Impact of the Digital Economy on Municipal Air Quality: Insights from Spatial Analysis

Urban morphology and air quality in dense residential environments in Hong Kong. Part I: District-level analysis

Digital economy and air quality are the key issues concerned by the government and academia. The healthy and sustainable development of the digital economy and the continuous optimization of urban air quality are not only conducive to high-quality economic development but also closely related to people’s livelihood. Based on the panel data of 228 cities from 2015 to 2020, using the panel regression and the mediating effect test methods, this paper verifies the impact of the digital economy development on urban air quality and then further analyzes the heterogeneity. The main results are as follows. Digital economy development can effectively improve urban air quality. The mediating effect of the urban industrial structure advancement accounts for 17.27%, and that of urban TFP accounts for 14.55%. The effect of improving air quality in cities with a high-level digital economy is more prominent, and the effect in large and medium-sized cities is more extensive. Meanwhile, in cities with a high urbanization rate, the effect of digital economy on improving air quality is more prominent.

Air pollution has seriously hindered China’s sustainable development. The impact mechanism of industrial upgrading on air pollution is still unclear, given the rapid digital economy. It is necessary to analyze the impact of industrial structure upgrading on air pollution through the digital economy. To investigate the impact of industrial upgrading and the digital economy on air pollution, this paper selected the industrial advanced index and the digital economy index to construct a panel regression model to explore the improvement effect of industrial upgrading on air pollution and selected China’s three typical areas to construct a zonal regression model. The concentrations of air pollutants showed a downward trend during 2013–2020. Among them, the SO2 concentration decreased by 63%, which is lower than the PM2.5 and NO2 concentrations. The spatial pattern of air pollutants is heavier in the north than in the south and heavier in the east than in the west, with the North China Plain being the center of gravity. These air pollutants have significant spatial spillover effects, while local spatial correlation is dominated by high-high and low-low clustering. Industrial upgrading has a stronger suppressive effect on the PM2.5 concentration than the suppressive effect on the SO2 and NO2 concentrations, while the digital economy has a stronger improvement effect on the SO2 concentration than its improvement effect on the PM2.5 and NO2 concentrations. Industrial upgrading has a stronger improvement effect on air pollution in the Yangtze River Delta urban agglomeration than in Beijing–Tianjin–Hebei and its surrounding areas, while the improvement in air pollution attributable to the digital economy in Beijing–Tianjin–Hebei and its surrounding areas is stronger than in the Yangtze River Delta urban agglomeration. There are significant differences in the effects of industrial upgrading and the digital economy on the various types of air pollutants.

Measurements and model simulations of air pollution in urban agglomerations and industrial places have shown high concentrations of gaseous and particulate matter pollutants such as photochemical gaseous pollutants and particulate matter. The world’s urban population increased over the past 50 years with an average rate of 2.7% year. By contrast, the total world population increased with an average rate of only 1.8% year. This illustrates the increasing global importance of urban agglomerations and industrial activities, thus their growing significance for the world’s air quality and climate problems. Air quality degradation in urban agglomerations and industrial sites has significant effects to human health leading to increased morbidity and mortality, to urban and regional air quality degradation and consequently to the earth’s climate. The sustainable development is the second focus of the current special issue. The usual assumption is that it is difficult to achieve the growth of enterprise in an environmentally friendly manner. This paradigm usually associated with developed countries is now affecting all other regions of the globe. The main question is if the development of enterprise is compatible with environmental protection. An important research area is that which deals with development and growth finding its way, in accordance with the principles of sustainability, considering social and environmental impacts as well. The present special issue of the Journal Water Air and Soil Pollution—Focus contains 14 selected papers that were presented at the 1st International Conference on Environmental Management, Engineering, Planning and Economics (CEMEPE), which was held together with a special conference of the Society for Ecotoxicology and Environmental Safety (SECOTOX) and took place on the Greek island of Skiathos from June 24 to 28, 2007. The papers presented in the Conference covered a wide range of scientific disciplines related to environment. The guest editors decided to present a special issue that focuses mainly on urban air quality and sustainable development. The papers study the air quality in urban and industrial sites with measurements and modeling tools and the related health effects, as well as papers that deal with important factors that lead to sustainable development. The papers presented here are based on those given at the Conference but have been subjected to peer review by at least two independent referees. The 14 papers that successfully passed the review process are presented here. We are grateful to the reviewers for their careful and objective evaluation of the submitted papers and the Organizing Committee of the CEMEPE Conference. Water Air Soil Pollut: Focus (2009) 9:1 DOI 10.1007/s11267-008-9203-9

