@Article{RobertiAnfoCampDegr:2013:EnApEm,
               author = "Roberti, D{\'e}bora R and Anfossi, Domenico and Campos Velho, 
                         Haroldo Fraga de and Degrazia, Gerv{\'a}sio Annes",
          affiliation = "Department of Physics, Federal University of Santa Maria (UFSM), 
                         Santa Maria, 97105-900, Brazil and {} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and Department of Physics, Federal 
                         University of Santa Maria (UFSM), Santa Maria, 97105-900, Brazil",
                title = "Entropic approach for emission rate estimation of area pollutant 
                         sources",
              journal = "American Journal of Environmental Engineering",
                 year = "2013",
               volume = "3",
               number = "1",
                pages = "56--62",
             keywords = "atmospheric pollutant, source identification, inverse problems, 
                         entropic regularization.",
             abstract = "The estimation of the area source pollutant strength is a relevant 
                         issue for atmospheric environment. This characterizes an inverse 
                         problem in the atmospheric pollution dispersion. In the inverse 
                         analysis, an area source domain is considered, where the strength 
                         of such area source term is assumed unknown. The inverse problem 
                         is formulated as a non-linear optimization approach, whose 
                         objective function is given by the square difference between the 
                         measured pollutant concentration and the mathematical models, 
                         associated with a regularization operator. The forward problem is 
                         addressed by a source-receptor scheme, where a regressive 
                         Lagrangian model is applied to compute the transition matrix. A 
                         quasi-Newton method is employed for minimizing the objective 
                         function. The second order maximum entropy regularization is used, 
                         and the regularization parameter is calculated by the L-curve 
                         technique. This inverse problem methodology is tested with 
                         synthetic observational data, producing good inverse solutions.",
                  doi = "1 0.5923/j. ajee .20130301.08",
                  url = "http://dx.doi.org/1 0.5923/j. ajee .20130301.08",
                 issn = "2166-4633 and 2166-465X",
                label = "lattes: 5142426481528206 3 RobertiAnfoCampDegr:2013:EnApEm",
             language = "en",
           targetfile = "10.5923.j.ajee.20130301.08.pdf",
                  url = "http://article.sapub.org/10.5923.j.ajee.20130301.08.html",
        urlaccessdate = "27 abr. 2024"
}