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Sustainability reporting has emerged as a pivotal tool for corporate accountability, integrating environmental, social, and economic performance into transparent disclosures that align with global frameworks such as the Global Reporting Initiative (GRI) Standards and the United Nations Sustainable Development Goals (SDGs). This study evaluates the environmental sustainability performance of Turkey’s automotive manufacturing sector by analyzing the extent and depth of GRI-based disclosures and their alignment with SDG targets. A mixed-method approach, combining quantitative Key Performance Indicator (KPI) coverage analysis with qualitative content assessment, was applied to sustainability reports from 12 major manufacturers. By identifying the most frequently reported indicators, assessing their coverage of economic, environmental, and social dimensions, and evaluating their direct relevance to specific SDGs, this research fills a critical gap and provides actionable insights for policymakers, industry leaders, and sustainability practitioners. The results indicate that while social indicators achieve the highest average disclosure rate (77.3%), environmental themes dominate narrative emphasis, reflecting sectoral materiality and regulatory pressures rather than proportional (KPI) coverage. Key gaps include underreporting of governance-related SDGs (e.g., SDG 5, SDG 8, SDG 16), limited target-level mapping, and a lack of measurable, outcome-based indicators. The study proposes a structured methodology for linking GRI metrics to SDG targets, enabling more consistent benchmarking and highlighting opportunities for balanced integration across all sustainability pillars. The findings contribute to both academic discourse and industry practice by demonstrating the need to bridge the gap between quantitative breadth and qualitative depth in sustainability reporting, ensuring more robust alignment with the 2030 Agenda. Full article

(This article belongs to the Special Issue Water Environmental Control of Pollutants and Environmental Sustainability)

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16 pages, 1758 KB

Open AccessArticle

Predicting Biochemical Recurrence After Robot-Assisted Prostatectomy with Interpretable Machine Learning Model

by Tianwei Zhang, Hisamitsu Ide, Jun Lu, Yan Lu, Toshiyuki China, Masayoshi Nagata, Tsuyoshi Hachiya and Shigeo Horie

J. Clin. Med. 2025, 14(19), 7079; https://doi.org/10.3390/jcm14197079 (registering DOI) - 7 Oct 2025

Abstract

Background: This study aimed to develop and evaluate machine learning (ML) models to predict biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP). Methods: We retrospectively analyzed clinical data from 1125 patients who underwent RARP between July 2013 and December 2023. The dataset was divided into a training set (70%) and a testing set (30%) using a stratified sampling strategy. Five ML models were developed using the training set. Model performance was evaluated on the testing set using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and F1 scores. Additionally, model interpretability was assessed using SHapley Additive exPlanations (SHAP) values to determine the contribution of individual features. Results: Among the five ML models, the LightGBM model achieved the best prediction ability with an AUC of 0.881 (95%CI: 0.840–0.922) in the testing set. For model interpretability, SHAP values explained the contribution of individual features to the model, revealing that pathological T stage (pT), positive surgical margin (PSM), prostate-specific antigen (PSA) nadir, initial PSA, systematic prostate biopsy positive rate, seminal vesicle invasion (SVI), pathological International Society of Urological Pathology Grade Group (pGG), and perineural invasion (PI) were the key contributors to the predictive performance. Conclusions: We developed and validated ML models to predict BCR following RARP and identified that the LightGBM model with 8 variables achieved promising performance and demonstrated a high level of clinical applicability. Full article

(This article belongs to the Section Nephrology & Urology)

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33 pages, 3430 KB

Open AccessArticle

DLG–IDS: Dynamic Graph and LLM–Semantic Enhanced Spatiotemporal GNN for Lightweight Intrusion Detection in Industrial Control Systems

by Junyi Liu, Jiarong Wang, Tian Yan, Fazhi Qi and Gang Chen

Electronics 2025, 14(19), 3952; https://doi.org/10.3390/electronics14193952 (registering DOI) - 7 Oct 2025

