An isotope-dilution ultra-performance liquid chromatography–electrospray tandem mass spectrometry method combined with dansylation was established to sensitively quantify four steroid estrogens (estrone, 17α-estradiol, 17β-estradiol and 17α-ethynylestradiol) and bisphenol A in sewage influent and effluent. A simple hexane extraction was performed from a small volume (10 mL), followed by dansyl chloride derivatization and purification with a silica cartridge. The method effectively reduced the matrix effects in sample extract and permitted the selective and sensitive determination of target compounds from complicated matrices. The detection limits of the method for steroid estrogens were 0.20–0.90 ng L⁻¹ in influent and 0.10–0.20 ng L⁻¹ in effluent samples. For bisphenol A, the limits detection of the method were 20 and 0.80 for influent and effluent samples, respectively. Recoveries of 85%–96% were observed in all matrices. The method was applied to analyze residual estrogens and bisphenol A in sewage influent and effluent samples from Beijing, China. The concentrations of bisphenol A (636–1200 ng L⁻¹) were up to 250 times higher than those of steroid estrogens. Estrone was the dominant estrogen in influent and effluent samples, while similar concentrations of 17α-estradiol and 17β-estradiol were detected in all samples.

Low-cost air quality sensors offer high-resolution spatiotemporal measurements that can be used for air resources management and exposure estimation. Yet, such sensors require frequent calibration to provide reliable data, since even after a laboratory calibration they might not report correct values when they are deployed in the field, due to interference with other pollutants, as a result of sensitivity to environmental conditions and due to sensor aging and drift. Field calibration has been suggested as a means for overcoming these limitations, with the common strategy involving periodical collocations of the sensors at an air quality monitoring station. However, the cost and complexity involved in relocating numerous sensor nodes back and forth, and the loss of data during the repeated calibration periods make this strategy inefficient. This work examines an alternative approach, a node-to-node (N2N) calibration, where only one sensor in each chain is directly calibrated against the reference measurements and the rest of the sensors are calibrated sequentially one against the other while they are deployed and collocated in pairs. The calibration can be performed multiple times as a routine procedure. This procedure minimizes the total number of sensor relocations, and enables calibration while simultaneously collecting data at the deployment sites. We studied N2N chain calibration and the propagation of the calibration error analytically, computationally and experimentally. The in-situ N2N calibration is shown to be generic and applicable for different pollutants, sensing technologies, sensor platforms, chain lengths, and sensor order within the chain. In particular, we show that chain calibration of three nodes, each calibrated for a week, propagate calibration errors that are similar to those found in direct field calibration. Hence, N2N calibration is shown to be suitable for calibration of distributed sensor networks.

Ecological effects of atmospheric nitrogen (N) and sulfur (S) deposition on two hardwood forest sites in the eastern United States were simulated in the context of a changing climate using the dynamic coupled biogeochemical/ecological model chain ForSAFE-Veg. The sites are a mixed oak forest in Shenandoah National Park, Virginia (Piney River) and a mixed oak-sugar maple forest in Great Smoky Mountains National Park, Tennessee (Cosby Creek). The sites have received relatively high levels of both S and N deposition and the climate has warmed over the past half century or longer. The model was used to evaluate the composition of the understory plant communities, the alignment between plant species niche preferences and ambient conditions, and estimate changes in relative species abundances as reflected by plant cover under various scenarios of future atmospheric N and S deposition and climate change. The main driver of ecological effects was soil solution N concentration. Results of this research suggested that future climate change might compromise the capacity for the forests to sustain habitat suitability. However, vegetation results should be considered preliminary until further model validation can be performed. With expected future climate change, preliminary estimates suggest that sustained future N deposition above 7.4 and 5.0 kg N/ha/yr is expected to decrease contemporary habitat suitability for indicator plant species located at Piney River and Cosby Creek, respectively.

Long- and short-term exposure to PM2.5 is of great concern in China due to its adverse population health effects. Characteristic of the severity of the situation in China is that in the Jing-Jin-Ji region considered in this work a total of 2725 excess deaths have been attributed to short-term PM2.5 exposure during the period January 10–31, 2013. Technically, the processing of large space-time PM2.5 datasets and the mapping of the space-time distribution of PM2.5 concentrations often constitute high-cost projects. To address this situation, we propose a synthetic modeling framework based on the integration of (a) the Bayesian maximum entropy method that assimilates auxiliary information from land-use regression and artificial neural network (ANN) model outputs based on PM2.5 monitoring, satellite remote sensing data, land use and geographical records, with (b) a space-time projection technique that transforms the PM2.5 concentration values from the original spatiotemporal domain onto a spatial domain that moves along the direction of the PM2.5 velocity spread. An interesting methodological feature of the synthetic approach is that its components (methods or models) are complementary, i.e., one component can compensate for the occasional limitations of another component. Insight is gained in terms of a PM2.5 case study covering the severe haze Jing-Jin-Ji region during October 1–31, 2015. The proposed synthetic approach explicitly accounted for physical space-time dependencies of the PM2.5 distribution. Moreover, the assimilation of auxiliary information and the dimensionality reduction achieved by the synthetic approach produced rather impressive results: It generated PM2.5 concentration maps with low estimation uncertainty (even at counties and villages far away from the monitoring stations, whereas during the haze periods the uncertainty reduction was over 50% compared to standard PM2.5 mapping techniques); and it also proved to be computationally very efficient (the reduction in computational time was over 20% compared to standard mapping techniques).

