Search Results (104)

European bioeconomy policies stress the need for responsible, efficient feedstock use and timely, comprehensive data on ecosystems and bioeconomic activities. This paper addresses the data gap by: (i) providing holistic county-level (sub-NUTS3) biomass maps for the Republic of Ireland (RoI), covering primary feedstocks (PFs) and secondary feedstocks (SFs, i.e., by-products and waste); (ii) identifying feedstock uses during the study period. In total, 221 feedstocks were mapped: 85 solid PFs (approx. 43 million tonnes dry matter (tDM) nationally) and 136 solid SFs (approx. 6 million tDM nationally), plus 6 liquid PFs (approx. 18 thousand million m³ nationally) and 8 liquid SFs (approx. 39 thousand million m³ nationally). The mapping indicates that environmentally sustainable bio-based value chains (BBVCs) requiring large amounts of solid or liquid SF should prioritise processing sites near major feedstock sources in the southeast and southwest of the RoI. The northwest and east coast have the lowest availability, while the west and midlands have the most variety in quantity and type of feedstock. Counties with abundant feedstocks do not necessarily have high feedstock diversity, except for Cork. Granular sub-NUTS3 mapping of quantities and fate provides a powerful foundation for future feedstock strategies and empowers stakeholders to design innovative BBVCs. Full article

Designing robust drinking water treatment schemes for eutrophic sources requires shifting from considering each treatment step separately to considering the full treatment process as a connected system. This study evaluated how treatment configuration and arrangement influence microbial community dynamics, organic carbon removal, and biological stability in a full-scale drinking water treatment plant. A Dutch treatment plant was monitored, operating two parallel lines: one conventional (coagulation, sedimentation, and rapid sand filtration) and one advanced (ion exchange, ceramic microfiltration, and advanced oxidation), both converging into granular activated carbon (GAC) filtration. Microbial and chemical water quality was assessed across treatment stages and seasons. This plant experiences periods of discoloration, taste, and odor issues, and an exceedance of Aeromonas counts in the distribution network. Advanced oxidation achieved a high bacterial cell inactivation (~90%); however, it significantly increased assimilable organic carbon (AOC) (300–900% increase), challenging biological stability. GAC filtration partially reduced AOC levels (from 70 μg Ac-C/L to 12 μg Ac-C/L) but also supported dense (10⁵ cells/mL) and diverse microbial communities (Shannon diversity index 5.83). Moreover, Gammaproteobacteria, which harbor opportunistic pathogens such as Aeromonas, persisted during the treatment. Archaea were highly sensitive to oxidative and physical stress, leading to reduced diversity downstream. Beta diversity analysis revealed that treatment configuration, rather than seasonality, governed the community composition. The findings highlight that treatment arrangement, oxidation, GAC operation, and organic and microbial loads critically influence biological stability. This study proposes integrated strategies to achieve resilient and biologically stable drinking water production when utilizing complex water sources such as eutrophic lakes. Full article

The accelerating pace of global population growth, urbanization, and industrialization is exerting considerable pressure on freshwater resources. In developing countries, where infrastructure constraints often hinder the adoption of advanced treatment technologies, cost-effective and efficient wastewater solutions are essential. Algal–bacterial bioremediation represents a promising, eco-friendly method for removing organic pollutants through biological processes. This study evaluates a hybrid treatment system composed of three ponds: a covered anaerobic pond for organic matter digestion, a microalgal pond equipped with rotating biological contactors (RBCs) that facilitate interactions between heterotrophic bacteria and diatoms, and a final settling pond. Granular activated carbon embedded within the RBC enhances biofilm formation by attracting heterotrophic bacteria, thereby increasing treatment efficiency. Under optimal conditions—10 g of activated carbon and 1.7 d hydraulic retention time—the system achieved removal efficiencies of 95.8% for total suspended solids (TSS), 96.3% for turbidity, 85% for biological oxygen demand (BOD), and 99.9% for Escherichia coli. Bacteriological analysis showed complete removal of fecal coliform and total coliform. The characteristics of the outflow treated wastewater are 3 mg/L, 0.9 NTU, and 3.2 mg/L for TSS, turbidity, and BOD, respectively, while E. coli detection is under detection limit. The treated effluent complies with Category A for the reuse of treated wastewater in the Egyptian code for the reuse of treated municipal wastewater for agricultural purposes, offering a scalable and sustainable solution for wastewater management in resource-constrained regions. Full article