Abstract

Industrial control systems (ICSs) face escalating security challenges due to evolving cyber threats and the inherent limitations of traditional intrusion detection methods, which fail to adequately model spatiotemporal dependencies or interpret complex protocol semantics. To address these gaps, this paper proposes DLG–IDS —a lightweight intrusion detection framework that innovatively integrates dynamic graph construction for capturing real–time device interactions and logical control relationships from traffic, LLM–driven semantic enhancement to extract fine–grained embeddings from graphs, and a spatio–temporal graph neural network (STGNN) optimized via sparse attention and local window Transformers to minimize computational overhead. Evaluations on SWaT and SBFF datasets demonstrate the framework’s superiority, achieving a state–of–the–art accuracy of 0.986 while reducing latency by 53.2% compared to baseline models. Ablation studies further validate the critical contributions of semantic fusion, sparse topology modeling, and localized temporal attention. The proposed solution establishes a robust, real–time detection mechanism tailored for resource–constrained industrial environments, effectively balancing high accuracy with operational efficiency. Full article

(This article belongs to the Topic AI and Data-Driven Advancements in Industry 4.0, 2nd Edition)

18 pages, 1427 KB

Open AccessArticle

Plant Growth-Promoting Bacteria from Tropical Soils: In Vitro Assessment of Functional Traits

by Juliana F. Nunes, Maura S. R. A. da Silva, Natally F. R. de Oliveira, Carolina R. de Souza, Fernanda S. Arcenio, Bruno A. T. de Lima, Irene S. Coelho and Everaldo Zonta

Microorganisms 2025, 13(10), 2321; https://doi.org/10.3390/microorganisms13102321 (registering DOI) - 7 Oct 2025

Abstract

Plant growth-promoting bacteria (PGPBs) offer a sustainable alternative for enhancing crop productivity in low-fertility tropical soils. In this study, 30 bacterial isolates were screened in vitro for multiple PGP traits, including phosphate solubilization (from aluminum phosphate—AlPO₄ and thermophosphate), potassium release from phonolite rock, siderophore production, indole-3-acetic acid (IAA) synthesis, ACC deaminase activity, and antagonism against Fusarium spp. Statistical analysis revealed significant differences (p < 0.05) among the isolates. The most efficient isolates demonstrated a solubilization capacity ranging from 24.0 to 45.2 mg L⁻¹ for thermophosphate and 21.7 to 23.5 mg L⁻¹ for potassium from phonolite. Among them, Pseudomonas azotoformans K22 showed the highest AlPO₄ solubilization (16.6 mg L⁻¹). IAA production among the isolates varied widely, from 1.34 to 9.65 µg mL⁻¹. Furthermore, 17 isolates produced carboxylate-type siderophores, and only Pseudomonas aeruginosa SS183 exhibited ACC deaminase activity, coupled with strong antifungal activity (91% inhibition). A composite performance index identified P. azotoformans K22, E. hormaechei SS150, S. sciuri SS120, and B. cereus SS18 and SS17 as the most promising isolates. This study provides a valuable foundation for characterizing plant growth-promoting traits and identifies key candidates for future validation and the development of microbial consortia. Full article

(This article belongs to the Special Issue Plant Growth-Promoting Bacteria)

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23 pages, 3836 KB

Open AccessArticle

Kinetically Assisted Chemical Removal of Organic Contaminants by Reactive Oxygen Species: Insights from ReaxFF Molecular Dynamics Simulations

by Zixu Wang, Yuhai Li, Peng Zhang, Fei Wang, Laixi Sun, Qingshun Bai, Mingzhi Zhu and Baoxu Wang

Molecules 2025, 30(19), 4010; https://doi.org/10.3390/molecules30194010 (registering DOI) - 7 Oct 2025

