Fast Urban Development Research Articles

Microplastics and Endocrine Disruptors in Typical Wastewater Treatment Plants in Megacity Shanghai.

The fast development of China's urbanization has led to a notable release of emerging pollutants, including microplastics (MPs) and endocrine disruptors (EDCs). Generally, these pollutants enter the coastal environment through the discharge of wastewater treatment plants (WWTPs) and finally threaten the organisms in the receiving waterbody. The study investigated the environmental behavior of MPs and EDCs in two typical WWTPs in one of the megacities in China, Shanghai. The abundance of MPs in the influent ranged from 321 to 976 items/L. Four shapes (films, fragments, fibers, and microbead) were found, while fibers and films dominated. Transparent (31-63%) and white (20-47%) MPs were more frequently observed, while polyethylene terephthalate, cellulose, and cellophane were the main polymetric materials. The size of the MPs fell between 15.8 μm and 2220 μm, and the smaller one (<500 μm) dominated. The removal efficiencies of the two WWTPs for MPs ranged from 64% to 92%, and both WWTPs performed better for large pieces of MPs (>500 μm). For EDCs, total concentrations in the influent were detected, ranging from 113 to 2780 ng/L. Two groups, including phenolic estrogens (PEs) and steroid estrogens (SEs), were detected, and PEs, especially bisphenol A (BPA), were the predominant individuals among the studied EDCs. Specifically, PEs ranged from 82.8 to 2637 ng/L, while SEs ranged from 27.3 to 143 ng/L. The removal efficiencies of the WWTPs for EDCs varied (82.8-100%) as well, possibly due to the different treatment compartments and contamination load in the influent. Seasonal variations for both MPs and EDCs were observed. Specifically, concentrations of MPs and EDCs in WWTPs influent were higher in the wet season, as well as the removal efficiency. Furthermore, there was a correlation observed between the concentrations of MPs and EDCs, suggesting that MPs and EDCs may originate from the same source and that EDCs released by MPs cannot be ignored during treatment. Finally, the study evaluated the environmental risk of the effluents. MPs led to a minor risk (Level I), while EDCs might lead to an adverse impact on algae (RQs = 0.0014-0.024) and fish (RQs = 3.4-30.2). In summary, WWTPs received considerable amounts of MPs and EDCs. Although the WWTPs removed the contaminants efficiently, the environmental risk of the effluent needs to be noted.

AUTOMATIC GENERATION OF ROUTING GRAPHS FOR INDOOR-OUTDOOR TRANSITIONAL SPACE TO SUPPORT SEAMLESS NAVIGATION

Abstract. With the fast development of urbanization, the complexity of built environments has dramatically increased, driving a need for assistance in seamless indoor-outdoor navigation. This requires integration of spatial information of indoor and outdoor environments from heterogeneous data sources. While outdoor road network data is largely available from many sources (such as OpenStreetMap), indoor spatial information is either inexistent or is inconsistently represented using several different standards. Among these standards, IndoorGML is a well-developed standard with the focus on indoor location-based services. This standard has already been accepted by Open Geospatial Consortium (OGC) and is now under active development. Although in IndoorGML some mechanisms have been defined to enable integration of indoor and outdoor networks, there is still a lack of concrete guidelines for determination of indoor-outdoor connections. It also lacks solid scientific foundations and efficient tools to extract the connecting nodes and edges that link indoor and outdoor spaces. To address this gap, in this study we focus on the connection of indoor and outdoor spaces and aim to provide a tool, which can automatically construct navigation graphs of the indoor-outdoor transitional space to support seamless integration of indoor-outdoor navigation. To this end, voxel-based modeling approaches are used to model the connecting space between indoor and outdoor environments. Based on Python, we develop the intended tool, which can generate voxel models from point clouds, identify navigable space by taking into account the characteristics of agents (such as pedestrians, wheelchairs, and vehicles), and automatically build navigation graphs linking IndoorGML networks with outdoor street networks. It is expected that the methodology and tools developed from this project will benefit the IndoorGML ecosystem and greatly advance the capability of IndoorGML in representing navigable space to support location-based services.

