Impacts of Migration on Urban Environmental Pollutant Emissions in China: A Comparative Perspective

Abstract

In recent years, researchers have devoted considerable attention to identifying the causes of urban environmental pollution. To determine whether migrant populations significantly affect urban environments, we examined the relationship between urban environmental pollutant emissions and migrant populations at the prefectural level using data obtained for 90 Chinese cities evidencing net in-migration. By dividing the permanent populations of these cities into natives and migrants in relation to the population structure, we constructed an improved Stochastic Impacts by Regression on Population, Affluence and Technology model (STIRPAT) that included not only environmental pollutant emission variables but also variables on the cities' attributes. We subsequently conducted detailed analyses of the results of the models to assess the impacts of natives and migrants on environmental pollutant emissions. The main findings of our study were as follows: 1) Migrant populations have significant impacts on environmental emissions both in terms of their size and concentration. Specifically, migrant populations have negative impacts on Air Quality Index (AQI) as well as PM 2.5 emissions and positive impacts on emissions of NO 2 and CO 2 . 2) The impacts of migrant populations on urban environmental pollutant emissions were 8 to 30 times weaker than that of local populations. 3) Urban environmental pollutant emissions in different cities differ significantly according to variations in the industrial structures, public transportation facilities, and population densities.

How Does an Environmental Amenity Attract Voluntary Migrants? Evidence from Ambient Air Quality in China

“…Third, we address the potential endogeneity concern due to measurement error by using air quality information as a proxy for environmental quality and counting the seriously polluted days in a province, which is likely to minimize the spatial and geographical heterogeneities of collected air pollution levels within a region. Finally, to address the potential reverse causality that air pollution levels can be affected by population density [19][20][21], we focus on environmental migration from polluted areas to areas with better air quality. This approach to reverse causality considers that a lower population density results in higher levels of air pollution, which is highly unlikely in practice.…”

Spatio-temporal Differentiation and Driving Factors of Industrial Ecology of Restricted Development Zone from Adaptive Perspective: A Case Study of Shandong, China

“…At present, research on industrial ecology mainly focuses on qualitative descriptions, while research on the strength of specific influencing factors needs to be further developed. According to relevant research results (Tong et al, 2012;Wang and Ding, 2017;Zhang et al, 2018;Guo et al, 2019), and in combination with the actual situation of the study area, this paper selected economic development, industrial structure, foreign investment, science and technology, government regulation, and environmental regulation to perform a quantitative analysis of the driving factors of industrial ecology.…”

“…The industrial system is an important manifestation of the economic level of the human-land relationship system; accordingly, its structural type and organizational scale affect to a great extent the economic development efficiency and resource utilization efficiency. At the same time, the industrial development model also directly determines its antagonistic stress or its coupling, symbiotic effect on the ecological system (Ren and Shang, 2005;Liu et al, 2007;Wang et al, 2020). Therefore, it is of urgent practical significance to explore the mechanism of influence of regional development on resources and environment from the perspective of industry.…”

Spatio-Temporal Characteristics of SO2 across Weifang from 2008 to 2020

“…(1) It is related to SO 2 emission. According to the conclusions of Guo et al [8] and Wang et al [44], they believe that population density is positively correlated with industrial production scale and energy consumption, resulting in the increase in SO 2 emission. The population and GDP scale of the western region (such as Shouguang and Qingzhou county) and the eastern region (such as Gaomi) rank among the top five in Weifang city, which shows that these regions have large SO 2 emissions.…”

“…(1) It is related to SO2 emission. According to the conclusions of Guo et al[8] and Wang et al[44], they believe that population density is positively correlated with industrial production scale and energy consumption, resulting in the increase in SO2 emission. The population and…”