Hospital admissions due to diseases of arteries and veins peaked at physiological equivalent temperature −10 to 10 °C in Germany in 2009–2011

We aimed to understand relationships of the weather as biometeorological and hospital admissions due to diseases of arteries and veins by subtypes, which have been scarcely studied, in a national setting in recent years. This is an ecological study. Ten percent of daily hospital admissions from the included hospitals (n?=?1,618) across Germany that were available between 1 January 2009 and 31 December 2011 (n?=?5,235,600) were extracted from Statistisches Bundesamt, Germany. We identified I70-I79 Diseases of arteries, arterioles and capillaries and I80-I89 Diseases of veins, lymphatic vessels and lymph nodes by International Classification of Diseases version 10 as the study outcomes. Daily weather data from 64 weather stations that covered 13 German states including air temperature, humidity, wind speed, cloud cover, radiation flux and vapour pressure were obtained and generated into physiologically equivalent temperature (PET). Two-way fractional-polynomial prediction was plotted with 95 % confidence intervals. For most of the subtypes from diseases of arteries and veins, hospital admissions slightly peaked in spring and dropped when PET was at 10 °C. There were no other large differences across 12 months. Admissions of peripheral vascular diseases, arterial embolism and thrombosis, phlebitis and thrombophlebitis, oesophageal varices and nonspecific lymphadenitis peaked when PET was between 0 and ?10 °C, while others peaked when PET was between 0 and 10 °C. More medical resources could have been needed on days when PETs were at ?10 to 10 °C than on other days. Adaptation to such weather change for health professionals and the general public would seem to be imperative.     

Speciated arsenic in air: measurement methodology and risk assessment considerations

Accurate measurement of arsenic (As) in air is critical to providing a more robust understanding of arsenic exposures and associated human health risks. Although there is extensive information available on total arsenic in air, less is known on the relative contribution of each arsenic species. To address this data gap, the authors conducted an in-depth review of available information on speciated arsenic in air. The evaluation included the type of species measured and the relative abundance, as well as an analysis of the limitations of current analytical methods. Despite inherent differences in the procedures, most techniques effectively separated arsenic species in the air samples. Common analytical techniques such as inductively coupled plasma mass spectrometry (ICP-MS) and/or hydride generation (HG)- or quartz furnace (GF)-atomic absorption spectrometry (AAS) were used for arsenic measurement in the extracts, and provided some of the most sensitive detection limits. The current analysis demonstrated that, despite limited comparability among studies due to differences in seasonal factors, study duration, sample collection methods, and analytical methods, research conducted to date is adequate to show that arsenic in air is mainly in the inorganic form. Reported average concentrations of As(III) and As(V) ranged up to 7.4 and 10.4 ng/m3, respectively, with As(V) being more prevalent than As(III) in most studies. Concentrations of the organic methylated arsenic compounds are negligible (in the pg/m3 range). However because of the variability in study methods and measurement methodology, the authors were unable to determine the variation in arsenic composition as a function of source or particulate matter (PM) fraction. In this work, the authors include the implications of arsenic speciation in air on potential exposure and risks. The authors conclude that it is important to synchronize sample collection, preparation, and analytical techniques in order to generate data more useful for arsenic inhalation risk assessment, and a more robust documentation of quality assurance/quality control (QA/QC) protocols is necessary to ensure accuracy, precision, representativeness, and comparability.     

Effect of solution pH on SO2, NO(x), and Hg removal from simulated coal combustion flue gas in an oxidant-enhanced wet scrubber

This paper presents a study on the simultaneous removal of SO2, NO(x) and Hg (both Hg0 and Hg2+) from a simulated flue gas by oxidant injection in a bench-simulated wet limestone scrubber for a wide range of slurry pH. The slurry pH strongly influenced the chemical mechanism in the scrubber and, therefore, affected pollutant removal. This paper also examines the potential ClO2(gas) reemission from a developed multipollutant scrubber at different slurry pHs. To better understand the chemical mechanisms at each slurry pH and to apply a mass balance to the process, detailed product ion analyses were performed for all experiments. Ion analysis covered three different chlorine species (chlorite, chloride, chlorate), sulfate, nitrite and nitrate. Different NO(x) removal efficiencies and mechanisms were found in acidic and alkaline pHs in the multipollutant scrubber. The acidic solution was favorable for NO and Hg0 oxidation, but increasing the slurry pH above 7.0 was disadvantageous for NO and Hg oxidation/removal. However the rate of NO(x) absorption (by percentage) was higher for the alkaline solution.     