To maintain a high standard of environmental quality, industrial plants must be able to foresee and control the impacts resulting from their activities. One of the most challenging issues for the metallurgical and mining industry when it comes to protecting the environment is the measurement of particulate matter emissions generated by the wind action over the erodible surfaces of stockpiles of granular materials. It is known that the emissive phenomenon starts from a specific threshold friction velocity, which is an inherent characteristic of each material. This parameter can be derived from relationships available in the scientific and technical literature, which, however, only provide qualitative estimations. Therefore, the threshold friction velocity of the specific materials under investigation must be assessed through laboratory tests. This article discusses the results obtained for nine raw materials sampled in a metallurgical plant by applying three different procedures, (1) the sieve-based analysis suggested by U.S. EPA; (2) the laboratory tests performed with an Environmental Wind Tunnel; and (3) the PI-SWERL tests (i.e., tests performed with a Portable In-Situ Wind ERosion Lab), and presents a comparative analysis of the three methods. Findings indicate that the EPA methodology tends to be less accurate than the wind tunnel and PI-SWERL tests, though its accuracy can be slightly improved by adding an additional sieve size for materials with finer aggregates. The wind tunnel and PI-SWERL provided comparable results, with PI-SWERL offering practical advantages due to its portability and an effective synchronization between its data acquisition systems. Full article

Septic wastewater, or septage, represents a specific type of wastewater with a high concentration of organic matter and significant variability in composition, which places increased demand on its treatment. With the increasing pressure for decentralized solutions for small areas with no established sewage infrastructure, technologies that can ensure stable operation of the treatment plant are coming to the fore. This paper compares the technologies used for septic wastewater treatment, i.e., sequencing batch reactor (SBR), membrane bioreactor (MBR), and aerobic granular sludge reactor (AGS). For the AGS technology, a trial run of a selected wastewater collection plant is carried out. Full article

The spatiotemporal dynamics of soil nutrients in the crop row zone are critical determinants of crop yield, necessitating precision fertilization for optimal plant growth. However, previous studies have predominantly focused on plant-available nutrient status at the scale of entire cropping systems, yet a granular understanding of their distribution patterns across precise temporal and spatial dimensions remains limited. Therefore, this study investigated maize–legume intercropping systems to quantify the dynamics of soil alkaline-hydrolyzable nitrogen (AN), available phosphorus (AP), and available potassium (AK) across distinct growth stages, soil depths, and row positions. The experiment comprised five treatments: maize–soybean intercropping, maize–peanut intercropping, and monocultures of maize, soybean, and peanut. Throughout the two-year study, maize–soybean intercropping significantly enhanced the plant height of both maize and soybean relative to their respective monocultures (p < 0.05). In contrast, within the maize–peanut system, intercropping significantly promoted peanut plant height but suppressed stem diameter in both species (p < 0.05); these effects were consistent across both study years. Both systems exhibited a “benefit-sacrifice” pattern, where dry matter was preferentially allocated to maize, thereby increasing total system productivity despite suppressing legume growth. Furthermore, during the mid-to-late growth stages, intercropped maize showed an enhanced capacity for nitrogen uptake from deeper soil layers. In contrast, the alkaline-hydrolyzable nitrogen content in intercropped soybean and peanut remained lower than in their respective monocultures throughout the growth period, with reductions ranging from 8.49% to 34.79%. Intercropping significantly increased the soil available phosphorus content in the root zones of maize, soybean, and peanut compared to their respective monocultures. The available phosphorus content in the 0–20 cm soil layer was consistently higher than in monoculture systems, with a maximum increase of 41.70%. Moreover, intercropping effectively mitigated soil potassium depletion, resulting in a smaller decline in available potassium. This effect was most pronounced in the maize–peanut intercropping pattern within the 20–40 cm soil layer. The distribution of soil available nutrients (N, P, K) was also influenced by drip tape placement. The levels of these nutrients for soybean and peanut were higher at 50 cm from the drip tape than at 30 cm, while for maize, levels were higher at 80 cm than at 40 cm. Intercropping increased the thousand-kernel weight of maize and soybean but decreased that of peanut. Overall, the strategic row configuration optimized the yield performance of both intercropping systems, resulting in land equivalent ratios greater than 1, which indicates distinct yield advantages for both intercropping patterns. Full article

