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A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method.

Xiaoling Ren1, Zhenfu Luo2, Shuyu Qin3

  • 1China University of Mining and Technology-Beijing, Beijing, 100083, China. 378814620@qq.com.

Scientific Reports
|December 3, 2021
PubMed
Summary
This summary is machine-generated.

A new method, ideal grey close function cluster correlation analysis (IGCFCCA), evaluates air quality using monitored data. This study applied IGCFCCA to Ningxia Province, China, classifying air quality into three levels for scientific management.

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Area of Science:

  • Environmental Science
  • Data Analysis
  • Atmospheric Chemistry

Background:

  • Effective air quality evaluation is crucial for public health and environmental management.
  • Existing methods may not fully capture complex air quality dynamics from large datasets.
  • China's air quality standards provide a framework for assessing pollutant levels.

Purpose of the Study:

  • To introduce and validate a novel evaluation method: ideal grey close function cluster correlation analysis (IGCFCCA).
  • To assess the air quality of Ningxia Province, China, using the proposed IGCFCCA method.
  • To provide quantitative correlation degrees for different air quality classifications.

Main Methods:

  • Application of ideal grey close function cluster correlation analysis (IGCFCCA).
  • Selection of key air quality indexes: sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter (PM10, PM2.5), and ozone (O3).
  • Correlation analysis to determine the relationship between classified air quality and China's first-level air quality standard.

Main Results:

  • Air quality in Ningxia Province in 2018 was classified into three distinct levels.
  • Months with relatively poor air quality (March-May) were classified as the first level.
  • Months with better air quality (August-September) were classified as the third level, with other months in the second level.
  • Quantitative correlation degrees were determined: 0.674 (first), 0.697 (second), and 0.71 (third).

Conclusions:

  • The IGCFCCA method provides a scientifically sound approach for evaluating air quality with large datasets.
  • The study successfully classified Ningxia's air quality, offering insights into seasonal variations.
  • Results offer a basis for targeted air quality management strategies and improvements.