries. This necessitates a specialized regulatory framework with incentives to drive lasting investments that align with decarbonization and reindustrialization objectives. This study conducted a comprehensive assessment of animal house boundary residual biomass sources to determine their biogas potential. Industrial livestock activities revealed substantial technical-energy potentials: 1,896 TJ/year for pig farming and 187 TJ/year for dairy cattle practices. The research’s primary objective was a geospatial analysis pinpointing hotspots for biogas production from residual biomass within the dairy cattle and porcine subsectors in the specific region of Antioquia, in Colombia. This research is of great interest as it contributes to the growing field of sustainable energy production. It highlights the potential of utilizing residual biomass to transform local energy landscapes in alignment with global sustainability imperatives.

Financial dynamics, green transition and hydrogen economy in Europe

The introduction of the Next Generation funding scheme provides an opportunity for the EU-25 to make significant financial progress towards a radical and fully sustainable Green economy. This study examines the financial implications of a complete transition to hydrogen energy. In this paper, we propose the Hydrogen Production Safe Supply and Storage energy model by analyzing the conversion of electricity from offshore wind farms to hydrogen, which serves as both an energy storage and fuel for a variety of sectors, including transportation, households, industries, and governments. We analyze the financial impact of the Green transition across the EU-25 economies, based on a panel auto-regressive distributed lag model and the simulation procedure proposed by Jordan and Philips (2018). In addition to electricity production and consumption, the variables used include greenhouse gas emissions, real output per capita, and total environmental tax revenue. According to the study's financial insights, increased renewable electricity production results in a significant reduction in household energy consumption, as well as an increase in consumption in the transportation, industrial, and public sectors. These findings underscore the economic implications of transitioning to renewable energy and highlight the financial imperatives, such as targeted state aid, the immediate expansion of the hydrogen supply network, further research on safe mobile hydrogen containment, and an extensive upgrade of the regional hydrogen supply network within the EU-25.

Climate change and its impact on asthma.

Earth's climate is changing at an unprecedented pace, primarily due to anthropogenic causes including greenhouse gas emissions. Evidence shows a strong link between climate change and its effects on asthma. Healthcare professionals must be educated to advocate for and lead effective strategies to reduce the health risks of climate change.

Examining the role of ruminants in sustainable food systems

AbstractSustainable food systems provide food security while stewarding economic, social, and environmental bases in ways to meet future generations' needs. Sustainable food systems encompass the health of animals, people, and ecosystems. Healthy and productive ruminants can produce meat and milk products with fewer resources, and consequently, often fewer greenhouse gas emissions are produced. Ruminant livestock faces the dual challenge of being impacted by and contributing to climate change, while also experiencing increased demand for ruminant meat and milk products due to growing global population and increased incomes. This challenge presents different ways forward depending upon solutions and how one values certain aspects of sustainability, ranging from simply building upon past improvements in ruminant agriculture to dramatic reductions in ruminant livestock populations. Better understanding the concerns with ruminant's role in sustainable food systems is important, as is understanding the different viewpoints and interpretation of evidence both for and against ruminant agriculture. This review provides a brief overview of some of the key issues related to the role ruminant animals play in sustainable food systems, including greenhouse gas emissions, feed‐food competition and land use, and human nutrition. The review also highlights how improved animal health outcomes can enhance ruminants' role in sustainable food systems. Ultimately, ruminants make unique contributions to human flourishing via providing nutrition, livelihoods, and ecosystem services from forage resources and grassland landscapes. However, the status quo is unlikely to meet the challenges of the coming decades, thus investing in research and development into sustainable ruminant systems is required.