Estimation and Modeling of Emission of Greenhouse Gases and Carbon Monoxide in Urban Landfill (Case Study: Aradkooh Landfill, Tehran)

Document Type : Research Paper

Authors

Department of Environmental Engineering, Faculty of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran

Abstract

Objective: Although sanitary landfilling remains a widely used waste management method in many places, one of its major challenges is the release of greenhouse gases such as methane, which contributes to air pollution, global warming, and safety hazards. Landfills are a major source of potent greenhouse gases, specially in developing countries where the majority of such emissions are produced. This is a critical issue for the case of Tehran, where the lack of research and modeling on gas production from the landfills hinders mitigation and control efforts. Given the current air pollution crisis in Tehran, the extent and proximity of Aradkooh landfill to Tehran have made this landfill's emissions a significant threat that could worsen the region's severe air pollution crisis. This fact has created an urgent need for accurate modeling and monitoring to inform effective recovery projects. Therefore, this study aims to (i) characterize landfill gas composition and formation processes, (ii) review and evaluate gas estimation methods, and (iii) apply the USEPA LANDGEM model to estimate greenhouse gas emissions at the Aradkooh landfill in Tehran.
Method: Methane generation was modeled using LANDGEM, which applies a first-order decay equation to predict annual landfill gas emissions. Two parameter sets were used: default values provided by the software and theoretical values calibrated to local conditions.
Results: Biogas generation potential was primarily determined by waste volume and composition. In Tehran, effective biogas potential was calculated as the difference between total waste input and the portion processed annually. Favorable landfill conditions, including adequate burial depth and engineered covers, supported efficient anaerobic degradation and methane recovery.
Conclusions: Modeling results under the two scenarios highlighted the importance of parameter selection for reliable emission forecasting. The study emphasized the need for accurate modeling and monitoring to support emission management. Future directions include applying advanced kinetic models, evaluating waste diversion impacts, validating results through field measurements, and testing mitigation measures such as geomembrane liners, nanomaterials, and biogas recovery for energy utilization.