Abstract

Organic contaminants on optical components critically impair intense laser systems. Oxygen plasma cleaning is a promising non-contact method, yet the mechanism by which the initial kinetic energy of reactive oxygen species assists chemically driven removal remains unclear. This study employs ReaxFF molecular dynamics to elucidate how reactive oxygen species chemically decompose dibutyl phthalate and how kinetic energy assists chemical reactions by enhancing transport, penetration, and energy transfer. While the core removal mechanism is chemical, kinetic energy promotes plasma-contaminant encounters and facilitates access to otherwise sluggish pathways. The results show that kinetic energy is a key promoter that enhances chemical decomposition, with the contaminant decomposition rate enhanced by up to 1310% and residues reduced by 81.13% compared to pure chemical reactions. This study identifies and quantifies two dominant reaction pathways (butyl chain cleavage & benzene ring cleavage). The analysis of diffusion and energy transfer reveals that higher kinetic energy improves reactive oxygen species transport, enables deeper penetration, and selectively activates specific reaction pathways by overcoming energy barriers. Synergy with flux, dose, and temperature is also demonstrated. This work provides atomic-level insights into kinetic promotion mechanisms, supporting optimized plasma cleaning processes and contributing to the performance stability and operational longevity of intense laser systems. Full article

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14 pages, 398 KB

Open AccessArticle

Feasibility of a Physiatry Assessment Clinic to Address Physical Impairment in Head and Neck Cancer Patients Following Neck Resection and Free Flap Reconstruction

by Lauren C. Capozzi, Chad Wagoner, Julia T. Daun, Lisa Murphy, Steven C. Nakoneshny, George J. Francis, Joseph C. Dort, Khara Sauro and S. Nicole Culos-Reed

Curr. Oncol. 2025, 32(10), 562; https://doi.org/10.3390/curroncol32100562 (registering DOI) - 7 Oct 2025

Abstract

Individuals with head and neck cancers are living longer than ever before, yet many live with the long-term effects of their cancer and treatment. The purpose of this study was to assess the feasibility of a physiatry assessment clinic (PAC) following neck resection and free flap reconstruction, during which physical function was assessed. Methods: Adult patients participating in a larger prehabilitation study were included. Attendance and the ability to complete the physical function assessment were examined. Exploratory analyses were completed to describe physical function, fitness, shoulder, and neck function among PAC attenders. To further understand PAC feasibility, patient-reported outcomes among PAC attenders and non-attenders were examined over 12 months (QuickDASH, NDII, EAT-10). Results: A total of 36 eligible participants (78.2%) from the larger prehabilitation study were approached to participate in the PAC, and 19 of the 36 attended (52.8%). Participants attended on average 8.6 ± 3.6 weeks post surgery, and 100% were able to complete the functional measures. Exploratory data suggest that those who did not attend (17 of 36 approached) had more advanced disease compared to those who attended (p < 0.05). Patient-reported outcomes suggested better shoulder function and swallow function at 6 months among those who attended the clinic versus those who did not. Conclusions: While recruitment to the PAC and assessment completion demonstrated feasibility, attendance posed challenges for patients. These findings highlight the need for innovative approaches to screening patients and tailoring rehabilitation services based on physical impairment. Full article

(This article belongs to the Special Issue Cancer Rehabilitation: Innovations in Practice & Enhancing Survivorship Care)

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13 pages, 1099 KB

Open AccessArticle

Photochemical Methods to Study the Radical-Induced Degradation of Anion-Exchange Membranes

by Panna Solyom, Thomas Nauser and Tamas Nemeth

Membranes 2025, 15(10), 305; https://doi.org/10.3390/membranes15100305 (registering DOI) - 7 Oct 2025

Abstract

We adapted two photochemical methods to generate radicals and assess their impact on anion exchange membrane stability, independent of base-induced degradation. Through the exposure of aqueous solutions of potassium nitrite or suspensions of TiO₂ to UV light at 365 nm, we generated hydroxyl radicals or a combination of hydroxyl and superoxide radicals. The methods’ applicability to anion exchange membranes (AEMs) is demonstrated on three commercial AEMs: PiperION-40, FM-FAA-3-PK-75, and PNB-R45. Changes in ion-exchange capacity, along with FT-IR and NMR analyses, revealed significant degradation in thinner, non-reinforced membranes, while thicker and reinforced membranes showed greater resistance. We attribute this to the limited penetration depth of highly reactive radicals into the membrane. Both methods are practical and inexpensive tools for benchmarking AEM stability against radical attack. Full article

