The hypothesis of this research was that attitudes and behaviours towards the management of biodegradable municipal waste (BMW) are spatially variable among the commercial sector (non-household sector), even within a city of modest (1.2 million) population. For a select number of representative electoral districts in the Dublin, Ireland region, businesses were surveyed regarding attitudes and behaviours towards waste management in general, and BMW management in particular. A total of 100 establishments were invited to fill in surveys with 71 completed surveys collected. Doorto-door interviews produced 20 responses; these were supplemented by 51 responses to a web-based survey. This resulted in a 71% response rate for the waste survey. It also showed the preference among businesses to the use of web-based survey modality rather than face-to-face interviews.Statistical analyses of the survey responses showed the majority of commercial respondents (34%) regarded "reducing the amount of waste generated" as the most important future issue they face. The majority of privately owned businesses (as opposed to publically owned enterprises, such as schools) believe they should pay for waste management services. These statistical results proved the hypothesis of the research and demonstrated that waste management initiatives designed for one area of the city (or, indeed, for uniform application to the city as a whole) could ignore the needs of some sectors. The survey responses suggest that targeted intervention strategies would lead to improved diversion rates of BMW from landfill, a requirement of the Landfill Directive 1999/31/EC.
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. Socioeconomic 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.
Multiple linear equations to predict selected parameters for the Kentucky watershed model (KWM) are presented. The independent variables consist of easily determinable watershed characteristics. The relationship provides a means by which the KWM can be used to predict streamflows from ungaged drainage basins. Examples are given for five test watersheds. Results are variable. INTRODUCTION include watershed data from other states in the southern re-Competition among users for a relatively fixed supply of gion. water has focused attention on the need for effective means to plan for the optimum use of this vital resource. Parametric models, which lend themselves to computer application and attempt to simulate the hydrologic cycle, have become recognized as useful aids to such planning. One of the better known and more comprehensive parametric models is the Stanford watershed model [Crawford and Linsley, 1966]. Because of its popularity it has undergone numerous modifications [e.g., James, 1965; Claborne and Moore, 1970; $hanholtz et al., 1972; Ligon et al., 1969]. However, each modification is basically a soil moisture accounting procedure in which mathematical expressions are used to define relationships between elements of the hydrologic cycle and the interactions between its components. Numerous parameters are utilized in this process, some of which are derived from historical records, some from climatological data, others from physical watershed characteristics, and still other nonmeasurable entities from estimation by trial-and-adjustment or optimization procedures. The effectiveness of these routines depends on the availability of a streamflow record of sufficient length to calibrate the model. Typically, several different combinations of parameters are utilized before an acceptable match can be found between predicted and recorded streamflows. The need of prior calibration makes it difficult to apply existing watershed models to ungaged watersheds. To circumvent this problem, attempts have been made to correlate model parameters to measurable physical watershed characteristics. James [1972], reporting on work by Ross [1970], discusses linear regression relationships that were developed to relate plant available water capacity (AWC), permeability of the A soil horizon, and overland flow surface slope to selected parameters in the Kentucky watershed model (KWM). Jarboe and Haan [1974] used a multiregression approach to estimate parameters for use in a monthly water yield model. Ambaruch and Simmons [1973] also reported some success with a multiregression approach, using data from several Tennessee Valley Authority watersheds. The study reported herein was undertaken to extend the work of Ross [1970] and Ambaruch and Simmons [1973] to
Phosphorus (P) in agricultural runoff is a major pollutant in many of Ireland's surface waters. Identification of areas that are at a high risk for P loss to surface waters is a critical component of river basin management. Two P ranking schemes (PRS's) were developed for Ireland, based on multi-criteria analysis approaches proposed in both the U.S. and Europe, to predict the relative likelihood of P loss at both the field and catchment scales. The Field PRS was evaluated by comparing predicted rankings of potential P loss and transport against measured edge-of-field Dissolved Reactive P (DRP) loss for three fields with varying soil P levels. Qualitatively, results indicated that the Field PRS rankings corresponded to the magnitudes of measured P loss for the field sites, as well as to a reasoned evaluation of the relative likelihood that the fields would lose P that would subsequently make its way to surface water. The Catchment PRS was evaluated on a total of thirty-one catchments and sub-catchments by comparing predicted rankings of potential P loss and transport against measured in-stream median Molybdate Reactive P (MRP). Rankings of the relative likelihood of P loss and transport predicted by the Catchment PRS were positively correlated with median in-stream MRP (r = 0.51, P<0.05). Although the data available for these evaluations were limited, especially at field scale, and further research may identify the opportunity for modifications, both field and catchment scale P ranking schemes demonstrated a potential for identifying critical P source areas within catchments dominated by grass-based agricultural production systems, such as those in Ireland.
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