Search Results (235)

Cooking-related emissions represent a major contributor to indoor air pollution in residential kitchens, producing complex mixtures of volatile organic compounds (VOCs), odor-causing gases, oil vapors, particulate matter (PM_2.5), and combustion-related pollutants (CO and NO_x). In this study, a controlled ozone-assisted oxidation approach was integrated into a recirculating (ductless) domestic kitchen hood equipped with a confined reaction chamber and experimentally evaluated under closed-loop operating conditions where treated air was returned to the indoor environment after post-treatment. A multivariate Response Surface Methodology (RSM) framework based on the Box–Behnken design was employed to quantify and optimize the coupled effects of temperature (20–30 °C), relative humidity (40–60%), ozone dosage (1–3 ppm within the confined reaction zone), and airflow rate (150–250 m³/h) on multi-pollutant removal performance. The results demonstrate that ozone assistance substantially improves the abatement of oxidation-sensitive pollutants, particularly VOCs and odor, while airflow rate strongly governs transport-dominated pollutants such as PM_2.5 and oil vapors. In contrast, CO and NO_x exhibited limited improvement, indicating that ozone-assisted oxidation alone is insufficient for comprehensive control of combustion-related gases under short-residence-time recirculating hood conditions. The main contribution of this work is the implementation of a demand-driven ozone management strategy, supported by dual ozone sensing for reaction-zone control and outlet safety verification, where ozone generation is activated only in the presence of reactive gaseous pollutants and automatically reduced or terminated once pollutant concentrations fall below predefined thresholds, minimizing unnecessary oxidant release. Residual ozone downstream of the reaction stage was continuously monitored to prevent excess ozone return to the occupied zone. Overall, the proposed closed-loop, feedback-controlled ozone-assisted recirculating range hood concept demonstrated device-level reductions in measured VOC/odor signals under controlled conditions, while also highlighting the need for complementary post-treatment components for particle- and combustion-related pollutants. However, the potential formation of secondary oxidation byproducts was not characterized in this study, and therefore the results should be interpreted with respect to device-level pollutant removal rather than comprehensive indoor air quality improvement. Full article

Accurate and physiologically relevant in vitro models are needed to predict nutrient digestibility and hindgut fermentation in pigs, as conventional in vivo trials are resource-intensive and raise animal welfare concerns. This study evaluated and compared the predictive performance of three in vitro digestion approaches—shaking (S), dialysis (D), and a combined shaking plus dialysis (SD) method—for estimating in vivo apparent total tract digestibility (ATTD) and fermentation characteristics across weaning, growing, and finishing pigs. Commercial diets were subjected to simulated gastric and small-intestinal digestion using S, D, or SD, followed by fecal inoculation to model hindgut fermentation for 12 and 48 h. During the gastrointestinal phase, crude protein digestibility was highest with D (>75%), intermediate with SD, and lowest with S (50–60%), indicating that product removal by dialysis mitigated enzyme inhibition from metabolite accumulation. After 48 h of fermentation, all methods showed strong linear correlations with in vivo ATTD (r > 0.93), but only D achieved high absolute agreement (Lin’s CCC > 0.95 for dry matter and crude protein). Moreover, D and SD at 48 h closely reflected in vivo fecal profiles of skatole, indole, and microbial enzyme activities, with D at 12 h showing an especially strong correlation for protease (r = 0.98). While D provided the most precise predictions of absolute values, the SD method offered an optimal balance between physiological relevance and operational efficiency, supporting its use as a robust, high-throughput platform for porcine feed evaluation and fecal nitrogenous odorant prediction. Full article

