Novel Insights into the Molecular-Level Mechanism Linking the Chemical Diversity and Copper Binding Heterogeneity of Biochar-Derived Dissolved Black Carbon and Dissolved Organic Matter

Abstract

Biochar-derived dissolved black carbon (DBC) varies in chemical composition and significantly affects the environmental fate of metal ions. However, the intrinsic molecular composition of DBC fractions and their molecular interaction mechanisms with metal ions remain unclear. We propose a novel, molecular-level covariant binding mechanism to comparatively interpret the heterogeneities, active sites, and sequential responses of copper binding with molecular compounds in DBC and natural dissolved organic matter (DOM). Relatively large proportions of lipid/aliphatic/peptide-like compounds with low mass distributions and lignin-like compounds with oxidized/unsaturated groups existed in acidic-and alkaline-extracted DBC, respectively. A larger percentage of tannin-like/condensed aromatic compounds and higher average conditional stability constants (logK̅ Cu ) of visible fluorescent components were found for DOM than for DBC. Overall, 200−320 Da and 320−480 Da molecular components contributed significantly to the logK̅ Cu values of UVA and visible fluorescent components, respectively, in DBC/DOM. Nitrogenous groups likely exhibited stronger binding affinities than phenolic/carboxylic groups. The sequential copper-binding responses of molecular compounds in DBC/DOM generally followed the order lipid/aliphatic/peptide-like compounds → tannin-like compounds → condensed aromatic compounds. These insights will improve the prediction of the potential effects of DBC on various contaminants and the risks of biochar application to ecosystems.

Direct and Indirect Electron Transfer Routes of Chromium(VI) Reduction with Different Crystalline Ferric Oxyhydroxides in the Presence of Pyrogenic Carbon

“…A considerable amount of soluble Cr(III) in the solution might relate to the complexation with dissolved organic matter from biochar. 51 Biochar increased the reduction rate of Cr(VI) by Fe-L and Fe-H to 1.5−2.0 × 10 −3 and 1.8−2.7 × 10 −3 h −1 , respectively (Figure 3g). It is worth noting that no further change in Cr total , Cr(VI), and Cr(III) was found with ferric oxyhydroxide alone (i.e., without biochar addition) during the further 7 day reaction (Figures 3 and S2), and the decrease of Cr(VI) and increase of Cr(III) with no Fe presence only happened after biochar addition (Figure 3c,f).…”

Heterogeneous Dynamic Behavior and Synergetic Evolution Mechanism of Internal Components and Released Gases during the Pyrolysis of Aquatic Biomass

“… , 2D-COS analysis generated synchronous and asynchronous maps by extending one-dimensional forms of variations into two-dimensional domains. − The characteristics of synchronous and asynchronous maps were well interpreted by Noda’s rules . Briefly, if the peak/region signals in synchronous/asynchronous maps were the same, the overall change in spectral intensity at the v 1 variable occurred predominantly prior to that at the v 2 variable . The reaction order was reversed when the signs were different.…”

“…43 Briefly, if the peak/region signals in synchronous/asynchronous maps were the same, the overall change in spectral intensity at the v 1 variable occurred predominantly prior to that at the v 2 variable. 21 The reaction order was reversed when the signs were different. If the signal in the synchronous map was zero, the sequential order of intensity variations became indeterminate.…”

“…12,20 Twodimensional correlation spectroscopy (2D-COS) can solve the above problem and provide spectral band correlations and heterogeneous changes in response to external perturbations by interpreting spectral datasets. 21,22 Yang et al probed char formation reactions during the biomass pyrolysis via analyzing char functional groups and bond breakage processes using 2D-FTIR−COS. 23,24 Wang et al explored the dynamic changes in functional groups (e.g., evolution order) during biomass char formation.…”

“…The complexity of pyrolysis reactions and resultant gaseous mixtures make the interpretation of TG–FTIR–GC/MS data difficult, particularly when distinguishing the subtle emission characteristics of gaseous species. For example, the absorbance peaks in TG–FTIR spectra represent complex gaseous species that usually overlap, which makes it difficult to explore the dynamic changes occurring for different gases. , Two-dimensional correlation spectroscopy (2D-COS) can solve the above problem and provide spectral band correlations and heterogeneous changes in response to external perturbations by interpreting spectral datasets. , Yang et al probed char formation reactions during the biomass pyrolysis via analyzing char functional groups and bond breakage processes using 2D-FTIR–COS. , Wang et al explored the dynamic changes in functional groups (e.g., evolution order) during biomass char formation. , Based on the spectral data of gaseous products, 2D-COS can provide comprehensive information regarding the dynamic releases and synergetic evolution mechanisms of internal components and released gases during biomass pyrolysis. , However, the utility of TG–FTIR–GC/MS combined with 2D-COS to explore the heterogeneous emissions, transformations, and emission mechanisms of gaseous species still remains unclear during the real-time biomass pyrolysis.…”