How does new-type urbanization affect air pollution? Empirical evidence based on spatial spillover effect and spatial Durbin model

Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.

A machine learning-based ensemble model for estimating diurnal variations of nitrogen oxide concentrations in Taiwan

Air pollution is inextricable from human activity patterns. This is especially true for nitrogen oxide (NOx), a pollutant that exists naturally and also as a result of anthropogenic factors. Assessing exposure by considering diurnal variation is a challenge that has not been widely studied. Incorporating 27 years of data, we attempted to estimate diurnal variations in NOx across Taiwan. We developed a machine learning-based ensemble model that integrated hybrid kriging-LUR, machine-learning, and an ensemble learning approach. Hybrid kriging-LUR was performed to select the most influential predictors, and machine-learning algorithms were applied to improve model performance. The three best machine-learning algorithms were suited and reassessed to develop ensemble learning that was designed to improve model performance. Our ensemble model resulted in estimates of daytime, nighttime, and daily NOx with high explanatory powers (Adj-R2) of 0.93, 0.98, and 0.94, respectively. These explanatory powers increased from the initial model that used only hybrid kriging-LUR. Additionally, the results depicted the temporal variation of NOx, with concentrations higher during the daytime than the nighttime. Regarding spatial variation, the highest NOx concentrations were identified in northern and western Taiwan. Model evaluations confirmed the reliability of the models. This study could serve as a reference for regional planning supporting emission control for environmental and human health.

Measurement of China's public health level: compilation and research of an index

BACKGROUND

With the development of the economy, public health has become increasingly important. Therefore, it is important to establish a comprehensive and scientific the public health level index (PHL) system to measure public health level as a research priority. The current research has limitations in exploring the PHL system; therefore, the field still lacks a comprehensive indicator system to measure the level of public health. Therefore, this paper aims to develop a multi-level public health index system and utilizes China as a case study to evaluate its public health status. The objective is to offer insights and recommendations for the improvement of public health initiatives in China and other regions.

METHODS

Utilizing data from 2011 to 2020, a comprehensive PHL was developed to encompass three vital indices: the Public Health Service Index (PHS), the Public Health Resource Index (PHR), and the Population Health Level Index (PHL). Subsequently, the PHL, PHS, PHR, and PH were meticulously calculated using a comprehensive evaluation method. Amid the current disparity between public health and economic progress, both the spatial Durbin model and the spatial lag model were finally employed to examine the influence of economic level (EL) on PHL, thus affirming the consistent reliability and accuracy of PHS.

RESULTS

Our findings revealed the following: (i) the PHL, PHS, and PHR indices show increasing trends in China; (ii) both EL and PHL exhibit high-high clustering and low-low clustering states; (iii) the PHL in the area has a positive spatial spillover effect on the surrounding area; (iv) EL will result in the siphoning effect of PHL; and (v) EL can enhance PHL through urbanization, PH, and PHS.

CONCLUSIONS

The PHL system constructed in this paper demonstrates multiple levels, pluralism, spatio-temporal comparability, and robustness. It can reflect not only the input and output of public health initiatives but also the interconnectedness and autonomy within the public health system. Therefore, it can be widely utilized in other areas of public health research.

Enhancing air treatment through controlled fabrication of transition metal-doped titanium dioxide nanocomposites for photocatalytic toluene degradation

Rapid industrial growth and urbanization have resulted in a significant rise in environmental pollution issues, particularly indoor air pollutants. As a result, it is crucial to design and develop technologies and/or catalysts that are not only cost-effective but also promising high performance and practical applicability. However, achieving this goal has been so far remained a challenging task. Herein, a series of transition metal M - TiO2 (M = W, Fe, Mn) nanocrystals was prepared for photocatalytic degradation of volatile organic compounds (VOCs), i.e., toluene. Of the nanocomposites tested, W-TiO2 showed significantly improved photocatalytic activity for VOC degradation under UV irradiation compared to the others. In particular, the optimized W dopant amount of 0.5 wt% resulted in the outstanding degradation performance of toluene (96%) for the obtained W-TiO2(0.5%) nanocomposite. Moreover, W-TiO2(0.5%) nanocomposite exhibited good stability for 32 h working under high toluene concentration (10 ppm) compared to the pristine TiO2. The current work demonstrates the potential usage of M - TiO2 nanocrystals, particularly W-TiO2(0.5%), as a promising photocatalyst for efficient VOCs degradation.

Spatiotemporal patterns and drivers of the urban air pollution island effect for 2273 cities in China

Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban-rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM2.5 and PM10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM2.5 and PM10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control.

