Search Results (172)

Ammonia (NH₃) emissions affect the environment, climate and human health and originate mainly from agricultural sources like synthetic nitrogen fertilizers. Accurate and replicable measurements of NH₃ emissions are crucial for research, inventories and evaluation of mitigation measures. There exist specific application limitations of NH₃ emission measurement techniques and a high variability in method performance between studies, in particular from small plots. Therefore, the aim of this study was the assessment of measurement methods for ammonia emissions from replicated small plots. Methods were evaluated in 18 trials on six sites in Germany (2021–2022). Urea was applied to winter wheat as an emission source. Two small-plot methods were employed: inverse dispersion modelling (IDM) with atmospheric concentrations obtained from Alpha samplers and the dynamic chamber Dräger tube method (DTM). Cumulative NH₃ losses assessed by each method were compared to the results of the integrated horizontal flux (IHF) method using Alpha samplers (Alpha IHF) as a micrometeorological reference method applied in parallel large-plot trials. For validation, Alpha IHF was also compared to IHF/ZINST with Leuning passive samplers. Cumulative NH₃ emissions assessed using Alpha IHF and DTM showed good agreement, with a relative root mean square error (rRMSE) of 11%. Cumulative emissions assessed by Leuning IHF/ZINST deviated from Alpha IHF, with an rRMSE of 21%. For low-wind-speed and high-temperature conditions, NH₃ losses detected with Alpha IDM had to be corrected to give acceptable agreement (rRMSE 20%, MBE +2 kg N ha⁻¹). The study shows that quantification of NH₃ emissions from small plots is feasible. Since DTM is constrained to specific conditions, we recommend Alpha IDM, but the approach needs further development. Full article

Ammonia (NH₃) is one of the characteristic gases used to detect food spoilage. In this study, the 10 wt% Ag-NiFe₂O₄ nanocomposite was synthesized via the hydrothermal method. Characterization results from SEM, XRD, and XPS analyzed the microstructure, elemental composition, and crystal lattice features of the composite, confirming its successful fabrication. Under the optimal working temperature of 280 °C, the composite exhibited excellent gas-sensing properties towards NH₃. The 10 wt% Ag-NiFe₂O₄ sensor demonstrates rapid response and recovery, as well as high sensitivity, towards 30 ppm NH₃, with response and recovery times of merely 3 s and 9 s, respectively, and a response value of 4.59. The detection limit is as low as 0.1 ppm, meeting the standards for food safety detection. Additionally, the sensor exhibits good short-term repeatability and long-term stability. Additionally, density functional theory (DFT) simulations were conducted to investigate the gas-sensing advantages of the Ag-NiFe₂O₄ composite by analyzing the electron density and density of states, thereby providing theoretical guidance for experimental testing. This study facilitates the rapid detection of food spoilage and promotes the development of portable food safety detection devices. Full article

Ammonia (NH₃) detection in liquids and biological fluids is essential for monitoring environmental contamination and industrial processes, ensuring food safety, and diagnosing health conditions. Existing detection techniques are often unsuitable for point-of-care (POC) use due to limitations including complex sample handling, lack of portability, and poor compatibility with miniaturized systems. This study introduces a proof-of-concept for a compact, portable device tailored for POC detection of gaseous ammonia released from liquid samples. The device combines a polyaniline (PANI)-based chemoresistive sensor with interdigitated electrodes and a resistance readout circuit, enclosed in a gas-permeable hydrophobic membrane that permits ammonia in the vapor phase only to reach the sensing layer, ensuring selectivity and protection from liquid interference. The ink formulation was optimized. PANI nanoparticle suspension exhibited a monomodal, narrow particle size distribution with an average size of 120 nm and no evidence of larger aggregates. A key advancement of this device is its ability to limit the impact of water vapor, a known source of interference in PANI-based sensors, while maintaining a simple sensor design. A tailored signal processing strategy was implemented, extracting the slope of resistance variation over time as a robust metric for ammonia quantification. The sensor demonstrated reliable performance across a concentration range of 1.7 to 170 ppm with strong logarithmic correlation (R² = 0.99), and very good linear correlations in low (R² = 0.96) and high (R² = 0.97) subranges. These findings validate the feasibility of this POC platform for sensitive, selective, and practical ammonia detection in clinical and environmental applications. Full article

