Modified stochastic diffusion particle tracking model driven by skew Brownian motion: Analysis of sediment particle motion in turbulent flow under the effects of ejection and sweep.

Turbulent bursting events have been classified into outward interactions (Q1), ejections (Q2), inward interactions (Q3), and sweeps (Q4) in various studies. Ejections (Q2) and sweeps (Q4) have been identified as significant contributors to time consumption, momentum flux, and sediment flux. Additionally, research has shown that the distribution of these events varies nonuniformly at different bed elevations. Despite extensive investigations into the nonuniform distribution of turbulent bursting events, their impact on sediment transport has been rarely explored. In this work, we developed a modified stochastic diffusion particle tracking model (SD-PTM) driven by skew Brownian motion (SBM) using the stochastic Lagrangian approach to scrutinize sediment particle movement in turbulent flows. The model incorporates turbulent characteristics derived from a direct numerical simulation dataset, allowing for a comprehensive analysis of sediment particle dynamics. Moreover, the proposed model accounts for the nonuniform spatial distribution of ejection and sweep events, as well as the particle movement direction during these events. Numerical simulations of the model were conducted to trace sediment particle trajectories in the streamwise and vertical directions. The analysis of sediment transport involved calculating the variance of particle trajectories to examine anomalous diffusion. The model's performance was evaluated by comparing it with flow velocity and sediment concentration profiles obtained from measurements in previous studies. In conclusion, our study suggests that the motion of sediment particles in turbulent flow can be thoroughly investigated under extreme flow conditions using the modified SD-PTM driven by SBM.

Semi-analytical modeling of sediment-laden open-channel flows with the effects of stratification, hindered settling, and eddy viscosities.

This study proposes semi-analytical models for simultaneous distribution of fluid velocity and suspended sediment concentration in an open-channel turbulent flow using three kinds of eddy viscosities. Apart from the classical parabolic eddy viscosity which is based on a log-law velocity profile, we consider two recently proposed eddy viscosities based on the concept of velocity and length scales. To deal with the flows with high sediment concentration, several turbulent features such as the hindered settling mechanism and the stratification effect are incorporated in the model. The governing system of highly nonlinear differential equations is solved using the homotopy analysis method (HAM), which produces solutions in the form of convergent series. Numerical and theoretical convergence analyses are provided for all three types of eddy viscosities. The effects of parameters on the derived models are discussed physically. Experimental data on both dilute and non-dilute flows are considered to verify the HAM-based solutions. The effects of the stratification correction factor (ß) and the turbulent Schmidt number (α) reveal that they should be determined optimally for applicability of the proposed models in terms of accurate prediction with data. This optimal procedure required further investigation of these parameters, and, thus, an analysis of ß and α is carried out, which linked them with the particle diameter through particle settling velocity, reference fluid velocity, and reference sediment concentration by proposing regression equations. Furthermore, using the optimal values of the parameters, the proposed models corresponding to the eddy viscosities based on the exponentially decreasing turbulent kinetic energy function and von Karman's similarity hypothesis are seen to be superior to the model corresponding to a parabolic eddy viscosity. Finally, a comment on the HAM is made where it is observed that the method can remove the numerical singularity of the governing equations at the water surface, which arises because of the consideration of vanishing eddy viscosity thereat.

Development of a noise-assisted multivariate empirical mode decomposition framework for characterizing PM 2.5 air pollution in Taiwan and its relation to hydro-meteorological factors.

To better understand air pollution problems, the relationships between PM2.5 and hydro-meteorological variables are studied using a state-of-the-art multivariate nonlinear and non-stationary filtering method, noise-assisted multivariate empirical mode decomposition (NAMEMD), and the time-dependent intrinsic correlation (TDIC) algorithm. Three characteristic scales (annual, diurnal and semi-diurnal) are shown to be significant to PM2.5 characterization, based on using NAMEMD filtering. Temporal fluctuations of local correlations among PM2.5 and hydro-meteorological variables are presented. On diurnal and semi-diurnal scales, seasonal variation of the local correlation between temperature and humidity is observed. A combined wind speed and direction analysis can be conducted using the NAMEMD-based algorithm. The pollutant roses that are generated from the reconstructed wind directions reveal the sources of PM2.5 on different scales. PM2.5 is found to be related to land breeze at the diurnal scale and to winter monsoons at the annual scale. The scale-dependent wind direction that contributes to the increase of PM2.5 can be identified.

Effect of Floodplain Restoration on Photolytic Removal of Pharmaceuticals.

Floodplain restoration is popular to address excess nutrients, but its ability to enhance photolysis of emerging contaminants has not been evaluated. We used the numerical model MIKE-21 to simulate photolysis reactions within the inundated surface water of restored floodplains along a mid-size river. We examined both "high" and "low" floodplain scenarios where inundation occurs 5% (storms) and 50% (baseflow) of the year, respectively. We simulated photolysis of the pharmaceuticals morphine, codeine, and methamphetamine and, for context, compared it with nitrate removal (denitrification and plant uptake). Pollutant removal due to floodplain restoration was greater for the low floodplain (e.g., 18.8% for morphine) than for the high floodplain (5.6% for morphine) due to greater water exchange relative to channel flow. The fastest- and slowest-reacting pollutants (morphine and methamphetamine, respectively) were always transport- and reaction/kinetics-limited within floodplain surface water, respectively. Yet, those with intermediate decay-rate constants switched from reaction limitation to transport limitation as the floodplain length increased, and removal leveled off at an optimum length of ∼1000 m. However, as the floodplain width increased, the required floodplain length for 30% removal decreased. Optimal restored floodplain conditions for photolysis would maximize light exposure, which may differ from those for nutrients.

Determination of potential sources of PCBs and PBDEs in sediments of the Niagara River.

Sediments from Niagara River, an important waterway connecting two of the Great Lakes (Lake Erie to Lake Ontario), were analyzed for 14 congeners of polychlorinated biphenyls (PCBs) and 9 congeners of polybrominated diphenyl ethers (PBDEs) using accelerated solvent extraction and gas chromatography/mass spectrometry. Total concentrations of PCBs ranged from 1.7 to 124.6 ng/g were PCBs 138 and 153 were found in all samples. All sites but one showed PBDE in sediments with total concentrations as high as 148 ng/g, suggesting that PBDE is becoming an important class of POP. A land-use and coverage map was used to trace potential localized sources of PCB and PBDE contamination. Results indicate that the highest levels of PCBs and PBDEs were found in sediments collected from areas closest to the discharge locations of municipal wastewater treatment plants (WWTP) and local industries. This is the first study that suggests the importance of WWTP discharges as a potential source of PBDE contamination in the Great Lakes.