In this study, the positive matrix factorization (PMF) source apportionment model was employed to quantify the contributions of airport activities to particle number concentrations (PNCs) at Amsterdam Schiphol. Time-resolved particle number size distributions in parallel with the concentrations of auxiliary variables, including gaseous pollutants (NOₓ and CO), black carbon, PM₂.₅ mass, and number of arrivals/departures were measured for 32 sampling days over a 6-month period near Schiphol airport to be used in the model. PMF results revealed that airport activities, cumulatively, accounted for around 79.3% of PNCs and our model segregated them into three major groups: (i) aircraft departures, (ii) aircraft arrivals, and (iii) ground service equipment (GSE) (with some contributions of local road traffic, mostly from airport parking lots). Aircraft departures and aircraft arrivals showed mode diameters <20 nm and contributed, respectively, to 46.1% and 26.7% of PNCs. The factor GSE/local road traffic, with a mode diameter of around 60–80 nm, accounted for 6.5% of the PNCs. Road traffic related mainly to the surrounding freeways was characterized with a mode diameter of 30–40 nm; this factor contributed to 18.0% of PNCs although its absolute PNCs was comparable with that of areas heavily impacted by traffic emissions. Lastly, urban background with a mode diameter at 150–225 nm, had a minimal contribution (2.7%) to PNCs while dominating the particle volume/mass concentrations with a contribution of 58.2%. These findings illustrate the dominant role of the airport activities in ambient PNCs in the surrounding areas. More importantly, the quantification of the contributions of different airport activities to PNCs is a useful tool to better control and limit the increased PNCs near the airports that could adversely impact the health of the adjacent urban communities.

Stibnite (Sb₂S₃) dissolution and transformation on mineral surfaces are the fundamental steps controlling the fate of antimony (Sb) in the environment. The molecular-level understanding of Sb₂S₃-mineral-water interfacial reactions is of great importance. Herein, Sb₂S₃ oxidative dissolution and sequestration on pyrite (FeS₂) were explored. The results show that FeS₂ accelerated the rate of Sb₂S₃ oxidative dissolution by a factor of 11.4-fold under sunlight due to heterogeneous electron transfer. The electron transfer from Sb₂S₃ to FeS₂ separated photogenerated hole (h⁺) and electron (e⁻) pairs, facilitating the generation of hydroxyl radicals (OH) on Sb₂S₃ and FeS₂, and superoxide radicals (O₂⁻) on FeS₂. Surface O₂⁻ was the dominant oxidant for Sb(III) oxidation with 91% contribution, as evidenced by radical trapping experiments. OH was preferentially adsorbed on Sb₂S₃, but was released with Sb₂S₃ dissolution, and subsequently contributable to Sb(III) oxidation in solution. The Sb(III) oxidation and sequestration on FeS₂ surface coupled Fe²⁺/Fe³⁺ cycling and inhibited FeS₂ dissolution, as evidenced by X-ray absorption near edge structure and X-ray photoelectron spectroscopy. The insights gained from this study further our understanding of Sb₂S₃ transformation and transport at the environmental mineral-water interfaces.

A widespread monitoring network of Airbox microsensors was implemented since 2016 to provide high-resolution spatial distributions of ground-level PM₂.₅ data in Taiwan. We developed models for estimating ground-level PM₂.₅ concentrations for all the 3 km × 3 km grids in Taiwan by combining the data from air quality monitoring stations and the Airbox sensors. The PM₂.₅ data from the Airbox sensors (AB-PM₂.₅) was used to predict daily mean PM₂.₅ levels at the grids in 2017 using a semiparametric additive model. The estimated PM₂.₅ level at the grids was further applied as a predictor variable in the models to predict the monthly mean concentration of PM₂.₅ at all the grids in the previous year. The modeling–predicting procedures were repeated backward for the years from 2016 to 2006. The model results revealed that the model R² increased from 0.40 to 0.87 when the AB-PM₂.₅ data were included as a nonlinear component in the model, indicating that AB-PM₂.₅ is a significant predictor of ground-level PM₂.₅ concentration. The cross-validation (CV) results demonstrated that the root of mean squared prediction errors of the estimated monthly mean PM₂.₅ concentrations were smaller than 5 μg/m³ and the R² of the CV models of 0.79–0.88 during 2006–2017. We concluded that Airbox sensors can be used with monitoring data to more accurately estimate long-term exposure to PM₂.₅ for cohorts of small areas in health impact assessment studies.