Spillover effects of urban form on urban land use efficiency: evidence from a comparison between the Yangtze and Yellow Rivers of China

The contradiction between the basin's economic importance and its role as an ecological barrier impedes efficient urban land use. This study aims to propose an integrated approach to compare the urban land use of two representative basin areas of the Yangtze River Economic Belt and the Yellow River Basin and to investigate the impact of urban form on urban land use efficiency. Urban form was characterized by landscape indexes including Patch Density, Largest Patch Index, Edge Density, Patch Cohesion Index, and Agglomeration Index based on FRAGSTATS 4.0 software, and urban land use efficiency was measured by using Slack-Based Model-Undesirable, considering urban land becomes an emission source. Furthermore, spatial econometric models were adopted to explore direct effects and spatial spillover effects of urban form on urban land use efficiency. From 2000 to 2018, changes in urban form in both Yangtze River Economic Belt and Yellow River Basin showed increased fragmentation, enhanced heterogeneity, and more complex patch shapes. The high values of urban land use efficiency were concentrated in lower reaches of the Yangtze and Yellow Rivers. Spatial econometric models suggested that between different basins and various sized cities, the impact of urban form on urban land use efficiency had a spatial spillover effect and regional heterogeneity. Results indicated that input factors such as capital and labor should be more concentrated in metropolitan areas and urban agglomerations, thus promoting higher land use efficiency.

Effects of urbanisation on PM2.5 concentrations: A systematic review and meta-analysis

While urbanisation greatly improves a population's quality of life, it also has significant effects on urban air pollution. Previous studies have determined how urbanisation affects PM2.5 concentrations; the findings, however, have not been consistent. This study conducts a meta-analysis to systematically organise existing research and draw more conclusive and broadly applicable results regarding the impact of different factors of urbanisation on PM2.5 concentrations. The main research findings are as follows: (1) the Environmental Kuznets Curve (EKC) is proven to hold true in terms of the effect of population and land urbanisation on PM2.5 concentrations, while there is no consistent conclusion on the non-linear relationship between economic urbanisation and PM2.5 concentrations; (2) publication bias is evident in research on the economic and comprehensive urbanisation dimensions under linear assumptions; (3) there are notable heterogeneities in existing research in this field. The meta-regression model further indicates that model design, sample design, and publication characteristics might be responsible for these heterogeneities. This study innovatively applies a meta-analysis to investigate the effect of urbanisation on PM2.5 concentrations. The findings will contribute to scholars designing more rigorous research frameworks in this field.

New-Type Urbanization on pollution and carbon reduction impact mechanism and co-benefits analysis

How to simultaneously reduce environmental pollution and CO2 emissions is a challenging issue for various countries, particularly in China. Unlike traditional urbanization process that inevitably deteriorates environment, China initiated a New-Type Urbanization (NTU) strategy in 2014 following four principles: people-centeredness, optimal layout, ecological civilization, and cultural inheritance. Previous studies conduct research on NTU's influencing pollution and carbon reduction (PCR), respectively, while ignoring synergistic governance. The research objectives of this study are to investigate the potential mechanisms of NTU's influencing PCR and co-benefits for PCR. By leveraging 30 provincial-level data from China spanning 2005 to 2019, we comprehensively construct an index and assess NTU from six domains: population, economic, environmental, spatial, equitable, and social urbanizations and combine a coupling coordination model with a 2-way fixed effects model for empirical analysis. Our findings demonstrate that (1) NTU tends to significantly suppress pollution and carbon emissions, and this finding is reliable after several robustness tests and solving endogeneity with relief degree of land surface as an instrumental variable (IV). (2) The reducing effects seem to be achieved by promoting talent agglomeration, facilitating economic agglomeration and strengthening environmental regulations. (3) NTU tends to have both current and time-lag effects on pollution and carbon reduction, and their co-benefits are mainly influenced by the time-lag effect. Accordingly, policy recommendations are recommended: governments need to plan urbanization rationally, including strengthening public infrastructure and social welfare, pursuing the strategy of introducing talents, planning land and resource use rationally and efficiently, and strengthening environmental regulations. In addition, a mechanism should be developed to reduce pollution and carbon in an integrated manner for the long term. Our study broadens the horizons for international scholars engaged in sustainable urbanization research, enriching the array of research methodologies.

