Paper
19 March 2013 Background assessment and distribution of as in soil of Jiangxi Province, China
Miaojie Han, Dengfeng Wang, Zhiyuan Wei, Shumei Tang, Zhiping Qi
Author Affiliations +
Proceedings Volume 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering; 87620L (2013) https://doi.org/10.1117/12.2019702
Event: Third International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2013), 2013, Sanya, China
Abstract
To clarify the distribution and estimate the background concentration of arsenic (As) is significant to the prevention and control of soil As contamination. Taking Jiangxi as study area, demonstrating the distribution of As in cultivation and parent materials layers, and estimating the soil background concentrations of As by five approaches, which are Geometric mean and geometric standard (GM+2GSD), Iterative 2-σ technique, Upper confidence limit (UCL0.95), Accumulative frequency method and Deep layer soil element method. The results indicate that the content of As in cultivation layer is 15.2 mg kg-1, and the spatial variation of As in cultivation layer higher than the parent materials layer. The result of Iterative 2-σ technique is highest among the five methods, which is 23.0 mg kg-1, and other four methods’ results are highly consistent. The estimation results of GM+2GSD is accepted as the soil background concentration of As in study area. This method is easy calculation and can be applied to estimating the regional soil background concentrations of trace elements.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Miaojie Han, Dengfeng Wang, Zhiyuan Wei, Shumei Tang, and Zhiping Qi "Background assessment and distribution of as in soil of Jiangxi Province, China", Proc. SPIE 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 87620L (19 March 2013); https://doi.org/10.1117/12.2019702
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KEYWORDS
Arsenic

Soil contamination

Magnesium

Soil science

Contamination

Statistical analysis

Agriculture

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