Communities in low-income and middle-income countries (LMIC) are disproportionally affected by industrial pollution compared to more developed nations. This study evaluates the dispersal and associated health risk of contaminant-laden soil and dust at a copper (Cu) smelter in Tsumeb, Namibia. It is Africa’s only smelter capable of treating complex Cu ores that contain high arsenic (As) contents (<1%). The analyses focused on the primary trace elements associated with ore processing at the smelter: As, Cu, and lead (Pb). Portable X-Ray fluorescence spectrometry (pXRF) of trace elements in soils (n = 83) and surface dust wipes (n = 80) showed that elemental contamination was spatially associated with proximity to smelter operations. Soil concentrations were below US EPA soil guidelines. Dust wipe values were elevated relative to sites distal from the facility and similar to those at other international smelter locations (As = 1012 μg/m² (95% CI 687–1337); Cu = 1838 μg/m² (95% CI 1191–2485); Pb = 1624 μg/m² (95% CI 862–2385)). Source apportionment for Pb contamination was assessed using Pb isotopic compositions (PbIC) of dust wipes (n = 22). These data revealed that the PbIC of 73% (n = 16/22) of these wipes corresponded to the PbIC of smelter slag and tailings, indicating contribution from industrial emissions to ongoing exposure risk. Modeling of carcinogenic risk showed that dust ingestion was the most important pathway, followed by inhalation, for both adults and children. Dermal contact to trace elements in dust was also determined to pose a carcinogenic risk for children, but not adults. Consequently, contemporary smelter operations remain an ongoing health risk to the surrounding community, in spite of recent efforts to improve emissions from the operations.

Simulation model is very essential for predicting the environmental fate and the potential environmental consequences of chemical pollutants including those from accidental chemical spills. However very few of such simulation model is seen related to Chinese costal water body. As the first step toward our final goal to develop a simulation model for the prediction and the risk assessment of chemical pollutants in Chinese coastal water, this study developed a three-dimensional (3D) hydrodynamic model of Xiamen Bay (XMB). This hydrodynamic model was externally derived by meteorological data, river discharge and boundary conditions of XMB. We used the model to calculate the physical factors, especially water temperature, salinity and flow field, from June to September 2016 in XMB. The results demonstrated a good match between observations and simulations, which underscores the feasibility of this model in predicting the spatial-temporal concentration of chemical pollutants in the coastal water of XMB. Longitudinal salinity distributions and the mixing profile of river-sea interactions are discussed, including the obvious gradation of salinity from the river towards sea sites shown by the model. We further assumed that 1000 kg and 1000 mg/L of a virtual chemical pollutant leaked out from Jiulong River (JR) estuary (point source) and whole XMB (non-point source), respectively. The model illustrates that it takes three months for XMB to become purified when point source pollution occurs in the estuary, while half a year to be required in the case of non-point source pollution across the entire bay. Moreover, the model indicated that pollutants can easily accumulate in the western coastal zone and narrow waters like Maluan Bay, which can guide environmental protection strategies.

The occurrence of environmental antibiotic resistance genes (ARGs) are often attributed to selective pressure from antibiotics from point source pollution. However, the potential effects of natural production of antibiotics, environmental factors, and anthropogenic pressure on the development and spread of ARGs have not been fully investigated. This study evaluated the occurrence and distribution of erythromycin resistance methylase (erm) genes in urban soils. The ermA, ermB, ermC, ermD, ermF, ermG, ermT, and ermY genes were detected with detection frequencies ranging from 20% to 80% and abundances ranging between 5.95 × 101 and 6.94 × 106 copies g−1 dw soil. Both polyketide synthase (PKS) type I and type II biosynthesis genes—which are responsible for biosynthesis of polyketides, such as erythromycin—were detected in all soil samples with a range between 5.77 × 102 and 9.39 × 106 copies g−1 dw soil. The abundances of PKS genes were significantly correlated with 16S rRNA genes (r = 0.487 to 0.741, p < 0.001) and absolute abundances of ermB, ermC, ermD, ermG, and ermY (r = 0.302–0.490, p < 0.05), suggesting that the wide occurrence of ARGs in soils could be potentially driven by naturally produced antibiotics. Erythromycin was strongly correlated with ermB, ermC, ermF and ermY genes (r = 0.462 to 0.667, p < 0.05), but no significant correlation was observed between macrolides and PKS genes, suggesting other environmental factors may have contributed to detected macrolides. The fact that erm gene presented higher extent of variability than PKS genes in different land use types suggests that anthropogenic activity might also influence the occurrence of erm genes in urban soils.

