Search Results (2,930)

Background/Objectives: Inflammatory bowel disease (IBD) requires frequent specialist follow-up, yet patients in remote areas face significant geographic barriers to care. Healthcare delivery also contributes substantially to greenhouse gas (GHG) emissions, with patient travel a major source. The Promoting Access and Care through Centres of Excellence (PACE) virtual care program was designed to improve access for IBD patients in underserved regions of Ontario. This study estimated travel-related carbon dioxide (CO₂) emissions potentially avoided. Methods: A retrospective cohort study was conducted using the PACE registry at the Mount Sinai Hospital IBD Centre between June 2016 and October 2024. Adults with Crohn’s disease, ulcerative colitis, or IBD-unclassified residing ≥100 km from the Centre and completing ≥1 virtual visit were included. Two-way travel distance avoided was calculated using Google Maps, adjusting for any travel to local facilities. Carbon emissions were estimated using a composite base-case factor of 260 g CO₂/km with predefined sensitivity analyses covering alternative vehicle-mix and transport scenarios. Results: Among 389 IBD patients, 2222 virtual visits were completed. The mean (±SD) two-way distance avoided per visit was 843 ± 812 km, corresponding to 219 ± 211 kg CO₂ per visit. The mean cumulative reduction per patient was 1252 ± 2245 kg CO₂, totalling 487,104 kg (487 tonnes) over eight years. Conclusions: The PACE program was associated with substantial estimated reductions in travel-related CO₂ emissions for IBD patients in remote Ontario, with results robust across vehicle mix and transport assumptions. Virtual care may offer a scalable pathway advancing both equitable access and healthcare-sector decarbonization. Full article

The transport sector has emerged as a significant source of greenhouse gases and airborne pollutants. However, few studies have carried out a comprehensive assessment of the synergistic benefits between air pollutant and carbon emission reductions that account for the unique regional characteristics of individual provinces. In this study, we establish nonlinear prediction models for future activity levels of on-road mobile sources by integrating economic and demographic drivers. We then dynamically quantify the co-benefits of simultaneous air pollutant and CO₂ abatement under diverse mitigation scenarios. Environmental tax rates and carbon trading prices are combined with conventional elasticity coefficients and coordinate-based methodologies to convert emission cuts into economic advantages. The results show that under the most optimistic scenario, 47.86% of the CO₂ emissions could be mitigated, while emissions of NO_X may increase by 60.49% in the absence of mitigation strategies (BAU scenario). Marginal CO₂ emissions under the ELC scenario indicates a peak around 2027. Elasticity coefficients for all pollutants gradually converge toward 1, indicating that more stringent mitigation efforts enhance co-benefits. Findings in this study could provide essential insights for the co-management of CO₂ and air pollutants from road mobile sources in Guangxi and other key regions along the Belt and Road Initiative. Full article

This review analyzes sustainable and regenerative development in the beef production chain, focusing on environmental impacts and pasture-based cattle farming. Livestock emissions account for about 14.5% of global anthropogenic greenhouse gases, with beef cattle contributing 3–3.2% mainly from enteric fermentation and manure management. Pasture-based cow-calf operations generate 60–70% of these emissions, posing significant challenges for producers. Improper grazing degrades soil and vegetation, reducing productivity, while climate change and technology introduce new animal health issues. At the same time, given that beef is an important food item worldwide, it is important to strive for the regenerative management of beef cattle farming. This article lists possibilities for researchers, beef cattle breeders, and farmers to follow and implement, in the hope that the sector will become regenerative. Scientific innovation in grazing-based beef cattle systems should focus on precision livestock monitoring, regenerative pasture management, genetic selection, and improving animal health, as well as identifying opportunities within the value chain. Such innovations could help to optimize productivity, enhance sustainability, improve animal welfare, and generate new income streams through ecosystem services or premium grass-fed markets. Full article

Climate change has been identified by the World Health Organization (WHO) as “the single greatest health threat to humanity”. To investigate this subject, we conducted a narrative review of the literature about sustainability in the OR, with the aim of exploring the existing knowledge and identifying prevailing challenges in the field. A combined automated and manual database search of the literature was performed using Medline (PubMed), Scopus, Ovid, and the Cochrane Library, covering publications available up to and including 21 May 2025. The significance of environmental sustainability is recognized across all healthcare systems. To fulfil the United Nations Sustainable Development Goals, the healthcare sector must undergo a transformation towards more eco-friendly practices, which will also affect clinical decision-making. Net-zero is an internationally agreed goal for avoiding worsening global heating in the second half of the 21st century, as it aims to balance the quantities of greenhouse gases released into and removed from the atmosphere, achieving carbon neutrality. Nevertheless, the operating room (OR) is among the most significant contributors to environmental pollution, with the major carbon hotspots determined by the use of energy, procurement and disposal of consumables and the waste of water. In response to this challenge, leading medical societies, surgical teams, government bodies, and industry stakeholders endorse Green Surgery (GS) by taking steps to address healthcare sustainability and its impact on climate change. Therefore, a movement toward “greening” healthcare, or improving the environmental footprint of healthcare has been built. Full article

