Seasonal variations of carbonic anhydrase activity in Chongqing urban section of Jialing River and its influencing factors
Autor: | Qian Shen, Wenjing Gao, Zhi Zhang, Min Wang, Yudong Nie, Lu Yang, Yinfan Li |
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Rok vydání: | 2017 |
Předmět: |
China
Environmental Engineering 010504 meteorology & atmospheric sciences Health Toxicology and Mutagenesis 010501 environmental sciences 01 natural sciences Algal bloom Rivers Total inorganic carbon Water Quality Carbonic anhydrase Tributary Environmental Chemistry Carbonic Anhydrases 0105 earth and related environmental sciences Total organic carbon geography geography.geographical_feature_category biology Ecology Urbanization Public Health Environmental and Occupational Health Carbonic anhydrase activity General Medicine General Chemistry Eutrophication Models Theoretical Pollution Monitoring program Environmental chemistry biology.protein Environmental science Seasons Water quality Environmental Monitoring |
Zdroj: | Chemosphere. 179:202-212 |
ISSN: | 0045-6535 |
Popis: | Carbonic anhydrase (CA) is an enzyme in algal carbon-utilization that plays an important role in the formation of algal blooms. A year-long monitoring program in the shore area of Chongqing Urban Section of the Jialing River (JR) was launched to determine the variations in carbonic anhydrase activity (CAA) and its change mechanism in the hydro-fluctuation belt of the tributaries in the Three Gorges Reservoir (TGR) area. The variations in basic water quality parameters, different carbon forms, and CAA were investigated from November 2013 to October 2014. Results showed that the mean CAA value in JR was 0.67 ± 0.31 EU/106 cells. CAA was high during the flood stage, low during the impounding stage, and peaked on April 3, 2014 during the discharging stage. No significant difference was observed in the CAA of different sampling sites in JR. However, a significant difference was observed between the CAA of JR and that of the Yangtze River. Correlation analyses showed that water temperature, pH, algal cell density, and dissoluble organic carbon were positively correlated with CAA, whereas CO2 and dissoluble inorganic carbon were negatively correlated with CAA. A model for CAA and related parameters was built through principal component regression. The equation was expressed as follows: CAA = 0.116T + 0.00746Cells+0.0156pH−0.0157CO2−0.0150DIC+0.0135DOC+0.565. Results revealed that CAA in JR was controlled by multiple factors, which could be used for CAA monitoring. The model demonstrated a potential value in controlling algal blooms. |
Databáze: | OpenAIRE |
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