Journal of Geographical Sciences >
Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants
Author: Zhang Xiaoping, PhD and Associate Professor, specialized in regional sustainable development. E-mail: zhangxp@ucas.ac.cn
Received date: 2017-05-31
Accepted date: 2017-11-18
Online published: 2018-03-30
Supported by
National Natural Science Foundation of China, No.41771133
Science and Technology Service (STS) Program of Chinese Academy of Sciences, No.KFJ-EW-STS-089
Copyright
Ambient air pollution brought by the rapid economic development and industrial production in China has exerted a significant influence on socio-economic activities and public health, especially in the densely populated urban areas. Therefore, scientific examination of regional variation of urban air quality and its dominant factors is of great importance to regional environmental management. Based on daily air quality index (AQI) datasets spanning from 2014 to 2016, this study analysed the spatiotemporal characteristics of air quality across different regions throughout China and ascertained the determinants of urban air quality in disparate regions. The main findings are as follows: (1) The annual average value of the urban AQI in China decreased from 2014 to 2016, indicating a desirable trend in air quality at the national scale. (2) The attainment rate of the urban AQI exhibited an apparent spatially stratified heterogeneity, wherein North China retained a high AQI value. The increase of Moran’s I Index reported an apparent spillover effect among adjacent regions. (3) Both at the national and regional scales, the seasonal tendency of air quality in each year is similar, wherein good in summer and relatively poor in winter. (4) Results drawn from the Geographic Detector analysis show that dominant factors influencing AQI vary significantly across urban agglomerations. Topographical and meteorological variations in urban areas may lead to complex spatiotemporal variations in pollutant concentration. Whereas given the same natural conditions, the human-dominated factors, such as industrial structure and urban form, exert significant impacts on urban air quality.The spatial spillover effects and regional heterogeneity of urban air quality illustrated in this study suggest the governments and institutions should set priority to the importance of regional cooperation and collaboration in light of environment regulation and pollution prevention.
ZHANG Xiaoping , GONG Zezhou . Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants[J]. Journal of Geographical Sciences, 2018 , 28(5) : 563 -578 . DOI: 10.1007/s11442-018-1491-z
Figure 1 The location of the study area (a) and sample cities (b) |
Figure 2 The daily AQI average of sample cities in China in 2014, 2015, and 2016 |
Figure 3 The spatial distribution of the attainment rate for the annually averaged AQI in China |
Figure 4 Global autocorrelation of AQI for China in 2014, 2015, and 2016 |
Figure 5 Spatial agglomeration variation of annual AQI in China |
Table 1 Description of regional divisions in China |
Region | Province | Number of city (2014) | Number of city (2015 and 2016) |
---|---|---|---|
A | Nationwide | 161 | 366 |
B | Heilongjiang, Jilin, Liaoning | 16 | 37 |
C | Beijing, Tianjin, Hebei | 13 | 13 |
D | Shanghai, Jiangsu, Zhejiang | 25 | 39 |
E | Hubei, Hunan, Anhui, Jiangxi | 14 | 54 |
F | Guangdong, Guangxi, Fujian, Hainan | 30 | 46 |
G | Sichuan, Guizhou, Yunnan, Chongqing, Tibet | 15 | 54 |
H | Gansu, Shaanxi, Qinghai, Ningxia, Xinjiang, Inner Mongolia | 19 | 65 |
I | Shandong, Shanxi, Henan | 29 | 58 |
