Influence of Urban-Growth Pattern on Air Quality in China: A Study of 338 Cities

Reconsidering the effects of urban form on PM2.5 concentrations: an urban shrinkage perspective

The phenomenon of urban shrinkage is currently occurring worldwide; however, the "growth-oriented" planning paradigm is not suitable for these shrinking cities. Reconsidering the relationship between urban form and PM_2.5 concentrations from the perspective of urban shrinkage can help provide a research reference for controlling air pollution and optimizing the spatial layout of shrinking cities. This study takes shrinking areas in China as the research subject, which are divided into four research groups according to their shrinkage degree. The empirical results indicate that the average PM_2.5 concentrations decrease with the aggravation of urban shrinkage. In terms of the effect of urban form on PM_2.5 concentrations, the urban size is always positively related to PM_2.5 concentrations, while the impact of urban fragmentation on PM_2.5 concentrations is negligible. Further, urban shape positively affects PM_2.5 concentrations only in moderately and severely shrinking cities. Cities with sprawling urban forms have higher PM_2.5 concentrations, except for those facing severe shrinking trends. This study suggests that governments in shrinking cities should reasonably adjust both the urban form and land use to improve air quality based on the degree of urban shrinkage.

Effects of urban form on air quality: A case study from China comparing years with normal and reduced human activity due to the COVID-19 pandemic

This study explored the dynamic and complex relationships between air quality and urban form when considering reduced human activities. Applying the random forest method to data from 62 prefecture-level cities in China, urban form-air quality relationships were compared between 2015 (a normal year) and 2020 (which had significantly reduced air pollution due to COVID-19 lockdowns). Significant differences were found between these two years; urban compactness, shape, and size were of prime importance to air quality in 2020, while fragmentation was the most critical factor in improving air quality in 2015. An important influence of traffic mode was also found when controlling air pollution. In general, in the pursuit of reducing air pollution across society, the best urban forms are continuous and compact with reasonable building layouts, population, and road densities, and high forest area ratios. A polycentric urban form that alleviates the negative impacts of traffic pollution is preferable. Urban development should aim to reduce air pollution, and optimizing the effects of urban form on air quality is a cost-effective way to create better living environments. This study provides a reference for decision-makers evaluating the effects of urban form on air pollution emission, dispersion, and concentration in the post-pandemic era.

The Associations Between Urban Form and Major Non-communicable Diseases: a Systematic Review

In the current century, non-communicable diseases (NCDs), particularly cardiovascular diseases, diabetes, cancer, and chronic respiratory diseases, are the most important cause of mortality all over the world. Given the effect of the built environment on people's health, the present study seeks to conduct a systematic review in order to investigate the relationship between urban form and these four major NCDs as well as their main risk factors. Two independent reviewers in November 2020 after an extensive search through PubMed and Scopus identified 77 studies. Studies published in English were included if they addressed one or more attributes of urban form in relation to any major NCDs and their main risk factors. Publication date, country, geographical scale, study design, methods of built environment measurement, and findings of the relationships among variables were extracted from eligible studies. The findings suggest that the elements of urban form (density, transportation and accessibility, characteristics of building and streetscape, land use, spatial layouts and configuration) could increase or inhibit these diseases through their effect on physical activity, diet, air pollution, blood pressure, and obesity. However, there are study shortages, contradictions, and ambiguities in these relationships which are mainly due to methodological and conceptual challenges. As a result, more in-depth research is needed to achieve solid and consistent results that could be made into clear guidelines for planning and designing healthier cities.