The 15-minute city offers a new framework for sustainability, liveability, and health

Urban air quality, which is related to the health of local residents of the Pearl River Delta Region, China, (PRD) has been a hot topic among the masses and academic circles. In addition to economic growth, China’s rapidly increasing urbanization rate has also brought great pressure on urban air quality, in the Region, where due to its huge economic size and population, urban air quality has become the focus of local residents. This study first analyzed the spatio-temporal trends and correlation of land use and PM2.5 average annual concentration, which represents air quality in the PRD from 2000 to 2018, and according to Moran index, PM2.5 concentration in this area has spatial correlation in the study time. Secondly, the spatial error model of the PRD was constructed by using spatial effect, spatial modeling theory and spatial model estimation. The spatial-temporal evolution and influencing factors of PM2.5 concentration were discussed in fixed overall effect. The results showed that the area of cultivated land in the PRD decreased and the area of artificial surface increased year by year, while the PM2.5 concentration increased first and then decreased. In addition, the area of cultivated land and forestland were negatively correlated, while the area of grassland and water body were positively correlated with PM2.5 concentration. The conclusion of this study has a certain theoretical reference for urban land use planning and air quality assurance.

Since the environmental quality in metropolitan areas has significant impact on public health and everyday life of urban residents, it is of great importance to provide scientific information about the urban air pollutant concentration, which has gained much concern from both the governmental authorities and the scientific fields. This study illustrated the urban air quality of 113 sample cities in China by the comparison between the aggregate air quality index (AAQI) and the air quality index (AQI) and then depicted its spatial differentiation based on spatial interpolation. Furthermore, this study analyzed the influential factors behind the air quality variations among these cities by employing panel data models. The results indicated that the urban air quality showed a significant agglomeration feature at the national scale, with North China retaining the highest values both in terms of AAQI and AQI. From temporal perspective, the urban air quality reported a desirable trend nationwide from 2014 to 2016. Results from the regression models indicated that the urban air quality was affected by geographical locations, socioeconomic factors, and environmental regulations, among which urbanization level and industrial structure were reported to be the important socioeconomic factors exerting more significant impacts on the urban air quality. We suggest that more efforts should be devoted to develop comprehensive indices for evaluation of the urban air quality and to explore new avenues to improve urban air quality from industrialization and urbanization perspectives.

An atmospheric chemistry model (CiTTyCAT) is used to quantify the effects of trees on urban air quality in scenarios of high photochemical pollution. The combined effects of both pollutant deposition to and emission of biogenic volatile organic compounds (BVOC) from the urban forest are considered, and the West Midlands, metropolitan area in the UK is used as a case study. While all trees can be beneficial to air quality in terms of the deposition of O3, NO2, CO, and HNO3, some trees have the potential to contribute to the formation of O3 due to the reaction of BVOC and NOx. A number of model scenarios are used to develop an urban tree air quality score (UTAQS) that ranks trees in order of their potential to improve air quality. Of the 30 species considered, pine, larch, and silver birch have the greatest potential to improve urban air quality, while oaks, willows, and poplars can worsen downwind air quality if planted in very large numbers. The UTAQS classification is designed with practitioners in mind, to help them achieve sustainable urban air quality. The UTAQS classification is applicable to all urban areas of the UK and other mid-latitude, temperate climate zones that have tree species common to those found in UK urban areas. The modeling approach used here is directly applicable to all areas of the world given the appropriate input data. It provides a tool that can help to achieve future sustainable urban air quality.