Air pollutant dispersion around high-rise building cluster forms: the case of Port City, Colombo, Sri Lanka

Air quality in dense urban environments is a growing concern, especially in rapidly developing cities. In the face of growing traffic associated with urbanisation, there is evidence for high levels of pollutant concentration at street level which is influenced by building forms. In this paper, we examine the potential effects of high-rise, cluster developments permitted by the local planning authorities in the newly established Port City development in Colombo, Sri Lanka. We designed possible building forms based on specific guidelines for the development in terms of plot coverage, floor area ratio, and maximum height. The three-dimensional building clusters were simulated using the RANS RNG k-epsilon turbulence model, to determine pollutant dispersion of a complex street formation in a high-dense high-rise building cluster, within the development and the surrounding context (existing Colombo). Results show that while increased porosity within the built fabric facilitates better pollution dispersion, a low correlation was seen between wind velocity and pollution concentration, especially in deep narrow high-rise canyons. Dispersion patterns at street level and at the urban canopy differed with each built form and are dependent on each canyon geometry. Thus, the study highlights the need for building regulations to take a holistic approach to capture the various elements of a complex urban cluster rather than the current two-dimensional parameters proposed for Port City, Colombo.

The impact of population agglomeration on ecological resilience: Evidence from China

Due to climate change and human activities, ecological and environmental issues have become increasingly prominent and it is crucial to deeply study the coordinated development between human activities and the ecological environment. Combining panel data from 31 provinces in China spanning from 2011 to 2020, we employed a fixed-effects model, a threshold regression model, and a spatial Durbin model to empirically examine the intricate impacts of population agglomeration on ecological resilience. Our findings indicate that population agglomeration can have an impact on ecological resilience and this impact depends on the combined effects of agglomeration and crowding effects. Also, the impact of population agglomeration on ecological resilience exhibits typical dual-threshold traits due to differences in population size. Furthermore, population agglomeration not only directly impacts the ecological resilience of the local area, but also indirectly affects the ecological resilience of surrounding areas. In conclusion, we have found that population agglomeration does not absolutely impede the development of ecological resilience. On the contrary, to a certain extent, reasonable population agglomeration can even facilitate the progress of ecological resilience.

Driving forces and relationship between air pollution and economic growth based on EKC hypothesis and STIRPAT model: evidence from Henan Province, China

The aim of this research is to analyze the main influencing factors and relationship between atmospheric environment and economic society. Using the panel data of 18 cities in Henan Province from 2006 to 2020, this paper employed some advanced econometric estimation included entropy method, extended environmental Kuznets curve (EKC) and STIRPAT model to conduct empirical estimations. The results show that most regions in Henan Province have verified the existence of the EKC hypothesis; and the peak of air pollution level in all cities of Henan Province generally occurred in around 2014. Multiple linear Ridge regression indicated that the positive driving forces of air pollution in most cities in Henan Province are industrial structure and population size; the negative driving forces are urbanization level, technical level and greening degree. Finally, we used the grey GM (1, 1) model to predict the atmospheric environment of Henan Province in 2025, 2030, 2035 and 2040. What should pay close attention to is that air pollution levels in northeastern and central Henan Province will continue to remain high.

Green industrial transition: Leveraging environmental innovation and environmental tax to achieve carbon neutrality. Expanding on STRIPAT model

Anthropogenic global warming strategies on carbon mitigation are driven by encouraging green innovation and using carbon taxes, yet an empirical model to validate this is non-existing. Moreover, the existing stochastic effects by regression on population, wealth, and technology (STIRPAT) model has been found to lack policy tools on taxes and institutions that cut carbon emissions. This study amends the STIRPAT model with environmental technology, environmental taxes, and strong institutional frameworks to create a new model STIRPART(stochastic impacts by regression on population, affluence, regulation, and technology) to understand the factors impacting carbon pollution using the emerging 7 economies. Using data from 2000 to 2020, the Driscoll-Kraay fixed effects are employed in this analysis to conduct evidential tests of the impacts of environmental policies, eco-friendly innovations, and strong institutions. The outcomes indicate that environmental technology, environmental taxation, and institution quality decrease E7's carbon emissions by 0.170%, 0.080%, and 0.016%, respectively. It is recommended that E7 policymakers should adopt the STIRPART postulate as the theoretical basis for policies favoring environmental sustainability. The key contribution is the amendment of the STIRPAT model and the enhancement of the market-based mechanisms, such as patents, strong institutions, and carbon taxes, to enable environmental policy to be carried out sustainably and cost-effectively.

