The present study deals with groundwater pollution in multilayer aquifer. The model is based on decomposition of finite layers in semi-infinite groundwater reservoir. A constant pollutant source is injected at the input boundary of the uppermost layer (UML) of the landfill. At the intermediate inlet boundary, some average value for the longitudinal exchange of the input source concentration in each sub-layer is considered from the previous layer. Initially, the aquifer is not solute free in each sub layer that means some constant background contaminant concentration exists. In each sub layer, concentration gradient is assumed to be zero at the extreme boundary. The linear sorption and first orders decay terms are considered to model the groundwater pollution in multilayer aquifer. The Laplace transform technique is adopted to solve one-dimensional (1D) advection-dispersion equation (ADE). This approach is helpful to understand the solute migration in finite sub layers. The results are elucidated for the different time periods to examine the peak of pollutant concentration level in geological formations.

This study derives an analytical solution of a one-dimensional (1-D) Advection-Dispersion Equation (ADE) for solute transport with two contaminant sources incorporating the source term. Groundwater velocity is considered as a linear function of space while the dispersion as a nth power of velocity and analytical solutions are obtained for , and . The solution is derived using the Generalized Integral Transform Technique (GITT) with a new regular Sturm-Liouville Problem (SLP). Analytical solutions are compared with numerical solutions obtained in MATLAB pedpe solver and are found to be in good agreement. The obtained solutions are illustrated for linear combination of exponential input distribution and its particular cases. The dispersion coefficient and temporal variation of the source term on the solute distribution are demonstrated graphically for the set of input data based on similar data available in the literature. As an illustration, model predictions are used to estimate the time histories of the radiological doses of uranium at different distances from the sources boundary in order to understand the potential radiological impact on the general public for such problem.

Mathematical models for pollutant transport in semi-infinite aquifers are based on the advection-dispersion equation (ADE) and its variants. This study employs the ADE incorporating time-dependent dispersion and velocity and space-time dependent source and sink, expressed by one function. The dispersion theory allows mechanical dispersion to be directly proportional to seepage velocity. Initially the aquifer is assumed contaminant free and an additional source term is considered at the inlet boundary. A flux type boundary condition is considered in the semi-infinite part of the domain. Laplace transform technique (LTT) is then applied to obtain a closed form analytical solution. The effect of source/sink term as a function in the one-dimensional advection-dispersion equation is explained through the graphical representation for the set of input data based on similar data available in hydrological literature. Matlab software is used to obtain the graphical representation of the obtained solution. The obtained analytical solution of the proposed model may be helpful in the groundwater hydrology areas.

The aim of this study is to develop analytical solutions for one-dimensional advection-dispersion equation in a semi-infinite heterogeneous porous medium. The geological formation is initially not solute free. The nature of pollutants and porous medium are considered non-reactive. Dispersion coefficient is considered squarely proportional to the seepage velocity where as seepage velocity is considered linearly spatially dependent. Varying type input condition for multiple point sources of arbitrary time-dependent emission rate pattern is considered at origin. Concentration gradient is considered zero at infinity. A new space variable is introduced by a transformation to reduce the variable coefficients of the advection-dispersion equation into constant coefficients. Laplace Transform Technique is applied to obtain the analytical solutions of governing transport equation. Obtain results are shown graphically for various parameter and value on the dispersion coefficient and seepage velocity. The developed analytical solutions may help as a useful tool for evaluating the aquifer concentration at any position and time.

In the present study, analytical solutions are obtained for two-dimensional advection dispersion equation for conservative solute transport in a semi-infinite heterogeneous porous medium with pulse type input point source of uniform nature. The change in dispersion parameter due to heterogeneity is considered as linear multiple of spatially dependent function and seepage velocity whereas seepage velocity is nth power of spatially dependent function. Two forms of the seepage velocity namely exponentially decreasing and sinusoidal form are considered. First order decay and zero order production are also considered. The geological formation of the porous medium is considered of heterogeneous and adsorbing nature. Domain of the medium is uniformly polluted initially. Concentration gradient is considered zero at infinity. Certain new transformations are introduced to transform the variable coefficients of the advection diffusion equation into constant coefficients. Laplace Transform Technique (LTT) is used to obtain analytical solutions of advection-diffusion equation. The solutions in all possible combinations of temporally and spatially dependence dispersion are demonstrated with the help of graphs.

Marine debris has become a major form of pollution and a serious ecosystem health concern. The present study evaluates the accumulation, origin, and fate of debris in intertidal coral habitats of Mumbai-one of the world's highly populated coastal cities on the west coast of India. Predominantly, seven hermatypic coral species belonging to seven genera and five families were identified and mainly represented by Pseudosidastrea, Porites, and Bernardpora. In terms of number, the mean density of marine debris was 1.60 ± 0.13 SE items/m², which is higher than the global average. The mean density of plastic debris was 1.46 ± 0.14 SE items/m². Approximately 9% of total coral colonies were in physical contact with debris, and 22% of these colonies showed visible signs of partial bleaching. Single use plastic bags and wrappers were dominant plastic debris. The study area was characterized as ‘very poor cleanliness’ according to the Beach Quality Indexes, which include the Clean Coast Index, General Index, and Hazardous Items Index. The numerical model indicates the influence of river discharge and probable areas of plastic accumulation with high tidal currents in this region, maneuvering the spatial advection of litter in the nearshore areas. Combined analysis of ground-truthing and model simulation implies that the possible contributing sources of litter were representatives of land-based and sea-originated. The overall results point to increasing anthropogenic stressors threatening coastal coral communities, including marine debris pollution. It is advocated to adopt an integrated coastal zone management approach supported by coordinated policy frameworks could guide the mitigation of the debris footprint in coastal environments.

