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Using machine learning (ML) algorithms to digital soil mapping (DSM) allows theelucidation of relationships between soil properties and environmental variables enabling the precise prediction of soil nutrient levels. The accuracy of the predicted values using the random forest (RF) algorithm, which is the most popular ML algorithm for digital soil mapping, and multiple linear regression (MLR) were compared to create digital maps of soil chemical properties in the ThungKula Ronghai (TKR) region, Thailand. The spectral indices including moisture stress index (MSI), normalized difference water index (NDWI), saturation index (SI), brightness index (BI), and coloration index (CI) obtained from remote sensing (RS) data were found to be more effective for predicting the various soil properties than the topographic indices derived from the DEM in the plain area. The MLR and RF models successfully predicted soil chemical properties with good predictiveaccuracy. The results indicated that the RF model has a slightly higher accuracy than the MLR model.However, the MLR model is superior in interpreting the relationship with the model equations.

Plastic waste can be transferred to the river by wind, flood, and unexpected artificial disposal, which gives a negative impact on the environment and human health. Rivers collect plastic wastes from their watersheds according to geographical factors. Therefore, characterization of plastic distribution and composition with respect to land-uses can be understandable for fate of plastic wastes. Plastic debris surveyed from the main (Tuul river) and tributary river shores in Ulaanbaatar (UB) city, Mongolia from the upperstream to downstream to understand behavior and control of plastic waste along the major river in the urbanized city. Sampling areas are divided into the apartment and housing/ger (traditional yurt) area, industrial and agricultural areas. The composition of collected plastics along the Tuul river in the UB city was composed of 63% micro, 15% of meso, 18% of macro, and 5% of mega-sized plastics on the number basis. Foam and films were dominant in the material-based fractions. Especially, polystyrene foams occupied 99% of micro and 72% of meso-sized plastic fractions, whereas the film type makes up 55% of macro and 77% of mega-sized plastics. From the viewpoint of sampling location, foam and fiber types of microplastic were less in the upperstream of Tuul River, but higher amounts of foam and fibers were found at downstream of the river. Polystyrene foams transported easily with river flow and wind coupling with their degradation process because of their least density and smaller sizes. Although films were abundant in housing/ger areas, foams distributed everywhere along the rivers. Conversely, industrial areas released the least number of plastic wastes. Plastic waste distribution along branch tributaries was different from the Tuul River shore. Macro and Mega plastics tended to distribute along the shore of tributaries connecting to Tuul river. The size distribution may vary according to catchment area and types of land-uses. Also see: https://micro2022.sciencesconf.org/426761/document, In MICRO 2022, Online Atlas Edition: Plastic Pollution from MACRO to nano

Over the past few decades, anthropogenic activities have concentrated in the transboundary Selenga River basin, especially in the two-thirds of it located in the Mongolian territory. In this study, we measure the concentration of arsenic (As) in riverbed sediments and the mobilization and accumulation of this metalloid in sediments of the Selenga River system. Higher concentrations of As were detected in the sediments collected from the Orkhon River system than those from downstream of Selenga River in Russia. The observed difference indicates that the Orkhon River watershed is highly affected by anthropogenic activities involving soil excavation. In particular, high concentrations of As (3.6-4.9 mg kg^), in comparison with the average for the entire Selenga River system (2.8 mg kg^), were detected in sediment samples collected downstream of gold mining areas and near Darkhan City. Around this city, As pollution might be related to the combustion of coal with high As content. Gold mining is a main source of As pollution in rural areas. Notably, the content of fine fractions in sediment samples collected downstream of the Zaamar mining area was half that measured in samples collected upstream of it. However, no correlation was observed between As concentration and fine particle content in sediment samples collected throughout the whole research area, suggesting that the proportion of fine particle sediments is not a controlling factor in As distribution in the riverbed. Heavy and coarse particles released by mining sites seem to quickly deposit on the riverbed near their source. However, fine particles can co-precipitate at river junctions due to changes in water quality. These deposition processes can limit the extent to which As pollution can spread in a large area, but redissolution of As from secondary minerals is now recognized as a key factor in the widespread groundwater As contamination observed around the world.

This study aims to estimate soil carbon storage in Shinjuku Gyoen National Garden,Tokyo Metropolis. Undisturbed soil samples were collected in the Gyoen from regions of differentland use using a core cylinder. A modified investigation was used by combining measurement ofvertical structure of soil compactness in order to estimate cumulative carbon content withoutinterfering with the park landscape. Softness obtained using a cone penetrometer was converted tosoil bulk density (g cm-3) and samples for measurement of total carbon content (g kg-1) werecollected using a boring stick. The carbon storage in the Gyoen (0 – 100 cm) was estimated as 316± 83.1 t C ha-1 in turf areas and 198 ± 61.3 t C ha-1 in forest areas, respectively, which areequivalent or slightly larger than the standard values obtained for Andosols and Brown Forest soils,respectively. The large difference in the cumulative carbon storage between turf area and forestarea for the entire profile (0 – 100 cm) can be explained by the difference in the pedogenesisprocess of humus accumulation together with the diagenesis process of humus decomposition,both of which depend on the humus quality of vegetation and land use history. The use of theSoftness obtained from measurement of vertical soil compactness was discussed as a proxy ofbulk density. It is shown that vertical soil compactness differs in same land use regions in theGyoen. Although the estimated values of cumulative carbon content had issues withoverestimation in some cases, we suggest that the use of the Softness as a substitute for bulkdensity is applicable for estimating soil carbon storage. Subsurface structure, regulated by land usehistory and land creating history should be taken into account for the reliable evaluation of soilcarbon storage in urban areas.