Microplastics (MPs) are emerging pollutants detected in diverse environments and human tissues. Among them, airborne MPs (AMPs) remain poorly characterized due to limited data and methodological inconsistencies. Although regarded as analogous to particulate matter (PM), detailed comparisons with its components are scarce. To address this gap, this study implemented a unified and seasonal protocol for simultaneous measurement of AMPs and PM across three sites in Japan. AMPs were identified using micro-Raman spectroscopy, enabling polymer- and morphology-resolved analysis. A total of 106 AMPs were identified across all sites and seasons. Polyethylene (PE) was consistently dominant, followed by polyethylene terephthalate (PET) and polyamide (PA). Site-specific variation was evident, with certain polymers being relatively more abundant depending on the local environment. Feret diameter analysis showed a modal range of 4–6 μm, with fragments predominating over granular and fibrous particles. Significant correlations between AMP concentrations and PM components were determined, including syringaldehyde (SYAL), tungsten (W), cobalt (Co), and chromium (Cr), suggesting links to local sources, while indicating that AMP dynamics are not always aligned with PM behavior. This study provides one of the first integrated datasets of AMPs and PM components, offering insights into their occurrence, sources, and atmospheric relevance. Full article

Granular jamming grippers have emerged as a versatile solution in soft robotics due to their ability to manipulate objects of various shapes and sizes, earning them the label of “universal grippers”. They are composed of granular material confined within an elastic membrane that conforms to the object like a fluid and solidifies upon vacuum application, enabling a firm grip through friction and grain interlocking. This work provides a systematic review of the state of the art, addressing their physical principles, the influence of grain and membrane properties, performance characterization methods, and applications across diverse fields. Additionally, the main control variables of these grippers closely related to state variables used in control systems are discussed, along with the current knowledge gaps. Finally, five potential directions for future research are proposed. Full article

Anammox is a novel and energy-efficient biological nitrogen removal technology. Enhancing its performance in treating low-strength nitrogen wastewater is essential for expanding its practical applications. In response to challenges such as low nitrogen removal efficiency (NRE), poor operational stability, limited environmental resistance, and the interference of organic compounds commonly found in real wastewater, this study developed a two-stage upflow anammox biofilm reactor system (R1 and R2) enhanced by an Fe²⁺-coupled organic substrate strategy for deep nitrogen removal under low-nitrogen conditions. Results showed that sodium acetate at a chemical oxygen demand (COD) concentration of 40 mg/L provided the greatest enhancement to anammox activity, achieving an average total nitrogen removal efficiency (NRE) of 90.02%. However, the reactor performance was significantly inhibited under higher COD conditions (e.g., COD = 60 mg/L). Under an influent Fe²⁺ concentration of 10 mg/L, the reactors’ NRE increased and then decreased as the COD concentration rose from 0 to 100 mg/L, resulting in the highest efficiency being achieved at an average NRE of 94.11%, observed under 10 mg/L Fe²⁺ coupled with 60 mg/L of COD in the two-stage anammox system. Scanning electron microscopy revealed that the co-addition of Fe²⁺ and organic substrates led to the formation of granular protrusions and pores on the sludge surface, which favored the structural stability of the biomass. At a COD level of 40 mg/L, the contents of extracellular polymeric substances and heme c in anammox biofilm were significantly higher compared to the addition of 10 mg/L Fe²⁺ alone, whereas excessive COD inhibited both indicators. These findings suggest that moderate levels of Fe²⁺ coupled with organic matter can promote anammox activity for deep nitrogen removal, while excessive organics have inhibitory effects. This study provides theoretical support for enhancing nitrogen removal from low-strength wastewater using Fe²⁺ and organic-substrate-assisted anammox processes. Full article