Do We Understand Trends in Atmospheric Sulfur Species?

ABSTRACT

Anomalies appear to exist in our understanding of atmospheric sulfur compounds, specifically as evidenced in the time trends of the different chemical forms of these compounds. Trends determined at a number of locations by several different groups seem to indicate that, responding to emission reductions across North America, the concentration of SO₂ in the atmosphere is declining more rapidly than that of aerosol SO₄ ^2-. A number of possible reasons for this discrepancy are examined, but it is not possible to provide a definitive answer at this stage. The intent is to stimulate debate, because shortcomings in our understanding of the processes involved could have profound implications for the credibility of abatement strategies and policies for both acid deposition and fine particulate matter (PM).     

Experimental investigation of wellbore integrity and CO2–brine flow along the casing–cement microannulus

Wellbore integrity is one of the key performance criteria in the geological storage of CO₂. It is significant in any proposed storage site but may be critical to the suitability of depleted oil and gas reservoirs that may have 10’s to 1000’s of abandoned wells. Much previous work has focused on Portland cement which is the primary material used to seal wellbore systems. This work has emphasized the potential dissolution of Portland cement. However, an increasing number of field studies (e.g., Carey et al., 2007), experimental studies (e.g., Kutchko et al., 2006) and theoretical considerations indicate that the most significant leakage mechanism is likely to be flow of CO₂ along the casing–cement microannulus, cement–cement fractures, or the cement–caprock interface.In this study, we investigate the casing–cement microannulus through core-flood experiments. The experiments were conducted on a synthetic wellbore system consisting of a 5-cm diameter sample of cement that was cured with an embedded rectangular length of steel casing that had grooves to accommodate fluid flow. The experiments were conducted at 40 $°$ C and 14 MPa pore pressure for 394 h. During the experiment, 6.2 l of a 50:50 mixture of supercritical CO₂ and 30,000 ppm NaCl-rich brine flowed through 10-cm of limestone before flowing through the 6-cm length cement–casing wellbore system. Approximately 59,000 pore volumes of fluid moved through the casing–cement grooves. Scanning electron microscopy revealed that the CO₂–brine mixture impacted both the casing and the cement. The Portland cement was carbonated to depths of 50–250 $\mu$m by a diffusion-dominated process. There was very little evidence for mass loss or erosion of the Portland cement. By contrast, the steel casing reacted to form abundant precipitates of mixed calcium and iron carbonate that lined the channels and in one case almost completely filled a channel. The depth of steel corroded was estimated at 25– $30\mu$m and was similar in value to results obtained with a simplified corrosion model.The experimental results were applied to field observations of carbonated wellbore cement by Carey et al. (2007) and Crow et al. (2009) to show that carbonation of the field samples was not accompanied by significant CO₂–brine flow at the casing–cement interface. The sensitivity of standard-grade steel casing to corrosion suggests that relatively straight-forward wireline logging of external casing corrosion could be used as a useful indicator of flow behind casing. These experiments also reinforce other studies that indicate rates of Portland cement deterioration are slow, even in the high-flux CO₂–brine experiments reported here.     

Regional source identification using Lagrangian stochastic particle dispersion and HYSPLIT backward-trajectory models

