City Size Research Articles

Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model.

Based on the panel data of 227 prefecture-level and above cities in China from 2002 to 2018, a panel linkage equation model is constructed to explore the bidirectional influence relationship between haze pollution and urban sprawl, and the results of the study find that, firstly, there is a bidirectional promotion of causality between haze pollution and urban sprawl. That is, PM2.5 not only has a significant positive effect on urban sprawl, but also urban sprawl has a significant positive correlation with haze pollution, which is further strengthened by adding the air flow coefficient instrumental variable. Second, the heterogeneity analysis yields that haze pollution has different effects on urban sprawl in different regions. Under the sub-regional samples, haze pollution and urban sprawl have a bi-directional significant negative impact relationship in the eastern region, none of the haze pollution and urban sprawl have a bi-directional significant impact relationship in the western region, but both the central region and the northeastern region have a significant positive impact relationship. Under different city sizes, haze pollution and urban sprawl in large, medium and small cities have a bi-directional significant positive impact relationship, and from the numerical size, the degree of influence of haze pollution on urban sprawl in large cities is greater than that in small and medium cities; while the degree of influence of urban sprawl on haze pollution in medium cities is greater than that in large and small cities. Accordingly, it is proposed that urban governance should be adapted to local conditions, focus on innovative technologies to reduce energy consumption, and utilize big data to manage cities.

Exploring the influence of transportation on urban spatial structure using the spatial Durbin model: evidence from 265 prefecture-level cities in China

The interactive relation between transportation and urban spatial structure remains a significant yet challenging issue in transport engineering and urban planning. Most previous studies indicate that the coordination of transportation and urban structure is conducive to solve urban diseases and promote urban sustainable development. Grounded in the theory of city-region spatial structure, this study examines the spatiotemporal dynamics of urban spatial structure from 2006 to 2019 and investigates the impact of transportation on shaping urban spatial structure in prefecture-level cities in China using spatial Durbin model. Major findings include: first, the nighttime light remote sensing data is employed to characterize urban spatial structure with the mono-centricity index ranging from 0.26 to 0.48. The coastal cities tend to exhibit the polycentric structure, while the cities in western region often display the monocentric structure. Second, there is a gradual decline in mono-centricity structure in these cities. Spatial heterogeneity in urban spatial structure is evident in eastern, central, western and northeastern China. Third, transportation significantly and positively influences spatial structure, however, the impact varies across regions and city sizes. Finally, policy implications are proposed based on these findings, such as promoting the integrated land use-transportation development, implementing targeted regional policies, and enhancing land use spatial planning.

Seasonal anthropogenic heat fluxes over 200 cities in China: An investigation of driving factors with three-dimensional building forms

Various studies have highlighted substantial the impact of urban development on AHFs. Therefore, it is crucial to investigate the factors that influence AHFs to develop effective development and planning strategies for mitigating urban heat. This study chose 200 cities in China to explore seasonal variations in AHFs, and how anthropogenic activities, natural factors, and urban structures interact to impact AHF changes. We synergistically utilized remotely sensed technology, the energy-consumption inventory method, and meteorological in-situ observation to develop a spatiotemporal downscaling method of AHF. In addition, we utilized the Multi-scale Geographically Weighted Regression (MGWR) model to explore how socioeconomic, blue-green spaces, and urban structures interact to influence AHF variations. We further evaluated how city size and economic zones alter the composition of dominant factors concerning AHF. Results show that cities highest AHF values were observed in north, northwest, and northeast China, where the AHF reached 85.58 W m−2. Vegetation and water body play a crucial role in explaining AH emissions, followed by urban area, building coverage, building volume, and GDP per capital. The modification effects of economic zones were higher than city sizes. The results offer valuable insights for sustainable development strategies geared towards alleviating heat-related challenges in urban environments.

Exploring Urban Compactness and Greenhouse Gas Emissions in the Road Transport Sector: A Case Study of Big Cities in South Korea

This study examined the relationship between urban compactness and greenhouse gas (GHG) emissions in the road transport sector in South Korea, focusing on 84 cities, particularly 27 metropolitan areas with populations of approximately 500,000. We developed an urban compactness index (UCI) using Moran’s I, entropy, and the Gini coefficient, integrating city size into the analysis. Cities were categorized into five groups based on their size to analyze GHG emissions and regional variations in compactness comparatively. Our results revealed a significant inverse relationship between UCI and per capita road transport GHG emissions, which was more pronounced in larger cities. Specifically, cities with a population over 1 million displayed reduced per capita road transport GHG emissions in compact urban structures. In conclusion, these findings suggest that larger cities can effectively reduce per capita road transport GHG emissions through urban planning for compact development. Additionally, planners need to consider city size when analyzing the UCI and formulating urban planning strategies aimed at achieving carbon neutrality.

