We discuss 15 years (2000–2015) of daily-integrated PM₂.₅ samples from the Cape Grim Station. Ion beam analysis and positive matrix factorisation are used to identify six source-type fingerprints: fresh sea salt (57%); secondary sulfate (14%); smoke (13%); aged sea salt (12%); soil dust (2.4%); and industrial metals (1.5%). An existing hourly radon-only baseline selection technique is modified for use with the daily-integrated observations. Results were not significantly different for days on which >20 hours were below the baseline radon threshold compared with days when all 24 hours satisfied the baseline criteria. This relaxed daily baseline criteria increased the number of samples for analysis by almost a factor of two. Two radon baseline thresholds were tested: historic (100 mBq m⁻³), and revised (50 mBq m⁻³). Median aerosol concentrations were similar for both radon thresholds, but maximum values were higher for the 100 mBq m⁻³ threshold. Back trajectories indicated more interaction with southern Australia and the Antarctic coastline for air masses selected with the 100 mBq m⁻³ threshold. Radon-only baseline selection using the 50 mBq m⁻³ threshold was more selective of minimal terrestrial influence than a similar recent study using wind direction and back trajectories. The ratio of concentrations between terrestrial and baseline days for the primary sources soil, smoke and industrial metals was 3.4, 2.6, and 5.5, respectively. Seasonal cycles of soil dust had a summer maximum and winter minimum. Seasonal cycles of smoke were of similar amplitude for terrestrial and baseline events, but of completely different shape: peaking in autumn and spring for terrestrial events, compared to summer for baseline conditions. Seasonal cycles of industrial metals had a summer maximum and winter minimum. A significant fraction of the Cape Grim baseline smoke and industrial metal contributions appeared to be derived from long-term transport (>3 weeks since last terrestrial influence).

Tools to predict environmental fate processes during remediation of persistent organic pollutants (POPs) in soil are desperately needed since they can elucidate the overall behavior of the chemical and help to improve the remediation process. A dynamic multimedia fate model (SoilPlusVeg) was further developed and improved to account for rhizoremediation processes. The resulting model was used to predict Polychlorinated Biphenyl (PCB) fate in a highly contaminated agricultural field (1089 ng/g d.w.) treated with tall fescue (Festuca arundinacea), a promising plant species for the remediation of contaminated soils. The model simulations allowed to calculate the rhizoremediation time (about 90 years), given the available rhizoremediation half-lives and the levels and fingerprints of the PCB congeners, to reach the legal threshold, to show the relevance of the loss processes from soil (in order of importance: degradation, infiltration, volatilization, etc.) and their dependence on meteorological and environmental dynamics (temperature, rainfall, DOC concentrations). The simulations showed that the effective persistence of PCBs in soil is deeply influenced by the seasonal variability. The model also allowed to evaluate the role of DOC as a possible enhancer of PCB degradation as a microorganism “spoon feeder” of PCBs in the soil solution. Additionally, we preliminary predicted how the contribution of PCB metabolites could modify the PCB fingerprint and their final total concentrations. This shows that the SoilPlusVeg model could be used in selecting the best choices for a sustainable rhizoremediation of a POP contaminated site.

Mercury (Hg) is a potent neurotoxicant known to induce important adverse effects on fish, but a deeper understanding is lacking regarding how environmental exposure affects the brain morphology and neural plasticity of specific brain regions in wild specimens. In this work, it was evaluated the relative volume and cell density of the lateral pallium, hypothalamus, optic tectum and molecular layer of the cerebellum on wild Liza aurata captured in Hg-contaminated (LAR) and non-contaminated (SJ) sites of a coastal system (Ria de Aveiro, Portugal). Given the season-related variations in the environment that fish are naturally exposed, this assessment was performed in the winter and summer. Hg triggered a deficit in cell density of hypothalamus during the winter that could lead to hormonal dysfunctions, while in the summer Hg promoted larger volumes of the optic tectum and cerebellum, indicating the warm period as the most critical for the manifestation of putative changes in visual acuity and motor-dependent tasks. Moreover, in fish from the SJ site, the lateral pallium relative volume and the cell density of the hypothalamus and optic tectum were higher in the winter than in summer. Thus, season-related stimuli strongly influence the size and/or cell density of specific brain regions in the non-contaminated area, pointing out the ability of fish to adapt to environmental and physiological demands. Conversely, fish from the Hg-contaminated site showed a distinct seasonal profile of brain morphology, presenting a larger optic tectum in the summer, as well as a larger molecular layer of the cerebellum with higher cell density. Moreover, Hg exposure impaired the winter-summer variation of the lateral pallium relative size (as observed at SJ). Altogether, seasonal variations in fish neural morphology and physiology should be considered when performing ecotoxicological studies in order to better discriminate the Hg neurotoxicity.