Effect of Green Credit Policy on PM 2.5 in China Based on Panel Regression Model

With Chinas fast economic and urban development, the problem of PM 2.5 has become increasingly apparent. Although China has announced the Green Credit Policy that aims to mitigate the air pollution problems, the effect of this policy is controversial. The data used in this paper contain measurements of PM 2.5 Level and other factors that can affect the PM 2.5 concentration in different areas of China from 2008 to 2018. By analyzing the data using Panel Regression Model, this paper will show the effect of Green Credit Policy on PM 2.5 and the differ-ences between its effects on the whole region, eastern, central and western region. It will also demonstrate how does green credit policy affect PM 2.5. The results illustrate that even though Green Credit Policy can reduce the concentration of PM 2.5 in general, the mitigation effect is not significant in eastern and central ar-eas. It also shows that the policy lowers PM 2.5 concentration by promoting technological progress and improving production efficiency. Moreover, urbaniza-tion and economic development play an important role in reducing the PM 2.5 level in all regions. High openness only affects PM 2.5 level in the western re-gions.

Understanding Urban Area Attractiveness Based on Private Car Trajectory Data Using a Deep Learning Approach

With the fast development of urbanization and motorization, an increasing number of people choose to buy private cars to fulfill their daily travel needs. In particular, many people from various positions of the city drive their cars to specified areas, and then they will stop and stay for a certain period of time, leading to a spatiotemporal evolution of urban area attractiveness (AA). In this paper, we aim at understanding urban AA based on analyses of private car trajectory datasets. Specifically, by extracting point-of-stop (PoS) data from the private car trajectories, we design the variational Bayesian Gaussian mixture models (VBGMM) to deduce the probability density distribution of PoSs and connect it to the variation of AA. We establish a deep learning model based on long short-term memory (LSTM) to capture the evolution of the AA. Furthermore, we integrate dropout in the LSTM method to address challenging issues such as overfitting and time-consuming training of complex neural networks in the AA prediction. We conduct experiments by using real-world private car trajectory data to evaluate the performance of the proposed method. The results validate that our proposed method outperforms existing ones in terms of various metrics. To the authors’ knowledge, our work is the first one to utilize private car trajectory data to study urban area attractiveness, thereby facilitating a new perspective regarding an understanding of human travel behavior and the evolution of urban mobility.

THE ROLE OF BLOCKCHAIN TECHNOLOGY IN SMART CITY

In late decades, the fast development of urbanization gives a huge headways in creating proficient, astute and practical arrangements. Keen city needs these arrangements in giving better administration of waste, water, electricity, land and different e-administration administrations. In this paper, Blockchain technology utilization for smart cities has been discussed.

Retracted] Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats

The fast urban development leads to many complex problems. A smart city aims to solve these problems using scientific approaches. Urban Green Space (UGS) is a fundamental component of urban infrastructure. It needs to be upgraded simultaneously with the concept of the smart city. Methods of smart UGS planning and sustainable landscape design help integrate ecological performance and other functions of UGS. Smart UGS planning is a technical management tool and a human‐centered smart application. A novel UGS classification method based on function combinations is proposed in the present work. Five types of UGS (Scenic UGS, Residential UGS, Commercial UGS, Office UGS, and Road UGS) in Baqiao District of Xi’an, Shaanxi Province, are selected as sample sites. Interviewees’ socio‐economic attributes, visiting frequencies, and differences in demands are investigated. Eventually, the UGSs researched in this work are optimized based on public preferences and the current conditions of the sites. Results demonstrate the following. (1) The public’s preference for different types of UGS is different considerably. (2) Based on the public’s preference, Scenic UGS is improved in terms of quantity, function, and management; Residential UGS is upgraded regarding quantity and accessibility; and Commercial UGS, Office UGS, and Road UGS are improved in terms of quality. The results could provide methodological references for planning different types of UGS and innovative insights for smart UGS planning and sustainable landscape design.

Intelligent transportation systems design based on mass customization

In this era characterized by fast development of urbanization, public transportation problem is one of the main obstacles for people to promote their life satisfaction in China. This paper aims at discussing problems on mass customization public transportation, providing suggestions and consults for its sustainable development and improvement. A mass customization model for public transportation is constructed based on client requirement and cost analysis, and case studies are made to validate route planning results. Results show that mass customization public transportation can make high profit for bus companies and relieve traffic congestion and air contamination.

