Biogas residue and organic manure are frequently used for crop planting. However, the evaluation of antibiotic resistant bacteria (ARB), antibiotic resistance genes (ARGs) and bacterial community before their applications to fields is still lacking. This study monitored the variations of bacteria resistant to sulfadiazine, tetracycline and norfloxacin, 57 resistance genes for sulfonamides, tetracyclines and fluoroquinolones as well as the bacterial community during the 28-day aerobic storage of biogas residue and organic manure by using viable plate counts, high-throughput qPCR and Illumina MiSeq sequencing methods. Then two storage conditions, incubator (25 °C) and natural environment, were used to assess the responses of ARB and ARGs to the environmental factors. Results showed that a total of 35 and 21 ARGs were detected in biogas residue and organic manure, respectively. ARB and ARGs were enriched up to 8.01-fold in biogas residue after the 28-day storage, but varied in a narrow range during the storage of organic manure. Compared with the incubator condition, the proliferation of ARB and ARGs in biogas residue under the natural condition was relatively inhibited by the varied and complicated environmental factors. However, we found that there was no significant difference of ARB and ARGs in organic manure between the incubator and natural conditions. Bacterial community was also shifted during the storage of biogas residue, especially Bacteroidetes_VC2.1_Bac22, Aequorivita, Luteimonas and Arenimonas. Network analysis revealed that the relationship in biogas residue was much more complicated than that in organic manure, which ultimately resulted in large successions of ARB and ARGs during the short-term storage of biogas residue. Therefore, we suggest that further measures should be taken before the application of biogas residue to fields.

To examine the mechanism of hexavalent chromium [Cr(VI)]-induced carcinogenesis, a cross-sectional study in workers with or without exposure to Cr(VI) as well as in vitro administration of Cr(VI) in 16HBE cells was conducted. We explored the associations between Cr(VI) exposure, methylation modification of DNA repair genes and their expression levels, and genetic damage. Results showed that hypermethylation of CpG sites were observed in both occupationally exposed workers and 16HBE cells administrated Cr(VI). DNA damage markers including 8-hydroxydeoxyguanosine (8-OHdG) and micronucleus frequency in Cr(VI)-exposed workers were significantly higher than the control group. Among workers, blood Cr concentration was positively correlaed with the methylation level of CpG sites in DNA repair genes including CpG6,7, CpG8, CpG9,10,11 of MGMT, CpG11 of HOGG1; CpG15,16,17, CpG19 of RAD51, and genetic damage markers including 8-OHdG and micronucleus frequency. Significant negative association between methylation levels of CpG sites in DNA repair genes and corresponding mRNA was also observed in 16HBE cells. This indicated that Cr(VI) exposure can down-regulate DNA repair gene expression by hypermethylation, which leads to enhanced genetic damage. The methylation level of these CpG sites of DNA repair genes can be potential epigenetic markers for Cr(VI)-induced DNA damage.

Ambient air pollution has been associated with adverse respiratory outcomes, especially among children with asthma. This study reports on associations between daily ambient air pollutant concentrations and the respiratory symptoms of schoolchildren living in Durban, South Africa. This city is Africa's busiest port and a key hub for imported crude oil and exported refined petroleum and petrochemical products, and it experiences a mixture of air pollutants that reflects emissions from industry, traffic and biomass burning. Children in four communities in the highly industrialized southern portion of the city were compared to children of similar socio-economic profiles living in the north of the city. One school was selected in each community. A total of 423 children were recruited. Symptom logs were completed every 1.5–2 h over 3-week period in each of four seasons. Ambient concentrations of NO₂, NO, SO₂, CO, O₃, PM₂.₅ and PM₁₀ were measured throughout the study. Generalized estimating equation (GEE) models were used to estimate odds ratios (ORs) and assess lag effects (1–5 days) using single pollutant (single lags or distributed lags) models. Concentrations of SO₂ and NOₓ were markedly higher in the south, while PM₁₀ did not vary. Significant increase in the odds ratios of cough were identified for the various lags analyzed. The OR of symptoms was further increased among those living in the south compared to the north. In conclusion, in this analysis of over 70,000 observations, we provide further evidence that exposure to PM₁₀, SO₂, NO₂ and NO is associated with significantly increased occurrence of respiratory symptoms among children. This was evident for cough, shortness of breath, and chest tightness, across the four pollutants and for different lags of exposure. This is the first study describing these changes in sub-Saharan Africa.

Foodstuffs may be contaminated by organophosphate esters (OPEs) and become an important source of human exposure since OPEs are ubiquitous in the environment. In the present study, 10 OPEs were analyzed in various food matrices collected from a city in Eastern China including chicken, pork, fishes, vegetables, tofu, eggs, milk and cereals. The concentrations of Σ₁₀OPEs ranged from 1.1 to 9.6 ng g⁻¹ fresh weight (fw) in the foodstuffs. Cereals had the highest residual level of total OPEs with a mean value of 5.7 ng g⁻¹ fw. Tris(2-ethylhexyl) phosphate was detected in all foodstuff samples and showed the highest median residual concentration of 1.3 ng g⁻¹ fw among the OPE analogs. The daily dietary intake of OPEs was calculated as 3.6 and 2.4 μg d⁻¹ for adults and children. Cereals were identified as the major contributor to the total OPEs among different types of foodstuffs. Preliminary exposure assessment revealed that the current non-cancer health risks of OPEs via dietary intake were in the range of 10⁻⁵-10⁻³, indicating low risk levels. Moreover, the hazard index of OPEs indicated that the risk for children (3 × 10⁻³) was higher than adults (2 × 10⁻³).

Airborne systems such as lightweight and highly portable unmanned aerial vehicles (UAVs) are becoming increasingly widespread in both academia and industry - with an ever-increasing range of applications, including (but not limited to), air quality sampling, wildlife monitoring and land-use mapping.In this work, high-resolution airborne photogrammetry obtained using a multi-rotor system operating at low survey altitudes, is combined with ground-based radiation mapping data acquired at an interim storage facility for wastes removed as part of the large-scale Fukushima clean-up program. The investigation aimed to assess the extent to which the remediation program at a specific site has contained the stored contaminants, as well as present a new methodology for rapidly surveying radiological sites globally. From the three-dimensional rendering of the site of interest, it was possible to not only generate a powerful graphic confirming the elevated radiological intensity existing at the location of the waste bags, but also to also illustrate the downslope movement of contamination due to species leakage from the large 1m³ storage bags. The entire survey took less than 1 h to perform, and was subsequently post-processed using graphical information software to obtain the renderings. The conclusions within this study not only highlight the usefulness of incorporating three-dimensional renderings within radiation mapping protocols, but also conclude that current methods of monitoring these storage facilities in the long term could be improved through the integration of UAVs within the standard protocol.

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.