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Quantification of paving equipment emmissions on asphalt construction sites

Bock, R. (2020) Quantification of paving equipment emmissions on asphalt construction sites.

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Abstract:The research focuses on the use of a model to predict emissions from paving equipment on a projectscale. With the growing importance of emission reduction and emission reporting, companies try to keep their impact on the environment as low as possible. For a long time, emissions of non-road machinery were dismissed as being of little significance, but in recent years predictions have shown that they have a large impact on air quality especially in urban areas. Previous studies of current models have shown large uncertainties on a smaller scale and emission factors that poorly reflect inuse emissions. Despite the increased attention to non-road machinery, a large data gap surrounds paving equipment emissions. This study investigates the question: “How can emissions modeling help Dura Vermeer estimate the impact of measures to reduce nonroad emissions on asphalt construction sites and what parameters could be adjusted to improve the accuracy of the model?” In this research, two different emission reduction measures are considered, on the one hand replacing older machines with newer ones that have higher emission standards, and on the other hand switching the fuel used from regular diesel to HVO fuels or blends of the two. Much of this study was based on a literature review, further data sources were Dura Vermeer and four companies from the ASPARi group. The provided data included vehicle specifications, fuel consumption data, and load factors from in-use vehicles. The focus of the literature review was the current emission models and their calculation procedures. Also, the uncertainty of the models and studies evaluating the assumptions made in the model were considered. Based on the literature review an emissions model was then chosen and restructured to better fit the intended purpose. The data collected was used to adjust the model, provide the input data, and provide comparative values for the results. The expectation was that a model would show the effect of different emission reduction measures on the amount of the pollutant emitted and the environmental cost indicator (ECI) connected to the emissions. This proved only partly true, as the NOx and PM emissions were significantly reduced by both considered measures, but the ECI of the emissions was largely unaffected. This connects to the measures lacking influence on the CO2 emissions, which contribute to 99% of the ECI. The model further shows that each pollutant requires a different strategy to reduce the pollutant emissions and that the effectiveness of each strategy depends on the intent and initial emissions of the vehicle. Further findings showed that the idling rate was more influential on the emissions than expected. The results indicate a correlation between high idling rates and lower emissions. Another finding was a confirmation of the large uncertainty and lack of measurements when connecting the parameters to emission values, that was already expected from the literature review. The research highlights the need for company internal emission measurements and the necessity to add further parameters to the model.
Item Type:Essay (Bachelor)
Faculty:ET: Engineering Technology
Programme:Civil Engineering BSc (56952)
Link to this item:https://purl.utwente.nl/essays/85019
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