Cadmium (Cd) uptake and accumulation in crop plants, especially in wheat (Triticum aestivum) and rice (Oryza sativa) is one of the main concerns for food security worldwide. A field experiment was done to investigate the effects of limestone, lignite, and biochar on growth, physiology and Cd uptake in wheat and rice under rotation irrigated with raw effluents. Initially, each treatment was applied alone at 0.1% and combined at 0.05% each and wheat was grown in the field and then, after wheat harvesting, rice was grown in the same field without additional application of amendments. Results showed that the amendments applied increased the grain and straw yields as well as gas exchange attributes compared to the control. In both crops, highest Cd concentrations in straw and grains and total uptake were observed in control treatments while lowest Cd concentrations was observed in limestone + biochar treatment. No Cd concentrations were detected in wheat grains with the application of amendments except limestone (0.1%). The lowest Cd harvest index was observed in limestone + biochar and lignite + biochar treatments for wheat and rice respectively. Application of amendments decreased the AB-DTPA extractable Cd in the soil while increasing the Cd immobilization index after each crop harvest. The benefit-cost ratio and Cd contents in plants revealed that limestone + biochar treatment might be an effective amendment for increasing plant growth with lower Cd concentrations.

We estimated the sample size (the number of samples) required to evaluate the concentration of radiocesium (¹³⁷Cs) in Japanese fir (Abies firma Sieb. & Zucc.), 5 years after the outbreak of the Fukushima Daiichi Nuclear Power Plant accident. We investigated the spatial structure of the contamination levels in this species growing in a mixed deciduous broadleaf and evergreen coniferous forest stand. We sampled 40 saplings with a tree height of 150 cm–250 cm in a Fukushima forest community. The results showed that: (1) there was no correlation between the ¹³⁷Cs concentration in needles and soil, and (2) the difference in the spatial distribution pattern of ¹³⁷Cs concentration between needles and soil suggest that the contribution of root uptake to ¹³⁷Cs in new needles of this species may be minor in the 5 years after the radionuclides were released into the atmosphere. The concentration of ¹³⁷Cs in needles showed a strong positive spatial autocorrelation in the distance class from 0 to 2.5 m, suggesting that the statistical analysis of data should consider spatial autocorrelation in the case of an assessment of the radioactive contamination of forest trees. According to our sample size analysis, a sample size of seven trees was required to determine the mean contamination level within an error in the means of no more than 10%. This required sample size may be feasible for most sites.

Short chain chlorinated paraffins (SCCPs) are ubiquitously present as persistent organic pollutants in the environment. However, little information on the interaction of SCCPs with plants is currently available. In this work, young pumpkin plants (Cucurbita maxima × C. Moschata) were hydroponically exposed to the congener of chlorinated decane, 1,2,5,5,6,9,10-heptachlorodecane (1,2,5,5,6,9,10-HepCD), to investigate the uptake, translocation and transformation of chlorinated decanes in the intact plants. It was found that parent HepCD was taken up by the pumpkin roots, translocated from root to shoots, and phytovolatilized from pumpkin plants to air via the plant transpiration flux. Our data suggested that dechlorination of 1,2,5,5,6,9,10-HepCD to lower chlorinated decanes and rearrangement of chlorine atoms in the molecule were all mediated by the whole pumpkin seedlings. Chlorinated decanes were found in the shoots and roots of blank controls, indicating that chlorinated decanes in the air could be absorbed by leaves and translocated from shoots to roots. Lower chlorinated congeners (C10H17Cl5) tended to detain in air compared to higher chlorinated congeners (C10H16Cl6 and other C10H15Cl7). Potential transformation pathway and behavior of 1,2,5,5,6,9,10-HepCD in pumpkin were proposed based on these experiments.

