Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms
A genetic algorithm is paired with a Lagrangian puff atmospheric model to reconstruct the source characteristics of an atmospheric release. Observed meteorological and ground concentration measurements from the real-world Dipole Pride controlled release experiment are used to test the methodology. A...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2017-02-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2017.1300005 |
| _version_ | 1797684882770493440 |
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| author | Alessio Petrozziello Guido Cervone Pasquale Franzese Sue Ellen Haupt Raffaele Cerulli |
| author_facet | Alessio Petrozziello Guido Cervone Pasquale Franzese Sue Ellen Haupt Raffaele Cerulli |
| author_sort | Alessio Petrozziello |
| collection | DOAJ |
| description | A genetic algorithm is paired with a Lagrangian puff atmospheric model to reconstruct the source characteristics of an atmospheric release. Observed meteorological and ground concentration measurements from the real-world Dipole Pride controlled release experiment are used to test the methodology. A sensitivity study is performed to quantify the relative contribution of the number and location of sensor measurements by progressively removing them. Additionally, the importance of the meteorological measurements is tested by progressively removing surface observations and vertical profiles. It is shown that the source term reconstruction can occur also with limited meteorological observations. The proposed general methodology can be applied to reconstruct the characteristics of an unknown atmospheric release given limited ground and meteorological observations. |
| first_indexed | 2024-03-12T00:37:11Z |
| format | Article |
| id | doaj.art-7243d2faaf9d4e5a998adba2bc6414da |
| institution | Directory Open Access Journal |
| issn | 0883-9514 1087-6545 |
| language | English |
| last_indexed | 2024-03-12T00:37:11Z |
| publishDate | 2017-02-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Artificial Intelligence |
| spelling | doaj.art-7243d2faaf9d4e5a998adba2bc6414da2023-09-15T09:33:55ZengTaylor & Francis GroupApplied Artificial Intelligence0883-95141087-65452017-02-0131211913310.1080/08839514.2017.13000051300005Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic AlgorithmsAlessio Petrozziello0Guido Cervone1Pasquale Franzese2Sue Ellen Haupt3Raffaele Cerulli4The Pennsylvania State UniversityThe Pennsylvania State UniversityEcology and the EnvironmentNational Center for Atmospheric ResearchUniversity of SalernoA genetic algorithm is paired with a Lagrangian puff atmospheric model to reconstruct the source characteristics of an atmospheric release. Observed meteorological and ground concentration measurements from the real-world Dipole Pride controlled release experiment are used to test the methodology. A sensitivity study is performed to quantify the relative contribution of the number and location of sensor measurements by progressively removing them. Additionally, the importance of the meteorological measurements is tested by progressively removing surface observations and vertical profiles. It is shown that the source term reconstruction can occur also with limited meteorological observations. The proposed general methodology can be applied to reconstruct the characteristics of an unknown atmospheric release given limited ground and meteorological observations.http://dx.doi.org/10.1080/08839514.2017.1300005 |
| spellingShingle | Alessio Petrozziello Guido Cervone Pasquale Franzese Sue Ellen Haupt Raffaele Cerulli Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms Applied Artificial Intelligence |
| title | Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms |
| title_full | Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms |
| title_fullStr | Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms |
| title_full_unstemmed | Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms |
| title_short | Source Reconstruction of Atmospheric Releases with Limited Meteorological Observations Using Genetic Algorithms |
| title_sort | source reconstruction of atmospheric releases with limited meteorological observations using genetic algorithms |
| url | http://dx.doi.org/10.1080/08839514.2017.1300005 |
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