Photoacoustic spectroscopy (PAS) has become a valuable technique for trace gas detection due to its high sensitivity and potential for miniaturization. This study presents the development and evaluation of a near-infrared PAS system using a 1532 nm semiconductor laser and a multipass cell (MPC) designed to enhance the optical path and thereby improve the detection of ammonia (NH₃). The minimum detection limit was determined to be 770 ppb, with a normalized noise equivalent absorption (NNEA) coefficient of 1.07 × 10⁻⁸ W cm⁻¹ Hz⁻¹/². While competitive with similar PAS systems, these results indicate that mid-infrared technologies still offer superior detection thresholds. The findings suggest that while this near-infrared setup may not yet match the sensitivity of systems using quantum cascade lasers or QEPAS, it offers notable advantages in terms of simplicity, cost, and potential for field deployment. The system’s configuration makes it a viable and efficient tool for industrial gas monitoring and real-time environmental applications, with future improvements likely to come from transitioning to the mid-infrared region and advancing laser stabilization and miniaturization techniques. Full article

Ammonia (NH₃) is a promising carbon-free marine fuel that is aligned with the International Maritime Organization’s (IMO) decarbonization targets. However, its high toxicity and flammability pose serious explosion hazards, particularly in confined fuel preparation spaces. This study investigates the influence of the ignition source location on the explosion characteristics of ammonia within an ammonia fuel preparation room using computational fluid dynamics (CFD) simulations via the FLACS platform. Nineteen ignition scenarios are established along the X-, Y-, and Z-axes. Key parameters, such as the maximum overpressure, pressure rise rate, reduction rate of flammable gas, ignition detection time, and spatial–temporal distributions of temperature and combustion products, are evaluated. The results show that the ignition location plays a critical role in the explosion dynamics. Ceiling-level ignition (Case 19) produced the highest overpressure (4.27 bar) and fastest pressure rise rate (2.20 bar/s), indicating the most hazardous condition. In contrast, the forward wall ignition (Case 13) resulted in the lowest overpressure (3.24 bar) and limited flame propagation. These findings provide essential insights into the risk assessment and safety design of ammonia-fueled marine systems. Full article

Unmanned aerial vehicles, also termed as unarmed aerial vehicles, are used for various purposes in and around the environment, such as delivering things, spying on opponents, identification of aerial images, extinguishing fire, spraying the agricultural fields, etc. As there are multi-functions in a single UAV model, it can be used for various purposes as per the user’s requirement. The UAVs are used for faster communication of identified information, entry through the critical atmospheres, and causing no harm to humans before entering a collapsed path. In relation to the above discussion, a UAV system is designed to classify and transmit information about the atmospheric conditions of the environment to a central controller. The UAV is equipped with advanced sensors that are capable of detecting air pollutants such as carbon monoxide (CO), carbon dioxide (CO₂), methane (CH₄), ammonia (NH₃), hydrogen sulfide (H₂S), etc. These sensors present in the UAV model monitor the quality of air, time-to-time, as the UAV navigates through different areas and transmits real-time data regarding the air quality to a central unit; this data includes detailed information on the concentrations of different pollutants. The central unit analyzes the data that are captured by the sensor and checks whether the quality of air meets the atmospheric standards. If the sensed levels of pollutants exceed the thresholds, then the system present in the UAV triggers a warning alert; this alert is communicated to local authorities and the public to take necessary precautions. The developed UAV is furnished with cameras which are used to capture real-time images of the environment and it is processed using the YOLO V3 algorithm. Here, the YOLO V3 algorithm is defined to identify the context and source of pollution, such as identifying industrial activities, traffic congestion, or natural sources like wildfires. Full article

