Biodiesel is considered as a valuable and less toxic alternative to diesel. However, cellular and molecular effects of repeated exposure to biodiesel emissions from a recent engine equipped with a diesel particle filter (DPF) remain to be characterized. To gain insights about this point, the lung transcriptional signatures were analyzed for rats (n = 6 per group) exposed to filtered air, 30% rapeseed biodiesel (B30) blend or reference diesel (RF0), upstream and downstream a DPF, for 3 weeks (3 h/day, 5 days/week).Genomic analysis revealed a modest regulation of gene expression level (lower than a 2-fold) by both fuels and a higher number of genes regulated downstream the DPF than upstream, in response to either RF0 or to B30 exhaust emissions. The presence of DPF was found to notably impact the lung gene signature of rats exposed to B30. The number of genes regulated in common by both fuels was low, which is likely due to differences in concentrations of regulated pollutants in exhausts, notably for compound organic volatiles, polycyclic aromatic hydrocarbons, NO or NOx. Nevertheless, we have identified some pathways that were activated for both exhaust emissions, such as integrin-, IGF-1- and Rac-signaling pathways, likely reflecting the effects of gas phase products. By contrast, some canonical pathways relative to “oxidative phosphorylation” and “mitochondrial dysfunction” appear as specific to B30 exhaust emission; the repression of transcripts of mitochondrial respiratory chain in lung of rats exposed to B30 downstream of DPF supports the perturbation of mitochondria function.This study done with a recent diesel engine (compliant with the European IV emission standard) and commercially-available fuels reveals that the diesel blend composition and the presence of an after treatment system may modify lung gene signature of rats repeatedly exposed to exhaust emissions, however in a rather modest manner.

Light absorption by brown carbon (BrC) is dynamic due to atmospheric aging processes, leading to complex and poorly constrained effects on photochemistry and climate. In this study, a smog chamber was used to simulate the heterogeneous ozone (O₃) aging of soot particles. Twelve aging times and seven O₃ concentrations were set to investigate the effects of aging degree on BrC light absorption. The results showed that light absorption by BrC was enhanced after O₃ aging, but followed a non-monotonic trend with an initial increase and subsequent decrease. An aging time of 60 min and O₃ concentration of 1.2 ppm were optimal for enhancing BrC absorption, where the contribution of BrC to total absorption and the contribution of BrC relative to black carbon absorption at 370 nm of ozonized soot were 23.0 ± 1.8% and 30.0 ± 3.0%, respectively, much greater than those of fresh soot (8.1 ± 1.1% and 8.8 ± 1.3%, respectively). The absorption Ångström exponent (AAE) and delta C (ΔC) of ozonized soot at 60 min ranged from 1.18 ± 0.01 to 1.31 ± 0.03 and from 13.5 ± 7.0 to 24.3 ± 13.5 μg m⁻³, respectively, and were greater than those of fresh soot (1.12 ± 0.02 and 8.0 ± 0.8 μg m⁻³), but also showed non-monotonic trends, suggesting the formation of BrC during O₃ aging. Comparative results indicated that AAE might be a better BrC indicator for soot than ΔC. The non-monotonic trend was tentatively explained by changes in organic carbon, oxygenated functional groups and conjugated structures, as well as polycyclic aromatic hydrocarbon (PAH) degradation and oxygenated PAH formation. The relative intensities of oxidative formation and degradation of chromophores may determine BrC evolution during O₃ aging. This study will be useful for clarifying BrC evolution in the atmosphere and estimating its radiative forcing.

This study investigates the influence of meteorology, land use, built environment, and traffic characteristics on near-road ultrafine particle (UFP) concentrations. To achieve this objective, minute-level UFP concentrations were measured at various locations along a major arterial road in the Greater Toronto Area (GTA) between February and May 2019. Each location was visited five times, at least once in the morning, mid-day, and afternoon. Each visit lasted for 30 min, resulting in 2.5 h of minute-level data collected at each location. Local traffic information, including vehicle class and turning movements, were processed using computer vision techniques. The number of fast-food restaurants, cafes, trees, traffic signals, and building footprint, were found to have positive impacts on the mean UFP, while distance to the closest major road was negatively associated with UFP. We employed the Extreme Gradient Boosting (XGBoost) method to develop prediction models for UFP concentrations. The Shapley additive explanation (SHAP) measures were used to capture the influence of each feature on model output. The model results demonstrated that minute-level counts of local traffic from different directions had significant impacts on near-road UFP concentrations, model performance was robust under random cross-validation as coefficients of determination (R²) ranged from 0.63 to 0.69, but it revealed weaknesses when data at specific locations were eliminated from the training dataset. This result indicates that proper cross-validation techniques should be developed to better evaluate machine learning models for air quality predictions.