Air pollutant levels depend on emissions but can also be affected by the meteorological situation. We examined air pollutant trends (PM₁₀, NO₂, O₃ and SO₂) in Slovenia, where in the past the main issue were SO₂ levels. Now, the population is still exposed to PM₁₀ and ozone levels that are above the recommended levels.Our goal was to assess if the levels of air pollutants were decreasing from 2002 to 2017 due to emission ceilings or were more influenced by changes in the meteorological situation. We modelled the relationship between levels, meteorological parameters, and seasonality and then used the models with the best estimated generalisation to adjust levels for meteorology. Models showed a significant relationship between meteorological parameters and PM₁₀, NO₂, and O₃ levels, but not SO₂. We analysed trends of raw and adjusted levels and compared them. Trends of PM₁₀ and SO₂ were decreasing at all locations for raw and adjusted data. The largest decrease was observed in SO₂ levels where the largest decrease in emissions occurred. Trends of NO₂ were also significant and negative at most locations. Levels of O₃ did not exhibit a significant trend at most locations.Results show that changes in the meteorological situation affected PM₁₀ levels the most, especially where the entire period (2002–2017) could be observed. There is strong empirical evidence that changes in meteorological parameters contributed to the decrease in PM₁₀ levels while the decrease in NO₂ and SO₂ levels can be attributed to emission ceilings.

Telomere length (TL) is an index of cellular aging and can predict the incidences of many age-related diseases. Change of TL might be affected by environmental pollution and individual's genetic background. In this cohort study, we aimed to evaluate the associations between polycyclic aromatic hydrocarbons (PAHs) exposure and longitudinal TL shortening, and investigate whether genetic variations in TERT-CLPTM1L can modify these associations. We measured the baseline concentrations of twelve urinary PAH metabolites and genotyped six variants at TERT-CLPTM1L among 1243 coke-oven workers. The relative leukocyte TL was detected in both baseline and follow-up (4 years later) visits. The TL shortening were estimated by TL decline and TL ratio. We found that the urinary level of 1-hydroxypyrene (1-OHP) had significant dose-response relationships with increased TL decline [β(95%CI) = 0.078(0.023, 0.133), P = 0.005] and TL ratio [β(95%CI) = 0.096(0.037, 0.155), P = 0.002]. Besides, urinary 1-hydroxynaphthalene (1-OHNa) was marginally dose-related with elevated TL decline [β(95%CI) = 0.053(-0.001, 0.107), P = 0.055] and TL ratio [β(95%CI) = 0.057(-0.002, 0.116), P = 0.058]. Analyses of TERT-CLPTM1L variants showed that the rs401681 and rs465498 could modify the effect of 1-OHP on increasing TL decline (Pᵢₙₜₑᵣₐcₜᵢₒₙ = 0.012 and 0.035, respectively) and TL ratio (Pᵢₙₜₑᵣₐcₜᵢₒₙ = 0.014 and 0.067, respectively), which were pronounced among rs401681TT and rs465498CC carriers, but not seen among rs401681TC + CC and rs465498CT + TT carriers. In conclusion, elevated exposure to PAHs can accelerate the TL shortening and this effect can be modified by TERT-CLPTM1L variants. These results may add potential evidence for gene-environment interactions on dynamic changes of telomere length. Further studies are warranted to validate these findings and uncover the underlying mechanisms.