(This article belongs to the Section Membrane Applications for Energy)

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15 pages, 899 KB

Open AccessArticle

Functional and Bioactive Characterization of Hemp Cake Proteins and Polyphenols from Non-Psychoactive Cannabis sativa

by María Quinteros, Paola Wilcaso, Carlos Ribadeneira and Edgar Vilcacundo

Processes 2025, 13(10), 3184; https://doi.org/10.3390/pr13103184 (registering DOI) - 7 Oct 2025

Abstract

The agro-industrial residue known as hemp cake, derived from non-psychoactive Cannabis sativa L., represents a sustainable alternative for the development of protein-rich ingredients. In Ecuador, particularly in Bolívar Province, this by-product has been underutilized. However, similar challenges in the valorization of hemp residues have also been reported in other regions, where they are often discarded or used as low-value animal feed. These issues are not exclusive to Bolívar, and since protein stability depends primarily on drying and storage rather than geographic relocation, the valorization strategies proposed in this study can be extrapolated to other production zones. Protein concentrates were extracted from freeze-dried flower cake (TL, freeze-dried hemp cake) and oven-dried flower cake (TS, oven-dried hemp cake) using isoelectric precipitation, yielding protein concentrates from freeze-dried cake (CPL) and oven-dried cake (CPS). Protein content was determined using the Dumas combustion method, the Bradford dye-binding method, and the bicinchoninic acid (BCA) method. Functional properties such as solubility, water absorption, oil absorption, foaming capacity, and foam stability were evaluated, together with total phenolic and flavonoid content and in vitro antioxidant and anti-inflammatory activity. Results demonstrated high protein values (up to 90.42%), remarkable functional properties, and strong bioactive potential, supporting hemp cake concentrates as sustainable alternatives for food, nutraceutical, and pharmaceutical applications Full article

(This article belongs to the Special Issue Bioactive Compound Function Characterization in Biochemical Engineering)

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19 pages, 912 KB

Open AccessArticle

Functional Independence Assessment in Children and Adolescents with Achondroplasia: A Multicenter Cross-Sectional Study Using the WeeFIM Scale

by Chung-Lin Lee, Hung-Hsiang Fang, Chih-Kuang Chuang, Dau-Ming Niu, Ju-Li Lin, Mei-Chyn Chao, Yen-Yin Chou, Pao Chin Chiu, Chia-Chi Hsu, Tzu-Hung Chu, Yin-Hsiu Chien, Huei-Ching Chiu, Ya-Hui Chang, Yuan-Rong Tu, Yun-Ting Lo, Hsiang-Yu Lin and Shuan-Pei Lin

Diagnostics 2025, 15(19), 2532; https://doi.org/10.3390/diagnostics15192532 - 7 Oct 2025

Abstract

Background/Objectives: Achondroplasia is the most common skeletal dysplasia, affecting 1 in 25,000 births. Limited research exists on the assessment of functional independence using standardized tools in children and adolescents with achondroplasia. The WeeFIM scale provides a comprehensive evaluation of daily living skills across multiple functional domains. This study aimed to assess the functional independence levels in children and adolescents with achondroplasia using WeeFIM and analyze functional capabilities. Methods: This multicenter cross-sectional study included 46 participants aged 6–18 years with confirmed achondroplasia. Data were collected through standardized WeeFIM assessments from medical centers and online surveys (2021–2024). WeeFIM evaluates 18 functional items across 3 domains: self-care (8 items), mobility (5 items), and cognition (5 items), scored 1–7 (complete dependence to independence). Results: Participants included 26 males (56.5%) and 20 females (43.5%). Most (78.3%) were diagnosed during infancy. The mean functional scores were highest for cognition (34.0/35, 97.1%), followed by self-care (51.2/56, 91.4%) and mobility (31.5/35, 90.0%). Most participants achieved near-complete independence in cognitive functions. Mobility tasks, particularly stair climbing and bathtub transfers, showed the greatest challenges. Functional independence increased with age, with significant improvements during early childhood to adolescence transition. Conclusions: Children and adolescents with achondroplasia demonstrate high functional independence across daily activities, with cognitive abilities largely unaffected. Although specific mobility challenges exist, most participants achieve independence with appropriate accommodations. These findings provide valuable baseline data for clinical care planning and support optimistic functional outcomes for pediatric patients with achondroplasia. Full article