This study explores the generation of ultrafine particle emissions, measured in particle number (PN), based on a portable emissions measurement system (PEMS) in the City of Toronto between October and December 2019. Two driving routes were designed to include busy arterial roads and highways. All measurements were conducted between 10 a.m. and 4 p.m. Altogether, emissions from 31 drives were collected, leading to approximately 200,000 s of data. A spike detection algorithm was employed to isolate PN spikes in time series data. A sensitivity analysis was also conducted to identify the most optimum method for spike detection. The results indicate that the average emission rate during a PN spike is approximately 8 times the emission rate along the rest of the drive. In each test trip, about 25% of the duration was attributed to spike events, contributing 75% of total PN emissions. A Pearson correlation of 0.45 was estimated between the number of PN spikes and the number of sharp accelerations (above 8.5 km/h/s). The Pearson correlation between the occurrence of high engine torque (above 65.0 Nm) and the number of PN spikes was estimated at 0.80. The number of PN spikes was highest on arterial roads where the vehicle speed was relatively low, but with high variability, and including a high number of sharp accelerations. This pattern of UFP emissions leads to high UFP concentrations along arterial roads in the inner city core.

Veterinary antibiotics have been detected as contaminants of emerging concern in soil environment worldwide. Animal manure is frequently applied to agricultural fields to improve soil fertility, which can result in introducing large amount of antibiotics into soil environment. However, few attempts have been made to identify the spatial and temporal dynamics of veterinary antibiotics in soil at the hillslope scale with different land uses. This study was performed to explore the pattern and variability of veterinary antibiotics in the soil in response to rainfall events. Results showed that higher concentrations of veterinary antibiotics were generally found in cropland (292.6 ± 280.1 ng/g) and orchard (228.1 ± 230.5 ng/g) than in forestland (13.5 ± 9.9 ng/g). After rainfall events, antibiotics accumulated in the soil at the positions where manure was applied, especially under high-intensity rainfall conditions. However, the antibiotic concentration in soil slightly increased from the top to the bottom of hills, thus indicating the restricted contribution of runoff to antibiotic transport, especially under low-intensity rainfall conditions. In addition, most antibiotics were sequestered in the surface soil (0–10 cm), and higher antibiotic concentrations were observed in deep soil (20–40 cm) in cropland than orchard. The soil aggregate, organic matter, and clay content played important roles in antibiotic sequestration along the hillslope subject to low-, medium-, and large-amount rainfall events, respectively. This study identified that land use, rainfall conditions, and soil structures jointly affect the spatial and temporal variability of antibiotics in soils on hillslopes.

Microbial communities in activated sludge (AS) have a significant influence on the functions and stability of aeration tanks in wastewater treatment plants (WWTPs). The microbial community structure is affected by various factors, among which operational parameters outcompeted as the key factors in shaping its structure. However, as an important operational parameter of aeration tank, the mechanisms by which sludge retention time (SRT) affect community properties remain unclear. In this study, 144 AS samples from aeration tanks of 48 full-scale WWTPs operating under different SRT conditions were examined via high-throughput Illumina-MiSeq sequencing technology. The results indicated that SRT significantly affected the diversity, composition, assembly, and co-occurrence patterns of the microbial community in aeration tanks. Moreover, our results provided clear evidence that the microbial communities in aeration tanks operating under SRT of 10–20 days have the highest biodiversity, the lowest stochastic processes influence, the more stable molecular ecological network structure, the lowest risks of filamentous sludge bulking and enhanced nitrogen removal potential. The microbial communities could be more stable and resilient to disturbance when aeration tanks were operated under this SRT condition. The findings of this study provided a reference for the optimization of aeration tanks from an of microbial community perspective.

