Communication ecology of webbing clothes moth: 4. Identification of male- and female-produced pheromones

Summary. We investigated the hypothesis that aggregation signals produced by male webbing clothes moths (WCM), Tineola bisselliella (Hum.) (Lepidoptera: Tineidae), and close-range male attractant signals produced by females have a pheromonal basis, at least in part. Gas chromatographic-electroantennographic detection (GC-EAD) and GC-mass spectrometric analyses of bioactive methanolic extracts of male WCM disclosed three candidate pheromone components: hexadecanoic acid methyl ester (16:Ester), (Z)-9-hexadecenoic acid methyl ester (Z9—16:Ester), and octadecanoic acid methyl ester (18:Ester). In bioassay experiments in a large Plexiglas™ arena, a blend of synthetic 16:Ester plus Z9—16:Ester was attractive to male and virgin (but not mated) female WCM; the 18:Ester was inactive. GC-EAD analyses of pheromone gland extracts from female WCM revealed (E,Z)-2,13-octadecadienal (E2Z13—18:Ald) and (E,Z)-2,13-octadecadienol (E2Z13—18:OH) as candidate sex pheromone components. In arena bioassay experiments, 1—5 female equivalents of synthetic E2Z13—18:Ald (0.2 ng) and E2Z13—18:OH (0.1 ng) were more attractive to male WCM than were two virgin female WCM. We anticipate that the combination of aggregation and sex pheromones, male-produced sonic aggregation signals, and habitat-derived semiochemicals will be highly effective in attracting male and female WCM to commercial traps. Received 12 January 2001; accepted 8 June 2001.     

Dynamic Games in the Economics and Management of Pollution

The paper provides a survey of the literature which utilizes dynamic state-space games to formulate and analyze intertemporal, many decision-maker problems in the economics and management of pollution.     

A Bayesian network analysis of workplace accidents caused by falls from a height

This article analyses, using Bayesian networks, the circumstances surrounding workplace tasks performed using auxiliary equipment (ladders, scaffolding, etc.) that may result in falls. The information source was a survey of employees working at a height. We were able to determine the usefulness of this approach – innovative in the accident research field – in identifying the causes that have the greatest bearing on accidents involving auxiliary equipment: in these cases, the adoption of incorrect postures during work and a worker’s inadequate knowledge of safety regulations. Likewise, the duration of tasks was also associated with both these variables, and therefore, with the accident rate. Bayesian networks also enable dependency relationships to be established between the different causes of accidents. This information – which is not usually furnished by conventional statistical methods applied in the field of labour risk prevention – allow a causality model to be defined for workplace accidents in a more realistic way. With this statistic tool, the expert is also provided with useful information that can be input to a management model for labour risk prevention.     

An experimental study of the influence of biofuel origin on particle-associated PAH emissions

The chemical speciation of the 16 polycyclic aromatic hydrocarbons associated to the particulate matter of conventional diesel fuel, rapeseed methyl esters, waste cooking oil methyl esters, waste cooking oil ethyl esters and their conventional fuel blends has been carried out. The speciation of these individual compounds was made by a combination of thermal extraction, solid phase micro-extraction and GC/MS analysis. This PAH speciation method was applied to a real samples obtained from a diesel engine under two different operating modes, urban and extraurban modes. The purpose of this work was to study the relationship between the amount, type and carcinogenic potency of polycyclic aromatic hydrocarbons in engine emissions and the multi-component biodiesel fuel composition.