Estimation of total flux of polycyclic aromatic hydrocarbons facilitated by methane ebullition into water column from global lake sediments

Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model

The water body's suspended concentration reflects many coastal environmental indicators, which is important for predicting ecological hazards. The modeling of any concentration in water requires solving the settling-diffusion equation (SDE), and the values of several key input parameters therein (settling velocity ws, eddy diffusivity Ds, and erosion rates p(t)) directly determine the prediction performance. The time-consuming large-scale simulations would benefit if the parameter values could be estimated through available observations in the target sea area. The present work proposes a new optimization method for synchronously estimating the three parameters from limited concentration observations. First, an analytical solution to the one-dimensional vertical (1DV) SDE for suspended concentrations in an unsteady scenario is derived. Second, the near bottom suspended sediment concentration (SSC) profiles are measured with high-resolution observation. Third, the key parameters are optimized through the best fit of the measured SSC profiles and those modeled with the unsteady solution. Nonlinear least square fitting (NLSF) is introduced to judge the best fits automatically. The high-resolution concentration measurements in a specially-designed cylindrical tank experiment using the Yellow River Delta sediments test the proposed method. The method performs well in the initial period of turbulence generation when sediment resuspension is significant. It optimizes p(t), ws, and Ds with reasonable values and uniqueness of their combination. The proposed theory is a practical tool for quickly estimating key substance transport parameters from limited observations; it also has the potential to construct local parametric models to benefit the 3D modeling of coastal substance transport. Although the present work takes SSC as an example, it can be extended to any suspended particulate concentration in the water.

The greenhouse effect of antibiotics: The influence pathways of antibiotics on methane release from freshwater sediment

The impact of antibiotics on methane (CH₄) release from sediment involves both CH₄ production and consumption processes. However, most relevant studies lack a discussion of the pathways by which antibiotics affect CH₄ release and do not highlight the role played by the sediment chemical environment in this influence mechanism. Here, we collected field surface sediments and grouped them with various antibiotic combination concentration gradients (50, 100, 500, 1000 ng g^-1) under a 35-day indoor anaerobic constant temperature incubation. We found that the positive effect of antibiotics on sediment CH₄ release potential appeared later than the positive effect on sediment CH₄ release flux. Still, the positive effect of high-concentration antibiotics (500, 1000 ng g^-1) occurred with a lag in both processes. Also, the positive effect of high-concentration antibiotics was significantly higher than low-concentration antibiotics (50, 100 ng g^-1) in the later incubation period (p < 0.05). We performed a multi-collinearity assessment of sediment biochemical indicators, followed by a generalized linear model with negative binomial regression (GLM-NB) to obtain essential variables. In particular, we conducted the interaction analysis on CH₄ release potential and flux regression for the influence pathways construction. The partial least-squares path modeling (PLS-PM) demonstrated that the positive effect of antibiotics on CH₄ release (Total effect = 0.2579) was primarily attributed to their effect on the sediment chemical environment (Direct effect = 0.5107). These findings greatly expand our understanding of the antibiotic greenhouse effect in freshwater sediment. Further studies should more carefully consider the effects of antibiotics on the sediment chemical environment, and continuously improve the mechanistic studies of antibiotics on sediment CH₄ release.