Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis

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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 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
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
https://www.mdpi.com/1660-4601/17/1/360/htm##ijerph-17-00360-t002
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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