Exploring the Effects of Organic Matter Characteristics on Fe(II) Oxidation Kinetics in Coastal Seawater

Implications of ocean acidification on micronutrient elements-iron, copper and zinc, and their primary biological impacts: A review

This review has been undertaken to understand the effectiveness of ocean acidification on oceanic micronutrient metal cycles (iron, copper and zinc) and its potential impacts on marine biota. Ocean acidification will slow down the oxidation of Fe(II) thereby retarding Fe(III) formation and subsequent hydrolysis/precipitation leading to an increase in iron bioavailability. Further, the increased primary production sustains enzymatic bacteria assisted Fe(III) reduction and subsequently the binding of weaker ligands favours the dissociation of free Fe(II) ions, thus increasing the bioavailability. The increasing pCO2 condition increases the bioavailability of copper ions by decreasing the availability of free CO32- ligand concentration. The strong complexation by dissolved organic matter may decrease the bioavailable iron and zinc ion concentration. Since ocean acidification affects the bioavailability of essential metals, studies on the uptake rates of these elements by phytoplankton should be carried out to reveal the future scenario and its effect on natural environment.

Photodegradation Kinetics and Deep Learning-Based Intelligent Colorimetric Method for Bioavailability-Based Dissolved Iron Speciation

Via the photodegradation of dissolved iron (dFe) complexes in the euphotic zone, released free Fe(III) is the most important source of bioavailable iron for eukaryotic phytoplankton. There is an urgent need to establish bioavailability-based dissolved iron speciation (BDIS) methods. Herein, an intelligent system with dFe pretreatment and a colorimetric sensor is developed for real-time monitoring of newly generated Fe(III) ions. According to the photodegradation kinetics of dFe, including kinetic constant and photogenerated time of free Fe(III) ions, 3 sources, 6 kinds, and 12 species of dFe are determined by our photocatalytic-assisted colorimetric sensor and deep learning model within 20.0 min. The algal dFe-uptake for 4 days can be predicted by BDIS with correlation coefficient 0.85, which could be explained by the hard and soft acids and bases theory (HSAB) and density functional theory (DFT). These results successfully demonstrate the proof-of-concept for photodegradation kinetics-based speciation and bioavailability assessments of dissolved metals.