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The Comparison of Lagrangian and Gaussian Models in Predicting of Air Pollution Emission Using Experimental Study, a Case Study: Ammonia Emission

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Abstract

Ammonia, as a colorless gas with a sharp odor, is considered as one of the created odors in the composting and landfill of solid waste. We used experimental data to study the robustness of AERMOD and the forward Lagrangian stochastic (FLS) in predicting ammonia emission in short range. The study area was Kahrizak landfill and composting plants, Tehran, Iran. The boundary layer parameters for the FLS were calculated on the basis of mean values of temperature, wind speed, and direction. While, the boundary layers of AERMOD were computed on the basis of exact meteorological data. The results depicted that AERMOD prediction at distances less than 1000 m from the sources and the locations inside the sources were poor. However, the results of FLS indicated more agreement with the field measurement, which the coefficient of determination was 0.83. Both models predicted, in the distance of 2000 m from the source, the ammonia concentration would be insignificant.

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Acknowledgments

We wish to acknowledge Mr. Ernest Rammel’s assistance in editing our manuscript. In addition, the authors would like to thank Mr. Arman DaneshiKohani for his help in the preparation of this article.

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Authors and Affiliations

  1. Kharazmi University, Tehran, Iran

    Mohsen Asadi & Gholamreza Asadollahfardi

  2. Iran University of Science and Technology, Tehran, Iran

    Hossayn Fakhraee

  3. University of Tehran, Tehran, Iran

    Mohsen Mirmohammadi

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  1. Mohsen Asadi
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  2. Gholamreza Asadollahfardi
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  3. Hossayn Fakhraee
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  4. Mohsen Mirmohammadi
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Correspondence to Mohsen Mirmohammadi.

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Asadi, M., Asadollahfardi, G., Fakhraee, H. et al. The Comparison of Lagrangian and Gaussian Models in Predicting of Air Pollution Emission Using Experimental Study, a Case Study: Ammonia Emission. Environ Model Assess 22, 27–36 (2017). https://doi.org/10.1007/s10666-016-9512-8

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