Abstract of PhD Thesis

A New Approach to Waste Management Systems for Biodegradable Municipal Waste (BMW)

Mary Purcell, University College Dublin (2009)

As generators of solid waste, individuals and institutions (commercial establishments, etc.) are at the core of integrated waste management. Attitudes of waste generators towards waste management have socio-economic links (MORI, 2002). Yet, these relationships are largely ignored in the design of current waste management programmes in the interest of providing a uniform service within a given service area.

The novel / innovative aspect of this research lies in the premise that socio-economic factors must be integrated into both the strategic design (one or more years planning horizon) and tactical (day-to-day) management of solid waste. With a focus on biodegradable municipal waste (BMW), the first hypothesis of this research postulates that BMW generation is spatially variable within a diverse ‘landscape’ of residential areas and commercial establishments. The second hypothesis of this research is that attitudes about the management of BMW are also spatially variable. Both hypotheses were found to be true, so this research reasons that management of BMW can be better accomplished by targeting site-specific intervention strategies than by using the "one size fits all" approach in current design practice.

This research was conducted in the greater Dublin (Ireland) area, which is comprised of four independent local governments. A novel geographical information system (GIS) ‘estimation model’ to predict BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were used as model inputs on an electoral district basis. Existing data from scientific literature were used to assign BMW generation rates. These data were combined to give overall BMW estimates for each electoral district in the region, both on a household size basis and a social-class basis for residential waste and on a commercial basis, and predictions were validated against data in the EPA National Waste Database. The household prediction technique gave a more accurate overall estimate of household waste generation than did the social class technique. Both techniques produced estimates that differed from the reported local authority data; the closest estimate of reported data was a 16% over-prediction, and was produced using the household size technique for 2002. However, given that local authority reported figures for the region are below the national average, with some of the waste generated from apartment complexes being reported as commercial waste, predictions arising from this research are believed to be closer to actual waste generation than a comparison to reported data would suggest. Predictions of commercial waste generation were within 5% of the reported figures for the region. Estimates of total waste generation for the 322 electoral districts had a mean of either 34.2 t wk-1 or 40.8 t wk-1 with a standard deviation of 29.5 t or 28.4 t, depending on whether the household basis or social class basis, respectively, was used to predict household waste generation. These statistical measures confirmed the first hypothesis of the research.

For a select number of representative electoral districts in the study area, residents and businesses were surveyed to determine their attitudes towards waste management in general, and BMW management in particular. A total of 921 survey responses were collected. Door-to-door interviews produced 688 responses in the residential sector, which were supplemented by 162 responses to a web-based survey. A total of 71 individual businesses (out of 100 asked) agreed to being surveyed. Statistical analyses of the survey responses showed that the local authority in which respondents resided significantly influenced most responses (including waste service satisfaction and backyard composting activity). Many responses (including waste service satisfaction, waste management influences) were also significantly related to the respondents’ personal characteristics (e.g., education level, type of accommodation, age etc.). These statistical results proved the second major hypothesis of the research and, importantly, demonstrated that waste management initiatives designed for one area of the region (or, indeed, for the region as a whole) could ignore the needs of other areas in the region. The survey responses thus indicated that targeted intervention strategies designed for specific geographic areas would lead to improved diversion rates of BMW from landfill, a requirement of the Landfill Directive 1999/31/EC.

Using survey responses and GIS model predictions as a basis for goal setting, logic modelling and behavioural research were then used to develop site-specific waste management intervention strategies that would enhance and promote waste diversion activities and general ‘optimal’ waste behaviour. The main strategies for the residential sector include (a) the introduction of a brown bin (organics) collection service and community workshops in the Dún Laoghaire Rathdown local authority; (b) extending a community composting project in the Dublin City local authority; (c) initiating a waste promotion /motivation scheme in South Dublin (d) Waste Booklet distribution to promote waste reduction activities in Fingal (e) region wide distribution of a Waste Booklet to the commercial sector.