Exposure and inhalation risk assessment in an aluminium cast-house

To date the exposure, absorption and respiratory health effects of cast-house workers have not been described since most studies performed in the aluminium industry are focused on exposure and health effects of potroom personnel. In the present study, we assessed the external exposure and the absorbed dose of metals in personnel from the aluminium cast house. This was combined with an evaluation of respiratory complaints and the lung function of the personnel. 30 workers from an aluminium casting plant participated and 17 individuals of the packaging and distribution departments were selected as controls. The exposure was assessed by the quantification of total inhalable fume with metal fraction and by the determination of urinary aluminium, chromium, beryllium, manganese and lead concentration. Carbon monoxide (CO), carbon dioxide (CO2), aldehydes and polyaromatic hydrocarbons and man-made mineral fibres concentration were assessed as well. In order to evaluate their respiratory status each participant filled out a questionnaire and their lung function was tested by forced spirometry. Total inhalable fume exposure was maximum 4.37 mg m(-3). Exposure to the combustion gases, man-made mineral fibres and metal fume was well below the exposure limits. Beryllium could not be detected in the urine. The values of aluminium, manganese and lead in the urine were all under the respective reference value. One individual had a urinary chromium excretion above the ACGIH defined biological exposure index (BEI) of 30 microg g(-1) creatinine. There was no significant difference in any of the categories of the respiratory questionnaire and in the results of the spirometry between cast house personnel and referents (Chi-square, all p > 0.05). Exposure in cast houses seem to be acceptable under these conditions. However, peak exposure to fumes cannot be excluded and the potential risk of chromium and beryllium exposure due to the recycling of aluminium requires further attention.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

EPA's monitoring program at Love Canal 1980

Summary As stated at the beginning of this paper conclusions reached thus far cannot be discussed in this paper. However, a great deal of information is available for examination.EPA displayed its ability to coordinate widely separated laboratories, both Federal and private, into a smooth working team in a very short period of time. A very comprehensive study plan was also developed and implemented quickly. EPA was fortunate to have already had GCA under contract when the emergency arose. In no small part the success of the field effort was due to the managerial and technical abilities of the GCA team.Within a period of 6 weeks a plan was developed, a prime contractor retained, subcontractors hired, and field activities begun. Within a period of 3 months in excess of 8600 field samples were collected and over 12,000 field and QC samples were analyzed. During this same period 2 major data systems were developed, debugged, and placed into operation.In short this EPA project was probably the most comprehensive multimedia field project ever attempted by EPA and certainly the data is being subjected to the most strenuous quality control measures ever imposed by this Agency. The entire program is presently under peer review and the results are being prepared for publication by EPA Headquarters.Note. Originally intended to be published as part of the special issue on Exposure Monitoring: An International Workshop (Las Vegas, Nevada, October 19–22, 1981).     

The Variability of Estimates of Variance, and Its Effect on Power Analysis in Monitoring Design

Power analysis can be a valuable aid in the design of monitoringprograms. It requires an estimate of variance, which may come from a pilot study or an existing study in a similar habitat. For marine benthic infauna, natural variation in abundances canbe considerable, raising the question of reliability of varianceestimates. We used two existing monitoring programs to generatemultiple estimates of variance. These estimates were found to differ from nominated best estimates by 50% or more in 43% of cases, in turn leading to under or over-estimation of samplesize in the design of a notional monitoring program. The twostudies, from the same general area, using the same samplingmethods and spanning a similar time scale, gave estimatesvarying by more than an order of magnitude for 25% of taxa.We suggest that pilot studies for ecological monitoring programsof marine infauna should include at least two sampling times.     

Aerosol Scavenging: Model Application and Sensitivity Analysis in the Indian Context

Sulfate aerosols have been found to bethe major contributors to precipitation acidity. Thus,in view of the long-term ecological repercussions theyhave on aquatic ecosystems and their acidity-potential,the present analysis focuses on a case study applicationof the layer-averaged aerosol-scavenging model (Okita et al., 1996) for predicting values of the wet scavengingcoefficient and sulfate concentrations in precipitationsamples on the basis of the information available forsome selected Indian cities. Through sensitivityanalysis (Pandey et al., 1997) the scavengingcoefficient has been found to be very strongly dependenton precipitation intensity. Comparison of modelpredictions has been done with the measured values forDelhi, Mumbai, Calcutta and Chennai in India.