Abstract: Atmospheric microplastics are increasingly recognized as emerging contaminants in urban air, yet evidence from Philippine cities outside Metro Manila remains scarce. This study investigated polymer-confirmed suspended airborne microplastics across four urban roadside environments in Cagayan de Oro City, in southern Philippines: C.M. Recto Avenue, J.R. Borja Street, Gaabucayan Street, and Nazareth Street. Atmospheric particles were collected from 12 roadside stations, or three from each site, using a respirable dust sampler during a standardized mid-day sampling period, then subjected to alkaline digestion, microscopic examination, and ATR-FTIR confirmation. Of 99 suspected particles, 44 were verified as synthetic polymers and included in the final analysis. Mean atmospheric microplastic concentrations ranged from 0.0079 to 0.0212 items m⁻³, with J.R. Borja Street showing the highest concentration and Nazareth Street the lowest. Abundance did not differ significantly among roads, whereas particle shape, color, and polymer composition varied significantly, while size-class distribution did not. Fibers were the dominant morphology (56.8%), transparent particles were the most common color class (52.3%), and polypropylene and polyethylene terephthalate were the predominant polymers. These findings confirm the presence of atmospheric microplastics across roadside environments in Cagayan de Oro City and indicate that spatial variation is more evident in particle characteristics than in overall abundance.

Abstract: Addressing the issue that evaluations of historic districts often rely heavily on qualitative analysis and lack quantitative support, this study constructs a comprehensive quantitative assessment system integrating the SOR model with image semantic segmentation technology. Taking Cuojie Street in Hefei as a case study, the DeepLab-V3+ algorithm is employed to analyze street-view images, extracting eight physical spatial features—including green view ratio and enclosure ratio—as environmental stimulus variables (S). Combined with the Semantic Difference (SD) method, we quantified the public's psychological perceptions (Organism O) and behavioral responses (Reaction R). Multiple regression analysis indicates: (1) Cultural visual distinctiveness and color diversity are core factors positively driving the perception of historical atmosphere; (2) Enclosure ratio exhibits a significant trade-off effect: while it strengthens cultural identity, excessively high levels lead to a decline in physical comfort; (3) Green view ratio and walkable space play a decisive role in the perception of environmental comfort. Based on this quantitative analysis, this paper proposes micro-renewal strategies such as visual anchoring and color correction, flexible interface design, three-dimensional greening, and refined operation and maintenance. This study precisely maps subjective psychological perceptions to objective physical pixels, providing a scientific reference for evidence-based renewal and sustainable development of similar districts.

Abstract: As the global population continues to grow, the demand for forest products and services also increases. However, with natural forests in the tropics declining and becoming less accessible for timber production, there is a growing reliance on planted forests to meet these demands. Planted forests are often seen as a solution to environmental issues although this viewpoint is debated, with many considering that planted forests are not ‘nature positive’. Here we examine evidence from the literature to determine whether planted forests primarily contribute to, or offer solutions to, pressing global environmental challenges – biodiversity conservation, climate change mitigation, clean water supplies, and declining natural forests. Findings are mixed for biodiversity conservation, with positive contribution of plantations depending on proximity to, and management of, natural vegetation in the plantation matrix. Plantations can contribute positively to water yield and quality but this depends on site characteristics, previous land use, management practices, species selection and rotation length influence these outcomes. When replacing grass or crop land, plantations reduce water yield for downstream users. Planted forests can sequester atmospheric carbon and positively contribute to climate change mitigation if established on cleared or degraded land but not when replacing natural forests. Planted forest can alleviate pressure on natural forests by providing alternative sources for timber but establishment costs are high, and timber harvesting is not a major driver of tropical natural forests. In conclusion, well-planned and designed planted forests can make a positive contribution to nature, address global environmental challenges and provide multiple ecosystem services, particularly when integrated with other landscape restoration activities.

