Quantifying odour impacts from aged organic waste to be considered as a priority constraint in route optimization for waste collection trucks.

Route optimization has been used for years to plan the routes for municipal solid waste (MSW) collection trucks to achieve cost reductions. Historically, optimized routes had overlooked a number of aspects and parameters in their design. This study aims to consider MSW odour detection as a performance indicator and a priority constraint in the optimization process by quantifying the impact of objectionable odours from uncollected aged MSW that contains a high percentage of food waste (typically called wet garbage). Odours from 48 aged food waste samples were rated on a scale from 0 to 3 to mark the beginning of the critical time of objectionable odour detection. The critical time was found to take place approximately at the hour 13.6, which was then used, along with the estimated food waste weight in the bin, to define the beginning of a time window that puts the bin on a high priority status for collection over the other, less odoriferous bins. Three optimization scenarios for collection of 100 MSW bins in the city of Madaba, Jordan, were conducted under different constraints: least travelled distance, maximum collected volume and least odour impact. Without the application of the odour consideration, a total travelled distance of 143 km was the shortest travelled distance achieved, with 53 bins emitting odours and leaving 81 m3 of uncollected waste. However, when odour impact was the main routing constraint, a total travelled distance of 161 km was needed and 13 m3 of waste was left uncollected.

Anti-littering in developing countries: Motivating the people of Jordan.

Littering in developing countries remains a problem that has not been overcome, and past research based on a trial-and-error approach has not solved the problem. In this study, a questionnaire was constructed and distributed to the people of Jordan. People were asked to indicate what motivates them to use the litter bins. The motivators were divided into intrinsic motivators and extrinsic motivators. The responses to the questionnaire were statistically analysed according to the score for each motivator and the responders' attributes. The highest level intrinsic motivators were the 'sense of morals and ethics' and 'following the way they were raised'. The highest impact of extrinsic motivators was the presence of children followed by increasing number of receptacles, being in a clean place and the presence of recycling programmes. Studying the respondents' attributes showed there are differences in people's responses to intrinsic motivators according to socio-demographical factors, while for extrinsic motivators these factors tend to diminish and people react almost the same. The results of this study can explain some of the differences in reported results in the literature on littering behaviour according to socio-demographic factors. To have an effective anti-littering approach in Jordan, the authorities should consider using a combination of intrinsic and extrinsic motivators. In the intrinsic motivators, the authorities should praise and remind people of their core values, morals and their children's behaviour and future. For the extrinsic motivators, the following descending order is suggested: convenient infrastructure, recycling programmes, anti-littering campaigns, rewards, penalties.

Modeling of dioxin levels in pine needles exposed to solid waste open combustion emissions.

Incomplete open combustion of solid waste produces a range of dioxin compounds which have the ability to accumulate in mediums such as organic soil and leave's wax at levels that are proportional to its ambient concentrations. Biomonitoring of contamination levels in pine needles have been used to assess the severity of atmospheric pollution due to the ability of the needles to store considerable amounts of pollutants including dioxin. Information about the dioxin levels in trees leaves are of an additional value since stored dioxin in leaves can also be conveyed to other animals higher in the food chain, or could migrate to underlying soils because of rain effect. Several biomonitoring studies have been conducted to assess the health impact of local solid waste incinerators, through time consuming and intensive laboratory testing. This study utilizes the results of these previous studies and proposes a statistical regression model that predicts the dioxin concentration in pine needles as function of distance away from emission source, plastic content of burned waste, and time of exposure. To increase the pool of data on which this model is based, 24 pine needle samples affected by a solid waste open combustion site in Amman have been tested at different distances from the emission source, resulting in a total sample size of 43 data points. Solid waste plastic content were obtained from other resources. The fitted nonlinear model had an R-squared value of 89% and a Standard Error Estimate of 0.5. The relationship between the independent variables and the dioxin contamination level appeared to be non-linear. The modeled dioxin concentration was found to be very sensitive to time of exposure, while being less sensitive to distance from emissions source.

Evaluating the effect of rain on the fate of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) accumulated in polluted trees in Amman, Jordan.

Open combustion of solid waste is one of the main sources of the emission of dioxin and dioxin-like compounds (DLCs). Ambient dioxin will eventually undergo depositions on soils and tree leaves. Pine trees have shown an ability to store dioxin in their needles allowing biomonitoring of dioxin atmospheric concentrations. Infiltration can transport dioxin to greater depths into the ground, on one hand, while vaporization can allow dioxin to return back to the atmosphere on the other. Several studies evaluated the migration of dioxin between two compartments; however, few studies have attempted to understand the fate of non-conservative PCDDs and PCDFs in an unsteady state system of more than two mediums. This study focused on the transportation of dioxin between polluted trees and the underlying soil through the effect of rain water. For approximately 10 years, pine trees in this study have been exposed to emissions generated by the open combustion of municipal solid waste (MSW) from a fixed location. Soil samples located further from the point source had generally lower dioxin concentrations. Dioxin concentrations were correlated to distance from the source using least square regression. Soil samples below contaminated trees had dioxin concentrations 10-35% greater than the calculated measurements for the same spots using the regression model. By detecting these spikes in concentrations, it was possible to identify pools of dioxin found directly under the contaminated trees-indicating a rinsing effect of rain water on the stored dioxin on the trees' needles.