- Title
- Using Qmsax* to evaluate the reasonable As(V) adsorption on soils with different pH
- Creator
- Lu, Guannan; Tian, Haixia; Liu, Yanju; Naidu, Ravi; Wang, Ziquan; He, Wenxiang
- Relation
- Ecotoxicology and Environmental Safety Vol. 160, p. 308-315
- Publisher Link
- http://dx.doi.org/10.1016/j.ecoenv.2018.05.043
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2018
- Description
- As a toxic metalloid element, arsenic (As) derived from human activities can pose hazardous risks to soil and water. The bioavailability of arsenic is influenced by its behavior, in particular its adsorption-desorption in the soil environment. The maximum adsorption amount (Qmax) calculated from Langmuir equation is an important parameter to estimate the adsorption capacity of adsorbents. However, the soil is a more complicated system compared with specific adsorbents. Thus, in this study, we tried to find a more reasonable parameter (Qmax*) to evaluate the adsorption capacity of soils. Eighteen Chinese soil samples with different pH were used for adsorption-desorption experiments. The maximum As(V) adsorption capacity calculated through Langmuir fitting for 18 samples were ranged from 50.25 (S13) to 312.50 (S4) mg kg−1. Besides, Qmax was highly related with soil pH. Using the difference value of adsorption amount and desorption amount to indicate the amount of non-electrostatic adsorption of As(V) onto soils, calculated the maximum adsorption amount of non-electrostatic adsorption (Qmax*). The average Qmax* of acidic and neutral soils was 162.18 mg kg−1 whereas that for alkaline soils it was only 79.52 mg kg−1. The result from multiple linear regression analysis showed Qmax* was strongly influenced by Feox and clay contents. Furthermore, hysteresis index (HI) in the As(V) desorption varied from 0.83 (S13) to 1.82 (S6). The results further indicated the risk of secondary pollution originating from the desorption process cannot be ignored.
- Subject
- arsenic; soil; non-electrostatic adsorption; desorption; principle component analysis
- Identifier
- http://hdl.handle.net/1959.13/1444193
- Identifier
- uon:42230
- Identifier
- ISSN:0147-6513
- Language
- eng
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