The transport mechanism of contaminated groundwater has been a problematic issue for many decades, mainly due to the bad impact of the contaminants on the quality of the groundwater system. In this paper, the exact solution of two-dimensional advection-dispersion equation (ADE) is derived for a semi-infinite porous media with spatially dependent initial and uniform/flux boundary conditions. The flow velocity is considered temporally dependent in homogeneous media however, both spatially and temporally dependent is considered in heterogeneous porous media. First-order degradation term is taken into account to obtain a solution using Laplace Transformation Technique (LTT) for both the medium. The solute concentration distribution and breakthrough are depicted graphically. The effect of different transport parameters is studied through proposed analytical investigation. Advection-dispersion theory of contaminant mass transport in porous media is employed. Numerical solution is also obtained using Crank Nicholson method and compared with analytical result. Furthermore, accuracy of the result is discussed with root mean square error (RMSE) for both the medium. This study has developed a transport and prediction 2-D model that allows the early remediation and removal of possible pollutant in both the porous structures. The result may also be used as a preliminary predictive tool for groundwater resource and management.

Agricultural use of pesticides continues to rise globally. Argentina ranks fifth in use. While pesticides help yields, they also pose risks to human health and the environment. Indoor dust can present high pesticide concentrations, raising concerns about chronic exposure in non-farming households. Studies of pesticides in indoor dust are few worldwide. This pioneering study aimed to identify and/or quantify for the first time pesticide occurrence in indoor dust from urban residences in the Pampas Region, southeast of Buenos Aires Province, Argentina. Pesticide residues in indoor dust from 48 non-agricultural homes in the Pampas plain region were analysed. Study participants completed questionnaires on household demographics, pet ownership, pesticide use, gardening, and habits like leaving shoes outside. We detected 41 out of 49 targeted pesticides, including metabolites and banned compounds. Seven of the 49 tested are dual-use compounds (i.e. pesticide & biocide or veterinary applications). The synergist piperonyl butoxide, the dual-use imidacloprid, and “agricultural only” pesticides carbaryl, glyphosate, and atrazine were detected in all dust samples. Glyphosate, 2,4-D, atrazine, imidacloprid, carbaryl, tetramethrin, and piperonyl butoxide had maximum concentrations exceeding 1, 000 μg kg−1. Complex mixtures of up to 32 residues were found per sample. Questionnaire responses revealed that most participants brought shoes inside (60 %), almost all had pets (93 %), and 51 % had used flea repellents (mainly imidacloprid and fipronil). Approximately 48 % reported pesticide use in the past year, and 19 % reported exposure via their (non-farmer) jobs, e.g., via disinfection and weeding. These findings highlight the prevalence of pesticide residues in residential settings and the need for further research on long-term exposure and risks. Improved tracking of agricultural, household, and mixed-use pesticide applications is crucial, particularly in regions heavily reliant on agriculture.

The macroplastics (MaPs) and microplastics (MiPs) polluting agricultural soils raise great concerns. Unfortunately, scientists know little about the occurrence of MaPs/MiPs in soil among different farming systems. In this study, we analyzed MaPs/MiPs in soils (0–30 cm) collected from six different farming systems (wheat-maize rotations, cotton, vegetables, permanent orchards, greenhouses with and without mulching) in Quzhou county, the North China Plain, by using fluorescence microscope and micro-Fourier transform infrared spectroscopy. The results showed that the abundance of MaPs and MiPs ranged from 0.2 to 46.8 kg ha−1, and 4.1 × 103–3.7 × 104 items kg−1, respectively. The prominent colors of the MaPs were white and black. The predominant shape, size and chemical composition of soil MiPs were fragments (45–62%), <1 mm (98–99%), and polyethylene (38–43%), respectively. MaPs were mainly detected in the 0–10 cm soil layer. MiP abundance in the 0–10 cm soil layer was significantly higher than that in the 20–30 cm soil layers among different farming systems, except for the fields with wheat-maize rotations and permanent orchards (p < 0.05). Overall, cotton fields showed the highest MaP and MiP abundance, followed by vegetable fields and orchards. Redundancy analysis revealed that tillage practices and plastic film management greatly influence the size distribution of MiPs. A strong negative correlation between large-sized plastic fractions (0.2–1 mm) and tillage frequency was tested while the years of application of plastic films and the abundance of plastic residues showed a strong positive correlation with small-sized plastic fractions (<0.2 mm). Our findings conclude that agricultural mulch films are an important source of MaPs and MiPs in agricultural soil and distributions are strongly influenced by agricultural management practices and farming systems. Further studies should take farming systems and farming practices into account, thereby exploring the potential mechanisms of plastic fragmentation and granularization in agricultural soil.

Water quality is under threat due to the presence of pathogenic and antibiotic-resistant bacteria. Escherichia coli (E. coli) serves as an indicator of faecal contamination and the potential presence of other harmful pathogens. Understanding E. coli concentrations helps in assessing the overall health risks associated with waterborne diseases and developing effective water management strategies. Therefore, we developed the first large-scale model, GloWPa-Ecoli C1 to simulate E. coli loads and concentrations in rivers and apply this model to China. The model provides the first comprehensive overview of microbial water quality across China's rivers. The model simulates E. coli concentrations in 2020 to range from 10−1.2 to 106.3 CFU/L, with 45.6 %–78.1 % of rivers exhibiting poor microbial water quality. Major hotspots of E. coli pollution are Haihe, Huaihe and Pearl River Basins. Direct discharge of human faecal waste contributes 80.2 % of the total E. coli load, while directly discharged livestock waste accounts for 13.1 %. To mitigate E. coli pollution in rivers in China, we recommend increasing human faecal waste collection rates, expanding wastewater treatment plant (WWTP) coverage, phasing out primary treatment WWTPs and eliminating direct livestock faecal waste discharge, particularly from smallholder farms. The study underscores the urgent need to improve microbial water quality in China's rivers. The findings provide actionable insights to inform policy development aimed at safeguarding water quality and public health. Furthermore, the modelling approach is applicable to other regions and microorganisms, offering a foundation for developing models to address antibiotic-resistant bacteria and other emerging water quality challenges.