Changes in tissue cholesterol and serum cortisol level during four reproductive phases of the male freshwater fish, Notopterus notopterus

The tissue cholesterol and serum cortisol changes during four reproductive phases has been studied in the freshwater fish Notopterus notopterus of male sex during four phases, preparatory (January - March), prespawning (April - May), spawning (August - September) and post spawning (November - December). The cholesterol content of the testis and liver increased during preparatory phase and maximum content of cholesterol was during spawning phase. The serum cortisol estimated by radioimmunoassay (RIA) technique which indicated that the level of the hormone was high during pre-spawning and spawning phases compared to other two phases. The increase in cholesterol during preparatory and spawning phases may be because of increase in cortisol synthesis needed for testicular growth and spermetogenesis during these phases. The gonadosomatic index (GSI) also increased during these phases.     

Statistical analysis of the physico-chemical data on the coastal waters of Cochin

Measurements of temperature, salinity, dissolved oxygen, nitrogen as ammonia, nitrate and nitrite, and phosphate along with chlorophyll were carried out at three stations on the coastal waters of Cochin, south west India, at two-levels of the water column over a period of five years. The data set has been factorised using principal component analysis (PCA) for extracting linear relationships existing among a set of variables. A graphical display of the scores generated from the PCA was done by means of boxplots and biplots, which helped in the interpretation of the data. The major factors conditioning the system are related to the input of fresh water from the estuary of the Periyar river and the high organic load of the bottom sediment in the coastal area which results in a reducing environment, as reflected in the parameters of dissolved oxygen, ammoniacal-nitrogen and nitrite-nitrogen. Another factor which contributes to the variation in the system is related to the unloading activity in the port area. The present approach presents a logical way to interpret the complex data of the physico-chemical measurements.     

Emissions of organic compounds and trace metals in fine particulate matter from motor vehicles: a tunnel study in Houston, Texas

Fine particulate matter (PM) samples collected in a highway tunnel in Houston, TX, were analyzed to quantify the concentrations of 14 n-alkanes, 12 polycyclic aromatic hydrocarbons, and nine petroleum biomarkers, as well as 21 metals, with the ultimate aim of identifying appropriate tracers for diesel engines. First, an exploratory multivariate dimensionality reduction technique called principal component analysis (PCA) was employed to identify all potential candidates for tracers. Next, emission indices were calculated to interpret PCA results physically. Emission indices of n-heneicosane, n-docosane, n-tricosane, n-tetracosane, n-pentacosane, fluoranthene, and pyrene were correlated highly and increased strongly with percentage carbon present in the tunnel emanating from diesel vehicles. This suggests that these organic compounds are useful molecular markers to separate emissions from diesel and gasoline engines. Additionally, the results are the first quantification of the metal composition of PM with aerodynamic diameters smaller than 2.5 microm (PM2.5) emissions from mobile sources in Houston. PCA of trace metal concentrations followed by emission index calculations revealed that barium in fine airborne particles can be linked quantitatively to diesel engine emissions, demonstrating its role as an elemental tracer for heavy-duty trucks.     

Role of cortisol on condition factor in the female freshwater fish, Notopterus notopterus during four reproductive phases

The condition of the female fish, Notopterus notopterus was studied during four phases of the reproductive cycle in control and after cortisol hormone treatment. The condition of the fish including condition factor (K) and somatic condition factor (Ks) was determined based on weight of the body, length of the fish and gonad weight. In control fish the condition of the fish improve during prespawning phase compared to other phases. The hormone cortisol level estimated by radioimmunoassay (RIA) technique was found to be increased in preparatory and decreased during prespawning phase, may be because of the hormone involvement in metabolic activity, vitellogenesis. In cortisol treatment, the condition of the fish decrease during prespawning phase, compared to other phase may be because of extra expenditure of energy for progressing reproductive activity such as vitellogenesis.     

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.     

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.     

Monitoring of Daily Integrated Exposure of Outdoor Workers to Respirable Particulate Matter in an Urban Region of India

It is more and more recognised that an estimation of the exposure of the population to air pollutants is more relevant than the ambient air quality, since it gives a better indication of health risk. Outdoor workers in an urban region are generally of low income status and are exposed to higher levels of both indoor and outdoor air pollution. Hence respondents from this population subgroup have been selected for this study. Outdoor workers are divided into two categories, viz. traffic constables and casual outdoor workers like watchmen, roadside shopkeepers etc. Most of the respondents are from the lower income group. Each respondent is monitored for a continuous 48-hour period. The sampling frequency is once a week.The study region is situated in the north-west part of the Greater Mumbai Municipal Corporation. It can be classified as industrial cum residential area. The daily integrated exposure of the outdoor workers consists of two major micro-environments, viz. occupational and indoor residential.A personal air sampler was used along with a cyclone to measure levels of Respirable Particulate Matter (RPM). The cyclone has a 50% removal efficiency for particle diameter of 5 m. Paired samples of PM10 (ambient) and RPM (personal) were collected to establish the correlation between them. The average 24-hour integrated exposure to RPM was 322 g/m3 and exceeded the corresponding PM10 level observed at the nearest Ambient Air Quality Monitoring Station by a factor of 2.25. The 90% confidence interval for this exposure is 283–368 g/m3. This study clearly demonstrates that the daily integrated exposure and therefore the health risk of outdoor workers in an urban area is significantly more serious than that indicated by ambient air quality data.