The intensification of global urbanization has exacerbated the negative impact of atmospheric environmental factors in urban areas, thus threatening the sustainability of future urban development. In order to ensure the sustainability of urban atmospheric environments, exploring the changing laws of urban air quality, identifying highly polluted areas in cities, and studying the relationship between air quality and land use have become issues of great concern. Based on AQI data from 340 air quality monitoring stations and urban land use data, this paper uses inverse distance weight (IDW), Getis-Ord Gi*, and a negative binomial regression model to discuss the spatiotemporal variation of air quality in the main urban area of Lanzhou and its relationship with urban land use. The results show that urban air quality has characteristics of temporal and spatial differentiation and spatially has characteristics of agglomeration of cold and hot spots. There is a close relationship between urban land use and air quality. Industrial activities, traffic pollution, and urban construction activities are the most important factors affecting urban air quality. Green spaces can reduce urban pollution. The impact of land use on air quality has a seasonal effect.

Measuring coupling coordination between urban economic development and air quality based on the Fuzzy BWM and improved CCD model

Traffic-Related Air Pollution in Relation to Incidence and Prognosis of Coronary Heart Disease

Purpose China is experiencing an economic revolution focused on reducing carbon emissions (CEs). Various technological research and development (R&D) frameworks also hasten the growth of the digital economy, which then fuels this economic revolution. Nevertheless, several correlation uncertainties in China have been observed between R&D investment and CE reduction with green economic transformation. This phenomenon is attributed to insufficient spatial impact considerations. Design/methodology/approach Therefore, this article explored the spatial impacts of the digital economy and R&D expenditures regarding environmental quality using Chinese-related panel data between 2012 and 2021. This study uses the Moran I index to test whether there is a spatial relevance between regional carbon emissions in China and assess the digital economic advancement level using the entropy weight approach. In addition, this article analyzes the direct and indirect impacts following the partial differentiation approach, and then creates an interaction term between the digital economy and R&D investment to assess the moderating effect for examining the influence of investing in R&D on reducing CO2 levels of the digital economy. Findings A positive spatial relevance between the digital economy and CEs was then highlighted from the empirical findings. The digital economy expansion also demonstrated higher local CEs while negatively impacting nearby regions. Notably, the digital economy concurrently lowered and increased local CEs in the Eastern and Central zones, respectively. Overall, a larger R&D investment directly impacted the capacity of the digital economy in decreasing the carbon emission intensity (CEI) at a regional level. An accelerated digital economy expansion and lower CEI were recorded in the Eastern zone owing to more significant R&D investments. Research limitations/implications China has gradually shifted its focus from reducing CEs to implementing “dual control of carbon” to achieve the “dual carbon” target. Future studies should then involve additional studies concerning the impact mechanism and path selection related to “dual carbon control.” Practical implications Investment in R&D plays a key role in reducing carbon emissions from the digital economy. By fostering innovation and technological advances, R&D investment activities can create more energy-efficient digital infrastructures, develop sustainable practices and optimize resource use. In addition, these R&D investments can facilitate the transition to renewable energy sources, enhance data management systems to minimize waste and promote the adoption of green technologies by businesses and consumers. As the digital economy continues to evolve, prioritizing R&D in this area is critical to achieving long-term sustainable development goals and addressing the pressing challenges of climate change. Stakeholders across industries must therefore recognize the importance of investment in research and development as a strategic approach that not only drives economic growth but also ensures environmental stewardship in an increasingly digital world. Social implications Investments in research and development not only foster innovation and technological progress, but also promote sustainable practices, which can have significant environmental benefits. In addition, they have the potential to create new jobs, improve public health through better air quality and drive economic growth in a manner consistent with climate goals. As society becomes increasingly dependent on digital solutions, it is critical to harness the power of the digital economy to achieve a more sustainable and inclusive society. Originality/value Research development investment is critical to all aspects of regulation. Research on R&D investment can provide direction to local governments in formulating digital economy policies and can be beneficial to local governments in considering regional differences in resource availability. The research and technical innovation strategies in the policies for developing the digital economy can substantially expedite carbon neutrality achievement by 2060.