The Perceived Role of Non-Elected Actors in Community Power Structure in Poland: Results of a Survey Experiment

Administrative decisions can be influenced not only by policies formulated by elected representatives but also by various external actors. From classic elitist and pluralist theories of community power to urban regime and network governance concepts, academic studies tell us that several institutional and individual actors with no electoral democratic legitimacy may have a significant impact on local government decision-making. In our paper, we ask the question who they are in contemporary Polish cities. Are there any systematic regularities in this respect concerning e.g. how they differ depending on the size of the local community? In this paper we look at the phenomenon through the lens of citizens’ perception of the influence on important administrative decisions made in local governments. In this research, we also check whether the style of local political leadership perceived by citizens is reflected in their expectations toward the propensity of local authorities to consider the opinions. Data is collected through a survey conducted on a representative sample of 2,000 Polish citizens who were asked about their perception of the impact of various business and societal actors. The study uses the survey experiment method in which various formulations of the question are randomly assigned to individual respondents, which allows us to measure the perceived influence of individual types of actors. Referring to the recent debate on the limitation of the applicability of regime theory to large cities only, we place a special attention to the impact of city size on the role of big and small businesses as well as various societal organizations.

Environmental performance driven optimization of urban modular housing layout in Singapore

ABSTRACT With the growing size of cities and the need to renew residential areas, architects are calling for more efficient use of already settled areas. This paper presents a performance-driven architectural design (PDAD) workflow for shape generation and genetic optimization based on environmental data, using public housing in the Singapore region as a case study. It integrates three-dimensional cellular automata, parametric performance simulation, genetic optimization algorithms, and hierarchical clustering algorithms. The results show that the average value of Useful Daylight Illuminance (UDI) is 85.19%, the average value of Energy Use Intensity (EUI) is 159.41 kWh/m2, and the average value of Predicted Mean Vote (PMV) is 0.64 for the optimal set of solutions produced after genetic optimization. The optimal solution set was further classified into 4 categories by a hierarchical clustering algorithm and was visualized for further evaluation and selection by the architect. The study helps architects to integrate data analysis results with human decision-making as a design research method in the early stages of design and leads to further discussion on bottom-up design approaches in the urban renewal process.

Unpacking urban scaling and socio-spatial inequalities in mobility: Evidence from England

Prior research on the scaling of city size and inequality has a primary focus on economic factors such as income. Limited research has addressed socio-spatial disparities in mobility, involving physical activities and social interactions among individuals and population groups. Utilising mobile phone app data, this study measured inequalities using multiple mobility-related indicators (i.e. the number of activity points, the radius of gyration, self-containment, and social interaction indices) and related to population size by scaling models. In England’s context, these indicators unfolding mobility patterns and social issues display different scaling regimes, varying from sublinear to super-linear. It was observed that larger cities are associated with greater social interactions, particularly among socioeconomically advantaged groups; however, they also exhibit exacerbated self-segregation. Due to the radiation effect of big cities, the performances (e.g. travel radius) of small surrounding towns deviate from the predicted values of scaling models. Within cities, the evenness of indicators is independent of population size and produces distinct spatial patterns. The findings expand upon previous research and provide a more nuanced understanding of the complex relationship between city size, urban inequality, and human mobility.

A Study on the Changes of Green Total Factor Productivity in Chinese Cities under Resource and Environmental Constraints

Confronting the dual challenges of excessive resource consumption and environmental pollution, the traditional extensive economic development pattern significantly impeded the high-quality development of the Chinese economy. Examining variations in green total factor productivity across different types of cities holds substantial practical significance for promoting coordinated regional development and facilitating the green transformation of urban economies. Panel data from 283 cities in China spanning the years 2006 to 2020 were selected for analysis. The window-Malmquist–Luenberger index model, incorporating a mixed distance function, was employed to assess changes in green total factor productivity among the sample cities. The results were then categorized and analyzed based on different city attributes. The findings indicate that (1) the variation in green total factor productivity across China’s four major regions from 2006 to 2020 is generally characterized by an initial decline followed by an increase; (2) the proportion of cities with significantly improved green total factor productivity decreases from the east to the central, western, and northeastern regions; (3) the increase in green total factor productivity is positively correlated with city size, suggesting that larger cities experience higher growth in green total factor productivity; (4) first- and second-tier cities exhibit a relatively high mean value of green total factor productivity growth, while third-, fourth-, and fifth-tier cities demonstrate relatively lower growth.

