Decisions Under Uncertainty in Municipal Solid Waste Cogeneration Investments

  • Athanasios Tolis
  • Athanasios Rentizelas
  • Konstantin Aravossis
  • Ilias Tatsiopoulos
Chapter
Part of the Green Energy and Technology book series (GREEN)

Abstract

The issue of Municipal Solid Waste (MSW) management is an ever increasing problem for all countries. Developed countries face the problem of dealing with very large amounts of MSW per capita, forcing them to develop new technologies and systems. On the other hand, countries with developing or transitional economies may generate lower amounts of MSW per capita, but the rate of increase is high and the current practices of MSW management are not as advanced as those of developed countries. Therefore, countries with developing or transitional economies may benefit from adopting MSW management technologies used by developed economies. One aspect of MSW management in developed economies is the energy recovery from MSW. The advantages of this type of technologies are mainly the significantly reduced waste volume for landfilling, the reduction of total greenhouse gas emissions, the potential for generating electricity or co-generation of electricity and heat. In this work, a comparative study of the most prominent co-generation technologies using MSW as a fuel source is presented, focusing on the evolution of their economical performance over time. An algorithm based on real-options has been applied for four technologies of MSW energy recovery: (1) incineration, (2) gasification, (3) landfill biogas exploitation using a pipeline system and (4) anaerobic digestion facilities. The financial contributors are identified and the impact of greenhouse gas trading is analyzed in terms of financial yields, considering landfilling as the baseline scenario. The greenhouse gas trading system presents an opportunity for investing in environmentally friendly technologies for MSW energy recovery, through the Clean Development Mechanism (CDM), in most developing countries. The results of this work indicate an advantage of combined heat and power over solely electricity generation. The most attractive technology among the ones examined proves to be incineration, mainly due to its higher power production efficiency, lower investment costs and lower emission rates. Despite the fact that these characteristics may not drastically change over time, either immediate or irreversible investment decisions might be reconsidered under the current selling prices of heat, power and CO2 allowances.

