Summary Washing with Na2EDTA is insufficient to remove both cationic and anionic metal species in contaminated soil. Therefore, washing with Na2EDTA enhanced with organic reducing agents was tested as a means to improve the efficiency of removal of heavy metals and to investigate its effect on the spectroscopic characteristics of contaminated soil. The results indicated that washing with Na2EDTA enhanced with organic reducing agents was effective in removing both arsenic and cationic metals from contaminated soil at the initial pH of the mixed washing agents. The increase in removal efficiencies (compared with a single Na2EDTA washing) under this washing regime was 19–31% for arsenic, 6–19% for cadmium, 3–12% for copper and 6–21% for lead in two samples. The results of metal fractionation indicated that the addition of either oxalic or ascorbic acids could increase the relative proportion of the residual fraction to varying degrees. The spectroscopic analysis demonstrated that these acids were effective in removing metals by dissolving soil minerals, such as amorphous iron oxides, and reducing mineral oxides. The X‐ray photoelectron spectroscopy (XPS) study showed that more Fe(III) was transformed to Fe(II) under Na2EDTA washing enhanced with oxalic acid than with ascorbic acid, and the dissolution of silicon oxides was very limited in the presence of either of these acids. Washing with Na2EDTA enhanced by both oxalic and ascorbic acid of the sampled soils improved removal efficiencies; properties of the washing agent, the physicochemical properties of samples and the pollution characteristics (e.g. the amounts of contamination and metal fractions) combined to influence the effect of washing. Highlights Washing with Na2EDTA and oxalic or ascorbic acids was effective in extracting arsenic and cationic metals. Oxalic acid was more effective than ascorbic acid in transforming Fe(III) to Fe(II). Addition of organic reducing acids increased the relative proportion of the residual fraction of metals. Metal removal was affected by dissolution of minerals such as scorodite, muscovite and feldspar.

ABSTRACT:This study investigates the usability of low-attitude unmanned aerial vehicle (UAV) acquiring high resolution images for the geometry reconstruction of opencast mine. Image modelling techniques like Structure from Motion (SfM) and Patch-based Multiview Stereo (PMVS) algorithms are used to generate dense 3D point cloud from UAV collections. Then, precision of 3D point cloud will be first evaluated based on Real-time Kinematic (RTK) ground control points (GCPs) at point level. The experimental result shows that the mean square error of the UAV point cloud is 0.11m. Digital surface model (DSM) of the study area is generated from UAV point cloud, and compared with that from the Terrestrial Laser Scanner (TLS) data for further comparison at the surface level. Discrepancy map of 3D distances based on DSMs shows that most deviation is less than ±0.4m and the relative error of the volume is 1.55%.

Drought index is an important tool for monitoring and evaluation. A new drought index for freshwater wetlands is developed based on water balance, then used to evaluate drought in Baiyangdian Wetland (BW).