Wood products made from Manchurian ash are widely used as furniture and decorations, particularly waterborne-coated Manchurian ash (Fraxinus mandshurica Rupr.). However, while waterborne coatings offer less air pollution, their odor emission dynamics under different environmental conditions remain poorly understood. To address these gaps, this study systematically analyzed 28-day volatile organic compounds (VOCs) and very volatile organic compounds (VVOCs) release profiles under controlled temperature, relative humidity, and air exchange rate-to-loading factor ratios (AER/Ls), using thermal desorption–gas chromatography–mass spectrometry/olfactometry (TD-GC-MS/O). Eighteen key odor-active compounds (OACs) were identified, comprising 11 wood-derived and seven coating components, exhibiting eight odor attributes: disinfectant-like, aromatic, tobacco-like, unpleasant, vinegar-like, flowery, sweety, and alcohol-like. The dominant attributes were disinfectant-like and aromatic. The results showed that temperature accelerated release rates and shortened equilibrium time, while increasing concentrations and odor intensity. Relative humidity prolonged equilibrium, with stage-dependent concentration effects, yet consistent odor intensity rise. Higher AER/L reduced equilibrium time and concentrations through dilution-dominated dynamics despite accelerated release rates from increased pressure differentials. These findings indicated that synergistic high-temperature (40 °C)/high-humidity (60% RH) conditions accelerate odorant emission, while optimized ventilation (AER/L 0.5 m³·m⁻²·h⁻¹) ensures effective mitigation. The findings will inform strategies to reduce odor impact and advance eco-efficient finishing technologies for wood products. Full article

The circular economy paradigm offers a critical framework for addressing agricultural sustainability challenges, yet limited empirical evidence exists regarding how ecological innovations create simultaneous value across environmental, economic, and social dimensions. This study examines stakeholder value creation mechanisms through a 200-day longitudinal case study (March–October 2025) of Fuyang, China’s ecological transformation utilizing exciton-mineral technology for livestock waste valorization. The mixed-methods approach combined environmental monitoring, economic performance data, social surveys (n = 4523), and governance document analysis across operations processing 3000–4500 tons of poultry waste monthly. Results indicated significant environmental improvements including 99.4% odor reduction (NH₃: 999 → 5.6 ppm), 387% soil biodiversity increase, and 42% methane emission reduction. Economic benefits included +20% farmer net profit and +57% egg price premium. Social outcomes encompassed 96.2% resident satisfaction and complete elimination of odor complaints. Governance innovation established China’s first permit-free bio-mineral production system. The findings suggest that ecological innovations embedding circularity as automatic outcomes, rather than requiring behavioral coordination, can accelerate circular agriculture transitions beyond policy mandates, pointing to a potentially scalable model for sustainable production–consumption systems in developing economies. Full article

Indoor environmental quality directly affects public health and quality of life, among which odor pollution is one of the primary drivers of indoor environmental complaints. Traditional research and management approaches, which rely predominantly on mass concentrations of individual chemical compounds, are fundamentally inadequate for addressing the inherent sensory complexity, dynamic evolution, and subjective perception of indoor odors. Through a systematic literature review, this paper for the first time establishes an integrated research framework for indoor odor pollution across the whole-life-cycle management of the built environment, structured around “source–evolution–evaluation–control”. This framework systematically analyzes emission characteristics of building-related pollution sources, revealing the profound impact of indoor dynamic chemical and biological transformation processes on odor properties. Sensory analysis, instrumental measurements, and intelligent sensing approaches are critically compared in terms of their underlying principles and application boundaries. From an engineering perspective, the effectiveness and limitations of source prevention, ventilation dilution, and terminal purification strategies are comprehensively evaluated. The analysis demonstrates that effective indoor odor management must transcend passive and fragmented mitigation practices, and that its future development depends on the deep integration of environmental chemistry, sensory science, materials science, and artificial intelligence. Finally, this review proposes that by constructing regulation systems based on real-time sensing, digital twins, and intelligent decision-making, indoor odor management can fundamentally shift from reactive complaint-driven responses to proactive health-oriented protection. This paradigm transformation provides a systematic theoretical foundation and a technological roadmap for achieving healthy, comfortable, and sustainable building environments. Full article

Brief treatment of a bottled young dry red wine with low-intensity natural emissions in the mid-infrared and far-infrared/near-microwave regions of the electromagnetic spectrum resulted in moderate changes in the concentrations of certain odorants in the wine headspace (vapor), as shown by headspace–solid-phase microextraction–gas chromatography/mass spectrometry (HS-SPME-GC/MS). The headspace levels of certain long-chain ethyl carboxylate esters and methyl salicylate were somewhat enhanced, whereas those of certain aromatic monohydric alcohols, a succinate ester, and oak lactone were somewhat depleted. A tentative explanation of these results is offered whereby waveform treatment results in general re-organization of non-covalent associations of both odorant (volatile) and non-volatile components in wine, leading to the preferential extra release of certain odorants into the headspace (vapor phase) and preferential increased trapping of certain other odorants in wine (liquid phase). Full article

