Minimization of model representativity errors in identification of point source emission from atmospheric concentration measurements-Reference-Cited by-同舟云学术

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Minimization of model representativity errors in identification of point source emission from atmospheric concentration measurements

Published:2017-11 Issue: Volume:169 Page:267-277
ISSN:1352-2310
Container-title:Atmospheric Environment
language:en
Short-container-title:Atmospheric Environment

Author:

Sharan Maithili,Singh Amit Kumar,Singh Sarvesh Kumar

Funder

Indo-French Centre for Applied Mathematics

DST-SERB, Govt. of India

CSIR, Govt. of India

Publisher

Elsevier BV

Subject

Atmospheric Science,General Environmental Science

Reference35 articles.

1. Source characterization of atmospheric releases using stochastic search and regularized gradient optimization;Addepalli;Inverse Problems Sci. Eng.,2011

2. Source characterization with a genetic algorithmcoupled dispersionbackward model incorporating scipuff;Allen;J. Appl. Meteorology Climatol.,2007

3. Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system;Anderson;J. Atmos. Sci.,2005

4. Reconstruction of an atmospheric tracer source using the principle of maximum entropy-i: Theory;Bocquet;Q. J. R. Meteorological Soc.,2005

5. Bayesian design of control space for optimal assimilation of observations. part i: consistent multiscale formalism;Bocquet;Q. J. R. Meteorological Soc.,2011

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of AERMOD for the identification of a point-source release in the FFT-07 experiment;Air Quality, Atmosphere & Health;2021-01-08

2. Investigating the impacts of atmospheric diffusion conditions on source parameter identification based on an optimized inverse modelling method;Atmospheric Environment;2019-05

3. Accountability of wind variability in AERMOD for computing concentrations in low wind conditions;Atmospheric Environment;2019-04

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