In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time of the interactions. Using GEANT4 simulations of a homogeneous lead tungstate calorimeter with high transverse and longitudinal segmentation, we investigated the discrimination of protons, positive pions, and positive kaons at 100 GeV. The analysis focuses on the impact of calorimeter granularity by progressively merging detector cells and extracting features like energy deposition patterns and timing information. Two machine learning approaches, XGBoost and fully connected deep neural networks, were employed to assess the classification performance across particle pairs. The results indicate that fine segmentation improves particle discrimination, with higher granularity yielding more detailed characterization of energy showers. Additionally, the results highlight the importance of shower radius, energy fractions, and timing variables in distinguishing particle types. The XGBoost model demonstrated computational efficiency and interpretability advantages over deep learning for tabular data structures, while achieving similar classification performance. This motivates further work required to combine high- and low-level feature analysis, e.g., using convolutional and graph-based neural networks, and extending the study to a broader range of particle energies and types. Full article

Benzo[a]pyrene is an important indicator of polycyclic aromatic hydrocarbons pollution that exhibits complex atmospheric dynamics influenced by meteorological factors and suspended particulate matter (SPM). Herein, the factors influencing B(a)P concentration were elucidated by analyzing the monthly environmental data for Kyoto, Japan, from 2001 to 2021 using an improved association rule algorithm. Results revealed that B(a)P concentrations were 1.3–3 times higher in cold seasons than in warm seasons and SPM concentrations were lower in cold seasons. The clustering performance was enhanced by optimizing the K-means method using the sum of squared error. The efficiency and reliability of the traditional Apriori algorithm were enhanced by restructuring its candidate itemset generation process, specifically by (1) generating C₂ exclusively from frequent itemset L₁ to avoid redundant database scans and (2) implementing the iterative pruning of nonfrequent subsets during L_k → C_k+1 transitions, adding the lift parameter, and eliminating invalid rules. Strong association rules revealed that B(a)P concentrations ≤ 0.185 ng/m³ were associated with specific meteorological conditions, including humidity ≤ 58%, wind speed ≥ 2 m/s, temperature ≥ 12.3 °C, and pressure ≤ 1009.2 hPa. Among these, changes in pressure had the most substantial impact on the confidence of the association rules, followed by humidity, wind speed, and temperature. Under the influence of high SPM concentrations, favorable meteorological conditions further accelerated pollutant dispersion. B(a)P concentration increased with increasing pressure, decreasing temperature, and decreasing wind speed. Principal component analysis confirmed the robustness and accuracy of our optimized association rule approach in quantifying complex, nonlinear relationships, while providing granular, interpretable insights beyond the traditional methods. Full article

Magnetic monopoles, though elusive as elementary particles, emerge as quantum excitations in granular quantum materials. Under certain conditions, they can undergo Bose condensation, leading to the formation of a novel state of matter known as the superinsulator. In this state, charge carriers, Cooper pairs and anti-Cooper pairs, are bound together by an electric flux string, forming neutral electric pions. This confinement mechanism results in an infinite resistance that persists even at finite temperatures. Superinsulators behave, thus, as dual superconductors. Full article