The use of magnetic susceptibility and chemical analysis data for characterizing heavy metal contamination of topsoil in Denizli city, Turkey

Denizli is one of the most rapidly growing cities in Turkey having experienced fast urban and industrial development in the last decades, engendering a serious threat to the environment and the population health. Therefore, this study used the magnetic susceptibility method to evaluate the contamination degree of most parts of Denizli city. X-ray fluorescence (XRF) analysis was performed on samples chosen from different parts of the study area to identify the quantity and origins of the heavy metals present in the study area corresponding to the magnetic susceptibility measurements. Multivariate statistical analysis such as Cluster analysis (CA) and the principal component analysis (PCA) was performed for the best understanding of the relationship between heavy metal contamination, magnetic susceptibility measurements and XRF analysis results. The environmental status of the study area was evaluated by the aid of elaboration and interpretation of the contamination factor (CF), geoaccumulation index (Igeo), Enrichment factor (EF) and the pollution load index (PLI) which allowed the comparison between the different polluted parts of the study area. The results obtained as maximum values from the calculation of the contamination factor were found as follows: Fe (30.98), Cr (25.86), Ni (14.71), Zn (9.24), Cu (7.96), Pb (5.86). The mean values obtained for the implemented geoaccumulation index were found for each element as follow; Fe (4.39), Cr (4.12), Ni (3.29), Cu (2.44), Pb (2.01) Zn (2.62) while the enrichment factor's results were found as follow Fe (11.80), Cr (11.07), Ni (5.90), Cu (3.87), Pb (2.71) Zn (4). The average value of the pollution load index reflects the heavy pollution of the study area by reaching a value of 7.7. The contour maps plotted for the distribution of heavy metals concentration and magnetic susceptibility measurement showed similar pollution degrees in the city industrial zone and near the main highway (Antalya Highway), which passes through the city. This high heavy metal load gradually decreases toward the city borders. Furthermore, the content of heavy metal and the PLI are notably positively correlated with the magnetic susceptibility measurements. Overall, results testify to the effectiveness of the magnetic susceptibility method for applications in determining environmental contamination caused by heavy metals.

Urban Environmental Design, Guidelines in Creating a Balanced Singapore: Lessons for the Urban Communities in Thailand

Singapore has many limited resources. But at the same time can develop the country and preserve the environment of the city in a balanced and sustainable way. Therefore, the design of the city on this issue of Singapore is being taken to study the guidelines, as well as bringing the ideas to be presented to the urban communities that are experiencing environmental problems. Thailand has considered applying, and from the study found that Singapore’s urban development is consistent with universal theory, sustainable development, Smart City, compact city and livable city. And when analyzing these theories together with Singapore’s urban environment design, can summarize the guidelines into 4 main issues which are the Guidelines for balancing the city, the Guidelines for linking areas and activities within the city, the Guidelines for land using and urban planning, and the Guidelines for designing landscape elements that promote the good environment in the city. Moreover, building confidence by creating a sense of the country ownership together, as well as the state and the people participation in the development process is an important factor that makes Singapore a fast urban development among the “Good urban environment”.

Spatiotemporal analysis of urban growth on forest and agricultural land using geospatial techniques and Shannon entropy method in the satellite town of Ethiopia, the western fringe of Addis Ababa city

Rapid conversion of conserved land and cropland to non-agricultural purposes is threatening the ecological areas and dominant agricultural activities that are the main sources of livelihood in urban fringe areas of Addis Ababa City. The combinations of government policy, socioeconomic, demographic dynamics, and biophysical triggers have driven such transformation. However, the recent fast urban expansion and infrastructural development could have accelerated the severity and rate at which urban growth impacts the ecosystem and fertile agricultural land. Yet, little attention is given about their impacts on forest and farming communities in the western fringe areas of Addis Ababa during the recent past. This study, therefore, aimed at quantifying and analyzing the trends of the urban growth and its impacts on flora and agricultural land in Sebeta-Awas town using an integrated GIS tool, remote sensing technique, and Shannon entropy method. Landsat TM of 1986, ETM+ of 2002, and OLI of 2019 were used to produce land use/land cover (LULC) classes. Object-based classification technique was carried out to generate the LULC and to measure the changes in the urban land-use class within the satellite town in the year 1986, 2002, and 2019. Shannon entropy method was applied to model study area’s urban sprawl, growth trend, and spatial change. Over the past three decades (1986–2019), Sebeta-Awas town has experienced severe urban sprawl following lack of proper development control and management. The annual urban growth rates of 1.2, 5.5, and ~15% for the periods of 1986, 2002, and 2019, respectively were obtained mainly at the expenses of agricultural land (25.48%) and forest land (16.6%), catalyzed urban sprawl which finally led to serious deforestation and reduction in rural farmland. The findings indicate that the average of entropy index increased from 0.02 in the year 1986 to 0.996 in the year 2019, indicating more dispersed urban growth to the outskirts, and spatially indicating anticlockwise shifting. In this regard, more than 90.2% of forest loss due to agricultural encroachment, built-up area expansion, and construction was widely observed in Sebeta and Alem Gena areas, of course, Northeast zone in this study. It is concluded that deforestation and continual evacuation of farming communities in the urban fringe areas due to rapid urban expansion in the name of investment and infrastructural development is expected to be worsened in the near future unless strong policy revision and management actions are undertaken.