This paper discusses the total replacement of egg white (EW) with faba bean protein concentrate (FPC) in a marshmallow formulation. The physico-chemical and techno-functional characterizations of the ingredients revealed that FPC, with a protein content of 68%, exhibited an interesting foaming capacity (200%) compared to EW, which had comparable foaming stability. The physico-chemical properties of the final products indicated that the FPC marshmallow (FPCM) had a higher density (0.519 g/mL), lower moisture (17.337%), and a water activity within the recommended range for this type of product. The FPCM had the highest hardness and elasticity values but the lowest cohesiveness and adhesiveness. Scanning electron microscopy showed that the FPCM structure is similar to that of the EW marshmallow (EWM). In front-face fluorescence spectroscopy measurements, the FPCM exhibited higher emission intensity for tryptophan with a maximum at 382 nm and vitamin A with a maximum located around 338 nm. FTIR analysis presented higher peaks at 850, 918, and 1034 cm⁻¹ for the EWM compared to the FPCM. In a hedonic evaluation, the majority of descriptors (hardness, odor, and general acceptability) showed similar scores for both formulations. All results demonstrated the success of the total substitution of egg white by FPC in the marshmallow formulation. Full article

Biochar has emerged as a promising material for carbon storage, exhibiting properties analogous to those of activated carbon. Biochar has a particularly high absorbance due to its high porosity, surface area, and functional groups, although these parameters depend on the feedstock and pyrolysis conditions. The sorbent properties of biochar make it suitable for many applications, including the biological treatment of organic waste. In the context of composting, biochar addition seems to positively impact the process performance and the final compost characteristics. Furthermore, it reduces greenhouse gas and odor emissions, which is a crucial step in preventing the full implementation of composting. The objective of this review is to provide a comprehensive description of the effects of biochar on composting emissions and the reported mechanisms, highlighting the limitations of current research. In summary, the use of biochar in composting is still in its early stages and requires further research and consensus on fundamental issues, such as the optimal biochar dosage and mitigation mechanisms. Moreover, there is a significant lack of full-scale implementation. Accordingly, future work should focus on overcoming these critical challenges to take a step forward towards a consistent and complete picture of the environmental impacts and a rigorous economic analysis of the use of biochar in composting. Full article

Complex odor emissions from wastewater treatment plants consist of multiple volatile compounds that exhibit heterogeneous temporal dynamics and low linear correlations, making accurate prediction and interpretation difficult when analyzed on a single-compound basis. This study investigates whether clustering can serve not only as an exploratory tool but as an essential preprocessing step to enhance machine-learning performance in multi-odor prediction systems. A total of 22 designated odorants were continuously monitored, and their pairwise dependencies were evaluated using Pearson correlation and mutual information. Data-driven clustering was performed through K-means, hierarchical linkage, and principal-component–based latent grouping, and the resulting structures were quantitatively compared with functional-group-based chemical classifications using the consistency ratio and Jaccard similarity index. Cluster validity was further examined using the Silhouette Coefficient, Davies–Bouldin Index, and Calinski–Harabasz Index. The predictive contribution of clustering was verified by training XGBoost regression models on both raw and cluster-structured datasets. The clustered dataset yielded higher predictive accuracy, with increased R² and reduced MAE and RMSE across most odorants. SHAP analysis further confirmed that clustering improved model interpretability by stabilizing feature contributions and reducing noise-driven importance shifts. The findings demonstrate that clustering is not a supplementary diagnostic tool, but a prerequisite for building reliable, high-performance machine-learning models in complex odor systems. This integrative framework offers a methodological foundation for multi-odor forecasting, source tracking, and next-generation odor management platforms. Full article

