Estimating waste transfer station delays using GPS

This paper examines the use of on-board global positioning system (GPS) data recorders as a method to collect field data on the movements of solid waste collection vehicles at transfer stations. The movements of five waste collection vehicles using four different transfer facilities were compared over a period of 1 year. The spatial data were analyzed using geofences to determine the amount of time each truck spent on each of four activities: queuing for access to the weigh scale, sitting on the weigh scale, queuing for access to the tipping floor, and unloading waste. The study found that queuing delays can be identified and measured using GPS data. The average time at a facility for all trucks was 16.4min per visit, with a standard deviation of 14.3min. Time at the facility ranged between 2 and 111min per visit and the distribution of time at the facility was positively skewed. Multi-compartment vehicles (co-collection and recycling trucks) spent significantly more time at unloading facilities. There were also significant differences in the length and the location of the queues at different facilities. At one facility, the longest delays were encountered while waiting for the weigh scale, at two facilities trucks experienced delays in obtaining access to the tipping floor, while at the fourth facility no significant delays developed.     

Community evacuation following a chlorine release, Mississippi

On 7th September 1986, four miles north of Collins, Mississippi, a train transporting chlorine derailed. Two cars ruptured and gas escaped. As a result, 100 families were evacuated. To study the evacuation process, we conducted person-to-person interviews with sixty-two families staying in the evacuation center. Only 52.5% of the families received their first directive to evacuate directly from police or other officials. Delays in evacuating tended to be shorter when people were warned by the police and were told the reason for evacuating. Lack of personal transportation and preexisting health problems resulted in delays in evacuation. Concerns about evacuation included fear of looting, lack of a place to go, lack of transportation, difficulty in moving with children and elderly persons, and the need to take care of pets. One third of the interviewees reported feeling panic. Community evacuation procedures would be improved if: (1) officials contact all households directly; (2) the warning message addresses people's concerns; and (3) transportation is provided.     

Resolving People-Park Conflicts through Negotiation: Reflections on the Richtersveld Experience

Protected areas in developing countries play a vital role in promoting the ideal of sustainable development.But 'people-park'conflicts are commonplace,threatening the future of these areas and the long term well-being of local communities. Surprisingly, little attention has been given to applying lessons learned in conflict studies to people-parkconflicts. In contrast to traditional adversarialresponses, negotiated approaches offer considerable potential for transforming people-park conflicts into mutually beneficial relationships.Experiencesin the Richtersveldregion of South Africa demonstrate the cardinal role negotiation can play in addressing key issues underlying people-park conflicts.     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.     

Using Multiple Antibiotic Resistance and land use characteristics to determine sources of fecal coliform bacterial pollution

Multiple Antibiotic Resistance (MAR) analysis and regression modeling techniques were used to identify surface water areas impacted by fecal pollution from human sources, and to determine the effects of land use on fecal pollution in Murrells Inlet, a small, urbanized, high-salinity estuary located between Myrtle Beach and Georgetown, South Carolina. MAR analysis was performed to identify areas in the estuary that are impacted by human-source fecal pollution. Additionally, regression analysis was performed to determine if an association exists between land use and fecal coliform densities over the ten-year period from 1989 to 1998. Land-use variables were derived using Geographic Information System (GIS) techniques and were used in the regression analysis.MAR analyses were conducted by comparing the frequency and patterns of antibiotic resistance found in Escherichia coli isolates derived from surface water samples and from sewage sources in the Murrells Inlet sewage collection system. The MAR results suggest that the majority of the fecal pollution detected in the Murrells Inlet estuary may be from non-human sources, including fecal coliforms isolated from areas in close proximity to high densities of active septic tanks.A MAR Index, which measures the frequency of antibiotic resistance, was calculated for each of twenty-three water samples and nine sewage samples. The antibiotic resistance pattern comparisons were performed using cluster analysis. Although the MAR indices indicated that several surface water sites had potential human-source contamination, the cluster analysis suggests that only one sampling site had MAR patterns that were similar to those found in the sewage samples. This site was in close proximity to several large pleasure boats as well as a sewage collection system lift station, but was not near areas with active septic tanks. The results of the regression analysis also suggest that sewage sources and rainfall runoff from urbanized areas may contribute to fecal pollution in the estuary.     

Monochlorobenzene Marine Risk Assessment with Special Reference to the Osparcom Region: North Sea

This risk assessment on monochlorobenzene was carried out for the marine environment, following methodology given in the EU risk assessment Regulation (1488/94) and Guidance Document of the EU New and Existing Substances Regulation (TGD, 1996). Data from analytical monitoring programmes in large rivers and estuaries in the North Sea area were collected and evaluated for effects and environmental concentrations. Risk is indicated by the ratio of predicted environmental concentration (PEC) to predicted no-effect concentration (PNEC) for the marine aquatic environment. In total, 27 data for fish, 24 data for invertebrates and 13 data for algae were evaluated. Acute and chronic toxicity studies were taken into account and appropriate assessment factors used to define a final PNEC value of 32 micro/l. Recent monitoring data indicate that monochlorobenzene levels in surface waters are below determination limits of 0.1, 0.2, 0.5 microg/l used in monitoring programs. Assuming that half of the lowest determination (0.1 microg/l) is typical, a PEC of 0.05 microg/l was derived. A worst case of 0.5 microg/l is assumed. PEC/PNEC ratios give safety factors of 60 to over 500, taking no account of dilution in the sea. Monochlorobenzene is not a 'toxic, persistent and liable to bioaccumulate' substance sensu the Oslo and Paris Conventions for the Prevention of Marine Pollution (OSPAR-DYNAMEC) criteria. Environmental fate and effects data indicate that current use of monochlorobenzene poses no unacceptable risk to the aquatic environment.