Previous studies have suggested that short-term exposure to ambient air pollution was associated with pediatric hospital admissions and emergency room visits for certain respiratory diseases; however, there is limited evidence on the association between short-term air pollution exposure and pediatric outpatient visits. Our aim was to quantitatively assess the short-term effects of ambient air pollution on pediatric outpatient visits for respiratory diseases. We conducted a time-series study in Yichang city, China between Jan 1, 2014 and Dec 31, 2015. Daily counts of pediatric respiratory outpatient visits were collected from 3 large hospitals, and then linked with air pollution data from 5 air quality monitoring stations by date. We used generalized additive Poisson models to conduct linear and nonlinear exposure-response analyses between air pollutant exposures and pediatric respiratory outpatient visits, adjusting for seasonality, day of week, public holidays, temperature, and relative humidity. Each interquartile range (IQR) increase in PM2.5 (lag 0), PM10 (lag 0), NO2 (lag 0), CO (lag 0), and O3 (lag 4) concentrations was significantly associated with a 1.91% (95% CI: 0.60%, 3.23%), 2.46% (1.09%, 3.85%), 1.88% (0.49%, 3.29%), 2.00% (0.43%, 3.59%), and 1.91% (0.45%, 3.39%) increase of pediatric respiratory outpatient visits, respectively. Similarly, the nonlinear exposure-response analyses showed monotonic increases of pediatric respiratory outpatient visits by increasing air pollutant exposures, though the associations for NO2 and CO attenuated at higher concentrations. These associations were unlikely modified by season. We did not observe significant association for SO2 exposure. Our results suggest that short-term exposures to PM2.5, PM10, NO2, CO, and O3 may account for increased risk of pediatric outpatient visits for respiratory diseases, and emphasize the needs for reduction of air pollutant exposures for children.

The impact of chronic exposure to air pollution and outcomes in the acute respiratory distress syndrome (ARDS) is unknown. The Nationwide Inpatient Sample (NIS) from 2011 was utilized for this analysis. The NIS is a national database that captures 20% of all US in-patient hospitalizations from 47 states. Patients with ARDS who underwent mechanical ventilation from the highest 15 ozone pollution cities were compared with the rest of the country. Secondary analyses assessed outcomes of ARDS patients for ozone pollution and particulate matter pollution on a continuous scale by county of residence. A total of 8,023,590 hospital admissions from the 2011 NIS sample were analyzed. There were 93,950 patients who underwent mechanical ventilation for ARDS included in the study. Patients treated in high ozone regions had significantly higher unadjusted hospital mortality (34.9% versus 30.8%, p < 0.01) than patients in cities with control levels of ozone. After controlling for all variables in the model, treatment in a hospital located in a high ozone pollution area was associated with an increased odds of in-hospital mortality (OR 1.11, 95% CI 1.08–1.15, p < 0.01). After adjustment for all variables in the model, for each increase in ozone exposure by 0.01 ppm the OR for death was 1.07 (95% CI 1.06–1.08, p < 0.01). Similarly, for each increase in particulate matter exposure by 10 μg/m³, the OR for death was 1.08 (95% CI 1.02–1.16, p < 0.01).Chronic exposure to both ozone and particulate matter pollution is associated with higher rates of mortality in ARDS. These preliminary findings need to be confirmed by further detailed studies.

The most common mass spectrometry approach analyzing contamination of the environment deals with targeted analysis, i.e. detection and quantification of the selected (priority) pollutants. However non-targeted analysis is becoming more often the method of choice for environmental chemists. It involves implementation of modern analytical instrumentation allowing for comprehensive detection and identification of the wide variety of compounds of the environmental interest present in the sample, such as pharmaceuticals and their metabolites, musks, nanomaterials, perfluorinated compounds, hormones, disinfection by-products, flame retardants, personal care products, and many others emerging contaminants. The paper presents the results of detection and identification of previously unreported organic compounds in snow samples collected in Moscow in March 2016. The snow analysis allows evaluation of long-term air pollution in the winter period. Gas chromatography coupled to a high resolution time-of-flight mass spectrometer has enabled us with capability to detect and identify such novel analytes as iodinated compounds, polychlorinated anisoles and even Ni-containing organic complex, which are unexpected in environmental samples. Some considerations concerning the possible sources of origin of these compounds in the environment are discussed.

