ESTIMATION OF SOIL CARBON STORAGE IN SHINJUKU GYOEN NATIONAL GARDEN BASED ON LAND USE HISTORY AND SOIL COMPACTNESS PROFILES

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

Occurrence of arsenic in the riverbed sediments of the Selenga river system

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

A global perspective on soil science education at third educational level; knowledge, practice, skills and challenges

The pivotal role of soil as a resource is not fully appreciated by the general public. Improving education in soil science represents a challenge in a world where soil resources are under serious threat. Today’s high school students, the world’s future landowners, agriculturalists, and decision makers, have the potential to change society’s apathy towards soils issues. This research aimed to compare the level of soil education in high and/or secondary schools in forty-three countries worldwide, together comprising 62% of the world's population. Comparisons were made between soil science content discussed in educationally appropriate textbooks via a newly proposed soil information coefficient (SIC). Interviews with teachers were undertaken to better understand how soil science education is implemented in the classroom. Statistical analyses were investigated using clustering. Results showed that gaps in soil science education were most commonly observed in countries where soil science is a non-compulsory or optional subject. Soil science concepts are predominantly a part of geography or environmental science curricula. Consequently, considerable variability in soil science education systems among investigated countries exists. Soil information coefficient‘s outcomes demonstrated that a methodological approach combining textbooks and the use of modern digitally based strategies in the educational process significantly improved soil education performances. Overall, soil science education is under-represented in schools worldwide. Dynamic new approaches are needed to improve pivotal issues such as: i) promoting collaborations and agreements between high school and universities; ii) encouraging workshops and practical exercises such as field activities; and, iii) implementing technology tools. This, in turn, will prepare the next generation to contribute meaningfully towards solving present and future soil problems

Comparison between random forest and multiple linear regression to create digital maps of soil chemical properties in the Thung Kula Ronghai region, Thailand

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-associated metal(loid)s in the urban river environments of Mongolia

The widespread distribution of plastic debris in riverine environment is one of the major concerns of environmental pollution because of its potential impact on the aquatic ecosystem. In this study, we investigated the accumulation of metal(loid)s on polystyrene foam (PSF) plastics collected from the floodplain of the Tuul River of Mongolia. The metal(loid)s sorbed on plastics were extracted from the collected PSF via sonication after peroxide oxidation. The size-dependent association of metal(loid)s with plastics indicates that PSFs act as vectors for pollutants in the urban river environment. The mean concentrations of metal(loid)s (i.e., B, Cr, Cu, Na, and Pb) indicate a higher accumulation of the metal(loid)s on meso-sized PSFs compared with macro- and micro-sized PSFs. In addition, the images from scanning electron microscopy (SEM) indicated not only the degraded surface of plastics showing fractures, holes, and pits but also the adhered mineral particles and microorganisms on the PSFs. The interaction of metal(loid)s with plastics was probably facilitated by the physical and chemical properties of altered surface of plastics through photodegradation, followed by an increase in surface area by size reduction and/or biofilm development in the aquatic environment. The enrichment ratio (ER) of metals on PSF samples suggested the continuous accumulation of heavy metals on plastics. Our results demonstrate that the widespread plastic debris could be a carrier of hazardous chemicals in the environment. Considering that the negative impacts of plastic debris on environmental health are major concerns to be addressed, the fate and behavior of the plastics especially their interaction with pollutants in aquatic environments should be further studied