Airborne eddy covariance (EC) measurement is one of the most effective methods to directly measure the surface mass and energy fluxes at the regional scale. It offers the possibility to bridge the scale gap between local- and global-scale measurements by ground-based sites and remote-sensing instrumentations, and to validate the surface fluxes estimated by satellite products or process-based models. In this study, we developed an unmanned aerial vehicle (UAV)-based EC system that can be operated to measure the turbulent fluxes in carbon dioxides, momentum, latent and sensible heat, as well as net radiation and photosynthetically active radiation. Flight tests of the developed UAV-based EC system over land were conducted in October 2020 in Inner Mongolia, China. The in-flight calibration was firstly conducted to correct the mounting error. Then, three flight comparison tests were performed, and we compared the measurement with those from a ground tower. The results, along with power spectral comparison and consideration of the differing measurement strategies indicate that the system can resolve the turbulent fluxes in the encountered measurement condition. Lastly, the challenges of the UAV-based EC method were discussed, and potential improvements with further development were explored. The results of this paper reveal the considerable potential of the UAV-based EC method for land surface process studies.

Coal gangue piles accumulate outside mines and can persist for years, negatively impacting the regional environment. To determine the main cause of soil pollution at coal gangues, several coal gangues in Guizhou Province, China that had undergone natural recovery via native plants for 8 years were investigated in summer 2019. Three plots (2 m × 2 m) from the coal gangue area were selected for the treatment (GP). Control plots that were 100 m away from GP were also investigated in contrast (CK-near). In addition, plots from forest, farmland and lake land that were far from GP and largely undisturbed were also investigated as more extreme contrasts (CK-far). A series of soil indicators that can be affected by coal-gangue, such as heavy metals (Mn, Cr, Cd, Ni, Zn, Cu, Pb), As, pH, cation exchange capacity (CEC), sulfur (S) and iron (Fe), were tested for in the plots. Plant species, coverage and height were also analyzed to uncover biodiversity and dominant species information. The results suggested that coal gangue significantly influences soil S, pH and plant species after 8 years of natural recovery. The CK-far plots contained relatively low soil sulfur content, normal pH (close to 7) and abundant plant biodiversity. Generally, pH related positively with both the Patrick (R = 0.79, n = 22, p < 0.001) and Shannon indices (R = 0.67, n = 22, p < 0.001); the soil S related negatively with both the Patrick (R = 0.85, n = 22, p < 0.001) and Shannon indices (R = − 0.79, n = 22, p < 0.001). S content was highest (S = 1.0%) in GP plots, was lower in CK-near plots (S = 0.3%) and was the lowest of all in the plots distant from the coal mine (S = 0.1%, CK-far). S content was negatively correlated with pH. Soil pH decreased significantly, from 7.0 in CK-far, to 5.9 in CK-near, to 4.2 in GP. Soil Fe was 3.4 times higher in GP and CK-near than in CK-far. The excess sulfur and Fe elements and the acidified soil drove changes in soil and vegetation in the coal gangue areas. After 8 years of natural recovery, only a few plants, like Miscanthus floridulus, were able to live near the coal gangue in the area where the soil was still acidic and high in S and Fe.

Ecosystem services serve as a bridge between the ecological environment and human society. The quantitative analysis and forecasting of ecosystem services can provide references for regional eco-environmental assessments and land-use planning for the future. In this study, taking Hainan Tropical Rainforest National Park (HTRNP) as an example, the value of regulating ecosystem services (RESs) in 2020 was assessed via ArcGIS 10.1 and the InVEST 3.5 model, and the per-unit value of RESs was calculated for different LULC types. In addition, in accordance with the Overall Planning for HTRNP and the objective of optimizing RESs, the value of RESs in short-term (to 2030) and long-term (to 2050) scenarios was forecast via a linear programming model. The results are as follows: (1) The RES value of HTRNP in 2020 was CNY 2090.67 × 10⁸, with climate regulation accounting for the largest proportion; the spatial distribution of RESs in the eastern and central areas was higher than that in the western area, but different indicators of RESs differed in their spatial patterns in varied geographic units. (2) The natural forest ecosystem in HTRNP accounts for 76.94% of the total area but 84.82% of the total value of RESs. The per-unit value is ranked from highest to lowest as follows: montane rainforests > wetlands > lowland rainforests > lowland secondary rainforests > tropical coniferous forests > deciduous monsoon rainforests > tropical cloud forests > shrub forests > timber forests > economic forests > rubber forests > grasslands > farmlands > settlements. (3) In the short-term scenario, the value of RESs is CNY 2216.64 × 10⁸, an increase of CNY 118.97 × 10⁸ compared to 2020, with an increase rate of 5.67%. In the long-term scenario, the value of RESs is CNY 2472.48 × 10⁸, an increase of CNY 374.81 × 10⁸ compared to 2020, with an increase rate of 17.87%. The results reveal the significance of ecosystem services in the national park and can inform more targeted and scientifically sound decision-making in the future.