The transition towards climate-neutral metallurgical production requires a broader transformation than the simple substitution of fossil-fuel combustion with electrical heating. While process electrification is a fundamental step towards reducing greenhouse gas emissions, achieving truly sustainable high-temperature processing also depends on the ability to maintain tightly controlled reaction environments, minimise thermal losses, and maximise the efficient use of process gases. These factors become increasingly important as the industry moves towards hydrogen-assisted processing routes and greater integration of renewable energy sources. By controlling heat transfer and gas composition, a stable processing environment can be maintained in which temperature, and gases’ partial pressure, can be accurately regulated throughout the treatment cycle. This study introduces the engineering concept of an airtight electrified indirect-fired rotary furnace, developed as a new process for efficient calcination, and also, hydrogen-based reduction processes. To assess the applicability of the proposed reactor concept, a bench-scale experimental campaign was carried out using two representative metallurgical processes: magnesite calcination and hydrogen-assisted reduction of lateritic ores. Throughout the testing campaign, the reactor maintained stable thermal conditions and a well-controlled process atmosphere, while the integrated monitoring system enabled continuous observation of temperature evolution and gas composition. The calcination trials achieved conversion efficiencies above 98%, whereas the hydrogen-reduction experiments successfully promoted the transformation of iron and nickel oxide phases into their metallic state. The results demonstrate that the integration of indirect electrical heating with airtight reactor operation provides a robust platform for hydrogen-assisted thermal processing. The proposed architecture improves atmosphere control and process efficiency while offering a scalable solution for the future implementation of electrified, low-carbon metallurgical technologies. Full article

Heavy-duty methanol engines are regarded as a promising low-carbon solution for commercial vehicle decarbonization, yet the comprehensive coupled characteristics of fuel consumption, multi-dimensional exhaust emissions, and the corresponding aftertreatment adaptability between stoichiometric and lean-burn technical routes remain insufficiently quantified, restricting the optimized application of methanol powertrains for China-VI emission compliance. To address this research gap, this study systematically investigates two China-VI compliant heavy-duty methanol engines with stoichiometric and lean-burn combustion strategies under cold-start and hot-start Worldwide Harmonized Transient Cycle. And a comparative analysis is conducted to clarify the differences in the fuel consumption, raw exhaust emission (including regulated pollutants, particulate matters, greenhouse gases, and unregulated pollutants), and the catalytic performance of aftertreatment systems between two engines with stoichiometric and lean-burn strategy. Results demonstrate that the lean-burn strategy achieves a 6% reduction in methanol fuel consumption compared with stoichiometric combustion, delivering superior fuel economy. In terms of regulated gaseous pollutants, both combustion strategies satisfy China-VI emission limits for CO and NO, while lean-burn combustion effectively lowers raw CO and NO emissions and reduces the purification pressure of aftertreatment systems. Non-methane Hydrocarbon emission under cold-start condition is identified as the primary compliance challenge, requiring a minimum aftertreatment conversion efficiency of 95%. Although lean-burn increases raw exhaust NMHC emission under hot-start condition, the post-catalyst emission could still meet the regulation limits. For particulate pollutants, lean-burn strategy realizes substantial reductions in both PM and PN emissions, which can meet emission standards without the corresponding aftertreatment system. In contrast, the stoichiometric combustion faces a risk of PN emission exceeding the regulation limit under cold-start conditions even with aftertreatment system. Additionally, lean-burn strategy optimizes greenhouse gas emission performance by cutting CO and CH₄ emissions. Regarding unregulated pollutants, lean-burn strategy increases raw exhaust unburned methanol and formaldehyde emissions, particularly under cold-start condition, but significantly inhibits NH₃ emission. This study quantitatively clarifies the performance trade-offs and adaptation advantages of lean-burn and stoichiometric strategy for heavy-duty methanol engines, providing fundamental data support and technical guidance for the low-carbon and low-pollution optimization of heavy-duty methanol vehicles. Full article

