Validation of evacuated canisters for sampling volatile organic compounds in healthcare settings

Healthcare settings present a challenging environment for assessing low-level concentrations of specific volatile organic compounds (VOCs) in the presence of high background concentrations of alcohol from the use of hand sanitizers and surface disinfectants. The purposes of this laboratory-based project were to develop and validate a sampling and analysis methodology for quantifying low-level VOC concentrations as well as high-level alcohol concentrations found together in healthcare settings. Sampling was conducted using evacuated canisters lined with fused silica. Gas chromatography/mass spectrometry analysis was performed using preconcentration (for ppb levels) and loop injection (for ppm levels). For a select list of 14 VOCs, bias, precision, and accuracy of both the preconcentration and loop injection methods were evaluated, as was analyte stability in evacuated canisters over 30 days. Using the preconcentration (ppb-level) method, all validation criteria were met for 13 of the 14 target analytes-ethanol, acetone, methylene chloride, hexane, chloroform, benzene, methyl methacrylate, toluene, ethylbenzene, m,p-xylene, o-xylene, alpha-pinene, and limonene. Using the loop injection (ppm-level) method, all validation criteria were met for each analyte. At ppm levels, alpha-pinene and limonene remained stable over 21 days, while the rest of the analytes were stable for 30 days. All analytes remained stable over 30 days at ppb levels. This sampling and analysis approach is a viable (i.e., accurate and stable) methodology that will enable development of VOC profiles for mixed exposures experienced by healthcare workers.     

A Multiple Criteria Decision Analysis Model Based on ELECTRE TRI-C for Erosion Risk Assessment in Agricultural Areas

This paper deals with a real-world decision-aiding problem for zoning the risk of erosion, total suspended solids emissions, and ecological consequences of their transfers towards the streams. One of these consequences is the decrease of fishes into the streams in agricultural watersheds, because of the clogging of spawning areas. Given the multiple criteria nature of the problem, the originality of our research is to adapt a new decision-aiding sorting method, ELECTRE TRI-C, for identifying risk zones in rural areas, where measures must be taken. The developed model was applied in a small watershed (Low Normandy, France) where the objective was to assess the most appropriate intervention for protecting the reproduction habitat of the salmonid fishes. Agricultural parcels were evaluated on multiple criteria for grouping them into four risk categories, which are related to risk levels as well as priorities on the improvement works. The decision-aiding sorting model is co-constructed, within a constructive approach, through an interaction process between decision-aiding analysts, environmental experts, and local actors for improving transparency and communication on the results. This model is linked with a geographical information system (GIS) for assessing a set of criteria and the visualization of the farming parcels along with their type of intervention they should be submitted to best practices. The assignment results were validated by the environmental experts. These results have a strong impact on the agricultural practices of the farmers into the watersheds. The model proposed in this paper can be considered as a useful decision aid tool in any regions for implementing public agricultural and environmental policies for protecting the ecological areas.     

Analysis of long-term water quality for effective river health monitoring in peri-urban landscapes—a case study of the Hawkesbury–Nepean river system in NSW, Australia

