Magette, W. L.

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Magette, W. L.
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Magette, W. L.

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  • Publication
    Characterization of household and commercial BMW generation according to socio-economic and other factors for the Dublin Region
    (Widner University, 2007-03-18)
    Purcell, M. 
    ;
    Magette, W. L. 
    Both planning and design of integrated municipal solid waste management systems require accurate prediction of solid waste generation. This research predicted the quantity and distribution of Biodegradable Municipal Waste (BMW) generation for the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A Geographical Information System (GIS) „model‟ of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research was used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region. The GIS facilitates the visual and spatial distribution of BMW to be assessed within the region. BMW generation was predicted within a diverse „landscape‟ of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals etc). By changing the input data, this estimation tool can be adapted for use in other Irish cities.
      199
  • Publication
    Targeted intervention strategies to optimise diversion of BMW in the Dublin, Ireland region
    (Elsevier, 2011-09)
    Purcell, M. 
    ;
    Magette, W. L. 
    Urgent transformation is required in Ireland to divert biodegradable municipal waste (BMW) from landfill and prevent increases in overall waste generation. When BMW is optimally managed, it becomes a resource with value instead of an unwanted by-product requiring disposal. An analysis of survey responses from commercial and residential sectors for the Dublin region in previous research by the authors proved that attitudes towards and behaviour regarding municipal solid waste is spatially variable. This finding indicates that targeted intervention strategies designed for specific geographic areas should lead to improved diversion rates of BMW from landfill, a requirement of the Landfill Directive 1999/31/EC. In the research described in this paper, survey responses and GIS model predictions from previous research were the basis for goal setting, after which logic modelling and behavioural research were employed to develop site-specific waste management intervention strategies. The main strategies devised include (a) roll out of the Brown Bin (Organics) Collection and Community Workshops in Dún Laoghaire Rathdown, (b) initiation of a Community Composting Project in Dublin City (c) implementation of a Waste Promotion and Motivation Scheme in South Dublin (d) development and distribution of a Waste Booklet to promote waste reduction activities in Fingal (e) region wide distribution of a Waste Booklet to the commercial sector and (f) Greening Irish Pubs Initiative. Each of these strategies was devised after interviews with both the residential and commercial sectors to help make optimal waste management the norm for both sectors. Strategy (b), (e) and (f) are detailed in this paper. By integrating a human element into accepted waste management approaches, these strategies will make optimal waste behaviour easier to achieve. Ultimately this will help divert waste from landfill and improve waste management practice as a whole for the region. This method of devising targeted intervention strategies can be adapted for many other regions.
      731Scopus© Citations 5
  • Publication
    Prediction of household and commercial BMW generation according to socio-economic and other factors for the Dublin region
    (Elsevier, 2009-04)
    Purcell, M. 
    ;
    Magette, W. L. 
    Both planning and design of integrated municipal solid waste management systems require accurate prediction of waste generation. This research predicted the quantity and distribution of biodegradable municipal waste (BMW) generation within a diverse 'landscape' of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals, etc.) in the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A geographical information system (GIS) 'model' of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research and data from the scientific literature were used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region, which can aid waste planning and policy decisions. This technique will also aid the design of future waste management strategies as a function of demographic changes and development. By changing the input data, this estimation tool can be adapted for use in other locations.
      4105Scopus© Citations 71