The main objective of this study was to investigate the capabilities of the receptor-oriented inverse mode Lagrangian Stochastic Particle Dispersion Model (LSPDM) with the 12-km resolution Mesoscale Model 5 (MM5) wind field input for the assessment of source identification from seven regions impacting two receptors located in the eastern United States. The LSPDM analysis was compared with a standard version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) single-particle backward-trajectory analysis using inputs from MM5 and the Eta Data Assimilation System (EDAS) with horizontal grid resolutions of 12 and 80 km, respectively. The analysis included four 7-day summertime events in 2002; residence times in the modeling domain were computed from the inverse LSPDM runs and HYPSLIT-simulated backward trajectories started from receptor-source heights of 100, 500, 1000, 1500, and 3000 m. Statistics were derived using normalized values of LSPDM- and HYSPLIT-predicted residence times versus Community Multiscale Air Quality model-predicted sulfate concentrations used as baseline information. From 40 cases considered, the LSPDM identified first- and second-ranked emission region influences in 37 cases, whereas HYSPLIT-MM5 (HYSPLIT-EDAS) identified the sources in 21 (16) cases. The LSPDM produced a higher overall correlation coefficient (0.89) compared with HYSPLIT (0.55-0.62). The improvement of using the LSPDM is also seen in the overall normalized root mean square error values of 0.17 for LSPDM compared with 0.30-0.32 for HYSPLIT. The HYSPLIT backward trajectories generally tend to underestimate near-receptor sources because of a lack of stochastic dispersion of the backward trajectories and to overestimate distant sources because of a lack of treatment of dispersion. Additionally, the HYSPLIT backward trajectories showed a lack of consistency in the results obtained from different single vertical levels for starting the backward trajectories. To alleviate problems due to selection of a backward-trajectory starting level within a large complex set of 3-dimensional winds, turbulence, and dispersion, results were averaged from all heights, which yielded uniform improvement against all individual cases.     

Prediction of PAH biodegradation in field contaminated soils using a cyclodextrin extraction technique

Biodegradation has been identified as a major loss process for organic contaminants in soils and, as a result, microbial strategies have been developed for the remediation of contaminated land. Prediction of the biodegradable fraction would be important for determining bioremediation end-points in the clean-up of contaminated land. The aim of this study was to investigate the ability of a cyclodextrin extraction to predict the extent to which polycyclic aromatic hydrocarbons (PAHs) would be degraded microbiologically in field contaminated soils; further testing the robustness and reproducibility of this extraction in chemically complex systems. Dichloromethane and hydroxypropyl-beta-cyclodextrin (HPCD) extractable fractions were measured together with the PAH biodegradable fraction in each of the six field contaminated soils. The amounts of PAHs degraded by the catabolic activity of the indigenous microflora in each of the soils were correlated with HPCD-extractable PAH concentrations. The regressions showed that the amounts of lower molecular weight PAHs extracted by the HPCD were not significantly (P > 0.05) different to the amounts that were degraded. However, higher molecular weight PAHs that were extracted by HPCD did differ significantly (P < 0.05) from the amounts degraded. Although the HPCD extraction did overestimate the microbially degradable fraction of the higher molecular weight PAHs, overall the correlations between the HPCD extractable fraction and the microbially degradable fraction were very close, with mean values of the slope of line for the six soils equalling 1. This study further describes the robust and reproducible nature of the aqueous-based soil extraction technique reliably measuring the extent to which PAHs will be microbially degraded in soil.     

Near-field loading dynamics of total phosphorus and short-term water quality variations at a rainbow trout cage farm in Lake Huron

Aquatic total phosphorus (Tot-P) is measured at fish-cages in Lake Huron for environmental regulatory compliance. An improved understanding of how Tot-P is manifested in the near-field (相似文献   

Gradient forests: calculating importance gradients on physical predictors

In ecological analyses of species and community distributions there is interest in the nature of their responses to environmental gradients and in identifying the most important environmental variables, which may be used for predicting patterns of biodiversity. Methods such as random forests already exist to assess predictor importance for individual species and to indicate where along gradients abundance changes. However, there is a need to extend these methods to whole assemblages, to establish where along the range of these gradients the important compositional changes occur, and to identify any important thresholds or change points. We develop such a method, called "gradient forest," which is an extension of the random forest approach. By synthesizing the cross-validated R2 and accuracy importance measures from univariate random forest analyses across multiple species, sampling devices, and surveys, gradient forest obtains a monotonic function of each predictor that represents the compositional turnover along the gradient of the predictor. When applied to a synthetic data set, the method correctly identified the important predictors and delineated where the compositional change points occurred along these gradients. Application of gradient forest to a real data set from part of the Great Barrier Reef identified mud fraction of the sediment as the most important predictor, with highest compositional turnover occurring at mud fraction values around 25%, and provided similar information for other predictors. Such refined information allows for more accurate capturing of biodiversity patterns for the purposes of bioregionalization, delineation of protected areas, or designing of biodiversity surveys.