In Dhaka, Bangladesh, fine particulate matter (PM₂.₅) air pollution shows strong seasonal trends, with significantly higher mean concentrations during winter than during the monsoon (winter = 178.1 μg/m³ vs. monsoon = 30.2 μg/m³). Large-scale open burning of post-harvest agricultural waste across the Indo-Gangetic Plain is a major source of PM₂.₅ air pollution in northern India during the non-monsoon period. This study evaluates the extent to which the seasonal differences in PM₂.₅ pollution concentrations in Dhaka are accounted for by biomass-burning vs. fossil-fuel combustion sources. To assess this, an index was developed based on elemental potassium (K) as a marker for biomass particulate matter, after adjusting for soil-associated K contributions. Alternatively, particulate sulfur was employed as a tracer index for fossil-fuel combustion PM₂.₅. By simultaneously regressing total PM₂.₅ on S and adjusted K, the PM₂.₅ mass for each day was apportioned into: 1) fossil-fuels combustion associated PM₂.₅; 2) biomass-burning associated PM₂.₅; and, 3) all other PM₂.₅. The results indicated that fossil-fuel combustion contributed 21.6% (19.5 μg/m³), while biomass contributed 40.2% (36.3 μg/m³) of overall average PM₂.₅ from September 2013 to December 2017. However, the mean source contributions varied by season: PM₂.₅ in Dhaka during the monsoon season was dominated by fossil-fuels sources (44.3%), whereas PM₂.₅ mass was dominated by biomass-burning (41.4%) during the remainder of the year. The contribution to PM₂.₅ and each of its source components by transport of pollution into Dhaka during non-monsoon time was also evaluated by: 1) Conditional bivariate (CBPF) and pollution rose plots; 2) Concentration weighted trajectories (CWT), and; 3) NASA satellite photos to identify aerosol loading and fire locations on high pollution days. The collective evidence indicates that, while the air pollution in Dhaka is contributed to by both local and transboundary sources, the highest pollution days were dominated by biomass-related PM₂.₅, during periods of crop-burning in the Indo-Gangetic Plain.

The increasing production and applications of graphene oxide (GO, a novel carbon nanomaterial) have raised numerous environmental concerns regarding its ecological risks. Triphenyl phosphate (TPhP) disperses in water and poses an increasing hazard to the ecosystem and human health. It is critical to study the environmental responses and molecular mechanisms of GO and TPhP together to assess both chemicals; however, this information is lacking. The present work revealed that GO promoted the bioaccumulation of TPhP in zebrafish larvae by 5.0%–24.3%. The TPhP-induced growth inhibition of embryos (malformation, mortality, heartbeat, and spontaneous movement) at environmentally relevant concentrations was significantly amplified by GO, and these results were supported by the downregulated levels of genes and proteins associated with cytoskeletal construction and cartilage and eye development. TPhP induced negligible alterations in the genes or proteins involved in oxidative stress and apoptosis, but those related proteins were all upregulated by GO. GO and TPhP coexposure activated the mTOR signaling pathway and subsequently promoted apoptosis in zebrafish by potentiating the oxidative stress induced by TPhP, presenting synergistic toxicity. These findings highlight the potential risks and specific molecular mechanisms of combining emerging carbon nanomaterials with coexisting organic contaminants.