This study aims to determine the optimal frequency for monitoring airborne pollutants in densely populated urban areas to effectively capture their temporal variations. While environmental organizations worldwide typically update air quality data hourly, there is no global consensus on the ideal monitoring frequency to adequately resolve pollutant (particulate matter) time series. By applying temporal variogram analysis to particulate matter (PM) data over time, we identified specific measurement intervals that accurately reflect fluctuations in pollution levels. Using January 2023 air quality data from the Joppa neighborhood of Dallas, Texas, USA, temporal variogram analysis was conducted on three distinct days with varying ${\mathrm{PM}}_{2.5}$ (particulate matter of size ≤ $2.5 \mathsf{\mu }\mathrm{m}$ in diameter) pollution levels. For the most polluted day, the optimal sampling interval for ${\mathrm{PM}}_{2.5}$ was determined to be 12.25 s. This analysis shows that highly polluted days are associated with shorter sampling intervals, highlighting the need for highly granular observations to accurately capture variations in PM levels. Using the variogram analysis results from the most polluted day, we trained machine learning models that can predict the sampling time using meteorological parameters. Feature importance analysis revealed that humidity, temperature, and wind speed could significantly impact the measurement time for ${\mathrm{PM}}_{2.5}$. The study also extends to the other size fractions measured by the air quality monitor. Our findings highlight how local conditions influence the frequency required to reliably track changes in air quality. Full article

The use of low-cost sensors has dramatically increased in recent years in all engineering sectors. In the buildings and automotive field, low-cost sensors open very interesting perspectives, because they allow one to monitor temperature and humidity distributions together with air quality in a widespread and punctual way and allow for the control of all energy parameters. The main issue remains the validation of the measurements. In this work, we propose an innovative approach to verify the measurements given by some low-cost systems built ad hoc for automotive applications. Two independent low-cost measurement systems were set to measure Particulate Air Matter (PM) concentration, TVOC concentration, CO₂ concentration, formaldehyde concentration, air temperature, relative humidity, pressure, air flow velocity, and GPS position. These systems were calibrated for PM concentration measurement by comparison with standard and certified sensors used by the regional authority of the Emilia-Romagna region (ARPAE, Italy) for characterizing air quality. The duration of the analysis, three days, is not representative of the diverse environmental conditions that occur across different seasons. However, the innovation of this approach lies in both the in-field comparison of low-cost and high-quality sensors and the use of proper conversion approaches for mass concentration measurements. A quantitative analysis of the sensors’ performance is given, with a focus on the effects of time granularity, relative humidity, mass conversion from particle counts, and size detection response. The results show that the low-cost sensors’ measurements of air temperature, relative humidity, and particle number concentration are in good agreement with high-quality sensors’ measurements, with a strong impact of relative humidity on performance indicators. Overall, good quality and consistency of the data among the sensors were achieved. Full article

Infilled joints or faults are often subjected to long-term stable shear forces, and nature surface processes of normal unloading can change the frictional balance. Therefore, it is essential to study the sliding behavior of such granular materials under such unloading conditions, since they are usually the filling matter. We conducted two groups of normal unloading direct shear tests considering two variables: unloading rate and the magnitude of constant shear force. Dry sands may slide discontinuously during normal unloading, and the slip velocity does not increase uniformly with unloading time. Due to horizontal particle interlacing and normal relaxation, there will be sliding velocity fluctuations and even temporary intermissions. At the stage of sliding acceleration, the normal force decreases with a higher unloading rate and increases with a larger shear force at the same sliding velocity. The normal forces obtained from the tests are less than those calculated by Coulomb’s theory in the conventional constant-rate shear test. Under the same unloading rate, the range of apparent friction coefficient variation is narrower under larger shear forces. This study has revealed the movement patterns of natural granular layers and is of enlightening significance in the prevention of corresponding geohazards. Full article