Atmospheric movements
; Nonlinear programming
; Adjoint methods
; Atmospheric transport and dispersions
; Inverse modeling
; Non-linear optimization
; Source term estimation
; Inverse problems
; atmospheric pollution
; concentration (composition)
; dispersion
; estimation method
; nonlinearity
; numerical model
; optimization
; paradigm shift
; pollutant source
; pollutant transport
; wind field
; atmospheric dispersion
; atmospheric transport
; dispersion
; genetic algorithm
; pollutant
; pollution transport
; priority journal
; Review
Scopus学科分类:
Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要:
Modeling the downwind hazard area resulting from the unknown release of an atmospheric contaminant requires estimation of the source characteristics of a localized source from concentration or dosage observations and use of this information to model the subsequent transport and dispersion of the contaminant. This source term estimation problem is mathematically challenging because airborne material concentration observations and wind data are typically sparse and the turbulent wind field chaotic. Methods for addressing this problem fall into three general categories: forward modeling, inverse modeling, and nonlinear optimization. Because numerous methods have been developed on various foundations, they often have a disparate nomenclature. This situation poses challenges to those facing a new source term estimation problem, particularly when selecting the best method for the problem at hand. There is, however, much commonality between many of these methods, especially within each category. Here we seek to address the difficulties encountered when selecting an STE method by providing a synthesis of the various methods that highlights commonalities, potential opportunities for component exchange, and lessons learned that can be applied across methods. � 2017 Elsevier Ltd
Aeris LLC, Louisville, CO, United States; Department of Meteorology and Atmospheric Science, Pennsylvania State University, University Park, PA, United States; Research Applications Laboratory, National Center for Atmospheric, Boulder, CO, United States
Recommended Citation:
Bieringer P,E,, Young G,et al. Paradigms and commonalities in atmospheric source term estimation methods[J]. Atmospheric Environment,2017-01-01,156