Pollution risk from the discharge of industrial waste or accidental spills during transportation poses a considerable threat to the security of rivers. The ability to quickly identify the pollution source is extremely important to enable emergency disposal of pollutants. This study proposes a new approach for point source identification of sudden water pollution in rivers, which aims to determine where (source location), when (release time) and how much pollutant (released mass) was introduced into the river. Based on the backward probability method (BPM) and the linear regression model (LR), the proposed LR–BPM converts the ill-posed problem of source identification into an optimization model, which is solved using a Differential Evolution Algorithm (DEA). The decoupled parameters of released mass are not dependent on prior information, which improves the identification efficiency. A hypothetical case study with a different number of pollution sources was conducted to test the proposed approach, and the largest relative errors for identified location, release time, and released mass in all tests were not greater than 10%. Uncertainty in the LR–BPM is mainly due to a problem with model equifinality, but averaging the results of repeated tests greatly reduces errors. Furthermore, increasing the gauging sections further improves identification results. A real-world case study examines the applicability of the LR–BPM in practice, where it is demonstrated to be more accurate and time-saving than two existing approaches, Bayesian–MCMC and basic DEA.

The high wastewater volumes produced during citrus production at pre- and post-harvest level presents serious pesticide point-source pollution for groundwater bodies. Biobeds are used for preventing such point-source pollution occurring at farm level. We explored the potential of biobeds for the depuration of wastewaters produced through the citrus production chain following a lab-to-field experimentation. The dissipation of pesticides used pre- or post-harvest was studied in compost-based biomixtures, soil, and a straw-soil mixture. A biomixture of composted grape seeds and skins (GSS-1) showed the highest dissipation capacity. In subsequent column studies, GSS-1 restricted pesticides leaching even at the highest water load (462Lm⁻³). Ortho-phenylphenol was the most mobile compound. Studies in an on-farm biobed filled with GSS-1 showed that pesticides were fully retained and partially or fully dissipated. Overall biobeds could be a valuable solution for the depuration of wastewaters produced at pre- and post-harvest level by citrus fruit industries.

This review summarizes and analyzes available data in the literature (mostly after 2000) on the occurrence of dichlorodiphenyltrichloroethane (DDT) and its main metabolites, dichlorodiphenyldichloroethane (DDD) and chlorodiphenyldichloroethylene (DDE), in the environment of the Pearl River Delta (PRD), South China. Generally, the concentration levels of the sum of DDT, DDD, and DDE, designated as DDTs thereafter, have not significantly declined since 1983. However, the composition of DDTs residues has changed with time. DDTs in soil, freshwater sediment and freshwater fish species were mainly residues from chronological use. There is evidence that new point sources, such as dicofol and anti-fouling paint, may have contributed DDTs to various environmental compartments. Risk assessment against existing criteria indicated that the levels of DDTs in water and some fish species may pose adverse effects to humans or wildlife, and those in sediment/soil may also cause negative impacts to the eco-environment of the PRD. The occurrence, possible input sources, and biological effects of DDTs in the environment of the Pearl River Delta, South China, are reviewed.

