The Driving Influence of Multi-Dimensional Urbanization on PM2.5 Concentrations in Africa: New Evidence from Multi-Source Remote Sensing Data, 2000-2018.

Guoen Wei,Zhenke Zhang,Binglin Liu,Shengnan Jiang,Yang Shen,Pingjun Sun,Xiao Ouyang

doi:10.3390/ijerph18179389

Abstract

Africa’s PM2.5 pollution has become a security hazard, but the understanding of the varying effects of urbanization on driven mechanisms of PM2.5 concentrations under the rapid urbanization remains largely insufficient. Compared with the direct impact, the spillover effect of urbanization on PM2.5 concentrations in adjacent regions was underestimated. Urbanization is highly multi-dimensional phenomenon and previous studies have rarely distinguished the different driving influence and interactions of multi-dimensional urbanization on PM2.5 concentrations in Africa. This study combined grid and administrative units to explore the spatio-temporal change, spatial dependence patterns, and evolution trend of PM2.5 concentrations and multi-dimensional urbanization in Africa. The differential influence and interaction effects of multi-dimensional urbanization on PM2.5 concentrations under Africa’s rapid urbanization was further analyzed. The results show that the positive spatial dependence of PM2.5 concentrations gradually increased over the study period 2000–2018. The areas with PM2.5 concentrations exceeding 35 μg/m3 increased by 2.2%, and 36.78% of the African continent had an increasing trend in Theil–Sen index. Urbanization was found to be the main driving factor causing PM2.5 concentrations changes, and economic urbanization had a stronger influence on air quality than land urbanization or population urbanization. Compared with the direct effect, the spillover effect of urbanization on PM2.5 concentrations in two adjacent regions was stronger, particularly in terms of economic urbanization. The spatial distribution of PM2.5 concentrations resulted from the interaction of multi-dimensional urbanization. The interaction of urbanization of any two different dimensions exhibited a nonlinear enhancement effect on PM2.5 concentrations. Given the differential impact of multi-dimensional urbanization on PM2.5 concentrations inside and outside the region, this research provides support for the cross-regional joint control strategies of air pollution in Africa. The findings also indicate that PM2.5 pollution control should not only focus on urban economic development strategies but should be an optimized integration of multiple mitigation strategies, such as improving residents’ lifestyles, optimizing land spatial structure, and upgrading the industrial structure.

Highlights

Since the turn of the century, global value chains and production networks have accelerated their penetration into various regions
Significant improvements are required to comprehensively analyze the impact of urbanization on PM2.5 concentrations in Africa from a broader perspective; (2) the joint analysis of grid and administrative units has not received much attention. Such analysis can achieve the integration of decision-making reference value and refined expression; and (3), few studies have integrated multiple spatial regression models to study the difference between the direct and spillover effects of urbanization on PM2.5 concentrations and analyzed the interaction effects between multi-dimensional urbanization, this can provide support for the cross-regional joint control of air pollution in Africa. To address these knowledge gaps, this study explores the spatial distribution characteristics of multi-dimensional urbanization and PM2.5 concentrations in Africa for 2000–2018 using grid and administrative units
The research structure consists of three parts: (1) Theil–Sen median trend degree and spatial autocorrelation methods were used to analyze the spatio-temporal evolution and spatial dependence patterns of PM2.5 concentrations and the multi-dimensional urbanization in Africa; (2) spatial regression models (SEM, spatial lag model (SLM), and spatial Durbin model (SDM)) were used to reveal the driving mechanism of PM2.5 concentrations under the rapid modernization; and (3) joint spatial regression model and geographic detector were employed to analyze the differential impact and interaction effects of multi-dimensional urbanization on PM2.5 concentrations

Summary

Objectives

The main objectives of this study are as follows: (1) to characterize the spatio-temporal pattern and spatial dependence features of PM2.5 concentrations and multi-dimensional urbanization;

Methods

Results

Discussion

Conclusion