Abstract: Rainfall is the mainly trigger of landslides in Japan, especially in mountainous regions with steep slopes and highly weathered terrain. This study examines rainfall conditions linked to landslides in Hiroshima Prefecture by analyzing multi-temporal precipitation data and establishing thresholds for the 2014 and 2018 disasters. Rainfall events were identified from satellite data using an inter-event dry-period. Intensity–duration (I–D) relationships, percentile thresholds, and Receiver Operating Characteristic analysis were used to assess rainfall thresholds. Additionally, topographic threshold analysis was preformed to evaluate how slope gradient and lithology influence rainfall-induced landslides. The results reveal notable differences in the triggering mechanisms between the two disasters. The 2014 landslides were caused by short-duration, intense rainfall (376 mm over about 40 hours), while the 2018 event resulted from prolonged rainfall exceeding 1000 mm over more than 11 days. I–D thresholds suggest that the 2014 event was primarily triggered by high intensity, whereas the 2018 event was driven by long duration. Landslides occurred most frequently on moderate to steep slopes, and lower triggering thresholds were observed in granitic terrain. These findings highlight that both rainfall features and terrain conditions jointly influence landslide occurrence, emphasizing the need to incorporate both factors into rainfall-based early-warning systems.

Abstract: Tropical wetlands are highly sensitive to climatic and anthropogenic disturbances, and the composition of their plant communities can reflect the capacity of these ecosystems to respond to environmental perturbations. This study evaluated the relationship between aquatic macrophyte richness, community structure, and habitat vulnerability to climate change in aquatic ecosystems located in the San Luis rural district, Barrancabermeja mu-nicipality (Santander, Colombia). Macrophyte communities were characterized at 47 monitoring sites distributed across six mesohabitats: floodplain depressions, swamp la-goons, wetlands, artificial ponds (jagüeyes), naturalized ponds, and stream riparian zones. A total of 63 species belonging to 30 families and 51 genera were recorded. The re-lationships among species richness, abundance, and mesohabitat types were assessed using multivariate analyses and statistical models, including principal component anal-ysis (PCA) and generalized linear models. Results revealed clear differences in vegetation community structure among mesohabitats and dominance patterns associated with an-thropogenic disturbance. Ecosystems with higher macrophyte diversity and greater rep-resentation of native species exhibited lower levels of climatic vulnerability, whereas hab-itats dominated by eutrophication-tolerant species and subjected to greater anthropogenic pressure showed higher susceptibility. These findings highlight the ecological importance of aquatic macrophytes as indicators of environmental change and as key functional components contributing to the resilience of tropical wetlands under climate change.

Abstract: Mining and industrial activities generate large volumes of waste, up to 99% of the extracted material, forming a major global residue source. In this context, the valorization of mining sludge for sustainable construction materials gains relevance. This study examines the fabrication of ceramic bricks incorporating mining sludge from the Panasqueira mine, evaluating sludge incorporation levels and sintering temperatures to optimize resource use and reduce environmental impacts. Bricks were produced by blending residual clays from Víznar (Granada, Spain) with Panasqueira sludge at substitution rates of 10, 25 and 50%, and fired at 800, 950 and 1100 °C. The samples were characterized by XRF, XRD, water absorption tests, porosimetry, ultrasound pulse velocity, compressive strength testing, ESEM, leaching analysis and colorimetry to assess their chemical, physical and mechanical behavior. Both clays and sludge are rich in SiO₂ and Al₂O₃, suitable for ceramic processing, while fluxing oxides promote vitrification and densification. Incorporating 25 and 50% sludge reduces porosity, increases ultrasonic velocity and improves mechanical strength, achieving optimal performance at 1100 °C. Moreover, firing immobilizes toxic metals and allows controlled color development, confirming the technical and environmental suitability of these bricks, whose microstructure and stability depend on sludge content and firing temperature, essential factors for sustainable construction and architectural rehabilitation.

