Urban and rural residents differ markedly in the resource use and pollution emissions associated with their food consumption, particularly in rapidly urbanizing China. Based on environmental footprint theory, we developed a framework that accounts for four footprint types: water, carbon, nitrogen, and phosphorus, and we conducted a scenario analysis. Using panel data from 31 provinces spanning 2015 to 2023, we characterized the spatiotemporal evolution of the environmental footprints of urban and rural food consumption. We then established three scenarios for 2030: a baseline scenario (S0), a developing dietary pattern scenario (S1), and a multi-objective optimization scenario (S2). These scenarios project how environmental footprints of urban residents would change under different dietary patterns. Urban water, carbon, nitrogen, and phosphorus footprints continued to increase, with the highest values observed along the southeastern coast. In rural areas, total food consumption declined, whereas the nitrogen and phosphorus footprints showed a decline then rise pattern, with high value zones shifting to the Chengdu-Chongqing region and the middle-lower Yangtze River. Under the developing dietary pattern scenario, rural footprints increased at a much faster rate than their urban counterparts. Under the multi-objective optimization scenario, reducing livestock meat consumption to the lower bound of the dietary guidelines substantially reduced all four footprints relative to the baseline. The benefit of dietary optimization for controlling nitrogen and phosphorus nonpoint source pollution was four to six times greater than that for carbon reduction. Our scenario projections, which rely on nationally averaged footprint coefficients, are subject to data uncertainties. Uncertainty analysis using Monte Carlo simulation with a truncated normal distribution shows that, although the absolute estimates carry substantial uncertainty, the relative ranking of urban-rural comparisons and scenarios is insensitive to coefficient variation. Guiding urban and rural residents toward the dietary pattern recommended by the Chinese Dietary Guidelines, in particular substantially reducing livestock meat consumption, is an effective way to alleviate resource pressure, lower carbon emissions, and achieve coordinated nitrogen and phosphorus mitigation.
To examine the association between diet quality and food carbon footprint among adult urban and rural residents in China. Data were derived from the 2018 wave of the China Health and Nutrition Survey (CHNS), including 11 573 adults aged ≥18 years with complete dietary and demographic information. Individual food carbon footprint was estimated using coefficients from a life-cycle assessment-based database and expressed as grams of CO2 equivalents per day (g CO2eq/d). Diet quality was evaluated using the China Dietary Guideline Index 2022(CDGI-2022). Multivariable linear regression models were applied to assess the relationship between CDGI-2022 scores and log-transformed total food carbon footprints. The median total food carbon footprint was higher among urban residents (1748.13 g CO2eq/d) than among rural residents (1644.85 g CO2eq/d) (P<0.001). Carbon footprints among urban residents were mainly driven by animal-source foods, whereas those among rural residents were primarily derived from plant-based foods. The mean CDGI-2022 score was higher in urban residents than in rural residents (48.12±11.31 vs.42.37±10.87, P<0.001). Multivariable regression analysis showed that CDGI-2022 total scores were positively associated with log-transformed total food carbon footprints in both urban (β=0.003, 95%CI 0.002-0.004) and rural residents (β=0.004, 95%CI 0.003-0.005). Scores for adequate- and moderate-intake components were positively associated with food carbon footprints (P<0.001). Higher scores for limited-intake components were inversely associated with carbon footprints among urban residents (β=-0.007, 95%CI -0.008--0.005), but no significant association was observed among rural residents. Under current dietary patterns in China, higher diet quality is associated with higher food consumption carbon footprints.