Agricultural carbon emissions represent a major source of greenhouse gases and play a critical role in achieving global climate mitigation and sustainable agricultural development targets. In China, the rapid transformation of agricultural production systems has led to substantial spatial heterogeneity in emission patterns and driving mechanisms of agricultural carbon emissions, while the underlying processes at the county scale remain insufficiently understood. This study investigated the spatiotemporal evolution and potential influencing factors of agricultural carbon emissions at the county level from 2000 to 2022 in Guangdong Province, China. First, agricultural carbon emissions were estimated based on a multi-source accounting framework covering land management, crop cultivation, animal production, and straw burning based on internationally recognized emission accounting methods and IPCC global warming potentials. Then, spatial clustering characteristics were analyzed using local spatial autocorrelation (LISA) to identify heterogeneous emission patterns. Finally, an interpretable machine learning framework combining Random Forest (RF) and SHapley Additive exPlanations (SHAP) was employed to quantify the nonlinear effects and relative contributions of multiple socioeconomic and agricultural drivers. The results showed that agricultural carbon emissions in Guangdong Province exhibited a fluctuating but overall decreasing trend, declining from 50.89 Mt CO₂-eq in 2000 to 39.24 Mt CO₂-eq in 2022, with an overall reduction of 22.9%. High-emission clusters were primarily concentrated in western and northern Guangdong, while low-emission areas were mainly located in the Pearl River Delta (PRD). The RF models demonstrated satisfactory predictive performance, with spatial cross-validated R² values ranging from 0.75 to 0.91 across different years. SHAP analysis suggested that ploughing area, fertilizer and pesticide usage, agricultural machinery power, and primary industry GDP were the dominant factors associated with agricultural carbon emissions, whereas urbanization consistently showed a negative association. Furthermore, these drivers exhibited pronounced nonlinear responses and distinct regional heterogeneity, particularly between the PRD and the western and northern parts of Guangdong Province. These findings suggested that agricultural carbon emissions are jointly influenced by agricultural production intensity, mechanization, and socioeconomic transition and can provide a scientific basis for developing region-specific low-carbon agricultural policies and promoting the sustainable transformation of agricultural systems. Full article

The environmental sustainability of farms can be improved by the adoption of sound manure management techniques, with anaerobic digestion (AD) being one of the most promising: AD offers the production of renewable fuel, biogas or biomethane, and prevents the emissions of odors and greenhouse gases. While anaerobic digestion (AD) is widely implemented for treating dairy, pig, and poultry manure, limited interest has been directed toward horse farms. A laboratory-scale experiment was performed to assess the biochemical methane potential of horse manure and straw-based horse litter. The test was conducted using a BioReactor Simulator system (six digesters, 2.0 L each) at 38 °C for 40 days, using inoculum from a 1 MWe biogas plant fed with dairy cow manure and silages. Horse manure presented total solids (TS) of 19.4% and volatile solids (VS) of 90.7% TS, while straw-based horse litter showed a TS of 49.8% and VS of 90.0% TS. Methane yields of 48.2 NL/kg, 237.6 NL/kgTS, and 262.1 NL/kgVS were obtained for horse manure, and 82.1 NL/kg, 164.9 NL/kgTS, and 183.2 NL/kgVS for the straw-based horse litter. These results are of practical interest for the management of large horse facilities or for the co-digestion of these feedstocks in existing AD plants. Full article

Climate and human activity shape cropland dynamics, while their cascading interactions remain an intricate black box blocking mechanistic understanding of land system shifts. Taking Jilin Province as a case, we developed an integrated framework combining OPGD (optimal parameter geographic detector), SEM (structural equation modeling) and GWR (geographically weighted regression) to quantify multi-scale cascading mechanisms of 13 environmental factors and cropland. Cropland conversion showed distinct spatial disparities: western plains saw mainly grassland reclamation, central urban plains experienced cropland occupation by construction, and eastern mountain areas had forest-to-cropland expansion. Over 2010–2019, cropland decreased by 1.39% (1257.7 ha) for construction, compensated by conversions from 4.99% grassland (4518.8 ha) and 3.01% forestland (2720.2 ha). Climate dominated cropland variations through indirect human-mediated pathways, with path coefficients of 0.664 for Climate → Human and 0.571 for Human → Cropland; climate exerted direct driving effects on grass–cropland transition in western ecologically fragile plains. Greenhouse gases, evapotranspiration, humidity, temperature and leaf area index controlled overall cropland variations. Central and western croplands were dominated by topography, whereas precipitation, population and GDP determined eastern cropland dynamics. This framework differentiated direct and indirect driving pathways of cropland evolution, guiding policy formulation for regional grain security. Full article