Figure 6 Monthly variations of AQI among different regions of China for 2014, 2015, and 2016 |
Figure 7 Determinants diagram of urban air quality |
Table 2 Impact factor partitions for the identified geographical factors |
Indices | First-grade | Second-grade | Third-grade | Fourth-grade | Fifth-grade |
---|---|---|---|---|---|
X1 (104 per) | <200 | 200-400 | 400-700 | 700-1000 | >1000 |
X2 (%) | <4 | 4-10 | 10-18 | 18-33 | >33 |
X3 (104 yuan) | <3 | 3-5 | 5-7.5 | 7.5-12 | >12 |
X4 (102) | <7 | 7-15 | 15-25 | 25-45 | >45 |
X5 (102 hm2) | <15 | 15-25 | 25-40 | 40-80 | >80 |
X6 (103 t) | <19 | 19-23 | 23-42 | 42-130 | >130 |
X7 (104 t) | <3 | 3-6 | 6-10 | 10-16 | >16 |
X8 (°) | <0.1 | 0.1-0.5 | 0.5-1.5 | 1.5-3.5 | >3.5 |
X9 (%) | <50 | 50-60 | 60-70 | 70-75 | >75 |
X10 (102 mm) | <4.5 | 4.5-7.5 | 7.5-10 | 10-15 | >15 |
X11 (m/s) | <1.4 | 1.4-1.8 | 1.8-2.2 | 2.2-2.6 | >2.6 |
X12 (℃) | <7 | 7-11 | 11-15 | 15-19 | >19 |
Figure 8 Spatial distribution of the 12 detected factors |
Table 3 Significance test of different factors affecting the urban AQI in China (Region A) |
X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 | X10 | X11 | X12 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
X1 | ||||||||||||
X2 | N | |||||||||||
X3 | N | N | ||||||||||
X4 | N | N | N | |||||||||
X5 | N | N | N | N | ||||||||
X6 | N | N | N | N | N | |||||||
X7 | N | N | Y | N | N | N | ||||||
X8 | N | N | N | N | N | N | N | |||||
X9 | N | N | Y | N | N | N | N | N | ||||
X10 | Y | Y | Y | Y | Y | Y | N | Y | N | |||
X11 | N | N | N | N | N | N | N | N | N | N | ||
X12 | Y | Y | Y | Y | Y | Y | Y | Y | Y | N | Y |
Table 4 Geographically determined weights of the factors affecting the urban AQI in the study area |
Factors | P value | ||||||||
---|---|---|---|---|---|---|---|---|---|
A | B | C | D | E | F | G | H | I | |
X1 | 0.1228 | 0.2636 | 0.4115 | 0.2606 | 0.1194 | 0.1440 | 0.2166 | 0.0907 | 0.1765 |
X2 | 0.1312 | 0.3477 | 0.0736 | 0.1213 | 0.1568 | 0.1759 | 0.1716 | 0.0448 | 0.1071 |
X3 | 0.0298 | 0.5177 | 0.4911 | 0.1972 | 0.0688 | 0.0830 | 0.1973 | 0.1315 | 0.1514 |
X4 | 0.1272 | 0.2982 | 0.8172 | 0.5873 | 0.1350 | 0.1104 | 0.1298 | 0.0447 | 0.4137 |
X5 | 0.1307 | 0.2824 | 0.3109 | 0.2576 | 0.0771 | 0.0421 | 0.5025 | 0.1660 | 0.2235 |
X6 | 0.1599 | 0.3471 | 0.3368 | 0.4776 | 0.0162 | 0.0134 | 0.0924 | 0.1616 | 0.0491 |
X7 | 0.1889 | 0.4813 | 0.1442 | 0.3482 | 0.0182 | 0.2016 | 0.0981 | 0.0888 | 0.0450 |
X8 | 0.1315 | 0.0705 | 0.2278 | 0.1232 | 0.1490 | 0.0442 | 0.4818 | 0.0145 | 0.2327 |
X9 | 0.2168 | 0.2764 | 0.2746 | 0.2559 | 0.1084 | 0.0067 | 0.3129 | 0.0231 | 0.1483 |
X10 | 0.2943 | 0.3289 | 0.0397 | 0.6956 | 0.1880 | 0.0592 | 0.4749 | 0.0575 | 0.0148 |
X11 | 0.1016 | 0.0562 | 0.2641 | 0.2289 | 0.1782 | 0.3815 | 0.4509 | 0.2087 | 0.2351 |
X12 | 0.3436 | 0.2479 | 0.7128 | 0.0077 | 0.1507 | 0.0450 | 0.3834 | 0.0365 | 0.1590 |
Table 5 The top three factors affecting the urban AQI for individual regions |
Region | Factors | P value | Factors | P value | Factors | P value |
---|---|---|---|---|---|---|
A | X12 | 0.3436 | X10 | 0.2943 | X9 | 0.2168 |
B | X3 | 0.5177 | X7 | 0.4813 | X2 | 0.3477 |
C | X4 | 0.8172 | X12 | 0.7128 | X3 | 0.4911 |
D | X10 | 0.6956 | X4 | 0.5873 | X6 | 0.4776 |
E | X10 | 0.1880 | X11 | 0.1782 | X2 | 0.1568 |
F | X11 | 0.3815 | X7 | 0.2016 | X2 | 0.1759 |
G | X5 | 0.5025 | X8 | 0.4818 | X10 | 0.4749 |
H | X11 | 0.2087 | X5 | 0.1660 | X6 | 0.1616 |
I | X4 | 0.4137 | X11 | 0.2351 | X8 | 0.2327 |
The authors have declared that no competing interests exist.
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