**1. Introduction**

Since implementing the reform and opening-up policy in 1978, China has been experiencing a rapid process of social and economic development, attracting worldwide attention [1,2]. With the development of China's urbanization process, the population influx into cities, the consumption of resources and the transformation of the economic structure have caused a variety of social and environmental impacts [3,4]. Among them, air pollution is particularly prominent because it is closely associated with negative health e ffects [5,6].

In recent years, one of the primary pollutants most a ffecting China has been fine particulate matter (PM2.5). PM2.5 refers to small particles or droplets in the air less than 2.5 microns in aerodynamic diameter [7,8]. PM2.5 easily binds to toxic and harmful substances due to its small size, long atmospheric residence time and extensive atmospheric transportation and seriously a ffects human health [9,10]. PM2.5 exposure in 2015 was estimated to result in 8.9 million deaths globally, among which 28% occurred in China [11]. To cope with severe and persistent PM2.5 pollution and to meet pollutant concentration targets [12,13], it is urgen<sup>t</sup> and necessary to explore the influence of human factors on PM2.5 [14–16]. Hao and Liu [17] used a spatial lag model and spatial error model to investigate the socioeconomic influencing factors of urban PM2.5 concentration in China. The results showed that the number of vehicles and the secondary industry had significantly positive e ffects on PM2.5 concentration in cities. Wang et al. [18] found a positive correlation between PM2.5 concentrations and urban area, and population and proportion of secondary industry, and determined the existence of an inverted U-shaped relationship between economic growth and PM2.5 concentration. Existing studies have confirmed the contributions of socioeconomic factors to PM2.5 pollution in China [13,19,20]; however, the dynamic relationships and causal interactions between them are still not well understood, especially in specific regions. The Granger causality test determines the causal relationships between variables based on the chronological order in which the events occurred [21]. The method has been widely used in the empirical analysis of the relationships between energy, environment, economic and social development, etc. [22–24]. As an important administrative unit of a country, "province" usually provides unified and periodic suggestions to the cities under its jurisdiction, but relevant studies at this scale were few. Understanding the principal environmental issues in each stage of development holds grea<sup>t</sup> significance for the formulation and implementation of pollution policy, and also for the improvement of public health in China with PM2.5 as the primary pollutant.

In this paper, the panel data from 2000 to 2015 in Liaoning Province that combine a satellite derived PM2.5 concentration data set and socioeconomic data were established. The panel Granger causality test was used as the main method to quantitatively test the causality among economic growth, urbanization, industrialization and PM2.5 concentration. This study provides an idea for the formulation of regional periodic pollution control objectives which is significant to regional pollution control.

#### **2. Materials and Methods**

#### *2.1. Study Area*

Liaoning Province is located in Northeast China, covering an area of 148,000 km2, including 14 prefecture-level cities (Figure 1). The population is 43.82 million, including 29.52 million urban residents. Liaoning Province is a region in Northeast China where cities characterized by heavy industry are concentrated.

In Liaoning Province, the secondary industry accounted for 48.12% of the total GDP in 2015, with the province ranking 5th among the 31 provinces in China. In April 2015, TomTom, the Dutch tra ffic navigation service provider, released a global tra ffic congestion ranking, and Shenyang, the capital of Liaoning Province, ranked 29th [25]. According to data from the China National Environmental Monitoring Centre, 11 out of 14 cities in Liaoning Province experienced severe air pollution in November 2015. Therefore, there is an urgen<sup>t</sup> need to study the relationships and interactions between socioeconomic factors and ambient pollution in Liaoning Province.

**Figure 1.** Location and cities in the study area.
