Ambient particulate matter (PM) exposure is associated with pulmonary and cardiovascular diseases; however, there is scant research linking data on animal and human cells. The objective of this study was to investigate these associations. Vascular remodeling plays a crucial role in both pulmonary and cardiovascular diseases. Therefore, we conducted a transcriptomic analysis using vascular smooth muscle cells (VSMCs) to identify potential regulators or markers of PM exposure. We demonstrated that fine and coarse PM increased VSMC proliferation in mice. We conducted a genome-wide cDNA microarray analysis, followed by a pathway analysis of VSMCs treated with coarse PM for durations of 24, 48, and 72 h. Sixteen genes were discovered to be time-dependently upregulated and involved in VSMC proliferation. Osteopontin (OPN) is indicated as one of the regulators of these upregulated genes. Both fine and coarse PM from industrial and urban areas significantly increased OPN expression in VSMCs and macrophages. Moreover, oropharyngeal instillation of fine and coarse PM for 8 weeks increased the VSMCs in the pulmonary arteries of mice. OPN level was consistently increased in the lung tissues, bronchoalveolar lavage fluid, and serum of mice. Moreover, we analyzed the plasma OPN levels of 72 healthy participants recruited from the studied metropolitan area. Each participant wore a personal PM2.5 sampler to assess their PM2.5 exposure over a 24 h period. Our results indicate that personal exposure to fine PM is positively correlated with plasma OPN level in young adults. The data obtained in this study suggest that exposure to fine and coarse PM may cause pulmonary vascular lesions in humans and that OPN level may be a biomarker of PM exposure in humans.

The persistence and toxicity of second generation anticoagulant rodenticides (SGARs) in animal tissues make these compounds dangerous by biomagnification in predatory species. Here we studied the levels of SGARs in non-target species of wildlife and the environmental factors that influence such exposure. Liver samples of terrestrial vertebrates (n = 244) found dead between 2007 and 2016 in the region of Aragón (NE Spain) were analysed. The presence of SGARs was statistically analysed with binary or ordinal logistic models to study the effect of habitat characteristics including human population density, percentage of urban surface, livestock densities and surface of different types of crops. SGARs residues were detected in 83 (34%) of the animals and levels >200 ng/g were found in common raven (67%), red fox (50%), red kite (38%), Eurasian eagle-owl (25%), stone marten (23%), Eurasian buzzard (17%), northern marsh harrier (17%), and Eurasian badger (14%). The spatial analysis revealed that the presence of SGARs residues in wildlife was more associated with the use of these products as biocides in urban areas and cattle farms rather than as plant protection products in agricultural fields. This information permits to identify potential habitats where SGARs may pose a risk for predatory birds and mammals.

The aim of this study was to chemically characterize the fine particulate matter (PM₂.₅) at a subtropical forest in East Asia under the influences of anthropogenic and biogenic sources and a complex topographic setting. Four seasonal campaigns were conducted at the Xitou Experimental Forest in central Taiwan from the winter of 2013 to the autumn of 2014. The results indicated that the ambient levels and chemical features of PM₂.₅ exhibited pronounced seasonal variations. Non-sea-salt sulfate (nss-SO₄²⁻) constituted the major component of PM₂.₅, followed by ammonium (NH₄⁺) and nitrate (NO₃⁻) during winter, summer and autumn. However, it was revealed that the mass fraction of NO₃⁻ increased to be comparable with that of nss-SO₄²⁻ in springtime. The mass contribution of secondary organic carbon (SOC) to PM₂.₅ peaked in summer (13.2%), inferring the importance of enhanced photo-oxidation reactions in SOC formation. Diurnal variations of O₃ and SO₂ coincided with each other, suggesting the transport of aged pollutants from distant sources, whereas CO and NOₓ were shown to be under the influences of both local and regional sources. Notably high sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) were observed, which were 0.93 ± 0.05 and 0.39 ± 0.20, respectively. Precursor gases (i.e. SO₂ and NOₓ) could be converted to sulfate and nitrate during the transport by the uphill winds. Furthermore, due to the high relative humidity at Xitou, enhanced aqueous-phase and/or heterogeneous reactions could further contribute to the formation of sulfate and nitrate at the site. This study demonstrated the significant transport of urban pollutants to a subtropical forest by the mountain-valley circulations as well as the long-range transport from regional sources, whereas the implications of which for regional climate change necessitated further investigation.