Abstract: For 24 of the 69 chemicals measured in U.S. National Health and Nutrition Examination Survey (NHANES) urine biomonitoring with data for both children aged 3–5 and adults aged 66 and older — including di-2-ethylhexyl phthalate (DEHP) and inorganic tin — no single regulatory exposure standard can be simultaneously epistemically grounded for both populations. This finding, which we term severe regulatory incommensurability, cannot be obtained from Bayesian inference or any significance test: it requires a geometric measure of the overlap between population-specific feasibility regions that has no probabilistic analog.We derive this result by applying the Theory of Epistemic Abductive Geometry (TEAG) — a possibilistic, constraint-based inference framework grounded in possibility theory and tropical mathematics — to the complete 179-chemical, 11-demographic-group dataset of Stanfield et al. (2022), the gold-standard Bayesian biomonitoring pipeline. TEAG recovers Bayesian median intake rate estimates with near-perfect agreement (r = 0.9965, RMSE = 0.15 log₁₀), establishing that the two frameworks agree on point estimates while diverging fundamentally on the geometric structure of the inference.The primary findings are: (i) the κ pairwise overlap coefficient is below 0.5 for 24 chemicals, meaning no intake rate achieves simultaneous epistemic feasibility above 50% for both age groups, with child-to-elder fold differences up to 8.6×; (ii) the TEAG admissible epistemic basin is on average 20.3× narrower than the Bayesian 95% credible interval, reflecting the geometric separation of measurement censoring, metabolite ambiguity, and demographic variability rather than false precision; (iii) demographic groups can be ordered by falsification priority — children aged 3–5 rank first at 1.89× mean distance from the committed population estimate; and (iv) 70% of 138 chemicals with longitudinal NHANES data (1999–2016, 9 cohorts) undergo epistemic phase transitions across cohorts, with atrazine mercapturate showing a 1.21 log₁₀ commitment reversal and arsenous acid — a severely incommensurate chemical — undergoing a persistent PCRB status change beginning in 2011–2012. A formal proof establishes that the κ incommensurability coefficient cannot be reproduced from any function of Bayesian posterior summary statistics, even given identical posterior means, variances, and credible interval widths.We call explicitly for population-differentiated reference doses for the 24 severely incommensurate chemicals and propose that κ < 0.5 between children and elderly adults in NHANES biomonitoring data be adopted as a standing geometric criterion for triggering age-stratified regulatory review.

Abstract: Rapid urbanization intensified spatial variability in air pollution across India, while monitoring networks are limited in capturing local exposure conditions. This study develops and evaluates an exposure assessment framework, with pilot findings from the Air Pollution Exposure on Adolescents’ Lungs (APEAL), a multi-centre prospective cohort study conducted in Delhi, Mumbai, Bengaluru, and Mysuru, which represent diverse air pollution levels. Residential measurements of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were conducted using standardized protocols. Results from pilot-phase showed that mean outdoor PM2.5 concentrations were highest in Delhi (90.4 ± 12.0 µg/m³), followed by Mumbai (57.2 ± 12.8 µg/m³), and Bengaluru (53.0 ± 9.0 µg/m³), with Mysuru having the lowest at 32.3 ± 9.3 µg/m³, indicating a north-south gradient attributed to anthropogenic activities. Optical properties of PM2.5, including absorption coefficients (Babs370 and Babs880), and calculated Absorption Angstrom Exponent (AAE), show significant variations and are primarily influenced by combustion sources. Further, this approach will include seasonal monitoring, chemical characterization, toxicity analysis, land-use regression (LUR) modelling, and time activity pattern to generate high-resolution exposure estimates. This methodology provides a robust, scalable framework for epidemiological studies and urban air pollution assessment in resource-limited settings, with relevance for urban planning and policy making.

Abstract: Agriculture faces compounding pressures from food insecurity, climate change, and resource scarcity, creating urgent demand for scalable analytical tools. This PRISMA 2020-compliant systematic review synthesises 582 peer-reviewed studies on machine learning (ML) and deep learning (DL) applications in agriculture, drawn from Scopus for the period January 2019 to March 2026. The 2026 data cover only the first quarter (January–March) and are therefore not directly comparable to full-year counts. Publication volume grew exponentially — from 6 papers in 2019 to 251 in 2025 — driven by the adoption of convolutional neural networks (CNNs), Vision Transformers (ViT), and YOLO-based object detectors. Plant disease detection (27.0%) and crop yield prediction (13.7%) dominated the application landscape. South Asia and East Asia together contributed 59.3% of the corpus, while Sub-Saharan Africa and Latin America each accounted for only 1.4%, revealing a profound mismatch between research output and global food insecurity burden. Median reported classification accuracy was 98.1% for disease detection, largely reflecting controlled laboratory datasets rather than field conditions. Median R² was 0.823 for yield prediction, based on 22 of 80 yield studies reporting this metric. Unit heterogeneity, dataset artefacts, and inconsistent evaluation practices limit cross-study comparability and the real-world interpretability of these figures. Open science practices remain critically low: only 7.7% of papers shared code and 14.1% shared data openly. Explainable AI, federated learning, and physics-informed modelling represent emerging frontiers. The review identifies benchmark standardisation, smallholder-relevant design, and geographic equity as the field's most pressing unresolved challenges.

