Environmental and Energy Benefits of Freight Delivery Consolidation in Urban Areas

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 Research Brief Final Report

Primary Investigators

Jane Lin
UIC College of Civil and Materials Engineering
MC 246, 842 West Taylor Street
Chicago, IL 60607


Over the last several decades, changes in the supply chain management practices and the growth in e-commerce have led to a rapid increase in the number of trips and miles driven by trucks. This research investigates the business cost and environmental impacts of a promising truck demand management strategy that has been used in European and Asian countries, delivery consolidation. We will simulate freight delivery activities in a hypothetical urban area using an agent-based model. Simulation will be conducted for up to eight scenarios consisting of various combinations of: the size of delivery vehicles, penetration of biodiesel fuel, fleet turnover rate, and fuel price. This research will provide valuable insights toward the development of a comprehensive strategy for sustainable goods movement in urban areas by filling some of the critical knowledge gaps.


The objective of this study is to examine the effectiveness of delivery consolidation in terms of air pollutant emissions, energy use, and costs to businesses. This research strives to investigate the following research questions:

  1. What is the benefit/cost of delivery consolidation to businesses?
  2. What is the social benefit of delivery consolidation in terms of reduction in total emissions and life cycle energy demand?
  3. Compared with other government programs to cut transportation-related air pollution and fuel use, is it worthwhile to consider providing subsidy to support delivery consolidation?
  4. How will the answers to the questions above be affected by: the size of delivery vehicles, penetration of biodiesel fuel, fleet turnover rate, and fuel price in the long term?


  1. Develop agent-based model: [a] Prepare land use, socioeconomic, and truck fleet database; [2] Define road network; [3] Program optimization algorithm for tour planning; [4] Develop an estimation module on air pollutant emissions and energy consumption rates
  2. Perform simulation runs
  3. Interpretation of outputs and sensitivity analysis
  4. Documentation

Project Information

  • Duration: 12 months
  • Dates: September 2009 – August 2010
  • Budget: $77,062 ($12,926 macthing funds)
  • Student Involvement: Two graduate students
  • Modal Orientation: Highway
  • Project ID: CFIRE 03-19
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