Flood vulnerability and risk assessment of urban traditional buildings in a heritage district of Kuala Lumpur, Malaysia

Abstract. Flood hazard is increasing in frequency and magnitude in major South East Asian metropolitan areas due to fast urban development and changes in climate, threatening people's property and life. Typically, flood management actions are mostly focused on large-scale defences, such as river embankments or discharge channels or tunnels. However, these are difficult to implement in town centres without affecting the value of their heritage districts and might not provide sufficient mitigation. Therefore, urban heritage buildings may become vulnerable to flood events, even when they were originally designed and built with intrinsic resilient measures, based on the local knowledge of the natural environment and its threats at the time. Their aesthetic and cultural and economic values mean that they can represent a proportionally high contribution to losses in any event. Hence it is worth investigating more localized, tailored mitigation measures. Vulnerability assessment studies are essential to inform the feasibility and development of such strategies. In this study we propose a multilevel methodology to assess the flood vulnerability and risk of residential buildings in an area of Kuala Lumpur, Malaysia, characterized by traditional timber housing. The multiscale flood vulnerability model is based on a wide range of parameters, covering building-specific parameters, neighbourhood conditions and catchment area conditions. The obtained vulnerability index shows the ability to reflect different exposure by different building types and their relative locations. The vulnerability model is combined with high-resolution fluvial and pluvial flood maps providing scenario events with 0.1 % annual exceedance probability (AEP). A damage function of generic applicability is developed to compute the economic losses at individual building and sample levels. The study provides evidence that results obtained for a small district can be scaled up to the city level, to inform both generic and specific protection strategies.

The Enlightenment of Cultural Identity in Coetzee’s Diaspora Writing on the Integration of New Citizens in China

As a diaspora writer, Coetzee has a deep understanding of the identity crisis, and his works reflect the profound thinking on this issue and the positive exploration of the solution to the problem. This paper starts with the narrative strategy of Coetzee’s works and analyzes that diaspora subject constantly encounters the identity crisis in the environment and through the expression of discourse constructs a new identity. This study examined the issue of identity of new citizens in the fast development of urbanization in China, which became an obstacle for them to get integrated to the city. After the analysis of questionnaire among new citizens, this study found that language use functions as a major element to influence their identity. Through the analysis of discourse mode and identity issues of Coetzee’s novels, the paper showed that the concept of respecting the individual, equality and harmony to get the identity adaptation of the new citizen is conducive to promoting the integration of different regional cultures, enhancing the understanding between people, and alleviating the personal pressure and social contradictions caused by the difficulties of integration. Thus the study can provide a feasible solution for the immigrant integration problem faced by new citizens in the process of urbanization in China.

Identifying Urban Structure Based on Transit-Oriented Development

The fast development of urbanization has led to imbalances in cities, causing congestion, pollution, and urban sprawl. In response to the growing concern over the distribution of demand and supply, a more coordinated urban structure is addressed in comprehensive planning processes. In this study, we attempt to identify urban structure using a Network–Activity–Human model under the Transit-Oriented Development (TOD) concept, since TOD is usually regarded as an urban spatial planning tool. In order to explore the strengths and weaknesses of the urban structure, we define the TOD index and unbalance degree and then classify the urban areas accordingly. We take the city of Beijing as a case study and identify nine urban types. The results show a hierarchical urban structure: the city center covers most of the hotspots which display higher imbalances, the surroundings of the city center are less developed, and the city edges show higher potentials in both exploitation and transportation development. Moreover, we discuss the extent to which the spatial scale influences the unbalance degree and apply a sensitivity analysis based on the goals of different stakeholders. This methodology could be utilized at any study scale and in any situation, and the results could offer suggestions for more accurate urban planning, strengthening the relationship between TOD and spatial organization.

Gut microbiota composition of Japanese macaques associates with extent of human encroachment.

