Glyphosate is the active ingredient of the commercial formulation Roundup®, which is used worldwide. This study aimed to investigate the toxic effects of pure glyphosate or Roundup® on pregnant mice and their fetuses during pregnancy. From gestation days (GDs) 1–19, ICR mice were orally administered distilled water, 0.5% glyphosate solution or 0.5%-glyphosate Roundup® solution. The ovaries and serum were collected at GD19. The results showed decreases in body weight gain and, ovary and liver weight in glyphosate-treated mice. Additionally, histopathological alterations in the ovary including increased atretic follicles, interstitial fibrosis and decreased mature follicles were observed in the groups treated with glyphosate. The serum concentrations of both progesterone and estrogen were markedly altered after glyphosate exposure, and there were also changes in the expression of GnRH, LHR, FSHR, 3β-HSD and Cyp19a1 genes at the hypothalamic-pituitary-ovarian axis. Furthermore, oxidative stress was observed in the treated mice, increasing the activity of T-AOC, CAT and GSH-Px, as well as the MDA content in both the serum and ovary. With regard to litters, the sex ratio was significantly altered by pure glyphosate. These results show that glyphosate is able to cause several effects on pregnant mice, such as ovarian failure, interference with hormone secretion by affecting the steroidogenesis-related gene expression, and oxidative stress. The sex ratio of litters was also influenced by prenatal exposure to pure glyphosate.

The extensive use of reclaimed wastewater (RW) as a source of urban landscape pond replenishment, stimulated by the lack of surface water (SW) resources, has raised public concern. Greater attention should be paid to pond sediments, which act as ‘sinks’ and ‘sources’ of contaminants to the overlying pond water. Three ponds replenished with RW (RW ponds) in three Chinese cities were chosen to investigate 22 indices of sediment quality in four categories: eutrophication, heavy metal, ecotoxicity and pathogens risk. RW ponds were compared with other ponds of similar characteristics in the same cities that were replenished with SW (SW ponds). Our results show a strong impact of RW to the eutrophication and pathogenic risks, which are represented by organic matter, water content, total nitrogen, total phosphorus and phosphorus fractions, and pathogens. In particular, total phosphorus concentrations in the RW pond sediments were, on average, 50% higher than those of SW ponds. Moreover, the content of phosphorus, extracted by bicarbonate/dithionite (normally represented by BD-P) and NaOH (NaOH-P), were 2.0- and 2.83-times higher in RW ponds, respectively. For pathogens, the concentrations of norovirus and rotavirus in RW pond sediments were, on average, 0.52 and 0.30- log times those of SW ponds. The duration of RW replenishment was proved to have a marked impact on the eutrophication and pathogens risks from sediments. The continued use of RW for replenishment increases the eutrophication risk, and the pathogens risk, especially by viral pathogens, becomes greater.

In urbanized regions with expansive impervious surfaces and often low vegetation cover, air pollution due to motor vehicles and other combustion sources, is a problem. The poor air quality days in Montreal, Quebec are mainly due to fine particulate matter and ozone. Businesses using wood ovens are a source of particulates. Careful vegetation selection and increased green roof usage can improve air quality. This paper reviews different green roofs and the capability of plants in particulate matter (PM), ozone (O3) as well as nitrogen dioxide (NO2) level reductions. Both the recommended green roof category and plants to reduce these pollutants in Montreal's zone 5 hardiness region are provided. Green roofs with larger vegetation including shrubs and trees, or intensive green roofs, remove air pollutants to a greater extent and are advisable to implement on existing, retrofitted or new buildings. PM is most effectively captured by pines. The small Pinus strobus ‘Nana’, Pinus mugho var. pumilio, Pinus mugho ‘Slowmound’ and Pinus pumila ‘Dwarf Blue’ are good candidates for intensive green roofs. Drought tolerant, deciduous broadleaved trees with low biogenic volatile organic compound emissions including Japanese Maple or Acer palmatum ‘Shaina’ and ‘Mikawa-Yatsubusa’ are options to reduce O3 levels. Magnolias are tolerant to NO2 and it is important in their metabolic pathways. The small cold-tolerant Magnolia ‘Genie’ is a good option to remove NO2 in urban settings and to indirectly reduce O3 formation. Given the emissions by Montreal businesses' wood ovens, calculations performed based on their respective complex roof areas obtained via Google Earth Pro indicates 88% Pinus mugho var. pumilio roof coverage can annually remove 92.37 kg of PM10 of which 35.10 kg is PM2.5. The removal rates are 4.00 g/m2 and 1.52 g/m2 for PM10 and PM2.5, respectively. This paper provides insight to addressing air pollution through urban rooftop greening.