Keywords

Main Subjects

References

Amiri, Z., & Zare Shahne, M. (2025). Modeling PM2.5 concentration in tehran using satellite-based Aerosol optical depth (AOD) and machine learning: Assessing input contributions and prediction accuracy. Remote Sensing Applications: Society and Environment, 38, 101549. https://doi.org/10.1016/J.RSASE.2025.101549
Alizad Oghyanous, F. and Shokrkar, H. (2020). Comparative Study and Simulation of Pollutant Emissions from Landfills of different Cities in Various Regions of Iran by Using LandGEM Software. Nashrieh Shimi va Mohandesi Shimi Iran, 39(2), 291-304. [In Persian]
Arhami, M., Hosseini, V., Zare Shahne, M., Bigdeli, M., Lai, A., & Schauer, J. J. (2017). Seasonal trends, chemical speciation and source apportionment of fine PM in Tehran. Atmospheric Environment, 153. https://doi.org/10.1016/j.atmosenv.2016.12.046
Arhami, M., Shahne, M. Z., Hosseini, V., Roufigar Haghighat, N., Lai, A. M., & Schauer, J. J. (2018). Seasonal trends in the composition and sources of PM2.5 and carbonaceous aerosol in Tehran, Iran. Environmental Pollution, 239. https://doi.org/10.1016/j.envpol.2018.03.111
Baldwin, T. D., Stinson, J., & Ham, R. K. (1998). Decomposition of Specific Materials Buried within Sanitary Landfills. Journal of Environmental Engineering, 124(12). https://doi.org/10.1061/(asce)0733-9372(1998)124:12(1193)
Boyaghchi, F. A., Khanpour, N., & Ashrafi, M. (2013). Emission rate assessment in landfill and energy generation technologies (Case Study: Aradkooh landfill). Journal of Environmental Studies, 39(3).
Bourbour, S., Zare Shahne, M., & Safarkhanloo, H. (2025). Non-Gaussian Misalignment Regression Model Development Based on On-Site and Satellite Meteorological and Air Pollutant Data in Tehran, Iran. International Journal of Environmental Research, 19(4), 1–22. https://doi.org/10.1007/S41742-025-00797-5/METRICS
Datatab. (2024). Wilcoxon test tutorial. Datatab. https://datatab.net/tutorial/wilcoxon-test
USEPA. (2004). https://www.epa.gov/land-research/landfill-gas-emissions-model-landgem
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. https://doi.org/10.1016/j.egypro.2016.11.169
Ghasemzade, R., & Pazoki, M. (2017). Estimation and modeling of gas emissions in municipal landfill (Case study: Landfill of Jiroft City). Pollution, 3(4).
Google Earth Engine. (2024). Sentinel. Google Developers. https://developers.google.com/earth-engine/datasets/catalog/ sentinel
Hssanabadi, M., Hassanvand, M. S., Khanizadeh, M., Faridi, S., Mokammel, A., Malekian Esfahani, B., Ahmadi Orkomi, A., & Momeniha, F. (2024). Investigating methods of estimating and measuring methane emissions in municipal solid waste landfills: a systematic review. Iranian Journal of Health and Environment, 17(3), 595–630. http://ijhe.tums.ac.ir/article-1-6930-en.html
IPCC. (2020). IPCC-2021. In The Complete Guide to Climate Change.
Iran Meteorological Organization. (2022). Homepage. IRIMO. https://irimo.ir
Javadi, M.A., Shahne, M.Z. & Amiri, Z. (2025) Integration of Sentinel-5P Satellite Data and Machine Learning for Spatiotemporal Prediction of NO2 in Delhi: Impacts of COVID-19 Lockdown. Atmospheric Pollution Research. 102702. doi:10.1016/J.APR.2025.102702.
Kafi, A. M., Hosseinipoor, M., Zare Shahne, M., Jamaat, A., Kafi, A. M., Hosseinipoor, M., Zare Shahne, M., & Jamaat, A. (2024). Integrating Sentinel-5P Satellite Data and Machine Learning Algorithms for Air Quality Index Prediction in Tehran: A Comprehensive Study on Factors Influencing Air Quality. EGUGA, 4506. https://doi.org/10.5194/EGUSPHERE-EGU24-4506
Kamalan, H., Sabour, M., & Shariatmadari, N. (2011). A review on available landfill gas models. Journal of Environmental Science and Technology, 4(2). https://doi.org/10.3923/jest.2011.79.92
Kamali, N., Zare Shahne, M., & Arhami, M. (2015). Implementing Spectral Decomposition of Time Series Data in Artificial Neural Networks to Predict Air Pollutant Concentrations. Https://Home.Liebertpub.Com/Ees, 32(5), 379–388. https://doi.org/10.1089/EES.2014.0350
Management of Low Levels of Landfill Gas | Environmental Protection Agency. (2013). Retrieved 19 September 2025, from https://www.epa.ie/publications/compliance--enforcement/waste/management-of-low-levels-of-landfill-gas.php
Mann, J. H. (2001). Chapter 2: Landfill Gas Basics. Landfill Gas Primer, An Overview for Environmental Health Professionals.
Mokhtari, M., Ebrahimi, A., & Rezaeinia, S. (2020). Prediction of Greenhouse Gas Emissions in Municipal Solid Waste Landfills Using LandGEM and IPCC Methods in Yazd, Iran. Journal of Environmental Health and Sustainable Development, 5(4), 1155–1161. https://doi.org/10.18502/JEHSD.V5I4.4964
Rahman, M. M. (2024). The Potential of Biomethane produced from Waste Landfill to Supplement Renewable Energy in Saudi Arabia. Engineering, Technology & Applied Science Research, 14(6), 18264–18270. https://doi.org/ 10.48084/ETASR.8985
Rezaee E, Abolhasani MH. (2018). Evaluation of landfill gas generation for exploitation energy (case study: landfill of shahinshahr). Iranian Journal of Research in Environmental Health. Fall 2018; 4 (3): 204-214. doi: 10.22038/jreh.2018.32776.1227 [In Persian]
Rodrigue, K. A., Essi, K., Cyril, K. M., & Albert, T. (2018). Estimation of Methane Emission from Kossihouen Sanitary Landfill and Its Electricity Generation Potential (Cô te d’Ivoire). Journal of Power and Energy Engineering, 06(07). https://doi.org/10.4236/jpee.2018.67002
Rupani, P. F., Delarestaghi, R. M., Abbaspour, M., Rupani, M. M., EL-Mesery, H. S., & Shao, W. (2019). Current status and future perspectives of solid waste management in Iran: a critical overview of Iranian metropolitan cities. In Environmental Science and Pollution Research (Vol. 26, Issue 32). https://doi.org/10.1007/s11356-019-06456-5
Shahne, M. Z., Arhami, M., Hosseini, V., & Al Haddad, E. (2022). Particulate emissions of real-world light-duty gasoline vehicle fleet in Iran. Environmental Pollution, 292, 118303. https://doi.org/10.1016/J.ENVPOL.2021.118303
Shahne, M. Z., & Arhami, M. (2023). Toxicity of PM2.5 sources based on their chemical profile using source apportionment results in Tehran, Iran. Journal of Environmental Studies, 49(1), 1–16. https://doi.org/10.22059/ JES.2023.339901.1008294
Talaiekhozani, A., & Nasiri, A. (2022). The Modeling of Carbon Dioxide, Methane and Non-Methane Organic Gases Emission Rates in Solid Waste Landfill in City of Jahrom, Iran. SSRN Electronic Journal. https://doi.org/ 10.2139/ssrn.3968310
Thompson, S., Sawyer, J., Bonam, R., & Valdivia, J. E. (2009). Building a better methane generation model: Validating models with methane recovery rates from 35 Canadian landfills. Waste Management, 29(7). https://doi.org/ 10.1016/j.wasman.2009.02.004
Waste Management Organization of Tehran Municipality. 2023. [In Persian]
Zare Shahne, M., Noori, A., & Alizade Attar, M. (2024). Air Pollution Variation During COVID-19 Pandemic Using Satellite and On-site Measurement Data in Six Provinces in Iran. Numerical Methods in Civil Engineering, 9(2), 86–97. https://doi.org/10.61186/NMCE.2407.1067
Zare Shahne, M., & Arhami, M. (2016). STUDY OF TEMPORAL COMPONENTS OF CARBON MONOXIDE CONCENTRATION AND METEOROLOGICAL VARIABLES IN TEHRAN. Sharif Journal of Civil Engineering, 32.2(1.1), 35–41. https://sjce.journals.sharif.edu/article_984_en.html
Zoqi, M. J., & Doosti, M. R. (2018). An approach towards designing a new sanitary landfill system for treatment of emissions from decomposition in urban gas network. Journal of Environmental Science and Technology. [In Persian]
 
Journal of Environmental Studies
Volume 51, Issue 2
September 2025
Pages 165-188

Files

Share

How to cite

Statistics