Search Results (1,752)

Organic waste causes severe pollution, while agriculture lacks quality fertilizers. Solid-state fermentation solves both issues. Nevertheless, traditional methods are slow and lead to nitrogen loss. They also emit greenhouse gases and yield uneven products. This fails to reach modern low-carbon standards. We urgently need efficient solid-state fermentation systems. Therefore, this review summarizes recent advances in parameter optimization and cutting-edge innovations. Firstly, key solid-state fermentation operational parameters, such as carbon-to-nitrogen ratio, aeration frequency, temperature, humidity and pH, are analyzed. The optimization of these parameters facilitates nitrogen retention and mitigates pollutant emissions. Secondly, emerging enhancement strategies are discussed. Elaboration on the electron-shuttle effect of modified biochar and advances in synthetic microbial consortia is provided. For process coupling, the mechanisms of hydrothermal carbonization (HTC) combined with solid-state fermentation are explored. Bioelectrochemically assisted solid-state fermentation (MCFT/BFC) based on Direct Inter-Species Electron Transfer (DIET) is also examined. Furthermore, feasible mitigation approaches for pollutants including greenhouse gases and antibiotic resistance genes (ARGs) are summarized. Subsequently, the applications of mathematical models, the Internet of Things (IoT), and artificial intelligence in solid-state fermentation are introduced. Finally, current challenges in large-scale application and risk management are analyzed. Future prospects involving multi-omics, life cycle assessment (LCA), and functional customization are discussed. Low-carbon solutions for high-value waste utilization are provided in this review. Full article

Accurate estimation of greenhouse gas (GHG) emissions from semiconductor etching processes requires process-specific information on the unreacted fraction (1−Ui) of process gases and the by-product generation rate (Bi). However, the default emission factors provided in the 2019 IPCC Guidelines have limited ability to reflect variations in actual process conditions, such as wafer size and plasma intensity. In this study, the 1−Ui and Bi values of SF6 and NF3 were measured using a semiconductor etching testbed designed to simulate representative Korean manufacturing conditions. Experiments were conducted using 200 mm and 300 mm wafers under three plasma intensity conditions (bias voltages of 150, 200, and 250 V). The measured values were compared with the default emission factors provided in the 2019 IPCC Guidelines. The results showed that the 1−Ui values of both SF6 and NF3 varied with wafer size and plasma intensity, and generally decreased as plasma intensity increased. In contrast, Bi exhibited different response patterns depending on the by-product species, with no consistent trend observed across process conditions. Comparison with the IPCC default emission factors revealed noticeable differences according to process gas, wafer size, and by-product species, indicating that generalized default factors may either overestimate or underestimate actual emissions under certain operating conditions. These findings provide measurement-based process-level data that can support the development of country-specific (Tier 2) and facility-specific (Tier 3) emission factors and contribute to improving the accuracy of greenhouse gas emission estimation in semiconductor etching processes. Full article

Anthropogenic greenhouse gases (GHGs) and emissions from maritime transport represent a significant challenge for atmospheric monitoring and control. The Istanbul Strait, characterized by its narrow, winding geography and high traffic density, presents a unique chokepoint where these emissions directly impact local air quality. This study proposes a gas-focused integrated framework that combines Sentinel-5 Precursor (Sentinel-5P) TROPOspheric Monitoring Instrument (TROPOMI) satellite observations with Automatic Identification System (AIS) data to analyze atmospheric trace pollutant time series in the Istanbul Strait during 2025. A bottom-up emission methodology based on the IMO 4th GHG Study was employed, yielding annual gaseous pollutant totals of 213,678 tons of carbon dioxide (CO₂), 5970 tons of nitrogen oxides (NO_x), and 686 tons of sulfur oxides (SO_x). Time-series and cross-correlation analyses demonstrated a quantifiable relationship between AIS-derived NO_x estimates and TROPOMI NO₂ tropospheric column densities (r = 0.76, p < 0.05, n = 12), validating the use of satellite sensors for marine atmospheric monitoring. A decision support system (DSS) proof of concept (PoC) was developed to evaluate emission control scenarios through speed optimization. The results indicate that implementing a 10% speed reduction strategy could reduce CO₂ emissions by 18% (38,462 tons) and generate net economic savings of EUR 3.07 million under the European Union Emissions Trading System (EU ETS) carbon pricing framework. Furthermore, a scenario with a 20% speed reduction resulted in a 35% decrease in CO₂ emissions. The findings underscore the potential of integrating satellite-based gas remote sensing with AIS data, thereby facilitating real-time atmospheric monitoring and strengthening emission control policy enforcement in maritime chokepoints. Full article

Inland waterbodies are a significant emitter of greenhouse gases, especially methane. They contribute 15.2% of all anthropogenic methane emissions. Major uncertainties are still present in emissions estimates for these systems; as a result, more in situ measurements are required to constrain them, especially when ebullition, a direct release of methane, is present. The Monitub Automated Floating Chamber (AFC) was developed to address existing challenges in floating chamber deployments, a common emissions measurement method, through the use of a custom floating chamber, datalogger, and generic calibration of the TGS2611-E00 sensor. This system is able to perform long-term, real-time monitoring of methane emissions from waterbodies at a low cost. This allows for the correlation of environmental drivers to further constrain uncertainties related to emissions, due to its high temporal frequency, and help to answer questions about the spatial heterogeneity of emissions, as more systems can be deployed at a lower cost. The Monitub AFC was deployed to an urban lake for testing, showing its ability to differentiate between diffusion and ebullition, and its capabilities as a long-term monitoring system. Full article