Due to high global demand, large amounts of abbattoir waste are generated from pork production. Mismanagement of abattoir waste on agricultural lands can result in soil and water contamination with pathogens and contaminants like metals and nutrients. Therefore, possible effects on soil organisms prior to application should be evaluated. Thus, the aim of this study was to determine the effects of fresh pig abattoir waste (PAWf) and waste after stabilization processes on E. andrei through tests of avoidance behavior, acute toxicity and chronic toxicity. In order to do this, the waste was evaluated fresh (i.e., non-treated), and after aerated composting (PAWa), natural composting (PAWn) and vermicomposting (PAWv). In addition, we used a natural soil with no history of agricultural use as control soil. The evaluation was based on avoidance behavior, mortality, initial and final earthworm weight, and reproduction, in addition to a set of enzyme assays formed by acetylcholinesterase, lipid peroxidation, catalase and glutathione S-transferase measured over time. The ecotoxicological results showed that PAWf and PAWa increased AChE activity at different experimental periods, while PAWn decreased activity at 14 days compared to the control. PAWf and PAWa increased TBARS levels at 7 and 14 days, respectively. CAT activity decreased at 3, 7 and 14 days in PAWv, while GST activity increased at 3 days in PAWa and at 3 and 14 days in PAWf compared to the control. In the acute toxicity test, PAWa and PAWn had a toxic effect on E. andrei, resulting in 100% mortality at 14 days of exposure. Based on our findings, pig abattoir waste should undergo vermicomposting prior to agricultural application to soils.

Natural organic matter (NOM) affects the environmental behaviors of AgNPs, which may change their phytotoxicity to plants. However, more evidence can be provided to illustrate how NOM influences AgNPs-induced phytotoxicity. In this study, using rice (Oryza sativa) as a model, the effects of NOM, Suwannee River humic acid (SRHA) and fulvic acid (FA), on the dissolution and phytotoxicity of AgNPs were investigated. Silver ions decreased in both AgNPs and AgNO₃ solution in the presence of NOM, and the effect of SRHA was stronger than FA. Image-XRF (iXRF) results showed that Ag mainly remained in the root rather than the shoot of rice seedling exposed to AgNPs. NOM mitigated the negative effects of AgNPs and AgNO₃ on rice with lower germination inhibition rate, less chlorophyll reduction, more relative biomass and less O₂•⁻ content. Moreover, NOM improved root cell viability according to FDA fluorescent dye as well as maintained the normal root morphology. Interestingly, the neutral sugars content from pectin, hemicellulose 1, hemicellulose 2 and cellulose of root cell wall in AgNPs and AgNO₃ treatments differed from the control, while it was close to the regular content in AgNPs/AgNO₃+SRHA/FA groups, which implied that NOM regulated the changes. Besides, SRHA led to less germination and less relative biomass than FA due to different chemical characters. Thus, NOM needs to be considered when studying the phytotoxicity of AgNPs.

Thallium (Tl) is a dispersed trace metal showing remarkable toxicity. Various anthropogenic activities may generate Tl contamination in river sediments, posing tremendous risks to aquatic life and human health. This paper aimed to provide insight into the vertical distribution, risk assessment and source tracing of Tl and other potentially toxic elements (PTEs) (lead, cadmium, zinc and copper) in three representative sediment cores from a riverine catchment impacted by multiple anthropogenic activities (such as steel-making and Pb–Zn smelting). The results showed high accumulations of Tl combined with associated PTEs in the depth profiles. Calculations according to three risk assessment methods by enrichment factor (EF), geoaccumulation index (Igₑₒ) and the potential ecological risk index (PERI) all indicated a significant contamination by Tl in all the sediments. Furthermore, lead isotopes were analyzed to fingerprint the contamination sources and to calculate their quantitative contributions to the sediments using the IsoSource software. The results indicated that a steel-making plant was the most important contamination source (∼56%), followed by a Pb–Zn smelter (∼20%). The natural parental bedrock was found to contribute ∼24%. The findings highlight the importance of including multiple anthropogenic sources for quantitative fingerprinting of Tl and related metals by the lead isotopic approach in complicated environmental systems.