Digital financial inclusion, resident consumption, and urban carbon emissions in China: A transaction cost perspective

Using data from 283 Chinese cities from 2011 to 2018, this study empirically investigates the impact of digital financial inclusion on urban carbon emissions. We conclude that digital financial inclusion significantly promotes urban carbon emissions. Moreover, as urban carbon emissions increase, the marginal effect first grows and then dwindles. A further investigation shows that digital financial inclusion significantly promotes urban carbon emissions by increasing resident consumption. Finally, we find that the impact of digital financial inclusion on urban carbon emissions is heterogeneous in terms of city size, city rank, and the commercial credit environment. In addition, digital financial inclusion has spillover effects on urban carbon emissions. It delivers positive effects on the local city while imposing significant suppressing effects on carbon emissions in neighbouring cities. The reason possibly is that digital financial inclusion in China is still in its early stage and it delivers ‘polarization effects’.

The impact of city size on income inclusive growth: A human capital perspective and evidence from China.

This paper methodically investigates the influence of inclusive income growth on city size, examining it through the dual lenses of "income" and "distribution." The analysis leverages meticulously collected panel data encompassing 276 Chinese cities at the prefecture level and above, spanning the period from 2005 to 2019. Theoretical analysis indicates that the effect of city size expansion on per capita income adheres to a 'U'-shaped trajectory, while its influence on the urban-rural income gap manifests an 'inverted U' pattern. Moreover, the inclusive income growth stemming from city size demonstrates notable heterogeneity across various geographic locations and city hierarchies. The findings reveal that human capital serves as the primary mechanism through which city size influences inclusive income growth. After decomposing the income inclusiveness index, it becomes evident that the expansion of city size exerts a more potent direct driving effect on the income of urban residents. On the one hand, city size expansion directly increases rural residents' income levels by improving labor productivity. On the other hand, it facilitates leapfrog income development by inducing the rural labor force to move to cities.

Can the construction of a high-speed rail alleviate haze pollution: an empirical analysis based on social networks and dynamic spatial econometric models.

With the increase in haze pollution in Chinese cities, answering the question of whether using a high-speed rail (HSR) as a green and efficient transportation system can alleviate haze pollution in China has become a research hotspot. This study empirically tests the impact of HSR network construction on haze pollution and its spatial spillover effects. (1) The construction of a HSR would have a mitigation effect on haze pollution in node cities and surrounding cities, and the more developed the HSR is, the more significant that this effect would be. (2) Haze pollution persists for a long time, the haze pollution from the previous year may have a positive promoting effect on the haze pollution in the following year. (3) The use of a HSR reduces haze pollution by replacing traditional road transportation and promoting industrial structure upgrading and technological innovation. (4) The inhibitory effect of HSR use on haze pollution varies due to regional differences and variation in city size.

Trading our way to a greener future: how environmental rights trading reduces urban carbon emissions in China-empirical analysis based on China's emission rights trading.

Environmental rights trading (ERT) is considered one of the crucial instruments for environmental governance in China, accelerating urban low-carbon sustainable development. This study utilized the Chinese Emissions Trading System (ETS), which has been implemented most widely, longest, and most typical, to represent ERT and examine its contribution to urban carbon emission reduction. Through a quasi-natural experiment perspective, urban panel data were collected from 2003 to 2019, and a time-varying difference-in-differences model and moderating models were developed. The study indicates that ERT can significantly reduce carbon emissions in cities, with robust results. In addition, the carbon reduction effect of ERT varies by city region, type, and size. This phenomenon is more obvious in central and western cities and resource-based cities. Finally, a framework to strengthen the carbon reduction effect of ERT was creatively constructed. The strengthening effects of green innovation, industrial structure, and clean energy are evident. This helps provide evidence for ERT layout and extension, especially in countries with high carbon reduction needs such as China. ERT affects not only policymakers but also a greener future for every organization and individual in the city.