The Footprints Project is a humanizing initiative that elicits and displays personal information from patients and families about a patient's life before illness. Key details recorded on a form are then written on a whiteboard in the patient's room to support person-centered care. The whiteboard keeps personal identity, preferences, and daily plans visible. The objective of this study was to explore how the Footprints Project evolved over time and to identify contextual determinants and practical strategies that may support its ongoing sustainability from the perspectives of patients, families, and clinicians. This qualitative descriptive study was co-designed with patients and families in a 23-bed university-affiliated medical-surgical Intensive Care Unit (ICU). Implementation followed a preparatory audit, staff surveys, multi-directional communication, and volunteer integration. We enrolled survivors of critical illness, family members of ICU patients, and clinicians to participate in focus groups and individual interviews. Transcripts were analyzed using conventional qualitative content analysis and interpreted with attention to constructs within the Clinical Sustainability Framework as a sensitizing lens. Participant interviews and focus groups with 7 patients, 19 family members and 40 clinicians identified four transitions reflecting the evolution and embedding of the Footprints Project: 1) transition from a nurse-led tool to an intentional interprofessional intervention; 2) transition from a patient-centered tool to a patient and family-partnered intervention; 3) transition from a stand-alone intervention to one embedded into daily workflows; and 4) transition in the format and content of the form and whiteboard. In this qualitative study, patients, families, and clinicians identified practical strategies and contextual features that supported the evolution and ongoing use of the Footprints Project through interprofessional and family-partnered efforts, workflow alignment and refreshed tools. Embedding Footprints into daily ICU workflows may strengthen person-centered care by making patient identity visible at the bedside. Interprofessional ownership and explicit family partnership can enhance consistency and sustainability. Updating and intentionally embedding tools may support staff engagement in high-acuity environments. These strategies may help ICUs to operationalize other humanizing practices in practice.
Dairy farms are under pressure to reduce greenhouse gas (GHG) emissions. Various carbon footprint (CF) accounting tools have been developed for calculating GHG emissions and pinpointing hotspots to support mitigation efforts. However, inconsistent methodologies often lead to variations of their results, unclear discrepancies pose barriers to credible reporting and decision making. Five open access, farm-level CF accounting tools applicable to EU livestock production were evaluated and compared for their methodologies. They were further tested through a case study of a dairy Farm in Finland for their consistency in quantifying emissions of milk production. The sensitivity of each tool was analyzed across nine mitigation scenarios to evaluate their practical utility in guiding mitigation strategies. A significant variability in total GHG emissions was observed, ranging from 415 to 913 t CO2 eq y-1, derived mainly from differences in scopes and the adoption of varying method tiers (in IPCC 2006 or IPCC 2019). While enteric fermentation and feed production remained the primary emission sources across all tools, their contributions fluctuated based on calculation methods. Solagro and the Cool Farm Tool were most responsive to mitigation strategies regarding manure management and yield improvements, while GLEAM-i and CAP'2ER (level 1) lacked the flexibility to model specific management shifts. The lack of methodological harmony causes inconsistent results, requiring careful tool selection to align with specific goals and data availability. Methodological frameworks can be harmonized with evolving standards (Product environmental footprint category rules for dairy products), meanwhile adapting scientific advances into calculations to ensure transparency and comparability.
Automated delineation of settlements at the level of single buildings is advancing on global scale due to developments in image processing techniques. However, in morphologically complex poverty areas (e.g., slums or informal settlements) automated image classification reaches limits. This gap of systematic, accurate geodata hinders the impetus of 'better data for better decisions' by the UN Sustainable Development Goals. To bridge this gap, we present a dataset of >320,000 building footprints derived from satellite imagery in 44 poverty areas across the globe. We use 'Manual Visual Image Interpretation' for consistent delineations of rooftops proxying building footprints. The method has been applied to 1. classify different morphological types representing poor living environments based on spatial features; 2. document multitemporal dynamics at different spatial scales; and, 3. assess interpreter-related uncertainties across interpreters. We release these data along with interpretation guidelines and validation. We provide a robust empirical basis for the global systematization and comparative analysis of settlement forms proxying poverty, while offering training and validation data for automated image classification.
