Literature DB >> 24281676

Spatial modeling of ecological areas by fitting the limiting factors for As in the vicinity of mine, Serbia.

Dragan Cakmak1, Veljko Perovic, Elmira Saljnikov, Darko Jaramaz, Biljana Sikiric.   

Abstract

Elevated arsenic (As) concentrations in soil are often found in the vicinity of certain mineral deposits that have been, or are currently, under exploitation, regardless of the target resource. Detailed study of such areas for safe agriculture requires considerable financial costs and long periods of time. Application of an appropriate spatial model that describes the behavior of arsenic in soil and plants can significantly ease the whole investigation process. This paper presents a model of ecological security of an area that, in the past, was an antimony mine and has a naturally high content of arsenic. For simulation and modeling the geographic information science (GIS) technology with the inserted predictors influencing the accessibility of As and its content in plants was used. The results obtained were the following: (1) a categorization of contaminated soils according to soil properties was developed; (2) the proposed methodology allows focusing on particular suspect area saving an energy and human resource input; and (3) new safe areas for growing crops in contaminated area were modeled. The application of the proposed model of As solubility to various crops grown around a former antimony mine near the village of Lisa, southwest Serbia showed that significant expansion of the areas suitable for growing potato, raspberry, and pasture was possible.

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Year:  2013        PMID: 24281676     DOI: 10.1007/s11356-013-2320-7

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  3 in total

1.  Identifying sources and assessing potential risk of heavy metals in soils from direct exposure to children in a mine-impacted city, Changsha, China.

Authors:  Zhenxing Wang; Liyuan Chai; Zhihui Yang; Yunyan Wang; Haiying Wang
Journal:  J Environ Qual       Date:  2010 Sep-Oct       Impact factor: 2.751

2.  Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.

Authors:  M Manzurul Hassan; Peter J Atkins
Journal:  J Environ Sci Health A Tox Hazard Subst Environ Eng       Date:  2011       Impact factor: 2.269

3.  Using indicator kriging for the evaluation of arsenic potential contamination in an abandoned mining area (Portugal).

Authors:  I M H R Antunes; M T D Albuquerque
Journal:  Sci Total Environ       Date:  2012-12-05       Impact factor: 7.963

  3 in total
  1 in total

1.  Multivariate analysis combined with GIS to source identification of heavy metals in soils around an abandoned industrial area, Eastern China.

Authors:  Jie Zhou; Ke Feng; Zongping Pei; Fang Meng; Jian Sun
Journal:  Ecotoxicology       Date:  2015-12-16       Impact factor: 2.823

  1 in total

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