A modified conceptual framework for peer relationship amongst community-dwelling older people in China: A qualitative study

Little is known about the pattern, influencing factors of peer relationships, or their interplays amongst community-dwelling older people. This qualitative study was undertaken to understand and present these issues under the guidance of existing Adams-Blieszner-Ueno integrative conceptual framework for friendship in the context of China. Semi-structured interviews were undertaken with 20 older adults in Chongqing, China. Interview transcripts were then analysed by performing content analysis under the guidance of existing categories of Adams-Blieszner-Ueno integrative conceptual framework for friendship and developing separate categories inductively to ensure all data was captured. The results revealed four themes-context, individual characteristics, interactive motifs and peer relationship patterns-and 16 categories. Based on the original Adams-Blieszner-Ueno integrative conceptual framework for friendship, the revised framework for peer relationships modified two dimensions (from structural context to social context, friendship patterns to peer relationship patterns) and added two categories (natural context and health status) that emerge from the data. Besides, different dimensions in the modified framework for peer relationships are explicitly interrelated and not completely independent from each other. In conclusion, this study modified the pre-existing Adams-Blieszner-Ueno integrative conceptual framework for friendship, especially identifying two additional categories, natural context and health status, to understand peer relationships amongst the Chinese community-dwelling older people through careful examination of the data. All domains concerning the modified conceptual framework of peer relationship may serve as possible targets for developing peer-involved programs and thus improving social health, well-being and successful ageing of Chinese older people.

Relationships between urban form and air quality: A reconsideration based on evidence from China's five urban agglomerations during the COVID-19 pandemic

The outbreak of Coronavirus disease 2019 (COVID-19) led to the widespread stagnation of urban activities, resulting in a significant reduction in industrial pollution and traffic pollution. This affected how urban form influences air quality. This study reconsiders the influence of urban form on air quality in five urban agglomerations in China during the pandemic period. The random forest algorithm was used to quantitate the urban form-air quality relationship. The urban form was described by urban size, shape, fragmentation, compactness, and sprawl. Air quality was evaluated by the Air Quality Index (AQI) and the concentration of six pollutants (CO, O₃, NO₂, PM_2.5, PM₁₀, SO₂). The results showed that urban fragmentation is the most important factor affecting air quality and the concentration of the six pollutants. Additionally, the relationship between urban form and air quality varies in different urban agglomerations. By analyzing the extremely important indicators affecting air pollution, the urban form-air quality relationship in Beijing-Tianjin-Hebei is rather complex. In the Chengdu-Chongqing and the Pearl River Delta, urban sprawl and urban compactness are extremely important indicators for some air pollutants, respectively. Furthermore, urban shape ranks first for some air pollutants both in the Triangle of Central China and the Yangtze River Delta. Based on the robustness test, the performance of the random forest model is better than that of the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model.

How does urbanization affect vegetation productivity in the coastal cities of eastern China?

Changes in terrestrial gross primary productivity (GPP) caused by rapid urbanization may result in negative effects on ecosystem services and ecosystem health. These impacts are of great concern in coastal zones where rapid urbanization is predominant. Knowing how urbanization affects vegetation productivity will be helpful for policymakers to make decisions on urban vegetation and ecosystem management. In this study, we chose 48 cities along the coastal zone of eastern China to evaluate the impacts of urbanization on vegetation GPP. The spatiotemporal comparison was used to identify the changes in built-up lands and vegetation GPP for multiple years (2000, 2005, 2010, and 2015). The area percentage of built-up lands was used to define the urbanization density. It was found that: (1) the actual vegetation GPP changed in different patterns with urbanization gradient from low to high intensity, including straight declining, depressed, and reversed S shapes at the city scale. The vegetation GPP change due to urbanization include both direct impact that is resulted directly from the loss of green land, and indirect impact that is induced by the change of macro-environment associated with urbanization. The slope of direct impacts change from low to high urbanization intensity were - 0.917, -0.925, -0.933, -0.938 for 2000, 2005, 2010, and 2015, respectively. The greater value means urban vegetation GPP loss faster as urbanization intensity increase. (2) A turning point on the maximum values for the indirect impacts was observed at approximately 0.8 of urbanization intensities, although it indicates both positive and negative value for the cities. However, no significant differences were observed for indirect impacts among provinces and coastal zones. The indirect impacts of urbanization on vegetation GPP were generally positive in the northern and middle coastal zones, and they were negative in the southern coastal zones. The results indicated that measures can be applied in the coastal cities in order to mitigate the negative impacts of urbanization on GPP. Our findings are helpful for policymakers to make decisions on urban planning and management.

