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- Jassim, Hassanean, 1978-, et al.
(författare)
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Determining the environmental impact of material hauling with wheel loaders during earthmoving operations
- 2019
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Ingår i: Journal of the Air and Waste Management Association. - : Taylor & Francis. - 1096-2247 .- 2162-2906. ; 69:10, s. 1195-1214
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Tidskriftsartikel (refereegranskat)abstract
- A method has been developed to estimate the environmental impact of wheel loaders used in earthmoving operations. The impact is evaluated in terms of energy use and emissions of air pollutants (CO2, CO, NOx, CH4, VOC, and PM) based on the fuel consumption per cubic meter of hauled material. In addition, the effects of selected operational factors on emissions during earthmoving activities were investigated to provide better guidance for practitioners during the early planning stage of construction projects. The relationships between six independent parameters relating to wheel loaders and jobsite conditions (namely loader utilization rates, loading time, bucket payload, horsepower, load factor, and server capacity) were analyzed using artificial neural networks, machine performance data from manufacturer’s handbooks, and discrete event simulations of selected earthmoving scenarios. A sensitivity analysis showed that the load factor is the largest contributor to air pollutant emissions, and that the best way to minimize environmental impact is to maximize the wheel loaders’ effective utilization rates. The new method will enable planners and contractors to accurately assess the environmental impact of wheel loaders and/or hauling activities during earthmoving operations in the early stages of construction projects.Implications: There is an urgent need for effective ways of benchmarking and mitigating emissions due to construction operations, and particularly those due to construction equipment, during the pre-construction phase of construction projects. Artificial Neural Networks (ANN) are shown to be powerful tools for analyzing the complex relationships that determine the environmental impact of construction operations and for developing simple models that can be used in the early stages of project planning to select machine configurations and work plans that minimize emissions and energy consumption. Using such a model, it is shown that the fuel consumption and emissions of wheel loaders are primarily determined by their engine load, utilization rate, and bucket payload. Moreover, project planners can minimize the environmental impact of wheel loader operations by selecting work plans and equipment configurations that minimize wheel loaders’ idle time and avoid bucket payloads that exceed the upper limits specified by the equipment manufacturer.
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| 2. |
- Kinobe, Joel, et al.
(författare)
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Mapping out the solid waste generation and collection models: The case of Kampala City
- 2015
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Ingår i: Journal of the Air and Waste Management Association. - : Informa UK Limited. - 1096-2247 .- 2162-2906. ; 65, s. 197-205
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a mapping of the waste collection systems in Kampala city, using geographical information system (GIS) ArcGIS mapping software. It discusses the existing models of waste collection to the final disposal destinations. It was found that food and yard wastes constitute 92.7% of the waste generated in Kampala. Recyclables and other special wastes constitute only 7.3% of the total waste, mainly because of the increased level of reuse and recycling activities. The generation rate of solid wastes was on average, 582, 169, 105, and 90 tons/day from poor areas, upscale wealthier areas, business centers, and market areas respectively. This tonnage of waste was collected, transported, and disposed of at the city landfill. The study found that in total, residential areas of poor people generate more waste than other categories stated earlier, mainly because of their large populations. In total, there were 133 unofficial temporary storage sites acknowledged by Kampala Capital City Authority (KCCA) but not formally designated, 59 illegal dump sites, and 35 officially recognized temporary waste storage locations. This paper presents large-scale data that can help with understanding the collection models and their influence on solid waste management in Kampala city, which could be used for similar cities in developing countries.
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