An ecosystem in a cold climate river basin is vulnerable to the effects of climate change affecting permafrost thaw and glacier retreat. We currently lack sufficient data and information if and how hydrological processes such as glacier retreat, snowmelt and freezing-thawing affect sediment and nutrient runoff and transport, as well as N₂O emissions in cold climate river basins. As such, we have implemented well-established, semi-empirical equations of nitrification and denitrification within the Soil and Water Assessment Tool (SWAT), which correlate the emissions with water, sediment and nutrients. We have tested this implementation to simulate emission dynamics at three sites on the Canadian prairies. We then regionalized the optimized parameters to a SWAT model of the Athabasca River Basin (ARB), Canada, calibrated and validated for streamflow, sediment and water quality. In the base period (1990–2005), agricultural areas (2662 gN/ha/yr) constituted emission hot-spots. The spring season in agricultural areas and summer season in forest areas, constituted emission hot-moments. We found that warmer conditions (+13% to +106%) would have a greater influence on emissions than wetter conditions (−19% to +13%), and that the combined effect of wetter and warmer conditions would be more offsetting than synergetic. Our results imply that the spatiotemporal variability of N₂O emissions will depend strongly on soil water changes caused by permafrost thaw. Early snow freshet leads to spatial variability of soil erosion and nutrient runoff, as well as increases of emissions in winter and decreases in spring. Our simulations suggest crop residue management may reduce emissions by 34%, but with the mixed results reported in the literature and the soil and hydrology problems associated with stover removal more research is necessary. This modelling tool can be used to refine bottom-up emission estimations at river basin scale, test plausible management scenarios, and assess climate change impacts including climate feedback.

Studying the characteristics of new particle formation (NPF) is important as it is generally recognized as a major contributor to particle pollution in urban environments. We investigated NPF events that occurred during a 1-year period in the urban environment of Brisbane, Australia, using a neutral cluster and air ion spectrometer (NAIS) which is able to monitor both neutral and charged particles and clusters down to a size of 0.8 nm. NPF events occurred on 41% of days, with the occurrence rate of 7% greater in the summer than in the winter. We derived the first diurnal event distribution of NPF events anywhere in the world and showed that the most probable starting time of an NPF event was near 08:30 a.m., being about an hour earlier in the winter than in the summer. During NPF days, 10% of particles were charged. The mean neutral and charged particle concentrations on NPF days were, respectively, 49% and 14% higher than those on non-event days. The mean formation rate of 2–3 nm particles during an NPF event was 20.8 cm⁻³ s⁻¹. The formation rate of negatively charged particles was about 10% higher than that of positively charged particles. The mean particle growth rate in the size range up to 20 nm was 6.2 nm h⁻¹. These results are compared and contrasted with corresponding values that have been derived with the scanning mobility particle sizer (SMPS) at the same location and with values that have been reported with the NAIS at other locations around the world. This is the first comprehensive study of the characteristics of NPF events over a significantly long period in Australia.

PM₁ might be more hazardous than PM₂.₅ (particulate matter with an aerodynamic diameter ≤ 1 μm and ≤2.5 μm, respectively). However, studies on PM₁ concentrations and its health effects are limited due to a lack of PM₁ monitoring data.To estimate spatial and temporal variations of PM₁ concentrations in China during 2005–2014 using satellite remote sensing, meteorology, and land use information.Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) data, Dark Target (DT) and Deep Blue (DB), were combined. Generalised additive model (GAM) was developed to link ground-monitored PM₁ data with AOD data and other spatial and temporal predictors (e.g., urban cover, forest cover and calendar month). A 10-fold cross-validation was performed to assess the predictive ability.The results of 10-fold cross-validation showed R² and Root Mean Squared Error (RMSE) for monthly prediction were 71% and 13.0 μg/m³, respectively. For seasonal prediction, the R² and RMSE were 77% and 11.4 μg/m³, respectively. The predicted annual mean concentration of PM₁ across China was 26.9 μg/m³. The PM₁ level was highest in winter while lowest in summer. Generally, the PM₁ levels in entire China did not substantially change during the past decade. Regarding local heavy polluted regions, PM₁ levels increased substantially in the South-Western Hebei and Beijing-Tianjin region.GAM with satellite-retrieved AOD, meteorology, and land use information has high predictive ability to estimate ground-level PM₁. Ambient PM₁ reached high levels in China during the past decade. The estimated results can be applied to evaluate the health effects of PM₁.