Global growth in electric mobility, portable electronics, and renewable energy storage has increased concerns about the environmental and economic impacts of managing end-of-life lithium-ion and lead-acid batteries. Although these batteries support the transition to renewable energy, their disposal presents significant challenges. Recycling has emerged as a key strategy to reduce resource depletion, limit pollution, and recover valuable materials. This study systematically reviewed and quantitatively synthesised the literature published between 2000 and 2025, assessing the environmental impacts of battery recycling programs. The review followed PRISMA guidelines to ensure a transparent and rigorous study selection process. Data from peer-reviewed articles, industry reports, and policy documents were analysed, focusing on indicators such as greenhouse gas emissions, energy use, material recovery efficiency, and economic returns. Statistical methods, including Hedges’ g, heterogeneity testing, and sensitivity analysis within a random-effects model, were applied to account for variability across technologies and battery types. The results show that recycling generally lowers emissions and improves resource recovery compared to virgin material extraction, though performance varies. Lead-acid recycling demonstrates stronger environmental benefits due to mature technologies and established systems, while lithium-ion recycling shows positive but lower gains, limited by higher energy demands and less-developed processes. Overall, recycling is essential for reducing environmental impacts and supporting a circular economy, though lithium-ion systems require further technological and policy advancements. These findings can be used by governments to strengthen regulatory frameworks to support recycling industries and invest in advanced lithium-ion recycling technologies to improve efficiency. Despite the existing limitations, the benefits of recycling outweigh the drawbacks, making it a necessary strategy for sustainable battery waste management. Full article

Emissions Trading Systems (ETSs) have become some of the most widely adopted market-based instruments for reducing greenhouse gas emissions. However, their environmental performance varies considerably across jurisdictions, suggesting that carbon pricing mechanisms operate under heterogeneous structural and institutional conditions. This study analyzes the factors influencing ${\mathrm{CO}}_2$ emissions performance in economies implementing ETSs. Grounded in Ecological Modernization Theory and Institutional Theory, the research combines a k-prototypes clustering model and an Artificial Neural Network (ANN). First, 58 ETSs across 53 countries were classified into four archetypes according to their institutional maturity, regulatory scope, and structural characteristics. Second, an ANN model was estimated using annual data from 2000–2021 to examine the influence of environmental, socio-demographic, economic, and development-related variables on ${\mathrm{CO}}_2$ emissions per capita. The results show that ETS performance depends not only on economic development levels but also on broader structural and institutional factors. Renewable energy consumption and renewable energy production emerge as the most influential drivers of lower ${\mathrm{CO}}_2$ emissions, particularly in developing economies. Conversely, urbanization, export-oriented activities, and governance weaknesses are associated with greater emissions pressures. Corruption also exhibits a stronger negative effect on environmental performance in emerging economies. Overall, the findings suggest that ETSs should not be viewed as standalone climate instruments; their effectiveness depends on complementary policies that promote renewable energy deployment, strengthen institutional quality, and address the pressures associated with trade and urbanization. Full article

Aquaculture has rapidly expanded, surpassing capture fisheries and playing a vital role in global food security. However, this growth raises environmental concerns, especially regarding nitrogen waste accumulation in recirculating aquaculture systems (RASs). Nitrogen compounds from uneaten feed and fish excreta, mainly ammonia (NH₃) and nitrite (NO₂⁻), lead to water pollution, eutrophication, and greenhouse gas emissions. This study describes the setup and the efficiency of a new photo-electrocatalytic (PEC) system in reducing nitrogen waste in a high-density RAS for rainbow trout (30 kg/m³). The PEC system, an evolution of a pure photocatalytic system, was integrated in the units of the RAS and tested for the first time in field conditions, combining photocatalysis and electrochemical oxidation to convert toxic nitrogen species (NH₃) into less harmful nitrogen forms (NO₃⁻ and N₂), aiming to mitigate both water and atmospheric pollution. Over a 4-week period, water nitrogen compounds, ammonia and greenhouse gases (carbon dioxide, nitrous oxide and methane) emitted by water were continuously monitored in two groups of three tanks (PEC vs. control). Each tank was equipped as an independent RAS unit. PEC treatment led to significantly lower NH₃ concentrations (0.96 ± 0.2 mg/L vs. 1.78 ± 0.2 mg/L, p < 0.01), lower NO₂⁻ levels and higher NO₃⁻ levels (61.77 ± 2.14 mg/L vs. 53.10 ± 2.14 mg/L, p < 0.01) in water, indicating efficient nitrogen oxidation. Gaseous emissions were also reduced: NH₃ (1.49 vs. 2.64 mg/m²/day, p < 0.05) and N₂O (1.44 vs. 2.88 mg/m²/day, p < 0.05). These results support PEC technology as a promising solution for improving nitrogen management in intensive aquaculture. Although challenges remain in optimizing energy use and scalability, PEC offers a valuable strategy for reducing environmental impact while sustaining productivity in the aquaculture industry. Full article