Antibiotic resistance is a major public health concern. Triclosan is an antimicrobial compound with direct links to antibiotic resistance that was widely used in soaps in the U.S. until its ban by the U.S. Food and Drug Administration. Benzalkonium chloride (BAC), a quaternary ammonium compound, has widely replaced triclosan in soaps marketed as an antibacterial. BAC has been detected in surface waters and its presence will likely increase following increased use in soap products. The objective of this study was to determine the effect of BAC on relative abundance of antibiotic resistance in a bacterial community from a surface water used as a source for drinking water treatment. Bench-scale microcosm experiments were conducted with microbial communities amended with BAC at concentrations ranging from 0.1 μg L⁻¹ to 500 μg L⁻¹. Phenotypic antibiotic resistance was quantified by culturing bacteria in the presence of different antibiotics, and genotypic resistance was determined using qPCR to quantify antibiotic resistance genes (ARGs). BAC at concentrations ranging from 0.1 μg L⁻¹ to 500 μg L⁻¹ was found to positively select for bacteria resistant to ciprofloxacin and sulfamethoxazole, and negatively select against bacteria with resistance to six other antibiotics. Exposure to BAC for 14 days increased the relative abundance of sul1 and blaTEM. This study re-highlights the importance of employing both culture and non-culture-based techniques to identify selection for antibiotic resistance. The widespread use of BAC will likely impact antibiotic resistance profiles of bacteria in the environment, including in source waters used for drinking water, wastewater treatment plants, and natural waterways.

In February 2014, the coalmine adjacent to the Hazelwood Power Station in the Latrobe Valley of Victoria, Australia, caught fire, with residents from the nearby town of Morwell and the wider area exposed to smoke for six weeks. Although there was evidence linking the mine-fire event with psychological distress, no studies have evaluated the degree of distress in relation to the level of smoke exposure. We aimed to investigate the exposure-response relationship between particulate matter 2.5 μm or less in diameter (PM₂.₅) released during the Hazelwood mine fire event and long-term symptoms of posttraumatic distress in the affected community, including the consideration of other key factors. A total of 3096 Morwell residents, and 960 residents from the largely unexposed comparison community of Sale, were assessed for symptoms of posttraumatic distress 2.5 years after the Hazelwood incident using the Impact of Events Scale-Revised (IES-R). Individual-level PM₂.₅ exposure was estimated by mapping participants’ self-reported location data on modelled PM₂.₅ concentrations related to the mine fire. Multivariate linear regression was used to evaluate the exposure-response relationship. Both mean and peak exposure to mine fire-related PM₂.₅ were found to be associated with participant IES-R scores with an interaction effect between age and mean PM₂.₅ exposure also identified. Each 10 μg/m³ increase in mean PM₂.₅ exposure corresponded to a 0.98 increase in IES-R score (95% CI: 0.36 to 1.61), and each 100 μg/m³ increase in peak PM₂.₅ exposure corresponded to a 0.36 increase (95% CI: 0.06 to 0.67). An age-effect was observed, with the exposure-response association found to be stronger for younger adults. The results suggest that increased exposure to PM₂.₅ emissions from the Hazelwood mine fire event was associated with higher levels of psychological distress associated with the mine fire and the most pronounced effect was on younger adults living in the affected community.