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).

Particulate matter with diameters <2.5 μm (i.e., PM₂.₅) has multiple natural and anthropological sources. The association between PM₂.₅ and the exacerbation of respiratory allergy and asthma has been well studied, but the components of PM₂.₅ that are responsible for allergies have not yet been determined. Here, we elucidated the effects of aqueous and organic extract of PM₂.₅ collected during four seasons in November 2014–December 2015 in two cities (Kawasaki, an industrial area and Fukuoka, an urban area affected by transboundary pollution matter) of Japan on respiratory health. Ambient PM₂.₅ was collected by high-volume air samplers and extracted into water soluble and lipid soluble components. Human airway epithelial cells, murine bone marrow-derived antigen-presenting cells (APC) and splenocytes were exposed to PM₂.₅ extracts. We measured the cell viability and release of interleukin (IL)-6 and IL-8 from airway epithelial cells, the DEC205 and CD86 expressions on APCs and cell proliferation, and TCR and CD19 expression on splenocytes. The water-soluble or aqueous extracts, especially those from Kawasaki in fall, had a greater cytotoxic effect than the lipid-soluble or organic extracts in airway epithelial cells, but they caused almost no pro-inflammatory response. Extract of fall, especially the aqueous extract from Fukuoka, increased the DEC205 and CD86 expressions on APC. Moreover, aqueous extracts of fall, summer, and spring from Fukuoka significantly increased proliferation of splenocytes. Organic extract of spring and summer from Kawasaki significantly elevated the TCR expression, and organic extract of summer from Kawasaki decreased the CD19 expression. These results suggest that PM₂.₅ extract samples are responsible for cytotoxicity in airway epithelial cells and for activating APCs and T-cells, which can contribute to the exacerbation of respiratory diseases such as asthma. These effects can differ by PM₂.₅ components, collection areas and seasons.

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.

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.

By identifying the main sources of nitrate (NO3−) can obtain useful information to support the management of NO3− pollution, particularly in subtropical catchments with shallow drinking water wells. This study used water chemistry and dual stable isotopes δ15N and δ18O methods to assess seasonal and spatial variations of NO3− in precipitation, surface water, and groundwater in an agricultural and forest subtropical catchment in Jiangxi Province, China. The maximum concentrations of nitrate-nitrogen (NO3−-N) and ammonium-nitrogen (NH4+-N) were 10.4 and 10.8 mg L−1in samples collected from 221 rainfall events from 2011 to 2013. About 4.4% and 12.3% NH4+-N concentrations of surface water and groundwater exceeded the thresholds of 1.0 and 0.2 mg L−1. The NO3−-N concentrations in surface water were closely correlated with NH4+-N concentrations in surface water and groundwater (r = −0.71 and r = −0.71, P < 0.05). The concentrations of NH4+-N and NO3−-N were significantly higher in a fishery pond and nearby drinking wells than in other monitoring points. Annual exports of NO3−-N and NH4+-N were 4.06 × 104 and 8.14 × 103 kg yr−1, respectively and NO3−-N is the main form of N loss. The δ15N values ranged from 0‰ to 20‰ in surface water and groundwater, and the δ18O values ranged from 0‰ to 15‰ and 1‰–13‰, respectively. Dual stable isotope natural abundance distribution and water chemistry [NO3−]/[Cl−] molar ratio information suggested that manure and sewage and soil N were the main sources of NO3− in surface water and manure and sewage in groundwater in summer and winter. In spring, water occurred denitrification and ammonium fertilizer, manure and sewage were the main sources of NO3− in surface water and groundwater which sampling points were closer residential area and fish ponds than paddy field and local farmers used more Manure. Manure applications should be reasonable around drinking water wells to protect the drinking water quality.

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.