This paper presents the design, development, and large-scale deployment of a vehicular IoT-based methane sensing system for urban environmental monitoring. The proposed solution integrates a low-cost metal oxide semiconductor (MOS) methane sensor with a dual chamber gas sampling mechanism, embedded processing, and wireless communication via 4G/5G networks using a smartphone as a gateway. Methane concentration data are collected from sensors installed in moving vehicles, georeferenced in real time using GNSS, and transmitted to a cloud-based platform for storage and analysis. Field experiments were conducted in the metropolitan region of São Paulo, Brazil, using 16 instrumented vehicles over a 20-month period, covering approximately 192,274 km and generating more than 48 million measurements. The results reveal spatially consistent methane concentration patterns and identify urban areas with elevated levels exceeding global background concentrations. A comparative analysis with a commercial infrared-based mobile methane monitoring system showed consistent agreement in the identification of spatial methane concentration patterns and potential emission hotspots. These results demonstrate the effectiveness of the proposed system for scalable urban methane monitoring. Full article

The transport sector contributes significantly to greenhouse gases and airborne pollutants. This study focuses on the co-benefits related to decreases in air pollutants and CO₂ emissions under various mitigation scenarios. The associated mitigations in PM_2.5 concentrations are predicted by establishing a random forest (RF) model and the health benefits are evaluated with the global exposure mortality model (GEMM). Environmental tax values and carbon trading prices are integrated alongside traditional elasticity coefficients and coordinate-based approaches to transform reductions into economic advantages. The results indicate that in the most favorable scenario (ELC), CO₂ emissions are expected to peak in 2032 with a reduction of 51.71%; this is supported by the marginal CO₂ emission curve, which intersects the zero axis around that same year, while the air pollution equivalents (APeq) are projected to decline by 25.65% in 2050. The efficiency of synergistic reductions between air pollutants and CO₂ ranks as SO₂ > NO_X > CO > HC > PM_2.5 > PM₁₀, and the elasticity coefficients for all pollutants are gradually aligning toward 1, suggesting that stricter mitigation efforts will enhance co-benefits. Furthermore, the economic benefits attributable to CO₂ reduction are anticipated to be 10.81 billion CNY by 2050, and 17,297 premature deaths associated with PM_2.5 exposure could be prevented. The findings in this study could provide essential insights for the co-management of CO₂ and air pollutants from road mobile sources. Full article

While remote sensing has been widely used to estimate vegetation biochemical and structural properties, relatively little work has systematically and experimentally linked vegetative fuel spectral reflectance to independently measured fuel combustibility, free-spreading fire behaviour, and fire emissions. This limits the development and validation of remote sensing products for operational wildland fire applications. We present a pilot-study evaluation of an experimental method that integrates imaging spectroscopy with free-spreading fires in a combustion wind tunnel to investigate relationships between wildland fuel spectral reflectance and combustibility, fire behaviour, and fire emissions. The pilot study used three common Australian fuels at two combustibility levels. Pre- and post-burn imaging spectroscopy observations (400–2500 nm) were collected during 26 experiments, alongside measurements of fuel biochemistry, calorimetry, moisture, rate of spread, combustion efficiency, and gaseous and particulate emissions. Statistically significant differences between fuel type and combustibility were found in fuel moisture, rate of spread, and emissions, with corresponding differences evident in the spectral signatures. Partial least squares regression (PLSR) indicated that pre-fire spectral information was informative for predicting several fire behaviour and emissions metrics. These results demonstrate the feasibility of the proposed methodology and provide a foundation for extending it to a wider range of wildland fuels. Data generated using this methodology have the potential to improve interpretation of remote sensing datasets and inform the design of future satellite instruments, with potential applications in assessing fuel condition, predicting fire behaviour, and estimating wildland fire emissions. Full article