Analysis of trace elements and ions in ambient fine particulate matter at three elementary schools in Ohio

The results from a chemical characterization study of fine particulate matter (PM2.5) measured at three elementary schools in Central and Southeast Ohio is presented here. PM2.5 aerosol samples were collected from outdoor monitors and indoor samplers at each monitoring location during the period of February 1, 1999, through August 31, 2000. The locations included a rural elementary school in Athens, OH, and two urban schools within Columbus, OH. The trace metal and ionic concentrations in the collected samples were analyzed using an X-ray fluorescence spectrophotometer and ion chromatography unit, respectively. Sulfate ion was found to be the largest component present in the samples at all three of the sites. Other abundant components included nitrate, chloride, ammonium, and sodium ions, as well as calcium, silicon, and iron. The average PM2.5 concentrations showed similar temporal variations among the three sites within the study region. PM2.5 and its major component, sulfate ion, showed strong seasonal variations with maximum concentrations observed during the summer at all three of the sites. The indoor environment was found to be more contaminated during the spring months (March through May) at New Albany (a suburb of Columbus, OH) and East Athens (rural Ohio area). Potential source contribution function analysis showed that particulate matter levels at the monitoring sites were affected by transport from adjoining urban areas and industrial complexes located along the Ohio River Valley. A preliminary outdoor source apportionment using the principal component analysis (PCA) technique was performed. The results from the PCA suggest that the study region was primarily impacted by industrial, fossil fuel combustion, and geological sources. The 2002 emissions inventory data for PM2.5 compiled by Ohio Environmental Protection Agency also showed impacts of similar source types, and this was used to validate the PCA analysis.     

Assessment of groundwater quality: a fusion of geochemical and geophysical information via Bayesian neural networks

Deplorable quality of groundwater arising from saltwater intrusion, natural leaching and anthropogenic activities is one of the major concerns for the society. Assessment of groundwater quality is, therefore, a primary objective of scientific research. Here, we propose an artificial neural network-based method set in a Bayesian neural network (BNN) framework and employ it to assess groundwater quality. The approach is based on analyzing 36 water samples and inverting up to 85 Schlumberger vertical electrical sounding data. We constructed a priori model by suitably parameterizing geochemical and geophysical data collected from the western part of India. The posterior model (post-inversion) was estimated using the BNN learning procedure and global hybrid Monte Carlo/Markov Chain Monte Carlo optimization scheme. By suitable parameterization of geochemical and geophysical parameters, we simulated 1,500 training samples, out of which 50 % samples were used for training and remaining 50 % were used for validation and testing. We show that the trained model is able to classify validation and test samples with 85 % and 80 % accuracy respectively. Based on cross-correlation analysis and Gibb’s diagram of geochemical attributes, the groundwater qualities of the study area were classified into following three categories: “Very good”, “Good”, and “Unsuitable”. The BNN model-based results suggest that groundwater quality falls mostly in the range of “Good” to “Very good” except for some places near the Arabian Sea. The new modeling results powered by uncertainty and statistical analyses would provide useful constrain, which could be utilized in monitoring and assessment of the groundwater quality.     

Comparison of microbial indicators under two water regimes in a soil amended with combined paper mill sludge and decomposed cow manure