Effects of Urban Vibrancy on an Urban Eco-Environment: Case Study on Wuhan City

In the context of rapid urbanisation and an emerging need for a healthy urban environment, revitalising urban spaces and its effects on the urban eco-environment in Chinese cities have attracted widespread attention. This study assessed urban vibrancy from the dimensions of density, accessibility, liveability, diversity, and human activity, with various indicators using an adjusted spatial TOPSIS (technique for order preference by similarity to an ideal solution) method. The study also explored the effects of urban vibrancy on the urban eco-environment by interpreting PM 2.5 and land surface temperature using “big” and “dynamic” data, such as those from mobile and social network data. Thereafter, spatial modelling was performed to investigate the influence of urban vibrancy on air pollution and temperature with inverted and extracted remote sensing data. This process identified spatial heterogeneity and spatial autocorrelation. The majority of the dimensions, such as density, accessibility, liveability, and diversity, are negatively correlated with PM 2.5, thereby indicating that the advancement of urban vibrancy in these dimensions potentially improves air quality. Conversely, improved accessibility increases the surface temperature in most of the districts, and large-scale infrastructure construction generally contributes to the increase. Diversity and human activity appear to have a cooling effect. In the future, applying spatial heterogeneity is advised to assess urban vibrancy and its effect on the urban eco-environment, to provide valuable references for spatial urban planning, improve public health and human wellbeing, and ensure sustainable urban development.

Urban Air Chemistry in Changing Times

Urban air chemistry is characterized by measurements of gas and aerosol composition. These measurements are interpreted from a long history for laboratory and theoretical studies integrating chemical processes with reactant (or emissions) sources, meteorology and air surface interaction. The knowledge of these latter elements and their changes have enabled chemists to quantitatively account for the averages and variability of chemical indicators. To date, the changes are consistent with dominating energy-related emissions for more than 50 years of gas phase photochemistry and associated reactions forming and evolving aerosols. Future changes are expected to continue focusing on energy resources and transportation in most cities. Extreme meteorological conditions combined with urban surface exchange are also likely to become increasingly important factors affecting atmospheric composition, accounting for the past leads to projecting future conditions. The potential evolution of urban air chemistry can be followed with three approaches using observations and chemical transport modeling. The first approach projects future changes using long term indicator data compared with the emission estimates. The second approach applies advanced measurement analysis of the ambient data. Examples include statistical modeling or evaluation derived from chemical mechanisms. The third method, verified with observations, employs a comparison of the deterministic models of chemistry, emission futures, urban meteorology and urban infrastructure changes for future insight.

The Modeling Study about Impacts of Emission Control Policies for Chinese 14th Five-Year Plan on PM2.5 and O3 in Yangtze River Delta, China

The Chinese government has made great efforts to combat air pollution through the reductions in SO2, NOx and VOCs emissions, as part of its socioeconomic Five-Year Plans (FYPs). China aims to further reduce the emissions of VOCs and NOx by 10% in its upcoming 14th FYP (2021–2025). Here, we used a regional chemical transport model (e.g., WRF/CMAQ) to examine the responses of PM2.5 and O3 to emission control policies of the 14th FYP in the Yangtze River Delta (YRD) region. The simulation results under the 4 emission control scenarios in the 2 winter months in 2025 indicate that the average concentrations of city mean PM2.5 in 41 cities in the YRD were predicted to only decrease by 10% under both S1 and S1_E scenarios, whereas the enhanced emission control scenarios (i.e., S2_E and S3_E) could reduce PM2.5 in each city by more than 20%. The model simulation results for O3 in the 3 summer months in 2025 show that the O3 responses to the emission controls under the S1 and S1_E scenarios show different control effects on O3 concentrations in the YRD with the increase and decrease effects, respectively. The study found that both enhanced emission control scenarios (S2_E and S3_E) could decrease O3 in each city by more than 20% with more reductions in O3 under the S3_E emission control scenario because of its higher control strengths for both NOx and VOCs emissions. It was found that emission reduction policies for controlling high emission sectors of NOx and VOCs such as S2_E and S3_E were more effective for decreasing both PM2.5 and O3 in the YRD. This study shows that O3 controls will benefit from well-designed air pollution control strategies for reasonable control ratios of NOx and VOCs emissions.