This study evaluated the influence of multiple traffic-related conditions, including proximity to a road, car parking, highway, road junction, and transport stop, commonly observed yet largely overlooked in many non-metropolitan cities of developing nations, on trace element (TE) contamination in roadside soil and the associated risks in a secondary South African city. Among the evaluated TEs (As, Ba, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, Zn), mean Cu and Pb concentrations exceeded national soil quality guidelines at 100% and 86% of sites, respectively, whereas pollution assessment revealed generally moderate Sb, Pb, Cr, Ni, Co, Mn, and Zn contamination at > 71% of sites; indicating 73% of TEs as potential environmental threats. Of the seven examined localities, a mean pollution load index above 1 suggested soil pollution at a site affected by most traffic conditions. Regression analysis indicated positive relationships between road proximity and concentrations of all TEs, with significant (p < 0.05) associations for 75% of the identified contaminants, along with As and Ba. Significant positive correlations between TEs exhibiting higher contamination suggested shared sources. This was further supported by principal component analysis, which associated 73% of TEs with one or more traffic variables, primarily road proximity, transport stop, and highway, and secondarily car parking. Moreover, origin from multiple traffic sources was suggested for most TEs. Nearly moderate ecological risks for Cd and Pb at two sampling points, and potential cancer risks for children from As, require follow-up investigation. The findings provide valuable insights into the globally underexamined pollution footprint of multiple traffic-related factors and highlight the need for their management to promote ecosystem sustainability in comparable cities.
Sulfate is a widespread and persistent byproduct in many advanced oxidation processes (AOPs) for wastewater treatment, yet its residue has been systematically overlooked. Despite the original intention and widespread adoption for degrading recalcitrant organic pollutants in industrial wastewaters, AOPs inadvertently produce substantial sulfate through catalyst/co-catalyst addition, pH adjustment, oxidant decomposition or electrolyte usage. Elevated sulfate levels affect the AOPs-treated effluent quality directly or indirectly by impairing subsequent biological treatment, posing public health and socio-economic impacts. This Making Waves critically examines the neglected sulfate footprint across mainstream AOPs and proposes forward-looking strategies for sulfate mitigation from both the source and the effluent. These include accelerating Fe(III)/Fe(II) cycling to reduce ferrous sulfate input, developing AOPs with broad pH adaptability and acid-free operation, reducing persulfate consumption and integrating post-treatment biological or bioelectrochemical systems for sulfate removal. Balancing organic pollutant degradation with sulfate management, shifting from treating sulfate as a passive burden to exercising active control, is essential for transitioning AOPs toward environmentally sustainable wastewater treatment technologies.
Healthcare contributes substantially to global greenhouse gas emissions; however, the environmental impact of clinical research activities remains poorly understood. Quantifying emissions is a necessary first step toward reducing the carbon footprint of research. To map and synthesise literature measuring carbon emissions associated with clinical research activities, with a focus on research domains assessed, tools and methods used and units of measurement reported. A scoping review was conducted following the Arksey and O'Malley methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guidance. PubMed, Web of Science, CINAHL, Scopus, EconBiz, GreenFile and ProQuest were searched from database inception to June 2026. Eligible studies reported measurement of carbon emissions related to clinical research activities. Data were charted and synthesised narratively. Twenty-five studies met the inclusion criteria, most published between 2019 and 2025 and primarily from Europe and the UK. Studies used a wide range of tools and resources, including life cycle assessment databases, online calculators, international standards, government emission factor datasets and healthcare-specific sustainability frameworks. A clear trade-off emerged between methodological rigour and accessibility: comprehensive life cycle assessment tools required expertise and licensing, while simpler calculators enabled rapid but less precise estimates. Carbon dioxide equivalent and global warming potential over a 100-year time horizon were the dominant reporting metrics, although variation in functional units limited comparability across studies. The methodological landscape for measuring emissions in clinical research is fragmented and lacks standardisation. Development of consensus guidance and reporting standards is needed to support consistent measurement and reduction of research-related emissions.
Ionic liquids (ILs) are regarded as environmentally friendly solvents due to their favorable physicochemical properties, including low volatility and high thermal stability. However, their high water solubility and poor degradation pose potential threats to aquatic ecosystems. Based on domestic and international research, the present study systematically reviews the toxic effects of ILs on multi-trophic-level organisms in aquatic food chains, including producers, primary and secondary consumers, and summarizes the toxic mechanisms of ILs in aquatic organisms. It also delves deeply into the key factors that influence the toxicity intensity of ILs. In addition, a comprehensive quantitative analysis of the large existing dataset is conducted, and the results of the Meta-analysis further reveal the impacts of different types of ILs and exposure conditions on aquatic organisms. These research results provide a theoretical basis and technical support for the green application of ILs, the assessment and early warning of ecological risks, and guidance for future research on ILs.
