ESTIMATION OF METHANE GENERATION AND ENERGY POTENTIAL OF NIGDE LANDFILL SITE USING FIRST ORDER MATHEMATICAL MODELLING APPROACHES

Öz

Methane content of landfill gas is approximately 50%. Methane has a significant calorific and economic value, rather than its greenhouse effect. Therefore, it is essentially important to estimate future LFG and methane production in terms of usage and management policies. More than a few models have been used to computerize prospective methane trends based on deposited waste characters and climatic information. This study aims to calculate LFG and methane production using different models. The model inputs were adopted from field measurements, waste characterization, meteorological information, and technical papers prepared by Conestoga-Rovers & Associates (CRA), Intergovernmental Panel on Climate Change (IPCC), and United States Environmental Protection Agency (EPA). This study indicates that the first order models have different outcomes for Niğde Landfill Site and the increase in methane generation potential value causes higher generation volumes of LFGs for the future. The maximum total LFG production is estimated as 600 million m³ with a methane potential of 126 m³/ton and total methane yield for the same method was calculated as 312.5 million m³. This study also estimates the maximum electricity generation from LFG. The maximum electricity generation was estimated 6.9 million kWh for 2042.

Anahtar Kelimeler

• Energy potential,Landfill gas,Methane generation,Methane modelling

NİĞDE DÜZENLİ DEPOLAMA ALANININ METAN ÜRETİMİ VE ENERJİ POTANSİYELİNİN BİRİNCİ DERECEDEN MATEMATİKSEL MODELLEME YAKLAŞIMLARI İLE TAHMİNLENMESİ

Öz

Düzenli depolama gazlarının (DDG) yaklaşık %50’sini metan gazı oluşturmaktadır. Metanın sera etkisinden başka önemli ölçüde kalorifik ve ekonomik değeri vardır. Bu nedenle, gelecekteki DDG ve metan üretiminin kullanım ve yönetim politikaları açısından tahmin edilmesi önemlidir. Gelecekteki metan salınımlarını katı atık karakteristiklerine ve iklim bilgilerine göre hesaplamak için birden fazla model kullanılmıştır. Bu çalışmada, farklı modeller kullanılarak DDG ve metan üretiminin hesaplanması amaçlanmıştır. Model girdileri saha ölçümlerinden, atık karakterizasyonundan, meteorolojik bilgilerinden ve Conestoga-Rovers & Associates (CRA), Hükümetler arası İklim Değişikliği Paneli (IPCC) ve Amerika Birleşik Devletleri Çevre Koruma Ajansı (EPA) tarafından hazırlanan teknik dokümanlardan elde edilmiştir. Bu çalışma, birinci derece modellerinin Niğde Depolama Sahası için farklı sonuçlara sahip olduğunu ve metan üretimi potansiyel değerindeki artışın, gelecek için daha yüksek DDG oluşumuna neden olduğunu göstermektedir. Toplam maksimum DDG üretimi, 126 m³/ton metan potansiyeli ile 600 milyon m³ olarak tahmin edilmiştir ve aynı yöntem için toplam metan verimi 312,5 milyon m³ olarak hesaplanmıştır. Bu çalışma aynı zamanda DDG’den elde edilecek maksimum elektrik üretimini de tahmin etmektedir. 2042 yılı için maksimum elektrik üretimi 6,9 milyon kWh olarak hesaplanmıştır.

Anahtar Kelimeler

• Enerji potansiyeli,Düzenli depolama gazı,Metan oluşumu,Metan modellemesi

Kaynakça

1. Afvalzorg H., 2015. Methane emissions. http://www.afvalzorg.nl/EN/Landfill-sites/Emissions-management/Methane-emissions.aspx (accessed 01 January 2017).
2. Amini H.R., Reinhart D.R., Mackie K.R., 2012. Determination of first-order landfill gas modeling parameters and uncertainties. Waste Management, 32, 305-316.
3. Bo-Feng C., Jian-Guo L., Qing-Xian G., Xiao-Qin N., Dong C., Lan-Cui L., Ying Z., Zhan-Sheng Z., 2014. Estimation of methane emissions from municipal solid waste landfills in China based on point emission sources. Advances in Climate Change Research, 5 (2), 81-91.
4. Broun R, Sattler M., 2016. A comparison of greenhouse gas emissions and potential electricity recovery from conventional and bioreactor landfills. Journal of Cleaner Production, 112, 2664-2673.
5. Christensen T.H., 2010. Solid Waste Technology & Management, in: Christensen, T.H. (Ed.), Solid Waste Technology & Management. Wiley, Lyngby, Denmark, pp. 685-686.
6. Conestoga-Rovers & Associates, 2011 Technologies and best management practices for reducing GHG emissions from landfills guidelines. Richmond, British Columbia pp 1-68.
7. Das D., Majhi B.K., Pal S., Jash T., 2016. Estimation of land-fill gas generation from municipal solid waste in Indian cities. Energy Procedia, 90, 50-56.
8. Donovan S.M., Bateson T., Gronow J.R., Voulvoulis N., 2010. Modelling the behaviour of mechanical biological treatment outputs in landfills using the GasSim model. Science of Total Environment, 408 (8), 1979-1984.