The Hawkesbury–Nepean River (HNR) system in South-Eastern Australia is the main source of water supply for the Sydney Metropolitan area and is one of the more complex river systems due to the influence of urbanisation and other activities in the peri-urban landscape through which it flows. The long-term monitoring of river water quality is likely to suffer from data gaps due to funding cuts, changes in priority and related reasons. Nevertheless, we need to assess river health based on the available information. In this study, we demonstrated how the Factor Analysis (FA), Hierarchical Agglomerative Cluster Analysis (HACA) and Trend Analysis (TA) can be applied to evaluate long-term historic data sets. Six water quality parameters, viz., temperature, chlorophyll-a, dissolved oxygen, oxides of nitrogen, suspended solids and reactive silicates, measured at weekly intervals between 1985 and 2008 at 12 monitoring stations located along the 300 km length of the HNR system were evaluated to understand the human and natural influences on the river system in a peri-urban landscape. The application of FA extracted three latent factors which explained more than 70 % of the total variance of the data and related to the ‘bio-geographical’, ‘natural’ and ‘nutrient pollutant’ dimensions of the HNR system. The bio-geographical and nutrient pollution factors more likely related to the direct influence of changes and activities of peri-urban natures and accounted for approximately 50 % of variability in water quality. The application of HACA indicated two major clusters representing clean and polluted zones of the river. On the spatial scale, one cluster was represented by the upper and lower sections of the river (clean zone) and accounted for approximately 158 km of the river. The other cluster was represented by the middle section (polluted zone) with a length of approximately 98 km. Trend Analysis indicated how the point sources influence river water quality on spatio-temporal scales, taking into account the various effects of nutrient and other pollutant loads from sewerage effluents, agriculture and other point and non-point sources along the river and major tributaries of the HNR. Over the past 26 years, water temperature has significantly increased while suspended solids have significantly decreased (p?<?0.05). The analysis of water quality data through FA, HACA and TA helped to characterise the key sections and cluster the key water quality variables of the HNR system. The insights gained from this study have the potential to improve the effectiveness of river health-monitoring programs in terms of cost, time and effort, particularly in a peri-urban context.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

Factor analysis of H2S emission at a wastewater lift station: a case study

Odor and corrosion are common problems in domestic wastewater collection, transportation, pumping, and treatment processes. Based on the comparison among odorous compounds and onsite observations at a wastewater lift station, H₂S is more likely to have caused the odor and corrosion problems than methanethiol and other organic sulfides. The field data from both air and wastewater quality monitoring demonstrated that more H₂S (1 ppmv) was formed at a more negative redox potential, lower pH, and a higher temperature of wastewater. Since the lower detection level of most current analytical techniques is much greater than human’s smell and the reference concentration for adverse health effects, automatic monitoring on the threshold of H₂S formation provides a mechanism to trigger control techniques only when necessary for cost saving purposes. Based on Gibbs free energy, a more negative redox potential is required to form H₂S with an increase in pH and a decrease in temperature and SO ₄ ^2? concentration. However, pH effect is more significant than both temperature and SO ₄ ^2? concentration for H₂S formation. It is recommended that H₂S control techniques be started when the redox potential is below ?44 mV, the pH is lower than 5.6, and the temperature is higher than 11.5 °C to control H₂S below the reference concentration. Corroded concrete particles were examined by X-ray diffraction, which showed that the dominant crystal form was quartz.     

Sensitivity of isolated eggs of pond snails: a new method for toxicity assays and risk assessment

The concentration of heavy metals in the environment is normally low. We here address whether using the development of isolated pond snail Radix auricularia eggs would provide a more sensitive endpoint and whether the gelatinous matrix of the egg mass surrounding the eggs indeed protects the snail embryos. In the present study, artificial removal of the gelatinous matrix of egg masses greatly increased the sensitivity of developing eggs to a heavy metal (cadmium). The sensitivity of isolated eggs to cadmium was determined using several convenient endpoints, including mortality, hatching rate, and heart rate, with an acute toxicity test and a subchronic test. In the acute toxicity test, a 96-h LC₅₀ value of 58.26 μg/L cadmium was determined. In the subchronic toxicity test, sublethal effects in terms of a significant reduction in hatching rate could be found in the 25-μg/L treatment, and a significant decrease of heart rate was observed in both treatments (5 and 25 μg/L). The high sensitivity of isolated eggs indicates that such tests can be efficient for toxicity assays and risk assessment, although one needs to keep in mind that the ecologically relevant measure of toxicity will be how eggs are affected when they are still inside the egg mass.     

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF_G) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF_G techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF_G technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.     