Plastic pollution has been reported in sediment, surface water and biota of freshwater systems especially in Europe, North and South America, and Asia with limited studies focussing on African great lakes. This study therefore investigated the occurrence, abundance and distribution of micro-, meso- and macro-plastic debris along shores and sediment of northern Lake Victoria. The abundance of micro-, meso- and macro-plastics measured as particles/kg dry sediment were in range of 0–1102, 0–218 and 0–100 respectively in shoreline sediment and 0–108, 0–33 and 0–77 respectively in lake sediment. The mean abundance of micro-, meso- and macro-plastic debris at fish landing beaches (75.2 ± 50.0, 16.7 ± 8.1 and 18.1 ± 4.6 respectively) were higher than what was recorded at recreational beaches (1.5 ± 0.6, 3.1 ± 3.1 and 3.8 ± 3.8 respectively). Similarly, mean abundance of micro-, meso- and macro-plastic debris in lake sediment were higher in areas of fish landing beaches (9.5 ± 2.6, 2.1 ± 1.5 and 7.7 ± 4.5 respectively) than what was recorded in areas of recreational beaches (0.7 ± 0.7, 0.2 ± 0.1, and 0 ± 0 respectively). Films, filaments, fragments, foam and pellets were the plastic types, with the shoreline sediment dominated by films (>54%) while lake sediment was dominated by filaments (>55%), across size groups (micro-, meso- and macro-plastics). Spearman’s rank correlation indicated strong and significant correlation between abundance of micro- and meso-plastics for total plastic, film plastic and fragment plastic in shoreline sediment. Significant correlation between macroplastics in shoreline sediment and microplastics in lake sediment for total plastics was observed. The FTIR analysis revealed that polyethylene, polypropylene, Polyethylene Terephthalate, Polyamide (nylon), and polyvinyl chloride were the major polymers. These results demonstrated that fish landing beaches along Lake Victoria are hotspot areas for plastic pollution of the lake and should therefore be targeted for management of plastic pollution of Lake Victoria.

Microplastics (MPs) are an emerging threat to ecosystem functioning and biota. The major sources of MPs are terrestrial and agricultural lands. But their fate, concentration in the terrestrial environment, and effects on soil and biota are poorly understood. There is a growing body of concern about the adverse effects of MPs on soil-dwelling organisms such as microbes in mycorrhizae and earthworms that mediate essential ecosystem services. Environmental concentrations and effects of MPs are considered to increase with increasing trend of its global production. MPs in the soil could directly impact plants through blocking the seed pore, limiting the uptake of water and nutrient through roots, aggregation, and accumulation in the root, shoot, and leaves. However, MPs can also indirectly impact plants by affecting soil physicochemical characteristics, soil-dwelling microbes, and fauna. An affected soil could impact plant community structure and perhaps primary production. In this article, we have assessed the potential direct and indirect impacts of MPs on plants. We have discussed both the positive and negative impacts of MPs on plants in terrestrial systems based on currently available limited literature on this topic and our hypothetical understandings. We have summarized the most current progress in this regard highlighting the future directions on microplastic research in terrestrial systems.

Topsoils near active and abandoned mining and smelting sites are highly polluted by metal(loid) contaminants, which are often bound to particulates emitted from ore processing facilities and/or windblown from waste disposal sites. To quantitatively determine the contaminant partitioning in the soil particulates, we tested an automated mineralogy approach on the heavy mineral fraction extracted from the mining- and smelting-polluted topsoils exhibiting up to 1920 mg/kg As, 5840 mg/kg Cu, 4880 mg/kg Pb and 3310 mg/kg Zn. A new generation of automated scanning electron microscopy (autoSEM) was combined and optimized with conventional mineralogical techniques (XRD, SEM/EDS, EPMA). Parallel digestions and bulk chemical analyses were used as an independent control of the autoSEM-calculated concentrations of the key elements. This method provides faster data acquisition, the full integration of the quantitative EDS data and better detection limits for the elements of interest. We found that As was mainly bound to the apatite group minerals, slag glass and metal arsenates. Copper was predominantly hosted by the sulfides/sulfosalts and the Cu-bearing secondary carbonates. The deportment of Pb is relatively complex: slag glass, Fe and Mn (oxyhydr)oxides, metal arsenates/vanadates and cerussite were the most important carriers for Pb. Zinc is mainly bound to the slag glass, Fe (oxyhydr)oxides, smithsonite and sphalerite. Limitations exist for the less abundant contaminants, which cannot be fully quantified by autoSEM due to spectral overlaps with some major elements (e.g., Sb vs. Ca, Cd vs. K and Ca in the studied soils). AutoSEM was found to be a useful tool for the determination of the modal phase distribution and element partitioning in the metal(loid)-bearing soil particulates and will definitely find more applications in environmental soil sciences in the future.