Endocrine-disrupting pesticides (EDPs) exert deleterious effects on the endocrine system, with documented evidence implicating specific pesticides in endocrine disruption, resulting in developmental delays during puberty and thyroid gland dysfunction, thereby increasing susceptibility to metabolic diseases. The disruption of intracellular insulin signaling, which is characterized by redox imbalance, toxicological effects, and proinflammatory activity, facilitates cellular adaptation to stress. However, this adaptive response can aberrantly induce a dysfunctional feedback loop characterized by diminished cellular insulin responsiveness, a prevalent feature of metabolic disorders. Despite significant advancements in the scientific understanding of EDPs, substantial knowledge gaps and uncertainties persist, impeding progress toward improved health outcomes. This review highlights current findings on the metabolic toxicity of pesticides in the context of obesity and diabetes, concentrating on crucial signaling pathways and a mechanistic perspective that offers insight into resistance channels as reviewed. These findings enhance our understanding of the potential impacts of EDPs on human health.
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This article presents a Sentinel-2 image dataset for railway presence classification across metropolitan France. The collection contains 10,000 true-color RGB PNG chips with equal representation of railway and railway-absent scenes. Each chip has dimensions of 224 × 224 pixels and covers a ground footprint of 512 m × 512 m. Railway chip locations were derived from retained OpenStreetMap railway=rail geometries. The railway class was constructed through geographically balanced sampling along the retained network and distance thinning between selected locations. Railway-absent chips were generated in the local surroundings of railway locations. A railway-absent chip was included only when its complete footprint did not intersect retained railway geometries and did not overlap an already accepted chip footprint. The image collection was generated from Copernicus Sentinel-2 Level-2A observations acquired by the Sentinel-2 satellite constellation. Bands B04, B03 and B02 were used to create the red, green and blue image channels. Retrieval covered the period from 23 June 2025 to 23 June 2026 and applied a maximum cloud-cover threshold of 10 percent together with least-cloud-cover mosaicking. The included files comprise the image collection and a CSV metadata table containing image filenames, class labels and stable candidate identifiers. The dataset provides material for railway-presence classification, comparison of image-classification architectures, spatial evaluation designs, and geospatial representation-learning workflows.
This study employed an ensemble species distribution model Biomod2 integrated with ArcGIS spatial analysis and utilized climate, soil, and human footprint data to predict the potential suitable habitats for Ophiopogon japonicus under various scenarios and to assess the key drivers governing its distribution. RESULTS:: revealed that mean diurnal temperature range, temperature seasonality, and human footprint were the primary factors determining its distribution. When anthropogenic disturbances were excluded, the area of highly suitable habitats expanded significantly, extending notably into regions such as Guizhou, Chongqing, and Jiangsu. Under a low carbon emission scenario, the suitable habitat area showed a trend of gradual increase followed by stabilization. In contrast, under a high emission scenario, it contracted substantially and exhibited increased spatial fragmentation. In short, human activities and climate change had a significant impact on the suitable producing areas for O. japonicus. The findings provided an important scientific basis for the conservation and utilization of key producing areas, the long-term preservation of germplasm resources, and the sustainable development of the O. japonicus industry. Furthermore, this study demonstrated that the ensemble modeling approach enhanced the scientific validity and robustness of producing area predictions, offering valuable insights for optimizing future habitat planning and adaptive management strategies of O. japonicus.