Coupling Cellular Automata and a Genetic Algorithm to Generate a Vibrant Urban Form-A Case Study of Wuhan, China

Enhancing urban vitality is a key goal for both the government and ordinary urban residents, and creating this vitality is emphasized in China’s urban development strategy. Enhancing urban vitality through the rational design of urban forms is a leading topic of Western urban research. An urban growth pattern (UGP) reflects the dual characteristics of a static pattern and the dynamic evolution of the external urban form. It affects urban vitality by influencing the spatial allocation of internal structural elements and patterns in the adjacent location. The cellular automata (CA) mode can effectively simulate the aggregation process of urban growth (infilling expansion or edge expansion). However, it does not simulate the diffusion of urban growth, specifically the evolution of outlying expansion. In addition, CA focuses on learning, simulating, and building knowledge about geographic processes, but does not spatially optimize collaborative land use against multiple objectives or model multi-scale land use. As such, this paper applies a coupling model called the “promoting urban vitality model,” based on cellular automata (CA) and genetic algorithm (GA) (abbreviated as UV-CAGA). UV-CAGA optimally allocates cells with different UGPs, creating a city form that promotes urban vitality. Wuhan, the largest city in Central China, was selected as a case study to simulate and optimize its urban morphology for 2025. The main findings were as follows. (1) The urban vitality of the optimized urban form scheme was 4.8% higher than the simulated natural expansion scheme. (2) Compared to 2015, after optimization, the simulated sizes of the newly increased outlying, edge, and infilling areas in 2025 were 6.51 km², 102.69 km², and 23.48 km², respectively; these increases accounted for 4.90%, 77.32%, and 17.68%, respectively, of the newly increased construction land area. This indicated that Wuhan is expected to have a very compact urban form. (3) The infilling expansion type resulted in the highest average urban vitality level (0.215); the edge expansion type had the second highest level (0.206); outlying growth achieved the lowest vitality level (0.199). The UV-CAGA model proposed in this paper improves on existing geographical process simulation and spatial optimization models. The study successfully couples the “bottom-up” CA model and “top-down” genetic algorithm to generate dynamic urban form optimization simulations. This significantly improves upon traditional CA models, which do not simulate the “diffusion” process. At the same time, the spatial optimization framework of the genetic algorithm in the model also provides insights related to other effects related to urban form optimization, such as urban environmental security, commuting, and air pollution. The integration of related research is expected to enrich and improve urban planning tools and improve the topic’s scientific foundation.

How Does Urban Sprawl Affect Public Health? Evidence from Panel Survey Data in Urbanizing China

This study takes urbanizing China as the research object, employs data from three follow-up surveys conducted by the Harmonized China Health and Retirement Longitudinal Study, and examines the effects of urban sprawl on public health from physical and mental health perspectives. Although urban sprawl does not necessarily increase the risk of each specific type of disease or psychological feeling, it has a significant impact on overall physical and mental health. Further analysis reveals significant heterogeneity in the effects of urban sprawl on the physical and mental health of different groups. Specifically, urban sprawl is detrimental to the physical health of males and females, but only has negative impact on the mental health of females. Younger groups are more vulnerable to physical and mental health damage from urban sprawl relative to middle-aged and older groups. In addition, urban sprawl has a significant negative impact on the health of the low-education group but a very limited impact on the health of the high-education counterpart. From an income perspective, however, the preference for suburban housing among middle- and high-income groups makes their health more vulnerable to the negative effects of urban sprawl than low-income groups living in urban centers.

Impacts of Energy Efficiency and Economic Growth on Air Pollutant Emissions: Evidence from Angara–Yenisey Siberia

Environmental problems of urban and rural areas are now high on the agenda of industrialized countries, becoming a key challenge for regional-level policymaking. The mutual influence of population growth, economic and technological development, and the anthropogenic pressure on the environment is still insufficiently studied in many countries, including Russia. In this paper, this relationship is studied for the municipalities of Angara–Yenisey Siberia using an ensemble of the STIRPAT-like regression models, adapted according to the available data. We found that population size and gross municipal product were positively associated with pollutant emissions (p < 0.01), while energy efficiency had no significant impact on air pollution. In addition to the poor national data quality and completeness issues, which can distort statistical conclusions, the cause of the observed lack of spatial correlation between energy efficiency and air pollutant emissions may be path dependence and an insufficient pace of transition to a greener economy. This leaves room for institutional transformations aimed at intensifying energy efficiency to reduce the environmental burden.