Heavy metals are concerned for its adverse effect on human health and long term burden on biogeochemical cycling in the ecosystem. In this study, a provincial-level emission inventory of 13 kinds of heavy metals including V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Sn, Sb, Ba and Pb from 10 anthropogenic sources was developed for China, based on the 2015 national emission inventory of primary particulate matters and source category-specific speciation profiles collected from 50 previous studies measured in China. Uncertainties associated with the speciation profiles were also evaluated. Our results suggested that total emissions of the 13 types of heavy metals in China are estimated at about 58000 ton for the year 2015. The iron production is the dominant source of heavy metal, contributing 42% of total emissions of heavy metals. The emissions of heavy metals vary significantly at regional scale, with largest amount of emissions concentrated in northern and eastern China. Particular, high emissions of Cr, Co, Ni, As and Sb (contributing 8%–18% of the national emissions) are found in Shandong where has large capacity of industrial production. Uncertainty analysis suggested that the implementation of province-specific source profiles in this study significantly reduced the emission uncertainties from (−89%, 289%) to (−99%, 91%), particularly for coal combustion. However, source profiles for industry sectors such as non-metallic mineral manufacturing are quite limited, resulting in a relative high uncertainty. The high-resolution emission inventories of heavy metals are essential not only for their distribution, deposition and transport studies, but for the design of policies to redress critical atmospheric environmental hazards at local and regional scales. Detailed investigation on source-specific profile in China are still needed to achieve more accurate estimations of heavy metals in the future.

Artificial lighting at night has becoming a new type of pollution posing an important anthropogenic environmental pressure on organisms. The objective of this research was to examine the potential association between nighttime artificial light pollution and nest densities of the three main sea turtle species along Florida beaches, including green turtles, loggerheads, and leatherbacks. Sea turtle survey data was obtained from the “Florida Statewide Nesting Beach Survey program”. We used the new generation of satellite sensor “Visible Infrared Imaging Radiometer Suite (VIIRS)” (version 1 D/N Band) nighttime annual average radiance composite image data. We defined light pollution as artificial light brightness greater than 10% of the natural sky brightness above 45° of elevation (>1.14 × 10⁻¹¹ Wm⁻²sr⁻¹). We fitted a generalized linear model (GLM), a GLM with eigenvectors spatial filtering (GLM-ESF), and a generalized estimating equations (GEE) approach for each species to examine the potential correlation of nest density with light pollution. Our models are robust and reliable in terms of the ability to deal with data distribution and spatial autocorrelation (SA) issues violating model assumptions. All three models found that nest density is significantly negatively correlated with light pollution for each sea turtle species: the higher light pollution, the lower nest density. The two spatially extended models (GLM-ESF and GEE) show that light pollution influences nest density in a descending order from green turtles, to loggerheads, and then to leatherbacks. The research findings have an implication for sea turtle conservation policy and ordinance making. Near-coastal lights-out ordinances and other approaches to shield lights can protect sea turtles and their nests. The VIIRS DNB light data, having significant improvements over comparable data by its predecessor, the DMSP-OLS, shows promise for continued and improved research about ecological effects of artificial light pollution.

Propamocarb (PM) is a widely used fungicide with property of affecting fatty acid and phospholipid biosynthesis in funguses. In this study, we explored its effects on mice gut microbiota and metabolism by exposing mice to 3, 30, and 300 mg/L PM through drinking water for a duration of 28 days. We observed that the transcription of hepatic genes related to regulate lipid metabolism were perturbed by PM exposure. The microbiota in the cecal contents and feces changed during or after PM exposure at phylum or genus levels. 16S rRNA gene sequencing for the cecal content revealed shifted in overall microbial structure after PM exposure, and operational taxonomic unit (OTU) analysis indicated that 32.2% of OTUs changed by 300 mg/mL PM exposure for 28 days. In addition, based on 1H NMR analysis,a total of 20 fecal metabolites mainly including succinate, short chain fatty acids, bile acids and trimethylamine were found to be significantly influenced by exposure to 300 mg/L PM.,. These metabolites were tightly correlated to host metabolism. Our findings indicated that high doses of PM exposure could disturb mice metabolism through, or partly through, altering the gut microbiota and microbial metabolites.

To better understand the precursor of disinfection by-products (DBPs) and provide useful information for water utilities to manage the drinking water, a study of DBP formation was conducted through chlorination of leaf organic matter (OM) from phoenix tree and algal OM from Chlorella vulgaris. DBPs investigated include trichloromethane (TCM), trichloroacetic acid (TCAA), dichloroacetic acid (DCAA), chloroacetic acid (CAA), dichloroacetonitrile (DCAN) and trichloroacetonitrile (TCNM). Results show that the specific yields (μg/mg C) of C-DBPs (TCM, CAA, DCAA and TCAA) from leaf OM were higher but the specific yields of N-DBPs (DCAN and TCNM) were lower than those from algal OM. Correlation analysis revealed that C-DBPs yields (μg/L) were significantly (p < 0.01) interrelated with each other (r = 0.937–0.996), and for each C-DBP, the hydrophobic OM contributed more to their formation (61–90% of total yields) as compared with hydrophilic OM. In spite of these characteristics, an in-depth examination was conducted revealing that the hydrophobicity and aromaticity of C-DBPs precursors were in the order of TCAA > DCAA & TCM > CAA. DCAN precursors were highly variable: they were dominated by hydrophobic OM (leaf OM: 86%) or hydrophilic OM (algal OM: 61%). Hydrophilic OM was the most important precursor for TCNM (76–79% of total yields), followed by hydrophobic neutral and base substances (29–45% of total yields), but the hydrophobic acids exhibited an inhibition role in TCNM formation.

