Spatial Effect of Digital Economy on Particulate Matter 2.5 in the Process of Smart Cities: Evidence from Prefecture-Level Cities in China

Abstract

During the COVID-19 pandemic, the digital economy has developed rapidly. The airborne nature of COVID-19 viruses has attracted worldwide attention. Therefore, it is of great significance to analyze the impact of the digital economy on particulate matter 2.5 (PM2.5) emissions. The research sample of this paper include 283 prefecture-level cities in China from 2011 to 2019 in China. Spatial Durbin model was adopted to explore the spatial spillover effect of digital economy on PM2.5 emissions. In addition, considering the impact of smart city pilot (SCP) policy, a spatial difference-in-differences (SDID) model was used to analyze policy effects. The estimation results indicated that (1) the development of the digital economy significantly reduces PM2.5 emissions. (2) The spatial spillover effect of the digital economy significantly reduces PM2.5 emissions in neighboring cities. (3) Smart city construction increases PM2.5 emissions in neighboring cities. (4) The reduction effect of the digital economy on PM2.5 is more pronounced in the sample of eastern cities and urban agglomerations.

Does the perception of smart governance enhance commercial investments? Evidence from Beijing, Shanghai, Guangzhou, and Hangzhou

“…There is coordination between the two subsystems of urban intelligence and sustainability in China, and their degree of coordination is on the rise [ 84 ]. Smart city construction reduces carbon emission intensity [ 85 ], PM2.5 emissions [ 86 ], and haze pollution [ 87 , 88 ] and promotes the quantity and quality of green innovation in cities [ 44 , 89 ].…”

Impact of the digital economy on carbon dioxide emissions in resource-based cities

“…In these cities, the proliferation of the digital economy can effectively optimize energy distribution and consumption patterns, thus aiding in controlling the growth of carbon emissions 29 , 30 . In contrast, mature cities, with more stable industrial and energy structures, experience the impact of the digital economy predominantly in enhancing the energy efficiency of existing industries and in promoting the application of efficient, low-carbon technologies 23 , 47 . In these cities, the effects of digital transformation may be more pronounced due to the existing infrastructure and technological level providing a solid foundation for the integration of new technologies.…”

“…Moreover, with the rise of emerging digital economy sectors like data centers and cloud services, the overall energy demand may increase, especially in cities where the energy structure is still predominantly fossil fuel-based 33 . Concurrently, the rapid growth of electronic waste presents new challenges for environmental management 47 . Hence, in the mid to later stages of the digital economy, resource-based cities face the necessity of recalibrating strategies to focus on more efficient energy utilization technologies, promoting the development and application of clean energy, and effectively managing electronic waste, ensuring environmental sustainability while pursuing economic growth 8 .…”

Does New Urbanization Promote Urban Metabolic Efficiency?

“…According to the "polarization-trickle-down" theory [54,55], the high demand for labor, capital, and other resources in the NU pilot cities will create a "siphon effect", which will deprive the surrounding areas of resources for urban development [56,57]. At the same time, however, the management experience, advanced technology, and important policy implementation knowledge of the NU pilot cities will be transferred to the peripheral regions through the "trickle-down effect", which will reduce the cost of trial and error in the surrounding areas [58,59]. According to the theory of externalities, on the one hand [60,61], the NU pilot cities may eliminate a large number of heavily polluting industries through industrial upgrading in the process of enhancing their own UME, thus reducing the UME of the surrounding areas through pollution transfer [62][63][64]; on the other hand, the improvement of public infrastructure and transport infrastructure in the NU pilot cities will reduce the cost of knowledge flow, thereby better serving as exemplary models and catalyzing agents, and thus enhancing the UME of the surrounding areas [65][66][67].…”