Mediating and spatial spillover effects of public participation in environmental pollution governance mediated via traditional and new media

A systematic study of public participation (Pub) in environmental pollution control can facilitate collaborative governance based on multiple factors, and promote the modernization of national governance. Based on the data of 30 Chinese provinces from 2011 to 2020, this study empirically analyzed the mechanism of Pub in environmental pollution governance. Based on multiple channels, a dynamic spatial panel Durbin model and an intermediary effect model were constructed. The main results are as follows: (1) Pub based on environmental letters and visits have no significant impact on local pollution reduction, while the Baidu search index of environmental pollution has the greatest effect on emission reduction, followed by environmental protection strategies based on the National People's Congress (NPC) and microblogging. (2) Pub not only has a direct positive impact on environmental control through its positive externality but also indirectly reduces environmental treatment by enhancing the intensity of environmental regulation. (3) Pub has a significant spatial spillover effect on environmental control based on geographical attenuation. Excluding environmental legislation, the direct spatial spillover effects of Pub under the networked platform and traditional channels are only significant within 1200 km and 1000 km, respectively, which decrease with increasing geographic distance within this range. When the environmental regulations are considered, the spatial spillover effects of suggestions proposed by NPC and the Chinese People's Political Consultative Conference (CPPCC) are significant within 800 km, while the attenuation boundary of Internet complaints, Baidu index, and microblogging public opinion is 1000 km. (4) The impact of Pub on environmental governance varies significantly among regions. Compared with central and western regions, the eastern region showed more effective pollution reduction based on Pub.

Urbanization and residents' health: from the perspective of environmental pollution

The development of urbanization has important implications for the environment and the human health. However, it is still lacking a comprehensive analysis between urbanization, environmental pollution, and residents' health based on a unified research system. In this study, we assessed the integrated level of urbanization by the entropy method based on the representative indicators. It has been found that there is a significant progress in the urbanization level in the provinces from 2005 to 2020. The impact of urbanization development on environmental pollution was analyzed using the system GMM (Generalized Method of Moments), and the results show an inverted U-shaped relationship between urbanization and environmental pollution. Fixed effect regression model analysis infers that urbanization has a dual impact on population health. Urbanization promotes residents' health by improving medical conditions, but the environmental pollution caused by urbanization is harmful to residents' health. This paper integrated urbanization, environmental pollution, and residents' health into a research system to analyze the impact of urbanization on environmental pollution and residents' health. Some policy recommendations have been proposed based on the research results for promoting high-quality development of urbanization, reducing environmental pollution, and improving residents' health.

Does digitalization make urban development greener? A case from 276 cities in China

Nowadays countries in the world are striving to transform their economic and social development modes to achieve the general goal of green development. With the rapid development of communication technology, digitalization has affected production and life, touching all aspects of society. Can digitalization make the world “greener”? To this end, this study conducts an empirical research based on the panel data of 276 cities in China from 2011 to 2020. Firstly, this paper separately measured the comprehensive level of urban digitalization and urban greening through the Entropy-TOPSIS method, then analyzed their spatial distribution characteristics and evolution process respectively, finally used the spatial Durbin model to explore the impact of digitalization on urban greening development. The following conclusions were drawn accordingly: (1). The development pattern of urban digitalization has changed from “multi-point” sporadic distribution to “group-type” aggregation with obvious spatial heterogeneity. The gap between cities is not narrowing. The Yangtze River Delta urban agglomeration has become an important high-level digital agglomeration area; (2). The urban greening develops with obvious spatial heterogeneity. The difference between eastern regions and western regions is prominent, and the urban spatial agglomeration characteristic is distinct. However, the spillover effect is weakened with distance, while the convergence characteristic becomes obvious; (3). Digitalization is significantly beneficial to the development of urban greening with obvious spatial heterogeneity. Digitalization in cities within urban agglomeration and in eastern regions has a stronger effect on promoting the urban greening, which is not obvious in cities located in western regions and non-urban agglomeration. Finally, according to the research results, suggestions for urban digitalization and greening development are put forward.

Coupling coordination analysis of urbanization and the ecological environment based on urban functional zones

Urbanization is an inevitable process in human social progress; additionally, the ecological environment is the carrier and foundation of human social development. Considering central Shanghai, China, as an example, this study quantitatively analyzed the coupling coordination relationship between urbanization and the ecological environment based on urban functional zones; remote sensing images, Open Street Map roads, and point of interest data were analyzed for the urban functional zones via the remote sensing-based ecological index (RSEI), comprehensive nighttime light index (CNLI), and coupling coordination degree (D). The results revealed that urban functional zones in central Shanghai were mainly mixed functional zones and comprehensive functional zones, which formed a spatial structure that gradually radiated outward from the urban core. Additionally, CNLI values were high; the proportion of CNLI between 0.6 and 1 was 94.37%. Moreover, the RSEI showed spatial differentiation; it was low in the center and gradually increased outward. Additionally, D was at the primary coordination level. The coupling coordination type in the core area corresponded to an ecological environment lag, which gradually transitioned to a state of systematic balanced development from the core area outward, but showed sluggish urbanization in some areas. This quantitative analysis of the coupling coordination between urbanization and the ecological environment based on urban functional zones provides effective scientific references for optimization of spatial planning.

