Distribution Of Contaminants Research Articles

Understanding the dynamics of enhanced light non-aqueous phase liquids (LNAPL) remediation at a polluted site: Insights from hydrogeophysical findings and chemical evidence

This study intricately unfolds a pioneering methodology for remediating contaminants in a persistent light non-aqueous phase liquids (LNAPL)-contaminated site. The remediation strategy seamlessly integrates enhanced desorption and in-situ chemical oxidation (ISCO), orchestrating the injection of PetroCleanze® (a desorbent) and RegenOx® (an oxidizer) through meticulously designed wells. These injections, based on detailed geological and hydrogeological assessments, aim at mobilizing residual contaminants for subsequent extraction. Real-time subsurface dynamics are investigated through geophysical monitoring, employing electrical resistivity tomography (ERT) to trace reagent migration pathways via their effect on bulk electrical conductivity. The integration of groundwater sampling data aims at providing additional insights into the transformations of contaminants in the spatiotemporal context. Vivid two-dimensional time-lapse ERT sections showcase the evolution of resistivity anomalies, providing high-resolution evidence of the heterogeneity, dispersion pathways of desorbent and oxidant, and residual LNAPL mobilization. Hydrochemical analyses complement this, revealing effective mobilization processes with increasing aqueous concentrations of total petroleum hydrocarbons (TPH) over time. Speciation analysis unveils the intricate interplay of desorption and oxidation, portraying the dynamic fractionation of hydrocarbon components. The hydrogeophysical and data-driven framework not only delivers qualitative and quantitative insights into reagent and contaminant distribution but also enhances understanding of spatial and temporal physio-chemical changes during the remediation process. Time-lapse ERT visually narrates the reagent's journey through time, while chemical analyses depict the unfolding processes of desorption and oxidation across space and time. The coupling of hydrogeophysical and chemical findings pictures the transformations of pollutants following the sequence of product injection and the push and pull activities, capturing the removal of mobilized contaminants through hydraulic barrier wells. This enhanced understanding proves instrumental towards optimizing and tailoring remediation efforts, especially in heterogeneous environmental settings. This study establishes a new standard for a sophisticated and innovative contaminant remediation approach, advancing environmental practices through the harmonized analysis of geophysical and chemical data.

Distribution and source of contamination of heavy metal mercury at paddy field in Mandailing Natal Regency, North Sumatera, Indonesia

Mandailing Natal Regency is administratively located in North Sumatera Province with 662,070 hectares width and a paddy field area of 40,051 hectares. Batang Gadis River stream is 180 KM long and became the source of livelihood for people in Mandailing Natal Regency as the source of drinking water, irrigation, and protein food source such as fish. Unlicensed Gold mining (PETI) occurred massively in Mandailing Natal Regency precisely at Sub-District Muara Sipongi, Sub-District Ulu Pungkut, Sub-District Huta Bargot, and Sub-District Naga Juang. The use of mercury for the amalgamation process in gold mining produces mercury waste which the run-off stream to the irrigation canals and at the end stream to Batang Gadis River Flow. This research conducted the distribution and source of contamination of heavy metal mercury at paddy fields in Mandailing Natal Regency, North Sumatera, Indonesia. The research was conducted to take soil sample analysis from paddy fields as much as 100 points from 20 paddy field locations near the amalgamation place or the water source for irrigation from Batang Gadis River that spread in five sub-districts. The soil sample analysis took for 25 cm depth. The results showed that the mercury concentration in all rice fields studied exceeded the quality standard threshold with the highest concentration found in Sub-District Naga Juang as much as 11.47 ppm followed by Sub-District Hutabargot with 10,77 ppm concentration. The factor that determines the paddy soil contamination by the mercury was the amalgamation waste which directly streams to irrigation canals compared with the paddy field with irrigation canals direct from the Batang Gadis River.