9. Du M., Peng C., Wang X., Chen H., Wang M., Zhu Q., 2017. Quantification of methane emissions from municipal solid waste landfills in China during the past decade. Renewable Sustainable Energy Reviews, 78, 272-279.
10. El-Fadel M., Findikakis A.N., Leckie J.O., 1997. Environmental impacts of solid waste landfilling. Environmental Management, 50 (1), 1-25.
11. IPCC, 2006. Guidelines for national greenhouse gas inventories: solid waste disposal. https://www.ipcc-nggip.iges.or.jp/public/2006gl/ (accessed 05 May 2017).
12. Ishii K., Furuichi T., 2013. Estimation of methane emission rate changes using age-defined waste in a landfill site. Waste Management, 33, 1861-1869.
13. Işın E.O., 2012. Determination of Landfill Gas by Using Mathematical Models. Master Thesis, Dokuz Eylül University , İzmir, Turkey, pp. 1-112.
14. Kiriş A, Saltabaş F., 2011. The landfill gas management at sanitary landfill site and Istanbul case study. Sigma Journal of Engineering and Natural Sciences, 3 (1), 209-218.
15. Machado S.L., Carvalho M.F., Gourc J.P., Vilar O.M., Nascimento J.C.F., 2009. Methane generation in tropical landfills: Simplified methods and field results. Waste Management, 29, 153-161.
16. National Waste Management and Action Plan 2023. Ministiry of Environment and Urbanization. http://webdosya.csb.gov.tr/db/cygm/haberler/ulusal_at-k_yonet-m--eylem_plan--20180328154824.pdf (accessed 09 November 2018)
17. Oonk H., 2010. Literature review: Methane from landfills (Methods to quantify generation, oxidation and emission). Assendelft, Netherlands, pp 1-75.
18. Penteado R., Cavalli M., Magnano E., Chiampo F., 2012. Application of the IPCC model to a Brazilian landfill: first results. Energy Policy, 42. 551-556.
19. Rajaram R., Siddiqui F.Z., Khan M.E., 2011. From Landfill Gas to Energy: Technologies and Challenges, first ed. CRS press Taylor & Francis Group, London, UK.
20. Sarptaş H., 2016. Assessment of landfill gas (LFG) energy potential based on estimates of LFG models. DEU Fen ve Muh 18, 491-501.
21. Scharff H., Jacobs J., 2006. Applying guidance for methane emission estimation for landfills. Waste Management, 26 (4), 417-429.
22. Staley B.F., Barlaz M.A., 2009. Composition of municipal solid waste in the United States and implications for carbon sequestration and methane yield. Journal of Environmental Engineering, 135, 901-909.
23. Thompson S, Sawyer J, Bonam R, Valdivia JE (2009) Building a better methane generation model: Validating models with methane recovery rates from 35 Canadian landfills. Waste Management, 29: 2085-2091.
24. Turkish State Meteorological Service (2017) https://mgm.gov.tr/eng/forecast-cities.aspx?m=NIGDE (accessed 01 January 2017).
25. Turkish Statistical Institute (2012) Municipal Waste Statistics. http://www.tuik.gov.tr/PreHaberBultenleri.do?id=16170 (accessed 01 January 2017)
26. Turkish Statistical Institute (2017) Turkish Statistical Institute. https://biruni.tuik.gov.tr/medas/?kn=119&locale=en (accessed 01 January 2017).
27. Uisung L., Jeongwoo H., Michael W., 2017. Evaluation of landfill gas emissions from municipal solid waste landfills for the life-cycle analysis of waste-to-energy pathways. Journal of Cleaner Production, 166 (2017), 335-342.
28. USEPA (2017) LFG energy project development handbook. http://www.epa.gov/lmop/publications-tools/handbook.html (accessed 08 August 2017).
29. Xin D., Hao Y., Shimaoka T., Nakayama H., Chai X., 2016. Site specific diel methane emission mechanisms in landfills: a field validated process based on vegetation and climate factors. Environmental Pollution, 218, 673-680.