Does new-type urbanization curb haze pollution? A case study from China

The rapid urbanization process has led to a high concentration of population and economic activities in urban space, thus leading to severe environmental pollution. The concept of new-type urbanization has been proposed in China to combat the pollution associated with urbanization. This study analyzes the interaction effect of new-type urbanization with land, industry, and technology on haze pollution, using Chinese provincial-level panel data, and employs a STIRPAT model with interaction terms for empirical testing. The results find that new-type urbanization can significantly reduce the national haze pollution level; meanwhile, the optimization of intensive urban land use level, industrial structure, and technological innovation can interact with it to promote haze reduction, and there is regional heterogeneity. The improvement of intensive urban land use and industrial structure in the central region will significantly enhance the haze reduction effect of new-type urbanization, while the improvement of technological innovation in the west will instead weaken its haze reduction effect, and the interaction in the eastern region is not significant. This research provides a theoretical basis for better implementation of new-type urbanization construction and effective promotion of green and sustainable urban development.

The Empirical Analysis of Environmental Regulation's Spatial Spillover Effects on Green Technology Innovation in China

Green technology innovation is one of the driving forces of industrial structure upgrading. This innovation is thought to be related to environmental regulation. The study uses panel data for 30 Chinese provinces and cities from 2009 to 2020 and presents a comprehensive research-based explanation of how environmental regulations impact green innovation. This study employs the spatial Durbin model to analyze the spillover effect of the region. The results show that the total impact of environmental regulations is 0.223%, of which the direct effect is 0.099%. This impact includes the effects of both formal and informal environmental regulation. It indicates that ecological regulations significantly enhance green technology innovation. Furthermore, the spatial spillover effect is significantly positive at the 1% level with a coefficient of 0.124. Such spillover effects represent a learning effect of regional environmental regulation. Based on the results, the study suggests a few policy measures based on the detailed outcomes.

The impact of industrial robots application on air pollution in China: Mechanisms of energy use efficiency and green technological innovation

The battle against air pollution in China persists, and haze remains over cities. Whether industrial robots, as the core technology of intelligent manufacturing, can improve city air quality in the process of production has not been determined. Using the International Federation of Robotics data and Chinese city air pollution data (2013-2018), this study finds that industrial robots significantly reduce city air pollution levels (PM2.5, PM10, and SO2), which remains robust after addressing endogeneity. The mechanism of action lies in the synergistic benefits of industrial robots in reducing city air pollution levels by effectively improving energy use efficiency and promoting green technological innovation. Heterogeneity analysis suggests that industrial robots, as the incarnation of green technology, can be an effective alternative tool to green policies, such as low-carbon piloting, resource planning, and environmental regulation. This study empirically confirms that industrial robots are environment-friendly technologies that can provide new policy ideas to promote air pollution prevention and control in the industrialization process.

Analysis of the Urban Land Use Efficiency in the New-Type Urbanization Process of China’s Yangtze River Economic Belt

The accelerated urbanization process in China has caused a shift in the urban land use structure. The Chinese government has issued ‘the National New-type Urbanization Plan’ focusing on the rational use of resources, which is of great significance for the intensification and sustainability of land use. In promoting the construction of the new-type urbanization (N-TU), enhancing the urban land use efficiency (ULUE) is crucial to regional coordinated development. This study uses panel data from 2011 to 2020 for 11 provinces (cities) in the Yangtze River Economic Belt (YREB) and adopts the super efficiency (SE) slacks-based measure (SBM) model with undesirable outputs and the entropy weight method to calculate the ULUE and N-TU levels. The study uses the System generalized method of moment (Sys-GMM) to study the N-TU’s impact on the ULUE empirically. The results indicate: (i) the overall trend of new-type urbanization level is gradually increasing and has the characteristics of uneven spatial distribution between provinces. (ii) The ULUE shows a fluctuating upward trend during the studied period. (iii) The N-TU and its subsystems have significant positive effects on the ULUE. Overall, this study aims to explore the relationship between the N-TU and ULUE enriching the theoretical analysis and empirical research in related fields, thus helping decision makers in the assessment and design of policy recommendations.