Urbanization Influences CO2 Emissions in the Pearl River Delta: A Perspective of the “Space of Flows”

Abstract

As the largest carbon emitter in the world, China is facing increasing challenge to reduce CO2 emissions. Given this issue, exploring the influencing factors is of great significance for scientific low-carbon emission policymaking. Although previous literature has explored the effects of urbanization on CO2 emissions, the impact of the space of flow on urban carbon emissions have been less explored. Due to the increasing connection between cities, its impact on urban carbon emissions cannot be ignored. Thus, this paper takes the space of flows into account as an aspect of urbanization to supplement the existing literature and empirically examines the multiple effects of urbanization on CO2 emissions in the Pearl River Delta (PRD) urban agglomeration. By using a STIRPAT model, statistical data, and web crawler data, we examined impacts of different types of urbanization on CO2 emissions. Our empirical results show that: (1) Within the PRD urban agglomeration, urban linkage intensity is strongly connected to urban socioeconomic growth, establishing a geographical structure with Guangzhou and Shenzhen as the double core. (2) Our results show that urbanization exerts two opposite effects on CO2 emissions: positively connects carbon emissions with population urbanization, integrated urban linkage flow, and energy intensity, whereas economic urbanization and social urbanization are shown to be negatively correlated. However, spatial urbanization has no significant positive effect on urban CO2 emissions. (3) It is worth noting that urban linkage flows are the second most important factor affecting urban carbon emissions after economic urbanization. Our study could formulate effective planning suggestions for future CO2 emission reduction paths and development modes in the PRD.

Spatiotemporal Variation and Development Stage of CO2 Emissions of Urban Agglomerations in the Yangtze River Economic Belt, China

“…Based on numerous previous studies on CO 2 emissions from urban agglomerations [31][32][33], population (POP), GDP per capita (GDPPC), the proportion of secondary industry (SI), carbon emission intensity (CI), and urbanization (UR) were selected as the influencing factors of CO 2 emissions in this study. All data were derived from the China City Statistical Yearbook (2009-2018 editions).…”

Spatial Patterns Exploration and Impacts Modelling of Carbon Emissions: Evidence from Three Stages of Metropolitan Areas in the YREB, China

“…While in the process of continuous concentration of population and industries, the LUCE efficiency of districts or counties should be improved by other ways to reduce carbon emissions in the region. Previous studies on the spatial patterns and impact modeling of LUCE have mainly concentrated on a single aspect of the research object [59][60][61], such as analyzing the spatial evolution characteristics [62] or the influencing factors of carbon emissions [63][64][65]. Few studies have focused on research objects at different development stages at the same time, thus failing to identify the spatial differentiation patterns and influencing factors of LUCE among different types of research objects.…”