Suchergebnisse

Abstract. Seismic risk analysis is necessary to mitigate the potential losses resulting from future earthquakes and supplement scientific risk management. In order to assist systematic evaluation and management of risk, it is indispensable to interpret risk in terms of social and economic
consequences due to hazardous events like earthquakes. There is an
interrelationship between hazards, physical risk, and the social
characteristics of populations. Therefore, based on the existing studies
focusing on each of these aspects, this paper presents the integrated
seismic risk assessment along the subdivisional administrative units of
Nepal using 2011 census data. The administrative unit "provinces" are
subdivided into districts and each district into municipalities and village development committees (VDCs). The districts, municipalities, and VDCs were considered as our study units. In this paper, the physical or seismic risk was evaluated from the exposure model, hazard curves, and the vulnerability model of the country, whereas the social vulnerability was assessed using social vulnerability index (SoVI) methods. To formulate the physical risk, the assets used were five types of buildings under the exposure model. This model was combined with the physical vulnerability functions of the building and the hazard curves of the country. The result of the physical risk has been presented as annual average loss (AAL). Similarly, among 92 social vulnerability variables, 54 variables were reduced to 7 weighted parameters using principal component analysis (PCA). The scores of a total of 45 parameters were used to evaluate the SoVI index, which was further combined with the physical risk to evaluate integrated risk. The results showed that populated cities like Kathmandu, Hetauda, and Janakpur have a highly integrated risk index. Similarly, the Terai region bordering its neighbor India and some parts of the central hilly region are highly vulnerable, while most parts of the mountainous region in the central and eastern regions are the least vulnerable. The results from the present study can be utilized as a part of a comprehensive risk management framework at the district level to recuperate and recover from earthquakes.

Abstract
Assessment of nanoparticle exposure is not an established routine among occupational hygienists. One of the discussions is about methods of quantification, if we should use number concentration, surface concentration or mass concentration for assessment, this is however also influenced by the access to proper measurement equipment. In this paper we discuss five available methods for exposure assessment. One is the Discmini from Testo, which has the advantage that it could be used for personal measurements, but on the other hand has some limitation according to measurement principles; used for Chimney sweepers. Another is the Nanoscan SMPS from TSI, which not is portable for personal measurements, but still is battery operated and could be moved around at a workplace, Nanoscan SMPS measure particle size distribution; this instrument have been used for logbook measurements among Ferrosilicon alloy workers. Number three is the Scanning Mobility Particle Sizer and the Fast mobility particle sizers from TSI , which is large, power demanding and only useable for stationary measurements, but on the other hand highly demandable for quantification. Number four is the Fast Mobility Particle Sizer, also from TSI, with the advantage of 1 second measurements, used in Ferroalloy industry and among Fire fighters. The fifth is the ELPI instrument from Dekati, which enable collection of samples for subsequent analysis on electron microscope, used in Ferroalloy industry. In this poster we compare type of results and discuss the advantages and disadvantages with the different methods and how useful they are for exposure assessment.

POSSM, the PCB On‐Site Spill Model, is a contaminant transport model developed to predict environmental concentrations associated with a chemical spill. The model predicts daily changes in chemical concentrations on a spill site (e.g., in soil and on vegetation) and losses of chemical due to volatilization, surface runoff/soil erosion, and leaching to groundwater. Spill areas consisting of soil/vegetation and/or an impervious surface (e.g., asphalt and concrete) can be analyzed, as can different spill cleanup practices. POSSM is used to analyze exposure levels associated with a hypothetical capacitor spill. While the model was developed for PCB spills, it is generally applicable to a number of organic compounds.