Keywords

Combustion Methane Fermentation Enthalpy Europe 

References

  1. 1.
    ACMAR (2009) Association of Communities and Municipalities of the Attica Region, 11.09.09 www.esdkna.gr
  2. 2.
    Barlow MT (2002) A diffusion model for electricity prices. Math Finan 12(4):287–298CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    Barton JR, Issaias I, Stentiford EI (2008) Carbon—making the right choice for waste management in developing countries. Waste Manag 28:690–698CrossRefGoogle Scholar
  4. 4.
    Brennan MJ, Schwartz E (1985) Evaluating natural resource investments. J Bus 58:135–157CrossRefGoogle Scholar
  5. 5.
    Clewlow L, Strickland C (2000) Energy derivatives: pricing and risk management. Lacima Publications, LondonGoogle Scholar
  6. 6.
    Dixit A, Pindyck R (1994) Investment under uncertainty. Princeton University Press, PrincetonGoogle Scholar
  7. 7.
    Eleftheriou P (2007) Energy from waste: a possible alternative energy source for large size municipalities. Waste Manag Res 25:483–486CrossRefGoogle Scholar
  8. 8.
    Fuss S, Szolgayova J, Obersteiner M, Gusti M (2008) Investment under market and climate policy uncertainty. Appl Energy 85:708–721CrossRefGoogle Scholar
  9. 9.
    Garg A, Smith R, Hill D, Longhurst PJ, Pollard SJT, Simms NJ (2009) An integrated appraisal of energy recovery options in the United Kingdom using solid recovered fuel derived from municipal solid waste. Waste Manag 29:2289–2297CrossRefGoogle Scholar
  10. 10.
    General Secretariat of National Statistical Service of Greece 10.09.2009, www.statistics.gr
  11. 11.
    Glasserman G (2004) Monte-Carlo methods in financial engineering. Springer-Verlag, NYMATHGoogle Scholar
  12. 12.
    Gohlke O (2009) Efficiency of energy recovery from municipal solid waste and the resultant effect on the greenhouse gas balance. Waste Manag Res 27:894–906CrossRefGoogle Scholar
  13. 13.
    Greek Ministry of Development (2009) 13.09.09 www.ypan.gr
  14. 14.
    Hansen TL, Jansen J, Davidson A, Christensen TH (2007) Effects of pre-treatment technologies on quantity and quality of source-sorted municipal organic waste for biogas recovery. Waste Manag 27:398–405CrossRefGoogle Scholar
  15. 15.
    Hesseling WFM (2002) Thermoselect Facility report, TNO R2002/126Google Scholar
  16. 16.
    HTSO SA (2009) Hellenic transmission system operator. 08.08.09, www.desmie.gr
  17. 17.
    Ingersoll JE, Ross SA (1992) Waiting to invest: investment and uncertainty. J Bus 65(1):1–29CrossRefGoogle Scholar
  18. 18.
    Junginger M, Faaij A, Turkenburg WC (2005) Global experience curves for wind farms. Energy Policy 33(2):133–150CrossRefGoogle Scholar
  19. 19.
    Kathirvale S, Yunus MM, Sopian K, Samduddin AH (2003) Energy potential from municipal solid waste in Malaysia. Renew Energy 29(4):559–567CrossRefGoogle Scholar
  20. 20.
    Kloeden PE, Platen E (1999) Numerical solution of stochastic differential equations. Springer, BerlinGoogle Scholar
  21. 21.
    Laurikka H, Koljonen T (2006) Emissions trading and investment decisions in the power sector-a case study in Finland. Energy Policy 34:1063–1074CrossRefGoogle Scholar
  22. 22.
    Luoranen M, Horttanainen M (2007) Feasibility of energy recovery from municipal solid waste in an integrated municipal energy supply and waste management system. Waste Manag Res 25:426–439CrossRefGoogle Scholar
  23. 23.
    Luoranen M, Horttanainen M (2008) Co-generation based energy recovery from municipal solid waste integrated with the existing energy supply system. Waste Manag 28:30–38CrossRefGoogle Scholar
  24. 24.
    Medina M (1997) The effect of income on municipal solid waste generation rates for countries of varying levels of economic development: a model. J Solid Waste Technol Manag 24(3):149–155Google Scholar
  25. 25.
    Møller J, Boldrin A, Christensen TH (2009) Anaerobic digestion and digestate use: accounting of greenhouse gases and global warming contribution. Waste Manag Res 29:813–824CrossRefGoogle Scholar
  26. 26.
    Murphy JD, McKeogh E (2004) Analysis of energy production from municipal solid waste. Renew Energy 29:1043–1057CrossRefGoogle Scholar
  27. 27.
    Øksendal B (2000) Stochastic deferential equations. Springer-Verlag, BerlinGoogle Scholar
  28. 28.
    Onu C (2000) Sustainable waste management in developing countries. In: Proceedings of the biennial congress of the institute of waste management of Southern Africa, WasteCon’00, Cape Town, South Africa, pp 367–378Google Scholar
  29. 29.
    Papageorgiou A, Barton JR, Karagiannidis A (2009) Assessment of the greenhouse effect impact of technologies used for energy recovery from municipal waste: a case for England. J Environ Manag 90:2999–3012CrossRefGoogle Scholar
  30. 30.
    Parrot L, Sotamenou J, Dia BK (2009) Municipal solid waste management in Africa: strategies and livelihoods in Yaoundé, Cameroon. Waste Manag 29:986–995CrossRefGoogle Scholar
  31. 31.
    Point Carbon (2009) Carbon market indicator. 12.08.2009, http://www.pointcarbon.com
  32. 32.
    Reimann D (2009) CEWEP energy report II (Status 2004–2007). Confederation of European waste to energy plantsGoogle Scholar
  33. 33.
    Rentizelas A, Tolis A, Tatsiopoulos I (2009) Biomass district energy trigeneration systems: emissions reduction and financial impact. Water Soil Air Pollut J Focus 9(1–2):139–150CrossRefGoogle Scholar
  34. 34.
    Rubin ES (2007) Learning rates and future cost of power plants with CO2 capture. IEA international workshop on technology learning and deployment, Paris, France, 11 June 2007Google Scholar
  35. 35.
    Shreve R (2004) Stochastic calculus for finance II: continuous-time models. Springer-Verlag, BerlinGoogle Scholar
  36. 36.
    Tatsiopoulos I, Tolis A (2003) Economic aspects of the cotton-stalk biomass logistics and comparison of supply chain methods. Biomass Bioenergy 24:199–214CrossRefGoogle Scholar
  37. 37.
    Trigeorgis L (1996) Real options. The MIT Press, CambridgeGoogle Scholar
  38. 38.
    Tsilemou K, Panagiotakopoulos D (2006) Approximate cost functions for solid waste treatment facilities. Waste Manag Res 24:310–322CrossRefGoogle Scholar
  39. 39.
    Troschinetz A, Mihelcic J (2009) Sustainable recycling of municipal solid waste in developing countries. Waste Manag 29(2):915–923CrossRefGoogle Scholar
  40. 40.
    Tuhkanen S, Pipatti R, Sipilä K, Mäkinen T (2000) The effect of new solid waste treatment systems of greenhouse gas emissions. 5th international conference on greenhouse gas control technologies (GHGT-5), Cairns, AustraliaGoogle Scholar
  41. 41.
    Unnikrishnan S, Singh A (2010) Energy recovery in solid waste management through CDM in India and other countries. Resour Conserv Recycl 54(10):630–640CrossRefGoogle Scholar
  42. 42.
    Williams P (2005) Waste treatment and disposal, 2nd edn. Wiley, ChichesterCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Athanasios Tolis
    • 1
  • Athanasios Rentizelas
    • 1
  • Konstantin Aravossis
    • 1
  • Ilias Tatsiopoulos
    • 1
  1. 1.School of Mechanical Engineering, Industrial Engineering LaboratoryNational Technical University of AthensAthensGreece

Personalised recommendations