Exposure to essential and non-essential elements may be elevated for green sea turtles (Chelonia mydas) that forage close to shore. Biomonitoring of trace elements in turtle blood can identify temporal trends over repeated sampling events, but any interpretation of potential health risks due to an elevated exposure first requires a comparison against a baseline. This study aims to use clinical reference interval (RI) methods to produce exposure baseline limits for essential and non-essential elements (Na, Mg, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Sb, Ba, and Pb) using blood from healthy subadult turtles foraging in a remote and offshore part of the Great Barrier Reef. Subsequent blood biomonitoring of three additional coastal populations, which forage in areas dominated by agricultural, urban and military activities, showed clear habitat-specific differences in blood metal profiles relative to the those observed in the offshore population. Coastal turtles were most often found to have elevated concentrations of Co, Mo, Mn, Mg, Na, As, Sb, and Pb relative to the corresponding RIs. In particular, blood from turtles from the agricultural site had Co concentrations ranging from 160 to 840 μg/L (4–25 times above RI), which are within the order expected to elicit acute effects in many vertebrates. Additional clinical blood biochemistry and haematology results indicate signs of a systemic disease and the prevalence of an active inflammatory response in a high proportion (44%) of turtles from the agricultural site. Elevated Co, Sb, and Mn in the blood of these turtles significantly correlated with elevated markers of acute inflammation (total white cell counts) and liver dysfunction (alkaline phosphatase and total bilirubin). The results of this study support the notion that elevated trace element exposures may be adversely affecting the health of nearshore green sea turtles.

With the progress of global industrialization and environmental deterioration, the relationship between human health and the living environment has become an increasing focus of attention. Polychlorinated biphenyls (PCBs, including dioxin-like polychlorinated biphenyls and non-dioxin-like polychlorinated biphenyls), as part of the organic chlorine contaminants, have been suspected as playing a role in the etiopathogenesis of endometriosis. Several population-based studies have proposed that exposure to PCBs may increase the risk of developing endometriosis, while some epidemiological studies have failed to find any association between PCBs and endometriosis. The purpose of this review is to discuss the potential pathophysiological relationship between endometriosis and PCBs with a focus on both dioxin-like polychlorinated biphenyls and non-dioxin-like polychlorinated biphenyls.

In the Pampas, public concern has strongly risen because of the intensive use of glyphosate for weed control and fallow associated with biotech crops. The present study was aimed to evaluate the occurrence and concentration of the herbicide and its main metabolite (AMPA) in soil and other environmental compartments of the mentioned agroecosystem, including groundwater, in relation to real-world agricultural management practices in the region. Occurrence was almost ubiquitous in solid matrices (83–100%) with maximum concentrations among the higher reported in the world (soil: 8105 and 38939; sediment: 3294 and 7219; suspended particulate matter (SPM): 584 and 475 μg/kg of glyphosate and AMPA). Lower detection frequency was observed in surface water (27–55%) with maximum concentrations in whole water of 1.80 and 1.90 μg/L of glyphosate and AMPA, indicating that SPM analysis would be more sensitive for detection in the aquatic ecosystem. No detectable concentrations of glyphosate or AMPA were observed in groundwater. Glyphosate soil concentrations were better correlated with the total cumulative dose and total number of applications than the last spraying event dose, and an increment of 1 mg glyphosate/kg soil every 5 spraying events was estimated. Findings allow to infer that, under current practices, application rates are higher than dissipation rates. Hence, glyphosate and AMPA should be considered “pseudo-persistent” pollutants and a revisions of management procedures, monitoring programs, and ecological risk for soil and sediments should be also recommended.

Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the proposed hybrid models can be used as effective and simple tools for air pollution forecasting and warning as well as for management.