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A platform for research: civil engineering, architecture and urbanism
Spatial statistics of atmospheric particulate matter in China
https://orcid.org/0000-0003-1401-0691
https://orcid.org/0000-0002-2011-9215
Abstract In this paper, the spatial dynamics of the atmospheric particulate matters (resp. PM10 and PM2.5) are studied using turbulence methodologies. It is found experimentally that the spatial correlation function ρ(r) shows a log-law on the mesoscale range, i.e., 50 ≤ r ≤ 500 km, with an experimental scaling exponent β = 0.45. The spatial structure function shows a power-law behavior on the mesoscale range 90 ≤ r ≤ 500 km. The experimental scaling exponent is convex, showing that the intermittent correction is relevant in characterizing the spatial dynamic of particulate matter. The measured singularity spectrum f(α) also shows its multifractal nature. Experimentally, the particulate matter is more intermittent than the passive scalar, which could be partially due to the mesoscale movements of the atmosphere, and also due to local sources, such as local industry activities.
Highlights Particulate matter concentrations in China were studied in a multiscale view. Logarithm spatial correlation pattern was retrieved experimentally. Multifractality nature was identified.
Spatial statistics of atmospheric particulate matter in China
https://orcid.org/0000-0003-1401-0691
https://orcid.org/0000-0002-2011-9215
Abstract In this paper, the spatial dynamics of the atmospheric particulate matters (resp. PM10 and PM2.5) are studied using turbulence methodologies. It is found experimentally that the spatial correlation function ρ(r) shows a log-law on the mesoscale range, i.e., 50 ≤ r ≤ 500 km, with an experimental scaling exponent β = 0.45. The spatial structure function shows a power-law behavior on the mesoscale range 90 ≤ r ≤ 500 km. The experimental scaling exponent is convex, showing that the intermittent correction is relevant in characterizing the spatial dynamic of particulate matter. The measured singularity spectrum f(α) also shows its multifractal nature. Experimentally, the particulate matter is more intermittent than the passive scalar, which could be partially due to the mesoscale movements of the atmosphere, and also due to local sources, such as local industry activities.
Highlights Particulate matter concentrations in China were studied in a multiscale view. Logarithm spatial correlation pattern was retrieved experimentally. Multifractality nature was identified.
Spatial statistics of atmospheric particulate matter in China
https://orcid.org/0000-0003-1401-0691
https://orcid.org/0000-0002-2011-9215
Abstract In this paper, the spatial dynamics of the atmospheric particulate matters (resp. PM10 and PM2.5) are studied using turbulence methodologies. It is found experimentally that the spatial correlation function ρ(r) shows a log-law on the mesoscale range, i.e., 50 ≤ r ≤ 500 km, with an experimental scaling exponent β = 0.45. The spatial structure function shows a power-law behavior on the mesoscale range 90 ≤ r ≤ 500 km. The experimental scaling exponent is convex, showing that the intermittent correction is relevant in characterizing the spatial dynamic of particulate matter. The measured singularity spectrum f(α) also shows its multifractal nature. Experimentally, the particulate matter is more intermittent than the passive scalar, which could be partially due to the mesoscale movements of the atmosphere, and also due to local sources, such as local industry activities.
Highlights Particulate matter concentrations in China were studied in a multiscale view. Logarithm spatial correlation pattern was retrieved experimentally. Multifractality nature was identified.
Spatial statistics of atmospheric particulate matter in China
Gao, Shenghui (author) / Wang, Yangjun (author) / Huang, Yongxiang (author) / Zhou, Quan (author) / Lu, Zhiming (author) / Shi, Xiang (author) / Liu, Yulu (author)
Atmospheric Environment ; 134 ; 162-167
2016-03-29
6 pages
Article (Journal)
Electronic Resource
English
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