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1.
Environ Sci Technol ; 57(32): 12053-12062, 2023 08 15.
Article in English | MEDLINE | ID: mdl-37527409

ABSTRACT

Spectrophotometric acid-base titration is a simple and powerful technique to evaluate the properties of proton binding sites of natural organic matter (NOM) at environmentally relevant concentrations. However, it is challenging to quantify the chemical charges (Q) carried by NOM at these concentrations. Based on a previous work, which relates the variation of Q with the specific UV-vis differential absorbance (ΔAλ,pH) at a given wavelength (λ) and pH of a dissolved NOM sample, the present work proposes a method to investigate any NOM sample. It determines specific features in the absorbance spectra attributed to proton-inert chromophores (A0,λ) and to the deprotonation processes of carboxylic (A1,λ) and phenolic groups (A2,λ). It enables to select sample-specific wavelength (λmid), where both these functional groups significantly contribute to the variation of absorbance with pH. The linear regression analysis of Aλmid,pH vs Q for various NOM reference samples evidenced that the sample-specific slope (SNOM) and intercept (INOM) were related to the intrinsic spectroscopic properties of the sample (A0,λmid, A1,λmid, and A2,λmid). This approach can thus be used to approximate the Q values of the NOM samples at environmentally relevant concentrations: a pre-requisite for predicting the fate and behavior of metal ions in natural systems.


Subject(s)
Metals , Protons , Spectrum Analysis , Spectrophotometry , Ions , Humic Substances/analysis
2.
Environ Sci Technol ; 56(14): 10494-10503, 2022 07 19.
Article in English | MEDLINE | ID: mdl-35749641

ABSTRACT

Potentiometric acid-base titration curves collected on humic (nano)particles as a function of pH and salt concentration reflect the electrostatics of the particles and the amount of chemical charges (Q) they carry. In turn, the interpretation of titration data helps quantify their reactivity toward metals provided that both intrinsic chemical and nonspecific electrostatic contributions to proton binding are correctly unraveled. Establishing a titration curve requires several steps, i.e., blank subtraction, relative curve positioning with respect to the electrolyte concentration, and absolute curve positioning achieved by the estimation of particle charge Q0 at low pH. Failure to properly establish each step may lead to the misevaluation of nanoparticle charging behavior. Here, we report (i) a simple procedure to measure and position titration curves for humic substances (HS) versus salt concentration and (ii) an original approach for absolute curve positioning upon the exploitation of proton affinity spectra. The latter do not depend on Q0 and they thus constrain the titration data analysis using the soft Poisson-Boltzmann-based titration (SPBT) formalism for nanoparticles in the thick electric double-layer regime. We illustrate the benefits of our approach by analyzing titration measurements for a large range of humic nanoparticles and by comparing the outcome with results from the literature.


Subject(s)
Humic Substances , Protons , Catalytic Domain , Humic Substances/analysis , Hydrogen-Ion Concentration , Organic Chemicals , Potentiometry
3.
MethodsX ; 9: 101721, 2022.
Article in English | MEDLINE | ID: mdl-35592462

ABSTRACT

UV-vis spectrophotometric acid-base titration can characterize dissolved organic matter (DOM) acid-base properties. However, it requires incremental pH adjustment, which make the procedure time consuming and the results subjected to dilution effect. This study brings forth a new approach, referred as the "buffer method" for pH adjustments, by using carefully selected pH-buffers to adjust the pH. This, statistically validated method minimizes the pH adjustment time and lightens the laboratory work load. Chemical product cost associated with this novel method is slightly increased as compared to the previous approach, due to the necessity to use pH-buffers. • Buffer method: Acid-base titration by using buffer for pH adjustment • Buffer method validated by statistical means • Rapid, reliable and economical method.

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