(This article belongs to the Section Clinical Diagnosis and Prognosis)

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23 pages, 1082 KB

Open AccessReview

Colchicine in Contemporary Pharmacotherapy: Mechanistic Insights and Clinical Horizons

by Łukasz Wołowiec, Joanna Osiak-Gwiazdowska, Albert Jaśniak, Weronika Mucha, Małgorzata Wojtaluk, Weronika Czerniecka, Anna Wołowiec, Joanna Banach and Grzegorz Grześk

J. Clin. Med. 2025, 14(19), 7078; https://doi.org/10.3390/jcm14197078 - 7 Oct 2025

Abstract

Colchicine, a natural alkaloid, has emerged as a promising anti-inflammatory therapy with applications in cardiovascular diseases, dermatological conditions, and COVID-19 management. Its mechanisms, including the modulation of neutrophil activity, the inhibition of the NLRP3 inflammasome, and the mitigation of cytokine storms, have expanded its therapeutic potential beyond traditional uses. This review synthesizes current evidence on colchicine’s clinical applications and mechanisms of action. In cardiovascular medicine, colchicine has been shown to reduce risks of pericarditis, coronary artery disease and atrial fibrillation. In dermatology, most evidence derives from small-scale studies, case series, and retrospective analyses, suggesting potential benefits in conditions such as leukocytoclastic vasculitis, cutaneous amyloidosis, and pemphigus, although these findings require confirmation through randomized controlled trials (RCTs). Emerging studies also indicate a potential role for colchicine in improving outcomes in severe COVID-19. Overall, colchicine demonstrates broad therapeutic utility, warranting further research to clarify its effectiveness across diverse clinical settings. Full article

(This article belongs to the Section Pharmacology)

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17 pages, 3914 KB

Open AccessArticle

Genomic and Functional Characterization of Acetolactate Synthase (ALS) Genes in Stress Adaptation of the Noxious Weed Amaranthus palmeri

by Jiao Ren, Mengyuan Song, Daniel Bimpong, Fulian Wang, Wang Chen, Dongfang Ma and Linfeng Du

Plants 2025, 14(19), 3088; https://doi.org/10.3390/plants14193088 - 7 Oct 2025

Abstract

Acetolactate synthase (ALS) is an important enzyme in plant branched-chain amino acid biosynthesis and the target of several major herbicide classes. Despite its agronomic importance, the role of ALS genes in stress adaptation in the invasive weed Amaranthus palmeri remains unstudied. In this study, four ApALS genes with high motif conservation were identified and analyzed in A. palmeri. Phylogenetic analysis classified ApALS and other plant ALS proteins into two distinct clades, and the ApALS proteins were predicted to localize to the chloroplast. Gene expression analysis demonstrated that ApALS genes are responsive to multiple stresses, including salt, heat, osmotic stress, glufosinate ammonium, and the ALS-inhibiting herbicide imazethapyr, suggesting roles in both early and late stress responses. Herbicide response analysis using an Arabidopsis thaliana ALS mutant (AT3G48560) revealed enhanced imazethapyr resistance, associated with higher chlorophyll retention. Furthermore, high sequence homology between AT3G48560 and ApALS1 suggests a conserved role in protecting photosynthetic function during herbicide stress. This study provides the first comprehensive analysis of the ALS gene family in A. palmeri and offers important insights into its contribution to stress resilience. These findings establish a vital foundation for developing novel strategies to control this pervasive agricultural weed and present potential genetic targets for engineering herbicide tolerance in crops. Full article