Distribution of mercury contamination on paddy fields in various levels of soil depth in gold mine area at Sub-District Hutabargot, Mandailing Natal Regency, Indonesia

Unauthorised Gold Mining in Mandailing Natal Regency could serious problems for the environment and human health. It is because waste from the amalgamation process contains mercury released into the waterways that are irrigation sources. The main damage impact from the mercury waste released into irrigation canals would be seen on the paddy field. For this reason, it is necerssary to tests and studies to see the contaminated level of mercury on paddy fields. This research was conducted from June to July 2023 in Sub-District Hutabargot, Mandailing Natal Regency by took soil sampling in the 0-10 cm, 11-20 cm, 21-20 cm, 31-40 cm, 41-50 cm, 51-60 cm, 61-70 cm, 71-80 cm, 81-90 cm, and 91-100 cm on soil depth in 7 sampling points. The resulting study obtained at least 170 amalgamation points that the waste released into the waters. The mercury content on the paddy soil in Sub-District Hutabargot which is irrigation irrigated by amalgamation process exceeding the threshold. There is an increase of mercury content in the 30 cm soil depth and then decreases with increasing soil depth. For a depth of more than 60 cm, the mercury content on the paddy soil is under the threshold.

Elucidating the influence of the lower and upper microbiological limits: When is a 3-class sampling plan useful to test for pathogens in food?

The potential advantages of using 3-class sampling plans in the management of pathogens in food has been discussed for years. Using a 3-class plan, some lots would be accepted if, among a total number of samples n, the pathogen was detected in no more than a predefined number of samples c (such as c = 1) exceeding a microbiological limit m, and no sample was at a level above a predefined maximal concentration M. We built upon and extended beyond published methodologies and developed a web application to evaluate the performance of 2-class and 3-class sampling plans. We showed that there is little benefit of a 3-class plan over a 2-class plan with equal values for m, n and c under the classical assumption of a lognormal distribution of bacteria concentration in the lot with a standard deviation of 0.8 log cfu/g, for m value set to “absence in 25g” and M set to values > 1 cfu/g. In this situation, the lot will almost always be rejected based on the criterion “>c detected samples” and will almost never (or seldom) be rejected based on only the criterion “at least one sample > M cfu/g”. However, the benefit of a 3-class plan is realized when the distribution of pathogens is not a simple lognormal but includes a proportion of samples contaminated beyond the lognormal distribution, at levels > M. When this is the case, the performance of a 3-class plan relative to the 2-class plan with equal values of m, n, and c improves, then becomes essentially equivalent, as the proportion of highly contaminated samples increases. The behavior of 3-class plan may be useful in such situations. While such distributions of pathogens have been observed across lots in the food supply, better characterization of within-lot contamination distribution in food is needed to better evaluate the performance of sampling plans.

Near real-time interpolative algorithm for modelling air quality in underground mines

As real-time air quality monitoring becomes more prevalent in US underground mines, it is important to provide the highest data reliability with the fewest possible sensors. Real-time sensors remain costly, and these costs are not exclusively financial; the time required to install, calibrate, and maintain real-time sensors poses a large barrier to widespread implementation. Current atmospheric monitoring systems typically rely on displaying point-specific values. This requires operators to infer real-time airborne contamination distributions. Monitoring and control software utilizing mine ventilation network (MVN) solvers has been implemented in limited cases because of their ability to simulate ventilation systems quickly, but these solvers use a one-dimensional representation of the mine, limiting spatial resolution of estimated distributions. Computational fluid dynamics (CFD) has likewise been considered as a means to improve spatial resolution, but processing times prevent its use as a basis for monitoring and control. For the real-time monitoring of airborne contamination distributions, we propose a spatial interpolation method that can estimate the distribution of airborne contaminants in near-real time. This method provides a middle ground between fast processing times and increased spatial resolution. With the use of a pathfinding algorithm and optimization through absolute percentage error minimization, this method outperforms spatial interpolation with a Euclidean distance. By providing contamination distribution information to operators, this method and its derivatives stand to outperform current atmospheric monitoring systems.

Critical Environmental Injustice: A Case Study Approach to Understanding Disproportionate Exposure to Toxic Emissions.

