Effect of mercuric chloride on terrestrial slug Semperula maculata and histopathology of reproductive organs: a comprehensive study

Since the last few decades, terrestrial diversity is found to be under stress due to the contamination by various chemicals and gases of aquatic and agricultural media. The bioaccumulation of these compounds at certain concentrations in different tissues produces histopathological changes leading to behavioral changes in target animals. This study focused on terrestrial molluscan slug, Semperula maculata, against lethal concentrations of mercury chloride (HgCl₂). Bioaccumulation of Hg was highest in ovotestis, while lowest in the molluscan penis. Histopathological changes were observed in the cellular arrangement of reproductive organs. Alterations in the penis and the dart gland included dilated unicellular, multicellular glands, and muscular dystrophy, dilated peripheral glandular cells, respectively; dilation being maximal in the prostate gland. Ovotestis showed depleted number of gametocytes. Vacoulized pre-vitellogenic oocytes with early vitellogenic oocytes were noted under light microscopy. Mercury produced toxicity on secretory functions and lowered the rate of reproduction in animals. Evidence indicates that Hg produced gamete degeneration, impacted reproductive capacity and survival of this species in the ecosystem.     

Larvicidal activity of neem and karanja oil cakes against mosquito vectors, Culex quinquefasciatus (say), Aedes aegypti (L.) and Anopheles stephensi (L.)

Larvicidal effect of neem (Azadirachta indica) and karanja (Pongamia glabra) oil cakes (individuals and combination) was studied against mosquito species. Both the oil cakes showed larvicidal activity against the mosquito species tested. The combination of neem and karanja oil cakes in equal proportion proved to have better effect than the individual treatments. The combination of the two oil cakes recorded an LC95 of 0.93, 0.54 and 0.77% against the mosquitoes, Culex quinquefasciatus, Aedes aegypti and Anopheles stephensi respectively The increase in efficacy of the combination treatment over individuals in all the mosquito larvae tested was found to range about 4 to 10 fold in terms of LC50 and 2 to 6 fold in terms of LC95.     

Regional data refine local predictions: modeling the distribution of plant species abundance on a portion of the central plains

Species distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the consequences of extrapolating locally collected data to regional landscapes. Similarly, the process of using regional data to inform local prediction for species distribution models has not been adequately evaluated. Using boosted regression trees, we examined errors associated with extrapolating models developed with locally collected abundance data to regional-scale spatial extents and associated with using regional data for predictions at a local extent for a native and non-native plant species across the northeastern central plains of Colorado. Our objectives were to compare model results and accuracy between those developed locally and extrapolated regionally, those developed regionally and extrapolated locally, and to evaluate extending species distribution modeling from predicting the probability of presence to predicting abundance. We developed models to predict the spatial distribution of plant species abundance using topographic, remotely sensed, land cover and soil taxonomic predictor variables. We compared model predicted mean and range abundance values to observed values between local and regional. We also evaluated model prediction performance based on Pearson's correlation coefficient. We show that: (1) extrapolating local models to regional extents may restrict predictions, (2) regional data can help refine and improve local predictions, and (3) boosted regression trees can be useful to model and predict plant species abundance. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network may improve our ability to monitor changes in local species abundance.     

The Influence of the Pacific Decadal Oscillation on Annual Floods in the Rivers of Western Canada

We analyzed annual peak flow series from 127 naturally flowing or naturalized streamflow gauges across western Canada to examine the impact of the Pacific Decadal Oscillation (PDO) on annual flood risk, which has been previously unexamined in detail. Using Spearman's rank correlation ρ and permutation tests on quantile‐quantile plots, we show that higher magnitude floods are more likely during the negative phase of the PDO than during the positive phase (shown at 38% of the stations by Spearman's rank correlations and at 51% of the stations according to the permutation tests). Flood frequency analysis (FFA) stratified according to PDO phase suggests that higher magnitude floods may also occur more frequently during the negative PDO phase than during the positive phase. Our results hold throughout much of this region, with the upper Fraser River Basin, the Columbia River Basin, and the North Saskatchewan River Basin particularly subject to this effect. Our results add to other researchers' work questioning the wholesale validity of the key assumption in FFA that the annual peak flow series at a site is independently and identically distributed. Hence, knowledge of large‐scale climate state should be considered prior to the design and construction of infrastructure.     

Degradation of phenol by Acinetobacter strain isolated from aerobic granules

Aerobic granules effectively degrade phenol at high concentrations from which no Acinetobacter species, that can effectively degrade high concentrations of phenol, have ever been isolated from aerobic granules. The phenol-fed aerobic granule studied was made by merging several smaller granules, each with a core of proteins and nucleic acids surrounded by an outer layer enriched with polysaccharides. In the present study, a strain of Acinetobacter sp. was isolated from the phenol-fed aerobic granules and was identified using DNA sequencing. The fluorescent in situ hybridisation combined with the confocal laser scanning microscope test revealed that the isolated Acinetobacter strain was mainly distributed in the core regime of granule. Batch tests revealed that the suspended Acinetobacter strain could effectively degrade phenol at an initial phenol concentration of up to 1000 mg l(-1) with no cell growth taking place at a phenol concentration of 1500 mg l(-1). The Haldane model describes the inhibitory kinetics of the phenol degradation data. The suspended Acinetobacter strain had a propensity to attach to the surface of sterilized polyurethane foam at a concentration of 12.3mg dry cells mg(-1) dry foam. The immobilized cells could not only degrade phenol at a rate similar to the suspended cells at phenol concentration of 500 mg l(-1), but also effectively degraded phenol at 1500 mg l(-1). The polysaccharides outer layer protected the Acinetobacter strain from phenol's toxicity; while the strain may also contribute to bioaggregation of the granule for its high propensity to attach to solid surface.     