(This article belongs to the Special Issue Molecular, Biochemical and Developmental Adaptations of Plants Under Abiotic Stress)

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21 pages, 3762 KB

Open AccessArticle

Rapid Detection of Foodborne Pathogenic Bacteria in Beef Using Surface-Enhanced Raman Spectroscopy

by Huixin Zuo, Yingying Sun, Mingming Huang, Yuqi Liu, Yimin Zhang and Yanwei Mao

Foods 2025, 14(19), 3434; https://doi.org/10.3390/foods14193434 - 7 Oct 2025

Abstract

Foodborne pathogenic bacteria in meat pose a serious threat to human health. Traditional detection methods for these bacteria are often time-consuming and labor-intensive. In this study, we applied surface-enhanced Raman scattering (SERS) combined with portable Raman spectroscopy as a rapid and convenient detection technique. SERS is a sensitive and fast method that enhances light scattering on rough metal surfaces. Silver nanoparticles (AgNPs) were used as SERS substrates to identify and analyze four pathogenic bacteria, including Escherichia coli (E. coli) O157:H7, Salmonella typhimurium (S. typhimurium), Staphylococcus aureus (S. aureus), and Listeria monocytogenes (L. monocytogenes), in beef. We optimized the detection conditions of AgNPs and established the limit of detection (LOD) for these four pathogenic bacteria in both pure culture and beef samples. The LODs were as low as 4–23 CFU/mL in beef samples, indicating high detection sensitivity. Linear discriminant analysis (LDA) was used to analyze the SERS spectra, yielding an accuracy of 91.7–97.3%. This study not only provides a rapid and portable detection method for pathogenic bacteria in beef but also overcomes the limitations of traditional methods that are often time-consuming and not suitable for on-site detection. However, the current study is limited to the detection of the four specific pathogenic bacteria, and further research is needed to expand the range of detectable pathogens and to improve the robustness of the detection models for more complex meat samples. Overall, this research demonstrates the potential of SERS combined with portable Raman spectroscopy as a powerful tool for the rapid detection of pathogenic bacteria in meat products, which could significantly enhance food safety monitoring and control. Full article

(This article belongs to the Special Issue Application of Surface-Enhanced Raman Spectroscopy in Food Analysis and Quality Control)

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21 pages, 765 KB

Open AccessArticle

AI-Driven Sustainable Competitive Advantage in Tourism and Hospitality: Mediating Roles of Digital Culture and Skills

by Abdulrahman Abdullah Alhelal, Ahmed Abdulaziz Alshiha and Bassam Samir Al-Romeedy

Sustainability 2025, 17(19), 8903; https://doi.org/10.3390/su17198903 - 7 Oct 2025

Abstract

This study explored how AI affects the sustainability of competitive advantage in the tourism and hospitality sector, with a particular focus on the mediating roles of digital culture and digital skills in the lens of the Technology Acceptance Model (TAM). Data were collected via a structured questionnaire distributed to a purposive sample of 488 managers and supervisors working in five-star hotels, travel agencies, and DMCs across Saudi Arabia. The findings revealed that AI has a significant direct effect on sustainable competitive advantage and also exerts strong positive effects on both digital culture and digital skills. In turn, both of these internal enablers significantly contribute to sustaining a competitive advantage. Mediation analysis further showed that both digital culture and digital skills partially mediate the relationship between AI and sustainable competitiveness. The study addresses a notable gap in tourism research by providing localized evidence from a market undergoing rapid transformation under Vision 2030, and, taken together, extends TAM to an organizational lens by demonstrating AI’s role in shaping culture and skills that underpin a durable advantage while pointing to actionable priorities—targeting high-value AI use cases, conducting capability audits, institutionalizing continuous learning through visible leadership and role-based upskilling, and embedding culture- and skills-oriented KPIs within AI governance. Full article

