基于点和场浓度测量的城市尺度空气污染的贝叶斯源识别

IF 2.1 3区地球科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computational Geosciences Pub Date : 2023-06-18 DOI:10.1007/s10596-023-10206-5

Elissar Al Aawar, Samah El Mohtar, I. Lakkis, A. K. Alduwais, I. Hoteit

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Bayesian source identification of urban-scale air pollution from point and field concentration measurements

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来源期刊

Computational Geosciences 地学-地球科学综合

CiteScore

6.10

自引率

4.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing. Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered. The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.