Public health research and environmental health research, specifically, have focused on toxic exposure-encompassing individuals or communities that are disproportionately exposed to contaminants that are harmful or potentially harmful to them. Yet, little research has applied critical environmental justice theory-characterized by the idea that marginalized communities need to be treated as indispensable rather than disposable-to the study of toxic exposure. To fill this gap, the current paper offers a case study approach applying critical environmental justice theory to the study of disproportionate and unequal exposure to toxic contaminants. This case study is of Kettleman City, a rural, unincorporated community in the heart of California's Central Valley (USA). This community experiences the co-location of environmental hazards, including residing at the intersection of two major highways and hosting a class I hazardous-waste landfill, which is one of the few licensed to accept PCBs. PCBs are a contaminant that has been linked with several adverse health outcomes, including cancers and low birthweight. Residents may also experience poor air quality from proximity to the highways. This case highlights the uneven distribution of pollution and environmental degradation that may be shouldered by the community, along with their experiences of adverse health and social impacts. This analysis reveals the importance of incorporating a critical environmental justice perspective to unpack experiences of not only disproportionate exposure but also disproportionate procedural and recognitional inequality. This research highlights the untapped potential of environmental justice to catalyze exposure science in challenging the unequal distribution of contaminants.

Geospatial evaluation and bio-remediation of heavy metal-contaminated soils in arid zones

Introduction: Soil pollution directly impacts food quality and the lives of both humans and animals. The concentration of heavy metals in Egypt’s drain-side soils is rising, which is detrimental to the quality of the soil and crops. The key to reducing the detrimental effects on the ecosystem is having accurate maps of the spatial distribution of heavy metals and the subsequent use of environmentally sustainable remediation approaches. The objective of this work is to assess soil contamination utilizing spatial mapping of heavy metals, determine contamination levels using Principal Component Analysis (PCA), and calculate both the contamination severity and the potential for bioremediation in the soils surrounding the main drain of Bahr El-Baqar. Furthermore, evaluating the capacity of microorganisms (bacteria, fungi, and “Actinomycetes) to degrade heavy elements in the soil.Methodology: 146 soil sample locations were randomly selected near the Bahr El-Baqar drain to examine the degree of soil pollution Ordinary Kriging (OK), method was used to map and analyze the spatial distribution of soil contamination by seven heavy metals (Cr, Fe, Zn, Cd, Pb, As, and Ni). Modified contamination degree (mCd) and PCA were used to assess the research area’s soil pollution levels. The process involved isolating, identifying, and classifying the microorganisms present in the soil of the study area. The study findings showed that variography suggested the Stable model effectively matched pH, SOM, and Cd values. Furthermore, the exponential model proved suitable for predicting Fe, Pb and Ni, while the spherical model was appropriate for Ni, Cr, and Zn.Results: The study revealed three levels of contamination, with an extremely high degree (EHDC) affecting approximately 97.49% of the area. The EHDC exhibited average concentrations of heavy metals: 79.23 ± 17.81 for Cr, 20,014.08 ± 4545.91 for Fe, 201.31 ± 112.97 for Zn, 1.33 ± 1.37 for Cd, 40.96 ± 26.36 for Pb, 211.47 ± 13.96 for As, and 46.15 ± 9.72 for Ni. Isolation and identification of microorganisms showed a significant influence on the breakdown of both organic and inorganic pollutants in the environment. The study demonstrated exceptionally high removal efficiency for As and Cr, with a removal efficiency reached 100%, achieved by Rhizopus oryzae, Pseudomonas aeruginosa, and Bacillus thuringiensis.Conclusion: This study has designated management zones for soil contamination by mapping soil pollutants, geo-identified them, and found potential microorganisms that could significantly reduce soil pollution levels.

Contaminant distribution and migration in roofing rainwater: Implications for sustainable utilization and pollution control

Understanding contaminant distribution and migration characteristics is crucial for the sustainable utilization of roofing rainwater resources, given the impacts of rapid urbanization and climate change. This study undertook the monitoring of 15 typical rainfall events in Xi'an, China, to analyze the distribution and migration of organic matter, nitrogen, and typical emerging contaminants (ECs) during wet deposition (WD), roofing erosion, and roof runoff (RR). The results indicate the concentration levels of organic matter, and nitrogen as follows: COD, 22.69 ± 1.52–132.83 ± 3.43 mg/L; TOC, 3.45 ± 0.22–27.64 ± 1.12 mg/L; TON, 4.99 ± 0.28–12.38 ± 1.55 mg/L; DTN, 4.54 ± 0.10–11.87 ± 0.83 mg/L; PTN, 1.32 ± 0.14–6.57 ± 0.40 mg/L. Additionally, specific emerging contaminants were found at the following concentrations: endocrine disruptors, 19.65–178.85 ng/L; pharmaceuticals, 17.78–67.45 ng/L; bactericides, 4.42–119.45 ng/L; personal care products, 7.79–44.10 ng/L; pesticides, 5.50–34.85 ng/L; flame retardants, 1.80–20.90 ng/L. The nitrogen pollution level surpasses that of road runoff and is predominantly attributed to WD. The detection rate of ECs is notably high, with Bisphenol A (BPA) being detected in up to 100 % of samples. Significant differences in pollutant distribution were identified between the initial and late stages of rainfall (P < 0.05). Weak first flush effects (1 < MFF20 < 2) were observed for pollutants present in the runoff of over 50 % of the rainfall events monitored. Furthermore, by controlling the initial 20 % of WD, an effective decrease in nitrogen flux below the threshold level was observed. Consequently, four modes of contaminant migration pathways and a novel strategy have been developed to guide the pollution control and sustainable utilization of roofing rainwater.