An incubation study was conducted under laboratory conditions to compare the effects of soil amendment of combined paper mill sludge (PS) and decomposed cow manure (DCM) on selected microbial indicators. A lateritic soil (Typic Haplustalf) was amended with 0 (control), 20 or 80tha(-1) (wet weight) of PS or DCM. The amended soils were then adjusted to 60% water holding capacity (WHC) or submerged conditions, and incubated at 27 degrees C in dark for up to 120days (d). The microbial biomass C (MBC), the basal soil respiration and the enzyme activities of the beta-glucosidase, acid phosphatase and sulphatase were analyzed at day 15, 30, 45, 60 and 120. Compared to the unamended soil (control), the MBC, the basal soil respiration and the enzyme activities increased with the rate of PS and DCM. At similar rate, the DCM treatment increased significantly the MBC, the soil respiration and the enzyme activities compared to the PS treatment. Also, the water regimes affected the microbial activities. At 60% WHC, the MBC and soil respiration increased during the first 30d and decreased thereafter. The enzyme activities showed similar trends, where they increased for the first 60d, and decreased thereafter. In contrast, under submerged condition, the MBC and enzymes activities declined during 120d, whereas the soil respiration increased. Compared to the control, the used of PS and DCM had no negative impact of the soil microbial parameters, even at the highest application rate. Long-term field experiments are required to confirm these laboratory results.     

Fetal spina bifida: What we tell the parents

Worldwide, about 150 000 infants are born with spina bifida yearly, making this condition one of the most common fetal central nervous system anomalies compatible with life. Over the last decade, major changes have been introduced in the prenatal diagnosis and management of spina bifida. In this review, we provide a brief summary of the current management of fetal spina bifida and present essential information that should be provided to expecting parents when their fetus has been diagnosed with spina bifida. This information is focused around common parental questions, as encountered in our typical clinical practice, to facilitate knowledge translation.     

Comparing PFAS to other groundwater contaminants: Implications for remediation

Established groundwater contaminants such as chlorinated solvents and hydrocarbons have impacted groundwater at hundreds of thousands of sites around the United States and have been responsible for multibillion dollar remediation expenditures. An important question is whether groundwater remediation for the emerging contaminant class comprised of per‐ and polyfluoroalkyl substances (PFAS) will be a smaller, similar, or a larger‐scale problem than the established groundwater contaminants. A two‐pronged approach was used to evaluate this question in this paper. First, nine quantitative scale‐of‐remediation metrics were used to compare PFAS to four established contaminants: chlorinated solvents, benzene, 1,4‐dioxane, and methyl tert‐butyl ether. These metrics reflected the prevalence of the contaminants in the U.S., attenuation potential, remediation difficulty, and research intensity. Second, several key challenges identified with PFAS remediation were evaluated to see similar situations (qualitative analogs) that have been addressed by the remediation field in the past. The results of the analysis show that four out of nine of the evaluated quantitative metrics (production, number of potential sites, detection frequency, required destruction/removal efficiency) indicate that the scale of PFAS groundwater remediation may be smaller compared to the current scale of remediation for conventional groundwater contaminants. One attenuation metric, median plume length, suggests that overall PFAS remediation could pose a greater challenge compared to hydrocarbon sites, but only slightly larger than chlorinated volatile organic compounds sites. The second attenuation metric, hydrophobic sorption, was not definitive regarding the potential scale of PFAS remediation. The final three metrics (regulatory criteria, in‐situ remediation capability, and research intensity) all indicate that PFAS remediation might end up being a larger scale problem than the established contaminants. An assessment of the evolution of groundwater remediation capabilities for established contaminants identified five qualitative analogs for key PFAS groundwater remediation issues: (a) low‐level detection analytical capabilities; (b) methods to assess the risk of complex chemical mixtures; (c) nonaqueous phase dissolution as an analog for partitioning, precursors, and back diffusion at PFAS sites; (d) predictions of long plume lengths for emerging contaminants; and (e) monitored natural attenuation protocols for other non‐degrading groundwater contaminants. Overall the evaluation of these five analogs provided some comfort that, while remediating the potential universe of PFAS sites will be extremely challenging, the groundwater community has relevant past experience that may prove useful. The quantitative metrics and the qualitative analogs suggest a different combination of remediation approaches may be needed to deal with PFAS sites and may include source control, natural attenuation, in‐situ sequestration, containment, and point‐of‐use treatment. However, as with many chlorinated solvent sites, while complete restoration of PFAS sites may be uncommon, it should be possible to prevent excessive exposure of PFAS to human and ecological receptors.