This study presents a non-invasive approach to monitoring post-harvest fruit quality by applying CO₂ laser photoacoustic spectroscopy (CO₂LPAS) to study the respiration of “Conference” pears from local and commercially stored (supermarket) sources. Concentrations of ethylene (C₂H₄), ethanol (C₂H₆O), and ammonia (NH₃) were continuously monitored under shelf-life conditions. Our results reveal that ethylene emission peaks earlier in supermarket pears, likely due to post-harvest treatments, while ethanol accumulates over time, indicating fermentation-related deterioration. Significantly, ammonia levels increased during the late stages of senescence, suggesting its potential role as a novel biomarker for fruit degradation. The application of CO₂LPAS enabled highly sensitive, real-time detection of trace gases without damaging the fruit, offering a powerful alternative to traditional monitoring methods. Additionally, artificial intelligence (AI) models, particularly convolutional neural networks (CNNs), were explored to enhance data interpretation, enabling early detection of ripening and spoilage patterns through volatile compound profiling. This study advances our understanding of post-harvest physiological processes and proposes new strategies for improving storage and distribution practices for climacteric fruits. Full article

The environmental impact of livestock by-products presents significant challenges, particularly in regions with intensive farming and high pollution levels, such as the Po Valley. This study evaluated the effectiveness of biochar and wood vinegar in reducing gaseous emissions during the laboratory-scale storage of livestock slurry, digestate, and liquid fractions. Various types and applications of biochar, both with and without wood vinegar, were tested across three independent incubation periods of varying durations. The results showed that ammonia (NH₃) emissions were lower from slurry compared to raw digestate and the liquid fraction, while methane (CH₄) emissions exhibited the opposite trend. Pyrolysis biochar effectively reduced NH₃ emissions by 47% on average when applied as a 5 cm surface layer. However, its effectiveness was inconsistent when mixed into the material or when produced via gasification. Biochar activated with wood vinegar significantly reduced NH₃ emissions from both slurry and digestate by 61%, but it also led to increased emissions of CH₄ and CO₂. Nitrous oxide (N₂O) emissions were detected only after at least one month of incubation and were higher when biochar was used as a cover alone or when activated with wood vinegar. Overall, applying biochar as a cover and activating it with wood vinegar proved effective in reducing NH₃ emissions during the storage of livestock by-products. However, the effectiveness varied significantly depending on the type of biochar and its method of application, particularly with respect to CH₄ emissions, highlighting the need for careful consideration when using wood vinegar-activated biochar. Full article

Ammonia (NH₃) is a common agricultural gas, and its accurate detection is critical to agricultural production. In this study, nano-CuO/CeO₂ composites were prepared to achieve a wide range of ammonia detection at room temperature. Characterization data verified the composite heterojunction structure of CuO/CeO₂, which demonstrates an outstanding large specific surface area for ammonia detection. It provides more active sites for NH₃ molecules, which brings a very high response to ammonia (70.3% @100 ppm NH₃), a large detection range (0.5–200 ppm NH₃), and a fast response/recovery time (13 s/17 s @20 ppm NH₃). Systematic testing showed that the nano-CuO/CeO₂ composites also exhibit excellent extended-term stability and selectivity. Further studies showed that the p-n heterojunction structure of CuO/CeO₂ allowed the composite to retain its gas-sensitive properties to ammonia, in addition to the improved ammonia-detection range of the composite based on the synergistic effect of these two materials. The mechanism of CuO/CeO₂ heterojunction nanocomposites towards ammonia detection was also elucidated from a microscopic perspective at the molecular level. Finally, a triboelectric nanogenerator (TENG) that can be driven by wind power has been prepared, upon which the feasibility of the combination of the TENG and the ammonia sensor to realize environmental monitoring was investigated. Full article

