High soil surface temperature and loosened soil are major limiting factors of plant productivity in arid and semi-arid coal mining areas of China. Moreover, the extensive and illegitimate burning of crop residues is causing environmental pollution; whereas, these residues could be converted to biochar to benefit soil quality. In this study, the effect of wheat straw biochar (WSB) at rates of 0% (control, CK), 1% (low, LB), 2% (medium, MB) and 4% (high, HB) on soil temperature at different depths (5, 10, 15, and 20 cm) and moisture levels (10 and 20%) was investigated under high soil surface temperature of 50 °C and air humidity of 40%. Our data suggested that soil bulk density was inversely, and soil moisture was directly corelated with soil thermal parameters. Moreover, the increasing rate of WSB addition linearly decreased the soil thermal properties. The maximum decrease in soil bulk density at both moisture levels (10% and 20%) was measured in HB treatment compared to respective CKs. The highest decrease in soil thermal conductivity (59.8% and 24.7%) was found under HB treatment in comparison to respective controls (CK10% and CK20% moisture). The soil volumetric heat capacity was also strongly corelated with soil moisture content (r = 0.91). The WSB treatments displayed differential responses to soil temperature. Under 10% soil moisture, temperature of LB, MB and HB treatments was higher as compared to CK at 5–20 cm depth, and MB treated soil had the smallest increase in temperature. At the 15-cm depth, the MB treatment decreased the temperature by 0.93 °C as compared to the CK20%. Therefore, the effect of WSB on soil temperature was influenced by soil moisture content, soil depth and WSB application rates. It suggested that MB treatment could be a useful farming practice for mitigating soil temperature fluctuation.

Synthetic aperture radar (SAR) technology has become an important means of flood monitoring because of its large coverage, repeated observation, and all-weather and all-time working capabilities. The commonly used thresholding and change detection methods in emergency monitoring can quickly and simply detect floods. However, these methods still have some problems: (1) thresholding methods are easily affected by low backscattering regions and speckle noise; (2) changes from multi-temporal information include urban renewal and seasonal variation, reducing the precision of flood monitoring. To solve these problems, this paper presents a new flood mapping framework that combines semi-automatic thresholding and change detection. First, multiple lines across land and water are drawn manually, and their local optimal thresholds are calculated automatically along these lines from two ends towards the middle. Using the average of these thresholds, the low backscattering regions are extracted to generate a preliminary inundation map. Then, the neighborhood-based change detection method combined with entropy thresholding is adopted to detect the changed areas. Finally, pixels in both the low backscattering regions and the changed regions are marked as inundated terrain. Two flood datasets, one from Sentinel-1 in the Wharfe and Ouse River basin and another from GF-3 in Chaohu are chosen to verify the effectiveness and practicality of the proposed method.

Phosphorus from secondary effluents and coal gangue from coal mining have caused serious environmental problems. The feasibility of phosphate removal from secondary effluents using calcinated coal gangue loaded with zirconium oxide (CCG-Zr) was explored. Major influencing factors like the calcinated temperature, CCG-Zr ratio, adsorbent dose, time and solution pH, etc. were investigated. Newly developed CCG-Zr accomplished a significantly higher phosphate removal for phosphate (93%) compared with CCG (35%) at a calcinated temperature of 600 °C and CCG-Zr mass ratio of 1:1. For CCG-Zr the maximum phosphate removal rate (93%) was noted at an initial phosphate concentration of 2 mg/L within 20 min. The CCG-Zr displayed a higher phosphate removal rate (85–98%) over a wide range of solution pH (2.5~8.5). The adsorption isotherms fitted better to the Freundlich (R2 = 0.975) than the Langmuir model (R2 = 0.967). The maximum phosphate adsorption capacity of the CCG-Zr was 8.55 mg/g. These results suggested that the CCG-Zr could potentially be applied for the phosphate removal from secondary effluents.

Underground coal mining induces surface subsidence, leading to disasters such as damage to buildings and infrastructure, landslides, and surface water accumulation. Preventing and controlling disasters in subsidence areas and reutilizing land depend on understanding subsidence regularity and obtaining surface subsidence monitoring data. These data are crucial for the reutilization of regional land resources and disaster prevention and control. Subsidence hazards are also a key constraint to mine development. Recently, with the rapid advancement of UAV technology, the use of UAV photogrammetry for surface subsidence monitoring has become a significant trend in this field. The periodic imagery data quickly acquired by UAV are used to construct DEM through point cloud filtering. Then, surface subsidence information is obtained by differencing DEM from different periods. However, due to the accuracy limitations inherent in UAV photogrammetry, the subsidence data obtained through this method are characterized by errors, making it challenging to achieve high-precision ground surface subsidence monitoring. Therefore, this paper proposes a spatial domain filtering algorithm for UAV photogrammetry combined with surface deformation caused by coal mining based on the surface subsidence induced by coal mining and combined with the characteristics of the surface change. This algorithm significantly reduces random error in the differential DEM, achieving high-precision ground subsidence monitoring using UAV. Simulation and field test results show that the surface subsidence elevation errors obtained in the simulation tests are reduced by more than 50% compared to conventional methods. In field tests, this method reduced surface subsidence elevation errors by 39%. The monitoring error for surface subsidence was as low as 8 mm compared to leveling survey data. This method offers a new technical pathway for high-precision surface subsidence monitoring in mining areas using UAV photogrammetry.

In mining safety and other fields, similar material simulation is the main research method to study the movement and deformation of rock formation and ground surface. However, the inaccurate subsidence laws could be obtained because the strength of the composition materials like gypsum and lime is easily affected by moisture. Therefore, it is crucial to monitor the moisture content when carrying simulation experiments. This paper discussed the feasibility of indirectly measuring the moisture content of similar material models using the three-dimensional (3D) laser scanning reflection intensity through three experiments on similar material specimens. The results showed that the laser reflection intensity was sensitive to the moisture content, incidence angle, and distance with three different relationships and the influence of the two factors could be weakened through the established correction models. However, it was recommended restricting the incidence angle to less than 20° and setting the distance from 4 to 10 m to reduce the complexity of correction. The accuracy of this method reached 1.1% under the monitoring condition of 4 m and the normal incidence, which could meet the requirements for monitoring the moisture content of similar material models. The research results of the paper provide a new method to monitor the moisture content in similar material models.

There is a lot of research on the urban thermal environment, mainly on air temperature. However, fewer studies focus on soil temperature that is influenced by built environment, especially on the horizontal heat impacts from buildings. In this research, soil temperature was investigated at different depths in Beijing, China, to compare the differences between two locations. One was next to the building and the other was far away from the building (10 m). The locations are referred to as site A and site B, respectively. These two sites were chosen to compare the differences in soil temperatures between them to present the horizontal heat impact from facade. The results show that facades caused horizontal heat impacts on the soil at different depths in the winter, spring, and summer. Basically, facades functioned as heat sources to the soil surrounding them. The mean temperature differences between the two sites were 3.282, 4.698 and 0.316 K in the winter, spring and summer, respectively. Additionally, the thermal effects of the buildings were not only exhibited as higher soil temperatures but the temporal appearance of the maximum and minimum temperature was also influenced. Buildings functioned as heat sources to heat soil in the winter and spring and stabilized soil temperature so that it would not fluctuate too much in the summer. Additionally, the coefficient of variation indicates that buildings primarily increased the soil temperature in the winter and spring and stabilized the soil temperature in the summer.