Abstract: Water and land are critical natural resources that require effective management, particularly in rapidly urbanizing areas such as Cagayan de Oro City, Philippines. This study aims to assess erosion susceptibility and prioritize conservation needs across nine watersheds using GIS-based morphometric analysis. The entire extent of each watershed was analyzed beyond political boundaries to ensure comprehensive evaluation of geomorphological characteristics. Key morphometric parameters, including drainage density, stream frequency, slope, and basin shape, were computed to determine watershed behavior and erosion risk. Results indicate that the Cagayan de Oro River Basin is the most erosion-prone, followed by the Umalag, Iponan, and Cugman watersheds, while the Bugo–Alae watershed exhibits the lowest susceptibility. Higher slope gradients and elongated basin shapes were associated with increased erosion risk, whereas higher drainage density and stream frequency corresponded to lower susceptibility. These findings provide a scientific basis for prioritizing watershed management and conservation strategies, supporting sustainable land use planning and erosion mitigation in the study area.

Abstract: Background. The food industry contributes significantly to global greenhouse gas emissions, water consumption, and waste generation. Although environmental impact assessment tools have rapidly diversified, methodological fragmentation continues to limit comparability across studies and the formulation of coherent sustainability strategies. Objective. This study conducted a systematic review to synthesize, critically appraise, and map the evidence on methods, technologies, and applications used in assessing the sustainability of food industry processes, with a view to identifying the most effective approaches and the main research gaps. Data sources and eligibility. The Web of Science Core Collection was queried on November 27, 2025 using a structured strategy based on Boolean operators and Topic fields. Original articles and reviews in English, published between 2020 and 2025, that reported quantitative or qualitative indicators of environmental impact, according to the PICO framework, were included. Results. From an initial 1000 records, 225 studies were included and narratively synthesized into seven major themes. LCA predominated as the standard method, but with significant heterogeneity in system boundaries and functional units. Emerging technologies indicated potential for reducing resource consumption, dependent on subsector and scale. Conclusions: Harmonization of assessment frameworks, industrial validation of circular technologies, and robust comparative studies are essential for the transition to a sustainable food system.

Abstract: In this research we analyzed land cover/use processes and their impact on biodiversity in the Megalopolis of Mexico City. We used land cover/use databases from 1976 and 2018, both validated, improved and adapted for conducting landscape dynamic analysis. We also included records of 159 threatened species of fungi, vascular plants and vertebrates to construct spatially explicit biodiversity richness models based upon niche ecological algorithms. The results showed that human settlement encroachment was the main factor driving land cover/use changes, significantly affecting rural and natural landscapes. The extent and location of the dramatic shrinking of agricultural lands was clearly demonstrated. Afforestation was the second most important land cover/use process occurring mainly on native grasslands and shrublands. Biodiversity richness was depleted substantially, affecting about 35 % of the most important biodiversity hot spots and rendering the remainder more vulnerable due to extensive fragmentation of native ecosystems. The results are discussed in the light of the implications of the value of interdisciplinary methodological approaches, potential water recharge, governance of territorial disputes, loss of cultural heritage and poorly implemented environmental policies. Furthermore, the study highlights the urgent need to generate an innovative model for development which gives equal importance to the conservation of natural and rural landscapes as a fundamental form of subsistence for human settlements. Protecting biocultural heritage is of paramount importance. The region's genetic resources and cultural diversity are unique and have played a fundamental role in providing various benefits from nature to urban and rural inhabitants. These findings can serve as a guide for other similar megacities around the world.

Abstract: This study evaluates the environmental performance of feed‑grade soy protein concentrate (SPC‑Feed) produced by Porta Hnos. S.A. in Córdoba, Argentina, through a cradle‑to‑gate plus end‑of‑life Life Cycle Assessment (LCA), with a specific focus on carbon footprint (CF). The assessment follows ISO 14040, 14044, and 14067 standards, using SimaPro^® with Ecoinvent 3.10 and Agri‑footprint 6.0 databases. Primary agricultural data were collected from soybean‑producing farms in Córdoba for the 2023/2024 season, while industrial process data correspond to the 2024 production year. System boundaries include soybean cultivation, soybean pressing, SPC extraction and drying, packaging, transportation to local and international markets, and packaging end‑of‑life. Results show CF values ranging from 0.608 to 0.851 kg CO₂‑eq per kg of SPC‑Feed, depending on market destination and packaging type. Agricultural production contributes ≈25% of total emissions, driven mainly by crop residues (54.7%), herbicide use, and fuel consumption. Industrial emissions are dominated by natural gas use in cogeneration and thermal processes, representing ≈43% of total CF. Downstream emissions are highly dependent on transport distances, especially for international markets. Comparative assessments indicate that SPC‑Feed produced in Argentina exhibits lower carbon intensity than similar products modeled for Brazil, USA, and Europe, primarily due to favorable agricultural conditions and the absence of land‑use‑change emissions. These findings support the environmental competitiveness of Argentine SPC‑Feed and highlight opportunities for further emission reductions through energy efficiency and logistics optimization.