Methane oxidation in compost-based landfill cover with vegetation during wet and dry conditions in the tropics

The effect of compost and vegetation on methane (CH4) oxidation was investigated during wet and dry conditions in a tropical region. A laboratory-scale experiment was conducted to examine the performance of nonvegetated and vegetated landfill cover systems in terms of CH4 oxidation efficiency. Two types of landfill cover materials (compost and sandy loam) and two species of tropical grasses (Sporobolus virginicus and Panicum repens) were studied for their effect on the CH4 oxidation reaction. It was found that the use of compost as cover material could maintain a high methane oxidation rate (MOR) of 12 mol CH4/m3 x day over a 250-day period. Leachate application showed a positive effect on promoting methanotrophic activity and increasing MOR. A high MOR of 12 mol CH4/m3 x day was achieved when using compost cover with P. repens during wet and dry seasons when leachate irrigation was practiced. In dry conditions, a lower MOR of 8 mol CH4/m3 x day was observed for 80 days.     

Feasibility of landfill gas as a liquefied natural gas fuel source for refuse trucks

The purpose of this paper is to develop a methodology to evaluate the feasibility of using landfill gas (LFG) as a liquefied natural gas (LNG) fuel source for heavy-duty refuse trucks operating on landfills. Using LFG as a vehicle fuel can make the landfills more self-sustaining, reduce their dependence on fossil fuels, and reduce emissions and greenhouse gases. Acrion Technologies Inc. in association with Mack Trucks Inc. developed a technology to generate LNG from LFG using the CO2 WASH process. A successful application of this process was performed at the Eco Complex in Burlington County, PA. During this application two LNG refuse trucks were operated for 600 hr each using LNG produced from gases from the landfill. The methodology developed in this paper can evaluate the feasibility of three LFG options: doing nothing, electricity generation, and producing LNG to fuel refuse trucks. The methodology involved the modeling of several components: LFG generation, energy recovery processes, fleet operations, economic feasibility, and decision-making. The economic feasibility considers factors such as capital, maintenance, operational, and fuel costs, emissions and tax benefits, and the sale of products such as surplus LNG and food-grade carbon dioxide (CO2). Texas was used as a case study. The 96 landfills in Texas were prioritized and 17 landfills were identified that showed potential for converting LFG to LNG for use as a refuse truck fuel. The methodology was applied to a pilot landfill in El Paso, TX. The analysis showed that converting LFG to LNG to fuel refuse trucks proved to be the most feasible option and that the methodology can be applied for any landfill that considers this option.     

Applying Fuzzy logic and the point count system to select landfill sites

The treatment of solid waste is currently one of the major environmental problems facing municipalities. Thousands of tonnes of waste are generated each day, requiring a large area for disposal purposes. It is difficult to find suitable areas for the construction of such sanitary landfills as numerous criteria must be met, and landfill sites vary considerably in terms of their sophistication. The selection criteria for landfill sites should be as simple as possible, and with this in mind, we have evaluated a large number of random cases for the suitability of the site for landfill purposes using the recently advocated fuzzy approach. Using the fuzzy classification, we have attempted to develop a simple classification which uses only certain point values for available attributes. A normalized average of such attributes based on the proposed classifier is further evaluated using additionally generated random data sets. The results appear to be encouraging and indicate that the present classifier can be used as a substitute for the fuzzy-based ranking of landfill sites.     

Short-term wind speed forecasting: Application of linear and non-linear time series models

This study forecasts day-ahead wind speed at 15 minute intervals at the site of a wind turbine located in Maharashtra, India. Wind speed exhibits non-stationarity, seasonality and time-varying volatility clustering. Univariate linear and non-linear time series techniques namely MSARIMA, MSARIMA-GARCH and MSARIMA-EGARCH have been employed for forecasting wind speed using data span ranging from 3 days to 15 days. Study suggests that mean absolute percentage error (MAPE) values first decrease with the increase in data span, reaches its minima and then start increasing. All models provide superior forecasting performances with 5 days data span. It is further evident that ARIMA-GARCH model generates lowest MAPE with 5 days data span. All these models provide superior forecasts with respect to current industry practices. This study establishes that employing various linear and non-linear time series techniques for forecasting day-ahead wind speed can benefit the industry in terms of better operational management of wind turbines and better integration of wind energy into the power system, which have huge financial implications for wind power generators in India.