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21 pages, 5895 KB

Open AccessArticle

Intelligent 3D Potato Cutting Simulation System Based on Multi-View Images and Point Cloud Fusion

by Ruize Xu, Chen Chen, Fanyi Liu and Shouyong Xie

Agriculture 2025, 15(19), 2088; https://doi.org/10.3390/agriculture15192088 - 7 Oct 2025

Abstract

The quality of seed pieces is crucial for potato planting. Each seed piece should contain viable potato eyes and maintain a uniform size for mechanized planting. However, existing intelligent methods are limited by a single view, making it difficult to satisfy both requirements simultaneously. To address this problem, we present an intelligent 3D potato cutting simulation system. A sparse 3D point cloud of the potato is reconstructed from multi-perspective images, which are acquired with a single-camera rotating platform. Subsequently, the 2D positions of potato eyes in each image are detected using deep learning, from which their 3D positions are mapped via back-projection and a clustering algorithm. Finally, the cutting paths are optimized by a Bayesian optimizer, which incorporates both the potato’s volume and the locations of its eyes, and generates cutting schemes suitable for different potato size categories. Experimental results showed that the system achieved a mean absolute percentage error of 2.16% (95% CI: 1.60–2.73%) for potato volume estimation, a potato eye detection precision of 98%, and a recall of 94%. The optimized cutting plans showed a volume coefficient of variation below 0.10 and avoided damage to the detected potato eyes, producing seed pieces that each contained potato eyes. This work demonstrates that the system can effectively utilize the detected potato eye information to obtain seed pieces containing potato eyes and having uniform size. The proposed system provides a feasible pathway for high-precision automated seed potato cutting. Full article

(This article belongs to the Section Artificial Intelligence and Digital Agriculture)

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24 pages, 2338 KB

Open AccessArticle

Comparative (Bio)monitoring of Airborne PAHs Using Mosses and Filters

by Małgorzata Rajfur, Paweł Świsłowski, Tymoteusz Turlej, Oznur Isinkaralar, Kaan Isinkaralar, Sara Almasi, Arianna Callegari and Anca-Iulia Stoica

Molecules 2025, 30(19), 4009; https://doi.org/10.3390/molecules30194009 - 7 Oct 2025

Abstract

The present investigation provides a comparative six-month analysis of atmospheric pollution by polycyclic aromatic hydrocarbons (PAHs) in the urban region of Opole, Poland. The study employs dual monitoring methods: traditional quartz filter-based active air sampling and active moss biomonitoring using Pleurozium schreberi, Sphagnum fallax, and Dicranum polysetum mosses. The experimental campaign took place from August 2021 to February 2022, spanning the autumn and winter seasons. PAH concentrations were measured using gas chromatography–mass spectrometry (GC-MS) following methodical sample extraction protocols. Filters documented transient air changes in PAHs, particularly high-molecular-weight (HMW) components such as benzo[a]pyrene (BaP), which exhibited considerable increases during the colder months due to heightened heating activities and less dispersion. The size of particles deposited on the filters varied from 0.16 to 73.6 μm, with an average size of 0.71 μm. Mosses exhibited cumulative uptake trends, with D. polysetum showing the greatest bioaccumulation efficiency, particularly for low- and medium-molecular-weight PAHs, followed by P. schreberi and S. fallax. Meteorological indices, including sun radiation and air temperature, demonstrated significant negative relationships with PAH buildup in mosses. Diagnostic ratio analysis verified primarily pyrogenic sources (e.g., fossil fuel burning), although petrogenic contributions were detected in D. polysetum, indicating its increased sensitivity to evaporative emissions. The study shows that the integration of moss biomonitoring with traditional filter samples provides a strong, complementary framework for assessing air quality, particularly in fluctuating meteorological settings. The results advocate for the integration of moss-based methodologies into environmental monitoring initiatives and provide significant insights into contaminant dynamics influenced by seasonal and meteorological factors. Full article

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