Spatiotemporal evolution and the driving factors of PM2.5 in Chinese urban agglomerations between 2000 and 2017

https://doi.org/10.1016/j.ecolind.2021.107491Get rights and content
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Highlights

  • Dynamic time warping was used to cluster the concentration change pattern.

  • Geographical detector method was used to quantify the driving force.

  • Spatial correlation appears at the scale of urban agglomeration.

  • Temperature and air pressure are the most important meteorological driving factors.

  • Population density and road density are the most important anthropogenic driving factors.

Abstract

Fine particulate matter (PM2.5) threatens public health severely, which, luckily, can be governed by referring to its spatiotemporal distribution and key driving factors. However, very few explored it in the long-term, broadly, and systematically. In this study, nine Chinese key urban agglomerations were targeted to explore the spatial distribution of PM2.5 and the evolution of its major driving factors from 2000 to 2017. Spatiotemporal distribution and change tendency were evaluated by spatial autocorrelation analysis and dynamic time warping (DTW), and the entire research period was divided into four stages according to the evaluation. Subsequently, the geographical detector method (GDM) was adopted to quantify the relationship between anthropogenic and meteorological factors with PM2.5 concentration in the entire period and sub-stages. As the findings indicate: 1) In 2000–2017, PM2.5 concentration increased firstly in all agglomerations and then declined by fluctuation; it was mainly gathered in the plain areas where the core cities of urban agglomerations were located, with the highest concentration in North China. 2) Variation of PM2.5 concentration appeared similar tendency and regional aggregation, e.g., five urban agglomerations around the central plains urban agglomeration (CPUA) had similar patterns. 3) The Driving factors of PM2.5 showed noticeable spatiotemporal differences. It is indicated that the critical meteorological factors refer to temperature and air pressure, while the key anthropogenic factors are population density (PD) and road density (RD). Except for the population density showing a relatively persistent high influence on urban agglomeration, especially significant in northern China, the rest of the anthropogenic factors represented different characteristics. Specifically, the proportion of secondary industry (PSP) and gross domestic product per capita (GDPP) showed relatively strong effects in the early stage but weakening dramatically in the later stage. Foreign direct investment (FI) increased in developed urban agglomerations in the entire stage while showed a downward trend in underdeveloped cities. Road density was enhanced dramatically in the early stage but weakened slowly in the later stage. The findings reveal the change tendency of PM2.5 concentration in urban agglomerations and the evolution of its driving factors, which help the Chinese government adopt effective strategies to cope with pollution.

Keywords

PM2.5
Spatiotemporal evolution
Driving factors
Geographical detector
Dynamic time warping

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These authors contributed equally to this work.