Taranakite is a mineral consisting of a hydrated layered aluminum phosphate, with the formula K₃Al₅(PO₃OH)₆(PO₄)₂·18H₂O; its structure belongs to the R-3C group. If the mineral grows in an environment rich in bat and bird guano, the high nitrogen guano content induces the intercalation of NH₄⁺ into the structure, replacing the potassium ion. The thermal decomposition of guano-derived taranakite releases water and ammonia. The aim of this work is to confirm the presence of ammonium in the guano-derived taranakite. Thermogravimetric analysis (TGA) was performed on taranakite collected in Pollera Cave (Liguria), and the gases evolved during its decomposition were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. All the samples were characterized before and after thermal analysis by means of powder X-ray diffractometry (PXRD) and scanning electron microscopy (SEM). The release of crystallization water occurs at a temperature below 200 °C; further ammonia can be detected above 200 °C. Full article

In this study, an in situ electrochemical modulation method based on an ultramicro interdigitated array electrode (UIAE) sensor chip was developed for the detection of ammonia nitrogen (NH₃-N) in neutral aqueous solutions. One comb of the UIAE was used as the working electrode for both the modulating and sensing functions, while the other comb was used as the counter electrode. Utilizing its enhanced mass transfer and proximity effects, the feasibility of in situ modulation of the solution environment near the UIAE chip to generate an electrochemical response for NH₃-N was investigated using electrochemical methods. The proposed method enhances the concentration of hydroxide ions and active chloride in the local solution near the sensor chip. These reactive species play a key role in improving the sensor’s electrocatalytic oxidation capability toward ammonia nitrogen, facilitating the sensitive detection of ammonia nitrogen in neutral environments. A linear relationship was displayed, ranging from 0.15–2.0 mg/L (as nitrogen) with a sensitivity of 3.7936 µA·L·mg⁻¹ (0.0664 µA µM⁻¹ mm⁻²), which was 2.45 times that in strong alkaline conditions without modulation. Additionally, the relative standard deviation of the measurement remained below 2.9% over five days of repeated experiments, indicating excellent stability. Full article

Malodorous gases—particularly hydrogen sulfide (H₂S), ammonia (NH₃), and volatile sulfur compounds (VSCs)—significantly degrade water quality, threaten public health, and disrupt ecosystems. Their production stems from microbial activity, nutrient overload, and industrial discharges, often magnified by low dissolved oxygen. This review integrates current insights into the microbial sulfur and nitrogen cycles to elucidate how these gases form, and surveys advances in detection technologies such as gas chromatography and laser-based sensors. We also assess diverse mitigation methods—including biotechnological approaches (e.g., biofilters, biopercolators), physicochemical treatments, and chemical conversion (Claus Process)—within relevant regulatory contexts in Colombia and worldwide. A case study of the Bogotá River exemplifies how unmanaged effluents and eutrophication perpetuate odor issues, underscoring the need for integrated strategies that reduce pollution at its source, restore ecological balance, and employ targeted interventions. Overall, this review highlights innovative, policy-driven solutions and collaborative efforts as pivotal for safeguarding aquatic environments and surrounding communities from the impacts of odorous emissions. Full article

This study presents the fabrication and characterization of highly selective, room-temperature gas sensors based on ternary zinc oxide–molybdenum disulfide–titanium dioxide (ZnO-MoS₂-TiO₂) nanoheterostructures. Integrating two-dimensional (2D) MoS₂ with oxide nano materials synergistically combines their unique properties, significantly enhancing gas sensing performance. Comprehensive structural and chemical analyses, including scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Raman spectroscopy, and Fourier transform infrared spectroscopy (FTIR), confirmed the successful synthesis and composition of the ternary nanoheterostructures. The sensors demonstrated excellent selectivity in detecting low concentrations of nitrogen dioxide (NO₂) among target gases such as ammonia (NH₃), methane (CH₄), and carbon dioxide (CO₂) at room temperature, achieving up to 58% sensitivity at 4 ppm and 6% at 0.1 ppm for NO₂. The prototypes demonstrated outstanding selectivity and a short response time of approximately 0.51 min. The impact of light-assisted enhancement was examined under 1 mW/cm² weak ultraviolet (UV), blue, yellow, and red light-emitting diode (LED) illuminations, with the blue LED proving to deliver the highest sensor responsiveness. These results position ternary ZnO-MoS₂-TiO₂ nanoheterostructures as highly sensitive and selective room-temperature NO₂ gas sensors that are suitable for applications in environmental monitoring, public health, and industrial processes. Full article