The study of aerosol dispersion characteristics in wastewater treatment plants (WWTPs) has attracted extensive attention. Oxidation ditch (OD) is a commonly implemented process during biological wastewater treatment. This study assessed the component characteristics, source apportionment, and exposure risks of aerosols generated from a WWTP using the OD process (AWO). The results indicated that the aeration part of oxidation ditch (ODA) exhibited the highest concentrations and proportions of the respiratory fractions (RF) of bacteria, Enterobacteriaceae, Staphylococcus aureus, and Pseudomonas aeruginosa. Some pathogenic or opportunistic-pathogenic bacteria and carcinogenic metal(loid)s were detected in the AWO. The source apportionment results indicated that the outdoor wastewater treatment processes and ambient air contributed to the constitution of the AWO. The indoor aerosols were mainly constituted by composition of the wastewater treatment process such as the sludge dewatering room (SDR). The pathogenic or opportunistic-pathogenic bacteria with eight genera (Colinsella, Dermatophilus, Enterobactor, Erycherichia-Shigella, Ledionella, Selenomonas, Xanthobacter, and Veillonella) were largely attributed to wastewater or sludge. The risk assessment suggested that inhalation was the main exposure pathway for aerosols (including bacteria and metal(loid)s). Additionally, As indicated the highest non-carcinogenic risks. Furthermore, As, Cd, and Co were associated with high carcinogenic risks. The ODA and sludge dewatering room (SDR) indicated the highest carcinogenic and non-carcinogenic risks of metal(loid)s, respectively. Thus, the AWO should be sufficiently researched and monitored to mitigate their harmful effects on human health, particularly with regard to the health of the site workers.

Olive mill wastewaters (OMW) discharging in river ecosystems cause significant adverse effects on their water chemistry and biological communities. We here examined the effects of OMW loads in four streams of a Mediterranean basin characterized by changing flow. The diatom and macroinvertebrate community structures were compared between upstream (control) and downstream (impacted) sites receiving OMW discharge. We also tested if effects occurred at the organism level, i.e. the occurrence of deformities in diatom valves, and the sediment toxicity on the midge Chironomus riparius. We evaluated these effects through a two-year analysis, at various levels of chemical pollution and dilution capacity. The impacted sites had high phenol concentrations and organic carbon loads during and after olive mill (OM) operation, and were characterized by higher abundances of pollution-tolerant diatom and macroinvertebrate taxa. Diatom valve deformities occurred more frequently at the impacted sites. The development of C. riparius was affected by phenolic compounds and organic carbon concentrations in the sediments. The similarity in the diatom and macroinvertebrate assemblages between control and impacted sites decreased at lower flows. Diatoms were more sensitive in detecting deterioration in the biological status of OMW receiving waterways than macroinvertebrates. Our results indicate that the negative effects of OMW extended to the whole benthic community, at both assemblage and organism level.

Volunteer cleanup operations collect large datasets on anthropogenic litter that are seldom analyzed. Here we assess the influence of land use in both near-stream and watershed scale source domains on anthropogenic litter concentration (standing stock, kg km−1) in riparian zones of Iowa, USA. We utilized riparian litter concentration data on four classes of anthropogenic litter (metal, recyclable, garbage, and tires) from volunteer cleanup operations. Anthropogenic litter data were tested for correlation with near-stream and watershed scale land uses (developed, road density, agricultural, and open lands). Road density (road length/area) and developed land use (% area) were significantly correlated to anthropogenic litter, but agricultural (% area) and open lands (% area) were not. Metal objects correlated to near-stream road density (r = 0.79, p = 0.02), while garbage and recyclable materials correlated to watershed scale road density (r = 0.69, p = 0.06 and r = 0.71, p = 0.05 respectively). These differences in the important spatial scales of land use may be related to differences in transport characteristics of anthropogenic litter. Larger, denser metal objects may be transported more slowly through the watershed/channelized system and thus, dependent on more proximal sources, whereas smaller, less dense garbage and recyclable material are likely transported more rapidly, resulting in concentrations that depend more on watershed scale supply. We developed a linear regression model that used near-stream road density and the total amount of observed litter to predict an average anthropogenic litter density of 188 kg km−1 and a standing stock of 946 t in all Iowa streams (>4th Strahler order). The techniques employed in this study can be applied to other professional and volunteer litter datasets to develop prevention and cleanup efforts, inform investigations of process, and assess management actions.

Perchlorate is a pervasive, water-soluble contaminant that competitively inhibits the sodium/iodide symporter, reducing the available iodide for thyroid hormone synthesis. Insufficient iodide uptake can lead to hypothyroidism and metabolic syndromes. Because metabolism, obesity and non-alcoholic fatty liver disease (NAFLD) are tightly linked, we hypothesized that perchlorate would act as an obesogen and cause NAFLD via accumulation of lipids in liver of developing threespine stickleback (Gasterosteus aculeatus). We performed an upshift/downshift exposure regime (clean water to perchlorate treated water or perchlorate treated water to clean water) on stickleback embryos at two concentrations (30 mg/L and 100 mg/L) plus the control (0 mg/L) over the course of 305 days. Adult stickleback were euthanized, H&E stained and analyzed for liver morphology. Specifically, we counted the number of lipid droplets, and measured the area of each droplet and the total lipid area of a representative section of liver. We found that perchlorate treated fish had more and larger lipid droplets, and a larger percentage of lipid in their liver than control fish. These data indicate that perchlorate causes NAFLD and hepatic steatosis in stickleback at concentrations commonly found at contaminated sites. These data also indicate the potential of perchlorate to act as an obesogen. Future studies should investigate the obesogenic capacity of perchlorate by examining organ specific lipid accumulation and whether perchlorate induces these effects at concentrations commonly found in drinking water. Work is also needed to determine the mechanisms by which perchlorate induces lipid accumulation.

