Search

It is of great significance to understand the particle distribution characteristics at different heights to effectively control particle pollution. Based on fractal theory, the fractal dimension of outdoor particles in a high-rise building in Xi'an and its relationship with the concentration of particles with different particle sizes are discussed and analyzed in this paper. The results indicate that the atmosphere in Xi'an is mainly composed of fine particles and that the average proportion of particles ranging from 0 to 1.0 µm is approximately 99.885% of the total particulates. The fractal dimension of particles in the atmosphere at different heights ranges from 5.014 to 5.764, with an average fractal dimension of 5.456. In summer, the fractal dimension of the outdoor particles on the 17th floor was the largest, at 5.764. The fractal dimension in summer is relatively high, being 0.158 higher than that in winter on average. The larger the fractal dimension, the higher the proportion of fine particles. In addition, the fractal dimension can characterize the adsorption of toxic and harmful gases by particles well. It provides parameter support for understanding particle distribution and the effective control of atmospheric particles at different heights and application values. [ABSTRACT FROM AUTHOR]

Background: To produce jasmine tea of excellent quality, it is crucial to select jasmine flowers at their optimal growth stage during harvesting. However, achieving this goal remains a challenge due to environmental and manual factors. This study addresses this issue by classifying different jasmine flowers based on visual attributes using the YOLOv7 algorithm, one of the most advanced algorithms in convolutional neural networks. Results: The mean average precision (mAP value) for detecting jasmine flowers using this model is 0.948, and the accuracy for five different degrees of openness of jasmine flowers, namely small buds, buds, half‐open, full‐open and wiltered, is 87.7%, 90.3%, 89%, 93.9% and 86.4%, respectively. Meanwhile, other ways of processing the images in the dataset, such as blurring and changing the brightness, also increased the credibility of the algorithm. Conclusion: This study shows that it is feasible to use deep learning algorithms for distinguishing jasmine flowers at different growth stages. This study can provide a reference for jasmine production estimation and for the development of intelligent and precise flower‐picking applications to reduce flower waste and production costs. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

[Display omitted] • AC@Cu0 was fabricated for reactive adsorption of H 2 S. • The highest adsorption capacity reached 77.7 mg/g under 60% relative humidity. • Element sulfur, sulfide and sulfate were produced by the catalytic oxidation and reactive adsorption of AC@Cu0. • The desulfurization mechanisms under various atmospheres were explored. The reactive adsorption of H 2 S under different atmospheres is of great significance to protect the staff on site from exposure risks of polluted gases. The Cu0-loaded activated carbon (AC@Cu0) adsorbent was synthesized and characterized, which was used to dynamic adsorption of H 2 S under ambient temperature and different relative humidity (RH). When RH was 60%, the highest adsorption capacity reached 77.7 mg/g. The desulfurization products comprised element sulfur, sulfide and sulfate by the catalytic oxidation and reactive adsorption of AC@Cu0. In addition to the chemical nature of AC@Cu0, the structural properties (surface area and pore volume) also play a crucial role in adsorption. DFT calculations were used to reveal the effect of Cu and H 2 O in the desulfurization process. The adsorption energy of H 2 S on activated carbon was improved, and the energy barrier of the dissociation of H 2 S was decreased when Cu was introduced under the moist atmosphere. Density of states and the interaction region indicator (IRI) analyses indicated that the strong attractive force was formed between Cu and S. According to the results of DFT calculations, the presence of Cu and H 2 O could promote the adsorption of H 2 S. Combined with the experimental and calculation results, possible desulfurization mechanisms were proposed, which provides novel insights for the efficient removal of H 2 S by adsorptive desulfurization, especially under moist conditions. [ABSTRACT FROM AUTHOR]

Active sampling is a dependable approach for gaseous pollutants monitoring, offering high accuracy and precision that is unaffected by environmental factors such as wind and temperature in comparison to passive sampling. To measure long-term average concentrations while minimizing the use of materials, a reduced sampling rate is necessary. Thus, this study aims to develop a novel low sampling rate (down to 1 mL/min) and cost-efficient active sampler (LASP) for medium/long-term monitoring of gaseous pollutants. The LASP mainly consisted of a syringe pump, a Y-shaped fitting with two one-way valves, and a control unit for intermittent operation. Results showed that LASP can obtain a sampling rate of less than 1 mL/min and sampling rate exhibited a high level of stability. Daily average concentrations measurements for nitrogen dioxide and formaldehyde by LASP had normalized mean biases of 2.8% and 5.2%, respectively. These numbers were − 5.8% and 6.1% for weekly-average samplings. This study demonstrated applications of LASP in real outdoor (daily-average) and indoor (weekly-average) air quality measurements. It worked well with low noise levels, and without interfering with occupants' daily activities. LASP can assist in improving our ability to monitor air quality and pollutants emissions, thereby supporting health research and policy development. Gaseous air pollution is an important hazardous factor threatening human health. Medium/long-term air quality monitoring is essential for outdoor and indoor air quality assessment and control. However, air sampler for medium/long-term sampling is lacking. This study developed a novel low sampling rate and cost-efficient active sampler and applied it to medium/long-term air sampling. The sampler can work at a sampling rate of less than 1 mL/min. This technology provides a feasible strategy for medium/long-term monitoring of gaseous air pollutants in both environments and emission hotspots. [Display omitted] • LASP realized low sampling rates by automatic intermittent operation. • LASP can reach a sampling rate of less than 1 mL/min. • Accuracy of LASP for single sampling durations of up to one week was satisfactory. • LASP worked well, generated low noise, and did not disturb occupants' activities. • LASP can improve air monitoring ability and reduce long-term monitoring costs. [ABSTRACT FROM AUTHOR]