Beginning in September 2024, three large-footprint pulsed-field ablation (PFA) systems were introduced in Japan for atrial fibrillation (AF) ablation. To compare acute procedural outcomes and safety profiles between PFA and thermal ablation. This multi-center observational study included 4969 consecutive index AF ablation procedures (69 ± 11 years, 1495 women, 2705 paroxysmal) performed between January 2024 and July 2025. Among them, 2817 and 2152 procedures were performed with thermal ablation and PFA (FARAPULSE 53.3%, PulseSelect 41.3%, and VARIPULSE 5.5%), respectively. PFA procedures were performed under deeper sedation (70.5% deep sedation) compared with thermal ablation. The total PFA application numbers were 50 ± 13 for FARAPULSE, 49 ± 13 for PulseSelect, and 24 ± 8.5 for VARIPULSE. Touch-up ablation for pulmonary veins was more frequently required with balloon-based thermal ablation than with PFA (7.2% vs. 1.5%, p < 0.01). Adjunctive posterior wall isolation was more common in the PFA-group than Thermal-group (30.3% vs. 11.4%, p < 0.01). Fluoroscopy time was significantly longer (27.8 ± 17.1 vs. 24.9 ± 17.6 min, p < 0.01) and total procedure time significantly shorter in the PFA-group than Thermal-group (106 ± 48.5 vs. 131 ± 54.4 min, p < 0.01). The overall complication rate (2.4% vs. 4.4%, p < 0.01) and phrenic nerve palsy rate (0.1% vs. 1.5%, p < 0.01) were significantly lower, while coronary spasms tended to be more frequent in the PFA-group. No gastric hypomotility or pericarditis occurred in the PFA-group despite much lower use of esophageal temperature monitoring (3.2% vs. 83.1%, p < 0.01). This large real-world registry demonstrated a significantly lower incidence of procedure-related complications with large-footprint PFA devices compared with thermal ablation systems, despite early-phase adoption.
Cropland systems face the challenge of providing adequate nutrition while managing environmental constraints, such as climate change and water scarcity. In China, where agricultural production supports a large portion of the global population with limited land and water resources, achieving balance between efficiency and sustainability in cropland systems is a critical issue. The purpose of this study is to develop a spatially explicit diagnostic framework that integrates crop production, calorie-output data, and environmental impact models to assess cropland efficiency (CE) and sustainability (CS) across regions and crop types in China. The study aims to identify how these two calorie-based performance dimensions interact and where they either reinforce or undermine each other. Crop production data, life cycle assessment, water-footprint accounting and a coupling coordination degree (CCD) model were integrated to evaluate CE, CS and their coordination within a common analytical framework. Random forest models and SHapley Additive exPlanations (SHAP) were then used to characterize the non-linear associations of climate, soil, hydrogeology and management factors on CE, CS and CCD. CE and CS varied substantially across regions, crop types and water-supply conditions. In the Northwest, maximum calorie-based productivities reached about 55.01 kcal g-1N for NUE, 1.95 Mcal g-1 PO43--eq for eutrophication productivity and 2.08 Mcal m-3 for grey-water-footprint productivity. CE and CS were highly correlated nationally (R2 = 0.98), but their hotspots were not fully aligned: CE hotspots were concentrated mainly in Northeast and North China, whereas CS hotspots shifted towards South, Northeast and North China. Irrigation increased CE by roughly one-third in water-scarce Northwest and North China, but reduced GHG productivity by an average of about 13% across regions and by up to 48% in South China. Pulses showed consistently higher CE and CS than cereals and sugar crops. Nitrogen fertilization and irrigation intensity were the dominant management drivers, with positive effects at moderate levels but negative effects on CS and CCD when inputs became excessive. Improving cropland performance requires region- and crop-specific strategies, not uniform input expansion. Precision irrigation, balanced nutrient management, soil conservation and crop restructuring can improve the coordination between calorie-based efficiency and environmental sustainability when matched to local water availability, soil conditions, crop portfolios and socio-economic feasibility. The framework provides a transferable diagnostic approach for identifying efficiency-sustainability synergies and trade-offs, while local recommendations still require field validation, farmer-level economic assessment and policy implementation analysis.
Hypoxic stress triggers transcriptional signaling mainly through hypoxia-inducible transcription factors (HIFs), which bind hypoxia response elements (HREs) in gene regulatory regions. However, only a small proportion (~1%) of known HREs are occupied by HIFs during hypoxia, suggesting the involvement of additional hypoxia-responsive factors. To address this gap, we utilized MNase-defined cistrome Occupancy Analysis sequencing (MOA-seq), with the term cistrome referring to all genomic regions where transcription factors and other trans-acting regulators are bound to cis-acting elements across the genome for a particular cell type or treatment. This MNase-based assay enables genome-wide, high-resolution (<30 bp) identification of transcription factor (TF) occupancy footprints embedded within larger regions, most of which were previously annotated as open or accessible chromatin. Applying this in situ cistrome mapping to fixed nuclei from endothelial cells under normoxia or hypoxia (1, 3, or 24 hr) revealed thousands of hypoxia-responsive genomic sites with dynamic TF footprints. The affected genes were enriched in canonical hypoxia-induced pathways, such as angiogenesis. Motif analysis identified over 100 candidate TFs potentially mediating these multifaceted genomic responses. By grouping hypoxia-modified occupancy signals across the hypoxia exposure times, we clustered differentially occupied MOA sites into defined 10 distinct TF kinetic clusters, half of which were associated with HIF1A. HIF1A-proximal binding sites suggested co-activators, while non-HIF1A clusters pointed to additional TFs that may have HIF1A-independent roles. This analysis provides insight into how multiple TF networks coordinate hypoxia responses and highlights the power of cistrome profiling to deepen our understanding of the complex genomic response to low oxygen conditions.
