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The analysis of greenhouse gas emission characteristics on urban roads is of great significance for understanding the sources and sinks of urban greenhouse gases and their changing patterns. Based on tunable diode laser derivative absorption spectroscopy technology, which features high resolution, high sensitivity, and fast response, a vehicle-mounted system capable of simultaneously detecting CO2 and CH4 has been developed. The system has a response time of 0.38 s, with detection sensitivities of 5 ppb for CH4 and 0.2 ppm for CO2, power consumption of approximately 4.8 W, a weight of less than 3 kg, and dimensions of 255 mm × 275 mm × 85 mm. Using this system, monitoring campaigns were conducted on the same road in Beijing, running north–south, during different time periods in April and June 2023. The results show that there is little correlation between changes in CO2 and CH4 concentrations on the road, and these gas concentrations exhibit different influencing factors and spatiotemporal characteristics. The CO2 concentration on the road is primarily related to the degree of traffic congestion and does not exhibit significant seasonal variations. The average CO2 concentration measured on the road is much higher than the global average CO2 concentration during the same period. On the other hand, the CH4 concentration on the road is not strongly correlated with traffic congestion but is closely related to the leakage of methane from specific emission wells or covers. The CH4 concentration is higher in the morning, gradually decreases as the sun rises, and then increases again after sunset. The CH4 concentration measured at night in June is significantly lower than that in April, reflecting some seasonal variation. The CH4 concentration on the Beijing urban road is slightly higher than the global average CH4 concentration during the same period. The vehicle-mounted experiments verified the feasibility of using this self-developed system for vehicle-mounted detection of greenhouse gas concentrations on urban roads. The research results can provide data for analyzing the spatial pattern of regional carbon sources and sinks. [ABSTRACT FROM AUTHOR]

The efficient identification of rice pests and diseases is crucial for preventing crop damage. To address the limitations of traditional manual detection methods and machine learning-based approaches, a new rice pest and disease recognition model based on an improved YOLOv7 algorithm has been developed. The model utilizes the lightweight network MobileNetV3 for feature extraction, reducing parameterization, and incorporates the coordinate attention mechanism (CA) and the SIoU loss function for enhanced accuracy. The model has been tested on a dataset of 3773 rice pest and disease images, achieving an accuracy of 92.3% and an mAP@.5 of 93.7%. The proposed MobileNet-CA-YOLO model is a high-performance and lightweight solution for rice pest and disease detection, providing accurate and timely results for farmers and researchers. [ABSTRACT FROM AUTHOR]

To achieve the CO2 emission control as the urgent task of Carbon Peak and Carbon Neutrality, the CO2 desorption experiments were performed with a new tri-solvent MEA-EAE(2-(ethylamino)ethanol)-DEEA(N, N-diethylethanolamine) with five solid acid catalysts: blended catalysts of γ-Al2O3/H-ZSM-5 = 2:1, H-Beta (Hβ), H-mordenite, HND-8, and HND-580 as H2SO4 replacement. A series of sets of experiments were performed in a typical recirculation process by means of both heating directly at 363 K and temperature programming method within 303~358 K to evaluate the key parameters: average desorption rate (ADR), heat duty (HD), and desorption factors (DF). After analyses, the 0.5 + 2 + 2 mol/L MEA-EAE-DEEA with catalyst HND-580 possessed the best CO2 desorption act at relatively low amine regeneration temperatures with minimized HD and the biggest DF among the other catalysts. Comparing with other tri-solvents + catalysts studied, the order of DF was MEA-BEA-DEEA + HND-8 > MEA-EAE-DEEA + HND-580 ≈ MEA-EAE-DEEA + HND-8 > MEA-EAE-AMP + HND-8. This combination has its own advantage of big cyclic capacity and wider operation region of CO2 loading range of lean and rich amine solution (αlean~αrich), which is applicable in an industrial amine scrubbing process of a pilot plant in carbon capture. [ABSTRACT FROM AUTHOR]

The traditional detection method of CO2 concentration in seed respiration has defects such as low detection accuracy, low detection efficiency, and inability to monitor in real time. In order to solve these problems, we report a seed respiration CO2 detection system based on wavelength modulation spectroscopy (WMS) techniques in tunable diode laser absorption spectroscopy (TDLAS). This system uses a 2004 nm distributed feedback (DFB) laser as the light source, and a double-layer seed respiration device (about 1.5 L) is designed based on Herriott cell with an effective optical path of about 21 meters. Then, the second harmonic (2f) signal is extracted by the wavelength modulation method for CO2 concentration inversion. When the ambient temperature and pressure changes greatly, the corrected 2f signal is used for CO2 concentration inversion to improve the accuracy. A series of verification and comparison experiments have proved that the seed respiration CO2 detection system has the advantages of strong stability, high sampling frequency, and high detection accuracy. Finally, we used the developed system to measure the respiration intensity and respiration rate of 1 g corn seeds. The respiration intensity curves and respiration rate change details show that the seed respiration CO2 detection system is more suitable for a small amount of seeds than nondispersive infrared (NDIR) CO2 sensor and gas chromatography in real-time monitoring of the breathing process. [ABSTRACT FROM AUTHOR]

Sulfamethoxazole is a widely—used antibiotic with high water solubility and low biodegradability, which was considered a refractory environmental pollutant. Hence, a series of functionalized hybrids uniting Cu3P with TiN were prepared. The Cu3P/TiN—x composites remarkably removed the sulfamethoxazole in solution compared with Cu3P and TiN alone. All the as—prepared Cu3P/TiN—x hybrids integrated the advantages of strong adsorption and photocatalysis and achieved removal rates above 70% of sulfamethoxazole. Among the composites, the Cu3P/TiN—2 with a 1:1 molar ratio of Cu: Ti reached a 90% removal rate under dark adsorption for 30 min and subsequent photodegradation for 120 min. The enhanced performance of the Cu3P/TiN—x composites is attributed to the introduced flocculent TiN with a large specific surface area and high conductivity that provide more reactive sites and high electron transferability. Meanwhile, the strong corrosion resistance and chemical stability were also beneficial to the improved performance. Cycling experiments further demonstrate the stability and reliability of the composites. In addition, the capture experiments indicated that the superoxide radical (·O2−) and hydroxyl radical (·OH) played a major role in sulfamethoxazole degradation. [ABSTRACT FROM AUTHOR]