The amount of municipal solid waste (MSW) generated worldwide is constantly growing. In many countries, anaerobic digestion (AD) is the recommended process for converting organic waste, playing a crucial role in the transition to a circular economy. Capturing and using biogas helps to reduce greenhouse gas emissions. This paper summarizes the results of comprehensive studies conducted at three municipal waste biogas plants (MWBPs) located in Poland. These studies include measurements related to concentrations of odor (c_od) and odorants (C) as well as microclimate parameters. We statistically analyzed the research obtained. However, the microclimatic parameters were not used in a final PCA model and were only used in exploratory correlation. Principal component analysis (PCA) is one of the methods of statistical factor analysis, which allows for the organization of a large set of data from three objects from the annual study. The use of PCA allowed us to determine which substance at a specific biogas plant is primarily responsible for odor nuisance and to estimate the percentage of variability contained in the first two principal components. The obtained results clearly indicate the influence of the technological regime and the type of fermentation feed on the determining effect of a specific odorant. In connection with the vision of creating new MWBPs that are consistent with circular economy assumptions, it seems advisable to extend the conducted analysis to include an immission study outside the plant boundaries. This study could play a crucial role in public consultations and serve as a tool for minimizing odor nuisance. Full article

This study aimed to investigate the effects of pineapple pomace as a functional feed additive on growth performance, fecal microbiota composition, short-chain fatty acids (SCFAs), and odor substance emissions in weaned piglets. The experiment utilized 90 weaned three-way crossbred piglets (Duroc–Yorkshire–Guoshou Black Pig) at 28 days of age, randomly divided into three groups of 10 pigs each: the control group (CON, basal diet), the fish meal group (FM, basal diet + 2% imported fish meal), and the pineapple pomace group (PPC, basal diet + 2% pineapple pomace compound). The results indicated the PPC group exhibited significantly higher average daily gain (ADG) (p < 0.05) and significantly lower feed conversion ratio (FCR) (p < 0.05) than the CON group. 16S rRNA sequencing analysis revealed that the PPC group significantly increased fecal microbiota species richness and diversity (p < 0.01) while enriching beneficial bacteria including Lactobacillus, Bifidobacterium, and butyrate-producing bacteria such as Blautia. Concurrently, acetic acid and butyric acid levels in feces were significantly elevated in the PPC group (p < 0.05), with butyric acid production markedly higher than in the FM group (p < 0.05). However, no significant differences were observed in the levels of branched-chain fatty acids (BCFAs), such as isobutyric acid and isovaleric acid (p < 0.05). Moreover, PPC supplementation led to a significant decrease in fecal levels of indole and 3-methylindole (skatole) (p < 0.05). In summary, dietary inclusion of 2% pineapple pomace improves growth performance and intestinal health in weaned piglets by modulating the fecal microbiota, promoting beneficial SCFA production, and inhibiting protein putrefaction. These findings support PPC as an effective and sustainable alternative to fish meal, contributing to the development of environmentally friendly feeding strategies in pig production. Full article

Volatile organosulfur compounds (VSCs) play significant roles in atmospheric chemistry and malodorous pollution. Accurate measurement of VSCs is challenging due to their high reactivity and adsorption tendencies, which are strongly influenced by sampling materials. This study comprehensively evaluates the performance of six types of sampling bags and passivated canisters for measuring nine VSCs. The results indicate that passivated canisters provide stable storage for all target VSCs for up to 7 days under dry conditions. Among the bags, polyvinyl fluoride (PVF) bags exhibited the lowest blank levels and preserved most VSCs (except disulfides) stably for 8 h. Field comparisons in a power battery recycling plant showed good agreement between PVF bag and canister measurements under dry conditions. However, in high-humidity stack gases, canisters showed severe losses of methanethiol and ethanethiol, likely due to humidity-driven conversion on metal surfaces, underscoring the necessity of drying humid-air samples. The application of these methods revealed significant VSCs emissions and distinct compositional profiles from power battery recycling processes, particularly pyrolysis drying, lithium leaching, and nickel–cobalt leaching processes, with concentrations of total VSCs reaching up to 1046.86 ppb. This work provides crucial guidance for selecting appropriate sampling methods for reliable VSCs measurement and offers the first emissions characteristics of VSCs from the power battery recycling industry, supporting future environmental monitoring and pollution control. Full article

