Numerical Simulation of Magnesium Dust Dispersion and Explosion in 20 L Apparatus via an Euler–Lagrange Method

Computational fluid dynamics (CFD) was used to investigate the explosion characteristics of a Mg/air mixture in a 20 L apparatus via an Euler–Lagrange method. Various fluid properties, namely pressure field, velocity field, turbulence intensity, and the degree of particle dispersion, were obtained and analyzed. The simulation results suggested that the best delayed ignition time was 60 ms after dust dispersion, which was consistent with the optimum delayed ignition time adopted by experimental apparatus. These results indicate that the simulated Mg particles were evenly diffused in the 20 L apparatus under the effect of the turbulence. The simulations also reveal that the pressure development in the explosion system can be divided into the pressure rising stage, the maximum pressure stage, and pressure attenuation stage. The relative error of the maximum explosion pressure between the simulation and the experiments is approximately 1.04%. The explosion model provides reliable and useful information for investigating Mg explosions.

Effects of moisture content on explosion characteristics of incense dust in incense factory

Incense is an indispensable material with religion and life in Asia. It is also a bridge of cultural expression and inheritance. Because the operating environment concentration of dust generated during the production process is considerable, most of the research pertaining to the hazard of incense factories has investigated air pollution, such as PM2.5, PM10, and VOCs. However, the production of incense causes dust dispersion, high temperature from ovens, and static electricity generated by friction. It can all possibly lead a dust explosion. To prevent and alleviate hazard from re-occurring, we used sandalwood dust at an incense factory in Taiwan, measured the effect of moisture content on the explosion parameters under normal conditions by 20-L apparatus, and used the oven to diminish its moisture content to 0%, 10.0%, and 15.0% as a control group to analyze the explosion characteristics at the different moisture contents, such as maximum explosion pressure and explosion limit. The results showed that the minimum ignition energy of dry dust was 30 mJ. Beyond doubt, incense factories face potential explosion hazards. The above results could be evaluated by the most dangerous range to avoid incense dust in this range at the workplace, lessening hazards caused by a dust explosion. The effect of moisture content on the suppression of the dust explosion was explored.

Improved Dust Detection over East Asia Using Geostationary Satellite Data

This paper presents an improved algorithm, based on the D*-parameter, for dust detection over the East Asian region using brightness temperature differences (BTDs) between the infrared channels of the Advanced Himawari Imager (AHI) onboard Himawari-8. The developed algorithm defines a dust index in the form of the ratio of BTDs: BTD between the 10.4 μm and 12.4 μm channels (BTD10.4–12.4) to that between the 8.6 μm and 10.4 μm channels (BTD8.6–10.4). To identify dust with this index, threshold values were determined empirically. A masking technique using the BTD8.6–10.4 was utilized in the dust index to mitigate the problem of detecting clear-sky deserts and fog over the ocean as dust. BTD8.6–10.4 was analyzed for dust, clear-sky desert, and fog over the ocean cases during 2017 and 2018 with this method. Fog over the ocean and clear-sky desert were distinguished by the criteria of BTD8.6–10.4 > −1.1 K and BTD8.6–10.4 > −1 K, respectively. Based on these thresholds, the influence of fog over the ocean and clear-sky desert was filtered out. The results showed that the dust area was qualitatively consistent with RGB images and ground observation data. Comparison with the AERONET aerosol optical depth (AOD) demonstrated that the D*-parameter was exponentially proportional to AOD, and the correlation coefficient between them was approximately 0.6. The improved Asian Dust detection algorithm can be applied to the monitoring of dust dispersion and movement and also serve as a quantitative indicator of Asian Dust.

Dust Dispersion and Its Effect on Vegetation Spectra at Canopy and Pixel Scales in an Open-Pit Mining Area

Dust pollution is severe in some mining areas in China due to rapid industrial development. Dust deposited on the vegetation canopy may change its spectra. However, a relationship between canopy spectra and dust amount has not been quantitatively studied, and a pixel-scale condition for remote sensing application has not been considered yet. In this study, the dust dispersion characteristics in an iron mining area were investigated using the American Meteorological Society (AMS) and the U.S. Environmental Protection Agency (EPA) regulatory model (AERMOD). Further, based on the three-dimensional discrete anisotropic radiative transfer (DART) model, the spectral characteristics of vegetation canopy under the dusty condition were simulated, and the influence of dustfall on vegetation canopy spectra was studied. Finally, the dust effect on vegetation spectra at the canopy scale was extended to a pixel scale, and the response of dust effect on vegetation spectra at the pixel scale was determined under different fractional vegetation covers (FVCs). The experimental results show that the dust pollution along a haul road was more severe and extensive than that in a stope. Taking dust dispersion along the road as an example, the variation of vegetation canopy spectra increased with the height of dust deposited on the vegetation canopy. At the pixel scale, a lower vegetation FVC would weaken the influence of dust on the spectra. The results derived from simulation spectral data were tested using satellite remote sensing images. The tested result indicates that the influence of dust retention on the pixel spectra with different FVCs was consistent with that created with the simulated data. The finding could be beneficial for those making decisions on monitoring vegetation under dusty conditions and reducing dust pollution in mining areas using remote sensing technology.