The theory-guided air quality model solves the mathematical equations of chemical and physical processes in pollution transportation numerically. While the data-driven model, as another scientific research paradigm with powerful extraction of complex high-level abstractions, has shown unique advantages in the PM₂.₅ prediction applications. In this paper, to combine the two advantages of strong interpretability and feature extraction capability, we integrated the partial differential equation of PM₂.₅ dispersion with deep learning methods based on the newly proposed DPGN model. We extended its ability to perform long-term multi-step prediction and used advection and diffusion effects as additional constraints for graph neural network training. We used hourly PM₂.₅ monitoring data to verify the validity of the proposed model, and the experimental results showed that our model achieved higher prediction accuracy than the baseline models. Besides, our model significantly improved the correct prediction rate of pollution exceedance days. Finally, we used the GNNExplainer model to explore the subgraph structure that is most relevant to the prediction to interpret the results. We found that the hybrid model is more biased in selecting stations with Granger causality when predicting.

In this study, we investigated the daily variability of PM₁₀ concentrations in January in Korea during the past 19 years (2001–2019), as well as the associated atmospheric circulation patterns. The daily PM₁₀ concentrations were classified into three cases: low (L; < 50 μg/m³), high (H; 50–100 μg/m³), and extremely high (EH; ≥ 100 μg/m³). We found that the strength of the East Asian winter monsoon influenced the PM₁₀ variability in the L and H cases. However, the EH cases were strongly influenced by the rapid growth of barotropic warming (anticyclonic anomaly) over the eastern North Atlantic and Northern Europe (ENE), and the stationary Rossby waves grew rapidly over Eurasia within only four days. Analysis of the quasi-geostrophic geopotential tendency budget revealed that the anticyclonic anomaly over the ENE was enhanced by vorticity advection. Linear baroclinic model experiments confirmed that vorticity forcing over the ENE induces favorable atmospheric conditions for the occurrence of EH PM₁₀ events in East Asia. As a result, the PM₁₀ concentration sharply increased sharply by approximately three times over four days. This study suggests that understanding atmospheric teleconnections between the ENE and East Asia can effectively predict the occurrence of EH PM₁₀ events in Korea, helping to reduce the human health risks from atmospheric pollution.

Oil spills occurring either in oceans or inland waterways may cause serious economic losses and ecological damage. Previous studies pertaining to oil spills and their consequences are primarily based on marine environments, whereas few have focused on oil spills occurring in inland waterways characterised by pronounced flow advection transport effects, which differ from the marine environment. A generalised flume experiment is performed to investigate the spread and transport of oil spills, and the relationships between the area and thickness of oil slick over time are analysed parametrically. An oil spill model combined with a depth–integrated two–dimensional non–uniform flow model, which is suitable for modelling inland waterways based on the Lagrangian method, is established; it is calibrated and verified using measured data from the flume experiment. The model is applied to three scenarios on the Luoqi reach of the Yangtze River, and spilled oil drifting trajectory maps are obtained and analysed considering the field wind parameters. The results show that the drift distance of the oil slick in the inland waterway is primarily controlled by the flow velocity with effects of advection transport; however, the oil spill trajectory spreads toward the wind direction when the flow velocity is relatively small compared with the wind speed. The results of this study serve as a reference for predicting the spread and transport of oil spills in inland waterways.

The identification and quantification of pharmaceutical and personal care products (PPCPs) in aquatic ecosystems is critical to further studies and elucidation of their fate as well as the potential threats to aquatic ecology and human health. This study used mass balances to analyse the sources, transformation, and transport of PPCPs in rivers based on the population and consumption habits of residents, the removal level of sewage treatment, the persistence and partitioning mechanisms of PPCPs, hydrological conditions, and other natural factors. Our results suggested that in an urbanized river of Guangzhou City, China, the daily consumption of PPCPs was the main reason for the variety of species and concentrations of PPCPs. Through the determination of PPCPs in the river water samples and a central composite design (CCD) methodology, the dominant elimination mechanisms of caffeine and carbamazepine from river water were photolysis and biodegradation, but that of triclosan was sorption rather than biodegradation. The mass data of 3 PPCPs were estimated and corroborated using the measured data to evaluate the accuracy of the mass balance. Finally, caffeine, carbamazepine and triclosan discharged from the Shijing River into the Pearl River accounted for 97.81%, 99.52%, and 28.00%, respectively, of the total mass of these three compounds in the surface water of Shijing River. The results suggest that photolysis are the main process of natural attenuation for selected PPCPs in surface waters of river systems, and the transfer processes of PPCPs is mainly attributed to riverine advection. In addition, the low concentration of dissolved oxygen inhibited the degradation of PPCPs in the surface water of Shijing River.