The production of hot mix asphalt (HMA) is energy-intensive, resulting in carbon dioxide (CO₂) and greenhouse gas (GHG) emissions. The primary energy source (accounting for over 97%) and emissions source is the rotary drum employed for the drying and heating of the aggregates. Quantifying the CO₂ emissions associated with combustion is of crucial importance in order to facilitate a more profound comprehension of the environmental impacts of HMA production. The objectives of this study are to develop a methodological framework for the quantification of combustion-related carbon dioxide emissions in the context of asphalt production. The proposed framework investigates three complementary approaches: (i) an energy-balance-based thermal energy (TE) model, (ii) recordings of fuel consumption and (iii) direct measurement of exhaust-gas composition. By applying these methods in parallel and cross-comparing their results batch by batch, the framework enables reliable verification of actual CO₂ emissions from the module A3—production stage of asphalt manufacturing. In this stage, the predominant source of greenhouse gases is fuel combustion during aggregate drying and heating. A comprehensive set of data was collected from two HMA batch plants, each operating under distinct conditions. The parameters considered included fuel type, asphalt mixture type, asphalt production time, aggregate moisture content, mixing temperature, and production rate. The TE model demonstrated a robust linear correlation with measured energy consumption (R² = 0.97), and fuel-based CO₂ estimates exhibited minimal discrepancy compared to direct exhaust-gas measurements on average (mean difference 1.0%; t-test p = 0.674). However, systematic discrepancies were observed between the two plants (with overestimation of up to 20% at one plant (AP1) and underestimation of up to 12% at the other (AP2)). This demonstrates that energy-based CO₂ estimation methods require plant-specific calibration against direct measurement before they can be reliably applied in life cycle assessment (LCA) and environmental product declaration (EPD) practice. Measured CO₂ emission intensities ranged from 17.39 to 21.76 kg/t at AP1 and from 16.05 to 18.44 kg/t at AP2; the casing-losses factor of the TE model was calibrated to CL = 23% for the studied diesel-fired plants (mean deviation +0.4% from measured energy); and aggregate moisture content explained 74% of the variance in measured energy consumption (R² = 0.743). Full article

Small lakes are widespread, yet their biogeochemistry, particularly regarding greenhouse gases, remains insufficiently studied. This article presents the findings from an investigation of six small lakes in the Southern European part of Russia, conducted from September to October 2024. The primary aim was to examine the coupled distribution of methane (CH₄) and sulfide sulfur (a key metabolite of H₂S) in the lake sediments, in relation to geochemical parameters such as pH, Eh, sediment density, moisture, and the contents of sulfate ions (SO₄²⁻), organic matter, and granulometric composition. The studied sediment layers, reaching depths of up to 110 cm, consist primarily of silty clay. The lakes studied represent both freshwater (0.2–0.7 g/L) and brackish (1.3–24.2 g/L) systems. During the study period, the water column exhibited temperatures of 10.4–22.1 °C, pH values of 7.36–8.53, and dissolved O₂ concentrations ranging from 3.16 mg/L (34% saturation) to 11.79 mg/L (125% saturation). Methane concentrations in the water varied widely, from 1.6 µL/L to 37,380 µL/L. The lowest values were found in the highly mineralized Lake Bolshoy Tambukan (1.6–2.0 µL/L), while exceptionally high concentrations were detected in the bottom waters of the thermally stratified freshwater Lake Staroe. In the shallow, productive freshwater lakes, a significant portion of the organic matter undergoes limited mineralization in the water column and settles to the sediments as partially decomposed remains of sand- and coarse-silt-sized organisms. The subsequent degradation of this labile organic matter reduces bottom-water oxygen, triggering intense anaerobic processes in the upper sediment layer. In these freshwater sediments, where sulfate concentrations are relatively low, sulfate reduction is typically suppressed. Combined with an abundance of labile substrates, this condition fosters intensive methanogenesis, resulting in maximum CH₄ concentrations (33–179 µg/g). Under stable thermal stratification, such high CH₄ concentrations can also accumulate in the bottom water (e.g., up to 37. 4 mL/L in Lake Staroe), posing a risk of significant pulse emissions during autumn mixing. Conversely, the brackish Lake Bolshoy Tambukan exemplifies the crucial role of sulfate reduction, which is stimulated by sulfate-dependent anaerobic oxidation of CH₄. This process acts as a powerful natural biogeochemical barrier that curtails the emission of a major greenhouse gas. The sediments of this lake exhibited minimal CH₄ content (0.14–0.57 µg/g) alongside maximal sulfide sulfur concentrations (1.06–8.57 mg/g). Overall, this theoretical and experimental analysis demonstrates that sulfate reduction is a key determinant of redox potential, acid–base conditions, and the vertical distribution of CH₄ in the anaerobic sediments of small lakes in Southern Russia. Given the projected salinization of lakes in steppe and arid landscapes under climate change, a reduction in CH₄ emissions to the atmosphere is likely due to the enhanced sulfate-dependent anaerobic CH₄ oxidation associated with sulfate reduction in the sediments. Full article

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

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

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