Abstract: Emerging contaminants (ECs) and microplastics (MPs) are increasingly detected in surface waters, wastewaters, and drinking water, often as complex mixtures, transformation products, and particle-associated burdens that challenge routine monitoring. This critical review examines current analytical strategies for the detection and characterization of both molecular and particulate emerging contaminants in aquatic systems, with particular emphasis on their relevance to environmental and human-health risk assessment. For molecular ECs, targeted LC–MS/MS and GC–MS(/MS) approaches are evaluated alongside high-resolution mass spectrometry (HRMS)-based suspect and non-target screening, retrospective data mining, and transformation-product elucidation. For MPs, particle-resolved vibrational spectroscopy (µ-FTIR and µ-Raman) is critically assessed in comparison with complementary thermal/mass-based methods such as pyrolysis–GC–MS and TED–GC–MS. Particular attention is given to the influence of sampling design, matrix-adapted sample preparation, analytical confidence, and method-dependent size and polymer coverage on data quality and interstudy comparability. The review further highlights the risks of ECs in relation to exposure pathways, mixture effects, and the role of MPs as vectors of ECs, additives, and microorganisms. Finally, key priorities are identified for next-generation monitoring frameworks, including harmonized workflows, transparent confidence reporting, and stronger integration of analytical evidence with fate, exposure, and risk assessment.

Abstract: This study assessed the spatial and temporal variability of rainfall erosivity (R factor) and its implications for potential soil loss in the Velhas River Basin, Minas Gerais, Brazil. Rainfall erosivity was estimated using data from 48 rain gauge stations and precipitation derived from CHIRPS product, processed in a cloud-based environment Google Earth Engine. Between 2014 and 2024, annual R values exhibited high variability, ranging from 3,900 to more than 9,000 MJ mm ha⁻¹ h⁻¹ yr⁻¹, with peak values recorded in the wettest year (2022) and the lowest values in 2014. Potential soil loss was estimated using the RUSLE model for the years of minimum and maximum erosivity, yielding values between 0.60 and 274.17 Mg ha⁻¹ yr⁻¹. The highest soil losses occurred in areas of exposed soil and agricultural land, whereas forest formations exhibited lower rates even under high rainfall erosivity conditions. The comparison between observed and estimated datasets revealed strong spatial and statistical agreement according to the Pearson correlation coefficient (r ≈ 0.999), although CHIRPS slightly underestimated extreme values. These results demonstrate the strong potential for integrating observed and remote sensing data in hydrosedimentological analyses at the basin scale.

Abstract: Disasters in the Philippines are recurrent and deeply disruptive, yet their lessons often fade from collective consciousness once immediate recovery ends. Existing research has tended to emphasize logistical response and physical survival, leaving gaps in understanding how disaster experiences are remembered, narrated, and mediated as cultural and governance resources. This study addresses that gap by taking Typhoon Basyang in Iligan City as a critical case to examine how survival is framed through memory, solidarity, and digital mediation, and why these processes matter for resilience and policy. Guided by phenomenology, collective memory, and digital ethnography, the research employed a qualitative case study design integrating interviews, focus groups, GIS mapping, AI-assisted coding, and digital ethnographic analysis. Twenty purposively selected participants (S1–S20) provided narratives that anchored the inquiry in lived experience, substantiating theoretical insights with concrete accounts of trauma, solidarity, and resilience, while data saturation confirmed analytical robustness. Findings reveal that survival extended beyond physical endurance to processes of remembering, narrating, and embedding experiences into collective identity, highlighting the importance of memory as both archive and resource for preparedness. While the scope was limited to a single locality and one institutional actor, SMCII, this constraint provided depth of contextual analysis. In addressing the gap between logistical accounts and cultural memory, the study demonstrates how resilience is sustained through narrative, digital mediation, and institutional presence, and although grounded in Iligan City, its insights extend beyond local boundaries, reframing survival as lived memory and digitally mediated resilience in ways that contribute to global disaster scholarship and offering lessons on how communities worldwide can sustain vigilance and identity long after the recovery phase has ended.

