Selecting environmental factors to predict spatial distribution of soil organic carbon stocks, northwestern Iran.

Knowledge of environmental factors controlling soil organic carbon (SOC) stocks can help predict spatial distribution SOC stocks. So, this study was carried out to select the best environmental factors to model and estimate the spatial distribution of SOC stocks in northwestern Iran. Soil sampling was performed at 210 points by multiple conditioned Latin Hypercube method (cLHm) and SOC stocks were measured.

Predicting spatial distribution of soil organic matter using regression approaches at the regional scale (Eastern Azerbaijan, Iran).

Soil organic matter (SOM) is one of the important factors in arid and semiarid areas, which describes the soil quality. Spatial estimation of SOM is important to understand the SOM storage and the emphasis of the SOM in the global carbon cycle and environmental issues. Mapping of SOM content can have significant uses in environmental modeling.

Evaluation of heavy metal contamination and ecological risk of soil adjacent to Saravan municipal solid waste disposal site, Rasht, Iran.

This study was performed on the soil of the Hyrcanian forests near Saravan municipal solid waste dumpsite, Rasht, Iran. In this research, the contents of metals (As, Pb, Cr, Cd, Cu, Hg, and Zn) were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The geoaccumulation index (I), contamination factor (CF), and enrichment factor (EF), as well as pollution load index (PLI), were used to evaluate the metals contamination.