Spatial distribution of CO2 Impact on the indoor air quality of classrooms within a University

Indoor air quality (IAQ) remains a public and global concern. While CO2 does not pose health risks to occupants, high CO2 levels indicate insufficient ventilation, potentially accumulating pollutant concentrations. In buildings, occupants are identified as the main source of indoor carbon dioxide (CO2) through exhalation. Standard classrooms may have occupant density between 1.8 and 2.4m2/person. Therefore, the IAQ of classrooms and lecture theatres remain a concern. This study investigated airflow and contaminant (using CO2 as a proxy) distribution in two classrooms modelled using CFX a Computational Fluid Dynamics (CFD) software, verified against experimental measurements. The model provides the visualization of flow patterns so that the effects of external and internal flow fields in the classroom can be studied. The results show that there are large differences in classroom indoor ventilation performance due to the effects of wind direction and wind speed on building surface wind pressure from outdoor wind speeds. Windward high-pressure surfaces and leeward vortices created by building shading promote indoor air quality in buildings with windcatcher openings. The concentration distribution of CO in the classrooms showed an upward convergence with the thermal plume generated by the respiratory differences of the personnel and the temperature of the lighting equipment. The results of this study have important implications for improving classroom design guidelines for school buildings, especially in terms of ventilation strategies and air quality monitoring.

Microaeration promotes volatile siloxanes conversion to methane and simpler monomeric products

The ubiquitous use of volatile siloxanes in a myriad of product formulations has led to a widespread distribution of these persistent contaminants in both natural ecosystems and wastewater treatment plants. Microbial degradation under microaerobic conditions is a promising approach to mitigate D4 and D5 siloxanes while recovering energy in wastewater treatment plants. This study examined D4/D5 siloxanes biodegradation under both anaerobic and microaerobic conditions (PO2 = 0, 1, 3 %) using wastewater sludge. Results show that the use of microaeration in an otherwise strictly anaerobic environment significantly enhances siloxane conversion to methane. 16S rRNA gene sequencing identified potential degraders, including Clostridium lituseburense, Clostridium bifermentans and Synergistales species. Furthermore, chemical analysis suggested a stepwise siloxane conversion preceding methanogenesis under microaerobic conditions. This study demonstrates the feasibility of microaerobic siloxane biodegradation, laying groundwork for scalable removal technologies in wastewater treatment plants, ultimately highlighting the importance of using bio-based approaches in tackling persistent pollutants.

Occurrence and Health Risk Assessment of Phthalates in Municipal Drinking Water Supply of a Central Indian City.

In this study, the occurrence of phthalates in the municipal water supply of Nagpur City, India, was studied for the first time. The study aimed to provide insights into the extent of phthalate contamination and identify potential sources of contamination in thecity's tap water. We analyzed fifteen phthalates and the total concentration (∑15phthalates) ranged from 0.27 to 76.36µgL-1. Prominent phthalates identified were di-n-butyl phthalate (DBP), di-isobutyl phthalate (DIBP), benzyl butyl phthalate (BBP), di (2-ethylhexyl) phthalate (DEHP), di-n-octyl phthalate (DNOP), and di-nonyl phthalate (DNP). Out of the fifteen phthalates analyzed, DEHP showed the highest concentration in all the samples with the median concentration of 2.27µgL-1, 1.39µgL-1, 1.83µgL-1, 2.02µgL-1, respectively in Butibori, Gandhibaag, Civil Lines, and Kalmeshwar areas of the city. In 30% of the tap water samples, DEHP was found higher than the EPA maximum contaminant level of 6µgL-1. The average daily intake (ADI) of phthalates via consumption of tap water was higher for adults (median: 0.25µgkg-1day-1) compared to children (median: 0.07µgkg-1day-1). The hazard index (HI) calculated for both adults and children was below the threshold level, indicating no significant health risks from chronic toxic risk. However, the maximum carcinogenic risk (CR) for adults (8.44 × 10-3) and children (7.73 × 10-3) was higher than the threshold level. Knowledge of the sources and distribution of phthalate contamination in municipal drinking water is crucial for effective contamination control and management strategies.