Abstract: Urban housing in Nigerian cities has become a major concern due to rapid urbanization, population growth, and the increasing demand for affordable accommodation. In cities such as Ibadan, housing development often prioritizes cost and speed over environmental performance, resulting in buildings that do not adequately respond to local climatic conditions and consequently provide poor indoor thermal comfort. This study examines climate-responsive design strategies for affordable urban housing in Ibadan, Nigeria, with a focus on improving comfort while maintaining affordability. A qualitative, design-based approach was adopted, drawing on climatic analysis, relevant literature, and field observations in rapidly developing areas such as Moniya. The study evaluated key passive design strategies, including building orientation, natural ventilation, solar shading, material selection, and spatial planning. Findings reveal that many existing housing developments neglect these principles, leading to excessive heat gain and poor airflow. However, the study demonstrates that the integration of simple, cost-effective climate-responsive strategies can significantly enhance indoor comfort and reduce reliance on mechanical cooling systems. It concludes that incorporating climate-responsive design is essential for improving housing performance and addressing energy challenges within the Nigerian context.

Abstract: The concepts of anthromes and human appropriation of net primary production (HANPP) are both valuable in understanding our human-dominated planet, yet they have never been integrated theoretically or empirically. Here we utilize an extensive county-level dataset on HANPP and its product-level components to derive, through cluster analysis, ten contemporary US anthromes. From highest to lowest density of harvested HANPP, the anthromes are: Rainfed Corn-Soy, Dairy Fodder, Spring Wheat-Small Grain, Winter Wheat-Sorghum and Corn-Soy Dry Margin, Subtropical Soy-Cotton, Commercial Timber, Mixed Hardwood and Pasture, Recovered Eastern Forest, Prairie-Sagebrush Rangeland, and Arid and Alpine Sparse Grazing. Expanding to thirteen anthromes maintains these, while bifurcating the commercial timber (softwood, hardwood), rainfed corn-soy (core, fringe) and mixed hardwood and pasture anthromes. Cluster analysis was more successful than hierarchical modeling at producing empirically meaningful anthromes.

Abstract: The accumulation of agricultural waste poses significant agronomic and environmental challenges in tropical smallholder farming systems where organic wastes are still underutilized. This study evaluated the effectiveness of vermicomposting with Eisenia fetida to enhance nutrient recovery and the quality of organic fertilizers generated from agricultural waste. Four substrate treatments—cow dung, chicken manure, and vegetable waste (T2), cow dung and vegetable waste (T3), poultry manure and vegetable waste (T1), and a control group free of earthworms (T4)—were assessed during 60 days. Bulk density, pH, electrical conductivity, organic carbon, total nitrogen, accessible phosphorus and potassium, and the C: N ratio were among the significant physicochemical properties that were investigated. Vermicomposting significantly increased the nutritional content; the C: N ratio decreased from 26.43 (control) to 12.23, suggesting improved compost maturity, and T2 contained the greatest quantities of potassium (1.45%), phosphorus (1.21%), and total nitrogen (2.63%). Another sign of improved mineralization efficiency was a significant decrease in organic carbon during the decomposition phase. Vermicomposting improved nutrient availability, compost maturity, and structural quality in comparison to traditional composting. These results show that vermicomposting is a successful resource recovery technique that increases nutrient availability, improves resource efficiency, supports sustainable and climate-resilient agricultural systems, and turns agricultural waste into useful organic fertilizer.

Abstract: The immature stages and biology of Neoplinthus tigratus porculus (Fabricius, 1801) (Coleoptera: Curculionidae: Molytinae) associated with common hop (Humulus lupulus L.) are described for the first time. Morphology and diagnostic characters of mature larvae and pupae are documented and compared with related Molytinae and selected Cleonini (Lixinae). The mature larva generally fits the diagnostic characters of Molytinae larvae but differs in several traits, particularly the very short endocranial line and the relative length of frontal setae, with fs4 distinctly shorter than fs5. Together with the presence of five frontal setae, this combination represents useful characters for distinguishing the species. The larva and pupa are covered with cuticular asperities. Biological observations show that the species develops mainly within the root collar and roots of Humulus lupulus, where larvae feed internally and older instars overwinter. Infested plants are characterized by swollen and weakened roots, often containing multiple larvae.