Research on urban scaling laws suggests that cities with larger populations tend to be more resource-efficient, yet whether these findings hold across spatial scales, varying definitions of 'urban' and the entire rural-urban continuum remains unresolved. Herein, we leverage high-resolution maps for the entire contiguous United States of America to examine how built environment material stocks, service provisioning, and operational greenhouse gas (GHG) emissions scale with population size across the country. Results show that residential building footprints, i.e., the ground area covered by buildings, useful floor area, and material stocks scale moderately sub-linearly (scaling exponent β in the [0.82, 0.89] interval). Non-residential buildings and mobility infrastructure (area, materials) scale more strongly sub-linearly (β in the [0.42, 0.74] interval). These patterns are robust across sensitivity tests. Furthermore, people living in high-density urban areas require less than half of per capita building footprints, mobility infrastructure area, total infrastructure mass, and residential on-road GHG emissions, compared to residents in low-density rural areas, demonstrating substantial environmental benefits of dense settlements. The online version contains supplementary material available at 10.1007/s44498-026-00125-w. Supplementary Information SI1. This Supplementary Information contains supplementary methodological details, additional explanations, robustness tests, figures, and results, including Supplementary Notes S1, S20, Supplementary Figures S1, S18, Supplementary Tables S1, S24, and Supplementary References. Supplementary Information SI2. This Supplementary Information file provides the numerical data underlying Tables S3, S4, S10, S11, S19, and S23 reported in Supplementary Information SI1.
Medications account for a substantial share of greenhouse gas (GHG) emissions in healthcare institutions (up to 30%). Hospital pharmacists are key stakeholders with the capacity to influence the carbon footprint of healthcare facilities. To compare two methodological approaches for estimating the carbon footprint associated with medications used in healthcare institutions and to calculate the GHG-to-monetary-unit ratio (euro/CAD) for each method. Prospective descriptive study. A monetary-based method derived from the OpenIO-Canada tool was compared with a physical method based on life cycle assessment of medications, as proposed by ECOVAMED. A convenience sample was drawn from the CHU Sainte-Justine formulary for the fiscal year from April 1, 2024, to March 31, 2025. GHG emissions estimated using each method were calculated and compared. An additional calculation of GHG emissions per euro spent was performed. A total of 487 medications out of the 2,098 listed in the CHU Sainte-Justine formulary were successfully matched with data from the ECOVAMED database. These 487 medications accounted for 23% of formulary items, 34% of doses administered, and 54% of total drug expenditures. GHG emissions estimated using the physical method represented 21% of those estimated using the monetary method (1,286,116 vs. 6,235,474 kg CO₂e). Regarding the mean ± standard deviation of kg CO₂e by route of administration based on ECOVAMED data, values were 666,593 ± 8,637 kg CO₂e for parenterally administered medications and 17,833 ± 57 kg CO₂e for enterally administered medications, corresponding to a 37.3-fold difference. This study is the first to directly compare a monetary-based method and a physical-based method for estimating greenhouse gas (GHG) emissions associated with medications used in hospital pharmacy. Based on the available literature, the monetary-based method appears to be a valid and rapid approach for estimating the overall GHG emissions of hospital pharmacy activities. However, it may either overestimate or underestimate actual emissions. In contrast, the physical-based method enables medication-specific GHG estimates and is more relevant for informing decisions related to medication selection, prescribing, and preparation within healthcare institutions. It can also support both healthcare decision-makers and clinicians in implementing more sustainable practices. Further research is needed to better compare and validate these two approaches.
