Quantifying errors in micro-scale emissions models using a case-study approach

To quantify the level of uncertainty attached to forecasts of CO2 emissions, an analysis of errors is undertaken; looking at both errors inherent in the model structure and the uncertainties in the input data. Both error types are treated in relation to CO2 emissions modelling using a case-study from Brisbane, Australia. To estimate input data uncertainty, an analysis of traffic conditions using Monte Carlo simulation is used. Model structure induced uncertainties are also quantified by statistical analysis for a number of traffic scenarios. To arrive at an optimal overall CO2 prediction, the interaction between the two components is taken into account. Since a more complex model does not necessarily yield higher overall accuracy, a compromise solution is found. The results suggest that the CO2 model used in the analysis produces low overall uncertainty under free flow traffic conditions. When average traffic speeds approach congested conditions, however, there are significant errors associated with emissions estimates.

• Record URL:
  • https://doi.org/10.1016/j.trd.2013.01.010
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1361920913000163
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Zhu, Sicong
  • Ferreira, Luis
• Publication Date: 2013-6

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 19-25
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 21
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Case studies; Computer models; Error analysis; Forecasting; Greenhouse gases; Monte Carlo method; Statistical analysis; Traffic congestion
• Geographic Terms: Brisbane (Australia)
• Subject Areas: Environment; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01482850
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 3 2013 9:20AM