The Grey Relational Analysis of Chemical Elements in Atmospheric Fine Particles(PM2.5)

The main cause of haze is atmospheric fine particles PM2.5. This is very important to research the evolution characteristics of physical chemistry about PM2.5, especially the persistent observation for PM2.5. This paper used the Grey Relational Method to analyze the correlation between PM2.5 and other air quality index in this paper. The study concludes the influence of between PM2.5 and other indicators.

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Air quality changes and Grey relational analysis of pollutants exceeding standards during the COVID-19 pandemic in Wuhan

10.21203/rs.3.rs-34041/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Junhong Ji ◽

Runqi Chang

Keyword(s):

Air Quality ◽

Grey Relational Analysis ◽

Future Research ◽

Quality Changes ◽

The Past ◽

Relational Analysis ◽

The World ◽

New Ideas ◽

The Individual ◽

Grey Relational

Abstract The COVID-19 has spread widely around the world, and the air quality during that period has changed significantly. On the contrary, air quality also can affect the development of the pandemic. Therefore, it is pretty necessary to study air quality changes during the pandemic. This paper achieves this goal by applying the Over-standard multiples method and Grey relational analysis to study the individual and overall change trends of pollutants in Wuhan during the same period in the past seven years. The result shows that the concentrations of SO2 and O3 increased affected by the pandemic but still meet the standard. However, the pandemic promoted a decrease in PM2.5, PM10, and NO2 concentrations, but it had just reached the standard or even exceeded the standard. This article discussed the feasibility of using Grey relational analysis to analyze pollutants exceeding the standard from an overall perspective and provided new ideas for future research.

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The Impact of Air Quality on Inbound Tourist Arrivals over China Based on Grey Relational Analysis

Sustainability ◽

10.3390/su131910972 ◽

2021 ◽

Vol 13 (19) ◽

pp. 10972

Author(s):

Wei Zhang ◽

Ziqiang Liu ◽

Yujie Zhang ◽

Elly Yaluk ◽

Li Li

Keyword(s):

Air Pollution ◽

Air Quality ◽

Quality Indicators ◽

Grey Relational Analysis ◽

Pollution Index ◽

Ambient Air ◽

Relational Analysis ◽

Grey Relational ◽

The Impact ◽

Relational Order

Air pollution has a significant impact on tourism; however, research in this area is still limited. In this study, we applied grey relational analysis to panel data from 31 provinces in China and evaluated the relationship between air quality and inbound tourist arrivals. The study focused on provincial-level disparities for the different key air quality evaluation standards during 2009–2012 and 2013–2019. For instance, we considered PM10, SO2, NO2 and the excellent and good ratings of Air Pollution Index (API) during 2009–2012 and the additional PM2.5, CO, O3 and the excellent and good ratings of Air Quality Index (AQI) from 2013 to 2019. Results indicate that: (1) Inbound tourist arrivals are significantly and positively affected by ambient air quality, and the impact from 2013 to 2019 was greater than that from 2009 to 2012; (2) there is regional diversity in inbound tourist arrivals, and the impact of the different air quality indicators varies; (3) inbound tourists showed greater sensitivity to air pollution under the AQI standard; (4) the impact of air quality indicators on the inbound tourist arrivals shows grey relational order, and the concentration of PM2.5, PM10 and SO2 have less impact than NO2, CO and O3 on changes in tourism numbers; (5) consistency in the air quality impact on foreign tourists and compatriot tourists from HK, MO and TW varies by air quality indicators. This study highlights the need for appropriate measures to improve air quality for high-quality and sustainable development of inbound tourism.

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