Prediction of the solubility of zinc, copper, nickel, cadmium, and lead in metal-contaminated soils

Risk assessment of metal-contaminated soil depends on how precisely one can predict the solubility of metals in soils. Responses of plants and soil organisms to metal toxicity are explained by the variation in free metal ion activity in soil pore water. This study was undertaken to predict the free ion activity of Zn, Cu, Ni, Cd, and Pb in metal-contaminated soil as a function of pH, soil organic carbon, and extractable metal content. For this purpose, 21 surface soil samples (0–15 cm) were collected from agricultural lands of various locations receiving sewage sludge and industrial effluents for a long period. One soil sample was also collected from agricultural land which has been under intensive cropping and receiving irrigation through tube well water. Soil samples were varied widely in respect of physicochemical properties including metal content. Total Zn, Cu, Ni, Cd, and Pb in experimental soils were 2,015?±?3,373, 236?±?286, 103?±?192, 29.8?±?6.04, and 141?±?270 mg kg^?1, respectively. Free metal ion activity, viz., pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺, as estimated by the Baker soil test was 9.37?±?1.89, 13.1?±?1.96, 12.8?±?1.89, 11.9?±?2.00, and 11.6?±?1.52, respectively. Free metal ion activity was predicted by pH-dependent Freundlich equation (solubility model) as a function of pH, organic carbon, and extractable metal. Results indicate that solubility model as a function of pH, Walkley–Black carbon (WBC), and ethylenediaminetetraacetic acid (EDTA)-extractable metals could explain the variation in pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺ to the extent of 59, 56, 46, 52, and 51 %, respectively. Predictability of the solubility model based on pH, KMnO₄-oxidizable carbon, and diethylenetriaminepentaacetic acid-extractable or CaCl₂-extractable metal was inferior compared to that based on EDTA-extractable metals and WBC.     

Ozone facilitated dechlorination of 2-chloroethanol and impact of organic solvents and activated charcoal

The ozone-initiated oxidation of 2-chloroethanol was followed by monitoring the consumption of the halogenated organic substrate. Gas chromatographic analysis of the ozonated products showed an increase in conversion from about 1 % after 3 h of ozone treatment to about 22 % after 12 h. The yields of major ozonated products identified and quantified namely acetaldehyde, acetic acid, and chloride ion increased proportionately as a function of ozone treatment time. The percent conversion of 2-chloroethanol in the presence of acetic acid or ethyl acetate were found to be higher than those under solvent-free conditions with similar products obtained. The use of activated charcoal during the ozonolyis of 2-chloroethanol showed a significant increase in the percent conversion of the substrate compared to solvent free ozonation. Based on the experimental findings, the overall mechanism for the reaction between 2-chloroethanol and ozone is described.     

Arsenic and other trace elements in two catfish species from Paranaguá Estuarine Complex, Paraná, Brazil

Concentrations of arsenic and four additional trace elements (Cu, Cr, Ni, and Zn) were determined by inductively coupled plasma–optical emission spectrometry in the muscular tissue of the yellow catfish (Cathorops spixii) and the urutu catfish (Genidens genidens) from Paranaguá Estuarine Complex, Brazil (PEC). The PEC can be characterized by an environment of high ecological and economic importance in which preserved areas of rainforest and mangroves coexist with urban activities as ports and industries. The average concentrations (in milligram per kilogram dry weight) of elements in the muscle tissue of C. spixii are as follows: Zn (31), As (17), Cu (1.17), Cr (0.62), and Ni (0.28). Similar concentrations could be found in G. genidens with exception of As: Zn (36), As (4.78), Cu (1.14), Cr (0.51), and Ni (0.14). Fish from the geographic northern rural region (Guaraqueçaba–Benito) display higher As concentrations in the muscle tissues than fish found in the south-western (urban) part of the PEC. An international comparison of muscle tissue concentrations of trace elements in fish was made. Except for Ni in C. spixii, a tendency of decrease in element concentration with increasing size (age) of the fish could be observed. According to the National Health Surveillance Agency of Brazil, levels of Cr and As exceeded the permissible limits for seafood. An estimation of the provisional tolerable weekly intake of As was calculated with 109 % for C. spixii and with 29 % for G. genidens.