The effect of the corticosteroid hormone cortexolone on the metabolites produced during phenanthrene biotransformation in Cunninghamella elegans

The metabolism of phenanthrene and the mammalian corticosteroid hormone cortexolone by the fungus Cunninghamella elegans was studied. The amounts of the cortexolone transformation products, cortisol and epicortisol, were affected by the presence of phenanthrene. Approximately 40% more cortisol was produced by C. elegans in cultures with phenanthrene. In contrast, epicortisol formation decreased. C. elegans transformed phenanthrene to phenanthrene trans-1,2-,3,4-, and 9,10-dihydrodiols, phenols, diphenols (diols) and glucoside conjugates of 1-, 2-, 3-, 4-, and 9-phenanthrols. Almost all of the phenanthrene initially added was metabolized to ethyl acetate extractable metabolites. In the mycelia and culture medium extracts, phenanthrol glucosides represented 80% and 94% of the total metabolites, respectively. The major metabolite was the glucoside conjugate of 1-phenanthrol. The presence of cortexolone affected the biodegradation of phenanthrene by decreasing the amounts of phenanthrene metabolites compared to control cultures.     

The thief process for mercury removal from flue gas

The Thief Process is a cost-effective variation to activated carbon injection (ACI) for removal of mercury from flue gas. In this scheme, partially combusted coal from the furnace of a pulverized coal power generation plant is extracted by a lance and then re-injected into the ductwork downstream of the air preheater. Recent results on a 500-lb/h pilot-scale combustion facility show similar removals of mercury for both the Thief Process and ACI. The tests conducted to date at laboratory, bench, and pilot-scales demonstrate that the Thief sorbents exhibit capacities for mercury from flue gas streams that are comparable to those exhibited by commercially available activated carbons. A patent for the process was issued in February 2003. The Thief sorbents are cheaper than commercially-available activated carbons; exhibit excellent capacities for mercury; and the overall process holds great potential for reducing the cost of mercury removal from flue gas. The Thief Process was licensed to Mobotec USA, Inc. in May of 2005.     

“My garden is an expression of me”: Exploring householders' relationships with their gardens

Domestic gardens offer immense potential as sites for native biodiversity conservation. In urban areas they often comprise the largest land use, thus presenting an accessible and immediate way for urban dwellers to connect with nature and to support and enhance native biodiversity. This paper presents findings from a study of 55 domestic gardens undertaken in Dunedin, New Zealand, which explores householders' relationships with their gardens. The study data was derived from two interviews with householders, two photo exercises (approximately a year apart), together with a number of biological studies of the gardens. Gardens proved to be very important for our householders; for physical and mental health, as an expression of ownership and identity, as sites for social relationships, for connecting with nature and as site of domestic produce production. Householders' connections with nature were idiosyncratic, multifaceted and exhibited in ways that are more complex and varied than those usually considered by those working in the natural sciences and indeed biophilia supporters. We emphasize the importance of the people side of nature in seeking to build and support positive ecological change in the urban environment and the value of combining natural and social science approaches.     

Forecasting air quality time series using deep learning

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O₃) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O₃ exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours.

Implications: Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.     

Flexible foraging strategies in a diving seabird with high flight cost

How central-place foragers change search strategy in response to environmental conditions is poorly known. Foragers may vary the total distance travelled and how far they range from the central place in response to variation in the distribution of their prey. One potential reason as to why they would extend the length of their foraging trip and its distance from the colony would be to increase prey quality or quantity, despite incurring higher transit costs. To test this trade-off hypothesis in a species with high flight costs, we recorded the foraging behaviour of razorbills (Alca torca) using state-of-the-art techniques that log both individual horizontal (flight activity) and vertical (dive activity) movements. We show that the distance that razorbills travelled to foraging locations increased with sea-surface temperature, which may relate to higher prey quality or quantity. This relation is supported by an indirect index of patch quality, based on dive profiles, which also increased with travel distance from the colony. Furthermore, we show that this index was highest during the daily peak in diving activity, around midday. Taken together, these results suggest that razorbills are capable of adjusting their search strategies sensitively in response to proximate environmental cues.     

DATA REQUIREMENTS OF A WATER QUALITY MANAGEMENT PROGRAM1

ABSTRACT: Routine data collection currently consumes a large amount of the total resources devoted to water quality management. All too often data collection becomes an end in itself, with little thought given to the purpose of the data collection. The problem generally stems from a lack of proper routine surveillance system design and a failure on the part of the designers to initially identify the data needs of the management program. This study attempts, in a general way, to delineate the data needs of a water quality management program. This first required an identification of the activities involved in water quality management. The activities were then discussed in terms of the types of information needed to successfully complete their assigned tasks. Several detailed examples are given. The results of the discussion are summarized and several strategies are proposed to relate the results to surveillance system design.     

Investigation of a drum explosion of 30% aqueous KOCN

A 30% aqueous solution of KOCN placed in a 55 gallon HDPE drum at 50 °C began venting gas almost immediately. Although a vent was kept open the drum exploded within 1–2 h of being filled. This report reviews the steps taken after the accident to find its cause and to recommend safe operating conditions. The DIERS vent sizing package (VSP), used as a closed system adiabatic reactor, was able to simulate the incident under controlled laboratory conditions. Data were thereby collected for the first time on the runaway kinetics of the KOCN hydrolysis. Isothermal data were obtained in a highly sensitive microwatt heat flow calorimeter in an open system. It was demonstrated that even under isothermal conditions, the hydrolysis rates accelerated once underway, reaching maxima in 30 h at 25 °C and 6.7 h at 40 °C. There is satisfactory agreement of these results with other work on 0.5% KOCN solutions reported in earlier studies.     

Depletable externalities and pigouvian taxation

In their book Baumol and Oates [“The Theory of Environmental Policy: Externalities, Public Outlays, and the Quality of Life,” Prentice-Hall, Englewood Cliffs, N.J. (1975).] argue that whether an externality is depletable (private) or undepletable (public) is the key characteristic in determining the optimal pricing pattern. They argue that unlike the undepletable case a negative depletable externality requires not only a charge or tax on the generator of the externality but a payment or compensation to the victim in order to achieve Pareto optimality. It is shown that the key characteristic determining whether compensation of victims is required for efficiency is not the depletability of the externality but whether the victim can costlessly control or limit the amount of the damaging substance received.