Stable isotope fractionation of toluene under dynamic phase exchange was studied aiming at ascertaining the effects of gas-liquid partitioning and biodegradation of toluene stable isotope composition in liquid-air phase exchange reactors (Laper). The liquid phase consisted of a mixture of aqueous minimal media, a known amount of a mixture of deuterated (toluene-d) and non-deuterated toluene (toluene-h), and bacteria of toluene degrading strain Pseudomonas putida KT2442. During biodegradation experiments, the liquid and air-phase concentrations of both toluene isotopologues were monitored to determine the observable stable isotope fractionation in each phase. The results show a strong fractionation in both phases with apparent enrichment factors beyond −800‰. An offset was observed between enrichment factors in the liquid and the gas phase with gas-phase values showing a stronger fractionation in the gas than in the liquid phase. Numerical simulation and parameter fitting routine was used to challenge hypotheses to explain the unexpected experimental data. The numerical results showed that either a very strong, yet unlikely, fractionation of the phase exchange process or a – so far unreported – direct consumption of gas phase compounds by aqueous phase microorganisms could explain the observed fractionation effects. The observed effect can be of relevance for the analysis of volatile contaminant biodegradation using stable isotope analysis in unsaturated subsurface compartments or other environmental compartment containing a gas and a liquid phase.

The effectiveness and feasibility of the three biochar materials for remediation of arsenic (As) and lead (Pb) contaminated soil were explored in this study. Significant reduction of bioaccessibility and migration risks of both heavy metals have been explained mechanistically by incubation, column experiments and numerical simulation. Langmuir equation fitted As and Pb sorption isotherms better in the control and biochar (BC) amended soils, while Freundlich model was more suitable for iron modified biochar (Fe-BC) and sulfur/iron modified biochar (S/Fe-BC) amended soils, indicating that modified biochar promoted chemical adsorption process for As and Pb. For the three biochar materials, S/Fe-BC showed the best effects on reducing the bioavailability of As and Pb, with a decrease of 40.42%–64.21%. The reduction in bioaccessibility by metal portioning into available and non-available fractions was better for illustrating the mechanisms including adsorption, precipitation/coprecipitation and As(III) oxidation behind S/Fe-BC efficacy. Moreover, S/Fe-BC can effectively inhibit the leaching behavior of As and Pb under acid rain, which increased by 99.89% and 90.18%, respectively, compared with the control. The HYDRUS-1D modeling indicated that S/Fe-BC could continuously treat As (100 mg/L) and Pb (1000 mg/L) contaminated water for 16.22 years and 40.86 years, respectively, and ensure the groundwater quality criteria being met. Based on these insights, we believe that our study will provide meaningful information about the potentials of biochar derived materials for soil heavy metals’ remediation.

Radon is a natural radioactive gas present in the environment, which is considered as the second most important lung cancer cause worldwide. Currently, radon gas is under focus and was classified as contaminant of emerging concern, which is responsible for serious biological/health effects in human. In presented work we propose the numerical model and analysis method for radon diffusion rate measurements and radon transport parameters determination. The experimental setup for radon diffusion was built in a classical, two chamber configuration, in which the radon source and outlet reservoirs are separated by the sample being tested. The main difference with previously known systems is utilization of only one radon detector, what was achieved by a careful characterization of the Rn-222 source and development of a numerical model, which allows for exact determination of radon transport parameters by fitting simulated radon concentration profile in the outlet reservoir to experimental data. For verification of the developed system, several insulation materials commonly used in building industry and civil engineering, as well as, common building materials (gypsum, hardened cement paste, concrete) were tested for radon diffusion rate through these barriers. The results of radon transmittance, permeability and diffusion coefficients for investigated materials are in compliance with values known previously from the literature. The analysis method is fast and efficient, and requires measurement period varying from a dozen or so hours up to 2–3 days depending on material properties. The described method is entirely based on a numerical analysis of the proposed differential equation model using freely available SCILAB software and experimental data obtained during sample measurements.