Quantifying Disparities in Per- and Polyfluoroalkyl Substances (PFAS) Levels in Drinking Water from Overburdened Communities in New Jersey, 2019-2021.

Policymakers have become increasingly concerned regarding the widespread exposure and toxicity of per- and polyfluoroalkyl substances (PFAS). While concerns exist about unequal distribution of PFAS contamination in drinking water, research is lacking. We assess the scope of PFAS contamination in drinking water in New Jersey (NJ), the first US state to develop regulatory levels for PFAS in drinking water. We test for inequities in PFAS concentrations by community sociodemographic characteristics. We use PFAS testing data for community water systems (CWS) () from the NJ Department of Environmental Protection (NJDEP) from 2019 to 2021 and demographic data at the block group level from the US Census to estimate the demographics of the NJ population served by CWS. We use difference in means tests to determine whether CWSs serving "overburdened communities" (OBCs) have a statistically significant difference in likelihood of PFAS detections. OBCs are defined by the NJDEP to be census block groups in which: a) at least 35% of the households qualify as low-income, b) at least 40% of the residents identify as people of color, or c) at least 40% of the households have limited English proficiency. We calculate statewide summary statistics to approximate the relative proportions of sociodemographic groups that are served by CWSs with PFAS detections. We find that 63% of all CWSs tested by NJDEP from 2019 to 2021 had PFAS detections in public drinking water, collectively serving 84% of NJ's population receiving water from CWSs. Additionally, CWSs serving OBCs had a statistically significant higher likelihood of PFAS detection and a higher likelihood of exposure above state MCLs. We also find that a larger proportion of people of color lived in CWS service areas with PFAS detections compared to the non-Hispanic white population. These findings quantitatively identify disparities in PFAS contamination of drinking water by CWS service area and highlight the extent of PFAS drinking water contamination and the importance of PFAS remediation efforts for protecting environmental health and justice. https://doi.org/10.1289/EHP12787.

A framework for risk assessment of groundwater contamination integrating hydrochemical, hydrogeological, and electrical resistivity tomography method.

Groundwater contamination have been widely concerned. To reliably conduct risk assessment, it is essential to accurately delineate the contaminant distribution and hydrogeological condition. Electrical resistivity tomography (ERT) has become a powerful tool because of its high sensitivity to hydrochemical parameters, as well as its advantages of non-invasiveness, spatial continuity, and cost-effectiveness. However, it is still difficult to integrate hydrochemical, hydrogeological, and ERT datasets for risk assessment. In this study, we develop a general framework for risk assessment by sequentially jointing hydrochemical, hydrogeological, and ERT surveys, while establishing petrophysical relationships among these data. This framework can be used in groundwater-contaminated site and help to delineate the distribution of contaminants. In this study, it was applied to a nitrogen-contaminated site where field ERT survey and borehole information provided valuable measurement data for validating the consistency of contamination and hydrogeological condition. Risk assessment was conducted based on the refined results by the establishment of relationship between conductivity and contaminants concentration with . The contamination source was identified and the transport direction was predicted with the good agreement of = 0.965 between simulated and observed groundwater head, which can help to propose measures for anti-seepage and monitoring. This study thus enhances the reliability of risk assessment and prediction through a thought-provoking innovation in the realm of groundwater environmental assessment.

