Data-driven models are suitable for simulating biological wastewater treatment processes with complex intrinsic mechanisms. However, raw data collected in the early stage of biological experiments are normally not enough to train data-driven models. In this study, an integrated modeling approach incorporating the random standard deviation sampling (RSDS) method and deep neural networks (DNNs) models, was established to predict volatile fatty acid (VFA) production in the anaerobic fermentation process. check details The RSDS method based on the mean values (x¯) and standard deviations (α) calculated from multiple experimental determination was initially developed for virtual data augmentation. The DNNs models were then established to learn features from virtual data and predict VFA production. The results showed that when 20000 virtual samples including five input variables of the anaerobic fermentation process were used to train the DNNs model with 16 hidden layers and 100 hidden neurons in each layer, the best correlation coefficient of 0.998 and the minimal mean absolute percentage error of 3.28% were achieved. This integrated approach can learn nonlinear information from virtual data generated by the RSDS method, and consequently enlarge the application range of DNNs models in simulating biological wastewater treatment processes with small datasets.Wastewater treatment plants (WWTPs) have long been recognized as point sources of N2O, a potent greenhouse gas and ozone-depleting agent. Multiple mechanisms, both biotic and abiotic, have been suggested to be responsible for N2O production from WWTPs, with basis on extrapolation from laboratory results and statistical analyses of metadata collected from operational full-scale plants. In this study, random forest (RF) analysis, a machine-learning approach for feature selection from highly multivariate datasets, was adopted to investigate N2O production mechanism in activated sludge tanks of WWTPs from a novel perspective. Standardized measurements of N2O effluxes coupled with exhaustive metadata collection were performed at activated sludge tanks of three biological nitrogen removal WWTPs at different times of the year. The multivariate datasets were used as inputs for RF analyses. Computation of the permutation variable importance measures returned biomass-normalized dissolved inorganic carbon concentration (DIC·VSS-1) and specific ammonia oxidation activity (sOURAOB) as the most influential parameters determining N2O emissions from the aerated zones (or phases) of activated sludge bioreactors. For the anoxic tanks, dissolved-organic-carbon-to-NO2-/NO3- ratio (DOC·(NO2–N + NO3–N)-1) was singled out as the most influential. These data analysis results clearly indicate disparate mechanisms for N2O generation in the oxic and anoxic activated sludge bioreactors, and provide evidences against significant contributions of N2O carryover across different zones or phases or niche-specific microbial reactions, with aerobic NH3/NH4+ oxidation to NO2- and anoxic denitrification predominantly responsible from aerated and anoxic zones or phases of activated sludge bioreactors, respectively.Investigating contamination pathways and hydraulic connections in complex hydrological systems will benefit greatly from multi-tracer approaches. The use of non-toxic synthetic DNA tracers is promising, because unlimited numbers of tracers, each with a unique DNA identifier, could be used concurrently and detected at extremely low concentrations. This study aimed to develop multiple synthetic DNA tracers as free molecules and encapsulated within microparticles of biocompatible and biodegradable alginate and chitosan, and to validate their field utility in different systems. Experiments encompassing a wide range of conditions and flow rates (19 cm/day-39 km/day) were conducted in a stream, an alluvial gravel aquifer, a fine coastal sand aquifer, and in lysimeters containing undisturbed silt loam over gravels. The DNA tracers were identifiable in all field conditions investigated, and they were directly detectable in the stream at a distance of at least 1 km. The DNA tracers showed promise at tracking fast-flowing water in the stream, gravel aquifer and permeable soils, but were unsatisfactory at tracking slow-moving groundwater in the fine sand aquifer. In the surface water experiments, the microencapsulated DNA tracers’ concentrations and mass recoveries were 1-3 orders of magnitude greater than those of the free DNA tracers, because encapsulation protected them from environmental stressors and they were more negatively charged. The opposite was observed in the gravel aquifer, probably due to microparticle filtration by the aquifer media. Although these new DNA tracers showed promise in proof-of-concept field validations, further work is needed before they can be used for large-scale investigations.Microplastic (MP) has been identified as an emerging vector that transports hydrophobic organic compounds (HOCs) across aquatic environments due to its hydrophobic surfaces and small size. However, it is also recognized that environmental factors affect MP’s chemical vector effects and that attached biofilms could play a major role, although the specific mechanisms remain unclear. To explore this issue, an in situ experiment was conducted at Xiangshan Bay of southeastern China, and dynamics of HOCs (i.e., polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs)) and bacterial communities related to the model MP (i.e., PE fibers) were analyzed and compared. Through bacterial characterizations including the 16S rRNA approach, higher summer temperatures (31.4 ± 1.07 °C) were found to promote colonizing bacterial assemblages with larger biomasses, higher activity and more degrading bacteria than winter temperatures (13.3 ± 2.49 °C). Consequently, some sorbed pollutants underwent significant dee that MP’s HOC vector effects are essentially determined by interactions between attached pollutants and microbial assemblages, which are further related to bacterial activity and pollutant features. Further studies of biofilm effects on MP toxicity and on the metabolic pathways of MP-attached HOCs are required.