The application of surfactants is an effective way to inhibit the migration of organic contaminants (OCs) from soil to plants, and thus would be a great candidate method for producing safe agricultural products in organic-contaminated farmland. In this study, it was found that cetyltrimethyl ammonium bromide (CTMAB) reduced the OCs in cabbage by 22.0–64.1%, and those in lettuce by 18.8–36.5%. We developed a mathematical model to predict the accumulation of OCs in plants in the presence of surfactants. The successive partitioning of OCs among three phases, namely, soil, soil water and plant roots, was considered. The equilibrium of OC between the soil and soil water was scaled using the sorption coefficient of OCs on soils normalized by the soil organic carbon (Kₒc) and carbon-normalized OCs sorption coefficient with the sorbed surfactants (Kₛₛ). To precisely calculate the Kₒc and Kₛₛ, the bioavailable and bound OCs were measured using a sequential extraction method. Linear positive correlations between the logarithm of Kₒc (or Kₛₛ) and the logarithm of the octanol-water partition coefficient (log Kₒw) of OCs were established for laterite soils, paddy soils and black soils. In the presence of CTMAB, the equilibrium of OCs between the soil water and plant roots was scaled using the carbon-normalized OC sorption coefficient with the sorbed surfactants (Kₛf), whose logarithmic value was linearly correlated with the log Kₒw of the OCs. A three-phase-successive partition-limited model was developed based on these relationships, demonstrating an average prediction accuracy of 76.6 ± 36.8%. Our results indicated that the decrease in bioavailable OCs in soils and the increase in sorption of OCs on roots should be taken into consideration when predicting plant uptake. This research provides a validated mathematical model for predicting the concentration of OCs in plants in the presence of surfactants.

The hydro-acoustic noise radiating from underwater tunnels during vehicle passage may be harmful to aquatic fauna, and this is a particular concern for endangered species. Therefore, the effects of underwater noise radiation and propagation on aquatic biodiversity must be investigated. In this study, the dynamic response of the sediment and tunnel structure in the Yangtze River in China was explored by conducting a field test, and the associated noise radiation from the tunnel was recorded and investigated. A three-dimensional numerical model was then developed to simulate the vibration of the tunnel-sediment coupling system induced by random traffic-flow models. Next, a modal acoustic transfer vector-based method was used to predict underwater noise radiation by use of a three-dimensional finite-element acoustic model. Finally, the accuracy of the simulated results was verified by comparison with measurements. The results showed that the noise radiation induced by passing vehicles was approximately 14 dB greater than the background noise, with a main frequency range of 12–25 Hz. The random traffic-flow model had obvious influence of the simulated noise level above 20 Hz. Vehicle-induced underwater noise may thus have a direct effect on fish species that can perceive low-frequency sound pressure. The proposed method can be used for further investigation of methods to reduce the effect of underwater noise on aquatic fauna, especially endangered species.

A dissolved air flotation (DAF) system is one of the water treatment processes that purifies contaminants through a buoyancy effect by attaching the moiety of micro-bubbles on their free surface. Since the DAF system was first used in the drinking water treatment in the 1960s, it has been recognized as an effective treatment for the water purification process. Most previous works laid great emphasis on the internal flow behaviors of fluid to improve the purification efficiency of the DAF system. Nevertheless, the practical implementation with a pilot plant indeed revealed some technical incompleteness for the DAF system. To circumvent for the technical incompleteness, numerical simulation based on computational fluid dynamics (CFD) has been carried out to understand the in-depth knowledge on internal flow phenomena in the DAF system. However, the standard k-ε turbulence model has been conventionally used in the most studies without any proper consideration process. Accordingly, the objectives of this study were to investigate the major effects on the internal flow behaviors for an efficient numerical simulation of DAF when a different turbulence model and micro-bubble parameters are used. As a result, the present study found that the standard k-ε model would be not proper for the internal flow simulation of the DAF process and a careful consideration would be required for a more accurate prediction. In addition, the present study examined a desirable internal flow pattern with various operating conditions of the micro-bubble. Consequently, the main findings of this study are expected to provide realistic information to related researchers for designing the DAF system with the optimal operating parameters.

