Early warning sign attributes for the safety of drinking water treatment works

A proactive risk management strategy seeks to prevent accidents from taking place and maintain the safety of a system. In this context, the task of identifying and disseminating early warning signs and signals is among the most important. The problem is that warning signs that are present before an accident takes place are often being overlooked and not picked up or identified as warning signs. If these warning signs were responded to, then an accident may be averted. Accidents occuring in the critical domain of a drinking water treatments works can have serious implications for the public health of consumers of the water supplied. Realising and comprehending early warning signs is a major challenge for the domain of systems safety and especially in the domain of a water treatment works. The approaches that are typically used to enhance the realisation, comprehension and dissemination of early warning signs in the water treatment domain in Ireland mainly involves the creation of accident scenarios, the use of monitoring data and procedures for the dissemination of warnings. While all of these approaches are all useful to inform the mental or process models of possible accident scenarios, nevertheless, accidents are still occurring in this domain. Therefore, a new approach to enhance the comprehension of and effective dissemination of early warning signs is required in order to improve safety and proactive risk management strategies. The contributions of this thesis is the provision of a set of attributes associated with the early warning sign concept that provides meaningful data on the early warning signs and allows recipients to better comprehend them. The values of these attributes were customised for application in the water treatment domain. This research proves that early warning signs at a water treatment works received with information on their attributes are comprehended and communicated more effectively and efficiently than the usual pragmatic approach and thereby improves the safety and proactive risk management strategies.

Real time analysis of atmospheric single particles in urban environments using aerosol time of flight mass spectrometry

In order to determine the size-resolved chemical composition of single particles in real-time an ATOFMS was deployed at urban background sites in Paris and Barcelona during the MEGAPOLI and SAPUSS monitoring campaigns respectively. The particle types detected during MEGAPOLI included several carbonaceous species, metal-containing types and sea-salt. Elemental carbon particle types were highly abundant, with 86% due to fossil fuel combustion and 14% attributed to biomass burning. Furthermore, 79% of the EC was apportioned to local emissions and 21% to continental transport. The carbonaceous particle types were compared with quantitative measurements from other instruments, and while direct correlations using particle counts were poor, scaling of the ATOFMS counts greatly improved the relationship. During SAPUSS carbonaceous species, sea-salt, dust, vegetative debris and various metal-containing particle types were identified. Throughout the campaign the site was influenced by air masses altering the composition of particles detected. During North African air masses the city was heavily influenced by Saharan dust. A regional stagnation was also observed leading to a large increase in carbonaceous particle counts. While the ATOFMS provides a list of particle types present during the measurement campaigns, the data presented is not directly quantitative. The quantitative response of the ATOFMS to metals was examined by comparing the ion signals within particle mass spectra and to hourly mass concentrations of; Na, K, Ca, Ti, V, Cr, Mn, Fe, Zn and Pb. The ATOFMS was found to have varying correlations with these metals depending on sampling issues such as matrix effects. The strongest correlations were observed for Al, Fe, Zn, Mn and Pb. Overall the results of this work highlight the excellent ability of the ATOFMS in providing composition and mixing state information on atmospheric particles at high time resolution. However they also show its limitations in delivering quantitative information directly.