Abstract
To analyze the relationship between air quality index (AQI) and housing price, six relationship indexes between air quality index and housing price were calculated using grey spectrum theory, specifically grey association spectrum, grey cospectrum, grey amplitude spectrum, grey phase spectrum, grey lag time length, and grey condense spectrum. Three main change periods were extracted. There was a negative correction between the air quality and the housing price in Handan. The results provide a basis for the government’s measures to prevent haze.
Highlights
Housing prices have been driven by land price and have had a strong e ect on land price [1]. e increase in population is expected to reduce the land area per capita, resulting in the rise of housing price [2]. ere are commercial housing and social housing in China, and commercial housing has been the focus of most research works [3]
Analysis of factors related to air pollution is the key to haze control. e relationship between outdoor air pollution and sick building syndrome symptoms is researched [11]. e problem of air pollution has been taken seriously in recent years in China, and equipment to measure air quality have
Scholars have performed further research projects. e traditional grey model has been used to provide particulate matter information for the roadside inhabitants [13]. e grey model with fractional order accumulation has been used to predict air quality [14], and grey relational analysis has been used to determine whether carbon price has multiple timescales [15]
Summary
We selected a city in southern Hebei Province, Handan. AQI and housing price were here analyzed from April 2015 to December 2018. e AQI data were collected from China’s air quality online monitoring platform [19]. The three main periods in Handan AQI were extracted. E first period of Handan housing price lasted 20 months; the second 10 months; and the third 2.86 months. –0.04 Figure 6: Grey association spectrum analysis of AQI and housing price. –1.5 Figure 8: Grey phase spectrum of AQI and housing price. E calculated results of grey condense spectrum are shown in Figure 10 and Table 1. E highest grey condense spectrum values were 2.86 months, 10 months, and 3.33 months and the amplitude of these were 0.0403, − 0.0201, and 0.0182. E calculated results of grey condense spectrum are shown in Figure 10 and Table 1. e highest grey condense spectrum values were 2.86 months, 10 months, and 3.33 months and the amplitude of these were 0.0403, − 0.0201, and 0.0182. ese results show that AQI and housing price fluctuated closely across a 2- to 10-month period
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