Quantitative assessment on soil enzyme activities of heavy metal contaminated soils with various soil properties. (November 2015)

• Record Type: Journal Article
• Authors: Xian, Yu; Wang, Meie; Chen, Weiping
• Is Part Of: Chemosphere. Volume 139(2015)
• Page Start: 604
• Page End: 608
• Publication Date: 2015-11
• Subjects: Soil heavy metal toxicity -- Soil enzyme activity -- Soil properties -- Quantitative model -- Ecological risk assessment; Pollution -- Periodicals; Pollution -- Physiological effect -- Periodicals; Environmental sciences -- Periodicals; Atmospheric chemistry -- Periodicals; 551.511
• DOI: 10.1016/j.chemosphere.2014.12.060
• Languages: English
• ISSNs: 0045-6535

Abstract

Highlights: Joint effects of heavy metals and soil properties on soil enzyme activities were determined. Arylsulfatase could be used as an indicator to study the toxicity of heavy metals. Changes of arylsulfatase activity with SOM content fitted well an exponential model. The model illustrated the offset of SOM to heavy metal toxicity on soil enzymes activities. Abstract: Soil enzyme activities are greatly influenced by soil properties and could be significant indicators of heavy metal toxicity in soil for bioavailability assessment. Two groups of experiments were conducted to determine the joint effects of heavy metals and soil properties on soil enzyme activities. Results showed that arylsulfatase was the most sensitive soil enzyme and could be used as an indicator to study the enzymatic toxicity of heavy metals under various soil properties. Soil organic matter (SOM) was the dominant factor affecting the activity of arylsulfatase in soil. A quantitative model was derived to predict the changes of arylsulfatase activity with SOM content. When the soil organic matter content was less than the critical point A (1.05% in our study), the arylsulfatase activity dropped rapidly. When the soil organic matter content was greater than the critical point A, the arylsulfatase activity gradually rose to higher levels showing that instead of harm the soil microbial activities were enhanced. The SOM content needs to be over the critical point B (2.42% in our study) to protect its microbial community from harm due to the severe Pb pollution (500 mg kg −1 in our study). The quantitative model revealed the pattern of variation of enzymatic toxicity due to heavy metals under various SOM contents. The applicability of the model under wider soil properties need to be tested. The model however may provide a methodological basis for ecological risk assessment of heavy metals in soil.