Trade liberalization, city size, and urban wage premium: evidence from China’s city and individual micro-data

In the context of trade liberalization and new urbanization, it is important to study how urban openness leads to wage premiums and improvements in income distribution. This paper utilizes micro-data from the Chinese Household Income Project and matching data from 144 cities to investigate the relationship between trade liberalization, urban scale, and urban wage premiums. The results indicate that trade liberalization significantly increases urban wage premiums, which is particularly evident during the early stages of China’s accession to the WTO. However, this effect may fluctuate over time. Surprisingly, in China, the urban scale can increase labor wage income, but it does not magnify the wage premium effect of trade liberalization. Heterogeneity tests based on regions, firms, and income groups suggest that the wage premium effect of trade liberalization is higher in eastern and central region cities than in western region cities, labor wage growth in the service sector is more pronounced than in the industrial sector, and the impact of trade liberalization on wage growth for the middle and lower-income groups is greater than for the high-income group, which helps to narrow income disparities among different groups. These findings are of great policy significance for improving income distribution through labor market liberalization. In this context, they highlight the importance of comprehensive openness and new urbanization in China.

Spatial earnings inequality

Earnings inequality in Germany has increased dramatically. Measuring inequality locally at the level of cities annually since 1985, we find that behind this development is the rapidly worsening inequality in the largest cities, driven by increasing earnings polarisation. In the cross-section, local earnings inequality rises substantially in city size, and this city-size inequality penalty has increased steadily since 1985, reaching an elasticity of .2 in 2010. Inequality decompositions reveal that overall earnings inequality is almost fully explained by the within-locations component, which in turn is driven by the largest cities. The worsening inequality in the largest cities is amplified by their greater population weight. Examining the local earnings distributions directly reveals that this is due to increasing earnings polarisation that is strongest in the largest places. Both upper and lower distributional tails become heavier over time, and are the heaviest in the largest cities. We establish these results using a large and spatially representative administrative data set, and address the top-coding problem in these data using a parametric distribution approach that outperforms standard imputations.

Using the Degree-Day Method to Analyze Central Heating Energy Consumption in Cities of Northern China

In the context of global population growth and energy scarcity, building energy consumption has become a critical issue with implications for the sustainable development of human society. Winter heating consumption constitutes a large portion of total energy used in buildings, especially in regions with cold climates. This paper employs the degree-day method to analyze the energy consumption of central heating in northern Chinese cities. The study sample consists of 60 target cities, including 30 located in severe cold regions and the remaining 30 in cold regions. By utilizing heating energy consumption and climate data from 2019, the relationships between heating intensity (kWh/m2) and heating degree days (HDDs) are established for the selected cities. Additionally, statistical analysis and model comparisons are conducted. The results show strong positive correlations between heating intensity and HDDs in both severe cold regions and cold regions, with the actual heating base temperatures for the two regions being 21 °C and 22.3 °C, respectively. Moreover, the deviation index of heating intensity is introduced to analyze the energy consumption characteristics of central heating in northern cities from three perspectives: city size, level of heating development, and geographical regions. The analysis suggests that cities with large population, strong economies, and high levels of development exhibit better energy-saving performance. Lastly, several improvement suggestions are proposed to address the potential problems related to energy conservation of central heating systems in cities of northern China.

Depressive disorder benefits of cities: Evidence from the China

BackgroundRapid urbanization is a major trend in global population migration. There is growing debate about whether this urban-rural disparity exacerbate depression at the individual level. This study aims to investigate how urban living has a beneficial impact on individual mental health. MethodsBased on the data of 15,764 participants in the 2018 China Health and Retirement Longitudinal Study (CHARLS), we perform analysis of variance to identify the gap in depression levels between urban and rural areas. Extensive comparisons and detailed statistical analyses are carried out to demonstrate the differences in social participation between urban and rural residents. Finally, we conduct a series of mediation and moderation analyses to reveal the underlying mechanisms of depressive disorder benefits of cities. ResultsThe results indicate that those who lived in urban areas were less likely to suffer from depression (β = −1.461, 95 % CI = [−1.691, −1.235], p < 0.001). Social engagement is found to mediate the relationship between residence type (β = 0.164, 95 % CI = [0.136, 0.193], p < 0.001) and individual depression (β = −0.462, 95 % CI = [−0.587, −0.337], p < 0.001). City size plays a moderating role in the association between urban living and social engagement. LimitationsThe mechanism is conducted through cross-sectional data. Self-reported depression status is accessed in this study, which could lead to measurement error. ConclusionThis study demonstrates the beneficial effects of urban living on individual depression, and reveals the mechanism by which urbanization at different scales affects the prevalence of depression.