How Does Low-Density Urbanization Reduce the Financial Sustainability of Chinese Cities? A Debt Perspective

Low-density urbanization threatens urban social and ecological sustainability not only directly by excessively encroaching on suburban farmland and ecological space, but may also indirectly do so by undermining the financial basis of sustainable urban development. To address this relationship, this study empirically examines the effect of low-density urbanization on local government debt by using panel data of prefecture-level cities in China from 2006 to 2015. Results show that the scale of local government debt increases significantly with a rise in urban expansion. Furthermore, this study found that low-density urbanization affects local government debt in two ways. First, low-density urban expansion reduces the land output efficiency, which decreases potential fiscal revenue and thus increases local government debt. Second, low-density urban expansion raises the construction and maintenance expenditure of urban infrastructure, which increases the demand for urban construction financing and thus pushes up the scale of debt. The results of the heterogeneous study indicate that low-density urbanization significantly affects local government debt mainly in Central/Western regions, small and medium-sized cities, cities with high fiscal stress and development pressure, and residentially expanding cities. On the contrary, low-density urbanization has no significant effect on the Eastern regions, large cities, cities with low fiscal stress and development pressure, and spatially expanding cities. This study theoretically explored and empirically verified a critical indirect effect of low-density urbanization on urban sustainability by increasing fiscal risks, which is, and will continue to be, a common and vital challenge faced by cities in China and other rapidly urbanizing developing countries.

Analysing the Driving Forces and Environmental Effects of Urban Expansion by Mapping the Speed and Acceleration of Built-Up Areas in China between 1978 and 2017

Abundant data sets produced from long-term series of high-resolution remote sensing data have made it possible to explore urban issues across different spatiotemporal scales. Based on a 40-year impervious area data set released by Tsinghua University, a method was developed to map the speed and acceleration of urban built-up areas. With the mapping results of the two indices, we characterised the spatiotemporal dynamics of built-up area expansion and captured different types of expansion. Combined with socioeconomic data, we examined the temporal changes and spatial heterogeneity of driving forces with an ordinary least square (OLS) model and a panel data model, as well as exploring the environmental effects of the expansion. Our results reveal that China has experienced drastic urban expansion over the last four decades. Among all cities, megacities and large cities in eastern China, as well as megacities in central and northeast China have experienced the most dramatic urban expansion. A growing number of cities are categorised as thriving, which means that they have both high expansion speed and acceleration. The overall driving force of urban expansion has significantly increased. More specifically, it was associated with population increase in the early stages; however, since 2000, it has been substantially associated with increases in GDP and fixed asset investments. The major driving factors also differ between regions and urban sizes. Urban expansion is identified as being closely associated with environmental deterioration; thus, speed and acceleration should be included as key indicators in exploring the environmental effects of urban expansion. In summary, the results of the presented case study, based on a data set of China, indicate that speed and acceleration are useful in analysing the driving forces of urban expansion and its environmental effects, and may generate more interest in related research.

Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-based Weighted Co-word Analysis

The purpose of this paper is to analyze the characteristics and human effects of atmospheric pollution in the Yangtze River Basin (YRB). An AQI(Air Quality Index)-based weighted co-word method is applied to explore the characteristics of keywords taken from the data, using authoritative media sources and government reports. Hierarchical clustering techniques are utilized to classify and visualize the keywords and display the different types of incidents. The results reveal the following four main clusters: enterprise pollution, coal-burning pollution, traffic pollution, and air pollutants. Cluster 1 is divided into 7 sub-clusters to offer powerful insight into the structural characteristics of industrial activities. This study is one of the first attempts to use a bibliometric approach to visualize the underlying and interconnected sub-clusters from grey data. It also provides an atmospheric pollution mapping for formulating government policies by understanding the human effects of air pollution incidents.