A natural experiment indicated that a link between the presence and concentration of four elements, copper, lead, nickel, and zinc in the influent to two wastewater reclamation plants to the presence and concentrations of the same four elements in the tap water of residential properties. There were 36 populations of results that were assessed for the normality of their distribution, the difference in their median concentrations, the similarity in the ratios of their median concentrations, and the correlations of the concentrations. The results of this study suggest that brass corrosion is the major source of these four elements in the water reclamation plants influent and that there are two distinct populations of brass sources, those in the early stages of dezincification where the release of the non-copper elements is dominant and those in the later stages where the release of copper dominates and the type of brass that is corroding. Statistical analysis of residential tap waters and water reclamation plant influent showed that metals found in both came from brass corrosion.

This study determines spatial trends and congener patterns of 2378-substituted polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) in surficial sediments of Lakes Erie and Ontario. Sediments are enriched in 2378-PCDFs in Lake Ontario, and the PCDD/F concentrations increased from shallow near-shore sediments towards deep-water depositional zone sediments. In Lake Erie, sediments were dominated by octachlorodibenzo-p-dioxin, and the highest PCDD/F concentrations were observed in the western basin and the southern shoreline of the central basin with a decrease towards the eastern basin and the northern shoreline of the central basin. Principal components analysis revealed that chemical manufacture and disposal of chemical waste along the Niagara River has been a major PCDD/F source to Lake Ontario; while PCDD/Fs in Lake Erie are from multiple sources including industrial sources along the Detroit River, major tributaries along the southern shoreline of the lake, and atmospherically-derived material from the upper lakes and connecting channels. Lake-wide 2378-PCDD/F congener patterns are first reported in L. Erie and L. Ontario sediments.

Microplastics are emerging contaminants ubiquitously distributed in the environment, with rivers acting as their main mode of transport in surface freshwater systems. However, the relative importance of hydrologic processes and source-related variables for benthic microplastic distribution in river sediments is not well understood. We therefore sampled and characterized microplastics in river sediments across the Meramec River watershed (eastern Missouri, United States) and applied a hydrologic modeling approach to estimate the relative importance of river discharge, river sediment load, land cover, and point source pollution sites to understand how these environmental factors affect microplastic distribution in benthic sediments. We found that the best model for the Meramec River watershed includes both source-related variables (land cover and point sources) but excludes both hydrologic transport-related variables (discharge and sediment load). Prior work has drawn similar and dissimilar conclusions regarding the importance of anthropogenic versus hydrologic variables in microplastic distribution, though we acknowledge that comparisons are limited by methodological differences. Nevertheless, our findings highlight the complexity of microplastic pollution in freshwater systems. While generating a universal predictive model might be challenging to achieve, our study demonstrates the potential of using a modeling approach to determine the controlling factors for benthic microplastic distribution in fluvial systems.

In the past decades, research on water pollution microplastics (MPs) has intensified tremendously. However, the relationship between MPs and environmental factors in urban river networks is under researched. Our study selected 65 sampling sites from a sophisticated urban river network system in Shanghai Municipality, China. Here, the combined influence of land-use types, river width, and water quality parameters to explore MPs distribution patterns. We found that MPs abundance ranged from 0.7 to 24.3 items/L, and the spatial difference in abundance was significant at a limited number of sampling sites. Fibrous MPs were the most abundant MPs in the river system. 72.7% of MPs <3 mm. Of the ten polymers detected, polypropylene and polyethylene terephthalate were predominant. In addition, cotton fiber was the main non-plastic component found in the samples. Moreover, land-use types showed no significant impact on MPs in the buffer zone of the sampling sites. However, point source pollution may cause an abnormal increase in MPs abundance. Through redundant analysis, we found that the phytoplankton abundance (e.g., chlorophyll-a) was influenced by MPs shape, while the river width influence MPs size. Construction activities were identified as the leading point source of pollution for the abnormal increase in local MPs pollution. Our results will inform on MPs distribution patterns in the super-metropolis river system.