Ambient submicron particles (PM₁) exert significant impacts on visibility degradation during severe pollution episodes of urban China. The U.S. IMPROVE algorithms are widely used for assessing the extinction effect of atmospheric aerosols, but only suitable for fine particulate matter. A proper algorithm for PM₁ extinction estimation is lacking and becomes urgent, especially after the online measurement of PM₁ species is routine by aerosol mass spectrometers. Here we conducted three-month in-situ measurements to explore mass scattering efficiencies (MSE) of PM₁ major species at a supersite of eastern China. Results indicated that MSEs of ammonium sulfate and nitrate increase quickly and then keep stable with the mass accumulation, while those of organic matter keep at ∼5.5 m²/g but with a large vibration in the whole mass range. The algorithm for reconstructing PM₁ dry scattering coefficient was derived from the integral of the variation patterns for the three PM₁ species. The algorithm was then validated and compared with other empirical algorithms through separate field measurements. Good correlations between the reconstructed and measured dry scattering coefficient were observed with R square higher than 0.9 and slope of 1.01–1.05, indicating that the reconstructed algorithm can predict the dry scattering coefficient well based on PM₁ chemical composition measurements in urban China. Our study is expected to provide observed insights on the variation of MSE in the wide mass range especially in the high region, as well as accurate formulas for ambient PM₁ dry scattering apportionment.

Over 80,000 endocrine-disrupting chemicals (EDCs) are considered emerging contaminants (ECs), which are of great concern due to their effects on human health. Quantitative structure-activity relationship (QSAR) models are a promising alternative to in vitro methods to predict the toxicological effects of chemicals on human health. In this study, we assessed a deep-learning based QSAR (DL-QSAR) model to predict the qualitative and the quantitative effects of EDCs on the human endocrine system, and especially sex-hormone binding globulin (SHBG) and estrogen receptor (ER). Statistical analyses of the qualitative responses indicated that the accuracies of all three DL-QSAR methods were above 90%, and greater than the other statistical and machine learning models, indicating excellent classification performance. The quantitative analyses, as assessed using deep-neural-network-based QSAR (DNN-QSAR), resulted in a coefficient of determination (R²) of 0.80 and predictive square correlation coefficient (Q²) of 0.86, which implied satisfactory goodness of fit and predictive ability. Thus, DNN was able to transform sparse molecular descriptors into higher dimensional spaces, and was superior for assessment qualitative responses. Moreover, DNN-QSAR demonstrated excellent performance in the discipline of computational chemistry by handling multicollinearity and overfitting problems.

Mesoporous nanocomposite of MgFe₂O₄ nanoparticles (NPs) and graphene oxide (GO) was synthesized using facile sonication method. Its potential was tested for the removal of Ni (II) and Pb (II) ions from water. The 2:1 w/w ratio of MgFe₂O₄:GO was optimum for the maximum removal of metal ions. Nanocomposite was characterized employing XRD, FT-IR, VSM, SEM-EDX, XPS, TEM and BET analyses. It possessed higher surface area (63.0 m² g⁻¹) than pristine NPs. Batch experiments were performed to study the effect of process parameters viz. pH, dose, contact time, initial metal ion concentration, co-existing ions and temperature. Statistical parameters were also determined. Langmuir, Temkin and Freundlich models were followed in perfect way. Langmuir model showed the monolayer adsorption of metal ions onto the homogeneous surface of nanocomposite with maximum adsorption capacity of 100.0 mg g⁻¹ and 143.0 mg g⁻¹ for Ni (II) and Pb (II) ions respectively, which was higher than the same for MgFe₂O₄ NPs and GO. Kinetic studies demonstrated that the pseudo-second order model well described the adsorption process. The ΔS° and ΔG° values revealed spontaneous nature of adsorption process. Positive ΔH° values using MgFe₂O₄ NPs and nanocomposite indicated endothermic removal; whereas using GO the removal was exothermic. The observed trend for coexisting ions correlated with hydrated ion radii. Efficiency of the adsorbents was also tested for realistic nickel electroplating industrial effluent. Apart from the higher adsorption potential of nanofabricated composite, its magnetic properties are advantageous in utilizing metal loaded nanocomposite for adsorption-desorption cycles for reuse.