An Evaluation Model for Urban Comprehensive Carrying Capacity: An Empirical Case from Harbin City

Urbanization has brought notable benefits for cities, but has also resulted in severe and diverse challenges in China. Previous studies have contributed to the definitions and evaluation of urbanization. However, there remain a great deal of ambiguities regarding urban comprehensive carrying capacity, and its measurable indicators still need further exploration given the urban development. This study aims to explore a model for evaluating urban comprehensive carrying capacity and thus to promote urban development. A total of 48 indicators which fell into 8 subsystems were identified to evaluate the urban comprehensive carrying capacity through literature reviews and interviews. The indicator set was developed for evaluation indicator selecting. Meanwhile, the dynamic system was explored, and an evaluation model based on the entire array polygon method was designed to evaluate urban comprehensive carrying capacity. Finally, a case study was conducted to provide suggestions for the decision-maker to implement the evaluation model. The results of this study show that the evaluation indicator system was dynamic due to urban development. Meanwhile, the model of the entire array polygon method was able to effectively evaluate urban comprehensive carrying capacity through the case study. Furthermore, this study found that there is an imbalance among subsystems in urban development according to the standard deviation. The findings are useful for setting up a benchmark framework for urban sustainability and providing an evaluation and monitoring model for decision maker to improve the urban carrying capacity.

Spatial Heterogeneity in the Determinants of Urban Form: An Analysis of Chinese Cities with a GWR Approach

It is of great significance to investigate the determinants of urban form for shaping sustainable urban form. Previous studies generally assumed the determinants of urban form did not vary across spatial units, without taking spatial heterogeneity into account. In order to advance the theoretical understanding of the determinants of urban form, this study attempted to examine the spatial heterogeneity in the determinants of urban form for 289 Chinese prefecture-level cities using a geographically weighted regression (GWR) method. The results revealed the spatially varying relationship between urban form and its underlying factors. Population growth was found to promote urban expansion in most Chinese cities, and decrease urban compactness in part of the Chinese cities. Cities with larger administrative areas were more likely to have dispersed urban form. Industrialization was demonstrated to have no impact on urban expansion in cities located in the eastern coastal region of China, which constitutes the country’s most developed regions. Local financial revenue was found to accelerate urban expansion and increase urban shape irregularity in many Chines cities. It was found that fixed investment exerted a bidirectional impact on urban expansion. In addition, urban road networks and public transit were also identified as the determinants of urban form for some cities, which supported the complex urban systems (CUS) theory. The policy implications emerging from this study lies in shaping sustainable urban form for China’s decision makers and urban planners.

How Does Polycentric Urban Form Affect Urban Commuting? Quantitative Measurement Using Geographical Big Data of 100 Cities in China

The relationship between polycentric urban form and urban commuting has been widely debated in Western academic circles. However, qualitative and quantitative studies have not reached a unified conclusion. The evolution of urban form in China is remarkably different from that of developed Western countries. Many Chinese cities have begun using polycentric structures as their future development strategies. This study quantitatively measures whether polycentric urban form can improve commuting efficiency in China by using traditional statistics and emerging geographic big data. We use the polycentric index (PI) as the dependent variable and the congestion delay index (CDI) and mean traffic speed (MTS) as the main independent variables. Control variables include urban morphological space compactness (CT), number of private cars per thousand people (PC), number of buses per thousand (PB), urban road area per capita (PUA) and urban population density (PD). Regression models are employed to detect the relationships among the variables. The main research conclusions are as follows: (1) A high degree of PI results in low CDI and fast MTS; (2) a compact spatial form increases the impact of polycentricity on commuting efficiency; (3) maturity road infrastructure is an important measure to promote urban commuting under a polycentric urban form; and (4) the order of effect magnitude of polycentricity on MTS is PD > PC > CT > PUA > PB; on CDI, PD > PC > PB > CT > PUA. The results can be used in examining whether the current polycentric urban pattern planning in China’s cities can effectively improve commuting efficiency. They also provide a reference for the healthy development of China’s urban space and policy formulation of subsequent urban planning.