A severe air quality degradation event occurred in the Santiago Metropolitan Area (SMA), Chile, in June 2014. Meteorological and air quality measurements from 11 stations in the area as well as numerical simulations using the Weather and Research Forecasting (WRF) model were used to explain the main reasons for the occurrence of elevated particulate matter (PM) concentrations. The conditions were characterized with formation of a coastal low in central Chile between the southeastern anticyclone and a high-pressure system over Argentina. At a local scale, these conditions generated a depression at the base of the inversion layer, an increase in the vertical thermal stability, lower humidity and low-wind conditions, which were conducive to a decrease in pollutant dispersion and insufficient ventilation of the polluted air. Measurements and simulations using the WRF model revealed a vertical structure of the boundary layer during these stagnant conditions and provided a basis for a trajectory analysis. The back-trajectory calculation showed that the transport of air parcels was contained in the valley during the highest concentrations. The analysis also enabled the definition of the threshold values of a simple indicator of air pollution (ventilation coefficient, VC), which confirmed the evolution of the episode and divided the observed daily concentrations into two groups, with one including values above the limits prescribed by the national air quality standards (NAQS) and the other including values below these limits. For the SMA, the daily PM concentrations above the NASQ limits were associated with an overall mean threshold value of VC below 500 m² s⁻¹ (for PM₂.₅) and 300 m² s⁻¹ (for PM₁₀). To apply the VC analysis to other pollutants and different geographic locations, different threshold values should be evaluated.

Stormwater is viewed as an alternative resource to mitigate water shortages. However, stormwater reuse is constrained due to the presence of many toxic pollutants such as hydrocarbons. Effective mitigation requires robust mathematical models for stormwater quality prediction based on an understanding of pollutant processes. However, the rise in global temperatures will impose changes to pollutant processes. This study has proposed a new perspective on modelling the build-up process of hydrocarbons, with a focus on volatile organic compounds (VOCs). Among organic compounds, VOCs are the most susceptible to changes as a result of global warming due to their volatility. Seven VOCs, namely, benzene, toluene, ethylbenzene, para-xylene, meta-xylene, ortho-xylene and styrene in road dust were investigated. The outcomes are expected to lay the foundation to overcoming the limitations in current modelling approaches such as not considering the influence of temperature and volatility, on the build-up process. A new conceptualisation is proposed for the classical build-up model by mathematically defining the volatility of VOCs in terms of temperature. Uncertainty in the re-conceptualised build-up model was quantified and was used to understand the build-up patterns in the future scenarios of global warming. Results indicated that for the likely scenarios, the variability in VOCs build-up gradually increases at the beginning of the dry period and then rapidly increases after around seven days, while the build-up reaches a near-constant value in a shorter dry period, limiting the variability. These initial research outcomes need to be further investigated given the expected impacts of global warming into the future.

Batch and saturated soil column experiments were conducted to investigate sorption and mobility of two ¹⁴C-labeled contaminants, the hydrophobic chlordecone (CLD) and the sulfadiazine (SDZ), in the absence or presence of functionalized multi-walled carbon nanotubes (MWCNTs). The transport behaviors of CLD, SDZ, and MWCNTs were studied at environmentally relevant concentrations (0.1–10 mg L⁻¹) and they were applied in the column studies at different times. The breakthrough curves and retention profiles were simulated using a numerical model that accounted for the advective-dispersive transport of all compounds, attachment/detachment of MWCNTs, equilibrium and kinetic sorption of contaminants, and co-transport of contaminants with MWCNTs. The experimental results indicated that the presence of mobile MWCNTs facilitated remobilization of previously deposited CLD and its co-transport into deeper soil layers, while retained MWCNTs enhanced SDZ deposition in the topsoil layers due to the increased adsorption capacity of the soil. The modeling results then demonstrated that the mobility of engineered nanoparticles (ENPs) in the environment and the high affinity and entrapment of contaminants to ENPs were the main reasons for ENP-facilitated contaminant transport. On the other hand, immobile MWCNTs had a less significant impact on the contaminant transport, even though they were still able to enhance the adsorption capacity of the soil.

Assessing build-up and wash-off process uncertainty is important for accurate interpretation of model outcomes to facilitate informed decision making for developing effective stormwater pollution mitigation strategies. Uncertainty inherent to pollutant build-up and wash-off processes influences the variations in pollutant loads entrained in stormwater runoff from urban catchments. However, build-up and wash-off predictions from stormwater quality models do not adequately represent such variations due to poor characterisation of the variability of these processes in mathematical models. The changes to the mathematical form of current models with the incorporation of process variability, facilitates accounting for process uncertainty without significantly affecting the model prediction performance. Moreover, the investigation of uncertainty propagation from build-up to wash-off confirmed that uncertainty in build-up process significantly influences wash-off process uncertainty. Specifically, the behaviour of particles <150 μm during build-up primarily influences uncertainty propagation, resulting in appreciable variations in the pollutant load and composition during a wash-off event.