In recent decades, human-wildlife interaction and associated anthropogenic food provisioning has been increasing and becoming more severe due to fast population growth and urban development. Noting the role of the gut microbiome in host physiology like nutrition and health, it is thus essential to understand how human-wildlife interactions and availability of anthropogenic food in habitats can affect an animal's gut microbiome. This study, therefore, set out to examine the gut microbiota of Japanese macaques (Macaca fuscata) with varying accessibility to anthropogenic food and the possibility of using gut microbiota as indicator for macaques' reliance on anthropogenic food. Using 16S ribosomal RNA gene sequencing, we described the microbial composition of Japanese macaques experiencing different types of human disturbance and anthropogenic food availability-captive, provisioned, crop-raiding, and wild. In terms of alpha diversity, our results showed that observed richness of gut microbiota did not differ significantly between disturbance types but among collection sites, whereas Shannon diversity index differed by both disturbance types and sites. In terms of beta diversity, captive populations harbored the most distinctive gut microbial composition, and had the greatest difference compared with wild populations. Whereas for provisioned and crop-raiding groups, the macaques exhibited intermediate microbiota between wild and captive. We identified several potential bacterial taxa at different taxonomic ranks whose abundance potentially could help in assessing macaques' accessibility to anthropogenic food. This study revealed the flexibility of the gut microbiome of Japanese macaques and provided possible indices based on the gut microbiome profile in assessing macaques' accessibility to/reliance on anthropogenic foods.

Functional Shift in Public Buildings. The Case of The Sport and Recreation Centre 'Boro and Ramiz'

It is evident that public buildings are crucial and inseparable elements for a society. While people perform in these spaces their everyday life activities, they get connected to each other as a community. Through these activities an emotional bond is created with these objects, becoming a meaningful presence for the city. All of these public spaces not only have a vital importance for people, but are closely associated with the society’s identity. In cities where fast urban growth and development has happened; several public buildings, once considered as monumental, have been left non-functional, partially unused or even converted their functional activity due to historical, political, social and economic changes. This phenomenon has negatively affected the overall condition of the city and its image. Such types of structures are evident in the central areas of Prishtina, which are considered as important identifying areas for the cultural and historical background of Kosova . The research takes in consideration the functional conversion of public buildings of the past in relation to the image of a city; also their importance to the society, represented by one of the most monumental structures located in Prishtina, “The Sport and Recreation Centre ‘Boro and Ramiz’”. Through analyzing the relation of this specific public building with the society, culture and memory, the importance of such building typology for maintaining the identity of a culture, and the necessity of these buildings to remain public and to maintain their function is expounded.

Endangered but genetically stable-Erythrophleum fordii within Feng Shui woodlands in suburbanized villages.

Feng Shui woodlands are naturally or artificially formed green areas in southern China. They are precious for maintaining ecosystem balance in modern semiurban environments. However, they are generally small and geographically isolated from each other, and the status of genetic diversity of the plant species within them has been almost neglected. Therefore, we studied the genetic diversity of the endangered Erythrophleum fordii in eight Feng Shui woodlands (a total of 1,061 individuals) in Guangzhou, a large city in southern China, using microsatellites. For comparison, one population with 33 individuals sampled in a nature reserve was also studied. Although our results indicate that significant demographic declines occurred historically in E. fordii, such declines have not resulted in consistent reductions in genetic variation over generations in Feng Shui populations in the recent past, and the levels of genetic variation in these populations were higher than or comparable to the genetic variation of the population in the nature reserve. In addition, our parentage and paternity analyses indicated widespread and potential long‐distance pollen flow within one Feng Shui woodland, indicating the presence of an unbroken pollination network, which would at least partially alleviate the genetic erosion due to habitat fragmentation and the unequal gene contributions of E. fordii parents to their progenies when favorable recruitment habitats are absent under most of the parent trees. Overall, our results suggest that E. fordii in Feng Shui woodlands may not be driven to extinction in the near future. Nevertheless, uncontrolled fast urban development with a lack of awareness of Feng Shui woodlands will cause the local extinction of E. fordii, which has already happened in some Feng Shui woodlands.

Identification of technology spillover among airport alliance from the perspective of efficiency evaluation: The case of China

The development of airport alliances has undergone hardships, although airport alliances have emerged simultaneously with other airline alliances in an attempt to improve competitiveness. Technology spillover is a major benefit of airport alliances, but the effects of such spillover are not as obvious as might be expected. This paper proposes a three-stage DEA-based methodological framework to uncover the existence and characteristics of technology spillover among allied airports, and identify whether the technology spillover of airport alliances outperforms the self-development of airports. A case study that concerns multi-airport companies and non-allied airports in China, where airports and airlines are rapidly expanding, is included. The results show that the technology spillover of airport alliances does not become wide spread among all of the allied airports, which is most likely because civil aviation in China is still in a stage of rapid development. However, such spillover does appear among small- and mid-sized allied airports in cities with fast urban economic development. Finally, the related implications of our methodological framework are discussed along with our findings.