What can urban transport policy achieve? How transport-policy-invariant characteristics relate to city-level car ownership and car use

Most case and comparative studies discuss urban characteristics that can hardly be influenced by urban transport policies. However, these studies do not quantify the impact of the so-called contextual factors on car ownership and car use. This paper focuses on these contextual factors and their associations with car ownership and car use. Regression models show that contextual factors - such as city size, the share of households with children and the jobs-housing balance - explain a substantial part of the variance in car ownership and car trips in 44 German cities. Residual analyses reveal that neglecting contextual factors leads to biases in comparative studies and consequently in the evaluation of urban transport policies. Thus, there is a risk that cities with favourable contextual factors may be mistakenly viewed as successful examples of transport policy, whereas successful policies in cities with less favourable contextual factors may be overlooked.

Worldwide scaling of waste generation in urban systems

The production of waste as a consequence of human activities is one of the most fundamental challenges facing our society and global ecological systems. Waste generation is rapidly increasing, with corresponding shifts in the structure of our societies, where almost all nations are moving from rural agrarian societies to urban and technological ones. However, the connections between these societal shifts and waste generation have not yet been described. In this study we applied scaling theory to establish a new understanding of waste in urban systems and identified universal scaling laws of waste generation across diverse urban systems worldwide for three forms of waste: wastewater, municipal solid waste, and greenhouse gases. We found that wastewater generation scales superlinearly, municipal solid waste scales linearly, and greenhouse gas emissions scale sublinearly with city size. In specific cases, production can be understood in terms of city size coupled with financial and natural resources. For example, wastewater generation can be understood in terms of the increased economic activity of larger cities, and the deviations from the scaling relationship, indicating relative efficiency, depend on gross domestic product per person and local rainfall. The temporal evolution of these scaling relationships reveals a loss of economies of scale and a general increase in waste production, where sublinear scaling relationships become linear. Our findings suggest general mechanisms controlling waste generation across diverse cities and global urban systems. Our approach offers a systematic framework to uncover these underlying mechanisms that might be key to reducing waste and pursuing a more sustainable future.

Life satisfaction along the urban-rural continuum: a global assessment

ABSTRACT This paper assesses differences in life satisfaction along the urban-rural continuum in 111 countries across the globe. It combines survey data with a consistent definition of settlements to maximize international comparability. Once controlled for observed individual characteristics, differences in life satisfaction between people living in cities and in rural areas change with development levels. We found a positive difference at low development levels, which disappears or reverts for high-income countries. Among the factors associated with such differences are city-rural gaps in reported health problems, in physical infrastructure (built-up area), in expectations for future economic conditions, as well as in perceived housing affordability. We also show that life satisfaction varies by city size. Globally, large cities between one and five million inhabitants drive the observed city-premium, with stark heterogeneity across income levels. More specifically, residents in large metropolises over five million inhabitants report the highest and lowest life satisfaction in low- and high- income countries, respectively.

The effect of city size on the disability rate of the older adults: empirical evidence from CHARLS data.

Exploring the value orientation of city development from the perspective of people's well-being is key to clarifying the current debate on city size strategies. Based on the survey data of the China Health and Retirement Longitudinal Study in two phases, and by using the unbalanced panel-ordered logit model, stepwise analysis method, and KHB method, among others, we discuss the impact of city size on the disability rate of older adults. The study finds that city size significantly and positively affects the activities of daily living (ADL) of older adults, with odd ratios of 1.3286 (95% CI = [1.082243, 1.631089]), and exhibits significant group heterogeneity in terms of age, registered residence, income, and education level. City size has indeed played an mediation role through the health improvement effect, disease mitigation effect, emotional effect, and employment structure optimization effect, with a cumulative contribution rate of the mediation effect of 35.17%. In addition, the urban sprawl index has a significant moderation role. Robust urban sprawl is conducive to promoting the improvement of the regional health environment, the improvement of the medical security policy, the optimization of the family support policy, and the employment structure, thus helping to reduce the disability rate of older adults.