Prioritisation of citizen‐centric information for disaster response

In the aftermath of a disaster event, and in the absence of trained professionals, many responsibilities are assumed by uninjured citizens who are willing and able to help, such as care of the injured or search and rescue. These citizens are constrained by communications and logistics problems but are less equipped to deal with them as most often they are cut off from any coordinated assistance. The method proposed in this study would increase the survivability of those injured or trapped by a disaster event by providing a facility to allow citizens to coordinate and share information among themselves. This is facilitated by the proposed deployment and the autonomous management of an ad hoc infrastructure that liaises directly with survivors without central control. Furthermore, as energy concerns present critical constraints to these networks, this research proposes a system of categorising information elements within the network to ensure efficient information exchange.     

Determination of the sources of toxic elements in environmental particles using microscopic and statistical analysis techniques

Samples of urban dust were physically fractionated into subsamples having unique size, density, ferromagnetism, and elemental compositional characteristics. The high density fractions containing the majority of each of the potentially toxic metals (Pb, Cd, Zn, Cr, Co, Mn) were subjected to X-ray microanalysis and to bulk analysis using instrumental neutron activation. Microanalysis was used to classify individual particles with respect to primary sources. The bulk analytical results were subjected to factor analysis to delineate the underlying factors (particle sources) responsible for the compositional variation in the subsamples. The advantages of the combined use of microanalytical and statistical techniques for source definition are described. X-ray microanalysis is used to substantiate the attribution of a given factor to a suspected particle source, to aid in the determination of the number of factors (sources) present, and to assess the extent to which a given factor represents a unique source of particles. Bulk analysis/factor analysis promotes the most effective use of X-ray microanalysis to characterize major particle types, and provides data on some toxic trace metals (e.g., Cd) that are not detectable using X-ray microanalysis. Target transformation factor analysis also is more useful in the quantitative determination of the relative mass contributions of major sources to the total dust sample.     

Policy planning under uncertainty: efficient starting populations for simulation-optimization methods applied to municipal solid waste management

Evolutionary simulation-optimization (ESO) techniques can be adapted to model a wide variety of problem types in which system components are stochastic. Grey programming (GP) methods have been previously applied to numerous environmental planning problems containing uncertain information. In this paper, ESO is combined with GP for policy planning to create a hybrid solution approach named GESO. It can be shown that multiple policy alternatives meeting required system criteria, or modelling-to-generate-alternatives (MGA), can be quickly and efficiently created by applying GESO to this case data. The efficacy of GESO is illustrated using a municipal solid waste management case taken from the regional municipality of Hamilton-Wentworth in the Province of Ontario, Canada. The MGA capability of GESO is especially meaningful for large-scale real-world planning problems and the practicality of this procedure can easily be extended from MSW systems to many other planning applications containing significant sources of uncertainty.