Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis
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ID: 265916
2020
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Abstract
Pollutant analysis and pollution source tracing are critical issues in air quality management, in which correlation analysis is important for pollutant relation modeling. A dynamic correlation analysis method was proposed to meet the real-time requirement in atmospheric management. Firstly, the spatio-temporal analysis framework was designed, in which the process of data monitoring, correlation calculation, and result presentation were defined. Secondly, the core correlation calculation method was improved with an adaptive data truncation and grey relational analysis. Thirdly, based on the general framework and correlation calculation, the whole algorithm was proposed for various analysis tasks in time and space, providing the data basis for ranking and decision on pollutant effects. Finally, experiments were conducted with the practical data monitored in an industrial park of Hebei Province, China. The different pollutants in multiple monitoring stations were analyzed crosswise. The dynamic features of the results were obtained to present the variational correlation degrees from the proposed and contrast methods. The results proved that the proposed dynamic correlation analysis could quickly acquire atmospheric pollution information. Moreover, it can help to deduce the influence relation of pollutants in multiple locations.
| Reference Key |
bai2020internationaldynamic
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| Authors | Yu-ting Bai;Xue-bo Jin;Xiao-yi Wang;Xiao-kai Wang;Ji-ping Xu;Bai, Yu-ting;Jin, Xue-bo;Wang, Xiao-yi;Wang, Xiao-kai;Xu, Ji-ping; |
| Journal | International journal of environmental research and public health |
| Year | 2020 |
| DOI |
10.3390/ijerph17010360
|
| URL | |
| Keywords |
spatio-temporal analysis
correlation degree
air pollution management
pollutant source tracing
National Center for Biotechnology Information
NCBI
NLM
MEDLINE
China
pubmed abstract
nih
national institutes of health
national library of medicine
research support
non-u.s. gov't
algorithms
Evaluation Study
environmental monitoring / methods*
pmid:31948076
pmc6981785
doi:10.3390/ijerph17010360
yu-ting bai
xue-bo jin
ji-ping xu
air pollutants / analysis*
air pollution / analysis*
environmental pollutants
environmental pollution
spatio-temporal analysis*
|
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