This study investigates the occurrence of six phthalates and distribution of the three most-detected phthalates in the karst region of northern Puerto Rico (KRNPR) using data from historical records and current field measurements. Statistical data analyses, including ANOVA, Chi-Square, and logistic regression models are used to examine the major factors affecting the presence and concentrations of phthalates in the KRNPR. The most detected phthalates include DEHP, DBP, and DEP. At least one phthalate specie is detected above DL in 7% of the samples and 24% of the sampling sites. Concentrations of total phthalates average 5.08 ± 1.37 μg L−1, and range from 0.093 to 58.4 μg L−1. The analysis shows extensive spatial and temporal presence of phthalates resulting from dispersed phthalate sources throughout the karst aquifers. Hydrogeological factors are significantly more important in predicting the presence and concentrations of phthalates in eogenetic karst aquifers than anthropogenic factors. Among the hydrogeological factors, time of detection and hydraulic conductivities larger than 300 m d−1 are the most influential factors. Persistent presence through time reflects continuous sources of phthalates entering the aquifers and a high capacity of the karst aquifers to store and slowly release contaminants for long periods of time. The influence of hydraulic conductivity reveals the importance of contaminant fate and transport mechanisms from contamination sources. This study improves the understanding of factors affecting the spatial variability and fate of phthalates in karst aquifers, and allows us to better predict their occurrence based on these factors.

The molecular marker-based chemical mass balance (MM-CMB) method performs well in the source apportionment of organic carbon (OC) but has some difficulty with contributions from primary sources to inorganic secondary ions when apportioning PM2.5 (particles with aerodynamic diameter of 2.5 μm or less) sources. Positive matrix factorization (PMF) with the input of inorganic and organic tracers can properly estimate the contributions of primary and secondary sources to inorganic secondary ions; however, PMF is unable to apportion several PM2.5 sources with large fractions of organic carbon and few elemental compositions. In this study regarding data collected in 2011 and 2012 at three sites in Wuhan, China, the MM-CMB model was used to apportion OC in the PM2.5, and the PMF model was used to apportion the inorganic ions (sulfate, nitrate, and ammonia), dust, and EC. The source contributions of PM2.5 were estimated by reconstructing masses of bulk chemical components that had been apportioned to real-world sources using suitable source apportionment methods. Good performance of this hybrid source apportionment strategy was observed with ten resolved factors, explaining 70–80% of measured PM2.5 mass on average. The hybrid strategy takes the advantages of both models in PM2.5 source apportionment and yields unique source apportionment results for PM2.5 bulk chemical components, which could provide new information for optimizing air quality regulations for the emission abatement of target PM mass and compositions for countries around the world.

Particulate matter (PM) is one of the most serious environmental problems, exacerbating respiratory and vascular illnesses. Plants have the ability to reduce non-point source PM pollution through retention on leaves and branches. Studies of the dynamic processes of PM retention by plants and the mechanisms influencing this process will help to improve the efficiency of urban greening for PM reduction. We examined dynamic processes of PM retention and the major factors influencing PM retention by six trees with different branch structure characteristics in wind tunnel experiments at three different wind speeds. The results showed that the changes of PM numbers retained by plant leaves over time were complex dynamic processes for which maximum values could exceed minimum values by over 10 times. The average value of PM measured in multiple periods and situations can be considered a reliable indicator of the ability of the plant to retain PM. The dynamic processes were similar for PM₁₀ and PM₂.₅. They could be clustered into three groups simulated by continually-rising, inverse U-shaped, and U-shaped polynomial functions, respectively. The processes were the synthetic effect of characteristics such as species, wind speed, period of exposure and their interactions. Continually-rising functions always explained PM retention in species with extremely complex branch structure. Inverse U-shaped processes explained PM retention in species with relatively simple branch structure and gentle wind. The U-shaped processes mainly explained PM retention at high wind speeds and in species with a relatively simple crown. These results indicate that using plants with complex crowns in urban greening and decreasing wind speed in plant communities increases the chance of continually-rising or inverse U-shaped relationships, which have a positive effect in reducing PM pollution.