Abstract
With the continuous progress of human production and life, air quality has become the focus of attention. In this paper, Beijing, Tianjin, Hebei, Shanxi, Shandong and Henan provinces were taken as the study area, where there are 58 air quality monitoring stations from which daily and monthly data are obtained. Firstly, the temporal characteristics of the air quality index (AQI) are explored. Then, the spatial distribution of the AQI is mapped by the inverse distance weighted (IDW) method, the ordinary kriging (OK) method and the Bayesian maximum entropy (BME) method. Additionally, cross-validation is utilized to evaluate the mapping results of these methods with two indexes: mean absolute error and root mean square interpolation error. Furthermore, the correlation analysis of meteorological factors, including precipitation anomaly percentage, precipitation, mean wind speed, average temperature, average water vapor pressure and average relative humidity, potentially affecting the AQI was carried out on both daily and monthly scales. In the study area and period, AQI shows a clear periodicity, although overall, it has a downward trend. The peak of AQI appeared in November, December and January. BME interpolation has a higher accuracy than OK. IDW has the maximum error. Overall, the AQI of winter (November), spring (February) is much worse than summer (May) and autumn (August). Additionally, the air quality has improved during the study period. The most polluted areas of air quality are concentrated in Beijing, the southern part of Tianjin, the central-southern part of Hebei, the central-northern part of Henan and the western part of Shandong. The average wind speed and average relative humidity have real correlation with AQI. The effect of meteorological factors such as wind, precipitation and humidity on AQI is putative to have temporal lag to different extents. AQI of cities with poor air quality will fluctuate greater than that of others when weather changes and has higher correlation with meteorological factors.
Highlights
Nowadays, with the development of the social economy and the impact of human production and life, environmental problems are becoming more and more serious; urban air quality is getting worse and worse; and it is urgent to study and solve the problem of air quality [1,2]
Considering that the search diameter should be less than half of the study area, we look for the optimal parameters in [2, 3.5]
The mid-eastern China of Beijing, Tianjin, Hebei, Shanxi, Shandong and Henan provinces were taken as the study area
Summary
With the development of the social economy and the impact of human production and life, environmental problems are becoming more and more serious; urban air quality is getting worse and worse; and it is urgent to study and solve the problem of air quality [1,2]. It is a substitute for the air pollution index after the second half of the year 2012. AQI is based on the comprehensive assessment of six pollutants: sulfur dioxide, nitrogen dioxide, PM10, PM2.5, ozone and carbon monoxide, as stipulated by the Chinese government’s Ambient Air Quality Standard (GB3095-2012); see [13]. Time series analysis is an important method to study the temporal characteristics of air quality, while spatial interpolation is a primary method for exploring its spatial patterns. AQI takes the maximum of the six IAQI (individual air quality index) values (SO2, NO2, PM10, PM2.5, O3, CO). The monitoring network is composed of 23 ground-based monitoring sites scattered around the entire study area These meteorological data are abstracted from the daily dataset of China Ground International Exchange Stations. When we use the data before November 2014 to perform the spatial interpolation, we only use the data of complete data stations
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