Artificial Intelligence (AI) is widely recognized as a force that will fundamentally transform traditional chicken farming models. It can reduce labor costs while ensuring welfare and at the same time increase output and quality. However, the breadth of AI’s contribution to chicken farming has not been systematically quantified on a large scale; few people know how far current AI has actually progressed or how it will improve chicken farming to enhance the sector’s sustainability. Therefore, taking “AI + sustainable chicken farming” as the theme, this study retrieved 254 research papers for a comprehensive descriptive analysis from the Web of Science (May 2003 to March 2025) and analyzed AI’s contribution to the sustainable in recent years. Results show that: In the welfare dimension, AI primarily targets disease surveillance, behavior monitoring, stress detection, and health scoring, enabling earlier, less-invasive interventions and more stable, longer productive lifespans. In economic dimension, tools such as automated counting, vision-based weighing, and precision feeding improve labor productivity and feed use while enhancing product quality. In the environmental dimension, AI supports odor prediction, ventilation monitoring, and control strategies that lower emissions and energy use, reducing farms’ environmental footprint. However, large-scale adoption remains constrained by the lack of open and interoperable model and data standards, the compute and reliability burden of continuous multi-sensor monitoring, the gap between AI-based detection and fully automated control, and economic hurdles such as high upfront costs, unclear long-term returns, and limited farmer acceptance, particularly in resource-constrained settings. Environmental applications are also underrepresented because research has been overly vision-centric while audio and IoT sensing receive less attention. Looking ahead, AI development should prioritize solutions that are low cost, robust, animal friendly, and transparent in their benefits so that return on investment is visible in practice, supported by open benchmarks and standards, edge-first deployment, and staged cost–benefit pilots. Technically, integrating video, audio, and environmental sensors into a perception–cognition–action loop and updating policies through online learning can enable full-process adaptive management that improves welfare, enhances resource efficiency, reduces emissions, and increases adoption across diverse production contexts. Full article

The persistent issue of odor nuisance poses significant challenges to the sustainable development of livestock farming. While previous studies have primarily focused on individual gas concentrations, a comprehensive understanding of overall odor impact based on human perception remains limited. This study introduces a novel perspective by employing the odor activity value (OAV)—calculated from the ratio of gas concentration to its olfactory threshold—to evaluate the actual odor contribution of various compounds. Through a meta-analysis of data from 123 papers, we systematically assessed odor emission characteristics and mitigation strategies across different manure management stages. The results indicated that ammonia (NH₃) (with maximum concentration of 8056 ppm) and hydrogen sulfide (H₂S) (with maximum concentration of 20,057 ppm) were the most concentrated odor components in the whole manure management links. However, considering the olfactory threshold, trimethylamine (TMA) (with OAVmax 380800), H₂S (with OAVmax 48919512), butyric acid (with OAVmax 801684), and aldehydes (with OAVmax 11707) played major odor-causing roles. Notably, biological methods (83%), covering (77%), and additives (39%) were the most efficient odor mitigation strategies in the barn, manure storage, and manure treatment link, respectively. Therefore, employing the OAV-based approach is crucial for identifying priority pollutants and developing targeted control strategies across different livestock species and management stages, ultimately guiding more effective odor mitigation and healthier cohabitation. Full article

The present study provided an exhaustive examination of VOC emissions originating from 13 different raw materials susceptible to being used in the sampling of the human volatilome and encompassing both polymeric and non-polymeric compositions. To achieve this aim, thermodesorption coupled with comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (TD-GC×GC/ToFMS) was employed. For each material, we report the total number of detected peaks, total volatile organic compound (TVOC) concentration, distribution of VOC emissions across different chemical families, minimum and maximum individual concentrations, as well as hypotheses regarding the origins of some specific VOCs depending on the material considered. The findings from this investigation revealed that materials, such as silicone and polyurethane, could emit an extensive array of VOCs, with up to 2000 chromatographic peaks detected, and emissions of total volatile organic compounds (TVOCs) reaching levels of 5.4 µg·g⁻¹ and 9.8 µg·g⁻¹, respectively. In the case of polyamide, some VOCs could be related to potential reagents involved in its synthesis. While highlighting materials that should be used with caution depending on the topic and target analytes, this study identified materials that exhibited minimal VOC emissions, such as polytetrafluoroethylene, aluminum, and stainless steel, after an adequate conditioning step. The selected analytical technique, TD-GC×GC/ToFMS, proved its relevance to identify and characterize semi-quantitatively VOC emissions coming from those materials. Such information was essential within the frame of the development of a body odor sampling system, our primary objective. Full article