Explore an evolutionary recurrent ANFIS for modelling multi-step-ahead flood forecasts

Reliable and precise multi-step-ahead flood forecasts are crucial and beneficial to decision makers for mitigating flooding risks. For a river basin undergoing fast urban development, its regional meteorological condition interacts frequently with intensive human activities and climate change, which gives rise to the non-stationary process between rainfall and runoff whose non-stationary features is difficult to be captured by a non-recurrent data-driven model with a static learning mechanism. This study proposes a recurrent Adaptive-Network-based Fuzzy Inference System (R-ANFIS) embedded with Genetic Algorithm and Least Square Estimator (GL) that optimize model parameters for making multi-step-ahead forecasts. The main merit of the proposed method (R-ANFIS(GL)) lies in capturing the features of the non-stationary process between rainfall and runoff series as well as in alleviating time-lag effects encountered in multi-step-ahead flood forecasting. To demonstrate model reliability and effectiveness, the R-ANFIS(GL) model was implemented to make multi-step-ahead forecasts from horizons t + 1 up to t + 8 for a famous benchmark chaotic time series and a flood inflow series of the Three Gorges Reservoir (TGR) in China. For comparison purpose, two ANFIS neural networks of different structures (one dynamic and one static neural networks) were also implemented. Numerical and experimental results indicated that the R-ANFIS(GL) model not only outperformed the two comparative networks but significantly enhanced the accuracy of multi-step-ahead forecasts for both chaotic time series and the reservoir inflow case during flood seasons, where effective mitigation of time-lag bottlenecks was achieved. We demonstrated that the R-ANFIS(GL) model could suitably configure the complex non-stationary rainfall-runoff process and effectively integrate the monitored rainfall and discharge data with the latest outputs of the model so that the time shift problem could be alleviated and model reliability as well as forecast accuracy for future horizons could be significantly improved.

Recent Progress in Urban Flood Risk Management in the Typhoon Committee Area

ABSTRACT The typhoon region is urbanizing rapidly with the increasing trend of population and economy. Fast urban development has also brought many potential troubles, and urban flooding is one of the most serious. Many aspects of urban areas are vulnerable to flood disasters and climate change. How to minimize losses caused by urban floods and harmonize relationship between floods and socio-economic development has been a significant problem that governments and international organizations work on. In recent years, risk management ideas have been introduced into flood management in the Typhoon Committee Area (TCA). This paper presents a brief review of urban flood issues and flood management in the TCA, and identifies good practices and research progress of urban flood risk management from the model cities study. In addition, some ideas about the improvement of urban flood risk management are also discussed in the paper.

What Is the Efficiency of Fast Urbanization? A China Study

Urbanization is commonly described as the process of population flow from rural to urban areas. As the largest developing country, China has experienced an unprecedentedly fast and large urbanization process since 1980s, which will continue for the coming future. The immense scale of the process has brought multidimensional benefits across all sectors in the country, yet also consumed a vast amount of resources and caused various types of environmental problems. The conflict between limited resources and an unstoppable urbanization process has become a pressing issue, which presents the urgent need for efficiency pursuance in the process of urbanization in order to ensure sustainable urban development. It is considered that the improvement of urbanization efficiency in large developing countries such as China has great implications for global sustainability. There is little existing study conducted to understand what efficiency achieved in the current fast urban development era in China. This study investigates the urbanization efficiency and its changes in the contemporary China. A set of input-output indicators are employed for analyzing the efficiency, in which both desirable and undesirable outputs are considered. The Super-efficiency Slack-based Measure (SBM) model and DEA-based Malmquist Production Index (MPI) are adopted collectively for conducting data analysis. The research is conducted at provincial level in China and the data collected for analysis are from 30 provinces for the period of 2006–2015. The results from this study show that the overall urbanization efficiency in China during the surveyed period is low, although certain improvement has been achieved. The difference between good and poor performers is considerable. In general, those provinces with better social and economic background have better urbanization efficiency performance. East China is much better than the rest of China, whilst Southwest region has the poorest performance.