Integrated application of multiple indicators and geographic information system-based approaches for comprehensive assessment of environmental impacts of toxic metals-contaminated agricultural soils and vegetables

Conventional monitoring and mapping approaches are laborious, expensive, and time-consuming because they need a large number of data and consequently extensive sampling and experimental operations. Therefore, due to the growing concern about the potential of contamination of soils and agricultural products with heavy metals (HMs), a field experiment was conducted on 77 farm lands in an area of 2300 ha in the southeast of Shiraz (Iran) to investigate the source of metal contamination in the soils and vegetables and to model spatial distribution of HMs (iron, Fe; manganese, Mn; copper, Cu; zinc, Zn; cadmium, Cd; nickel, Ni, and lead, Pb) over the region using geographic information system (GIS) and geostatistical (Ordinary Kriging, OK) approaches and compare the results with deterministic approaches (Inverse Distance Weighting, IDW with different weighting power). Furthermore, some ecological and health risks indices including Pollution index (PI), Nemerow integrated pollution index (NIPI), pollution load index (PLI), degree of contamination (Cdeg), modified contamination degree (mCd), PIaverage and PIvector for soil quality, multi-element contamination (MEC), the probability of toxicity (MERMQ), the potential ecological index (RI), total hazard index (THI) and total carcinogenic risk index (TCR) based on ingestion, inhalation, and dermal exposure pathways for adults and children respectively for analyzing the noncarcinogenic and carcinogenic risks were calculated. Experimental semivariogram of the mentioned HMs were calculated and theoretical models (i.e., exponential, spherical, Gaussian, and linear models) were fitted in order to model their spatial structures and to investigate the most representative models. Moreover, principal component analysis (PCA) and cluster analysis (CA) were used to identify sources of HMs in the soils. Results showed that IDW method was more efficient than the OK approach to estimate the properties and HMs contents in the soils and plants. The estimated daily intake of metals (DIM) values of Pb and Ni exceeded their safe limits. In addition, Cd was the main element responsible for ecological risk. The PIave and PIvector indices showed that soil quality in the study area is not suitable. According to mCd values, the soils classified as ultra-high contaminated for Cu and Cd, extremely high for Zn and Pb, very high, high, and very low degree of contamination for Ni, Mn, and Fe, respectively. 36, 60, and 4 % of the sampling sites had high, medium, and low risk levels with 49, 21, and 9 % probability of toxicity, respectively. The maximum health risk index (HRI) value of 20.42 with extremely high risk for children was obtained for Ni and the HI for adults and children were 0.22 and 1.55, respectively. The THI values of Pb and Cd were the highest compared to the other HMs studied, revealing a possible non-cancer risk in children associated with exposure to these metals. The routes of exposure with the greatest influence on the THI and TCR indices were in the order of ingestion > inhalation > dermal. Therefore, ingestion, as the main route of exposure, is the route of greatest contribution to health risks. PCA analysis revealed that Fe, Mn, Cu, and Ni may originate from natural sources, while Fe was appeared to be controlled by fertilizer, and Cu primarily coming from pesticide, while Cd and Pb were mainly associated with the anthropogenic contamination, atmospheric depositions, and terrific in the urban soils. While, Zn mainly originated from fertilization. Findings are vital for developing remediation approaches for controlling the contaminants distribution as well as for monitoring and mapping the quality and health of soil resources.

Contamination and Spatial Distribution of Metal(loid)s in the Stream Sediment near the Greenhouse

As greenhouse horticulture continues to increase in South Korea, the effects of metal(loid)s from wastewater discharges on stream sediments were analyzed. A total of 106 samples were analyzed for cadmium (Cd), boron (B), copper (Cu), nickel (Ni), lead (Pb), zinc (Zn), chromium (Cr), manganese (Mn), and iron (Fe). The coefficient of variation (CV) of the metal(loid)s components was 96.58% for Mn, 93.40 for Zn, 62.47 for B, 58.90 for Pb, and 58.14 for Cd, suggesting anthropogenic sources. Correlation analysis suggested a cumulative source for Cd-Zn and B, and cluster analysis suggested an anthropogenic source for Cu, Pb, B, and Mn. The contamination factor (CF) suggested the need to trace the source of contamination to Pb (3.21 ± 1.89) and B (1.33 ± 0.83) and EF to Pb (3.30 ± 1.81) and B (1.44 ± 0.94). The analytical results identify anthropogenic sources of Pb, B, and Cd. The high contamination of Cd suggests the influence of mining areas, and Pb suggests the influence of traffic, fertilizers, pesticides, and fossil fuels in greenhouses, in addition to the influence of mines. B confirmed the impact of the facility’s vegetable wastewater and suggested the need to further examine the cumulative impact of Mn, Fe, etc. By utilizing the facility horticulture wastewater for ecological restoration and other agricultural uses, we aim to prevent stream sediment pollution and realize a sustainable agricultural environment.

