Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
11033325 | Waste Management | 2018 | 6 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Geotechnical Engineering and Engineering Geology
Authors
Assal Haddad, Shadi Moqbel,