Water quality in aquaculture has a direct impact on the growth and development of the aquatic organisms being cultivated. The rapid, accurate and comprehensive control of water quality in aquaculture ponds is crucial for the management of aquaculture water environments. Traditional water quality monitoring methods often use manual sampling, which is not only time-consuming but also reflects only small areas of water bodies. In this study, unmanned aerial vehicles (UAV) equipped with high-spectral cameras were used to take remote sensing images of experimental aquaculture ponds. Concurrently, we manually collected water samples to analyze critical water quality parameters, including total nitrogen (TN), ammonia nitrogen (NH₄⁺-N), total phosphorus (TP), and chemical oxygen demand (COD). Regression models were developed to assess the accuracy of predicting these parameters based on five preprocessing techniques for hyperspectral image data (L2 norm, Savitzky–Golay, first derivative, wavelet transform, and standard normal variate), two spectral feature selection methods were utilized (successive projections algorithm and competitive adaptive reweighted sampling), and three machine learning algorithms (extreme learning machine, support vector regression, and eXtreme gradient boosting). Additionally, a deep learning model incorporating the full spectrum was constructed for comparative analysis. Ultimately, according to the determination coefficient (R²) of the model, the optimal prediction model was selected for each water quality parameter, with R² values of 0.756, 0.603, 0.94, and 0.858, respectively. These optimal models were then utilized to visualize the spatial concentration distribution of each water quality parameter within the aquaculture district, and evaluate the rationality of the model prediction by combining manual detection data. The results show that UAV hyperspectral technology can rapidly reverse the spatial distribution map of water quality of aquaculture ponds, realizing rapid and accurate acquisition for the quality of aquaculture water, and providing an effective method for monitoring aquaculture water environments. Full article

Di-isopropyl methyl phosphonate (DIMP) has no major commercial uses but is a by-product or a precursor in the synthesis of the nerve agent sarin (GB). Also, DIMP is utilized as a simulant compound for the chemical warfare agents sarin and soman in order to test and calibrate sensitive IMS instrumentation that warns against the deadly chemical weapons. DIMP was measured from 2 ppb_v (15 μg m⁻³) to 500 ppb_v in the air using a pocket-held ToF ion mobility spectrometer, model LCD-3.2E, with a non-radioactive ionization source and ammonia doping in positive ion mode. Excellent sensitivity (LoD of 0.24 ppb_v and LoQ of 0.80 ppb_v) was noticed; the linear response was up to 10 ppb_v, while saturation occurred at >500 ppb_v. DIMP identification by IMS relies on the formation of two distinct peaks: the monomer M·NH₄⁺, with a reduced ion mobility K₀ = 1.41 cm² V⁻¹ s⁻¹, and the dimer M₂·NH₄⁺, with K₀ = 1.04 cm² V⁻¹ s⁻¹ (where M is the DIMP molecule); positive reactant ions (Pos RIP) have K₀ = 2.31 cm² V⁻¹ s⁻¹. Quantification of DIMP at trace levels was also achieved by GC-MS over the concentration range of 1.5 to 150 μg mL⁻¹; using a capillary column (30 m × 0.25 mm × 0.25 μm) with a TG-5 SilMS stationary phase and temperature programming from 60 to 110 °C, DIMP retention time (RT) was ca. 8.5 min. The lowest amount of DIMP measured by GC-MS was 1.5 ng, with an LoD of 0.21 μg mL⁻¹ and an LoQ of 0.62 μg mL⁻¹ DIMP. Our results demonstrate that these methods provide robust tools for both on-site and off-site detection and quantification of DIMP at trace levels, a finding which has significant implications for forensic investigations of chemical agent use and for environmental monitoring of contamination by organophosphorus compounds. Full article