Advertisement

Operational Research

, Volume 17, Issue 3, pp 807–819 | Cite as

Development of a model for assessing Greenhouse Gas (GHG) emissions from terminal and drayage operations

  • Giorgos E. Konstantzos
  • Georgios K. D. Saharidis
  • Maria Loizidou
Original Paper
  • 274 Downloads

Abstract

Within a seaport terminal, the main sources of emissions include (1) building use and maintenance, (2) ocean-going vessels and harbour crafts, (3) cargo handling equipment and (4) heavy-duty vehicles (HDV) used for the transportation of the containers (which considered to be one of the most polluting elements of port operations). The main objective of this work was the development of a mathematical model for the quantification of Greenhouse Gas emissions produced by HDV during container transport in ports. Several models and tools have been developed for this purpose; however most of them utilize an over-simplified fuel and energy consumption-based approach. Firstly, a critical review of emissions calculations models was performed, and following the results of this analysis COPERT was chosen to be used as a basis for modeling the fleet in port operation. The next step was to analyse in depth COPERT’s methodology and equations in order to identify potential limitations. The following step was to evaluate and address those limitations by introducing new elements and factors (e.g. emissions from stop-and-go traffic, idling, emissions increase due to air conditioning operation etc.). The final step was the modification of COPERT’s equation and the development of the improved model.

Keywords

Greenhouse Gas (GHG) emissions CO2 equivalent Emissions calculations Emissions model Port terminals Terminal operations Heavy-duty vehicles (HDV) Drayage operations 

Abbreviations

APU

Auxiliary power unit

CH4

Methane

CO2

Carbon dioxide

CO2 eq.

CO2 equivalent

COPERT

Computer program to calculate emissions from road transport

EGR

Exhaust gas recirculation

FC

Fuel consumption

GHG

Greenhouse gas (es)

GVW

Gross vehicle weight

GWP

Global warming potential

HDV

Heavy-duty vehicle

IPCC

International Panel on Climate Change

LDV

Light-duty vehicle

N2O

Nitrous oxide

NOx

Nitrogen oxides

SCR

Selective catalytic reduction

US EPA

United States Environmental Protection Agency

References

  1. Brodrick C-J, Dwyer HA, Farshchi M, Harris DB, King FG (2002) Effects of engine speed and accessory load on idling emissions from heavy-duty diesel truck engines. J Air Waste Manage Assoc 52:1026–1031CrossRefGoogle Scholar
  2. Chen Gang, Govindan Kannan, Golias Mihalis M (2013) Reducing truck emissions at container terminals in a low carbon economy: proposal of a queueing-based bi-objective model for optimizing truck arrival pattern. Transport Res R Log 55:3–22CrossRefGoogle Scholar
  3. Clark N, Khan A, Thompson G, Wayne W, Gautam M and Lyons D, (2005). Idle emissions from heavy-duty diesel vehicles. s.l.: Center for Alternative Fuels, Engines, and Emissions (CAFEE)Google Scholar
  4. Gaines L and Hartman C-J (2008). Energy use and emissions comparison of idling reduction options for heavy-duty diesel trucks. In: 88th Annual meeting of the transportation research board. Center for Transportation Research, Argonne National Laboratory, Washington, DC. Paper No. 09-3395Google Scholar
  5. IPCC (2014) Climate change 2014: synthesis report. In: Core Writing Team, Pachauri RK and Meyer LA (eds) Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. IPCC, GenevaGoogle Scholar
  6. Khan AS et al (2006) Idle emissions from heavy-duty diesel vehicles: review and recent data. J Air Waste Manage 56:1404–1419CrossRefGoogle Scholar
  7. Konstantzos EG, Saharidis KDG, Kolomvos G, Loizidou M (2013) COMPETE: development of a prototype model for assessing GHG emissions from terminal and drayage operations. D4.2 Critical review of emissions calculation models. COMPETE Project, THALES 2012 Funding ProgramGoogle Scholar
  8. Koupal, JW (2001). Air conditioning activity effects in MOBILE6. s.l.: Environmental Protection Agency (EPA) 2001Google Scholar
  9. Kouridis C et al (2009) Uncertainty estimates and guidance for road transport emission calculations. JRC. EUR 24296 EN—2010Google Scholar
  10. Lim H (2002) Study of exhaust emissions from idling heavy-duty diesel trucks and commercially available idle-reducing devices. s.l.: US Environmental Protection AgencyGoogle Scholar
  11. Ntziachristos L et al (2012). Exhaust emissions from road transport. s.l.: EMEP/EEA emission inventory guidebook 2009, updated May 2012Google Scholar
  12. Panis LI, Broekx S, Liu R (2006) Modelling instantaneous traffic emission and the influence of traffic speed limits. Sci Total Environ 371:270–285CrossRefGoogle Scholar
  13. Rahman ASM et al (2013) Impact of idling on fuel consumption and exhaust emissions and available idle-reduction technologies for diesel vehicles—a review. Energ Convers Manage 74:171–182CrossRefGoogle Scholar
  14. Rexeis M et al (2005). Heavy duty vehicle emissions—Final Report for ARTEMIS WP 400. ARTEMIS. TUG reportGoogle Scholar
  15. Smit R, Brown AL, Chan YC (2008) Do air pollution emissions and fuel consumption models for roadways include the effects of congestion in the roadway traffic flow? Environ Modell Softw 23(2008):1262–1270CrossRefGoogle Scholar
  16. Storey JME et al (2003). Particulate matter and aldehyde emissions from idling heavy-duty diesel trucks. Soc Autom Eng paper 01–0289Google Scholar
  17. Suzuki H, Ishii H, Sakai K and Fujimori K (2008) Regulated and unregulated emission components characteristics of urea SCR vehicles. 2008, JSAE proceedings, 39(6)Google Scholar
  18. USEPA (2008) DrayFLEET: EPA SmartWay drayage activity and emissions model and case studies. s.l.: U.S. Environmental Protection AgencyGoogle Scholar
  19. USEPA (2010a) MOVES 2010 highway vehicle temperature, humidity, air conditioning, and inspection and maintenance adjustments. s.l.: EPA-420-R-10-027Google Scholar
  20. USEPA (2010b) SMARTWAY—Designing and implementing a freight sustainability program: tools, best practices, and lessons learned. s.l.: US Environmental Protection AgencyGoogle Scholar
  21. Zietsman J, Villa JC, Forrest TL and Storey JM (2005). Mexican truck idling emissions at the El Paso-Ciudad Juarez Border Location. s.l.: Southwest University Transportation Center, Texas Transportation Institute, Texas A & M UniversityGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Giorgos E. Konstantzos
    • 1
  • Georgios K. D. Saharidis
    • 2
  • Maria Loizidou
    • 1
  1. 1.School of Chemical Engineering, Unit of Environmental Science and TechnologyNational Technical University of AthensAthensGreece
  2. 2.University of ThessalyVolosGreece

Personalised recommendations