Global Situation of Bioremediation of Leachate-Contaminated Soils by Treatment with Microorganisms: A Systematic Review.

This systematic review presents the current state of research in the last five years on contaminants in soils, especially in leachates from solid waste landfills, with emphasis on biological remediation. In this work, the pollutants that can be treated by microorganisms and the results obtained worldwide were studied. All the data obtained were compiled, integrated, and analyzed by soil type, pollutant type, bacterial type, and the countries where these studies were carried out. This review provides reliable data on the contamination of soils worldwide, especially soils contaminated by leachate from municipal landfills. The extent of contamination, treatment objectives, site characteristics, cost, type of microorganisms to be used, and time must be considered when selecting a viable remediation strategy. The results of this study can help develop innovative and applicable methods for evaluating the overall contamination of soil with different contaminants and soil types. These findings can help develop innovative, applicable, and economically feasible methods for the sustainable management of contaminated soils, whether from landfill leachate or other soil types, to reduce or eliminate risk to the environment and human health, and to achieve greater greenery and functionality on the planet.

Geostatistical characterization of the soil of Aguascalientes, México, by using spatial estimation techniques.

Four spatial estimation techniques available in commercial computational packages are evaluated and compared, namely: regularized splines interpolation, tension splines interpolation, inverse distance weighted interpolation, and ordinary Kriging estimation, in order to establish the best representation for the shallow stratigraphic configuration in the city of Aguascalientes, in Central Mexico. Data from 478 sample points along with the software ArcGIS (Environmental Systems Research Institute, Inc. (ESRI), ArcGIS, ver. 9.3, Redlands, California 2008) to calculate the spatial estimates. Each technique was evaluated based on the root mean square error, calculated from a validation between the generated estimates and measured data from 64 sample points which were not used in the spatial estimation process. The present study shows that, for the estimation of the hard-soil layer, ordinary Kriging offered the best performance among the evaluated techniques.