Evolutionary lagrangian inverse modeling for PM 10 pollutant dispersion

Alejandro Peña, Jesús A. Hernández, María Victoria Toro

Research output: Chapter in Book/Report/Conference proceedingBook chapter as a result of researchpeer-review

2 Scopus citations


One of the main concerns when it comes to mitigating the effects of the concentration of the particulate matter PMx in an area of study is the fact to determine its behavior over time, overcoming both physical and mathematical limitations in terms of a phenomenon of dispersion. Therefore, this chapter develops and analyzes a model based on the principles of evolutionary computation (EC) in order to determine the space-time behavior of the concentration of the particulate matter PMx in a study area. The proposed model has three submodels within an integrated solution, which constitute the individual to evolve. The transformation of the possible solutions or generational population is made by using an asynchronous evolutionary model, due to genetic dependency between substructures. The proposed model was validated for configurations of n sources of emissions and m monitoring stations that measure the quality of the air in a study area.

Original languageEnglish
Title of host publicationSoft Computing Methods for Practical Environment Solutions
Subtitle of host publicationTechniques and Studies
PublisherIGI Global
Number of pages20
ISBN (Print)9781615208937
StatePublished - 2010
Externally publishedYes


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