Mobile in situ concentration and meteorology data were collected for the Chino Dairy Complex in the Los Angeles Basin by AMOG (AutoMObile trace Gas) Surveyor on 25 June 2015 to characterize husbandry emissions in the near and far field in convoy mode with MISTIR (Mobile Infrared Sensor for Tactical Incident Response), a mobile upwards-looking, column remote sensing spectrometer. MISTIR reference flux validated AMOG plume inversions at different information levels including multiple gases, GoogleEarth imagery, and airborne trace gas remote sensing data. Long-term (9-yr.) Infrared Atmospheric Sounding Interferometer satellite data provided spatial and trace gas temporal context.For the Chino dairies, MISTIR-AMOG ammonia (NH₃) agreement was within 5% (15.7 versus 14.9 Gg yr⁻¹, respectively) using all information. Methane (CH₄) emissions were 30 Gg yr⁻¹ for a 45,200 herd size, indicating that Chino emission factors are greater than previously reported.Single dairy inversions were much less successful. AMOG-MISTIR agreement was 57% due to wind heterogeneity from downwind structures in these near-field measurements and emissions unsteadiness. AMOG CH₄, NH₃, and CO₂ emissions were 91, 209, and 8200 Mg yr⁻¹, implying 2480, 1870, and 1720 head using published emission factors. Plumes fingerprinting identified likely sources including manure storage, cowsheds, and a structure with likely natural gas combustion.NH₃ downwind of Chino showed a seasonal variation of a factor of ten, three times larger than literature suggests. Chino husbandry practices and trends in herd size and production were reviewed and unlikely to add seasonality. Higher emission seasonality was proposed as legacy soil emissions, the results of a century of husbandry, supported by airborne remote sensing data showing widespread emissions from neighborhoods that were dairies 15 years prior, and AMOG and MISTIR observations. Seasonal variations provide insights into the implications of global climate change and must be considered when comparing surveys from different seasons.

In this study, we conducted an assessment of polyurethane foam (PUF) passive sampling for metals combining active sampling. Remarkably, we found that the metals collected in the passive samples differed greatly from those collected in active samples. By composition, Cu and Ni accounted for significantly higher proportions in passive samples than in active samples, leading to significantly higher uptake rates of Cu and Ni. In assessing seasonal variation, metals in passive samples had higher concentrations in summer (excluding Heshan), which differed greatly from the pattern of active samples (winter > summer), indicating that the uptake rates of most metals were higher in summer than in winter. Overall, due to the stable passive uptake rates, we considered that PUF passive samplers can be applied to collect atmospheric metals. Additionally, we created a snapshot of the metal pollution in the Pearl River Delta using principal component analysis of PUF samples and their source apportionment.

The relative impact of non-exhaust sources (i.e. road dust, tire wear, road wear and brake wear particles) on urban air quality is increasing. Among them, road dust resuspension has generally the highest impact on PM concentrations but its spatio-temporal variability has been rarely studied and modeled. Some recent studies attempted to observe and describe the time-variability but, as it is driven by traffic and meteorology, uncertainty remains on the seasonality of emissions. The knowledge gap on spatial variability is much wider, as several factors have been pointed out as responsible for road dust build-up: pavement characteristics, traffic intensity and speed, fleet composition, proximity to traffic lights, but also the presence of external sources. However, no parameterization is available as a function of these variables.We investigated mobile road dust smaller than 10 μm (MF10) in two cities with different climatic and traffic conditions (Barcelona and Turin), to explore MF10 seasonal variability and the relationship between MF10 and site characteristics (pavement macrotexture, traffic intensity and proximity to braking zone). Moreover, we provide the first estimates of emission factors in the Po Valley both in summer and winter conditions. Our results showed a good inverse relationship between MF10 and macro-texture, traffic intensity and distance from the nearest braking zone. We also found a clear seasonal effect of road dust emissions, with higher emission in summer, likely due to the lower pavement moisture. These results allowed building a simple empirical mode, predicting maximal dust loadings and, consequently, emission potential, based on the aforementioned data. This model will need to be scaled for meteorological effect, using methods accounting for weather and pavement moisture. This can significantly improve bottom-up emission inventory for spatial allocation of emissions and air quality management, to select those roads with higher emissions for mitigation measures.