Genetic improvement has been identified as a key practice for reducing the environmental impact of livestock systems through improved production efficiency. Beef-on-dairy (BxD) production comprises an increasingly large portion of beef supply chains and provides data collection opportunities for understanding the environmental impact of genetic improvement. Life cycle assessment (LCA) is the gold standard for measuring product-level environmental footprints and, to date, has not been applied to assess the mitigation potential of targeted genetic improvement in BxD production. The objectives of this study were to provide a framework for incorporating genetic improvement into an LCA, quantify the role of targeted genetic improvement in BxD production systems in the US and UK, and demonstrate the value of targeted genetic improvement as a key intervention for reducing the environmental impact of beef production. Life cycle assessments were completed for three BxD populations, a typical US feedlot system (US) and a premium (UK-HQ) and commodity (UK-HY) system in the UK. Each population was comprised of animals from two different genetic backgrounds: benchmark animals sired by industry average genetics, and genetically targeted animals (GT) sired by bulls from a breeding program targeting selection of traits that optimize BxD production. Within the benchmark and GT populations, animals were assigned to one of five genetic tiers, with five being the highest merit level, based on their sire's value for a BxD genetic index. Individual-level data were available for each of the growing phases, defined as weaning, rearing-milk, rearing-fed, grazing (UK-HQ only), and finishing. Average phenotypic performance in each sire tier was determined for average daily gain (ADG), days at the growing phase, feed dry matter intake (DMI) in finishing (US and UK-HY), and carcass weight. Using these performance averages, LCA runs evaluated each combination of genetic background (benchmark and GT), population (US, UK-HQ and UK-HY), sire genetic tier (Tier 1-Tier 5) and marketing year (2024 and 2029). The life cycle impact assessment characterized sixteen environmental impact categories covering water use and quality, land use, air quality, resource use, and climate change. Across all populations and sire genetic tiers, the main processes contributing to the relevant impact categories were feed production, manure management, and, for climate change only, enteric fermentation. The finishing phase had the largest impact among all growing phases, ranging from 50-89% of impact across the relevant impact categories. Higher genetic merit (i.e., higher sire tiers) consistently led to concurrent reductions across damage categories that aggregated to lower overall environmental impact. Comparisons of benchmark Tier 3 to GT Tier 5, representing the effect of genetic improvement, resulted in reductions in overall environmental footprint of -8.7% for the US, -9.6% for the UK-HY, and -4.2% for the UK-HQ populations in the 2024 marketing year, driven in part by climate change reductions of -4.7%, -8.8%, and -4.7%, respectively. This study demonstrates that genetic improvement in commercial systems for improved production efficiency confers systemic environmental benefits that accumulate over time, underscoring the value of targeted genetic improvement as a foundational practice for improving the sustainability of livestock production.
Industrial, commercial, and institutional (ICI) food waste is a large, poorly quantified component of municipal solid waste. Landfill disposal of food waste results in greenhouse gas emissions and lost resources. Here, we apply a spatial-probabilistic modelling approach for estimating sector-specific ICI food waste generation and demonstrate this technique for Montreal, Canada. We identified 14,508 ICI establishments from municipal food inspection records and classified them into 14 subsectors. Point locations were matched to building footprints to acquire areal estimates for each establishment. Values for other operational variables were taken from a set of 421 Canadian ICI facility audits. A Monte Carlo approach was used to estimate uncertainty (relative standard error) for each establishment, with results summarized by establishment type and subsector. Overall, the model showed that the ICI sectors in Montreal sent 215.4 ± 7.8 kt yr-1 of food waste to landfill, with 6% of the mapped grid cells accounting for over 50% of total disposal. Food service and retail contributed 83% of the total ICI food waste, while the food manufacturing subsector had the greatest uncertainty. Areas with a higher intensity of food waste generation had consistently lower uncertainty, suggesting that they could be strategic areas to target policy interventions. Our approach draws on readily accessible building footprint data and could be adapted for cities in other regions where food waste audits are available. By explicitly modelling sector-specific and geographic variability, our model can help pinpoint where urban food waste reduction and landfill diversion strategies could be most effective, supporting efforts toward a circular bioeconomy.