Temporal evolution of plastic additive contents over the last decades in two major European rivers (Rhone and Rhine) from sediment cores analyses

Although global plastic distribution is at the heart of 21st century environmental concerns, little information is available concerning how organic plastic additives contaminate freshwater sediments, which are often subject to strong anthropogenic pressure. Here, sediment core samples were collected in the Rhone and the Rhine watersheds (France), dated using 137Cs and 210Pbxs methods and analysed for nine phthalates (PAEs) and seven organophosphate esters (OPEs). The distribution of these organic contaminants was used to establish a chronological archive of plastic additive pollution from 1860 (Rhine) and 1930 (Rhone) until today. Sediment grain size and parameters related to organic matter (OM) were also measured as potential factors that may affect the temporal distribution of OPEs and PAEs in sediments. Our results show that OPE and PAE levels increased continuously in Rhone and Rhine sediments since the first records. In both rivers, ∑PAEs levels (from 9.1 ± 1.7 to 487.3 ± 27.0 ng g−1 dry weight (dw) ± standard deviation and from 4.6 ± 1.3 to 65.2 ± 11.2 ng g−1 dw, for the Rhine and the Rhone rivers, respectively) were higher than ∑OPEs levels (from 0.1 ± 0.1 to 79.1 ± 13.7 ng g−1 dw and from 0.6 ± 0.1 to 17.8 ± 2.3 ng g−1 dw, for Rhine and Rhone rivers, respectively). In both rivers, di(2-ethylhexyl) phthalate (DEHP) was the most abundant PAE, followed by diisobutyl phthalate (DiBP), while tris (2-chloroisopropyl) phosphate (TCPP) was the most abundant OPE. No relationship was found between granulometry and additives concentrations, while organic matter helps explain the vertical distribution of PAEs and OPEs in the sediment cores. This study thus establishes a temporal trajectory of PAEs and OPEs contents over the last decades, leading to a better understanding of historical pollution in these two Western European rivers.

Polydimethylsiloxane dialysis passive sampler monitoring of chlorinated solvent contaminated sites – A field study

The complexity of the subsurface contaminated by chlorinated solvents such as trichloroethylene (TCE) makes it challenging to gain a complete understanding of contamination distribution and establish a conceptual site model (CSM). High-resolution vertical contaminant concentration profiling across both the unsaturated zone and the saturated aquifer is desirable for mapping the distribution of contamination. A Fick's law-based polydimethylsiloxane (PDMS) dialysis passive sampler was developed and evaluated on a field scale for its potential application. This study tests the passive sampler at two TCE contaminated sites, and the sampling results were compared with the results from different sampling methods based on the relative percent difference. The PDMS dialysis passive sampler obtained more representative soil gas concentrations in the unsaturated zone than a portable monitoring and sampling device, which caused soil gas flow disturbance by soil gas pumping during sample collection. In the saturated aquifer sampling, the results obtained by the PDMS dialysis passive sampler correlated well with those obtained by a commercial polyethylene passive diffusion bag, and exhibited higher sensitivity under low TCE concentration conditions. Furthermore, the PDMS dialysis passive samplers were densely deployed inside each monitoring well at multiple depths, at two sites, to achieve high-resolution monitoring across the unsaturated zone and saturated aquifer. Based on the PDMS dialysis sampler data, a more comprehensive three-dimensional CSM was systematically established.

