Background. China has undergone a rapid industrial revolution and urbanization during the past three decades. This expansion is largely responsible for the release of a large amount of heavy metals into soils and is increasingly raising concerns over the potential effects on human health and the environment. The problem is drawing increasing attention, especially after an extensive nationwide soil survey report in 2014. A number of studies have examined soil contamination by heavy metals in China. However, most of these studies have been small in scale and it is therefore challenging to get a general overview of the level of contamination across the entire country. Objectives. The present study is aimed at presenting a synthesized overview of the extent, pattern, and impact of heavy metal contamination of soils in China, including mitigation approaches. Methods. Eighty-six journal articles and other literature such as reports, internet sources, and statistical yearbooks were narratively and critically syn...

Assessing the spatial dynamics of soil organic carbon (SOC) is essential for carbon monitoring. Since variability of SOC is mainly attributed to biophysical land surface variables, integrating a compressive set of such indices may support the pursuit of an optimum set of predictor variables. Therefore, this study was aimed at predicting the spatial distribution of SOC in relation to remotely sensed variables and other covariates. Hence, the land surface variables were combined from remote sensing, topographic, and soil spectral sources. Moreover, the most influential variables for prediction were selected using the random forest (RF) and classification and regression tree (CART). The results indicated that the RF model has good prediction performance with corresponding R² and root-mean-square error (RMSE) values of 0.96 and 0.91 mg·g⁻¹, respectively. The distribution of SOC content showed variability across landforms (CV = 78.67%), land use (CV = 93%), and lithology (CV = 64.67%). Forestland had the highest SOC (13.60 mg·g⁻¹) followed by agriculture (10.43 mg·g⁻¹), urban (9.74 mg·g⁻¹), and water body (4.55 mg·g⁻¹) land uses. Furthermore, soils developed in bauxite and laterite lithology had the highest SOC content (14.69 mg·g⁻¹). The SOC content was remarkably lower in soils developed in sandstones; however, the values obtained in soils from the rest of the lithologies could not be significantly differentiated. The mean SOC concentration was 11.70 mg·g⁻¹, where the majority of soils in the study area were classified as highly humus and extremely humus. The soils with the highest SOC content (extremely humus) were distributed in the mountainous regions of the study area. The biophysical land surface indices, brightness removed vegetation indices, topographic indices, and soil spectral bands were the most influential predictors of SOC in the study area. The spatial variability of SOC may be influenced by landform, land use, and lithology of the study area. Remotely sensed predictors including land moisture, land surface temperature, and built-up indices added valuable information for the prediction of SOC. Hence, the land surface indices may provide new insights into SOC modeling in complex landscapes of warm subtropical urban regions.

Wolkite is a town like many developing countries, faces problems associated with poor solid waste management. The town has only one major landfill site, which is found at Gasore kebele, near to the town. However, the waste dumping in this site has been affecting the surrounding community. The objectives of this study were to evaluate the current solid waste deposal site and socioeconomic impact of the current solid waste disposal site in the study area. The data were collected through field observation, key informant interview, focus group discussion, and household survey. Geospatial data were also used to evaluate the current solid disposal site. In this study, fifty-two household and two focus group discussion were participated. The quantitative data coded and analyzed using SPSS software. The data described using descriptive statistics and qualitative data were also expressed using narrative description whereas the geospatial data were analyzed by ArcGIS. The study result showed that the landfill site is proximate to stream and river, church, mosque, rural settlement, main road, and vegetation. The disposal site has affecting negatively to the local community; besides, the municipal waste is disposed arbitrarily on open field, roadside, dumped everywhere and solid waste disposed jointly with liquid at the landfill site, therefore, this study recommends to select suitable landfill site in the of the town.

Solid waste, which is a consequence of day-to-day activity of human kind, needs to be managed properly. This study deals with municipal solid waste source identification, characterization and physical composition analysis the case of wolkite town, Ethiopia. inorder to conduct this study both primary and secondary data were collected and analyzed, subsequently the Findings of this study revealed that household, hotel, restorante, Kera, schools & university, chat chewing residence are identified as major source of solid waste. Regarding solid waste physical composition and characterization analysis result indicated that in wolkite town the larger portion of solid waste generating is food and food related which constituted 25.86% followed by ash and fine sand which constituted 24.3%, the third major kind of solid waste generated from the town at the household level is a mixture of different material named as other, then manure constituted 12.17%, chat, leaves &grasses, plastic, Festal, paper, textile, and glass & ceramic constituted 5.7%, 5.7%, 4.2%, 3.42%, 1.9% and 0.39%. Thus the finding of this study recommend to work on community awareness creation about proper solid waste management, and, it is very crucial to apply appropriate solid waste management system mechanism and establish small scale enterprise those will collect solid waste in the town.