To evaluate the seasonal distribution of antibiotic resistance genes (ARGs) and explore the reason for their patterns in different seasons and different systems, two wastewater treatment systems were selected and analyzed using high-throughput qPCR. Linear discriminant analysis (LDA) effect size (LEfSe) was used to discover the differential ARGs (biomarkers) and estimate the biomarkers’ effect size. We found that the total absolute abundances of ARGs in inflows and excess sludge samples had no obvious seasonal fluctuations, while those in winter outflow samples decreased in comparison with the inflow samples. Eleven differentially abundant ARGs (biomarker genes, BmGs) (aadA5-02, aac-6-II, cmlA1-01, cmlA1-02, blaOXA10-02, aadA-02, tetX, aadA1, ereA, qacEΔ1-01, and blaTEM) in summer samples and 10 BmGs (tet-32, tetA-02, aacC2, vanC-03, aac-6-I1, tetE, ermB, mefA, tnpA - 07, and sul2) in winter samples were validated. According to 16S rRNA gene sequencing, the relative abundance of bacteria at the phylum level exhibited significant seasonal changes in outflow water (OW), and biomarker bacteria (BmB) were discovered at the family (or genus) level. Synechococcus and vadinCA02 are BmB in summer, and Trichococcus, Lactococcus, Pelosinus, Janthinobacterium, Nitrosomonadaceae and Sterolibacterium are BmB in winter. In addition, BmB have good correlations with BmGs in the same season, which indicates that bacterial community changes drive different distributions of ARGs during seasonal changes and that LEfSe is an acute and effective method for finding significantly different ARGs and bacteria between two or more classes.In conclusion, this study demonstrated the seasonal changes of BmGs and BmB at two wastewater treatment systems.

Bogota registers frequent episodes of poor air quality from high PM₁₀ concentrations. It is one of the main Latin American megacities, located at 2600 m in the tropical Andes, but there is insufficient data on PM₁₀ source contribution. A characterization of the chemical composition and the source apportionment of PM₁₀ at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO₄²⁻, Cl⁻, NO₃⁻, NH₄⁺), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM₁₀ components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM₁₀, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM₁₀) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions + road dust) was the major PM₁₀ source, accounting for ∼50% of the PM₁₀. The results provided novel data about PM₁₀ chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.

Microplastics (MPs) are the most numerous debris reported in marine environments and assessment of the amounts of MPs that accumulate in wild organisms is necessary for risk assessment. Our objective was to assess MP contamination in mussels collected around the coast of Scotland (UK) to identify characteristics of MPs and to evaluate risk of human exposure to MPs via ingestion of mussels. We deployed caged mussels (Mytilus edulis) in an urbanised estuary (Edinburgh, UK) to assess seasonal changes in plastic pollution, and collected mussels (Mytilus spp and subtidal Modiolus modiolus) from eight sampling stations around Scotland to enumerate MP types at different locations. We determined the potential exposure of humans to household dust fibres during a meal to compare with amounts of MPs present in edible mussels. The mean number of MPs in M. modiolus was 0.086 ± 0.031 (SE, n = 6)/g ww (3.5 ± 1.29 (SE) per mussel). In Mytilus spp, the mean number of MPs/g ww was 3.0 ± 0.9 (SE, n = 36) (3.2 ± 0.52 (SE) per mussel), but weight dependent. The visual accuracy of plastic fibres identification was estimated to be between 48 and 50%, using Nile Red staining and FT-IR methodologies, respectively, halving the observed amounts of MPs in wild mussels. We observed an allometric relationship between the number of MPs and the mussels wet weight. Our predictions of MPs ingestion by humans via consumption of mussels is 123 MP particles/y/capita in the UK and can go up to 4620 particles/y/capita in countries with a higher shellfish consumption. By comparison, the risk of plastic ingestion via mussel consumption is minimal when compared to fibre exposure during a meal via dust fallout in a household (13,731–68,415 particles/Y/capita).

Photodemethylation can be one of the primary processes for loss of neurotoxic methylmercury (MeHg) in freshwater lakes. Few studies have quantified seasonal variations in photodemethylation rate constants as a function of dissolved organic matter (DOM). We conducted 1-week irradiation experiments in two seasons to test for spatial and temporal differences in photodemethylation potential in temperate lake waters. Six study lakes in Kejimkujik National Park, Nova Scotia were sampled in summer and fall to include a range of naturally occurring DOM concentrations (4.4–13.4 and 3.9–16.4 mg C L⁻¹, respectively). A negative linear relationship (R² = 0.76, p = 0.01) was found between DOM concentration and photodemethylation rate constant across seasons, indicating that DOM is a strong predictor of MeHg photodemethylation independent of seasonal effects. The two highest carbon lakes (BDW and PEB) had significantly higher energy-normalized photodemethylation rate constants in summer compared to fall corresponding with lower DOM concentrations in summer relative to fall. Additionally, there were negative linear relationships between MeHg photodemethylation and DOM photomineralization (R²s = 0.58–0.72) and DOM photobleaching (R²s = 0.83–0.90). This key finding suggests that competition for photons within DOM structures may reduce the potential for MeHg photodemethylation in high carbon waters and that this relationship persists across seasons.