Polybrominated diphenyl ethers (PBDEs) are toxic chemicals widely distributed in the environment, but few studies are available on their potential toxicity to rice at metabolic level. Therefore we exposed ten rice (Oryza sativa) varieties to 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47), a predominant congener of PBDEs, in hydroponic solutions with different concentrations. Two varieties that showed different biological effects to BDE-47, YY-9 and LJ-7, were screened as sensitive and tolerant varieties according to changes of morphological and physiological indicators. Metabolic research was then conducted using gas chromatography−mass spectrometry combined with diverse analyses. Results showed that LJ-7 was more active in metabolite profiles and adopted more effective antioxidant defense machinery to protect itself against oxidative damages induced by BDE-47 than YY-9. For LJ-7, the contents of 13 amino acids and 24 organic acids, especially l-glutamic acid, beta-alanine, glycolic acid and glyceric acid were up-regulated significantly which contributed to scavenging reactive oxygen species. In the treatment of 500 μg/L BDE-47, the contents of these four metabolites increased by 33.6-, 19.3-, 10.6- and 10.2-fold, respectively. The levels of most saccharides (such as d-glucose, lactulose, maltose, sucrose and d-cellobiose) also increased by 1.7–12.4 fold which promoted saccharide-related biosynthesis metabolism. Elevation of tricarboxylic acid cycle and glyoxylate and dicarboxylate metabolism enhanced energy-producing processes. Besides, the contents of secondary metabolites, chiefly polyols and glycosides increased significantly to act on defending oxidative stress induced by BDE-47. In contrast, the levels of most metabolites decreased significantly for YY-9, especially those of 13 amino acids (by 0.9%–67.1%) and 19 organic acids (by 7.8%–70.0%). The positive metabolic responses implied LJ-7 was tolerant to BDE-47, while the down-regulation of most metabolites indicated the susceptible nature of YY-9. Since metabolic change might affect the yield and quality of rice, this study can provide useful reference for rice cultivation in PBDEs-polluted areas.

This article exploits a new approach for synthesis of polysaccharide-based grafted sodium styrene sulfonate (SSS) super absorbent hydrogels (SAHs) in aqueous solution by γ-radiation under ambient conditions. Important optimal conditions for preparation of hydrogels with the best swelling ratio, such as gamma irradiation dose and the ratio of feed composition have been discussed. Characterization techniques such as the SEM/EDS, FTIR and DSC were used in describing the newly prepared hydrogels. The FTIR gave characteristic peaks for -SO₃Na group at 1042 and 988 cm⁻¹, showing successful grafting of SSS onto the polysaccharide base material. The dependence of swelling behaviors in various pH solutions and salts solutions were investigated in detail. The prepared hybrid hydrogel showed most optimum swelling capacity at neutral pH whereas equilibrium swelling of SAHs was achieved within 5 h. The swelling of SAHs influenced obviously to metal ion removal percentage in solution.

In this study, the molecular mechanisms involved in Ralstonia eutropha Q2-8-induced increased biomass and reduced cadmium (Cd) and arsenic (As) uptake in wheat plants (Triticum aestivum cv. Yangmai 16) were investigated in growth chambers. Strain Q2-8 significantly increased plant biomass (22–75%) without and with Cd (5 μM) + As (10 μM) stress and reduced plant above-ground tissue Cd (37%) and As (34%) contents compared to those in the controls. Strain Q2-8 significantly increased the proportions of Cd and As in wheat root cell walls. Under Cd and As stress, 109 root proteins were differentially expressed among which those involved in metabolisms, stress and defence, and energy were dominant in the presence of strain Q2-8. Furthermore, energy-, defence-, and cell wall biosynthesis-related proteins were found to be up-regulated. Notably, differentially expressed cell wall biosynthesis-related proteins in roots were only found in bacteria-inoculated plants under Cd and As stress. The results suggest that strain Q2-8 can alleviate Cd and As toxicity to wheat plant seedlings and reduce above-ground tissue Cd and As uptake by increasing the efficiency of root energy metabolism, defence, and cell wall biosynthesis under Cd and As stress.

Mg-Al-Ox supported monometallic (Ni) and bimetallic (Ni-Co) catalysts with different compositions of Mg and Al were investigated for CO₂ reforming of CH₄, using both coal and pure gas feeds, to limit the emission of these environmental pollutant gases into the atmosphere. Results showed that all the catalysts were active for dry reforming reaction using both feeds. Reactants conversion, stoichiometric product selectivity, and resistance to carbon deposition of catalysts remarkably improved when the Mg/Al ratio was greater than 1. Characterization results revealed changes in the bulk structure, textural and surface properties as the Mg/Al ratio and composition of catalysts changed. Improved active metal reduction, metal-support and metal-metal interaction (in the bimetallic) were also noted in the catalysts with Mg/Al ratio greater than 1. With respect to feed composition, less carbon deposition was recorded in the corresponding catalysts using coal gas compared to the pure gas. Ni-Co interaction and their interaction with MgO facilitated better basicity, increased metal dispersion and smaller particle size in Ni-Co-Mg₁.₇-Al₁-Ox, which showed best catalytic performance with no carbon deposition in both feeds. These interactions and properties stabilized the Ni site, which made the Ni-Co-Mg₁.₇-Al₁-Ox, catalyst resistant to sintering and carbon deposition.