The driving effect of digital economy on interregional collaborative governance of carbon reduction: A case study of the Beijing-Tianjin-Hebei region

BackgroundAs China's "Internet + Health" initiative advances, the digital economy significantly influences the quality of medical and health services. However, there is a research gap concerning the digital economy's specific impacts, mechanisms, and marginal effects on these services. This gap impedes a comprehensive understanding of the digital economy's potential in healthcare.AimsThis study aims to clarify the digital economy's impact mechanisms on medical and health services levels, offering a scientific foundation for more targeted and effective policy formulation, thereby fostering sustainable digital development in healthcare.MethodsUtilizing panel data from China's 31 provinces (2011–2020), this paper employs the Spatial Durbin Model to analyze the spatial and marginal effects of the digital economy on healthcare service levels. To ensure analysis accuracy and robustness, the study refines the spatial weight matrix and addresses model endogeneity using the Generalized Spatial Two-Stage Least Squares method. Additionally, it examines regional disparities in the digital economy's impact through SDM and explores intermediary mechanisms and threshold effects using a mediation effect model and a panel threshold model.ResultsFindings indicate that the digital economy positively affects medical and health services in both local and neighboring regions, with variations across areas. The eastern region particularly benefits from the digital economy's enhancement of service levels, while the central and western regions see less impact. The digital economy enhances services by improving medical resource levels and promoting their coordinated development. However, this positive effect is moderated by the digital economy's and the region's economic development levels, with more pronounced impacts in regions with higher digital and economic development.ConclusionsThe digital economy plays a crucial role in improving medical and health services, and its full potential is beneficial for the industry's advancement and sustainability. Nonetheless, addressing the uneven digital economy development across regions is essential to ensure equitable benefits for all areas.

More than half, or 56%, of the world's population lives in cities. It is projected that the proportion of the population living in cities will continue to increase. In Latvian cities, the proportion of inhabitants is approaching 70%. As the urban population grows, the question of air quality in urban environments becomes increasingly relevant, affecting everyone on a daily basis. Already, a large portion of the world's population lives in areas where air quality does not meet acceptable standards. Air pollution affects the quality of life for every urban resident, as it impacts nearly all demographic groups and is particularly dangerous for people with chronic illnesses. In recent years, there has been an increasing amount of research conducted on snow pollution loads in temperate climate zones. Various bioindicators are being studied in urban environments, providing precise results on urban air quality. Until now, various fragmented studies have been conducted worldwide, examining specific objects and specific types of pollution and the pollution in their vicinity, without conducting a comprehensive study of the city. The city is a complex and dynamic entity with pronounced changes over time and space, to conduct a thorough study, multiple methods of air pollution occurrence must be used, and the city must be viewed holistically as a dynamic object over time and space. The hypothesis proposed in the doctoral thesis is that by comprehensively assessing long-term and short-term air pollution, it is possible to evaluate the dynamics of urban air pollution over time and space. The objective of the doctoral thesis is to develop a methodology for assessing the spatial distribution risk of air pollution based on bioindication methods and heavy metal concentrations in snow. The theoretical section of the doctoral thesis examines the impact of heavy metals and particulate matter (PM) suspended in the air on human health, provides an overview of various methods for determining air pollution in urban environments, and examines the complex interaction of various methods. The study also examines the impact of major transport corridors on urban air quality. For the first time in Europe, continuous seven-year data on the accumulation of various heavy metals and other chemical elements in snow cover in urban areas have been obtained with high resolution of 1 km², covering the entire city's territory. A large portion of Latvia's population lives in cities, therefore, studies on air quality, including analysis of snow and street dust, are crucial to determine the origin, distribution, and level of heavy metals in urban areas, near streets, and roads. Studies on urban air quality are vital for the development of urban planning documents and the establishment of sustainable development strategies for cities. This doctoral thesis consists of thirteen thematically unified scientific publications.