Pharmaceutical Contaminants in Wastewater and Receiving Water Bodies of South Africa: A Review of Sources, Pathways, Occurrence, Effects, and Geographical Distribution

The focus of this review article was to outline the sources, pathways, effects, occurrence, and spatial distribution of the most prescribed pharmaceuticals in wastewater and receiving waters of South Africa. Google Scholar, Web of Science, and Scopus were used to gather data from different regions. A zone-wise classification method was used to determine the spatial distribution and data deficiencies in different regions of South Africa. This review revealed that over 100 pharmaceutical compounds have been reported in South Africa’s various water sources and wastewater, with most studies and highest concentrations being documented in Gauteng and Kwa-Zulu Natal. The pharmaceutical concentration in water samples ranged from ng/L to µg/L. Aspirin, ketoprofen, diclofenac, ibuprofen, naproxen, erythromycin, tetracycline, sulfamethoxazole, acetaminophen, streptomycin, ciprofloxacin, ampicillin, carbamazepine, atenolol, pindolol, efavirenz, and zidovudine residues were among the frequently detected pharmaceutical residues in water bodies and wastewaters of South Africa. Based on the spatial distribution data, Gauteng has the highest number of pharmaceuticals (108) detected in waste and surface water, with the Northern Cape having no monitoring evidence. Therefore, to precisely ascertain the geographical distribution of pharmaceutical contaminants in South Africa, this review recommends that further research be carried out to track their occurrence in aquatic environments and WWTP, especially in isolated regions like Limpopo.

Two‐stage soil core sampler to collect a less‐compressed core from forested areas

AbstractA two‐stage sampler was designed to investigate the vertical distribution of heavy metals and trace elements that contaminate forest soils through atmospheric deposition. The hand‐corer consisted of two L‐shaped aluminum angles that were driven separately into the soil to reduce friction between the corer wall and the soil. This allowed for soil cores to be collected with less compression than with traditional corers. The corer is easily made, inexpensive, lightweight, and easy to carry. The degree of compression of soil cores collected at a depth of 20 cm from various montane forests in Japan was usually less than 10% (collected core length &gt;18 cm); although, more compression occurred in soil with a higher air content. The degree of compression of soil cores collected from urban forests was lower than that in montane forests. When the two‐stage sampler was compared with a tube‐type sampler in a Japanese cedar (Cryptomeria japonica) forest, the compression degree of a soil core collected with the two‐stage sampler was a quarter that of the tube‐type sampler. The collection of less‐compressed soil cores will allow for reconstruction of a more accurate linear depth distribution of contaminants. To demonstrate this, we investigated the vertical distribution of Pb, Sb, and radioactive 137Cs in soil cores collected from conifer plantations on Mount Tsukuba, Japan, in April 2011. The migration centers of anthropogenic Pb, Sb, and 137Cs were positioned at 7.9, 7.5, and 3.3 cm from the ground surface, respectively. These distances probably reflect differences in the history of atmospheric pollution.

Bayesian hybrid-kernel machine-learning-assisted sensitivity analysis and sensitivity-relevant inverse modeling for groundwater DNAPL contamination

Accurate source characterization and transport parameter estimation is important when seeking to predict the spatiotemporal distribution of dense non-aqueous phase liquid (DNAPL) contaminants in groundwater. However, this is a complex multimodal search problem prone to equifinality and premature convergence, which leads to considerable error. To address this, a sensitivity-relevant dynamic swarm intelligence (SRD-SI) algorithm embedded in a homotopy-variation mechanism is proposed in the present study to rationally balance the inversion processes of sensitivity-varied source characteristics and DNAPL transport parameters. In this approach, global optima are progressively approached in conjunction with the homotopy variation of the search space. Furthermore, to avoid computationally expensive numerical model repetition during the sensitivity analysis and inverse iterations, a Bayesian-based optimization framework that combines multiple kernel functions in a kernel extreme learning machine (KELM) model is designed considering the complex site conditions and statistical characteristics of the input variables, thus creating the Bayesian hybrid KELM (BHK-ELM) model for the reliable surrogate modeling of numerical DNAPL-transport simulations. The results show that the BHK-ELM model recognizes and effectively reconstructs the complex input − output mapping of the numerical model by increasing the determination coefficient R2 to 0.9988 while improving the computational efficiency approximately 4500-fold. Because source characteristics and boundary conditions are far more sensitive than transport parameters to the contaminant distribution, conventional inverse modeling methods struggle to accurately identify these transport parameters. In contrast, the proposed inverse modeling system combining sensitivity analysis, swarm intelligence, and homotopy variation is more stable and provides significantly more accurate estimations for all unknown variables. Compared with the traditional SI algorithm, the homotopy-variation SRD-SI reduced the maximum inversion relative error from 46.22 % to 9.53 %, while the mean inversion relative error was reduced from 11.09 % to 3.90 %.